From 2d88be851e7cf7ddbdf8e4b8cfa807081738ac93 Mon Sep 17 00:00:00 2001 From: Roman Kh Date: Tue, 1 Aug 2023 14:16:03 +0300 Subject: [PATCH] Update documentation --- .github/workflows/status.yml | 21 + .github/workflows/test-install.yml | 65 + .gitignore | 6 + LICENSE | 199 ++ NOTICE | 18 + README.md | 82 + __init__.py | 11 + notebooks/Convert_cubes.ipynb | 176 ++ notebooks/convert_cubes.py | 37 + pylintrc | 31 + requirements.txt | 1 + seismiqb/__init__.py | 18 + seismiqb/batch/__init__.py | 2 + seismiqb/batch/crop_batch.py | 1138 ++++++++ seismiqb/batch/visualization_batch.py | 424 +++ seismiqb/dataset.py | 258 ++ seismiqb/field/__init__.py | 3 + seismiqb/field/base.py | 486 ++++ seismiqb/field/synthetic.py | 339 +++ seismiqb/field/viewer.py | 210 ++ seismiqb/field/visualization.py | 613 +++++ seismiqb/functional/__init__.py | 6 + seismiqb/functional/base.py | 10 + seismiqb/functional/geologic_transforms.py | 98 + seismiqb/functional/geometric_transforms.py | 271 ++ seismiqb/functional/similarity_metrics.py | 248 ++ seismiqb/geometry/__init__.py | 7 + seismiqb/geometry/base.py | 1166 +++++++++ seismiqb/geometry/benchmark_mixin.py | 133 + seismiqb/geometry/conversion_mixin.py | 378 +++ seismiqb/geometry/converted.py | 231 ++ seismiqb/geometry/export_mixin.py | 342 +++ seismiqb/geometry/memmap_loader.py | 437 ++++ seismiqb/geometry/metric_mixin.py | 69 + seismiqb/geometry/segy.py | 701 +++++ seismiqb/geometry/segyio_loader.py | 280 ++ seismiqb/geometry/utils.py | 10 + seismiqb/grids.py | 852 ++++++ seismiqb/labels/__init__.py | 4 + seismiqb/labels/fault/__init__.py | 4 + seismiqb/labels/fault/approximation.py | 179 ++ seismiqb/labels/fault/base.py | 371 +++ seismiqb/labels/fault/coords_utils.py | 215 ++ seismiqb/labels/fault/extractor.py | 1574 +++++++++++ seismiqb/labels/fault/filtering_utils.py | 399 +++ seismiqb/labels/fault/formats.py | 328 +++ seismiqb/labels/fault/postprocessing.py | 315 +++ seismiqb/labels/fault/surfaces_extractor.py | 552 ++++ seismiqb/labels/fault/triangulation.py | 321 +++ seismiqb/labels/fault/visualization.py | 124 + seismiqb/labels/horizon/__init__.py | 3 + seismiqb/labels/horizon/attributes.py | 1021 ++++++++ seismiqb/labels/horizon/base.py | 896 +++++++ seismiqb/labels/horizon/extraction.py | 988 +++++++ seismiqb/labels/horizon/horizon_extractor.py | 414 +++ seismiqb/labels/horizon/processing.py | 646 +++++ seismiqb/labels/horizon/visualization.py | 192 ++ seismiqb/labels/mixins.py | 92 + seismiqb/labels/well/__init__.py | 2 + seismiqb/labels/well/base.py | 397 +++ seismiqb/matching/__init__.py | 4 + seismiqb/matching/collection.py | 719 ++++++ seismiqb/matching/functional.py | 69 + seismiqb/matching/intersection.py | 830 ++++++ seismiqb/matching/well_seismic_tie.py | 1305 ++++++++++ seismiqb/metrics.py | 963 +++++++ seismiqb/nn/__init__.py | 4 + seismiqb/nn/layers.py | 345 +++ seismiqb/nn/losses.py | 26 + seismiqb/nn/utils.py | 171 ++ seismiqb/plotters/__init__.py | 5 + seismiqb/plotters/cmaps.py | 255 ++ seismiqb/plotters/plot.py | 20 + seismiqb/plotters/show_3d.py | 154 ++ seismiqb/samplers.py | 1027 ++++++++ seismiqb/synthetic/parameters.py | 95 + seismiqb/utils/__init__.py | 13 + seismiqb/utils/accumulator2d.py | 215 ++ seismiqb/utils/accumulator3d.py | 712 +++++ seismiqb/utils/cache.py | 488 ++++ seismiqb/utils/charisma.py | 182 ++ seismiqb/utils/classes.py | 355 +++ seismiqb/utils/decorators.py | 122 + seismiqb/utils/dtype_conversion.py | 24 + seismiqb/utils/format_conversion.py | 36 + seismiqb/utils/functions.py | 286 ++ seismiqb/utils/groupby.py | 186 ++ seismiqb/utils/storage.py | 245 ++ setup.py | 102 + tests/README.md | 141 + tests/notebooks/cache_test.ipynb | 559 ++++ tests/notebooks/charisma_test.ipynb | 207 ++ .../notebooks/fault_test_01_preparation.ipynb | 185 ++ tests/notebooks/fault_test_02_base.ipynb | 340 +++ .../fault_test_03_sticks_processing.ipynb | 263 ++ .../fault_test_04_mask_creation.ipynb | 227 ++ .../geometry_test_01_preparation.ipynb | 269 ++ .../geometry_test_02_data_format.ipynb | 272 ++ .../geometry_test_03_transforms.ipynb | 131 + .../horizon_test_01_preparation.ipynb | 177 ++ tests/notebooks/horizon_test_02_base.ipynb | 408 +++ .../horizon_test_03_attributes.ipynb | 180 ++ .../horizon_test_04_processing.ipynb | 434 ++++ .../horizon_test_05_extraction.ipynb | 429 +++ tests/notebooks/template_test.ipynb | 192 ++ tests/run_notebook_test.py | 230 ++ tests/utils.py | 33 + tutorials/01_Geometry_part_1.ipynb | 692 +++++ tutorials/01_Geometry_part_2.ipynb | 579 +++++ tutorials/02_Horizon.ipynb | 837 ++++++ tutorials/03_Augmentations.ipynb | 451 ++++ tutorials/05_Synthetic_Generator.ipynb | 2299 +++++++++++++++++ tutorials/README.md | 6 + tutorials/plot/01_maps.ipynb | 304 +++ tutorials/plot/02_slides.ipynb | 206 ++ tutorials/plot/03_hist.ipynb | 264 ++ tutorials/plot/04_batch.ipynb | 277 ++ 117 files changed, 37964 insertions(+) create mode 100644 .github/workflows/status.yml create mode 100644 .github/workflows/test-install.yml create mode 100644 .gitignore create mode 100644 LICENSE create mode 100644 NOTICE create mode 100644 README.md create mode 100644 __init__.py create mode 100644 notebooks/Convert_cubes.ipynb create mode 100644 notebooks/convert_cubes.py create mode 100644 pylintrc create mode 100644 requirements.txt create mode 100644 seismiqb/__init__.py create mode 100644 seismiqb/batch/__init__.py create mode 100644 seismiqb/batch/crop_batch.py create mode 100644 seismiqb/batch/visualization_batch.py create mode 100644 seismiqb/dataset.py create mode 100644 seismiqb/field/__init__.py create mode 100644 seismiqb/field/base.py create mode 100644 seismiqb/field/synthetic.py create mode 100644 seismiqb/field/viewer.py create mode 100644 seismiqb/field/visualization.py create mode 100644 seismiqb/functional/__init__.py create mode 100644 seismiqb/functional/base.py create mode 100644 seismiqb/functional/geologic_transforms.py create mode 100644 seismiqb/functional/geometric_transforms.py create mode 100644 seismiqb/functional/similarity_metrics.py create mode 100644 seismiqb/geometry/__init__.py create mode 100644 seismiqb/geometry/base.py create mode 100644 seismiqb/geometry/benchmark_mixin.py create mode 100644 seismiqb/geometry/conversion_mixin.py create mode 100644 seismiqb/geometry/converted.py create mode 100644 seismiqb/geometry/export_mixin.py create mode 100644 seismiqb/geometry/memmap_loader.py create mode 100644 seismiqb/geometry/metric_mixin.py create mode 100644 seismiqb/geometry/segy.py create mode 100644 seismiqb/geometry/segyio_loader.py create mode 100644 seismiqb/geometry/utils.py create mode 100644 seismiqb/grids.py create mode 100644 seismiqb/labels/__init__.py create mode 100644 seismiqb/labels/fault/__init__.py create mode 100644 seismiqb/labels/fault/approximation.py create mode 100644 seismiqb/labels/fault/base.py create mode 100644 seismiqb/labels/fault/coords_utils.py create mode 100644 seismiqb/labels/fault/extractor.py create mode 100644 seismiqb/labels/fault/filtering_utils.py create mode 100644 seismiqb/labels/fault/formats.py create mode 100644 seismiqb/labels/fault/postprocessing.py create mode 100644 seismiqb/labels/fault/surfaces_extractor.py create mode 100644 seismiqb/labels/fault/triangulation.py create mode 100644 seismiqb/labels/fault/visualization.py create mode 100644 seismiqb/labels/horizon/__init__.py create mode 100644 seismiqb/labels/horizon/attributes.py create mode 100644 seismiqb/labels/horizon/base.py create mode 100644 seismiqb/labels/horizon/extraction.py create mode 100644 seismiqb/labels/horizon/horizon_extractor.py create mode 100644 seismiqb/labels/horizon/processing.py create mode 100644 seismiqb/labels/horizon/visualization.py create mode 100644 seismiqb/labels/mixins.py create mode 100644 seismiqb/labels/well/__init__.py create mode 100644 seismiqb/labels/well/base.py create mode 100644 seismiqb/matching/__init__.py create mode 100644 seismiqb/matching/collection.py create mode 100644 seismiqb/matching/functional.py create mode 100644 seismiqb/matching/intersection.py create mode 100644 seismiqb/matching/well_seismic_tie.py create mode 100644 seismiqb/metrics.py create mode 100644 seismiqb/nn/__init__.py create mode 100644 seismiqb/nn/layers.py create mode 100644 seismiqb/nn/losses.py create mode 100644 seismiqb/nn/utils.py create mode 100644 seismiqb/plotters/__init__.py create mode 100644 seismiqb/plotters/cmaps.py create mode 100644 seismiqb/plotters/plot.py create mode 100644 seismiqb/plotters/show_3d.py create mode 100644 seismiqb/samplers.py create mode 100644 seismiqb/synthetic/parameters.py create mode 100644 seismiqb/utils/__init__.py create mode 100644 seismiqb/utils/accumulator2d.py create mode 100644 seismiqb/utils/accumulator3d.py create mode 100644 seismiqb/utils/cache.py create mode 100644 seismiqb/utils/charisma.py create mode 100644 seismiqb/utils/classes.py create mode 100644 seismiqb/utils/decorators.py create mode 100644 seismiqb/utils/dtype_conversion.py create mode 100644 seismiqb/utils/format_conversion.py create mode 100644 seismiqb/utils/functions.py create mode 100644 seismiqb/utils/groupby.py create mode 100644 seismiqb/utils/storage.py create mode 100644 setup.py create mode 100644 tests/README.md create mode 100644 tests/notebooks/cache_test.ipynb create mode 100644 tests/notebooks/charisma_test.ipynb create mode 100644 tests/notebooks/fault_test_01_preparation.ipynb create mode 100644 tests/notebooks/fault_test_02_base.ipynb create mode 100644 tests/notebooks/fault_test_03_sticks_processing.ipynb create mode 100644 tests/notebooks/fault_test_04_mask_creation.ipynb create mode 100644 tests/notebooks/geometry_test_01_preparation.ipynb create mode 100644 tests/notebooks/geometry_test_02_data_format.ipynb create mode 100644 tests/notebooks/geometry_test_03_transforms.ipynb create mode 100644 tests/notebooks/horizon_test_01_preparation.ipynb create mode 100644 tests/notebooks/horizon_test_02_base.ipynb create mode 100644 tests/notebooks/horizon_test_03_attributes.ipynb create mode 100644 tests/notebooks/horizon_test_04_processing.ipynb create mode 100644 tests/notebooks/horizon_test_05_extraction.ipynb create mode 100644 tests/notebooks/template_test.ipynb create mode 100644 tests/run_notebook_test.py create mode 100644 tests/utils.py create mode 100644 tutorials/01_Geometry_part_1.ipynb create mode 100644 tutorials/01_Geometry_part_2.ipynb create mode 100644 tutorials/02_Horizon.ipynb create mode 100644 tutorials/03_Augmentations.ipynb create mode 100644 tutorials/05_Synthetic_Generator.ipynb create mode 100644 tutorials/README.md create mode 100644 tutorials/plot/01_maps.ipynb create mode 100644 tutorials/plot/02_slides.ipynb create mode 100644 tutorials/plot/03_hist.ipynb create mode 100644 tutorials/plot/04_batch.ipynb diff --git a/.github/workflows/status.yml b/.github/workflows/status.yml new file mode 100644 index 0000000..bf84843 --- /dev/null +++ b/.github/workflows/status.yml @@ -0,0 +1,21 @@ +name: status + +on: [push] + +jobs: + + lint-test: + + runs-on: ubuntu-latest + + container: + image: analysiscenter1/ds-py3:latest + + steps: + - uses: actions/checkout@v1 + + - name: Update pylint + run: pip3 install pylint==2.11.1 + + - name: Check pylint + run: pylint -rn --rcfile pylintrc seismiqb diff --git a/.github/workflows/test-install.yml b/.github/workflows/test-install.yml new file mode 100644 index 0000000..d671484 --- /dev/null +++ b/.github/workflows/test-install.yml @@ -0,0 +1,65 @@ +name: Tests + +on: + pull_request: + branches: + - master + + push: + branches: + - master + +jobs: + + set_matrix: + + runs-on: ubuntu-latest + + outputs: + matrix: ${{ steps.set-matrix.outputs.matrix }} + + steps: + - id: set-matrix + shell: bash + run: | + if ${{ github.event_name == 'pull_request' }}; then + echo "::set-output name=matrix::{\"os\":[\"ubuntu-latest\"], \"python-version\":[3.8]}" + else + echo "::set-output name=matrix::{\"os\":[\"ubuntu-latest\", \"windows-latest\"], \"python-version\":[3.8]}" + fi + + test_install: + + runs-on: ${{ matrix.os }} + needs: set_matrix + + strategy: + matrix: ${{fromJSON(needs.set_matrix.outputs.matrix)}} + fail-fast: false + + steps: + - name: Set up Python ${{ matrix.python-version }} on ${{ matrix.os }} + uses: actions/setup-python@v2 + with: + python-version: ${{ matrix.python-version }} + + - name: Install via pip from github + run: | + pip install --user -U pip + pip install wheel + pip install git+https://github.com/GeoscienceML/seismiqb.git@${{ github.sha }}#egg=seismiqb[test] + + - name: Run 'import' in installed environment + run: python -c 'import seismiqb' + + - name: Checkout SeismiQB + uses: actions/checkout@v2 + with: + submodules: true + + - name: Run basic tests + env: + BASE_DIR: ${{ github.workspace }} + run: | + pip install -U pytest + pytest -m "not slow" --tb=line --disable-pytest-warnings -v --pyargs diff --git a/.gitignore b/.gitignore new file mode 100644 index 0000000..58ddb6d --- /dev/null +++ b/.gitignore @@ -0,0 +1,6 @@ +*.pyc +.cache/ +__pycache__/ +.ipynb_checkpoints/ +build/ +*.egg-info/ \ No newline at end of file diff --git a/LICENSE b/LICENSE new file mode 100644 index 0000000..d62439f --- /dev/null +++ b/LICENSE @@ -0,0 +1,199 @@ + Apache License + Version 2.0, January 2004 + http://www.apache.org/licenses/ + + TERMS AND CONDITIONS FOR USE, REPRODUCTION, AND DISTRIBUTION + + 1. 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We also recommend that a + file or class name and description of purpose be included on the + same "printed page" as the copyright notice for easier + identification within third-party archives. + + Licensed under the Apache License, Version 2.0 (the "License"); + you may not use this file except in compliance with the License. + You may obtain a copy of the License at + + http://www.apache.org/licenses/LICENSE-2.0 + + Unless required by applicable law or agreed to in writing, software + distributed under the License is distributed on an "AS IS" BASIS, + WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + See the License for the specific language governing permissions and + limitations under the License. diff --git a/NOTICE b/NOTICE new file mode 100644 index 0000000..442b7d3 --- /dev/null +++ b/NOTICE @@ -0,0 +1,18 @@ +seismiQB + +This software contains code developed by Data Analysis Center. + +The copyright of the relevant parts of code belongs to: +Sergey Tsimfer +Alexey Kozhevin +Svetlana Sorokina +Alexander Koryagin +Gazprom neft +Stepan Goryachev +Darima Mylzenova +Antonina Arefina +Roman Khudorozhkov +Evgeniy Strievich +Dmitry Podvyaznikov +Anna Altynova +and other developers. diff --git a/README.md b/README.md new file mode 100644 index 0000000..4980aa2 --- /dev/null +++ b/README.md @@ -0,0 +1,82 @@ +
+ +# seismiQB + +Installation • +Getting Started • +Citation + + +[![License](https://img.shields.io/github/license/analysiscenter/batchflow.svg)](https://www.apache.org/licenses/LICENSE-2.0) +[![Python](https://img.shields.io/badge/python-3.8-blue.svg)](https://python.org) +[![PyTorch](https://img.shields.io/badge/PyTorch-2.0-green.svg)](https://pytorch.org) +[![Status](https://github.com/GeoscienceML/seismiqb/actions/workflows/status.yml/badge.svg?branch=master&event=push)](https://github.com/GeoscienceML/seismiqb/actions/workflows/status.yml) +[![Test installation](https://github.com/GeoscienceML/seismiqb/actions/workflows/test-install.yml/badge.svg?branch=master&event=push)](https://github.com/GeoscienceML/seismiqb/actions/workflows/test-install.yml) +
+ +--- + + +**seismiQB** is a framework for research and deployment of deep learning models on post-stack seismic data. +It covers all main stages of model development and its production usage for seismic interpretation. The main features are: + +* Optimized IO for `SEG-Y` storage: by using our library **[segfast](https://github.com/analysiscenter/segfast)**, combined with quantization and compression, we are working with the most popular transport format by an order of magnitude faster; +* Labelling classes, matching core interpretation entities: horizons, faults, facies, wells, and more; +* Pipelines for preparing the model inputs, e.g. patches (2d or 3d) of seismic data and corresponding segmentation masks; +* Geologic transformations, as well as more traditional ML augmentations; +* Advanced primitives for train/inference to saturate even the fastest GPUs; +* Fast and convenient export: all predicted objects are easy to convert to popular formats (SEG-Y, CHARISMA, LAS) for validation by geophysicists; + + + +## Installation +**seismiQB** is compatible with Python 3.8+ and well tested on Ubuntu 20.04. + + # pipenv + pipenv install git+https://github.com/GeoscienceML/seismiqb.git#egg=seismiqb + + # pip / pip3 + pip3 install git+https://github.com/GeoscienceML/seismiqb.git + + # developer version (add `--depth 1` if needed) + git clone https://github.com/GeoscienceML/seismiqb.git + + +## Getting started + +After installation just import **seismiQB** into your code. A quick demo of our primitives and methods: +```python +import seismiqb + +field = Field('/path/to/cube.sgy') # Initialize field with SEG-Y +field.load_labels('path/to/horizons/*.char', labels_class='horizon') # Add labeling + +# Labels +field.horizons.interpolate() # Fill in small holes +field.horizons.smooth_out() # Smooth out and remove spikes +field.horizons.evaluate() # Compute a quality control metric + +# Visualizations +field.geometry.print() # Display key stats about SEG-Y +field.show_slide(index=100, axis=1) # Show 100-th crossline +field.show('horizons:0/metric') # Show QC metric for one horizon + +``` + +Be sure to check out our [tutorials](tutorials) to get more info about the **seismiQB** primitives and usage. + + + +## Citing + +Please cite **seismiQB** in your publications if it helps your research. + + Khudorozhkov R., Tsimfer S., Kozhevin A., Koryagin A., Sorokina S., Strievich E. SeismiQB library for seismic interpretation with deep learning. 2023. + +``` +@misc{seismiQB_2023, + author = {R. Khudorozhkov and S. Tsimfer and A. Kozhevin and A. Koryagin and S. Sorokina and E. Strievich}, + title = {SeismiQB library for seismic interpretation with deep learning}, + year = 2023 +} +``` diff --git a/__init__.py b/__init__.py new file mode 100644 index 0000000..e99fa4a --- /dev/null +++ b/__init__.py @@ -0,0 +1,11 @@ +"""Init file. +Also disables the OMP warnings, which are produced by Numba or Tensorflow and can't be disabled otherwise. +The change of env variable should be before any imports, relying on it, so we place it on top. +""" +#pylint: disable=wrong-import-position +import os +os.environ['KMP_WARNINGS'] = '0' + +from .seismiqb import * +__path__ = [os.path.join(os.path.dirname(__file__), 'seismiqb')] +__version__ = '1.0.0' diff --git a/notebooks/Convert_cubes.ipynb b/notebooks/Convert_cubes.ipynb new file mode 100644 index 0000000..a92c3e5 --- /dev/null +++ b/notebooks/Convert_cubes.ipynb @@ -0,0 +1,176 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Cube conversion\n", + "\n", + "This notebooks creates an optimized version of each `SEG-Y` cube.\n", + "The exact format (`HDF5`, `QHDF5`, `QSGY`) depends on `FORMAT` and `QUANTIZE` parameters.\n", + "\n", + "Pseudocode of this notebook looks like:\n", + "\n", + "```python\n", + "for each cube:\n", + " mkdir\n", + " infer geometry\n", + " if SHOW, log to std.out\n", + " \n", + " convert segy to a desired QUANTIZED FORMAT\n", + "```\n", + "\n", + "* `paths` controls which cubes are converted\n", + "* `RECREATE` determines whether already converted volumes should be re-converted\n", + "* `CONVERT` controls whether the cubes should be converted\n", + "* `FORMAT` and `QUANTIZE` determine the exact format to convert to\n", + "* `SHOW` allows to control whether results are shown in the notebook itself\n", + "* `DRY` can be used to check which operations will happen, without actually executing them" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "tags": [] + }, + "outputs": [], + "source": [ + "import os\n", + "import sys\n", + "import warnings\n", + "warnings.filterwarnings(\"ignore\")\n", + "\n", + "from glob import glob\n", + "import matplotlib.pyplot as plt\n", + "\n", + "sys.path.insert(0, '..')\n", + "sys.path.insert(0, '../..')\n", + "from seismiqb import Geometry\n", + "from batchflow import Notifier" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "tags": [] + }, + "outputs": [], + "source": [ + "# Global parameters\n", + "SEPARATOR = '▆'*60\n", + "\n", + "RECREATE = False\n", + "SHOW = True\n", + "DRY_RUN = False\n", + "\n", + "# Conversion options. Format should be one of {'qsgy', 'hdf5', 'qhdf5'}\n", + "CONVERT = True\n", + "FORMAT = 'qsgy'\n", + "POSTFIX = False\n", + "QUANTIZE = True\n", + "CONVERSION_KWARGS = {\n", + " # 'chunk_size_divisor' : 3, # keep smaller chunks in `hdf5`\n", + "}\n", + "\n", + "CUBE = '*_*'" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "tags": [] + }, + "outputs": [], + "source": [ + "paths = sorted(glob(f'/data/seismic_data/seismic_interpretation/{CUBE}/*.s*y'))\n", + "[print(path) for path in paths[:]];" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "tags": [] + }, + "outputs": [], + "source": [ + "%%time\n", + "for path_cube in Notifier('n')(paths[:]):\n", + " if not os.path.exists(path_cube):\n", + " continue\n", + " \n", + " # Make an instance with no actual init\n", + " geometry = Geometry.new(path=path_cube, init=False)\n", + " path_converted = geometry.make_output_path(format=FORMAT, postfix=POSTFIX, quantize=QUANTIZE)\n", + "\n", + " if os.path.exists(path_converted) and not RECREATE:\n", + " print(f'{path_converted} already exists, skipping\\n')\n", + " continue\n", + " if DRY_RUN:\n", + " print(f'Will convert ::: {path_cube}\\nto ::: {path_converted}\\n')\n", + " continue\n", + "\n", + " if SHOW:\n", + " print(SEPARATOR); print(SEPARATOR);\n", + " print('Working with', path_cube)\n", + "\n", + " \n", + " # Re-open geometry, collect stats\n", + " geometry = Geometry.new(path=path_cube,\n", + " index_headers=Geometry.INDEX_HEADERS_POSTSTACK,\n", + " additional_headers=Geometry.ADDITIONAL_HEADERS_POSTSTACK_FULL,\n", + " reload_headers=True,\n", + " collect_stats=True, recollect_stats=True)\n", + " if SHOW:\n", + " # Textual\n", + " geometry.print()\n", + " print()\n", + " geometry.print_textual()\n", + "\n", + " # Graphs\n", + " geometry.show('snr')\n", + " plt.show()\n", + "\n", + "\n", + " # Conversion\n", + " if CONVERT is False:\n", + " continue\n", + " geometry_converted = geometry.convert(format=FORMAT, postfix=POSTFIX, quantize=QUANTIZE, **CONVERSION_KWARGS)\n", + " if SHOW:\n", + " geometry_converted.print()\n", + " print('\\n'*3)" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3 (ipykernel)", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.8.10" + }, + "widgets": { + "application/vnd.jupyter.widget-state+json": { + "state": {}, + "version_major": 2, + "version_minor": 0 + } + } + }, + "nbformat": 4, + "nbformat_minor": 4 +} diff --git a/notebooks/convert_cubes.py b/notebooks/convert_cubes.py new file mode 100644 index 0000000..07c458d --- /dev/null +++ b/notebooks/convert_cubes.py @@ -0,0 +1,37 @@ +import os +from contextlib import redirect_stderr +from nbtools import run_notebook +import argparse + +parser = argparse.ArgumentParser(description='sgy converter') +parser.add_argument('-c', '--cube', help='cube name', default='*_*') +parser.add_argument('-f', '--force', action='store_true', help='recreate cube if exists') +parser.add_argument('-s', '--save', action='store_true', help='whether to save output notebook') +parser.add_argument('-p', '--postfix', action='store_true', help='add postfix to the created file') +parser.add_argument('--format', default='qsgy', help='format of cube') +parser.add_argument('--nonconvert', action='store_true', help='whether cubes should be converted') +parser.add_argument('--nonquantize', action='store_true', help='disable quantization of cube') + +args = vars(parser.parse_args()) + +PATH = 'Convert_cubes.ipynb' +OUTPUT_PATH = 'Convert_cubes_executed.ipynb' + +INPUTS = dict( + CUBE = args['cube'], + RECREATE = args['force'], + CONVERT = not args['nonconvert'], + FORMAT = args['format'], + QUANTIZE = not args['nonquantize'] +) + +with open(os.devnull, 'w') as fnull: + with redirect_stderr(fnull) as err: + exceptions = run_notebook(PATH, INPUTS, inputs_pos=3, display_links=False, out_path_ipynb=OUTPUT_PATH) + +if exceptions['failed cell number'] is not None: + print('Cell:', exceptions['failed cell number']) + print(exceptions['traceback']) + +if not args['save']: + os.remove(OUTPUT_PATH) diff --git a/pylintrc b/pylintrc new file mode 100644 index 0000000..8ff5727 --- /dev/null +++ b/pylintrc @@ -0,0 +1,31 @@ +[MASTER] +ignore=batchflow +extension-pkg-whitelist=numpy +init-hook='import sys; sys.path.append(".")' + +[FORMAT] +max-line-length=120 +max-parents=20 +max-attributes=100 +max-args=25 +max-locals=25 +max-branches=20 +max-statements=100 +variable-rgx=(.*[a-z][a-z0-9_]{1,30}|[a-z_])$ # snake_case + single letters +argument-rgx=(.*[a-z][a-z0-9_]{1,30}|[a-z_])$ # snake_case + single letters + +[MESSAGE CONTROL] +disable=no-value-for-parameter, no-self-use, too-few-public-methods, unsubscriptable-object, no-member, too-many-lines, + arguments-differ, too-many-locals, import-error, cyclic-import, duplicate-code, relative-beyond-top-level, + unused-argument, too-many-public-methods, invalid-name, attribute-defined-outside-init, arguments-renamed, + abstract-method, no-name-in-module, import-self + +[TYPECHECK] +ignored-modules=numpy, numba + +[BASIC] +class-rgx=[A-Z_][a-zA-Z0-9_]+$ +good-names=bar,df,fn + +[MISCELLANEOUS] +notes= diff --git a/requirements.txt b/requirements.txt new file mode 100644 index 0000000..945c9b4 --- /dev/null +++ b/requirements.txt @@ -0,0 +1 @@ +. \ No newline at end of file diff --git a/seismiqb/__init__.py b/seismiqb/__init__.py new file mode 100644 index 0000000..c4fe3f1 --- /dev/null +++ b/seismiqb/__init__.py @@ -0,0 +1,18 @@ +""" Init file. """ +# pylint: disable=wildcard-import +# Core primitives +from .dataset import SeismicDataset +from .batch import SeismicCropBatch + +# Data entities +from .field import Field, SyntheticField +from .geometry import Geometry, array_to_segy, array_to_sgy +from .labels import Horizon, HorizonExtractor, Fault, FaultExtractor, skeletonize, Well, MatchedWell +from .metrics import HorizonMetrics, FaultsMetrics, FaciesMetrics +from .samplers import GeometrySampler, HorizonSampler, FaultSampler, ConstantSampler, SeismicSampler +from .grids import BaseGrid, RegularGrid, ExtensionGrid, LocationsPotentialContainer + +# Utilities and helpers +from .functional import * +from .utils import * +from .plotters import * diff --git a/seismiqb/batch/__init__.py b/seismiqb/batch/__init__.py new file mode 100644 index 0000000..28c4644 --- /dev/null +++ b/seismiqb/batch/__init__.py @@ -0,0 +1,2 @@ +""" Batch of seismic data crops. """ +from .crop_batch import SeismicCropBatch diff --git a/seismiqb/batch/crop_batch.py b/seismiqb/batch/crop_batch.py new file mode 100644 index 0000000..797f447 --- /dev/null +++ b/seismiqb/batch/crop_batch.py @@ -0,0 +1,1138 @@ +""" Seismic Crop Batch. """ +import os +import traceback +from warnings import warn +from functools import wraps +from inspect import signature + +import numpy as np +import cv2 +from scipy.interpolate import interp1d +from scipy.ndimage import gaussian_filter1d, gaussian_filter +from scipy.signal import butter, sosfiltfilt + +from batchflow import DatasetIndex, Batch +from batchflow import action, any_action_failed, SkipBatchException +from batchflow import apply_parallel as apply_parallel_decorator + +from .visualization_batch import VisualizationMixin +from ..labels import Horizon +from ..utils import to_list, groupby_all +from .. import functional + +from ..labels.fault import skeletonize + + + +def add_methods(method_names): + """ Add augmentations to batch class. """ + def _add_methods(cls): + def create_batch_method(method_name): + method = getattr(functional, method_name) + requires_rng = 'rng' in signature(method).parameters + + @wraps(method) + def wrapper(self, _, buffer, *args, src=None, dst=None, **kwargs): + _ = src, dst + buffer[:] = method(buffer, *args, **kwargs) + wrapper = cls.use_apply_parallel(wrapper, requires_rng=requires_rng) + return wrapper + + for method_name in method_names: + setattr(cls, method_name, create_batch_method(method_name)) + return cls + return _add_methods + +@add_methods(['rotate_2d', 'rotate_3d', 'scale_2d', 'scale_3d', + 'affine_transform', 'perspective_transform', 'elastic_transform', + 'compute_instantaneous_amplitude', 'compute_instantaneous_phase', 'compute_instantaneous_frequency']) +class SeismicCropBatch(Batch, VisualizationMixin): + """ Batch with ability to generate 3d-crops of various shapes. + + The first action in any pipeline with this class should be `make_locations` to transform batch index from + individual cubes into crop-based indices. The transformation uses randomly generated postfix (see `:meth:.salt`) + to obtain unique elements. + """ + apply_defaults = { + 'init': 'preallocating_init', + 'post': 'noop_post', + 'target': 'for', + } + + # Inner workings + @action + def add_components(self, components, init=None): + """ Add new components, checking that attributes of the same name are not present in dataset. + + Parameters + ---------- + components : str or list + new component names + init : array-like + initial component data + + Raises + ------ + ValueError + If a component or an attribute with the given name already exists in batch or dataset. + """ + for component in to_list(components): + if hasattr(self.dataset, component): + msg = f"Component with `{component}` name cannot be added to batch, "\ + "since attribute with this name is already present in dataset." + raise ValueError(msg) + super().add_components(components=components, init=init) + + def __setattr__(self, name, value): + super().__setattr__(name, value) + if isinstance(value, np.ndarray) and value.ndim == 4 and name not in self.name_to_order: + self.name_to_order[name] = np.array(['i', 'x', 'd']) + + def get(self, item=None, component=None): + """ Custom access for batch attributes. + If `component` is one of the registered components, get it, optionally indexed with `item`. + Otherwise, try to get `component` as the attribute of a field, corresponding to `item`. + """ + if component in self.components: + # Faster, than `getattr(self, component)`, as we already know that the component exists + data = self._data[component] + if item is not None: + return data[item] + + elif component in self.__dict__: + data = self.__dict__[component] + if item is not None: + return data[item] + + else: # retrieve from `dataset` + if item is not None: + field_name = self._data['field_names'][item] + field = self.dataset.fields[field_name] + if component == 'fields': + return field + return getattr(field, component) + + # Not often used, mainly for introspection/debug. Not optimized + data = getattr(self.dataset, component) + + return data + + def deepcopy(self, preserve=False): + """ Create a copy of a batch with the same `dataset` and `pipeline` references. """ + #pylint: disable=protected-access + new = super().deepcopy() + + if preserve: + new._dataset = self.dataset + new.pipeline = self.pipeline + return new + + + # Batch action parallelization + def preallocating_init(self, src=None, dst=None, buffer_type=None, return_indices=True, **kwargs): + """ Preallocate a buffer. """ + if src is None and dst is None: + raise ValueError('Specify either `src` or `dst`!.') + dst = dst if dst is not None else src + + # Check if the operation can be done in-place + inplace = False + if src is None: + inplace = False + if dst == src: + inplace = True + + if inplace: + buffer = self.get(component=src) + else: + if src is None or buffer_type is not None: + dtype = np.float32 # TODO: determine based on geometries + buffer = (getattr(np, buffer_type))((len(self), *self.crop_shape), dtype=dtype) + else: + buffer = self.get(component=src).copy() + self.add_components(dst, buffer) + + return list(zip(self.indices, buffer)) if return_indices else buffer + + def noop_post(self, all_results, **kwargs): + """ Check for errors after the action, otherwise does nothing. """ + _ = kwargs + + if any_action_failed(all_results): + all_errors = self.get_errors(all_results) + print(all_errors) + traceback.print_tb(all_errors[0].__traceback__) + raise RuntimeError("Could not assemble the batch!") from all_errors[0] + return self + + def normalize_post(self, all_results, func, src=None, mode='meanstd', **kwargs): + """ Post function to store""" + self.noop_post(all_results, **kwargs) + normalization_stats = [item[1] for item in all_results] + self.add_components(f'normalization_stats_{src}', normalization_stats) + return self + + # Core actions + @action + def make_locations(self, generator, batch_size=None, keep_attributes=None): + """ Use `generator` to create `batch_size` locations. + Each location defines position in a cube and can be used to retrieve data/create masks at this place. + + Generator can be either Sampler or Grid to make locations in a random or deterministic fashion. + `generator` must be a callable and return (batch_size, 9+) array, where the first nine columns should be: + (field_id, label_id, orientation, i_start, x_start, d_start, i_stop, x_stop, d_stop). + `generator` must have `to_names` method to convert cube and label ids into actual strings. + + Alternatively, `generator` may be a ready-to-use ndarray with the same structure. In this case, `to_names` + is called directly from dataset. Should be used with caution and mainly for debugging purposes. + + Field and label ids are transformed into names of actual fields and labels (horizons, faults, facies, etc). + Then we create a new instance of `SeismicCropBatch`, where the index is set to a enumeration of locations. + + After parsing contents of generated (batch_size, 9+)-shaped array we add following attributes: + - `locations` with triplets of slices + - `orientations` with crop orientation: 0 for iline direction, 1 for crossline direction + - `shapes` + - `crop_shape`, computed from `shapes` + - `field_names` + - `label_names` + - `generated` with originally generated data + If `generator` creates more than 9 columns, they are not used, but still stored in the `generated` attribute. + + Parameters + ---------- + generator : callable or np.ndarray + Sampler or Grid to retrieve locations. Must be a callable that works off of a positive integer. + batch_size : int + Number of locations to generate. + keep_attributes : str or sequence of str + Components to keep in a newly created batch. + + Returns + ------- + SeismicCropBatch + A new instance of Batch. + """ + # Get ndarray with `locations` and `orientations`, convert IDs to names, that are used in dataset + if callable(generator): + generated = generator(batch_size) + field_names, label_names = generator.to_names(generated[:, [0, 1]]).T + elif isinstance(generator, np.ndarray): + generated = generator + field_names, label_names = self.dataset.to_names(generated[:, [0, 1]]).T + else: + raise ValueError(f'`generator` should either be callable or ndarray, got {type(generator)} instead!') + + # Locations: 3D slices in the cube coordinates + locations = [[slice(i_start, i_stop), slice(x_start, x_stop), slice(d_start, d_stop)] + for i_start, x_start, d_start, i_stop, x_stop, d_stop in generated[:, 3:9]] + + # Additional info + orientations = generated[:, 2] + shapes = generated[:, [6, 7, 8]] - generated[:, [3, 4, 5]] + crop_shape = shapes[0] if orientations[0] == 0 else shapes[0][[1, 0, 2]] + + # Create a new SeismicCropBatch instance + new_index = np.arange(len(locations), dtype=np.int32) + new_batch = type(self)(DatasetIndex.from_index(index=new_index)) + + # Keep chosen components in the new batch + if keep_attributes: + keep_attributes = [keep_attributes] if isinstance(keep_attributes, str) else keep_attributes + for component in keep_attributes: + if hasattr(self, component): + new_batch.add_components(component, self.get(component=component)) + + # Set all freshly computed attributes. Manually keep the reference to the `pipeline` + # Note: `pipeline` would be set by :meth:`~.Pipeline._exec_one_action` anyway, so this is not necessary. + new_batch.add_components(('locations', 'generated', 'shapes', 'orientations', 'field_names', 'label_names'), + (locations, generated, shapes, orientations, field_names, label_names)) + new_batch.crop_shape = crop_shape + new_batch.name_to_order = {} + new_batch.pipeline = self.pipeline + return new_batch + + + # Loading of cube data and its derivatives + @apply_parallel_decorator(init='preallocating_init', post='noop_post', buffer_type='empty', target='for') + def load_seismic(self, ix, buffer, dst, src=None, src_geometry='geometry', **kwargs): + """ Load data from cube for stored `locations`. + + Parameters + ---------- + dst : str + Component of batch to put loaded crops in. + slicing : str + If 'custom', use `load_crop` method to make crops. + if 'native', crop will be loaded as a slice of geometry. Preferred for 3D crops to speed up loading. + src_geometry : str + Field attribute with desired geometry. + """ + field = self.get(ix, 'fields') + locations = self.get(ix, 'locations') + orientation = self.get(ix, 'orientations') + + if orientation == 1: + buffer = buffer.transpose(1, 0, 2) + field.load_seismic(locations=locations, src=src_geometry, buffer=buffer, **kwargs) + + load_cubes = load_crops = load_seismic + + + @apply_parallel_decorator(init='preallocating_init', post='normalize_post', target='for') + def normalize(self, ix, buffer, src, dst=None, mode='meanstd', stats=None, clip_to_quantiles=None): + """ Normalize `src` with provided stats. + Depending on the parameters, stats for normalization will be taken from (in order of priority): + - supplied `stats`, if provided + - the field that created this `src`, if `stats=True` or `stats='field'` + - from `normalization_stats_{stats}` component (each `normalize` action put used statistics into + normalization_stats_{src} component) + - computed from `src` data directly + + Parameters + ---------- + mode : {'mean', 'std', 'meanstd', 'minmax'}, callable or None + If str, then normalization description. + If callable, then it will be called on `src` data with additional `stats` argument. + If None, `mode` from normalizer instance will be used. + stats : dict or str, optional + If provided, then used to get statistics for normalization. + If dict, stats for each field. + If 'field', field normalization statistics will be used. + If other str, `normalization_stats_{stats}` will be used. + If None, item statistics will be used. + clip_to_quantiles : bool + Whether to clip the data to quantiles, specified by `q` parameter. + Quantile values are taken from `stats`, provided by either of the ways. + """ + field = self.get(ix, 'fields') + + # Prepare normalization stats + if isinstance(stats, dict): + if field.short_name in stats: + stats = stats[field.short_name] + elif stats in {'field', True}: + stats = field.normalization_stats + elif isinstance(stats, str): + stats = getattr(self, f'normalization_stats_{stats}')[ix] + + buffer, stats = field.normalizer.normalize(buffer, normalization_stats=stats, mode=mode, + return_stats=True, inplace=True) + return buffer, stats + + @apply_parallel_decorator(init='preallocating_init', post='noop_post', target='for') + def denormalize(self, ix, buffer, src, dst=None, mode=None, stats=None): + """ Denormalize images using provided statistics. + + Parameters + ---------- + mode : {'mean', 'std', 'meanstd', 'minmax'}, callable or None + If str, then normalization description. + If callable, then it will be called on `src` data with additional `stats` argument. + If None, `mode` from normalizer instance will be used. + stats : dict or str, optional + If provided, then used to get statistics for normalization. + If dict, stats for each field. + If 'field', field normalization statistics will be used. + If other str, `normalization_stats_{stats}` will be used. + """ + field = self.get(ix, 'fields') + + # Prepare normalization stats + if isinstance(stats, dict): + if field.short_name in stats: + stats = stats[field.short_name] + elif stats in {'field', True}: + stats = field.normalization_stats + elif isinstance(stats, str): + stats = getattr(self, f'normalization_stats_{stats}')[ix] + + buffer = field.normalizer.denormalize(buffer, normalization_stats=stats, mode=mode, inplace=True) + return buffer + + @apply_parallel_decorator(init='preallocating_init', post='noop_post', target='for') + def quantize(self, ix, buffer, src, dst=None): + """ Quantize image. """ + field = self.get(ix, 'fields') + buffer[:] = field.quantizer.quantize(buffer) + return buffer + + @apply_parallel_decorator(init='preallocating_init', post='noop_post', target='for') + def dequantize(self, ix, buffer, src, dst=None): + """ Dequantize image (lossy). """ + field = self.get(ix, 'fields') + buffer[:] = field.quantizer.dequantize(buffer) + return buffer + + @apply_parallel_decorator(init='indices', post='_assemble', target='for') + def compute_attribute(self, ix, dst, src='images', attribute='semblance', window=10, stride=1, device='cpu'): + """ Compute geological attribute. + + Parameters + ---------- + dst : str + Destination batch component + src : str, optional + Source batch component, by default 'images' + attribute : str, optional + Attribute to compute, by default 'semblance' + window : int or tuple, optional + Window to compute attribute, by default 10 (for each axis) + stride : int, optional + Stride for windows, by default 1 (for each axis) + device : str, optional + Device to compute attribute, by default 'cpu' + + Returns + ------- + SeismicCropBatch + Batch with loaded masks in desired components. + """ + from ..utils.layers import compute_attribute #pylint: disable=import-outside-toplevel + image = self.get(ix, src) + result = compute_attribute(image, window, device, attribute) + return result + + + # Loading of labels + @action + @apply_parallel_decorator(init='preallocating_init', post='noop_post', buffer_type='zeros', target='for') + def create_masks(self, ix, buffer, dst, src=None, indices='all', width=3, src_labels='labels', + sparse=False, **kwargs): + """ Create masks from labels in stored `locations`. + + Parameters + ---------- + dst : str + Component of batch to put loaded masks in. + indices : str, int or sequence of ints + Which labels to use in mask creation. + If 'all', then use all labels. + If 'single' or `random`, then use one random label. + If int or array-like, then element(s) are interpreted as indices of desired labels. + width : int + Width of the resulting label. + src_labels : str + Dataset attribute with labels dict. + sparse : bool, optional + Whether create sparse mask (only on labeled slides) or not, by default False. Unlabeled + slides will be filled with -1. + """ + field = self.get(ix, 'fields') + locations = self.get(ix, 'locations') + orientation = self.get(ix, 'orientations') + + if orientation == 1: + buffer = buffer.transpose(1, 0, 2) + field.make_mask(locations=locations, orientation=orientation, buffer=buffer, + width=width, indices=indices, src=src_labels, sparse=sparse, **kwargs) + + + @action + @apply_parallel_decorator(init='indices', post='_assemble', target='for') + def create_regression_masks(self, ix, dst, src=None, indices='all', src_labels='labels', scale=False): + """ Create masks with relative depth. """ + field = self.get(ix, 'fields') + location = self.get(ix, 'locations') + return field.make_regression_mask(location=location, indices=indices, src=src_labels, scale=scale) + + + @action + @apply_parallel_decorator(init='indices', post='_assemble', target='for') + def compute_label_attribute(self, ix, dst, src='amplitudes', atleast_3d=True, dtype=np.float32, **kwargs): + """ Compute requested attribute along label surface. Target labels are defined by sampled locations. + + Parameters + ---------- + src : str + Keyword that defines label attribute to compute. + atleast_3d : bool + Whether add one more dimension to 2d result or not. + dtype : valid dtype compatible with requested attribute + A dtype that result must have. + kwargs : misc + Passed directly to one of attribute-evaluating methods. + + Notes + ----- + Correspondence between the attribute and the method that computes it + is defined by :attr:`~Horizon.ATTRIBUTE_TO_METHOD`. + + TODO: can be improved with `preallocating_init` + """ + field = self.get(ix, 'fields') + location = self.get(ix, 'locations') + label_index = self.get(ix, 'generated')[1] + src = src.replace('*', str(label_index)) + + result = field.load_attribute(src=src, location=location, atleast_3d=atleast_3d, dtype=dtype, **kwargs) + return result + + + # Rebatch and its callables + @action + def rebatch_on_condition(self, src=None, condition='area', threshold=None, keep_attributes=None, **kwargs): + """ Compute a condition on each item of `src`, keep only elements that returned value bigger than `threshold`. + Modifies (slices) all of the components in a batch instance, as well as its index. + + Parameters + ---------- + src : str + Name of the component to use as input for `condition`. + condition : callable, {'area', 'discontinuity_size'} + If callable, then applied to each item of `src`. + If 'area', then labeled area of a mask is computed, using the specified axis for projection. + If 'discontinuity_size', then we compute the biggest discontinuity size. + threshold : number + A value to compare computed conditions against. + keep_attributes : sequence, optional + Additional batch attributes to slice with the new index. + kwargs : dict + Passed directly to `condition` function. + """ + # Select correct function to compute + if callable(condition): + pass + elif condition == 'area': + condition = self._compute_mask_area + elif condition == 'discontinuity_size': + condition = self._compute_discontinuity_size + elif condition == 'crop_area': + condition = self._compute_crop_area + + # Compute indices to keep + data = self.get(component=src) + indices = np.array([i for i, item in enumerate(data) + if condition(item, **kwargs) > threshold]) + + if len(indices) > 0: + self.index = DatasetIndex.from_index(index=indices) + else: + raise SkipBatchException + + # Re-index components and additional attributes passed + keep_attributes = keep_attributes = keep_attributes or [] + keep_attributes += list(self.components or []) + keep_attributes = list(set(keep_attributes)) + + for component in keep_attributes: + component_data = self.get(component=component) + if isinstance(component_data, np.ndarray): + component_data = component_data[indices] + else: + component_data = [component_data[i] for i in indices] + setattr(self, component, component_data) + return self + + @staticmethod + def _compute_mask_area(array, axis=-1, **kwargs): + """ Compute the area of a projection (along the `axis`, by default depth), of a horizon mask. """ + _ = kwargs + labeled_traces = array.max(axis=axis) + area = labeled_traces.sum() / labeled_traces.size + return area + + @staticmethod + def _compute_crop_area(array, axis=(1, 2), **kwargs): + """ Compute the area of a projection (along the `axis`, by default depth), of a horizon mask. """ + _ = kwargs + return 1 - np.isnan(array).sum(axis=axis) / array.size + + @staticmethod + def _compute_discontinuity_size(array, **kwargs): + """ Compute the size of the biggest discontinuity (allegedly, fault) in the horizon mask. + Assumes the array in (inline, crossline, depth) orientation. Tested mostly for 2D crops. + """ + _ = kwargs + + # Get point cloud of labeled points. For each trace (for each (i, x) pixel) compute depth stats + points = np.array(np.nonzero(array)).T # (iline, xline, depth) point cloud + points = groupby_all(points) # (iline, xline, _, min_depth, max_depth, _) + condition = points[:-1, 1] == points[1:, 1] - 1 # get only sequential traces + + # Upper/lower bounds + mins = points[:-1, 3][condition] + mins_next = points[1:, 3][condition] + upper = np.max(np.array([mins, mins_next]), axis=0) # maximum values of `min_depth` for each pixel + + maxs = points[:-1, 4][condition] + maxs_next = points[1:, 4][condition] + lower = np.min(np.array([maxs, maxs_next]), axis=0) # minimum values of `max_depth` for each pixel + + return (upper - lower).max() + + + # Methods to work with (mostly, horizon) masks + @apply_parallel_decorator(init='preallocating_init', post='noop_post', target='for') + def filter_sides(self, _, buffer, ratio, side, axis=0, src=None, dst=None): + """ Filter out left or right side of a crop. + Assumes the array in (inline, crossline, depth) orientation. Tested mostly for 2D crops. + + Parameters + ---------- + ratio : float + The ratio of the crop lines to be filtered out. + side : str + Which side to filter out. Possible options are 'left' or 'right'. + """ + if not 0 <= ratio <= 1: + raise ValueError(f"Invalid value ratio={ratio}: must be a float in [0, 1] interval.") + + # Get the amount of crop lines and kept them on the chosen crop part + max_len = buffer.shape[axis] + length = round(max_len * (1 - ratio)) + + locations = [slice(None)] * 3 + locations[axis] = slice(0, max_len-length) if side == 'left' else slice(length, max_len) + buffer[tuple(locations)] = 0 + + + @apply_parallel_decorator(init='data', post='_assemble', target='for') + def shift_masks(self, crop, n_segments=3, max_shift=4, min_len=5, max_len=10, src=None, dst=None): + """ Randomly shift parts of the crop up or down. + + Parameters + ---------- + n_segments : int + Number of segments to shift. + max_shift : int + Max size of shift along vertical axis. + min_len : int + Min size of shift along horizontal axis. + max_len : int + Max size of shift along horizontal axis. + """ + crop = np.copy(crop) + for _ in range(n_segments): + # Point of starting the distortion, its length and size + begin = np.random.randint(0, crop.shape[1]) + length = np.random.randint(min_len, max_len) + shift = np.random.randint(-max_shift, max_shift) + + # Apply shift + if shift != 0: + segment_to_shift = crop[:, begin:min(begin + length, crop.shape[1]), :] + shifted_segment = np.roll(segment_to_shift, shift=shift, axis=-1) + crop[:, begin:min(begin + length, crop.shape[1]), :] = shifted_segment + return crop + + @apply_parallel_decorator(init='data', post='_assemble', target='for') + def bend_masks(self, crop, angle=10, src=None, dst=None): + """ Rotate part of the mask on a given angle. + Must be used for crops in (xlines, depths, inlines) format. + + Parameters + ---------- + angle : float + Rotation angle in degrees. + """ + shape = crop.shape + point_x = np.random.randint(0, shape[0]) + point_d = int(np.argmax(crop[point_x, :, :])) + + if np.sum(crop[point_x, point_d, :]) == 0.0: + return crop + + matrix = cv2.getRotationMatrix2D((point_d, point_x), angle, 1) + rotated = cv2.warpAffine(crop, matrix, (shape[1], shape[0])).reshape(shape) + + combined = np.zeros_like(crop) + if point_x >= shape[0]//2: + combined[:point_x, :, :] = crop[:point_x, :, :] + combined[point_x:, :, :] = rotated[point_x:, :, :] + else: + combined[point_x:, :, :] = crop[point_x:, :, :] + combined[:point_x, :, :] = rotated[:point_x, :, :] + return combined + + @apply_parallel_decorator(init='data', post='_assemble', target='for') + def linearize_masks(self, crop, n=3, shift=0, kind='random', width=None, src=None, dst=None): + """ Sample `n` points from the original mask and create a new mask by interpolating them. + + Parameters + ---------- + n : int + Number of points to sample. + shift : int + Maximum amplitude of random shift along the depths axis. + kind : {'random', 'linear', 'slinear', 'quadratic', 'cubic', 'previous', 'next'} + Type of interpolation to use. If 'random', then chosen randomly for each crop. + width : int + Width of interpolated lines. + """ + # Parse arguments + if kind == 'random': + kind = np.random.choice(['linear', 'slinear', 'quadratic', 'cubic', 'previous', 'next']) + if width is None: + width = np.sum(crop, axis=2) + width = int(np.round(np.mean(width[width!=0]))) + + # Choose the anchor points + axis = 1 - np.argmin(crop.shape) + *nz, _ = np.nonzero(crop) + min_, max_ = nz[axis][0], nz[axis][-1] + idx = [min_, max_] + + step = (max_ - min_) // n + for i in range(0, max_-step, step): + idx.append(np.random.randint(i, i + step)) + + # Put anchors into new mask + mask_ = np.zeros_like(crop) + slc = (idx if axis == 0 else slice(None), + idx if axis == 1 else slice(None), + slice(None)) + mask_[slc] = crop[slc] + *nz, y = np.nonzero(mask_) + + # Shift depths randomly + x = nz[axis] + y += np.random.randint(-shift, shift + 1, size=y.shape) + + # Sort and keep only unique values, based on `x` to remove width of original mask + sort_indices = np.argsort(x) + x, y = x[sort_indices], y[sort_indices] + _, unique_indices = np.unique(x, return_index=True) + x, y = x[unique_indices], y[unique_indices] + + # Interpolate points; put into mask + interpolator = interp1d(x, y, kind=kind) + indices = np.arange(min_, max_, dtype=np.int32) + depths = interpolator(indices).astype(np.int32) + + slc = (indices if axis == 0 else indices * 0, + indices if axis == 1 else indices * 0, + np.clip(depths, 0, crop.shape[2]-1)) + mask_ = np.zeros_like(crop) + mask_[slc] = 1 + + # Make horizon wider + structure = np.ones((1, width), dtype=np.uint8) + shape = mask_.shape + mask_ = mask_.reshape((mask_.shape[axis], mask_.shape[2])) + mask_ = cv2.dilate(mask_, kernel=structure, iterations=1).reshape(shape) + return mask_ + + + @apply_parallel_decorator(init='data', post='_assemble', target='for') + def smooth_labels(self, crop, eps=0.05, src=None, dst=None): + """ Smooth labeling for segmentation mask: + - change `1`'s to `1 - eps` + - change `0`'s to `eps` + Assumes that the mask is binary. + """ + label_mask = crop == 1 + crop[label_mask] = 1 - eps + crop[~label_mask] = eps + return crop + + + # Predictions + @action + @apply_parallel_decorator(init='indices', post=None, target='for') + def update_accumulator(self, ix, src, accumulator, dst=None): + """ Update accumulator with data from crops. + Allows to gradually accumulate predictions in a single instance, instead of + keeping all of them and assembling later. + + Parameters + ---------- + src : str + Component with crops. + accumulator : Accumulator3D + Container for aggregation. + """ + crop = self.get(ix, src) + location = self.get(ix, 'locations') + if self.get(ix, 'orientations') == 1: + crop = crop.transpose(1, 0, 2) + elif self.get(ix, 'orientations') == 2: + crop = crop.transpose(1, 2, 0) + accumulator.update(crop, location) + return self + + @action + @apply_parallel_decorator(init='indices', post='_masks_to_horizons_post', target='for') + def masks_to_horizons(self, ix, src, dst, threshold=0.5, mode='mean', minsize=0, prefix='predict'): + """ Convert predicted segmentation mask to a list of Horizon instances. + + Parameters + ---------- + src_masks : str + Component of batch that stores masks. + dst : str/object + Component of batch to store the resulting horizons. + threshold, mode, minsize, mean_threshold, adjacency, prefix + Passed directly to :meth:`Horizon.from_mask`. + """ + _ = dst + + # Threshold the mask, transpose and rotate the mask if needed + mask = self.get(ix, src) + if self.get(ix, 'orientations'): + mask = mask.transpose(1, 0, 2) + + field = self.get(ix, 'fields') + origin = [self.get(ix, 'locations')[k].start for k in range(3)] + horizons = Horizon.from_mask(mask, field=field, origin=origin, threshold=threshold, + mode=mode, minsize=minsize, prefix=prefix) + return horizons + + def _masks_to_horizons_post(self, horizons_lists, dst=None, **kwargs): + """ Flatten list of lists of horizons, recieved from each worker. """ + _ = kwargs + if dst is None: + raise ValueError('Specify `dst`!') + + # Check for errors, flatten lists + self.noop_post(horizons_lists, **kwargs) + setattr(self, dst, [horizon for horizon_list in horizons_lists for horizon in horizon_list]) + return self + + + @action + @apply_parallel_decorator(init='indices', target='for') + def save_masks(self, ix, src, dst=None, save_to=None, savemode='numpy', + threshold=0.5, mode='mean', minsize=0, prefix='predict'): + """ Save extracted horizons to disk. """ + os.makedirs(save_to, exist_ok=True) + + # Get correct mask + mask = self.get(ix, src) + if self.get(ix, 'orientations'): + mask = np.transpose(mask, (1, 0, 2)) + + # Get meta parameters of the mask + field = self.get(ix, 'fields') + origin = [self.get(ix, 'locations')[k].start for k in range(3)] + endpoint = [self.get(ix, 'locations')[k].stop for k in range(3)] + + # Extract surfaces + horizons = Horizon.from_mask(mask, field=field, origin=origin, mode=mode, + threshold=threshold, minsize=minsize, prefix=prefix) + + if horizons and len(horizons[-1]) > minsize: + horizon = horizons[-1] + str_location = '__'.join([f'{start}-{stop}' for start, stop in zip(origin, endpoint)]) + savepath = os.path.join(save_to, f'{prefix}_{str_location}') + + if savemode in ['numpy', 'np', 'npy']: + np.save(savepath, horizon.points) + + elif savemode in ['dump']: + horizon.dump(savepath) + + return self + + + # Actions to work with components + @action + def concat_components(self, src, dst, axis=-1): + """ Concatenate a list of components and save results to `dst` component. + + Parameters + ---------- + src : array-like + List of components to concatenate of length more than one. + dst : str + Component of batch to put results in. + axis : int + The axis along which the arrays will be joined. + """ + if len(src) == 1: + warn("Since `src` contains only one component, concatenation not needed.") + + items = [self.get(None, attr) for attr in src] + + concat_axis_size = sum(item.shape[axis] for item in items) + shape = list(items[0].shape) + shape[axis] = concat_axis_size + + buffer = np.empty(shape, dtype=np.float32) + + size_counter = 0 + slicing = [slice(None) for _ in range(axis + 1)] + for item in items: + item_size = item.shape[axis] + slicing[-1] = slice(size_counter, size_counter + item_size) + buffer[tuple(slicing)] = item + size_counter += item_size + setattr(self, dst, buffer) + return self + + @action + def transpose(self, src, order, dst=None): + """ Change order of axis. """ + #pylint: disable=access-member-before-definition + if src is None: + src = list(self.name_to_order.keys()) + + dst = dst or src + src = [src] if isinstance(src, str) else src + dst = [dst] if isinstance(dst, str) else dst + + for src_, dst_ in zip(src, dst): + current_order = self.name_to_order[src_] + data = self.get(component=src_) + + # Select correct order of axis + if order == 'channels_last': + order_ = np.argsort(data.shape[1:])[::-1] + elif isinstance(order, str): + order_ = [current_order.tolist().index(item) for item in order] + else: + order_ = list(order) + + # Update meta, transpose data with corrected on batch dimension order + self.name_to_order[src_] = current_order[list(order_)] + setattr(self, dst_, data.transpose(0, *(i+1 for i in order_))) + return self + + + @action + def adaptive_expand(self, src, dst=None, axis=1, symbol='c'): + """ Add channels dimension to 4D components if needed. + If component data has shape `(batch_size, 1, n_x, n_d)`, the same shape is kept + If component data has shape `(batch_size, n_i, n_x, n_d)` and `n_i > 1`, an axis at `axis` position is created. + """ + dst = dst or src + src = [src] if isinstance(src, str) else src + dst = [dst] if isinstance(dst, str) else dst + + for src_, dst_ in zip(src, dst): + data = self.get(component=src_) + if data.ndim == 4 and data.shape[1] != 1: + data = np.expand_dims(data, axis=axis) + self.name_to_order[src_] = np.insert(self.name_to_order[src_], axis-1, symbol) + setattr(self, dst_, data) + return self + + @action + def adaptive_squeeze(self, src, dst=None, axis=1): + """ Remove channels dimension from 5D components if needed. + If component data has shape `(batch_size, n_c, n_i, n_x, n_d)` and `axis=1 + or shape `(batch_size, n_i, n_x, n_d, n_c)` and `axis=-1` + and `n_c == 1` , axis at position `axis` will be squeezed. + """ + dst = dst or src + src = [src] if isinstance(src, str) else src + dst = [dst] if isinstance(dst, str) else dst + + for src_, dst_ in zip(src, dst): + data = self.get(component=src_) + if data.ndim == 5 and data.shape[axis] == 1: + data = np.squeeze(data, axis=axis) + self.name_to_order[src_] = np.delete(self.name_to_order[src_], axis-1) + setattr(self, dst_, data) + return self + + + # Augmentations: values + @apply_parallel_decorator(init='preallocating_init', post='noop_post', target='for') + def additive_noise(self, _, buffer, scale, **kwargs): + """ Add random value to each entry of crop. Added values are centered at 0. + + Parameters + ---------- + scale : float + Standard deviation of normal distribution. + """ + buffer += scale * self.random.standard_normal(dtype=np.float32, size=buffer.shape) + + @apply_parallel_decorator(init='preallocating_init', post='noop_post', target='for') + def multiplicative_noise(self, _, buffer, scale, **kwargs): + """ Multiply each entry of crop by random value, centered at 1. + + Parameters + ---------- + scale : float + Standard deviation of normal distribution. + """ + buffer *= 1 + scale * self.random.standard_normal(dtype=np.float32, size=buffer.shape) + + + @apply_parallel_decorator(init='preallocating_init', post='noop_post', target='for') + def translate(self, _, buffer, shift=5, scale=0.0, **kwargs): + """ Add and multiply values by uniformly sampled values. """ + shift = self.random.uniform(-shift, shift) + scale = self.random.uniform(1 - scale, 1 + scale) + + buffer += np.float32(shift) + buffer *= np.float32(scale) + + @apply_parallel_decorator(init='preallocating_init', post='noop_post', target='for') + def invert(self, _, buffer, **kwargs): + """ Change sign of values. """ + buffer *= -1 + + @apply_parallel_decorator(init='preallocating_init', post='noop_post', target='for') + def equalize(self, _, buffer, mode='default', **kwargs): + """ Apply histogram equalization. """ + #pylint: disable=import-outside-toplevel + import torch + import kornia + + tensor = torch.from_numpy(buffer) + + if mode == 'default': + tensor = kornia.enhance.equalize(tensor) + else: + tensor = kornia.enhance.equalize_clahe(tensor) + + buffer[:] = tensor.numpy() + + + @apply_parallel_decorator(init='preallocating_init', post='noop_post', target='for') + def binarize(self, _, buffer, threshold=0.5, **kwargs): + """ Binarize image by threshold. """ + buffer[:] = buffer > threshold + + + # Augmentations: geometric. `rotate_2d/3d`, `scale_2d/3d`, + # 'affine_transform', 'perspective_transform' and 'elastic_transform' are added by decorator + @apply_parallel_decorator(init='preallocating_init', post='noop_post', target='for') + def flip(self, _, buffer, axis=0, **kwargs): + """ Flip crop along the given axis. + + Parameters + ---------- + axis : int + Axis to flip along + """ + locations = [slice(None)] * buffer.ndim + locations[axis] = slice(None, None, -1) + buffer[:] = buffer[tuple(locations)] + + @apply_parallel_decorator(init='data', post='_assemble') + def center_crop(self, crop, shape, **kwargs): + """ Central crop of defined shape. """ + return functional.center_crop(crop, shape) + + @apply_parallel_decorator(init='data', post='_assemble', target='for') + def resize(self, crop, size=None, factor=2, interpolation=1, **kwargs): + """ Resize image. By default uses a bilinear interpolation.""" + if size is None: + # for 2D crop + if crop.shape[0] == 1: + h, w = int(crop.shape[1] // factor), int(crop.shape[2] // factor) + # for 3D crop + else: + h, w = int(crop.shape[0] // factor), int(crop.shape[1] // factor) + size = (h, w) + return functional.resize(array=crop, size=size, interpolation=interpolation) + + @apply_parallel_decorator(init='data', post='_assemble', target='for') + def skeletonize_seismic(self, crop, smooth=True, axis=0, width=3, sigma=3, **kwargs): + """ Perform skeletonize of seismic on 2D slide """ + if smooth: + crop = gaussian_filter(crop, sigma=sigma, mode='nearest') + crop = crop.squeeze() + skeletonized_max = skeletonize(crop, axis=axis, width=width) + skeletonized_min = skeletonize(-crop, axis=axis, width=width) + skeletonized = skeletonized_max - skeletonized_min + return skeletonized.reshape(1, *skeletonized.shape) + + + # Augmentations: geologic. `compute_instantaneous_amplitude/phase/frequency` are added by decorator + @apply_parallel_decorator(init='preallocating_init', post='noop_post', target='for') + def sign_transform(self, _, buffer, **kwargs): + """ Element-wise indication of the sign of a number. """ + buffer[:] = np.sign(buffer) + + @action + @apply_parallel_decorator(init='indices', post='_assemble', target='for') + def bandpass_filter(self, ix, src, dst, lowcut=None, highcut=None, axis=1, order=4, sign=True): + """ Keep only frequencies between `lowcut` and `highcut`. Frequency bounds `lowcut` and `highcut` + are measured in Hz. + + NOTE: use action `SeismicCropBatch.plot_frequencies` to look at the component's spectrum. The action + shows power spectrum in the same units as required here by parameters `lowcut` and `highcut`. + + Parameters + ---------- + lowcut : float + Lower bound for frequencies kept. + highcut : float + Upper bound for frequencies kept. + order : int + Filtering order. + sign : bool + Whether to keep only signs of resulting image. + """ + field = self.get(ix, 'fields') + sampling_frequency = field.sample_rate + crop = self.get(ix, src) + + sos = butter(order, [lowcut, highcut], btype='band', output='sos', fs=sampling_frequency) + filtered = sosfiltfilt(sos, crop, axis=axis) + if sign: + filtered = np.sign(filtered) + return filtered + + + # Augmentations: misc + @apply_parallel_decorator(init='preallocating_init', post='noop_post', target='for') + def gaussian_filter(self, _, buffer, axis=1, sigma=2, order=0, **kwargs): + """ Apply a gaussian filter along specified axis. """ + buffer[:] = gaussian_filter1d(buffer, sigma=sigma, axis=axis, order=order) + + + @apply_parallel_decorator(init='preallocating_init', post='noop_post', target='for', requires_rng=True) + def cutout_2d(self, _, buffer, patch_shape, n_patches, fill_value=0, rng=None, **kwargs): + """ Change patches of data to zeros. + + Parameters + ---------- + patch_shape : int or array-like + Shape of patches along each axis. If int, square patches will be generated. If array of length 2, + patch will be the same for all channels. + n_patches : number + Number of patches to cut. + fill_value : number + Value to fill patches with. + """ + # Parse arguments + if isinstance(patch_shape, (int, np.integer)): + patch_shape = np.array([patch_shape, patch_shape, buffer.shape[-1]]) + if len(patch_shape) == 2: + patch_shape = np.array([*patch_shape, buffer.shape[-1]]) + + patch_shape = np.array(patch_shape).astype(np.int32) + upper_bounds = np.clip(np.array(buffer.shape) - np.array(patch_shape), a_min=1, a_max=buffer.shape) + + # Generate locations for erasing + for _ in range(int(n_patches)): + starts = rng.integers(upper_bounds) + stops = starts + patch_shape + + slices = [slice(start, stop) for start, stop in zip(starts, stops)] + buffer[tuple(slices)] = fill_value + + + @action + def fill_bounds(self, src, dst=None, margin=0.05, fill_value=0): + """ Fill bounds of crops with `fill_value`. To remove predictions on bounds. """ + if (np.array(margin) == 0).all(): + return self + + dst = dst or src + src = [src] if isinstance(src, str) else src + dst = [dst] if isinstance(dst, str) else dst + + if isinstance(margin, (int, float)): + margin = (margin, margin, margin) + + for src_, dst_ in zip(src, dst): + crop = self.get(component=src_).copy() + pad = [int(np.floor(s) * m) if isinstance(m, float) else m for m, s in zip(margin, crop.shape[1:])] + pad = [m if s > 1 else 0 for m, s in zip(pad, crop.shape[1:])] + pad = [(item // 2, item - item // 2) for item in pad] + for i in range(3): + slices = [slice(None), slice(None), slice(None), slice(None)] + slices[i+1] = slice(pad[i][0]) + crop[slices] = fill_value + + slices[i+1] = slice(crop.shape[i+1] - pad[i][1], None) + crop[slices] = fill_value + setattr(self, dst_, crop) + return self diff --git a/seismiqb/batch/visualization_batch.py b/seismiqb/batch/visualization_batch.py new file mode 100644 index 0000000..af1505d --- /dev/null +++ b/seismiqb/batch/visualization_batch.py @@ -0,0 +1,424 @@ +""" A mixin with batch visualizations. """ +from collections import defaultdict +import numpy as np +from scipy.fft import rfftfreq, rfft + +from ..plotters import plot +from ..utils import DelegatingList, to_list + + + +class VisualizationMixin: + """ Methods for batch components visualizations. """ + @property + def default_plot_components(self): + """ Return a list of default components to plot, that are actually present in batch. """ + components = [['images'], ['masks'], ['images', 'masks'], ['predictions'], ['images', 'predictions']] + components = [items for items in components if all(hasattr(self, item) for item in items)] + return components + + def get_layer_config(self, component, layer_index, item_index, zoom, + augment_mask, augment_prediction, data_cmap, mask_cmap, mask_color): + """ Retrieve requested component from batch, preprocess its data and infer its display parameters. + + Component data is obtained by its name and index in batch. + If `zoom` parameter is provided, component is sliced according to it. + A default colormap or a color is chosen for component display based on it category (data/mask/prediction). + + Component is treated as mask if it contains 'mask' in its name. + Component is treated as prediction if it contains 'prediction' in its name and its data is in [0, 1] range. + Else component is treated as just general data. + + General data is always displayed with `data_cmap`, if `cmap` parameter is not provided explicitly. + Masks and predictions are in a way different from other data, since they have their own display scenarios. + + Specific scenario depends on whether component augmentation is enabled by `augment_mask`/`augment_prediction` + and whether component is displayed on a first subplot layers or not. + + Mask/prediction on a first subplot layer is always displayed with `mask_cmap` no matter what. + Else it is displayed with `mask_cmap` if augmentation is disabled, else it is dispalyed with `mask_color`. + + Parameters + ---------- + component : str + Name of component to plot. + layer_index : int + Index of the layer a component is displayed upon. + item_index : int + Index of batch component to retrieve. + zoom : tuple of two slices + Additional limits to show batch components in. + augment_mask: bool + If True, hide 0s in binary mask and automatically choose color for 1s. + Doesn't affect component if it is on a first subplot layer. + augment_prediction : bool or number from [0, 1] + If True, mask lower then threshold in prediction component. Threshold is 0.5 if value is True. + Doesn't affect component if it is on a first subplot layer. + data_cmap : valid matplotlib colormap + Colormap to use for general data components display. + mask_cmap : valid matplotlib colormap + Colormap to use for masks/predictions components display. + mask_color : valid matplotib color + Color to use for masks/predictions components display. + """ + data = getattr(self, component)[item_index].squeeze() + + if zoom is not None: + data = data[zoom] + + cmap = data_cmap + mask = None + vmin, vmax = None, None + + if 'mask' in component: + if not augment_mask or layer_index == 0: + augment_mask = False + cmap = mask_cmap + else: + cmap = mask_color + elif 'prediction' in component and (data.min() >= 0.0 and data.max() <= 1.0): + if augment_prediction is False or layer_index == 0: + cmap = mask_cmap + vmin, vmax = 0, 1 + else: + threshold = 0.5 if augment_prediction is True else augment_prediction + mask = f'<{threshold}' + cmap = mask_color + vmin, vmax = threshold, 1 + + config = { + 'data': data, + 'cmap': cmap, + 'mask': mask, + 'augment_mask': augment_mask, + 'vmin': vmin, + 'vmax': vmax + } + return config + + def get_plot_config(self, components, item_index, zoom, add_suptitle, add_location, + augment_mask, augment_prediction, data_cmap, mask_cmap, mask_color): + """ Retrieve requested components from batch, preprocess their data and infer parameters for their display. + + Component data is obtained by its name and index in batch. + If `zoom` parameter is provided, component is sliced according to it. + A default colormap or a color is chosen for component display based on it category (data/mask/prediction). + + Component is treated as mask if it contains 'mask' in its name. + Component is treated as prediction if it contains 'prediction' in its name and its data is in [0, 1] range. + Else component is treated as just general data. + + General data is always displayed with `data_cmap`, if `cmap` parameter is not provided explicitly. + Masks and predictions are in a way different from other data, since they have their own display scenarios. + + Specific scenario depends on whether component augmentation is enabled by `augment_mask`/`augment_prediction` + and whether component is displayed on a first subplot layers or not. + + Mask/prediction on a first subplot layer is always displayed with `mask_cmap` no matter what. + Else it is displayed with `mask_cmap` if augmentation is disabled, else it is dispalyed with `mask_color`. + + Parameters + ---------- + components : double nested list of str + Names of component to plot arranged in order of their display on subplots/layers. + item_index : int + Index of batch component to retrieve. + zoom : tuple of two slices + Additional limits to show batch components in. + add_suptitle : bool + If True, display suptitle with batch item index, field name (if it exists) and location info (if requested). + add_location : bool, str or iterable of str + If True or 'suptitle', add location info to suptitle. If 'title', add location info to title. + If 'ticks', replace ticks labels from relative (e.g. from 0 to 256) to absolute (e.g. from 1056 to 1312). + If list, add location info to corresponding annotation objects ('suptitle', 'title', 'ticks'). + augment_mask: bool + If True, hide 0s in binary mask and automatically choose color for 1s. + Doesn't affect component if it is on a first subplot layer. + augment_prediction : bool or number from [0, 1] + If True, mask lower then threshold in prediction component. Threshold is 0.5 if value is True. + Doesn't affect component if it is on a first subplot layer. + data_cmap : valid matplotlib colormap + Colormap to use for general data components display. + mask_cmap : valid matplotlib colormap + Colormap to use for masks/predictions components display. + mask_color : valid matplotib color + Color to use for masks/predictions components display. + """ + # pylint: disable=too-many-statements + # Make plot config layer-wise + layers_indices = list(map(lambda item: list(range(len(item))), components)) + config = components.map(self.get_layer_config, layers_indices, item_index=item_index, zoom=zoom, + augment_mask=augment_mask, augment_prediction=augment_prediction, + data_cmap=data_cmap, mask_cmap=mask_cmap, mask_color=mask_color) + config = config.to_dict() + + # Infer slide extent from its location and zoom + location = self.locations[item_index] + labels = ['INLINE', 'CROSSLINE', 'DEPTH'] + for x, y, z in [[0, 1, 2], [0, 2, 1], [1, 2, 0]]: + if location[z].stop - location[z].start == 1: + x_label = labels[x] + x_start, x_stop = location[x].start, location[x].stop + + y_label = labels[y] + y_start, y_stop = location[y].start, location[y].stop + + z_label = labels[z] + z_start = location[z].start + + if zoom is not None: + x_zoom, y_zoom = zoom + + if x_zoom.start is not None: + x_start = x_start + x_zoom.start + if x_zoom.stop is not None: + if x_zoom.stop >= 0: + x_stop = x_start + x_zoom.stop + else: + x_stop = x_stop + zoom[0].stop + 1 + + if y_zoom.start is not None: + y_start = y_start + y_zoom.start + if y_zoom.stop is not None: + if y_zoom.stop >= 0: + y_stop = y_stop + y_zoom.stop + else: + y_stop = y_stop + y_zoom.stop + 1 + break + else: + raise ValueError("Data must be 2D or pseudo-3D.") + + # Annotate x and y axes + config['xlabel'] = x_label + config['ylabel'] = y_label + if 'ticks' in add_location: + config['extent'] = (x_start, x_stop, y_stop, y_start) + + location_info = f"{z_label}={z_start}", f"{x_label} <{x_start}:{x_stop}>", f"{y_label} <{y_start}:{y_stop}>" + + # Construct suptitle + if add_suptitle: + suptitle = f'batch item #{item_index}' + + batch_index = self.indices[item_index] + field = self.get(batch_index, 'fields') + if hasattr(field, 'short_name'): + suptitle += f' | field `{field.short_name}`' + + if 'suptitle' in add_location: + suptitle += '\n' + ' '.join(location_info) + config['suptitle'] = suptitle + + # Make titles for individual axis + title = [', '.join(item) for item in components] + if 'title' in add_location: + for axis_index, axis_info in enumerate(location_info[:len(title)]): + title[axis_index] += '\n' + axis_info + config['title'] = title + + return config + + def plot(self, components=None, idx=0, zoom=None, add_suptitle=True, add_location='suptitle', augment_mask=True, + augment_prediction=True, data_cmap='Greys_r', mask_cmap='gist_heat', mask_color='darkorange', **kwargs): + """ Plot requested batch components. + + Parameters + ---------- + components : double nested list of str + Names of component to plot arranged in order of their display on subplots/layers. + idx : int + Index of batch component to retrieve. + zoom : tuple of two slices + Additional limits to show batch components in. + add_suptitle : bool + If True, display suptitle with batch item index, field name (if it exists) and location info (if requested). + add_location : bool, str or iterable of str + If True or 'suptitle', add location info to suptitle. If 'title', add location info to title. + If 'ticks', replace ticks labels from relative (e.g. from 0 to 256) to absolute (e.g. from 1056 to 1312). + If list, add location info to corresponding annotation objects ('suptitle', 'title', 'ticks'). + augment_mask: bool + If True, hide 0s in binary mask and automatically choose color for 1s. + Doesn't affect component if it is on a first subplot layer. + augment_prediction : bool or number from [0, 1] + If True, mask lower then threshold in prediction component. Threshold is 0.5 if value is True. + Doesn't affect component if it is on a first subplot layer. + data_cmap : valid matplotlib colormap + Colormap to use for general data components display. + mask_cmap : valid matplotlib colormap + Colormap to use for masks/predictions components display. + mask_color : valid matplotib color + Color to use for masks/predictions components display. + kwargs : misc + For `batchflow.plot`. + """ + if components is None: + components = self.default_plot_components + elif isinstance(components, str): + components = [[components]] + else: + components = [to_list(item) for item in components] + components = DelegatingList(components) + + if add_location is False: + add_location = [] + elif add_location is True: + add_location = ['suptitle'] + else: + add_location = to_list(add_location) + + config = self.get_plot_config(components=components, item_index=idx, zoom=zoom, + add_suptitle=add_suptitle, add_location=add_location, + augment_mask=augment_mask, augment_prediction=augment_prediction, + data_cmap=data_cmap, mask_cmap=mask_cmap, mask_color=mask_color) + + config = { + 'scale': 0.8, + **config, + **kwargs + } + + if 'ncols' not in config and 'nrows' not in config: + config['ncols'] = len(config['data']) + + return plot(**config) + + def plot_roll(self, n=1, components=None, indices=None, zoom=None, + add_location='title', augment_mask=True, augment_prediction=True, + data_cmap='Greys_r', mask_cmap='gist_heat', mask_color='darkorange', **kwargs): + """ Plot requested components of batch items with specified indices if provided, else choose indices randomly. + + Parameters + ---------- + n : int + Number of batch indices to sample. Not used, when `indices` provided. + components : double nested list of str + Names of component to plot arranged in order of their display on subplots/layers. + indices : int or list of int + Indices of batch component to retrieve. + zoom : tuple of two slices + Additional limits to show batch components in. + add_location : bool, str or iterable of str + If True or 'title', add location info to title. + If 'ticks', replace ticks labels from relative (e.g. from 0 to 256) to absolute (e.g. from 1056 to 1312). + If list, add location info to corresponding annotation objects ('title', 'ticks'). + augment_mask: bool + If True, hide 0s in binary mask and automatically choose color for 1s. + Doesn't affect component if it is on a first subplot layer. + augment_prediction : bool or number from [0, 1] + If True, mask lower then threshold in prediction component. Threshold is 0.5 if value is True. + Doesn't affect component if it is on a first subplot layer. + data_cmap : valid matplotlib colormap + Colormap to use for general data components display. + mask_cmap : valid matplotlib colormap + Colormap to use for masks/predictions components display. + mask_color : valid matplotib color + Color to use for masks/predictions components display. + kwargs : misc + For `batchflow.plot`. + """ + if components is None: + components = self.default_plot_components + elif isinstance(components, str): + components = [[components]] + else: + components = [to_list(item) for item in components] + components = DelegatingList(components) + + if add_location is False: + add_location = [] + elif add_location is True: + add_location = ['title'] + else: + add_location = to_list(add_location) + + if indices is None: + indices = self.random.choice(len(self), size=min(n, len(self)), replace=False) + else: + indices = to_list(indices) + + config = defaultdict(list) + for idx in indices: + config_idx = self.get_plot_config(components=components, item_index=idx, zoom=zoom, + add_suptitle=False, add_location=add_location, + augment_mask=augment_mask, augment_prediction=augment_prediction, + data_cmap=data_cmap, mask_cmap=mask_cmap, mask_color=mask_color) + for name, value in config_idx.items(): + if not isinstance(value, list): + value = [value] * len(components) + config[name].extend(value) + + config = { + 'scale': 0.8, + **config, + **kwargs + } + + if 'ncols' not in config and 'nrows' not in config: + config['ncols'] = len(components) + + return plot(**config) + + def plot_frequencies(self, indices=(0, ), src='images', trace_indices=((0, 0), (-1, -1)), axis=2, + sample_interval=None, displayed_name=None, **kwargs): + """ Show Fourier frequency spectrum of a component. X-axis of the plot corresponds to frequency + values in Hz while y-axis stands for amplitudes of specific frequencies. + + The method selects for the analysis specific traces and batch items. Traces are 1d slices + taken along the chosen axis. + + Uses Hz as x-axis units. + + Parameters + ---------- + indices : int or sequence of int + Takes items with these indices to demonstrate the spectrum. + src : str + The component, which spectrum is shown. + trace_indices : sequence of tuples + Uses traces with these indices. + axis : int + Axis along which traces are taken. By default set to 2. This value correpsonds + to depth, which is the most natural direction to research the spectrum. + sample_interval : float or None + Inverse of the sampling rate. Measured in seconds. The same argument that `scipy.fftpack.fftfreq` + uses under the name of `d`. Specifies units of the x-axis of the spectrum plot. If set to + None, `show_frequencies` uses Hz (`1000 / (sample rate in ms)`). In this way, x-axis units correspond + to units of `lowcut`/ `highcut` arguments of `SeismicCropBatch.bandpass_filter`. + displayed_name : str or None + Whenever supplied, assumes that traces are taken from field with this name. + kwargs : dict + Arguments for customizing plot. For instance, removing/changing labels and titles. + """ + indices = indices if isinstance(indices, (list, tuple)) else (indices, ) + insert_index = len(trace_indices[0]) if axis == -1 else axis + plot_data = [] + plot_label = [] + + # Iterate over item-indices and traces, gather info about spectrum. + for idx in indices: + field = self.get(self.indices[idx], 'fields') + sample_interval = sample_interval or field.sample_interval + + # Try to get the name of a field + if displayed_name is None: + displayed_name = field.displayed_name + + data = self.get(self.indices[idx], src) + frequencies = rfftfreq(data.shape[axis], sample_interval) # `rfftfreq` is responsible for choosing units + # of x-axis and expects `sample_spacing` in seconds + + for trace_idx in trace_indices: + trace_idx_ = tuple(np.insert(np.array(trace_idx, dtype=np.object_), insert_index, slice(0, None))) + amplitudes = rfft(data[trace_idx_]) + plot_data.append((frequencies, np.abs(amplitudes))) + plot_label.append(f'FIELD: {displayed_name} IDX: {idx} TRACE: {trace_idx}') + + plot_params = {'title': f'Spectrum of {src}-component', + 'label': plot_label, + 'xlabel': 'Frequency, Hz', + 'ylabel': 'Amplitude'} + kwargs = { + **plot_params, + **kwargs + } + return plot(plot_data, mode='curve', **kwargs) diff --git a/seismiqb/dataset.py b/seismiqb/dataset.py new file mode 100644 index 0000000..c9f1322 --- /dev/null +++ b/seismiqb/dataset.py @@ -0,0 +1,258 @@ +""" Container for storing seismic data and labels. """ +#pylint: disable=too-many-lines, too-many-arguments +from textwrap import indent + +import numpy as np +import pandas as pd + +from batchflow import DatasetIndex, Dataset, Pipeline + +from .field import Field, SyntheticField +from .geometry import Geometry +from .batch import SeismicCropBatch +from .utils import AugmentedDict +from .plotters import plot + +class SeismicDataset(Dataset): + """ Container of fields. + + Getitem is re-defined to index stored fields. + Getattr is re-defined to return the same attributes from all stored fields, wrapped into `AugmentedDict`. + + Can be initialized with: + - a nested dictionary, where keys are field-like entities (path to seismic cube, instance of Geometry or Field), + and values are either: + - dictionary with keys defining attribute to store loaded labels in and values as + sequences of label-like entities (path to a label or instance of label class) + - sequence with label-like entities. This way, labels will be stored in `labels` attribute + - string to define path(s) to labels (same as those paths wrapped in a list) + - None as a signal that no labels are provided for a field. + - a sequence with field-like entities (same as dictionary where every value is None) + - one field-like entity (same as sequence with only one element) + Named arguments are passed for each field initialization. + """ + #pylint: disable=keyword-arg-before-vararg + def __init__(self, index, batch_class=SeismicCropBatch, *args, **kwargs): + if args: + raise TypeError('Positional args are not allowed for `SeismicDataset` initialization!') + + # Convert `index` to a dictionary + if isinstance(index, (str, Geometry, Field, SyntheticField)): + index = [index] + if isinstance(index, (tuple, list, DatasetIndex)): + index = {item : None for item in index} + + if isinstance(index, dict): + self.fields = AugmentedDict() + for field_idx, labels_idx in index.items(): + if isinstance(field_idx, (Field, SyntheticField)): + field = field_idx + if labels_idx is not None: + field.load_labels(labels=labels_idx, **kwargs) + else: + field = Field(geometry=field_idx, labels=labels_idx, **kwargs) + + self.fields[field.short_name] = field + else: + raise TypeError('Dataset should be initialized with a string, a ready-to-use Geometry or Field,' + f' sequence or a dict, got {type(index)} instead.') + + dataset_index = DatasetIndex(list(self.fields.keys())) + super().__init__(dataset_index, batch_class=batch_class) + self._names = None + + @classmethod + def from_horizon(cls, horizon): + """ Create dataset from an instance of Horizon. """ + return cls({horizon.field.geometry : {'horizons': [horizon]}}) + + + # Inner workings + def __getitem__(self, key): + """ Index a field with either its name or ordinal. """ + if isinstance(key, (int, np.integer, str)): + return self.fields[key] + raise KeyError(f'Unsupported key for subscripting, {key}') + + + def get_nested_iterable(self, attribute): + """ Create an `AugmentedDict` with field ids as keys and their `attribute` as values. + For example, `dataset.get_nested_iterable('labels')` would + return an `AugmentedDict` with labels for every field. + """ + return AugmentedDict({idx : getattr(field, attribute) for idx, field in self.fields.items()}) + + def __getattr__(self, key): + """ Create nested iterables for a key. + For example, `dataset.labels` would return an `AugmentedDict` with labels for every field. + """ + if isinstance(key, str) and key not in self.indices: + return self.get_nested_iterable(key) + raise AttributeError(f'Unknown attribute {key}') + + @property + def names(self): + """ 2D index of available fields and labels. """ + if self._names is None: + names = {} + for i, (field_name, field_labels) in enumerate(self.labels.items()): + for j, label in enumerate(field_labels): + names[(i, j)] = field_name, label.short_name + self._names = names + return self._names + + def to_names(self, id_array): + """ Convert the first two columns of sampled locations into field and label string names. """ + return np.array([self.names[tuple(ids)] for ids in id_array]) + + + def gen_batch(self, batch_size=None, shuffle=False, n_iters=None, n_epochs=None, drop_last=False, **kwargs): + """ Remove `n_epochs` and `drop_last` from passed arguments. + Set default value `batch_size` to the size of current dataset, removing the need to + pass it to `next_batch` and `run` methods. + """ + if (n_epochs is not None and n_epochs != 1) or drop_last: + raise TypeError(f'`SeismicCubeset` does not work with `n_epochs`, `shuffle` or `drop_last`!' + f'`{n_epochs}`, `{shuffle}`, `{drop_last}`') + + batch_size = batch_size or len(self) + return super().gen_batch(batch_size, n_iters=n_iters, shuffle=shuffle, **kwargs) + + + # Default pipeline and batch for fast testing / introspection + def data_pipeline(self, sampler, batch_size=4, width=4): + """ Pipeline with default actions of creating locations, loading seismic images and corresponding masks. """ + return (self.p + .make_locations(generator=sampler, batch_size=batch_size) + .create_masks(dst='masks', width=width) + .load_cubes(dst='images') + .adaptive_reshape(src=['images', 'masks']) + .normalize(src='images')) + + def data_batch(self, sampler, batch_size=4, width=4): + """ Get one batch of `:meth:.data_pipeline` with `images` and `masks`. """ + return self.data_pipeline(sampler=sampler, batch_size=batch_size, width=width).next_batch() + + + # Textual and visual representation of dataset contents + def __str__(self): + msg = f'Seismic Dataset with {len(self)} field{"s" if len(self) > 1 else ""}:\n' + msg += '\n\n'.join([indent(str(field), prefix=' ') for field in self.fields.values()]) + return msg + + + def show_slide(self, loc, idx=0, axis='iline', zoom=None, src_labels='labels', + indices='all', width=5, plotter=plot, **kwargs): + """ Show slide of the given cube on the given line. + + Parameters + ---------- + loc : int + Number of slide to load. + idx : str, int + Number of cube in the index to use. + axis : int or str + Number or name of axis to load slide along. + zoom : tuple of slices, None or 'auto' + Tuple of slices to apply directly to 2d images. If None, slicing is not applied. + If 'auto', zero traces on bounds will be dropped. + src_labels : str + Dataset components to show as labels. + indices : str, int or sequence of ints + Which labels to use in mask creation. + If 'all', then use all labels. + If 'single' or `random`, then use one random label. + If int or array-like, then element(s) are interpreted as indices of desired labels. + width : int + Width of the resulting label. + plotter : instance of `plot` + Plotter instance to use. + Combined with `positions` parameter allows using subplots of already existing plotter. + """ + components = ('images', 'masks') if getattr(self, src_labels)[idx] else ('images',) + cube_name = self.indices[idx] + geometry = self.fields[cube_name].geometry + crop_shape = np.array(geometry.shape) + + axis = geometry.parse_axis(axis) + crop_shape[axis] = 1 + + location = np.zeros((1, 9), dtype=np.int32) + location[0, 2] = axis + location[0, axis + 3] = loc + location[0, axis + 6] = loc + location[0, [6, 7, 8]] += crop_shape + + # Fake generator with one point only + generator = lambda batch_size: location + generator.to_names = lambda array: np.array([[cube_name, 'unknown']]) + + pipeline = (Pipeline() + .make_locations(generator=generator) + .load_cubes(dst='images', src_labels=src_labels) + .normalize(src='images')) + + if 'masks' in components: + labels_pipeline = (Pipeline() + .create_masks(src_labels=src_labels, dst='masks', width=width, indices=indices)) + + pipeline = pipeline + labels_pipeline + + batch = (pipeline << self).next_batch() + # TODO: Make every horizon mask creation individual to allow their distinction while plot. + data = [np.squeeze(getattr(batch, comp)) for comp in components] + xmin, xmax, ymin, ymax = 0, data[0].shape[0], data[0].shape[1], 0 + + if zoom == 'auto': + zoom = geometry.compute_auto_zoom(loc, axis) + if zoom: + data = [image[zoom] for image in data] + xmin = zoom[0].start or xmin + xmax = zoom[0].stop or xmax + ymin = zoom[1].stop or ymin + ymax = zoom[1].start or ymax + + # Plotting defaults + header = geometry.axis_names[axis] + total = geometry.shape[axis] + + if axis in [0, 1]: + xlabel = geometry.index_headers[1 - axis] + ylabel = 'DEPTH' + if axis == 2: + xlabel = geometry.index_headers[0] + ylabel = geometry.index_headers[1] + + kwargs = { + 'cmap': ['Greys_r', 'darkorange'], + 'title': f'Data slice on cube `{geometry.short_name}`\n {header} {loc} out of {total}', + 'xlabel': xlabel, + 'ylabel': ylabel, + 'extent': (xmin, xmax, ymin, ymax), + 'legend': src_labels, + 'augment_mask': [False, True], + **kwargs + } + + return plotter(data, **kwargs) + + # Facies + def evaluate_facies(self, src_horizons, src_true=None, src_pred=None, metrics='dice'): + """ Calculate facies metrics for requested labels of the dataset and return dataframe of results. + + Parameters + ---------- + scr_horizons : str + Name of field attribute that contains base horizons. + src_true : str + Name of field attribute that contains ground-truth labels. + src_pred : str + Name of field attribute that contains predicted labels. + metrics: str or list of str + Metrics function(s) to calculate. + """ + metrics_values = self.fields.evaluate_facies(src_horizons=src_horizons, src_true=src_true, + src_pred=src_pred, metrics=metrics) + result = pd.concat(metrics_values.flat) + + return result diff --git a/seismiqb/field/__init__.py b/seismiqb/field/__init__.py new file mode 100644 index 0000000..5458fca --- /dev/null +++ b/seismiqb/field/__init__.py @@ -0,0 +1,3 @@ +""" A container for all information about the field: geometry and labels, as well as convenient API. """ +from .base import Field +from .synthetic import SyntheticField diff --git a/seismiqb/field/base.py b/seismiqb/field/base.py new file mode 100644 index 0000000..54a6bee --- /dev/null +++ b/seismiqb/field/base.py @@ -0,0 +1,486 @@ +""" A container for all information about the field: geometry and labels, as well as convenient API. """ +import os +import re +import itertools +from glob import glob +from difflib import get_close_matches +from concurrent.futures import ThreadPoolExecutor + +import numpy as np + +from batchflow.notifier import Notifier + +from .visualization import VisualizationMixin +from ..geometry import Geometry +from ..labels import Horizon, Fault +from ..metrics import FaciesMetrics +from ..utils import AugmentedList +from ..utils import CharismaMixin + + + +class Field(CharismaMixin, VisualizationMixin): + """ A common container for all information about the field: cube geometry and various labels. + + To initialize, one must provide: + - geometry-like entity, which can be a path to a seismic cube or instance of `:class:Geometry`; + additional parameters of geometry instantiation can be passed via `geometry_kwargs` parameters. + + - optionally, `labels` in one of the following formats: + - dictionary with keys defining attribute to store loaded labels in and values as + sequences of label-like entities (path to a label or instance of label class) + - sequence with label-like entities. This way, labels will be stored in `labels` attribute + - string to define path(s) to labels (same as those paths wrapped in a list) + - None as a signal that no labels are provided for a field. + + - `labels_class` defines the class to use for loading and can be supplied in one of the following formats: + - dictionary with same keys as in `labels`. Values are either string (e.g. `horizon`) or + the type to initialize label itself (e.g. `:class:.Horizon`) + - a single string or type to use for all of the labels + - if not provided, we try to infer the class from name of the attribute to store the labels in. + The guess is based on a similarity between passed name and a list of pre-defined label types. + For example, `horizons` will be threated as `horizon` and loaded as such. + >>> {'horizons': 'path/to/horizons/*'} + would be loaded as instances of `:class:.Horizon`. + + - `labels_kwargs` are passed for instantiation of every label. + + Examples + -------- + Initialize field with only geometry: + >>> Field(geometry='path/to/cube.sgy') + >>> Field(geometry=Geometry(...)) + + The most complete labels definition: + >>> Field(geometry=..., labels={'horizons': ['path/to/horizon', Horizon(...)], + 'fans': 'paths/to/fans/*', + 'faults': ['path/to/fault1', 'path/to/fault2', ], + 'lift_geometry': 'path/to/geometry_target.hdf5'}) + + Use a `labels_class` instead; this way, all of the labels are stored as `labels` attribute, no matter the class: + >>> Field(geometry=..., labels='paths/*', labels_class='horizon') + >>> Field(geometry=..., labels=['paths/1', 'paths/2', 'paths/3'], labels_class='fault') + """ + #pylint: disable=redefined-builtin + def __init__(self, geometry, labels=None, labels_class=None, geometry_kwargs=None, labels_kwargs=None, **kwargs): + # Attributes + self.labels = [] + self.horizons, self.facies, self.fans, self.channels, self.faults = [], [], [], [], [] + self.loaded_labels = [] + + # Geometry: description and convenient API to a seismic cube + if isinstance(geometry, str): + geometry_kwargs = geometry_kwargs or {} + geometry = Geometry.new(geometry, **{**kwargs, **geometry_kwargs}) + self.geometry = geometry + + # Labels: objects on a field + if labels: + labels_kwargs = labels_kwargs or {} + self.load_labels(labels, labels_class, **{**kwargs, **labels_kwargs}) + + + # Label initialization inner workings + METHOD_TO_NAMES = { + '_load_horizons': ['horizon', 'facies', 'fans', 'channels', Horizon], + '_load_faults': ['fault', Fault], + '_load_geometries': ['geometries', 'geometry', Geometry], + } + NAME_TO_METHOD = {name: method for method, names in METHOD_TO_NAMES.items() for name in names} + + def load_labels(self, labels=None, labels_class=None, mode='w', **labels_kwargs): + """ Load labels and store them in the instance. Refer to the class documentation for details. """ + if isinstance(labels, str): + labels = self.make_path(labels, makedirs=False) + labels = glob(labels) + if isinstance(labels, (tuple, list)): + labels = {'labels': labels} + if not isinstance(labels, dict): + raise TypeError(f'Labels type should be `str`, `sequence` or `dict`, got {type(labels)} instead!') + + # Labels class: make a dictionary + if labels_class is None: + labels_class_dict = {label_dst : None for label_dst in labels.keys()} + if isinstance(labels_class, (type, str)): + labels_class_dict = {label_dst : labels_class for label_dst in labels.keys()} + if isinstance(labels_class, dict): + labels_class_dict = labels_class + + for label_dst, label_src in labels.items(): + # Try getting provided `labels_class`, else fallback on NAME_TO_METHOD closest match + label_class = labels_class_dict.get(label_dst) + + if label_class is None: + # Roughly equivalent to ``label_class = self.NAME_TO_METHOD.get(label_dst)`` + str_names = [name for name in (self.NAME_TO_METHOD.keys()) + if isinstance(name, str)] + matched = get_close_matches(label_dst, str_names, n=1) + if matched: + label_class = matched[0] + + if label_class is None: + raise TypeError(f"Can't determine the label class for `{label_dst}`!") + + if isinstance(label_class, str): + method = self.NAME_TO_METHOD[label_class] + label_class = self.METHOD_TO_NAMES[method][-1] + + # Process paths: get rid of service files + if isinstance(label_src, str): + label_src = self.make_path(label_src, makedirs=False) + label_src = glob(label_src) + if not isinstance(label_src, (tuple, list)): + label_src = [label_src] + label_src = self._filter_paths(label_src) + + # Load desired labels, based on class + method_name = self.NAME_TO_METHOD[label_class] + method = getattr(self, method_name) + result = method(label_src, label_class=label_class, **labels_kwargs) + + if mode == 'w': + setattr(self, label_dst, result) + self.loaded_labels.append(label_dst) + else: + if not hasattr(self, label_dst): + setattr(self, label_dst, AugmentedList()) + else: + getattr(self, label_dst).extend(result) + + if label_dst not in self.loaded_labels: + self.loaded_labels.append(label_dst) + + if 'labels' not in labels and not self.labels: + setattr(self, 'labels', result) + + @staticmethod + def _filter_paths(paths): + """ Remove paths for service files. """ + return [path for path in paths + if not isinstance(path, str) or \ + not any(ext in path for ext in ['.dvc', '.gitignore', '.meta', '.sgy_meta'])] + + def _load_horizons(self, paths, max_workers=4, filter=True, interpolate=False, sort=True, + label_class=Horizon, **kwargs): + """ Load horizons from paths or re-use already created ones. """ + # Separate paths from ready-to-use instances + horizons, paths_to_load = [], [] + for item in paths: + if isinstance(item, str): + paths_ = self._filter_paths(glob(item)) + paths_to_load.extend(paths_) + + elif isinstance(item, label_class): + item.field = self + horizons.append(item) + + # Load from paths in multiple threads + with ThreadPoolExecutor(max_workers=min(max_workers, len(paths_to_load) or 1)) as executor: + function = lambda path: self._load_horizon(path, filter=filter, interpolate=interpolate, + constructor_class=label_class, **kwargs) + loaded = list(executor.map(function, paths_to_load)) + horizons.extend(loaded) + + if sort: + sort = sort if isinstance(sort, str) else 'd_mean' + horizons.sort(key=lambda label: getattr(label, sort)) + return horizons + + def _load_horizon(self, path, filter=True, interpolate=False, constructor_class=Horizon, **kwargs): + """ Load a single horizon from path. """ + horizon = constructor_class(path, field=self, **kwargs) + if filter: + horizon.filter(inplace=True) + if interpolate: + horizon.interpolate(inplace=True) + return horizon + + + def _load_faults(self, paths, max_workers=4, pbar='t', interpolate=False, label_class=Fault, **kwargs): + """ Load faults from paths. """ + with ThreadPoolExecutor(max_workers=min(max_workers, len(paths) or 1)) as executor: + function = lambda path: self._load_fault(path, interpolate=interpolate, + constructor_class=label_class, **kwargs) + loaded = list(Notifier(pbar, total=len(paths))(executor.map(function, paths))) + + faults = [fault for fault in itertools.chain(*loaded) if len(fault) > 0] + return faults + + def _load_fault(self, path, interpolate=False, constructor_class=Fault, **kwargs): + """ Load a single fault from path. """ + if isinstance(path, constructor_class): + path.field = self + return [path] + + faults = constructor_class.load(path, self, interpolate=interpolate, **kwargs) + return faults + + def _load_geometries(self, paths, constructor_class=Geometry.new, **kwargs): + if isinstance(paths, str): + path = paths + if isinstance(paths, (tuple, list)): + if not paths: + raise FileNotFoundError('No such file or directory') + if len(paths) > 1: + raise ValueError(f'Path for Geometry loading is non-unique!, {paths}') + path = paths[0] + return constructor_class(path, **kwargs) + + + # Other methods of initialization + @classmethod + def from_horizon(cls, horizon): + """ Create a field from a single horizon. """ + return cls(geometry=horizon.geometry, labels={'horizons': horizon}) + + @classmethod + def from_dvc(cls, tag, dvc_path=''): + """ Create a field from a dvc tag. """ + + + # Inner workings + def __getattr__(self, key): + """ Redirect calls for missing attributes, properties and methods to `geometry`. """ + if not key.endswith('state__') and 'geometry' in self.__dict__ and hasattr(self.geometry, key): + return getattr(self.geometry, key) + raise AttributeError(f'Attribute `{key}` does not exist in either Field or associated Geometry!') + + def __getattribute__(self, key): + """ Wrap every accessed list with `AugmentedList`. + The wrapped attribute is re-stored in the instance, so that we return the same object as in the instance. """ + result = super().__getattribute__(key) + if isinstance(result, list) and not isinstance(result, AugmentedList): + result = AugmentedList(result) + if not (key in vars(self.__class__) and isinstance(getattr(self.__class__, key), property)): + setattr(self, key, result) + return result + + + # Methods to call from Batch + def load_seismic(self, locations, src='geometry', buffer=None, **kwargs): + """ Load data from cube. + + Parameters + ---------- + locations : sequence + A triplet of slices to specify the location of a subvolume. + src : str + Attribute with desired geometry. + """ + _ = kwargs + geometry = getattr(self, src) + if buffer is None: + shape = geometry.locations_to_shape(locations) + buffer = np.empty(shape, dtype=np.float32) + + geometry.load_crop(locations, buffer=buffer) + return buffer + + def make_mask(self, locations, orientation=0, buffer=None, indices='all', width=3, src='labels', + sparse=False, enumerate_labels=False, **kwargs): + """ Create masks from labels. + + Parameters + ---------- + location : int or sequence + If integer, then location along specified `axis`. + Otherwise, a triplet of slices to define exact location in the cube. + axis : int or str + Axis identifier. must be provided if `location` is integer. + indices : str, int or sequence of ints + Which labels to use in mask creation. + If 'all', then use all labels. + If 'single' or `random`, then use one random label. + If int or array-like, then element(s) are interpreted as indices of desired labels. + width : int + Width of the resulting label. + src : str + Attribute with desired labels. + sparse : bool + Create mask only for labeled slices (for Faults). Unlabeled slices will be marked by -1. + enumerate_labels : bool + Whether to use enumeration as mask values for successive labels. + """ + # Parse buffer + if buffer is None: + shape = self.geometry.locations_to_shape(locations) + buffer = np.zeros(shape, dtype=np.float32) + + if sparse: + buffer -= 1 + + # Parse requested labels + labels = getattr(self, src) + labels = [labels] if not isinstance(labels, (tuple, list)) else labels + if len(labels) == 0: + return buffer + + indices = [indices] if isinstance(indices, int) else indices + if isinstance(indices, (tuple, list, np.ndarray)): + labels = [labels[idx] for idx in indices] + + # Add mask of each component to the buffer + for i, label in enumerate(labels, start=1): + alpha = 1 if enumerate_labels is False else i + label.add_to_mask(buffer, locations=locations, width=width, axis=orientation, + sparse=sparse, alpha=alpha, **kwargs) + return buffer + + + def make_regression_mask(self, location, axis=None, indices='all', src='labels', **kwargs): + """ Create regression mask from labels. Works only with horizons. """ + # + labels = getattr(self, src) + labels = [labels] if not isinstance(labels, (tuple, list)) else labels + + if len(labels) > 1: + pass + else: + shape = tuple(slc.stop - slc.start for slc in location[:2]) + mask = np.full((*shape, 1), -1, dtype=np.float32) + labels[0].add_to_regression_mask(mask=mask[..., 0], locations=location, **kwargs) + return mask + + + # Attribute retrieval + def load_attribute(self, src, _return_label=False, **kwargs): + """ Load desired geological attribute from geometry or labels. + + Parameters + ---------- + src : str + Identificator of `what` to load and `from where`. + The part before the slash identifies the instance, for example: `geometry`, `horizons:0`, `faults:123`. + In general it is `attribute_name:idx`, where `attribute_name` is the attribute to retrieve, and + optional `idx` can be used to slice it. + The part after the slash is passed directly to instance's `load_attribute` method. + kwargs : dict + Additional parameters for attribute computation. + """ + # Prepare `src` + src = src.strip('/') + if '/' not in src: + src = 'geometry/' + src + + label_id, *src = src.split('/') + src = '/'.join(src) + + # Select instance + if any(sep in label_id for sep in ':-'): + label_attr, label_idx = re.split(':|-', label_id) + + if label_attr not in self.loaded_labels: + raise ValueError(f"Can't determine the label attribute for `{label_attr}`!") + label_idx = int(label_idx) + label = getattr(self, label_attr)[label_idx] + else: + label = getattr(self, label_id) + + data = label.load_attribute(src, **kwargs) + + if _return_label: + return data, label + return data + + @property + def available_attributes(self): + """ A list of all load-able attributes from a current field. """ + #pylint: disable=unidiomatic-typecheck + available_names = [] + + for name in ['geometry'] + self.loaded_labels: + labels = getattr(self, name) + + if isinstance(labels, list): + for idx, label in enumerate(labels): + if type(label) is Horizon: + available_attributes = ['depths', 'amplitudes', 'metrics', + 'instant_amplitudes', 'instant_phases', + 'fourier_decomposition', 'wavelet_decomposition'] + else: + available_attributes = [] + available_names.extend([f'{name}:{idx}/{attr}' for attr in available_attributes]) + else: + if isinstance(labels, Geometry): + available_attributes = ['mean_matrix', 'std_matrix', 'snr'] + available_names.extend([f'{name}/{attr}' for attr in available_attributes]) + return available_names + + + # Utility functions + def make_path(self, path, name=None, makedirs=True): + """ Make path by mapping some of the symbols into pre-defined strings: + - `**` or `%` is replaced with basedir of a cube + - `*` is replaced with `name` + + Parameters + ---------- + path : str + Path to process. + name : str + Replacement for `*` symbol. + makedirs : bool + Whether to make dirs preceding the path. + """ + basedir = os.path.dirname(self.path) + name = name or self.short_name + + path = (path.replace('~', basedir) + .replace('$', name) + .replace('//', '/')) + + if makedirs and os.path.dirname(path): + os.makedirs(os.path.dirname(path), exist_ok=True) + return path + + + # Cache: introspection and reset + @property + def attached_instances(self): + """ All correctly loaded/added instances. """ + instances = [] + for src in self.loaded_labels: + item = getattr(self, src) + if isinstance(item, list): + instances.extend(item) + else: + instances.append(item) + return instances + + def reset_cache(self): + """ Clear cached data from underlying entities. """ + self.geometry.reset_cache() + self.attached_instances.reset_cache() + + @property + def cache_nbytes(self): + """ Total nbytes of cached data. """ + nbytes = self.geometry.cache_nbytes + + if len(self.attached_instances) > 0: + nbytes += sum(self.attached_instances.cache_nbytes) + return nbytes + + # Facies + def evaluate_facies(self, src_horizons, src_true=None, src_pred=None, metrics='dice'): + """ Calculate facies metrics for requested labels of the field and return dataframe of results. + + Parameters + ---------- + scr_horizons : str + Name of field attribute that contains base horizons. + src_true : str + Name of field attribute that contains ground-truth labels. + src_pred : str + Name of field attribute that contains predicted labels. + metrics: str or list of str + Metrics function(s) to calculate. + """ + horizons = getattr(self, src_horizons) + true_labels = getattr(self, src_true) if src_true is not None else None + pred_labels = getattr(self, src_pred) if src_pred is not None else None + + fm = FaciesMetrics(horizons=horizons, true_labels=true_labels, pred_labels=pred_labels) + result = fm.evaluate(metrics) + + return result diff --git a/seismiqb/field/synthetic.py b/seismiqb/field/synthetic.py new file mode 100644 index 0000000..78cc990 --- /dev/null +++ b/seismiqb/field/synthetic.py @@ -0,0 +1,339 @@ +""" A wrapper around `SyntheticGenerator` to provide the same API, as regular `:class:.Field`. """ +import numpy as np + +from batchflow import Config +from ..utils import lru_cache +from ..plotters import plot + +class GeometryMock: + """ Mock for Geometry. """ + def __getattr__(self, _): + return None + + +class SyntheticField: + """ A wrapper around `SyntheticGenerator` to provide the same API, as regular `:class:.Field`. + + The intended use of this class is: + - define a `param_generator` function, that returns a dictionary with parameters of seismic generation. + The parameters may be randomized, so the generated data is different each time. + - initialize an instance of this class. + - use `get_attribute` method to get synthetic images, horizon/fault masks, velocity models. + In order to ensure that they match one another, supply the same `locations` (triplet of slices), for example: + >>> locations = (slice(10, 11), slice(100, 200), slice(1000, 1500)) + >>> synthetic = synthetic_field.get_attribute(locations=locations, attribute='synthetic') + >>> velocity = synthetic_field.get_attribute(locations=locations, attribute='velocity') + would make synthetic and velocity images for the same underlying synthetic model. + + Using the same generator for multiple calls with different requested attributes relies on LRU caching of + the generator instances. Due to this, the `cache_maxsize` should always be bigger than the number of successive + calls to `get_attribute` with the same `attribute`. If synthetic field is used in any data loading pipelines, + this traslates to having `cache_maxsize` bigger than the `batch_size`. + + Methods `load_seismic` and `make_masks` are thin wrappers around `get_attribute` to make API of this class + identical to that of `:class:.Field`. + + Under the hood, we keep track of internal cache (with `locations` as key) to use the same instance of generator + multiple times. The size of cache is parametrized at initialization and should be bigger than the batch size. + Other than that, the `locations` is also used to infer shape of requested synthetic data, + if it is not provided at initialization / from `param_generator`. + + Parameters + ---------- + param_generator : callable, optional + If provided, should return a dictionary with parameters to generate synthetic. + Refer to `:meth:.default_param_generator` for example of implementation. + Can be omitted if the `data_generator` is supplied instead. + data_generator : callable, optional + If provided, then a callable to populate an instance of `SyntheticGenerator` with data. + Should take `generator` as the only required argument. Disables the `param_generator` option. + Note that the logic of keeping the same instance of `generator` for multiple calls with the same `locations` + is performed by class internals and still available in that case. + attribute : str + Attribute to get from the generator if `labels` are requested. + crop_shape : tuple of int + Default shape of the generated synthetic images. + If not provided, we use the shape from `param_generator` or `locations`. + name : str + Name of the the field. Used to comply with `:class:.Field` API. + cache_maxsize : int + Number of cached generators. Should be equal or bigger than the batch size. + """ + GENERATOR_CONSTRUCTOR = None + + #pylint: disable=method-hidden, protected-access, not-callable + def __init__(self, param_generator=None, data_generator=None, name='synthetic_field', cache_maxsize=128, + default_attribute=None, default_shape=None): + # Data generation + self.param_generator = param_generator + self.data_generator = data_generator + self._make_generator = lru_cache(maxsize=cache_maxsize)(self._make_generator) + self._cache_maxsize = cache_maxsize + + # Defaults + self.default_attribute = default_attribute + self.default_shape = default_shape + + # String info + self.path = self.short_path = f'{name}_path' + self.name = self.short_name = self.short_name = name + self.index_headers = self.axis_names = ['INLINE_3D', 'CROSSLINE_3D'] + + # Attributes to comply with `:class:.Field` API + self.geometry = GeometryMock() + self.spatial_shape = (-1, -1) + self.shape = (-1, -1, -1) + self.depth = -1 + self.dead_traces_matrix = self.mean_matrix = self.std_matrix = None + + # Properties + self._normalization_stats = None + + @property + def labels(self): + """ Property for sampler creation. Used as a signal that this field is in fact synthetic. """ + return self + + # Generator creation + def get_generator(self, locations=None, shape=None): + """ Get a generator with data of a given `shape`. + If called with the same parameters twice, returns the same instance: `locations` is used as a hash value. + """ + if locations is None: + shape = shape if shape is not None else self.default_shape + + if shape is None: + raise ValueError('Shape is undefined: pass it directly or supply a `default_shape` at initialization!') + locations = self.shape_to_locations(shape) + + hash_value = self.locations_to_hash(locations) + + generator = self._make_generator(hash_value) + self._populate_generator(generator=generator, locations=locations) # Works in-place! + return generator + + # @lru_cache + def _make_generator(self, hash_value): + """ Create a generator instance. During initialization, wrapped in `lru_cache`. """ + return self.GENERATOR_CONSTRUCTOR(seed=abs(hash_value)) + + def _populate_generator(self, generator, locations=None): + """ Call `generator` methods to populate it with data: impedance model, horizon surfaces, faults, etc. """ + if hasattr(generator, '_populated'): + return None + + if self.data_generator is not None: + self.data_generator(generator) + + else: + # Generate parameters, use them to populate `generator` in-place + shape = self.locations_to_shape(locations) + params = self.param_generator(shape=shape, rng=generator.rng) + params = Config(params) + + # Compute velocity model, using the velocity vector and horizon matrices + (generator + .init_shapes(**params['init_shapes']) + .make_velocities(**params['make_velocities']) + .make_horizons(**params['make_horizons']) + .make_velocity_model(**params['make_velocity_model']) + ) + + # Faults + for fault_params in params.get('make_fault_2d', []): + generator.make_fault_2d(**fault_params) + + for fault_params in params.get('make_fault_3d', []): + generator.make_fault_3d(**fault_params) + + # Finalize synthetic creation + (generator + .make_density_model(**params['make_density_model']) + .make_impedance_model(**params['make_impedance_model']) + .make_reflectivity_model(**params['make_reflectivity_model']) + + .make_synthetic(**params['make_synthetic']) + .postprocess_synthetic(**params['postprocess_synthetic']) + .cleanup(**params['cleanup']) + ) + + generator.params = params + + generator._populated = True + return None + + + # Getting data + def get_attribute(self, locations=None, shape=None, attribute='synthetic', buffer=None, **kwargs): + """ Output requested `attribute`. + If `locations` is not provided, uses `shape` to create a random one. + For the same `locations` values, uses the same generator instance (with the same velocity model): + >>> locations = (slice(10, 11), slice(100, 200), slice(1000, 1500)) + >>> synthetic = synthetic_field.get_attribute(locations=locations, attribute='synthetic') + >>> impedance = synthetic_field.get_attribute(locations=locations, attribute='impedance') + """ + _ = kwargs + + generator = self.get_generator(locations=locations, shape=shape) + + # Select what is `labels` + if attribute == 'labels': + if self.default_attribute is not None: + attribute = self.default_attribute + else: + attribute = generator.params.get('attribute') + + if attribute is None: + raise ValueError('Attribute `labels` is undefined: use `default_attribute`' + 'or a key in `param_generator` to define what to retrieve!') + + # Main: velocity, reflectivity, synthetic + if attribute in ['synthetic', 'geometry', 'image']: + result = generator.get_attribute(attribute='synthetic') + elif 'velocity' in attribute: + result = generator.get_attribute(attribute='velocity_model') + elif 'impedance' in attribute: + result = generator.get_attribute(attribute='impedance_model') + elif 'reflect' in attribute: + result = generator.get_attribute(attribute='reflectivity_model') + elif 'upward' in attribute: + result = generator.get_increasing_impedance_model() + + # Labels: horizons and faults + elif 'horizon' in attribute: + # Remove extra kwargs + _ = kwargs.pop('orientation', None) + _ = kwargs.pop('sparse', None) + + kwargs = { + 'indices': 'all', + 'width': 3, + 'format': 'mask', + **kwargs + } + result = generator.get_horizons(**kwargs) + elif 'amplified' in attribute: + result = generator.get_horizons(indices='amplified', format='mask', width=kwargs.get('width', 3)) + elif 'fault' in attribute: + result = generator.get_faults(format='mask', width=kwargs.get('width', 3)) + + # Fallback + else: + result = generator.get_attribute(attribute=attribute) + + result = result.reshape(shape) + + if buffer is not None: + buffer[:] = result + else: + buffer = result + return buffer + + + def load_seismic(self, locations=None, shape=None, src='synthetic', buffer=None, **kwargs): + """ Wrapper around `:meth:.get_attribute` to comply with `:class:.Field` API. """ + return self.get_attribute(locations=locations, shape=shape, attribute=src, buffer=buffer, **kwargs) + + def make_mask(self, locations=None, shape=None, src='labels', buffer=None, **kwargs): + """ Wrapper around `:meth:.get_attribute` to comply with `:class:.Field` API. """ + return self.get_attribute(locations=locations, shape=shape, attribute=src, buffer=buffer, **kwargs) + + + # Utilities + def shape_to_locations(self, shape): + """ Make a randomized locations with desired shape. """ + starts = np.random.randint((0, 0, 0), (10000, 10000, 10000)) + return tuple(slice(start, start + s) + for start, s in zip(starts, shape)) + + def locations_to_shape(self, locations): + """ Compute shape of a given locations. """ + return tuple(slc.stop - slc.start for slc in locations) + + def locations_to_hash(self, locations): + """ Compute hash value of a given locations. """ + return hash(tuple((slc.start, slc.stop, slc.step) for slc in locations)) + + + @classmethod + def velocity_to_seismic(cls, velocity, ricker_width=4.3): + """ Generate synthetic seismic out of velocity predictions. """ + result = [] + for velocity_array in velocity: + generator = cls.GENERATOR_CONSTRUCTOR() + + # Generating synthetic out of predicted velocity for all items + generator.velocity_model = velocity_array + generator.shape = generator.shape_padded = velocity_array.shape + generator.depth = generator.depth_padded = velocity_array.shape[-1] + + (generator + .make_density_model(randomization=None) + .make_impedance_model() + .make_reflectivity_model() + .make_synthetic(ricker_width=ricker_width, ricker_points=100)) + result.append(generator.synthetic) + + return np.stack(result).astype(np.float32) + + # Normalization + def make_normalization_stats(self, n=100, shape=None, attribute='synthetic'): + """ Compute normalization stats (`mean`, `std`, `min`, `max`, quantiles) from `n` generated `attributes`. """ + data = [self.get_attribute(shape=shape, attribute=attribute) for _ in range(n)] + data = np.array(data) + + q01, q05, q95, q99 = np.quantile(data, (0.01, 0.05, 0.95, 0.99)) + + normalization_stats = { + 'mean': np.mean(data), + 'std': np.std(data), + 'min': np.min(data), + 'max': np.max(data), + 'q_01': q01, + 'q_05': q05, + 'q_95': q95, + 'q_99': q99, + } + self._normalization_stats = normalization_stats + return normalization_stats + + @property + def normalization_stats(self): + """ Property with default normalization stats for synthetic images. """ + if self._normalization_stats is None: + self.make_normalization_stats() + return self._normalization_stats + + # Visualization + def __repr__(self): + return f"""""" + + def __str__(self): + msg = f"SyntheticField `{self.short_name}`" + + if self.param_generator is not None: + attribute = self.param_generator.get('attribute') + if attribute is not None: + msg += f':\n - labels: attribute `{attribute}`' + return msg + + def show_slide(self, locations=None, shape=None, **kwargs): + """ Create one generator and show underlying models, synthetic and masks. """ + generator = self.get_generator(locations=locations, shape=shape) + self._last_generator = generator + return generator.show_slide(**kwargs) + + def plot_roll(self, shape=None, attribute='synthetic', n=25, **kwargs): + """ Show attribute-images for a number of generators. """ + data = [[self.get_attribute(shape=shape, attribute=attribute)[0]] for _ in range(n)] + + # Display images + plot_config = { + 'suptitle': f'Roll of `{attribute}`', + 'title': list(range(n)), + 'cmap': 'Greys_r', + 'colorbar': True, + 'ncols': 5, + **kwargs + } + return plot(data, **plot_config) diff --git a/seismiqb/field/viewer.py b/seismiqb/field/viewer.py new file mode 100644 index 0000000..6d371c6 --- /dev/null +++ b/seismiqb/field/viewer.py @@ -0,0 +1,210 @@ +""" Interactive field viewer. """ +from ipywidgets import widgets +from IPython.display import display + +import matplotlib.pyplot as plt + + + +class FieldViewer: + """ Interactive viewer of a field. + + Creates a figure with two axis -- base map and slice map, as well as some additional controls. + On the base map we show a top-view image of a field with requested attribute from a geometry / one of the labels. + On the slice map we show one slice from a cube along desired axis. + + Requires the `ipympl` library and the `%matplotlib widget` magic to work. + """ + out = widgets.Output() + + def __init__(self, field, figsize=(8, 8)): + # ax[0] is a `base_map` / `base_ax` + # ax[1] is a `slice_img` / `slice_ax` + + # Attributes + self.field = field + + # Initial state + location = self.field.shape[0] // 2 + self.state_base = {'attribute': 'geometry/snr'} + self._state_base = {} # previous `state_base` + + self.state_slice = {'location': location, 'axis': 0} + self._state_slice = {} # previous `state_slice` + + # Make widgets + self.attribute_dropdown = widgets.Dropdown(options=self.field.available_attributes, + value=self.field.available_attributes[2], + description='Base map', + layout=widgets.Layout(max_width='350px')) + self.location_text = widgets.IntText(value=location, description='INLINE', + layout=widgets.Layout(max_width='150px')) + self.location_slider = widgets.IntSlider(value=location, max=self.field.shape[0] - 1, description='INLINE', + continuous_update=False, layout=widgets.Layout(min_width='500px')) + self.axis_button = widgets.Button(description='swap axis', layout=widgets.Layout(min_width='200px')) + + self.hbox = widgets.HBox([self.attribute_dropdown, self.location_text, self.location_slider, self.axis_button], + layout=widgets.Layout(min_width='1000px')) + + # Make figure + with widgets.Output(): + plt.ioff() + self.fig, self.ax = plt.subplots(1, 2, figsize=figsize, tight_layout=True) + self.base_ax, self.slice_ax = self.ax + self.vbox = widgets.VBox([self.hbox, + self.fig.canvas]) + + # Setup widgets + self.attribute_dropdown.observe(self.attribute_dropdown_update, names='value') + self.location_text.observe(self.location_text_update, names='value') + self.location_slider.observe(self.location_slider_update, names='value') + self.axis_button.on_click(self.axis_button_onclick) + + self.fig.canvas.mpl_connect('button_press_event', self.fig_onclick) + self.fig.canvas.header_visible = False + + # Initialize plots + with widgets.Output(): + self.draw_base(force=True) + self.draw_slice(force=True) + + display(self.vbox) + + + # Draw methods + def draw_base(self, force=False): + """ Draw base top-view map on the left axis. """ + # Cache + if force is False and self.state_base == self._state_base: + return + + attribute = self.state_base['attribute'] + + # Remove previous image, draw new one. TODO: change to `set_data` + if self.base_ax.get_images(): + self.base_ax.get_images()[0].remove() + self.base_ax.created_colorbar.ax.remove() + self.field.show(attributes=attribute, ax=self.base_ax, labelright=False, colorbar_fraction=1.0) + + # Update previous state + self._state_base = {**self.state_base} + + def draw_slice(self, force=False): + """ Draw slice from a field on the right axis. """ + # Cache + if force is False and self.state_slice == self._state_slice: + return + + location, axis = self.state_slice['location'], self.state_slice['axis'] + + # Remove all previous lines + lines = [children for children in self.base_ax.get_children() + if hasattr(children, 'created_by_draw') or hasattr(children, 'created_by_zoom')] + for line in lines: + line.remove() + + # Add a line; mark it with attribute + if axis == 0: + line = self.base_ax.vlines(location, 0, self.field.shape[1], color='r', linewidth=3) + elif axis == 1: + line = self.base_ax.hlines(location, 0, self.field.shape[0], color='r', linewidth=3) + line.created_by_draw = True + + # Remove previous image, draw new one. TODO: change to `set_data` + if self.slice_ax.get_images(): + self.slice_ax.clear() + self.slice_ax.created_colorbar.ax.remove() + self.field.show_slide(location, axis=axis, ax=self.slice_ax) + + # Update previous state + self._state_slice = {**self.state_slice} + + def zoom_line(self, point): + """ Highlight selected (on the right axis) region on the top-view map (left axis). """ + lines = [children for children in self.base_ax.get_children() + if hasattr(children, 'created_by_zoom')] + for line in lines: + line.remove() + + location, axis = self.state_slice['location'], self.state_slice['axis'] + if axis == 0: + start = max(point - 100, 0) + stop = min(point + 100, self.field.shape[1] - 1) + line = self.base_ax.vlines(location, start, stop, color='w', linewidth=5) + elif axis == 1: + start = max(point - 100, 0) + stop = min(point + 100, self.field.shape[0] - 1) + line = self.base_ax.hlines(location, start, stop, color='w', linewidth=5) + line.created_by_zoom = True + + # For some reason, we need to manually update the figure (not a full redraw though) + self.fig.canvas.draw_idle() + + + # State reactions + def refresh(self, force=False): + """ Re-draw both base and slice axis, if needed, and update state of widgets. """ + self.draw_base(force=force) + self.draw_slice(force=force) + + self.location_text.value = self.state_slice['location'] + self.location_slider.value = self.state_slice['location'] + + @out.capture() + def change_axis(self): + """ Swap axis and update state of widgets. """ + self.state_slice['axis'] = 1 - self.state_slice['axis'] + self.state_slice['location'] = self.field.shape[self.state_slice['axis']] // 2 + self.refresh() + + if self.state_slice['axis'] == 0: + self.location_text.description = 'INLINE' + self.location_slider.description = 'INLINE' + self.location_slider.max = self.field.shape[0] - 1 + self.axis_button.description = 'change axis to crossline' + + elif self.state_slice['axis'] == 1: + self.location_text.description = 'CROSSLINE' + self.location_slider.description = 'CROSSLINE' + self.location_slider.max = self.field.shape[1] - 1 + self.axis_button.description = 'change axis to inline' + + + # Event reactions + @out.capture() + def attribute_dropdown_update(self, change): + """ Select base map attribute by a dropdown. """ + self.state_base['attribute'] = change['new'] + self.refresh() + + @out.capture() + def location_text_update(self, change): + """ Change location by entering a number. """ + self.state_slice['location'] = change['new'] + self.refresh() + + @out.capture() + def location_slider_update(self, change): + """ Change location by moving a slider. """ + self.state_slice['location'] = change['new'] + self.refresh() + + @out.capture() + def axis_button_onclick(self, button): + """ Change axis button. """ + self.change_axis() + + @out.capture() + def fig_onclick(self, event): + """ If clicked on the left axis, then change location. + If clicked on the right axis, then select zoom region. + """ + if event.xdata is not None and event.ydata is not None: + point = int(event.xdata + 0.5), int(event.ydata + 0.5) + + if event.inaxes == self.base_ax: + self.state_slice['location'] = point[self.state_slice['axis']] + self.refresh() + + elif event.inaxes == self.slice_ax: + self.zoom_line(point[0]) diff --git a/seismiqb/field/visualization.py b/seismiqb/field/visualization.py new file mode 100644 index 0000000..349bafa --- /dev/null +++ b/seismiqb/field/visualization.py @@ -0,0 +1,613 @@ +""" A mixin with field visualizations. """ +#pylint: disable=global-variable-undefined, too-many-statements +import re +from copy import copy +from collections import defaultdict +from itertools import cycle + +import numpy as np +from batchflow.plotter.plot import Subplot + +from ..functional import compute_instantaneous_amplitude, compute_instantaneous_phase, compute_instantaneous_frequency +from ..utils import DelegatingList, to_list +from ..plotters import plot, show_3d +from ..labels.horizon.attributes import AttributesMixin + +COLOR_GENERATOR = iter(Subplot.MASK_COLORS) +NAME_TO_COLOR = {} + + + +class VisualizationMixin: + """ Methods for field visualization: textual, 2d along various axis, 2d interactive, 3d. """ + # Textual representation + def __repr__(self): + return f"""""" + + REPR_MAX_LEN = 100 + REPR_MAX_ROWS = 5 + + def __str__(self): + processed_prefix = 'un' if self.geometry.has_stats is False else '' + labels_prefix = ' and labels:' if self.labels else '' + msg = f'Field `{self.short_name}` with {processed_prefix}processed geometry{labels_prefix}\n' + + for label_src in self.loaded_labels: + labels = getattr(self, label_src) + names = [label.short_name for label in labels] + + labels_msg = '' + line = f' - {label_src}: [' + while names: + line += names.pop(0) + + if names: + line += ', ' + else: + labels_msg += line + break + + if len(line) > self.REPR_MAX_LEN: + labels_msg += line + line = '\n ' + ' ' * len(label_src) + + if len(labels_msg) > self.REPR_MAX_LEN * self.REPR_MAX_ROWS: + break + + if names: + labels_msg += f'\n {" "*len(label_src)}and {len(names)} more item(s)' + labels_msg += ']\n' + msg += labels_msg + return msg[:-1] + + # 2D along axis + ATTRIBUTE_TO_ALIASES = { + compute_instantaneous_amplitude: ['iamplitudes', 'instantaneous_amplitudes'], + compute_instantaneous_phase: ['iphases', 'instantaneous_phases'], + compute_instantaneous_frequency: ['ifrequencies', 'instantaneous_frequencies'], + } + ALIASES_TO_ATTRIBUTE = {alias: name for name, aliases in ATTRIBUTE_TO_ALIASES.items() for alias in aliases} + + def load_slide(self, index, axis=0, attribute=None, src_geometry='geometry'): + """ Load one slide of data along specified axis and apply `transform`. + Refer to the documentation of :meth:`.Geometry.load_slide` for details. + + Parameters + ---------- + index : int, str + If int, then interpreted as the ordinal along the specified axis. + If `'random'`, then we generate random index along the axis. + If string of the `'#XXX'` format, then we interpret it as the exact indexing header value. + axis : int + Axis of the slide. + attribute : callable or str + If callable, then directly applied to the loaded data. + If str, then one of pre-defined aliases for pre-defined geological transforms. + """ + slide = getattr(self, src_geometry).load_slide(index=index, axis=axis) + + if attribute: + if isinstance(attribute, str) and attribute in self.ALIASES_TO_ATTRIBUTE: + attribute = self.ALIASES_TO_ATTRIBUTE[attribute] + if callable(attribute): + slide = attribute(slide) + else: + raise ValueError(f'Unknown transform={attribute}') + return slide + + + def show_slide(self, index, axis='i', attribute=None, zoom=None, width=9, + src_geometry='geometry', src_labels='labels', + enumerate_labels=False, indices='all', augment_mask=True, plotter=plot, **kwargs): + """ Show slide with horizon on it. + + Parameters + ---------- + index : int, str + Index of the slide to show. + If int, then interpreted as the ordinal along the specified axis. + If `'random'`, then we generate random index along the axis. + If string of the `'#XXX'` format, then we interpret it as the exact indexing header value. + axis : int + Number of axis to load slide along. + attribute : callable or str + If callable, then directly applied to the loaded data. + If str, then one of pre-defined aliases for pre-defined geological transforms. + width : int + Horizon thickness. If None given, set to 1% of seismic slide depth. + zoom : tuple, None or 'auto' + Tuple of slices to apply directly to 2d images. If None, slicing is not applied. + If 'auto', zero traces on bounds will be dropped. + """ + axis = self.geometry.parse_axis(axis) + index = self.geometry.get_slide_index(index, axis=axis) + locations = self.geometry.make_slide_locations(index, axis=axis) + + # Load seismic and mask + seismic_slide = self.load_slide(index=index, axis=axis, attribute=attribute, src_geometry=src_geometry) + + src_labels = src_labels if isinstance(src_labels, (tuple, list)) else [src_labels] + masks = [] + for src in src_labels: + masks.append(self.make_mask(locations=locations, orientation=axis, src=src, width=width, + indices=indices, enumerate_labels=enumerate_labels)) + mask = sum(masks) + + seismic_slide, mask = np.squeeze(seismic_slide), np.squeeze(mask) + xmin, xmax, ymin, ymax = 0, seismic_slide.shape[0], seismic_slide.shape[1], 0 + + if zoom == 'auto': + zoom = self.geometry.compute_auto_zoom(index, axis) + if zoom: + seismic_slide = seismic_slide[zoom] + mask = mask[zoom] + xmin = zoom[0].start or xmin + xmax = zoom[0].stop or xmax + ymin = zoom[1].stop or ymin + ymax = zoom[1].start or ymax + + # defaults for plotting if not supplied in kwargs + header = self.geometry.axis_names[axis] + total = self.geometry.shape[axis] + + if axis in [0, 1]: + xlabel = self.geometry.index_headers[1 - axis] + ylabel = 'DEPTH' + if axis == 2: + xlabel = self.geometry.index_headers[0] + ylabel = self.geometry.index_headers[1] + total = self.geometry.depth + + kwargs = { + 'cmap': ['Greys_r', 'darkorange'], + 'title': f'{header} {index} out of {total}', + 'suptitle': f'Field `{self.short_name}`', + 'xlabel': xlabel, + 'ylabel': ylabel, + 'extent': (xmin, xmax, ymin, ymax), + 'legend': ', '.join(src_labels), + 'labeltop': False, + 'labelright': False, + 'curve_width': width, + 'grid': [None, 'both'], + 'colorbar': [True, None], + 'augment_mask': augment_mask, + **kwargs + } + + return plotter(data=[seismic_slide, mask], **kwargs) + + def show_section(self, locations, zoom=None, plotter=plot, linecolor='gray', linewidth=3, **kwargs): + """ Show seismic section via desired traces. + Under the hood relies on :meth:`load_section`, so works with geometries in any formats. + + Parameters + ---------- + locations : iterable + Locations of traces to construct section. + zoom : tuple, None or 'auto' + Tuple of slices to apply directly to 2d images. If None, slicing is not applied. + If 'auto', zero traces on bounds will be dropped. + plotter : instance of `plot` + Plotter instance to use. + Combined with `positions` parameter allows using subplots of already existing plotter. + linecolor : str or None + Color of line to mark node traces. If None, lines will not be drawn. + linewidth : int + With of the line. + """ + self.geometry.show_section(locations, zoom=zoom, plotter=plotter, linecolor=linecolor, + linewidth=linewidth, **kwargs) + + # 2D depth slice + def show_points(self, src='labels', plotter=plot, **kwargs): + """ Plot 2D map of labels points. Meant to be used with spatially disjoint objects (e.g. faults). """ + map_ = np.zeros(self.spatial_shape) + denum = np.zeros(self.spatial_shape) + + for label in getattr(self, src): + map_[label.points[:, 0], label.points[:, 1]] += label.points[:, 2] + denum[label.points[:, 0], label.points[:, 1]] += 1 + denum[denum == 0] = 1 + map_ = map_ / denum + map_[map_ == 0] = np.nan + + labels_class = type(getattr(self, src)[0]).__name__ + kwargs = { + 'title': f'{labels_class}s on `{self.short_name}`', + 'xlabel': self.index_headers[0], + 'ylabel': self.index_headers[1], + 'cmap': ['Reds', 'black'], + 'colorbar': True, + 'augment_mask': True, + **kwargs + } + return plotter([map_, self.dead_traces_matrix], **kwargs) + + + # 2D top-view maps + def show(self, attributes='snr', mode='image', title_pattern='{attributes} of {label_name}', + bbox=False, savepath=None, load_kwargs=None, show=True, plotter=plot, **kwargs): + """ Show one or more field attributes on one figure. + + Parameters + ---------- + attributes : str, np.ndarray, dict or sequence of them + Attributes to display. + If str, then use `:meth:.load_attribute` to load the data. For example, `geometry/snr`, `labels:0/depths`. + If instead of label index contains `:*`, for example, `labels:*/amplitudes`, then run this method + for each of the objects in `labels` attribute. + If np.ndarray, then directly used as data to display. + If dict, then should define either string or np.ndarray (and used the same as previous types), + as well as other parameters for `:meth:.load_attribute`. + If sequence of them, then either should be a list to display loaded entities one over the other, + or nested list to define separate axis and overlaying for each of them. + For more details, refer to `:func:plot`. + mode : 'image' or 'histogram' + Mode to display images. + title_pattern : str with key substrings to be replaced by corresponding variables values + If {src_label} in pattern, replaced by name of labels source (e.g. 'horizons:0'). + If {label_name} in pattern, replaced by label name (e.g. 'predicted_#3.char'). + If {attributes} in pattern, replaced by list of attributes names (e.g. '['depths', 'amplitudes']'). + If multiple labels displayed on single subplot, pattern will be repeated in title for every one of them. + bbox : bool + Whether crop horizon by its bounding box or not. + savepath : str, optional + Path to save the figure. `**` is changed to a field base directory, `*` is changed to field base name. + load_kwargs : dict + Loading parameters common for every requested attribute. + show : bool + Whether to show created plot or not. + plotter : instance of `plot` + Plotter instance to use. + Combined with `positions` parameter allows using subplots of already existing plotter. + kwargs : dict + Additional parameters for plot creation. + + Examples + -------- + Simplest possible plot of a geometry-related attribute: + >>> field.show('mean_matrix') + + Display attribute of a fan over the geometry map: + >>> field.show(['mean_matrix', 'fans:0/mask']) + + Display attributes on separate axis: + >>> field.show(['mean_matrix', 'horizons:0/fourier', custom_data_array], combine='separate') + + Use various parameters for each of the plots: + >>> field.show([{'src': 'labels:0/fourier', 'window': 20, 'normalize': True}, + {'src': 'labels:0/fourier', 'window': 40, 'n_components': 3}], + combine='separate') + + Display amplitudes and gradients for each of the horizons in a field: + >>> field.show(['horizons:*/amplitudes', 'horizons:*/gradient'], combine='separate') + + Display several attributes on multiple axes with overlays and save it near the cube: + >>> field.show(['geometry/std_matrix', 'horizons:3/amplitudes', + ['horizons:3/instant_phases', 'fans:3/mask'], + ['horizons:3/instant_phases', predicted_mask]], + savepath='~/IMAGES/complex.png') + """ + # Wrap given attributes load parameters in a structure that allows applying functions to its nested items + load_params = DelegatingList(attributes) + load_params = load_params.map(lambda item: copy(item) if isinstance(item, dict) else item) + + # Prepare data loading params + load_params = load_params.map(self._make_load_params, common_params=load_kwargs) + + # Extract names of labels sources that require wildcard loading + detect_wildcard = lambda params: params['src_labels'] if params['label_num'] == '*' else [] + labels_require_wildcard_loading = load_params.map(detect_wildcard).flat + + # If any attributes require wildcard loading, run `show` for every label item + if any(labels_require_wildcard_loading): + plotters = [] + + reference_labels_source = labels_require_wildcard_loading[0] + n_items = len(getattr(self, reference_labels_source)) + for label_num in range(n_items): + #pylint: disable=cell-var-from-loop + substitutor = lambda params: {**params, 'src': params['src'].replace('*', str(label_num))} + label_attributes = load_params.map(substitutor) + + plotter_ = self.show(attributes=label_attributes, mode=mode, bbox=bbox, title_pattern=title_pattern, + savepath=savepath, load_kwargs=load_kwargs, show=show, plotter=plotter, **kwargs) + plotters.append(plotter_) + + return plotters + + data_params = load_params.map(self._load_data) + + # Prepare default plotting parameters + plot_config = data_params.map(self._make_plot_config, mode=mode).to_dict() + plot_config = {**plot_config, **kwargs} + + plot_config = { + 'suptitle': f'Field `{self.short_name}`', + 'augment_mask': True, + **plot_config + } + + if mode == 'image': + plot_config['colorbar'] = True + plot_config['xlabel'] = self.index_headers[0] + plot_config['ylabel'] = self.index_headers[1] + + if title_pattern and 'title' not in plot_config: + plot_config['title'] = data_params.map(self._make_title, shallow=True, title_pattern=title_pattern) + + if bbox: + bboxes_list = data_params.map(lambda params: params['bbox']) + lims_list = [np.stack([bboxes]).transpose(1, 2, 0) for bboxes in bboxes_list] + plot_config['xlim'] = [(lims[0, 0].min(), lims[0, 1].max()) for lims in lims_list] + plot_config['ylim'] = [(lims[1, 1].max(), lims[1, 0].min()) for lims in lims_list] + + if savepath: + first_label_name = data_params.reference_object['label_name'] + plot_config['savepath'] = self.make_path(savepath, name=first_label_name) + + # Plot image with given params and return resulting figure + plotter_ = plotter(mode=mode, show=show, **plot_config) + plotter_.force_show() + return plotter_ + + # Auxilary methods utilized by `show` + ALIAS_TO_ATTRIBUTE = AttributesMixin.ALIAS_TO_ATTRIBUTE + + def _make_load_params(self, attribute, common_params): + # Transform load parameters into dict if needed, extract string indicating data source to use + if isinstance(attribute, str): + params = {'src': attribute} + elif isinstance(attribute, np.ndarray): + params = {'src': 'user data', 'data': attribute} + elif isinstance(attribute, dict): + params = copy(attribute) + else: + raise TypeError(f'Attribute should be either str, dict or array! Got {type(attribute)} instead.') + + # Extract source labels names and attribute names, detect if any labels sources require wildcard loading, + # i.e. loading of data for every label stored in requested attribute (e.g. 'horizons:*/depths') + attribute_name, label_num, src_labels = (re.split(':([0-9, *]+)/', params['src'])[::-1] + ['', 'geometry'])[:3] + params['attribute_name'] = self.ALIAS_TO_ATTRIBUTE.get(attribute_name, attribute_name) + params['src_labels'] = src_labels + params['label_num'] = label_num + + # Make data loading defaults + default_params = {'dtype': np.float32} + + if params['attribute_name'] in ['instantaneous_amplitudes', 'instantaneous_phases']: + default_params['channels'] = 'middle' + + if params['attribute_name'] in ['fourier_decomposition', 'wavelet_decomposition']: + default_params['n_components'] = 1 + + if attribute_name in ['mask', 'full_binary_matrix']: + params['fill_value'] = 0 + + # Merge defaults with provided parameters + params = {**default_params, **(common_params or {}), **params} + + return params + + def _load_data(self, load_params): + params = {'attribute_name': load_params.pop('attribute_name'), + 'src_labels': load_params.pop('src_labels'), + 'label_num': load_params.pop('label_num')} + + postprocess = load_params.pop('postprocess', lambda x: x) + + if 'data' not in load_params: + data, label = self.load_attribute(_return_label=True, **load_params) + params['label_name'] = label.short_name + params['bbox'] = label.bbox[:2] + else: + data = load_params['data'] + params['label_name'] = self.short_name + params['bbox'] = np.array([[0, max] for max in data.shape]) + + params['data'] = postprocess(data.squeeze()) + + return params + + CMAP_TO_ATTRIBUTE = { + 'Depths': ['full_matrix'], + 'Reds': ['spikes', 'quality_map', 'quality_grid'], + 'Metric': ['metric'], + 'RdYlGn': ['probabilities'] + } + ATTRIBUTE_TO_CMAP = {attr: cmap for cmap, attributes in CMAP_TO_ATTRIBUTE.items() + for attr in attributes} + + def _make_plot_config(self, data_params, mode): + params = {'data': data_params['data']} + + src_labels = data_params['src_labels'] + attribute_name = data_params['attribute_name'] + + # Choose default cmap + if attribute_name == 'full_binary_matrix' or mode == 'histogram': + global_name = f"{src_labels}/{attribute_name}" + if global_name not in NAME_TO_COLOR: + NAME_TO_COLOR[global_name] = next(COLOR_GENERATOR) + cmap = NAME_TO_COLOR[global_name] + else: + cmap = self.ATTRIBUTE_TO_CMAP.get(attribute_name, 'Seismic') + + params['cmap'] = cmap + + # Choose default alpha + if attribute_name in ['full_binary_matrix']: + alpha = 0.7 + else: + alpha = 1.0 + + # Bounds for metrics + if 'metric' in attribute_name: + params['vmin'], params['vmax'] = -1.0, 1.0 + + params['alpha'] = alpha + + return params + + def _make_title(self, data_params, title_pattern): + linkage = defaultdict(list) + + for params in to_list(data_params): + if isinstance(params, list): + params = params[0] + src_label = params['src_labels'] + if params['label_num']: + src_label += ':' + params['label_num'] + label_name = params['label_name'] + + linkage[(src_label, label_name)].append(params['attribute_name']) + + title = '' + for (src_label, label_name), attributes in linkage.items(): + title += '\n' * (title != '') + part = title_pattern + part = part.replace('{src_label}', src_label) + part = part.replace('{label_name}', label_name) + part = part.replace('{attributes}', ','.join(attributes)) + title += part + + return title + + # 2D interactive + def viewer(self, figsize=(8, 8), **kwargs): + """ Interactive field viewer. """ + from .viewer import FieldViewer #pylint: disable=import-outside-toplevel + return FieldViewer(field=self, figsize=figsize, **kwargs) + + + # 3D interactive + def show_3d(self, src='labels', aspect_ratio=None, zoom=None, n_points=100, threshold=100, + sticks_step=None, stick_nodes_step=None, sticks=False, stick_orientation=None, + slides=None, margin=(0, 0, 20), colors=None, **kwargs): + """ Interactive 3D plot for some elements of a field. + Roughly, does the following: + - take some faults and/or horizons + - select `n` points to represent the horizon surface and `sticks_step` and `stick_nodes_step` for each fault + - triangulate those points + - remove some of the triangles on conditions + - use Plotly to draw the tri-surface + - draw few slides of the cube if needed + + Parameters + ---------- + src : str, Horizon-instance or list + Items to draw, by default, 'labels'. If item of list (or `src` itself) is str, then all items of + that dataset attribute will be drawn. + aspect_ratio : None, tuple of floats or Nones + Aspect ratio for each axis. Each None in the resulting tuple will be replaced by item from + `(geometry.shape[0] / geometry.shape[1], 1, 1)`. + zoom : tuple of slices or None + Crop from cube to show. By default, the whole cube volume will be shown. + n_points : int + Number of points for horizon surface creation. + The more, the better the image is and the slower it is displayed. + threshold : number + Threshold to remove triangles with bigger depth differences in vertices. + sticks_step : int or None + Number of slides between sticks. If None, fault triangulation (nodes and simplices) will be used. + stick_nodes_step : int or None + Distance between stick nodes. If None, fault triangulation (nodes and simplices) will be used. + sticks : bool + If True, show fault sticks. If False, show interpolated surface. + stick_orientation : 0, 1 or 2 + Axis which defines stick_orientation + slides : list of tuples + Each tuple is pair of location and axis to load slide from seismic cube. + margin : tuple of ints + Added margin for each axis, by default, (0, 0, 20). + colors : dict, list or str. + Mapping of label class name to color defined as str, by default, all labels will be shown in green. + Also can be 'random' to set all label items colors randomly. + show_axes : bool + Whether to show axes and their labels. + width, height : number + Size of the image. + savepath : str + Path to save interactive html to. + kwargs : dict + Other arguments of plot creation. + """ + src = src if isinstance(src, (tuple, list)) else [src] + coords = [] + simplices = [] + + if zoom is None: + zoom = [slice(0, s) for s in self.shape] + else: + zoom = [ + slice(item.start or 0, item.stop or stop) for item, stop in zip(zoom, self.shape) + ] + zoom = tuple(zoom) + triangulation_kwargs = { + 'n_points': n_points, + 'threshold': threshold, + 'sticks_step': sticks_step, + 'stick_nodes_step': stick_nodes_step, + 'slices': zoom, + 'sticks': sticks, + 'stick_orientation': stick_orientation + } + + labels = [getattr(self, src_) if isinstance(src_, str) else [src_] for src_ in src] + labels = sum(labels, []) + + if colors == 'random': + colors = ['rgb(' + ', '.join([str(c) for c in np.random.randint(0, 255, size=3)]) + ')' for _ in labels] + if isinstance(colors, str): + colors = [colors] + if isinstance(colors, list): + cycled_colors = cycle(colors) + colors = [next(cycled_colors) for _ in range(len(labels))] + + if colors is None: + colors = ['green' for _ in labels] + if isinstance(colors, dict): + colors = [colors.get(type(label).__name__, colors.get('all', 'green')) for label in labels] + + simplices_colors = [] + for label, color in zip(labels, colors): + if label is not None: + x, y, z, simplices_ = label.make_triangulation(**triangulation_kwargs) + if len(simplices_) == 0: + continue + if x is not None: + simplices += [simplices_ + sum(len(item) for item in coords)] + simplices_colors += [[color] * len(simplices_)] + coords += [np.stack([x, y, z], axis=1)] + + if len(simplices) > 0: + simplices = np.concatenate(simplices, axis=0) + coords = np.concatenate(coords, axis=0) + simplices_colors = np.concatenate(simplices_colors) + else: + simplices = None + coords = np.zeros((0, 3)) + simplices_colors = None + title = self.short_name + + default_aspect_ratio = (self.shape[0] / self.shape[1], 1, 1) + aspect_ratio = [None] * 3 if aspect_ratio is None else aspect_ratio + aspect_ratio = [item or default for item, default in zip(aspect_ratio, default_aspect_ratio)] + + axis_labels = (self.index_headers[0], self.index_headers[1], 'DEPTH') + + images = [] + if slides is not None: + for loc, axis in slides: + image = self.geometry.load_slide(loc, axis=axis) + if axis == 0: + image = image[zoom[1:]] + elif axis == 1: + image = image[zoom[0], zoom[-1]] + else: + image = image[zoom[:-1]] + images += [(image, loc, axis)] + + show_3d(coords[:, 0], coords[:, 1], coords[:, 2], simplices, title, zoom, simplices_colors, margin=margin, + aspect_ratio=aspect_ratio, axis_labels=axis_labels, images=images, **kwargs) diff --git a/seismiqb/functional/__init__.py b/seismiqb/functional/__init__.py new file mode 100644 index 0000000..0c8dfbf --- /dev/null +++ b/seismiqb/functional/__init__.py @@ -0,0 +1,6 @@ +""" General functions for working with seismic data. """ +# pylint: disable=wildcard-import +from .base import * +from .geologic_transforms import * +from .geometric_transforms import * +from .similarity_metrics import * diff --git a/seismiqb/functional/base.py b/seismiqb/functional/base.py new file mode 100644 index 0000000..da1abee --- /dev/null +++ b/seismiqb/functional/base.py @@ -0,0 +1,10 @@ +""" Useful functions. """ +import numpy as np +from scipy.ndimage import gaussian_filter + + +def make_gaussian_kernel(kernel_size=(3, 3), sigma=1.): + """ Create Gaussian kernel with given parameters: kernel size and std. """ + n = np.zeros(kernel_size) + n[tuple(np.array(n.shape) // 2)] = 1 + return gaussian_filter(n, sigma=sigma) diff --git a/seismiqb/functional/geologic_transforms.py b/seismiqb/functional/geologic_transforms.py new file mode 100644 index 0000000..4ca1172 --- /dev/null +++ b/seismiqb/functional/geologic_transforms.py @@ -0,0 +1,98 @@ +""" Functions for geologic transforms. """ +from warnings import warn + +import numpy as np +try: + import cupy as cp + CUPY_AVAILABLE = True +except ImportError: + cp = np + CUPY_AVAILABLE = False + + + +# Device management +def to_device(array, device='cpu'): + """ Transfer array to chosen GPU, if possible. + If `cupy` is not installed, does nothing. + + Parameters + ---------- + device : str or int + Device specificator. Can be either string (`cpu`, `gpu:4`) or integer (`4`). + """ + if isinstance(device, str) and ':' in device: + device = int(device.split(':')[1]) + if device in ['cuda', 'gpu']: + device = 0 + + if isinstance(device, int): + if CUPY_AVAILABLE: + with cp.cuda.Device(device): + array = cp.asarray(array) + else: + warn('Performance Warning: computing metrics on CPU as `cupy` is not available', RuntimeWarning) + return array + +def from_device(array): + """ Move the data from GPU, if needed. + If `cupy` is not installed or supplied array already resides on CPU, does nothing. + """ + if CUPY_AVAILABLE and hasattr(array, 'device'): + array = cp.asnumpy(array) + return array + + +# Helper functions +def hilbert(array, axis=-1): + """ Compute the analytic signal, using the Hilbert transform. """ + xp = cp.get_array_module(array) if CUPY_AVAILABLE else np + N = array.shape[axis] + fft = xp.fft.fft(array, n=N, axis=axis) + + h = xp.zeros(N) + if N % 2 == 0: + h[0] = h[N // 2] = 1 + h[1:N // 2] = 2 + else: + h[0] = 1 + h[1:(N + 1) // 2] = 2 + + if array.ndim > 1: + ind = [xp.newaxis] * array.ndim + ind[axis] = slice(None) + h = h[tuple(ind)] + + result = xp.fft.ifft(fft * h, axis=axis) + return result + +def compute_instantaneous_amplitude(array, axis=-1, analytic=None): + """ Compute instantaneous amplitude. """ + xp = cp.get_array_module(array) if CUPY_AVAILABLE else np + analytic = analytic if analytic is not None else hilbert(array, axis=axis) + amplitude = xp.abs(analytic) + return amplitude.astype(np.float32) + +def compute_instantaneous_phase(array, continuous=False, axis=-1, analytic=None): + """ Compute instantaneous phase. """ + xp = cp.get_array_module(array) if CUPY_AVAILABLE else np + analytic = analytic if analytic is not None else hilbert(array, axis=axis) + + phase = xp.angle(analytic) % (2 * xp.pi) - xp.pi + if continuous: + phase = xp.abs(phase) + return phase.astype(np.float32) + +def compute_instantaneous_frequency(array, axis=-1, sample_rate=1.0, analytic=None): + """ Compute instantaneous frequency. """ + iphases = compute_instantaneous_phase(array, axis=axis, analytic=analytic) + frequency = np.diff(iphases, axis=axis, prepend=0) / (2 * np.pi) * sample_rate + return frequency.astype(np.float32) + +def compute_spectral_decomposition(array, frequencies, wavelet='mexh', sample_rate=1.0, method='fft', axis=-1): + """ Compute spectral decomposition by convolving data with wavelets at different scales. """ + import pywt #pylint: disable=import-outside-toplevel + frequencies = np.array(frequencies) + scales = sample_rate / (frequencies * np.sqrt(2) * np.pi) + spectral = pywt.cwt(array, scales=scales, wavelet=wavelet, axis=axis, method=method)[0] + return spectral diff --git a/seismiqb/functional/geometric_transforms.py b/seismiqb/functional/geometric_transforms.py new file mode 100644 index 0000000..7c7ad61 --- /dev/null +++ b/seismiqb/functional/geometric_transforms.py @@ -0,0 +1,271 @@ +""" Geometric transforms. """ +from math import ceil, atan, cos, sin + +import numpy as np +import cv2 + + + +# Rotate +def rotate_2d(array, angle, adjust=False, fill_value=0): + """ Rotate an image along the first two axes. + Assumes `channels_last` format. + + Parameters + ---------- + angle : number + Angle of rotation in degrees. + adjust : bool + If True, then image is upscaled prior to rotation to avoid padding. + fill_value : number + Padding value. + """ + if adjust: + array, initial_shape = adjust_shape(array, angle=angle) + array = _rotate_2d(array=array, angle=angle, fill_value=fill_value) + if adjust: + array = center_crop(array, shape=initial_shape) + return array + +def rotate_3d(array, angle, adjust=False, fill_value=0): + """ Rotate an image in 3D. + Angles are defined as Tait-Bryan angles and the sequence of extrinsic rotations axes is (axis_2, axis_0, axis_1). + + Parameters + ---------- + angle : number + Angle of rotation in degrees. + fill_value : number + Padding value. + """ + if adjust: + raise NotImplementedError('`adjust` is not implemented for 3D rotation!') + + if angle[0] != 0: + array = _rotate_2d(array, angle[0], fill_value) + if angle[1] != 0: + array = _rotate_2d(array.transpose(1, 2, 0), angle[1], fill_value).transpose(2, 0, 1) + if angle[2] != 0: + array = _rotate_2d(array.transpose(2, 0, 1), angle[2], fill_value).transpose(1, 2, 0) + return array + +def _rotate_2d(array, angle, fill_value=0): + """ Rotate an image along the first two axes. """ + shape = array.shape + matrix = cv2.getRotationMatrix2D((shape[1]//2, shape[0]//2), angle, 1) + return cv2.warpAffine(array, matrix, (shape[1], shape[0]), borderValue=fill_value).reshape(shape) + +# Resize +def resize(array, size, interpolation=1): + """ Resize image. """ + # interpolation=1 means bilinear + if array.shape[0] == 1: + resized = cv2.resize(src=array.squeeze(), dsize=(size[1], size[0]), interpolation=interpolation) + resized = resized.reshape(1, *resized.shape) + else: + resized = cv2.resize(src=array, dsize=(size[1], size[0]), interpolation=interpolation) + return resized + +# Scale +def scale_2d(array, scale, adjust=False): + """ Zoom in/out of the image along the first two axes. + + Parameters + ---------- + scale : tuple or float + Zooming factor for the first two axis. + adjust : bool + If True, then image is upscaled prior to rotation to avoid padding. + """ + scale = scale if isinstance(scale, (list, tuple, np.ndarray)) else [scale] * 2 + + if adjust: + array, initial_shape = adjust_shape(array, angle=0, scale=(*scale, 1)) + array = _scale_2d(array, scale) + if adjust: + array = center_crop(array, shape=initial_shape) + return array + +def scale_3d(array, scale, adjust=False): + """ Zoom in/out of the image in 3D. + + Parameters + ---------- + scale : tuple or float + Zooming factor for the first two axis. + """ + if adjust: + raise NotImplementedError('`adjust` is not implemented for 3D rotation!') + scale = scale if isinstance(scale, (list, tuple)) else [scale] * 3 + array = _scale_2d(array, + [scale[0], scale[1]]) + array = _scale_2d(array.transpose(1, 2, 0), + [1, scale[-1]]).transpose(2, 0, 1) + return array + +def _scale_2d(array, scale): + """ Zoom in/out of the image along the first two axes. """ + shape = array.shape + matrix = np.zeros((2, 3)) + matrix[:, :-1] = np.diag([scale[1], scale[0]]) + matrix[:, -1] = np.array([shape[1], shape[0]]) * (1 - np.array([scale[1], scale[0]])) / 2 + return cv2.warpAffine(array, matrix, (shape[1], shape[0])).reshape(shape) + + +# Adjust shape +def adjust_shape(array, angle=0, scale=(1, 1, 1)): + """ Resize image to avoid padding for rotation/scaling operations. """ + initial_shape = array.shape + adjusted_shape = adjust_shape_3d(shape=array.shape, angle=angle, scale=scale) + array = cv2.resize(array, dsize=(adjusted_shape[1], adjusted_shape[0])).reshape(*adjusted_shape) + return array, initial_shape + +def adjust_shape_3d(shape, angle=0, scale=(1, 1, 1)): + """ Compute adjusted 3D crop shape to rotate/scale it and get central crop without padding. + + Adjustments is based on assumption that rotation angles are defined as Tait-Bryan angles and + the sequence of extrinsic rotations axes is (axis_2, axis_0, axis_1), and scale performed after rotation. + + Parameters + ---------- + shape : tuple + Input shape. + angle : float or tuple of floats + Rotation angles about each axis. + scale : int or tuple, optional + Scale for each axis. + + Returns + ------- + tuple + Adjusted shape. + """ + angle = angle if isinstance(angle, (tuple, list)) else (angle, 0, 0) + scale = scale if isinstance(scale, (tuple, list)) else (scale, scale, 1) + + shape = np.ceil(np.array(shape) / np.array(scale)).astype(int) + if angle[2] != 0: + shape[2], shape[0] = _adjust_shape_for_rotation((shape[2], shape[0]), angle[2]) + if angle[1] != 0: + shape[2], shape[1] = _adjust_shape_for_rotation((shape[2], shape[1]), angle[1]) + if angle[0] != 0: + shape[0], shape[1] = _adjust_shape_for_rotation((shape[0], shape[1]), angle[0]) + return tuple(shape) + +def _adjust_shape_for_rotation(shape, angle): + """ Compute adjusted 2D crop shape to rotate it and get central crop without padding. """ + angle = abs(2 * np.pi * angle / 360) + limit = atan(shape[1] / shape[0]) + x_max, y_max = shape + if angle != 0: + if angle < limit: + x_max = shape[0] * cos(angle) + shape[1] * sin(angle) + 1 + else: + x_max = (shape[0] ** 2 + shape[1] ** 2) ** 0.5 + 1 + + if angle < np.pi / 2 - limit: + y_max = shape[0] * sin(angle) + shape[1] * cos(angle) + 1 + else: + y_max = (shape[0] ** 2 + shape[1] ** 2) ** 0.5 + 1 + return (int(ceil(x_max)), int(ceil(y_max))) + + +# Crops +def center_crop(array, shape): + """ Cut center crop of given shape. """ + old_shape, new_shape = np.array(array.shape), np.array(shape) + if (new_shape > old_shape).any(): + raise ValueError(f'Output shape={new_shape} can\'t be larger than input shape={old_shape}!') + + corner = old_shape // 2 - new_shape // 2 + slices = tuple(slice(start, start + length) for start, length in zip(corner, new_shape)) + return array[slices] + + +# Coordinate transforms +def affine_transform(array, alpha=10, rng=None): + """ Perspective transform. Moves three points to other locations. + Guaranteed not to flip image or scale it more than 2 times. + + Parameters + ---------- + alpha : float + Maximum distance along each axis between points before and after transform. + """ + rng = rng or np.random.default_rng(rng) + + shape = np.array(array.shape)[:2] + alpha = max(alpha, min(shape) // 16) + + center = shape // 2 + square_size = min(shape) // 3 + + pts1 = np.float32([center + square_size, + center - square_size, + [center[0] + square_size, center[1] - square_size]]) + pts2 = pts1 + rng.uniform(-alpha, alpha, size=pts1.shape).astype(np.float32) + matrix = cv2.getAffineTransform(pts1, pts2) + + return cv2.warpAffine(array, matrix, (shape[1], shape[0])).reshape(array.shape) + + +def perspective_transform(array, alpha, rng=None): + """ Perspective transform. Moves four points to other four. + Guaranteed not to flip image or scale it more than 2 times. + + Parameters + ---------- + alpha : float + Maximum distance along each axis between points before and after transform. + """ + rng = rng or np.random.default_rng(rng) + + shape = np.array(array.shape)[:2] + alpha = max(alpha, min(shape) // 16) + + center_ = shape // 2 + square_size = min(shape) // 3 + + pts1 = np.float32([center_ + square_size, + center_ - square_size, + [center_[0] + square_size, center_[1] - square_size], + [center_[0] - square_size, center_[1] + square_size]]) + pts2 = pts1 + rng.uniform(-alpha, alpha, size=pts1.shape).astype(np.float32) + matrix = cv2.getPerspectiveTransform(pts1, pts2) + + return cv2.warpPerspective(array, matrix, (shape[1], shape[0])).reshape(array.shape) + +def elastic_transform(array, alpha=40, sigma=4, rng=None): + """ Transform indexing grid of the first two axes. + + Parameters + ---------- + alpha : float + Maximum shift along each axis. + sigma : float + Smoothening factor. + """ + rng = rng or np.random.default_rng(rng) + shape_size = array.shape[:2] + + grid_scale = 4 + alpha //= grid_scale + sigma //= grid_scale + grid_shape = (shape_size[0]//grid_scale, shape_size[1]//grid_scale) + + blur_size = int(4 * sigma) | 1 + rand_x = cv2.GaussianBlur(rng.random(size=grid_shape, dtype=np.float32) * 2 - 1, + ksize=(blur_size, blur_size), sigmaX=sigma) * alpha + rand_y = cv2.GaussianBlur(rng.random(size=grid_shape, dtype=np.float32) * 2 - 1, + ksize=(blur_size, blur_size), sigmaX=sigma) * alpha + if grid_scale > 1: + rand_x = cv2.resize(rand_x, shape_size[::-1]) + rand_y = cv2.resize(rand_y, shape_size[::-1]) + + grid_x, grid_y = np.meshgrid(np.arange(shape_size[1]), np.arange(shape_size[0])) + grid_x = (grid_x.astype(np.float32) + rand_x) + grid_y = (grid_y.astype(np.float32) + rand_y) + + return cv2.remap(array, grid_x, grid_y, + borderMode=cv2.BORDER_REFLECT_101, + interpolation=cv2.INTER_LINEAR).reshape(array.shape) diff --git a/seismiqb/functional/similarity_metrics.py b/seismiqb/functional/similarity_metrics.py new file mode 100644 index 0000000..a5336c3 --- /dev/null +++ b/seismiqb/functional/similarity_metrics.py @@ -0,0 +1,248 @@ +""" Metrics for denoising seismic data. """ +import numpy as np +from scipy import fftpack + +try: + import torch + TORCH_AVAILABLE = True +except ImportError: + TORCH_AVAILABLE = False + +try: + from torchmetrics.functional import structural_similarity_index_measure,\ + peak_signal_noise_ratio, mean_squared_error,\ + error_relative_global_dimensionless_synthesis, universal_image_quality_index + METRICS = { + 'ssim': structural_similarity_index_measure, + 'psnr': peak_signal_noise_ratio, + 'ergas': error_relative_global_dimensionless_synthesis, + 'uqi': universal_image_quality_index, + 'mse': mean_squared_error + } +except ImportError: + METRICS = {} + + + + + +def compute_similarity_metric(array1, array2, metrics='all'): + """ Compute similarity metrics for a pair of images. + + Parameters + ---------- + array1, array2 : np.ndarray or torch.Tensor + Source images to evaluate. Works with (B, ...) arrays as well. + metrics : dict, list or str + Specifies functions to compute and their parameters. + Available names are {'ssim', 'psnr', 'ergas', 'uqi', 'mse'}. + + If dict, then should contain metric names as keys and their parameters as values. + If list, then consists of metric names, and they are evaluated with default parameters. + If 'all', then evaluate all metrics with default parameters. + + Returns + ------- + dict + Dictionary with metric names as keys and computed metrics as values. + """ + #pylint: disable=not-a-mapping + if not TORCH_AVAILABLE: + raise ImportError('Install `torch` library!') + if not METRICS: + raise ImportError('Install `torchmetrics` library!') + + # Parse `metrics` + if metrics == 'all': + metrics = list(METRICS.keys()) + if isinstance(metrics, str): + metrics = [metrics] + if isinstance(metrics, (tuple, list)): + metrics = dict.fromkeys(metrics, {}) + + for metric_name in metrics.keys(): + if metric_name not in METRICS: + raise ValueError(f'Incorrect metric name `{metric_name}`!') + + # Convert arrays to tensors. TODO: do that only when the metric requires + array1, array2 = torch.Tensor(array1), torch.Tensor(array2) + + returns = {} + for metric_name, metric_kwargs in metrics.items(): + result = METRICS[metric_name](array1, array2, **metric_kwargs) + returns[metric_name] = result.item() if isinstance(result, torch.Tensor) else result + return returns + + + +def local_correlation_map(image, prediction, map_to='pred', window_size=9, n_dims=1): + """ Local correlation map between an image and estimated noise. + + Parameters + ---------- + window_size : int + if `n_dims` is 1, correlation is measured between corresponding parts of traces of `window_size` size. + if `n_dims` is 2, correlation is measured between flattened windows of size (`window_size`, `window_size`). + n_dims : int + Number of dimensions for `window_size`. + + Returns + ------- + np.ndarray + Array of the same shape. + """ + image = image.squeeze() + prediction = prediction.squeeze() + image_noise = np.abs(image - prediction) + image = image if map_to == 'image' else prediction + img_shape = image.shape + + # "same" padding along trace for 1d window or both dims for 2d + pad = window_size // 2 + pad_width = [[pad, window_size - (1 + pad)], [pad * (n_dims - 1), (window_size - (1 + pad)) * (n_dims - 1)]] + + image = np.pad(image, pad_width=pad_width, mode='mean') + image_noise = np.pad(image_noise, pad_width=pad_width, mode='mean') + + # Vectorization + window_shape=[window_size, window_size if n_dims == 2 else 1] + image_view = np.lib.stride_tricks.sliding_window_view(image, window_shape=window_shape) + image_noise_view = np.lib.stride_tricks.sliding_window_view(image_noise, window_shape=window_shape) + + straighten = (np.dot(*image_view.shape[:2]), np.dot(*image_view.shape[2:])) + image_view = image_view.reshape(straighten) + image_noise_view = image_noise_view.reshape(straighten) + + pearson = _pearson_corr_2d(image_view, image_noise_view).reshape(img_shape) + return np.nan_to_num(pearson) + +def _pearson_corr_2d(x, y): + """ Squared Pearson correlation coefficient between corresponding rows of 2d input arrays. """ + x_centered = x - x.mean(axis=1, keepdims=True).reshape(-1, 1) + y_centered = y - y.mean(axis=1, keepdims=True).reshape(-1, 1) + corr = (x_centered * y_centered).sum(axis=1) + corr /= np.sqrt((x_centered**2).sum(axis=1) * (y_centered**2).sum(axis=1)) + return corr ** 2 + + +def local_similarity_map(image, prediction, map_to='pred', lamb=0.5, window_size=9, n_dims=1, **kwargs): + """ Local Similarity Map between an image and estimated noise. + Chen, Yangkang, and Sergey Fomel. "`Random noise attenuation using local signal-and-noise orthogonalization + `_" + + Parameters + ---------- + lamb : float + Regularization parameter from 0 to 1. + window_size : int + Size of the window for a local similarity estimation. + n_dims : int + Number of dimensions for `window_size`. + tol : float, optional + Tolerance for `shaping_conjugate_gradient`. + N : int, optional + Maximum number of iterations for `shaping_conjugate_gradient`. + + Returns + ------- + np.ndarray + Array of the same shape. + """ + image = image.squeeze() + prediction = prediction.squeeze() + image_noise = np.abs(image - prediction) + image = image if map_to == 'image' else prediction + img_shape = image.shape + + pad = window_size // 2 + pad_width = [[pad, window_size - (1 + pad)], [pad * (n_dims - 1), (window_size - (1 + pad)) * (n_dims - 1)]] + + image = np.pad(image, pad_width=pad_width, mode='mean') + image_noise = np.pad(image_noise, pad_width=pad_width, mode='mean') + + window_shape=[window_size, window_size if n_dims == 2 else 1] + image_view = np.lib.stride_tricks.sliding_window_view(image, window_shape=window_shape) + image_noise_view = np.lib.stride_tricks.sliding_window_view(image_noise, window_shape=window_shape) + + straighten = (np.dot(*image_view.shape[:2]), np.dot(*image_view.shape[2:])) + image_view = image_view.reshape(straighten) + image_noise_view = image_noise_view.reshape(straighten) + + H = np.eye(window_size**n_dims, dtype=np.float) * lamb + H = np.lib.stride_tricks.as_strided(H, shape=(image_view.shape[0], window_size**n_dims, window_size**n_dims), + strides=(0, 8 * window_size**n_dims, 8)) + + sim_local = _local_similarity(a=image_view, b=image_noise_view, H=H, **kwargs) + return sim_local.reshape(img_shape) + +def _local_similarity(a, b, H, *args, **kwargs): + """ Local Similarity between an image and estimated noise. """ + A = np.array([np.diag(a[i]) for i in range(len(a))]) + B = np.array([np.diag(b[i]) for i in range(len(b))]) + c1 = _shaping_conjugate_gradient(L=A, H=H, d=b, *args, **kwargs) + c2 = _shaping_conjugate_gradient(L=B, H=H, d=a, *args, **kwargs) + return np.sum(c1 * c2, axis=1) + +def _shaping_conjugate_gradient(L, H, d, tol=1e-5, N=20): + """ Vectorized Shaping Conjugate gradient Algorithm for a system with smoothing operator. + Fomel, Sergey. "`Shaping regularization in geophysical-estimation problems + `_". + Variables and parameters are preserved as in the paper. + """ + p = np.zeros_like(d) + m = np.zeros_like(d) + r = -d + sp = np.zeros_like(d) + sm = np.zeros_like(d) + sr = np.zeros_like(d) + EPS = 1e-5 + for i in range(N): + gm = (np.transpose(L, axes=[0, 2, 1]) @ r[..., np.newaxis]).squeeze() - m + gp = (np.transpose(H, axes=[0, 2, 1]) @ gm[..., np.newaxis]).squeeze() + p + gm = H @ gp[..., np.newaxis] + gr = L @ gm + + rho = np.sum(gp ** 2, axis=1) + if i == 0: + beta = np.zeros((L.shape[0], 1)) + rho0 = rho + else: + beta = (rho / (rho_hat + EPS))[..., np.newaxis] + if np.all(beta < tol) or np.all(rho / (rho0 + EPS) < tol): + return m + + sp = gp + beta * sp + sm = gm.squeeze() + beta * sm + sr = gr.squeeze() + beta * sr + + alpha = rho / (np.sum(sr ** 2, axis=1) + np.sum(sp ** 2, axis=1) - np.sum(sm ** 2, axis=1) + EPS) + alpha = alpha[..., np.newaxis] + + p -= alpha * sp + m -= alpha * sm + r -= alpha * sr + rho_hat = rho + return m + + + +def fourier_power_spectrum(image, prediction, fourier_map='pred', map_to=None, **kwargs): + """ Fourier Power Spectrum for an image. + + Parameters + ---------- + fourier_map : str + If 'image', computes power spectrum for `image`. + If 'pred', computes power spectrum for `prediction`. + + Returns + ------- + np.ndarray + Array of the same shape. + """ + image = image if fourier_map == 'image' else prediction + image = image.squeeze() + img_fft = fftpack.fft2(image, **kwargs) + shift_fft = fftpack.fftshift(img_fft) + spectrum = np.abs(shift_fft)**2 + return np.log10(spectrum).squeeze() diff --git a/seismiqb/geometry/__init__.py b/seismiqb/geometry/__init__.py new file mode 100644 index 0000000..58aa92d --- /dev/null +++ b/seismiqb/geometry/__init__.py @@ -0,0 +1,7 @@ +""" A class for working with seismic data. """ +from .base import Geometry +from .segyio_loader import SegyioLoader, SafeSegyioLoader +from .memmap_loader import MemmapLoader +from .segy import GeometrySEGY +from .converted import GeometryHDF5 +from .export_mixin import array_to_segy, array_to_sgy diff --git a/seismiqb/geometry/base.py b/seismiqb/geometry/base.py new file mode 100644 index 0000000..5fd6d36 --- /dev/null +++ b/seismiqb/geometry/base.py @@ -0,0 +1,1166 @@ +""" Base class for working with seismic data. """ +import os +import sys +from textwrap import dedent +from contextlib import contextmanager + +import numpy as np + +import cv2 +from scipy.interpolate import interp1d +from scipy.signal import savgol_filter +from scipy.ndimage import binary_erosion + +from batchflow import Normalizer + +from .benchmark_mixin import BenchmarkMixin +from .conversion_mixin import ConversionMixin +from .export_mixin import ExportMixin +from .metric_mixin import MetricMixin + +from ..utils import SQBStorage, lru_cache, CacheMixin, TransformsMixin, select_printer, transformable, take_along_axis +from ..plotters import plot + + + +class Geometry(BenchmarkMixin, CacheMixin, ConversionMixin, ExportMixin, MetricMixin, TransformsMixin): + """ Class to infer information about seismic cube in various formats and provide format agnostic interface to them. + + During the SEG-Y processing, a number of statistics are computed. They are saved next to the cube under the + `.segy_meta` extension, so that subsequent loads (in, possibly, other formats) don't have to recompute them. + Most of them are loaded at initialization, but the most memory-intensive ones are loaded on demand. + + Based on the extension of the path, a different subclass is used to implement key methods for data indexing. + Currently supported extensions are SEG-Y and TODO: + The last two are created by converting the original SEG-Y cube. + During the conversion, an extra step of `int8` quantization can be performed to reduce the disk usage. + + Independent of the exact format, `Geometry` provides the following: + - attributes to describe shape and structure of the cube like `shape` and `lengths`, + as well as exact values of file-wide headers, for example, `depth`, `delay`, + `sample_rate` and `sample_interval`. + + - method :meth:`collect_stats` to infer information about the amplitudes distribution: + under the hood, we make a full pass through the cube data to collect global, spatial and depth-wise stats. + + - :meth:`load_slide` (2D entity) or :meth:`load_crop` (3D entity) methods to load data from the cube: + - :meth:`load_slide` takes an ordinal index of the slide and its axis; + - :meth:`load_crop` works off of complete location specification (triplet of slices). + + - textual representation of cube geometry: method `print` shows the summary of an instance with + information about its location and values; `print_textual` allows to see textual header from a SEG-Y. + + - visual representation of cube geometry: + - :meth:`show` to display top view on cube with computed statistics; + - :meth:`show_slide` to display front view on various slices of data. + + Parameters + ---------- + path : str + Path to seismic cube. Supported formats are `segy`, TODO. + meta_path : str, optional + Path to pre-computed statistics. If not provided, use the same as `path` with `_meta` postfix. + + SEG-Y parameters + ---------------- + TODO + + HDF5 parameters + --------------- + TODO + """ + # Headers to use as a unique id of a trace + INDEX_HEADERS_PRESTACK = ('FieldRecord', 'TraceNumber') + INDEX_HEADERS_POSTSTACK = ('INLINE_3D', 'CROSSLINE_3D') + INDEX_HEADERS_CDP = ('CDP_Y', 'CDP_X') + + # Headers to load from SEG-Y cube + ADDITIONAL_HEADERS_PRESTACK_FULL = ('FieldRecord', 'TraceNumber', 'TRACE_SEQUENCE_FILE', + 'CDP', 'CDP_TRACE', 'offset') + ADDITIONAL_HEADERS_POSTSTACK_FULL = ('INLINE_3D', 'CROSSLINE_3D', 'CDP_X', 'CDP_Y') + + # Value to use in dead traces + FILL_VALUE = 0.0 + + # Attributes to store in a separate file with meta + PRESERVED = [ # loaded at instance initialization + # Crucial geometry properties + 'n_traces', 'depth', 'delay', 'sample_interval', 'sample_rate', 'shape', + 'shifts', 'lengths', 'ranges', 'increments', 'regular_structure', + 'index_matrix', 'absent_traces_matrix', 'dead_traces_matrix', + 'n_alive_traces', 'n_dead_traces', + + # Additional info from SEG-Y + 'segy_path', 'segy_text', + + # Scalar stats for cube values: computed for the entire SEG-Y / its subset + 'min', 'max', 'mean', 'std', 'n_value_uniques', + 'subset_min', 'subset_max', 'subset_mean', 'subset_std', + 'quantile_precision', 'quantile_support', 'quantile_values', + ] + + PRESERVED_LAZY = [ # loaded at the time of the first access + 'index_unsorted_uniques', 'index_sorted_uniques', 'index_value_to_ordinal', + 'min_vector', 'max_vector', 'mean_vector', 'std_vector', + 'min_matrix', 'max_matrix', 'mean_matrix', 'std_matrix', + ] + + PRESERVED_LAZY_CACHED = [ # loaded at the time of the first access, stored in the instance + 'headers', + ] + + PRESERVED_LAZY_MISC = [ # additional stats that may be absent. loaded at the time of the first access + 'quantization_ranges', 'quantization_error', 'rotation_matrix', 'area', + ] + + PRESERVED_LAZY_ALL = PRESERVED_LAZY + PRESERVED_LAZY_CACHED + PRESERVED_LAZY_MISC + + @staticmethod + def new(path, *args, **kwargs): + """ A convenient selector of appropriate (SEG-Y or HDF5) geometry. """ + #pylint: disable=import-outside-toplevel + extension = os.path.splitext(path)[1][1:] + + if extension in {'sgy', 'segy', 'seg', 'qsgy'}: + from .segy import GeometrySEGY + cls = GeometrySEGY + elif extension in {'hdf5', 'qhdf5'}: + from .converted import GeometryHDF5 + cls = GeometryHDF5 + else: + raise TypeError(f'Unknown format of the cube: {extension}') + return cls(path, *args, **kwargs) + + def __init__(self, path, meta_path=None, safe=False, use_cache=False, init=True, **kwargs): + # Path to the file + self.path = path + + # Names + self.name = os.path.basename(self.path) + self.short_name, self.format = os.path.splitext(self.name) + + # Meta + self._meta_path = meta_path + self.meta_storage = SQBStorage(self.meta_path) + + # Instance flags + self.safe = safe + self.use_cache = use_cache + + # Lazy properties + self._quantile_interpolator = None + self._normalization_stats = None + self._quantization_stats = None + self._quantizer = None + self._normalizer = None + + # Init from subclasses + if init: + self._init_kwargs = kwargs + self.init(path, **kwargs) + + # Meta: store/load pre-computed statistics and attributes from disk + def __getattr__(self, key): + """ Load item from stored meta. """ + if key not in self.__dict__ and (key in self.PRESERVED_LAZY_ALL) \ + and self.meta_storage.exists and self.meta_storage.has_item(key): + value = self.meta_storage.read_item(key) + if key in self.PRESERVED_LAZY_CACHED: + setattr(self, key, value) + return value + return object.__getattribute__(self, key) + + @property + def meta_path(self): + """ Paths to the file with stored meta. """ + if self._meta_path is not None: + return self._meta_path + + if hasattr(self, 'path'): + if 'hdf5' in self.path: + return self.path + return self.path + '_meta' + raise ValueError('No `meta_path` exists!') + + def load_meta(self, keys): + """ Load `keys` from meta storage and setattr them to `self`. """ + items = self.meta_storage.read(keys) + for key, value in items.items(): + setattr(self, key, value) + + def dump_meta(self, path=None): + """ Dump all attributes, referenced in `PRESERVED_*` lists, to a storage. + If no `path` is provided, uses `meta_storage` of the `self`. """ + storage = self.meta_storage if path is None else SQBStorage(path) + items = {key : getattr(self, key) for key in self.PRESERVED + self.PRESERVED_LAZY + self.PRESERVED_LAZY_MISC + if getattr(self, key, None) is not None} + items['type'] = 'geometry-meta' + storage.store(items) + + + # Redefined protocols + def __getnewargs__(self): + return (self.path, ) + + def __getstate__(self): + self.reset_cache() + state = self.__dict__.copy() + for name in ['loader', 'axis_to_projection'] + self.PRESERVED_LAZY_CACHED: + state.pop(name, None) + return state + + def __setstate__(self, state): + for key, value in state.items(): + setattr(self, key, value) + + if self.converted: + self.init(self.path, **self._init_kwargs) + else: + self.loader = self._infer_loader_class(self._init_kwargs.get('loader_class', 'memmap'))(self.path) + + + # Data loading + def __getitem__(self, key): + """ Slice the cube using the usual `NumPy`-like semantics. """ + key, axis_to_squeeze = self.process_key(key) + + crop = self.load_crop(key) + if axis_to_squeeze: + crop = np.squeeze(crop, axis=tuple(axis_to_squeeze)) + return crop + + def process_key(self, key): + """ Convert tuple of slices/ints into locations. """ + # Convert to list + if isinstance(key, (int, slice)): + key = [key] + elif isinstance(key, tuple): + key = list(key) + + # Pad not specified dimensions + if len(key) != len(self.shape): + key += [slice(None)] * (len(self.shape) - len(key)) + + # Parse each subkey. Remember location of integers for later squeeze + key_, axis_to_squeeze = [], [] + for i, (subkey, limit) in enumerate(zip(key, self.shape)): + if isinstance(subkey, slice): + slc = slice(max(subkey.start or 0, 0), + min(subkey.stop or limit, limit), subkey.step) + + elif isinstance(subkey, (int, np.integer)): + subkey = subkey if subkey >= 0 else limit - subkey + slc = slice(subkey, subkey + 1) + axis_to_squeeze.append(i) + + if slc.start < 0 or slc.stop > limit: + raise ValueError(f'Slice `{slc}` is outside geometry boundaries!') + key_.append(slc) + + return key_, axis_to_squeeze + + + # Data loading: cache + def load_slide(self, index, axis=0, limits=None, buffer=None, safe=None, use_cache=None): + """ Load one slide of data along specified axis. + Under the hood, relies on :meth`:`load_slide_native`, implemented in subclasses. + Also allows to use slide cache to speed up the loading process. + + Parameters + ---------- + index : int, str + If int, then interpreted as the ordinal along the specified axis. + If `'random'`, then we generate random index along the axis. + If string of the `'#XXX'` format, then we interpret it as the exact indexing header value. + axis : int + Axis of the slide. + limits : sequence of ints, slice, optional + Slice of the data along the depth (last) axis. + buffer : np.ndarray, optional + Buffer to read the data into. If possible, avoids copies. + safe : bool or None + Whether to force usage of public (safe) or private API of data loading. + If None, then uses instance-wide value (default False). + use_cache : bool or None + Whether to use cache for lines. + If None, then uses instance-wide value (default False). + If bool, forces that behavior. + """ + # Parse parameters + index = self.get_slide_index(index=index, axis=axis) + axis = self.parse_axis(axis) + + if limits is not None and axis==2: + raise ValueError('Providing `limits` with `axis=2` is meaningless!') + + safe = safe if safe is not None else self.safe + use_cache = use_cache if use_cache is not None else self.use_cache + + # Actual data loading + if use_cache is False: + return self.load_slide_native(index=index, axis=axis, limits=limits, buffer=buffer, safe=safe) + + slide = self.load_slide_cached(index=index, axis=axis, limits=limits) + if buffer is not None: + buffer[:] = slide + else: + buffer = slide + return slide + + take = load_slide # for compatibility with numpy API + + @lru_cache(128) + def load_slide_cached(self, index, axis=0, limits=None): + """ Cached version of :meth:`load_slide_native`. """ + return self.load_slide_native(index=index, axis=axis, limits=limits, buffer=None, safe=True) + + def load_crop(self, locations, buffer=None, safe=None, use_cache=None): + """ Load crop (3D subvolume) from the cube. + Uses either public or private API of `h5py`: the latter reads data directly into preallocated buffer. + Also allows to use slide cache to speed up the loading process. + + Parameters + ---------- + locations : sequence + A triplet of slices to specify the location of a subvolume. + buffer : np.ndarray, optional + Buffer to read the data into. If possible, avoids copies. + safe : bool + Whether to force usage of public (safe) or private API of data loading. + use_cache : bool or None + Whether to use cache for lines. + If None, then uses instance-wide value (default False). + If bool, forces that behavior. + """ + safe = safe if safe is not None else self.safe + use_cache = use_cache if use_cache is not None else self.use_cache + + if use_cache is False: + return self.load_crop_native(locations=locations, buffer=buffer, safe=safe) + return self.load_crop_cached(locations=locations, buffer=buffer) + + def load_crop_cached(self, locations, axis=None, buffer=None): + """ Cached version of :meth:`load_crop`. """ + # Parse parameters + shape = self.locations_to_shape(locations) + axis = axis or self.get_optimal_axis(shape=shape) + to_projection_transposition, from_projection_transposition = self.compute_axis_transpositions(axis) + + locations = [locations[idx] for idx in to_projection_transposition] + locations = tuple(locations) + + # Prepare buffer + if buffer is None: + buffer = np.empty(shape, dtype=np.float32) + buffer = buffer.transpose(to_projection_transposition) + + # Load data + for i, idx in enumerate(range(locations[0].start, locations[0].stop)): + buffer[i] = self.load_slide_cached(index=idx, axis=axis)[locations[1], locations[2]] + + # View buffer in original ordering + buffer = buffer.transpose(from_projection_transposition) + return buffer + + def add_to_mask(self, mask, locations=None, **kwargs): + """ Load data from `locations` and put into `mask`. Is used for labels which are geometries. """ + mask[:] = self.load_crop(locations) + return mask + + def enable_cache(self): + """ Enable cache for loaded slides. """ + self.use_cache = True + + def disable_cache(self): + """ Disable cache for loaded slides, and clear existing cache. """ + self.use_cache = False + self.reset_cache() + + @contextmanager + def enabled_cache(self, enable=True): + """ Context manager for enabling cache. """ + try: + if enable: + self.enable_cache() + yield self + finally: + self.disable_cache() + + def load_subset(self, n_traces=100_000, seed=42): + """ Load a subset of data. Returns an array of (n_traces, depth) shape. """ + rng = np.random.default_rng(seed=seed) + if self.converted is False: + alive_traces_indices = self.index_matrix[~self.dead_traces_matrix].ravel() + indices = rng.choice(alive_traces_indices, size=n_traces) + data = self.load_by_indices(indices) + else: + indices = rng.choice(self.shape[0], size=n_traces // self.shape[1], replace=False) + data = [] + for index in indices: + slide = self.load_slide(index=index, axis=0) + slide_bounds = self.compute_auto_zoom(index=index, axis=0)[0] + data.append(slide[slide_bounds].ravel()) + data = np.concatenate(data) + return data + + + # Coordinate system conversions + def lines_to_ordinals(self, array): + """ Convert values from inline-crossline coordinate system to their ordinals. + In the simplest case of regular grid `ordinal = (value - value_min) // value_step`. + In the case of irregular spacings between values, we have to manually map values to ordinals. TODO. + """ + # Indexing headers + if self.regular_structure: + for i in range(self.index_length): + array[:, i] -= self.shifts[i] + if self.increments[i] != 1: + array[:, i] //= self.increments[i] + else: + raise NotImplementedError + + # Depth to units + if array.shape[1] == self.index_length + 1: + array = array.astype(np.float32) + array[:, self.index_length] -= self.delay + array[:, self.index_length] /= self.sample_interval + return array + + def ordinals_to_lines(self, array): + """ Convert ordinals to values in inline-crossline coordinate system. + In the simplest case of regular grid `value = value_min + ordinal * value_step`. + In the case of irregular spacings between values, we have to manually map ordinals to values. TODO. + """ + array = array.astype(np.float32) + + # Indexing headers + if self.regular_structure: + for i in range(self.index_length): + if self.increments[i] != 1: + array[:, i] *= self.increments[i] + array[:, i] += self.shifts[i] + else: + raise NotImplementedError + + # Units to depth + if array.shape[1] == self.index_length + 1: + array[:, self.index_length] *= self.sample_interval + array[:, self.index_length] += self.delay + return array + + def lines_to_cdp(self, points): + """ Convert lines to CDP. """ + return (self.rotation_matrix[:, :2] @ points.T + self.rotation_matrix[:, 2].reshape(2, -1)).T + + def cdp_to_lines(self, points): + """ Convert CDP to lines. """ + inverse_matrix = np.linalg.inv(self.rotation_matrix[:, :2]) + lines = (inverse_matrix @ points.T - inverse_matrix @ self.rotation_matrix[:, 2].reshape(2, -1)).T + return np.rint(lines) + + + # Stats and normalization + @property + def quantile_interpolator(self): + """ Quantile interpolator for arbitrary values. """ + if self._quantile_interpolator is None: + self._quantile_interpolator = interp1d(self.quantile_support, self.quantile_values) + return self._quantile_interpolator + + def get_quantile(self, q): + """ Get q-th quantile of the cube data. Works with any `q` in [0, 1] range. """ + #pylint: disable=not-callable + return self.quantile_interpolator(q).astype(np.float32) + + def make_normalization_stats(self): + """ Values for performing normalization of data from the cube. """ + q_01, q_05, q_95, q_99 = self.get_quantile(q=[0.01, 0.05, 0.95, 0.99]) + self._normalization_stats = { + 'mean': self.mean, + 'std': self.std, + 'min': self.min, + 'max': self.max, + 'q_01': q_01, + 'q_05': q_05, + 'q_95': q_95, + 'q_99': q_99, + } + return self._normalization_stats + + @property + def normalization_stats(self): + """ Property with default normalization stats for synthetic images. """ + if self._normalization_stats is None: + self.make_normalization_stats() + return self._normalization_stats + + def make_normalizer(self, mode='meanstd', clip_to_quantiles=False, q=(0.01, 0.99), normalization_stats=None): + """ Create normalizer. """ + if normalization_stats == 'field': + normalization_stats = self.normalization_stats + self._normalizer = Normalizer(mode=mode, clip_to_quantiles=clip_to_quantiles, q=q, + normalization_stats=normalization_stats) + return self._normalizer + + @property + def normalizer(self): + """ Normalizer instance. If it doesn't already exist, it will be created with default parameters. """ + if self._normalizer is not None: + return self._normalizer + return self.make_normalizer() + + def make_quantization_stats(self, ranges=0.99, clip=True, center=False, dtype=np.int8, + n_quantile_traces=100_000, seed=42): + """ Compute quantization statistics. """ + self._quantization_stats = self.compute_quantization_parameters(ranges=ranges, clip=clip, center=center, + dtype=dtype, + n_quantile_traces=n_quantile_traces, seed=seed) + return self._quantization_stats + + @property + def quantization_stats(self): + """ Property with default normalization stats for synthetic images. """ + if self._quantization_stats is None: + self.make_quantization_stats() + return self._quantization_stats + + def make_quantizer(self, ranges=0.99, clip=True, center=False, dtype=np.int8, + n_quantile_traces=100_000, seed=42): + """ Compute quantization statistics and create quantizer. """ + self.make_quantization_stats(ranges=ranges, clip=clip, center=center, dtype=dtype, + n_quantile_traces=n_quantile_traces, seed=seed) + self._quantizer = self.quantization_stats['quantizer'] + return self._quantizer + + @property + def quantizer(self): + """ Quantizer instance. If it doesn't already exist, it will be created with default parameters. """ + if self._quantizer is not None: + return self._quantizer + return self.make_quantizer() + + def estimate_impulse(self, wavelet_length=40, n_traces=10_000, seed=42): + """ Estimate impulse on a random subset of data. + The idea is to average traces in the frequency domain to get the frequencies of an impulse, produced them. + """ + data = self.load_subset(n_traces=n_traces, seed=seed) + + # FFT domain + data_fft = np.fft.rfft(data, axis=-1) + wavelet_fft = np.mean(np.abs(data_fft), axis=0) + + # Depth domain + wavelet_estimation = np.real(np.fft.irfft(wavelet_fft)[:wavelet_length//2]) + wavelet_estimation = np.concatenate((wavelet_estimation[1:][::-1], wavelet_estimation), axis=0) + return wavelet_estimation + + + # Spatial matrices + @property + def snr(self): + """ Signal-to-noise ratio. """ + eps = 1 + snr = np.log((self.mean_matrix**2 + eps) / (self.std_matrix**2 + eps)) + snr[self.std_matrix == 0] = np.nan + return snr + + @transformable + def get_dead_traces_matrix(self): + """ Dead traces matrix. + Due to decorator, allows for additional transforms at loading time. + + Parameters + ---------- + dilation_iterations : int, optional + Number of dilation iterations to apply. + """ + return self.dead_traces_matrix.copy() + + @transformable + def get_alive_traces_matrix(self): + """ Alive traces matrix. + Due to decorator, allows for additional transforms at loading time. + + Parameters + ---------- + dilation_iterations : int, optional + Number of dilation iterations to apply. + """ + return 1 - self.dead_traces_matrix + + def get_grid(self, frequency=100, iline=True, xline=True, margin=20): + """ Compute the grid over alive traces. """ + #pylint: disable=unexpected-keyword-arg + # Parse parameters + frequency = frequency if isinstance(frequency, (tuple, list)) else (frequency, frequency) + + # Prepare dilated `dead_traces_matrix` + dead_traces_matrix = self.get_dead_traces_matrix(dilation_iterations=margin) + + if margin: + dead_traces_matrix[:+margin, :] = 1 + dead_traces_matrix[-margin:, :] = 1 + dead_traces_matrix[:, :+margin] = 1 + dead_traces_matrix[:, -margin:] = 1 + + # Select points to keep + idx_i, idx_x = np.nonzero(~dead_traces_matrix) + grid = np.zeros_like(dead_traces_matrix) + if iline: + mask = (idx_i % frequency[0] == 0) + grid[idx_i[mask], idx_x[mask]] = 1 + if xline: + mask = (idx_x % frequency[1] == 0) + grid[idx_i[mask], idx_x[mask]] = 1 + return grid + + + # Properties + def __len__(self): + """ Number of meaningful traces in a Geometry. """ + if hasattr(self, 'n_alive_traces'): + return self.n_alive_traces + return self.n_traces + + @property + def axis_names(self): + """ Names of the axes: indexing headers and `DEPTH` as the last one. """ + return list(self.index_headers) + ['DEPTH'] + + @property + def bbox(self): + """ Bounding box with geometry limits. """ + return np.array([[0, s] for s in self.shape]) + + @property + def spatial_shape(self): + """ Shape of the cube along indexing headers. """ + return tuple(self.shape[:2]) + + @property + def textual(self): + """ Wrapped textual header of SEG-Y file. """ + text = self.segy_text[0] + lines = [text[start:start + 80] for start in range(0, len(text), 80)] + return '\n'.join(lines) + + @property + def file_size(self): + """ Storage size in GB. """ + return round(os.path.getsize(self.path) / (1024**3), 3) + + @property + def nbytes(self): + """ Size of the instance in bytes. """ + attributes = set(['headers']) + attributes.update({attribute for attribute in self.__dict__ + if 'matrix' in attribute or '_quality' in attribute}) + + return self.cache_size + sum(sys.getsizeof(getattr(self, attribute)) + for attribute in attributes if hasattr(self, attribute)) + + @property + def ngbytes(self): + """ Size of instance in gigabytes. """ + return self.nbytes / (1024 ** 3) + + + # Attribute retrieval. Used by `Field` instances + def load_attribute(self, src, **kwargs): + """ Load instance attribute from a string, e.g. `snr` or `std_matrix`. + Used from a field to re-direct calls. + """ + return self.get_property(src=src, **kwargs) + + @transformable + def get_property(self, src, **_): + """ Load a desired instance attribute. Decorated to allow additional postprocessing steps. """ + return getattr(self, src) + + + # Textual representation + def __repr__(self): + msg = f'geometry `{self.short_name}`' + if not hasattr(self, 'shape'): + return f'' + return f'' + + def __str__(self): + if not hasattr(self, 'shape'): + return f'' + + msg = f""" + Processed geometry for cube {self.path} + Index headers: {self.index_headers} + Traces: {self.n_traces:,} + Shape: {tuple(self.shape)} + Time delay: {self.delay} ms + Sample interval: {self.sample_interval} ms + Sample rate: {self.sample_rate} Hz + Area: {self.area:4.1f} km² + + File size: {self.file_size:4.3f} GB + Instance (in-memory) size: {self.ngbytes:4.3f} GB + """ + + if self.converted and os.path.exists(self.segy_path): + segy_size = os.path.getsize(self.segy_path) / (1024 ** 3) + msg += f'SEG-Y original size: {segy_size:4.3f} GB\n' + + if hasattr(self, 'dead_traces_matrix'): + msg += f""" + Number of dead traces: {self.n_dead_traces:,} + Number of alive traces: {self.n_alive_traces:,} + Fullness: {self.n_alive_traces / self.n_traces:2.2f} + """ + + if self.has_stats: + msg += f""" + Value statistics: + mean | std: {self.mean:>10.2f} | {self.std:<10.2f} + min | max: {self.min:>10.2f} | {self.max:<10.2f} + q01 | q99: {self.get_quantile(0.01):>10.2f} | {self.get_quantile(0.99):<10.2f} + Number of unique values: {self.n_value_uniques:>10} + """ + + if self.quantized: + try: + msg += f""" + Quantization ranges: {self.quantization_ranges[0]:>10.2f} | {self.quantization_ranges[1]:<10.2f} + Quantization error: {self.quantization_error:>10.3f} + """ + except AttributeError: + pass + return dedent(msg).strip() + + def print(self, printer=print): + """ Show textual representation. """ + select_printer(printer)(self) + + def print_textual(self, printer=print): + """ Show textual header from original SEG-Y. """ + select_printer(printer)(self.textual) + + def print_location(self, printer=print): + """ Show ranges for each of the headers. """ + msg = '\n'.join(f'{header+":":<35} [{uniques[0]}, {uniques[-1]}]' + for header, uniques in zip(self.index_headers, self.index_sorted_uniques)) + select_printer(printer)(msg) + + def log(self): + """ Log info about geometry to a file next to the cube. """ + self.print(printer=os.path.dirname(self.path) + '/CUBE_INFO.log') + + + # Visual representation + def show(self, matrix='snr', plotter=plot, **kwargs): + """ Show geometry related top-view map. """ + matrix_name = matrix if isinstance(matrix, str) else kwargs.get('matrix_name', 'custom matrix') + kwargs = { + 'cmap': 'magma', + 'title': f'`{matrix_name}` map of cube `{self.short_name}`', + 'xlabel': self.index_headers[0], + 'ylabel': self.index_headers[1], + 'colorbar': True, + **kwargs + } + matrix = getattr(self, matrix) if isinstance(matrix, str) else matrix + return plotter(matrix, **kwargs) + + def show_histogram(self, n_traces=100_000, seed=42, bins=50, plotter=plot, **kwargs): + """ Show distribution of amplitudes in a random subset of the cube. """ + data = self.load_subset(n_traces=n_traces, seed=seed) + + kwargs = { + 'title': (f'Amplitude distribution for {self.short_name}' + + f'\n Mean/std: {np.mean(data):3.3f}/{np.std(data):3.3f}'), + 'label': 'Amplitudes histogram', + 'xlabel': 'amplitude', + 'ylabel': 'density', + **kwargs + } + return plotter(data, bins=bins, mode='histogram', **kwargs) + + def show_slide(self, index, axis=0, zoom=None, plotter=plot, **kwargs): + """ Show seismic slide in desired index. + Under the hood relies on :meth:`load_slide`, so works with geometries in any formats. + Parameters + ---------- + index : int, str + Index of the slide to show. + If int, then interpreted as the ordinal along the specified axis. + If `'random'`, then we generate random index along the axis. + If string of the `'#XXX'` format, then we interpret it as the exact indexing header value. + axis : int + Axis of the slide. + zoom : tuple, None or 'auto' + Tuple of slices to apply directly to 2d images. If None, slicing is not applied. + If 'auto', zero traces on bounds will be dropped. + plotter : instance of `plot` + Plotter instance to use. + Combined with `positions` parameter allows using subplots of already existing plotter. + """ + axis = self.parse_axis(axis) + slide = self.load_slide(index=index, axis=axis) + xmin, xmax, ymin, ymax = 0, slide.shape[0], slide.shape[1], 0 + + if zoom == 'auto': + zoom = self.compute_auto_zoom(index, axis) + if zoom: + slide = slide[zoom] + xmin = zoom[0].start or xmin + xmax = zoom[0].stop or xmax + ymin = zoom[1].stop or ymin + ymax = zoom[1].start or ymax + + # Plot params + if len(self.index_headers) > 1: + title = f'{self.axis_names[axis]} {index} out of {self.shape[axis]}' + + if axis in [0, 1]: + xlabel = self.index_headers[1 - axis] + ylabel = 'DEPTH' + else: + xlabel = self.index_headers[0] + ylabel = self.index_headers[1] + else: + title = '2D seismic slide' + xlabel = self.index_headers[0] + ylabel = 'DEPTH' + + kwargs = { + 'title': title, + 'suptitle': f'Field `{self.short_name}`', + 'xlabel': xlabel, + 'ylabel': ylabel, + 'cmap': 'Greys_r', + 'colorbar': True, + 'extent': (xmin, xmax, ymin, ymax), + 'labeltop': False, + 'labelright': False, + **kwargs + } + return plotter(slide, **kwargs) + + def show_spectrum(self, n_traces=1000, seed=42, frequency_threshold=150, + filter_length=31, filter_order=3, **kwargs): + """ Show power and phase spectrums of a random subset of a cube data. """ + data = self.load_subset(n_traces=n_traces, seed=seed) + spectrum = np.fft.rfft(data, axis=-1) + + power_spectrum = np.abs(spectrum).mean(axis=0) + phase_spectrum = np.angle(spectrum).mean(axis=0) + frequencies = np.fft.rfftfreq(n=self.depth, d=self.sample_interval * 1e-3) + + if frequency_threshold is not None: + mask = frequencies <= frequency_threshold + frequencies = frequencies[mask] + power_spectrum = power_spectrum[mask] + phase_spectrum = phase_spectrum[mask] + + power_spectrum_smoothed = savgol_filter(power_spectrum, filter_length, filter_order) + f1, f2 = frequencies[[np.argmax(power_spectrum), np.argmax(power_spectrum_smoothed)]] + + kwargs = { + 'combine': 'separate', + 'ncols': 2, + 'suptitle': f'Spectrum on `{self.short_name}`', + 'title': ['power spectrum', 'phase spectrum'], + 'label': [[f'power spectrum: max at {f1:3.1f} Hz', f'power spectrum smoothed: max at {f2:3.1f} Hz'], ''], + **kwargs + } + plotter = plot([[(frequencies, power_spectrum), (frequencies, power_spectrum_smoothed)], + (frequencies, phase_spectrum)], mode='curve', **kwargs) + plotter.subplots[0].ax.axvline(f1, color='cornflowerblue', linewidth=1) + plotter.subplots[0].ax.axvline(f2, color='goldenrod', linewidth=1) + return plotter + + def show_section(self, locations, zoom=None, plotter=plot, linecolor='gray', linewidth=3, show=True, + savepath=None, **kwargs): + """ Show seismic section via desired traces. + Under the hood relies on :meth:`load_section`, so works with geometries in any formats. + + Parameters + ---------- + locations : iterable + Locations of traces to construct section. + zoom : tuple, None or 'auto' + Tuple of slices to apply directly to 2d images. If None, slicing is not applied. + If 'auto', zero traces on bounds will be dropped. + plotter : instance of `plot` + Plotter instance to use. + Combined with `positions` parameter allows using subplots of already existing plotter. + linecolor : str or None + Color of line to mark node traces. If None, lines will not be drawn. + linewidth : int + With of the line. + show : bool + Whether to show created plot or not. + savepath : str + Path to save the plot to. + kwargs : dict + kwargs for plotter + """ + section, indices, nodes = self.load_section(locations) + xmin, xmax, ymin, ymax = 0, section.shape[0], section.shape[1], 0 + + if zoom == 'auto': + nonzero = np.nonzero((section != 0).any(axis=1))[0] + if len(nonzero) > 0: + start, stop = nonzero[[0, -1]] + zoom = (slice(start, stop + 1), slice(None)) + else: + zoom = None + if zoom: + section = section[zoom] + xmin = zoom[0].start or xmin + xmax = zoom[0].stop or xmax + ymin = zoom[1].stop or ymin + ymax = zoom[1].start or ymax + + # Plot params + title = f'Section via {str(locations)[1:-1]}' + xlabel = f'{self.index_headers[0]}/{self.index_headers[1]}' + ylabel = 'DEPTH' + + kwargs = { + 'title': title, + 'suptitle': f'Field `{self.short_name}`', + 'xlabel': xlabel, + 'ylabel': ylabel, + 'cmap': 'Greys_r', + 'colorbar': True, + 'extent': (xmin, xmax, ymin, ymax), + 'labeltop': False, + 'labelright': False, + **kwargs + } + + plt = plotter(section, show=show, **kwargs) + + xticks = plt[0].ax.get_xticks().astype('int32') + nearest_ticks = np.argmin(np.abs(xticks.reshape(-1, 1) - nodes.reshape(1, -1)), axis=0) + xticks[nearest_ticks] = nodes + labels = np.array(list(map('\n'.join, indices.astype('int32').astype(str))))[xticks % section.shape[0]] + + plt[0].ax.set_xticks(xticks[:-1]) + plt[0].ax.set_xticklabels(labels[:-1]) + + if linecolor: + for pos in nodes: + plt[0].ax.plot([pos, pos], [0, section.shape[1]], color=linecolor, linewidth=linewidth) + + if savepath is not None: + plt.save(savepath=savepath) + + return plt + + def show_section_map(self, locations, linecolor='green', linewidth=3, pointcolor='blue', + pointsize=100, marker='*', show=True, savepath=None, **kwargs): + """ Show section line on 2D geometry map. + + Parameters + ---------- + locations : iterable + Locations of traces to construct section. + linecolor : str, optional + Color of section line, by default 'green' + linewidth : int, optional + Width of section line, by default 3 + pointcolor : str, optional + Color of points at locations, by default 'blue' + pointsize : int, optional + Size of points at locations, by default 100 + marker : str, optional + Points marker, by default '*' + show : bool + Whether to show created plot or not. + savepath : str + Path to save the plot to. + kwargs : dict + kwargs for `show` method to plot geometry map (e.g., 'matrix') + + Returns + ------- + plotter + Plot instance + """ + title = f'Section via {str(locations)[1:-1]}' + locations = np.array(locations) + + kwargs = { + 'title': title, + 'labeltop': False, + 'labelright': False, + 'matrix': 'snr', + **kwargs + } + + plotter = self.show(show=show, **kwargs) + plotter[0].ax.scatter(locations[:, 0], locations[:, 1], c=pointcolor, s=pointsize, marker=marker) + plotter[0].ax.plot(locations[:, 0], locations[:, 1], color=linecolor, linewidth=linewidth) + + if savepath is not None: + plotter.save(savepath=savepath) + + return plotter + + # Utilities for 2D slides + def get_slide_index(self, index, axis=0): + """ Get the slide index along specified axis. + Integer `12` means 12-th (ordinal) inline. + String `#244` means inline 244. + + Parameters + ---------- + index : int, str + If int, then interpreted as the ordinal along the specified axis. + If `'random'`, then we generate random index along the axis. + If string of the `'#XXX'` format, then we interpret it as the exact indexing header value. + axis : int + Axis of the slide. + """ + if isinstance(index, (int, np.integer)): + if index >= self.shape[axis]: + raise KeyError(f'Index={index} is out of geometry bounds={self.shape[axis]}!') + return index + if index == 'random': + return np.random.randint(0, self.lengths[axis]) + if isinstance(index, str) and index.startswith('#'): + index = int(index[1:]) + return self.index_value_to_ordinal[axis][index] + raise ValueError(f'Unknown type of index={index}') + + def get_slide_bounds(self, index, axis=0): + """ Compute bounds of the slide: indices of the first/last alive traces of it. + + Parameters + ---------- + index : int + Ordinal index of the slide. + axis : int + Axis of the slide. + """ + dead_traces = take_along_axis(self.dead_traces_matrix, index=index, axis=axis) + left_bound = np.argmin(dead_traces) + right_bound = len(dead_traces) - np.argmin(dead_traces[::-1]) # the first dead trace + return left_bound, right_bound + + def compute_auto_zoom(self, index, axis=0): + """ Compute zoom for a given slide. """ + return slice(*self.get_slide_bounds(index=index, axis=axis)), slice(None) + + # General utility methods + STRING_TO_AXIS = { + 'i': 0, 'il': 0, 'iline': 0, 'inline': 0, + 'x': 1, 'xl': 1, 'xline': 1, 'xnline': 1, + 'd': 2, 'depth': 2, + } + + def parse_axis(self, axis): + """ Convert string representation of an axis into integer, if needed. """ + if isinstance(axis, str): + if axis in self.index_headers: + axis = self.index_headers.index(axis) + elif axis in self.STRING_TO_AXIS: + axis = self.STRING_TO_AXIS[axis] + return axis + + def make_slide_locations(self, index, axis=0): + """ Create locations (sequence of slices for each axis) for desired slide along given axis. """ + locations = [slice(0, item) for item in self.shape] + + axis = self.parse_axis(axis) + locations[axis] = slice(index, index + 1) + return locations + + def process_limits(self, limits): + """ Convert given `limits` to a `slice`. """ + if limits is None: + return slice(0, self.depth, 1) + if isinstance(limits, (tuple, list)): + limits = slice(*limits) + return limits + + @staticmethod + def locations_to_shape(locations): + """ Compute shape of a location. """ + return tuple(slc.stop - slc.start for slc in locations) + + def get_slide_mask(self, index, axis=0, kernel_size=9, threshold=None, erosion=11, dilation=60): + """ Get mask with dead pixels on a given slide. + Under the hood, we compute ptp value for each pixel, and deem everything lower than `threshold` be a dead pixel. + + Parameters + ---------- + index : int, str + Index of the slide to load. + If int, then interpreted as the ordinal along the specified axis. + If `'random'`, then we generate random index along the axis. + If string of the `'#XXX'` format, then we interpret it as the exact indexing header value. + axis : int + Axis of the slide. + kernel_size : int + Window size for computations. + threshold : number + Minimum ptp value to consider a pixel to be a dead one. + erosion : int + Amount of binary erosion for postprocessing. + dilation : int + Amount of binary dilataion for postprocessing. + + Returns + ------- + mask : np.ndarray + Boolean mask with 1`s at dead pixels and 0`s at alive ones. + """ + locations = [slice(None)] + locations[axis] = slice(index, index+1) + return self.get_crop_mask(tuple(locations), axis, kernel_size, threshold, erosion, dilation) + + def get_crop_mask(self, locations, axis=0, kernel_size=9, threshold=None, erosion=11, dilation=60): + """ Get mask with dead pixels on a given crop. + Under the hood, we compute ptp value for each pixel, and deem everything lower than `threshold` be a dead pixel. + + Parameters + ---------- + locations : tuple of slices + Slices of the crop to load. + axis : int + Direction to split crop into slides to process. + kernel_size : int + Window size for computations. + threshold : number + Minimum ptp value to consider a pixel to be a dead one. + erosion : int + Amount of binary erosion for postprocessing. + dilation : int + Amount of binary dilataion for postprocessing. + + Returns + ------- + mask : np.ndarray + Boolean mask with 1`s at dead pixels and 0`s at alive ones. + """ + threshold = threshold or self.std / 10 + array = self.load_crop(locations) + array = array if array.dtype == np.float32 else array.astype(np.uint8) + mask = np.zeros_like(array, dtype=np.bool_) + + ptp_kernel = np.ones((kernel_size, kernel_size), dtype=array.dtype) + erosion_kernel = np.ones((erosion, erosion), dtype=array.dtype) if erosion else None + dilation_kernel = np.ones((dilation, dilation), dtype=array.dtype) + + for i in range(array.shape[axis]): + slide = take_along_axis(array, i, axis) + ptps = cv2.dilate(slide, ptp_kernel) - cv2.erode(slide, ptp_kernel) + mask_ = ptps <= threshold + if erosion: + mask_ = binary_erosion(mask_, structure=erosion_kernel, border_value=True) + if dilation: + mask_ = cv2.dilate(mask_.astype('uint8'), dilation_kernel).astype('bool') + slc = [slice(None)] * 3 + slc[axis] = i + mask[tuple(slc)] = mask_ + + return mask diff --git a/seismiqb/geometry/benchmark_mixin.py b/seismiqb/geometry/benchmark_mixin.py new file mode 100644 index 0000000..9a5e8d3 --- /dev/null +++ b/seismiqb/geometry/benchmark_mixin.py @@ -0,0 +1,133 @@ +""" Collection of tools for benchmarking and testing array-like geometries. """ +import time + +import numpy as np + +from batchflow import Notifier + + +class BenchmarkMixin: + """ Methods for testing and benchmarking the geometry. """ + def equal(self, other, return_explanation=False): + """ Check if two geometries are equal: have the same shape, headers and values. """ + condition = (self.shape == other.shape).all() + if condition is False: + explanation = f'Different shapes, {self.shape} != {other.shape}' + return (False, explanation) if return_explanation else False + + condition = (self.headers == other.headers).all().all() + if condition is False: + explanation = 'Different `headers` dataframes!' + return (False, explanation) if return_explanation else False + + condition = (self.mean_matrix == other.mean_matrix).all() + if condition is False: + explanation = 'Different `mean_matrix` values!' + return (False, explanation) if return_explanation else False + + for i in range(self.shape[0]): + condition = (self[i] == other[i]).all() + if condition is False: + explanation = f'Different values in slide={i}!' + return (False, explanation) if return_explanation else False + + return (True, '') if return_explanation else True + + + @staticmethod + def make_random_slide_locations(bounds, allowed_axis=(0, 1, 2), rng=None): + """ Create random slide locations along one of the axis. """ + rng = rng or np.random.default_rng(rng) + axis = rng.choice(a=allowed_axis) + index = rng.integers(*bounds[axis]) + + locations = [slice(None), slice(None), slice(None)] + locations[axis] = slice(index, index + 1) + return locations + + @staticmethod + def make_random_crop_locations(bounds, size_min=10, size_max=100, rng=None): + """ Create random crop locations. """ + rng = rng or np.random.default_rng(rng) + if isinstance(size_min, int): + size_min = (size_min, size_min, size_min) + if isinstance(size_max, int): + size_max = (size_max, size_max, size_max) + + point = rng.integers(*bounds) + shape = rng.integers(low=size_min, high=size_max) + locations = [slice(start, np.clip(start+size, bound_min, bound_max)) + for start, size, bound_min, bound_max in zip(point, shape, bounds[0], bounds[1])] + return locations + + def benchmark(array_like, n_slides=300, slide_allowed_axis=(0, 1, 2), + n_crops=300, crop_size_min=(10, 10, 256), crop_size_max=(128, 128, 512), seed=42, pbar=False): + """ Calculate average loading timings. + Output is user, system and wall timings in milliseconds for slides and crops. + TODO: separate timings for each slide axis + + Parameters + ---------- + array_like : array like + An object with numpy-like getitem semantics and `shape` attribute. + n_slides : int + Number of slides to load. + slide_allowed_axis : sequence of int + Allowed projections to generate slides along. + n_crops : int + Number of crops to load. + crop_size_min : int or tuple of int + A minimum size of generated crops. + If tuple, then each number corresponds to size along each axis. + crop_size_max : int or tuple of int + A maximum size of generated crops. + If tuple, then each number corresponds to size along each axis. + seed : int + Seed for the random numbers generator. + pbar : bool, str + If bool, then whether to display progress bar. + If str, then type of progress bar to display: `'t'` for textual, `'n'` for widget. + """ + #pylint: disable=no-self-argument, import-outside-toplevel + import psutil + + # Parse parameters + bbox = np.array([[0, s] for s in array_like.shape]) + + rng = np.random.default_rng(seed) + timings = {} + + # Calculate the average loading slide time + if n_slides: + timestamp_start, wall_start = psutil.cpu_times(), time.perf_counter() + for _ in Notifier(pbar, desc='Slides benchmark')(range(n_slides)): + slide_locations = BenchmarkMixin.make_random_slide_locations(bounds=bbox, rng=rng, + allowed_axis=slide_allowed_axis) + slide_locations = tuple(slide_locations) + _ = array_like[slide_locations] + timestamp_end, wall_end = psutil.cpu_times(), time.perf_counter() + + timings['slide'] = { + 'user': 1000 * (timestamp_end[0] - timestamp_start[0]) / n_slides, + 'system': 1000 * (timestamp_end[2] - timestamp_start[2]) / n_slides, + 'wall': 1000 * (wall_end - wall_start) / n_slides + } + + # Calculate the average loading crop time + if n_crops: + timestamp_start, wall_start = psutil.cpu_times(), time.perf_counter() + for _ in Notifier(pbar, desc='Crops benchmark')(range(n_crops)): + crop_locations = BenchmarkMixin.make_random_crop_locations(bbox.T, rng=rng, + size_min=crop_size_min, + size_max=crop_size_max) + crop_locations = tuple(crop_locations) + _ = array_like[crop_locations] + timestamp_end, wall_end = psutil.cpu_times(), time.perf_counter() + + timings['crop'] = { + 'user': 1000 * (timestamp_end[0] - timestamp_start[0]) / n_crops, + 'system': 1000 * (timestamp_end[2] - timestamp_start[2]) / n_crops, + 'wall': 1000 * (wall_end - wall_start) / n_crops + } + + return timings diff --git a/seismiqb/geometry/conversion_mixin.py b/seismiqb/geometry/conversion_mixin.py new file mode 100644 index 0000000..6b7cda2 --- /dev/null +++ b/seismiqb/geometry/conversion_mixin.py @@ -0,0 +1,378 @@ +""" Mixin for geometry conversions. """ +import os + +import cv2 +import numpy as np +import h5pickle as h5py +import hdf5plugin + +from batchflow import Notifier, Quantizer + + +def resize_3D(array, factor): + """ Resize 3D array along the last axis. """ + resampled_depth = int(array.shape[2] * factor) + buffer = np.empty(shape=(*array.shape[:2], resampled_depth), dtype=array.dtype) + + for i, item in enumerate(array): + cv2.resize(item, dsize=(resampled_depth, array.shape[1]), dst=buffer[i]) + return buffer + + + +class ConversionMixin: + """ Methods for converting data to other formats. """ + #pylint: disable=redefined-builtin, import-outside-toplevel + PROJECTION_NAMES = {0: 'projection_i', 1: 'projection_x', 2: 'projection_d'} # names of projections + TO_PROJECTION_TRANSPOSITION = {0: [0, 1, 2], 1: [1, 0, 2], 2: [2, 0, 1]} # re-order axis to given projection + FROM_PROJECTION_TRANSPOSITION = {0: [0, 1, 2], 1: [1, 0, 2], 2: [1, 2, 0]} # revert the previous re-ordering + + @staticmethod + def compute_axis_transpositions(axis): + """ Compute transpositions of original (inline, crossline, depth) axes to a given projection. + Returns a transposition to that projection and from it. + """ + return ConversionMixin.TO_PROJECTION_TRANSPOSITION[axis], ConversionMixin.FROM_PROJECTION_TRANSPOSITION[axis] + + + # Quantization + def compute_quantization_parameters(self, ranges=0.99, clip=True, center=False, dtype=np.int8, + n_quantile_traces=100_000, seed=42): + """ Compute parameters, needed for quantizing data to required range. + Also evaluates quantization error by comparing subset of data with its dequantized quantized version. + On the same subset, stats like mean, std and quantile values are computed. + + Parameters + ---------- + ranges : float or sequence of two numbers + Ranges to quantize data to. + If float, then used as quantile to clip data to. If two numbers, then this exact range is used. + clip : bool + Whether to clip data to selected ranges. + center : bool + Whether to make data have 0-mean before quantization. + n_quantile_traces : int + Size of the subset to compute quantiles. + seed : int + Seed for quantile traces subset selection. + + Returns + ------- + quantization_parameters : dict + Dictionary with keys for stats and methods of data transformation. + `'quantizer'` key is the instance, which can be `called` to quantize arbitrary array. + """ + if isinstance(ranges, float): + qleft, qright = self.get_quantile([1 - ranges, ranges]) + value = min(abs(qleft), abs(qright)) + ranges = (-value, +value) + + if center: + ranges = tuple(item - self.v_mean for item in ranges) + + quantizer = Quantizer(ranges=ranges, clip=clip, center=center, mean=self.mean, dtype=dtype) + + # Load subset of data to compute quantiles + alive_traces_indices = self.index_matrix[~self.dead_traces_matrix].ravel() + indices = np.random.default_rng(seed=seed).choice(alive_traces_indices, size=n_quantile_traces) + data = self.load_by_indices(indices) + quantized_data = quantizer.quantize(data) + + mean, std = quantized_data.mean(), quantized_data.std() + quantile_values = np.quantile(quantized_data, q=self.quantile_support) + quantile_values[0], quantile_values[-1] = -127, +128 + + # Estimate quantization error + dequantized_data = quantizer.dequantize(quantized_data) + quantization_error = np.mean(np.abs(dequantized_data - data)) / self.std + + return { + 'ranges': quantizer.ranges, 'center': quantizer.center, 'clip': clip, + + 'quantizer': quantizer, + 'transform': quantizer.quantize, + 'dequantize': quantizer.dequantize, + 'quantization_error': quantization_error, + + 'min': -127, 'max': +127, + 'mean': mean, 'std': std, + 'quantile_values': quantile_values, + } + + # Convert SEG-Y + def convert_to_hdf5(self, path=None, overwrite=True, postfix=False, projections='ixd', + quantize=False, quantization_parameters=None, dataset_kwargs=None, chunk_size_divisor=1, + pbar='t', store_meta=True, **kwargs): + """ Convert SEG-Y file to a more effective storage. + + Parameters + ---------- + path : str + If provided, then path to save file to. + Otherwise, file is saved under the same name with different extension. + postfix : bool or str + Whether to add before extension. Used only if the `path` is not provided. If True, it will be + created automatically depending on conversion parameters. + projections : str + Which projections of data to store: `i` for the inline one, `x` for the crossline, `d` for depth. + quantize : bool + Whether to quantize data to `int8` dtype. If True, then `q` is appended to extension. + quantization_parameters : dict, optional + If provided, then used as parameters for quantization. + Otherwise, parameters from the call to :meth:`compute_quantization_parameters` are used. + pbar : bool, str + If bool, then whether to display progress bar. + If str, then type of progress bar to display: `'t'` for textual, `'n'` for widget. + store_meta : bool + Whether to store meta in the same file. + dataset_kwargs : dict, optional + Parameters, passed directly to the dataset constructor. + If not provided, we use the blosc compression with `lz4hc` compressor, clevel 6 and no bit shuffle. + kwargs : dict + Other parameters, passed directly to the file constructor. + """ + # Quantization + if quantize: + if quantization_parameters is None: + quantization_parameters = self.compute_quantization_parameters() + dtype, transform = np.int8, quantization_parameters['transform'] + else: + dtype, transform = np.float32, lambda array: array + + # Default path: right next to the original file with new extension + if path is None: + path = self.make_output_path(format='hdf5', quantize=quantize, postfix=postfix, projections=projections, + chunk_size_divisor=chunk_size_divisor) + + # Dataset creation parameters + if dataset_kwargs is None: + dataset_kwargs = dict(hdf5plugin.Blosc(cname='lz4hc', clevel=6, shuffle=0)) + + # Remove file, if exists + if os.path.exists(path) and overwrite: + os.remove(path) + + # Create file and datasets inside + with h5py.File(path, mode='w-', **kwargs) as file: + total = sum((letter in projections) * self.shape[idx] + for idx, letter in enumerate('ixd')) + progress_bar = Notifier(pbar, total=total, ncols=110) + name = os.path.basename(path) + + for p in projections: + # Projection parameters + axis = self.parse_axis(p) + projection_name = self.PROJECTION_NAMES[axis] + projection_transposition = self.TO_PROJECTION_TRANSPOSITION[axis] + projection_shape = self.shape[projection_transposition] + + # Create dataset + dataset_kwargs_ = {'chunks': (1, *projection_shape[1:] // chunk_size_divisor), + **dataset_kwargs} + projection = file.create_dataset(projection_name, shape=projection_shape, dtype=dtype, + **dataset_kwargs_) + + # Write data on disk + progress_bar.set_description(f'Converting to {name}:{p}') + for idx in range(self.shape[axis]): + slide = self.load_slide(idx, axis=axis) + slide = transform(slide) + projection[idx, :, :] = slide + + progress_bar.update() + progress_bar.close() + + # Save meta to the same file. If quantized, replace stats with the correct ones + from .base import Geometry + geometry = Geometry.new(path) + + if store_meta: + self.dump_meta(path=path) + + if quantize: + quantization_parameters['quantization_ranges'] = quantization_parameters['ranges'] + for key in ['quantization_ranges', 'center', 'clip', 'quantization_error', + 'min', 'max', 'mean', 'std', 'quantile_values']: + geometry.meta_storage.store_item(key=key, value=quantization_parameters[key], overwrite=True) + return geometry + + def repack_segy(self, path=None, format=8, transform=None, quantization_parameters=None, + chunk_size=25_000, max_workers=4, pbar='t', store_meta=True, overwrite=True): + """ Repack SEG-Y file with a different `format`: dtype of data values. + Keeps the same binary header (except for the 3225 byte, which stores the format). + Keeps the same header values for each trace: essentially, only the values of each trace are changed. + + The most common scenario of this function usage is to convert float32 SEG-Y into int8 one: + the latter is a lot faster and takes ~4x less disk space at the cost of some information loss. + + Parameters + ---------- + path : str, optional + Path to save file to. If not provided, we use the path of the current cube with an added postfix. + format : int + Target SEG-Y format. + Refer to :attr:`~.MemmapLoader.SEGY_FORMAT_TO_TRACE_DATA_DTYPE` for + list of available formats and their data value dtype. + transform : callable, optional + Callable to transform data from the current file to the ones, saved in `path`. + Must return the same dtype, as specified by `format`. + quantization_parameters : dict, optional + If provided, then used as parameters for quantization. + Otherwise, parameters from the call to :meth:`compute_quantization_parameters` are used. + chunk_size : int + Maximum amount of traces in each chunk. + max_workers : int or None + Maximum number of parallel processes to spawn. If None, then the number of CPU cores is used. + pbar : bool, str + If bool, then whether to display progress bar. + If str, then type of progress bar to display: `'t'` for textual, `'n'` for widget. + overwrite : bool + Whether to overwrite existing `path` or raise an exception. Also removes `meta` files. + """ + if format == 8 and transform is None: + quantization_parameters = quantization_parameters or self.compute_quantization_parameters() + transform = quantization_parameters['transform'] + + path = self.loader.convert(path=path, format=format, transform=transform, + chunk_size=chunk_size, max_workers=max_workers, pbar=pbar, overwrite=overwrite) + + meta_path = path + '_meta' + if overwrite and os.path.exists(meta_path): + os.remove(meta_path) + + # Re-open geometry, store values that were used for quantization + from .base import Geometry + geometry = Geometry.new(path, collect_stats=True) + + quantization_parameters['quantization_ranges'] = quantization_parameters['ranges'] + for key in ['quantization_ranges', 'center', 'clip', 'quantization_error']: + geometry.meta_storage.store_item(key=key, value=quantization_parameters[key], overwrite=True) + return geometry + + + def make_output_path(self, format='hdf5', quantize=False, postfix=False, projections='ixd', + chunk_size_divisor=1, sgy_format=8): + """ Compute output path for converted file, based on conversion parameters. """ + format = format.lower() + + if format.startswith('q'): + quantize = True + format = format[1:] + + fmt_prefix = 'q' if quantize else '' + + if not isinstance(postfix, str): + if not postfix: + postfix = '' + else: + if format == 'hdf5': + if len(projections) < 3: + postfix = '_' + projections + if chunk_size_divisor != 1: + postfix = '_' + f'c{chunk_size_divisor}' + + if format == 'sgy': + if quantize: + postfix = '_' + f'f{sgy_format}' + + dirname = os.path.dirname(self.path) + basename = os.path.basename(self.path) + shortname = os.path.splitext(basename)[0] + path = os.path.join(dirname, shortname + postfix + '.' + fmt_prefix + format) + return path + + + def convert(self, format='qsgy', path=None, postfix=False, projections='ixd', overwrite=True, + quantize=False, quantization_parameters=None, dataset_kwargs=None, chunk_size_divisor=1, + pbar='t', store_meta=True, sgy_format=8, transform=None, chunk_size=25_000, max_workers=4, **kwargs): + """ Convert SEG-Y file to a more effective storage. + Automatically select the conversion format, based on `format` parameter. + Available formats are {'hdf5', 'qhdf5', 'qsgy}. + + Parameters are passed to either :meth:`.convert_to_hdf5` or :meth:`.repack_sgy`: + refer to their documentation for parameters description. + """ + format = format.lower() + + if format.startswith('q'): + quantize = True + format = format[1:] + + if path is None: + path = self.make_output_path(format=format, postfix=postfix, quantize=quantize, projections=projections, + chunk_size_divisor=chunk_size_divisor, sgy_format=sgy_format) + + # Actual conversion + if 'hdf5' in format: + geometry = self.convert_to_hdf5(path=path, overwrite=overwrite, projections=projections, + quantize=quantize, quantization_parameters=quantization_parameters, + dataset_kwargs=dataset_kwargs, chunk_size_divisor=chunk_size_divisor, + pbar=pbar, store_meta=store_meta) + elif 'sgy' in format and quantize: + geometry = self.repack_segy(path=path, overwrite=overwrite, format=sgy_format, + transform=transform, quantization_parameters=quantization_parameters, + chunk_size=chunk_size, max_workers=max_workers, pbar=pbar) + else: + raise ValueError(f'Unknown/unsupported combination of format={format} and quantize={quantize}!') + + return geometry + + + # Resample SEG-Y + def resample(self, path=None, factor=2, quantize=True, quantization_parameters=None, pbar='t', + overwrite=True, **kwargs): + """ Resample SEG-Y file along the depth dimension with optional quantization. + + Parameters + ---------- + path : str, optional + Path to save file to. If not provided, we use the path of the current cube with an added postfix. + factor : number + Scale factor along the depth axis. + quantize : bool + Whether to quantize SEG-Y data. + If the geometry is already using quantized values, no quantization is applied. + quantization_parameters : dict, optional + If provided, then used as parameters for quantization. + Otherwise, parameters from the call to :meth:`compute_quantization_parameters` are used. + pbar : bool, str + If bool, then whether to display progress bar. + If str, then type of progress bar to display: `'t'` for textual, `'n'` for widget. + overwrite : bool + Whether to overwrite existing `path` or raise an exception. Also removes `meta` files. + """ + # Path + path = path or self.make_output_path('sgy', quantize=quantize, postfix=f'_r{factor}') + + # Quantization parameters + if quantize and not self.quantized: + quantization_parameters = quantization_parameters or self.compute_quantization_parameters() + quantization_transform = quantization_parameters['transform'] + else: + quantization_transform = lambda array: array + + # Spec: use `self` as `array_like` to infer shapes + spec = self.make_export_spec(self) + spec.sample_interval /= factor + spec.samples = np.arange(self.depth * factor, dtype=np.int32) + spec.format = 8 if quantize else 5 + + # Final data transform: resample and optional quantization + transform = lambda array: quantization_transform(resize_3D(array, factor=factor)) + + self.array_to_segy(self, path=path, spec=spec, transform=transform, format=spec.format, + pbar=pbar, zip_segy=False, **kwargs) + + # Re-open geometry, store values that were used for quantization + meta_path = path + '_meta' + if overwrite and os.path.exists(meta_path): + os.remove(meta_path) + + from .base import Geometry + geometry = Geometry.new(path, collect_stats=True) + + if quantize and not self.quantized: + quantization_parameters['quantization_ranges'] = quantization_parameters['ranges'] + for key in ['quantization_ranges', 'center', 'clip', 'quantization_error']: + geometry.meta_storage.store_item(key=key, value=quantization_parameters[key], overwrite=True) + return geometry diff --git a/seismiqb/geometry/converted.py b/seismiqb/geometry/converted.py new file mode 100644 index 0000000..e39af3f --- /dev/null +++ b/seismiqb/geometry/converted.py @@ -0,0 +1,231 @@ +""" Converted geometry: optimized storage. """ + +import numpy as np +import h5pickle as h5py + +from .base import Geometry +from ..utils import repack_hdf5 + + + +class GeometryHDF5(Geometry): + """ Class to work with cubes in HDF5 format. + We expect a certain structure to the file: mostly, this file should be created by :meth:`ConversionMixin.convert`. + + The file should contain data in one or more projections. When the data is requested, we choose the fastest one + to actually perform the data reading step. + Some of the projections may be missing — in this case, other (possibly, slower) projections are used to load data. + + Additional meta attributes like coordinates, SEG-Y parameters, etc, can be also in the same file. + + Refer to the documentation of the base class :class:`Geometry` for more information about attributes and parameters. + """ + FILE_OPENER = h5py.File + + def init(self, path, mode='r', **kwargs): + """ Init for HDF5 geometry. The sequence of actions: + - open file handler + - check available projections in the file + - add attributes from file: meta and info about shapes/dtypes. + + Default mode is r to multiple opens for reading. + If you want to allow other file opens for both read/write, provide 'r+' mode. + """ + # Open the file + self.file = self.FILE_OPENER(path, mode, swmr=True) + + # Check available projections + self.available_axis = [axis for axis, name in self.PROJECTION_NAMES.items() + if name in self.file] + self.available_names = [self.PROJECTION_NAMES[axis] for axis in self.available_axis] + + # Save projection handlers to instance + self.axis_to_projection = {} + for axis in self.available_axis: + name = self.PROJECTION_NAMES[axis] + projection = self.file[name] + + self.axis_to_projection[axis] = projection + + # Parse attributes from meta / set defaults + self.add_attributes(**kwargs) + + def add_attributes(self, **kwargs): + """ Add attributes from the file. """ + # Innate attributes of converted geometry + self.index_headers = ('INLINE_3D', 'CROSSLINE_3D') + self.index_length = 2 + self.converted = True + + # Infer attributes from the available projections + axis = self.available_axis[0] + projection = self.axis_to_projection[axis] + + shape = np.array(projection.shape)[self.FROM_PROJECTION_TRANSPOSITION[axis]] + self.shape = shape + *self.lengths, self.depth = shape + + self.dtype = projection.dtype + self.quantized = (projection.dtype == np.int8) + + # Get from meta / set defaults + required_attributes = self.PRESERVED + self.PRESERVED_LAZY + self.PRESERVED_LAZY_CACHED + meta_exists_and_has_attributes = self.meta_storage.exists and self.meta_storage.has_items(required_attributes) + + if meta_exists_and_has_attributes: + self.load_meta(keys=self.PRESERVED) + self.has_stats = True + else: + self.set_default_index_attributes(**kwargs) + self.has_stats = False + + def set_default_index_attributes(self, **kwargs): + """ Set default values for seismic attributes. """ + self.n_traces = np.prod(self.shape[:2]) + self.delay, self.sample_interval, self.sample_rate = 0.0, 1.0, 1000 + self.compute_dead_traces() + for key, value in kwargs.items(): + setattr(self, key, value) + + def compute_dead_traces(self, frequency=100): + """ Fallback for dead traces matrix computation, if no full stats are collected. """ + slides = [] + + for idx in range(0, self.depth, frequency): + slides.append(self.load_slide_native(index=idx, axis=2)) + + std_matrix = np.std(slides, axis=0) + + self.dead_traces_matrix = (std_matrix == 0).astype(np.bool_) + self.n_dead_traces = np.sum(self.dead_traces_matrix) + self.n_alive_traces = np.prod(self.lengths) - self.n_dead_traces + + # General utilities + def get_optimal_axis(self, locations=None, shape=None): + """ Choose the fastest axis from available projections, based on shape. """ + shape = shape or self.locations_to_shape(locations) + + for axis in np.argsort(shape): + if axis in self.available_axis: + return axis + return None + + + # Load data: 2D + def load_slide_native(self, index, axis=0, limits=None, buffer=None, safe=False): + """ Load slide with public or private API of `h5py`. """ + if safe or buffer is None or buffer.dtype != self.dtype: + buffer = self.load_slide_native_safe(index=index, axis=axis, limits=limits, buffer=buffer) + else: + self.load_slide_native_unsafe(index=index, axis=axis, limits=limits, buffer=buffer) + return buffer + + def load_slide_native_safe(self, index, axis=0, limits=None, buffer=None): + """ Load slide with public API of `h5py`. Requires an additional copy to put data into buffer. """ + # Prepare locations + loading_axis = axis if axis in self.available_axis else self.available_axis[0] + to_projection_transposition, from_projection_transposition = self.compute_axis_transpositions(loading_axis) + + locations = self.make_slide_locations(index=index, axis=axis) + locations = [locations[idx] for idx in to_projection_transposition] + + if limits is not None: + locations[-1] = self.process_limits(limits) + locations = tuple(locations) + + # Load data + slide = self.axis_to_projection[loading_axis][locations] + + # Re-order and squeeze the requested axis + slide = slide.transpose(from_projection_transposition) + slide = slide.squeeze(axis) + + # Write back to buffer + if buffer is not None: + buffer[:] = slide + else: + buffer = slide + return buffer + + def load_slide_native_unsafe(self, index, axis=0, limits=None, buffer=None): + """ Load slide with private API of `h5py`. Reads data directly into buffer. """ + # Prepare locations + loading_axis = axis if axis in self.available_axis else self.available_axis[0] + to_projection_transposition, from_projection_transposition = self.compute_axis_transpositions(loading_axis) + + locations = self.make_slide_locations(index=index, axis=axis) + locations = [locations[idx] for idx in to_projection_transposition] + + if limits is not None: + locations[-1] = self.process_limits(limits) + locations = tuple(locations) + + # View buffer in projections ordering + buffer = np.expand_dims(buffer, axis) + buffer = buffer.transpose(to_projection_transposition) + + # Load data + self.axis_to_projection[loading_axis].read_direct(buffer, locations) + + # View buffer in original ordering + buffer = buffer.transpose(from_projection_transposition) + buffer = buffer.squeeze(axis) + return buffer + + + # Load data: 3D + def load_crop_native(self, locations, axis=None, buffer=None, safe=False): + """ Load crop with public or private API of `h5py`. """ + axis = axis or self.get_optimal_axis(locations=locations) + if axis not in self.available_axis: + raise ValueError(f'Axis={axis} is not available!') + + if safe or axis == 2 or buffer is None or buffer.dtype != self.dtype: + buffer = self.load_crop_native_safe(locations=locations, axis=axis, buffer=buffer) + else: + self.load_crop_native_unsafe(locations=locations, axis=axis, buffer=buffer) + return buffer + + def load_crop_native_safe(self, locations, axis=None, buffer=None): + """ Load slide with public API of `h5py`. Requires an additional copy to put data into buffer. """ + # Prepare locations + to_projection_transposition, from_projection_transposition = self.compute_axis_transpositions(axis) + + locations = [locations[idx] for idx in to_projection_transposition] + locations = tuple(locations) + + # Load data + crop = self.axis_to_projection[axis][locations] + + # Re-order back from projections' ordering + crop = crop.transpose(from_projection_transposition) + + # Write back to buffer + if buffer is not None: + buffer[:] = crop + else: + buffer = crop + return buffer + + def load_crop_native_unsafe(self, locations, axis=None, buffer=None): + """ Load slide with private API of `h5py`. Reads data directly into buffer. """ + # Prepare locations + to_projection_transposition, from_projection_transposition = self.compute_axis_transpositions(axis) + locations = [locations[idx] for idx in to_projection_transposition] + locations = tuple(locations) + + # View buffer in projections ordering + buffer = buffer.transpose(to_projection_transposition) + + # Load data + self.axis_to_projection[axis].read_direct(buffer, locations) + + # View buffer in original ordering + buffer = buffer.transpose(from_projection_transposition) + return buffer + + def repack_hdf5(self, dst_path=None, projections = (0, ), transform=None, dtype='float32', pbar='t', inplace=False, + **dataset_kwargs): + """ Recreate hdf5 file with conversion and compression. """ + repack_hdf5(self.path, dst_path=dst_path, projections=projections, transform=transform, dtype=dtype, pbar=pbar, + inplace=inplace, **dataset_kwargs) diff --git a/seismiqb/geometry/export_mixin.py b/seismiqb/geometry/export_mixin.py new file mode 100644 index 0000000..f5e6286 --- /dev/null +++ b/seismiqb/geometry/export_mixin.py @@ -0,0 +1,342 @@ +""" Mixin to hold methods for exporting array-like data as SEG-Y files. """ +import os +import shutil +from concurrent.futures import ThreadPoolExecutor + +import numpy as np +import segyio + +from batchflow.notifier import Notifier + +from .memmap_loader import MemmapLoader + + +class ExportMixin: + """ Methods for exporting arrays (or array-likes) to a SEG-Y files with given spec. """ + #pylint: disable=redefined-builtin, protected-access + + # Specs for export + def make_export_spec(self, array_like, origin=(0, 0, 0)): + """ Create a description of the current geometry. + Includes file-wide attributes: `sample_interval`, `delay`, `format` and `sorting`, + coordinate descriptions: `ilines`, `xlines` and `samples`, and matrices for other headers. + Can be used directly to create SEG-Y file by `segyio`. + + Parameters + ---------- + array_like : array like + An object with numpy-like getitem semantics. + origin : tuple of three integers + Coordinates of the upper leftmost point of the `array_like`. + """ + # Parse parameters + file_handler = self.loader.file_handler + slices = tuple(slice(o, o+s) for o, s in zip(origin, array_like.shape)) + + spec = segyio.spec() + + # File-wide values + spec.sample_interval = self.sample_interval + spec.delay = int(self.delay) + int(self.sample_interval * origin[-1]) + spec.format = 5 if file_handler.format is None else int(file_handler.format) + spec.sorting = 2 if file_handler.sorting is None else int(file_handler.sorting) + + # Structure + spec.ilines = self.index_sorted_uniques[0][slices[0]] + spec.xlines = self.index_sorted_uniques[1][slices[1]] + spec.samples = np.arange(array_like.shape[2], dtype=np.int32) + + # Additional matrices + spec.cdp_x_matrix = self.compute_header_values_matrix('CDP_X')[slices[:2]] + spec.cdp_y_matrix = self.compute_header_values_matrix('CDP_Y')[slices[:2]] + return spec + + @staticmethod + def default_export_spec(array_like, origin=(0, 0, 0), sample_interval=2.0, delay=0, sorting=2, format=5, + iline_shift=1, iline_step=1, xline_shift=1, xline_step=1, + cdp_x_shift=100_000, cdp_x_step=25, cdp_y_shift=300_000, cdp_y_step=25): + """ Create default description of SEG-Y file. + Includes file-wide attributes: `sample_interval`, `delay`, `format` and `sorting`, + coordinate descriptions: `ilines`, `xlines` and `samples`, and matrices for other headers. + Can be used directly to create SEG-Y file by `segyio`. + + Parameters + ---------- + array_like : array like + An object with numpy-like getitem semantics. + origin : tuple of three integers + Coordinates of the upper leftmost point of the `array_like`. + sample_interval, delay, sorting, format : numbers + Directly used in SEG-Y creation, according to SEG-Y standard. + *_shift : int + Starting (minimum) value of corresponding header. + *_step : int + Increment between consecutive values of corresponding header. + """ + spec = segyio.spec() + + # File-wide values + spec.sample_interval = sample_interval + spec.delay = int(delay) + int(sample_interval * origin[-1]) + spec.sorting = sorting + spec.format = format + + # Structure + i_start, x_start = iline_shift + origin[0], xline_shift + origin[1] + spec.ilines = np.arange(i_start, i_start + iline_step * array_like.shape[0], dtype=np.int32) + spec.xlines = np.arange(x_start, x_start + xline_step * array_like.shape[1], dtype=np.int32) + spec.samples = np.arange(array_like.shape[2], dtype=np.int32) + + # Additional matrices + spec.cdp_x_matrix = np.tile(cdp_x_shift + cdp_x_step * spec.ilines.reshape(-1, 1), array_like.shape[1]) + spec.cdp_y_matrix = np.tile(cdp_y_shift + cdp_y_step * spec.xlines.reshape(-1, 1), array_like.shape[0]).T + return spec + + # Public APIs + @staticmethod + def array_to_segy(array_like, path, spec=None, origin=(0, 0, 0), pbar='t', zip_segy=False, remove_segy=False, + engine='memmap', format=5, transform=None, endian_symbol='>', chunk_size=20, max_workers=4, + **kwargs): + """ Convert an `array_like` object to a SEG-Y file. + In order to determine values of bin/trace headers, one should provide `spec`: + - if no spec provided, we use the default one. It fills coordinate values with shifted ranges. + - if a path to SEG-Y file or the instance of :class:`GeometrySEGY` is provided, we use its + headers to create a matching spec. The resulting file will have the same headers, as that file, + and it is easy to compare two such SEG-Y files in geological software. + + Parameter `origin`, coupled with the fact that this function works with arbitrary shaped `array_like`, + allows one to save `array_like` which is a subset of the original (used for `spec`) SEG-Y file. + For example, if the spec SEG-Y has the (1000, 2000, 3000) shape, + and `array_like` has the (500, 1000, 1500) shape, we can use origin (250, 50, 750) meaning that `array_like` + should be placed in the middle 1/8 of the volume. + + This method has two underlying implementations for actually writing the data: + - engine `segyio` uses segyio library to write data on a trace-by-trace basis. + It is slow, but well-tested and easy to understand/maintain. + - engine `memmap` uses numpy memory mapping mechanism to write data in chunks in multiple threads. + It is a lot faster and also allows to write SEG-Ys with arbitrary data formats: for example, integer values. + + # TODO: write the textual header, as well as the extended ones. + # TODO: full-copy of trace headers or additional headers to write. + + Parameters + ---------- + array_like : array like + An object with numpy-like getitem semantics. + path : str + Path to save the SEG-Y to. + spec : object + Object with the following mandatory attributes: + - file-wide parameters `sample_interval`, `delay`, `format` and `sorting` + - coordinate grid along each axis `ilines`, `xlines` and `samples` + - mapping from ordinal spatial coordinates to header values: `cdp_x_matrix` and `cdp_y_matrix`. + Refer to :meth:`make_export_spec` and :meth:`default_export_spec` for details. + origin : tuple of three integers + Coordinates of the upper leftmost point of the `array_like`. + pbar : bool, str + If bool, then whether to display progress bar. + If str, then type of progress bar to display: `'t'` for textual, `'n'` for widget. + zip_segy : bool + Whether to compress the created SEG-Y into a zip archive. May take a lot of time with no progress bar. + remove_segy : bool + Whether to remove the SEG-Y. Useful when combined with `zip_segy` to keep only the zipped version. + engine : {'segyio', 'memmap'} + Which engine for file writing to use. + format : int + Target SEG-Y format. Refer to SEG-Y standard for detailed description. + transform : callable, optional + Function to transform array values before writing. Useful to change the dtype. + Must return the same dtype, as specified by `format`. + endian_symbol, chunk_size, max_workers + Directly passed to :meth:`array_to_segy_memmap`. + """ + #pylint: disable=import-outside-toplevel + from .segy import GeometrySEGY + + # Select the spec + if spec is None: + spec = ExportMixin.default_export_spec(array_like=array_like, origin=origin, format=format, **kwargs) + if isinstance(spec, str): + spec = GeometrySEGY(spec) + if isinstance(spec, GeometrySEGY): + spec = spec.make_export_spec(array_like=array_like, origin=origin) + + # Export the data + if engine == 'segyio': + ExportMixin.array_to_segy_segyio(array_like=array_like, path=path, spec=spec, pbar=pbar) + else: + ExportMixin.array_to_segy_memmap(array_like=array_like, path=path, spec=spec, pbar=pbar, + format=format, endian_symbol=endian_symbol, transform=transform, + chunk_size=chunk_size, max_workers=max_workers) + + # Finalize: optionally, compress to `zip` and remove `SEG-Y` + if zip_segy: + dir_name = os.path.dirname(os.path.abspath(path)) + file_name = os.path.basename(path) + shutil.make_archive(os.path.splitext(path)[0], 'zip', dir_name, file_name) + if remove_segy: + os.remove(path) + + def export_array(self, array_like, path, origin=(0, 0, 0), pbar='t', zip_segy=False, remove_segy=False, + engine='memmap', format=5, transform=None, endian_symbol='>', chunk_size=20, max_workers=4): + """ An alias to :meth:`array_to_segy` which uses `self` as spec. """ + spec = self.make_export_spec(array_like=array_like, origin=origin) + ExportMixin.array_to_segy(array_like=array_like, path=path, spec=spec, pbar=pbar, + zip_segy=zip_segy, remove_segy=remove_segy, + engine=engine, format=format, transform=transform, endian_symbol=endian_symbol, + chunk_size=chunk_size, max_workers=max_workers) + + + # Export engines + @staticmethod + def array_to_segy_segyio(array_like, path, spec, pbar='t'): + """ Write `array_like` as a SEG-Y file to `path` according to `spec`. + Does so on a trace-by-trace basis. + """ + with segyio.create(path, spec) as dst_file: + # Write binary header + dst_file.bin.update({ + segyio.BinField.Samples: len(spec.samples), + segyio.BinField.Interval: int(spec.sample_interval * 1000), + }) + + # Iterate over traces, writing headers/data to the dst + basename = os.path.basename(path) + notifier = Notifier(pbar, total=len(spec.ilines), desc=f'Writing `{basename}`') + + c = 0 + for i, il in notifier(enumerate(spec.ilines)): + # Load full slice: speeds-up the case where `array_like` is HDF5 dataset + slide = array_like[i] + + for x, xl in enumerate(spec.xlines): + # Write trace header values + dst_file.header[c].update({ + segyio.TraceField.INLINE_3D: il, + segyio.TraceField.CROSSLINE_3D: xl, + segyio.TraceField.CDP_X: spec.cdp_x_matrix[i, x], + segyio.TraceField.CDP_Y: spec.cdp_y_matrix[i, x], + + segyio.TraceField.TRACE_SAMPLE_COUNT: len(spec.samples), + segyio.TraceField.TRACE_SAMPLE_INTERVAL: int(spec.sample_interval * 1000), + segyio.TraceField.DelayRecordingTime: spec.delay + }) + + # Write trace data values + dst_file.trace[c] = slide[x] + c += 1 + + + @staticmethod + def array_to_segy_memmap(array_like, path, spec, format=5, endian_symbol='>', transform=None, + chunk_size=20, max_workers=4, pbar='t'): + """ Write `array_like` as a SEG-Y file to `path` according to `spec`. + Does so by chunks along the inline direction in multiple threads. + Threads are used instead of processes to avoid the need to pass `array_like` between processes. + + Parameters + ---------- + format : int + Target SEG-Y format. Refer to SEG-Y standard for detailed description. + transform : callable, optional + Function to transform array values before writing. Useful to change the dtype. + Must return the same dtype, as specified by `format`. + endian_symbol : {'>', '<'} + Symbol of big/little endianness. + chunk_size : int + Maximum number of full inlines to include in one chunk. + max_workers : int + Maximum number of threads for parallelization. + pbar : bool, str + If bool, then whether to display progress bar. + If str, then type of progress bar to display: `'t'` for textual, `'n'` for widget. + """ + # Parse parameters + n_traces = len(spec.ilines) * len(spec.xlines) + n_samples = len(spec.samples) + spec.format = format + + # Compute target dtype, itemsize, size of the dst file + dst_dtype = endian_symbol + MemmapLoader.SEGY_FORMAT_TO_TRACE_DATA_DTYPE[spec.format] + dst_itemsize = np.dtype(dst_dtype).itemsize + dst_size = 3600 + n_traces * (MemmapLoader.TRACE_HEADER_SIZE + n_samples * dst_itemsize) + + # Create new file + dst_mmap = np.memmap(path, mode='w+', shape=(dst_size, ), dtype=np.uint8) + dst_mmap[:3600] = 0 + + # Write file-wide 'Interval', 'Samples' and 'Format' headers + # TODO: can be changed to a custom 400-bytes long np.dtype + dst_mmap[3217-1:3217-1+2] = np.array([int(spec.sample_interval * 1000)], dtype=endian_symbol + 'u2').view('u1') + dst_mmap[3221-1:3221-1+2] = np.array([n_samples], dtype=endian_symbol + 'u2').view('u1') + dst_mmap[3225-1:3225-1+2] = np.array([spec.format], dtype=endian_symbol + 'u2').view('u1') + + # Zero-fill all of headers, if on Windows. + # On POSIX complaint systems, memmap is initialized with zeros by default. + if os.name == 'nt': + mmap_trace_dtype = np.dtype([('headers', np.uint8, MemmapLoader.TRACE_HEADER_SIZE), + ('data', dst_dtype, n_samples)]) + dst_mmap = np.memmap(path, mode='r+', offset=3600, shape=(n_traces, ), dtype=mmap_trace_dtype) + dst_mmap['headers'] = 0 + + # Prepare the export dtype + mmap_trace_headers_dtype = MemmapLoader._make_mmap_headers_dtype(('INLINE_3D', 'CROSSLINE_3D', + 'CDP_X', 'CDP_Y', + 'TRACE_SAMPLE_COUNT', + 'TRACE_SAMPLE_INTERVAL', + 'DelayRecordingTime')) + mmap_trace_dtype = np.dtype([*mmap_trace_headers_dtype, + ('data', dst_dtype, n_samples)]) + + # Split the whole file along ilines into chunks no larger than `chunk_size` + n_chunks, last_chunk_size = divmod(len(spec.ilines), chunk_size) + chunk_sizes = [chunk_size] * n_chunks + if last_chunk_size: + chunk_sizes += [last_chunk_size] + chunk_starts = np.cumsum([0] + chunk_sizes[:-1]) + + # Write trace headers and values in chunks in multiple threads + basename = os.path.basename(path) + with Notifier(pbar, total=len(spec.ilines), desc=f'Writing `{basename}`') as progress_bar: + with ThreadPoolExecutor(max_workers=max_workers) as executor: + def callback(future): + chunk_size = future.result() + progress_bar.update(chunk_size) + + for start, chunk_size_ in zip(chunk_starts, chunk_sizes): + future = executor.submit(write_chunk, path=path, + shape=n_traces, offset=3600, dtype=mmap_trace_dtype, + spec=spec, array_like=array_like, transform=transform, + start=start, chunk_size=chunk_size_) + future.add_done_callback(callback) + + +def write_chunk(path, shape, offset, dtype, spec, array_like, transform, start, chunk_size): + """ Write one chunk on disk: headers values and actual data. + We create memory mapping anew in each worker, as it is easier and creates no significant overhead. + """ + # Create memory mapping and compute correct trace indices (TRACE_SEQUENCE_FILE) + dst_mmap = np.memmap(path, mode='r+', shape=shape, offset=offset, dtype=dtype) + tsf_start = start * len(spec.xlines) + tsf_end = tsf_start + chunk_size * len(spec.xlines) + dst_traces = dst_mmap[tsf_start : tsf_end] + + # Write trace headers + dst_traces['INLINE_3D'] = np.repeat(spec.ilines[start:start+chunk_size], len(spec.xlines)) + dst_traces['CROSSLINE_3D'] = np.tile(spec.xlines, chunk_size) + dst_traces['CDP_X'] = spec.cdp_x_matrix[start:start+chunk_size].ravel() + dst_traces['CDP_Y'] = spec.cdp_y_matrix[start:start+chunk_size].ravel() + + dst_traces['TRACE_SAMPLE_COUNT'] = len(spec.samples) + dst_traces['TRACE_SAMPLE_INTERVAL'] = int(spec.sample_interval * 1000) + dst_traces['DelayRecordingTime'] = spec.delay + + # Write trace data + data = array_like[start:start+chunk_size] + if transform is not None: + data = transform(data) + dst_traces['data'] = data.reshape(-1, len(spec.samples)) + return chunk_size + +# Convenient aliases for staticmethod +array_to_segy = array_to_sgy = ExportMixin.array_to_segy diff --git a/seismiqb/geometry/memmap_loader.py b/seismiqb/geometry/memmap_loader.py new file mode 100644 index 0000000..0fecfc1 --- /dev/null +++ b/seismiqb/geometry/memmap_loader.py @@ -0,0 +1,437 @@ +""" Class to load headers/traces from SEG-Y via memory mapping. """ +import os +from functools import partial +from concurrent.futures import ProcessPoolExecutor +import dill + +import numpy as np +import pandas as pd +from numba import njit, prange + +import segyio + +try: + from batchflow import Notifier +except ImportError: + from tqdm.auto import tqdm + def Notifier(pbar, *args, **kwargs): + """ Progress bar. """ + if pbar: + return tqdm(*args, **kwargs) + return lambda iterator: iterator + +from .segyio_loader import SegyioLoader + + + +class MemmapLoader(SegyioLoader): + """ Custom reader/writer for SEG-Y files. + Relies on memory mapping mechanism for actual reads of headers and traces. + + SEG-Y description + ----------------- + Here we give a brief intro into SEG-Y format. Each SEG-Y file consists of: + - file-wide information, in most cases the first 3600 bytes. + - the first 3200 bytes are reserved for textual info about the file. + Most software uses this to keep track of processing operations, date of creation, author, etc. + - 3200-3600 bytes contain file-wide headers, which describe the number of traces, + used format, depth, acquisition parameters, etc. + - 3600+ bytes can be used to store the extended textual information, which is optional and indicated by + one of the values in 3200-3600 bytes. + + - a sequence of traces, where each trace is a combination of header and its actual data. + - header is the first 240 bytes and it describes the meta info about that trace: + its coordinates in different types, the method of acquisition, etc. + - data is an array of values, usually amplitudes, which can be stored in multiple numerical types. + As the original SEG-Y is quite old (1975), one of those numerical formats is IBM float, + which is very different from standard IEEE floats; therefore, a special caution is required to + correctly decode values from such files. + + For the most part, SEG-Y files are written with constant size of each trace, although the standard itself allows + for variable-sized traces. We do not work with such files. + + + Implementation details + ---------------------- + We rely on `segyio` to infer file-wide parameters. + + For headers and traces, we use custom methods of reading binary data. + Main differences to `segyio C++` implementation: + - we read all of the requested headers in one file-wide sweep, speeding up by an order of magnitude + compared to the `segyio` sequential read of every requested header. + Also, we do that in multiple processes across chunks. + + - a memory map over traces data is used for loading values. Avoiding redundant copies and leveraging + `numpy` superiority allows to speed up reading, especially in case of trace slicing along the samples axis. + This is extra relevant in case of loading horizontal (depth) slices. + """ + def __init__(self, path, endian='big', strict=False, ignore_geometry=True): + # Re-use most of the file-wide attributes from the `segyio` loader + super().__init__(path=path, endian=endian, strict=strict, ignore_geometry=ignore_geometry) + + # Endian symbol for creating `numpy` dtypes + self.endian_symbol = self.ENDIANNESS_TO_SYMBOL[endian] + + # Prefix attributes with `file`/`mmap` to avoid confusion. + # TODO: maybe, add `segy` prefix to the attributes of the base class? + self.file_format = self.metrics['format'] + self.file_traces_offset = self.metrics['trace0'] + self.file_trace_size = self.metrics['trace_bsize'] + + # Dtype for data of each trace + mmap_trace_data_dtype = self.SEGY_FORMAT_TO_TRACE_DATA_DTYPE[self.file_format] + if isinstance(mmap_trace_data_dtype, str): + mmap_trace_data_dtype = self.endian_symbol + mmap_trace_data_dtype + self.mmap_trace_data_dtype = mmap_trace_data_dtype + self.mmap_trace_data_size = self.n_samples if self.file_format != 1 else (self.n_samples, 4) + + # Dtype of each trace + # TODO: maybe, use `np.uint8` as dtype instead of `np.void` for headers as it has nicer repr + self.mmap_trace_dtype = np.dtype([('headers', np.void, self.TRACE_HEADER_SIZE), + ('data', self.mmap_trace_data_dtype, self.mmap_trace_data_size)]) + self.data_mmap = self._construct_data_mmap() + + def _construct_data_mmap(self): + """ Create a memory map with the first 240 bytes (headers) of each trace skipped. """ + return np.memmap(filename=self.path, mode='r', shape=self.n_traces, dtype=self.mmap_trace_dtype, + offset=self.file_traces_offset)["data"] + + + # Headers + def load_headers(self, headers, chunk_size=25_000, max_workers=4, pbar=False, + reconstruct_tsf=True, **kwargs): + """ Load requested trace headers from a SEG-Y file for each trace into a dataframe. + If needed, we reconstruct the `'TRACE_SEQUENCE_FILE'` manually be re-indexing traces. + + Under the hood, we create a memory mapping over the SEG-Y file, and view it with a special dtype. + That dtype skips all of the trace data bytes and all of the unrequested headers, leaving only passed `headers` + as non-void dtype. + + The file is read in chunks in multiple processes. + + Parameters + ---------- + headers : sequence + Names of headers to load. + chunk_size : int + Maximum amount of traces in each chunk. + max_workers : int or None + Maximum number of parallel processes to spawn. If None, then the number of CPU cores is used. + pbar : bool, str + If bool, then whether to display progress bar over the file sweep. + If str, then type of progress bar to display: `'t'` for textual, `'n'` for widget. + reconstruct_tsf : bool + Whether to reconstruct `TRACE_SEQUENCE_FILE` manually. + """ + _ = kwargs + if reconstruct_tsf and 'TRACE_SEQUENCE_FILE' in headers: + headers = list(headers) + headers.remove('TRACE_SEQUENCE_FILE') + + # Construct mmap dtype: detailed for headers + mmap_trace_headers_dtype = self._make_mmap_headers_dtype(headers, endian_symbol=self.endian_symbol) + mmap_trace_dtype = np.dtype([*mmap_trace_headers_dtype, + ('data', self.mmap_trace_data_dtype, self.mmap_trace_data_size)]) + + # Split the whole file into chunks no larger than `chunk_size` + n_chunks, last_chunk_size = divmod(self.n_traces, chunk_size) + chunk_sizes = [chunk_size] * n_chunks + if last_chunk_size: + chunk_sizes += [last_chunk_size] + chunk_starts = np.cumsum([0] + chunk_sizes[:-1]) + + # Iterate over chunks + buffer = np.empty((self.n_traces, len(headers)), dtype=np.int32) + + with Notifier(pbar, total=self.n_traces) as progress_bar: + with ProcessPoolExecutor(max_workers=max_workers) as executor: + + def callback(future, start): + chunk_headers = future.result() + chunk_size = len(chunk_headers) + buffer[start : start + chunk_size] = chunk_headers + progress_bar.update(chunk_size) + + for start, chunk_size_ in zip(chunk_starts, chunk_sizes): + future = executor.submit(read_chunk, path=self.path, + shape=self.n_traces, offset=self.file_traces_offset, + dtype=mmap_trace_dtype, headers=headers, + start=start, chunk_size=chunk_size_) + future.add_done_callback(partial(callback, start=start)) + dataframe = pd.DataFrame(buffer, columns=headers) + + if reconstruct_tsf: + dataframe['TRACE_SEQUENCE_FILE'] = self.make_tsf_header() + return dataframe + + def load_header(self, header, chunk_size=25_000, max_workers=None, pbar=False, **kwargs): + """ Load exactly one header. """ + return self.load_headers(headers=[header], chunk_size=chunk_size, max_workers=max_workers, + pbar=pbar, reconstruct_tsf=False, **kwargs) + + @staticmethod + def _make_mmap_headers_dtype(headers, endian_symbol='>'): + """ Create list of `numpy` dtypes to view headers data. + + Defines a dtype for exactly 240 bytes, where each of the requested headers would have its own named subdtype, + and the rest of bytes are lumped into `np.void` of certain lengths. + + Only the headers data should be viewed under this dtype: the rest of trace data (values) + should be processed (or skipped) separately. + + We do not apply final conversion to `np.dtype` to the resulting list of dtypes so it is easier to append to it. + + Examples + -------- + if `headers` are `INLINE_3D` and `CROSSLINE_3D`, which are 189-192 and 193-196 bytes, the output would be: + >>> [('unused_0', numpy.void, 188), + >>> ('INLINE_3D', '>i4'), + >>> ('CROSSLINE_3D', '>i4'), + >>> ('unused_1', numpy.void, 44)] + """ + header_to_byte = segyio.tracefield.keys + byte_to_header = {val: key for key, val in header_to_byte.items()} + start_bytes = sorted(header_to_byte.values()) + byte_to_len = {start: end - start + for start, end in zip(start_bytes, start_bytes[1:] + [MemmapLoader.TRACE_HEADER_SIZE + 1])} + requested_headers_bytes = {header_to_byte[header] for header in headers} + + # Iterate over all headers + # Unrequested headers are lumped into `np.void` of certain lengths + # Requested headers are each its own dtype + dtype_list = [] + unused_counter, void_counter = 0, 0 + for byte, header_len in byte_to_len.items(): + if byte in requested_headers_bytes: + if void_counter: + unused_dtype = (f'unused_{unused_counter}', np.void, void_counter) + dtype_list.append(unused_dtype) + + unused_counter += 1 + void_counter = 0 + + header_name = byte_to_header[byte] + value_dtype = 'i2' if header_len == 2 else 'i4' + value_dtype = endian_symbol + value_dtype + header_dtype = (header_name, value_dtype) + dtype_list.append(header_dtype) + else: + void_counter += header_len + + if void_counter: + unused_dtype = (f'unused_{unused_counter}', np.void, void_counter) + dtype_list.append(unused_dtype) + return dtype_list + + # Data loading + def load_traces(self, indices, limits=None, buffer=None): + """ Load traces by their indices. + Under the hood, we use a pre-made memory mapping over the file, where trace data is viewed with a special dtype. + Regardless of the numerical dtype of SEG-Y file, we output IEEE float32: + for IBM floats, that requires an additional conversion. + + Parameters + ---------- + indices : sequence + Indices (TRACE_SEQUENCE_FILE) of the traces to read. + limits : sequence of ints, slice, optional + Slice of the data along the depth axis. + buffer : np.ndarray, optional + Buffer to read the data into. If possible, avoids copies. + """ + limits = self.process_limits(limits) + + if self.file_format != 1: + traces = self.data_mmap[indices, limits] + else: + traces = self.data_mmap[indices, limits.start:limits.stop] + if limits.step != 1: + traces = traces[:, ::limits.step] + traces = self._ibm_to_ieee(traces) + + if buffer is None: + return np.require(traces, dtype=self.dtype, requirements='C') + buffer[:] = traces + return buffer + + def load_depth_slices(self, indices, buffer=None): + """ Load horizontal (depth) slices of the data. + Requires a ~full sweep through SEG-Y, therefore is slow. + + Parameters + ---------- + indices : sequence + Indices (ordinals) of the depth slices to read. + buffer : np.ndarray, optional + Buffer to read the data into. If possible, avoids copies. + """ + depth_slices = self.data_mmap[:, indices] + if self.file_format == 1: + depth_slices = self._ibm_to_ieee(depth_slices) + depth_slices = depth_slices.T + + if buffer is None: + return np.require(depth_slices, dtype=np.float32, requirements='C') + buffer[:] = depth_slices + return buffer + + def _ibm_to_ieee(self, array): + """ Convert IBM floats to regular IEEE ones. """ + array_bytes = (array[:, :, 0], array[:, :, 1], array[:, :, 2], array[:, :, 3]) + if self.endian in {"little", "lsb"}: + array_bytes = array_bytes[::-1] + return ibm_to_ieee(*array_bytes) + + + # Conversion to other SEG-Y formats (data dtype) + def convert(self, path=None, format=8, transform=None, chunk_size=25_000, max_workers=4, + pbar='t', overwrite=True): + """ Convert SEG-Y file to a different `format`: dtype of data values. + Keeps the same binary header (except for the 3225 byte, which stores the format). + Keeps the same header values for each trace: essentially, only the values of each trace are transformed. + + The most common scenario of this function usage is to convert float32 SEG-Y into int8 one: + the latter is a lot faster and takes ~4 times less disk space at the cost of some data loss. + + Parameters + ---------- + path : str, optional + Path to save file to. If not provided, we use the path of the current cube with an added postfix. + format : int + Target SEG-Y format. + Refer to :attr:`SEGY_FORMAT_TO_TRACE_DATA_DTYPE` for list of available formats and their data value dtype. + transform : callable, optional + Callable to transform data from the current file to the ones, saved in `path`. + Must return the same dtype, as specified by `format`. + chunk_size : int + Maximum amount of traces in each chunk. + max_workers : int or None + Maximum number of parallel processes to spawn. If None, then the number of CPU cores is used. + pbar : bool, str + If bool, then whether to display progress bar. + If str, then type of progress bar to display: `'t'` for textual, `'n'` for widget. + overwrite : bool + Whether to overwrite existing `path` or raise an exception. + """ + #pylint: disable=redefined-builtin + # Default path + if path is None: + dirname = os.path.dirname(self.path) + basename = os.path.basename(self.path) + path = os.path.join(dirname, basename.replace('.', f'_f{format}.')) + + # Compute target dtype, itemsize, size of the dst file + dst_dtype = self.endian_symbol + self.SEGY_FORMAT_TO_TRACE_DATA_DTYPE[format] + dst_itemsize = np.dtype(dst_dtype).itemsize + dst_size = self.file_traces_offset + self.n_traces * (self.TRACE_HEADER_SIZE + self.n_samples * dst_itemsize) + + # Exceptions + traces = self.load_traces([0]) + if transform(traces).dtype != dst_dtype: + raise ValueError('dtype of `dst` is not the same as the one returned by `transform`!.' + f' {dst_dtype}!={transform(traces).dtype}') + + if os.path.exists(path) and not overwrite: + raise OSError(f'File {path} already exists! Set `overwrite=True` to ignore this error.') + + # Serialize `transform` + transform = dill.dumps(transform) + + # Create new file and copy binary header + src_mmap = np.memmap(self.path, mode='r') + dst_mmap = np.memmap(path, mode='w+', shape=(dst_size,)) + dst_mmap[:self.file_traces_offset] = src_mmap[:self.file_traces_offset] + + # Replace `format` bytes + dst_mmap[3225-1:3225-1+2] = np.array([format], dtype=self.endian_symbol + 'u2').view('u1') + + # Prepare dst dtype + dst_trace_dtype = np.dtype([('headers', np.void, self.TRACE_HEADER_SIZE), + ('data', dst_dtype, self.n_samples)]) + + # Split the whole file into chunks no larger than `chunk_size` + n_chunks, last_chunk_size = divmod(self.n_traces, chunk_size) + chunk_sizes = [chunk_size] * n_chunks + if last_chunk_size: + chunk_sizes += [last_chunk_size] + chunk_starts = np.cumsum([0] + chunk_sizes[:-1]) + + # Iterate over chunks + name = os.path.basename(path) + with Notifier(pbar, total=self.n_traces, desc=f'Convert to `{name}`', ncols=110) as progress_bar: + with ProcessPoolExecutor(max_workers=max_workers) as executor: + def callback(future): + chunk_size = future.result() + progress_bar.update(chunk_size) + + for start, chunk_size_ in zip(chunk_starts, chunk_sizes): + future = executor.submit(convert_chunk, + src_path=self.path, dst_path=path, + shape=self.n_traces, offset=self.file_traces_offset, + src_dtype=self.mmap_trace_dtype, dst_dtype=dst_trace_dtype, + endian=self.endian, transform=transform, + start=start, chunk_size=chunk_size_) + future.add_done_callback(callback) + return path + + +def read_chunk(path, shape, offset, dtype, headers, start, chunk_size): + """ Read headers from one chunk. + We create memory mapping anew in each worker, as it is easier and creates no significant overhead. + """ + # mmap is created over the entire file as + # creating data over the requested chunk only does not speed up anything + mmap = np.memmap(filename=path, mode='r', shape=shape, offset=offset, dtype=dtype) + + buffer = np.empty((chunk_size, len(headers)), dtype=np.int32) + for i, header in enumerate(headers): + buffer[:, i] = mmap[header][start : start + chunk_size] + return buffer + + +def convert_chunk(src_path, dst_path, shape, offset, src_dtype, dst_dtype, endian, transform, start, chunk_size): + """ Copy the headers, transform and write data from one chunk. + We create all memory mappings anew in each worker, as it is easier and creates no significant overhead. + """ + # Deserialize `transform` + transform = dill.loads(transform) + + # Create mmaps: src is read-only, dst is read-write + src_mmap = np.memmap(src_path, mode='r', shape=shape, offset=offset, dtype=src_dtype) + dst_mmap = np.memmap(dst_path, mode='r+', shape=shape, offset=offset, dtype=dst_dtype) + + # Load all data from chunk + src_traces = src_mmap[start : start + chunk_size] + dst_traces = dst_mmap[start : start + chunk_size] + + # If `src_traces_data` is in IBM float, convert to float32 + src_traces_data = src_traces['data'] + if len(src_traces_data.shape) == 3: + array_bytes = (src_traces_data[:, :, 0],src_traces_data[:, :, 1], + src_traces_data[:, :, 2], src_traces_data[:, :, 3]) + if endian in {"little", "lsb"}: + array_bytes = array_bytes[::-1] + src_traces_data = ibm_to_ieee(*array_bytes) + + # Copy headers, write transformed data + dst_traces['headers'] = src_traces['headers'] + dst_traces['data'] = transform(src_traces_data) + return chunk_size + + +@njit(nogil=True, parallel=True) +def ibm_to_ieee(hh, hl, lh, ll): + """ Convert 4 arrays representing individual bytes of IBM 4-byte floats into a single array of floats. + Input arrays are ordered from most to least significant bytes and have `np.uint8` dtypes. + The result is returned as an `np.float32` array. + """ + # pylint: disable=not-an-iterable + res = np.empty_like(hh, dtype=np.float32) + for i in prange(res.shape[0]): + for j in prange(res.shape[1]): + mant = (((np.int32(hl[i, j]) << 8) | lh[i, j]) << 8) | ll[i, j] + if hh[i, j] & 0x80: + mant = -mant + exp16 = (np.int8(hh[i, j]) & np.int8(0x7f)) - 70 + res[i, j] = mant * 16.0**exp16 + return res diff --git a/seismiqb/geometry/metric_mixin.py b/seismiqb/geometry/metric_mixin.py new file mode 100644 index 0000000..6082ced --- /dev/null +++ b/seismiqb/geometry/metric_mixin.py @@ -0,0 +1,69 @@ +""" Collection of tools for evaluating quality of geometries. """ +import numpy as np + +from batchflow import Notifier + + + +class MetricMixin: + """ Tools to evaluate geometry quality or compare multiple geometries. """ + def compare(self, other, function, kernel_size=(5, 5), limits=None, chunk_size=(500, 500), pbar='t', **kwargs): + """ Compare two geometries by iterating over their values in lateral window. + + Parameters + ---------- + self, other : instances of Geometry + Geometries to compare. + function : callable + Function to compare values in each lateral window. Must take two 2D arrays as inputs. + kernel_size : sequence of two ints + Shape of the lateral window. + limits : sequence of ints, slice, optional + Slice of the data along the depth (last) axis. + chunk_size : sequence of two ints + Size of the data loaded at once. + pbar : bool, str + If bool, then whether to display progress bar. + If str, then type of progress bar to display: `'t'` for textual, `'n'` for widget. + kwargs : dict + Passed directly to `function`. + """ + # Parse parameters + limits = self.process_limits(limits) + window = np.array(kernel_size) + low = window // 2 + high = window - low + + # Compute the shape of `function` output + array_example = self[0:kernel_size[0], 0:kernel_size[1]].reshape(-1, self.depth) + size = function(array_example, array_example, **kwargs).size + metric_matrix = np.full((*self.spatial_shape, size), np.nan, dtype=np.float32) + total = np.prod(self.shape[:2] - window) + + with Notifier(pbar, total=total) as progress_bar: + # Iterate over geometries in lateral chunks + for i_chunk_start in range(0, self.shape[0], chunk_size[0] - window[0]): + for x_chunk_start in range(0, self.shape[1], chunk_size[1] - window[1]): + i_chunk_end = min(i_chunk_start + chunk_size[0], self.shape[0]) + x_chunk_end = min(x_chunk_start + chunk_size[1], self.shape[1]) + + chunk_locations = [slice(i_chunk_start, i_chunk_end), + slice(x_chunk_start, x_chunk_end), + limits] + self_chunk = self.load_crop(chunk_locations) + other_chunk = other.load_crop(chunk_locations) + chunk_shape = self_chunk.shape + + # Iterate over chunks in lateral kernels + for i_anchor in range(low[0], chunk_shape[0] - high[0]): + for x_anchor in range(low[1], chunk_shape[1] - high[1]): + i_kernel_slice = slice(i_anchor - low[0], i_anchor + high[0]) + x_kernel_slice = slice(x_anchor - low[1], x_anchor + high[1]) + + self_subset = self_chunk[i_kernel_slice, x_kernel_slice].reshape(-1, chunk_shape[-1]) + other_subset = other_chunk[i_kernel_slice, x_kernel_slice].reshape(-1, chunk_shape[-1]) + result = function(self_subset, other_subset, **kwargs) + + metric_matrix[i_chunk_start + i_anchor, x_chunk_start + x_anchor] = result + progress_bar.update() + return metric_matrix diff --git a/seismiqb/geometry/segy.py b/seismiqb/geometry/segy.py new file mode 100644 index 0000000..ef698ad --- /dev/null +++ b/seismiqb/geometry/segy.py @@ -0,0 +1,701 @@ +""" Class to work with seismic data in SEG-Y format. """ +#pylint: disable=not-an-iterable +from concurrent.futures import ThreadPoolExecutor + +import numpy as np +from numba import njit, prange +import cv2 + +from batchflow import Notifier + +from .base import Geometry +from .segyio_loader import SegyioLoader +from .memmap_loader import MemmapLoader + + + +class GeometrySEGY(Geometry): + """ Class to infer information about SEG-Y cubes and provide convenient methods for working with them. + + In order to initialize instance, one must supply `path`, `index_headers` and `additional_headers`: + - `path` is a location of SEG-Y file + - `index_headers` are used as the gather/trace unique identifier: + for example, `INLINE_3D` and `CROSSLINE_3D` has a one-to-one correspondence with trace numbers. + Another example is `FieldRecord` and `TraceNumber`. + - `additional_headers` are also loaded. + Default value of `index_headers` is ['INLINE_3D', 'CROSSLINE_3D'] with additional ['CDP_X', 'CDP_Y'], + so that post-stack cube can be loaded by providing path only. + + For brevity, we use the 'inline/crossline' words to refer to the first/second indexing header in documentation + and developer comments, as that is the most common scenario. + + To simplify indexing, we use ordinals of unique values of each indexing header pretty much everywhere after init. + In the simplest case of regular structure, we can convert ordinals into unique values by using + `value = value_min + ordinal * value_step`, where `value_min` and `value_step` are inferred from trace headers. + + For faster indexing of the traces we use indexing matrix, that maps + `(ordinal_for_indexing_header_0, ordinal_for_indexing_header_1)` into the actual trace number to be loaded. + + At initialization or by manually calling method :meth:`collect_stats` we make a full pass through + the cube in order to analyze distribution of amplitudes, storing global, spatial and depth-wise stats. + They are available as attributes, e.g. `mean`, `mean_matrix` and `mean_vector`. + + Refer to the documentation of the base class :class:`Geometry` for more information about attributes and parameters. + """ + # Headers to use as a unique id of a trace + INDEX_HEADERS_PRESTACK = ('FieldRecord', 'TraceNumber') + INDEX_HEADERS_POSTSTACK = ('INLINE_3D', 'CROSSLINE_3D') + INDEX_HEADERS_CDP = ('CDP_Y', 'CDP_X') + + # Headers to load from SEG-Y cube + ADDITIONAL_HEADERS_PRESTACK_FULL = ('FieldRecord', 'TraceNumber', 'TRACE_SEQUENCE_FILE', + 'CDP', 'CDP_TRACE', 'offset') + ADDITIONAL_HEADERS_POSTSTACK_FULL = ('INLINE_3D', 'CROSSLINE_3D', 'CDP_X', 'CDP_Y') + + def init(self, path, index_headers=INDEX_HEADERS_POSTSTACK, additional_headers=ADDITIONAL_HEADERS_POSTSTACK_FULL, + loader_class=MemmapLoader, reload_headers=False, dump_headers=True, load_headers_params=None, + collect_stats=True, recollect_stats=False, collect_stats_params=None, dump_meta=True, + **kwargs): + """ Init for SEG-Y geometry. The sequence of actions: + - initialize loader instance + - load headers by reading SEG-Y or reading from meta + - compute additional attributes from indexing headers + - validate structure of the coordinate system, created by the indexing headers + - collect stats by full SEG-Y sweep or reading from meta + - dump meta for future inits. + """ + # Store attributes + self.index_headers = list(index_headers) + self.additional_headers = list(additional_headers) + self.index_length = len(index_headers) + self.converted = False + + # Initialize loader + self.loader = self._infer_loader_class(loader_class)(path) + + # Retrieve some of the attributes directly from the `loader` + self.n_traces = self.loader.n_traces + self.depth = self.loader.n_samples + self.delay = self.loader.delay + self.sample_interval = self.loader.sample_interval + self.sample_rate = self.loader.sample_rate + + self.dtype = self.loader.dtype + self.quantized = (self.dtype == np.int8) + + self.segy_path = self.loader.path + try: + self.segy_text = [item.decode('ascii') for item in self.loader.text] + except: #pylint: disable=bare-except + self.segy_text = ['*'*3200] + + # If all stats are already available in meta, use them + required_attributes = self.PRESERVED + self.PRESERVED_LAZY + self.PRESERVED_LAZY_CACHED + meta_exists_and_has_attributes = self.meta_storage.exists and self.meta_storage.has_items(required_attributes) + + if meta_exists_and_has_attributes and not (reload_headers or recollect_stats): + self.load_meta(keys=self.PRESERVED) + self.has_stats = True + return + + # Load all of the requested headers, either from SEG-Y directly or previously stored dump + headers_to_load = list(set(index_headers) | set(additional_headers)) + + if self.meta_storage.has_item(key='headers') and not reload_headers: + headers = self.meta_storage.read_item(key='headers') + else: + load_headers_params = load_headers_params or {} + headers = self.load_headers(headers_to_load, **load_headers_params) + if dump_headers: + self.meta_storage.store_item(key='headers', value=headers) + self.headers = headers + + # Infer attributes based on indexing headers: values and coordinates + self.add_index_attributes() + + if 'INLINE_3D' in self.index_headers and 'CROSSLINE_3D' in self.index_headers: + self.rotation_matrix = self.compute_rotation_matrix() + + # Collect amplitude stats, either by passing through SEG-Y or from previously stored dump + required_attributes = self.PRESERVED + self.PRESERVED_LAZY + meta_exists_and_has_attributes = self.meta_storage.exists and self.meta_storage.has_items(required_attributes) + + if meta_exists_and_has_attributes and not recollect_stats: + self.load_meta(keys=self.PRESERVED) + self.has_stats = True + elif collect_stats: + collect_stats_params = collect_stats_params or {} + self.collect_stats(**collect_stats_params) + self.has_stats = True + else: + self.compute_dead_traces() + self.has_stats = False + + if hasattr(self, 'n_alive_traces') and self.n_alive_traces is not None: + try: + self.area = self.compute_area() + except IndexError: + self.area = -1. + + # Dump inferred attributes to a separate file for later loads + if dump_meta and not meta_exists_and_has_attributes: + self.dump_meta() + + def _infer_loader_class(self, loader_class): + """ Select appropriate loader class. """ + if isinstance(loader_class, type): + return loader_class + if 'seg' in loader_class: + return SegyioLoader + return MemmapLoader + + def load_headers(self, headers_to_load, reconstruct_tsf=True, chunk_size=25_000, max_workers=4, pbar=False): + """ Load all of the requested headers into dataframe. """ + return self.loader.load_headers(headers_to_load, reconstruct_tsf=reconstruct_tsf, + chunk_size=chunk_size, max_workers=max_workers, pbar=pbar) + + def add_index_attributes(self): + """ Add attributes, based on the values of indexing headers. """ + # For each indexing headers compute set of its values, its sorted version, + # and the mapping from each unique value to its ordinal in sorted list + self.index_unsorted_uniques = [np.unique(self.headers[index_header]) + for index_header in self.index_headers] + self.index_sorted_uniques = [np.sort(item) for item in self.index_unsorted_uniques] + self.index_value_to_ordinal = [{value: i for i, value in enumerate(item)} + for item in self.index_sorted_uniques] + + # Infer coordinates for indexing headers + self.shifts = [np.min(item) for item in self.index_sorted_uniques] + self.lengths = [len(item) for item in self.index_sorted_uniques] + self.ranges = [(np.min(item), np.max(item)) for item in self.index_sorted_uniques] + self.shape = np.array([*self.lengths, self.depth]) + + # Check if indexing headers provide regular structure + self.increments = [] + regular_structure = True + for i, index_header in enumerate(self.index_headers): + increments = np.diff(self.index_sorted_uniques[i]) + unique_increments = set(increments) or set([1]) + + if len(unique_increments) > 1: + print(f'`{index_header}` has irregular spacing! {unique_increments}') + regular_structure = False + else: + self.increments.append(unique_increments.pop()) + self.regular_structure = regular_structure + + # Create indexing matrix + if self.index_length == 2: + index_matrix = self.compute_header_values_matrix('TRACE_SEQUENCE_FILE') + index_matrix[index_matrix != -1] -= 1 + self.index_matrix = index_matrix + + self.absent_traces_matrix = (self.index_matrix == -1).astype(np.bool_) + + def compute_dead_traces(self, frequency=100): + """ Fallback for dead traces matrix computation, if no full stats are collected. """ + slices = self.loader.load_depth_slices(list(range(0, self.depth, frequency))) + + if slices.shape[-1] == np.prod(self.lengths): + slices = slices.reshape(slices.shape[0], *self.lengths) + std_matrix = np.std(slices, axis=0) + + self.dead_traces_matrix = (std_matrix == 0).astype(np.bool_) + self.n_dead_traces = np.sum(self.dead_traces_matrix) + self.n_alive_traces = np.prod(self.lengths) - self.n_dead_traces + + + def compute_header_values_matrix(self, header): + """ Mapping from ordinal inline/crossline coordinate to the value of header. """ + index_values = self.headers[self.index_headers].values + index_ordinals = self.lines_to_ordinals(index_values) + idx_0, idx_1 = index_ordinals[:, 0], index_ordinals[:, 1] + + dtype = self.headers[header].dtype + matrix = np.full(self.lengths, -1, dtype=dtype) + matrix[idx_0, idx_1] = self.headers[header] + return matrix + + + # Compute additional stats from CDP/LINES correspondence + def compute_rotation_matrix(self, n_points=10): + """ Compute transform from INLINE_3D/CROSSLINE_3D coordinates to CDP_X/CDP_Y system. """ + ix_points = [] + cdp_points = [] + + for _ in range(n_points): + idx = np.random.randint(self.n_traces) + row = self.headers.iloc[idx] + + # INLINE_3D -> CDP_X, CROSSLINE_3D -> CDP_Y + ix_point = (row['INLINE_3D'], row['CROSSLINE_3D']) + cdp_point = (row['CDP_X'], row['CDP_Y']) + + ix_points.append(ix_point) + cdp_points.append(cdp_point) + rotation_matrix, inliers = cv2.estimateAffine2D(np.float32(ix_points), np.float32(cdp_points)) + + if 0 in inliers: + return None + return rotation_matrix + + def compute_area(self, shift=50): + """ Compute approximate area of the cube in square kilometers. """ + central_i = self.shape[0] // 2 + central_x = self.shape[1] // 2 + + tsf = self.index_matrix[central_i, central_x] + tsf_di = self.index_matrix[central_i, central_x + shift] + tsf_dx = self.index_matrix[central_i + shift, central_x] + + row = self.headers.iloc[tsf] + row_di = self.headers.iloc[tsf_di] + row_dx = self.headers.iloc[tsf_dx] + + # CDP_X/CDP_Y coordinate system is rotated on 90 degrees with respect to INLINE_3D/CROSSLINE_3D + if row_di['CDP_X'] - row['CDP_X'] == 0 and row_dx['CDP_Y'] - row['CDP_Y'] == 0: + row_di, row_dx = row_dx, row_di + + # Size of one "trace bin" + cdp_x_delta_km = abs(row_di['CDP_X'] - row['CDP_X']) / shift / 1000 + cdp_y_delta_km = abs(row_dx['CDP_Y'] - row['CDP_Y']) / shift / 1000 + area = cdp_x_delta_km * cdp_y_delta_km * self.n_alive_traces + return round(area, 2) + + + # Collect stats + def collect_stats(self, chunk_size=20, max_workers=16, + n_quantile_traces=100_000, quantile_precision=3, seed=42, pbar='t'): + """ One sweep through the entire SEG-Y data to collects stats, which are available as instance attributes: + - global: one number for the entire cube, e.g. `mean` + - spatial: a matrix of values for each trace, e.g. `mean_matrix` + - depth-wise: one value for each depth slice, e.g. `mean_vector`. + Other than `mean`, we also collect `min`, `max` and `std`. + Moreover, we compute a certain amount of quantiles: they are computed from a random subset of the traces. + TODO: add `limits`? + + The traces are iterated over in chunks: chunking is performed along the first indexing header, e.g. `INLINE_3D`. + Computation of stats is performed in multiple threads to speed up the process. + + Implementation detail: we store buffers for stats, e.g. `mean_matrix` in the instance itself. + Each thread has the access to buffers and modifies them in-place. + Moreover, even the underlying numba functions are using the same buffers in-place: + this way we avoid unnecessary copies and data conversions. + + Parameters + ---------- + chunk_size : int + Number of full inlines to include in one chunk. + max_workers : int + Maximum number of threads for parallelization. + n_quantile_traces : int + Size of the subset to compute quantiles. + quantile_precision : int + Compute an approximate quantile for each value with that number of decimal places. + seed : int + Seed for quantile traces subset selection. + pbar : bool, str + If bool, then whether to display progress bar. + If str, then type of progress bar to display: `'t'` for textual, `'n'` for widget. + """ + # pylint: disable=too-many-statements + # Prepare chunks + n = self.lengths[0] + n_chunks, last_chunk_size = divmod(n, chunk_size) + chunk_sizes = [chunk_size] * n_chunks + if last_chunk_size: + chunk_sizes += [last_chunk_size] + n_chunks += 1 + + chunk_starts = np.cumsum([0] + chunk_sizes[:-1]) + chunk_ends = np.cumsum(chunk_sizes) + chunk_weights = np.array(chunk_sizes, dtype=np.float64) / n + + # Define buffers: chunked vectors + self.min_vector_chunked = np.full((n_chunks, self.depth), np.inf, dtype=np.float32) + self.max_vector_chunked = np.full((n_chunks, self.depth), -np.inf, dtype=np.float32) + self.mean_vector_chunked = np.zeros((n_chunks, self.depth), dtype=np.float64) + self.var_vector_chunked = np.zeros((n_chunks, self.depth), dtype=np.float64) + + # Define buffers: matrices + self.min_matrix = np.full(self.lengths, np.inf, dtype=np.float32) + self.max_matrix = np.full(self.lengths, -np.inf, dtype=np.float32) + self.mean_matrix = np.zeros(self.lengths, dtype=np.float64) + self.var_matrix = np.zeros(self.lengths, dtype=np.float64) + + # Read data in chunks, compute stats for each of them, store into buffer + description = f'Collecting stats for `{self.name}`' + with Notifier(pbar, total=n, desc=description, ncols=110) as progress_bar: + with ThreadPoolExecutor(max_workers=max_workers) as executor: + def callback(future): + chunk_size = future.result() + progress_bar.update(chunk_size) + + for chunk_i, (start, end) in enumerate(zip(chunk_starts, chunk_ends)): + future = executor.submit(self.collect_stats_chunk, + start=start, end=end, chunk_i=chunk_i) + future.add_done_callback(callback) + + # Finalize vectors + self.min_vector = np.average(self.min_vector_chunked, axis=0, weights=chunk_weights) + self.max_vector = np.average(self.max_vector_chunked, axis=0, weights=chunk_weights) + mean_vector = np.average(self.mean_vector_chunked, axis=0, weights=chunk_weights) + var_vector = np.average(self.var_vector_chunked + (self.mean_vector_chunked - mean_vector)**2, + axis=0, weights=chunk_weights) + + self.mean_vector = mean_vector.astype(np.float32) + self.std_vector = np.sqrt(var_vector).astype(np.float32) + + # Finalize matrices + self.mean_matrix = self.mean_matrix.astype(np.float32) + self.std_matrix = np.sqrt(self.var_matrix).astype(np.float32) + self.dead_traces_matrix = (self.min_matrix == self.max_matrix).astype(np.bool_) + + # Clean-up redundant buffers + del (self.min_vector_chunked, self.max_vector_chunked, + self.mean_vector_chunked, self.var_vector_chunked, + self.var_matrix) + + # Add scalar values + self.min = self.min_matrix[~self.dead_traces_matrix].min() + self.max = self.max_matrix[~self.dead_traces_matrix].max() + self.mean = self.mean_matrix[~self.dead_traces_matrix].mean() + + n_dead_traces = np.sum(self.dead_traces_matrix) + n_alive_traces = np.prod(self.lengths) - n_dead_traces + self.std = np.sqrt((self.std_matrix[~self.dead_traces_matrix] ** 2).sum() / n_alive_traces) + + # Load subset of data to compute quantiles + alive_traces_indices = self.index_matrix[~self.dead_traces_matrix].reshape(-1) + indices = np.random.default_rng(seed=seed).choice(alive_traces_indices, + size=min(self.n_traces, n_quantile_traces)) + data = self.load_by_indices(indices) + + quantile_support = np.round(np.linspace(0, 1, num=10**quantile_precision+1), + decimals=quantile_precision) + quantile_values = np.quantile(data, q=quantile_support) + quantile_values[0], quantile_values[-1] = self.min, self.max + + # Store stats of the subset to compare against fair ones + self.subset_min = data.min() + self.subset_max = data.max() + self.subset_mean = data.mean() + self.subset_std = data.std() + self.n_value_uniques = len(np.unique(data)) + self.quantile_precision = quantile_precision + self.quantile_support, self.quantile_values = quantile_support, quantile_values + + # Store the number of alive/dead traces + self.n_alive_traces = n_alive_traces + self.n_dead_traces = n_dead_traces + + def collect_stats_chunk(self, start, end, chunk_i): + """ Read requested chunk, compute stats for it. """ + # Retrieve chunk data + indices = self.index_matrix[start:end].reshape(-1) + + data = self.load_by_indices(indices) + data = data.reshape(end - start, self.lengths[1], self.depth) + + # Actually compute all of the stats. Modifies buffers in-place + _collect_stats_chunk(data, + min_vector=self.min_vector_chunked[chunk_i], + max_vector=self.max_vector_chunked[chunk_i], + mean_vector=self.mean_vector_chunked[chunk_i], + var_vector=self.var_vector_chunked[chunk_i], + min_matrix=self.min_matrix[start:end], + max_matrix=self.max_matrix[start:end], + mean_matrix=self.mean_matrix[start:end], + var_matrix=self.var_matrix[start:end]) + return end - start + + + # Data loading: arbitrary trace indices + def load_by_indices(self, indices, limits=None, buffer=None): + """ Read requested traces from SEG-Y file. + Value `-1` is interpreted as missing trace, and corresponding traces are filled with zeros. + + Parameters + ---------- + indices : sequence + Indices (TRACE_SEQUENCE_FILE) of the traces to read. + limits : sequence of ints, slice, optional + Slice of the data along the depth (last) axis. + buffer : np.ndarray, optional + Buffer to read the data into. If possible, avoids copies. + """ + if buffer is None: + limits = self.process_limits(limits) + buffer = np.empty((len(indices), self.depth), dtype=self.dtype)[:, limits] + else: + buffer = buffer.reshape((len(indices), -1)) + + if -1 in indices: + # Create new buffer to avoid copy on advanced indexing + mask = indices >= 0 + buffer_ = np.empty_like(buffer)[:mask.sum()] + self.loader.load_traces(indices=indices[mask], limits=limits, buffer=buffer_) + + buffer[mask] = buffer_ + buffer[~mask] = self.FILL_VALUE + else: + self.loader.load_traces(indices=indices, limits=limits, buffer=buffer) + return buffer + + def load_depth_slices(self, indices, buffer=None): + """ Read requested depth slices from SEG-Y file. """ + if buffer is None: + buffer = np.empty((len(indices), self.n_traces), dtype=self.dtype) + else: + buffer = buffer.reshape((len(indices), self.n_traces)) + + buffer = self.loader.load_depth_slices(indices, buffer=buffer) + if buffer.shape[-1] == np.prod(self.lengths): + buffer = buffer.reshape(len(indices), *self.lengths) + else: + idx = np.nonzero(self.index_matrix >= 0) + matrix = np.zeros(shape=(*self.spatial_shape, len(indices)), dtype=self.dtype) + matrix[idx] = buffer.T + buffer = matrix.transpose(2, 0, 1) + return buffer + + @property + def mmap(self): + """ 3D memory map, that views the entire SEG-Y as one 3D array. """ + return self.loader.data_mmap.reshape(self.shape) + + # Data loading: 2D + def load_slide_native(self, index, axis=0, limits=None, buffer=None, safe=False): + """ Load one slide of data along specified axis. + + Parameters + ---------- + index : int, str + If int, then interpreted as the ordinal along the specified axis. + If `'random'`, then we generate random index along the axis. + If string of the `'#XXX'` format, then we interpret it as the exact indexing header value. + axis : int + Axis of the slide. + limits : sequence of ints, slice, optional + Slice of the data along the depth (last) axis. + buffer : np.ndarray, optional + Buffer to read the data into. If possible, avoids copies. + """ + _ = safe + if axis in {0, 1}: + index = self.get_slide_index(index=index, axis=axis) + indices = np.take(self.index_matrix, indices=index, axis=axis) + slide = self.load_by_indices(indices=indices, limits=limits, buffer=buffer) + else: + slide = self.load_depth_slices([index], buffer=buffer).squeeze(0) + return slide + + # Data loading: 3D + def load_crop_native(self, locations, buffer=None, safe=False): + """ Load crop (3D subvolume) from the cube. + + Parameters + ---------- + locations : sequence + A triplet of slices to specify the location of a subvolume. + buffer : np.ndarray, optional + Buffer to read the data into. If possible, avoids copies. + """ + _ = safe + shape = self.locations_to_shape(locations) + axis = np.argmin(shape) + + if axis in {0, 1} or shape[-1] > 50: #TODO: explain this constant + indices = self.index_matrix[locations[0], locations[1]].reshape(-1) + buffer = self.load_by_indices(indices=indices, limits=locations[-1], buffer=buffer) + + shape = [((slc.stop or stop) - (slc.start or 0)) for slc, stop in zip(locations, self.shape)] + buffer = buffer.reshape(shape) + else: + indices = np.arange(locations[-1].start, locations[-1].stop) + data = self.load_depth_slices(indices).transpose(1, 2, 0)[locations[0], locations[1]] + + if buffer is None: + buffer = data + else: + buffer[:] = data + return buffer + + def get_optimal_axis(self, locations=None, shape=None): + """ Choose the fastest axis for loading given locations. """ + shape = shape or self.locations_to_shape(locations) + return np.argsort(shape)[0] + + def load_section(self, locations, dtype=None): + """ Load section through `locations`. + + Parameters + ---------- + locations : iterable + Locations of traces to construct section. + + dtype : None or numpy.dtype, optional + Type of the resulting image, by default None (transforms to self.dtype) + + Returns + ------- + section, indices, nodes: tuple with 3 elements + section : numpy.ndarray + 2D array with loaded and interpolated traces of section. + indices : numpy.ndarray + Float coordinates of section traces. + nodes : numpy.ndarray + Positions of node traces (from `locations`) in `traces` array. + """ + locations = np.array(locations) + dtype = dtype or self.dtype + + indices = [] + for start, stop in zip(locations[:-1], locations[1:]): + indices.append(get_line_coordinates(start, stop)[:-1]) + indices.append(np.array([locations[-1]], dtype='float32')) + + support, weights = get_line_support(np.concatenate(indices)) + + all_support_traces = np.concatenate(support) + unique_support, traces_indices = np.unique(all_support_traces, axis=0, return_inverse=True) + traces_indices = traces_indices.reshape(-1, 4) + + traces = self.load_by_indices(self.index_matrix[unique_support[:, 0], unique_support[:, 1]]) + section = interpolate(traces, traces_indices, weights) + if np.issubdtype(dtype, np.integer): + section = section.astype(dtype) + nodes = np.cumsum([0] + [len(item) for item in indices[:-1]]) + indices = np.concatenate(indices) + return section, indices, nodes + +@njit(nogil=True) +def _collect_stats_chunk(data, + min_vector, max_vector, mean_vector, var_vector, + min_matrix, max_matrix, mean_matrix, var_matrix): + """ Compute stats of a 3D array: min, max, mean, variance. + + We use provided buffers to avoid unnecessary copies. + We use buffers for mean and var to track the running sum of values / squared values. + """ + shape = data.shape + + for i in range(shape[0]): + for x in range(shape[1]): + for d in range(shape[2]): + # Read traces values + trace_value = data[i, x, d] + trace_value64 = np.float64(trace_value) + + # Update vectors + min_vector[d] = min(min_vector[d], trace_value) + max_vector[d] = max(max_vector[d], trace_value) + mean_vector[d] += trace_value64 + var_vector[d] += trace_value64 ** 2 + + # Update matrices + min_matrix[i, x] = min(min_matrix[i, x], trace_value) + max_matrix[i, x] = max(max_matrix[i, x], trace_value) + mean_matrix[i, x] += trace_value64 + var_matrix[i, x] += trace_value64 ** 2 + + # Finalize vectors + area = shape[0] * shape[1] + mean_vector /= area + var_vector /= area + var_vector -= mean_vector ** 2 + + # Finalize matrices + mean_matrix /= shape[2] + var_matrix /= shape[2] + var_matrix -= mean_matrix ** 2 + + return (min_vector, max_vector, mean_vector, var_vector, + min_matrix, max_matrix, mean_matrix, var_matrix) + +@njit +def get_line_coordinates(start, stop): + """ Get float coordinates of traces for line from `start` to `stop`. + + Parameters + ---------- + start : numpy.ndarray + + stop : numpy.ndarray + + Returns + ------- + locations : numpy.ndarray + array of shape (N, 2) and dtype float32 with coordinates for section traces. + """ + direction = stop - start + distance = np.power(direction, 2).sum() ** 0.5 + locations = np.empty((int(np.ceil(distance)) + 1, 2), dtype=np.float32) + for i in [0, 1]: + locations[:, i] = np.linspace(start[i], stop[i], int(np.ceil(distance)) + 1) + return locations + +@njit +def get_line_support(locations): + """ Get support for non-integer locations. + + Parameters + ---------- + locations : numpy.ndarray + array of shape (N, 2) and dtype float32 + + Returns + ------- + support, weights : tuple with two elements + + support : numpy.ndarray + array of shape (N, 4, 2) and dtype int32 with coordinates of support traces for each location. + weights : numpy.ndarray + array of shape (N, 4) with weights for support traces for interpolation. If some location has integer + coordinates, support will have duplicated traces and nan weights. + """ + ceil, floor = np.ceil(locations), np.floor(locations) + support = np.empty((len(locations), 4, 2), dtype='int32') + support[:, 0] = floor + support[:, 1, 0] = floor[:, 0] + support[:, 1, 1] = ceil[:, 1] + support[:, 2, 0] = ceil[:, 0] + support[:, 2, 1] = floor[:, 1] + support[:, 3] = ceil + + distances = ((support - np.expand_dims(locations, 1)) ** 2).sum(axis=-1) ** 0.5 + weights = 1 / distances + weights = weights / np.expand_dims(weights.sum(axis=-1), 1) + + return support, weights + +@njit(parallel=True) +def interpolate(traces, traces_indices, weights, dtype='float32'): + """ Interpolate traces with float coordinates by traces from support. + + Parameters + ---------- + traces : numpy.ndarray + array of shape (M, geometry.shape[2]) with loaded traces from support. + traces_indices : numpy.ndarray + array of shape (N, 4) with indices of corresponging traces in `traces` for each support trace. + weights : numpy.ndarray + array of shape (N, 4) with weights for support traces for interpolation. If some location has integer + coordinates, support will have duplicated traces and nan weights. + dtype : str, optional + resulting dtype, by default 'float32' + + Returns + ------- + numpy.ndarray + array of shape (N, geometry.shape[2]) + """ + image = np.empty((len(traces_indices), traces.shape[1]), dtype=dtype) + for i in prange(len(traces_indices)): + trace_weights = weights[i] + image[i] = traces[traces_indices[i][0]] + if not np.isnan(trace_weights[0]): + image[i] *= trace_weights[0] + for j in range(1, 4): + image[i] += traces[traces_indices[i][j]] * trace_weights[j] + return image diff --git a/seismiqb/geometry/segyio_loader.py b/seismiqb/geometry/segyio_loader.py new file mode 100644 index 0000000..1f61149 --- /dev/null +++ b/seismiqb/geometry/segyio_loader.py @@ -0,0 +1,280 @@ +""" A thin wrapper around `segyio` for convenient loading of seismic traces. """ +import numpy as np +import pandas as pd + +import segyio + + + +class SegyioLoader: + """ A thin wrapper around `segyio` library for convenient loading of headers and traces. + + Most of the methods directly call public API of `segyio`. + For trace loading we use private methods and attributes of `segyio.SegyFile`, which allow: + - reading data into pre-defined buffer + - read only parts of the trace. + This gives up to 50% speed-up over public API for the scenario of loading sequence of traces, + and up to 15% over public API in case of loading full lines (inlines or crosslines). + """ + TRACE_HEADER_SIZE = 240 + + SEGY_FORMAT_TO_TRACE_DATA_DTYPE = { + 1: "u1", # IBM 4-byte float: has to be manually transformed to an IEEE float32 + 2: "i4", + 3: "i2", + 5: "f4", + 6: "f8", + 8: "i1", + 9: "i8", + 10: "u4", + 11: "u2", + 12: "u8", + 16: "u1", + } + + ENDIANNESS_TO_SYMBOL = { + "big": ">", + "msb": ">", + + "little": "<", + "lsb": "<", + } + + def __init__(self, path, endian='big', strict=False, ignore_geometry=True): + # Parse arguments for errors + if endian not in self.ENDIANNESS_TO_SYMBOL: + raise ValueError(f'Unknown endian {endian}, must be one of {self.ENDIANNESS_TO_SYMBOL}') + + # Store arguments + self.path = path + self.endian = endian + + # Open SEG-Y file + self.file_handler = segyio.open(path, mode='r', endian=endian, + strict=strict, ignore_geometry=ignore_geometry) + self.file_handler.mmap() + + # Number of traces and depth + self.n_samples = self.file_handler.trace.shape + self.n_traces = self.file_handler.trace.length + self.dtype = self.file_handler.dtype + + # Sample interval, rate and delay + self.sample_interval = self._infer_sample_interval() # ms + self.sample_rate = 1000 / self.sample_interval # Hz + self.samples = np.arange(self.n_samples) * self.sample_interval + self.delay = self.file_handler.header[0].get(segyio.TraceField.DelayRecordingTime) + + # Misc + self.metrics = self.file_handler.xfd.metrics() + self.text = [self.file_handler.text[i] for i in range(1 + self.file_handler.ext_headers)] + + + def _infer_sample_interval(self): + """ Get sample interval from file headers. """ + bin_sample_interval = self.file_handler.bin[segyio.BinField.Interval] + trace_sample_interval = self.file_handler.header[0][segyio.TraceField.TRACE_SAMPLE_INTERVAL] + # 0 means undefined sample interval, so it is removed from the set + union_sample_interval = {bin_sample_interval, trace_sample_interval} - {0} + + if len(union_sample_interval) != 1: + raise ValueError("Cannot infer sample interval from file headers: " + "either both `Interval` (bytes 3217-3218 in the binary header) " + "and `TRACE_SAMPLE_INTERVAL` (bytes 117-118 in the header of the first trace) " + "are undefined or they have different values.") + return union_sample_interval.pop() / 1000 # convert from seconds to milliseconds + + + # Headers + def headers_to_bytes(self, headers): + """ Compute the byte location of a header. """ + return [getattr(segyio.TraceField, header) for header in headers] + + def load_headers(self, headers, reconstruct_tsf=True, **kwargs): + """ Load requested trace headers from a SEG-Y file for each trace into a dataframe. + If needed, we reconstruct the `'TRACE_SEQUENCE_FILE'` manually be re-indexing traces. + + Each header is loaded separately, requiring repeated reads from the file. + + Parameters + ---------- + headers : sequence + Names of headers to load. + reconstruct_tsf : bool + Whether to reconstruct `TRACE_SEQUENCE_FILE` manually. + """ + _ = kwargs + if reconstruct_tsf and 'TRACE_SEQUENCE_FILE' in headers: + headers = list(headers) + headers.remove('TRACE_SEQUENCE_FILE') + + dataframe = {} + for header in headers: + dataframe[header] = self.load_header(header) + if reconstruct_tsf: + dataframe['TRACE_SEQUENCE_FILE'] = self.make_tsf_header() + + dataframe = pd.DataFrame(dataframe) + return dataframe + + def load_header(self, header): + """ Read one header from the file. """ + return self.file_handler.attributes(getattr(segyio.TraceField, header))[:] + + def make_tsf_header(self): + """ Reconstruct the `TRACE_SEQUENCE_FILE` header. """ + dtype = np.int32 if self.n_traces < np.iinfo(np.int32).max else np.int64 + return np.arange(1, self.n_traces + 1, dtype=dtype) + + + # Data loading: traces + def load_traces(self, indices, limits=None, buffer=None): + """ Load traces by their indices. + By pre-allocating memory for all of the requested traces, we significantly speed up the process. + + Parameters + ---------- + indices : sequence + Indices (TRACE_SEQUENCE_FILE) of the traces to read. + limits : sequence of ints, slice, optional + Slice of the data along the depth axis. + buffer : np.ndarray, optional + Buffer to read the data into. If possible, avoids copies. + """ + limits = self.process_limits(limits) + samples = self.samples[limits] + n_samples = len(samples) + + if buffer is None: + buffer = np.empty((len(indices), n_samples), dtype=self.dtype) + + for i, index in enumerate(indices): + self.load_trace(index=index, buffer=buffer[i], limits=limits) + return buffer + + def process_limits(self, limits): + """ Convert given `limits` to a `slice`. """ + if limits is None: + return slice(0, self.n_samples, 1) + if isinstance(limits, (tuple, list)): + limits = slice(*limits) + + # Use .indices to avoid negative slicing range + indices = limits.indices(self.n_samples) + if indices[-1] < 0: + raise ValueError('Negative step is not allowed.') + if indices[1] <= indices[0]: + raise ValueError('Empty traces after setting limits.') + return slice(*indices) + + def load_trace(self, index, buffer, limits): + """ Load one trace into buffer. """ + self.file_handler.xfd.gettr(buffer, index, 1, 1, + limits.start, limits.stop, limits.step, + buffer.size) + + # Data loading: depth slices + def load_depth_slices(self, indices, buffer=None): + """ Load horizontal (depth) slices of the data. + Requires a ~full sweep through SEG-Y, therefore is slow. + + Parameters + ---------- + indices : sequence + Indices (ordinals) of the depth slices to read. + buffer : np.ndarray, optional + Buffer to read the data into. If possible, avoids copies. + """ + if buffer is None: + buffer = np.empty((len(indices), self.n_traces), dtype=self.dtype) + + for i, index in enumerate(indices): + self.load_depth_slice(index=index, buffer=buffer[i]) + return buffer + + def load_depth_slice(self, index, buffer): + """ Load one depth slice into buffer. """ + self.file_handler.xfd.getdepth(index, buffer.size, 1, buffer) + + + # Convenience and utility methods + def make_chunk_iterator(self, chunk_size=None, n_chunks=None, limits=None, buffer=None): + """ Create on iterator over the entire file traces in chunks. + + Each chunk contains no more than `chunk_size` traces. + If `chunk_size` is not provided and `n_chunks` is given instead, there are no more than `n_chunks` chunks. + One and only one of `chunk_size` and `n_chunks` should be provided. + + Each element in the iterator is a dictionary with `'data'`, `'start'` and `'end'` keys. + + Parameters + ---------- + chunk_size : int, optional + Maximum size of the chunk. + n_chunks : int, optional + Maximum number of chunks. + limits : sequence of ints, slice, optional + Slice of the data along the depth (last) axis. Passed directly to :meth:`load_traces`. + buffer : np.ndarray, optional + Buffer to read the data into. If possible, avoids copies. Passed directly to :meth:`load_traces`. + + Returns + ------- + iterator, info : tuple with two elements + + iterator : iterable + An iterator over the entire SEG-Y traces. + Each element in the iterator is a dictionary with `'data'`, `'start'` and `'end'` keys. + info : dict + Description of the iterator with `'chunk_size'`, `'n_chunks'`, `'chunk_starts'` and `'chunk_ends'` keys. + """ + # Parse input parameters + if chunk_size is None and n_chunks is None: + raise ValueError('Either `chunk_size` or `n_chunks` should be provided!') + if chunk_size is not None and n_chunks is not None: + raise ValueError('Only one of `chunk_size` and `n_chunks` should be provided!') + + if n_chunks is not None: + chunk_size = self.n_traces // n_chunks + + # Define start and end for each chunk + n_chunks, last_chunk_size = divmod(self.n_traces, chunk_size) + chunk_sizes = [chunk_size] * n_chunks + if last_chunk_size: + n_chunks += 1 + chunk_sizes += [last_chunk_size] + + chunk_starts = np.cumsum([0] + chunk_sizes[:-1]) + chunk_ends = np.cumsum(chunk_sizes) + + # Prepare iterator + iterator = ({'data': self.load_traces(list(range(start, end)), limits=limits, buffer=buffer), + 'start': start, 'end': end} for start, end in zip(chunk_starts, chunk_ends)) + info = { + 'chunk_size': chunk_size, + 'n_chunks': n_chunks, + 'chunk_starts': chunk_starts, + 'chunk_ends': chunk_ends + } + return iterator, info + + def chunk_iterator(self, chunk_size=None, n_chunks=None, limits=None, buffer=None): + """ A shorthand for :meth:`make_chunk_iterator` with no info returned. """ + return self.make_chunk_iterator(chunk_size=chunk_size, n_chunks=n_chunks, + limits=limits, buffer=buffer)[0] + + +class SafeSegyioLoader(SegyioLoader): + """ A thin wrapper around `segyio` library for convenient loading of headers and traces. + + Unlike :class:`SegyioLoader`, uses only public APIs to load traces. + + Used mainly for performance measurements. + """ + def load_trace(self, index, buffer, limits): + """ Load one trace into buffer. """ + buffer[:] = self.file_handler.trace.raw[index][limits] + + def load_depth_slice(self, index, buffer): + """ Load one depth slice into buffer. """ + buffer[:] = self.file_handler.depth_slice[index] diff --git a/seismiqb/geometry/utils.py b/seismiqb/geometry/utils.py new file mode 100644 index 0000000..b820ccb --- /dev/null +++ b/seismiqb/geometry/utils.py @@ -0,0 +1,10 @@ +""" Useful functions, related to geometry. """ + + +def time_to_sample(time, geometry): + """ Convert time (in ms) into geometry sample value. """ + return round((time - geometry.delay) / geometry.sample_interval) + +def sample_to_time(sample, geometry): + """ Convert geometry sample value into time. """ + return round(sample * geometry.sample_interval + geometry.delay) diff --git a/seismiqb/grids.py b/seismiqb/grids.py new file mode 100644 index 0000000..5f43939 --- /dev/null +++ b/seismiqb/grids.py @@ -0,0 +1,852 @@ +""" Generator of predetermined locations based on field or current state of labeled surface. Mainly used for inference. + +Locations describe the cube and the exact place to load from in the following format: +(field_id, label_id, orientation, i_start, x_start, d_start, i_stop, x_stop, d_stop). + +Locations are passed to `make_locations` method of `SeismicCropBatch`, which +transforms them into 3D slices to index the data and other useful info like origin points, shapes and orientation. + +Each of the classes provides: + - `call` method (aliased to either `sample` or `next_batch`), that generates given amount of locations + - `to_names` method to convert the first two columns of sampled locations into string names of field and label + - convenient visualization to explore underlying `locations` structure +""" +import numpy as np +from numba import njit + +from .utils import make_ranges + + + +class BaseGrid: + """ Deterministic generator of crop locations. """ + def __init__(self, crop_shape=None, batch_size=64, + locations=None, orientation=None, origin=None, endpoint=None, field=None, label_name='unknown', + **kwargs): + self._iterator = None + self.crop_shape = np.array(crop_shape) + self.batch_size = batch_size + + if locations is None: + self._make_locations() + else: + self.locations = locations + self.orientation = orientation + self.origin = origin + self.endpoint = endpoint + self.ranges = np.array([origin, endpoint]).T + self.shape = endpoint - origin + self.field = field + self.field_name = field.short_name + self.label_name = label_name + + def _make_locations(self): + raise NotImplementedError('Must be implemented in sub-classes') + + def to_names(self, id_array): + """ Convert the first two columns of sampled locations into field and label string names. """ + return np.array([(self.field_name, self.label_name) for ids in id_array]) + + # Iteration protocol + @property + def iterator(self): + """ Iterator that generates batches of locations. """ + if self._iterator is None: + self._iterator = self.make_iterator() + return self._iterator + + def make_iterator(self): + """ Iterator that generates batches of locations. """ + return (self.locations[i:i+self.batch_size] for i in range(0, len(self), self.batch_size)) + + def __call__(self, batch_size=None): + _ = batch_size + return next(self.iterator) + + def next_batch(self, batch_size=None): + """ Yield the next batch of locations. """ + _ = batch_size + return next(self.iterator) + + def __len__(self): + """ Total number of locations to be generated. """ + return len(self.locations) + + @property + def length(self): + """ Total number of locations to be generated. """ + return len(self.locations) + + @property + def n_iters(self): + """ Total number of iterations. """ + return np.ceil(len(self) / self.batch_size).astype(np.int32) + + # Concatenate multiple grids into one + def join(self, other): + """ Update locations of a current grid with locations from other instance of BaseGrid. """ + if not isinstance(other, BaseGrid): + raise TypeError('Other should be an instance of `BaseGrid`') + if self.field_name != other.field_name: + raise ValueError('Grids should be for the same field!') + + locations = np.concatenate([self.locations, other.locations], axis=0) + locations = np.unique(locations, axis=0) + batch_size = min(self.batch_size, other.batch_size) + + if self.orientation == other.orientation: + orientation = self.orientation + else: + orientation = 2 + + self_origin = self.origin if isinstance(self, RegularGrid) else self.actual_origin + other_origin = other.origin if isinstance(other, RegularGrid) else other.actual_origin + origin = np.minimum(self_origin, other_origin) + + self_endpoint = self.endpoint if isinstance(self, RegularGrid) else self.actual_endpoint + other_endpoint = other.endpoint if isinstance(other, RegularGrid) else other.actual_endpoint + endpoint = np.maximum(self_endpoint, other_endpoint) + + label_name = other.label_name if isinstance(other, ExtensionGrid) else self.label_name + + return BaseGrid(locations=locations, batch_size=batch_size, orientation=orientation, + origin=origin, endpoint=endpoint, field=self.field, label_name=label_name) + + def __add__(self, other): + return self.join(other) + + def __and__(self, other): + return self.join(other) + + + # Useful info + def __repr__(self): + return f'' + + @property + def original_crop_shape(self): + """ Original crop shape. """ + return self.crop_shape if self.orientation == 0 else self.crop_shape[[1, 0, 2]] + + @property + def actual_origin(self): + """ The upper leftmost point of all locations. """ + return self.locations[:, [3, 4, 5]].min(axis=0).astype(np.int32) + + @property + def actual_endpoint(self): + """ The lower rightmost point of all locations. """ + return self.locations[:, [6, 7, 8]].max(axis=0).astype(np.int32) + + @property + def actual_shape(self): + """ Shape of the covered by the grid locations. """ + return self.endpoint - self.origin + + @property + def actual_ranges(self): + """ Ranges of covered by the grid locations. """ + return np.array(tuple(zip(self.origin, self.endpoint))) + + def show(self, grid=True, markers=False, n_patches=None, **kwargs): + """ Display the grid over field overlay. + + Parameters + ---------- + grid : bool + Whether to show grid lines. + markers : bool + Whether to show markers at location origins. + n_patches : int + Number of locations to display with overlayed mask. + kwargs : dict + Other parameters to pass to the plotting function. + """ + n_patches = n_patches or int(np.sqrt(len(self))) // 5 + plotter = self.field.geometry.show('dead_traces_matrix', cmap='Gray', colorbar=False, **kwargs) + ax = plotter[0].ax + + if grid: + spatial = self.locations[:, [3, 4]] + for i in np.unique(spatial[:, 0]): + sliced = spatial[spatial[:, 0] == i][:, 1] + ax.vlines(i, sliced.min(), sliced.max(), colors='pink') + + spatial = self.locations[:, [3, 4]] + for x in np.unique(spatial[:, 1]): + sliced = spatial[spatial[:, 1] == x][:, 0] + ax.hlines(x, sliced.min(), sliced.max(), colors='pink') + + if markers: + ax.scatter(self.locations[:, 3], self.locations[:, 3], marker='x', linewidth=0.1, color='r') + + overlay = np.zeros_like(self.field.dead_traces_matrix) + for n in range(0, len(self), len(self)//n_patches - 1): + slc = tuple(slice(o, e) for o, e in zip(self.locations[n, [3, 4]], self.locations[n, [6, 7]])) + overlay[slc] = 1 + ax.scatter(*self.locations[n, [3, 4]], marker='x', linewidth=3, color='g') + + kwargs = { + 'cmap': 'green', + 'alpha': 0.3, + 'colorbar': False, + 'matrix_name': 'Grid visualization', + 'ax': ax, + **kwargs, + } + self.field.geometry.show(overlay, **kwargs) + + + def to_chunks(self, size, overlap=0.05, orientation=None): + """ Split the current grid into chunks along `orientation` axis. + + Parameters + ---------- + size : int + Length of one chunk along the splitting axis. + overlap : number + If integer, then number of slices for overlapping between consecutive chunks. + If float, then proportion of `size` to overlap between consecutive chunks. + + Returns + ------- + iterator with instances of `RegularGrid`. + """ + if orientation is None: + if self.orientation != 2: + orientation = self.orientation + + if not isinstance(size, (tuple, list)): + size_ = [None, None, None] + + if orientation is not None: + orientation = self.field.geometry.parse_axis(orientation) + size_[orientation] = size + else: + size_ = size + + if not isinstance(overlap, (tuple, list)): + overlap = [overlap, overlap, overlap] + return RegularGridChunksIterator(grid=self, size=size_, overlap=overlap) + + +class RegularGrid(BaseGrid): + """ Regular grid over the selected `ranges` of cube, covering it with overlapping locations. + Filters locations with less than `threshold` meaningful traces. + + Parameters + ---------- + field : Field + Field to create grid for. + ranges : sequence + Nested sequence, where each element is either None or sequence of two ints. + Defines ranges to create grid for inline, crossline and depths. + crop_shape : sequence + Shape of crop locations to generate. + orientation : int + Either 0 or 1. Defines orientation of a grid. Used in `locations` directly. + threshold : number + Minimum amount of non-dead traces in a crop to keep it in locations. + If number in 0 to 1 range, then used as percentage. + strides : sequence, optional + Strides between consecutive crops. Only one of `strides`, `overlap` or `overlap_factor` should be specified. + overlap : sequence, optional + Overlaps between consecutive crops. Only one of `strides`, `overlap` or `overlap_factor` should be specified. + overlap_factor : sequence, optional + Ratio of overlap between consecutive crops. + Only one of `strides`, `overlap` or `overlap_factor` should be specified. + batch_size : int + Number of batches to generate on demand. + field_id, label_id : int + Used as the first two columns of sampled values. + label_name : str, optional + Name of the inferred label. + locations : np.array, optional + Pre-defined locations. If provided, then directly stored and used as the grid coordinates. + """ + def __init__(self, field, ranges, crop_shape, orientation=0, strides=None, overlap=None, overlap_factor=None, + filtering_matrix='dead_traces_matrix', threshold=0, batch_size=64, + field_id=-1, label_id=-1, label_name='unknown', locations=None, **kwargs): + # Make correct crop shape + orientation = field.geometry.parse_axis(orientation) + crop_shape = np.array(crop_shape) + crop_shape = crop_shape if orientation == 0 else crop_shape[[1, 0, 2]] + + if strides is not None: + strides = np.array(strides) + strides = strides if orientation == 0 else strides[[1, 0, 2]] + + # Make ranges + ranges = make_ranges(ranges, field.shape) + ranges = np.array(ranges) + self.ranges = ranges + + # Infer from `ranges` + self.origin = ranges[:, 0] + self.endpoint = ranges[:, 1] + self.shape = ranges[:, 1] - ranges[:, 0] + + # Make `strides` + if (strides is not None) + (overlap is not None) + (overlap_factor is not None) > 1: + raise ValueError('Only one of `strides`, `overlap` or `overlap_factor` should be specified!') + overlap_factor = [overlap_factor] * 3 if isinstance(overlap_factor, (int, float)) else overlap_factor + + if strides is not None: + strides = strides if isinstance(strides, (tuple, list, np.ndarray)) else [strides] * 3 + if np.issubdtype(np.array(strides).dtype, np.floating): + strides = np.array(crop_shape) * np.array(strides) + strides = np.maximum(strides, 1).astype(int) + else: + if overlap is not None: + strides = [c - o for c, o in zip(crop_shape, overlap)] + elif overlap_factor is not None: + strides = [max(1, c // f) for c, f in zip(crop_shape, overlap_factor)] + else: + strides = crop_shape + self.strides = np.array(strides) + + # Update threshold: minimum amount of non-empty traces + if isinstance(filtering_matrix, str): + filtering_matrix = getattr(field, filtering_matrix) + self.filtering_matrix = filtering_matrix + + if 0 < threshold < 1: + threshold = int(threshold * crop_shape[0] * crop_shape[1]) + self.threshold = threshold + + self.field_id = field_id + self.label_id = label_id + self.orientation = orientation + self.field = field + self.field_name = field.short_name + self.label_name = label_name + self.unfiltered_length = None + super().__init__(crop_shape=crop_shape, batch_size=batch_size, locations=locations, field=field, + orientation=self.orientation, origin=self.origin, endpoint=self.endpoint) + + @staticmethod + def _arange(start, stop, stride, limit): + grid = np.arange(start, stop, stride, dtype=np.int32) + grid = np.unique(np.clip(grid, 0, limit)) + return np.sort(grid) + + def _make_locations(self): + # Ranges for each axis + i_args, x_args, d_args = tuple(zip(self.ranges[:, 0], + self.ranges[:, 1], + self.strides, + self.field.shape - self.crop_shape)) + i_grid = self._arange(*i_args) + x_grid = self._arange(*x_args) + d_grid = self._arange(*d_args) + self.unfiltered_length = len(i_grid) * len(x_grid) * len(d_grid) + self._i_grid, self._x_grid, self._d_grid = i_grid, x_grid, d_grid + + # Create points: origins for each crop. Keep only those that produce crops with more than `threshold` points + order = (1, 2, 3, 0) if self.orientation == 0 else (2, 1, 3, 0) + points = np.array(np.meshgrid(i_grid, x_grid, d_grid, indexing='ij')).transpose(order).reshape(-1, 3) + + if self.filtering_matrix is not None: + points = filter_points(points, self.filtering_matrix, self.crop_shape, self.threshold) + + # Buffer: (cube_id, i_start, x_start, d_start, i_stop, x_stop, d_stop) + buffer = np.empty((len(points), 9), dtype=np.int32) + buffer[:, 0] = self.field_id + buffer[:, 1] = self.label_id + buffer[:, 2] = self.orientation + buffer[:, [3, 4, 5]] = points + buffer[:, [6, 7, 8]] = points + buffer[:, [6, 7, 8]] += self.crop_shape + self.locations = buffer + + def __repr__(self): + return f'' + + +@njit +def filter_points(points, filtering_matrix, crop_shape, threshold): + """ Remove locations covering less than `threshold` of present traces. """ + mask = np.ones(len(points), dtype=np.bool_) + + for j, (i, x, _) in enumerate(points): + sliced = filtering_matrix[i:i+crop_shape[0], x:x+crop_shape[1]] + n_alive_traces = sliced.size - sliced.sum() + if n_alive_traces <= threshold: + mask[j] = False + return points[mask] + + +class RegularGridChunksIterator: + """ Split regular grid into chunks along `orientation` axis. Supposed to be iterated over. + + Parameters + ---------- + grid : BaseGrid + Grid to split into chunks. + size : int or None or tuple of two ints or Nones + Length of chunks along corresponding axes. `None` indicates that there is no chunking along the axis. + overlap : number + If integer, then number of slices for overlapping between consecutive chunks. + If float, then proportion of `size` to overlap between consecutive chunks. + """ + def __init__(self, grid, size, overlap): + self.grid = grid + + size_i, size_x, size_d = size + overlap_i, overlap_x, overlap_d = overlap + + if size_i is not None: + step_i = int(size_i*(1 - overlap_i)) if np.issubdtype(type(overlap_i), np.floating) else size_i - overlap_i + else: + step_i = size_i = self.grid.shape[0] + + if size_x is not None: + step_x = int(size_x*(1 - overlap_x)) if np.issubdtype(type(overlap_x), np.floating) else size_x - overlap_x + else: + step_x = size_x = self.grid.shape[1] + + if size_d is not None: + step_d = int(size_d*(1 - overlap_d)) if np.issubdtype(type(overlap_d), np.floating) else size_d - overlap_d + else: + step_d = size_d = self.grid.shape[2] + + self.size_i, self.size_x, self.size_d = size_i, size_x, size_d + self.step_i, self.step_x, self.step_d = step_i, step_x, step_d + + self._iterator = None + + @property + def iterator(self): + """ Cached sequence of chunks. """ + # pylint: disable=protected-access + if self._iterator is None: + iterator = [] + grid = self.grid + + grid_i = RegularGrid._arange(*grid.ranges[0], self.step_i, max(0, grid.endpoint[0] - self.size_i)) + grid_x = RegularGrid._arange(*grid.ranges[1], self.step_x, max(0, grid.endpoint[1] - self.size_x)) + grid_d = RegularGrid._arange(*grid.ranges[2], self.step_d, max(0, grid.endpoint[2] - self.size_d)) + + for start_i in grid_i: + stop_i = start_i + self.size_i + for start_x in grid_x: + stop_x = start_x + self.size_x + for start_d in grid_d: + stop_d = start_d + self.size_d + + chunk_origin = np.array([start_i, start_x, start_d]) + chunk_endpoint = np.array([stop_i, stop_x, stop_d]) + + # Filter points beyond chunk ranges along `orientation` axis + mask = ((grid.locations[:, 3] >= start_i) & + (grid.locations[:, 6] <= stop_i) & + (grid.locations[:, 4] >= start_x) & + (grid.locations[:, 7] <= stop_x) & + (grid.locations[:, 5] >= start_d) & + (grid.locations[:, 8] <= stop_d)) + chunk_locations = grid.locations[mask] + + if len(chunk_locations): + chunk_grid = BaseGrid(field=grid.field, locations=chunk_locations, + origin=chunk_origin, endpoint=chunk_endpoint, + batch_size=grid.batch_size) + iterator.append(chunk_grid) + self._iterator = iterator + return self._iterator + + def __iter__(self): + for chunk_grid in self.iterator: + yield chunk_grid + + def __len__(self): + return len(self.iterator) + + +class ExtensionGrid(BaseGrid): + """ Generate locations to enlarge horizon from its boundaries both inwards and outwards. + + For each point on the boundary of a horizon, we test 4 possible directions and pick `top` best of them. + Each location is created so that the original point is `stride` units away from the left/right edge of a crop. + Only the locations that would potentially add more than `threshold` pixels remain. + + Refer to `_make_locations` method and comments for more info about inner workings. + + Parameters + ---------- + horizon : Horizon + Surface to extend. + crop_shape : sequence + Shape of crop locations to generate. Note that both iline and crossline orientations are used. + stride : int + Overlap with already known horizon for each location. + threshold : int + Minimum amount of potentially added pixels for each location. + randomize : bool + Whether to randomize the loop for computing the potential of each location. + batch_size : int + Number of batches to generate on demand. + mode : {'best_for_each_independent', 'up', 'down', 'left', 'right', + 'vertical', 'horizontal', 'best_for_all', 'best_for_each'} + Mode for directions of locations to generate. + If mode is 'up', 'down', 'left' or 'right', then use only that direction. + If 'vertical' ('horizontal'), then use up and down (right and left) directions. + + If 'best_for_all', then select one direction for all points, based on total potentially added points. + + If 'best_for_each', then select direction for each point individually, based on total potentially added points. + The potential of locations is computed sequentially: if one of the previous locations already covers area, + it is considered to covered for all of the next potentials. + + If 'best_for_each_independent', then select direction for each point individually, based on total potentially + added points. The potential of locations is computed independently of other locations. + + top : int + Number of the best directions to keep for each point. Relevant only in `best_*` modes. + """ + def __init__(self, horizon, crop_shape, stride=16, batch_size=64, + top=1, threshold=4, prior_threshold=8, randomize=True, mode='best_for_each', **kwargs): + self.top = top + self.stride = stride + self.threshold = threshold + self.prior_threshold = prior_threshold + self.randomize = randomize + self.mode = mode + + self.horizon = horizon + self.field = horizon.field + self.field_name = horizon.field.short_name + self.label_name = horizon.short_name + + self.uncovered_before = None + self.locations_stats = {} + + allowed_directions = ['up', 'down', 'left', 'right'] + + if self.mode in ['best_for_all', 'best_for_each', 'best_for_each_independent']: + self.directions = allowed_directions + elif self.mode in allowed_directions: + self.directions = [self.mode] + elif self.mode == 'vertical': + self.directions = ['up', 'down'] + elif self.mode == 'horizontal': + self.directions = ['left', 'right'] + else: + raise ValueError('Provided wrong `mode` argument, for possible options look at the docstring.') + + super().__init__(crop_shape=crop_shape, batch_size=batch_size) + + + def _make_locations(self): + # Get border points (N, 3) + # Create locations for all four possible directions, stack into (4*N, 6) + # Compute potential added area for each of the locations, while also updating coverage matrix + # For each point, keep `top` of the best (potentially add more points) locations + # Keep only those locations that potentially add more than `threshold` points + #pylint: disable=too-many-statements + + crop_shape = self.crop_shape + crop_shape_t = crop_shape[[1, 0, 2]] + + # True where dead trace / already covered + coverage_matrix = self.field.dead_traces_matrix.copy().astype(np.bool_) + coverage_matrix[self.horizon.full_matrix > 0] = True + self.uncovered_before = coverage_matrix.size - coverage_matrix.sum() + + # Compute boundary points of horizon: both inner and outer borders + border_points = np.stack(np.where(self.horizon.boundaries_matrix), axis=-1) + depths = self.horizon.matrix[border_points[:, 0], border_points[:, 1]] + + # Shift depths up + border_points += (self.horizon.i_min, self.horizon.x_min) + depths -= crop_shape[2] // 2 + + # Buffer for locations (orientation, i_start, x_start, d_start, i_stop, x_stop, d_stop). + buffer = np.empty((len(border_points), 7), dtype=np.int32) + buffer[:, 0] = 0 + buffer[:, [1, 2]] = border_points + buffer[:, 3] = depths + buffer[:, [4, 5]] = border_points + buffer[:, 6] = depths + + # Repeat the same data along new 0-th axis: shift origins/endpoints + n_directions = len(self.directions) + buffer = np.repeat(buffer[np.newaxis, ...], n_directions, axis=0) + directions_iterator = 0 + + if 'up' in self.directions: + # Crops with fixed INLINE, moving CROSSLINE: [-stride:-stride + shape] + buffer[directions_iterator, :, [2, 5]] -= self.stride + + np.clip(buffer[directions_iterator, :, 2], 0, self.field.shape[1], + out=buffer[directions_iterator, :, 2]) + np.clip(buffer[directions_iterator, :, 5], 0, self.field.shape[1], + out=buffer[directions_iterator, :, 5]) + + buffer[directions_iterator, :, [4, 5, 6]] += crop_shape.reshape(-1, 1) + directions_iterator += 1 + + if 'down' in self.directions: + # Crops with fixed INLINE, moving CROSSLINE: [-shape + stride:+stride] + buffer[directions_iterator, :, [2, 5]] -= (crop_shape[1] - self.stride) + + np.clip(buffer[directions_iterator, :, 2], 0, self.field.shape[1] - crop_shape[1], + out=buffer[directions_iterator, :, 2]) + np.clip(buffer[directions_iterator, :, 5], 0, self.field.shape[1] - crop_shape[1], + out=buffer[directions_iterator, :, 5]) + + buffer[directions_iterator, :, [4, 5, 6]] += crop_shape.reshape(-1, 1) + directions_iterator += 1 + + if 'left' in self.directions: + # Crops with fixed CROSSLINE, moving INLINE: [-stride:-stride + shape] + buffer[directions_iterator, :, [1, 4]] -= self.stride + + np.clip(buffer[directions_iterator, :, 1], 0, self.field.shape[0], + out=buffer[directions_iterator, :, 1]) + np.clip(buffer[directions_iterator, :, 4], 0, self.field.shape[0], + out=buffer[directions_iterator, :, 4]) + + buffer[directions_iterator, :, [4, 5, 6]] += crop_shape_t.reshape(-1, 1) + buffer[directions_iterator, :, 0] = 1 + directions_iterator += 1 + + if 'right' in self.directions: + # Crops with fixed CROSSLINE, moving INLINE: [-shape + stride:+stride] + buffer[directions_iterator, :, [1, 4]] -= (crop_shape[1] - self.stride) + + np.clip(buffer[directions_iterator, :, 1], 0, self.field.shape[0] - crop_shape[1], + out=buffer[directions_iterator, :, 1]) + np.clip(buffer[directions_iterator, :, 4], 0, self.field.shape[0] - crop_shape[1], + out=buffer[directions_iterator, :, 4]) + + buffer[directions_iterator, :, [4, 5, 6]] += crop_shape_t.reshape(-1, 1) + buffer[directions_iterator, :, 0] = 1 + directions_iterator += 1 + + update_coverage_matrix = self.mode not in ['best_for_all', 'best_for_each_independent'] + if self.randomize and update_coverage_matrix: + buffer = buffer[np.random.permutation(n_directions)] + + # Array with locations for each of the directions + # Each 4 consecutive rows are location variants for each point on the boundary + buffer = buffer.transpose((1, 0, 2)).reshape(-1, 7) + self.locations_stats['possible'] = buffer.shape[0] + + # Compute potential addition for each location + # for 'best_for_all' and 'best_for_each_independent' modes potential calculated independently + potential = compute_potential(locations=buffer, coverage_matrix=coverage_matrix, + shape=crop_shape, stride=self.stride, prior_threshold=self.prior_threshold, + update_coverage_matrix=update_coverage_matrix) + + if self.mode in ['best_for_each', 'best_for_each_independent']: + # For each trace get the most potential direction index + # Get argsort for each group of four + argsort = potential.reshape(-1, n_directions).argsort(axis=-1)[:, -self.top:].reshape(-1) + + # Shift argsorts to original indices + shifts = np.repeat(np.arange(0, len(buffer), n_directions, dtype=np.int32), self.top) + indices = argsort + shifts + + elif self.mode == 'best_for_all': + # Get indices of locations corresponding to the best direction + # The best direction is a direction ('left', 'right', 'up' or 'down') with maximal potentially added traces + positive_potential = potential.copy() + positive_potential[positive_potential < 0] = 0 + + best_direction_idx = np.argmax(positive_potential.reshape(-1, n_directions).sum(axis=0)) + indices = range(best_direction_idx, len(buffer), n_directions) + + else: + indices = slice(None) + + # Keep only top locations; remove locations with too small potential if needed + potential = potential[indices] + buffer = buffer[indices, :] + + # Drop locations duplicates + buffer, unique_locations_indices = np.unique(buffer, axis=0, return_index=True) + potential = potential[unique_locations_indices] + + self.locations_stats['top_locations'] = buffer.shape[0] + + mask = potential > self.threshold + buffer = buffer[mask] + potential = potential[mask] + self.locations_stats['selected'] = buffer.shape[0] + + # Correct the depth + np.clip(buffer[:, 3], 0, self.field.depth - crop_shape[2], out=buffer[:, 3]) + np.clip(buffer[:, 6], 0 + crop_shape[2], self.field.depth, out=buffer[:, 6]) + + locations = np.empty((len(buffer), 9), dtype=np.int32) + locations[:, [0, 1]] = -1 + locations[:, 2:9] = buffer + self.locations = locations + self.potential = potential.reshape(-1, 1) + + if update_coverage_matrix: + self.uncovered_best = coverage_matrix.size - coverage_matrix.sum() + else: + # In the 'best_for_all' and 'best_for_each_independent' we don't update the `coverage_matrix`` + self.uncovered_best = self.uncovered_after + + + @property + def uncovered_after(self): + """ Number of points not covered in the horizon, if all of the locations would + add their maximum potential amount of pixels to the labeling. + """ + coverage_matrix = self.field.dead_traces_matrix.copy().astype(np.bool_) + coverage_matrix[self.horizon.full_matrix > 0] = True + + for (i_start, x_start, _, i_stop, x_stop, _) in self.locations[:, 3:]: + coverage_matrix[i_start:i_stop, x_start:x_stop] = True + return coverage_matrix.size - coverage_matrix.sum() + + def show(self, markers=False, overlay=True, frequency=1, **kwargs): + """ Display the grid over horizon overlay. + + Parameters + ---------- + markers : bool + Whether to show markers at location origins. + overlay : bool + Whether to show overlayed mask for locations. + frequency : int + Frequency of shown overlayed masks. + kwargs : dict + Other parameters to pass to the plotting function. + """ + hm = self.horizon.full_matrix.astype(np.float32) + hm[hm < 0] = np.nan + plotter = self.field.geometry.show(hm, cmap='Depths', colorbar=False, **kwargs) + ax = plotter[0].ax + + self.field.geometry.show('dead_traces_matrix', ax=ax, cmap='Grey', colorbar=False, **kwargs) + + if markers: + ax.scatter(self.locations[:, 3], self.locations[:, 4], marker='x', linewidth=0.1, color='r') + + if overlay: + overlay = np.zeros_like(self.field.dead_traces_matrix) + for n in range(0, len(self), frequency): + slc = tuple(slice(o, e) for o, e in zip(self.locations[n, [3, 4]], self.locations[n, [6, 7]])) + overlay[slc] = 1 + + kwargs = { + 'cmap': 'blue', + 'alpha': 0.3, + 'colorbar': False, + 'title': f'Extension Grid on `{self.label_name}`', + 'ax': ax, + **kwargs, + } + self.field.geometry.show(overlay, **kwargs) + +@njit +def compute_potential(locations, coverage_matrix, shape, stride, prior_threshold, update_coverage_matrix=True): + """ For each location, compute the amount of points it would potentially add to the labeling. + If the shape of a location is not the same, as requested at grid initialization, we place `-1` value instead: + that is filtered out later. That is used to filter locations out of field bounds. + + For each location, we also check whether one of its sides (left/right/up/down) contains more + than `prior_threshold` covered points. + """ + area = shape[0] * shape[1] + buffer = np.empty((len(locations)), dtype=np.int32) + + for i, (orientation, i_start, x_start, _, i_stop, x_stop, _) in enumerate(locations): + sliced = coverage_matrix[i_start:i_stop, x_start:x_stop] + + if sliced.size == area: + + if orientation == 0: + left, right = sliced[:stride, :].sum(), sliced[:-stride, :].sum() + prior = max(left, right) + elif orientation == 1: + up, down = sliced[:, :stride].sum(), sliced[:, :-stride].sum() + prior = max(up, down) + + if prior >= prior_threshold: + covered = sliced.sum() + buffer[i] = area - covered + + if update_coverage_matrix: + coverage_matrix[i_start:i_stop, x_start:x_stop] = True + else: + buffer[i] = -1 + else: + buffer[i] = -1 + + return buffer + +class LocationsPotentialContainer: + """ Container for saving history of `ExtensionGrid`. + + It saves locations and their potential from each grid provided in the method `update_grid`. + Also, it removes repetitions from the grid locations and potentials. + """ + def __init__(self, locations=None, potential=None): + if locations is None: + locations = np.empty(shape=(0, 9), dtype=np.int32) + if potential is None: + potential = np.empty(shape=(0, 1), dtype=np.int32) + + ncols = locations.shape[1] + + self.initial_dtype = locations.dtype + self.locations_dtype = {'names': [f'col_{i}' for i in range(ncols)], + 'formats': ncols * [self.initial_dtype]} + + self.locations = locations.view(self.locations_dtype) + self.potential = potential + + self.stats = { + 'repeated_locations': [], + 'total_repeated_locations': 0 + } + + def update_grid(self, grid): + """ Update grid and container locations and potential. + + For the container, we update potentials for existing locations and safe new locations and their potentials. + For the grid, we remove locations and potentials pairs that are saved in the container. It helps reduce + locations amount and avoid repetitive locations processing such as model inference on these locations. + """ + # Choose locations and potential pairs that are not in the container + grid_locations = grid.locations.view(self.locations_dtype) + + repeated_locations = np.in1d(grid_locations, self.locations) + repeated_potential = np.in1d(grid.potential, self.potential) + repeated_locations_potential = repeated_locations & repeated_potential + + new_locations = grid_locations[~repeated_locations_potential] + new_potential = grid.potential[~repeated_locations_potential] + + # Safe stats + repeated_locations = len(grid_locations) - len(new_locations) + self.stats['repeated_locations'].append(repeated_locations) + self.stats['total_repeated_locations'] += repeated_locations + + # Update container: save new potentials for old locations and save new locations with their potential + if len(new_locations) > 0: + if len(self.locations) > 0: + repeated_locations_history = np.in1d(self.locations, new_locations) + locations = self.locations[~repeated_locations_history] + potential = self.potential[~repeated_locations_history] + + self.locations = np.vstack([locations, new_locations]) + self.potential = np.vstack([potential, new_potential]) + else: + self.locations = new_locations + self.potential = new_potential + + new_locations = new_locations.view(self.initial_dtype).reshape(-1, grid.locations.shape[1]) + else: + new_locations = np.empty(shape=(0, grid.locations.shape[1])) + new_potential = np.empty(shape=(0, 1)) + + # Update grid: set locations and grid with values that are not in the container + grid.locations, grid.potential = new_locations, new_potential diff --git a/seismiqb/labels/__init__.py b/seismiqb/labels/__init__.py new file mode 100644 index 0000000..cb5c57c --- /dev/null +++ b/seismiqb/labels/__init__.py @@ -0,0 +1,4 @@ +""" Labeled structures in a seismic volume. """ +from .horizon import Horizon, HorizonExtractor +from .fault import Fault, FaultExtractor, skeletonize +from .well import Well, MatchedWell diff --git a/seismiqb/labels/fault/__init__.py b/seismiqb/labels/fault/__init__.py new file mode 100644 index 0000000..b856c12 --- /dev/null +++ b/seismiqb/labels/fault/__init__.py @@ -0,0 +1,4 @@ +""" Labeled fault structures in a seismic volume. """ +from .base import Fault +from .postprocessing import skeletonize +from .surfaces_extractor import FaultExtractor diff --git a/seismiqb/labels/fault/approximation.py b/seismiqb/labels/fault/approximation.py new file mode 100644 index 0000000..d2db5f4 --- /dev/null +++ b/seismiqb/labels/fault/approximation.py @@ -0,0 +1,179 @@ +""" Approximation utilities to convert cloud of points to sticks. """ + +import numpy as np +from sklearn.decomposition import PCA +import cv2 +from numba import njit + +from .postprocessing import thin_line, split_array + + +def points_to_sticks(points, sticks_step=10, nodes_step='auto', fault_orientation=None, stick_orientation=2, + threshold=5, move_bounds=False): + """ Get sticks from fault which is represented as a cloud of points. + + Parameters + ---------- + points : np.ndarray + Fault points. + sticks_step : int + Number of slides between sticks. + nodes_step : int + Maximum distance between stick nodes + fault_orientation : int (0, 1 or 2) + Direction of the fault + stick_orientation : int (0, 1 or 2) + Direction of each stick + threshold : int + Threshold to remove nodes which are too close, by default 5. If nodes_step is int, real threshold will be equal + to `min(threshold, nodes_step // 2)`. + move_bounds : bool + Whether to extend fault by moving bound sticks to the nearest slide with index which is a multiple of + sticks_step. + + Returns + ------- + numpy.ndarray + Array of sticks. Each item of array is a stick: sequence of 3D points. + """ + if fault_orientation is None: + pca = PCA(1) + pca.fit(points) + fault_orientation = 0 if np.abs(pca.components_[0][0]) > np.abs(pca.components_[0][1]) else 1 + + if stick_orientation != 2: + fault_orientation = 2 + + points = points[np.argsort(points[:, fault_orientation])] + if len(points) == 0: + return [] + + slides = split_array(points, points[:, fault_orientation]) + + sticks = [] + + indices = [i for i, slide_points in enumerate(slides) if slide_points[0, fault_orientation] % sticks_step == 0] + + if move_bounds and 0 not in indices: + first_stick = slides[0] + first_stick[:, fault_orientation] = max( + 0, first_stick[0, fault_orientation] - (first_stick[0, fault_orientation] % sticks_step) + ) + + if move_bounds and len(slides)-1 not in indices: + last_stick = slides[-1] + shift = sticks_step - last_stick[0, fault_orientation] % sticks_step + if shift == sticks_step: + shift = 0 + last_stick[:, fault_orientation] = last_stick[0, fault_orientation] + shift + + indices = [0] + indices + [len(slides) - 1] + + indices = sorted(list(set(indices))) + + for idx in indices: + slide_points = slides[idx] + slide_points = slide_points[np.argsort(slide_points[:, stick_orientation])] + slide_points = thin_line(slide_points, stick_orientation) + if len(slide_points) > 5: + nodes = find_stick_nodes(points=slide_points, fault_orientation=fault_orientation, + stick_orientation=stick_orientation, nodes_step=nodes_step, + threshold=threshold).astype('float32') + + # Remove redundant nodes from sticks with the large number of nodes + if len(nodes) > 4 and nodes_step == 'auto': + normal = 3 - fault_orientation - stick_orientation + nodes = nodes[np.unique(remove_redundant_nodes(nodes[:, [normal, stick_orientation]]))] + else: + nodes = slide_points[[0, -1]] + if len(nodes) > 1: + sticks.append(nodes) + + return sticks + + +def find_stick_nodes(points, fault_orientation, stick_orientation, nodes_step='auto', threshold=5): + """ Get sticks from the line (with some width) defined by cloud of points + + Parameters + ---------- + points : numpy.ndarray + 3D points located on one 2D slide + fault_orientation : int (0, 1 or 2) + Direction of the fault + stick_orientation : int (0, 1 or 2) + Direction of each stick + nodes_step : int or 'auto' + The step between sequent nodes. If 'auto', the optimal number will be chosen. + threshold : int, optional + Threshold to remove nodes which are too close, by default 5. If nodes_step is int, real threshold will be equal + to `min(threshold, nodes_step // 2)`. + + Returns + ------- + numpy.ndarray + Stick nodes + """ + if len(points) <= 2: + return points + + if nodes_step != 'auto': + threshold = min(threshold, nodes_step // 2) + + normal = 3 - fault_orientation - stick_orientation + + mask = np.zeros(points.ptp(axis=0)[[normal, stick_orientation]] + 1) + mask[ + points[:, normal] - points[:, normal].min(), + points[:, stick_orientation] - points[:, stick_orientation].min() + ] = 1 + + if nodes_step == 'auto': + line_threshold = cv2.threshold(mask.astype(np.uint8) * 255, 127, 255, 0)[1] + line_contours = cv2.findContours(line_threshold, cv2.RETR_TREE, cv2.CHAIN_APPROX_TC89_KCOS)[0] + nodes = np.unique(np.squeeze(np.concatenate(line_contours)), axis=0) #TODO: unique? + nodes[:, 0] = nodes[:, 0] + points[:, stick_orientation].min() + nodes[:, 1] = nodes[:, 1] + points[:, normal].min() + else: + indices = list(range(0, len(points), nodes_step)) + if len(points) - 1 not in indices: + indices = indices + [len(points) - 1] + nodes = points[indices][:, [stick_orientation, normal]] + + new_points = np.zeros((len(nodes), 3)) + new_points[:, fault_orientation] = points[0, fault_orientation] + new_points[:, stick_orientation] = nodes[:, 0] + new_points[:, normal] = nodes[:, 1] + new_points = new_points[np.argsort(new_points[:, stick_orientation])] + + if threshold > 0: + # Remove nodes which are too close + mask = np.concatenate([[True], np.abs(new_points[2:] - new_points[1:-1]).sum(axis=1) > threshold, [True]]) + new_points = new_points[mask] + return new_points + +@njit +def node_deviation(start, end, point): + """ The distance (in 2D) between `point` and line from `start` to `end`. """ + return np.abs(point[0] - (point[1] - start[1]) / (end[1] - start[1]) * (end[0] - start[0]) - start[0]) + +@njit +def remove_redundant_nodes(nodes, threshold=1.5): + """ Remove unnecessary points from stick. """ + nodes_diff = np.ediff1d(nodes[:, 1]) + pos = np.argmax(np.minimum(nodes_diff[:-1], nodes_diff[1:]), axis=0) + 1 # node farthest from neighbors + filtered_nodes = [pos] + for direction in [-1, 1]: + current_pos = pos + pos_to_check = pos + direction + + while (pos_to_check + direction < len(nodes)) and (pos_to_check + direction >= 0): + if node_deviation(nodes[current_pos], nodes[pos_to_check + direction], nodes[pos_to_check]) > threshold: + filtered_nodes += [current_pos] + current_pos = pos_to_check + pos_to_check = current_pos + direction + else: + pos_to_check += direction + + filtered_nodes += [0, len(nodes)-1] + return filtered_nodes diff --git a/seismiqb/labels/fault/base.py b/seismiqb/labels/fault/base.py new file mode 100644 index 0000000..e74bf24 --- /dev/null +++ b/seismiqb/labels/fault/base.py @@ -0,0 +1,371 @@ +""" Fault class and processing methods. """ + +import os +import numpy as np +import pandas as pd + +from .triangulation import sticks_to_simplices, triangle_rasterization +from .approximation import points_to_sticks +from .visualization import FaultVisualizationMixin, get_fake_one_stick_fault +from .formats import FaultSticksMixin, FaultSerializationMixin +from ...utils import insert_points_into_mask, take_along_axis + +class Fault(FaultSticksMixin, FaultSerializationMixin, FaultVisualizationMixin): + """ Class to represent Fault object. + + Initialized from `storage` and `field`, where storage can be one of: + - csv-like file in FAULT_STICKS format. + - npy file with ndarray of (N, 3) shape or array itself. + - npz file with 'points', 'nodes', 'simplices' and 'sticks' or dict with the same keys. + + Each fault has 3 representations: + - points : cloud of surface points. The most accurate way to define surface but + not so handy for manual editing and occupies the most memory. Is needed + to create masks. + - sticks : polylines that approximate fault surface. Usually are placed on a sequence + of ilines or crosslines. The most common result of the experts labeling but + is not enough flexible. + - nodes and simplices : approximation of the surface by triangulation. Is needed to + approximate arbitrary surface. + + All representations can be converted to each other: + sticks -------> (nodes, simplices) + ^ | + └--- points < -----┘ + + Convertion from sticks to nodes/simplices is simply concating and triangles creation. + To convert triangulation (nodes and simplices) to points, we rasterize each triangle. + Convertion from points to sticks is more difficult and assumes that points are on almost + flat 3d plane. Note that convertion from points to sticks leads to loss of information + due to the approximation. + + Parameters + ---------- + storage : str, numpy.ndarray or dict + str - path to file (FaultSticks or npy/npz) + numpy.ndarray of (N, 3) shape - array of fault points + dict - fault data: points, sticks, nodes and/or simplices. Can include one of them. + field : Field + + name : str, optional + fault name, by default None + direction : int or None, optional + direction of the fault surface, by default None + """ + + # Columns used from the file + COLUMNS = ['INLINE_3D', 'CROSSLINE_3D', 'DEPTH'] + + def __init__(self, storage, field, name=None, direction=None, stick_orientation=None, **kwargs): #pylint: disable=super-init-not-called + self.name = name + self.field = field + + self.short_name = name + self._points = None + self._sticks = None + self._nodes = None + self._simplices = None + self.direction = None + self.stick_orientation = stick_orientation + self.sticks_step = None + self.stick_nodes_step = None + + if isinstance(storage, str): + source = 'file' + elif isinstance(storage, np.ndarray): + source = 'points' + elif isinstance(storage, dict): + source = 'dict' + elif isinstance(storage, pd.DataFrame): + source = 'df' + getattr(self, f'from_{source}')(storage, **kwargs) + + self.create_stats() + + if len(self) > 0 and self.direction is None: + self.set_direction(direction) + + def interpolate(self): + """ Create points of fault surface from sticks or nodes and simplices. """ + _ = self.points + + def has_component(self, component): + """ Check if faults has points, sticks, simplices or nodes. """ + return getattr(self, '_'+component) is not None + + def create_stats(self): + """ Compute fault stats (bounds, bbox, etc.) """ + if self.has_component('points'): + data = self.points + elif self.has_component('nodes'): + data = self.nodes + elif self.has_component('sticks'): + data = np.concatenate(self.sticks) + else: + self.bbox = None + return + + if len(data) == 0: # It can be for empty fault file. + data = np.zeros((1, 3)) + + i_min, x_min, d_min = np.min(data, axis=0) + i_max, x_max, d_max = np.max(data, axis=0) + + self.d_min, self.d_max = int(d_min), int(d_max) + self.i_min, self.i_max, self.x_min, self.x_max = int(i_min), int(i_max), int(x_min), int(x_max) + + self.i_length = (self.i_max - self.i_min) + 1 + self.x_length = (self.x_max - self.x_min) + 1 + self.bbox = np.array([[self.i_min, self.i_max], + [self.x_min, self.x_max], + [self.d_min, self.d_max]], + dtype=np.int32) + + def set_direction(self, direction): + """ Find azimuth of the fault. """ + if self.direction is not None: + return + if direction is None: + if self.has_component('sticks') and len(self.sticks) > 0: + ptp = np.abs([item[:, :2].ptp(axis=0) for item in self.sticks]) # pylint: disable=invalid-sequence-index + self.direction = int((ptp == 0).sum(axis=0).argmax()) + else: + if self.has_component('points') and len(self.points) > 0: + data = self.points + else: + data = self.nodes + mean_depth = np.argsort(data[:, 2])[len(data[:, 2]) // 2] + depth_slice = data[data[:, 2] == data[:, 2][mean_depth]] + self.direction = 0 if depth_slice[:, 0].ptp() > depth_slice[:, 1].ptp() else 1 + elif isinstance(direction, int): + self.direction = direction + elif isinstance(direction[self.field.short_name], int): + self.direction = direction[self.field.short_name] + else: + self.direction = direction[self.field.short_name][self.name] + + def reset_storage(self, storage): + """ Clear 'points', 'sticks', 'nodes' or 'simplices' storage. """ + setattr(self, '_' + storage, None) + + @classmethod + def load(cls, path, field, name=None, interpolate=False, **kwargs): + """ Load faults. """ + if not isinstance(path, str) or os.path.splitext(path)[1][1:] not in ['char', '']: + faults = [cls(path, field=field, name=name, **kwargs)] + else: + faults = [cls(df, field=field, name=name, **kwargs) for name, df in cls.split_charisma(path).items()] + + if interpolate: + for fault in faults: + fault.interpolate() + + return faults + + def from_points(self, points, transform=False, **kwargs): + """ Initialize points cloud. """ + if transform: + points = self.field.geometry.lines_to_cubic(points) + self._points = points + self.short_name = self.name + + def from_file(self, path, **kwargs): + """ Init from path to either FAULT_STICKS csv-like file or from npy/npz. """ + path = self.field.make_path(path, makedirs=False) + self.path = path + + self.name = self.name or os.path.basename(path) + self.short_name = self.short_name or os.path.splitext(path)[0] + + ext = os.path.splitext(path)[1][1:] + + if ext == 'npz': + self.load_npz(path, **kwargs) + self.format = 'file-npz' + elif ext == 'npy': + self.load_npy(path, **kwargs) + self.format = 'file-npy' + elif ext == 'sqb': + self.load_sqb(path, **kwargs) + self.format = 'file-sqb' + else: + self.load_fault_sticks(path, **kwargs) + self.format = 'file-sticks' + + def from_dict(self, storage, transform=False, **kwargs): + """ Load fault from dict with 'points', 'nodes', 'simplices' and 'sticks'. """ + for key in ['points', 'nodes']: + data = storage.get(key) + if data is not None and transform: + data = self.field.geometry.lines_to_cubic(data) + setattr(self, '_' + key, data) + + sticks = storage.get('sticks') + if sticks is not None and transform: + sticks = [self.field.geometry.lines_to_cubic(item) for item in sticks] + setattr(self, '_sticks', sticks) + + setattr(self, '_simplices', storage.get('simplices')) + + def from_df(self, storage, **kwargs): + """ Load fault sticks. """ + self.load_fault_sticks(storage, **kwargs) + + # Transformation of attributes: sticks -> (nodes, simplices) -> points -> sticks + + @property + def simplices(self): + """ Approximation of the surface by triangulation. Is needed to approximate arbitrary surface. + Exists in pair with nodes. + """ + if self._simplices is None: + if self._points is None and self._sticks is None: + raise AttributeError("'simplices' can't be created ('points' and 'sticks' don't exist)") + + self.sticks_to_simplices() + + return self._simplices + + @property + def nodes(self): + """ Approximation of the surface by triangulation. Is needed to approximate arbitrary surface. + Exists in pair with simplices. + """ + if self._nodes is None: + if self._points is None and self._sticks is None: + raise AttributeError("'nodes' can't be created ('points' and 'sticks' don't exist)") + + self.sticks_to_simplices() + + return self._nodes + + @property + def points(self): + """ Cloud of surface points. The most accurate way to define surface but not so handy + for manual editing and occupies the most memory. Is needed to create masks. + """ + if self._points is None: + if self._simplices is None and self._sticks is None: + raise AttributeError("'points' can't be created ('nodes'/'simplices' and 'sticks' don't exist)") + if len(self.simplices) > 1: + self.simplices_to_points() + elif len(self.nodes) > 0: + fake_fault = get_fake_one_stick_fault(self) + points = fake_fault.points + self._points = points[points[:, self.direction] == self.sticks[0][0, self.direction]] + + return self._points + + @property + def sticks(self): + """ Polylines that approximate fault surface. Usually are placed on a sequence of ilines or crosslines. + The most common result of the experts labeling but is not enough flexible. + """ + if self._sticks is None: + if self._simplices is None and self._points is None: + raise AttributeError("'sticks' can't be created ('nodes'/'simplices' and 'points' don't exist)") + self.points_to_sticks() + + return self._sticks + + def simplices_to_points(self, width=1): + """ Interpolate triangulation. + + Parameters + ---------- + simplices : numpy.ndarray + Array of shape (n_simplices, 3) with indices of nodes to connect into triangle. + nodes : numpy.ndarray + Array of shape (n_nodes, 3) with coordinates. + width : int, optional + Thickness of the simplex to draw, by default 1. + + Returns + ------- + numpy.ndarray + Array of shape (n_points, 3) + """ + points = [] + for triangle in self.simplices: + points.append(triangle_rasterization(self.nodes[triangle].astype('float32'), width)) + self._points = np.concatenate(points, axis=0).astype('int32') + + def points_to_sticks(self, slices=None, sticks_step=10, stick_nodes_step=10, stick_orientation=2, + nodes_threshold=5, move_bounds=False): + """ Create sticks from fault points. """ + points = self.points.copy() + if slices is not None: + for i in range(3): + points = points[points[:, i] <= slices[i].stop] + points = points[points[:, i] >= slices[i].start] + stick_orientation = stick_orientation if stick_orientation is not None else 2 + self._sticks = points_to_sticks(points=points, sticks_step=sticks_step, nodes_step=stick_nodes_step, + fault_orientation=self.direction, stick_orientation=stick_orientation, + threshold=nodes_threshold, move_bounds=move_bounds) + self.stick_orientation = stick_orientation + self.sticks_step = sticks_step + self.stick_nodes_step = stick_nodes_step + + def sticks_to_simplices(self, max_simplices_depth=None, max_nodes_distance=None): + """ Create nodes/simplices from fault sticks. """ + self._simplices, self._nodes = sticks_to_simplices( + self.sticks, self.direction, max_simplices_depth, max_nodes_distance + ) + + + def add_to_mask(self, mask, locations=None, width=1, axis=None, sparse=False, alpha=1, **kwargs): + """ Add fault to background. + + Parameters + ---------- + mask : ndarray + Background to add fault to. + locations : ndarray + Where the fault is located. + width : int + Width of an added fault. + axis : int or None, optional + Orientation of the crop to insert fault, by default None (unknown or crop is 3D) + sparse : bool, optional + Whether create sparse mask (only on labeled slides) or not, by default False + """ + _ = kwargs + + if axis is not None and axis not in (2, self.direction): + return mask + + mask_bbox = np.array([[locations[0].start, locations[0].stop], + [locations[1].start, locations[1].stop], + [locations[2].start, locations[2].stop]], + dtype=np.int32) + points = self.points + + if (self.bbox[:, 1] < mask_bbox[:, 0]).any() or (self.bbox[:, 0] >= mask_bbox[:, 1]).any(): + return mask + + if sparse and self.has_component('sticks'): + loc = np.unique(self.nodes[:, self.direction]) + loc = loc[np.logical_and(mask_bbox[self.direction, 0] <= loc, loc < mask_bbox[self.direction, 1])] + + points = points[np.isin(points[:, self.direction], loc)] + + unlabeled_slides = take_along_axis(mask, loc - mask_bbox[self.direction, 0], self.direction) + unlabeled_slides = loc[unlabeled_slides[:, 0, 0] == -1] + + slices = [slice(None)] * 3 + slices[self.direction] = unlabeled_slides - mask_bbox[self.direction, 0] + mask[tuple(slices)] = 0 + + insert_points_into_mask(mask, points, mask_bbox, width=width, axis=1-self.direction, alpha=alpha) + return mask + + def __len__(self): + """ The size of the fault. """ + if self.bbox is None: + return 0 + return self.bbox[2].ptp() * (self.bbox[self.direction].ptp() + 1) + + def __add__(self, other): + points = np.concatenate([self.points, other.points]) + return type(self)({'points': points}, field=self.field, name=f"{self.name}+{other.name}", + direction=self.direction) diff --git a/seismiqb/labels/fault/coords_utils.py b/seismiqb/labels/fault/coords_utils.py new file mode 100644 index 0000000..264e52e --- /dev/null +++ b/seismiqb/labels/fault/coords_utils.py @@ -0,0 +1,215 @@ +""" Faults extraction helpers for 3D coordinates processing. """ +import numpy as np +from numba import njit +import cv2 as cv + +# Coordinates operations +def dilate_coords(coords, dilate=3, axis=0, max_value=None): + """ Dilate coordinates with (dilate, 1) structure along the given axis. + + Note, the function returns unique and sorted coords. + + Parameters + ---------- + coords : np.ndarray of (N, 3) shape + Coordinates to dilate along the axis. Sorting is not required. + axis : {0, 1, 2} + Axis along which to dilate coordinates. + max_value : None or int, optional + The maximum possible value for coordinates along the provided axis. + Used for values clipping into valid range. + """ + dilated_coords = np.tile(coords, (dilate, 1)) + + # Create dilated coordinates + for i in range(dilate): + start_idx, end_idx = i*len(coords), (i + 1)*len(coords) + dilated_coords[start_idx:end_idx, axis] += i - dilate//2 + + # Clip to the valid values + mask = dilated_coords[:, axis] >= 0 + + if max_value is not None: + mask &= dilated_coords[:, axis] < max_value + + dilated_coords = dilated_coords[mask] + + # Get sorted unique values + dilated_coords = np.unique(dilated_coords, axis=0) + return dilated_coords + + +# Distance evaluation +@njit +def bboxes_intersected(bbox_1, bbox_2, axes=(0, 1, 2)): + """ Check bounding boxes intersection on preferred axes. + + Bboxes are intersected if they have at least 1 overlapping point. + + Parameters + ---------- + bbox_1, bbox_2 : np.ndarrays of (3, 2) shape. + Objects bboxes. + axes : sequence of int values from {0, 1, 2} + Axes to check bboxes intersection. + """ + for axis in axes: + overlap_size = min(bbox_1[axis, 1], bbox_2[axis, 1]) - max(bbox_1[axis, 0], bbox_2[axis, 0]) + 1 + + if overlap_size < 1: + return False + return True + +@njit +def bboxes_adjacent(bbox_1, bbox_2, adjacency=1): + """ Bounding boxes adjacency ranges. + + Bboxes are adjacent if they are distant not more than on `adjacency` points. + + Parameters + ---------- + bbox_1, bbox_2 : np.ndarrays of (3, 2) shape. + Objects bboxes. + adjacency : int + Amount of points between two bboxes to decide that they are adjacent. + """ + borders = np.empty((3, 2), dtype=np.int32) + + for i in range(3): + borders_i_0 = max(bbox_1[i, 0], bbox_2[i, 0]) + borders_i_1 = min(bbox_1[i, 1], bbox_2[i, 1]) + + if borders_i_1 - borders_i_0 < -adjacency: + return None + + borders[i, 0] = min(borders_i_0, borders_i_1) + borders[i, 1] = max(borders_i_0, borders_i_1) + + return borders + +def bboxes_embedded(bbox_1, bbox_2, margin=3): + """ Check that one bounding box is inside the other (embedded). + + Parameters + ---------- + bbox_1, bbox_2 : np.ndarrays of (3, 2) shape. + Objects bboxes. + margin : int + Possible bboxes difference (on each axis) to decide that one is inside another. + """ + swap = np.count_nonzero(bbox_1[:, 1] >= bbox_2[:, 1]) <= 1 # is second not inside first + + if swap: + bbox_1, bbox_2 = bbox_2, bbox_1 + + for i in range(3): + is_embedded = (bbox_2[i, 0] >= bbox_1[i, 0] - margin) and (bbox_2[i, 1] <= bbox_1[i, 1] + margin) + + if not is_embedded: + return is_embedded, swap + + return is_embedded, swap + +@njit +def compute_distances(coords_1, coords_2, max_threshold=10000): + """ Find approximate minimum and maximum distances between two arrays of coordinates. + We assume coords to have the same length and compare only corresponding points. + A little bit faster than difference between np.ndarrays with `np.max` and `np.min`. + + Parameters + ---------- + coords_1, coords_2 : np.ndarrays of (N, 1) shape + Coords for which find distances. + max_threshold : int, float or None + Early stopping: threshold for max distance value. + """ + min_distance = max_threshold + max_distance = 0 + + for coord_1, coord_2 in zip(coords_1, coords_2): + distance = np.abs(coord_1 - coord_2) + + if distance >= max_threshold: + return -1, distance + + if distance > max_distance: + max_distance = distance + + if distance < min_distance: + min_distance = distance + + return min_distance, max_distance + +def find_contour(coords, projection_axis): + """ Find closed contour of coords projection. + + Under the hood, we make a 2D coords projection and find its contour. + + Note, returned contour coordinates are equal to 0 for the projection axis. + + Parameters + ---------- + coords : np.ndarray of (N, 3) shape + 3D object coordinates. Sorting is not required. + projection_axis : {0, 1} + Axis for making 2D projection. + Note, this function doesn't work for axis = 2. + """ + bbox = np.column_stack([np.min(coords, axis=0), np.max(coords, axis=0)]) + bbox = bbox[(1 - projection_axis, 2), :] + + # Create object image mask + origin = bbox[:, 0] + image_shape = bbox[:, 1] - bbox[:, 0] + 1 + + mask = np.zeros(image_shape, np.uint8) + mask[coords[:, 1 - projection_axis] - origin[0], coords[:, 2] - origin[1]] = 1 + + # Get only the main object contour: object can contain holes with their own contours + contours, _ = cv.findContours(mask, cv.RETR_TREE, cv.CHAIN_APPROX_NONE) + + # Extract unique and sorted coords + contour = contours[0].reshape(len(contours[0]), 2) # Can be non-unique + + contour_coords = np.zeros((len(contour), 3), np.int32) + contour_coords[:, 1 - projection_axis] = contour[:, 1] + origin[0] + contour_coords[:, 2] = contour[:, 0] + origin[1] + + contour_coords = np.unique(contour_coords, axis=0) # np.unique is here for sorting and unification + return contour_coords + +@njit +def restore_coords_from_projection(coords, projection_buffer, axis): + """ Get values along `axis` for 2D projection coordinates from 3D coords. + + Example + ------- + Useful, where we have subsetted original `coords` and zero-out the result along some axis:: + coords, indices, axis + subset = coords[indices] + subset[:, axis] = 0 + + restore_coords_from_projection(coords, subset, axis) # change zeros back to original values from `coords` + + + Parameters + ---------- + coords : np.ndarray of (N, 3) shape + Original coords from which restore the axis values. Sorting is not required. + projection_buffer : np.ndarray of (N, 3) shape + Buffer with projection coordinates. Initially, values along `axis` are zeros. Sorting is not required. + Changed inplace. + axis : {0, 1, 2} + Axis for which restore coordinates. + """ + known_axes = np.array([i for i in range(3) if i != axis]) + + for i, buffer_line in enumerate(projection_buffer): + values = coords[(coords[:, known_axes[0]] == buffer_line[known_axes[0]]) & \ + (coords[:, known_axes[1]] == buffer_line[known_axes[1]]), + axis] + + projection_buffer[i, axis] = min(values) if len(values) > 0 else -1 + + projection_buffer = projection_buffer[projection_buffer[:, axis] != -1] + return projection_buffer diff --git a/seismiqb/labels/fault/extractor.py b/seismiqb/labels/fault/extractor.py new file mode 100644 index 0000000..f193b0b --- /dev/null +++ b/seismiqb/labels/fault/extractor.py @@ -0,0 +1,1574 @@ +""" Faults extractor from point cloud. """ +import numpy as np + +from cc3d import connected_components +from scipy.ndimage import find_objects + +from batchflow import Notifier + +from .base import Fault +from .postprocessing import skeletonize +from .coords_utils import (bboxes_adjacent, bboxes_embedded, bboxes_intersected, compute_distances, dilate_coords, + find_contour, restore_coords_from_projection) +from ...utils import groupby_min, groupby_max, make_ranges, int_to_proba + + + +class FaultExtractor: + """ Extract fault surfaces from a skeletonized or smoothed probabilities array. + + Main naming rules, which help to understand what's going on: + - Component is a 2D connected component on slide (corresponds to :class:`~.Component` instance). + - Prototype is a 3D points cloud of merged components (corresponds to :class:`~.FaultPrototype` instance). + Instances of :class:`~.FaultPrototype` are essentially the same as :class:`~.Fault` instances, + but with their own processing methods such as concat, split, etc. + - `coords` are spatial coordinates ndarray in format (iline, xline, depth) with (N, 3) shape. + - `points` are coords and probabilities values ndarray in format (iline, xline, depth, proba) with (N, 4) shape. + Note, that probabilities can be converted into (0, 255) values for applying integer storage for points. + + Implementation details + ---------------------- + The extraction algorithm is: + + 0) Label connected components for each 2D slide of the input array. + + 1) Create prototypes. + We extract prototype approximations as a set of similar components on neighboring slides on `direction` axis: + - first, we select one of the unmerged 2D component, prioritizing the longest component + - find the closest one on the next slide, and save them into one prototype. + We repeat this until we fail to find close enough objects. + + Distance between components is computed axis-wise and further optimized by early exits on thresholds. + + We can have a situation, where two components are considered to be close, but have different lengths: + in this case, we split (depth-wise) each component into up to three parts: + - one on the overlap with the second component + - one above the overlap and one below it: may be absent if not required + The overlapping parts are then merged as usual. + + For more, see the :meth:`~.extract_one_prototype`. + + 2) Merge connected prototypes. + As we potentially did some splitting of components during the prototype creation, + we concat them back where we need. + + For this, we find prototypes which are connected as puzzle details. + For more, see the :meth:`~.concat_connected_prototypes`. + + This operation is recommended to be repeated for both `depth` and `self.direction` axes, + and also for multiple prototype overlap thresholds. + You can see the recommended operations sequence in the :meth:`~.run`. + + 3) Merge embedded prototypes. + We can have a situation where one prototype is completely inside the other. + That is caused by prototypes concatenation order. + + For more, see the :meth:`~.concat_embedded_prototypes`. + ------------------------------------------------------- + + + To sum up, the algorithm is: + 0) Initialize container with smoothed probabilities predictions. + 1) Extract first prototype approximations with :meth:`~.extract_prototypes`. + 2) Iteratively concat close prototypes with :meth:`~.concat_connected_prototypes`. + 3) Concat internal prototypes pieces with :meth:`~.concat_embedded_prototypes`. + As an example of the overall pipeline, see the :meth:`~.run`. + + + Parameters + ---------- + data : np.ndarray or :class:`~.Geometry` instance, optional + A 3D volume with smoothed or skeletonized predictions. By default we assume the data to be already skeletonized. + ranges : sequence, optional + Nested sequence, where each element is either None or sequence of two ints. + Defines data ranges for faults extraction. + do_skeletonize : bool, optional + Whether the `data` argument needs to be skeletonized. + Should be True, if the data is smoothed model output. + direction : {0, 1} + Extraction direction, 0 for ilines and 1 for crosslines. + It is the same as the prediction direction. + component_len_threshold : int, optional + Threshold to filter out too small connected components on data slides. + If 0, then no filter applied (recommended for higher accuracy). + If more than 0, then extraction will be faster but some small prototypes can be not extracted. + shape : sequence of three ints, optional + Field shape. + """ + # pylint: disable=protected-access + def __init__(self, data=None, ranges=None, do_skeletonize=False, direction=0, + component_len_threshold=0, shape=None): + # Data parameters + self.shape = data.shape if data is not None else shape + + self.direction = direction + self.orthogonal_direction = 1 - self.direction + + self.proba_transform = None + + # Make ranges + ranges = make_ranges(ranges=ranges, shape=self.shape) + ranges = np.array(ranges) + self.ranges = ranges + + self.origin = ranges[:, 0] + + # Internal parameters + self._dilation = 3 # constant for internal operations + self.component_len_threshold = component_len_threshold + + self._unprocessed_slide_idx = self.origin[self.direction] # first index of the slide with unmerged components + + # Containers + self.prototypes_queue = [] # prototypes for extraction + self.prototypes = [] # extracted prototypes + + if data is not None: + self.container = self._init_container(data=data, do_skeletonize=do_skeletonize) + else: + self.container = None + + def _init_container(self, data, do_skeletonize=False): + """ Extract connected components on each slide and save them into container. + + Returns + ------- + container : dict + Dicts where keys are slide indices and values are dicts in the following format: + {'components' : list of :class:`.Component` instances, + 'lengths' : list of corresponding lengths}. + """ + container = {} + + # Process data slides: extract connected components and their info + for slide_idx in Notifier('t')(range(*self.ranges[self.direction])): + # Get skeletonized slide + slide = data.take(slide_idx, axis=self.direction) + slide = slide[slice(*self.ranges[self.orthogonal_direction]), slice(*self.ranges[2])] + + if do_skeletonize: + skeletonized_slide = skeletonize(slide, width=3).astype(bool) + else: + skeletonized_slide = slide > np.min(slide) # for signed dtypes + + # Extract connected components from the slide + labeled_slide = connected_components(skeletonized_slide) + objects = find_objects(labeled_slide) + + # Get components info + components, lengths = [], [] + + for idx, object_bbox in enumerate(objects, start=1): + # Extract component mask + object_mask = labeled_slide[object_bbox] == idx + + # Filter by proba + object_proba = slide[object_bbox][object_mask].max().astype(data.dtype) # TODO: think about percentile + + if np.issubdtype(data.dtype, np.integer): + object_proba = int_to_proba(object_proba) + + if object_proba < 0.1: # TODO: think about more appropriate threshold + continue + + # Check length + length = np.count_nonzero(object_mask) + + if length <= self.component_len_threshold: + continue + + lengths.append(length) + + # Extract 3D coords and probabilities + coords_2D = np.nonzero(object_mask) + coords = np.zeros((len(coords_2D[0]), 3), dtype=np.int32) + + coords[:, self.direction] = slide_idx + coords[:, self.orthogonal_direction] = coords_2D[0].astype(np.int32) + object_bbox[0].start + \ + self.origin[self.orthogonal_direction] + coords[:, 2] = coords_2D[1].astype(np.int32) + object_bbox[1].start + self.origin[2] + + probas = slide[object_bbox][coords_2D[0], coords_2D[1]] + + # Convert probas to integer values for saving them in points array with 3D-coordinates + if not np.issubdtype(data.dtype, np.integer): + probas = np.round(probas * 255) + self.proba_transform = lambda x: x / 255 + if probas.dtype != coords.dtype: + probas = probas.astype(coords.dtype) + + points = np.hstack((coords, probas.reshape(-1, 1))) + + # Bbox + bbox = np.empty((3, 2), dtype=np.int32) + + bbox[self.direction, :] = slide_idx + + bbox[self.orthogonal_direction, 0] = object_bbox[0].start + self.origin[self.orthogonal_direction] + bbox[self.orthogonal_direction, 1] = object_bbox[0].stop + self.origin[self.orthogonal_direction] - 1 + + bbox[2, 0] = object_bbox[1].start + self.origin[2] + bbox[2, 1] = object_bbox[1].stop + self.origin[2] - 1 + + # Save component + component = Component(points=points, slide_idx=slide_idx, bbox=bbox) + components.append(component) + + container[slide_idx] = { + 'components': components, + 'lengths': lengths + } + + return container + + @classmethod + def from_prototypes(cls, prototypes, shape): + """ Initialize extractor from prototypes. + + Useful for applying operations on prototypes from different data chunks. + + Parameters + ---------- + prototypes : list of :class:`~.FaultPrototype` instances, optional + Prototypes for applying :class:`~.FaultExtractor` methods on. + shape : sequence of three ints, optional + Field shape from which the `prototypes` were extracted. + """ + instance = cls(direction=prototypes[0].direction, shape=shape) + + instance.prototypes = prototypes + instance.shape = shape + return instance + + # Prototypes extraction from the data volume + def extract_prototypes(self): + """ Extract all fault prototypes from the point cloud. + + Returns + ------- + prototypes: list of the :class:`~.FaultPrototype` instances + Prototypes extracted from the data volume. + """ + prototype = self.extract_one_prototype() + + while prototype is not None: + self.prototypes.append(prototype) + prototype = self.extract_one_prototype() + + return self.prototypes + + def extract_one_prototype(self): + """ Extract one fault prototype from the point cloud. + + Under the hood, we find unmerged 2D component and find the closest one on the next slide. + If components are close enough, they are merged into one 3D surface - fault prototype. + Merging repeats until we are unable to find close enough components on next slides. + + Returns + ------- + prototype: :class:`~.FaultPrototype` instance + Prototype extracted from the data volume. + """ + # Get intial 2D component and init prototype (or get from queue) + if len(self.prototypes_queue) == 0: + component, component_idx = self._find_unmerged_component() + + if component is None: # Nothing to merge + return None + + self.container[component.slide_idx]['lengths'][component_idx] = -1 # Mark component as merged + + prototype = FaultPrototype(points=component.points, direction=self.direction, last_component=component, + proba_transform=self.proba_transform) + else: + prototype = self.prototypes_queue.pop(0) + component = prototype.last_component + + # Find closest components on next slides + for next_slide in range(component.slide_idx + 1, self.ranges[self.direction][1]): + # Find the closest component on the slide_idx_ to the current + component, split_indices = self._find_closest_component(component=component, slide_idx=next_slide) + + # Postprocess prototype - it need to be splitted if it is out of component ranges + if component is not None: + prototype, new_prototypes = prototype.split(split_indices=split_indices, axis=2) + self.prototypes_queue.extend(new_prototypes) + + prototype.append(component) + else: + break + + return prototype + + def _find_unmerged_component(self): + """ Find the longest unmerged component on the first slide with unmerged components. + Under the hood, we start from the very first slide, use all of its components, and then move to the next slides + while keeping track of the index of slide with not all merged components. + + Returns + ------- + component : :class:`.Component` instance or None + First unmerged component in the data container. + Can be None if there are no suitable components in the container. + component_idx : int or None + The index of the found component. + """ + for slide_idx in range(self._unprocessed_slide_idx, self.ranges[self.direction][1]): + slide_info = self.container[slide_idx] + + if len(slide_info['lengths']) > 0: + component_idx = np.argmax(slide_info['lengths']) + + if slide_info['lengths'][component_idx] != -1: + self._unprocessed_slide_idx = slide_idx + component = self.container[slide_idx]['components'][component_idx] + return component, component_idx + + return None, None + + def _find_closest_component(self, component, slide_idx, distances_threshold=None, + depth_iteration_step=10, depths_threshold=20, distance_neighborhood=3): + """ Find the closest component to the provided on next slide, get splitting indices for prototype. + + Parameters + ---------- + component : instance of :class:`~.Component` + Component for which find the closest one on the next slide. + slide_idx : int + Slide num on which to find the closest component. + distances_threshold : int, optional + Threshold for the max possible axis-wise distance between components, + where axis is `self.orthogonal_direction`. + depth_iteration_step : int + The depth iteration step to find distances between components. + Value 1 is recommended for higher accuracy. + Value more than 1 is less accurate but speeds up this method. + depths_threshold : int + Depth-length threshold to decide to split closest component or prototype. + If one component is longer than another more than on depths_threshold, + then we need to split the longest one into parts: + - one part is the closest component; + - another parts corresponds to the other components, + which are not allowed to merge into the current prototype. + distance_neighborhood : int + Area in which to find close components to choose the closest and longest one. + For example, if we have two close enough components with distances 0 and 0 + distance_neighborhood and + the second is longer than the closest, then we will choose it. + We make this because one component on the next slide can be splitted into two parts and we want to concat it + with the longest one. In this case distance_neighborhood is allowable error for finding the close enough + components. + + Returns + ------- + closest_component : :class:`.Component` instance + The next slide closest component to the provided one. + prototype_split_indices : list of two ints or Nones + Depth coordinates for splitting extracted prototype (if needed). + Indices are evaluated as components overlap range by the depth axis. + """ + # Dilate component bbox for detecting close components: component on next slide can be shifted + dilated_bbox = component.bbox.copy() + dilated_bbox[self.orthogonal_direction, :] += (-self._dilation // 2, self._dilation // 2) + dilated_bbox[self.orthogonal_direction, 0] = max(0, dilated_bbox[self.orthogonal_direction, 0]) + dilated_bbox[self.orthogonal_direction, 1] = min(dilated_bbox[self.orthogonal_direction, 1], + self.shape[self.orthogonal_direction]) + + min_distance = distances_threshold if distances_threshold is not None else 100 + + # Init returned values + closest_component = None + selected_component_length = -1 + prototype_split_indices = [None, None] + component_split_indices = [None, None] + + # Iter over components and find the closest one + for other_component_idx, other_component in enumerate(self.container[slide_idx]['components']): + if self.container[slide_idx]['lengths'][other_component_idx] == -1: + continue + + # Check bboxes intersection + if not bboxes_intersected(dilated_bbox, other_component.bbox, axes=(self.orthogonal_direction, 2)): + continue + + # Check closeness of some points (as depth-wise distances) + # Faster then component overlap, but not so accurate + overlap_depths = (max(component.bbox[2, 0], other_component.bbox[2, 0]), + min(component.bbox[2, 1], other_component.bbox[2, 1])) + + step = min(depth_iteration_step, (overlap_depths[1]-overlap_depths[0])//3) + step = max(step, 1) + + indices_1 = np.in1d(component.coords[:, -1], np.arange(overlap_depths[0], overlap_depths[1]+1, step)) + indices_2 = np.in1d(other_component.coords[:, -1], np.arange(overlap_depths[0], overlap_depths[1]+1, step)) + + coords_1 = component.coords[indices_1, self.orthogonal_direction] + coords_2 = other_component.coords[indices_2, self.orthogonal_direction] + + components_distances = compute_distances(coords_1, coords_2, + max_threshold=min_distance+distance_neighborhood) + + if (components_distances[0] == -1) or (components_distances[0] > distance_neighborhood): + # Components are not close + continue + + if components_distances[1] >= min_distance + distance_neighborhood: + # `other_component` is not close enough + continue + + # The most depthwise distant points in components are close enough -> we can combine components + # Also, we want to find the longest close enough component + if selected_component_length < len(other_component): + min_distance = components_distances[1] + selected_component_length = len(other_component) + closest_component = other_component + merged_idx = other_component_idx + overlap_borders = overlap_depths + + if closest_component is not None: + # Process (split if needed) founded component and get split indices for prototype + self.container[closest_component.slide_idx]['lengths'][merged_idx] = -1 # mark component as merged + + # Get prototype split indices: + # check that the new component is smaller than the previous one (for each border) + if overlap_borders[0] - component.bbox[2, 0] > depths_threshold: + prototype_split_indices[0] = overlap_borders[0] + + if component.bbox[2, 1] - overlap_borders[1] > depths_threshold: + prototype_split_indices[1] = overlap_borders[1] + + # Split new component: check that the new component is bigger than the previous one (for each border) + # Create splitted items and save them as new elements for merge + if overlap_borders[0] - closest_component.bbox[2, 0] > depths_threshold: + component_split_indices[0] = overlap_borders[0] + + if closest_component.bbox[2, 1] - overlap_borders[1] > depths_threshold: + component_split_indices[1] = overlap_borders[1] + + closest_component, new_components = closest_component.split(split_indices=component_split_indices) + self._add_new_components(new_components) + + return closest_component, prototype_split_indices + + def _add_new_components(self, components): + """ Add new components into the container. + + New items are created after splitting. + """ + for component in components: + if len(component) > self.component_len_threshold: + self.container[component.slide_idx]['components'].append(component) + self.container[component.slide_idx]['lengths'].append(len(component)) + + + # Prototypes concatenation + def concat_connected_prototypes(self, overlap_ratio_threshold=None, axis=2, + border_threshold=20, width_split_threshold=100): + """ Concat prototypes which are connected as puzzle details. + + Under the hood, we compare prototypes with each other and find connected pairs. + For this, we get neighboring borders and compare them: + if they are almost overlapped after spatial shift then we merge corresponding prototypes. + + Parameters + ---------- + overlap_ratio_threshold : float or None + Prototypes borders overlap ratio to decide that prototypes are not close. + Possible values are float numbers in the (0, 1] interval or None. + If None, then default values are used: 0.5 for the depth axis and 0.9 for others. + axis : {0, 1, 2} + Axis along which to find prototype borders connections. + Recommended values are 2 (for depths) and `self.direction`. + border_threshold : int + Minimal amount of points out of borders overlap to decide that prototypes are not close. + width_split_threshold : int or None + Merging prototypes width (along `self.direction` axis) difference threshold to decide + that they need to be splitted. + If value is None, then no splitting applied. But there are the risk of interpenetration of + triangulated surfaces in this case. + With lower values more splitting applied and smaller prototypes are extracted. + If you want more detailing, then provide smaller `width_split_threshold` (near to 10). + If you want to extract bigger surfaces, then provide higher `width_split_threshold` (near to 100 or None). + + Returns + ------- + prototypes: list of the :class:`~.FaultPrototype` instances + Prototypes instances after concatenation. + """ + #pylint: disable=too-many-branches + margin = 1 # local constant for code prettifying + + if overlap_ratio_threshold is None: + overlap_ratio_threshold = 0.5 if axis in (-1, 2) else 0.9 + + overlap_axis = self.direction if axis in (-1, 2) else 2 + + # Under the hood, we check borders connectivity (as puzzles) + borders_to_check = ('up', 'down') if axis in (-1, 2) else ('left', 'right') + + # Presort objects by overlap axis for early stopping + sort_axis = overlap_axis + prototypes_starts = np.array([prototype.bbox[sort_axis, 0] for prototype in self.prototypes]) + prototypes_order = np.argsort(prototypes_starts) + reodered_prototypes = [self.prototypes[idx] for idx in prototypes_order] + + new_prototypes = [] + + for i, prototype_1 in enumerate(reodered_prototypes): + prototype_for_merge = None + best_overlap = -1 + + for prototype_2 in reodered_prototypes[i+1:]: + # Exit if we out of sort_axis ranges for prototype_1 + if (prototype_1.bbox[sort_axis, 1] < prototype_2.bbox[sort_axis, 0]): + break + + adjacent_borders = bboxes_adjacent(prototype_1.bbox, prototype_2.bbox) + + if adjacent_borders is None: + continue + + # Check that bboxes overlap is enough + overlap_threshold = min(prototype_1.bbox[overlap_axis, 1] - prototype_1.bbox[overlap_axis, 0], + prototype_2.bbox[overlap_axis, 1] - prototype_2.bbox[overlap_axis, 0]) + overlap_threshold *= overlap_ratio_threshold + + overlap_length = adjacent_borders[overlap_axis][1] - adjacent_borders[overlap_axis][0] + + if overlap_length < overlap_threshold: + continue + + # Find object borders on close borders + is_first_upper = prototype_1.bbox[axis, 0] < prototype_2.bbox[axis, 0] + + border_1 = prototype_1.get_border(border=borders_to_check[is_first_upper], + projection_axis=self.orthogonal_direction) + border_2 = prototype_2.get_border(border=borders_to_check[~is_first_upper], + projection_axis=self.orthogonal_direction) + + # Get objects width in area near to overlap for intersection threshold + # to avoid concatenation of objects with too little overlap + neighborhood_range = (min(adjacent_borders[axis]) - 20, max(adjacent_borders[axis]) + 20) + + neighboring_border_1 = border_1[(border_1[:, axis] >= neighborhood_range[0]) & \ + (border_1[:, axis] <= neighborhood_range[1])] + neighboring_border_2 = border_2[(border_2[:, axis] >= neighborhood_range[0]) & \ + (border_2[:, axis] <= neighborhood_range[1])] + + if len(neighboring_border_1) == 0 or len(neighboring_border_2) == 0: + continue + + width_neighboring_1 = np.ptp(neighboring_border_1[:, overlap_axis]) + width_neighboring_2 = np.ptp(neighboring_border_2[:, overlap_axis]) + + # TODO: think about more appropriate criteria than proportion + overlap_threshold = 0.5*max(width_neighboring_1, width_neighboring_2) + + # Get borders in the area of interest + overlap_range = (min(adjacent_borders[axis]) - margin, max(adjacent_borders[axis]) + margin) + + border_1 = border_1[(border_1[:, axis] >= overlap_range[0]) & \ + (border_1[:, axis] <= overlap_range[1])] + border_2 = border_2[(border_2[:, axis] >= overlap_range[0]) & \ + (border_2[:, axis] <= overlap_range[1])] + + # If one data border is much longer than other, then we can't connect them as puzzle details + if len(border_1) == 0 or len(border_2) == 0: + continue + + length_ratio = min(len(border_1), len(border_2)) / max(len(border_1), len(border_2)) + + if length_ratio < overlap_ratio_threshold: + continue + + # Correct border_threshold for too short borders + if (1 - overlap_ratio_threshold) * min(len(border_1), len(border_2)) < border_threshold: + corrected_border_threshold = min(2*margin, border_threshold) + else: + corrected_border_threshold = border_threshold + + # Shift one of the objects, making their borders intersected + shift = 1 if is_first_upper else -1 + border_1[:, axis] += shift + + # Check that one component border is inside another (for both) + border_1_width = np.ptp(border_1[:, overlap_axis]) + border_2_width = np.ptp(border_2[:, overlap_axis]) + + if border_1_width <= border_2_width: + overlap_range = self._borders_overlap(border_1, border_2, + border_threshold=corrected_border_threshold, + overlap_threshold=overlap_threshold, + overlap_axis=overlap_axis) + else: + overlap_range = self._borders_overlap(border_2, border_1, + border_threshold=corrected_border_threshold, + overlap_threshold=overlap_threshold, + overlap_axis=overlap_axis) + + if overlap_range is None: + continue + + # Select the best one prototype for merge + border_length = border_1[:, axis].max() - border_1[:, axis].min() + 1 + overlap_ratio = (overlap_range[1] - overlap_range[0]) / border_length + + if best_overlap < overlap_ratio: + best_overlap_range = overlap_range + best_overlap = overlap_ratio + prototype_for_merge = prototype_2 + + best_border_1_width = border_1_width + best_border_2_width = border_2_width + + is_first_upper_than_best = is_first_upper + + # Split for avoiding wrong prototypes shapes: + # - concat only overlapped parts + # - lower part can't be wider then upper; + # - if one prototype is much bigger than it should be splitted. + if prototype_for_merge is None: + continue + + width_threshold = min(best_border_1_width, best_border_2_width) - 2*margin + + if (best_overlap_range[1] - best_overlap_range[0]) < width_threshold: + prototype_for_merge, new_prototypes_ = prototype_for_merge.split(best_overlap_range, + axis=self.direction) + new_prototypes.extend(new_prototypes_) + + prototype_1, new_prototypes_ = prototype_1.split(best_overlap_range, axis=self.direction) + new_prototypes.extend(new_prototypes_) + + elif axis in (-1, 2): + width_diff = 5 + + lower_is_wider = (is_first_upper_than_best and \ + prototype_for_merge.width - best_border_1_width > width_diff) or \ + (not is_first_upper_than_best and prototype_1.width - best_border_2_width > width_diff) + + too_big_width_diff = (width_split_threshold is not None) and \ + (np.abs(prototype_1.width - prototype_for_merge.width) > width_split_threshold) + + if (lower_is_wider or too_big_width_diff): + if is_first_upper_than_best: + prototype_for_merge, new_prototypes_ = prototype_for_merge.split(best_overlap_range, + axis=self.direction) + else: + prototype_1, new_prototypes_ = prototype_1.split(best_overlap_range, axis=self.direction) + + new_prototypes.extend(new_prototypes_) + + prototype_for_merge.concat(prototype_1) + prototype_1._already_merged = True + + self.prototypes = [prototype for prototype in self.prototypes + if not getattr(prototype, '_already_merged', False)] + self.prototypes.extend(new_prototypes) + return self.prototypes + + def _borders_overlap(self, border_1, border_2, border_threshold, overlap_axis, overlap_threshold=0): + """ Check that `border_1` is almost inside the dilated `border_2` and return their overlap range. + + We apply dilation for `border_2` because the fault can be shifted on neighboring slides. + + Parameters + ---------- + border_1, border_2 : np.ndarrays of (N, 3) shape + Contours coordinates for check. + border_threshold : int + Minimal amount of points out of overlap to decide that `border_1` is not inside `border_2`. + overlap_threshold : int + Minimal amount of overlapped points to decide that borders are overlapping. + + Returns + ------- + overlap_range : tuple of two ints or None + The longest overlap range on the `overlap_axis` for provided borders. + None, if there are no overlap. + Note, that two borders can have more than one overlapping area, we choose the longest one. + """ + border_1_set = set(tuple(x) for x in border_1) + + # Objects can be shifted on `self.orthogonal_direction`, so apply dilation for coords + border_2_dilated = dilate_coords(coords=border_2, dilate=self._dilation, + axis=self.orthogonal_direction, + max_value=self.shape[self.orthogonal_direction]) + + border_2_dilated = set(tuple(x) for x in border_2_dilated) + + overlap = border_1_set.intersection(border_2_dilated) + borders_overlapped = len(overlap) > overlap_threshold + + if borders_overlapped and (len(border_1_set - border_2_dilated) < border_threshold): + return get_range(overlap, axis=overlap_axis) + + return None + + def concat_embedded_prototypes(self, border_threshold=100): + """ Concat embedded prototypes (with 2 or more close borders). + + Under the hood, we compare different prototypes to find pairs in which one prototype is inside another. + If more than two borders of internal prototype is connected with other prototype, then we merge them. + + Internal logic looks similar to `.concat_connected_prototypes`, + but now we find embedded bboxes and need two borders coincidence instead of one. + + Embedded prototypes examples: + + |||||| or ||||||| or |||||| etc. + ...||| |...||| |||... + ||| ||||||| + |||||| + + - where | means one prototype points, and . - other prototype points. + + Parameters + ---------- + border_threshold : int + Minimal amount of points out of borders overlap to decide that prototypes are not close. + + Returns + ------- + prototypes: list of the :class:`~.FaultPrototype` instances + Prototypes after concatenation. + """ + # Presort objects by other valuable axis for early stopping + sort_axis = self.direction + prototypes_starts = np.array([prototype.bbox[sort_axis, 0] for prototype in self.prototypes]) + prototypes_order = np.argsort(prototypes_starts) + reodered_prototypes = [self.prototypes[idx] for idx in prototypes_order] + + margin = 3 # local constant + + for i, prototype_1 in enumerate(reodered_prototypes): + for prototype_2 in reodered_prototypes[i+1:]: + # Check that prototypes are embedded + if (prototype_1.bbox[sort_axis, 1] < prototype_2.bbox[sort_axis, 0]): + break + + is_embedded, swap = bboxes_embedded(prototype_1.bbox, prototype_2.bbox, margin=margin) + + if not is_embedded: + continue + + coords = prototype_1.coords if swap is False else prototype_2.coords + other = prototype_2 if swap is False else prototype_1 + + # Check borders connections + close_borders_counter = 0 + + for border_position in ('up', 'down', 'left', 'right'): # TODO: get more optimal order depend on bboxes + # Find internal object border + border = other.get_border(border=border_position, projection_axis=self.orthogonal_direction) + border = border.copy() # will be shifted + + # Shift border to make it intersected with another object + shift = -1 if border_position in ('up', 'left') else 1 + shift_axis = self.direction if border_position in ('left', 'right') else 2 + border[:, shift_axis] += shift + + # Get main object coords in the area of the interest for speeding up evaluations + slices = other.bbox.copy() + slices[:, 0] -= margin + slices[:, 1] += margin + + coords_sliced = coords[(coords[:, 0] >= slices[0, 0]) & (coords[:, 0] <= slices[0, 1]) & \ + (coords[:, 1] >= slices[1, 0]) & (coords[:, 1] <= slices[1, 1]) & \ + (coords[:, 2] >= slices[2, 0]) & (coords[:, 2] <= slices[2, 1])] + + # Check that the shifted border is inside the main_object area + corrected_border_threshold = min(border_threshold, len(border)//2) + + overlap_axis = self.direction if border in ('up', 'down') else 2 + + if self._borders_overlap(border, coords_sliced, + border_threshold=corrected_border_threshold, + overlap_axis=overlap_axis) is not None: + close_borders_counter += 1 + + if close_borders_counter >= 2: + break + + # If objects have more than 2 closed borders then they are parts of the same prototype -> merge them + if close_borders_counter >= 2: + prototype_2.concat(prototype_1) + prototype_1._already_merged = True + break + + self.prototypes = [prototype for prototype in self.prototypes + if not getattr(prototype, '_already_merged', False)] + return self.prototypes + + + def split_horseshoe(self, height_ratio_threshold=0.7, height_diff_threshold=30, axis=2, frequency=5): + """ Split prototypes which looks like horseshoe. + + Under the hood, we iterate over prototype components to find sharp drop in their + height and after that a sharp increase. For example: + + ||||||||||| + ||| |||| + ||| |||| + + Parameters + ---------- + height_ratio_threshold : float in [0, 1] + Heigts ratio to decide that one component is much bigger than other. + height_diff_threshold : int + Minimal difference between heights to check that one is much bigger than other. + We have no need in splitting very small objects. + axis : {0, 1, 2} + Axis along which to check heights changing. + frequency : int + Traces iteration frequency for heights comparison. + + Returns + ------- + prototypes: list of the :class:`~.FaultPrototype` instances + Prototypes after splitting. + """ + traces_axis = 2 if axis == self.direction else self.direction + new_prototypes = [] + + for prototype in self.prototypes: + # Skip too small prototypes + if prototype.bbox[axis, 1] - prototype.bbox[axis, 0] <= height_diff_threshold: + continue + + sign = +1 + previous_height = 0 + + for line in range(prototype.bbox[traces_axis, 0], prototype.bbox[traces_axis, 1] + 1, frequency): + # Compare current and previous heights + points_ = prototype.points[prototype.points[:, traces_axis] == line, axis] + + if len(points_) == 0: + continue + + height = np.ptp(points_) + + height_ratio = min(height, previous_height) / max(height, previous_height) + height_diff = height - previous_height + + if (height_ratio <= height_ratio_threshold) and (np.abs(height_diff) > height_diff_threshold): + #pylint: disable=chained-comparison + if sign > 0 and height_diff < 0: + sign = -1 + elif sign < 0 and height_diff > 0: + sign = +1 + + # Split prototype because we found height increase after decrease + prototype, new_prototypes_ = prototype.split(split_indices=(line-frequency, None), + axis=traces_axis) + new_prototypes.extend(new_prototypes_) + + previous_height = height + + self.prototypes.extend(new_prototypes) + return self.prototypes + + + # Addons + def run(self, prolongate_in_depth=False, concat_iters=20, overlap_ratio_threshold=None, + additional_filters=False, **filtering_kwargs): + """ Recommended extracting procedure. + + The procedure is: + - extract prototypes from the point cloud; + - filter too small prototypes (for speed up, optional); + - concat connected prototypes (concat by depth axis, concat by `self.direction` axis) `concat_iters` times + with changed `overlap_ratio_threshold`; + - filter too small prototypes (for speed up, optional); + - concat embedded prototypes; + - filter all unsuitable prototypes (optional). + + Parameters + ---------- + prolongate_in_depth : bool + Whether to maximally prolongate faults in depth or not. + If True, then surfaces will be tall and thin. + If False, then surfaces will be more longer for `self.direction` than for depth axis. + This parameter affects concatenation axis order: + - if True, than we apply concat by depth axis until `overlap_ratio_threshold` reaches the minimal value; + - otherwise, we alternate concatenation by depth and `self.direction` axes. + concat_iters : int + Maximal amount of :meth:`~.concat_connected_prototypes` operations. + One operation include both concat along the depth and `self.direction` axes. + overlap_ratio_threshold : dict or None + Prototype borders overlap ratio to decide that prototypes should be concated into one. + Note, it is decrementally changed over concatenation iterations. + Keys are concatenation axes (depth and `self.direction`) and values are in the (start, stop, step) format. + additional_filters : bool + Whether to apply additional filtering for speed up. + filtering_kwargs + The :meth:`~.filter_prototypes` kwargs. + These kwargs are applied only in the filtration after whole extraction procedure. + + Returns + ------- + prototypes : list of the :class:`~.FaultPrototype` instances + Resulting prototypes. + stats : dict + Amount of prototypes after each proceeding. + """ + stats = {} + + if overlap_ratio_threshold is None: + overlap_ratio_threshold = { + self.direction: (0.9, 0.7, 0.05), # (start, stop, step) + 2: (0.9, 0.5, 0.05) + } + + depth_overlap_threshold = overlap_ratio_threshold[2][0] + direction_overlap_threshold = overlap_ratio_threshold[self.direction][0] + + # Extract prototypes from data + if len(self.prototypes) == 0: + _ = self.extract_prototypes() + stats['extracted'] = len(self.prototypes) + + # Filter for speed up + if additional_filters: + self.prototypes = self.filter_prototypes(min_height=3, min_width=3, min_n_points=10) + stats['filtered_extracted'] = len(self.prototypes) + + # Concat connected (as puzzles) prototypes + stats['after_connected_concat'] = {} + + for i in Notifier('t')(concat_iters): + stats['after_connected_concat'][i] = [] + # Concat by depth axis + _ = self.concat_connected_prototypes(overlap_ratio_threshold=depth_overlap_threshold, + axis=2) + stats['after_connected_concat'][i].append(len(self.prototypes)) + + # Concat by direction axis + if (not prolongate_in_depth) or (depth_overlap_threshold <= overlap_ratio_threshold[2][1]): + _ = self.concat_connected_prototypes(overlap_ratio_threshold=direction_overlap_threshold, + axis=self.direction) + + stats['after_connected_concat'][i].append(len(self.prototypes)) + + # Early stopping + if (depth_overlap_threshold <= overlap_ratio_threshold[2][1]) and \ + (direction_overlap_threshold <= overlap_ratio_threshold[self.direction][1]) and \ + (stats['after_connected_concat'][i][-1] == stats['after_connected_concat'][i-1][-1]): + break + + depth_overlap_threshold = round(depth_overlap_threshold - overlap_ratio_threshold[2][-1], 2) + depth_overlap_threshold = max(depth_overlap_threshold, overlap_ratio_threshold[2][1]) + + if (not prolongate_in_depth) or (depth_overlap_threshold <= overlap_ratio_threshold[2][1]): + direction_overlap_threshold = round(direction_overlap_threshold - \ + overlap_ratio_threshold[self.direction][-1], 2) + direction_overlap_threshold = max(direction_overlap_threshold, + overlap_ratio_threshold[self.direction][1]) + + # Filter for speed up + if additional_filters: + self.prototypes = self.filter_prototypes(min_height=3, min_width=3, min_n_points=10) + stats['filtered_connected_concat'] = len(self.prototypes) + + # Concat embedded + _ = self.concat_embedded_prototypes() + stats['after_embedded_concat'] = len(self.prototypes) + + # Split wrong objects + _ = self.split_horseshoe() + stats['after_split_horseshoe'] = len(self.prototypes) + return self.prototypes, stats + + def filter_prototypes(self, min_height=40, min_width=20, min_n_points=100): + """ Filer out unsuitable prototypes. + + min_height : int + Minimal preferred prototype height (along the depth axis). + min_width : int + Minimal preferred prototype width (along the `self.direction` axis). + min_n_points : int + Minimal preferred points amount. + + Returns + ------- + prototypes: list of the :class:`~.FaultPrototype` instances + Filtered prototypes. + """ + filtered_prototypes = [] + + for prototype in self.prototypes: + if (prototype.height >= min_height) and (prototype.width >= min_width) and \ + (prototype.n_points >= min_n_points): + + filtered_prototypes.append(prototype) + + return filtered_prototypes + + def prototypes_to_faults(self, field): + """ Convert all prototypes to faults. """ + faults = [Fault(prototype.coords, field=field) for prototype in self.prototypes] + return faults + + +class FromComponentExtractor(FaultExtractor): + """ Extractor for finding prototypes from provided components. + + All you need is just to run the :meth:`~.extract_from_component`.""" + def extract_one_prototype(self, component, height_threshold=0.6): + """ Extract one prototype from the point cloud starting from the provided component. + + Similar to the :meth:`.FaultExtractor.extract_one_prototype`, but this one finds prototype components to + the left and right sides of the provided one, while the original one finds only to the right. + + Parameters + ---------- + height_threshold : float in [0, 1] range, None + Neighboring components height ratio threshold. + If ratio more than threshold, then components are from one prototype. Otherwise not. + If None, then no threshold is applied. + On some slides component can be splitted into separate parts and these parts have a significant height + decrease (most frequently in Y areas). + """ + component_idx = np.argwhere(np.array(self.container[component.slide_idx]['components']) == component)[0][0] + self.container[component.slide_idx]['lengths'][component_idx] = -1 # Mark component as merged + + prototype = FaultPrototype(points=component.points, direction=self.direction, last_component=component, + proba_transform=self.proba_transform) + + # Find closest components on further slides + self._find_prototype_components(prototype=prototype, component=component, slide_step=1, + height_threshold=height_threshold) + + # Find closest components on previous slides + first_slide_idx = prototype.bbox[self.direction, 0] + first_slide_points = prototype.points[prototype.points[:, self.direction] == first_slide_idx] + component = Component(points=first_slide_points, slide_idx=first_slide_idx) + + self._find_prototype_components(prototype=prototype, component=component, slide_step=-1, + height_threshold=height_threshold) + + self.prototypes.append(prototype) + return prototype + + def _find_prototype_components(self, prototype, component, slide_step, height_threshold=0.6): + """ Find prototype components starting from the provided and going on `slide_step`. + + Similar to the :meth:`.FaultExtractor.extract_one_prototype`, but without split. + + Parameters + ---------- + height_threshold : float in [0, 1] range, optional + Neighboring components height ratio threshold. + If ratio more than threshold, then components are from one prototype. Otherwise not. + If None, then no threshold is applied. + On some slides component can be splitted into separate parts and these parts have a significant height + decrease (most frequently in Y areas). + """ + stop_slide = self.ranges[self.direction][0] if slide_step < 0 else self.ranges[self.direction][1] + previous_height = component.bbox[-2][1] - component.bbox[-2][0] + 1 + + for next_slide in range(component.slide_idx + slide_step, stop_slide, slide_step): + # Find the closest component on the the next slide to the current + component, _ = self._find_closest_component(component=component, slide_idx=next_slide, depths_threshold=20) + + if component is not None: + # TODO: think about splitting necessity + height = component.bbox[-2][1] - component.bbox[-2][0] + 1 + heights_ratio = min(height, previous_height)/max(height, previous_height) + + if (height_threshold is not None) and (heights_ratio > height_threshold): + prototype.append(component) + previous_height = height + else: + break + else: + break + + return prototype + + def find_similar_components(self, component): + """ Find components similar to the provided one in the data container. + + Similar component is the closest component on the same slide as the provided. + + Similar to the :meth:`.FaultExtractor._find_closest_component`, but finds all close components, + not the longest one. + """ + # Dilate component bbox for detecting close components + dilated_bbox = component.bbox.copy() + dilated_bbox[self.orthogonal_direction, :] += (-self._dilation // 2, self._dilation // 2) + dilated_bbox[self.orthogonal_direction, 0] = max(0, dilated_bbox[self.orthogonal_direction, 0]) + dilated_bbox[self.orthogonal_direction, 1] = min(dilated_bbox[self.orthogonal_direction, 1], + self.shape[self.orthogonal_direction]) + + closest_components = [] + + # Iter over components and find the closest one + for other_component in self.container[component.slide_idx]['components']: + # Check bboxes intersection + if not bboxes_intersected(dilated_bbox, other_component.bbox, axes=(self.orthogonal_direction, 2)): + continue + + # Check closeness of some points (as depth-wise distances) + # Faster then component overlap, but not so accurate + overlap_depths = (max(component.bbox[2, 0], other_component.bbox[2, 0]), + min(component.bbox[2, 1], other_component.bbox[2, 1])) + + # Select valid coords for distances finding + valid_depths = component.coords[(component.coords[:, -1] >= overlap_depths[0]) & \ + (component.coords[:, -1] <= overlap_depths[1]), -1] + + indices_1 = np.in1d(component.coords[:, -1], valid_depths) + indices_2 = np.in1d(other_component.coords[:, -1], valid_depths) + + coords_1 = component.coords[indices_1, self.orthogonal_direction] + coords_2 = other_component.coords[indices_2, self.orthogonal_direction] + + components_distances = compute_distances(coords_1, coords_2, max_threshold=100) + + if (components_distances[0] == -1) or (components_distances[0] > 1): + # Components are not close + continue + + closest_components.append(other_component) + + return closest_components + + def extract_from_component(self, component): + """ Extract prototypes which conclude the provided component. """ + prototypes = [] + closest_components = self.find_similar_components(component=component) + + for component_ in closest_components: + prototype = self.extract_one_prototype(component=component_) + prototypes.append(prototype) + + return prototypes + + +class Component: + """ Extracted 2D connected component. + + Parameters + ---------- + points : np.ndarray of (N, 4) shape + Spatial coordinates and probabilities in the (ilines, xlines, depths, proba) format. + Sorting is not required. Also usually `points` created in :class:`.~FaultExtractor` will be unsorted. + slide_idx : int + Index of the slide from which component was extracted. + bbox : np.ndarray of (3, 2) shape + 3D bounding box. + length : int + Component length. + """ + def __init__(self, points, slide_idx, bbox=None, length=None): + self.points = points + self.slide_idx = slide_idx + + self._bbox = bbox + + + @property + def coords(self): + """ Spatial coordinates in the (ilines, xlines, depths) format.""" + return self.points[:, :3] + + @property + def bbox(self): + """ 3D bounding box. """ + if self._bbox is None: + self._bbox = np.column_stack([np.min(self.coords, axis=0), np.max(self.coords, axis=0)]) + return self._bbox + + def __len__(self): + """ Number of points in a component. """ + return len(self.points) + + + def split(self, split_indices): + """ Depth-wise component split by indices. + + Parameters + ---------- + split_indices : sequence of two ints or None + Depth values (upper and lower) to split component into parts. If None, then no need in split. + + Returns + ------- + self : `~.Component` instance + The most closest component to the `self` after split. + new_components : list of `~.Component` instances + Components created from splitted parts. + """ + new_components = [] + + # Cut upper part of the component and save it as another item + if split_indices[0] is not None: + # Extract closest part + mask = self.points[:, 2] >= split_indices[0] + self, new_component = self._split_by_mask(mask=mask) + + new_components.append(new_component) + + # Cut lower part of the component and save it as another item + if split_indices[1] is not None: + # Extract closest part + mask = self.points[:, 2] <= split_indices[1] + self, new_component = self._split_by_mask(mask=mask) + + new_components.append(new_component) + + return self, new_components + + def _split_by_mask(self, mask): + """ Split component into two parts by boolean mask. + + Returns + ------- + self : `~.Component` instance + The most closest component to the `self` after split. + new_component : `~.Component` instance + Component created from splitted part. + """ + # Create new Component from extra part + new_component_points = self.points[~mask] + new_component = Component(points=new_component_points, slide_idx=self.slide_idx) + + # Extract suitable part + self.points = self.points[mask] + self._bbox = None + return self, new_component + + + +class FaultPrototype: + """ Class for faults prototypes. Provides a necessary API for convenient prototype extraction process. + + Note, the `last_component` parameter is preferred during the extraction from 3D volume and is optional: + it is used for finding closest components on next slides. + + Parameters + ---------- + points : np.ndarray of (N, 4) shape + Prototype coordinates and probabilities. + Sorting is not required. Also usually `points` created in :class:`.~FaultExtractor` will be unsorted. + direction : {0, 1} + Direction along which the prototype is extracted (the same as prediction direction). + last_component : instance of :class:`~.Component` + The last added component into prototype. Useful during the extraction from 3D data volume. + """ + def __init__(self, points, direction, last_component=None, proba_transform=None): + self.points = points + self.direction = direction + self.proba_transform = proba_transform + + self._bbox = None + + self._last_component = last_component + + self._contour = None + self._borders = {} + + # Properties + @property + def coords(self): + """ Spatial coordinates in (ilines, xlines, depth) format. """ + return self.points[:, :3] + + @property + def bbox(self): + """ 3D bounding box. """ + if self._bbox is None: + self._bbox = np.column_stack([np.min(self.coords, axis=0), np.max(self.coords, axis=0)]) + return self._bbox + + # Stats for filtering + @property + def height(self): + """ Height (along the depth axis). """ + return self.bbox[2, 1] - self.bbox[2, 0] + + @property + def width(self): + """ Width (along the `self.direction` axis). """ + return self.bbox[self.direction, 1] - self.bbox[self.direction, 0] + + @property + def n_points(self): + """ Amount of the surface points. """ + return len(self.points) + + @property + def proba(self): + """ 90% percentile of approximate proba values in [0, 1] interval. """ + proba_value = np.percentile(self.points[:, 3], 90) # is integer value from 0 to 255 + if self.proba_transform is not None: + proba_value = self.proba_transform(proba_value) + return proba_value + + @property + def max_proba(self): + """ Maximum of approximate proba values in [0, 1] interval. """ + proba_value = np.max(self.points[:, 3]) + if self.proba_transform is not None: + proba_value = self.proba_transform(proba_value) + return proba_value + + # Properties for internal needs + @property + def last_component(self): + """ Last added component. """ + if self._last_component is None: + last_slide_idx = self.points[:, self.direction].max() + + component_points = self.points[self.points[:, self.direction] == last_slide_idx] + self._last_component = Component(points=component_points, slide_idx=last_slide_idx) + return self._last_component + + + # Contouring + @property + def contour(self): + """ Contour of 2D projection on axis, orthogonal to the extraction direction. + + Note, output projection axis coordinates are zeros. + """ + if self._contour is None: + projection_axis = 1 - self.direction + self._contour = find_contour(coords=self.coords, projection_axis=projection_axis) + return self._contour + + def get_border(self, border, projection_axis): + """ Get contour border. + + Parameters + ---------- + border : {'up', 'down', 'left', 'right'} + Which object border to get. + projection_axis : {0, 1} + Which projection is used to get the 2D contour coordinates. + + Returns + ------- + border : np.ndarray of (N, 3) shape + Sorted coordinates of the requested border. + """ + if border not in self._borders: + # Delete extra border from contour + # For border removing we apply groupby which works only for the last axis, so we swap axes coords + if border in ('left', 'right'): + border_coords = self.contour.copy() + border_coords[:, [-1, 1-projection_axis]] = border_coords[:, [1-projection_axis, -1]] + border_coords = border_coords[border_coords[:, 1-projection_axis].argsort()] # Groupby needs sorted data + else: + border_coords = self.contour + + # Delete border by applying groupby + if border not in ('up', 'left'): + border_coords = groupby_max(border_coords) + else: + border_coords = groupby_min(border_coords) + + # Restore 3D coordinates + projection_axis = 1 - self.direction + + if border in ('left', 'right'): + border_coords[:, [-1, 1-projection_axis]] = border_coords[:, [1-projection_axis, -1]] + + border_coords = restore_coords_from_projection(coords=self.coords, projection_buffer=border_coords, + axis=projection_axis) + self._borders[border] = border_coords + + return self._borders[border] + + + # Extension operations + def append(self, component): + """ Append new component into prototype. + + Parameters + ---------- + component : instance of :class:`~.Component` + Component to add into the prototype. + """ + self.points = np.vstack([self.points, component.points]) + + self._contour = None + self._borders = {} + + self._last_component = component + + self._bbox = self._concat_bbox(component.bbox) + + def concat(self, other): + """ Concatenate two prototypes. """ + self.points = np.vstack([self.points, other.points]) + + self._bbox = self._concat_bbox(other.bbox) + + self._contour = None + self._borders = {} + + self._last_component = None + + def _concat_bbox(self, other_bbox): + """ Concat bboxes of two objects into one. """ + bbox = np.empty((3, 2), np.int32) + bbox[:, 0] = np.min((self.bbox[:, 0], other_bbox[:, 0]), axis=0) + bbox[:, 1] = np.max((self.bbox[:, 1], other_bbox[:, 1]), axis=0) + return bbox + + + # Split operations + def split(self, split_indices, axis=2): + """ Axis-wise prototype split by indices. + + Parameters + ---------- + split_indices : sequence of two ints or None + Axis values (upper and lower) to split prototype into parts. If None, then no need in split. + + Returns + ------- + prototype : `~.FaultPrototype` instance + The closest prototype to the `self` after splitting. + new_prototypes : list of `~.FaultPrototype` instances + Prototypes created from splited parts. + """ + new_prototypes = [] + + # No splitting applied + if (split_indices[0] is None) and (split_indices[1] is None): + return self, new_prototypes + + objects_separating_axis = self.direction if axis in (-1, 2) else 2 + + # Cut upper part and separate disconnected objects + if (split_indices[0] is not None) and \ + (np.min(self.points[:, axis]) < split_indices[0] < np.max(self.points[:, axis])): + mask = self.points[:, axis] >= split_indices[0] + + self, new_prototypes_ = self._split_by_mask(mask=mask, objects_separating_axis=objects_separating_axis) + new_prototypes.extend(new_prototypes_) + + # Cut lower part and separate disconnected objects + if (split_indices[1] is not None) and \ + (np.min(self.points[:, axis]) < split_indices[1] < np.max(self.points[:, axis])): + mask = self.points[:, axis] <= split_indices[1] + + self, new_prototypes_ = self._split_by_mask(mask=mask, objects_separating_axis=objects_separating_axis) + new_prototypes.extend(new_prototypes_) + + new_prototypes.extend(self._separate_objects(self.points, axis=objects_separating_axis)) + + # Update self + self.points = new_prototypes[-1].points + self._bbox = new_prototypes[-1].bbox + self._contour = None + self._borders = {} + self._last_component = None + return self, new_prototypes[:-1] + + def _split_by_mask(self, mask, objects_separating_axis): + """ Split prototype into parts by boolean mask. + + Returns + ------- + prototype : `~.FaultPrototype` instance + The closest prototype to the `self` after splitting. + new_prototypes : list of `~.FaultPrototype` instances + Prototypes created from splited parts. + """ + # Create new prototypes from extra part + new_prototype_points = self.points[~mask] + + if len(new_prototype_points) > 0: + new_prototypes = self._separate_objects(new_prototype_points, axis=objects_separating_axis) + + # Extract suitable part + self.points = self.points[mask] + return self, new_prototypes + + def _separate_objects(self, points, axis): + """ Separate points into different objects depend on their connectedness. + + After split we can have the situation when splitted part has more than one connected item. + This method separate disconnected parts into different prototypes. + + Returns + ------- + prototypes: list of the :class:`~.FaultPrototype` instances + Prototypes created from the separated parts. + """ + # Get coordinates along the axis + unique_direction_points = np.unique(points[:, axis]) + + # Slides distance more than 1 -> different objects + split_indices = np.nonzero(unique_direction_points[1:] - unique_direction_points[:-1] > 1)[0] + + if len(split_indices) == 0: + return [FaultPrototype(points=points, direction=self.direction, proba_transform=self.proba_transform)] + + # Separate disconnected objects and create new prototypes instances + start_indices = unique_direction_points[split_indices + 1] + start_indices = np.insert(start_indices, 0, 0) + + end_indices = unique_direction_points[split_indices] + end_indices = np.append(end_indices, unique_direction_points[-1]) + + prototypes = [] + + for start_idx, end_idx in zip(start_indices, end_indices): + points_ = points[(start_idx <= points[:, axis]) & (points[:, axis] <= end_idx)] + prototype = FaultPrototype(points=points_, direction=self.direction, proba_transform=self.proba_transform) + prototypes.append(prototype) + + return prototypes + + + +# Helpers +def get_range(coords, axis, diff_threshold=2): + """ Get the longest sequential range of coords on axis. + + Helper for the :meth:`~.FaultExtractor._borders_overlap`. + + Parameters + ---------- + coords : set of tuples of three ints + Coordinates in (iline, xline, depth) format. + axis : {0, 1, 2} + Axis on which to get coordinates range. + diff_threshold : int + Maximal possible difference between points values in one sequential range. + + Returns + ------- + overlap_range : tuple of two ints + The longest sequential range on the `axis` for provided coords. + Sequential range is the orderly sequence of coords with difference in values not more than `diff_threshold`. + """ + # Extract values + values = list(set(elem[axis] for elem in coords)) + values.sort() + + # Find sequential ranges + diff = np.diff(values) + + split_indices = np.argwhere(diff > diff_threshold).reshape(-1) + + if len(split_indices) == 0: + return (np.min(values), np.max(values)) + + ranges = [split_indices[0] + 1, *np.diff(split_indices), len(values) - split_indices[-1] - 1] + + # Find the longest range + longest_range_idx = np.argmax(ranges) + + if longest_range_idx == len(ranges) - 1: + range_ = (split_indices[-1] + 1, len(values) - 1) + elif longest_range_idx == 0: + range_ = (0, split_indices[0]) + else: + range_ = (split_indices[longest_range_idx-1] + 1, split_indices[longest_range_idx]) + + return (values[range_[0]], values[range_[1]]) diff --git a/seismiqb/labels/fault/filtering_utils.py b/seismiqb/labels/fault/filtering_utils.py new file mode 100644 index 0000000..1ade41d --- /dev/null +++ b/seismiqb/labels/fault/filtering_utils.py @@ -0,0 +1,399 @@ +""" Faults utils: filterings, groupings. """ +from collections import defaultdict +import numpy as np +from .coords_utils import bboxes_adjacent, dilate_coords + + +# Filters +# Filter too small faults +def filter_faults(faults, min_length_threshold=2000, min_height_threshold=20, min_n_points_threshold=30, + **sticks_kwargs): + """ Filter too small faults. + + Faults are filtered by amount of points, length and height. + Used as default filtering after prototypes extraction. + + Parameters + ---------- + faults : sequence of :class:`~.Fault` instances + Faults for filtering. + min_length_threshold : int + Filter out faults with length less than `min_length_threshold`. + min_height_threshold : int + Filter out faults with height less than `min_height_threshold`. + Note, that height is evaluated from sticks. + sticks_kwargs : dict, optional + Arguments for fault conversion into sticks view. + """ + config_sticks = { + 'sticks_step': 10, + 'stick_nodes_step': 10, + 'move_bounds': False, + **sticks_kwargs + } + + filtered_faults = [] + + for fault in faults: + if (len(fault.points) < min_n_points_threshold) or (len(fault) < min_length_threshold): + continue + + fault.points_to_sticks(sticks_step=config_sticks['sticks_step'], + stick_nodes_step=config_sticks['stick_nodes_step'], + move_bounds=config_sticks['move_bounds']) + + if len(fault.sticks) <= 2: # two sticks are not enough + continue + + if np.concatenate([item[:, 2] for item in fault.sticks]).ptp() < min_height_threshold: + continue + + filtered_faults.append(fault) + + return filtered_faults + + +# Filter small disconnected faults +def filter_disconnected_faults(faults, direction=0, height_threshold=200, width_threshold=40, **kwargs): + """ Filter small enough faults without any adjacent neighbors. + + Parameters + ---------- + faults : sequence of :class:`~.Fault` or :class:`~.FaultPrototype` instances + Faults for filtering. + direction : {0, 1} + Faults direction. + height_threshold : int + Filter out disconnected faults with height less than `height_threshold`. + width_threshold : int + Filter out disconnected faults with width less than `width_threshold`. + **kwargs : dict + Adjacency kwargs for :func:`._group_adjacent_faults`. + """ + # Create groups of adjacent faults + groups, _ = _group_adjacent_faults(faults, **kwargs) + + grouped_faults_indices = set(groups.keys()) + + for group_members in groups.values(): + grouped_faults_indices = grouped_faults_indices.union(group_members) + + # Filtering + filtered_faults = [] + + for i, fault in enumerate(faults): + if i in grouped_faults_indices: + filtered_faults.append(fault) + + else: + height = fault.bbox[2, 1] - fault.bbox[2, 0] + width = fault.bbox[direction, 1] - fault.bbox[direction, 0] + + if height > height_threshold or width > width_threshold: + filtered_faults.append(fault) + + return filtered_faults + +def _group_adjacent_faults(faults, adjacency=5, adjacent_points_threshold=5): + """ Add faults into groups by adjacency criterion. + + Helper for the :func:`~.filter_disconnected_faults`. + + Parameters + ---------- + faults : sequence of :class:`~.Fault` or :class:`~.FaultPrototype` instances + Faults for filtering. + adjacency : int + Axis-wise distance between two faults to consider them to be grouped. + adjacent_points_threshold : int + Minimal amount of points into adjacency area to consider two faults are in one group. + """ + # Containers for adjacency graph + groups = {} # group owner -> items + owners = {} # item -> group owner + + for i, fault_1 in enumerate(faults): + if i not in owners.keys(): + owners[i] = i + + for j, fault_2 in enumerate(faults[i+1:]): + adjacent_borders = bboxes_adjacent(fault_1.bbox, fault_2.bbox, adjacency=adjacency) + + if adjacent_borders is None: + continue + + # Check points amount in the adjacency area + for fault in (fault_1, fault_2): + adjacent_points = fault.points[(fault.points[:, 0] >= adjacent_borders[0][0]) & \ + (fault.points[:, 0] <= adjacent_borders[0][1]) & \ + (fault.points[:, 1] >= adjacent_borders[1][0]) & \ + (fault.points[:, 1] <= adjacent_borders[1][1]) & \ + (fault.points[:, 2] >= adjacent_borders[2][0]) & \ + (fault.points[:, 2] <= adjacent_borders[2][1])] + + if len(adjacent_points) < adjacent_points_threshold: + adjacent_borders = None + break + + if adjacent_borders is None: + continue + + # Graph update + owners[i+1+j] = owners[i] + + if owners[i] not in groups.keys(): + groups[owners[i]] = set() + + groups[owners[i]].add(i+1+j) + + return groups, owners + + + +# Groupings +# Group connected faults +def group_connected_prototypes(prototypes, connectivity_stats=None, ratio_threshold=0.0): + """ Group connected prototypes. + + Connected prototypes are prototypes where at least one prototype has border overlap + with another more than `ratio_threshold`. + + Parameters + ---------- + prototypes : sequence of :class:`~.FaultPrototype` instances + Prototypes for grouping. + You can use this method with :class:`~.Fault` instances after conversion. + connectivity_stats : dict or None, optional + Output of :meth:`.eval_connectivity_stats`. + Can be useful for multiple calls with different `ratio_threshold` values. + ratio_threshold : float + Overlap ratio to consider that prototypes are connected and can be grouped together. + """ + # Eval connectivity stats + if connectivity_stats is None: + connectivity_stats = eval_connectivity_stats(prototypes) + + # Unpack connectivity graph info + owners = {} # item -> owner + groups = defaultdict(set) # owner -> set(items) + + for axis in (2, prototypes[0].direction): + connectivity_stats_axis = connectivity_stats[axis] + + for prototype_1_idx, connect in connectivity_stats_axis.items(): + for prototype_2_idx, stat_values in connect.items(): + + if stat_values['overlap_ratio'] > ratio_threshold: + owners, groups = _add_connected_pair(prototype_1_idx, prototype_2_idx, owners=owners, groups=groups) + + # Label prototypes group + for idx, label in enumerate(prototypes): + label.group_idx = idx + + for group_owner_idx, group_items in groups.items(): + prototypes[group_owner_idx].group_idx = group_owner_idx + + for item_idx in group_items: + prototypes[item_idx].group_idx = group_owner_idx + + return prototypes + +def eval_connectivity_stats(prototypes): + """ Evaluation of overlap length and ratio for each prototypes pair. + + Note, zero-overlapping stats are omitted. + + It is a simplified version of `~.FaultExtractor.concat_connected_prototypes`. + """ + direction = prototypes[0].direction + orthogonal_direction = 1 - direction + + margin = 1 # local constant for code prettifying + borders_to_check = {2: ('up', 'down'), direction: ('left', 'right')} + + connectivity_stats = {2: defaultdict(dict), direction: defaultdict(dict)} + + for i, prototype_1 in enumerate(prototypes): + for j, prototype_2 in enumerate(prototypes[i+1:]): + # Check prototypes adjacency + adjacent_borders = bboxes_adjacent(prototype_1.bbox, prototype_2.bbox) + + if adjacent_borders is None: + continue + + for axis in (2, direction): + check_borders = borders_to_check[axis] + + # Find object contours on close borders + is_first_upper = prototype_1.bbox[axis, 0] < prototype_2.bbox[axis, 0] + + contour_1 = prototype_1.get_border(border=check_borders[is_first_upper], + projection_axis=orthogonal_direction) + contour_2 = prototype_2.get_border(border=check_borders[~is_first_upper], + projection_axis=orthogonal_direction) + + # Get border contours in the area of interest + overlap_range = (min(adjacent_borders[axis]) - margin, max(adjacent_borders[axis]) + margin) + + contour_1 = contour_1[(contour_1[:, axis] >= overlap_range[0]) & \ + (contour_1[:, axis] <= overlap_range[1])] + contour_2 = contour_2[(contour_2[:, axis] >= overlap_range[0]) & \ + (contour_2[:, axis] <= overlap_range[1])] + + # If one data contour is much longer than other, then we can't connect them as puzzle details + if len(contour_1) == 0 or len(contour_2) == 0: + continue + + # Shift one of the objects, making their contours intersected + shift = 1 if is_first_upper else -1 + contour_1[:, axis] += shift + + # Save stats + overlap_1, overlap_1_ratio = _contours_overlap_stats(contour_1, contour_2, + dilation_direction=orthogonal_direction) + overlap_2, overlap_2_ratio = _contours_overlap_stats(contour_2, contour_1, + dilation_direction=orthogonal_direction) + + if overlap_1 > 0: + connectivity_stats[axis][i][j+i+1] = {'overlap_length': overlap_1, 'overlap_ratio': overlap_1_ratio} + connectivity_stats[axis][j+i+1][i] = {'overlap_length': overlap_2, 'overlap_ratio': overlap_2_ratio} + + return connectivity_stats + +def _contours_overlap_stats(contour_1, contour_2, dilation_direction, dilation=3): + """ Evaluate contours overlap. + + Under the hood, we eval `contour_1` overlap statistics with dilated `contour_2`, + because we suppsose that connected prototypes can be shifted to each other. + """ + contour_1_set = set(tuple(x) for x in contour_1) + + # Objects can be shifted on `dilation_direction`, so apply dilation for coords + contour_2_dilated = dilate_coords(coords=contour_2, dilate=dilation, + axis=dilation_direction) + + contour_2_dilated = set(tuple(x) for x in contour_2_dilated) + + # Eval stats + overlap = contour_1_set.intersection(contour_2_dilated) + return len(overlap), len(overlap)/len(contour_1_set) + +def _add_connected_pair(prototype_1_idx, prototype_2_idx, owners, groups): + """ Add prototypes pair into group. + + We save connectivity info into two dicts: + - owners (item -> owner) - information about which group the item belongs to; + - groups (owner -> [items]) - information about which items are in the group. + Items and owners here are prototypes indices. + """ + if (prototype_1_idx not in owners) and (prototype_2_idx not in owners): + # Add both, because they are new + owners[prototype_1_idx] = prototype_1_idx + owners[prototype_2_idx] = prototype_1_idx + + groups[prototype_1_idx].add(prototype_2_idx) + + elif (prototype_1_idx not in owners) and (prototype_2_idx in owners): + # Add first into second + owners[prototype_1_idx] = owners[prototype_2_idx] + + groups[owners[prototype_2_idx]].add(prototype_1_idx) + + elif (prototype_1_idx in owners) and (prototype_2_idx not in owners): + # Add second into first + owners[prototype_2_idx] = owners[prototype_1_idx] + + groups[owners[prototype_1_idx]].add(prototype_2_idx) + + else: + # Merge two groups + main_owner = owners[prototype_1_idx] + other_owner = owners[prototype_2_idx] + + if main_owner != other_owner: + for item in groups[other_owner]: + owners[item] = main_owner + + groups[main_owner].update(groups[other_owner]) + groups[main_owner].add(other_owner) + + del groups[other_owner] + + return owners, groups + + +# Group faults with topK biggest faults and filter faults out of groups +def groups_with_biggest_faults(faults, height_threshold=None, groups_num=None, + adjacency=5, adjacent_points_threshold=5): + """ Get faults which can be merged in groups with the biggest faults. + + The biggest faults are faults with height more than `height_threshold` or + which have topK-height, where K is `groups_num`. + + Groups are formed with adjacent faults. + + Note, that one of `height_threshold` or `groups_num` should be provided. + + Parameters + ---------- + faults : sequence of :class:`~.Fault` or :class:`~.FaultPrototype` instances + Faults for filtering. + height_threshold : int or None + Height threshold to consider that fault is big enough for being the biggest fault in the group. + Group is a set of faults, adjoint with the biggest fault. + groups_num : int or None + Amount of groups to return. + Under the hood, we find `groups_num` biggest faults and use the minimal height as threshold. + adjacency : int + Axis-wise distance between two faults to consider them to be grouped. + adjacent_points_threshold : int + Minimal amount of fault points into adjacency area to consider that two faults are in one group. + """ + #pylint: disable=invalid-unary-operand-type + if (groups_num is None) and (height_threshold is None): + raise ValueError("One of `groups_num` or `height_threshold` must be not None!") + + # Get height threshold from groups num + if height_threshold is None: + heights = [fault.bbox[-1][1]-fault.bbox[-1][0]+1 for fault in faults] + height_threshold = np.sort(heights)[-groups_num:-groups_num+1] + + # Find neighbors for the biggest faults and faults, that are included in groups with the biggest faults + filtered_faults = [] + + for fault_1 in faults: + if (fault_1 not in filtered_faults) and (fault_1.bbox[-1][1] - fault_1.bbox[-1][0] + 1 < height_threshold): + continue + + if fault_1 not in filtered_faults: + filtered_faults.append(fault_1) + + for fault_2 in faults: + if fault_2 in filtered_faults: + continue + + adjacent_borders = bboxes_adjacent(fault_1.bbox, fault_2.bbox, adjacency=adjacency) + + if adjacent_borders is None: + continue + + # Check points amount in the adjacency area + for fault in (fault_1, fault_2): + adjacent_points = fault.points[(fault.points[:, 0] >= adjacent_borders[0][0]) & \ + (fault.points[:, 0] <= adjacent_borders[0][1]) & \ + (fault.points[:, 1] >= adjacent_borders[1][0]) & \ + (fault.points[:, 1] <= adjacent_borders[1][1]) & \ + (fault.points[:, 2] >= adjacent_borders[2][0]) & \ + (fault.points[:, 2] <= adjacent_borders[2][1])] + + if len(adjacent_points) < adjacent_points_threshold: + adjacent_borders = None + break + + if adjacent_borders is None: + continue + + if fault_2 not in filtered_faults: + filtered_faults.append(fault_2) + + return filtered_faults diff --git a/seismiqb/labels/fault/formats.py b/seismiqb/labels/fault/formats.py new file mode 100644 index 0000000..f0e05bd --- /dev/null +++ b/seismiqb/labels/fault/formats.py @@ -0,0 +1,328 @@ +""" Mixins to deal with fault storing files. """ + +import os +import glob +import warnings + +import numpy as np +import pandas as pd +from sklearn.decomposition import PCA + +from .postprocessing import split_array +from ...utils import CharismaMixin, SQBStorage, make_interior_points_mask + +class FaultSticksMixin(CharismaMixin): + """ Mixin to load, process and dump FaultSticks files. """ + FAULT_STICKS_SPEC = ['inline_marker', 'INLINE_3D', 'CROSSLINE_3D', 'CDP_X', 'CDP_Y', 'DEPTH', 'name', 'number'] + REDUCED_FAULT_STICKS_SPEC = ['INLINE_3D', 'CROSSLINE_3D', 'DEPTH', 'name', 'number'] + + @classmethod + def read_df(cls, path): + """ Automatically detect format of csv-like file and create pandas.DataFrame from FaultSticks/CHARISMA file. """ + with open(path, encoding='utf-8') as file: + line_len = len([item for item in file.readline().split(' ') if len(item) > 0]) + + if line_len == 0: + return pd.DataFrame({}) + + if line_len == 3: + names = cls.REDUCED_CHARISMA_SPEC + elif line_len == 5: + names = cls.REDUCED_FAULT_STICKS_SPEC + elif line_len == 8: + names = cls.FAULT_STICKS_SPEC + elif line_len >= 9: + names = cls.CHARISMA_SPEC + else: + raise ValueError('Fault labels must be in FAULT_STICKS, CHARISMA or REDUCED_CHARISMA format.') + + return pd.read_csv(path, sep=r'\s+', names=names) + + def split_df_into_sticks(self, df, return_direction=False): + """ Group nodes in FaultSticks dataframe into sticks. + + Parameters + ---------- + df : pandas.DataFrame + FaultSticks + return_direction : bool, optional + Whether return direction of fault, by default False. + + Returns + ------- + pandas.Series or (pandas.Series, int) + Sequence of stick nodes and (optionally) direction of the fault. + """ + col, direction = None, None + + ilines_diff = sum(df['INLINE_3D'][1:].values - df['INLINE_3D'][:-1].values == 0) + xlines_diff = sum(df['CROSSLINE_3D'][1:].values - df['CROSSLINE_3D'][:-1].values == 0) + if ilines_diff > xlines_diff: # Use iline as an index + col = 'INLINE_3D' + direction = 0 + else: # Use xline as an index + col = 'CROSSLINE_3D' + direction = 1 + + if 'number' in df.columns: # Dataframe has stick index + col = 'number' + + if col is None: + raise ValueError('Wrong format of sticks: there is no column to group points into sticks.') + + df = df.sort_values('DEPTH') + sticks = df.groupby(col).apply(lambda x: x[self.COLUMNS].values).reset_index(drop=True) + + return (sticks, direction) if return_direction else sticks + + def remove_broken_sticks(self, sticks): + """ Remove sticks with one node and remove sticks from fault with one stick. """ + # Remove sticks with one node. + mask = sticks.apply(len) > 1 + if not mask.all(): + warnings.warn(f'{self.name}: Fault has one-point sticks.') + sticks = sticks.loc[mask] + + # Filter faults with one stick. + if len(sticks) == 1: + warnings.warn(f'{self.name}: Fault has an only one stick') + sticks = pd.Series() + elif len(sticks) == 0: + warnings.warn(f'{self.name}: Empty file') + sticks = pd.Series() + + return sticks + + def load_fault_sticks(self, path, transform=True, verify=True, + recover_lines=True, remove_broken_sticks=False, **kwargs): + """ Get sticks from FaultSticks file. + + Parameters + ---------- + path : str + Path to file. + transform : bool, optional + Whether transform from cubic coordinates to line or not, by default True + verify : bool, optional + Filter points outside of the cube, by default True + recover_lines : bool, optional + Fill broken iline/crossline coordinate (extremely large values) from CDP, by default True + remove_broken_sticks : bool, optional + Whether remove sticks with one node and remove sticks from fault with one stick, + by default False + """ + if isinstance(path, str): + df = self.read_df(path) + else: + df = path + + if len(df) == 0: + self._sticks = [[]] + self.direction = 1 + return + + if recover_lines and 'CDP_X' in df.columns: + df = self.recover_lines_from_cdp(df) + + points = df[self.REDUCED_CHARISMA_SPEC].values + + if transform: + points = self.field_reference.geometry.lines_to_ordinals(points) + df[self.REDUCED_CHARISMA_SPEC] = np.round(points).astype(np.int32) + + if verify: + mask = make_interior_points_mask(points, self.field_reference.shape) + df = df.iloc[mask] + + if len(df) == 0: + self._sticks = None + return + + sticks, direction = self.split_df_into_sticks(df, return_direction=True) + if remove_broken_sticks: + sticks = self.remove_broken_sticks(sticks) + + # Order sticks with respect of fault direction. Is necessary to perform following triangulation. + if len(sticks) > 1: + pca = PCA(1) + coords = pca.fit_transform(np.array([stick[0][:2] for stick in sticks.values])) + indices = np.array([i for _, i in sorted(zip(coords, range(len(sticks))))]) + sticks = sticks.iloc[indices] + + self._sticks = sticks.values + + # fix several slides sticks + if direction is not None: + ptp = np.array([np.ptp(stick[:, direction]) for stick in self.sticks]) + if (ptp > 2).any(): + warnings.warn(f"{self.name}: there sticks on several slides in both directions") + + for stick in self.sticks[np.logical_and(ptp > 0, ptp <= 2)]: + stick[:, direction] = stick[0, direction] + + self.direction = direction + self.stick_orientation = 2 + + def dump_fault_sticks(self, path): + """ Dump fault sticks into FaultSticks format. """ + path = self.field.make_path(path, name=self.field.short_name, makedirs=False) + + sticks_df = [] + for stick_idx, stick in enumerate(self.sticks): + stick = self.field.geometry.ordinals_to_lines(stick).astype(int) + cdp = self.field.geometry.lines_to_cdp(stick[:, :2]) + df = { + 'inline_marker': 'INLINE-', + 'INLINE_3D': stick[:, 0], + 'CROSSLINE_3D': stick[:, 1], + 'CDP_X': cdp[:, 0], + 'CDP_Y': cdp[:, 1], + 'DEPTH': stick[:, 2], + 'name': os.path.basename(path), + 'number': stick_idx + } + sticks_df.append(pd.DataFrame(df)) + sticks_df = pd.concat(sticks_df) + sticks_df.to_csv(path, header=False, index=False, sep=' ') + + def show_file(self): + """ Show content of the initial FaultSticks file as a text. """ + with open(self.path, encoding='utf-8') as f: + print(f.read()) + + @classmethod + def check_format(cls, path, verbose=False): + """ Find errors in fault file. + + Parameters + ---------- + path : str + Path to file or glob expression + verbose : bool + Response if file is successfully read. + """ + for filename in glob.glob(path): + if os.path.splitext(filename)[1] == '.dvc': + continue + try: + df = cls.read_df(filename) + sticks = cls.split_df_into_sticks(cls, df) + except ValueError: + print(filename, ': wrong format') + else: + if 'name' in df.columns and len(df.name.unique()) > 1: + print(filename, ': file must be splitted.') + continue + + if len(sticks) == 1: + print(filename, ': fault has an only one stick') + continue + + if any(len(item) == 1 for item in sticks): + print(filename, ': fault has one point stick') + continue + mask = sticks.apply(lambda x: len(np.unique(np.array(x)[:, 2])) == len(x)) + if not mask.all(): + print(filename, ': fault has horizontal parts of sticks.') + continue + + if verbose: + print(filename, ': OK') + + @classmethod + def split_charisma(cls, path): + """ Split file with multiple faults (indexed by 'name' column) into separate dataframes. """ + df = cls.read_df(path) + if 'name' in df.columns: + return dict(list(df.groupby('name'))) + return {path: df} + + @classmethod + def _fault_to_csv(cls, df, dst): + """ Save the fault to csv. """ + df.to_csv(os.path.join(dst, df.name), sep=' ', header=False, index=False) + + +class FaultSerializationMixin: + """ Mixin for npy/npz storage of fault components (points, sticks, nodes, simplices). """ + def load_npz(self, path, transform=False): + """ Load fault points, nodes and sticks from npz file. """ + npzfile = np.load(path, allow_pickle=False) + + sticks = npzfile.get('sticks') + sticks_labels = npzfile.get('sticks_labels') + + self.from_dict({ + 'points': npzfile.get('points'), + 'nodes': npzfile.get('nodes'), + 'simplices': npzfile.get('simplices'), + 'sticks': self._labeled_array_to_sticks(sticks, sticks_labels) if sticks is not None else None, + }, transform=transform) + + direction = npzfile.get('direction') + if direction is not None: + direction = int(direction) + self.direction = direction + + def load_npy(self, path): + """ Load fault points from npy file. """ + points = np.load(path, allow_pickle=False) + self._points = points + + def dump_npz(self, path, attributes_to_create=None): + """ Dump fault to npz. """ + path = self.field.make_path(path, name=self.short_name, makedirs=False) + + if attributes_to_create: + if isinstance(attributes_to_create, str): + attributes_to_create = [attributes_to_create] + for item in attributes_to_create: + getattr(self, item) + + kwargs = {'direction': self.direction} + if self.has_component('sticks'): + sticks, sticks_labels = self._sticks_to_labeled_array(self.sticks) + kwargs['sticks'] = sticks + kwargs['sticks_labels'] = sticks_labels + + for item in ['points', 'nodes', 'simplices']: + if self.has_component(item): + kwargs[item] = getattr(self, item) + + np.savez(path, **kwargs) + + + def load_sqb(self, path): + """ Load fault from SQB file. """ + storage = SQBStorage(path) + if storage.get('type') != 'fault': + raise TypeError('SQB storage is not marked as fault!') + + self.from_dict({key : storage[key] for key in ['points', 'nodes', 'simplices', 'sticks']}) + self.direction = storage['direction'] + + def dump_sqb(self, path): + """ Dump fault to SQB file. """ + storage = SQBStorage(path) + storage.update({ + 'type': 'fault', + 'points': self.points, + 'nodes': self.nodes, + 'simplices': self.simplices, + 'sticks': self.sticks, + 'direction': self.direction + }) + + + def _sticks_to_labeled_array(self, sticks): + """ Auxilary method to dump fault into npz with allow_pickle=False. """ + labels = sum([[i] * len(item) for i, item in enumerate(sticks)], []) + return np.concatenate(sticks), labels + + def _labeled_array_to_sticks(self, sticks, labels): + """ Auxilary method to dump fault into npz with allow_pickle=False. """ + sticks = split_array(sticks, labels) + array = np.empty(len(sticks), dtype=object) + for i, item in enumerate(sticks): + array[i] = item + return array diff --git a/seismiqb/labels/fault/postprocessing.py b/seismiqb/labels/fault/postprocessing.py new file mode 100644 index 0000000..44db01a --- /dev/null +++ b/seismiqb/labels/fault/postprocessing.py @@ -0,0 +1,315 @@ +""" Utils for faults postprocessing. """ +import numpy as np +from numba import njit, prange +from numba.types import bool_ + +from ...functional import make_gaussian_kernel + + +@njit(parallel=True) +def skeletonize(slide, width=5, rel_height=0.5, prominence=0.05, threshold=0.05, distance=None, mode=0, axis=1): + """ Perform skeletonize of faults on 2D slide + + Parameters + ---------- + slide : numpy.ndarray + + width : int, optional + width of peaks, by default 5 + rel_height, threshold : float, optional + parameters of :meth:~.find_peaks` + prominence : float + prominence threshold value + threshold : float + nullify values below the threshold + mode : int (from 0 to 4) + which value to place in the output + 0: ones + 1: peak prominences + 2: values from initial slide + 3: values from initial slide multiplied by prominences + 4: average between values from initial slide and prominences + Returns + ------- + numpy.ndarray + skeletonized slide + """ + skeletonized_slide = np.zeros_like(slide, dtype='float32') + for i in prange(slide.shape[axis]): #pylint: disable=not-an-iterable + x = slide[:, i] if axis == 1 else slide[i] + peaks, prominences = find_peaks(x, width=width, prominence=prominence, + rel_height=rel_height, threshold=threshold, distance=distance) + if mode == 0: + values = np.ones(len(peaks), dtype='float32') + elif mode == 1: + values = prominences + elif mode == 2: + values = x[peaks] + elif mode == 3: + values = x[peaks] * prominences + elif mode == 4: + values = (x[peaks] + prominences) / 2 + + if axis == 1: + skeletonized_slide[peaks, i] = values + else: + skeletonized_slide[i, peaks] = values + return skeletonized_slide + +@njit +def find_peaks(x, width=5, prominence=0.05, rel_height=0.5, threshold=0.05, distance=None): + """ See :meth:`scipy.signal.find_peaks`. """ + lmax = (x[1:] - x[:-1] >= 0) + rmax = (x[:-1] - x[1:] >= 0) + mask = np.empty(len(x)) + mask[0] = rmax[0] + mask[-1] = lmax[-1] + mask[1:-1] = np.logical_and(lmax[:-1], rmax[1:]) + mask = np.logical_and(mask, x >= threshold) + peaks = np.where(mask)[0] + + if distance is not None: + keep = _select_by_peak_distance(peaks, x[peaks], distance) + peaks = peaks[keep] + + prominences, left_bases, right_bases = _peak_prominences(x, peaks, -1) + widths = _peak_widths(x, peaks, rel_height, prominences, left_bases, right_bases) + mask = np.logical_and(widths[0] >= width, prominences >= prominence) + return peaks[mask], prominences[mask] + +@njit +def _peak_prominences(x, peaks, wlen): + prominences = np.empty(peaks.shape[0], dtype=np.float32) + left_bases = np.empty(peaks.shape[0], dtype=np.intp) + right_bases = np.empty(peaks.shape[0], dtype=np.intp) + + for peak_nr in range(peaks.shape[0]): + peak = peaks[peak_nr] + i_min = 0 + i_max = x.shape[0] - 1 + + if wlen >= 2: + i_min = max(peak - wlen // 2, i_min) + i_max = min(peak + wlen // 2, i_max) + + # Find the left base in interval [i_min, peak] + i = left_bases[peak_nr] = peak + left_min = x[peak] + while i_min <= i and x[i] <= x[peak]: + if x[i] < left_min: + left_min = x[i] + left_bases[peak_nr] = i + i -= 1 + + i = right_bases[peak_nr] = peak + right_min = x[peak] + while i <= i_max and x[i] <= x[peak]: + if x[i] < right_min: + right_min = x[i] + right_bases[peak_nr] = i + i += 1 + + prominences[peak_nr] = x[peak] - max(left_min, right_min) + + return prominences, left_bases, right_bases + +@njit +def _peak_widths(x, peaks, rel_height, prominences, left_bases, right_bases): + widths = np.empty(peaks.shape[0], dtype=np.float64) + width_heights = np.empty(peaks.shape[0], dtype=np.float64) + left_ips = np.empty(peaks.shape[0], dtype=np.float64) + right_ips = np.empty(peaks.shape[0], dtype=np.float64) + + for p in range(peaks.shape[0]): + i_min = left_bases[p] + i_max = right_bases[p] + peak = peaks[p] + # Validate bounds and order + height = width_heights[p] = x[peak] - prominences[p] * rel_height + + # Find intersection point on left side + i = peak + while i_min < i and height < x[i]: + i -= 1 + left_ip = i + if x[i] < height: + # Interpolate if true intersection height is between samples + left_ip += (height - x[i]) / (x[i + 1] - x[i]) + + # Find intersection point on right side + i = peak + while i < i_max and height < x[i]: + i += 1 + right_ip = i + if x[i] < height: + # Interpolate if true intersection height is between samples + right_ip -= (height - x[i]) / (x[i - 1] - x[i]) + + widths[p] = right_ip - left_ip + left_ips[p] = left_ip + right_ips[p] = right_ip + + return widths, width_heights, left_ips, right_ips + +@njit +def _select_by_peak_distance(peaks, priority, distance): + peaks_size = peaks.shape[0] + distance_ = np.ceil(distance) + keep = np.ones(peaks_size, bool_) # Prepare array of flags + priority_to_position = np.argsort(priority) + + for i in range(peaks_size - 1, -1, -1): + j = priority_to_position[i] + if keep[j] == 0: + continue + + k = j - 1 + while k >= 0 and peaks[j] - peaks[k] < distance_: + keep[k] = 0 + k -= 1 + + k = j + 1 + while k < peaks_size and peaks[k] - peaks[j] < distance_: + keep[k] = 0 + k += 1 + return keep # Return as boolean array + +def faults_sizes(labels): + """ Compute sizes of faults. + + Parameters + ---------- + labels : numpy.ndarray + array of shape (N, 4) where the first 3 columns are coordinates of points and the last one + is for labels + Returns + ------- + sizes : numpy.ndarray + """ + sizes = [] + for array in labels: + i_len = array[:, 0].ptp() + x_len = array[:, 1].ptp() + sizes.append((i_len ** 2 + x_len ** 2) ** 0.5) + return np.array(sizes) + +@njit +def split_array(array, labels): + """ Split (groupby) array by values from labels. Labels must be sorted and all groups must be contiguous. """ + positions = [] + for i in range(1, len(labels)): + if labels[i] != labels[i-1]: + positions.append(i) + + return np.split(array, positions) + +@njit +def thin_line(points, column=0): + """ Make thick line. Works with sorted arrays by the axis of interest. """ + line = np.zeros_like(points) + p = points[0].copy() + n = 1 + pos = 0 + for i in range(1, len(points)): + if points[i, column] == points[i-1, column]: + p += points[i] + n += 1 + if i == len(points) - 1: + line[pos] = p / n + break + if (points[i, column] != points[i-1, column]): + line[pos] = p / n + n = 1 + pos += 1 + p = points[i].copy() + + return line[:pos+1] + +# Bilateral filtering +def bilateral_filter(data, kernel_size=3, kernel=None, padding='same', sigma_spatial=None, sigma_range=0.15): + """ Apply bilateral filtering for data 3d volume. + + Bilateral filtering is an edge-preserving smoothening, which takes special care for areas on faults edges. + Be careful with `sigma_range` value: + - The higher the `sigma_range` value, the more 'bilateral' result looks like a 'convolve' result. + - If the `sigma_range` too low, then no smoothening applied. + + Parameters + ---------- + data : np.ndarray + + kernel_size : int or sequence of ints + Size of a created gaussian filter if `kernel` is None. + kernel : ndarray or None + If passed, then ready-to-use kernel. Otherwise, gaussian kernel will be created. + padding : {'valid', 'same'} or sequence of tuples of ints, optional + Number of values padded to the edges of each axis. + sigma_spatial : number + Standard deviation (spread or “width”) for gaussian kernel. + The lower, the more weight is put into the point itself. + sigma_range : number + Standard deviation for additional weight which smooth differences in depth values. + The lower, the more weight is put into the depths differences between point in a window. + Note, if it is too low, then no smoothening is applied. + """ + if kernel is None: + if isinstance(kernel_size, int): + kernel_size = (kernel_size, kernel_size, kernel_size) + + if sigma_spatial is None: + sigma_spatial = [size//3 for size in kernel_size] + + kernel = make_gaussian_kernel(kernel_size=kernel_size, sigma=sigma_spatial) + + if padding == 'same': + padding = [(size//2, size - size//2 - 1) for size in kernel_size] + elif padding == 'valid': + padding = None + + if padding is not None: + data = np.pad(data, padding) + + result = _bilateral_filter(src=data, kernel=kernel, sigma_range=sigma_range) + + if padding is not None: + slices = tuple(slice(size//2, -(size - size//2 - 1)) for size in kernel_size) + result = result[slices] + return result + + +@njit(parallel=True) +def _bilateral_filter(src, kernel, sigma_range=0.15): + """ Jit-accelerated function to apply 3d bilateral filtering. + + The difference between gaussian smoothing and bilateral filtering is in additional weight multiplier, + which is a gaussian of difference of convolved elements. + """ + #pylint: disable=too-many-nested-blocks, consider-using-enumerate, not-an-iterable + k = [shape//2 for shape in kernel.shape] + raveled_kernel = kernel.ravel() / np.sum(kernel) + sigma_squared = sigma_range**2 + + i_range, x_range, z_range = src.shape + dst = src.copy() + + for iline in prange(0, i_range): + for xline in range(0, x_range): + for zline in range(0, z_range): + central = src[iline, xline, zline] + + # Get values in the squared window and apply kernel to them + element = src[max(0, iline-k[0]):min(iline+k[0]+1, i_range), + max(0, xline-k[1]):min(xline+k[1]+1, x_range), + max(0, zline-k[2]):min(zline+k[2]+1, z_range)].ravel() + + s, sum_weights = np.float32(0), np.float32(0) + for item, weight in zip(element, raveled_kernel): + # Apply additional weight for values differences (ranges) + weight *= np.exp(-0.5*((item - central)**2)/sigma_squared) + + s += item * weight + sum_weights += weight + + if sum_weights != 0.0: + dst[iline, xline, zline] = s / sum_weights + return dst diff --git a/seismiqb/labels/fault/surfaces_extractor.py b/seismiqb/labels/fault/surfaces_extractor.py new file mode 100644 index 0000000..7bdee75 --- /dev/null +++ b/seismiqb/labels/fault/surfaces_extractor.py @@ -0,0 +1,552 @@ +""" Extractor of fault surfaces from cloud of points. """ +from collections import defaultdict +from itertools import combinations + +import numpy as np +from scipy.ndimage import measurements +from scipy.sparse import lil_matrix +from scipy.sparse.csgraph import connected_components as connected_components_graph + +from batchflow import Notifier + +from .base import Fault + +class FaultExtractor: + """ Extract separate fault surfaces from array with fault labels (probabilities or binary values). + It uses assumption that the connected components on each slice in `components_axis` direction + are in the same direction (`faults_direction`) and do not have branches. + + The algorithm is based on four stages: + - merge connected components into small patches: sequences of connected components + (see :class:`.FaultPatch`) + - group patches around the holes + - group patches with large intersection of the bound components + - form separate fault instances from all groups of patches. + + Patches can be organized into directed graph: each patch is connected to the patches which touch its bottom + component by its top component. Top patches we will call `parents`, the sequent bottom patches we will + call `children`. + + Parameters + ---------- + array : str, numpy.ndarray or an object with the same slicing + Array with fault probabilities + origin : tuple of int, optional + Origin (offset) of the cube, is needed to make fault instances with right coordinates, by default (0, 0, 0) + faults_direction : 0 or 1, optional + Direction of faults: across ilines or xlines + components_axis : int, optional + Axis of cube slices where connected components will be searched + """ + def __init__(self, array, origin=(0, 0, 0), faults_direction=0, components_axis=2): + if faults_direction not in (0, 1): + raise ValueError(f'`faults_direction` must be 0 or 1 but {faults_direction} was given.') + + self.array = array + self.origin = origin + self.faults_direction = faults_direction + self.components_axis = components_axis + + self.labels, self.n_objects, self.objects = self.create_labels() + self.sizes = self.compute_sizes() + + self.sorted_labels = sorted(self.sizes, key=self.sizes.get, reverse=True) + + self.patchtop_to_patch = {} # key - top patch component, value - FaultPatch instance + self.patchbottom_to_patch = {} # key - bottom patch component, value - FaultPatch instance + + self.extended_components = {1: set(), -1: set()} # assemble components extended in a given direction + + self._candidates = {1: set(), -1: set()} # components indices to extend + self._connectivity_matrix = None # binary matrix of (len(self.patchtop_to_patch), len(self.patchtop_to_patch)). + # 1 on (i, j) position means that i-th and j-th patches must be merged. + + def create_labels(self): + """ Create slice-wise labeled cube. Axis of slices is defined by `self.components_axis`. """ + structure = np.zeros((3, 3, 3)) + slices = [slice(None) for _ in range(3)] + slices[self.components_axis] = 1 + structure[tuple(slices)] = 1 + + labels, n_objects = measurements.label(self.array, structure=structure) + objects = measurements.find_objects(labels) + objects = dict(enumerate(objects, start=1)) + + return labels, n_objects, objects + + def compute_sizes(self): + """ Compute sizes of components as a number of points. The zero label (background) is ignored. """ + sizes = {} + for idx, bbox in self.objects.items(): + mask = (self.labels[bbox] == idx) + sizes[idx] = mask.sum() + return sizes + + def idx_to_points(self, idx): + """ Get component points cloud (taking into account array origin). """ + points = np.stack(np.where(self.labels[self.objects[idx]] == idx), axis=1) + object_origin = [item.start for item in self.objects[idx]] + return points + object_origin + self.origin + + def idx_to_bbox(self, idx): + """ Get component bbox in the array. """ + return self.objects[idx] + + def idx_to_location(self, idx): + """ Get component slice location. """ + return self.objects[idx][self.components_axis].start + + def get_neighbors(self, idx, direction=1): + """ Find components on the next slice in the given direction (1 or -1) which touch component + with label `idx`. + """ + bbox = list(self.objects[idx]) + location = self.idx_to_location(idx) + if ((direction == 1 and location == self.array.shape[self.components_axis] - 1) or \ + (direction == -1 and location == 0)): + return [] + + bbox[self.components_axis] = location + mask = (self.labels[bbox[0], bbox[1], bbox[2]] == idx) + bbox[self.components_axis] += direction + components = np.unique(self.labels[bbox[0], bbox[1], bbox[2]][mask]) + + return components[components > 0] + + def compute_intersection_size(self, idx_a, idx_b): + """ Compute the area (the number of pixels) of ​​contact of two components on different slices. """ + bbox = [ + slice(min(i.start, j.start), max(i.stop, j.stop)) for i, j in zip(self.objects[idx_a], self.objects[idx_b]) + ] + + bbox[self.components_axis] = self.idx_to_location(idx_a) + a_mask = (self.labels[bbox[0], bbox[1], bbox[2]] == idx_a) + + bbox[self.components_axis] = self.idx_to_location(idx_b) + b_mask = (self.labels[bbox[0], bbox[1], bbox[2]] == idx_b) + + intersection = np.logical_and(a_mask, b_mask) + return intersection.sum() + + def create_patches(self, size_threshold=100, pbar='t'): + """ Create small patches. There are two sources of component indices to initialize patches: + - list of all connected components sorted by size + - candidates: components that stopped the extension of previous patches + (see description of extension of :class:`.FaultPatch`) + + As long as there are candidates they will be extended into patches. + Otherwise, from the list of components, the next one in size is taken, which has not yet been extended. + Since there are no candidates at the beginning, the largest component is extended first. + + Components smaller then `size_threshold` are skipped. + + Direction of extension is 0 (both directions) for components from list of all connected components. + Each candidate has its own direction to extend which depends on the reason why component was rejected in + patch extension. + """ + + # TODO: rewrite progress bar for used components + candidates = self._components_to_extend(size_threshold) + for anchor_idx, direction in Notifier(pbar)(candidates): + patch = FaultPatch(anchor_idx, direction, extractor=self) + + # Check if patch consists of one component which is a part of the already existed patch + if len(patch.components) == 1 and (direction == 0 or patch.top in self.extended_components[-direction]): + continue + + self.patchtop_to_patch[patch.top] = patch + self.patchbottom_to_patch[patch.bottom] = patch + + # Get mapping of patches to natural enumeration and its reverse version + self._labels_mapping = dict(enumerate(self.patchtop_to_patch.keys())) + self._labels_reverse_mapping = {v: k for k, v in self._labels_mapping.items()} + self._connectivity_matrix = lil_matrix( + (len(self.patchtop_to_patch), len(self.patchtop_to_patch)), dtype='uint8' + ) + + return self + + def _components_to_extend(self, size_threshold): + """ Generate components indices and direction to extend into patch. Components smaller + then `size_threshold` are skipped. """ + components_iter = iter(self.sorted_labels) + + while True: + if len(self._candidates[1]) > 0: + direction = 1 + elif len(self._candidates[-1]) > 0: + direction = -1 + else: + direction = 0 # extend in both directions + + if direction == 0: + try: + anchor = next(components_iter) + except StopIteration: + break # all components were extended + + if self.sizes[anchor] < size_threshold: + break + + # check if anchor was already extended in one of directions + if anchor in self.extended_components[1]: + direction = -1 + elif anchor in self.extended_components[-1]: + direction = 1 + else: + anchor = self._candidates[direction].pop() + if self.sizes[anchor] < size_threshold: + continue # skip patches creation if all components are too small + + if direction != 0 and anchor in self.extended_components[direction]: + continue + + yield anchor, direction + + def add_candidates(self, candidates_bottom, candidates_top): + """ Update candidates sets. """ + self._candidates[1].update(candidates_bottom) + self._candidates[-1].update(candidates_top) + + def find_holes(self, depth=10, threshold=0.9, pbar='t'): + """ Find holes of fault surfaces and merge patches around them into groups. + + To find holes, we search for a patches which touch more then one other patches (has several components + in `bottom_rejected`). Then we construct directed graphs of children of that root and check if they has + common inheritors. If yes, then two such branches from inheritors to root surround the hole and we + group them. + + Parameters + ---------- + depth : int, optional + Maximal depth of the constructed trees, by default 10 + threshold : float, optional + Two patches can be parent and child if they touch and ratio of intersection of touched components + to the minimal of them is larger then `threshold`, by default 0.9 + pbar : bool, optional + Progress bar, by default True + """ + groups = [] + for idx in Notifier(pbar, desc='Find holes')(self.patchtop_to_patch): + bottom_rejected = self.patchtop_to_patch[idx].bottom_rejected + for a, b in combinations(bottom_rejected, 2): + if a not in self.patchtop_to_patch or b not in self.patchtop_to_patch: + continue + tree_a = self._get_inheritors_tree(a, depth, threshold) + tree_b = self._get_inheritors_tree(b, depth, threshold) + + # Find common patches in both trees. + for item in set(tree_a) & set(tree_b): + if tree_a[item] == tree_b[item]: # Skip patch if in both trees it has common parents. + continue + + # Find paths from `item` to `idx` + parent = tree_a.get(item) + path_a = [item] + while parent is not None: + path_a.append(parent) + parent = tree_a.get(parent) + + parent = tree_b.get(item) + path_b = [item] + while parent is not None: + path_b.append(parent) + parent = tree_b.get(parent) + + if len(set(path_a) & set(path_b)) == 1: # Check if the first common ancestor in both trees is `idx`. + groups.append(list(set([idx, *path_a, *path_b]))) + + for group in groups: + idx = self._labels_reverse_mapping.get(group[0]) + if idx is not None: + for item in group[1:]: + idx_2 = self._labels_reverse_mapping[item] + self._connectivity_matrix[idx, idx_2] = 1 + self._connectivity_matrix[idx_2, idx] = 1 + + return self + + def _get_inheritors_tree(self, idx, depth, threshold): + """ Get tree of connected patches which starts from component `idx` which is no deeper than `depth`. + Two patches are connected if they touch and ratio of intersection of touched components to the + minimal of them is larger then `threshold`. + """ + components = [idx] + tree = {} + for _ in range(depth): + bottom_rejected = set() + for comp in components: + for bottom in self.patchtop_to_patch[comp].bottom_rejected: + if bottom in self.patchtop_to_patch: + leaf = list(self.patchtop_to_patch[comp].components.values())[-1][0] + intersection = self.compute_intersection_size(bottom, leaf) + a, b = self.sizes[bottom], self.sizes[leaf] + if intersection / min(a, b) >= threshold: + tree[bottom] = comp + bottom_rejected |= {bottom} + components = bottom_rejected + return tree + + + def merge_patches(self, thresholds, pbar='t'): + """ Merge patches with large intersections. see :meth:`.FaultPatch.find_largest_intersections`. """ + for idx, patch in Notifier(pbar, desc='Merge patches')(self.patchtop_to_patch.items()): + for bottom_idx in patch.find_largest_intersections(thresholds=thresholds): + if bottom_idx in self.patchtop_to_patch: + a = self._labels_reverse_mapping[idx] + b = self._labels_reverse_mapping[bottom_idx] + self._connectivity_matrix[a, b] = 1 + self._connectivity_matrix[b, a] = 1 + return self + + def extend_patches(self, size_threshold, intersection_threshold, pbar='t'): + """ Iterative merging of patches. Starts with the largest patch, to which tightly fitting patches are merged + in succession on both sides. """ + sorted_patches = sorted(self.patchtop_to_patch.values(), key=lambda x: x.size(), reverse=True) + extended_patches = {-1: [], 1: []} + for patch in Notifier(pbar, desc='Extend patches')(sorted_patches): + for direction in [-1, 1]: + mapping = self.patchtop_to_patch if direction == 1 else self.patchbottom_to_patch + idx_attr = 'top' if direction == 1 else 'bottom' + current_patch_idx = getattr(patch, idx_attr) + top_idx = mapping[current_patch_idx].top + + while True: + if top_idx in extended_patches[direction]: + break + extended_patches[direction].append(top_idx) + + patch = mapping[current_patch_idx] + next_patch_idx = patch.find_largest_neighbor( + size_threshold, intersection_threshold, direction=direction + ) + if next_patch_idx is None: + break + + a = self._labels_reverse_mapping[top_idx] + if next_patch_idx not in mapping: + break + + if mapping[next_patch_idx].top in extended_patches[-direction]: + break + b = self._labels_reverse_mapping[mapping[next_patch_idx].top] + + self._connectivity_matrix[a, b] = 1 + self._connectivity_matrix[b, a] = 1 + + extended_patches[-direction].append(mapping[next_patch_idx].top) + + current_patch_idx = next_patch_idx + return self + + def to_faults(self, field, pbar='t'): + """ Make Fault instances from groups of patches. + + Parameters + ---------- + field : Field + Field instance + pbar : bool, optional + Progress bar, by default True + + Returns + ------- + list + Fault instances linked with the field + """ + n_groups, groups = connected_components_graph(self._connectivity_matrix) + faults = [] + group_sizes = defaultdict(int) + + for idx in Notifier(pbar)(range(n_groups)): + patches_idx = [self._labels_mapping[item] for item in np.arange(len(self.patchtop_to_patch))[groups == idx]] + components = [ + list(self.patchtop_to_patch[patch].all_components) + self.patchtop_to_patch[patch].bottom_rejected + for patch in patches_idx + ] + + for patch in components: + points = np.concatenate([self.idx_to_points(i) for i in patch], axis=0) + fault = Fault({'points': points}, field=field, direction=self.faults_direction) + fault.short_name = '0' + fault.group_idx = idx + + faults.append(fault) + group_sizes[idx] += len(fault) + + for fault in faults: + fault.group_size = group_sizes[fault.group_idx] + return faults + +class FaultPatch: + """ A sequence of connected components in labeled array extended from anchor component. + + Each patch starts from anchor in one of the direction: up (-1) or bottom (+1). + If zero, anchor is extended in both direction and then all components merged into one patch. + When we say "intersection" of two components on the sequential slides we mean intersection + of their 2D masks (the word "contact" is more accurate). + + Anchor extension is iterative procedure and stops in 3 cases: + - in the intersection of the currently extended component with the next depth slide + there are more then one component + - the next slide has only one component in intersection but it has other component + in intersection with the current slide + - the next slide has only one component but it was already extended in that direction + + Components from intersection on the last step will be added to candidates fot the next fault + patch anchors. + + Examples (for direction = 1): + + a - anchor + tr - top_rejected + t - top + b - bottom + br - bottom_rejected + c - candidate + + ----tr--- + --------a/t------ ┐ + --------------------- | + ----------------------- | patch + --------------------- | + -------------b------------ ┘ + ---br/c---- ---br/c--- + ------ -------- + =========================================================================== + -----tr----- + ┌ -----a/t--------- + | -------------------- + patch | -------------------- + | -------------------- + └ ---------b------------- ------c----- candidate + ----------br/c--------------------- + ============================================================================ + Parameters + ---------- + anchor_idx : int + Index of the component to extend + extension_direction : -1, 0 or 1 + Direction of the patch extension (increase or decrease location of slice in corresponding axis). + 0 means extension in both directions. + extractor : FaultExtractor + """ + def __init__(self, anchor_idx, extension_direction, extractor): + self.anchor_idx = anchor_idx + self.extension_direction = extension_direction + self.extractor = extractor + + self.components = None + self.top = None # Top component + self.bottom = None # Bottom component + self.top_rejected = None + self.bottom_rejected = None + + if self.extension_direction == 0: + patch_bottom = FaultPatch(self.anchor_idx, 1, self.extractor) + patch_top = FaultPatch(self.anchor_idx, -1, self.extractor) + + self.components = {**patch_top.components, **patch_bottom.components} + self.top_rejected = patch_top.top_rejected + self.bottom_rejected = patch_bottom.bottom_rejected + else: + idx = self.anchor_idx + components_by_depth = {self.extractor.idx_to_location(idx): np.array([idx])} + self.extractor.extended_components[self.extension_direction].add(idx) + + while True: + # Find components on the next slide in the defined direction + neighbors = self.extractor.get_neighbors(idx, self.extension_direction) + + # Stop extension if there are more then one neighbor or the only one neighbor was already extended + if len(neighbors) != 1 or neighbors[0] in self.extractor.extended_components[self.extension_direction]: + neighbors_ = [] + break + + # Find other neighbors of the found neighbor on the slide of idx + neighbors_ = self.extractor.get_neighbors(neighbors[0], -self.extension_direction) + + # Stop extension if there are other neighbors + if len(neighbors_) > 1: + break + + components_by_depth[self.extractor.idx_to_location(neighbors[0])] = neighbors + self.extractor.extended_components[self.extension_direction].add(idx) + self.extractor.extended_components[-self.extension_direction].update([idx, neighbors[0]]) + idx = neighbors[0] + + self.components = dict(sorted(components_by_depth.items(), key=lambda x: x[0])) + self.top_rejected = list(self.extractor.get_neighbors(self.anchor_idx, -self.extension_direction)) + self.bottom_rejected = list(neighbors) + + if self.extension_direction == -1: + self.top_rejected, self.bottom_rejected = self.bottom_rejected, self.top_rejected + neighbors, neighbors_ = neighbors_, neighbors + + self.extractor.add_candidates(neighbors, neighbors_) + + self.top = list(self.components.values())[0][0] + self.bottom = list(self.components.values())[-1][0] + + @property + def all_components(self): + """ All components included into patch. """ + return np.concatenate(list(self.components.values())).astype(int) + + def find_largest_intersections(self, thresholds=(0.5, 0.9)): + """ Find children components that have large intersections with bottom components. + + Parameters + ---------- + thresholds : tuple, optional + Thresholds as a ratios of components sizes, by default (0.5, 0.9). + For each pair of bottom component and bottom rejected the first item is the ratio of the components + intersection to the size of the smallest item in pair. The second is the ratio of the components + intersection to the size of the largest item in pair. + + Returns + ------- + list + Sorted by size list of components filtered by thresholds. + """ + merge = {} + for leaf in self.bottom_rejected: + if leaf in self.extractor.patchtop_to_patch: + comp = self.all_components[-1] + intersection = self.extractor.compute_intersection_size(leaf, comp) + A, B = self.extractor.sizes[leaf], self.extractor.sizes[comp] + if len(self.bottom_rejected) == 1 and intersection / (min(A, B)) >= thresholds[1]: + merge[leaf] = 0 + else: + min_ = min(A, B) + max_ = max(A, B) + if min_ > 20 and intersection / max_ >= thresholds[0] and intersection / min_ >= thresholds[1]: + merge[leaf] = intersection / max_ + return list(sorted(merge, key=lambda x: merge[x])) + + def find_largest_neighbor(self, size_threshold=20, intersection_threshold=0.7, direction=1): + """ Find the largest components in the defined direction. """ + neighbors_list = self.bottom_rejected if direction == 1 else self.top_rejected + comp = self.all_components[-1 if direction == 1 else 0] + candidates = {} + for leaf in neighbors_list: + leaf_size = self.extractor.sizes[leaf] + comp_size = self.extractor.sizes[comp] + if leaf_size < size_threshold: + continue + intersection = self.extractor.compute_intersection_size(leaf, comp) + if intersection / min(leaf_size, comp_size) > intersection_threshold: + candidates[leaf] = leaf_size + if len(candidates) == 0: + return None + return sorted(candidates, key=lambda x: candidates[x], reverse=True)[0] # TODO: remove sorted + + def size(self): + """ Size of the patch as the number of points. """ + return sum([self.extractor.sizes[item[0]] for item in self.components.values()]) + + def __repr__(self): + if self.top == self.bottom: + return f"{self.top_rejected} ---> {self.bottom} ---> {self.bottom_rejected}" + return f"{self.top_rejected} ---> {self.top} -> [{len(self.components)} components] "\ + f"-> {self.bottom} ---> {self.bottom_rejected}" diff --git a/seismiqb/labels/fault/triangulation.py b/seismiqb/labels/fault/triangulation.py new file mode 100644 index 0000000..41bd95e --- /dev/null +++ b/seismiqb/labels/fault/triangulation.py @@ -0,0 +1,321 @@ +""" Triangulation functions. """ +import numpy as np +from numba import njit +from scipy.spatial import Delaunay + + +@njit +def triangle_rasterization(points, width=1): + """ Transform triangle to surface of the fixed thickness. + + Parameters + ---------- + points : numpy.ndarray + array of size 3 x 3: each row is a vertex of triangle + width : int + thicc + + Return + ------ + numpy.ndarray + array of size N x 3 where N is a number of points in rasterization. + """ + max_n_points = np.int32(triangle_volume(points, width)) + _points = np.empty((max_n_points, 3)) + i = 0 + r_margin = width - width // 2 + l_margin = width // 2 + for x in range(int(np.min(points[:, 0]))-l_margin, int(np.max(points[:, 0]))+r_margin): # pylint: disable=not-an-iterable + for y in range(int(np.min(points[:, 1]))-l_margin, int(np.max(points[:, 1])+r_margin)): + for z in range(int(np.min(points[:, 2]))-l_margin, int(np.max(points[:, 2]))+r_margin): + node = np.array([x, y, z]) + if distance_to_triangle(points, node) <= width / 2: + _points[i] = node + i += 1 + return _points[:i] + +@njit +def triangle_volume(points, width): + """ Compute triangle volume to estimate the number of points. """ + a = points[0] - points[1] + a = np.sqrt(a[0] ** 2 + a[1] ** 2 + a[2] ** 2) + + b = points[0] - points[2] + b = np.sqrt(b[0] ** 2 + b[1] ** 2 + b[2] ** 2) + + c = points[2] - points[1] + c = np.sqrt(c[0] ** 2 + c[1] ** 2 + c[2] ** 2) + + p = (a + b + c) / 2 + S = (p * (p - a) * (p - b) * (p - c)) ** 0.5 + r = S / p + r_ = r + width + 1 + p_ = p * r_ / r + return p_ * r_ * (width + 1) + +def sticks_to_simplices(sticks, orientation, max_simplices_depth=None, max_nodes_distance=None): + """ Compute triangulation of the fault. + + Parameters + ---------- + sticks : numpy.ndarray + Array of sticks. Each item of array is a stick: sequence of 3D points. + + Return + ------ + simplices : numpy.ndarray + Array of simplices where each item is a sequence of 3 nodes indices in initial flatten array. + nodes : numpy.ndarray + Concatenated array of sticks nodes. + """ + if len(sticks) == 0: + return np.zeros((0, 3)), np.zeros((0, 3)) + if len(sticks) == 1: + return np.zeros((0, 3)), sticks[0] + all_simplices = [] + nodes = np.concatenate(sticks) + shift = 0 + for s1, s2 in zip(sticks[:-1], sticks[1:]): + simplices = connect_two_sticks(s1, s2, orientation=orientation, max_nodes_distance=max_nodes_distance) + if len(simplices) > 0: + simplices += shift + all_simplices.append(simplices) + shift += len(s1) + if len(all_simplices) > 0: + all_simplices = np.concatenate(all_simplices) + mask = filter_triangles(all_simplices, nodes, max_simplices_depth) + return all_simplices[mask], nodes + return np.zeros((0, 3)), np.zeros((0, 3)) + +def connect_two_sticks(nodes1, nodes2, axis=2, orientation=0, max_nodes_distance=20): + """ Create triangles for two sequential sticks. """ + ranges1, ranges2 = filter_points(nodes1, nodes2, axis, max_nodes_distance) + + p1, p2 = nodes1[slice(*ranges1)], nodes2[slice(*ranges2)] + + points = np.concatenate([p1, p2]) + if len(points) <= 3: + return [] + try: + simplices = Delaunay(points[:, [orientation, axis]]).simplices + except: # pylint: disable=bare-except + return [] + l1 = (ranges1[1] - ranges1[0]) + simplices[simplices >= l1] += ranges2[0] + (len(nodes1) - ranges1[1]) + simplices += ranges1[0] + return simplices + +def filter_points(nodes1, nodes2, axis=2, max_nodes_distance=20): + """ Remove nodes which are too far from each other. """ + if max_nodes_distance is None: + return (0, len(nodes1)), (0, len(nodes2)) + + swap = False + if nodes2[0, axis] < nodes1[0, axis]: + swap = True + nodes1, nodes2 = nodes2, nodes1 + + for start in range(len(nodes1)): + if (nodes1[start, axis] - nodes2[0, axis]) > -max_nodes_distance: + break + + ranges1 = start, len(nodes1) + ranges2 = 0, len(nodes2) + + if swap: + nodes1, nodes2 = nodes2, nodes1 + ranges1, ranges2 = ranges2, ranges1 + + swap = False + if nodes2[-1, axis] < nodes1[-1, axis]: + swap = True + nodes1, nodes2 = nodes2, nodes1 + ranges1, ranges2 = ranges2, ranges1 + + for end in range(len(nodes2)-1, -1, -1): + if (nodes2[end, axis] - nodes1[-1, axis]) < max_nodes_distance: + break + + ranges2 = ranges2[0], end + + if swap: + nodes1, nodes2 = nodes2, nodes1 + ranges1, ranges2 = ranges2, ranges1 + + return ranges1, ranges2 + +def filter_triangles(triangles, points, max_simplices_depth=10): + """ Remove large triangles. """ + mask = np.ones(len(triangles), dtype='bool') + if max_simplices_depth is not None: + for i, tri in enumerate(triangles): + if points[tri].ptp(axis=0).max() > max_simplices_depth: + mask[i] = 0 + return mask + +@njit +def distance_to_triangle(triangle, node): + """ Paper: https://www.geometrictools.com/Documentation/DistancePoint3Triangle3.pdf + Realization: https://gist.github.com/joshuashaffer/99d58e4ccbd37ca5d96e """ + # pylint: disable=invalid-name, too-many-nested-blocks, too-many-branches, too-many-statements + B = triangle[0, :] + E0 = triangle[1, :] - B + E1 = triangle[2, :] - B + D = B - node + a = np.dot(E0, E0) + b = np.dot(E0, E1) + c = np.dot(E1, E1) + d = np.dot(E0, D) + e = np.dot(E1, D) + f = np.dot(D, D) + + det = a * c - b * b + s = b * e - c * d + t = b * d - a * e + + if det == 0: + return 0. + + # Terrible tree of conditionals to determine in which region of the diagram + # shown above the projection of the point into the triangle-plane lies. + if (s + t) <= det: + if s < 0.0: + if t < 0.0: + # region4 + if d < 0: + t = 0.0 + if -d >= a: + s = 1.0 + sqrdistance = a + 2.0 * d + f + else: + s = -d / a + sqrdistance = d * s + f + else: + s = 0.0 + if e >= 0.0: + t = 0.0 + sqrdistance = f + else: + if -e >= c: + t = 1.0 + sqrdistance = c + 2.0 * e + f + else: + t = -e / c + sqrdistance = e * t + f + + # of region 4 + else: + # region 3 + s = 0 + if e >= 0: + t = 0 + sqrdistance = f + else: + if -e >= c: + t = 1 + sqrdistance = c + 2.0 * e + f + else: + t = -e / c + sqrdistance = e * t + f + # of region 3 + else: + if t < 0: + # region 5 + t = 0 + if d >= 0: + s = 0 + sqrdistance = f + else: + if -d >= a: + s = 1 + sqrdistance = a + 2.0 * d + f # GF 20101013 fixed typo d*s ->2*d + else: + s = -d / a + sqrdistance = d * s + f + else: + # region 0 + invDet = 1.0 / det + s = s * invDet + t = t * invDet + sqrdistance = s * (a * s + b * t + 2.0 * d) + t * (b * s + c * t + 2.0 * e) + f + else: + if s < 0.0: + # region 2 + tmp0 = b + d + tmp1 = c + e + if tmp1 > tmp0: # minimum on edge s+t=1 + numer = tmp1 - tmp0 + denom = a - 2.0 * b + c + if numer >= denom: + s = 1.0 + t = 0.0 + sqrdistance = a + 2.0 * d + f # GF 20101014 fixed typo 2*b -> 2*d + else: + s = numer / denom + t = 1 - s + sqrdistance = s * (a * s + b * t + 2 * d) + t * (b * s + c * t + 2 * e) + f + + else: # minimum on edge s=0 + s = 0.0 + if tmp1 <= 0.0: + t = 1 + sqrdistance = c + 2.0 * e + f + else: + if e >= 0.0: + t = 0.0 + sqrdistance = f + else: + t = -e / c + sqrdistance = e * t + f + # of region 2 + else: + if t < 0.0: + # region6 + tmp0 = b + e + tmp1 = a + d + if tmp1 > tmp0: + numer = tmp1 - tmp0 + denom = a - 2.0 * b + c + if numer >= denom: + t = 1.0 + s = 0 + sqrdistance = c + 2.0 * e + f + else: + t = numer / denom + s = 1 - t + sqrdistance = s * (a * s + b * t + 2.0 * d) + t * (b * s + c * t + 2.0 * e) + f + + else: + t = 0.0 + if tmp1 <= 0.0: + s = 1 + sqrdistance = a + 2.0 * d + f + else: + if d >= 0.0: + s = 0.0 + sqrdistance = f + else: + s = -d / a + sqrdistance = d * s + f + else: + # region 1 + numer = c + e - b - d + if numer <= 0: + s = 0.0 + t = 1.0 + sqrdistance = c + 2.0 * e + f + else: + denom = a - 2.0 * b + c + if numer >= denom: + s = 1.0 + t = 0.0 + sqrdistance = a + 2.0 * d + f + else: + s = numer / denom + t = 1 - s + sqrdistance = s * (a * s + b * t + 2.0 * d) + t * (b * s + c * t + 2.0 * e) + f + + # account for numerical round-off error + sqrdistance = max(sqrdistance, 0) + dist = np.sqrt(sqrdistance) + return dist diff --git a/seismiqb/labels/fault/visualization.py b/seismiqb/labels/fault/visualization.py new file mode 100644 index 0000000..52e0ce6 --- /dev/null +++ b/seismiqb/labels/fault/visualization.py @@ -0,0 +1,124 @@ +""" Fault visualization mixin. """ + +import numpy as np + +from ..mixins import VisualizationMixin +from ...plotters import show_3d +from ...utils import make_slices + +class FaultVisualizationMixin(VisualizationMixin): + """ Mixin to visualize fault. """ + def __repr__(self): + return f"""""" + + def show_slide(self, index, **kwargs): + """ Show slides from seismic with fault. """ + defaults = {'cmap': ['Greys_r', 'red'], 'width': 5} + kwargs = {**defaults, **kwargs} + return super().show_slide(index, **kwargs) + + def compute_auto_zoom(self, index, axis, zoom_margin=20): + """ Get center slice of the fault. """ + _ = index + return tuple(slice(max(self.bbox[i][0]-zoom_margin, 0), + min(self.bbox[i][1]+zoom_margin, self.field.shape[i])) + for i in range(3) if i != axis) + + def show(self, axis=0, zoom='auto', **kwargs): + """ Show center of fault for different axes. """ + return self.show_slide(index=int(np.mean(self.bbox[axis])), zoom=zoom, axis=axis, **kwargs) + + def show_3d(self, sticks_step=None, stick_nodes_step=None, z_ratio=1., colors='green', + zoom=None, margin=20, sticks=False, **kwargs): + """ Interactive 3D plot. Roughly, does the following: + - select `n` points to represent the horizon surface + - triangulate those points + - remove some of the triangles on conditions + - use Plotly to draw the tri-surface + + Parameters + ---------- + sticks_step : int or None + Number of slides between sticks. If None, fault triangulation (nodes and simplices) will be used. + stick_nodes_step : int or None + Distance between stick nodes. If None, fault triangulation (nodes and simplices) will be used. + z_ratio : int + Aspect ratio between height axis and spatial ones. + zoom : tuple of slices or None. + Crop from cube to show. If None, the whole cube volume will be shown. + show_axes : bool + Whether to show axes and their labels, by default True + width, height : int + Size of the image, by default 1200, 1200 + margin : int + Added margin from below and above along height axis, by default 20 + savepath : str + Path to save interactive html to. + sticks : bool + If True, show fault sticks. If False, show interpolated surface. + kwargs : dict + Other arguments of plot creation. + """ + title = f'Fault `{self.name}` on `{self.field.short_name}`' + aspect_ratio = (self.i_length / self.x_length, 1, z_ratio) + axis_labels = (self.field.index_headers[0], self.field.index_headers[1], 'DEPTH') + + zoom = make_slices(zoom, self.field.shape) + + margin = [margin] * 3 if isinstance(margin, int) else margin + x, y, z, simplices = self.make_triangulation(zoom, sticks_step, stick_nodes_step, sticks=sticks) + if isinstance(colors, str): + colors = [colors for _ in simplices] + + show_3d(x, y, z, simplices, title=title, zoom=zoom, aspect_ratio=aspect_ratio, + axis_labels=axis_labels, margin=margin, colors=colors, **kwargs) + + def make_triangulation(self, slices=None, sticks_step=None, stick_nodes_step=None, + stick_orientation=None, sticks=False, **kwargs): + """ Return triangulation of the fault. It will created if needed. """ + # pylint: disable=too-many-boolean-expressions + if ((sticks_step is not None and sticks_step != self.sticks_step) or + (stick_nodes_step is not None and stick_nodes_step != self.stick_nodes_step) or + (stick_orientation is not None and stick_orientation != self.stick_orientation)): + # sticks must be recreated with new parameters from points + + temporary_fault = type(self)({'points': self.points}, field=self.field, direction=self.direction) + temporary_fault.points_to_sticks(slices, sticks_step or 10, stick_nodes_step or 10, + stick_orientation=stick_orientation) + return temporary_fault.make_triangulation(slices, sticks=sticks, **kwargs) + + if sticks: + sticks = self.sticks + faults = [ + type(self)({'sticks': [stick]}, direction=self.direction, stick_orientation=self.stick_orientation, + field=self.field, name=(self.short_name or "") + '_' + str(i)) + for i, stick in enumerate(sticks) + ] + x, y, z, simplices = [], [], [], [] + n_points = 0 + for fault in faults: + triangulation = fault.make_triangulation(slices) + if len(triangulation[3]) > 0: + simplices.append(triangulation[3] + n_points) + x.append(triangulation[0]) + y.append(triangulation[1]) + z.append(triangulation[2]) + n_points += len(triangulation[0]) + return [np.concatenate(data) if len(data) > 0 else data for data in [x, y, z, simplices]] + + if len(self.simplices) > 0: + return self.nodes[:, 0], self.nodes[:, 1], self.nodes[:, 2], self.simplices + if len(self.sticks) == 1 and len(self.sticks[0]) > 1: + fake_fault = get_fake_one_stick_fault(self) + return fake_fault.make_triangulation(slices, sticks_step, stick_nodes_step, **kwargs) + + return [], [], [], [] + +def get_fake_one_stick_fault(fault): + """ Create fault with additional shifted stick to visualize one stick faults. """ + stick = fault.sticks[0] + + fake_fault = type(fault)({'sticks': np.array([stick, stick + 1])}, stick_orientation=fault.stick_orientation, + direction=fault.direction, field=fault.field) + + return fake_fault diff --git a/seismiqb/labels/horizon/__init__.py b/seismiqb/labels/horizon/__init__.py new file mode 100644 index 0000000..daf9887 --- /dev/null +++ b/seismiqb/labels/horizon/__init__.py @@ -0,0 +1,3 @@ +""" Horizon class and mixins for POST-STACK data. """ +from .base import Horizon +from .horizon_extractor import HorizonExtractor diff --git a/seismiqb/labels/horizon/attributes.py b/seismiqb/labels/horizon/attributes.py new file mode 100644 index 0000000..6a59012 --- /dev/null +++ b/seismiqb/labels/horizon/attributes.py @@ -0,0 +1,1021 @@ +""" Mixin with computed along horizon geological attributes. """ +# pylint: disable=too-many-statements +from copy import copy +from ast import literal_eval + +from math import isnan +import numpy as np +from numba import njit, prange + +from cv2 import dilate +from scipy.signal import ricker +from scipy.ndimage import convolve +from scipy.ndimage.morphology import binary_fill_holes, binary_erosion +from skimage.measure import label +from sklearn.decomposition import PCA + +from ...functional import compute_spectral_decomposition, compute_instantaneous_amplitude, compute_instantaneous_phase +from ...utils import transformable, lru_cache + + + +class AttributesMixin: + """ Geological attributes along horizon: + - scalars computed from its depth map only: number of holes, perimeter, coverage + - matrices computed from its depth map only: presence mask, gradients along directions, etc + - properties of a carcass + - methods to cut data from the cube along horizon + - matrices derived from amplitudes along horizon: instant amplitudes/phases, decompositions, etc. + + Method for getting desired attributes is `load_attribute`. It works with nested keys, i.e. one can get attributes + of horizon subsets. Address method documentation for further details. + """ + # Modify computed matrices + def _dtype_to_fill_value(self, dtype): + if dtype == np.int32: + fill_value = self.FILL_VALUE + elif dtype == np.float32: + fill_value = np.nan + elif np.issubdtype(dtype, np.bool_): + fill_value = False + else: + raise TypeError(f'Incorrect dtype: `{dtype}`') + return fill_value + + def matrix_set_dtype(self, matrix, dtype): + """ Change the dtype and fill_value to match it. """ + matrix = matrix.astype(dtype) + mask = self._matrix_absence_mask(matrix) + matrix[mask] = self._dtype_to_fill_value(dtype) + return matrix + + def matrix_put_on_full(self, matrix): + """ Convert matrix from being horizon-shaped to cube-shaped. """ + if matrix.shape[:2] != self.field.spatial_shape: + background = np.full(shape=self.field.spatial_shape, + fill_value=self._dtype_to_fill_value(matrix.dtype), + dtype=matrix.dtype) + background[self.i_min:self.i_max + 1, self.x_min:self.x_max + 1] = matrix + else: + background = matrix.copy() + return background + + def matrix_fill_to_num(self, matrix, value): + """ Change the matrix values at points where horizon is absent to a supplied one. """ + mask = self._matrix_absence_mask(matrix) + matrix[mask] = value + return matrix + + def _matrix_absence_mask(self, matrix): + """ Provide bool mask of horizon absence points consistent with shape of given matrix. """ + if matrix.shape[:2] == self.shape: + return ~self.binary_matrix + if matrix.shape[:2] == self.field.spatial_shape: + return ~self.full_binary_matrix + msg = f"Can't define horizon absence mask with respect to provided matrix since its shape {matrix.shape} "\ + f"doesn't coincide with either horizon shape {self.shape} or field shape {self.field.spatial_shape}." + raise ValueError(msg) + + def matrix_num_to_fill(self, matrix, value): + """ Mark points equal to value as absent ones. """ + if value is np.nan: + mask = np.isnan(matrix) + else: + mask = (matrix == value) + + matrix[mask] = self._dtype_to_fill_value(matrix.dtype) + return matrix + + def matrix_normalize(self, matrix, mode): + """ Normalize matrix values. + + Parameters + ---------- + mode : bool, str, optional + If `min-max` or True, then use min-max scaling. + If `mean-std`, then use mean-std scaling. + """ + values = matrix[self.full_binary_matrix] + + if mode in ['min-max', True]: + min_, max_ = np.nanmin(values), np.nanmax(values) + matrix = (matrix - min_) / (max_ - min_) + elif mode == 'mean-std': + mean, std = np.nanmean(values), np.nanstd(values) + matrix = (matrix - mean) / std + else: + raise ValueError(f'Unknown normalization mode `{mode}`.') + return matrix + + def matrix_dilate(self, matrix, dilation_iterations=1): + """ Dilate matrix with (3, 3) kernel with special care for filling values. """ + fill_value = np.nan if issubclass(matrix.dtype.type, np.floating) else self.FILL_VALUE + + matrix = np.nan_to_num(matrix) + matrix[matrix == self.FILL_VALUE] = 0 + + matrix = dilate(matrix, kernel=np.ones((3, 3), np.uint8), iterations=dilation_iterations) + + matrix[self.field.dead_traces_matrix == 1] = fill_value + return matrix + + def matrix_enlarge(self, matrix, width=3): + """ Increase visibility of a sparse carcass metric. Should be used only for visualization purposes. """ + if matrix.ndim == 3 and matrix.shape[-1] != 1: + return matrix + + # Convert all the nans to a number, so that `dilate` can work with it + matrix = matrix.copy().astype(np.float32).squeeze() + matrix[np.isnan(matrix)] = self.FILL_VALUE + + # Apply dilations along both axis + structure = np.ones((1, 3), dtype=np.uint8) + dilated1 = dilate(matrix, structure, iterations=width) + dilated2 = dilate(matrix, structure.T, iterations=width) + + # Mix matrices + matrix = np.full_like(matrix, np.nan) + matrix[dilated1 != self.FILL_VALUE] = dilated1[dilated1 != self.FILL_VALUE] + matrix[dilated2 != self.FILL_VALUE] = dilated2[dilated2 != self.FILL_VALUE] + + mask = (dilated1 != self.FILL_VALUE) & (dilated2 != self.FILL_VALUE) + matrix[mask] = (dilated1[mask] + dilated2[mask] + 1) // 2 + + # Fix zero traces + matrix[np.isnan(self.field.std_matrix)] = np.nan + return matrix + + @staticmethod + def pca_transform(data, n_components=3, **kwargs): + """ Reduce number of channels along the depth axis. """ + flattened = data.reshape(-1, data.shape[-1]) + mask = np.isnan(flattened).any(axis=-1) + + pca = PCA(n_components, **kwargs) + transformed = pca.fit_transform(flattened[~mask]) + n_components = transformed.shape[-1] + + result = np.full((*data.shape[:2], n_components), np.nan).reshape(-1, n_components) + result[~mask] = transformed + result = result.reshape(*data.shape[:2], n_components) + return result + + + # Technical matrices + @property + def full_matrix(self): + """ A method for getting matrix in cubic coordinates. Allows for introspectable cache. """ + return self.matrix_put_on_full(self.matrix) + + @property + @lru_cache(maxsize=1, apply_by_default=True, copy_on_return=True) + def binary_matrix(self): + """ Boolean matrix with `True` values at places where horizon is present and `False` everywhere else. """ + return (self.matrix != self.FILL_VALUE).astype(np.bool_) + + @property + @lru_cache(maxsize=1, apply_by_default=True, copy_on_return=True) + def full_binary_matrix(self): + """ A method for getting binary matrix in cubic (ordinal) coordinates. Allows for introspectable cache. """ + return self.matrix_put_on_full(self.binary_matrix) + + @property + def mask(self): + """ An alias. """ + return self.full_binary_matrix + + @property + @lru_cache(maxsize=1, apply_by_default=True, copy_on_return=True) + def float_matrix(self): + """ Matrix with smoothed float values in cubic (ordinal) coordinates. """ + if self.dtype == np.float32: + return self.full_matrix + smoothed = self.smooth_out(mode='convolve', kernel_size=5, sigma_spatial=3, max_depth_difference=5, + inplace=False, dtype=np.float32) + return smoothed.full_matrix + + # Scalars computed from depth map + @property + def coverage(self): + """ Ratio between number of present values and number of good traces in cube. """ + coverage = len(self) / self.field.n_alive_traces + return round(coverage, 5) + + @property + def filled_coverage(self): + """ Ratio between number of points inside horizon filled contour and number of good traces in cube. """ + coverage = np.count_nonzero(self.filled_matrix) / self.field.n_alive_traces + return round(coverage, 5) + + @property + def number_of_holes(self): + """ Number of holes inside horizon borders. """ + holes_array = self.filled_matrix != self.binary_matrix + _, num = label(holes_array, connectivity=2, return_num=True, background=0) + return num + + @property + def perimeter(self): + """ Number of points in the borders. """ + return np.sum((self.borders_matrix == 1).astype(np.int32)) + + @property + def solidity(self): + """ Ratio of area covered by horizon to total area inside borders. """ + return len(self) / np.sum(self.filled_matrix) + + @property + def d_ptp(self): + """ Horizon spread across the depth. """ + return self.d_max - self.d_min + + # Matrices computed from depth map + @property + def borders_matrix(self): + """ Borders of horizons (borders of holes inside are not included). """ + filled_matrix = self.filled_matrix + structure = np.ones((3, 3)) + eroded = binary_erosion(filled_matrix, structure, border_value=0) + return filled_matrix ^ eroded # binary difference operation + + @property + def boundaries_matrix(self): + """ Borders of horizons (borders of holes inside included). """ + binary_matrix = self.binary_matrix + structure = np.ones((3, 3)) + eroded = binary_erosion(binary_matrix, structure, border_value=0) + return binary_matrix ^ eroded # binary difference operation + + @property + def filled_matrix(self): + """ Binary matrix with filled holes (except dead traces). """ + return self.filled_full_matrix[self.bbox[0, 0]:self.bbox[0, 1]+1, self.bbox[1, 0]:self.bbox[1, 1]+1] + + @property + def filled_full_matrix(self): + """ Full binary matrix with filled holes (except dead traces). """ + structure = np.ones((3, 3)) + filled_matrix = binary_fill_holes(self.full_binary_matrix, structure) + + filled_matrix[self.field.dead_traces_matrix] = 0 + return filled_matrix + + def grad_along_axis(self, axis=0): + """ Change of depths along specified direction. """ + grad = np.diff(self.matrix, axis=axis, prepend=self.FILL_VALUE) + grad[np.abs(grad) > self.d_min] = self.FILL_VALUE + grad[self.matrix == self.FILL_VALUE] = self.FILL_VALUE + return grad + + @property + def grad_i(self): + """ Change of depths along iline direction. """ + return self.grad_along_axis(1) + + @property + def grad_x(self): + """ Change of depths along xline direction. """ + return self.grad_along_axis(0) + + + # Carcass properties: should be used only if the horizon is a carcass + @property + def is_carcass(self): + """ Check if the horizon is a sparse carcass. """ + return len(self) / self.filled_matrix.sum() < 0.5 + + @property + def carcass_ilines(self): + """ Labeled inlines in a carcass. """ + uniques, counts = np.unique(self.points[:, 0], return_counts=True) + return uniques[counts > 256] + + @property + def carcass_xlines(self): + """ Labeled xlines in a carcass. """ + uniques, counts = np.unique(self.points[:, 1], return_counts=True) + return uniques[counts > 256] + + @property + def probabilities(self): + """ Map of the horizon presence probabilities. """ + if hasattr(self, 'proba_points'): + _map = np.zeros(self.full_matrix.shape, dtype=np.float32) + _map[self.proba_points[:, 0].astype(np.int32), + self.proba_points[:, 1].astype(np.int32)] = self.proba_points[:, 2] + + _map[~self.full_binary_matrix] = np.nan + return _map + + raise AttributeError(f'Horizon `{self.displayed_name}` hasn\'t `proba_points` attribute. Check, whether' + ' the horizon was initialized `from_mask` with `save_probabilities=True` option.') + + def compute_sparse_coverage(self, frequency, margin=1): + """ Ratio between number of present values on grid and number of grid traces. + + Helpful for evaluating carcass-like horizon coverage relationally to carcass. + """ + grid = self.field.get_grid(margin=margin, frequency=frequency) + horizon_on_grid = self.full_binary_matrix & grid + return np.count_nonzero(horizon_on_grid) / np.count_nonzero(grid) + + + # Retrieve data from seismic along horizon + @lru_cache(maxsize=1, apply_by_default=False, copy_on_return=True) + @transformable + def get_cube_values(self, window=1, offset=0, chunk_size=256, src_geometry=None, apply_float_correction=False, **_): + """ Get values from the cube along the horizon. + + Parameters + ---------- + window : int + Width of data slice along the horizon. + offset : int + Offset of data slice with respect to horizon depths matrix. + chunk_size : int + Size of data along depth axis processed at a time. + apply_float_correction : bool + Whether to apply float correction to fix step-like artifacts. + """ + geometry = self.field.geometry if src_geometry is None else getattr(self.field, src_geometry) + + if apply_float_correction: + window += 2 + + low = window // 2 - offset + high = max(window - low, 0) + chunk_size = min(chunk_size, self.d_max - self.d_min + window) + result = np.full((*self.field.spatial_shape, window), fill_value=np.nan, dtype=np.float32) + + for d_start in range(max(low, self.d_min), self.d_max + 1, chunk_size): + d_end = min(d_start + chunk_size, self.d_max + 1) + + # Get chunk from the cube (depth-wise) + location = (slice(None), slice(None), + slice(d_start - low, min(d_end + high, self.field.depth))) + location, _ = geometry.process_key(location) + data_chunk = geometry.load_crop(location, use_cache=False) + + # Check which points of the horizon are in the current chunk (and present) + idx_i, idx_x = np.asarray((self.matrix != self.FILL_VALUE) & + (self.matrix >= d_start) & + (self.matrix < d_end)).nonzero() + depths = self.matrix[idx_i, idx_x] + + # Convert spatial coordinates to cubic, convert depth to current chunk local system + idx_i += self.i_min + idx_x += self.x_min + depths -= d_start + + # Subsequently add values from the cube to result, then shift horizon 1 unit lower + for j in range(window): + result[idx_i, idx_x, j] = data_chunk[idx_i, idx_x, depths] + depths += 1 + mask = depths < data_chunk.shape[2] + idx_i = idx_i[mask] + idx_x = idx_x[mask] + depths = depths[mask] + + result[~self.full_binary_matrix] = np.nan + + if apply_float_correction: + result = self._apply_float_correction(result) + return result + + def get_layer_values(self, other, window=0, offset=0, src_geometry=None): + """ Get values from the cube between `self` and `other` horizons. + + Parameters + ---------- + window : int or sequence of two ints + Additional samples to get along depth axis. + If two ints, then number of samples above `self` and below `other` horizon. + offset : int + Offset of data slice with respect to extraction window. + + TODO: implement chunking + """ + # Parse parameters + if self.d_mean > other.d_mean: + self, other = other, self + geometry = self.field.geometry if src_geometry is None else getattr(self.field, src_geometry) + + window = window if isinstance(window, (tuple, list)) else (window, window) + d_start = max( self.d_min - window[0] - offset, 0) + d_stop = min(other.d_max + window[1] - offset, geometry.depth) + + # Prepare depth bounds between `self` and `other` + presence_matrix = self.full_binary_matrix & other.full_binary_matrix + idx_i, idx_x = np.nonzero(presence_matrix) + self_depths = self.full_matrix[idx_i, idx_x] + other_depths = other.full_matrix[idx_i, idx_x] + + self_depths -= d_start + window[1] + other_depths -= d_start - window[0] + + # Load data chunk, prepare output array + data = geometry[:, :, d_start:d_stop] + n = d_stop - d_start + result = np.full((*presence_matrix.shape, n), fill_value=np.nan, dtype=np.float32) + + # Subsequently add values from the cube to result, then shift indices 1 unit lower + for i in range(n): + mask = self_depths < other_depths + idx_i = idx_i[mask] + idx_x = idx_x[mask] + self_depths = self_depths[mask] + other_depths = other_depths[mask] + + result[idx_i, idx_x, i] = data[idx_i, idx_x, self_depths] + self_depths += 1 + + result[~presence_matrix] = np.nan + return result + + def _apply_float_correction(self, array): + """ Compute a three-point correction from int to float. + + As most of the loaded horizons are stored as int32 depths and only integer samples can be retrieved from + the cube, extracted values (amplitudes) and their derivatives may have step-like artifacts. + To eliminate them, we interpolate between depth-wise channels, using the size of difference between + int32 and float32 horizons as the weight for interpolation. + + Parameters + ---------- + array : array-like + Array of (I, X, D) shape. + + Returns + ------- + Array of (I, X, D-2) shape. + """ + shifts_matrix = self.float_matrix - self.full_matrix + middle = array[:, :, 1:-1] + output = middle.copy() + + mask = shifts_matrix > 0 + output[mask] = (1 - shifts_matrix[mask]).reshape(-1, 1) * middle[mask] + \ + +(shifts_matrix[mask]).reshape(-1, 1) * array[:, :, 2:][mask] + + mask = shifts_matrix < 0 + output[mask] = (1 + shifts_matrix[mask]).reshape(-1, 1) * middle[mask] + \ + +(-shifts_matrix[mask]).reshape(-1, 1) * array[:, :, :-2][mask] + + output[np.isnan(shifts_matrix)] = np.nan + return output + + + # Generic attributes loading + ATTRIBUTE_TO_ALIAS = { + # Properties + 'full_matrix': ['full_matrix', 'depths'], + 'full_binary_matrix': ['full_binary_matrix', 'mask'], + 'probabilities': ['proba', 'probabilities'], + + # Created by `get_*` methods + 'amplitudes': ['amplitudes', 'cube_values'], + 'metric': ['metric', 'metrics'], + 'instantaneous_phases': ['instant_phases', 'iphases'], + 'instantaneous_amplitudes': ['instant_amplitudes', 'iamplitudes'], + + 'fourier_decomposition': ['fourier', 'fourier_decomposition'], + 'wavelet_decomposition': ['wavelet', 'wavelet_decomposition'], + 'spectral_decomposition': ['spectral', ], + + 'median_diff': ['median_diff', 'mdiff', 'median_faults'], + 'grad': ['grad', 'gradient', 'gradient_diff', 'gradient_faults'], + 'max_grad': ['max_grad', 'max_gradient', 'maximum_gradient'], + 'max_abs_grad': ['max_abs_grad', 'max_abs_gradient', 'maximum_abs_gradient'], + } + ALIAS_TO_ATTRIBUTE = {alias: name for name, aliases in ATTRIBUTE_TO_ALIAS.items() for alias in aliases} + + ATTRIBUTE_TO_METHOD = { + 'amplitudes' : 'get_cube_values', + 'metric' : 'get_metric', + 'instantaneous_phases' : 'get_instantaneous_phases', + 'instantaneous_amplitudes' : 'get_instantaneous_amplitudes', + 'fourier_decomposition' : 'get_fourier_decomposition', + 'wavelet_decomposition' : 'get_wavelet_decomposition', + 'spectral_decomposition' : 'get_spectral_decomposition', + + 'median_diff': 'get_median_diff_map', + 'grad': 'get_gradient_map', + 'max_grad': 'get_max_gradient_map', + 'max_abs_grad': 'get_max_abs_gradient_map', + 'spikes': 'get_spikes_mask' + } + + def load_attribute(self, src, location=None, use_cache=True, enlarge=False, **kwargs): + """ Load horizon attribute values at requested location. + This is the intended interface of loading matrices along the horizon, and should be preferred in all scenarios. + + To retrieve the attribute, we either use `:meth:~.get_property` or `:meth:~.get_*` methods: as all of them are + wrapped with `:func:~.transformable` decorator, you can use its arguments to modify the behavior. + + Parameters + ---------- + src : str + Key of the desired attribute. Valid attributes are either properties or aliases, defined + by `ALIAS_TO_ATTRIBUTE` mapping, for example: + + - 'cube_values' or 'amplitudes': cube values at horizon points; + - 'metrics' or 'metric': horizon random support metrics. + - 'instantaneous_phases', 'instant_phases' or 'iphases': instantaneous phase; + - 'instantaneous_amplitudes', 'instant_amplitudes' or 'iamplitudes': instantaneous amplitude; + - 'fourier_decomposition' or 'fourier': fourier transform with optional PCA; + - 'wavelet decomposition' or 'wavelet': wavelet transform with optional PCA; + - 'full_matrix' or 'depths': horizon depth map in cubic coordinates; + - 'full_binary_matrix' or 'mask': mask of horizon presence; + location : sequence of 3 slices + First two slices are used as `iline` and `xline` ranges to cut crop from. + Last 'depth' slice is not used, since points are sampled exactly on horizon. + If None, `src` is returned uncropped. + enlarge : bool, optional + Whether to enlarge carcass maps. Defaults to True, if the horizon is a carcass, False otherwise. + Should be used only for visualization purposes. + kwargs : + Passed directly to attribute-evaluating methods from :attr:`.ALIAS_TO_ATTRIBUTE` depending on `src`. + + Examples + -------- + Load 'depths' attribute for whole horizon: + >>> horizon.load_attribute('depths') + + Load 'cube_values' attribute for requested slice of fixed width: + >>> horizon.load_attribute('cube_values', (x_slice, i_slice, 1), window=10) + + Load 'metrics' attribute with specific evaluation parameter and following normalization. + >>> horizon.load_attribute('metrics', metric='local_corrs', normalize='min-max') + """ + src = copy(src) + if isinstance(src, str): + src_name = src + if isinstance(src, dict): + src_name = src.pop('src') + kwargs.update(src) + + if '[' in src_name: + pos_, _pos = src_name.find('['), src_name.find(']') + channels = literal_eval(src_name[1+pos_:_pos]) + src_name = src_name[:pos_] + else: + channels = None + + src_name = self.ALIAS_TO_ATTRIBUTE.get(src_name, src_name) + enlarge = enlarge and self.is_carcass + + if src_name in self.ATTRIBUTE_TO_METHOD: + method = self.ATTRIBUTE_TO_METHOD[src_name] + data = getattr(self, method)(use_cache=use_cache, enlarge=enlarge, **kwargs) + else: + data = self.get_property(src_name, use_cache=use_cache, enlarge=enlarge, **kwargs) + + # TODO: Someday, we would need to re-write attribute loading methods + # so they use locations not to crop the loaded result, but to load attribute only at location. + if location is not None: + i_slice, x_slice, _ = location + data = data[i_slice, x_slice] + + if channels == 'middle': + channels = data.shape[-1] // 2 + if channels is not None: + data = data[..., channels] + return data + + + # Specific attributes loading + @lru_cache(maxsize=1, apply_by_default=False, copy_on_return=False) + @transformable + def get_property(self, src, **_): + """ Load a desired instance attribute. Decorated to allow additional postprocessing steps. """ + data = getattr(self, src, None) + if data is None: + aliases = list(self.ALIAS_TO_ATTRIBUTE.keys()) + raise ValueError(f'Unknown `src` {src}. Expected a matrix-property or one of {aliases}.') + return data + + @lru_cache(maxsize=1, apply_by_default=False, copy_on_return=True) + @transformable + def get_instantaneous_amplitudes(self, window=11, offset=0, **kwargs): + """ Calculate instantaneous amplitude along the horizon. + + Parameters + ---------- + window : int + Width of cube values cutout along horizon to use for attribute calculation. + offset : int + Constant shift of cube values cutout up or down from the horizon surface. + kwargs : + Passed directly to :meth:`.get_cube_values`. + + Notes + ----- + Since Hilbert transform produces artifacts at signal start and end, if one's intenston is to use `n` channels + of the resulting array, the `window` parameter value should better be somewhat bigger than the value of `n`. + """ + amplitudes = self.get_cube_values(window=window, offset=offset, use_cache=False, **kwargs) + return compute_instantaneous_amplitude(amplitudes) + + @lru_cache(maxsize=1, apply_by_default=False, copy_on_return=True) + @transformable + def get_instantaneous_phases(self, window=11, offset=0, **kwargs): + """ Calculate instantaneous phase along the horizon. + + Parameters + ---------- + window : int + Width of cube values cutout along horizon to use for attribute calculation. + offset : int + Constant shift of cube values cutout up or down from the horizon surface. + kwargs : dict + Passed directly to :meth:`.get_cube_values`. + """ + amplitudes = self.get_cube_values(window=window, offset=offset, use_cache=False, **kwargs) + return compute_instantaneous_phase(amplitudes) + + @lru_cache(maxsize=1, apply_by_default=False, copy_on_return=True) + @transformable + def get_metric(self, metric='support_corrs', supports=50, agg='nanmean', **kwargs): + """ Cached metrics calculation with disabled plotting option. + + Parameters + ---------- + metric, supports, agg : + Passed directly to :meth:`.HorizonMetrics.evaluate`. + kwargs : + Passed directly to :meth:`.HorizonMetrics.evaluate`. + """ + metrics = self.metrics.evaluate(metric=metric, supports=supports, agg=agg, + enlarge=False, visualize=False, savepath=None, **kwargs) + return metrics + + + @lru_cache(maxsize=1, apply_by_default=False, copy_on_return=True) + @transformable + def get_fourier_decomposition(self, window=50, **_): + """ Cached fourier transform calculation follower by dimensionality reduction via PCA. + + Parameters + ---------- + window : int + Width of amplitudes slice to calculate fourier transform on. + """ + amplitudes = self.load_attribute('amplitudes', window=window) + result = np.abs(np.fft.rfft(amplitudes)) + return result + + @lru_cache(maxsize=1, apply_by_default=False, copy_on_return=True) + @transformable + def get_wavelet_decomposition(self, widths=range(1, 14, 3), window=50, **_): + """ Cached wavelet transform calculation followed by dimensionality reduction via PCA. + + Parameters + ---------- + widths : list of numbers + Widths of wavelets to calculate decomposition for. + window : int + Width of amplitudes slice to calculate wavelet transform on. + """ + amplitudes = self.load_attribute('amplitudes', window=window) + result_shape = *amplitudes.shape[:2], len(widths) + result = np.empty(result_shape, dtype=np.float32) + for idx, width in enumerate(widths): + wavelet = ricker(window, width).reshape(1, 1, -1) + result[:, :, idx] = convolve(amplitudes, wavelet, mode='constant')[:, :, window // 2] + + return result + + @lru_cache(maxsize=1, apply_by_default=False, copy_on_return=True) + @transformable + def get_spectral_decomposition(self, frequencies=(15, 25, 35), wavelet='mexh', method='fft', + normalize=True, window=33, offset=0, **kwargs): + """ Compute spectral decomposition by convolving data with wavelets at different scales. + Scales are computed from frequencies to roughly match them. + + Parameters + ---------- + frequencies : sequence + Frequencies to compute wavelets scales. + normalize : bool + Whether to normalize each frequency-channel by removing outliers and scaling values to [0, 1] range. + window : int + Width of amplitudes slice to calculate wavelet transform on. + """ + amplitudes = self.get_cube_values(window=window, offset=offset, use_cache=False, **kwargs) + + sample_rate = self.field.sample_rate + spectral = compute_spectral_decomposition(amplitudes, frequencies=frequencies, wavelet=wavelet, + sample_rate=sample_rate, method=method) + spectral = spectral[..., window // 2].transpose(1, 2, 0) + + if normalize: + q = np.nanquantile(spectral, (0.01, 0.99), axis=(0, 1)).reshape(2, 1, 1, -1) + spectral = np.clip(spectral, a_min=q[0], a_max=q[1]) + spectral -= q[0] + spectral /= (q[1] - q[0]) + return spectral + + + def get_zerocrossings(self, side, window=15): + """ Get matrix of depths shifted to nearest point of sign change in cube values. + + Parameters + ---------- + side : -1 or 1 + Whether to look for sign change above the horizon (-1) or below (1). + window : positive int + Width of data slice above/below the horizon made along its surface. + """ + values = self.get_cube_values(window=window, offset=window // 2 * side, fill_value=0) + # reverse array along depth axis for invariance + values = values[:, :, ::side] + + sign = np.sign(values) + # value 2 in the array below mark cube values sign change along depth axis + cross = np.abs(np.diff(sign, axis=-1)) + + # put 2 at points, where cube values are precisely equal to zero + zeros = sign[:, :, :-1] == 0 + cross[zeros] = 2 + + # obtain indices of first sign change occurrences for every trace + # if trace doesn't change sign, corresponding index of sign change is 0 + cross_indices = np.argmax(cross == 2, axis=-1) + + # get cube values before sign change + start_points = self.matrix_to_points(cross_indices).T + start_values = values[tuple(start_points)] + + # get cube values after sign change + stop_points = start_points + np.array([[0], [0], [1]]) + stop_values = values[tuple(stop_points)] + + # calculate additional float shifts towards true zero-crossing point + float_shift = start_values - stop_values + # do not perform division at points, where both 'start' and 'stop' values are 0 + np.divide(start_values, float_shift, out=float_shift, where=float_shift != 0) + + # treat obtained indices as shifts for label depths matrix + shift = cross_indices.astype(np.float32) + # apply additional float shifts to shift matrix + shift += float_shift.reshape(shift.shape) + # account for shift matrix sign change + shift *= side + + result = self.full_matrix + shift + return result + + + # Maps with faults and spikes + @lru_cache(maxsize=1, apply_by_default=False, copy_on_return=True) + @transformable + def get_median_diff_map(self, iters=2, window_size=11, max_depth_difference=0, + threshold=2, dilation_iterations=0, **_): + """ Compute difference between depth map and its median filtered counterpart. + + Parameters + ---------- + iters : int + Number of median filter iterations to perform. + window_size : int + A window size to compute the median in. + max_depth_difference : number + If the distance between anchor point and the point inside filter is bigger than the threshold, + then the point is ignored in filter. + threshold : number + Threshold to consider a difference between matrix and median value is insignificant. + dilation_iterations : int + Number of iterations for binary dilation algorithm to increase areas with significant + differences between matrix and median filter. + """ + _ = dilation_iterations # transformable decorator argument + + medfilt = self.full_matrix.astype(np.float32) + medfilt[self.full_matrix == self.FILL_VALUE] = np.nan + + # Apply `_medfilt` multiple times. Note that there is no dtype conversion in between + # Also the method returns a new object + for _ in range(iters): + medfilt = _medfilt(src=medfilt, window_size=window_size, preserve_missings=True, + max_depth_difference=max_depth_difference) + + median_diff = self.full_matrix - medfilt + + if threshold is not None: + median_diff[np.abs(median_diff) < threshold] = 0 + + median_diff[self.full_matrix == self.FILL_VALUE] = np.nan + return median_diff + + @lru_cache(maxsize=1, apply_by_default=False, copy_on_return=True) + @transformable + def get_gradient_map(self, threshold=1, dilation_iterations=2, **_): + """ Compute combined gradient map along both directions. + + Parameters + ---------- + threshold : number + Threshold to consider a gradient value is insignificant. + dilation_iterations : int + Number of iterations for binary dilation algorithm to increase areas with significant gradients values. + """ + _ = dilation_iterations # transformable decorator argument + + grad_i = self.load_attribute('grad_i', on_full=True, dtype=np.float32, use_cache=False) + grad_x = self.load_attribute('grad_x', on_full=True, dtype=np.float32, use_cache=False) + + if threshold is not None: + grad_i[np.abs(grad_i) <= threshold] = 0 + grad_x[np.abs(grad_x) <= threshold] = 0 + + grad_i[grad_i == self.FILL_VALUE] = np.nan + grad_x[grad_x == self.FILL_VALUE] = np.nan + + grad = grad_i + grad_x + grad[np.abs(grad) > self.d_min] = np.nan + + grad[self.field.dead_traces_matrix == 1] = np.nan + return grad + + @lru_cache(maxsize=1, apply_by_default=False, copy_on_return=True) + @transformable + def get_max_gradient_map(self, **_): + """ Compute maximum of gradients along both directions. """ + grad_i = self.load_attribute('grad_i', on_full=True, dtype=np.float32, use_cache=False) + grad_x = self.load_attribute('grad_x', on_full=True, dtype=np.float32, use_cache=False) + + matrix = np.nanmax([grad_i, grad_x], axis=0) + matrix[matrix == self.FILL_VALUE] = np.nan + matrix = np.abs(matrix) + return matrix + + @lru_cache(maxsize=1, apply_by_default=False, copy_on_return=True) + @transformable + def get_max_abs_gradient_map(self, **_): + """ Compute maximum of abs gradients along both directions. """ + grad_i = self.load_attribute('grad_i', on_full=True, dtype=np.float32, use_cache=False) + grad_x = self.load_attribute('grad_x', on_full=True, dtype=np.float32, use_cache=False) + grad_i[grad_i == self.FILL_VALUE] = np.nan + grad_x[grad_x == self.FILL_VALUE] = np.nan + + matrix = np.nanmax([np.abs(grad_i), np.abs(grad_x)], axis=0) + matrix[matrix == self.FILL_VALUE] = np.nan + matrix[matrix == -self.FILL_VALUE] = np.nan + return matrix + + @lru_cache(maxsize=1, apply_by_default=False, copy_on_return=True) + @transformable + def get_spikes_mask(self, max_spike_width=7, min_spike_size=5, max_depths_distance=2, + dilation_iterations=0, nan_amount_to_ignore=1, points_distance=3): + """ Get spikes mask for the horizon. + + Parameters + ---------- + max_spike_width : int + Maximum possible spike size along the iline or xline axes. + min_spike_size : int + Minimum possible spike size along the depth axis. + max_depths_distance : int + Threshold to consider that depths are close. + If points has difference in depth not more than this threshold, then we + assume that depths are almost the same. + dilation_iterations : int + Number of iterations for binary dilation algorithm to increase the spikes. + nan_amount_to_ignore : int + Number of nan values to skip while finding spike start point. + points_distance : int + Distance between points to compare depths to find spikes. Must be more than 0. + """ + _ = dilation_iterations # transformable decorator argument + + matrix = self.full_matrix.astype(np.float32) + matrix[matrix == self.FILL_VALUE] = np.nan + + spikes = np.zeros_like(matrix) + + # We try to find spikes on four directions: + # from left to right, from up to down, from right to left, from down to up + for rotation_num in range(1, 5): + matrix = np.rot90(matrix) + rotated_spikes = _get_spikes_along_line(matrix=matrix, + max_spike_width=max_spike_width, min_spike_size=min_spike_size, + max_depths_distance=max_depths_distance, + nan_amount_to_ignore=nan_amount_to_ignore, + points_distance=points_distance) + spikes += np.rot90(rotated_spikes, k=4-rotation_num) + + spikes[spikes > 0] = 1 + spikes[self.field.dead_traces_matrix == 1] = np.nan + return spikes + +# Helper functions +@njit +def _get_spikes_along_line(matrix, max_spike_width=5, min_spike_size=4, max_depths_distance=2, + nan_amount_to_ignore=1, points_distance=3): + """ Find spikes on a matrix for the fixed search direction: from up to down, from left to right. + + Under the hood, the function iterates over matrix lines and find too huge depth differences on neighboring points. + These points might be spike's starting points. + + If start points were found, we check points on the right of them to find spike's end point. + We suppose that a depth on the point next to the spikes' end point is close to a depth + on the point before the spike's start point. + """ + spikes_mask = np.zeros_like(matrix) + line_length = matrix.shape[1] + + for line_idx in range(matrix.shape[0]): + line = matrix[line_idx] + + previous_not_nan_idx = -100 + previous_idx = 0 + + while previous_idx < line_length - points_distance: + # Check that point can be a spike's start point: find too huge depth difference + previous_depth = line[previous_idx] + + current_idx = previous_idx + points_distance + current_depth = line[current_idx] + + previous_idx += 1 # for next iter + + if isnan(previous_depth) and isnan(current_depth): + continue + + if (not isnan(previous_depth)) and isnan(current_depth): + previous_not_nan_idx = current_idx - points_distance + continue + + if isnan(previous_depth) and (not isnan(current_depth)): + if current_idx - previous_not_nan_idx < nan_amount_to_ignore + points_distance: + previous_depth = line[previous_not_nan_idx] + else: + continue + + depths_diff = current_depth - previous_depth + + if np.abs(depths_diff) < min_spike_size: + continue + + # Check a range of points indices where the spike can be and + # find a point with a depth close to a depth before the spike + spike_start_idx = current_idx + spike_potential_end_idx = spike_start_idx + max_spike_width + + if spike_potential_end_idx >= line_length: + spike_potential_end_idx = line_length - 1 + + standard_depth = previous_depth # depth before the spike + + for spike_potential_point_idx in range(spike_start_idx+1, spike_potential_end_idx+1): + depth = line[spike_potential_point_idx] + + if not isnan(depth): + depths_diff = np.abs(standard_depth - depth) + + if depths_diff <= max_depths_distance: + spikes_mask[line_idx, spike_start_idx:spike_potential_point_idx] = 1 + previous_idx = spike_potential_point_idx # we can skip checked and founded spikes area + break + + return spikes_mask + +@njit(parallel=True) +def _medfilt(src, window_size, preserve_missings, max_depth_difference): + """ Jit-accelerated function to apply 2d median filter with special care for `np.nan` values. """ + # max_depth_difference = 0: median across all non-equal-to-self elements in window + # max_depth_difference = -1: median across all elements in window + #pylint: disable=too-many-nested-blocks, consider-using-enumerate, not-an-iterable + k = window_size // 2 + + i_range, x_range = src.shape + dst = src.copy() + + for iline in prange(0, i_range): + for xline in range(0, x_range): + central = src[iline, xline] + + if preserve_missings and isnan(central): + continue + + element = src[max(0, iline-k):min(iline+k+1, i_range), + max(0, xline-k):min(xline+k+1, x_range)].ravel() + + # Find elements which are close or distant for the `central` + # 0 for close, 1 for distant, 2 for nan + indicator = np.zeros_like(element) + + for i, item in enumerate(element): + if not isnan(item): + if (abs(item - central) > max_depth_difference) or isnan(central): + indicator[i] = np.float32(1) + else: + indicator[i] = np.float32(2) + + # If there are more distant points than close in the window, then find median of distant points + n_close = (indicator == np.float32(0)).sum() + mask_distant = indicator == np.float32(1) + n_distant = mask_distant.sum() + if n_distant > n_close: + dst[iline, xline] = np.median(element[mask_distant]) + return dst diff --git a/seismiqb/labels/horizon/base.py b/seismiqb/labels/horizon/base.py new file mode 100644 index 0000000..25c5ece --- /dev/null +++ b/seismiqb/labels/horizon/base.py @@ -0,0 +1,896 @@ +""" Horizon class for POST-STACK data. """ +import os +from copy import copy +from textwrap import dedent + +import numpy as np + +from cc3d import connected_components +from scipy.ndimage import find_objects + +from .attributes import AttributesMixin +from .extraction import ExtractionMixin +from .processing import ProcessingMixin +from .visualization import HorizonVisualizationMixin +from ...utils import CacheMixin, CharismaMixin, SQBStorage +from ...utils import groupby_mean, groupby_min, groupby_max, groupby_prob, make_interior_points_mask +from ...utils import MetaDict + + + +class Horizon(AttributesMixin, CacheMixin, CharismaMixin, ExtractionMixin, ProcessingMixin, HorizonVisualizationMixin): + """ Contains spatially-structured horizon: each point describes a depth on a particular (iline, xline) point. + + Initialized from `storage` and `field`, where storage can be one of: + - csv-like file in CHARISMA or REDUCED_CHARISMA format. + - ndarray of (N, 3) shape. + - ndarray of (n_ilines, n_xlines) shape. + - dictionary: a mapping from (iline, xline) -> depth. + - mask: ndarray of (n_ilines, n_xlines, depth) with 1's at places of horizon location. + + Main storages are `matrix` and `points` attributes: + - `matrix` is a depth map, ndarray of (n_ilines, n_xlines) shape with each point + corresponding to horizon depth at this point. Note that shape of the matrix is generally smaller + than cube spatial range: that allows to save space. + Attributes `i_min` and `x_min` describe position of the matrix in relation to the cube spatial range. + Each point with absent horizon is filled with `FILL_VALUE`. + Note that since the dtype of `matrix` is `np.int32`, we can't use `np.nan` as the fill value. + In order to initialize from this storage, one must supply `matrix`, `i_min`, `x_min`. + + - `points` is a (N, 3) ndarray with every row being (iline, xline, depth). Note that (iline, xline) are + stored in cube coordinates that range from 0 to `n_ilines` and 0 to `n_xlines` respectively. + Stored depth is corrected on `time_delay` and `sample_interval` of the cube. + In order to initialize from this storage, one must supply (N, 3) ndarray. + + Depending on which attribute was created at initialization (`matrix` or `points`), the other is computed lazily + at the time of the first access. This way, we can greatly amortize computations when dealing with huge number of + `Horizon` instances, i.e. when extracting surfaces from predicted masks. + + Independently of type of initial storage, Horizon provides following: + - Attributes `i_min`, `x_min`, `i_max`, `x_max`, `d_min`, `d_max`, `d_mean`, `d_std`, `bbox`, + to completely describe location of the horizon in the 3D volume of the seismic cube. + + - Convenient methods of changing the horizon, `apply_to_matrix` and `apply_to_points`: + these methods must be used instead of manually permuting `matrix` and `points` attributes. + For example, filtration or smoothing of a horizon can be done with their help. + + - Method `add_to_mask` puts 1's on the `location` of a horizon inside provided `background`. + + - `get_cube_values` allows to cut seismic data along the horizon: that data can be used to evaluate + horizon quality. + + - `evaluate` allows to quickly assess the quality of a seismic reflection; + for more metrics, check :class:`~.HorizonMetrics`. + + - A number of properties that describe geometrical, geological and mathematical characteristics of a horizon. + For example, `borders_matrix` and `boundaries_matrix`: the latter contains outer and inner borders; + `coverage` is the ratio between labeled traces and non-zero traces in the seismic cube; + `solidity` is the ratio between labeled traces and traces inside the hull of the horizon; + `perimeter` and `number_of_holes` speak for themselves. + + - Multiple instances of Horizon can be compared against one another and, if needed, + merged into one (either in-place or not) via `check_proximity`, `overlap_merge`, `adjacent_merge` methods. + These methods are highly optimized in their accesses to inner attributes that are computed lazily. + + - A wealth of visualization methods: view from above, slices along iline/xline axis, etc. + """ + #pylint: disable=too-many-public-methods, import-outside-toplevel, redefined-builtin + + # Columns that are used from the file + COLUMNS = ['INLINE_3D', 'CROSSLINE_3D', 'DEPTH'] + + # Value to place into blank spaces + FILL_VALUE = -999999 + + + def __init__(self, storage, field, name=None, format=None, dtype=np.int32, **kwargs): + # Meta information + self.path = None + self.name = name + self.dtype = dtype + self.format = None + self.already_merged = None + + # Location of the horizon inside cube spatial range + self.i_min, self.i_max = None, None + self.x_min, self.x_max = None, None + self.i_length, self.x_length = None, None + self._bbox, self.raveled_bbox = None, None + self._len = None + + # Underlying data storages + self._matrix = None + self._points = None + self._depths = None + + # Depths information + self._d_min, self._d_max = None, None + self._d_mean, self._d_std = None, None + + # Field reference + self.field = field + + # Check format of storage, then use it to populate attributes + if format is not None: + self.format = format + + elif isinstance(storage, str): + path = self.field.make_path(storage, makedirs=False) + self.path = path + self.name = os.path.basename(path) if self.name is None else self.name + + if SQBStorage.is_storage(path): + # path to SQB storage + self.format = 'sqb' + + elif os.path.exists(path): + # path to csv-like file + self.format = 'charisma' + + else: + raise ValueError(f'Path {path} does not exist!') + + elif isinstance(storage, np.ndarray): + if storage.ndim == 2 and storage.shape[1] == 3: + # array with row in (iline, xline, depth) format + self.format = 'points' + + elif storage.ndim == 2 and (storage.shape == self.field.spatial_shape): + # matrix of (iline, xline) shape with every value being depth + self.format = 'full_matrix' + + elif storage.ndim == 2: + # matrix of (iline, xline) shape with every value being depth + self.format = 'matrix' + + elif isinstance(storage, dict): + # mapping from (iline, xline) to (depth) + self.format = 'dict' + + getattr(self, f'from_{self.format}')(storage, **kwargs) + + + # Logic of lazy computation of `points` or `matrix` from the other available storage; cache management + @property + def points(self): + """ Storage of horizon data as (N, 3) array of (iline, xline, depth) in cubic coordinates. + If the horizon is created not from (N, 3) array, evaluated at the time of the first access. + """ + if self._points is None and self.matrix is not None: + points = self.matrix_to_points(self.matrix).astype(self.dtype) + points += np.array([self.i_min, self.x_min, 0], dtype=self.dtype) + self._points = points + return self._points + + @points.setter + def points(self, value): + self._points = value + + @staticmethod + def matrix_to_points(matrix): + """ Convert depth-map matrix to points array. """ + idx = np.nonzero(matrix != Horizon.FILL_VALUE) + points = np.hstack([idx[0].reshape(-1, 1), + idx[1].reshape(-1, 1), + matrix[idx[0], idx[1]].reshape(-1, 1)]) + return points + + + @property + def matrix(self): + """ Storage of horizon data as depth map: matrix of (ilines_length, xlines_length) with each point + corresponding to depth. Matrix is shifted to a (i_min, x_min) point so it takes less space. + If the horizon is created not from matrix, evaluated at the time of the first access. + """ + if self._matrix is None and self.points is not None: + self._matrix = self.points_to_matrix(points=self.points, i_min=self.i_min, x_min=self.x_min, + i_length=self.i_length, x_length=self.x_length, dtype=self.dtype) + return self._matrix + + @matrix.setter + def matrix(self, value): + self._matrix = value + + @staticmethod + def points_to_matrix(points, i_min, x_min, i_length, x_length, dtype=np.int32): + """ Convert array of (N, 3) shape to a depth map (matrix). """ + matrix = np.full((i_length, x_length), Horizon.FILL_VALUE, dtype) + + matrix[points[:, 0].astype(np.int32) - i_min, + points[:, 1].astype(np.int32) - x_min] = points[:, 2] + + return matrix + + @property + def depths(self): + """ Array of depth only. Useful for faster stats computation when initialized from a matrix. """ + if self._depths is None: + if self._points is not None: + self._depths = self.points[:, -1] + else: + self._depths = self.matrix[self.matrix != self.FILL_VALUE] + return self._depths + + @property + def bbox(self): + """ Horizon bbox in 2d-array format. """ + if self._bbox is None and self.raveled_bbox is not None: + self._bbox = self.raveled_bbox.reshape(-1, 2) + elif self._bbox is None: + self._bbox = np.array([[self.i_min, self.i_max], + [self.x_min, self.x_max], + [self.d_min, self.d_max]], + dtype=np.int32) + return self._bbox + + + def reset_storage(self, storage=None, reset_cache=True): + """ Reset storage along with depth-wise lazy computed stats. """ + self._depths = None + self._d_min, self._d_max = None, None + self._d_mean, self._d_std = None, None + self._len = None + + if storage == 'matrix': + self._depth = None + self._matrix = None + + if len(self.points) > 0: + i_min, x_min, d_min = np.min(self.points, axis=0) + i_max, x_max, d_max = np.max(self.points, axis=0) + + self._d_min, self._d_max = d_min.astype(self.dtype), d_max.astype(self.dtype) + self.i_min, self.i_max, self.x_min, self.x_max = int(i_min), int(i_max), int(x_min), int(x_max) + + self.i_length = (self.i_max - self.i_min) + 1 + self.x_length = (self.x_max - self.x_min) + 1 + self.raveled_bbox = np.array([self.i_min, self.i_max, + self.x_min, self.x_max, + self.d_min, self.d_max], + dtype=np.int32) + elif storage == 'points': + self._points = None + + if reset_cache: + self.reset_cache() + + def copy(self, add_prefix=True): + """ Create a new horizon with the same data. + + Returns + ------- + A horizon object with new matrix object and a reference to the same field. + """ + prefix = 'copy_of_' if add_prefix else '' + return type(self)(storage=np.copy(self.matrix), field=self.field, i_min=self.i_min, x_min=self.x_min, + name=f'{prefix}{self.name}') + + __copy__ = copy + + def __sub__(self, other): + if not isinstance(other, type(self)): + raise TypeError(f"Operands types do not match. Got {type(self)} and {type(other)}.") + + presence = other.full_binary_matrix + discrepancies = self.full_matrix[presence] != other.full_matrix[presence] + if discrepancies.any(): + raise ValueError("Horizons have different depths where present.") + + res_matrix = self.full_matrix.copy() + res_matrix[presence] = self.FILL_VALUE + name = f"~{other.name}" + result = type(self)(storage=res_matrix, field=self.field, name=name) + + return result + + + # Properties, computed from lazy evaluated attributes + @property + def d_min(self): + """ Minimum depth value. """ + if self._d_min is None: + self._d_min = np.min(self.depths) + return self._d_min + + @property + def d_max(self): + """ Maximum depth value. """ + if self._d_max is None: + self._d_max = np.max(self.depths) + return self._d_max + + @property + def d_mean(self): + """ Average depth value. """ + if self._d_mean is None: + self._d_mean = np.mean(self.depths) + return self._d_mean + + @property + def d_std(self): + """ Std of depths. """ + if self._d_std is None: + self._d_std = np.std(self.depths) + return self._d_std + + def __len__(self): + """ Number of labeled traces. """ + if self._len is None: + if self._points is not None: + self._len = len(self.points) + else: + self._len = len(self.depths) + return self._len + + + # Initialization from different containers + def from_points(self, points, verify=True, dst='points', reset='matrix', **kwargs): + """ Base initialization: from point cloud array of (N, 3) shape. + + Parameters + ---------- + points : ndarray + Array of points. Each row describes one point inside the cube: two spatial coordinates and depth. + verify : bool + Whether to remove points outside of the cube range. + dst : str + Attribute to save result. + reset : str or None + Storage to reset. + """ + _ = kwargs + + if verify: + mask = make_interior_points_mask(points, self.field.shape) + points = points[mask] + + if self.dtype == np.int32: + points = np.rint(points) + if points.dtype != self.dtype: + points = points.astype(self.dtype) + setattr(self, dst, points) + + # Collect stats on separate axes. Note that depth stats are properties + if reset: + self.reset_storage(storage=reset, reset_cache=False) + + + def from_charisma(self, path, transform=True, **kwargs): + """ Init from path to either CHARISMA or REDUCED_CHARISMA csv-like file. """ + points = self.load_charisma(path=path, dtype=self.dtype, format='points', + fill_value=Horizon.FILL_VALUE, transform=transform, + verify=True) + + self.from_points(points, verify=False, **kwargs) + + def from_sqb(self, path, **kwargs): + """ Init from path to SQB storage file. """ + _ = kwargs + storage = SQBStorage(path) + if storage.get('type') != 'horizon': + raise TypeError('SQB storage is not marked as horizon!') + + points = storage['points'] + self.from_points(points, verify=False, **kwargs) + + for key in storage['attributes']: + setattr(self, key, storage[key]) + self.storage = storage + + + def from_matrix(self, matrix, i_min, x_min, d_min=None, d_max=None, length=None, **kwargs): + """ Init from matrix and location of minimum i, x points. """ + _ = kwargs + + if matrix.dtype != self.dtype: + if self.dtype == np.int32: + matrix = np.rint(matrix) + matrix = matrix.astype(self.dtype) + self.matrix = matrix + + self.i_min, self.x_min = i_min, x_min + self.i_max, self.x_max = i_min + matrix.shape[0] - 1, x_min + matrix.shape[1] - 1 + + self.i_length = (self.i_max - self.i_min) + 1 + self.x_length = (self.x_max - self.x_min) + 1 + + # Populate lazy properties with supplied values + self._d_min, self._d_max, self._len = d_min, d_max, length + self.raveled_bbox = np.array([self.i_min, self.i_max, + self.x_min, self.x_max, + self.d_min, self.d_max], + dtype=np.int32) + + + def from_full_matrix(self, matrix, **kwargs): + """ Init from matrix that covers the whole cube. """ + kwargs = { + 'i_min': 0, + 'x_min': 0, + **kwargs + } + self.from_matrix(matrix, **kwargs) + + + def from_dict(self, dictionary, transform=True, **kwargs): + """ Init from mapping from (iline, xline) to depths. """ + _ = kwargs + + points = self.dict_to_points(dictionary) + + if transform: + points = self.field.lines_to_cubic(points) + + self.from_points(points) + + @staticmethod + def dict_to_points(dictionary): + """ Convert mapping to points array. """ + points = np.hstack([np.array(list(dictionary.keys())), + np.array(list(dictionary.values())).reshape(-1, 1)]) + return points + + + @staticmethod + def from_mask(mask, field=None, origin=None, connectivity=26, + mode='mean', threshold=0.5, minsize=0, prefix='predict', + save_probabilities=False, **kwargs): + """ Convert mask to a list of horizons. + Returned list is sorted by length of horizons. + + Parameters + ---------- + field : Field + Horizon parent field. + origin : sequence + The upper left coordinate of a `mask` in the cube coordinates. + connectivity : {6, 18, 26} + Connectivity type, i.e. what neighboring voxels to treat as connected with target one. + Can be one of: 6 (voxels with common faces), 18 (+ edges), 26 (+ corners). + threshold : float + Parameter of mask-thresholding. + mode : str, {'mean', 'min', 'max', 'prob'} + Method used for finding the point of a horizon for each trace in each connected component. + If `mean/min/max`, then we take mean/min/max value of labeled points on a trace. + If `prob`, then we take weighted sum of labeled points on a trace. + minsize : int + Minimum length of a horizon to be extracted. + prefix : str + Name of horizon to use. + save_probabilities : bool + Whether to save mask values on the horizon surface in the `horizon.proba_points` attribute. + """ + _ = kwargs + + if 'mean' in mode: + group_function = lambda array, _: groupby_mean(array) + elif 'min' in mode: + group_function = lambda array, _: groupby_min(array) + elif 'max' in mode: + group_function = lambda array, _: groupby_max(array) + elif 'prob' in mode: + group_function = groupby_prob + + # Labeled connected regions with an integer + labeled = connected_components(mask >= threshold, connectivity=connectivity) + objects = find_objects(labeled) + + # Create an instance of Horizon for each separate region + horizons = [] + for i, bbox in enumerate(objects): + max_possible_length = 1 + for slc in bbox: + max_possible_length *= slc.stop - slc.start + + if max_possible_length >= minsize: + indices = np.nonzero(labeled[bbox] == i + 1) + + if len(indices[0]) >= minsize: + coords = np.vstack([indices[i] + bbox[i].start for i in range(3)]).T + values = mask[coords[:, 0], coords[:, 1], coords[:, 2]] + + points = group_function(coords, values) + origin + + horizon = Horizon(storage=points, field=field, verify=True, name=f'{prefix}_{i}') + + if len(horizon) > 0: + horizons.append(horizon) + + if save_probabilities: + values = mask[horizon.points[:, 0] - origin[0], + horizon.points[:, 1] - origin[1], + horizon.points[:, 2] - origin[2]] + + horizon.proba_points = np.vstack([horizon.points[:, 0], horizon.points[:, 1], values]).T + # We save coordinates in the `proba_points` because horizon points can be filtered + # and this prevents from inconsistency between points and mask values + + horizons.sort(key=len) + return horizons + + def from_subset(self, matrix, name=None): + """ Make new label with points matrix filtered by given presence matrix. + + Parameters + ---------- + matrix : np.array + Presence matrix of labels points. Must be in full cubes coordinates. + If consists of 0 and 1, keep points only where values are 1. + If consists of values from [0, 1] interval, keep points where values are greater than 0.5. + name : str or None + Name for new label. If None, original label name used. + + Returns + ------- + New `Horizon` instance with filtered points matrix. + """ + result = copy(self) + result.name = name or self.name + + filtering_matrix = (matrix < 0.5).astype(int) + result.filter(filtering_matrix, inplace=True) + + return result + + + def make_proportional_horizon(self, other, p, name=None): + """ Make a proportional conforming horizon between `self` and `other` in `p` proportion. """ + # pylint: disable=protected-access + if self.d_mean > other.d_mean: + self, other = other, self + name = name or f'{self.name}_{other.name}__{int(p * 100)}^100' + + matrix = self.full_matrix + p * (other.full_matrix - self.full_matrix) + matrix = np.ceil(matrix) + matrix[self.full_matrix < 0] = self.FILL_VALUE + matrix[other.full_matrix < 0] = self.FILL_VALUE + + horizon = Horizon(matrix, field=self.field, name=name) + horizon._proportional = {'p': p, 'name_1': self.name, 'name_2': other.name} + return horizon + + # Basic properties + @property + def shape(self): + """ Tuple of horizon dimensions.""" + return (self.i_length, self.x_length) + + @property + def size(self): + """ Number of elements in the full horizon matrix.""" + return self.i_length * self.x_length + + @property + def short_name(self): + """ Name without extension. """ + if self.name is not None: + return self.name.split('.')[0] + return None + + # Horizon usage: mask generation + def add_to_mask(self, mask, locations=None, width=3, alpha=1, **kwargs): + """ Add horizon to a background. + Note that background is changed in-place. + + Parameters + ---------- + mask : ndarray + Background to add horizon to. + locations : ndarray + Where the mask is located. + width : int + Width of an added horizon. + alpha : number + Value to fill background with at horizon location. + """ + _ = kwargs + low = width // 2 + high = max(width - low, 0) + + mask_bbox = np.array([[slc.start, slc.stop] for slc in locations], dtype=np.int32) + + # Getting coordinates of overlap in cubic system + (mask_i_min, mask_i_max), (mask_x_min, mask_x_max), (mask_d_min, mask_d_max) = mask_bbox + + #TODO: add clear explanation about usage of advanced index in Horizon + i_min, i_max = max(self.i_min, mask_i_min), min(self.i_max + 1, mask_i_max) + x_min, x_max = max(self.x_min, mask_x_min), min(self.x_max + 1, mask_x_max) + + if i_max > i_min and x_max > x_min: + overlap = self.matrix[i_min - self.i_min : i_max - self.i_min, + x_min - self.x_min : x_max - self.x_min] + + # Coordinates of points to use in overlap local system + idx_i, idx_x = np.nonzero((overlap != self.FILL_VALUE) & + (overlap >= mask_d_min + low) & + (overlap <= mask_d_max - high)) + depths = overlap[idx_i, idx_x] + + # Convert coordinates to mask local system + idx_i += i_min - mask_i_min + idx_x += x_min - mask_x_min + depths -= (mask_d_min + low) + + for shift in range(width): + mask[idx_i, idx_x, depths + shift] = alpha + + return mask + + + def add_to_regression_mask(self, mask, locations, scale=False): + """ Add depth matrix at `locations` to `mask`. """ + mask_bbox = np.array([[slc.start, slc.stop] for slc in locations], dtype=np.int32) + + # Getting coordinates of overlap in cubic system + (mask_i_min, mask_i_max), (mask_x_min, mask_x_max), (mask_d_min, mask_d_max) = mask_bbox + + i_min, i_max = max(self.i_min, mask_i_min), min(self.i_max + 1, mask_i_max) + x_min, x_max = max(self.x_min, mask_x_min), min(self.x_max + 1, mask_x_max) + + if i_max > i_min and x_max > x_min: + overlap = self.matrix[i_min - self.i_min : i_max - self.i_min, + x_min - self.x_min : x_max - self.x_min] + + # Coordinates of points to use in overlap local system + idx_i, idx_x = np.asarray((overlap != self.FILL_VALUE) & + (overlap >= mask_d_min) & + (overlap <= mask_d_max)).nonzero() + depths = overlap[idx_i, idx_x].astype(np.float32) + + if scale: + depths -= mask_d_min + depths /= (mask_d_max - mask_d_min) + + mask[idx_i, idx_x] = depths + return mask + + + # Evaluate horizon on its own / against other(s) + @property + def metrics(self): + """ Calculate :class:`~HorizonMetrics` on demand. """ + # pylint: disable=import-outside-toplevel + from ...metrics import HorizonMetrics + return HorizonMetrics(self) + + def evaluate(self, compute_metric=True, supports=50, visualize=True, savepath=None, printer=print, **kwargs): + """ Compute crucial metrics of a horizon. + + Parameters + ---------- + compute_metrics : bool + Whether to compute correlation map of a horizon. + supports, savepath, plot, kwargs + Passed directly to :meth:`HorizonMetrics.evaluate`. + printer : callable + Function to display message with metrics. + """ + # Textual part + if printer is not None: + msg = f""" + Number of labeled points: {len(self)} + Number of points inside borders: {np.sum(self.filled_matrix)} + Perimeter (length of borders): {self.perimeter} + Percentage of labeled non-bad traces: {self.coverage:4.3f} + Percentage of labeled traces inside borders: {self.solidity:4.3f} + Number of holes inside borders: {self.number_of_holes} + """ + printer(dedent(msg)) + + # Visual part + if compute_metric: + from ...metrics import HorizonMetrics # pylint: disable=import-outside-toplevel + if savepath is not None: + kwargs['savepath'] = self.field.make_path(savepath, name=self.short_name) + return HorizonMetrics(self).evaluate('support_corrs', supports=supports, agg='nanmean', + visualize=visualize, **kwargs) + return None + + + def check_proximity(self, other): + """ Compute a number of stats of location of `self` relative to the `other` Horizons. + + Parameters + ---------- + self, other : Horizon + Horizons to compare. + + Returns + ------- + dictionary with following keys: + - `difference_matrix` with matrix of depth differences + - `difference_mean` for average distance + - `difference_abs_mean` for average of absolute values of point-wise distances + - `difference_max`, `difference_abs_max`, `difference_std`, `difference_abs_std` + - `overlap_size` with number of overlapping points + - `window_rate` for percentage of traces that are in 5ms from one horizon to the other + """ + # Compute diffs + difference = np.where((self.full_matrix != self.FILL_VALUE) & (other.full_matrix != self.FILL_VALUE), + self.full_matrix - other.full_matrix, np.nan) + + mask = ~np.isnan(difference) + overlap_size = np.sum(mask) + masked_difference = difference[mask] + masked_abs_difference = np.abs(masked_difference) + window_rate = np.sum(masked_abs_difference < (5 / self.field.sample_interval)) / overlap_size + + present_at_1_absent_at_2 = ((self.full_matrix != self.FILL_VALUE) + & (other.full_matrix == self.FILL_VALUE)).sum() + present_at_2_absent_at_1 = ((self.full_matrix == self.FILL_VALUE) + & (other.full_matrix != self.FILL_VALUE)).sum() + + if masked_difference.size == 0: + masked_difference = masked_abs_difference = np.array([np.nan], dtype=np.float32) + + info_dict = { + 'difference_matrix' : difference, + 'difference_mean' : np.mean(masked_difference), + 'difference_max' : np.max(masked_difference), + 'difference_min' : np.min(masked_difference), + 'difference_std' : np.std(masked_difference), + + 'abs_difference_mean' : np.mean(masked_abs_difference), + 'abs_difference_max' : np.max(masked_abs_difference), + 'abs_difference_std' : np.std(masked_abs_difference), + + 'accuracy@0': np.mean(masked_abs_difference == 0), + 'accuracy@1': np.mean(masked_abs_difference <= 1), + 'accuracy@2': np.mean(masked_abs_difference <= 2), + + 'overlap_size': overlap_size, + 'overlap_coverage': overlap_size / self.field.n_alive_traces, + 'window_rate': window_rate, + + 'present_at_1_absent_at_2' : present_at_1_absent_at_2, + 'present_at_2_absent_at_1' : present_at_2_absent_at_1, + } + info_dict = {key : round(value, 4) if isinstance(value, (float, np.floating)) else value + for key, value in info_dict.items()} + return MetaDict(info_dict) + + def find_closest(self, *others): + """ Find closest horizon to `self` in the list of `others`. """ + proximities = [(other, self.check_proximity(other)) for other in others + if other.field.name == self.field.name] + + closest, proximity_info = min(proximities, key=lambda item: item[1].get('abs_difference_mean', np.inf)) + return closest, proximity_info + + # Alias for horizon comparisons + def compare(self, *others, clip_value=5, ignore_zeros=True, + printer=print, visualize=True, hist_kwargs=None, **kwargs): + """ Alias for `HorizonMetrics.compare`. """ + return self.metrics.compare(*others, clip_value=clip_value, ignore_zeros=ignore_zeros, + printer=printer, visualize=visualize, hist_kwargs=hist_kwargs, **kwargs) + + def compute_prediction_std(self, others): + """ Compute std of predicted horizons along depths and restrict it to `self`. """ + std_matrix = self.metrics.compute_prediction_std(list(set([self, *others]))) + std_matrix[self.mask == False] = np.nan #pylint: disable=singleton-comparison + return std_matrix + + + def equal(self, other, threshold_missing=0): + """ Return True if the horizons are considered equal, False otherwise. + If the `threshold_missing` is zero, then check if the points of `self` and `other` are the same. + If the `threshold_missing` is positive, then check that in overlapping points values are the same, + and number of missing traces is smaller than allowed. + """ + if threshold_missing == 0: + return np.array_equal(self.points, other.points) + + info = self.check_proximity(other) + n_missing = max(info['present_at_1_absent_at_2'], info['present_at_2_absent_at_1']) + return info['difference_mean'] == 0 and n_missing < threshold_missing + + # Merging + def merge_points(self, others, mode='mean', inplace=True, add_prefix=True): + """ Merge horizon with `others`. + + Parameters + ---------- + mode : str, {'mean', 'min', 'max'} + Method used for evaluating point depth in overlapping areas. + If `mean/min/max`, then we take mean/min/max depth value on a trace. + """ + if not isinstance(others, (list, tuple)): + others = [others] + + if 'mean' in mode: + group_function = groupby_mean + elif 'min' in mode: + group_function = groupby_min + elif 'max' in mode: + group_function = groupby_max + + points = np.vstack((self.points, *(other.points for other in others))) + order = np.lexsort((points[:, 1], points[:, 0])) + points = points[order] + points = group_function(points) + + if inplace: + self.points = points + self.reset_storage('matrix') + return self + + name = f"concated_{self.name}" if add_prefix else self.name + return type(self)(storage=points, field=self.field, name=name) + + # Save horizon to disk + def dump_sqb(self, data, path, format='points', transform=None, name=None, attributes=None): + """ Dump horizon points to SQB storage. + If `attributes` are provided, then saves additional instance attributes in the storage, + which will be re-loaded at opening. + """ + _ = format + attributes = attributes or [] + path = self.field.make_path(path, name=name or self.name) + os.makedirs(os.path.dirname(path), exist_ok=True) + + # Additional transform + points = data if transform is None else transform(data) + + storage = SQBStorage(path) + storage.update({ + 'type': 'horizon', + 'points': points, + 'original_path': self.path, + 'field_path': self.field.path, + 'attributes': attributes, + **{key : getattr(self, key) for key in attributes}, + }) + + def dump(self, path, format='char', transform=None, attributes=None, smooth_out=False, + kernel_size=7, sigma=2., max_depth_difference=5): + """ Save horizon points on disk. + + Parameters + ---------- + path : str + Path to a file to save horizon to. + format : {'char', 'sqb'} + Format of storage, either CHARISMA or SQB. + transform : None or callable + If callable, then applied to points after converting to ilines/xlines coordinate system. + attributes : sequence of str, optional + Additional attributes to dump into file. Used only if format is SQB. + smooth_out : bool + Whether to apply smoothening to the horizon surface, producing float-point numbers instead of ints. + kernel_size : int + Size of the filtering kernel. + sigma : number + Standard deviation of the Gaussian kernel. + max_depth_difference : number + If the distance between anchor point and the point inside filter is bigger than the threshold, + then the point is ignored in smoothening. + Can be used for separate smoothening on sides of discontinuity. + """ + # Add extension to `path`, if missing + format = format.lower() + # _, extension = os.path.splitext(path) + # if extension: + # path = path.replace(extension, '.' + format) + # else: + # path = path + '.' + format + + # Apply smoothing + if smooth_out: + horizon = self.smooth_out(mode='convolve', kernel_size=kernel_size, sigma_spatial=sigma, + max_depth_difference=max_depth_difference, inplace=False, dtype=np.float32) + else: + horizon = self + + # Dump + if format.startswith('c'): + horizon.dump_charisma(data=horizon.points.copy(), path=path, name=self.name, + format='points', transform=transform) + else: + horizon.dump_sqb(data=horizon.points.copy(), path=path, name=self.name, + format='points', transform=transform, attributes=attributes) + + def dump_float(self, path, format='char', transform=None, attributes=None, + kernel_size=7, sigma=2., max_depth_difference=5): + """ An alias to :meth:`.dump` with turned on smoothing by default. """ + self.dump(path=path, format=format, transform=transform, smooth_out=True, attributes=attributes, + kernel_size=kernel_size, sigma=sigma, max_depth_difference=max_depth_difference) diff --git a/seismiqb/labels/horizon/extraction.py b/seismiqb/labels/horizon/extraction.py new file mode 100644 index 0000000..43fa0d3 --- /dev/null +++ b/seismiqb/labels/horizon/extraction.py @@ -0,0 +1,988 @@ +""" Method for horizon extraction from 3D volume and their merging. """ +from enum import IntEnum +from time import perf_counter +from operator import attrgetter +from collections import defaultdict +from concurrent.futures import ThreadPoolExecutor + +import numpy as np +from cv2 import dilate +from numba import njit + +from cc3d import connected_components +from scipy.ndimage import find_objects + +from ...utils import MetaDict, groupby_all + +class MergeStatus(IntEnum): + """ Possible outcomes of the `:meth:~ExtractionMixin.verify_merge`. + Values describe the relative position of two horizons. + """ + # Definetely not mergeable + DEPTH_SEPARATED = 0 + SPATIALLY_SEPARATED = 1 + TOO_SMALL_OVERLAP = 2 + + # Maybe can merge + SPATIALLY_ADJACENT = 3 + + # Definetely merge + OVERLAPPING = 4 + + # Too big of an overlap: no reason to merge + TOO_BIG_OVERLAP = 5 + + + +class ExtractionMixin: + """ Methods for horizon extraction from 3D volumes and their later merge. """ + #pylint: disable=too-many-statements, too-many-nested-blocks, line-too-long, protected-access + @classmethod + def extract_from_mask(cls, mask, field=None, origin=None, minsize=1000, + prefix='extracted', verbose=False, max_iters=999): + """ Extract separate horizon instances from subvolume. + + Basic idea is to find all the connected regions inside the subvolume and mark them as individual horizons. + Some of the surfaces touch (either because of being too close or accidentally). To separate them we need to: + - if the connected point cloud has multiple labeled points at each trace, then we split it into three parts. + One is the minimum envelope of point cloud, the other is the maximum envelope, + and the third consists of the points where each trace contains only one point. + - each of the three point clouds is split into connected regions itself, which are considered to be + individual horizons. We need this step to separate surfaces that are connected by the third point cloud. + + After extracting some points as horizon instance, we remove those points from subvolume. + The above is repeated until `max_iters` is reached or no points remain in the original array. + + Returned list of horizons is sorted by length of horizons. + The entire procedure is heavily logged, providing timings and statistics in a separate returned dictionary. + + Parameters + ---------- + field : Field + Horizon parent field. + origin : sequence + The upper left coordinate of a `mask` in the cube coordinates. + minsize : int + Minimum length of a horizon to be extracted. + prefix : str + Name of horizon to use. + verbose : bool + Whether to print some of the intermediate statistics. + max_iters : int + Maximum number of outer iterations (re-labeling the whole cube, extracting surfaces, deleting points). + + Returns + ------- + (list_of_horizons, stats_dict) + Tuple with the list of extracted instances as the first element and logging stats as the second. + """ + mask = mask.copy() + total_points = int(mask.sum()) + + # `num` prefix for horizon count in category, `total` prefix for number of points in category + stats = MetaDict({ + "measurement_timings" : [], + "iteration_timings" : [], + + "num_objects" : [], + "num_deleted" : [], + "num_extracted_easy" : [], + "num_extracted_hard" : [], + + "num_easy" : 0, + "num_hard" : 0, + "num_hard_separated" : 0, + "num_hard_joined" : 0, + "num_extracted_from_easy" : 0, + "num_extracted_from_hard" : 0, + + "total_remaining_points" : [f'{total_points:,}'], + "total_deleted_points" : [], + }) + + if verbose: + print(f'Starting from {total_points:,} points in the mask') + + horizons = [] + for _ in range(max_iters): + start_timing = perf_counter() + num_deleted = 0 + num_extracted_easy = 0 + num_extracted_hard = 0 + total_deleted_points = 0 + total_extracted_points = 0 + + # Label connected entities + labeled = connected_components(mask) + objects = find_objects(labeled) + stats['measurement_timings'].append(round(perf_counter() - start_timing, 2)) + stats['num_objects'].append(len(objects)) + + for i, slices in enumerate(objects): + # Point cloud in `slices` coordinates + indices = np.nonzero(labeled[slices] == i + 1) + points = np.vstack(indices).T + + # iline, crossline, occurencies_ix, min_ix, max_ix, mean_ix + grouped_points = groupby_all(points) + + if len(points) == len(grouped_points): + # Point-cloud extracted cleanly, with no ambiguous points + stats['num_easy'] += 1 + + # Remove from the original mask + horizon_points = points + [slc.start or 0 for slc in slices] + mask[horizon_points[:, 0], horizon_points[:, 1], horizon_points[:, 2]] = 0 + num_deleted += 1 + total_deleted_points += len(horizon_points) + + # Horizon points validation: can be expanded + if len(points) < minsize: + continue + + horizons.append(horizon_points) + num_extracted_easy += 1 + total_extracted_points += len(horizon_points) + stats['num_extracted_from_easy'] += 1 + + else: + # Point-cloud contains multiple points at some traces + # Extract min/max envelopes, remove them from original mask, repeat the process + # We use separate indexing for spatial/depth coordinates to avoid advanced indexing for columns + stats['num_hard'] += 1 + + mask_min_max = (grouped_points[:, 3] == grouped_points[:, 4]) + if mask_min_max.any(): + # Joined surface: min==max + at_joined = grouped_points[mask_min_max] + ix_joined = at_joined[:, :2] + h_joined = at_joined[:, 3] + + # Two separate surfaces: min < max + # Can't be empty: if that is the case, surfaces would be identical -> extracted cleanly + at_separated = grouped_points[~mask_min_max] + ix_separated = at_separated[:, :2] + min_separated = at_separated[:, 3] + max_separated = at_separated[:, 4] + + surfaces = [(ix_joined, h_joined), + (ix_separated, min_separated), + (ix_separated, max_separated)] + stats['num_hard_joined'] += 1 + else: + # Two separate surfaces: min < max + ix = grouped_points[:, :2] + min_ = grouped_points[:, 3] + max_ = grouped_points[:, 4] + + surfaces = [(ix, min_), + (ix, max_)] + stats['num_hard_separated'] += 1 + + # Put each surface on the blank array and extract connected components + # Then, remove corresponding points from the original array + shape = tuple(slc.stop - slc.start for slc in slices) + + for ix_coords, h_coords in surfaces: + background = np.zeros(shape, dtype=np.int8) + background[ix_coords[:, 0], ix_coords[:, 1], h_coords] = 1 + + inner_labeled = connected_components(background) + inner_objects = find_objects(inner_labeled) + + for inner_i, inner_slices in enumerate(inner_objects): + inner_indices = np.nonzero(background[inner_slices] == inner_i + 1) + inner_points = np.vstack(inner_indices).T + + # Remove from the original mask + horizon_points = inner_points + [(slc.start or 0) + (inner_slc.start or 0) + for slc, inner_slc in zip(slices, inner_slices)] + mask[horizon_points[:, 0], horizon_points[:, 1], horizon_points[:, 2]] = 0 + num_deleted += 1 + total_deleted_points += len(horizon_points) + + # Horizon points validation: can be expanded + if len(inner_points) < minsize: + continue + + horizons.append(horizon_points) + + num_extracted_hard += 1 + total_extracted_points += len(horizon_points) + stats['num_extracted_from_hard'] += 1 + + # Log iteration stats + total_points -= total_deleted_points + stats['iteration_timings'].append(round(perf_counter() - start_timing, 2)) + + stats['num_deleted'].append(num_deleted) + stats['num_extracted_easy'].append(num_extracted_easy) + stats['num_extracted_hard'].append(num_extracted_hard) + + stats['total_remaining_points'].append(f'{total_points:,}') + stats['total_deleted_points'].append(total_deleted_points) + + if verbose: + print(f'Remaining points in the mask: {total_points:,}, num deleted: {num_deleted:>5}, ' + f'total extracted points {total_extracted_points:>7,}, ' + f'extracted easy: {num_extracted_easy:>3}, extracted hard: {num_extracted_hard:>3}') + + if num_deleted == 0: + break + + # Make `Horizon` instances + horizons.sort(key=len) + horizons = [cls(horizon_points + origin, field=field, name=f'{prefix}_{i}') + for i, horizon_points in enumerate(horizons)] + return horizons, stats + + + def verify_merge(self, other, mean_threshold=1.0, max_threshold=2, adjacency=0, + min_size_threshold=1, max_size_threshold=None): + """ Compute the relative position of two horizons, based on the thresholding parameters. + + Comparison is split into multiple parts: + - the simplest check is to look at horizons bounding boxes. + This check is performed with the `adjacency` in mind: by using it, one can allow touching horizons or + with gaps of multiple pixels. This parameter's detailed description is below. + If the bboxes are too far along ilines/crosslines, then horizons are SPATIALLY_SEPARATED + + - otherwise, we compare horizon matrices on overlap of their bboxes. + - if the size of actual overlap is 0, then horizons are SPATIALLY_ADJACENT + + - if the size of actual overlap is lower than the `min_size_threshold`: + - if the mean difference on overlap is lower than the `mean_threshold`, then horizons are TOO_SMALL_OVERLAP + - if the mean difference on overlap is bigger than the `mean_threshold`, then horizons are DEPTH_SEPARATED + + - if the size of actual overlap is bigger than the `max_size_threshold`: + - if the mean difference on overlap is lower than the `mean_threshold`, then horizons are TOO_BIG_OVERLAP + - if the mean difference on overlap is bigger than the `mean_threshold`, then horizons are DEPTH_SEPARATED + + - otherwise, the size of overlap is within allowed bounds: + - if the mean difference on overlap is lower than the `mean_threshold`, then horizons are OVERLAPPING + - if the mean difference on overlap is bigger than the `mean_threshold`, then horizons are DEPTH_SEPARATED + + Parameters + ---------- + self, other + Horizons to compare. + adjacency : int or sequence of ints + Allowed size of the gaps between bounding boxes along each of the axis: + - adjacency = +0 means trying to merge horizons with overlap of 1 pixel + - adjacency = +1 means trying to merge horizons with touching boundaries + - adjacency = +2 means trying to merge horizons with gap of 1 pixel between bboxes + + By using negative values, one can require the overlap of bboxes: + - adjacency = -1 means trying to merge horizons with overlap of 2 pixel + If the integer is passed, then the same adjacency rules apply along both iline and crossline directions. + + mean_threshold : number + Allowed mean difference on horizons overlap. + max_threshold : number + Allowed max difference on horizons overlap. + min_size_threshold : int + Minimum allowed size of the horizons overlap. + max_size_threshold : int + Maximum allowed size of the horizons overlap. Used only if explicitly passed. + Can be used to refrain from merging `almost completely the same horizons`. + + Returns + ------- + MergeStatus to describe relative positions of `self` and `other` horizons. + """ + # Adjacency parsing + adjacency = adjacency if isinstance(adjacency, tuple) else (adjacency, adjacency) + adjacency_i, adjacency_x = adjacency + + # Overlap bbox + overlap_i_min, overlap_i_max = max(self.i_min, other.i_min), min(self.i_max, other.i_max) + 1 + overlap_x_min, overlap_x_max = max(self.x_min, other.x_min), min(self.x_max, other.x_max) + 1 + + overlap_size_i = overlap_i_max - overlap_i_min + overlap_size_x = overlap_x_max - overlap_x_min + + # Simplest possible check: horizon bboxes are too far from each other + if overlap_size_i < 1 - adjacency_i or overlap_size_x < 1 - adjacency_x: + status = MergeStatus.SPATIALLY_SEPARATED + else: + status = MergeStatus.SPATIALLY_ADJACENT + + + # Compare matrices on overlap without adjacency: + if status != 1 and overlap_size_i > 0 and overlap_size_x > 0: + self_overlap = self.matrix[overlap_i_min - self.i_min:overlap_i_max - self.i_min, + overlap_x_min - self.x_min:overlap_x_max - self.x_min] + other_overlap = other.matrix[overlap_i_min - other.i_min:overlap_i_max - other.i_min, + overlap_x_min - other.x_min:overlap_x_max - other.x_min] + + mean_on_overlap, size_of_overlap = intersect_matrix(self_overlap, other_overlap, max_threshold) + + if size_of_overlap == 0: + # bboxes are overlapping, but horizons are not + status = MergeStatus.SPATIALLY_ADJACENT + + elif size_of_overlap < min_size_threshold: + # the overlap is too small + if mean_on_overlap < mean_threshold: + status = MergeStatus.TOO_SMALL_OVERLAP + else: + status = MergeStatus.DEPTH_SEPARATED + elif max_size_threshold is not None and size_of_overlap > max_size_threshold: + if mean_on_overlap < mean_threshold: + status = MergeStatus.TOO_BIG_OVERLAP + else: + status = MergeStatus.DEPTH_SEPARATED + else: # min_size_threshold <= size_of_overlap <= max_size_threshold + if mean_on_overlap <= mean_threshold: + status = MergeStatus.OVERLAPPING + else: + status = MergeStatus.DEPTH_SEPARATED + + return status + + + def overlap_merge(self, other, inplace=False): + """ Merge two horizons into one. Values on overlap are the floored average from the `self` and `other` values. + Can either merge horizons in-place of the first one (`self`), or create a new instance. + + TODO: this function is optimized to use only `matrix` storage from both of the horizons, + which is the most optimal in current paradigm. Implement the other ways to merge horizons + to use them accordingly, i.e. `merge_to_matrix_by_points`, `merge_to_points_by_points` methods. + """ + # Create shared background for both horizons + shared_i_min, shared_i_max = min(self.i_min, other.i_min), max(self.i_max, other.i_max) + shared_x_min, shared_x_max = min(self.x_min, other.x_min), max(self.x_max, other.x_max) + + background = np.zeros((shared_i_max - shared_i_min + 1, shared_x_max - shared_x_min + 1), + dtype=np.int32) + + # Coordinates inside shared for `self` and `other` + shared_self_i_min, shared_self_x_min = self.i_min - shared_i_min, self.x_min - shared_x_min + shared_other_i_min, shared_other_x_min = other.i_min - shared_i_min, other.x_min - shared_x_min + + # Add both horizons to the background + background[shared_self_i_min:shared_self_i_min+self.i_length, + shared_self_x_min:shared_self_x_min+self.x_length] += self.matrix + + background[shared_other_i_min:shared_other_i_min+other.i_length, + shared_other_x_min:shared_other_x_min+other.x_length] += other.matrix + + # Correct overlapping points + overlap_i_min, overlap_i_max = max(self.i_min, other.i_min), min(self.i_max, other.i_max) + 1 + overlap_x_min, overlap_x_max = max(self.x_min, other.x_min), min(self.x_max, other.x_max) + 1 + + overlap_i_min -= shared_i_min + overlap_i_max -= shared_i_min + overlap_x_min -= shared_x_min + overlap_x_max -= shared_x_min + + overlap = background[overlap_i_min:overlap_i_max, overlap_x_min:overlap_x_max] + mask = overlap >= 0 + overlap[mask] //= 2 + overlap[~mask] -= self.FILL_VALUE + background[overlap_i_min:overlap_i_max, overlap_x_min:overlap_x_max] = overlap + + background[background == 0] = self.FILL_VALUE + length = len(self) + len(other) - mask.sum() + + # Create new instance or change `self` + if inplace: + # Change `self` inplace, mark `other` as merged into `self` + self.from_matrix(background, i_min=shared_i_min, x_min=shared_x_min, + d_min=min(self.d_min, other.d_min), + d_max=max(self.d_max, other.d_max), length=length) + self.reset_storage('points', reset_cache=False) + other.already_merged = id(self) + merged = True + else: + # Return a new instance of horizon + merged = type(self)(storage=background, field=self.field, name=self.name, + i_min=shared_i_min, x_min=shared_x_min, + d_min=min(self.d_min, other.d_min), + d_max=max(self.d_max, other.d_max), length=length) + return merged + + + def adjacent_merge(self, other, mean_threshold=3.0, adjacency=3, inplace=False): + """ Check if adjacent merge (that is merge with some margin) is possible, and, if needed, merge horizons. + Can either merge horizons in-place of the first one (`self`), or create a new instance. + + TODO: this function may be outdated and should be used with caution. + + Parameters + ---------- + self, other : :class:`.Horizon` instances + Horizons to merge. + mean_threshold : number + Depth threshold for mean distances. + adjacency : int + Margin to consider horizons close (spatially). + inplace : bool + Whether to create new instance or update `self`. + """ + # Adjacency parsing + adjacency = adjacency if isinstance(adjacency, tuple) else (adjacency, adjacency) + adjacency_i, adjacency_x = adjacency + + # Simplest possible check: horizons are too far away from one another (depth-wise) + overlap_d_min, overlap_d_max = max(self.d_min, other.d_min), min(self.d_max, other.d_max) + if overlap_d_max - overlap_d_min < 0: + return False + + # Create shared background for both horizons + shared_i_min, shared_i_max = min(self.i_min, other.i_min), max(self.i_max, other.i_max) + shared_x_min, shared_x_max = min(self.x_min, other.x_min), max(self.x_max, other.x_max) + + background = np.zeros((shared_i_max - shared_i_min + 1, shared_x_max - shared_x_min + 1), dtype=np.int32) + + # Coordinates inside shared for `self` and `other` + shared_self_i_min, shared_self_x_min = self.i_min - shared_i_min, self.x_min - shared_x_min + shared_other_i_min, shared_other_x_min = other.i_min - shared_i_min, other.x_min - shared_x_min + + # Put the second of the horizons on background + background[shared_other_i_min:shared_other_i_min+other.i_length, + shared_other_x_min:shared_other_x_min+other.x_length] += other.matrix + + # Enlarge the image to account for adjacency + kernel = np.ones((1 + 2*adjacency_i, 1 + 2*adjacency_x), np.float32) + dilated_background = dilate(background.astype(np.float32), kernel).astype(np.int32) + + # Make counts: number of horizons in each point; create indices of overlap + counts = (dilated_background > 0).astype(np.int32) + counts[shared_self_i_min:shared_self_i_min+self.i_length, + shared_self_x_min:shared_self_x_min+self.x_length] += (self.matrix > 0).astype(np.int32) + counts_idx = counts == 2 + + # Determine whether horizon can be merged (adjacent and depth-close) or not + mergeable = False + if counts_idx.any(): + # Put the first horizon on dilated background, compute mean + background[shared_self_i_min:shared_self_i_min+self.i_length, + shared_self_x_min:shared_self_x_min+self.x_length] += self.matrix + + # Compute diffs on overlap + diffs = background[counts_idx] - dilated_background[counts_idx] + diffs = np.abs(diffs) + diffs = diffs[diffs < (-self.FILL_VALUE // 2)] + + if len(diffs) != 0 and np.mean(diffs) < mean_threshold: + mergeable = True + + if mergeable: + background[(background < 0) & (background != self.FILL_VALUE)] -= self.FILL_VALUE + background[background == 0] = self.FILL_VALUE + + length = len(self) + len(other) # since there is no direct overlap + + # Create new instance or change `self` + if inplace: + # Change `self` inplace, mark `other` as merged into `self` + self.from_matrix(background, i_min=shared_i_min, x_min=shared_x_min, + d_min=min(self.d_min, other.d_min), + d_max=max(self.d_max, other.d_max), length=length) + self.reset_storage('points', reset_cache=False) + other.already_merged = id(self) + merged = True + else: + # Return a new instance of horizon + merged = type(self)(storage=background, field=self.field, name=self.name, + i_min=shared_i_min, x_min=shared_x_min, + d_min=min(self.d_min, other.d_min), + d_max=max(self.d_max, other.d_max), + length=length) + return merged + return False + + + def merge_into(self, horizons, mean_threshold=1., max_threshold=1.2, min_size_threshold=1, max_size_threshold=None, + adjacency=1, max_iters=999, num_merged_threshold=1): + """ Try to merge instances from the list of `horizons` into `self`. + + For each horizon in the list, we check the possibility to merge it into the current `self` horizon: + - first of all, we select candidates to merge by optimized bbox check + - for each of the candidates: + - we use the `verify_merge` to better check the relations between `candidate` and `self` + - depending on the status, merge the candidate into `self` and remove it from the list. + The above is repeated until `max_iters` is reached or no horizon from the list can be merged to `self`. + + Parameters + ---------- + horizons : sequence + Horizons to merge into `self`. + adjacency, mean_threshold, max_threshold, min_size_threshold, max_size_threshold : number + Parameters for `:meth:~.verify_merge`. + max_iters : int + Maximum number of outer iterations (computing candidates, merging them and deleting from the original list). + num_merged_threshold : int + Minimum amount of merged horizons at outer iteration to perform the next iteration. + If the number of merged instances is less than this threshold, we break out of the outer loop. + + Returns + ------- + (self, horizons, stats_dict) + A tuple with: + - an instance where some of the items in `horizons` were merged to + - remaining horizons + - dictionary with timings and statistics + """ + if isinstance(horizons, (tuple, list)): + horizons = np.array([horizon for horizon in horizons if not horizon.already_merged]) + + # Pre-compute all the bounding boxes + bboxes = np.array([horizon.raveled_bbox for horizon in horizons], dtype=np.int32).reshape(-1, 6) + + # Adjacency parsing + adjacency = adjacency if isinstance(adjacency, tuple) else (adjacency, adjacency) + adjacency_i, adjacency_x = adjacency + + # Keep track of stats + merge_stats = defaultdict(int) + merge_stats.update({'iteration_timings' : [], + 'merge_candidates': [], + 'merges' : []}) + + for _ in range(max_iters): + start_timing = perf_counter() + num_merged = 0 + indices_merged = set() + + # Iline-axis + overlap_min_i = np.maximum(bboxes[:, 0], self.raveled_bbox[0]) + overlap_max_i = np.minimum(bboxes[:, 1], self.raveled_bbox[1]) + 1 + overlap_size_i = overlap_max_i - overlap_min_i + mask_i = (overlap_size_i >= 1 - adjacency_i) + indices_i = np.nonzero(mask_i)[0] + bboxes_i = bboxes[indices_i] + + # Crossline-axis + overlap_min_x = np.maximum(bboxes_i[:, 2], self.raveled_bbox[2]) + overlap_max_x = np.minimum(bboxes_i[:, 3], self.raveled_bbox[3]) + 1 + overlap_size_x = overlap_max_x - overlap_min_x + mask_x = (overlap_size_x >= 1 - adjacency_x) + indices_x = np.nonzero(mask_x)[0] + bboxes_x = bboxes_i[indices_x] + + # depth-axis: other threshold + overlap_min_h = np.maximum(bboxes_x[:, 4], self.raveled_bbox[4]) + overlap_max_h = np.minimum(bboxes_x[:, 5], self.raveled_bbox[5]) + 1 + overlap_size_h = overlap_max_h - overlap_min_h + mask_h = (overlap_size_h >= 1) + indices_h = np.nonzero(mask_h)[0] + bboxes_h = bboxes_x[indices_h] + + indices = indices_i[indices_x][indices_h] + merge_candidates = horizons[indices] + _ = bboxes_h + + merge_stats['merge_candidates'].append(len(indices)) + + # Merge all possible candidates + for idx, merge_candidate in zip(indices, merge_candidates): + # Compute the mergeability + merge_status = ExtractionMixin.verify_merge(self, merge_candidate, + mean_threshold=mean_threshold, + max_threshold=max_threshold, + min_size_threshold=min_size_threshold, + max_size_threshold=max_size_threshold, + adjacency=adjacency) + merge_stats[merge_status] += 1 + + # Merge, if needed + if merge_status == 4: + # Overlapping horizons: definitely merge + merged = ExtractionMixin.overlap_merge(self, merge_candidate, inplace=True) + + elif merge_status == 3 and (adjacency_i > 0 or adjacency_x > 0): + # Adjacent horizons: maybe we can merge it + merged = ExtractionMixin.adjacent_merge(self, merge_candidate, inplace=True, + mean_threshold=mean_threshold, + adjacency=adjacency) + merge_stats['merged_adjacent'] += (1 if merged else 0) + else: + # Spatially separated or too small of an overlap + # Can't merge for now, but maybe will be able later + merged = False + + # Keep values for clean-up + if merged: + indices_merged.add(idx) + num_merged += 1 + + # Once in a while, remove merged horizons from `bboxes` and `horizons` arrays + if indices_merged: + indices_merged = list(indices_merged) + horizons = np.delete(horizons, indices_merged, axis=0) + bboxes = np.delete(bboxes, indices_merged, axis=0) + + merge_stats['num_deletes'] += 1 + + # Global iteration info + merge_stats['iterations'] += 1 + merge_stats['merges'].append(num_merged) + merge_stats['iteration_timings'].append(round(perf_counter() - start_timing, 2)) + + # Exit condition: merged less horizons then threshold + if num_merged < num_merged_threshold or len(horizons) == 0: + break + + return self, horizons, MetaDict(merge_stats) + + @staticmethod + def merge_list(horizons, mean_threshold=1., max_threshold=2.2, + min_size_threshold=1, max_size_threshold=None, adjacency=1, + max_iters=999, num_merged_threshold=1, delete_threshold=0.01): + """ Merge each horizon to each in the `horizons`, until no merges are possible. + + Under the hood, we start by computing the bboxes of all horizons. Then, for each horizon we: + - first of all, we select candidates to merge by optimized bbox check + - for each of the candidates: + - we use the `verify_merge` to better check the relations between `candidate` and `self` + - depending on the status, merge the candidate into `self` + - remember the index of the candidate to clean up the `horizons` and `bboxes` arrays later. + The above is repeated until `max_iters` is reached or no two horizons from the list can be merged. + + We clean-up the `horizons` and `bboxes` only occasionnaly to amortize the costs of the deletion operation. + Other optimization is to flag horizons as unmerged at outer iteration: if horizon was not merged to any other, + then it would not be merged at any of the subsequent iterations. + + The entire procedure is heavily logged, providing timings and statistics in a separate returned dictionary. + + Parameters + ---------- + adjacency, mean_threshold, max_threshold, min_size_threshold, max_size_threshold : number + Parameters for `:meth:~.verify_merge`. + max_iters : int + Maximum number of outer iterations (computing bboxes, merging each horizon with all possible candidates, + deleting from the original list). + num_merged_threshold : int + Minimum amount of merged horizons at outer iteration to perform the next iteration. + If the number of merged instances is less than this threshold, we break out of the outer loop. + + Returns + ------- + (horizons, stats_dict) + A tuple with: + - remaining horizons + - dictionary with timings and statistics + """ + # Adjacency parsing + adjacency = adjacency if isinstance(adjacency, tuple) else (adjacency, adjacency) + adjacency_i, adjacency_x = adjacency + + # Flag all horizons. If at some iteration the horizon is not merged to any other, + # it would not be merged at all (i.e. rejected) + for horizon in horizons: + horizon.merge_count = 0 + horizon.id_separated = set() + horizons = np.array(horizons) + rejected_horizons = [] + + # Keep track of stats. Pretty much no overhead to the procedure + merge_stats = defaultdict(int) + merge_stats.update({'global_iteration_timings' : [], + 'global_merges' : [], + 'num_rejected_horizons' : []}) + + # Global iteration: iterate over the entire list, comparing each horizon to each other + for _ in range(max_iters): + start_timing = perf_counter() + num_merged = 0 + indices_merged = set() # used to periodically clean-up arrays + + # Pre-compute all the bounding boxes + bboxes = np.array([horizon.raveled_bbox for horizon in horizons], dtype=np.int32) + + # Cycle for the base horizons. As we are removing merged horizons from the list, we iterate with `while` + i = 0 + while True: + if i >= len(horizons): + break + if i in indices_merged: + i += 1 + continue + + current_horizon = horizons[i] + current_bbox = bboxes[i] + + # Filter: keep only overlapping/adjacent horizons + # Compute bbox overlaps: `overlap_size` > 0 means size of common pixels along the axis + # `overlap_size` = 0 means touching along the axis + # `overlap_size` < 0 means size of gap between horizons along the axis + + # adjacency = -1 -> try to merge horizons with overlap of 2 pixels + # adjacency = +0 -> try to merge horizons with overlap of 1 pixel + # adjacency = +1 -> try to merge horizons with touching boundaries + # adjacency = +2 -> try to merge horizons with gap of 1 pixel between boundaries + # TODO: check, if using depth as the first mask is faster + + # Iline-axis + overlap_min_i = np.maximum(bboxes[:, 0], current_bbox[0]) + overlap_max_i = np.minimum(bboxes[:, 1], current_bbox[1]) + 1 + overlap_size_i = overlap_max_i - overlap_min_i + mask_i = (overlap_size_i >= 1 - adjacency_i) + indices_i = np.nonzero(mask_i)[0] + bboxes_i = bboxes[indices_i] + + # Crossline-axis + overlap_min_x = np.maximum(bboxes_i[:, 2], current_bbox[2]) + overlap_max_x = np.minimum(bboxes_i[:, 3], current_bbox[3]) + 1 + overlap_size_x = overlap_max_x - overlap_min_x + mask_x = (overlap_size_x >= 1 - adjacency_x) + indices_x = np.nonzero(mask_x)[0] + bboxes_x = bboxes_i[indices_x] + + # depth-axis: other threshold + overlap_min_h = np.maximum(bboxes_x[:, 4], current_bbox[4]) + overlap_max_h = np.minimum(bboxes_x[:, 5], current_bbox[5]) + 1 + overlap_size_h = overlap_max_h - overlap_min_h + mask_h = (overlap_size_h >= 1) + indices_h = np.nonzero(mask_h)[0] + bboxes_h = bboxes_x[indices_h] + + indices = indices_i[indices_x][indices_h] + merge_candidates = horizons[indices] + _ = bboxes_h # TODO: can be used to pass already computed overlap sizes + + # Merge all possible candidates + for idx, merge_candidate in zip(indices, merge_candidates): + merge_stats['merge_candidates'] += 1 + + # Conditions to not use the candidate: + # - already merged + # - already verified the impossibility of merge + # - it is the horizon itself + if idx in indices_merged: + merge_stats['already_merged_hit'] += 1 + continue + if (id(merge_candidate) in current_horizon.id_separated or + id(current_horizon) in merge_candidate.id_separated): + merge_stats['id_separated_hit'] += 1 + continue + if merge_candidate is current_horizon: + # Can move code to the previous clause at the cost of code readability + continue + + # Compute the mergeability + merge_stats['verify'] += 1 + merge_status = ExtractionMixin.verify_merge(current_horizon, merge_candidate, + mean_threshold=mean_threshold, + max_threshold=max_threshold, + min_size_threshold=min_size_threshold, + max_size_threshold=max_size_threshold, + adjacency=(adjacency_i, adjacency_x)) + merge_stats[merge_status] += 1 + + # Merge, if needed + if merge_status == 4: + # Overlapping horizons: definetely merge + merged = ExtractionMixin.overlap_merge(current_horizon, merge_candidate, inplace=True) + current_horizon.id_separated = current_horizon.id_separated.union(merge_candidate.id_separated) + + elif merge_status == 3 and (adjacency_i > 0 or adjacency_x > 0): + # Adjacent horizons: maybe we can merge it + merged = ExtractionMixin.adjacent_merge(current_horizon, merge_candidate, inplace=True, + mean_threshold=mean_threshold, + adjacency=(adjacency_i, adjacency_x)) + merge_stats['merged_adjacent'] += (1 if merged else 0) + + elif merge_status == 0: + # Depth separated: can't merge and will not be able after other merges + current_horizon.id_separated.add(id(merge_candidate)) + merge_candidate.id_separated.add(id(current_horizon)) + merged = False + + else: + # Spatially separated or too small of an overlap + # Can't merge for now, but maybe will be able later + merged = False + + # Keep values for clean-up + if merged: + current_horizon.merge_count += 1 + indices_merged.add(idx) + num_merged += 1 + + # Update bbox stats + bboxes[i] = (current_horizon.i_min, current_horizon.i_max, + current_horizon.x_min, current_horizon.x_max, + current_horizon.d_min, current_horizon.d_max) + + # Once in a while, remove merged horizons from `bboxes` and `horizons` arrays + if len(indices_merged) > int(delete_threshold * len(horizons)): + indices_merged = list(indices_merged) + horizons = np.delete(horizons, indices_merged, axis=0) + bboxes = np.delete(bboxes, indices_merged, axis=0) + i -= sum(1 for idx in indices_merged if idx < i) + + indices_merged = set() + merge_stats['num_deletes'] += 1 + + # Move to the next horizon + i += 1 + + + # Clean-up at the end of global iteration + if indices_merged: + indices_merged = list(indices_merged) + horizons = np.delete(horizons, indices_merged, axis=0) + bboxes = np.delete(bboxes, indices_merged, axis=0) + i -= sum(1 for idx in indices_merged if idx < i) + + merge_stats['num_deletes'] += 1 + + # Reject horizons that has not participated in any merges: + # they will not be merged in the next iterations as well + if (adjacency_i <= 0 and adjacency_x <= 0): + rejected_horizons_ = [horizon for horizon in horizons + if horizon.merge_count == 0] + rejected_horizons.extend(rejected_horizons_) + + horizons = np.array([horizon for horizon in horizons + if horizon.merge_count > 0]) + else: + rejected_horizons_ = [] + merge_stats['num_rejected_horizons'].append(len(rejected_horizons_)) + + + # Global iteration info + merge_stats['global_iterations'] += 1 + merge_stats['global_merges'].append(num_merged) + merge_stats['global_iteration_timings'].append(round(perf_counter() - start_timing, 2)) + + # Exit condition: merged less horizons then threshold + if num_merged < num_merged_threshold: + break + + # Get back the rejects + horizons = list(horizons) + horizons.extend(rejected_horizons) + + for horizon in horizons: + delattr(horizon, 'merge_count') + delattr(horizon, 'id_separated') + + horizons = [horizon for horizon in horizons if not horizon.already_merged] + return sorted(horizons, key=len), MetaDict(merge_stats) + + + @staticmethod + def merge_list_concurrent(horizons, + max_concurrent_iters=2, max_workers=16, min_workers=4, min_length=1000, multiplier=0.8, + mean_threshold=1., max_threshold=2.2, adjacency=3, minsize=50, max_iters=1, + num_merged_threshold=1, delete_threshold=0.01): + """ Apply merge procedure in multiple threads. + Works by splitting the `horizons` list into multiple chunks, merging everything possible in each chunk, + and then applying one final merge to do cross-chunk merges. + + Parameters + ---------- + max_concurrent_iters : int + Number of times to split `horizons` into chunks and processing concurrently. + max_workers : int + Maximum number of chunks / workers to use. + min_workers : int + Minimum number of chunks / workers. If the optimal amount is lower, then we don't use concurrency at all. + min_length : int + If the chunk size is lower, we use fewer workers. + multiplier : float + Decrease in number of workers, if needed. + other parameters : dict + Passed directly to `merge_list` method. + """ + for _ in range(max_concurrent_iters): + threading_flag, num_workers = ExtractionMixin._compute_threading_parameters(length=len(horizons), + min_length=min_length, + max_workers=max_workers, + min_workers=min_workers, + multiplier=multiplier) + # No more threading is needed + if threading_flag is False: + break + + horizons.sort(key=attrgetter('i_min')) + + # Split list into chunks for each worker + chunk_size = len(horizons) // num_workers + chunks = [horizons[idx:idx+chunk_size] for idx in range(0, len(horizons), chunk_size)] + if len(chunks[-1]) < min_length: + chunks[-2].extend(chunks.pop(-1)) + + # Run merging procedure in a separate workers + with ThreadPoolExecutor(max_workers=len(chunks)) as executor: + function = lambda horizons_list: ExtractionMixin.merge_list(horizons_list, + adjacency=adjacency, + mean_threshold=mean_threshold, + max_threshold=max_threshold, + max_iters=max_iters, + num_merged_threshold=num_merged_threshold, + delete_threshold=delete_threshold) + processed = list(executor.map(function, chunks)) + + horizons = [horizon for chunk, _ in processed for horizon in chunk] + + # One final merge to combine horizons from different chunks + horizons, counter = ExtractionMixin.merge_list(horizons, adjacency=adjacency, + mean_threshold=mean_threshold, max_threshold=max_threshold, + num_merged_threshold=num_merged_threshold, + delete_threshold=delete_threshold) + return horizons, counter + + @staticmethod + def _compute_threading_parameters(length, max_workers, min_workers, min_length, multiplier=0.8): + """ Compute whether the concurrency is needed. + Works by computing chunk sizes: + - if chunks would be smaller than the `min_length`, discount the number of workers by `multiplier` + - if the number of workers is smaller than `min_workers`, no concurrency is needed + - otherwise, use current number of workers + """ + chunk_size = length // max_workers + + # Each chunk is big enough for current `num_workers=max_workers`, so use them all + if chunk_size >= min_length: + return True, max_workers + + # Gradually descrease the amount of available workers + num_workers = int(multiplier * max_workers) + if num_workers >= min_workers: + return ExtractionMixin._compute_threading_parameters(length, num_workers, + min_workers=min_workers, + min_length=min_length) + + # Chunks are too small even for the `num_workers=min_workers` + return False, None + + +@njit +def intersect_matrix(first, second, max_threshold): + """ Given two matrices of equal shapes, compute mean and max differences. + If the max difference is bigger than `max_threshold`, we break out of the loop early. + """ + # TODO: return flag of break/nobreak? + #pylint: disable=consider-using-enumerate + first = first.ravel() + second = second.ravel() + + s, c = 0, 0 # running sum and count + + for i in range(len(first)): + first_h = first[i] + second_h = second[i] + + # Check that both values are not `Horizon.FILL_VALUE`` + if first_h >= 0: + if second_h >= 0: + abs_diff = abs(first_h - second_h) + + if abs_diff > max_threshold: # early stopping on overflow + s = 999 + c = 1 + break + + s += abs_diff + c += 1 + + if c != 0: + mean = s / c + else: + mean = 999 + return mean, c diff --git a/seismiqb/labels/horizon/horizon_extractor.py b/seismiqb/labels/horizon/horizon_extractor.py new file mode 100644 index 0000000..1326664 --- /dev/null +++ b/seismiqb/labels/horizon/horizon_extractor.py @@ -0,0 +1,414 @@ +""" Extractor of horizon surfaces from a probability array. """ +from collections import Counter, defaultdict +from concurrent.futures import ThreadPoolExecutor + +import numpy as np + +from cc3d import connected_components +from scipy.ndimage import find_objects + + +from batchflow import Notifier +from .base import Horizon + + + +class HorizonExtractor: + """ Extractor of horizon surfaces from a probability array. + + The main idea of implementation is: + - extract connected components on each n-th slice, store them (with their indices) in a container + Do that for slices along the first and the second axis: usually, these are INLINE_3D and CROSSLINE_3D dims. + + - sample one line as a starter. Usually, we do that by sorting all extracted connected components by length. + Make a `HorizonPrototype` instance out of it. + - for that line, find intersections with orthogonal slices. + On these slices, find exact lines that are intersecting with the current one. + - Add lines to the prototype instance, until no more lines can be merged in either direction. + At the end, prototype is basically a collection of lines with known intersections. + + - repeat the last three steps to get more prototypes. + Optionally, convert prototypes to Horizon instances by iteratively merging lines with additional thresholds. + """ + def __init__(self, array, origin=None, step=10): + self.array = array + self.origin = [0] * 3 if origin is None else origin + self.step = step + + # Create a mapping: + # orientation ⟶ { + # slide_index ⟶ { + # 'origin' ⟶ 3D origin of the slide, its upper rightmost point, + # 'slide' ⟶ view on values in the original probability array, + # 'labeled_slide' ⟶ labeled connected components on a slide: each region its separate index, + # 'bboxes' ⟶ for each labeled component, its bounding box, + # 'lengths' ⟶ for each labeled component, its length, + # } + # } + self.container = {0: {}, 1: {}} + self.init_container(array=array) + + def init_container(self, array): + """ Create a mapping with connected components for a given probability array. """ + for orientation in [0, 1]: + for slide_idx in Notifier('t')(range(0, array.shape[orientation], self.step)): + + # Compute slide position + locations = [slice(None)] * 3 + locations[orientation] = slice(slide_idx, slide_idx + 1) + + origin = [0] * 3 + origin[orientation] = slide_idx + + # Label connected components + slide = array[tuple(locations)] + + # length = 100 + # locations_zfill = [slice(None)] * 3 + # locations_zfill[1-orientation] = slice((slide_idx + orientation * length // 2) % length, + # None, length) + # slide = slide.copy() + # slide[locations_zfill] = 0 + labeled_slide = connected_components(slide >= 0.5, connectivity=26) + + # Extract bboxes and compute length of each point cloud + bboxes = find_objects(labeled_slide) + bboxes = dict(enumerate(bboxes, start=1)) + lengths = {item_idx : (item_bbox[1-orientation].stop - item_bbox[1-orientation].start) + for item_idx, item_bbox in bboxes.items()} + + self.container[orientation][slide_idx] = { + 'origin': origin, + 'slide': slide, + 'labeled_slide': labeled_slide, + 'bboxes': bboxes, # `item_idx` -> bbox + 'lengths': lengths, # `item_idx` -> length + 'already_used': defaultdict(bool), # `item_idx` -> already merged or not + } + + def get_points(self, orientation, slide_idx, item_idx): + """ Given orientation, slide index and item index, extract the points of a line. """ + slide_dict = self.container[orientation][slide_idx] + item_origin = slide_dict['origin'] + item_bbox = slide_dict['bboxes'][item_idx] + + item_indices = (slide_dict['labeled_slide'][item_bbox] == item_idx).nonzero() + item_points = np.vstack([item_indices[j] + (item_bbox[j].start + item_origin[j]) + for j in range(3)]).T + return item_points + + def point_to_item_idx(self, orientation, point): + """ Get `item_idx` given point in 3D array and its orientation. """ + point = np.array(point) + slide_idx = point[orientation] + point[orientation] = 0 + + item_idx = self.container[orientation][slide_idx]['labeled_slide'][point[0], point[1], point[2]] + return item_idx + + def reset_already_used(self): + """ Reset `already_used` flag for all lines. """ + for orientation_dict in self.container.values(): + for slide_dict in orientation_dict.values(): + slide_dict['already_used'] = defaultdict(bool) + + + # Line sequences: iterator over lines for prototype creation + def make_line_sequence(self, line_length_threshold=50): + """ Iterator over lines from entire array, sorted by length in descending order. + Each element is contains full information about line: ((orientation, slide_index, item_index), line_length). + """ + iterator = {} + for orientation, orientation_dict in self.container.items(): + for slide_idx, slide_dict in orientation_dict.items(): + for item_idx, item_length in slide_dict['lengths'].items(): + if item_length > line_length_threshold and slide_dict['already_used'][item_idx] is False: + iterator[(orientation, slide_idx, item_idx)] = item_length + + return sorted(iterator.items(), key=lambda item:item[1], reverse=True) + + def make_slide_line_sequence(self, orientation=0, slide_idx=None, line_length_threshold=50): + """ Iterator over lines on a given slide, sorted by length in descending order. + Each element is contains full information about line: ((orientation, slide_index, item_index), line_length). + """ + slide_idx = slide_idx or (self.array.shape[orientation] // 2) + slide_idx = slide_idx // self.step * self.step + + iterator = {} + for item_idx, item_length in self.container[orientation][slide_idx]['lengths'].items(): + if item_length > line_length_threshold: + iterator[(orientation, slide_idx, item_idx)] = item_length + return sorted(iterator.items(), key=lambda item:item[1], reverse=True) + + + # Prototype extraction + def make_prototypes(self, sequence=None, n=None, line_length_threshold=50, max_iters=100, pbar='t'): + """ Make prototypes, starting from lines on a given orientation/slide. + Lines are sorted in descending order by their length, so we start from bigger lines. + """ + sequence = sequence or self.make_line_sequence(line_length_threshold=line_length_threshold) + n = n or len(sequence) + + prototypes = [] + with Notifier(pbar, total=n) as progress_bar: + for (orientation, slide_idx, item_idx), _ in sequence: + # Check if the line is already used in other prototype + if self.container[orientation][slide_idx]['already_used'][item_idx] is True: + progress_bar.update() + continue + + # Make prototype instance, add all intersecting lines to it + prototype = self.init_prototype(orientation=orientation, slide_idx=slide_idx, item_idx=item_idx) + prototype = self.extend_prototype(prototype=prototype, orientation=1-orientation, max_iters=max_iters) + prototypes.append(prototype) + + progress_bar.update() + if len(prototypes) == n: + progress_bar.close() + break + + prototypes.sort(key=len, reverse=True) + return prototypes + + + def init_prototype(self, orientation, slide_idx, item_idx): + """ Given orientation, slide and item index, extract line points and create a prototype instance out of it. """ + prototype = HorizonPrototype(origin=self.origin) + points = self.get_points(orientation=orientation, slide_idx=slide_idx, item_idx=item_idx) + prototype.add_points(points=points, orientation=orientation, slide_idx=slide_idx) + return prototype + + def extend_prototype(self, prototype, orientation, max_iters=100): + """ Extend given prototype, alternating between directions. """ + for outer_iter in range(max_iters): + prev_len = prototype.n_points + + for slide_idx in range(0, self.array.shape[orientation], self.step): + # Check intersections of current slide and prototype + intersections = prototype.get_intersections(orientation=orientation, + slide_idx=slide_idx) + if len(intersections) == 0: + continue + + # `intersections`` are (N, 3) array of coordinates: use them as indexer + slide_dict = self.container[orientation][slide_idx] + labeled_slide = slide_dict['labeled_slide'] + + intersections[:, orientation] = 0 + item_indices = labeled_slide[intersections[:, 0], + intersections[:, 1], + intersections[:, 2]] + item_indices = Counter(item_indices) + + # For each item prototype intersected with, add its points + for item_idx, item_occurencies in item_indices.items(): + if item_idx == 0: + continue + if slide_dict['already_used'][item_idx] is True: + continue + if outer_iter > 0 and item_occurencies < 2: + continue + + # Get line points, merge them into prototype, mark as merged + points = self.get_points(orientation=orientation, slide_idx=slide_idx, item_idx=item_idx) + prototype.add_points(points=points, orientation=orientation, slide_idx=slide_idx) + slide_dict['already_used'][item_idx] = True + + # If no points added, break. Otherwise, change the orientation and repeat + if prototype.n_points == prev_len: + break + orientation = 1 - orientation + return prototype + + + @staticmethod + def to_horizons(prototypes, field, reduction=7, d_ptp_threshold=20, size_threshold=40, max_iters=100, + n=3, pbar=False, max_workers=4): + """ Convert prototype instances to horizon instances. + Refer to :meth:`HorizonPrototype.to_horizons` to more details on parameters. + """ + horizons = [] + with Notifier(pbar, total=len(prototypes)) as progress_bar: + with ThreadPoolExecutor(max_workers=max_workers) as executor: + def callback(future): + horizons.extend(future.result()) + progress_bar.update() + + for prototype in prototypes: + future = executor.submit(prototype.to_horizons, field=field, + reduction=reduction, d_ptp_threshold=d_ptp_threshold, + size_threshold=size_threshold, max_iters=max_iters, n=n, pbar=False) + future.add_done_callback(callback) + horizons.sort(key=len, reverse=True) + return horizons + + +class HorizonPrototype: + """ Collection of lines along axes. """ + def __init__(self, origin): + # Mapping: + # orientation ⟶ { + # slide_index ⟶ { + # start coordinate ⟶ line points (N, 3) ndarray + # } + # } + self.origin = origin + self.container = {0: defaultdict(dict), 1: defaultdict(dict)} + + def add_points(self, points, orientation, slide_idx): + """ Add `points` to self, given their orientation and slide index. """ + key = points[0][1-orientation] + + slide_dict = self.container[orientation][slide_idx] + if key not in slide_dict: + slide_dict[key] = points + + def get_intersections(self, orientation, slide_idx): + """ Compute coordinates of intersections of lines in `self` with a given slide. """ + intersections = [] + + # For each line (represented by its start and points), search `slide_idx` + for points_dict in self.container[1 - orientation].values(): + for points in points_dict.values(): + if points[0, orientation] > slide_idx or points[-1, orientation] < slide_idx: + continue + + insertion_index = np.searchsorted(points[:, orientation], slide_idx) + # Check that `insertion_index` actually refers to the same value, as `slide_idx`: + # may not be true if there is no `slide_idx` value in `points` + if insertion_index < len(points) and points[:, orientation][insertion_index] == slide_idx: + intersections.append(points[insertion_index]) + + # TODO: in the perfect case, `break` works. + # If multiple lines are intersecting with a slide, it does not. + break + return np.array(intersections) + + # Introspection + @property + def n_points(self): + """ Total number of points in a prototype. """ + counter = 0 + for orientation_dict in self.container.values(): + for points_dict in orientation_dict.values(): + for points_ in points_dict.values(): + counter += len(points_) + return counter + + @property + def flat_points(self): + """ Points in a prototype, concatenated into one (N, 3) array. """ + buffer = np.empty((self.n_points, 3), dtype=np.int32) + counter = 0 + for orientation_dict in self.container.values(): + for points_dict in orientation_dict.values(): + for points_ in points_dict.values(): + buffer[counter:counter + len(points_)] = points_ + counter += len(points_) + points = np.array(buffer) + return points + + @property + def unique_flat_points(self): + """ Unique points in a prototype, concatenated into one (N, 3) array. """ + return np.unique(self.flat_points, axis=0) + + @property + def n_unique_points(self): + """ Number of unique points in a prototype. """ + return len(self.unique_flat_points) + + def __len__(self): + return self.n_points + + # Convert to Horizon instance + def naive_to_horizon(self, field, name='naive_prototype'): + """ Naive conversion of prototype to horizon instance: no correction on overlapping lines. + Should not be used other for debugging/introspection purposes. + """ + points = self.unique_flat_points + points += self.origin + return Horizon(self.unique_flat_points, field=field, name=name) + + def to_horizons(self, field, reduction=3, d_ptp_threshold=20, size_threshold=40, max_iters=100, n=3, pbar=False): + """ Convert Prototype instance to one or more Horizon instances. + + As Prototype is a collection of lines with intersections, we want to avoid depth-wise overlaps. + To do that, we sequentially merge lines with tight thresholds: + - at first, we merge lines with less depth variation (low `d_ptp`). + The threshold is gradually increased from 1 to `d_ptp_threshold`, so that we allow more and more variation. + - then, we merge lines with high overlap to already merged (big `overlap_size`) + The threshold is gradually decreased from `size_threshold` to 3, so that we allow less overlaps. + - repeat the first two steps multiple times, until the horizon size is no longer increasing. + + As some of the lines may overlap depth-wise even where it is not desirable, we use `reduction` to remove + a few points of either side of the line and produce better extracted horizons with negligible area reduction. + + Parameters + ---------- + reduction : int + Number of points on the left/right side of a line to remove. + d_ptp_threshold : int + Maximum allowed `d_ptp` of a line to merge during the first step. + size_threshold : int + Maxumum minimum overlap size threshold of a line to merge during the second step. + max_iters : int + Number of alternating iterations to perform. + n : int + Maximum number of horizons to extract. + pbar : bool, str + If bool, then whether to display progress bar. + If str, then type of progress bar to display: `'t'` for textual, `'n'` for widget. + """ + # Strip the first and the last points of each line in a prototype, convert to Horizon instances + line_horizons = [] + for orientation, orientation_dict in self.container.items(): + for slide_idx, points_dict in orientation_dict.items(): + for start, points in points_dict.items(): + if len(points) <= 2*reduction + 1: + continue + + points = points[reduction:-reduction] + points += self.origin + + line_horizon = Horizon(points, field=field, + name=f'line_{orientation}_{slide_idx}_{start}') + line_horizons.append(line_horizon) + line_horizons.sort(key=len, reverse=True) + + horizons = [] + for _ in range(n): + if len(line_horizons) == 0: + break + horizon = line_horizons.pop(0) + horizons.append(horizon) + + for _ in Notifier(pbar)(range(max_iters)): + prev_length = len(horizon) + + # Merge with small ptp + for d_ptp_threshold_ in range(1, d_ptp_threshold, +3): + candidates = [line_horizon for line_horizon in line_horizons + if line_horizon.d_ptp <= d_ptp_threshold_] + horizon, _, _ = horizon.merge_into(candidates, mean_threshold=0.01, max_threshold=0, adjacency=0) + + # Merge with bigger overlaps + for size_threshold_ in range(size_threshold, 3, -1): + horizon, _, _ = horizon.merge_into(line_horizons, mean_threshold=0.01, max_threshold=0, adjacency=0, + min_size_threshold=size_threshold_) + + # Remove already merged line horizons. Break, if no progress in horizon size + line_horizons = [line_horizon for line_horizon in line_horizons + if not line_horizon.already_merged] + if len(horizon) == prev_length or len(line_horizons) < 3: + break + horizons.sort(key=len, reverse=True) + return horizons + + def to_horizon(self, field, reduction=7, d_ptp_threshold=20, size_threshold=40, max_iters=100, n=3, pbar=False): + """ Alias for extracting one horizon with the biggest size. + Refer to :meth:`.to_horizons` for more details on parameters. + """ + return self.to_horizons(field=field, reduction=reduction, + d_ptp_threshold=d_ptp_threshold, size_threshold=size_threshold, + max_iters=max_iters, n=n, pbar=pbar)[0] diff --git a/seismiqb/labels/horizon/processing.py b/seismiqb/labels/horizon/processing.py new file mode 100644 index 0000000..a8d7740 --- /dev/null +++ b/seismiqb/labels/horizon/processing.py @@ -0,0 +1,646 @@ +""" Mixin for horizon processing. """ +from math import isnan +from functools import partialmethod +import numpy as np +from numba import njit, prange + +from cv2 import inpaint as cv2_inpaint +from skimage.measure import label +from scipy.ndimage.morphology import binary_fill_holes, binary_dilation, binary_erosion + +from ...functional import make_gaussian_kernel +from ...utils import make_bezier_figure + +class ProcessingMixin: + """ Methods for horizon processing. + + Contains methods for: + - Removing or adding points to the horizon surface. + - Smoothing out the horizon surface. + - Cutting shapes (holes or carcasses) from the horizon surface. + + Note, almost all of these methods can change horizon surface inplace or create a new instance. + In either case they return a filtered horizon instance. + """ + # Filtering methods + def filter(self, filtering_matrix=None, margin=0, inplace=False, add_prefix=True, **kwargs): + """ Remove points that correspond to 1's in `filtering_matrix` from the horizon surface. + + Note, this method may change horizon inplace or create a new instance. By default creates a new instance. + In either case it returns a processed horizon instance. + + Parameters + ---------- + filtering_matrix : None, str or np.ndarray + Mask of points to cut out from the horizon. + If None, then remove points corresponding to zero traces. + If str, then remove points corresponding to the `filtering_matrix` attribute. + If np.ndarray, then used as filtering mask. + margin : int + Amount of traces to cut out near to boundaries considering `filtering_matrix` appliance. + inplace : bool + Whether to apply operation inplace or return a new Horizon object. + add_prefix : bool + If True and not inplace, adds prefix to the horizon name. + kwargs : dict + Arguments to be passed in the loading attribute method in case when filtering_matrix is a str. + + Returns + ------- + :class:`~.Horizon` + Processed horizon instance. A new instance if `inplace` is False, `self` otherwise. + """ + if filtering_matrix is None: + filtering_matrix = self.field.dead_traces_matrix + elif isinstance(filtering_matrix, str): + filtering_matrix = self.load_attribute(filtering_matrix, **kwargs) + filtering_matrix[np.abs(filtering_matrix) > 1] = 1 + + if not issubclass(filtering_matrix.dtype.type, bool): + filtering_matrix = filtering_matrix > 0 + + if margin > 0: + filtering_matrix = binary_dilation(filtering_matrix, iterations=margin) + + filtering_matrix[:margin, :] = 1 + filtering_matrix[:, :margin] = 1 + filtering_matrix[-margin:, :] = 1 + filtering_matrix[:, -margin:] = 1 + + mask = filtering_matrix[self.points[:, 0], self.points[:, 1]] + points = self.points[mask == 0] + + if inplace: + self.points = points + self.reset_storage('matrix') + return self + + name = 'filtered_' + self.name if add_prefix else self.name + return type(self)(storage=points, field=self.field, name=name) + + despike = partialmethod(filter, filtering_matrix='spikes') + + def filter_disconnected_regions(self, erosion_rate=0, inplace=False): + """ Remove regions, not connected to the largest component of a horizon. + + Note, this method may change horizon inplace or create a new instance. By default creates a new instance. + In either case it returns a processed horizon instance. + """ + if erosion_rate > 0: + structure = np.ones((3, 3)) + matrix = binary_erosion(self.mask, structure, iterations=erosion_rate) + else: + matrix = self.mask + + labeled = label(matrix) + values, counts = np.unique(labeled, return_counts=True) + counts = counts[values != 0] + values = values[values != 0] + + object_id = values[np.argmax(counts)] + + filtering_matrix = np.zeros_like(self.mask) + filtering_matrix[labeled == object_id] = 1 + + if erosion_rate > 0: + filtering_matrix = binary_dilation(filtering_matrix, structure, iterations=erosion_rate) + + filtering_matrix = filtering_matrix == 0 + + return self.filter(filtering_matrix, inplace=inplace) + + + # Horizon surface transformations + def smooth_out(self, mode='convolve', iters=1, + kernel_size=(3, 3), sigma_spatial=0.8, kernel=None, sigma_range=2.0, + max_depth_difference=5, inplace=False, add_prefix=True, dtype=None): + """ Smooth out the horizon surface. + + Smoothening is applied without absent points changing. + + This method supports two types of smoothening: + - if `mode='convolve'`, then the method uses a convolution with a given or a gaussian kernel. + - if `mode='bilateral'`, then the method applies a bilateral filtering with a given or a gaussian kernel. + Bilateral filtering is an edge-preserving smoothening, which ignores areas with faults. + Be careful with `sigma_range` value: + - The higher the `sigma_range` value, the more 'bilateral' result looks like a 'convolve' result. + - If the `sigma_range` too low, then no smoothening applied. + + Note, this method may change horizon inplace or create a new instance. By default creates a new instance. + In either case it returns a processed horizon instance. + + Note, that the method makes dtype conversion only if the parameter `inplace` is False. + + Parameters + ---------- + mode : str + Smoothening type mode. Can be 'convolve' or 'bilateral'. + If 'convolve', then the method makes a convolution with a given kernel. + If 'bilateral', then the method applies a bilateral filtering with a given kernel. + iters : int + Number of times to apply smoothing. + kernel_size : int or sequence of ints + Size of a created gaussian filter if `kernel` is None. + sigma_spatial : number + Standard deviation (spread or “width”) for gaussian kernel. + The lower, the more weight is put into the point itself. + kernel : ndarray or None + If passed, then ready-to-use kernel. Otherwise, gaussian kernel will be created. + sigma_range : number + Standard deviation for additional weight which smooth differences in depth values. + The lower, the more weight is put into the depths differences between point in a window. + Note, if it is too low, then no smoothening is applied. + max_depth_difference : number + If the distance between anchor point and the point inside filter is bigger than the threshold, + then the point is ignored in smoothening. + Can be used for separate smoothening on sides of discontinuity. + inplace : bool + Whether to apply operation inplace or return a new Horizon object. + add_prefix : bool + If True and not inplace, adds prefix to the horizon name. + dtype : type + Output horizon dtype. Supported only if `inplace` is False. + + Returns + ------- + :class:`~.Horizon` + Processed horizon instance. A new instance if `inplace` is False, `self` otherwise. + """ + if 'conv' in mode: + smoothening_function, kwargs = _convolve, {} + else: + smoothening_function, kwargs = _bilateral_filter, {'sigma_range': sigma_range} + + if isinstance(kernel_size, int): + kernel_size = (kernel_size, kernel_size) + + kernel = kernel if kernel is not None else make_gaussian_kernel(kernel_size=kernel_size, sigma=sigma_spatial) + dtype = dtype if dtype is not None else self.dtype + + result = self.matrix.astype(np.float32) + result[result == self.FILL_VALUE] = np.nan + + # Apply smoothening multiple times. Note that there is no dtype conversion in between + # Also the method returns a new object + for _ in range(iters): + result = smoothening_function(src=result, kernel=kernel, + max_depth_difference=max_depth_difference, + **kwargs) + + result[(self.matrix == self.FILL_VALUE) | np.isnan(result)] = self.FILL_VALUE + result[self.field.dead_traces_matrix[self.i_min:self.i_max + 1, + self.x_min:self.x_max + 1]] = self.FILL_VALUE + + if dtype == np.int32 or (self.dtype == np.int32 and inplace is True): + result = np.rint(result).astype(np.int32) + + if inplace: + self.matrix = result + self.reset_storage('points') + return self + + name = 'smoothed_' + self.name if add_prefix else self.name + return type(self)(storage=result, i_min=self.i_min, x_min=self.x_min, field=self.field, name=name, dtype=dtype) + + def interpolate(self, iters=1, kernel_size=(3, 3), sigma=0.8, kernel=None, + min_present_neighbors=0, max_depth_ptp=None, inplace=False, add_prefix=True): + """ Interpolate horizon surface on the regions with missing traces. + + Under the hood, we fill missing traces with weighted neighbor values. + + Note, this method may change horizon inplace or create a new instance. By default creates a new instance. + In either case it returns a processed horizon instance. + + Parameters + ---------- + iters : int + Number of interpolation iterations to perform. + kernel_size : int or sequence of ints + If the kernel is not provided, shape of the square gaussian kernel. + sigma : number + Standard deviation (spread or “width”) for gaussian kernel. + The lower, the more weight is put into the point itself. + kernel : ndarray or None + Interpolation weights kernel. + min_present_neighbors : int + Minimal amount of non-missing neighboring points in a window to interpolate a central point. + max_depth_ptp : number + A maximum distance between values in a squared window for which we apply interpolation. + inplace : bool + Whether to apply operation inplace or return a new Horizon object. + add_prefix : bool + If True and not inplace, adds prefix to the horizon name. + + Returns + ------- + :class:`~.Horizon` + Processed horizon instance. A new instance if `inplace` is False, `self` otherwise. + """ + if isinstance(kernel_size, int): + kernel_size = (kernel_size, kernel_size) + + kernel = kernel if kernel is not None else make_gaussian_kernel(kernel_size=kernel_size, sigma=sigma) + + result = self.matrix.astype(np.float32) + result[self.matrix == self.FILL_VALUE] = np.nan + + # Apply `_interpolate` multiple times. Note that there is no dtype conversion in between + # Also the method returns a new object + for _ in range(iters): + result = _interpolate(src=result, kernel=kernel, min_present_neighbors=min_present_neighbors, + max_depth_ptp=max_depth_ptp) + + result[np.isnan(result)] = self.FILL_VALUE + result[self.field.dead_traces_matrix[self.i_min:self.i_max + 1, + self.x_min:self.x_max + 1]] = self.FILL_VALUE + + if self.dtype == np.int32: + result = np.rint(result).astype(np.int32) + + if inplace: + self.matrix = result + self.reset_storage('points') + return self + + name = 'interpolated_' + self.name if add_prefix else self.name + return type(self)(storage=result, i_min=self.i_min, x_min=self.x_min, field=self.field, name=name) + + def inpaint(self, inpaint_radius=1, neighbors_radius=1, method=0, inplace=False, add_prefix=True): + """ Inpaint horizon surface on the regions with missing traces. + + Under the hood, the method uses the inpainting method from OpenCV. + + Note, this method may change horizon inplace or create a new instance. By default creates a new instance. + In either case it returns a processed horizon instance. + + Parameters + ---------- + inpaint_radius : int + Radius of traces to inpaint near horizon boundaries. + When the surface has huge missing regions, we don't want to fill them completely, because + inpainting too far from existing horizon traces can be made with huge errors. + neighbors_radius : int + Parameter passed to the :meth:`cv2.inpaint` as `inpaintRadius`. + Radius of a circular neighborhood of each point inpainted that is considered by the algorithm. + method : int + Parameter passed to the :meth:`cv2.inpaint` as `flags`. Can be 0 or 1. + If 0, then Navier-Stokes algorithm is used. + If 1, then Telea algorithm is used. + inplace : bool + Whether to apply operation inplace or return a new Horizon object. + add_prefix : bool + If True and not inplace, adds prefix to the horizon name. + + Returns + ------- + :class:`~.Horizon` + Processed horizon instance. A new instance if `inplace` is False, `self` otherwise. + """ + image = self.matrix.astype(np.uint16) # dtype conversion for compatibility with the OpenCV method + dead_traces_matrix = self.field.dead_traces_matrix[self.i_min:self.i_max + 1, + self.x_min:self.x_max + 1] + + # We use all empty traces as inpainting mask because it is important for correct boundary conditions + # in differential equations, that are used in the inpainting method + holes_mask = (self.matrix == self.FILL_VALUE).astype(np.uint8) + holes_mask[dead_traces_matrix == 1] = 1 + + result = cv2_inpaint(src=image, inpaintMask=holes_mask, inpaintRadius=neighbors_radius, flags=method) + result = result.astype(self.dtype) + + # Filtering mask to remove traces, that are too far from existing traces + too_far_traces_mask = binary_erosion(holes_mask, iterations=inpaint_radius).astype(int) + + # Filter traces with anomalies (can be caused by boundary conditions in equations on horizon borders) + anomalies_mask = (result > self.d_max + 10) | (result < self.d_min - 10) + + result[(too_far_traces_mask == 1) | (anomalies_mask == 1) | (dead_traces_matrix == 1)] = self.FILL_VALUE + + if inplace: + self.matrix = result + self.reset_storage('points') + return self + + name = 'inpainted_' + self.name if add_prefix else self.name + return type(self)(storage=result, i_min=self.i_min, x_min=self.x_min, field=self.field, name=name) + + # Horizon distortions + def thin_out(self, factor=1, threshold=256, inplace=False, add_prefix=True): + """ Thin out the horizon by keeping only each `factor`-th line. + + Note, this method may change horizon inplace or create a new instance. By default creates a new instance. + In either case it returns a processed horizon instance. + + Parameters + ---------- + factor : integer or sequence of two integers + Frequency of lines to keep along ilines and xlines direction. + threshold : integer + Minimal amount of points in a line to keep. + inplace : bool + Whether to apply operation inplace or return a new Horizon object. + add_prefix : bool + If True and not inplace, adds prefix to the horizon name. + + Returns + ------- + :class:`~.Horizon` + Processed horizon instance. A new instance if `inplace` is False, `self` otherwise. + """ + if isinstance(factor, int): + factor = (factor, factor) + + uniques, counts = np.unique(self.points[:, 0], return_counts=True) + mask_i = np.isin(self.points[:, 0], uniques[counts > threshold][::factor[0]]) + + uniques, counts = np.unique(self.points[:, 1], return_counts=True) + mask_x = np.isin(self.points[:, 1], uniques[counts > threshold][::factor[1]]) + + points = self.points[mask_i + mask_x] + + if inplace: + self.points = points + self.reset_storage('matrix') + return self + + name = 'thinned_' + self.name if add_prefix else self.name + return type(self)(storage=points, field=self.field, name=name) + + def make_carcass(self, frequencies=100, margin=50, interpolate=False, add_prefix=True, inplace=False, **kwargs): + """ Cut carcass out of a horizon. Returns a new instance. + + Parameters + ---------- + frequencies : int or sequence of two ints + Frequencies of carcass lines along inline/crossline axis. + margin : int + Margin from geometry edges to exclude from carcass. + interpolate : bool + Whether to interpolate the result. + kwargs : dict + Other parameters for grid creation, see `:meth:~.Geometry.make_quality_grid`. + """ + #pylint: disable=import-outside-toplevel + carcass = self if inplace else self.copy(add_prefix=add_prefix) + carcass.name = carcass.name.replace('copy', 'carcass') + + grid_matrix = self.field.geometry.get_grid(frequency=frequencies, margin=margin) + carcass.filter(filtering_matrix=1-grid_matrix, inplace=True) + if interpolate: + carcass.interpolate(inplace=True) + return carcass + + def generate_holes_matrix(self, n=10, scale=1.0, max_scale=.25, + max_angles_amount=4, max_sharpness=5.0, locations=None, + points_proportion=1e-5, points_shape=1, + noise_level=0, seed=None): + """ Create matrix of random holes for horizon. + + Holes can be bezier-like figures or points-like. + We can control bezier-like and points-like holes amount by `n` and `points_proportion` parameters respectively. + We also do some noise amplifying with `noise_level` parameter. + + Parameters + ---------- + n : int + Amount of bezier-like holes on horizon. + points_proportion : float + Proportion of point-like holes on the horizon. A number between 0 and 1. + points_shape : int or sequence of int + Shape of point-like holes. + noise_level : int + Radius of noise scattering near the borders of holes. + scale : float or sequence of float + If float, each bezier-like hole will have a random scale from exponential distribution with parameter scale. + If sequence, each bezier-like hole will have a provided scale. + max_scale : float + Maximum bezier-like hole scale. + max_angles_amount : int + Maximum amount of angles in each bezier-like hole. + max_sharpness : float + Maximum value of bezier-like holes sharpness. + locations : ndarray + If provided, an array of desired locations of bezier-like holes. + seed : int, optional + Seed the random numbers generator. + """ + rng = np.random.default_rng(seed) + filtering_matrix = np.zeros_like(self.full_matrix) + + # Generate bezier-like holes + # Generate figures scales + if isinstance(scale, float): + scales = [] + sampling_scale = int( + np.ceil(1.0 / (1 - np.exp(-scale * max_scale))) + ) # inverse probability of scales < max_scales + while len(scales) < n: + new_scales = rng.exponential(scale, size=sampling_scale*(n - len(scales))) + new_scales = new_scales[new_scales <= max_scale] + scales.extend(new_scales) + scales = scales[:n] + else: + scales = scale + + # Generate figures-like holes locations + if locations is None: + idxs = rng.choice(len(self), size=n) + locations = self.points[idxs, :2] + + coordinates = [] # container for all types of holes, represented by their coordinates + + # Generate figures inside the field + for location, figure_scale in zip(locations, scales): + n_key_points = rng.integers(2, max_angles_amount + 1) + radius = rng.random() + sharpness = rng.random() * rng.integers(1, max_sharpness) + + figure_coordinates = make_bezier_figure(n=n_key_points, radius=radius, sharpness=sharpness, + scale=figure_scale, shape=self.shape, seed=seed) + figure_coordinates += location + + # Shift figures if they are out of field bounds + negative_coords_shift = np.min(np.vstack([figure_coordinates, [0, 0]]), axis=0) + huge_coords_shift = np.max(np.vstack([figure_coordinates - self.shape, [0, 0]]), axis=0) + figure_coordinates -= (huge_coords_shift + negative_coords_shift + 1) + + coordinates.append(figure_coordinates) + + # Generate points-like holes + if points_proportion: + points_n = int(points_proportion * len(self)) + idxs = rng.choice(len(self), size=points_n) + locations = self.points[idxs, :2] + + filtering_matrix[locations[:, 0], locations[:, 1]] = 1 + + if isinstance(points_shape, int): + points_shape = (points_shape, points_shape) + filtering_matrix = binary_dilation(filtering_matrix, np.ones(points_shape)) + + coordinates.append(np.argwhere(filtering_matrix > 0)) + + coordinates = np.concatenate(coordinates) + + # Add noise and filtering matrix transformations + if noise_level: + noise = rng.normal(loc=coordinates, + scale=noise_level, + size=coordinates.shape) + coordinates = np.unique(np.vstack([coordinates, noise.astype(int)]), axis=0) + + # Add valid coordinates onto filtering matrix + idx = np.where((coordinates[:, 0] >= 0) & + (coordinates[:, 1] >= 0) & + (coordinates[:, 0] < self.i_length) & + (coordinates[:, 1] < self.x_length))[0] + coordinates = coordinates[idx] + + filtering_matrix[coordinates[:, 0], coordinates[:, 1]] = 1 + + # Process holes + filtering_matrix = binary_fill_holes(filtering_matrix) + filtering_matrix = binary_dilation(filtering_matrix, iterations=4) + return filtering_matrix + + def make_holes(self, inplace=False, n=10, scale=1.0, max_scale=.25, + max_angles_amount=4, max_sharpness=5.0, locations=None, + points_proportion=1e-5, points_shape=1, + noise_level=0, seed=None): + """ Make holes on a horizon surface. + + Note, this method may change horizon inplace or create a new instance. By default creates a new instance. + In either case it returns a processed horizon instance. + """ + #pylint: disable=self-cls-assignment + filtering_matrix = self.generate_holes_matrix(n=n, scale=scale, max_scale=max_scale, + max_angles_amount=max_angles_amount, + max_sharpness=max_sharpness, locations=locations, + points_proportion=points_proportion, points_shape=points_shape, + noise_level=noise_level, seed=seed) + + return self.filter(filtering_matrix, inplace=inplace) + + make_holes.__doc__ += '\n' + '\n'.join(generate_holes_matrix.__doc__.split('\n')[1:]) + +# Helper functions +@njit(parallel=True) +def _convolve(src, kernel, max_depth_difference): + """ Jit-accelerated function to apply 2d convolution with special care for nan values. """ + #pylint: disable=too-many-nested-blocks, consider-using-enumerate, not-an-iterable + k = kernel.shape[0] // 2 + raveled_kernel = kernel.ravel() / np.sum(kernel) + + i_range, x_range = src.shape + dst = src.copy() + + for iline in prange(0, i_range): + for xline in range(0, x_range): + central = src[iline, xline] + + if isnan(central): + continue + + # Get values in the squared window and apply kernel to them + element = src[max(0, iline-k):min(iline+k+1, i_range), + max(0, xline-k):min(xline+k+1, x_range)].ravel() + + s, sum_weights = np.float32(0), np.float32(0) + for item, weight in zip(element, raveled_kernel): + if not isnan(item) and (abs(item - central) <= max_depth_difference): + s += item * weight + sum_weights += weight + + if sum_weights != 0.0: + dst[iline, xline] = s / sum_weights + return dst + +@njit(parallel=True) +def _bilateral_filter(src, kernel, max_depth_difference, sigma_range=0.1): + """ Jit-accelerated function to apply 2d bilateral filtering with special care for nan values. + + The difference between :func:`_convolve` and :func:`_bilateral_filter` is in additional weight multiplier, + which is a gaussian of difference of convolved elements. + """ + #pylint: disable=too-many-nested-blocks, consider-using-enumerate, not-an-iterable + k = kernel.shape[0] // 2 + raveled_kernel = kernel.ravel() / np.sum(kernel) + sigma_squared = sigma_range**2 + + i_range, x_range = src.shape + dst = src.copy() + + for iline in prange(0, i_range): + for xline in range(0, x_range): + central = src[iline, xline] + + if isnan(central): + continue # Because can't evaluate additional multiplier + + # Get values in the squared window and apply kernel to them + element = src[max(0, iline-k):min(iline+k+1, i_range), + max(0, xline-k):min(xline+k+1, x_range)].ravel() + + s, sum_weights = np.float32(0), np.float32(0) + for item, weight in zip(element, raveled_kernel): + if not isnan(item) and (abs(item - central) <= max_depth_difference): + weight *= np.exp(-0.5*((item - central)**2)/sigma_squared) + + s += item * weight + sum_weights += weight + + if sum_weights != 0.0: + dst[iline, xline] = s / sum_weights + return dst + +@njit(parallel=True) +def _interpolate(src, kernel, min_present_neighbors=1, max_depth_ptp=None): + """ Jit-accelerated function to apply 2d interpolation to nan values. """ + #pylint: disable=too-many-nested-blocks, consider-using-enumerate, not-an-iterable + k = kernel.shape[0] // 2 + raveled_kernel = kernel.ravel() / np.sum(kernel) + + i_range, x_range = src.shape + dst = src.copy() + + for iline in prange(0, i_range): + for xline in range(0, x_range): + central = src[iline, xline] + + if not isnan(central): + continue # We interpolate values only to nan points + + # Get neighbors and check whether we can interpolate them + element = src[max(0, iline-k):min(iline+k+1, i_range), + max(0, xline-k):min(xline+k+1, x_range)].ravel() + + filled_neighbors = kernel.size - np.isnan(element).sum() + if filled_neighbors < min_present_neighbors: + continue + + # Compare ptp with the max_distance_threshold + if max_depth_ptp is not None: + nanmax, nanmin = np.float32(element[0]), np.float32(element[0]) + + for item in element: + if not isnan(item): + if isnan(nanmax): + nanmax = item + nanmin = item + else: + nanmax = max(item, nanmax) + nanmin = min(item, nanmin) + + if nanmax - nanmin > max_depth_ptp: + continue + + # Apply kernel to neighbors to get value for interpolated point + s, sum_weights = np.float32(0), np.float32(0) + for item, weight in zip(element, raveled_kernel): + if not isnan(item): + s += item * weight + sum_weights += weight + + if sum_weights != 0.0: + dst[iline, xline] = s / sum_weights + return dst diff --git a/seismiqb/labels/horizon/visualization.py b/seismiqb/labels/horizon/visualization.py new file mode 100644 index 0000000..02618f5 --- /dev/null +++ b/seismiqb/labels/horizon/visualization.py @@ -0,0 +1,192 @@ +""" Mixin for horizon visualization. """ +from copy import copy +from textwrap import dedent + +import numpy as np +from scipy.spatial import Delaunay + +from ..mixins import VisualizationMixin +from ...plotters import show_3d +from ...utils import AugmentedList, DelegatingList, filter_simplices + + + +class HorizonVisualizationMixin(VisualizationMixin): + """ Methods for textual and visual representation of a horizon. """ + #pylint: disable=protected-access + def __repr__(self): + return f"""""" + + def __str__(self): + msg = f""" + Horizon {self.name} for {self.field.short_name} loaded from {self.format} + Ilines range: {self.i_min} to {self.i_max} + Xlines range: {self.x_min} to {self.x_max} + Depth range: {self.d_min} to {self.d_max} + Depth mean: {self.d_mean:.6} + Depth std: {self.d_std:.6} + + Length: {len(self)} + Perimeter: {self.perimeter} + Coverage: {self.coverage:3.5} + Solidity: {self.solidity:3.5} + Num of holes: {self.number_of_holes} + """ + + if self.is_carcass: + msg += f""" + Unique ilines: {self.carcass_ilines} + Unique xlines: {self.carcass_xlines} + """ + return dedent(msg) + + + # 2D + def find_self(self): + """ Get reference to the instance in a field. + If it was loaded/added correctly, then it should be one of `loaded_labels`. + Otherwise, we add it in a fake attribute and remove later. + """ + for src in self.field.loaded_labels: + labels = getattr(self.field, src) + + if isinstance(labels, list): + for idx, label in enumerate(labels): + if label is self: + return f'{src}:{idx}' + + # Instance is not attached to a field: add it temporarily (clean-up when finish plot creation) + self.field._unknown_label = AugmentedList([self]) + self.field.loaded_labels.append('_unknown_label') + return '_unknown_label:0' + + @staticmethod + def _show_add_prefix(attribute, prefix=None): + if isinstance(attribute, str): + attribute = ('/'.join([prefix, attribute])).replace('//', '/') + elif isinstance(attribute, dict): + attribute['src'] = ('/'.join([prefix, attribute['src']])).replace('//', '/') + return attribute + + + def show(self, attributes='depths', mode='image', show=True, **kwargs): + """ Field visualization with custom naming scheme. """ + attributes = DelegatingList(attributes) + attributes = attributes.map(lambda item: copy(item) if isinstance(item, dict) else item) + attributes = attributes.map(self._show_add_prefix, prefix=self.find_self()) + + kwargs = { + 'suptitle': f'`{self.name}` on field `{self.field.short_name}`', + **kwargs + } + plotter = self.field.show(attributes=attributes, mode=mode, show=show, **kwargs) + + # Clean-up + if self.field.loaded_labels[-1] == '_unknown_label': + delattr(self.field, '_unknown_label') + self.field.loaded_labels.pop(-1) + + return plotter + + def compute_auto_zoom(self, index, axis=None, zoom_margin=100): + """ Get slice around the horizon without zero-traces on bounds. """ + bounds = self.field.geometry.compute_auto_zoom(index, axis)[0] + return (bounds, slice(self.d_min - zoom_margin, self.d_max + zoom_margin)) + + # 3D + def show_3d(self, n_points=100, threshold=100., z_ratio=1., zoom=None, show_axes=True, + width=1200, height=1200, margin=(0, 0, 100), savepath=None, **kwargs): + """ Interactive 3D plot. Roughly, does the following: + - select `n` points to represent the horizon surface + - triangulate those points + - remove some of the triangles on conditions + - use Plotly to draw the tri-surface + + Parameters + ---------- + n_points : int + Number of points for horizon surface creation. + The more, the better the image is and the slower it is displayed. + threshold : int + Threshold to remove triangles with bigger depth differences in vertices. + z_ratio : int + Aspect ratio between height axis and spatial ones. + zoom : tuple of slices + Crop from cube to show. + show_axes : bool + Whether to show axes and their labels. + width, height : int + Size of the image. + margin : int + Added margin from below and above along depth axis. + savepath : str + Path to save interactive html to. + kwargs : dict + Other arguments of plot creation. + """ + title = f'Horizon `{self.short_name}` on `{self.field.short_name}`' + aspect_ratio = (self.i_length / self.x_length, 1, z_ratio) + axis_labels = (self.field.index_headers[0], self.field.index_headers[1], 'DEPTH') + if zoom is None: + zoom = [slice(0, i) for i in self.field.shape] + zoom[-1] = slice(self.d_min, self.d_max) + + x, y, z, simplices = self.make_triangulation(n_points, threshold, zoom) + + show_3d(x, y, z, simplices, title, zoom, None, show_axes, aspect_ratio, + axis_labels, width, height, margin, savepath, **kwargs) + + def make_triangulation(self, n_points, threshold, slices, **kwargs): + """ Create triangultaion of horizon. + + Parameters + ---------- + n_points: int + Number of points for horizon surface creation. + The more, the better the image is and the slower it is displayed. + slices : tuple + Region to process. + + Returns + ------- + x, y, z, simplices + `x`, `y` and `z` are np.ndarrays of triangle vertices, `simplices` is (N, 3) array where each row + represent triangle. Elements of row are indices of points that are vertices of triangle. + """ + _ = kwargs + weights_matrix = self.full_matrix.astype(np.float32) + + grad_i = np.diff(weights_matrix, axis=0, prepend=0) + grad_x = np.diff(weights_matrix, axis=1, prepend=0) + weights_matrix = (grad_i + grad_x) / 2 + weights_matrix[np.abs(weights_matrix) > 100] = np.nan + + idx = np.stack(np.nonzero(self.full_matrix > 0), axis=0) + mask_1 = (idx <= np.array([slices[0].stop, slices[1].stop]).reshape(2, 1)).all(axis=0) + mask_2 = (idx >= np.array([slices[0].start, slices[1].start]).reshape(2, 1)).all(axis=0) + mask = np.logical_and(mask_1, mask_2) + idx = idx[:, mask] + + probs = np.abs(weights_matrix[idx[0], idx[1]].flatten()) + probs[np.isnan(probs)] = np.nanmax(probs) + indices = np.random.choice(len(probs), size=n_points, p=probs / probs.sum()) + + # Convert to meshgrid + ilines = self.points[mask, 0][indices] + xlines = self.points[mask, 1][indices] + ilines, xlines = np.meshgrid(ilines, xlines) + ilines = ilines.flatten() + xlines = xlines.flatten() + + # Remove from grid points with no horizon in it + depths = self.full_matrix[ilines, xlines] + mask = (depths != self.FILL_VALUE) + x = ilines[mask] + y = xlines[mask] + z = depths[mask] + + # Triangulate points and remove some of the triangles + tri = Delaunay(np.vstack([x, y]).T) + simplices = filter_simplices(simplices=tri.simplices, points=tri.points, + matrix=self.full_matrix, threshold=threshold) + return x, y, z, simplices diff --git a/seismiqb/labels/mixins.py b/seismiqb/labels/mixins.py new file mode 100644 index 0000000..9f39f42 --- /dev/null +++ b/seismiqb/labels/mixins.py @@ -0,0 +1,92 @@ +""" Common labels mixins. """ + +import numpy as np + +from ..plotters import plot + +class VisualizationMixin: + """ Visualization utilities. """ + def load_slide(self, index, axis=0, width=3): + """ Create a mask at desired location along supplied axis. """ + axis = self.field.geometry.parse_axis(axis) + locations = self.field.geometry.make_slide_locations(index, axis=axis) + shape = self.field.geometry.locations_to_shape(locations) + width = width or max(5, min(9, shape[-1] // 100)) + + mask = np.zeros(shape, dtype=np.float32) + mask = self.add_to_mask(mask, locations=locations, width=width) + return np.squeeze(mask) + + def show_slide(self, index, width=None, axis='i', zoom=None, plotter=plot, **kwargs): + """ Show slide with horizon on it. + + Parameters + ---------- + index : int, str + Index of the slide to show. + If int, then interpreted as the ordinal along the specified axis. + If `'random'`, then we generate random index along the axis. + If string of the `'#XXX'` format, then we interpret it as the exact indexing header value. + width : int + Horizon thickness. If None given, set to 1% of seismic slide depth. + axis : int + Number of axis to load slide along. + zoom : tuple, None or 'auto' + Tuple of slices to apply directly to 2d images. If None, slicing is not applied. + If 'auto', zero traces on bounds will be dropped and image will be centered on label. + plotter : instance of `plot` + Plotter instance to use. + Combined with `positions` parameter allows using subplots of already existing plotter. + """ + # Make `locations` for slide loading + axis = self.field.geometry.parse_axis(axis) + index = self.field.geometry.get_slide_index(index, axis=axis) + + # Load seismic and mask + seismic_slide = self.field.geometry.load_slide(index=index, axis=axis) + mask = self.load_slide(index=index, axis=axis, width=width) + seismic_slide, mask = np.squeeze(seismic_slide), np.squeeze(mask) + xmin, xmax, ymin, ymax = 0, seismic_slide.shape[0], seismic_slide.shape[1], 0 + + if zoom == 'auto': + zoom = self.compute_auto_zoom(index, axis) + + if zoom is not None: + seismic_slide = seismic_slide[zoom] + mask = mask[zoom] + xmin = zoom[0].start or xmin + xmax = zoom[0].stop or xmax + ymin = zoom[1].stop or ymin + ymax = zoom[1].start or ymax + + # defaults for plotting if not supplied in kwargs + header = self.field.axis_names[axis] + total = self.field.shape[axis] + + if axis in [0, 1]: + xlabel = self.field.index_headers[1 - axis] + ylabel = 'DEPTH' + if axis == 2: + xlabel = self.field.index_headers[0] + ylabel = self.field.index_headers[1] + total = self.field.depth + + title = f'{self.__class__.__name__} `{self.name}` on cube'\ + f'`{self.field.short_name}`\n {header} {index} out of {total}' + + kwargs = { + 'cmap': ['Greys_r', 'darkorange'], + 'title': title, + 'xlabel': xlabel, + 'ylabel': ylabel, + 'extent': (xmin, xmax, ymin, ymax), + 'legend': False, + 'labeltop': False, + 'labelright': False, + 'curve_width': width, + 'grid': [False, True], + 'colorbar': [True, False], + 'augment_mask': [False, True], + **kwargs + } + return plotter(data=[seismic_slide, mask], **kwargs) diff --git a/seismiqb/labels/well/__init__.py b/seismiqb/labels/well/__init__.py new file mode 100644 index 0000000..c66e8e6 --- /dev/null +++ b/seismiqb/labels/well/__init__.py @@ -0,0 +1,2 @@ +""" !!. """ +from .base import Well, MatchedWell diff --git a/seismiqb/labels/well/base.py b/seismiqb/labels/well/base.py new file mode 100644 index 0000000..22ae877 --- /dev/null +++ b/seismiqb/labels/well/base.py @@ -0,0 +1,397 @@ +""" Well class to describe core logs. """ +import os + +import numpy as np +import pandas as pd +import scipy + +from lasio import LASFile + +from ...plotters import plot + + + +class Well: + """ A class to hold information about core logs and perform simple processing operations. + Main idea is to initialize the well instance from either LAS file or checkshot, and then combine multiple instances + into one with all (possibly, interpolated) available logs. + + TODO: write more docs + """ + def __init__(self, storage, field=None, name=None, **kwargs): + self.path = None + self.name = name + self.field = field + + # Attributes, available for wells, matched with seismic + self.vertical = None + self.location = None + self.points = None + self.bboxes = {} # log name to its bbox + + # pylint: disable=import-outside-toplevel + from ...field import Field + + if isinstance(storage, str): + path = storage + self.path = path + self.name = os.path.basename(path).split('.')[0] + + with open(path, mode='r', encoding='utf-8') as file: + line = file.readline() + + if 'LAS' in line or 'version' in line.lower(): + # LAS format: independent of software written by + self.from_las(path, **kwargs) + self.format = 'las' + elif 'Petrel checkshots format' in line: + # Checkshots can be saved by different software products and have different types + self.from_petrel_checkshot(path, **kwargs) + self.format = 'petrel_checkshot' + else: + # TODO: add more types of supported well files + raise TypeError(f'Unknown type of file! first line is: {line}') + elif isinstance(storage, pd.DataFrame): + self.data = storage + self.format = 'dataframe' + elif isinstance(storage, Field): + self.name = name or f'seismicdata on {storage.short_name}' + self.from_field(storage, **kwargs) + self.field = storage + self.format = 'field' + + @property + def keys(self): + """ Available logs. """ + return list(self.data.columns) + + @property + def n_logs(self): + """ Number of available logs. """ + return len(self.keys) + + + # Initialization from different containers + def from_las(self, path, **kwargs): + """ Initialize instance from LAS file. """ + self.lasfile = LASFile(path) + self.data = self.lasfile.df().rename_axis('DEPTH') + + def from_petrel_checkshot(self, path, **kwargs): + """ Initialize instance from a checkshot, saved by Petrel software. """ + #pylint: disable='anomalous-backslash-in-string + self.data = pd.read_csv(path, skiprows=14, header=None, sep='\s+', + names=['X', 'Y', 'Z', 'TWT', 'MD', 'Well', 'AvgV', 'IV'], + usecols=['X', 'Y', 'Z', 'TWT', 'MD', 'AvgV', 'IV']) + self.data = self.data.set_index('MD') + self.data['TWT'] = -self.data['TWT'] + self.data['Z'] = -self.data['Z'] + + def from_field(self, field, location=None, column_name='DATA', **kwargs): + """ Initialize instance from a known field geometry: available pseudo-logs are `TIME` and `SAMPLES`. """ + samples = np.arange(0, field.depth, 1, dtype=np.int32) + seismic_time = samples * field.sample_interval + data = {'SAMPLES': samples, 'TIME': seismic_time} + + if location is not None: + data[column_name] = field.geometry[location[0], location[1], :] + + self.data = pd.DataFrame(data).set_index('SAMPLES') + + + # Redefined protocols + def __getitem__(self, key): + return self.data[key] + + def __setitem__(self, key, value): + # TODO: add bbox computation, if matched to seismic + self.data.__setitem__(key, value) + + def __getattr__(self, key): + if not key.endswith('state__'): + return getattr(self.data, key) + raise AttributeError + + + # Methods to combine multiple wells into one + def merge_data(self, other, key_self='index', key_other='index', inplace=True, kind='linear', prefix=''): + """ Merge data from other well instance or dataframe. + Resamples the data of `other` to match points in `self` in one of the columns. + """ + self_df = self.data.copy() if inplace is False else self.data + self_x = self_df.index if key_self=='index' else self_df[key_self] + + other_df = other.data if isinstance(other, Well) else other + other_x = other_df.index if key_other=='index' else other_df[key_other] + other_df.reset_index(inplace=True) + + for column in set(other_df.columns) - {key_other}: + if column in self.keys: + if not prefix: + raise ValueError('!!.') + column_ = prefix + column + else: + column_ = column + + self_df[column_] = np.interp(self_x, other_x, other_df[column]) + + if inplace: + return self + return Well(self_df, name='+'+self.name, field=self.field) + + + def match_to_seismic(self, columns=('X', 'Y', 'TWT'), field=None, well=None): + """ Match `self` to a provided `well` or to default seismic pseudo-well. """ + field = field or self.field + assert field is not None, 'Making points requires field reference in either `Well` instance or method call!' + + # + cdp_xy_values = self.data[list(columns[:2])].values + ordinal_xy_values = field.lines_to_ordinals(field.cdp_to_lines(cdp_xy_values).astype(np.int32)) + + data = self.data.copy() + data[['INLINE_3D', 'CROSSLINE_3D']] = ordinal_xy_values + + # + matched_well = well or Well(storage=field, location=ordinal_xy_values[0], name=f'matched_{self.name}') + matched_well.merge_data(other=data, key_self='TIME', key_other=columns[-1]) + matched_well.data = matched_well.data.astype({'INLINE_3D': np.int32, 'CROSSLINE_3D': np.int32}) + + uniques = np.unique(ordinal_xy_values, axis=0) + matched_well.vertical = bool(len(uniques) == 1) + matched_well.location = ordinal_xy_values[0] + + points = matched_well.data.reset_index()[['INLINE_3D', 'CROSSLINE_3D', 'SAMPLES']] + matched_well.points = points.values.astype(np.int32) + + for column in matched_well.keys: + i_min, x_min = np.min(ordinal_xy_values, axis=0) + i_max, x_max = np.max(ordinal_xy_values, axis=0) + d_min, d_max = self.get_bounds(matched_well.data[column]) + + matched_well.bboxes[column] = np.array([[i_min, i_max], + [x_min, x_max], + [d_min, d_max]], + dtype=np.int32) + return matched_well + + + # Work with present logs + def add_seismic_trace(self, field, name): + """ Add seismic trace as a pseudo-log. """ + seismic_trace = field.mmap[self.points[:, 0], self.points[:, 1], self.points[:, 2]] + seismic_trace = seismic_trace.astype(np.float32) + self.data[name] = seismic_trace + + def compute_reflectivity(self, impedance_log='AI', name='R'): + """ Compute reflectivity from available impedance log. """ + impedance = self.data[impedance_log].values + reflectivity = self._compute_reflectivity(impedance) + self.data[name] = reflectivity + + @staticmethod + def _compute_reflectivity(impedance, fill_value=0): + reflectivity = impedance.copy() + reflectivity[1:] = ((impedance[1:] - impedance[:-1]) / + (impedance[1:] + impedance[:-1])) + reflectivity[0:1] = fill_value + return reflectivity + + def compute_synthetic(self, wavelet, reflectivity_log='R', name='SYNTHETIC'): + """ Compute synthetic trace from available reflectivity log and provided wavelet. """ + reflectivity = self.data[reflectivity_log].values + synthetic = self._compute_synthetic(reflectivity, wavelet) + self.data[name] = synthetic + + @staticmethod + def _compute_synthetic(reflectivity, wavelet): + reflectivity = np.nan_to_num(reflectivity, nan=0.0) + synthetic = np.convolve(reflectivity, wavelet, mode='same') + return synthetic + + def compute_filtered_log(self, log, order=5, frequency=60, btype='lowpass', name=None): + """ Apply filtration to a given log. """ + array = self.data[log].values + filtered_array = self._compute_filtered_log(array, order=order, frequency=frequency, + btype=btype, fs=self.field.sample_rate) + self.data[name] = filtered_array + + if log in self.bboxes: + bbox = self.bboxes[log].copy() + bbox[-1] += [1, -1] + filtered_array[:bbox[-1][0]] = np.nan + filtered_array[bbox[-1][1]:] = np.nan + self.bboxes[name] = bbox + + @staticmethod + def _compute_filtered_log(array, despike=None, order=5, frequency=60, btype='lowpass', fs=500): + if despike is not None: + array = scipy.signal.medfilt(array, despike) + + sosfilt = scipy.signal.butter(order, frequency, btype=btype, fs=fs, output='sos') + filtered_array = scipy.signal.sosfiltfilt(sosfilt, np.nan_to_num(array)) + filtered_array[filtered_array <= np.nanmin(array)] = np.nan + return filtered_array + + def compute_sampling_frequency(self): + """ Sampling frequency of the well data. Useful for frequency-domain filtrations. """ + return (1e6 * 0.3048) / self.DT.mean() + + + # Methods for Batch loads + def compute_overlap_mask(self, mask_bbox, log='AI'): + """ Compute a depth-wise mask of overlap between well log and a given mask bbox. """ + log_bbox = self.bboxes[log] + overlap_min = np.maximum(mask_bbox[:, 0], log_bbox[:, 0]) + overlap_max = np.minimum(mask_bbox[:, 1], log_bbox[:, 1] + 1) + + if not (overlap_max - overlap_min > 0).all(): + return None + + mask = (self.points[:, -1] >= mask_bbox[-1][0]) & (self.points[:, -1] < mask_bbox[-1][1]) + if self.vertical is False: + mask &= (self.points[:, 0] >= mask_bbox[0][0]) & (self.points[:, 0] < mask_bbox[0][1]) + mask &= (self.points[:, 1] >= mask_bbox[1][0]) & (self.points[:, 1] < mask_bbox[1][1]) + return mask + + def compute_overlap_size(self, mask_bbox, log='AI'): + """ Compute the number of pixels in a well within a given mask bbox. """ + overlap_mask = self.compute_overlap_mask(mask_bbox=mask_bbox, log=log) + return 0 if overlap_mask is None else overlap_mask.sum() + + def add_to_mask(self, mask, locations, log='AI', **kwargs): + """ Add values from log to a mask in a given location. """ + mask_bbox = np.array([[slc.start, slc.stop] for slc in locations], dtype=np.int32) + overlap_mask = self.compute_overlap_mask(mask_bbox=mask_bbox, log=log) + + if overlap_mask is not None: + points = self.points[overlap_mask] - mask_bbox[:, 0] + mask[points[:, 0], points[:, 1], points[:, 2]] = self.data[log].values[overlap_mask] + return mask + + + # Depth-wise filtration of logs + @staticmethod + def get_bounds(array): + """ Return the index of the first and the last meaningful elements in array. + Meaningful means non-nan and non-constant. + """ + diff = np.diff(array, prepend=array[0]) + diff = np.nan_to_num(diff, copy=False, nan=0.0) + mask = diff != 0 + return np.argmax(mask), len(array) - np.argmax(mask[::-1]) + + def filter(self, exclude=('INLINE_3D', 'CROSSLINE_3D', 'TWT', 'DEPTH', 'TIME')): + """ Fill insignificant values on left/right bounds of each log with nans. """ + for column in set(self.keys) - set(exclude): + d_min, d_max = self.get_bounds(self.data[column]) + self.data[column][:d_min] = np.nan + self.data[column][d_max:] = np.nan + + + # Visualization + @property + def short_name(self): + """ Name without extension. """ + if self.name is not None: + return self.name.split('.')[0] + return None + + def __repr__(self): + return f"""""" + + def plot(self, logs='all', layout='horizontal', dropkeys=None, zoom=None, combine='separate', **kwargs): + """ Show log curves. """ + horizontal_layout = layout.startswith('h') + + # Parse logs to use + logs = self.keys if logs == 'all' else logs + logs = [logs] if isinstance(logs, str) else logs + for key in dropkeys or []: + logs.remove(key) + keys = logs + n_subplots = len(logs) if combine == 'separate' else 1 + + # Parse limits + index_label = self.data.index.name + if zoom is None: + index_lim = [0, self.index[-1]] + else: + index_lim = [zoom.start, zoom.stop] + + # Default plot parameters + kwargs = { + 'suptitle': f'Well `{self.name}`', + 'title': keys, + 'mode': 'curve', + 'combine': combine, + 'label': keys if combine == 'overlay' else None, + **kwargs + } + + # Build layout + if horizontal_layout: + data = [(self.index, self[key]) for key in keys] + line_method = 'axvline' + + kwargs = { + 'xlabel': index_label, + 'xlabel_size': 20, + 'xlim': [index_lim] * n_subplots if combine == 'separate' else index_lim, + 'ylabel': '', + 'window': 100, 'alpha': 0.7, + 'ratio': 0.6, + 'ncols': min(2, n_subplots), + **kwargs + } + else: + data = [(self[key], self.index) for key in keys] + line_method = 'axhline' + + kwargs = { + 'ylabel': index_label, + 'ylabel_size': 20, + 'ylim': [index_lim] * n_subplots if combine == 'separate' else index_lim, + 'xlabel': '', + 'ratio': 0.4, + 'ncols': n_subplots, + **kwargs + } + + + plotter = plot(data, **kwargs) + for (column, subplot) in zip(keys, plotter.subplots): + ax = subplot.ax + if ax.axison is False: + continue + if not horizontal_layout: + ax.invert_yaxis() + + getattr(ax, line_method)(self.index[ 0], linestyle='--', color='orange') + getattr(ax, line_method)(self.index[-1], linestyle='--', color='orange') + + if combine == 'separate' and self.bboxes.get(column) is not None: + d_min, d_max = self.bboxes[column][-1] + getattr(ax, line_method)(d_min, linestyle='--', color='red') + getattr(ax, line_method)(d_max, linestyle='--', color='red') + return plotter + + +class MatchedWell(Well): + """ Automatic combination of multiple data sources. + TODO: extend the documentation + """ + def __init__(self, storage, additional_paths, field=None, name=None, data_name='DATA', **kwargs): + super().__init__(storage=field, field=field, name=name, **kwargs) + + main_well = Well(storage, field=field, **kwargs) + main_well.data['X'] //= 2 # bug in labeling + main_well.data['Y'] //= 2 # bug in labeling + + additional_paths = [additional_paths] if isinstance(additional_paths, str) else additional_paths + additional_wells = [Well(path, field=field) for path in additional_paths] + for well in additional_wells: + main_well.merge_data(well, key_self='index', key_other='index', inplace=True) + + main_well.match_to_seismic(field=field, well=self) + main_well.add_trace(field=field, name=data_name) diff --git a/seismiqb/matching/__init__.py b/seismiqb/matching/__init__.py new file mode 100644 index 0000000..c3b375a --- /dev/null +++ b/seismiqb/matching/__init__.py @@ -0,0 +1,4 @@ +""" Tools for matching seismic data. """ +from .intersection import Intersection +from .collection import FieldCollection +from .functional import * # pylint: disable=wildcard-import diff --git a/seismiqb/matching/collection.py b/seismiqb/matching/collection.py new file mode 100644 index 0000000..95af5f2 --- /dev/null +++ b/seismiqb/matching/collection.py @@ -0,0 +1,719 @@ +""" Collection of multiple intersecting fields. """ +import os +from glob import glob +from concurrent.futures import ProcessPoolExecutor + +import numpy as np +import pandas as pd +from numba import njit + +import matplotlib.pyplot as plt +import plotly.graph_objects as go + +from batchflow.notifier import Notifier +from .intersection import Intersection +from .functional import modify_trace + +from ..field import Field +from ..labels import Horizon +from ..plotters import plot +from ..geometry.memmap_loader import MemmapLoader + + + +class FieldCollection: + """ Collection of 2D fields and their intersections. """ + def __init__(self, fields, limits=slice(None), pad_width=0, threshold=10, + n_intersections=np.inf, geometry_kwargs=None): + self.fields = self.load_fields(fields, geometry_kwargs=geometry_kwargs) + self.n_fields = len(self.fields) + + self.intersections = self.compute_intersections(limits=limits, pad_width=pad_width, + threshold=threshold, n_intersections=n_intersections) + self.horizons = {} + + self.corrections = {} + + # Instance initialization + DEFAULT_GEOMETRY_KWARGS = { + 'index_headers': ['FieldRecord', 'CDP'], + 'additional_headers': ['CDP', 'CDP_X', 'CDP_Y'], + 'collect_stats': False, 'collect_stats_params': {'pbar': False}, + 'dump_headers': True, 'dump_meta': True + } + + def load_fields(self, fields, geometry_kwargs=None): + """ Load field instances from their paths. + If an element of `fields` is already an instance of Field, it is left untouched. + """ + # TODO: try to remove ~duplicate fields? + if isinstance(fields, str): + fields = sorted(list(glob(fields))) + + geometry_kwargs = geometry_kwargs if geometry_kwargs is not None else self.DEFAULT_GEOMETRY_KWARGS + return [Field(item, geometry_kwargs=geometry_kwargs) if isinstance(item, str) else item for item in fields] + + def compute_intersections(self, limits=slice(None), pad_width=0, threshold=10, n_intersections=np.inf): + """ Compute intersections over the present fields. """ + result = {} + for i, field_0 in enumerate(self.fields[:-1]): + for j, field_1 in enumerate(self.fields[i+1:], start=i+1): + intersections = Intersection.new(field_0=field_0, field_1=field_1, + limits=limits, pad_width=pad_width, threshold=threshold, + unwrap=False) + + for k, intersection in enumerate(intersections): + if k > n_intersections: + break + key = (i, j, k) + result[key] = intersection + intersection.key = (i, j, k) + + return result + + def load_horizon(self, path, add_instances=True, verbose=True): + """ Load horizon: save into dict for each field. """ + horizon_name = os.path.basename(path) + + df = pd.read_csv(path, sep=r'\s+', index_col=False, skiprows=[0], + names=['FIELD_NAME', '_', 'CDP_X', 'CDP_Y', 'DEPTH', '__'], + dtype={'FIELD_NAME': str, }) + self.horizons[horizon_name] = df + unique_field_names = df['FIELD_NAME'].unique() + + for field in self.fields: + if field.short_name not in unique_field_names: + if verbose: + print(f'Field "{field.short_name}" is not labeled in horizon') + continue + subdf = df[df['FIELD_NAME'] == field.short_name] + + # Prepare horizon points: (N, 3) array + horizon_ixd = subdf[['CDP_X', 'CDP_Y', 'DEPTH']].values + if not getattr(field, 'horizons'): + field.horizons = {horizon_name : horizon_ixd} + else: + field.horizons[horizon_name] = horizon_ixd + + # Prepare horizon instances + if add_instances: #TODO: refactor + indices = [] + for value in horizon_ixd[:, :2]: + index = np.argmin(np.abs(field.cdp_values - value).sum(axis=1)) + indices.append(index) + indices = np.array(indices) + + depths = (subdf['DEPTH'].values - field.delay) / field.sample_interval + points = np.array([np.zeros(len(indices), dtype=np.int32), + indices, + np.round(depths).astype(np.int32)]).T + horizon_instance = Horizon(points, field=field, name=horizon_name) + + if not hasattr(field, 'horizon_instances'): + field.horizon_instances = {horizon_name : horizon_instance} + else: + field.horizon_instances[horizon_name] = horizon_instance + + + # Work with intersections + def find_intersection(self, name_0, name_1): + """ Find intersection by names of shot lines. """ + for intersection in self.intersections.values(): + if (name_0 in intersection.field_0.name and name_1 in intersection.field_1.name) or \ + (name_1 in intersection.field_0.name and name_0 in intersection.field_1.name): + return intersection + raise KeyError(f'No intersection of `{name_0}` and `{name_1}` in collection!') + + def find_intersections(self, name): + """ Find all intersections of a given show with other lines. """ + return [intersection for intersection in self.intersections.values() + if name in intersection.field_0.name or name in intersection.field_1.name] + + def match_intersections(self, pbar='t', method='analytic', limits=None, pad_width=None, n=1, transform=None, + **kwargs): + """ Match traces on each intersection. """ + for intersection in Notifier(pbar)(self.intersections.values()): + intersection.match_traces(method=method, limits=limits, pad_width=pad_width, n=n, transform=transform, + **kwargs) + + def match_intersections_p(self, pbar='t', method='analytic', limits=None, pad_width=None, n=1, transform=None, + max_workers=8, **kwargs): + """ Match traces on each intersection. """ + with Notifier(pbar, total=len(self.intersections)) as progress_bar: + def callback(future): + matching_results = future.result() + key = matching_results.pop('key') + self.intersections[key].matching_results = matching_results + progress_bar.update(1) + + with ProcessPoolExecutor(max_workers=max_workers) as executor: + for intersection in self.intersections.values(): + future = executor.submit(intersection.match_traces, + method=method, limits=limits, pad_width=pad_width, + n=n, transform=transform, **kwargs) + future.add_done_callback(callback) + + def get_matched_value(self, key): + """ Get required `key` value from each of the intersections. """ + return [intersection.matching_results[key] for intersection in self.intersections.values()] + + def intersections_df(self, errors=False, corrections=False, indices=False): + """ Dataframe with intersections: each row describes quality of matching, mis-tie parameters for every crossing. + If corrections are available, also use them. + """ + df = [] + for key, intersection in self.intersections.items(): + intersection_dict = {'key': key, **intersection.to_dict()} + df.append(intersection_dict) + df = pd.DataFrame(df) + df.set_index('key', inplace=True) + + # Corrections are distributed + if self.corrections: + shifts_errors = np.abs(self.corrections['shift']['errors']) + gains_errors = np.abs(self.corrections['gain']['errors']) + angles_errors = np.abs(self.corrections['angle']['errors']) + suspicious = ((shifts_errors > shifts_errors.mean() + 3 * shifts_errors.std()) + + (gains_errors > gains_errors.mean() + 3 * gains_errors.std()) + + (angles_errors > angles_errors.mean() + 3 * angles_errors.std())) + + if errors: + df['shifts_errors'] = shifts_errors + df['gains_errors'] = gains_errors + df['angles_errors'] = angles_errors + df['suspicious'] = suspicious + + if corrections: + idx_0 = [key[0] for key in self.intersections] + df['shift_correction'] = self.corrections['shift']['x'][idx_0] + df['angle_correction'] = self.corrections['angle']['x'][idx_0] + df['gain_correction'] = self.corrections['gain']['x'][idx_0] + + columns = [ + 'field_0_name', 'field_1_name', 'distance', 'suspicious', + 'corr', 'petrel_corr', + 'shift', 'shift_correction', 'angle', 'angle_correction', 'gain', 'gain_correction', + ] + columns = [c for c in columns if c in df.columns.values] + columns += list(set(df.columns.values) - set(columns)) + df = df[columns] + return df + + def compute_horizon_metric(self, horizon_name=None): + """ Compute the difference between horizon and proposed shifts. + The first metric adds no shift, measuring the difference on horizon picks in the original file. + The second uses field corrections, and the last applies shifts from the intersections. + """ + shifts = self.corrections['shift']['x'] + + metrics = [] + for key, intersection in self.intersections.items(): + metric_0 = intersection.compute_horizon_metric(horizon_name=horizon_name, shift=0) + metric_1 = intersection.compute_horizon_metric(horizon_name=horizon_name, + shift=shifts[key[0]] - shifts[key[1]]) + metric_2 = intersection.compute_horizon_metric(horizon_name=horizon_name, + shift=intersection.matching_results['shift']) + + metrics.append((metric_0, metric_1, metric_2)) + + names = ['mean_horizon_shift', 'mean_horizon_to_correction_shift', 'mean_horizon_to_intersection_shift'] + values = np.array(metrics).mean(axis=0).round(4) + return dict(zip(names, values)) + + + # Work with fields + def distribute_corrections(self, skip_index=-1, max_iters=100, alpha=0.75, tolerance=0.00001): + """ Distribute computed mis-ties from each intersection to fields. + Under the hood, we iteratively optimize mis-ties of every type with respect to ~MSE loss. + + For the phase corrections, we also add phase unwrapping. Refer to the original article for details. + Bishop, Nunns "`Correcting amplitude, time, and phase mis-ties in seismic data + `_" + """ + a = np.array([key[:2] for key in self.intersections]) + n = self.n_fields + + # Shift + b = np.array(self.get_matched_value('shift')) + x, loss = distribute_misties(a=a, b=b, n=n, skip_index=skip_index, + max_iters=max_iters, alpha=alpha, tolerance=tolerance) + xk, xl = x[a[:, 0]], x[a[:, 1]] + errors = b - (xk - xl) + self.corrections['shift'] = {'x': x, 'errors': errors, 'loss': loss, 'b': b} + + # Gain + b = np.array(self.get_matched_value('gain')) + b = np.log(b) + x, loss = distribute_misties(a=a, b=b, n=n, skip_index=skip_index, + max_iters=max_iters, alpha=alpha, tolerance=tolerance) + xk, xl = x[a[:, 0]], x[a[:, 1]] + errors = b - (xk - xl) + self.corrections['gain'] = {'x': np.exp(x), 'errors': errors, 'loss': loss, 'b': b} + + # Angle + b = np.array(self.get_matched_value('angle')) + x, loss = distribute_misties(a=a, b=b, n=n, skip_index=skip_index, + max_iters=max_iters, alpha=alpha, tolerance=tolerance) + + b_arange = np.arange(len(b)) + + for _ in range(0, len(self.intersections)): + xk, xl = x[a[:, 0]], x[a[:, 1]] + + b_unwrapped = np.repeat(b[:, np.newaxis], 3, axis=-1) + [-360, 0, +360] + errors_unwrapped = np.abs(b_unwrapped - (xk - xl).reshape(-1, 1)) + argmins = np.argmin(errors_unwrapped, axis=-1) + + # Stop condition: no phase unwrapping required + if (argmins == 1).all(): + # TODO: add one-time forced perturbation + break + + b = b_unwrapped[b_arange, argmins] + x, loss = distribute_misties(a=a, b=b, n=n, skip_index=skip_index, + max_iters=max_iters, alpha=alpha, tolerance=tolerance) + + errors = b - (xk - xl) + self.corrections['angle'] = {'x': x, 'errors': errors, 'loss': loss, 'b': b} + # TODO: add return with info about the process + + # Store correction info in fields as well + for i, field in enumerate(self.fields): + field.correction_results = { + 'shift': self.corrections['shift']['x'][i], + 'angle': self.corrections['angle']['x'][i], + 'gain': self.corrections['gain']['x'][i], + } + + return (self.corrections['shift']['loss'][-1], + self.corrections['angle']['loss'][-1], + self.corrections['gain']['loss'][-1]) + + + def compute_suspicious_intersections(self): + """ For each intersection, compute whether it is suspicious. + # TODO: add more checks + """ + if self.corrections is None: + return [False] * len(self.intersections) + shifts_errors = np.abs(self.corrections['shift']['errors']) + gains_errors = np.abs(self.corrections['gain']['errors']) + angles_errors = np.abs(self.corrections['angle']['errors']) + suspicious = ((shifts_errors > shifts_errors.mean() + 3 * shifts_errors.std()) + + (gains_errors > gains_errors.mean() + 3 * gains_errors.std()) + + (angles_errors > angles_errors.mean() + 3 * angles_errors.std())) + return suspicious + + def remove_intersections(self, indices=None, skip_index=-1, max_iters=100, alpha=0.75, tolerance=0.00001): + """ Remove all suspicious intersections and re-distribute corrections. """ + if indices is None: + suspicious = self.compute_suspicious() + indices = np.nonzero(suspicious)[0] + keys = list(self.intersections.keys()) + for idx in np.sort(indices)[::-1]: + key = keys[idx] + self.intersections.pop(key) + + self.distribute_corrections(skip_index=skip_index, max_iters=max_iters, alpha=alpha, tolerance=tolerance) + return indices + + def remove_fields(self, indices): + """ Remove fields (and their intersections) by indices. + TODO: test + """ + for idx in np.sort(indices)[::-1]: + self.fields.pop(idx) + + new_intersections = {} + for key, intersection in self.intersections.items(): + if key[0] in indices or key[1] in indices: + continue + + new_key = (key[0] - (indices > key[0]).sum(), + key[1] - (indices > key[1]).sum(), + key[2]) + intersection.key = new_key + new_intersections[new_key] = intersection + self.intersections = new_intersections + + + def fields_df(self): + """ Dataframe with fields: each row describes a field with computed mis-ties. """ + shifts = self.corrections['shift']['x'] + gains = self.corrections['gain']['x'] + angles = self.corrections['angle']['x'] + + df, bad_intersections_keys = [], [] + for i, field in enumerate(self.fields): + intersections = [] + recomputed_corrs = [] + + for key, intersection in self.intersections.items(): + if i in key[:2]: + recomputed_corr = intersection.evaluate(shift=shifts[key[0]] - shifts[key[1]], + angle=angles[key[0]] - angles[key[1]],) + recomputed_corr = (recomputed_corr + 1) / 2 + recomputed_corrs.append(recomputed_corr) + + intersections.append(intersection) + + if intersections: + min_, mean_, std_ = np.min(recomputed_corrs), np.mean(recomputed_corrs), np.std(recomputed_corrs) + + for j, intersection in enumerate(intersections): + recomputed_corr = recomputed_corrs[j] + if recomputed_corr < 0.5 or abs(mean_ - recomputed_corr) > 0.25: + bad_intersections_keys.append(intersection.key) + + # Stats on intersections: no distribution of corrections + dicts = [intersection.matching_results for intersection in intersections] + corrs = [d['petrel_corr'] for d in dicts] + mean_intersection, std_intersection = np.mean(corrs), np.std(corrs) + else: + # field has no intersections + min_ = mean_ = std_ = mean_intersection = std_intersection = np.float64(-1) + + + correction_results = { + 'name': field.name, + 'shift': shifts[i], + 'angle': angles[i], + 'gain': gains[i], + + 'mean_recomputed_corr': mean_.round(3), + 'std_recomputed_corr': std_.round(3), + 'min_recomputed_corr': min_.round(3), + + 'n_intersections': len(intersections), + 'mean_corr_intersections': mean_intersection.round(3), + 'std_corr_intersections': std_intersection.round(3), + } + + field.correction_results = correction_results + df.append(correction_results) + + # Compute potential bad fields + n_bad_intersections = np.zeros(self.n_fields, dtype=np.int8) + if bad_intersections_keys: + bad_fields = np.array(bad_intersections_keys)[:, :2].flatten() + u, c = np.unique(bad_fields, return_counts=True) + argsort = np.argsort(c)[::-1] + u, c = u[argsort], c[argsort] + n_bad_intersections[u] = c + + df = pd.DataFrame(df).set_index('name') + df['n_bad_intersections'] = n_bad_intersections + + columns = [ + 'shift', 'angle', 'gain', 'n_bad_intersections', + 'mean_recomputed_corr', 'min_recomputed_corr',# 'std_recomputed_corr', + 'n_intersections', 'mean_corr_intersections',# 'std_corr_intersections' + ] + + return df[columns] + + + # Export: SEG-Y + def export_segy(self, path, method='traces', apply_angle=True, apply_gain=True, pad_width=10, pbar='t'): + """ Export present fields with suggested corrections. + Uses either trace headers or trace values to introduce corrections. + In the first case, only vertical and gain corrections are applied. + The second one uses interpolation and FFT-shift under the hood. + + `path` can contain the '$' symbol, which is replaced by the field name. Useful to save a lot of files. + """ + for field in Notifier(pbar, desc='Exporting SEG-Y files')(self.fields): + self._export_segy(field=field, path=path, method=method, + apply_angle=apply_angle, apply_gain=apply_gain, pad_width=pad_width) + + @staticmethod + def _export_segy(field, path, method='traces', apply_angle=True, apply_gain=True, pad_width=10): + """ Export one SEG-Y file. """ + #pylint: disable=protected-access + # Prepare correction + shift = -field.correction_results['shift'] + angle = -field.correction_results['angle'] if apply_angle else 0.0 + gain = 1/field.correction_results['gain'] if apply_gain else 1.0 + + # Make a copy of a file. To make sure that it is not IBM floats, we copy data and headers separately + path = field.make_path(path, name=field.name) + FieldCollection._copy_segy(field, path) + + # Prepare dst memory map + dst_loader = MemmapLoader(path) + mmap_trace_headers_dtype = dst_loader._make_mmap_headers_dtype(['DelayRecordingTime'], + endian_symbol=dst_loader.endian_symbol) + mmap_trace_dtype = np.dtype([*mmap_trace_headers_dtype, + ('data', dst_loader.mmap_trace_data_dtype, dst_loader.mmap_trace_data_size)]) + + mmap = np.memmap(filename=path, mode='r+', shape=dst_loader.n_traces, + offset=dst_loader.file_traces_offset, dtype=mmap_trace_dtype) + + # Modify copied file + if method == 'headers': + added_delay = np.round(shift).astype(np.int16) + mmap['DelayRecordingTime'] += added_delay + mmap['data'] *= gain + + elif method == 'traces': + data = field.load_slide(0) + + # Resample to MS + arange = np.arange(data.shape[1], dtype=np.float32) + arange_ms = np.arange(data.shape[1], step=(1 / field.sample_interval), dtype=np.float32) + interpolator = lambda trace: np.interp(arange_ms, arange, trace) + data = np.apply_along_axis(interpolator, 1, data) + + # Apply modifications + data = np.pad(data, ((0, 0), (pad_width, pad_width))) + for c in range(data.shape[0]): + data[c] = modify_trace(data[c], shift=shift, angle=angle, gain=gain) + data = data[:, pad_width:-pad_width] + + # Resample back to samples + interpolator = lambda trace: np.interp(arange, arange_ms, trace) + data = np.apply_along_axis(interpolator, 1, data) + mmap['data'] = data + return path + + @staticmethod + def _copy_segy(field, path): + """ Copy the data of SEG-Y file in float32 format, then copy trace headers. """ + data = field.geometry[:, :, :] + field.geometry.array_to_segy(data, path=path, format=5, pbar=False) + + src_loader = field.geometry.loader + src_mmap = np.memmap(field.path, mode='r', shape=src_loader.n_traces, + offset=src_loader.file_traces_offset, dtype=src_loader.mmap_trace_dtype) + + dst_loader = MemmapLoader(path) + dst_mmap = np.memmap(path, mode='r+', shape=dst_loader.n_traces, + offset=dst_loader.file_traces_offset, dtype=dst_loader.mmap_trace_dtype) + + dst_mmap['headers'] = src_mmap['headers'] + return path + + # Export: horizons + def export_horizons(self, path): + """ Save horizons with applied corrections. """ + for horizon_name in self.horizons: + self.export_horizon(horizon_name=horizon_name, path=path) + + def export_horizon(self, path, horizon_name=None, encoding=None): + """ Save one horizon with applied corrections. """ + path = path.replace('$', horizon_name) + df = self.horizons[horizon_name] + + depth_column = df['DEPTH'].copy() + for field in self.fields: + mask = df['FIELD_NAME'] == field.short_name + depth_column[mask] += -field.correction_results['shift'] # TODO: adjust z-shift on angle + + out_df = df.copy() + out_df['DEPTH'] = depth_column + + with open(path, 'w+', encoding=encoding) as file: + file.write(horizon_name + '\n') + out_df.to_csv(path, mode='a', index=False, header=False, sep='\t', encoding=encoding) + return path + + + # Visualize + def show_lines(self, arrow_step=10, arrow_size=20, annotate_index=True, annotate_name=False): + """ Display annotated shot lines on a 2d graph in CDP coordinates. """ + fig, ax = plt.subplots(figsize=(14, 8)) + + depths = np.array([field.depth for field in self.fields]) + colors = ['black', 'firebrick', 'gold', 'limegreen', 'magenta'] * 25 + depth_to_color = dict(zip(sorted(np.unique(depths)), colors)) + + # Data + for i, field in enumerate(self.fields): + color = depth_to_color[field.depth] + values = field.geometry.headers[['CDP_X', 'CDP_Y']].values + x, y = values[:, 0], values[:, 1] + ax.plot(x, y, color) + + idx = x.size // 2 + arrow_step_ = min(arrow_step, idx - 0, x.size - idx - 1) + ax.annotate('', size=arrow_size, + xytext=(x[idx-arrow_step_], y[idx-arrow_step_]), + xy=(x[idx+arrow_step_], y[idx+arrow_step_]), + arrowprops=dict(arrowstyle="->", color=color)) + + if annotate_index or annotate_name: + annotation = field.short_name if annotate_name else i + ax.annotate(annotation, xy=(x[0], y[0]), size=12) + + # Annotations + ax.set_title('2D profiles', fontsize=26) + ax.set_xlabel('CDP_X', fontsize=22) + ax.set_ylabel('CDP_Y', fontsize=22) + ax.grid() + fig.show() + + + def show_bubblemap(self, savepath=None): + """ Display annotated shot lines and their intersections on a 2d interactive graph in CDP coordinates. """ + fig = go.Figure() + + depths = np.array([field.depth for field in self.fields]) + colors = ['black', 'firebrick', 'gold', 'limegreen', 'magenta'] * 25 + depth_to_color = dict(zip(sorted(np.unique(depths)), colors)) + + intersections_df = self.intersections_df() + + # Line for each SEG-Y + for i, field in enumerate(self.fields): + correction_results = field.correction_results + values = field.geometry.headers[['CDP_X', 'CDP_Y']].values + color_ = depth_to_color[field.depth] + + name_ = f'{i} : "{field.short_name}.sgy"' + hovertemplate_ = (f' #{i}
' + f' FIELD : "{field.short_name}.sgy"
' + f' DEPTH : {field.depth}
' + ' CDP_X : %{x:,d}
' + ' CDP_Y : %{y:,d}
' + ' TSF : %{customdata}
' + f' MEAN INTERSECTION CORR : {correction_results["mean_corr_intersections"]:3.3f}
' + f' MEAN RECOMPUTED CORR : {correction_results["mean_recomputed_corr"]:3.3f}' + '') + + step = 30 + fig.add_trace(go.Scatter(x=values[::step, 0], y=values[::step, 1], + customdata=field.geometry.headers['TRACE_SEQUENCE_FILE'][::step], + name=name_, hovertemplate=hovertemplate_, + mode='lines', + line=dict(color=color_, width=2))) + + # Markers on intersections + for key, intersection in self.intersections.items(): + # Retrieve data + i, j = key[:2] + field_0, field_1 = intersection.field_0, intersection.field_1 + x, y = (intersection.coordinates_0 + intersection.coordinates_1) // 2 + + matching_results = intersection.matching_results + corr, shift = matching_results['corr'], matching_results['shift'] + angle, gain = matching_results['angle'], matching_results['gain'] + + # HTML things + name_ = f'"{field_0.short_name}.sgy" X "{field_1.short_name}.sgy"' + hovertemplate_ = (f' ({i}, {j})
' + f' {name_}
' + ' CDP_X : %{x:,d}
' + ' CDP_Y : %{y:,d}
' + f' BEST_CORR : {corr:3.3f}
' + f' BEST_PCORR : {(1 + corr)/2:3.3f}
' + f' SHIFT : {shift:3.3f}
' + f' ANGLE : {angle:3.3f}
' + f' GAIN : {gain:3.3f} ') + + size_ = 4 + (1 - corr) * 5 + color_ = 'red' if intersections_df.loc[[key]]['suspicious'].all() else 'green' + + fig.add_trace(go.Scatter(x=[x], y=[y], mode='markers', + name=name_, hoverlabel={}, + hovertemplate=hovertemplate_, + showlegend=False, + marker=dict(size=size_, color=color_))) + + + fig.update_layout(title=f'2D SEG-Y
{len(self.intersections)} intersections', + xaxis_title='CDP_X', yaxis_title='CDP_Y', + width=1200, height=500, margin=dict(l=10, r=10, t=40, b=10)) + fig.show() + + if savepath is not None: + fig.write_html(savepath) + + def show_histogram(self, keys=('corr', 'shift', 'angle', 'gain'), **kwargs): + """ Display histogram of mis-tie values across all intersections. """ + data = [np.array(self.get_matched_value(key)) for key in keys] + data = [item[~np.isnan(item)] for item in data] + + kwargs = { + 'title': list(keys), + 'xlabel': list(keys), + 'combine': 'separate', + 'ncols': 4, + **kwargs + } + return plot(data, mode='histogram', **kwargs) + + + +@njit +def distribute_misties(a, b, n, skip_index=-1, max_iters=100, alpha=0.75, tolerance=0.00001): + """ Distribute misties `b` on intersections `a` over `n` fields by a iterative optimization procedure. + Bishop, Nunns "`Correcting amplitude, time, and phase mis-ties in seismic data + `_" + + Probably, not as fast as highly-optimized linear solvers, but allows for more flexibility. + Also, usual run time is less than 1ms, so it is fast enough anyways. + + Parameters + ---------- + a : np.ndarray + (M, 2)-shaped matrix that describes geometry of intersections. + Each row is a pair of indices of intersecting lines. + b : np.ndarray + (M,)-shaped vector with misties on each intersection. + n : int + Number of lines in the intersections. + For each of them, we compute a distributed mistie as a result of this function. + + Example + ------- + To reproduce example from the original paper, one can use:: + a = np.array([ + [1, 2], + [0, 2], + [0, 1], + [0, 3], + [1, 3], + [2, 3], + ]) + b = np.array([21, 1, -19, 1, 20, -2]) + n = 4 + """ + x = np.zeros(n) + errors = np.empty(max_iters) + + for iteration in range(max_iters): + # Stop condition: no further decrease in error + xk, xl = x[a[:, 0]], x[a[:, 1]] + errors[iteration] = ((b - (xk - xl)) ** 2).mean() ** (1 / 2) + if iteration != 0: + stop_condition = (errors[iteration - 1] - errors[iteration]) / errors[iteration - 1] + if stop_condition < tolerance or errors[iteration] == 0.0: + break + else: + if errors[0] == 0: + break + + # Compute next iteration of solution + x_next = x.copy() + + for j in range(n): + if j == skip_index: + continue + + d, s = 0, 0.0 # number of intersections / sum of discrepancies + for i, idx in enumerate(a): + k, l = idx + + if k == j: + s += b[i] - (x[k] - x[l]) + d += 1 + if l == j: + s += (x[k] - x[l]) - b[i] + d += 1 + + if d != 0: + x_next[j] += (alpha / d) * s + + x = x_next + + return x, errors[:iteration+1] diff --git a/seismiqb/matching/functional.py b/seismiqb/matching/functional.py new file mode 100644 index 0000000..64a530e --- /dev/null +++ b/seismiqb/matching/functional.py @@ -0,0 +1,69 @@ +""" Functions used for matching tasks. """ +import numpy as np +from numba import njit + + + +def compute_correlation(array_0, array_1): + """ Correlation coefficient between two signals. Invariant to signal multiplication. """ + return (array_0 * array_1).mean() / (array_0.std() * array_1.std()) + +def compute_r2(array_0, array_1): + """ Determination coefficient between two signals. """ + return 1 - (((array_0 - array_1) ** 2).sum() / ((array_0 - array_0.mean()) ** 2).sum()) + + +def modify_trace(trace, shift=0, angle=0, gain=1): + """ Add a z-shift, phase shift and a gain multiplier to a trace. + + # TODO: can be optimized by a lot by passing (optional) `fft` of a trace. + + Parameters + ---------- + trace : np.ndarray + Signal to modify. + shift : number + Vertical shift to apply, measured in samples. Can be floating number: the trace resampled under the hood. + angle : number + Phase shift in degrees. Under the hood, the trace is FFT-shifted. + gain : number + Multiplier for trace values. + """ + # Phase shift + if abs(angle) >= 1: + fft = np.fft.rfft(trace) + fft *= np.exp(1.0j * np.deg2rad(angle)) + trace = np.fft.irfft(fft, n=len(trace)).astype(np.float32) + + # Depth shift + arange = np.arange(len(trace), dtype=np.float32) + trace = np.interp(arange, arange+shift, trace, left=0, right=0) + + # Gain: multiplier + trace = trace * gain + return trace + + +def minimize_proxy(x, trace_0, trace_1, metric='correlation'): + """ Proxy function for computing loss for the task of matching two traces with supplied metric. """ + # x is a 3-element array of (shift, angle, gain) + shift, angle, gain = x + _ = angle + modified_trace_1 = modify_trace(trace_1, shift=shift, angle=angle, gain=gain) + + if metric == 'correlation': + loss = -compute_correlation(trace_0, modified_trace_1) + elif metric == 'r2': + loss = -compute_r2(trace_0, modified_trace_1) + return loss + + +@njit +def compute_shifted_traces(trace, shifts): + """ Make an array with shifted `trace` for each `shift`. """ + buffer = np.empty((shifts.size, trace.size), dtype=np.float32) + arange = np.arange(len(trace), dtype=np.float32) + + for i, shift in enumerate(shifts): + buffer[i] = np.interp(arange, arange + shift, trace) + return buffer diff --git a/seismiqb/matching/intersection.py b/seismiqb/matching/intersection.py new file mode 100644 index 0000000..634c420 --- /dev/null +++ b/seismiqb/matching/intersection.py @@ -0,0 +1,830 @@ +""" Intersections between fields. """ +from textwrap import dedent + +import numpy as np +import scipy +import matplotlib.pyplot as plt + +from .functional import compute_correlation, compute_r2, modify_trace, minimize_proxy, compute_shifted_traces +from ..plotters import plot + + +def prepare_field(field): + """ Cache CDP values in a field as np.ndarray. """ + if getattr(field, 'cdp_values', None) is None: + field.cdp_values = field.geometry.headers[['CDP_X', 'CDP_Y']].values + return field + + +class Intersection: + """ Base class to describe an intersection between two fields. + + The usual workflow is to create an instance by :meth:`.new`, which finds one or multiple intersections between + two fields, then match extracted traces (that are padded / aggregated across multiple close indices) with either + analytic or optimization algorithms. Finally, use visualization tools to display interesting properties. + """ + @classmethod + def new(cls, field_0, field_1, limits=slice(None), pad_width=0, threshold=10, use_std=False, unwrap=True): + """ Create one or more instances of intersection classes with automatic class selection. + Preferred over directly instantiating objects. + """ + is_2d_0 = 1 in field_0.spatial_shape + is_2d_1 = 1 in field_1.spatial_shape + if is_2d_0 and is_2d_1: + return Intersection2d2d.new(field_0, field_1, limits=limits, pad_width=pad_width, + threshold=threshold, use_std=use_std, unwrap=unwrap) + + return Intersection2d3d(field_0, field_1) + + +class Intersection2d2d: + """ Intersection between two 2D fields. """ + @classmethod + def new(cls, field_0, field_1, limits=slice(None), pad_width=20, threshold=10, use_std=False, unwrap=True): + """ Create one or more instances of intersection. + Preferred over directly instantiating objects. + """ + prepare_field(field_0) + prepare_field(field_1) + + values_0 = field_0.cdp_values + values_1 = field_1.cdp_values + + bbox_0 = np.sort(values_0[[0, -1]].T, axis=-1) + bbox_1 = np.sort(values_1[[0, -1]].T, axis=-1) + + overlap = np.maximum(bbox_0[:, 0], bbox_1[:, 0]), np.minimum(bbox_0[:, 1], bbox_1[:, 1]) + if (overlap[1] - overlap[0]).min() < 0: + return False if unwrap else [] + + # pylint: disable=import-outside-toplevel + from shapely import LineString, MultiLineString, MultiPoint, GeometryCollection + # TODO: improve and describe edge cases + line_0 = LineString(values_0) + line_1 = LineString(values_1) + + intersection = line_0.intersection(line_1) + if isinstance(intersection, (MultiLineString, MultiPoint, GeometryCollection)): + # intersection = intersection.geoms[0] + points = [list(zip(*geometry.xy)) for geometry in intersection.geoms] + points = sum(points, []) + else: + points = list(zip(*intersection.xy)) + + result = [] + for point in points: + trace_idx_0 = ((values_0 - point) ** 2).sum(axis=-1).argmin() + trace_idx_1 = ((values_1 - point) ** 2).sum(axis=-1).argmin() + + trace_idx_0 = cls.adjust_index(field_0, trace_idx_0, use_std=use_std) + trace_idx_1 = cls.adjust_index(field_1, trace_idx_1, use_std=use_std) + if trace_idx_0 is False or trace_idx_1 is False: + continue + + instance = cls(field_0=field_0, field_1=field_1, + trace_idx_0=trace_idx_0, trace_idx_1=trace_idx_1, + limits=limits, pad_width=pad_width) + + if not any(other.is_similar(instance, threshold=threshold) for other in result): + result.append(instance) + + if not result: + return False if unwrap else [] + return result[0] if len(result) == 1 and unwrap else result + + @staticmethod + def adjust_index(field, trace_idx, n=3, use_std=False): + """ Move the trace index to one of the neighboring in case of dead trace at the `trace_idx`. """ + nhalf = (n - 1) // 2 + indices = list(range(max(0, trace_idx - nhalf), min(trace_idx + nhalf + 1, field.n_traces))) + + if use_std: + trace_data = field.geometry.load_by_indices(indices) + trace_std = trace_data.std(axis=1) + argmax_std = np.argmax(trace_std) + + if trace_std[argmax_std] == 0: + return False + return indices[argmax_std] + + dead_traces = field.geometry.dead_traces_matrix.reshape(-1)[indices] + argmin = np.argmin(dead_traces) + if dead_traces[argmin] is True: + return False + return indices[argmin] + + + def __init__(self, field_0, field_1, trace_idx_0, trace_idx_1, + limits=slice(None), pad_width=0, n=1, transform=None): + prepare_field(field_0) + prepare_field(field_1) + + self.field_0, self.field_1 = field_0, field_1 + self.trace_idx_0, self.trace_idx_1 = trace_idx_0, trace_idx_1 + self.limits = limits + self.pad_width = pad_width + self.n = n + self.transform = transform + self.max_depth = int(max(field_0.depth * field_0.sample_interval + field_0.delay, + field_1.depth * field_1.sample_interval + field_1.delay) + 1) + + # Compute distance + self.coordinates_0 = field_0.cdp_values[trace_idx_0] + self.coordinates_1 = field_1.cdp_values[trace_idx_1] + self.distance = ((self.coordinates_0 - self.coordinates_1).astype(np.float64) ** 2).sum() ** (1 / 2) + + self.matching_results = None + + def is_similar(self, other, threshold=10): + """ Check if other intersection is close index-wise. """ + if abs(self.trace_idx_0 - other.trace_idx_0) <= threshold and \ + abs(self.trace_idx_1 - other.trace_idx_1) <= threshold: + return True + return False + + + def to_dict(self, precision=3): + """ Represent intersection parameters (including computed matching values) as a dictionary. """ + intersection_dict = { + 'field_0_name': self.field_0.name, + 'field_1_name': self.field_1.name, + 'distance': self.distance, + } + + if self.matching_results is not None: + intersection_dict.update(self.matching_results) + + for key, value in intersection_dict.items(): + if isinstance(value, (float, np.floating)): + intersection_dict[key] = round(value, precision) + return intersection_dict + + + # Data + def prepare_traces(self, limits=None, index_shifts=(0, 0), pad_width=None, n=1, transform=None): + """ Prepare traces from both intersecting fields. + Under the hood, we load traces, pad to max depth, slice with `limits` and add additional `pad_width`. + Also, we average over `n` traces at loading to reduce noise. + """ + limits = limits if limits is not None else self.limits + pad_width = pad_width if pad_width is not None else self.pad_width + n = n if n is not None else self.n + transform = transform if transform is not None else self.transform + + trace_0 = self._prepare_trace(self.field_0, index=self.trace_idx_0 + index_shifts[0], + limits=limits, pad_width=pad_width, n=n, transform=transform) + trace_1 = self._prepare_trace(self.field_1, index=self.trace_idx_1 + index_shifts[1], + limits=limits, pad_width=pad_width, n=n, transform=transform) + return trace_0, trace_1 + + def _prepare_trace(self, field, index, limits=None, pad_width=None, n=1, transform=None): + # TODO: add taper + # Load data + nhalf = (n - 1) // 2 + indices = list(range(index - nhalf, index + nhalf + 1)) + traces = field.geometry.load_by_indices(indices) + trace = np.mean(traces, axis=0) + + # Resample to ms + arange = np.arange(trace.size, dtype=np.float32) + arange_ms = np.arange(trace.size, step=(1 / field.sample_interval), dtype=np.float32) + trace = np.interp(arange_ms, arange, trace, left=0, right=0) + + # Adjust for field delay: move the start of the trace to 0ms level + trace = np.pad(trace, (field.delay, 0)) if field.delay >= 0 else trace[-field.delay:] + + # Pad/slice + if trace.size < self.max_depth: + trace = np.pad(trace, (0, self.max_depth - trace.size)) + trace = trace[limits] + if pad_width > 0: + trace = np.pad(trace, pad_width) + + if transform is not None: + trace = transform(trace) + return trace + + + def prepare_horizons(self): + """ Prepare mappings from horizon name to its depth on intersection for both fields. """ + return (self._prepare_horizons(field=self.field_0, coordinates=self.coordinates_0), + self._prepare_horizons(field=self.field_1, coordinates=self.coordinates_1)) + + @staticmethod + def _prepare_horizons(field, coordinates): + horizon_to_depth = {} + for horizon_name, horizon_ixd in field.horizons.items(): + distances = ((horizon_ixd[:, :2] - coordinates) ** 2).sum(axis=1) ** (1 / 2) + idx = np.argmin(distances) + horizon_to_depth[horizon_name] = horizon_ixd[idx, -1] + return horizon_to_depth + + + # Matching algorithms + def match_traces(self, method='analytic', **kwargs): + """ Selector for matching method. + Refer to the documentation of :meth:`match_traces_analytic` and :meth:`match_traces_optimize` for details. + + TODO: add `mixed` mode, where we select the initial point by `analytic` method and then use optimization + procedure to find the exact location. + """ + if method in {'analytic'}: + matching_results = self.match_traces_analytic(**kwargs) + elif method in {'optimize'}: + matching_results = self.match_traces_optimize(**kwargs) + else: + matching_results = self.match_on_horizon(**kwargs) + + matching_results['petrel_corr'] = (matching_results['corr'] + 1) / 2 + if getattr(self, 'key'): + matching_results['key'] = self.key + self.matching_results = matching_results + return matching_results + + + def match_traces_optimize(self, limits=None, index_shifts=(0, 0), pad_width=None, n=1, transform=None, + init_shifts=range(-100, +100), init_angles=(0,), metric='r2', + bounds_shift=(-150, +150), bounds_angle=None, bounds_gain=(0.9, 1.1), + maxiter=100, eps=1e-6, **kwargs): + """ Match traces by iterative optimization of the selected loss function. + Slower, than :meth:`match_traces_analytic`, but allows for finer control. + + We use every combination of parameters in `init_shifts` and `init_angles` as + the starting point for optimization. This way, we try to avoid local minima, improving the result by a lot. + The optimization is bounded: `bounds_*` parameters allow to control the spread of possible values. + """ + _ = kwargs + + # Load data + trace_0, trace_1 = self.prepare_traces(limits=limits, index_shifts=index_shifts, + pad_width=pad_width, n=n, transform=transform) + + # For each element in init, perform optimize + minimize_results = [] + for init_shift in init_shifts: + for init_angle in init_angles: + bounds_angle_ = bounds_angle or (init_angle-eps, init_angle+eps) + minimize_result = scipy.optimize.minimize(fun=minimize_proxy, + x0=np.array([init_shift, init_angle, 1.0]), + args=(trace_0, trace_1, metric), + bounds=(bounds_shift, bounds_angle_, bounds_gain), + method='SLSQP', + options={'maxiter': maxiter, + 'ftol': 1e-6, 'eps': 1e-3}) + minimize_results.append(minimize_result) + minimize_results = np.array([(item.fun, *item.x) for item in minimize_results]) + + # Find the best result + argmin = np.argmin(minimize_results[:, 0]) + best_loss, best_shift, best_angle, best_gain = minimize_results[argmin] + if metric == 'correlation': + best_gain = self.compute_gain(data_0=trace_0, data_1=trace_1) + + best_corr = compute_correlation(trace_0, + modify_trace(trace_1, shift=best_shift, angle=best_angle, gain=best_gain)) + + return { + 'corr': best_corr, + 'shift': best_shift, + 'angle': best_angle, + 'gain': best_gain, + 'loss': best_loss, + } + + + def match_traces_analytic(self, limits=None, index_shifts=(0, 0), pad_width=None, n=1, transform=None, + twostep=False, twostep_margin=10, + max_shift=100, resample_factor=10, taper=True, + apply_correction=False, correction_step=3, return_intermediate=False, **kwargs): + """ Match traces by using analytic formulae. + Bishop, Nunns "`Correcting amplitude, time, and phase mis-ties in seismic data + `_" + Fast, but rather unflexible. + + Under the hood, the algorithm works as follows: + - we compute possible shifts with possibly non-whole numbers (`resample_factor`) + - compute correlation for each possible shift, resulting in cross-correlation function + - compute envelope and instantaneous phase of the cross-correlation + - argmax of the envelope is the optimal shift, and the phase at this shift is the optimal angle. + Essentially, this is equivalent to finding the best combination of the trace and its analytic counterpart, + which conveniently coincide with vertical and phase shifts. + """ + _ = kwargs + + # Load data + trace_0, trace_1 = self.prepare_traces(limits=limits, index_shifts=index_shifts, + pad_width=pad_width, n=n, transform=transform) + + # Prepare array of tested shifts + if twostep: + # Compute approximate `shift` to narrow the interval + shifts = np.linspace(-max_shift, max_shift, 2*max_shift + 1, dtype=np.float32) + shift = self._match_traces_analytic(trace_0=trace_0, trace_1=trace_1, shifts=shifts, taper=taper, + apply_correction=apply_correction, correction_step=correction_step, + return_intermediate=False)['shift'] + shifts = np.linspace(shift - twostep_margin, shift + twostep_margin, + 2*twostep_margin*resample_factor + 1, dtype=np.float32) + else: + shifts = np.linspace(-max_shift, max_shift, 2*max_shift*resample_factor + 1, dtype=np.float32) + + # Compute `shift` with required precision + matching_results = self._match_traces_analytic(trace_0=trace_0, trace_1=trace_1, shifts=shifts, + taper=taper, apply_correction=apply_correction, + correction_step=correction_step, + return_intermediate=return_intermediate) + + matching_results['corr'] = self.evaluate(shift=matching_results['shift'], + angle=matching_results['angle'], + gain=matching_results['gain'], + pad_width=pad_width, limits=limits, n=n) + return matching_results + + def _match_traces_analytic(self, trace_0, trace_1, shifts, + taper=True, apply_correction=False, correction_step=3, return_intermediate=False): + # Compute metrics for each shift on a resampled grid + # TODO: fix nan/inf values in case of short windows and large `max_shift`` + shifted_traces = compute_shifted_traces(trace=trace_1, shifts=shifts) + metrics = (trace_0 * shifted_traces).mean(axis=1) / (trace_0.std() * shifted_traces.std(axis=1)) + + # Compute envelope and phase of metrics + analytic_signal = scipy.signal.hilbert(metrics) + envelope = np.abs(analytic_signal) + instantaneous_phase = np.angle(analytic_signal) + instantaneous_phase = np.rad2deg(instantaneous_phase) + + # Optional taper + if taper: + taper = 0.1 if taper is True else taper + lentaper = int(taper * envelope.size) + taper = np.hanning(lentaper) + envelope[:lentaper // 2] *= taper[:lentaper // 2] + envelope[-lentaper // 2:] *= taper[-lentaper // 2:] + # envelope *= np.hanning(envelope.size) + + # Find the best shift and compute its relative quality + idx = np.argmax(envelope) + + # Optional correction: parabolic interpolation in the neighborhood of a maxima + if apply_correction is False: + shift = shifts[idx] + angle = instantaneous_phase[idx] + else: + # TODO: refactor / rethink + correction = ((metrics[idx-correction_step] - metrics[idx+correction_step]) / + (2*metrics[idx-correction_step] - 4*metrics[idx] + 2*metrics[idx+correction_step])) + quality = metrics[idx]\ + - 0.25 * (((metrics[idx-correction_step] - metrics[idx+correction_step]) * correction) / + (np.linalg.norm(trace_0) * np.linalg.norm(trace_1))) + _ = quality + + # Shift: correct according to values to the sides of maximum + corrected_idx = int(idx + correction) + shift = shifts[corrected_idx] + + # Angle: correct according to values to the sides of maximum + p0 = instantaneous_phase[idx] + p1 = instantaneous_phase[idx+correction_step] if correction >= 0 else \ + instantaneous_phase[idx-correction_step] + if p1 - p0 > 180: + p1 = p1 - 360 + elif p1 - p0 < -180: + p1 = p1 + 360 + angle = p0 + ((p1 - p0) * correction if correction >= 0 else (p0 - p1) * correction) + + gain = self.compute_gain(data_0=trace_0, data_1=trace_1) + + matching_results = { + 'shift': shift, + 'angle': angle, + 'gain': gain, + } + + if return_intermediate: + matching_results.update({ + 'trace_0': trace_0, + 'trace_1': trace_1, + 'shifts': shifts, + 'metrics': metrics, + 'envelope': envelope, + 'instantaneous_phase': instantaneous_phase, + }) + return matching_results + + + def match_on_horizon(self, horizon_name=None, **kwargs): + """ Use horizon picks to determine necessary corrections on intersection. + Note that it actually computes only the vertical mistie; angle is left at 0 and gain is the RMS ratio. + """ + horizon_to_depth_0, horizon_to_depth_1 = self.prepare_horizons() + + if horizon_name is None: + common_horizons = set(horizon_to_depth_0.keys()) & set(horizon_to_depth_1.keys()) + if len(common_horizons) == 1: + horizon_name = common_horizons.pop() + else: + raise ValueError('Provide horizon name for matching!') + + depth_0 = horizon_to_depth_0[horizon_name] + depth_1 = horizon_to_depth_1[horizon_name] + + shift = depth_0 - depth_1 + angle = 0.0 + gain = self.compute_gain() + corr = self.evaluate(shift=shift, angle=angle, gain=gain) + return { + 'shift': shift, + 'angle': angle, + 'gain': gain, + 'corr': corr + } + + def compute_gain(self, data_0=None, data_1=None, **kwargs): + """ Compute gain by as ratio between RMS data values. """ + if data_0 is None and data_1 is None: + data_0, data_1 = self.prepare_traces(**kwargs) + return (data_0**2).mean() ** (1/2) / (data_1**2).mean() ** (1/2) + + + def evaluate(self, shift=0, angle=0, gain=1, metric='correlation', + pad_width=None, limits=None, n=1, transform=None, **kwargs): + """ Compute provided metric with a given mistie parameters. """ + trace_0, trace_1 = self.prepare_traces(pad_width=pad_width, limits=limits, n=n, transform=transform) + metric_function = compute_correlation if metric == 'correlation' else compute_r2 + return metric_function(trace_0, modify_trace(trace_1, shift=shift, angle=angle, gain=gain)) + + def compute_horizon_metric(self, horizon_name=None, shift=0, **kwargs): + """ Compute the difference between horizon matching and suggested shift. """ + horizon_matching = self.match_on_horizon(horizon_name=horizon_name) + return np.abs(horizon_matching['shift'] - shift) + + def get_correction(self): + """ Get corrections from field. Used to see how intersection would behave after field corrections applied. """ + dict_0 = self.field_0.correction_results + dict_1 = self.field_1.correction_results + + shift = dict_0['shift'] - dict_1['shift'] + angle = dict_0['angle'] - dict_1['angle'] + gain = np.exp(np.log(dict_0['gain']) - np.log(dict_1['gain'])) + corr = self.evaluate(shift=shift, angle=angle, gain=gain) + return { + 'shift': shift, + 'angle': angle, + 'gain': gain, + 'corr': corr + } + + + # Visualization + def __repr__(self): + return (f'') + + def __str__(self): + return dedent(f""" + Intersection of "{self.field_0.short_name}.sgy" and "{self.field_1.short_name}.sgy" + distance {self.distance:4.2f} m + trace_idx_0 {self.trace_idx_0} + trace_idx_1 {self.trace_idx_1} + coordinates_0 {self.coordinates_0.tolist()} + coordinates_1 {self.coordinates_1.tolist()} + key {getattr(self, 'key', None)} + """).strip() + + def show_curves(self, method='analytic', limits=None, index_shifts=(0, 0), pad_width=None, n=1, transform=None, + shift=0, angle=0, gain=1, + max_shift=100, resample_factor=10, apply_correction=False, n_plots=3, **kwargs): + """ Display traces, cross-correlation vs shift and phase vs shift graphs. """ + # Get matching results with all the intermediate variables + matching_results = self.match_traces(method=method, + limits=limits, index_shifts=index_shifts, + pad_width=pad_width, n=n, transform=transform, + max_shift=max_shift, resample_factor=resample_factor, + apply_correction=apply_correction, + return_intermediate=True) + + trace_0, trace_1 = matching_results['trace_0'], matching_results['trace_1'] + trace_1 = modify_trace(trace_1, shift=shift, angle=angle, gain=gain) + shifts, metrics, envelope, instantaneous_phase = (matching_results['shifts'], + matching_results['metrics'], + matching_results['envelope'], + matching_results['instantaneous_phase']) + + # Prepare plotter parameters + limits = limits or self.limits + pad_width = pad_width or self.pad_width + start_tick = (limits.start or 0) - pad_width + ticks = np.arange(start_tick, start_tick + len(trace_0)) + + kwargs = { + 'title': [f'traces of "{self.field_0.short_name}.sgy" x "{self.field_1.short_name}.sgy"' + f'\n{shift=:3.3f} {angle=:3.3f} {gain=:3.3f}', + 'cross-correlation', 'instantaneous phase'], + 'label': [['trace_0', 'trace_1'], ['crosscorrelation', 'envelope'], 'instant phases'], + 'xlabel': ['depth', 'shift', 'shift'], 'xlabel_size': 16, + 'ylabel': ['amplitude', 'metric', 'phase (degrees)'], + 'xlim': [(start_tick, start_tick + len(trace_0)), + (-max_shift, +max_shift), + (-max_shift, +max_shift)], + 'ratio': 0.8, + **kwargs + } + + plotter = plot([[(ticks, trace_0), (ticks, trace_1)], + [(shifts, metrics), (shifts, envelope)], + [(shifts, instantaneous_phase)]][:n_plots], + mode='curve', **kwargs) + + # Add more annotations + shift = matching_results['shift'] + angle = matching_results['angle'] + corr = matching_results['corr'] + if n_plots >= 2: + plotter[1].ax.axvline(shift, linestyle='--', alpha=0.9, color='green') + plotter[1].add_legend(mode='curve', label=f'optimal shift: {shift:4.3f}', + alpha=0.9, color='green') + plotter[1].ax.axhline(corr, linestyle='--', alpha=0.9, color='red') + plotter[1].add_legend(mode='curve', label=f'max correlation: {corr:4.3f}', + alpha=0.9, color='red') + if n_plots >= 3: + plotter[2].ax.axvline(shift, linestyle='--', alpha=0.9, color='green') + plotter[2].add_legend(mode='curve', label=f'optimal angle: {angle:4.3f}') + return plotter + + + def show_lines(self, figsize=(14, 8), colors=('b', 'r'), arrow_step=20, arrow_size=30, savepath=None, show=True): + """ Display shot lines on a 2d graph in CDP coordinates. """ + fig, ax = plt.subplots(figsize=figsize) + + # Data + for field, color in zip([self.field_0, self.field_1], colors): + values = field.geometry.headers[['CDP_X', 'CDP_Y']].values + x, y = values[:, 0], values[:, 1] + ax.plot(x, y, color, label=field.short_name) + + idx = x.size // 2 + ax.annotate('', size=arrow_size, + xytext=(x[idx-arrow_step], y[idx-arrow_step]), + xy=(x[idx+arrow_step], y[idx+arrow_step]), + arrowprops=dict(arrowstyle="->", color=color)) + + # Annotations + ax.set_title(f'"{self.field_0.short_name}.sgy" and "{self.field_1.short_name}.sgy"', fontsize=26) + ax.set_xlabel('CDP_X', fontsize=22) + ax.set_ylabel('CDP_Y', fontsize=22) + ax.legend(prop={'size' : 22}) + ax.grid() + fig.tight_layout() + + if savepath: + fig.savefig(savepath, dpi=100, facecolor='white') + if show: + fig.show() + else: + plt.close(fig) + + + def show_metric_surface(self, metric='correlation', + limits=None, index_shifts=(0, 0), pad_width=None, n=1, transform=None, + shifts=range(-20, +20+1, 1), angles=range(-180, +180+1, 30), + figsize=(14, 8), cmap='seismic', levels=7, grid=True): + """ Display metric values as a function of shift and angle. """ + # Compute metric matrix: metric value for each combination of shift and angle + trace_0, trace_1 = self.prepare_traces(limits=limits, index_shifts=index_shifts, + pad_width=pad_width, n=n, transform=transform) + metric_function = compute_correlation if metric == 'correlation' else compute_r2 + + metric_matrix = np.empty((len(shifts), len(angles))) + for i, shift in enumerate(shifts): + for j, angle in enumerate(angles): + modified_trace_1 = modify_trace(trace_1, shift=shift, angle=angle) + + metric_matrix[i, j] = metric_function(trace_0, modified_trace_1) + + # Show contourf and contour + fig, ax = plt.subplots(1, figsize=figsize) + img = ax.contourf(angles, shifts, metric_matrix, cmap=cmap, levels=levels) + fig.colorbar(img) + + contours = ax.contour(angles, shifts, metric_matrix, levels=levels, colors='k', linewidths=0.4) + ax.clabel(contours, contours.levels, inline=True, fmt=lambda x: f'{x:2.1f}', fontsize=10) + + ax.set_title('METRIC SURFACE', fontsize=20) + ax.set_xlabel('PHASE (DEGREES)', fontsize=16) + ax.set_ylabel('SHIFT (MS)', fontsize=16) + ax.grid(grid) + fig.show() + + + def show_neighborhood(self, max_index_shift=7, limits=None, pad_width=None, n=1, transform=None, + max_shift=10, resample_factor=10): + """ Compute matching on all neighboring traces. """ + # Prepare data + k = max_index_shift * 2 + 1 + matrix = np.empty((k, k), dtype=np.float32) + iterator = range(-max_index_shift, max_index_shift + 1) + for i, index_shift_1 in enumerate(iterator): + for j, index_shift_2 in enumerate(iterator): + matching_results = self.match_traces_analytic(index_shifts=(index_shift_1, index_shift_2), + limits=limits, pad_width=pad_width, n=n, + transform=transform, + max_shift=max_shift, resample_factor=resample_factor) + matrix[i, j] = matching_results['corr'] + + # Visualize + value = matrix[max_index_shift, max_index_shift] + delta = max(matrix.max() - value, value - matrix.min()) + vmin, vmax = value - delta, value + delta + + return plot(matrix, colorbar=True, cmap='seismic', + title='Correlation values for neighbouring indices of intersection', + vmin=vmin, vmax=vmax, + extent=(-max_index_shift, +max_index_shift, + -max_index_shift, +max_index_shift)) + + + def show_composite_slide(self, sides=(0, 0), horizon_width=3, + limits=None, gap_width=1, gap_value=None, pad_width=None, transform=None, + shift=0, angle=0, gain=1, width='auto', title_prefix='', **kwargs): + """ Display sides of shot lines on one plot. """ + limits = limits if limits is not None else self.limits + pad_width = pad_width if pad_width is not None else self.pad_width + transform = transform if transform is not None else self.transform + + # Make combined slide + combined_slide, slide_0, slide_1 = self._prepare_combined_slide(sides=sides, data='field', + shift=shift, angle=angle, gain=gain, + limits=limits, gap_width=gap_width, + gap_value=gap_value, width=width, + pad_width=pad_width, transform=transform) + data = [combined_slide] + cmap = ['Greys_r'] + + mask_slide = self._prepare_combined_slide(sides=sides, data='labels', + shift=shift, angle=0, gain=1., + horizon_width=horizon_width, + limits=limits, gap_width=gap_width, gap_value=gap_value, width=width, + pad_width=pad_width, transform=transform)[0].astype(np.bool_) + data.append(mask_slide) + cmap.append('magenta') + + # Compute correlation on traces + correlation = kwargs.get('corr', compute_correlation(slide_0[-1], slide_1[0])) + + # Prepare plotter parameters + start_tick = (limits.start or 0) - pad_width + extent = (0, combined_slide.shape[0], start_tick + combined_slide.shape[1], start_tick) + + title = (f'"{self.field_0.short_name}.sgy":{sides[0]} x "{self.field_1.short_name}.sgy":{sides[1]}\n' + f'{shift=:3.2f} {angle=:3.1f} {gain=:3.3f}\n' + f'{correlation=:3.2f} corrected_correlation={(1 + correlation)/2:3.2f}') + if title_prefix is not None: + title = title_prefix + '\n' + title + + kwargs = { + 'cmap': cmap, + 'colorbar': True, + 'title': title, 'title_fontsize': 14, + 'extent': extent, + 'augment_mask': True, + 'labelright': False, 'labeltop': False, + **kwargs + } + return plot(data, **kwargs) + + def _prepare_combined_slide(self, sides, data='field', horizon_width=5, shift=0, angle=0, gain=1, + limits=None, width='auto', gap_width=1, gap_value=None, pad_width=None, + n=1, transform=None): + # Load data and orient it in a correct way + slide_0 = self._prepare_slide(self.field_0, self.trace_idx_0, sides[0], horizon_width=horizon_width, + data=data, limits=limits, pad_width=pad_width, transform=transform) + slide_1 = self._prepare_slide(self.field_1, self.trace_idx_1, sides[1], horizon_width=horizon_width, + data=data, limits=limits, pad_width=pad_width, transform=transform) + + if sides == (0, 0): + slide_1 = slide_1[::-1] + elif sides == (0, 1): + pass + elif sides == (1, 0): + slide_0 = slide_0[::-1] + slide_1 = slide_1[::-1] + elif sides == (1, 1): + slide_0 = slide_0[::-1] + + # Apply modifications to the right side + for c in range(slide_1.shape[0]): + slide_1[c] = modify_trace(slide_1[c], shift=shift, angle=angle, gain=gain) + + # Slice to limits. Done after the modification so that there is no empty areas on top/bottom of the image + slide_0 = slide_0[:, limits] + slide_1 = slide_1[:, limits] + + # Combine slides into one composite + width = slide_0.shape[1] if width == 'auto' else width + halfwidth = width//2 if width is not None else max(len(slide_0), len(slide_1)) + fv = gap_value if gap_value is not None else min(slide_0.min(), slide_1.min()) + + combined_slide = np.concatenate([slide_0[-halfwidth:], + np.full((gap_width, slide_0.shape[1]), fill_value=fv, dtype=np.float32), + slide_1[:+halfwidth]], axis=0) + return combined_slide, slide_0, slide_1 + + def _prepare_slide(self, field, trace_idx, side, data='field', horizon_width=5, + limits=None, pad_width=None, n=1, transform=None): + # Load data + if data == 'field': + slide = field.load_slide(0) + else: + slide = np.zeros(field.shape[1:], dtype=np.float32) + for horizon in getattr(field, 'horizon_instances', {}).values(): + slide += horizon.load_slide(0, width=horizon_width) + + slide = slide[:trace_idx + 1] if side == 0 else slide[trace_idx:] + + # Resample to ms + arange = np.arange(slide.shape[1], dtype=np.float32) + arange_ms = np.arange(slide.shape[1], step=(1 / field.sample_interval), dtype=np.float32) + arange_ms += field.delay / field.sample_interval if data != 'field' else 0 + interpolator = lambda trace: np.interp(arange_ms, arange, trace, left=0, right=0) + slide = np.apply_along_axis(interpolator, 1, slide) + + # Pad to adjust for field delays + slide = np.pad(slide, ((0, 0), (field.delay, 0))) if field.delay > 0 else slide[:, -field.delay:] + + # Pad to the same depth + slide = np.pad(slide, ((0, 0), (0, self.max_depth - slide.shape[1]))) + + + # Additional padding + slide = np.pad(slide, ((0, 0), (pad_width, pad_width))) + return slide + + def compare_composite_slides(self, sides=(0, 0), horizon_width=5, + limits=None, gap_width=1, gap_value=None, pad_width=None, transform=None, + shift=0, angle=0, gain=1, width='auto', figsize=(14, 20), **kwargs): + """ Display composite slides over intersection with and without corrections side-by-side. """ + _, ax = plt.subplots(1, 2, figsize=figsize) + self.show_composite_slide(sides=sides, horizon_width=horizon_width, + limits=limits, gap_width=gap_width, gap_value=gap_value, + pad_width=pad_width, transform=transform, + width=width, axes=ax[0], adjust_figsize=False, **kwargs) + + self.show_composite_slide(sides=sides, horizon_width=horizon_width, + limits=limits, gap_width=gap_width, gap_value=gap_value, + pad_width=pad_width, transform=transform, + shift=shift, angle=angle, gain=gain, + width=width, axes=ax[1], adjust_figsize=False, **kwargs) + plt.show() + + def compare_methods(self, sides=(0, 0), horizon_width=5, limits=None, gap_width=1, gap_value=None, + analytic_kwargs=None, optimize_kwargs=None, + pad_width=None, transform=None, width='auto', layout=None, figsize=(14, 20), **kwargs): + """ !!. """ + if getattr(self.field_0, 'correction_results', None) and getattr(self.field_1, 'correction_results', None): + n_plots = 4 + else: + n_plots = 3 + + layout = layout if layout is not None else (1, n_plots) + _, ax = plt.subplots(*layout, figsize=figsize) + ax = np.array(ax).flatten() + + # Graph 1: original slides + self.show_composite_slide(sides=sides, horizon_width=horizon_width, + limits=limits, gap_width=gap_width, gap_value=gap_value, + pad_width=pad_width, transform=transform, + title_prefix='original data', + width=width, axes=ax[0], adjust_figsize=False, **kwargs) + + # Graph 2: analytic method + analytic_kwargs = analytic_kwargs if analytic_kwargs is not None else {} + matching_dict = self.match_traces_analytic(**analytic_kwargs) + self.show_composite_slide(sides=sides, horizon_width=horizon_width, + limits=limits, gap_width=gap_width, gap_value=gap_value, + pad_width=pad_width, transform=transform, + **matching_dict, title_prefix='method=`analytic`', + width=width, axes=ax[1], adjust_figsize=False, **kwargs) + + # Graph 3: optimize method + optimize_kwargs = optimize_kwargs if optimize_kwargs is not None else {} + matching_dict = self.match_traces_optimize(**optimize_kwargs) + self.show_composite_slide(sides=sides, horizon_width=horizon_width, + limits=limits, gap_width=gap_width, gap_value=gap_value, + pad_width=pad_width, transform=transform, + **matching_dict, title_prefix='method=`optimize`', + width=width, axes=ax[2], adjust_figsize=False, **kwargs) + + if n_plots == 4: + matching_dict = self.get_correction() + self.show_composite_slide(sides=sides, horizon_width=horizon_width, + limits=limits, gap_width=gap_width, gap_value=gap_value, + pad_width=pad_width, transform=transform, + **matching_dict, title_prefix='method=`corrections`', + width=width, axes=ax[3], adjust_figsize=False, **kwargs) + + plt.show() + + + + +class Intersection2d3d: + """ TODO. """ diff --git a/seismiqb/matching/well_seismic_tie.py b/seismiqb/matching/well_seismic_tie.py new file mode 100644 index 0000000..28b8c72 --- /dev/null +++ b/seismiqb/matching/well_seismic_tie.py @@ -0,0 +1,1305 @@ +""" !!. """ +from copy import deepcopy +import numpy as np +import pandas as pd + +from scipy.signal import ricker, find_peaks, fftconvolve +from scipy.optimize import minimize +from scipy.linalg import toeplitz +from sklearn.linear_model import Ridge + +from ..geometry import array_to_segy +from ..plotters import plot + + + + +class WellSeismicMatcher: + """ Controller class for the process of well-seismic tie. + + At initialization, we extract `seismic_trace` from the provided `field` and process `well` in a way to obtain + values of `well_times`, `well_impedance` and `well_reflectivity`: only this information is required from input data. + An initial estimate of a wavelet is computed by :meth:`process_well`. + + After that, we use the concept of `state` to describe the state of well-seismic tie at each given step. + Essentially, each state is a dict with required `well_times` and `wavelet` keys: they completely + identify matching at any given stage and allow to visualize it or introspect in any other way. + Other keys can be used to store important info about operation that created this state. + + The first state should be created manually by :meth:`init_state` that takes an original `well_times`, + inferred at initialization, and a wavelet (most probably computed by :meth:`extract_wavelet`). + Methods that alter well-seismic tie automatically store their updated state to the `states` attribute, + and each subsequent call works of the selected (usually, the last) previous state. + + The usual pipeline of using this class looks like this: + - instance initialization, call of :meth:`process_well` with required parameters + - wavelet computation: either manual or :meth:`extract_wavelet` + - starting state initialization: :meth:`init_state` call with the computed wavelet + - t0 computation: :meth:`compute_t0` can be used to analytically compute t0 from elevations and speeds + or to guess it by optimizing cross correlation function between synthetic and real traces + - stretching and squeezing of `well_times`: by using either method of optimization, we change `well times` to + better tie the synthetic and real seismic traces. + Currently available methods are :meth:`optimize_extremas` and :meth:`optimize_well_times_pytorch`. + + The last three items create one or more states, that are stored in the instance. + At any point, states can be exported or visualized by `save_*` and `show_*` methods. + + Implementation details + ---------------------- + Instance attributes do not change: `well_times` attribute always points to the well times from the LAS file itself. + Everything time-related is stored in seconds. Other logs are unchanged. + Most of the utility methods are written in a way to accept `(**state)` as an argument. + + TODO: DTW optimization method; rethink resampling; better deterministic wavelet; + + Attributes + ---------- + well_times : np.array + Initial well times in seconds. + well_reflectivity : np.array + Well reflectivity values, indexed by MD. + seismic_times : np.array + Time values in seismic data in seconds. + seismic_trace : np.array + Seismic amplitudes, indexed by seismic times. + states : list + States describing well matching after given operation. + Each state is a dict with required `well_times` and `wavelet` keys. + """ + def __init__(self, well, field, coordinates): + # Well data + self.well = well + self.well_bounds = None + self.well_times = None + self.well_impedance = None + self.well_reflectivity = None + + # Seismic data: extract trace at well location + self.field = field + self.seismic_times = np.arange(0, field.depth, dtype=np.float32) * field.sample_interval * 1e-3 # seconds + self.seismic_trace = None + self.coordinates = None + + if coordinates is not None: + if isinstance(coordinates, dict): + coordinates = coordinates[self.well.name] + self.extract_seismic_trace(coordinates) + + self.states = [] + + + def extract_seismic_trace(self, coordinates): + """ Get data from a SEG-Y seismic data. + Should be overriden for custom algorithm of seismic times / seismic trace acquisition. + """ + # TODO: add averaging (copy from 2d matcher), add inclinometry warning + trace = self.field.geometry[coordinates[0], coordinates[1], :] + self.seismic_trace = trace + self.coordinates = coordinates + + + # Extended initialization + def process_well(self, impedance_log=None, recompute_ai=False, recompute_rhob=False, + filter_ai=False, filter_dt=False, filter_rhob=False): + """ Get data from a well with optional filtration. + Should be overriden for custom algorithm of well times / well reflectivity acquisition. + + Reflectivity is computed from an AI log. + If AI log is unavailable, it is recomputed from RHOB and DT logs. + If RHOB log is unavailable, it is recomputed from the DT log by Gardner's equation. + + Parameters + ---------- + impedance_log : str or None + If provided, then directly used for computation of reflectivity. + filter_* : bool, dict + If bool, then whether to apply filtration to a given log. + If dict, then parameters of the filtration. + `fs` parameter defaults to well sampling frequency. + recompute_* : bool + Whether to force recompute a given log. + """ + #pylint: disable=protected-access + fs = self.well.compute_sampling_frequency() + + # Sonic log, optionally filtered + dt_values = self.well.DT.values # us/ft + + if filter_dt: + filtration_parameters = { + 'order': 4, 'frequency': 30, 'btype': 'lowpass', 'fs': fs, + **(filter_dt if isinstance(filter_dt, dict) else {}), + } + dt_values = self.well._compute_filtered_log(dt_values, **filtration_parameters) + dt_values = np.nan_to_num(dt_values) + self.well['DT_FILTERED'] = dt_values + + # Prepare impedance log + if impedance_log is not None: + pass + elif 'AI' in self.well.keys and not recompute_ai: + impedance_log = 'AI' + else: + if recompute_rhob or 'RHOB' not in self.well.keys: + # Gardner's equation + vp = (0.3048 / dt_values) * 1e6 # m/s + self.well['RHOB_RECOMPUTED'] = 310 * (vp ** 0.25) # g/cm3 + rhob_log = 'RHOB_RECOMPUTED' + else: + rhob_log = 'RHOB' + + # Density values, optionally filtered + rhob_values = self.well[rhob_log].values + if filter_rhob: + filtration_parameters = { + 'order': 4, 'frequency': 30, 'btype': 'lowpass', 'fs': fs, + **(filter_rhob if isinstance(filter_rhob, dict) else {}), + } + rhob_values = self.well._compute_filtered_log(rhob_values, **filtration_parameters) + self.well['RHOB_FILTERED'] = rhob_values + + # Recomputed AI. Can omit unit conversions as they dont influence the reflectivity + self.well['AI_RECOMPUTED'] = rhob_values / (dt_values * 1e-6 / 0.3048) # kPa.s/m + impedance_log = 'AI_RECOMPUTED' + + # Filter impedance log + if filter_ai: + filtration_parameters = { + 'order': 4, 'frequency': 30, 'btype': 'lowpass', 'fs': fs, + **(filter_ai if isinstance(filter_ai, dict) else {}), + } + self.well['AI_FILTERED'] = self.well._compute_filtered_log(self.well[impedance_log], + **filtration_parameters) + impedance_log = 'AI_FILTERED' + + self.well.compute_reflectivity(impedance_log=impedance_log, name='R_RECOMPUTED') + + bounds = self.well.get_bounds(dt_values) + self.well_bounds = slice(bounds[0]-1, bounds[1]) + self.well_times = np.cumsum(dt_values[self.well_bounds]) * 1e-6 # seconds + self.well_impedance = self.well[impedance_log].values[self.well_bounds] + self.well_reflectivity = self.well['R_RECOMPUTED'].values[self.well_bounds] + + + def extract_wavelet(self, method='statistical', window=(1, 1), normalize=False, limits=slice(None), + taper=True, wavelet_length=61, state=-1, + smoothing=False, smoothing_length=7, smoothing_order=3, **kwargs): + """ Compute a wavelet by a chosen method. + Available methods are: + - `ricker` creates a fixed Ricker wavelet. Additional parameters are `a` for width. + - `ricker_f` creates a fixed Ricker wavelet. Additional parameters are `f` for peak frequency. + - `stats1` creates a wavelet with the same power spectrum as the one in seismic trace. + - `stats2` creates a wavelet with the same power spectrum as the one in autocorrelation of seismic trace. + - `stats3` creates a wavelet with the same power spectrum as the one in autocorrelation of seismic trace + with additional tapering. + - `division` creates a wavelet with the spectrum of divised spectras of reflectivity and seismic trace. + - `lstsq` computes an optimal wavelet by solving system of linear equations (~Wiegner). + + The last two wavelets should be used after initial well-seismic tie is already performed. + + TODO: add better deterministic wavelets. + + Parameters + ---------- + method : str + Which method to use for wavelet extraction. + normalize : bool + Whether to normalize output wavelet so that max value equals to 1. + taper : bool + Whether to apply taper to seismic trace / reflectivity before computations. + wavelet_length : int + Size of the wavelet. + smoothing : bool + Whether to apply smoothing to the power spectrum before IRFFT for statistical wavelets. + smoothing_length : int + Length of the smoothing kernel. + smoothing_order : int + Order of polynomial used for smoothing. + window : tuple of ints + Number of traces along each (inline/crossline) direction to use. + (1, 1) means that only the trace directly at well coordinates is used. + (3, 3) means that total of 9 traces centering at well coordinates are used. + limits : slice or None + If provided, then used to slice seismic trace(s) along depth dimension. + state : int, dict + If int, then the index of previous state to use. + If dict, then a state directly. + """ + # Prepare traces + c0, c1 = self.coordinates + window = np.clip(window, 0, self.field.spatial_shape) + k0, k1 = window + traces = self.field.geometry[c0 - k0//2 : c0 + (k0 - k0//2), c1 - k1//2 : c1 + (k1 - k1//2)] + traces = traces.reshape(-1, traces.shape[-1]) + traces = traces[:, limits] + trace = np.mean(traces, axis=0) + + if taper: + traces *= np.blackman(len(trace)) # TODO: taper selection, maybe? + lenhalf, wlenhalf, wlenflag = len(trace) // 2, wavelet_length // 2, wavelet_length % 2 + + # Optionally, prepare reflectivity + if method in {'lstsq', 'division'}: + state = state if isinstance(state, dict) else self.states[state] + reflectivity = self.resample_to_seismic(seismic_times=self.seismic_times, + well_times=state['well_times'], + well_data=np.nan_to_num(self.well_reflectivity))[limits] + if taper: + reflectivity *= np.blackman(len(trace)) + + # Create wavelet + if method == 'deterministic': + ... + elif method == 'ricker': + # Given `frequency`, one can compute width: a = geometry.sample_rate / (frequency * np.sqrt(2) * np.pi) + kwargs = {'points': wavelet_length, 'a': 4.5, **kwargs} + wavelet = ricker(**kwargs) + + elif method == 'ricker_f': + # ...or just use this method for wavelet creation + kwargs = {'f': 25, **kwargs} + f = kwargs['f'] + t = np.arange(wavelet_length) * self.field.sample_interval * 1e-3 + t -= t[wlenhalf] + pft2 = (np.pi * f * t) ** 2 + wavelet = (1 - 2 * pft2) * np.exp(-pft2) + + elif method == 'lstsq': + # Fit wavelet coeffs to the current reflectivity / seismic trace + projection = np.zeros((reflectivity.size, reflectivity.size)) + projection[:wavelet_length, :wavelet_length] = np.eye(wavelet_length) + + reflectivity_toeplitz = toeplitz(reflectivity) + operator = np.dot(reflectivity_toeplitz, projection) + + # wavelet = np.linalg.lstsq(op, trace)[0] + model = Ridge(alpha=0.1, fit_intercept=False) + model.fit(operator, trace) + wavelet = model.coef_[:wlenhalf + wlenflag] + wavelet = np.concatenate((wavelet[::-1], wavelet[wlenflag:]), axis=0) + + else: + # Compute power spectrum by different algorithms + if method in {'stats1', 'statistical'}: + power_spectrum = np.abs(np.fft.rfft(trace)) + + elif method in {'stats2', 'autocorrelation'}: + autocorrelation = fftconvolve(traces, traces[:, ::-1], mode='same', axes=-1) + autocorrelation = autocorrelation[:, lenhalf - wlenhalf : lenhalf + wlenhalf + wlenflag] + power_spectrum = np.sqrt(np.abs(np.fft.rfft(autocorrelation, axis=-1))).mean(axis=0) + + elif method in {'stats3'}: + autocorrelation = fftconvolve(traces, traces[:, ::-1], mode='same', axes=-1) + autocorrelation = autocorrelation[:, lenhalf - wlenhalf : lenhalf + wlenhalf + wlenflag] + autocorrelation *= np.hanning(autocorrelation.shape[1]) + power_spectrum = np.sqrt(np.abs(np.fft.rfft(autocorrelation, axis=-1))).mean(axis=0) + + # frequencies = np.fft.rfftfreq(len(autocorrelation), d=self.field.sample_interval * 1e-3) + # power_spectrum[0] = 0.0 + + elif method in {'division'}: + power_spectrum = np.fft.rfft(trace) / np.fft.rfft(reflectivity) + + if smoothing: + from scipy.signal import savgol_filter # pylint: disable=import-outside-toplevel + power_spectrum = savgol_filter(power_spectrum, smoothing_length, smoothing_order) + + # from scipy.signal import hilbert + # minphase = hilbert(np.log(power_spectrum)) + + wavelet = np.real(np.fft.irfft(power_spectrum)[:wlenhalf + wlenflag]) + wavelet = np.concatenate((wavelet[::-1], wavelet[wlenflag:]), axis=0) + + if normalize: + wavelet /= wavelet.max() + # if True: #post_taper + # wavelet *= np.hanning(wavelet.size) + return wavelet + + + def init_state(self, wavelet=None, state=-1): + """ Make the first state. By default, uses provided `wavelet` and takes original `well_times`. """ + if isinstance(state, dict): + previous_state = state + elif self.states: + previous_state = self.states[state] + else: + previous_state = { + 'well_times': self.well_times, + } + + state = { + 'type': 'init', + 'well_times': previous_state['well_times'], + 'wavelet': wavelet, + } + state['correlation'] = self.compute_metric(**state) + self.states.append(state) + + + def change_wavelet(self, keep_bounds=True, + method='statistical', normalize=False, taper=True, wavelet_length=61, state=-1, **kwargs): + """ Create a state with the computed wavelet. + Essentially, an alias to a combination of :meth:`extract_wavelet` and :meth:`init_state`. + """ + previous_state = state if isinstance(state, dict) else self.states[state] + wavelet = self.extract_wavelet(method=method, normalize=normalize, taper=taper, + wavelet_length=wavelet_length, state=state, **kwargs) + state = { + 'type': 'change_wavelet', + 'well_times': previous_state['well_times'], + 'wavelet': wavelet + } + if keep_bounds and 'bounds' in previous_state: + state['bounds'] = previous_state['bounds'] + state['correlation'] = self.compute_metric(**state) + self.states.append(state) + + + # Helper functions + def compute_resampled_synthetic(self, well_times=None, wavelet=None, limits=None, multiply=False, **kwargs): + """ Compute synthetic trace in seismic times. + + Uses the following process: + reflectivity -> reflectivity_resampled -> synthetic_trace. + + Other way to compute the synthetic trace may be: + impedance -> impedance_resampled -> reflectivity -> synthetic_trace + but it is less stable computationally. + + TODO: make two methods of computation a parameter + + Parameters + ---------- + limits : slice or None + If provided, then used to slice both seismic trace and synthetic trace to a given range. + multiply : bool + Whether to adjust the mean abs value of synthetic trace to that of seismic trace. + """ + #pylint: disable=protected-access + _ = kwargs + limits = limits if limits is not None else slice(None) + + # # Alternative way of computations + # impedance_resampled = self.resample_to_seismic(seismic_times=self.seismic_times[limits], + # well_times=well_times, + # well_data=self.well_impedance) + # reflectivity_resampled = self.well._compute_reflectivity(impedance_resampled) + # synthetic_trace = self.well._compute_synthetic(reflectivity_resampled, wavelet=wavelet) + + reflectivity_resampled = self.resample_to_seismic(seismic_times=self.seismic_times[limits], + well_times=well_times, + well_data=self.well_reflectivity) + synthetic_trace = self.well._compute_synthetic(reflectivity_resampled, wavelet=wavelet) + + if multiply: + synthetic_trace *= self.compute_multiplier(self.seismic_trace[limits], synthetic_trace) + return synthetic_trace + + @staticmethod + def resample_to_seismic(seismic_times, well_times, well_data): + """ Resample `well_data`, indexed by `well_times`, to `seismic_times`. + TODO: better interpolation + """ + return np.interp(x=seismic_times, xp=well_times, fp=well_data) + # return interp1d(x=well_times, y=well_data, kind='slinear', + # bounds_error=False, fill_value=(well_data[0], well_data[-1]))(seismic_times) + + @staticmethod + def compute_multiplier(seismic_trace, synthetic_trace): + """ Compute multiplicative difference between abs mean values. """ + return np.abs(seismic_trace).mean() / np.abs(synthetic_trace).mean() + + def compute_metric(self, metric='correlation', synthetic_trace=None, + well_times=None, wavelet=None, limits=None, **kwargs): + """ Compute a given metric between real and synthetic seismic traces. + + Parameters + ---------- + limits : slice or None + If provided, then used to slice both seismic trace and synthetic trace to a given range. + """ + _ = kwargs + limits = limits if limits is not None else slice(None) + + if synthetic_trace is None: + synthetic_trace = self.compute_resampled_synthetic(well_times=well_times, wavelet=wavelet, limits=limits) + + if metric == 'correlation': + value = self.correlation(self.seismic_trace[limits], synthetic_trace) + return value + + @staticmethod + def correlation(array_0, array_1): + """ Compute correlation coefficient between two arrays. """ + return ((array_0 - array_0.mean()) * (array_1 - array_1.mean())).mean() / (array_0.std() * array_1.std()) + + + # t0 optimization + def compute_t0(self, ranges=(-0.5, +1.5), n=1000, limits=None, state=-1, index=0): + """ Compute t0. + + Under the hood, uses either analytic formula to estimate t0 by elevations and their velocities or + just takes a given extrema on cross-correlation functions between synthetic and real seismic traces. + + TODO: better way to signal that analytic computation is needed; maybe, dont always compute cross correlations; + + Parameters + ---------- + ranges : tuple + Ranges of tested shifts for cross-correlation computation. + n : int + Number of shifts tested. + index : int + Index of the extrema to take. + If equals to -1, then analytic formula is used instead. + limits : slice or None + If provided, then used to slice both seismic trace and synthetic trace to a given range. + state : int, dict + If int, then the index of previous state to use. + If dict, then a state directly. + """ + previous_state = state if isinstance(state, dict) else self.states[state] + limits = limits if limits is not None else slice(None) + well_times = previous_state['well_times'] + wavelet = previous_state['wavelet'] + + # Compute correlation values. TODO: can be massively speed up by vectorization (the same as in 2d matching) + shifts = np.linspace(*ranges, n) + values = [self.compute_metric(well_times=well_times+shift, wavelet=wavelet, limits=limits) + for shift in shifts] + values = np.array(values) + + # Compute peaks and their corresponding metric values + peak_indices = find_peaks(values, distance=10, prominence=0.1)[0] + peak_values = values[peak_indices] + + argsort = np.argsort(peak_values)[::-1] + peak_indices = peak_indices[argsort] + peak_shifts = shifts[peak_indices] + peak_values = values[peak_indices] + + # Select the best t0 + if index == -1: + t0 = 2 * self.well.index[0] * np.diff(self.well_times)[0] / 0.3048 + else: + t0 = peak_shifts[index] + + new_well_times = self.well_times + t0 + correlation = self.compute_metric(well_times=new_well_times, wavelet=wavelet) + + # Save state + state = { + 'type': 'compute_t0', + 'well_times': new_well_times, + 'wavelet': wavelet, + 't0': t0, 'correlation': correlation, + 'shifts': shifts, 'values': values, + 'peak_shifts': peak_shifts, 'peak_values': peak_values, + } + self.states.append(state) + + + def optimize_t0(self, state=-1, limits=None, **kwargs): + """ Optimize the position of t0. + Directly minimizes metric in a small neighbourhood of the current (previous state) t0. + + Parameters + ---------- + limits : slice or None + If provided, then used to slice both seismic trace and synthetic trace to a given range. + state : int, dict + If int, then the index of previous state to use. + If dict, then a state directly. + """ + kwargs = { + 'method': 'SLSQP', + 'options': {'maxiter': 100, 'ftol': 1e-3, 'eps': 1e-6}, + **kwargs + } + previous_state = state if isinstance(state, dict) else self.states[state] + limits = limits if limits is not None else slice(None) + wavelet = previous_state['wavelet'] + + # Select t0 + if 't0' in previous_state: + t0_start = previous_state['t0'] + else: + t0_start = previous_state['well_times'][0] - self.well_times[0] + + # Actual optimization + def minimization_proxy(x): + return -self.compute_metric(well_times=self.well_times+x, wavelet=wavelet, limits=limits) + + optimization_results = minimize(minimization_proxy, x0=t0_start, **kwargs) + t0 = optimization_results['x'] + + # Save state + state = { + 'type': 'optimize_t0', + 'well_times': self.well_times + t0, + 'wavelet': previous_state['wavelet'], + 't0': t0, 'correlation': -optimization_results['fun'], + 'optimization_results': optimization_results, + } + self.states.append(state) + + + # Extrema optimization + @staticmethod + def stretch_well_times(well_times, position, alpha, left_bound, right_bound, **kwargs): + """ Stretch the `well_times` around `position` by a factor of `alpha`, while having `bounds` fixed. + + Stretching by a factor of `alpha` is applied to the left segment (segment x). + By having fixed left/right bounds, we can compute stretch factor `beta` for the right segment (segment y), + so that the time at the `right_bound` is unchanged. + | `left_bound` `position` `right_bound` + |----------------|-----------------------------------------o----------------------------------|---------------| + | + | + + This way, the entire stretching process depends only on `alpha` and the positions of fixed/moved points. + Out of them only `alpha` should/can be optimized. + """ + _ = kwargs + + # Maybe, add taper (~blackman)? + dt = np.diff(well_times, prepend=0) + x = dt[left_bound:position] + y = dt[position:right_bound] + + beta = 1 + (1 - alpha) * x.sum() / y.sum() + + new_dt = dt.copy() + new_dt[left_bound:position] *= alpha + new_dt[position:right_bound] *= beta + return np.cumsum(new_dt) + + def optimize_extrema(self, topk=20, threshold_max=0.050, threshold_min=0.001, threshold_nearest=0.010, + threshold_iv_max=500, alpha_bounds=(0.9, 1.1), state=-1, **kwargs): + """ Optimize `well_times` by stretching it around some point. + Points to stretch about are selected as extremas of synthetic trace: we take `topk` of them based on metric. + Each of those extremas is tested against the stretching process: we then select the best one. + + Thresholds regulate how much we allow to stretch each extrema and how close they should be to + the already-stretched ones. + + After successfull stretching, we store the `position` to keep it fixed in the next iterations of stretching. + This way, already moved extrema points stay in the the positions. + + TODO: explicitly add `limits`; add different strategies for extrema choice; + + Parameters + ---------- + topk : int + Number of extremas to test. + threshold_max : number + Max amount to shift the extrema position in seconds. Useful to constrain the optimization process. + threshold_min : number + Min amount to shift the extrema position in seconds. Useful to skip tiny shifts. + threshold_nearest : number + Min distance to already-shifted extrema in seconds. Useful to disallow stretching the same peak twice. + threshold_iv_max : number + Max difference in interval velocities after the shift in m/s. + alpha_bounds : tuple of two numbers + Maximum stretch/squeeze allowed. + limits : slice or None + If provided, then used to slice both seismic trace and synthetic trace to a given range. + state : int, dict + If int, then the index of previous state to use. + If dict, then a state directly. + """ + kwargs = { + 'method': 'SLSQP', + 'options': {'maxiter': 100, 'ftol': 1e-3, 'eps': 1e-6}, + **kwargs + } + + # Retrieve from previous state + previous_state = state if isinstance(state, dict) else self.states[state] + well_times, wavelet = previous_state['well_times'], previous_state['wavelet'] + bounds = previous_state.get('bounds', [1, len(well_times) - 1]) + + # Compute current state of synthetic; find extremas on it # TODO: maybe, use peaks of envelope? + synthetic_trace = self.compute_resampled_synthetic(**previous_state) + dt = np.diff(well_times, prepend=0) + + values = np.abs(synthetic_trace) + peak_indices = find_peaks(values, distance=5)[0] + peak_indices = peak_indices[np.argsort(values[peak_indices])[::-1]] # sort peaks by extrema value + + # For each extrema, check the potential correlation gain by stretching left/right side of it + results = [] + for index in range(min(topk, len(peak_indices))): + #pylint: disable=cell-var-from-loop + # Locate extreme in well times + peak_index = peak_indices[index] + peak_time = self.seismic_times[peak_index] + peak_position = np.searchsorted(well_times, peak_time) + + # Select left/right segments. Potentially early-stop + bounds_idx = np.searchsorted(bounds, peak_position) + + if peak_position <= bounds[0] or peak_position >= bounds[-1]: + continue + left_bound, right_bound = bounds[bounds_idx-1], bounds[bounds_idx] + + if min(abs(well_times[peak_position] - well_times[left_bound]), + abs(well_times[peak_position] - well_times[right_bound])) <= threshold_nearest: + continue + + x = dt[left_bound:peak_position] + y = dt[peak_position:right_bound] + xsum , ysum = x.sum(), y.sum() + + # Optimize via adjusting left-stretches `alpha` + def minimization_proxy(alpha): + beta = 1 + (1 - alpha) * xsum / ysum + + new_dt = dt.copy() + new_dt[left_bound:peak_position] *= alpha + new_dt[peak_position:right_bound] *= beta + + new_well_times = np.cumsum(new_dt) + # TODO: can add limits=(left bounds, right bounds) + return -self.compute_metric(well_times=new_well_times, wavelet=wavelet) + + # Prepare bounds and early stop, if too restrictive + s = threshold_max / xsum + tmax = min(x.min() * threshold_iv_max / 0.3048, 0.5) + optimization_bounds = (max(1 - s, alpha_bounds[0]), + min(1 + s, 1 / (1 - tmax), alpha_bounds[1])) + if optimization_bounds[0] > optimization_bounds[1]: + continue + + # Actual optimization + optimization_results = minimize(minimization_proxy, x0=1., bounds=[optimization_bounds], **kwargs) + + # Check if the stretch on either side is too small / too big + alpha = optimization_results['x'].item() + beta = 1 + (1 - alpha) * xsum / ysum + if (1 - threshold_min / xsum) <= alpha <= (1 + threshold_min / ysum) or \ + (1 - threshold_min / xsum) <= beta <= (1 + threshold_min / ysum) or \ + beta <= alpha_bounds[0] or beta >= alpha_bounds[1]: + continue + + iv_diffs_x = 0.3048 * (alpha - 1) / (alpha * x) + iv_diffs_y = 0.3048 * ( beta - 1) / ( beta * y) + if np.abs(iv_diffs_x).max() > threshold_iv_max or np.abs(iv_diffs_y).max() > threshold_iv_max: + continue + + results.append({ + 'position': peak_position, + 'alpha': alpha, 'beta': beta, + 'left_bound': left_bound, 'right_bound': right_bound, + 'correlation': -optimization_results['fun'], + 'xsum': xsum, 'ysum': ysum, + 'optimization_bounds': optimization_bounds, + 'optimization_results': optimization_results, + }) + + if len(results) == 0: + return False + + # Select the best extrema to stretch about + metrics = [item['correlation'] for item in results] + index = np.argmax(metrics) + state = results[index] + position = state['position'] + new_well_times = self.stretch_well_times(well_times, **state) + time_shift = well_times[position] - new_well_times[position] + + state.update({ + 'type': 'optimize_extrema', + 'well_times': new_well_times, + 'wavelet': wavelet, + 'time_shift': time_shift, + 'time_before': well_times[position], 'time_after': new_well_times[position], + 'correlation_delta': state['correlation'] - previous_state['correlation'], + 'bounds': sorted(bounds + [position]), + }) + self.states.append(state) + return True + + def optimize_extremas(self, steps=20, threshold_delta=0.01, verbose=True, + topk=20, threshold_max=0.050, threshold_min=0.001, threshold_nearest=0.010, + threshold_iv_max=500, alpha_bounds=(0.9, 1.1), **kwargs): + """ Optimize `well_times` by stretching multiple times about extrema positions. + Simply runs :meth:`optimize_extrema` in a loop with an early-stopping condition. + + Parameters + ---------- + steps : int + Number of steps of individual stretching to take. + threshold_delta : number + Early stop if the metric improves by less than this amount. + verbose : bool + Whether to print metric values and other info on each step. + other parameters : dict + Directly passed to :meth:`optimize_extrema`. + """ + for i in range(steps): + success = self.optimize_extrema(topk=topk, threshold_max=threshold_max, threshold_min=threshold_min, + threshold_nearest=threshold_nearest, + alpha_bounds=alpha_bounds, threshold_iv_max=threshold_iv_max, **kwargs) + if not success: + if verbose: + print('Early break: no good adjustment found!') + break + + state = self.states[-1] + correlation_delta = state['correlation_delta'] + + if verbose: + correlation = self.compute_metric(**state) + time_shift = state['time_shift'] * 1000 + alpha, beta = state['alpha'], state['beta'] + print(f'{i:3} :: {correlation=:3.5f} :: {correlation_delta=:3.5f} :: {time_shift=:>+7.4} ms' + f' || {alpha=:3.3f} :: {beta=:3.3f}') + + if correlation_delta < threshold_delta: + if verbose: + print('Early break: correlation is no longer increasing!') + break + + + # Pytorch well times optimization + @staticmethod + def compute_resampled_synthetic_pytorch(well_times, well_reflectivity, seismic_times, wavelet): + """ Compute synthetic trace in seismic times. + Same as :meth:`compute_resampled_synthetic`, but with `PyTorch` operations instead. + + TODO: replace the interpolation function: the current one is flawed / repo is broken; + """ + #pylint: disable=import-outside-toplevel + import torch + from xitorch.interpolate import Interp1D + reflectivity_resampled = Interp1D(well_times, well_reflectivity, + method='linear', assume_sorted=True, extrap=0.0)(seismic_times) + + synthetic_trace = torch.nn.functional.conv1d(input=reflectivity_resampled.reshape(1, 1, -1), + weight=wavelet.reshape(1, 1, -1), + padding='same') + return synthetic_trace.reshape(-1) + + + def optimize_well_times_pytorch(self, n_segments=100, n_iters=1000, + optimizer_params=None, regularization_params=None, bounds=None, + limits=None, pbar='t', state=-1): + """ Optimize well times by adjusting time values directly. + Originally, we allow for each element of `well_times` to be multiplied by a value. + Values are computed by optimizing the vector of multipliers with a usual PyTorch training loop. + + To constrain the amount of multipliers, we split the `well_times` into `n_segments`: each segment uses the same + multiplier. This way, the number of perturbations is much smaller and, essentially, regularized. + + Parameters + ---------- + n_segments : int + Number of segments to split `well_times` into. + n_iters : int + Number of optimization iterations. + optimizer_params : dict + Parameters for optimizer initialization. + regularization_params : dict + Regularization parameters: used keys are 'l1', 'l2', 'dl1', 'dl2'. + pbar : bool, str + If bool, then whether to display progress bar. + If str, then type of progress bar to display: `'t'` for textual, `'n'` for widget. + limits : slice or None + If provided, then used to slice both seismic trace and synthetic trace to a given range. + state : int, dict + If int, then the index of previous state to use. + If dict, then a state directly. + """ + #pylint: disable=import-outside-toplevel + import torch + from batchflow import Notifier + + limits = limits if limits is not None else slice(None) + + # Retrieve from previous state + previous_state = state if isinstance(state, dict) else self.states[state] + well_times, wavelet = previous_state['well_times'], previous_state['wavelet'] + + # Prepare variables for optimization: one multiplier for each segment + # TODO: figure out a better way to multiplicate values instead of `torch.repeat_interleave` + if n_segments == len(well_times) or n_segments == 'well': + multipliers = torch.ones(len(well_times), dtype=torch.float32, requires_grad=True) + segment_size = 1 + else: + if isinstance(n_segments, str) and n_segments.startswith('top'): + # TODO: very dirty, refactor + n_segments = int(n_segments[3:]) + + synthetic_trace = self.compute_resampled_synthetic(**previous_state) + dt = np.diff(well_times, prepend=0) + + values = np.abs(synthetic_trace) + peak_indices = find_peaks(values, distance=5)[0] + peak_indices = peak_indices[np.argsort(values[peak_indices])[::-1]] + peak_positions = [] + for index in range(n_segments): + peak_index = peak_indices[index] + peak_time = self.seismic_times[peak_index] + peak_position = np.searchsorted(well_times, peak_time) + peak_positions.append(peak_position) + peak_positions = np.sort(np.array(peak_positions)) + + segment_size = np.diff(peak_positions, prepend=0) + segment_size[-1] += len(well_times) - segment_size.sum() + segment_size = torch.from_numpy(segment_size) + else: + segment_size = len(well_times) // n_segments + 1 + multipliers = torch.ones(n_segments, dtype=torch.float32, requires_grad=True) + + + # Convert data to PyTorch. Clone everything, as CPU tensors share data with numpy arrays + seismic_times = torch.from_numpy(self.seismic_times).float().clone() + seismic_trace = torch.from_numpy(self.seismic_trace).float().clone() + well_reflectivity = torch.from_numpy(np.nan_to_num(self.well_reflectivity)).float().clone() + + well_times = torch.from_numpy(well_times).float().clone() + wavelet = torch.from_numpy(wavelet).float().clone() + dt = torch.from_numpy(np.diff(well_times, prepend=0)).float().clone() + + # Prepare infrastructure for train + optimizer_params = { + 'lr': 0.0002, + **(optimizer_params or {}) + } + optimizer = torch.optim.AdamW((multipliers,), **optimizer_params) + + regularization_params = { + 'l1': 0.0, 'l2': 0.0, + 'dl1': 0.0, 'dl2': 0.0, + **(regularization_params or {}) + } + + # Run train loop + loss_history = [] + notifier = Notifier(pbar, frequency=min(50, n_iters), + monitors=[{'source': loss_history, 'format': 'correlation={:5.4f}'}]) + for _ in notifier(n_iters): + multipliers_ = torch.repeat_interleave(multipliers, segment_size)[:len(well_times)] + multipliers_[0] = 1.0 + new_well_times = torch.cumsum(dt * multipliers_, dim=0) + synthetic_trace = self.compute_resampled_synthetic_pytorch(well_times=new_well_times, + well_reflectivity=well_reflectivity, + seismic_times=seismic_times, + wavelet=wavelet) + loss = -self.correlation(seismic_trace, synthetic_trace) + + # Regularization + dmultipliers = torch.diff(multipliers) + regularization = ( + regularization_params['l1'] * torch.abs(multipliers - 1).mean() + + regularization_params['l2'] * torch.abs((multipliers - 1) ** 2).mean() + + regularization_params['dl1'] * torch.abs(dmultipliers).mean() + + regularization_params['dl2'] * torch.abs(dmultipliers ** 2).mean() + ) + + # Update + (loss + regularization).backward() + + optimizer.step() + optimizer.zero_grad(set_to_none=True) + + loss_history.append(-loss.detach().numpy().item()) + + # Save state + multipliers_ = torch.repeat_interleave(multipliers, segment_size)[:len(well_times)] + multipliers_[0] = 1.0 + new_well_times = torch.cumsum(dt * multipliers_, dim=0).detach().numpy() + correlation = self.compute_metric(well_times=new_well_times, wavelet=previous_state['wavelet']) + state = { + 'type': 'optimize_well_times_pytorch', + 'well_times': new_well_times, + 'wavelet': previous_state['wavelet'], + 'correlation': correlation, + 'loss_history': loss_history, + 'multipliers': multipliers_.detach().numpy(), + } + self.states.append(state) + + + # Wavelet optimization + def optimize_wavelet(self, limits=None, state=-1, **kwargs): + """ Optimize wavelet's phase by direct minimization. + + Parameters + ---------- + limits : slice or None + If provided, then used to slice both seismic trace and synthetic trace to a given range. + state : int, dict + If int, then the index of previous state to use. + If dict, then a state directly. + """ + kwargs = { + 'method': 'SLSQP', + 'options': {'maxiter': 100, 'ftol': 1e-4, 'eps': 1e-7}, + **kwargs + } + + # Retrieve from previous state + previous_state = state if isinstance(state, dict) else self.states[state] + well_times, wavelet = previous_state['well_times'], previous_state['wavelet'] + + spectrum = np.fft.rfft(wavelet) + # power_spectrum = np.abs(spectrum) + # phase_spectrum = np.angle(spectrum) + + def minimization_proxy(phase_shift): + new_wavelet = np.fft.irfft(spectrum * np.exp(1.0j * phase_shift), n=len(wavelet)) + return -self.compute_metric(well_times=well_times, wavelet=new_wavelet, limits=limits) + + optimization_results = minimize(minimization_proxy, x0=0., bounds=[[-np.pi/2, +np.pi/2]], **kwargs) + + phase_shift = optimization_results['x'].item() + new_wavelet = np.fft.irfft(spectrum * np.exp(1.0j * phase_shift), n=len(wavelet)) + + state = { + 'type': 'optimize_wavelet', + 'well_times': well_times, + 'wavelet': new_wavelet, + 'correlation': -optimization_results['fun'], + 'phase_shift': phase_shift, + 'phase_shift_angles': np.rad2deg(phase_shift), + } + self.states.append(state) + + def optimize_wavelet_(self, n=10, delta=1., limits=None, state=-1, **kwargs): + """ Optimize wavelet's phases by directly changing them to maximize metric. + + TODO: explanation, references? + + Parameters + ---------- + n : int + Number of (first) frequency phases to optimize. + delta : number + Additive bound to keep the resulting phase values in. + limits : slice or None + If provided, then used to slice both seismic trace and synthetic trace to a given range. + state : int, dict + If int, then the index of previous state to use. + If dict, then a state directly. + """ + kwargs = { + 'method': 'SLSQP', + 'options': {'maxiter': 100, 'ftol': 1e-4, 'eps': 1e-7}, + **kwargs + } + + # Retrieve from previous state + previous_state = state if isinstance(state, dict) else self.states[state] + well_times = previous_state['well_times'] + wavelet = previous_state['wavelet'] + + spectrum = np.fft.rfft(wavelet) + power_spectrum = np.abs(spectrum) + phase_spectrum = np.angle(spectrum) + + # Optimization objective + def minimization_proxy(phase_shifts): + new_phase_spectrum = phase_spectrum.copy() + new_phase_spectrum[:len(phase_shifts)] = phase_shifts + new_wavelet = np.fft.irfft(power_spectrum * np.exp(1.0j * new_phase_spectrum), n=len(wavelet)) + return -self.compute_metric(well_times=well_times, wavelet=new_wavelet, limits=limits) + + x0 = phase_spectrum[:n] + optimization_bounds = np.array([x0-delta, x0+delta]).T + optimization_bounds = np.clip(optimization_bounds, -np.pi, +np.pi) + optimization_results = minimize(minimization_proxy, x0=x0, bounds=optimization_bounds, **kwargs) + + # Retrieve solution + phase_shifts = optimization_results['x'] + new_phase_spectrum = phase_spectrum.copy() + new_phase_spectrum[:len(phase_shifts)] = phase_shifts + new_wavelet = np.fft.irfft(power_spectrum * np.exp(1.0j * new_phase_spectrum), n=len(wavelet)) + + state = { + 'type': 'optimize_wavelet', + 'well_times': well_times, + 'wavelet': new_wavelet, + 'correlation': -optimization_results['fun'], + 'phase_shifts': phase_shifts, + } + self.states.append(state) + + + # Metrics + def evaluate_markers(self, markers, state=-1): + """ Compare predicted `well_times` on specific horizons to the marked one. + TODO: refactor to work with more formats; + """ + state = state if isinstance(state, dict) else self.states[state] + + if isinstance(markers, str): + markers = pd.read_csv(markers, sep='\t') + markers = markers[markers['Well'] == self.well.name] + + results_df = [] + for idx, row in markers.iterrows(): + marker_name = row['Top'] + if not marker_name.isupper(): + continue + + marker_depth = row['TVDSS [m]'] + marker_time = row['Time [s] X'] + idx = np.searchsorted(self.well.index, marker_depth) + if self.well.index[idx] - marker_depth > marker_depth - self.well.index[idx-1]: + idx -= 1 + predicted_time = state['well_times'][idx] + + results_df.append({ + 'Top': marker_name, + 'TVDSS [m]': marker_depth, + 'Time [s]': marker_time, + 'Predicted Time [s]': round(predicted_time, 6), + 'Diff Time [s]': round(predicted_time - marker_time, 6), + }) + + return pd.DataFrame(results_df) + + + # Export + def save_well_times(self, path, state=-1): + """ Save `well_times` as the depth-time table. """ + state = self.states[state] + path = self.field.make_path(path, name=self.well.name) + + well_times = state['well_times'] + depths = self.well.index.values[self.well_bounds] + + data = np.array([depths, well_times]).T + df = pd.DataFrame(data=data, columns=['MD, m', 'TWT, s']) + + df.to_csv(path, header=True, index=False, sep=' ') + + def save_wavelet(self, path, state=-1): + """ Save wavelet as time-value table. """ + state = self.states[state] + path = self.field.make_path(path, name=self.well.name) + + wavelet = state['wavelet'] + times = np.arange(len(wavelet)) * self.field.sample_interval * 1e-3 + + data = np.array([times, wavelet]).T + df = pd.DataFrame(data=data, columns=['TWT, s', 'VALUE']) + + df.to_csv(path, header=True, index=False, sep=' ') + + def save_las(self, path, state=-1): + """ Save well information with all used (possibly, recomputed and filtered) logs. """ + state = self.states[-1] + path = self.field.make_path(path, name=self.well.name) + + well_times = state['well_times'] + dt_optimized = np.diff(well_times, prepend=0) * 1e6 + well_impedance = self.well_impedance + + if well_times.size != self.well.shape[0]: + pad_width = (self.well_bounds.start, self.well.shape[0]-self.well_bounds.stop) + dt_optimized = np.pad(dt_optimized, pad_width=pad_width, constant_values=np.nan) + well_impedance = np.pad(well_impedance, pad_width=pad_width, constant_values=np.nan) + + lasfile = deepcopy(self.well.lasfile) + lasfile.append_curve('DT_OPTIMIZED', dt_optimized, unit='us/ft', descr='DT_OPTIMIZED') + lasfile.append_curve('AI_USED', well_impedance, unit='kPa.s/m', descr='AI_USED') + + if 'RHOB_FILTERED' in self.well.keys: + rhob_values = self.well['RHOB_FILTERED'] + if well_times.size != self.well.shape[0]: + rhob_values = np.pad(rhob_values, pad_width=pad_width, constant_values=np.nan) + lasfile.append_curve('RHOB_FILTERED', rhob_values, unit='kg/m^3', descr='RHOB_FILTERED') + + + lasfile.write(path, version=2.0) + + def save_synthetic(self, path, state=-1): + """ Save synthetic trace in SEG-Y format. """ + state = self.states[state] + path = self.field.make_path(path, name=self.well.name) + + synthetic_trace = self.compute_resampled_synthetic(**state) + synthetic_trace = synthetic_trace.reshape(1, 1, -1) + + array_to_segy(synthetic_trace, path=path, origin=(*self.coordinates, 0), pbar=False) + + + # Visualization + def show_state(self, state=-1, limits=slice(None), force_dt=False, **kwargs): + """ Show state. + Visualizes real-to-synthetic comparison, the wavelet, + original and state interval velocity, ratio between original and state velocties. + + If `well_times` are unchanged, the last two graphs are not displayed. + + Parameters + ---------- + force_dt : bool + Whether to show the last two graphs even if `well_times` are unchanged in the state. + limits : slice or None + If provided, then used to slice both seismic trace and synthetic trace to a given range. + state : int, dict + If int, then the index of previous state to use. + If dict, then a state directly. + kwargs : dict + Other parameters are directly passed to the plotting function. + """ + state = len(self.states) - 1 if state == -1 else state + state_name = '' if isinstance(state, dict) else state + state = state if isinstance(state, dict) else self.states[state] + + wavelet = state['wavelet'] + synthetic_trace = self.compute_resampled_synthetic(**state, multiply=True) + correlation = self.compute_metric(synthetic_trace=synthetic_trace) + + dt = np.diff(self.well_times) + dt_state = np.diff(state['well_times']) + + # Seismic to synthetic comparison; wavelet + well_times = state['well_times'][1:] + seismic_times = self.seismic_times[limits] + wavelet_times = self.seismic_times[:len(wavelet)] + wavelet_times -= wavelet_times[len(wavelet)//2 + 0] + + data = [[(seismic_times, self.seismic_trace[limits]), (seismic_times, synthetic_trace[limits])], + [(wavelet_times, wavelet)]] + + # Interval velocities: show only if changed + if not np.allclose(dt, dt_state) or force_dt: + iv = 0.3048 / dt + iv_state = 0.3048 / dt_state + iv_diff = np.abs(iv - iv_state) + data.append([(well_times, iv), (well_times, iv_state), (well_times, iv_diff)]) + + relative_iv = np.round(dt / dt_state, 6) + data.append([(well_times, relative_iv)]) + + kwargs = { + 'combine': 'overlay', + 'ncols': 2, + 'ratio': 0.3 if len(data) == 2 else 0.5, + 'suptitle': f'Well `{self.well.name}`\nstate={state_name}; {correlation=:3.3f}', + 'title': ['seismic vs synthetic', 'wavelet', + 'interval velocity', 'relative increase in velocity: dt/dt_state'], + 'xlabel': ['seismic time, s', 'time, s', + 'well time, s', 'well time, s'], + 'ylabel': ['amplitude', 'amplitude', + 'velocity, m/s', 'ratio'], + 'label': [['seismic_trace', 'synthetic_trace'], '', + ['original IV', 'state IV', 'diff IV'], ''], + 'xlabel_size': 18, + **kwargs + } + plotter = plot(data, mode='curve', **kwargs) + if len(data) == 4: + plotter.subplots[-1].ax.axhline(1, linestyle='dashed', alpha=.5, color='sandybrown', linewidth=3) + + return plotter + + + def show_wavelet(self, state=-1, **kwargs): + """ Display wavelet and its power/phase spectra. """ + state = len(self.states) - 1 if state == -1 else state + state_name = '' if isinstance(state, dict) else state + state = state if isinstance(state, dict) else self.states[state] + wavelet = state['wavelet'] + correlation = state['correlation'] + times = np.arange(len(wavelet)) * self.field.sample_interval + times -= times[-1] / 2 + + spectrum = np.fft.rfft(wavelet) + power_spectrum = 20 * np.log10(np.abs(spectrum)) + phase_spectrum = np.angle(spectrum) + frequencies = np.fft.rfftfreq(len(wavelet), d=self.field.sample_interval * 1e-3) + + kwargs = { + 'combine': 'separate', + 'ncols': 3, + 'ratio': 0.25, + 'suptitle': f'well `{self.well.name}`\nstate={state_name}; {correlation=:3.3f}', + 'title': ['wavelet', 'power spectrum', 'phase spectrum'], + 'xlabel': ['time, ms', 'Hz', 'Hz'], + **kwargs + } + return plot([(times, wavelet), (frequencies, power_spectrum), (frequencies, phase_spectrum)], + mode='curve', **kwargs) + + + def show_progress(self, start_idx=1, **kwargs): + """ Display correlation over the states. """ + data = [[state.get('correlation', self.compute_metric(**state)) for state in self.states[start_idx:]]] + + kwargs = { + 'combine': 'separate', + 'title': ['correlation over states', 'time shifts of states'], + 'xlabel': 'state index', + 'ylabel': ['correlation', 'time shift (ms)'], + **kwargs + } + + # Extrema optimization states + states = [state for state in self.states if state['type'] == 'optimize_extrema'] + if states: + time_shifts = [state['time_shift'] * 1000 for state in states] + data.append(time_shifts) + + plotter = plot(data, mode='curve', ncols=2 if states else 1, **kwargs) + + if states: + plotter[1].ax.lines.pop(0) + colors = np.where(np.array(time_shifts) > 0, 'r', 'b') + plotter[1].ax.bar(range(len(states)), time_shifts, color=colors) + return plotter + + + def show_crosscorrelation(self, state=1, n_peaks=3, **kwargs): + """ Display cross-correlation function between real and synthetic trace. + Requires for the state to be created by :meth:`compute_t0`. + """ + state = state if isinstance(state, dict) else self.states[state] + if state['type'] not in {'compute_t0'}: + raise TypeError('State type should be `compute_t0`.') + + kwargs = { + 'title': 'correlation VS shift of well data', + 'xlabel': 'shift, seconds', 'ylabel': 'correlation', + 'size': 18, 'title_size': 22, + **kwargs + } + + plotter = plot((state['shifts'], state['values']), mode='curve', **kwargs) + plotter[0].ax.scatter(state['peak_shifts'], state['peak_values'], s=15, c='r', marker='8') + + for idx in range(n_peaks): + shift = state['peak_shifts'][idx] + correlation = state['peak_values'][idx] + plotter[0].ax.axvline(shift, correlation, linestyle='dashed', color='orange', alpha=0.9, + label=f'{shift=:+2.3f} {correlation=:2.3f}') + plotter[0].ax.legend(prop={'size': 14}) + return plotter + + def show_time_shifts(self, zoom=None, **kwargs): + """ Display applied stretches. """ + zoom = zoom if zoom is not None else (0, self.seismic_times[-1]) + kwargs = { + 'title': 'Extrema shift visualization', + 'xlim': zoom, + 'ylabel': '', 'ylim': (0, 1), 'ytick_labels': '', + **kwargs + } + + plotter = plot((self.seismic_times, self.seismic_times * np.nan), mode='curve', **kwargs) + + states = [state for state in self.states if state['type'] == 'optimize_extrema'] + for i, state in enumerate(states): + time_before, time_after = state['time_before'], state['time_after'] + plotter[0].ax.axvline(time_before, linestyle='--', alpha=0.8, color='blue') + plotter[0].ax.axvline(time_after, linestyle='solid', alpha=1, color='green') + + text = f'{state["time_shift"] * 1000:+2.3f} ms' + plotter[0].ax.annotate(text, xy=(max(time_before, time_after), (i + 1) / len(states)), size=14) + return plotter diff --git a/seismiqb/metrics.py b/seismiqb/metrics.py new file mode 100644 index 0000000..598da40 --- /dev/null +++ b/seismiqb/metrics.py @@ -0,0 +1,963 @@ +""" Metrics for seismic objects: cubes and horizons. """ +from warnings import warn +from textwrap import dedent +from itertools import zip_longest + +import numpy as np +import pandas as pd + +try: + import cupy as cp + CUPY_AVAILABLE = True +except ImportError: + cp = np + CUPY_AVAILABLE = False +try: + import bottleneck + import numexpr + BOTTLENECK_NUMEXPR_AVAILABLE = True +except ImportError: + BOTTLENECK_NUMEXPR_AVAILABLE = False + +from batchflow.notifier import Notifier + +from .labels import Horizon +from .utils import Accumulator, to_list +from .plotters import plot + + + +# Device management +def to_device(array, device='cpu'): + """ Transfer array to chosen GPU, if possible. + If `cupy` is not installed, does nothing. + + Parameters + ---------- + device : str or int + Device specificator. Can be either string (`cpu`, `gpu:4`) or integer (`4`). + """ + if isinstance(device, str) and ':' in device: + device = int(device.split(':')[1]) + if device in ['cuda', 'gpu']: + device = 0 + + if isinstance(device, int): + if CUPY_AVAILABLE: + with cp.cuda.Device(device): + array = cp.asarray(array) + else: + warn('Performance Warning: computing metrics on CPU as `cupy` is not available', RuntimeWarning) + return array + +def from_device(array): + """ Move the data from GPU, if needed. + If `cupy` is not installed or supplied array already resides on CPU, does nothing. + """ + if CUPY_AVAILABLE and hasattr(array, 'device'): + array = cp.asnumpy(array) + return array + + + +# Functions to compute various distances between two atleast 2d arrays +def correlation(array1, array2, std1, std2, **kwargs): + """ Compute correlation. """ + _ = kwargs + xp = cp.get_array_module(array1) if CUPY_AVAILABLE else np + if xp is np and BOTTLENECK_NUMEXPR_AVAILABLE: + covariation = bottleneck.nanmean(numexpr.evaluate('array1 * array2'), axis=-1) + result = numexpr.evaluate('covariation / (std1 * std2)') + else: + covariation = (array1 * array2).mean(axis=-1) + result = covariation / (std1 * std2) + return result + + +def crosscorrelation(array1, array2, std1, std2, **kwargs): + """ Compute crosscorrelation. """ + _ = std1, std2, kwargs + xp = cp.get_array_module(array1) if CUPY_AVAILABLE else np + window = array1.shape[-1] + pad_width = [(0, 0)] * (array2.ndim - 1) + [(window//2, window - window//2)] + padded = xp.pad(array2, pad_width=tuple(pad_width)) + + accumulator = Accumulator('argmax') + for i in range(window): + corrs = (array1 * padded[..., i:i+window]).sum(axis=-1) + accumulator.update(corrs) + return accumulator.get(final=True).astype(float) - window//2 + +class BaseMetrics: + """ Base class for seismic metrics. + Child classes have to implement access to `data` and `bad_traces` attributes. + """ + # pylint: disable=attribute-defined-outside-init, blacklisted-name + PLOT_DEFAULTS = { + 'cmap': 'Metric', + 'mask_color': 'black' + } + + LOCAL_DEFAULTS = { + 'kernel_size': 3, + 'agg': 'nanmean', + 'device': 'gpu', + 'amortize': True, + } + + SUPPORT_DEFAULTS = { + 'supports': 100, + 'safe_strip': 50, + 'agg': 'nanmean', + 'device': 'gpu', + 'amortize': True, + } + + SMOOTHING_DEFAULTS = { + 'kernel_size': 21, + 'sigma': 10.0, + } + + EPS = 0.00001 + + + def evaluate(self, metric, plot_supports=False, enlarge=True, + width=5, visualize=True, savepath=None, plotter=plot, **kwargs): + """ Calculate desired metric, apply aggregation, then plot resulting metric-map. + To plot the results, set `plot` argument to True. + + Parameters + ---------- + metric : str + Name of metric to evaluate. + plot_supports : bool + Whether to show support traces on resulting image. Works only if `plot` set to True. + enlarge : bool + Whether to apply `:meth:.Horizon.matrix_enlarge` to the result. + width : int + Widening for the metric. Works only if `enlarge` set to True. + visualize : bool + Whether to use `:func:.plot` to show the result. + savepath : None or str + Where to save visualization. + plotter : instance of `plot` + Plotter instance to use. + Combined with `positions` parameter allows using subplots of already existing plotter. + kwargs : dict + Arguments to be passed in metric-calculation methods + (see `:meth:.compute_local` and `:meth:.compute_support`), + as well as plotting arguments (see `:func:.plot`). + """ + if 'support' in metric: + kwargs = {**self.SUPPORT_DEFAULTS, **kwargs} + elif 'local' in metric: + kwargs = {**self.LOCAL_DEFAULTS, **kwargs} + + self._last_evaluation = {**kwargs} + metric_fn = getattr(self, metric) + metric_map, plot_config = metric_fn(**kwargs) + + if cp is not np and cp.cuda.is_available(): + # pylint: disable=protected-access + cp._default_memory_pool.free_all_blocks() + + if hasattr(self, 'horizon') and self.horizon.is_carcass and enlarge: + metric_map = self.horizon.matrix_enlarge(metric_map, width) + + if visualize: + plot_config = {**self.PLOT_DEFAULTS, **plot_config} + if savepath is not None: + plot_config['savepath'] = self.horizon.field.make_path(savepath, name=self.name) + plotter = plotter(metric_map, **plot_config) + + if 'support' in metric and plot_supports: + support_coords = self._last_evaluation['support_coords'] + plotter[0].ax.scatter(support_coords[:, 0], support_coords[:, 1], s=33, marker='.', c='blue') + + # Store for debug / introspection purposes + self._last_evaluation['plotter'] = plotter + return metric_map + + def compute_local(self, function, data, bad_traces, kernel_size=3, + normalize=True, agg='mean', amortize=False, axis=0, device='cpu', pbar=None): + """ Compute metric in a local fashion, using `function` to compare nearest traces. + Under the hood, each trace is compared against its nearest neighbours in a square window + of `kernel_size` size. Results of comparisons are aggregated via `agg` function. + + Works on both `cpu` (via standard `NumPy`) and GPU (with the help of `cupy` library). + The returned array is always on CPU. + + Parameters + ---------- + function : callable + Function to compare two arrays. Must have the following signature: + `(array1, array2, std1, std2)`, where `std1` and `std2` are pre-computed standard deviations. + In order to work properly on GPU, must be device-agnostic. + data : ndarray + 3D array of data to evaluate on. + bad_traces : ndarray + 2D matrix of traces where the metric should not be computed. + kernel_size : int + Window size for comparison traces. + normalize : bool + Whether the data should be zero-meaned before computing metric. + agg : str + Function to aggregate values for each trace. See :class:`.Accumulator` for details. + amortize : bool + Whether the aggregation should be sequential or by stacking all the matrices. + See :class:`.Accumulator` for details. + axis : int + Axis to stack arrays on. See :class:`.Accumulator` for details. + device : str + Device specificator. Can be either string (`cpu`, `gpu:4`) or integer (`4`). + pbar : type or None + Progress bar to use. + """ + i_range, x_range = data.shape[:2] + k = kernel_size // 2 + 1 + + # Transfer to GPU, if needed + data = to_device(data, device) + bad_traces = to_device(bad_traces, device) + xp = cp.get_array_module(data) if CUPY_AVAILABLE else np + + # Compute data statistics + data_stds = data.std(axis=-1) + bad_traces[data_stds == 0.0] = 1 + if normalize: + data_n = data - data.mean(axis=-1, keepdims=True) + else: + data_n = data + + # Pad everything + padded_data = xp.pad(data_n, ((0, k), (k, k), (0, 0)), constant_values=xp.nan) + padded_stds = xp.pad(data_stds, ((0, k), (k, k)), constant_values=0.0) + padded_bad_traces = xp.pad(bad_traces, k, constant_values=1) + + # Compute metric by shifting arrays + total = kernel_size * kernel_size - 1 + pbar = Notifier(pbar, total=total) + + accumulator = Accumulator(agg=agg, amortize=amortize, axis=axis, total=total) + for i in range(k): + for j in range(-k+1, k): + # Comparison between (x, y) and (x+i, y+j) vectors is the same as comparison between (x+i, y+j) + # and (x, y). So, we can compare (x, y) with (x+i, y+j) and save computed result twice: + # matrix associated with vector (x, y) and matrix associated with (x+i, y+j) vector. + if (i == 0) and (j <= 0): + continue + shifted_data = padded_data[i:i+i_range, k+j:k+j+x_range] + shifted_stds = padded_stds[i:i+i_range, k+j:k+j+x_range] + shifted_bad_traces = padded_bad_traces[k+i:k+i+i_range, k+j:k+j+x_range] + + computed = function(data, shifted_data, data_stds, shifted_stds) + # Using symmetry property: + symmetric_bad_traces = padded_bad_traces[k-i:k-i+i_range, k-j:k-j+x_range] + symmetric_computed = computed[:i_range-i, max(0, -j):min(x_range, x_range-j)] + symmetric_computed = xp.pad(symmetric_computed, + ((i, 0), (max(0, j), -min(0, j))), + constant_values=xp.nan) + + computed[shifted_bad_traces == 1] = xp.nan + symmetric_computed[symmetric_bad_traces == 1] = xp.nan + accumulator.update(computed) + accumulator.update(symmetric_computed) + pbar.update(2) + pbar.close() + + result = accumulator.get(final=True) + return from_device(result) + + @staticmethod + def find_supports(supports, bad_traces, safe_strip, carcass_mode=False, horizon=None, + device='cpu', seed=None): + """ Find valid supports coordinates. + + Parameters + ---------- + supports : int or ndarray + If int, then number of supports to generate randomly from non-bad traces. + If ndarray, then should be of (N, 2) shape and contain coordinates of reference traces. + bad_traces : ndarray + 2D matrix of traces where the metric should not be computed. + safe_strip : int + Margin for computing metrics safely. + carcass_mode : bool + Whether to use carcass intersection nodes as supports traces. + Notice that it works only for a carcass. + Note, if `carcass_mode` is True, then the `horizon` argument must be provided. + horizon : :class:`.Horizon`, optional + Instance of a carcass horizon for which to create supports in intersection points. + device : str + Device specificator. Can be either string (`cpu`, `gpu:4`) or integer (`4`). + seed : int, optional + Seed the random numbers generator. + """ + xp = cp if (CUPY_AVAILABLE and device != 'cpu') else np + + if isinstance(supports, int): + if safe_strip: + bad_traces = bad_traces.copy() + bad_traces[:, :safe_strip], bad_traces[:, -safe_strip:] = 1, 1 + bad_traces[:safe_strip, :], bad_traces[-safe_strip:, :] = 1, 1 + + valid_traces = xp.where(bad_traces == 0) + + if carcass_mode and (horizon is not None) and horizon.is_carcass: + carcass_ilines = horizon.carcass_ilines + carcass_xlines = horizon.carcass_xlines + + carcass_ilines = to_device(carcass_ilines, device) + carcass_xlines = to_device(carcass_xlines, device) + + mask_i = xp.in1d(valid_traces[0], carcass_ilines) + mask_x = xp.in1d(valid_traces[1], carcass_xlines) + mask = mask_i & mask_x + + valid_traces = (valid_traces[0][mask], valid_traces[1][mask]) + + rng = xp.random.default_rng(seed=seed) + indices = rng.integers(low=0, high=len(valid_traces[0]), size=supports) + + support_coords = xp.asarray([valid_traces[0][indices], valid_traces[1][indices]]).T + + elif isinstance(supports, (tuple, list, np.ndarray)): + support_coords = xp.asarray(supports) + + else: + raise TypeError('Unknown type for the `supports` argument. ' + 'It must be one of: int, tuple, list or np.ndarray.') + + if len(support_coords) == 0: + raise ValueError('No valid support coordinates was found. ' + 'Check input surfaces for available common points.') + + return support_coords + + def compute_support(self, function, data, bad_traces, supports, safe_strip=0, carcass_mode=False, + normalize=True, agg='mean', amortize=False, axis=0, device='cpu', pbar=None, seed=None): + """ Compute metric in a support fashion, using `function` to compare all the traces + against a set of (randomly chosen or supplied) reference ones. + Results of comparisons are aggregated via `agg` function. + + Works on both `cpu` (via standard `NumPy`) and GPU (with the help of `cupy` library). + The returned array is always on CPU. + + Parameters + ---------- + function : callable + Function to compare two arrays. Must have the following signature: + `(array1, array2, std1, std2)`, where `std1` and `std2` are pre-computed standard deviations. + In order to work properly on GPU, must be device-agnostic. + data : ndarray + 3D array of data to evaluate on. + bad_traces : ndarray + 2D matrix of traces where the metric should not be computed. + supports : int or ndarray + If int, then number of supports to generate randomly from non-bad traces. + If ndarray, then should be of (N, 2) shape and contain coordinates of reference traces. + safe_strip : int + Margin for computing metrics safely. + carcass_mode : bool + Whether to use carcass intersection nodes as supports traces. + Notice that it works only for a carcass. + normalize : bool + Whether the data should be zero-meaned before computing metric. + agg : str + Function to aggregate values for each trace. See :class:`.Accumulator` for details. + amortize : bool + Whether the aggregation should be sequential or by stacking all the matrices. + See :class:`.Accumulator` for details. + axis : int + Axis to stack arrays on. See :class:`.Accumulator` for details. + device : str + Device specificator. Can be either string (`cpu`, `gpu:4`) or integer (`4`). + pbar : type or None + Progress bar to use. + seed : int, optional + Seed the random numbers generator for supports coordinates. + """ + # Transfer to GPU, if needed + data = to_device(data, device) + bad_traces = to_device(bad_traces, device) + xp = cp.get_array_module(data) if CUPY_AVAILABLE else np + + # Compute data statistics + data_stds = data.std(axis=-1) + bad_traces[data_stds == 0.0] = 1 + if normalize: + data_n = data - data.mean(axis=-1, keepdims=True) + else: + data_n = data + + horizon = getattr(self, 'horizon', None) + support_coords = BaseMetrics.find_supports(supports=supports, bad_traces=bad_traces, + safe_strip=safe_strip, carcass_mode=carcass_mode, + horizon=horizon, device=device, seed=seed) + + # Save for plot and introspection + if not hasattr(self, '_last_evaluation'): + self._last_evaluation = {} + + self._last_evaluation['support_coords'] = from_device(support_coords) + + # Generate support traces + support_traces = data_n[support_coords[:, 0], support_coords[:, 1]] + support_stds = data_stds[support_coords[:, 0], support_coords[:, 1]] + + # Compute metric + pbar = Notifier(pbar, total=len(support_traces)) + accumulator = Accumulator(agg=agg, amortize=amortize, axis=axis, total=len(support_traces)) + + valid_data = data_n[bad_traces != 1] + valid_stds = data_stds[bad_traces != 1] + + for i, _ in enumerate(support_traces): + computed = function(valid_data, support_traces[i], valid_stds, support_stds[i]) + accumulator.update(computed) + pbar.update() + pbar.close() + + result = xp.full(shape=(data_n.shape[0], data_n.shape[1]), fill_value=xp.nan, dtype=data_n.dtype) + result[bad_traces != 1] = accumulator.get(final=True) + + return from_device(result) + + + def local_corrs(self, kernel_size=3, normalize=True, agg='mean', amortize=False, + device='cpu', pbar=None, **kwargs): + """ Compute correlation in a local fashion. """ + metric = self.compute_local(function=correlation, data=self.data, bad_traces=self.bad_traces, + kernel_size=kernel_size, normalize=normalize, agg=agg, amortize=amortize, + device=device, pbar=pbar) + + title, plot_defaults = self.get_plot_defaults() + title = f'Local correlation, k={kernel_size}, with `{agg}` aggregation\nfor {title}' + plot_config = { + **plot_defaults, + 'title': title, + 'vmin': -1.0, 'vmax': 1.0, + **kwargs + } + return metric, plot_config + + def support_corrs(self, supports=100, safe_strip=0, carcass_mode=False, normalize=True, agg='mean', amortize=False, + device='cpu', pbar=None, **kwargs): + """ Compute correlation against reference traces. """ + metric = self.compute_support(function=correlation, data=self.data, bad_traces=self.bad_traces, + supports=supports, safe_strip=safe_strip, carcass_mode=carcass_mode, + normalize=normalize, agg=agg, device=device, amortize=amortize, + pbar=pbar) + + title, plot_defaults = self.get_plot_defaults() + n_supports = supports if isinstance(supports, int) else len(supports) + title = f'Support correlation with {n_supports} supports\nwith `{agg}` aggregation\nfor {title}' + plot_config = { + **plot_defaults, + 'title': title, + 'vmin': -1.0, 'vmax': 1.0, + 'colorbar': True, + 'bad_color': 'k', + **kwargs + } + return metric, plot_config + + + def local_crosscorrs(self, kernel_size=3, normalize=False, agg='mean', amortize=False, + device='cpu', pbar=None, **kwargs): + """ Compute cross-correlation in a local fashion. """ + metric = self.compute_local(function=crosscorrelation, data=self.data, bad_traces=self.bad_traces, + kernel_size=kernel_size, normalize=normalize, agg=agg, amortize=amortize, + device=device, pbar=pbar) + zvalue = np.nanquantile(np.abs(metric), 0.98).astype(np.int32) + + title, plot_defaults = self.get_plot_defaults() + title = f'Local cross-correlation, k={kernel_size}, with `{agg}` aggregation\nfor {title}' + plot_config = { + **plot_defaults, + 'title': title, + 'cmap': 'seismic_r', + 'vmin': -zvalue, 'vmax': zvalue, + **kwargs + } + return metric, plot_config + + def support_crosscorrs(self, supports=100, safe_strip=0, carcass_mode=False, normalize=False, + agg='mean', amortize=False, device='cpu', pbar=None, **kwargs): + """ Compute cross-correlation against reference traces. """ + metric = self.compute_support(function=crosscorrelation, data=self.data, bad_traces=self.bad_traces, + supports=supports, safe_strip=safe_strip, carcass_mode=carcass_mode, + normalize=normalize, agg=agg, amortize=amortize, device=device, pbar=pbar) + zvalue = np.nanquantile(np.abs(metric), 0.98).astype(np.int32) + + title, plot_defaults = self.get_plot_defaults() + n_supports = supports if isinstance(supports, int) else len(supports) + title = f'Support cross-correlation with {n_supports} supports with `{agg}` aggregation\nfor {title}' + plot_config = { + **plot_defaults, + 'title': title, + 'cmap': 'seismic_r', + 'vmin': -zvalue, 'vmax': zvalue, + **kwargs + } + return metric, plot_config + + + +class HorizonMetrics(BaseMetrics): + """ Evaluate metric(s) on horizon(s). + During initialization, data along the horizon is cut with the desired parameters. + To get the value of a particular metric, use :meth:`.evaluate`:: + HorizonMetrics(horizon).evaluate('support_corrs', supports=20, agg='mean') + + To plot the results, set `plot` argument of :meth:`.evaluate` to True. + + Parameters + horizons : :class:`.Horizon` or sequence of :class:`.Horizon` + Horizon(s) to evaluate. + Can be either one horizon, then this horizon is evaluated on its own, + or sequence of two horizons, then they are compared against each other, + or nested sequence of horizon and list of horizons, then the first horizon is compared against the + best match from the list. + other parameters + Passed direcly to :meth:`.Horizon.get_cube_values` or :meth:`.Horizon.get_cube_values_line`. + """ + AVAILABLE_METRICS = [ + 'local_corrs', 'support_corrs', + 'local_btch', 'support_btch', + 'local_kl', 'support_kl', + 'local_js', 'support_js', + 'local_hellinger', 'support_hellinger', + 'local_tv', 'support_tv', + 'instantaneous_phase', + ] + + def __init__(self, horizons, window=23, offset=0, normalize=False, chunk_size=256): + super().__init__() + horizons = list(horizons) if isinstance(horizons, tuple) else horizons + horizons = horizons if isinstance(horizons, list) else [horizons] + self.horizons = horizons + + # Save parameters for later evaluation + self.window, self.offset, self.normalize, self.chunk_size = window, offset, normalize, chunk_size + + # The first horizon is used to evaluate metrics + self.horizon = horizons[0] + self.name = self.horizon.short_name + + # Properties + self._data = None + self._probs = None + self._bad_traces = None + + + @classmethod + def evaluate_support(cls, horizons, metric='support_corrs', supports=100, bad_traces=None, safe_strip=0, + device='cpu', seed=None, **kwargs): + """ Evaluate support metric for given horizons using same support coordinates. + + Parameters + ---------- + horizons : list of :class:`.Horizon` + List of horizon instances for which evaluate the metric. + metric : str + Name of metric to evaluate. + supports : int or ndarray + If int, then number of supports to generate randomly from non-bad traces. + If ndarray, then should be of (N, 2) shape and contain coordinates of reference traces. + bad_traces : ndarray + 2D matrix of traces where the metric should not be computed. + safe_strip : int + Margin for computing metrics safely. + device : str + Device specificator. Can be either string (`cpu`, `gpu:4`) or integer (`4`). + seed : int, optional + Seed the random numbers generator. + kwargs : dict + Additional keyword arguments for the :meth:`.HorizonMetrics.evaluate`. + """ + xp = cp if (CUPY_AVAILABLE and device != 'cpu') else np + + horizons_bad_traces = [] + + # Generate support coordinates + if isinstance(supports, int): + # Get bad traces for all compared horizons + if bad_traces is None: + bad_traces = xp.zeros(shape=horizons[0].field.spatial_shape, dtype=int) + else: + bad_traces = to_device(bad_traces.copy(), device) + + for horizon in horizons: + horizon_bad_traces = (horizon.full_matrix == horizon.FILL_VALUE).astype(int) + horizon_bad_traces = to_device(horizon_bad_traces, device) + + horizons_bad_traces.append(horizon_bad_traces) + bad_traces |= horizon_bad_traces + + support_coords = BaseMetrics.find_supports(supports=supports, bad_traces=bad_traces, + safe_strip=safe_strip, carcass_mode=False, + horizon=None, device=device, seed=seed) + + metrics = [] + + for horizon in horizons: + horizon_metric = cls(horizon).evaluate(metric=metric, supports=support_coords, horizon=horizon, **kwargs) + metrics.append(horizon_metric) + + return metrics + + + def get_plot_defaults(self): + """ Axis labels and horizon/cube names in the title. """ + title = f'horizon `{self.name}` on cube `{self.horizon.field.short_name}`' + return title, { + 'xlabel': self.horizon.field.axis_names[0], + 'ylabel': self.horizon.field.axis_names[1], + } + + @property + def data(self): + """ Create `data` attribute at the first time of evaluation. """ + if self._data is None: + self._data = self.horizon.get_cube_values(window=self.window, offset=self.offset, + chunk_size=self.chunk_size) + self._data[self._data == Horizon.FILL_VALUE] = np.nan + return self._data + + @property + def bad_traces(self): + """ Traces to fill with `nan` values. """ + if self._bad_traces is None: + self._bad_traces = self.horizon.field.dead_traces_matrix.copy() + self._bad_traces[self.horizon.full_matrix == Horizon.FILL_VALUE] = 1 + return self._bad_traces + + + def compare(self, *others, clip_value=7, ignore_zeros=False, enlarge=True, width=9, printer=print, + visualize=True, hist_kwargs=None, show=True, savepath=None, **kwargs): + """ Compare `self` horizon against the closest in `others`. + Print textual and show graphical visualization of differences between the two. + Returns dictionary with collected information: `closest` and `proximity_info`. + + Parameters + ---------- + clip_value : number + Clip for differences graph and histogram + ignore_zeros : bool + Whether to ignore zero-differences on histogram. + enlarge : bool + Whether to enlarge the difference matrix, if one of horizons is a carcass. + width : int + Enlarge width. Works only if `enlarge` is True. + printer : callable, optional + Function to use to print textual information + visualize : bool + Whether to plot the graph + hist_kwargs, kwargs : dict + Parameters for histogram / main graph visualization. + show : bool + Whether to show created plot or not. + savepath : str + Path to save the plot to. + """ + closest, proximity_info = other, oinfo = self.horizon.find_closest(*others) + returns = {'closest': closest, 'proximity_info': proximity_info} + + msg = f""" + Comparing horizons: + {self.horizon.short_name.rjust(45)} + {other.short_name.rjust(45)} + {'—'*45} + Rate in 5ms: {oinfo['window_rate']:8.3f} + Mean / std of errors: {oinfo['difference_mean']:+6.2f} / {oinfo['difference_std']:5.2f} + Mean / std of abs errors: {oinfo['abs_difference_mean']:5.2f} / {oinfo['abs_difference_std']:5.2f} + Max abs error: {oinfo['abs_difference_max']:4.0f} + Accuracy@0: {oinfo['accuracy@0']:4.3f} + Accuracy@1: {oinfo['accuracy@1']:4.3f} + Accuracy@2: {oinfo['accuracy@2']:4.3f} + {'—'*45} + Lengths of horizons: {len(self.horizon):10,} + { len(other):10,} + {'—'*45} + Average depths of horizons: {self.horizon.d_mean:8.2f} + { other.d_mean:8.2f} + {'—'*45} + Coverage of horizons: {self.horizon.coverage:8.4f} + { other.coverage:8.4f} + {'—'*45} + Number of holes in horizons: {self.horizon.number_of_holes:8} + { other.number_of_holes:8} + {'—'*45} + Additional traces labeled: {oinfo['present_at_1_absent_at_2']:8} + (present in one, absent in other) {oinfo['present_at_2_absent_at_1']:8} + {'—'*45} + """ + msg = dedent(msg) + + if printer is not None: + printer(msg) + + if visualize: + # Prepare data + matrix = proximity_info['difference_matrix'].copy() + if enlarge and (self.horizon.is_carcass or other.is_carcass): + matrix = self.horizon.matrix_enlarge(matrix, width=width) + + # Field boundaries + bounds = self.horizon.field.dead_traces_matrix + + # Main plot: differences matrix + kwargs = { + 'title': (f'Depth comparison\n' + f'`self={self.horizon.short_name}` and `other={closest.short_name}`'), + 'suptitle': '', + 'cmap': ['seismic', 'lightgray'], + 'mask_color': ['black', (0, 0, 0, 0)], + 'colorbar': True, + 'vmin': [-clip_value, 0], + 'vmax': [+clip_value, 1], + + 'xlabel': self.horizon.field.index_headers[0], + 'ylabel': self.horizon.field.index_headers[1], + + 'ncols': 2, + 'augment_mask': True, + **kwargs, + } + + plotter = plot([matrix, bounds], show=False, **kwargs) + + legend_kwargs = { + 'color': ('white', 'blue', 'red', 'black', 'lightgray'), + 'label': ('self.depths = other.depths', + 'self.depths < other.depths', + 'self.depths > other.depths', + 'unlabeled traces', + 'dead traces'), + 'size': 20, + 'loc': 10, + } + + plotter[1].add_legend(**legend_kwargs) + + # Histogram and labels + hist_kwargs = { + 'xlabel': 'difference values', + 'ylabel': 'counts', + 'title': 'Histogram of horizon depth differences', + 'ncols': 2, + **(hist_kwargs or {}), + } + + graph_msg = '\n'.join(msg.replace('—', '').split('\n')[5:-7]) + graph_msg = graph_msg.replace('\n' + ' '*20, ', ').replace('\t', ' ') + graph_msg = ' '.join(item for item in graph_msg.split(' ') if item).strip('\n') + + matrix = proximity_info['difference_matrix'].copy() + hist_data = np.clip(matrix, -clip_value, clip_value) + hist_data = hist_data[~np.isnan(hist_data)] + + if ignore_zeros: + zero_mask = hist_data == 0.0 + # Data can be empty in case of two identical horizons + if zero_mask.sum() != hist_data.size: + # pylint: disable=invalid-unary-operand-type + hist_data = hist_data[~zero_mask] + + graph_msg += f'\nNumber of zeros in histogram: {zero_mask.sum()}' + + hist_plotter = plot(hist_data, mode='histogram', show=show, **hist_kwargs) + hist_plotter[1].add_text(graph_msg, size=15) + + if savepath is not None: + savepath = self.horizon.field.make_path(savepath, name=self.name) + plotter.save(savepath=savepath) + hist_plotter.save(savepath=savepath.replace('.', '_histogram.')) + + returns['plotter'] = plotter + + return returns + + Horizon.compare.__doc__ = compare.__doc__ + + @staticmethod + def compute_prediction_std(horizons): + """ Compute std along depth axis of `horizons`. Used as a measurement of stability of predicitons. """ + field = horizons[0].field + fill_value = horizons[0].FILL_VALUE + + mean_matrix = np.zeros(field.spatial_shape, dtype=np.float32) + std_matrix = np.zeros(field.spatial_shape, dtype=np.float32) + counts_matrix = np.zeros(field.spatial_shape, dtype=np.int32) + + for horizon in horizons: + fm = horizon.full_matrix + mask = fm != fill_value + + mean_matrix[mask] += fm[mask] + std_matrix[mask] += fm[mask] ** 2 + counts_matrix[mask] += 1 + + mean_matrix[counts_matrix != 0] /= counts_matrix[counts_matrix != 0] + mean_matrix[counts_matrix == 0] = fill_value + + std_matrix[counts_matrix != 0] /= counts_matrix[counts_matrix != 0] + std_matrix -= mean_matrix ** 2 + std_matrix[std_matrix < 0] = 0 + std_matrix = np.sqrt(std_matrix) + std_matrix[counts_matrix == 0] = np.nan + + return std_matrix + + + +class FaultsMetrics: + """ Faults metric class. """ + SHIFTS = [-20, -15, -5, 5, 15, 20] + + def similarity_metric(self, semblance, masks, threshold=None): + """ Compute similarity metric for faults mask. """ + if threshold: + masks = masks > threshold + if semblance.ndim == 2: + semblance = np.expand_dims(semblance, axis=0) + if semblance.ndim == 3: + semblance = np.expand_dims(semblance, axis=0) + + if masks.ndim == 2: + masks = np.expand_dims(masks, axis=0) + if masks.ndim == 3: + masks = np.expand_dims(masks, axis=0) + + res = [] + m = self.sum_with_axes(masks * (1 - semblance), axes=[1,2,3]) + weights = np.ones((len(self.SHIFTS), 1)) + weights = weights / weights.sum() + for i in self.SHIFTS: + random_mask = self.make_shift(masks, shift=i) + rm = self.sum_with_axes(random_mask * (1 - semblance), axes=[1,2,3]) + ratio = m/rm + res += [np.log(ratio)] + res = np.stack(res, axis=0) + res = (res * weights).sum(axis=0) + res = np.clip(res, -2, 2) + return res + + def sum_with_axes(self, array, axes=None): + """ Sum for several axes. """ + if axes is None: + return array.sum() + if isinstance(axes, int): + axes = [axes] + res = array + axes = sorted(axes) + for i, axis in enumerate(axes): + res = res.sum(axis=axis-i) + return res + + def make_shift(self, array, shift=20): + """ Make shifts for mask. """ + result = np.zeros_like(array) + for i, _array in enumerate(array): + if shift > 0: + result[i][:, shift:] = _array[:, :-shift] + elif shift < 0: + result[i][:, :shift] = _array[:, -shift:] + else: + result[i] = _array + return result + + +class FaciesMetrics: + """ Evaluate facies metrics. + To get the value of a particular metric, use :meth:`.evaluate`:: + FaciesMetrics(horizon, true_label, pred_label).evaluate('dice') + + Parameters + horizons : :class:`.Horizon` or sequence of :class:`.Horizon` + Horizon(s) to use as base labels that contain facies. + true_labels : :class:`.Horizon` or sequence of :class:`.Horizon` + Facies to use as ground-truth labels. + pred_labels : :class:`.Horizon` or sequence of :class:`.Horizon` + Horizon(s) to use as predictions labels. + """ + def __init__(self, horizons, true_labels=None, pred_labels=None): + self.horizons = to_list(horizons) + self.true_labels = to_list(true_labels or []) + self.pred_labels = to_list(pred_labels or []) + + + @staticmethod + def true_positive(true, pred): + """ Calculate correctly classified facies pixels. """ + return np.sum(true * pred) + + @staticmethod + def true_negative(true, pred): + """ Calculate correctly classified non-facies pixels. """ + return np.sum((1 - true) * (1 - pred)) + + @staticmethod + def false_positive(true, pred): + """ Calculate misclassified facies pixels. """ + return np.sum((1 - true) * pred) + + @staticmethod + def false_negative(true, pred): + """ Calculate misclassified non-facies pixels. """ + return np.sum(true * (1 - pred)) + + def sensitivity(self, true, pred): + """ Calculate ratio of correctly classified facies points to ground-truth facies points. """ + tp = self.true_positive(true, pred) + fn = self.false_negative(true, pred) + return tp / (tp + fn) + + def specificity(self, true, pred): + """ Calculate ratio of correctly classified non-facies points to ground-truth non-facies points. """ + tn = self.true_negative(true, pred) + fp = self.false_positive(true, pred) + return tn / (tn + fp) + + def dice(self, true, pred): + """ Calculate the similarity of ground-truth facies mask and preditcted facies mask. """ + tp = self.true_positive(true, pred) + fp = self.false_positive(true, pred) + fn = self.false_negative(true, pred) + return 2 * tp / (2 * tp + fp + fn) + + + def evaluate(self, metrics): + """ Calculate desired metric and return a dataframe of results. + + Parameters + ---------- + metrics : str or list of str + Name of metric(s) to evaluate. + """ + metrics = [getattr(self, fn) for fn in to_list(metrics)] + names = [fn.__name__ for fn in metrics] + rows = [] + + for horizon, true_label, pred_label in zip_longest(self.horizons, self.true_labels, self.pred_labels): + kwargs = {} + + if true_label is not None: + true = true_label.mask[horizon.mask] + kwargs['true'] = true + + if pred_label is not None: + pred = pred_label.mask[horizon.mask] + kwargs['pred'] = pred + + values = [fn(**kwargs) for fn in metrics] + + index = pd.MultiIndex.from_arrays([[horizon.field.short_name], [horizon.short_name]], + names=['field_name', 'horizon_name']) + data = dict(zip(names, values)) + row = pd.DataFrame(index=index, data=data) + rows.append(row) + + df = pd.concat(rows) + return df diff --git a/seismiqb/nn/__init__.py b/seismiqb/nn/__init__.py new file mode 100644 index 0000000..7099633 --- /dev/null +++ b/seismiqb/nn/__init__.py @@ -0,0 +1,4 @@ +""" Submodule for NN utilities. """ +#pylint: disable=wildcard-import +from .losses import * +from .layers import * diff --git a/seismiqb/nn/layers.py b/seismiqb/nn/layers.py new file mode 100644 index 0000000..a35ee91 --- /dev/null +++ b/seismiqb/nn/layers.py @@ -0,0 +1,345 @@ +""" Special layers for geological tasks. """ +import torch +import numpy as np +from torch import nn +import torch.nn.functional as F +from torch.cuda.amp import autocast +import scipy + +from batchflow.models.torch import ResBlock + + + +class InstantaneousPhaseLayer(nn.Module): + """ Instantaneous phase computation along depth axis. + + Parameters + ---------- + inputs : torch.Tensor, optional. + + continuous : bool, optional + Transform phase from (-pi, pi) to (-pi / 2, pi / 2) to make it continuous or not, by default False. + Transformation: f(phi) = abs(phi) - pi / 2. + """ + def __init__(self, inputs=None, continuous=False, **kwargs): + super().__init__() + self.continuous = continuous + + def _hilbert(self, x): + """ Hilbert transformation. """ + N = x.shape[-1] + fft = torch.fft.fft(x) + + h = torch.zeros(N, device=x.device) + if N % 2 == 0: + h[0] = h[N // 2] = 1 + h[1:N // 2] = 2 + else: + h[0] = 1 + h[1:(N + 1) // 2] = 2 + if x.ndim > 1: + shape = [1] * x.ndim + shape[-1] = N + h = h.view(*shape) + + result = torch.fft.ifft(fft * h) + return result + + def _angle(self, x): + """ Compute angle of complex number. """ + res = torch.atan(x.imag / x.real) + res[x.real == 0] = np.pi + res = res % (2 * np.pi) - np.pi + if self.continuous: + res = torch.abs(res) - np.pi / 2 + return res + + def forward(self, x): + """ Forward pass. """ + x = self._hilbert(x) + x = self._angle(x) + return x + + +class MovingNormalizationLayer(nn.Module): + """ Normalize tensor by mean/std in moving window. + + Parameters + ---------- + inputs : torch.Tensor, optional + + window : tuple, optional + window shape to compute statistics, by default (1, 1, 100). + padding : str, optional + 'valid' or 'same, by default 'same'. + fill_value : int, optional + Value to fill constant regions with std=0, by default 0. + """ + def __init__(self, inputs, window=(1, 1, 100), padding='same', fill_value=0): + super().__init__() + self.window = window + self.fill_value = fill_value + self.ndim = inputs.ndim + + self.kernel = torch.nn.Parameter( + torch.ones((1, 1, *window), dtype=inputs.dtype).cuda(), requires_grad=False + ) + + if padding == 'same': + pad = [(w // 2, w - w // 2 - 1) for w in self.window] + self.padding = (*pad[2], *pad[1], *pad[0], 0, 0, 0, 0) + else: + padding = None + + def init_normalizer_map(self, inputs): + """ Create normalization map. """ + normalizer = torch.ones(expand_dims(inputs[:1]).shape, dtype=inputs.dtype, requires_grad=False) + normalizer = F.pad(normalizer.to(inputs.device), self.padding) + return F.conv3d(normalizer, self.kernel)[0] + + @autocast(enabled=False) + def forward(self, x): + """ Forward pass. """ + normalization_map = self.init_normalizer_map(x) + + x = expand_dims(x) + + if self.padding is None: + num = x + else: + num = F.pad(x, self.padding) + + mean = F.conv3d(num, self.kernel) / normalization_map + mean_2 = F.conv3d(num ** 2, self.kernel) / normalization_map + std = torch.clip(mean_2 - mean ** 2, min=1e-10) ** 0.5 + + pad = self.padding + if self.padding == 'valid': + x = x[:, :, pad[4]:x.shape[2]-pad[5], pad[2]:x.shape[3]-pad[3], pad[0]:x.shape[4]-pad[1]] + result = (x - mean) / std + result = torch.nan_to_num(result, nan=self.fill_value) + return squeeze(result, self.ndim) + +class SemblanceLayer(nn.Module): + """ Semblance attribute. + + Parameters + ---------- + inputs : torch.Tensor, optional. + + window : tuple, optional + Window shape to compute attribute, by default (1, 5, 20). + fill_value : int, optional + Value to fill constant regions, by default 1. + """ + def __init__(self, inputs, window=(1, 5, 20), fill_value=1): + super().__init__() + self.ndim = inputs.ndim + self.window = window + self.fill_value = fill_value + self.device = inputs.device + + self.kernels = [ + torch.ones((1, 1, window[0], window[1], 1), dtype=inputs.dtype, requires_grad=False).to(self.device), + torch.ones((1, 1, 1, 1, window[2]), dtype=inputs.dtype, requires_grad=False).to(self.device), + torch.ones((1, 1, *window), dtype=inputs.dtype, requires_grad=False).to(self.device), + torch.ones((1, 1, window[0], window[1]), dtype=inputs.dtype, requires_grad=False).to(self.device) + ] + + def forward(self, x): + """ Forward pass. """ + window = self.window + x = expand_dims(x) + + padding = [(w // 2, w - w // 2 - 1) for w in window] + num = F.pad(x, (0, 0, *padding[1], *padding[0], 0, 0, 0, 0)) + num = F.conv3d(num, self.kernels[0]) ** 2 + + num = F.pad(num, (*padding[2], 0, 0, 0, 0, 0, 0, 0, 0)) + num = F.conv3d(num, self.kernels[1]) + + denum = F.pad(x, (*padding[2], *padding[1], *padding[0], 0, 0, 0, 0)) + denum = F.conv3d(denum ** 2, self.kernels[2]) + + normilizing = torch.ones(x.shape[:-1], dtype=x.dtype, requires_grad=False).to(x.device) + normilizing = F.pad(normilizing, (*padding[1], *padding[0], 0, 0, 0, 0)) + normilizing = F.conv2d(normilizing, self.kernels[3]) + + denum *= normilizing.view(*normilizing.shape, 1) + result = torch.nan_to_num(num / denum, nan=self.fill_value) + + return squeeze(result, self.ndim) + +class FrequenciesFilterLayer(nn.Module): + """ Frequencies filter. + + Parameters + ---------- + inputs : torch.Tensor, optional + + q : float, optional + Left quantile, by default 0.1. The right quantile will be `1 - q`. + window : int, optional + Window width (corresponds to depth axis) to compute phases, by default 200. + """ + def __init__(self, inputs=None, q=0.1, window=200): + super().__init__() + self.q = q + self.window = window + + def forward(self, inputs): + """ Forward pass. """ + inputs = inputs.view(-1, inputs.shape[-1]) + # TODO: remove disable after torch update + sfft = torch.stft(inputs, self.window, return_complex=True) #pylint: disable=unexpected-keyword-arg + q_ = int(sfft.shape[-2] * self.q) + sfft[:, :q_] = 0 + sfft[:, -q_:] = 0 + return torch.istft(sfft, self.window).view(*inputs.shape) + + +class InputLayer(nn.Module): + """ Input layer with possibility of instantaneous phase concatenation. + + Parameters + ---------- + inputs : torch.Tensor + + normalization : bool, optional + Normalize input or nor, by default False. + phases : bool, optional + Concat instantaneous phases to input or not, by default False. + continuous : bool, optional + Make phases continuous or not, by default False. + window : int, optional + Normalization window, by default 100 + base_block : torch.nn.Module, optional + Inputs transformations block, by default ResBlock. + """ + def __init__(self, inputs, normalization=False, phases=False, continuous=False, + window=100, base_block=ResBlock, **kwargs): + super().__init__() + self.normalization = normalization + self.phases = phases + if self.normalization: + self.normalization_layer = MovingNormalizationLayer(inputs, window) + if self.phases: + self.phase_layer = InstantaneousPhaseLayer(continuous) + phases_ = self.phase_layer(inputs) + inputs = self._concat(inputs, phases_) + self.base_block = base_block(inputs, **kwargs) + + def _concat(self, x, phases): + x = torch.cat([x, phases], dim=1) + return x + + def forward(self, x): + """ Forward pass. """ + if self.phases: + phases = self.phase_layer(x) + + if self.normalization: + x = self.normalization_layer(x) + x = torch.clip(x, -10, 10) # TODO: remove clipping + + if self.phases: + x = self._concat(x, phases) + + x = self.base_block(x) + return x + + +class GaussianLayer(nn.Module): + """ Layer for gaussian smoothing. + + Parameters + ---------- + inputs : torch.Tensor + + kernel_size : int, optional + kernel size, by default 5. + padding : str, optional + 'valid' or 'same, by default 'same'. + sigma : float or None, optional + + """ + def __init__(self, inputs, kernel_size=5, sigma=None, padding='same'): + super().__init__() + self.ndim = inputs.ndim + if isinstance(kernel_size, int): + kernel_size = [kernel_size] * 3 + kernel_size = np.array(kernel_size) + + if isinstance(sigma, (int, float)): + sigma = [sigma] * 3 + elif sigma is None: + sigma = kernel_size // 6 + sigma = np.array(sigma) + + kernel = self.gaussian_kernel(kernel_size, sigma) + kernel = np.expand_dims(kernel, axis=[0, 1]) + + self.kernel_size = kernel_size + if padding == 'same': + self.padding = [(w // 2, w - w // 2 - 1) for w in self.kernel_size] + elif padding == 'valid': + self.padding = None + else: + self.padding = padding + self.kernel = torch.nn.parameter.Parameter( + torch.tensor(kernel, dtype=inputs.dtype), requires_grad=False + ).to(inputs.device) + + def forward(self, x): + """ Forward pass. """ + x = expand_dims(x) + if self.padding is not None: + x = F.pad(x, (*self.padding[2], *self.padding[1], *self.padding[0], 0, 0, 0, 0)) + return squeeze(F.conv3d(x, self.kernel), self.ndim) + + def gaussian_kernel(self, kernel_size, sigma=None): + """ Create gaussian kernel of the specified size. """ + n = np.zeros(kernel_size) + n[tuple(np.array(n.shape) // 2)] = 1 + return scipy.ndimage.gaussian_filter(n, sigma=sigma) + + +def expand_dims(x): + """ Make tensor 5D. """ + if x.ndim == 4: + x = x.view(x.shape[0], 1, *x.shape[-3:]) + elif x.ndim == 3: + x = x.view(1, 1, *x.shape) + elif x.ndim == 2: + x = x.view(1, 1, 1, *x.shape) + return x + +def squeeze(x, ndim): + """ Squeeze axes after :func:`~expand_dims`. """ + if ndim == 4: + return x[:, 0] + if ndim == 3: + return x[0, 0] + if ndim == 2: + return x[0, 0, 0] + return x + + + +def compute_attribute(array, window=None, device='cuda:0', attribute='semblance', fill_value=None, **kwargs): + """ Compute semblance for the cube. """ + if isinstance(window, int): + window = np.ones(3, dtype=np.int32) * window + window = np.minimum(np.array(window), array.shape[-3:]) + inputs = torch.Tensor(array).to(device) + + if attribute == 'semblance': + layer = SemblanceLayer(inputs, window=window, fill_value=fill_value or 1) + elif attribute == 'moving_normalization': + layer = MovingNormalizationLayer(inputs, window=window, fill_value=fill_value or 1, **kwargs) + elif attribute == 'phase': + layer = InstantaneousPhaseLayer(inputs, **kwargs) + elif attribute == 'frequencies_filter': + layer = FrequenciesFilterLayer(inputs, window=window, **kwargs) + result = layer(inputs) + return result.cpu().numpy() diff --git a/seismiqb/nn/losses.py b/seismiqb/nn/losses.py new file mode 100644 index 0000000..2baa6e9 --- /dev/null +++ b/seismiqb/nn/losses.py @@ -0,0 +1,26 @@ +""" Loss functions for seismic interpretation tasks. """ +import torch +from torch import nn +import torch.nn.functional as F + + + +class DepthSoftmax(nn.Module): + """ Softmax activation for depth dimension. + + Parameters + ---------- + width : int + The predicted horizon width. Default is 3. + """ + def __init__(self, width=3): + super().__init__() + self.width_weights = torch.ones((1, 1, 1, width)) + + @torch.cuda.amp.autocast(enabled=False) + def forward(self, x): + """ Forward pass. """ + x = torch.nn.functional.softmax(x, dim=-1) + width_weights = self.width_weights.to(device=x.device, dtype=x.dtype) + x = F.conv2d(x, width_weights, padding=(0, 1)) + return x.float() diff --git a/seismiqb/nn/utils.py b/seismiqb/nn/utils.py new file mode 100644 index 0000000..eb0ebfe --- /dev/null +++ b/seismiqb/nn/utils.py @@ -0,0 +1,171 @@ +""" Helper function for models validation.""" +import os + +import numpy as np +from scipy.ndimage import find_objects, gaussian_filter +from scipy.ndimage.morphology import binary_dilation +from scipy.signal import find_peaks +from skimage.measure import label + +from batchflow import Pipeline, B +from batchflow.models.torch import TorchModel + +from .. import SeismicDataset, RegularGrid +from ..utils import Accumulator3D, take_along_axis + + +def make_slide_prediction(field, model_or_path, index, axis=0, + batch_size=64, crop_shape=(1, 256, 512), + inference_3d=True, inference_width=10, + minsize=5, threshold=0.1, dilation_iterations=1): + """ Make model inference on a field slide. + + Parameters + ---------- + field : instance of :class:`seismiqb.Field` + Field from which to get a slide. + model_or_path : str or instance of :class:`batchflow.TorchModel` + Model to use or path to a file from which initialize a model. + index : int + Number of slide. + axis : int + Number of axis to load slide along. + batch_size : int + Number of batches to generate for a slide. Affects inference speed and memory used. + crop_shape : tuple of ints + Shape of crop locations to generate for a slide. + Recommended to use the same `crop_shape` as for model training. Otherwise, can affect the prediction quality. + inference_3d : bool + Whether to apply inference on orthogonal projection. + If True, then prediction is smoothed depend on both projections inference. + inference_width : int + Amount of neighboring slides to infer. Affects prediction smoothing. + minsize : int + Objects with size less then minsize will be removed from prediction. + threshold : float or None + Values threshold to binarize prediction. If None, then no binarization applied. + dilation_iterations : int + Number of dilation iterations to apply. Makes predictions more visible. + Note, that it is applied only to binary predictions. + """ + # Prepare inference parameters + ranges = [None, None, None] + ranges[axis] = [index - inference_width, index + inference_width + 1] + + grid = RegularGrid(field=field, + threshold=0, orientation=axis, + ranges=ranges, + batch_size=batch_size, + crop_shape=crop_shape, overlap_factor=2) + + if inference_3d: + grid_other = RegularGrid(field=field, + threshold=0, orientation=1-axis, + ranges=ranges, + batch_size=batch_size, + crop_shape=crop_shape, overlap_factor=2) + grid += grid_other + + accumulator = Accumulator3D.from_grid(grid=grid, aggregation='weighted', fill_value=0) + + # Inference + model = TorchModel(model_or_path) if isinstance(model_or_path, str) else model_or_path + + inference_pipeline = ( + Pipeline() + .make_locations(generator=grid, batch_size=batch_size) + .load_cubes(dst='images') + .normalize(src='images') + + .import_model(name='model', source=model) + .predict_model('model', inputs=B('images'), outputs='sigmoid', save_to=B('predictions')) + .update_accumulator(src='predictions', accumulator=accumulator) + ) << SeismicDataset(field) + + inference_pipeline.run(n_iters=grid.n_iters, notifier='t', pbar=False) + prediction = accumulator.aggregate() + + # Smoothing + prediction = gaussian_filter(prediction, sigma=1.5) + + # Peaking + prediction[prediction < 0.1] = 0.0 + peaked = np.zeros_like(prediction) + + for i in range(prediction.shape[0]): + for x in range(prediction.shape[1]): + trace = prediction[i, x, :] + peaks, _ = find_peaks(trace, prominence=0.15, width=2) + peaked[i, x, peaks] = 1 + prediction = take_along_axis(peaked, index=inference_width, axis=axis) + + # Filter small objects + labeled = label(prediction, connectivity=2) + objects = find_objects(labeled) + + for i, slc in enumerate(objects): + indices = np.nonzero(labeled[slc] == i + 1) + + if len(indices[0]) <= minsize: + coords = tuple(indices[i] + slc[i].start for i in range(2)) + prediction[coords] = 0 + + # Modify slice + prediction = (prediction > threshold).astype(np.int32) + prediction = binary_dilation(prediction, iterations=dilation_iterations).astype(np.float32) + return prediction + + +def plot_slide_prediction(field, index, axis, prediction, zoom='auto', show=True, savepath=None, **kwargs): + """ Plot prediction on a field slide. + + Parameters + ---------- + field : instance of :class:`seismiqb.Field` + Field from which to get a slide. + index : int + Number of slide. + axis : int + Number of axis to load slide along. + prediction : np.ndarray + Prediction slide to plot on the field slide. + zoom : tuple of slices, None or 'auto' + Tuple of slices to apply directly to 2d images. + If None, slicing is not applied. + If 'auto', zero traces on bounds will be dropped. + show : bool + Whether to show plot. + savepath : str or None + Path to a file or directory to save plot (if provided). + kwargs : dict + Other parameters to pass to the plotting function. + """ + prediction[prediction == 0] = np.nan # For correct visualization + + # Parse parameters + if zoom is None: + zoom = (slice(None), slice(None)) + + if (savepath is not None) and os.path.isdir(savepath): + filename = f'{field.short_name}_axis_{axis}_index_{index}_zoom_{zoom}.png' + savepath = os.path.join(savepath, filename) + + if savepath is not None: + kwargs['savepath'] = savepath + + if kwargs.get('indices', None) is None: + # disable labels drawing on the slide by default + kwargs['indices'] = () + + # Plotting + plotter = field.show_slide(index=index, axis=axis, show=False, zoom=zoom, + suptitle_size=4, suptitle_y=0.88, + title=None, suptitle=None, + **kwargs) + plotter.plot(prediction.T, cmap='darkorange') + if show: + plotter.redraw() + + if savepath is not None: + plotter.config.update(plotter[0][0].config) + plotter.save() diff --git a/seismiqb/plotters/__init__.py b/seismiqb/plotters/__init__.py new file mode 100644 index 0000000..aaeefbf --- /dev/null +++ b/seismiqb/plotters/__init__.py @@ -0,0 +1,5 @@ +""" Init file. """ +# pylint: disable=wildcard-import +from .plot import plot +from .show_3d import show_3d +from .cmaps import * diff --git a/seismiqb/plotters/cmaps.py b/seismiqb/plotters/cmaps.py new file mode 100644 index 0000000..06b2666 --- /dev/null +++ b/seismiqb/plotters/cmaps.py @@ -0,0 +1,255 @@ +""" Predefined colormaps. """ +import numpy as np + +from matplotlib.colors import LinearSegmentedColormap, ListedColormap, ColorConverter +from matplotlib.cm import register_cmap, get_cmap + + + +def clist2cdict(clist): + """ Convert list of colors to dict of colors valid for `LinearSegmentedColormap`. """ + cdict = {'red': [], 'green': [], 'blue': []} + domain = np.linspace(0, 1, len(clist)) + for x, color in zip(domain, clist): + cdict['red'].append([x, color[0], color[0]]) + cdict['green'].append([x, color[1], color[1]]) + cdict['blue'].append([x, color[2], color[2]]) + return cdict + + +DEPTHS_CMAP = get_cmap('summer_r') +register_cmap('Depths', DEPTHS_CMAP) + + +METRIC_CDICT = { + 'red': [[0.0, None, 1.0], [0.33, 1.0, 1.0], [0.66, 1.0, 1.0], [1.0, 0.0, None]], + 'green': [[0.0, None, 0.0], [0.33, 0.0, 0.0], [0.66, 1.0, 1.0], [1.0, 0.5, None]], + 'blue': [[0.0, None, 0.0], [0.33, 0.0, 0.0], [0.66, 0.0, 0.0], [1.0, 0.0, None]] +} +METRIC_CMAP = LinearSegmentedColormap('Metric', METRIC_CDICT) +METRIC_CMAP.set_bad(color='black') +register_cmap(name='Metric', cmap=METRIC_CMAP) + + +SAMPLER_CMAP = ListedColormap([ColorConverter().to_rgb('blue'), + ColorConverter().to_rgb('red'), + ColorConverter().to_rgb('purple')]) +register_cmap(name='Sampler', cmap=SAMPLER_CMAP) + + +SEISMIC_CLIST = [ + (0.15, 0.22, 0.48), + (0.5, 0.7, 0.8), + (0.9, 0.9, 0.9), + (0.75, 0.25, 0.25), + (0.75, 0.0, 0.25) +] +SEISMIC_CMAP = LinearSegmentedColormap('Seismic', clist2cdict(SEISMIC_CLIST)) +register_cmap('Seismic', SEISMIC_CMAP) + + +SEISMIC2_CDICT = { + 'red': [[0.0, None, 0.0], [0.25, 0.5, 0.5], [0.5, 1., 1], [0.75, 0.75, 0.75], [1.0, 1, None]], + 'green': [[0.0, None, 0.0], [0.25, 0.5, 0.5], [0.5, 1., 1], [0.75, 0.25, 0.25], [1.0, 0., None]], + 'blue': [[0.0, None, 1.0], [0.25, 0.5, 0.5], [0.5, 1., 1], [0.75, 0., 0.0], [1.0, 0.0, None]], +} +SEISMIC2_CMAP = LinearSegmentedColormap('Seismic2', SEISMIC2_CDICT) +register_cmap(name='Seismic2', cmap=SEISMIC2_CMAP) + + +PETREL_COLORS = [ # 32:-32 slice of all Petrel colors + [0.4824, 0.7686, 0.9412, 1.0], + [0.4784, 0.7608, 0.9412, 1.0], + [0.4706, 0.749, 0.9373, 1.0], + [0.4667, 0.7412, 0.9333, 1.0], + [0.4588, 0.7294, 0.9333, 1.0], + [0.4549, 0.7216, 0.9294, 1.0], + [0.4471, 0.7098, 0.9294, 1.0], + [0.4431, 0.702, 0.9255, 1.0], + [0.4353, 0.6941, 0.9216, 1.0], + [0.4314, 0.6824, 0.9216, 1.0], + [0.4235, 0.6706, 0.9176, 1.0], + [0.4157, 0.6627, 0.9137, 1.0], + [0.4078, 0.651, 0.9137, 1.0], + [0.4039, 0.6392, 0.9098, 1.0], + [0.3961, 0.6275, 0.9059, 1.0], + [0.3882, 0.6157, 0.9059, 1.0], + [0.3804, 0.6078, 0.902, 1.0], + [0.3765, 0.5961, 0.898, 1.0], + [0.3686, 0.5843, 0.8941, 1.0], + [0.3608, 0.5725, 0.8941, 1.0], + [0.3529, 0.5608, 0.8902, 1.0], + [0.3451, 0.5451, 0.8863, 1.0], + [0.3373, 0.5333, 0.8824, 1.0], + [0.3294, 0.5216, 0.8824, 1.0], + [0.3216, 0.5098, 0.8784, 1.0], + [0.3137, 0.4941, 0.8745, 1.0], + [0.302, 0.4824, 0.8706, 1.0], + [0.2941, 0.4667, 0.8667, 1.0], + [0.2863, 0.4549, 0.8627, 1.0], + [0.2784, 0.4392, 0.8588, 1.0], + [0.2667, 0.4275, 0.8549, 1.0], + [0.2588, 0.4118, 0.851, 1.0], + [0.251, 0.3961, 0.851, 1.0], + [0.2392, 0.3804, 0.8471, 1.0], + [0.2314, 0.3647, 0.8431, 1.0], + [0.2196, 0.349, 0.8392, 1.0], + [0.2118, 0.3333, 0.8353, 1.0], + [0.2, 0.3176, 0.8275, 1.0], + [0.1882, 0.298, 0.8235, 1.0], + [0.1765, 0.2824, 0.8196, 1.0], + [0.1686, 0.2667, 0.8157, 1.0], + [0.1569, 0.2471, 0.8118, 1.0], + [0.1451, 0.2314, 0.8078, 1.0], + [0.1333, 0.2118, 0.8039, 1.0], + [0.1216, 0.1922, 0.7961, 1.0], + [0.1098, 0.1725, 0.7922, 1.0], + [0.0941, 0.1529, 0.7882, 1.0], + [0.0824, 0.1333, 0.7843, 1.0], + [0.0706, 0.1137, 0.7765, 1.0], + [0.0549, 0.0902, 0.7725, 1.0], + [0.0431, 0.0667, 0.7686, 1.0], + [0.0314, 0.0471, 0.7608, 1.0], + [0.0157, 0.0235, 0.7569, 1.0], + [0.0, 0.0, 0.749, 1.0], + [0.0196, 0.0196, 0.7216, 1.0], + [0.0353, 0.0353, 0.698, 1.0], + [0.051, 0.051, 0.6706, 1.0], + [0.0706, 0.0706, 0.6431, 1.0], + [0.0863, 0.0863, 0.6196, 1.0], + [0.1059, 0.1059, 0.5922, 1.0], + [0.1255, 0.1255, 0.5647, 1.0], + [0.1412, 0.1412, 0.5412, 1.0], + [0.1569, 0.1569, 0.5137, 1.0], + [0.1765, 0.1765, 0.4863, 1.0], + [0.1922, 0.1922, 0.4588, 1.0], + [0.2118, 0.2118, 0.4314, 1.0], + [0.2275, 0.2275, 0.4078, 1.0], + [0.2471, 0.2471, 0.3804, 1.0], + [0.2627, 0.2627, 0.3529, 1.0], + [0.2824, 0.2824, 0.3255, 1.0], + [0.302, 0.302, 0.302, 1.0], + [0.3176, 0.3176, 0.3176, 1.0], + [0.3373, 0.3373, 0.3373, 1.0], + [0.3608, 0.3608, 0.3608, 1.0], + [0.3765, 0.3765, 0.3765, 1.0], + [0.3961, 0.3961, 0.3961, 1.0], + [0.4196, 0.4196, 0.4196, 1.0], + [0.4353, 0.4353, 0.4353, 1.0], + [0.4549, 0.4549, 0.4549, 1.0], + [0.4784, 0.4784, 0.4784, 1.0], + [0.4941, 0.4941, 0.4941, 1.0], + [0.5137, 0.5137, 0.5137, 1.0], + [0.5373, 0.5373, 0.5373, 1.0], + [0.5529, 0.5529, 0.5529, 1.0], + [0.5725, 0.5725, 0.5725, 1.0], + [0.5961, 0.5961, 0.5961, 1.0], + [0.6118, 0.6118, 0.6118, 1.0], + [0.6353, 0.6353, 0.6353, 1.0], + [0.6549, 0.6549, 0.6549, 1.0], + [0.6745, 0.6745, 0.6745, 1.0], + [0.6941, 0.6941, 0.6941, 1.0], + [0.7137, 0.7137, 0.7137, 1.0], + [0.7333, 0.7333, 0.7333, 1.0], + [0.7529, 0.7529, 0.7529, 1.0], + [0.7725, 0.7725, 0.7725, 1.0], + [0.7922, 0.7922, 0.7922, 1.0], + [0.7922, 0.7882, 0.7843, 1.0], + [0.7765, 0.7686, 0.7529, 1.0], + [0.7569, 0.7451, 0.7216, 1.0], + [0.7412, 0.7255, 0.6902, 1.0], + [0.7255, 0.7059, 0.6588, 1.0], + [0.7098, 0.6863, 0.6275, 1.0], + [0.6941, 0.6667, 0.5961, 1.0], + [0.6745, 0.6431, 0.5647, 1.0], + [0.6588, 0.6235, 0.5333, 1.0], + [0.6431, 0.6, 0.502, 1.0], + [0.6275, 0.5804, 0.4706, 1.0], + [0.6118, 0.5608, 0.4392, 1.0], + [0.5922, 0.5373, 0.4078, 1.0], + [0.5765, 0.5176, 0.3765, 1.0], + [0.5608, 0.498, 0.3451, 1.0], + [0.5451, 0.4784, 0.3137, 1.0], + [0.5294, 0.4549, 0.2824, 1.0], + [0.5098, 0.4353, 0.251, 1.0], + [0.4941, 0.4157, 0.2196, 1.0], + [0.4784, 0.3961, 0.1882, 1.0], + [0.4627, 0.3725, 0.1569, 1.0], + [0.4471, 0.3529, 0.1255, 1.0], + [0.4275, 0.3333, 0.0941, 1.0], + [0.4118, 0.3098, 0.0627, 1.0], + [0.3961, 0.2902, 0.0314, 1.0], + [0.3804, 0.2706, 0.0, 1.0], + [0.4039, 0.2549, 0.0, 1.0], + [0.4235, 0.2392, 0.0, 1.0], + [0.4471, 0.2196, 0.0, 1.0], + [0.4667, 0.2078, 0.0, 1.0], + [0.4902, 0.1882, 0.0, 1.0], + [0.5098, 0.1725, 0.0, 1.0], + [0.5333, 0.1569, 0.0, 1.0], + [0.5529, 0.1412, 0.0, 1.0], + [0.5765, 0.1255, 0.0, 1.0], + [0.5961, 0.1098, 0.0, 1.0], + [0.6196, 0.0941, 0.0, 1.0], + [0.6431, 0.0784, 0.0, 1.0], + [0.6627, 0.0627, 0.0, 1.0], + [0.6863, 0.0471, 0.0, 1.0], + [0.7059, 0.0314, 0.0, 1.0], + [0.7294, 0.0157, 0.0, 1.0], + [0.749, 0.0, 0.0, 1.0], + [0.7569, 0.0235, 0.0, 1.0], + [0.7608, 0.0471, 0.0, 1.0], + [0.7686, 0.0667, 0.0, 1.0], + [0.7725, 0.0902, 0.0, 1.0], + [0.7765, 0.1137, 0.0, 1.0], + [0.7843, 0.1333, 0.0, 1.0], + [0.7882, 0.1529, 0.0, 1.0], + [0.7922, 0.1725, 0.0, 1.0], + [0.7961, 0.1922, 0.0, 1.0], + [0.8039, 0.2118, 0.0, 1.0], + [0.8078, 0.2314, 0.0, 1.0], + [0.8118, 0.2471, 0.0, 1.0], + [0.8157, 0.2667, 0.0, 1.0], + [0.8196, 0.2824, 0.0, 1.0], + [0.8235, 0.298, 0.0, 1.0], + [0.8275, 0.3176, 0.0, 1.0], + [0.8353, 0.3333, 0.0, 1.0], + [0.8392, 0.349, 0.0, 1.0], + [0.8431, 0.3647, 0.0, 1.0], + [0.8471, 0.3804, 0.0, 1.0], + [0.851, 0.3961, 0.0, 1.0], + [0.851, 0.4118, 0.0, 1.0], + [0.8549, 0.4275, 0.0, 1.0], + [0.8588, 0.4392, 0.0, 1.0], + [0.8627, 0.4549, 0.0, 1.0], + [0.8667, 0.4706, 0.0, 1.0], + [0.8706, 0.4824, 0.0, 1.0], + [0.8745, 0.4941, 0.0, 1.0], + [0.8784, 0.5098, 0.0, 1.0], + [0.8824, 0.5216, 0.0, 1.0], + [0.8824, 0.5333, 0.0, 1.0], + [0.8863, 0.549, 0.0, 1.0], + [0.8902, 0.5608, 0.0, 1.0], + [0.8941, 0.5725, 0.0, 1.0], + [0.8941, 0.5843, 0.0, 1.0], + [0.898, 0.5961, 0.0, 1.0], + [0.902, 0.6078, 0.0, 1.0], + [0.9059, 0.6196, 0.0, 1.0], + [0.9059, 0.6275, 0.0, 1.0], + [0.9098, 0.6392, 0.0, 1.0], + [0.9137, 0.651, 0.0, 1.0], + [0.9137, 0.6627, 0.0, 1.0], + [0.9176, 0.6706, 0.0, 1.0], + [0.9216, 0.6824, 0.0, 1.0], + [0.9216, 0.6941, 0.0, 1.0], + [0.9255, 0.702, 0.0, 1.0], + [0.9294, 0.7137, 0.0, 1.0], + [0.9294, 0.7216, 0.0, 1.0], + [0.9333, 0.7333, 0.0, 1.0], + [0.9333, 0.7412, 0.0, 1.0], + [0.9373, 0.749, 0.0, 1.0], + [0.9412, 0.7608, 0.0, 1.0], + [0.9412, 0.7686, 0.0, 1.0], + ] +PETREL_CMAP = ListedColormap(PETREL_COLORS, name='Petrel') +register_cmap(name='Petrel', cmap=PETREL_CMAP) diff --git a/seismiqb/plotters/plot.py b/seismiqb/plotters/plot.py new file mode 100644 index 0000000..c722604 --- /dev/null +++ b/seismiqb/plotters/plot.py @@ -0,0 +1,20 @@ +""" Plotter with redefined defaults. """ +import batchflow + + + +class plot(batchflow.plotter.plot): + """ Wrapper over original `plot` with custom defaults. """ + COMMON_DEFAULTS = { + **batchflow.plotter.plot.COMMON_DEFAULTS, + 'suptitle_size': 30, + } + + IMAGE_DEFAULTS = { + **batchflow.plotter.plot.IMAGE_DEFAULTS, + 'labeltop': True, + 'labelright': True, + 'xlabel_size': 22, + 'ylabel_size': 22, + 'transpose': (1, 0, 2) + } diff --git a/seismiqb/plotters/show_3d.py b/seismiqb/plotters/show_3d.py new file mode 100644 index 0000000..5ecd2c3 --- /dev/null +++ b/seismiqb/plotters/show_3d.py @@ -0,0 +1,154 @@ +""" 3D surface plotting. """ +import os + +import cv2 +import numpy as np +import matplotlib.pyplot as plt +try: + import plotly.figure_factory as ff + import plotly.graph_objects as go + PLOTLY_AVAILABLE = True +except ImportError: + PLOTLY_AVAILABLE = False + +from matplotlib.cm import get_cmap + + + +def show_3d(x, y, z, simplices, title, zoom, colors=None, show_axes=True, aspect_ratio=(1, 1, 1), + axis_labels=None, width=1200, height=1200, margin=(0, 0, 20), savepath=None, + images=None, bounds=False, resize_factor=2, colorscale='Greys', show=True, camera=None, **kwargs): + """ Interactive 3D plot for some elements of cube. + + Parameters + ---------- + x, y, z : numpy.ndarrays + Triangle vertices. + simplices : numpy.ndarray + (N, 3) array where each row represent triangle. Elements of row are indices of points + that are vertices of triangle. + title : str + Title of plot. + zoom : tuple of slices + Crop from cube to show. + colors : list or None + List of colors for each simplex. + show_axes : bool + Whether to show axes and their labels. + aspect_ratio : tuple of floats. + Aspect ratio for each axis. + axis_labels : tuple + Titel for each axis. + width, height : number + Size of the image. + margin : tuple of ints + Added margin for each axis, by default, (0, 0, 20). + savepath : str + Path to save interactive html to. + images : list of tuples + Each tuple is triplet of image, location and axis to load slide from seismic cube. + bounds : bool or int + Whether to draw bounds on slides. If int, width of the border. + resize_factor : float + Resize factor for seismic slides. Is needed to spedify loading and ploting of seismic slices. + colorscale : str + Colormap for seismic slides. + show : bool + Whether to show figure. + camera : dict + Parameters for initial camera view. + kwargs : dict + Other arguments of plot creation. + """ + #pylint: disable=too-many-arguments + if not PLOTLY_AVAILABLE: + raise ImportError('Install `plotly` to use 3d interactive viewer!') + + # Arguments of graph creation + kwargs = { + 'title': title, + 'colormap': [plt.get_cmap('Depths')(x) for x in np.linspace(0, 1, 10)], + 'edges_color': 'rgb(70, 40, 50)', + 'show_colorbar': False, + 'width': width, + 'height': height, + 'aspectratio': {'x': aspect_ratio[0], 'y': aspect_ratio[1], 'z': aspect_ratio[2]}, + **kwargs + } + cmin, cmax = kwargs.pop('cmin', None), kwargs.pop('cmax', None) + if isinstance(colorscale, str) and colorscale in plt.colormaps(): + cmap = get_cmap(colorscale) + levels = np.arange(0, 256, 1) / 255 + colorscale = [ + (level, f'rgb({r * 255}, {g * 255}, {b * 255})') + for (r, g, b, _), level in zip(cmap(levels), levels) + ] + + if simplices is not None: + if colors is not None: + fig = ff.create_trisurf(x=x, y=y, z=z, color_func=colors, simplices=simplices, **kwargs) + else: + fig = ff.create_trisurf(x=x, y=y, z=z, simplices=simplices, **kwargs) + else: + fig = go.Figure() + if images is not None: + for image, loc, axis in images: + shape = image.shape + if resize_factor != 1: + image = cv2.resize(image.astype('float32'), tuple(np.array(shape)[::-1] // resize_factor)) + image = image[::-1] + if bounds: + bounds = int(bounds) + fill = cmax if cmax is not None else image.max() + image[:bounds, :] = fill + image[-bounds:, :] = fill + image[:, :bounds] = fill + image[:, -bounds:] = fill + + grid = np.meshgrid( + np.linspace(0, shape[0], image.shape[0]), + np.linspace(0, shape[1], image.shape[1]) + ) + if axis == 0: + x, y, z = loc * np.ones_like(image), grid[0].T + zoom[1].start, grid[1].T + zoom[2].start + elif axis == 1: + y, x, z = loc * np.ones_like(image), grid[0].T + zoom[0].start, grid[1].T + zoom[2].start + else: + z, x, y = loc * np.ones_like(image), grid[0].T + zoom[0].start, grid[1].T + zoom[1].start + + fig.add_surface(x=x, y=y, z=z, surfacecolor=np.flipud(image), cmin=cmin, cmax=cmax, + showscale=False, colorscale=colorscale) + # Update scene with title, labels and axes + fig.update_layout( + { + 'width': kwargs['width'], + 'height': kwargs['height'], + 'scene': { + 'xaxis': { + 'title': axis_labels[0] if show_axes else '', + 'showticklabels': show_axes, + 'range': [zoom[0].stop + margin[0], zoom[0].start - margin[0]] + }, + 'yaxis': { + 'title': axis_labels[1] if show_axes else '', + 'showticklabels': show_axes, + 'range': [zoom[1].start - margin[1], zoom[1].stop + margin[1]] + }, + 'zaxis': { + 'title': axis_labels[2] if show_axes else '', + 'showticklabels': show_axes, + 'range': [zoom[2].stop + margin[2], zoom[2].start - margin[2]] + }, + 'camera': camera or {'eye': {"x": 1.25, "y": 1.5, "z": 1.5}}, + } + } + ) + if show: + fig.show() + + if isinstance(savepath, str): + ext = os.path.splitext(savepath)[1][1:] + if ext == 'html': + fig.write_html(savepath) + elif ext in ['png', 'jpg', 'jpeg', 'pdf']: + fig.write_image(savepath, format=ext) diff --git a/seismiqb/samplers.py b/seismiqb/samplers.py new file mode 100644 index 0000000..1152ef4 --- /dev/null +++ b/seismiqb/samplers.py @@ -0,0 +1,1027 @@ +""" Generator of (label-dependant) randomized locations, mainly for model training. + +Locations describe the cube and the exact place to load from in the following format: +(field_id, label_id, orientation, i_start, x_start, d_start, i_stop, x_stop, d_stop). + +Locations are passed to `make_locations` method of `SeismicCropBatch`, which +transforms them into 3D slices to index the data and other useful info like origin points, shapes and orientation. + +Each of the classes provides: + - `call` method (aliased to either `sample` or `next_batch`), that generates given amount of locations + - `to_names` method to convert the first two columns of sampled locations into string names of field and label + - convenient visualization to explore underlying `locations` structure +""" +import numpy as np +from numba import njit + +from batchflow import Sampler, ConstantSampler +from .labels import Horizon, Fault, Well, MatchedWell +from .field import Field, SyntheticField +from .geometry import Geometry +from .utils import filtering_function, insert_points_into_mask, AugmentedDict +from .plotters import plot + + + +class BaseSampler(Sampler): + """ Common logic of making locations. Refer to the documentation of inherited classes for more details. """ + dim = 9 # dimensionality of sampled points: field_id and label_id, orientation, locations + + def _make_locations(self, field, points, matrix, crop_shape, ranges, threshold, filtering_matrix): + # Parse parameters + ranges = ranges if ranges is not None else [None, None, None] + ranges = [item if item is not None else [0, c] + for item, c in zip(ranges, field.shape)] + ranges = np.array(ranges) + + crop_shape = np.array(crop_shape) + crop_shape_t = crop_shape[[1, 0, 2]] + n_threshold = np.int32(crop_shape[0] * crop_shape[1] * threshold) + + # Apply filtration + if filtering_matrix is not None: + points = filtering_function(points, filtering_matrix) + + # Keep only points, that can be a starting point for a crop of given shape + i_mask = ((ranges[:2, 0] <= points[:, :2]).all(axis=1) & + ((points[:, :2] + crop_shape[:2]) <= ranges[:2, 1]).all(axis=1)) + x_mask = ((ranges[:2, 0] <= points[:, :2]).all(axis=1) & + ((points[:, :2] + crop_shape_t[:2]) <= ranges[:2, 1]).all(axis=1)) + mask = i_mask | x_mask + + points = points[mask] + i_mask = i_mask[mask] + x_mask = x_mask[mask] + + # Keep only points, that produce crops with horizon larger than threshold; append flag + # TODO: Implement threshold check via filtering points with matrix obtained by + # convolution of horizon binary matrix and a kernel with size of crop shape + if threshold != 0.0: + points = spatial_check_points(points, matrix, crop_shape[:2], i_mask, x_mask, n_threshold) + else: + _points = np.empty((i_mask.sum() + x_mask.sum(), 4), dtype=np.int32) + _points[:i_mask.sum(), 0:3] = points[i_mask, :] + _points[:i_mask.sum(), 3] = 0 + + _points[i_mask.sum():, 0:3] = points[x_mask, :] + _points[i_mask.sum():, 3] = 1 + + points = _points + + # Transform points to (orientation, i_start, x_start, d_start, i_stop, x_stop, d_stop) + buffer = np.empty((len(points), 7), dtype=np.int32) + buffer[:, 0] = points[:, 3] + buffer[:, 1:4] = points[:, 0:3] + buffer[:, 4:7] = points[:, 0:3] + buffer[buffer[:, 0] == 0, 4:7] += crop_shape + buffer[buffer[:, 0] == 1, 4:7] += crop_shape_t + + self.n = len(buffer) + self.crop_shape = crop_shape + self.crop_shape_t = crop_shape_t + self.crop_depth = crop_shape[2] + self.ranges = ranges + self.threshold = threshold + self.n_threshold = n_threshold + return buffer + + + @property + def orientation_matrix(self): + """ Possible locations, mapped on field top-view map. + - np.nan where no locations can be sampled. + - 1 where only iline-oriented crops can be sampled. + - 2 where only xline-oriented crops can be sampled. + - 3 where both types of crop orientations can be sampled. + """ + matrix = np.zeros_like(self.matrix, dtype=np.float32) + orientations = self.locations[:, 0].astype(np.bool_) + + i_locations = self.locations[~orientations] + matrix[i_locations[:, 1], i_locations[:, 2]] += 1 + + x_locations = self.locations[orientations] + matrix[x_locations[:, 1], x_locations[:, 2]] += 2 + + matrix[matrix == 0] = np.nan + return matrix + + +class GeometrySampler(BaseSampler): + """ Generator of crop locations, based on a field. Not intended to be used directly, see `SeismicSampler`. + Makes locations that: + - start from the non-dead trace on a field, excluding those marked by `filtering_matrix` + - contain more than `threshold` non-dead traces inside + - don't go beyond cube limits + + Locations are produced as np.ndarray of (size, 9) shape with following columns: + (field_id, field_id, orientation, i_start, x_start, d_start, i_stop, x_stop, d_stop). + Depth location is randomized in desired `ranges`. + + Under the hood, we prepare `locations` attribute: + - filter non-dead trace coordinates so that only points that can generate + either inline or crossline oriented crop (or both) remain + - apply `filtering_matrix` to remove more points + - keep only those points and directions which create crops with more than `threshold` non-dead traces + - store all possible locations for each of the remaining points + For sampling, we randomly choose `size` rows from `locations` and generate depth in desired range. + + Parameters + ---------- + field : Field + Field to base sampler on. + crop_shape : tuple + Shape of crop locations to generate. + threshold : float + Minimum proportion of labeled points in each sampled location. + ranges : sequence, optional + Sequence of three tuples of two ints or `None`s. + If tuple of two ints, then defines ranges of sampling along corresponding axis. + If None, then field limits are used (no constraints). + filtering_matrix : np.ndarray, optional + Map of points to remove from potentially generated locations. + field_id, label_id : int + Used as the first two columns of sampled values. + """ + def __init__(self, field, crop_shape, threshold=0.05, ranges=None, filtering_matrix=None, + field_id=0, label_id=0, **kwargs): + matrix = (1 - field.dead_traces_matrix).astype(np.float32) + idx = np.nonzero(matrix != 0) + points = np.hstack([idx[0].reshape(-1, 1), + idx[1].reshape(-1, 1), + np.zeros((len(idx[0]), 1), dtype=np.int32)]).astype(np.int32) + + self.locations = self._make_locations(field=field, points=points, matrix=matrix, + crop_shape=crop_shape, ranges=ranges, threshold=threshold, + filtering_matrix=filtering_matrix) + self.kwargs = kwargs + + self.field_id = field_id + self.label_id = label_id + + self.field = field + self.matrix = matrix + self.name = field.short_name + self.short_name = field.short_name + super().__init__() + + def sample(self, size): + """ Get exactly `size` locations. """ + idx = np.random.randint(self.n, size=size) + sampled = self.locations[idx] + + depths = np.random.randint(low=self.ranges[2, 0], + high=self.ranges[2, 1] - self.crop_depth, + size=size, dtype=np.int32) + + buffer = np.empty((size, 9), dtype=np.int32) + buffer[:, 0] = self.field_id + buffer[:, 1] = self.label_id + + buffer[:, [2, 3, 4, 6, 7]] = sampled[:, [0, 1, 2, 4, 5]] + buffer[:, 5] = depths + buffer[:, 8] = depths + self.crop_depth + return buffer + + def __repr__(self): + return f'' + + +class HorizonSampler(BaseSampler): + """ Generator of crop locations, based on a single horizon. Not intended to be used directly, see `SeismicSampler`. + Makes locations that: + - start from the labeled point on horizon, excluding those marked by `filtering_matrix` + - contain more than `threshold` labeled pixels inside + - don't go beyond cube limits + + Locations are produced as np.ndarray of (size, 9) shape with following columns: + (field_id, label_id, orientation, i_start, x_start, d_start, i_stop, x_stop, d_stop). + Depth location is randomized in (0.1*shape, 0.9*shape) range. + + Under the hood, we prepare `locations` attribute: + - filter horizon points so that only points that can generate + either inline or crossline oriented crop (or both) remain + - apply `filtering_matrix` to remove more points + - keep only those points and directions which create crops with more than `threshold` labels + - store all possible locations for each of the remaining points + For sampling, we randomly choose `size` rows from `locations`. If some of the sampled locations does not fit the + `threshold` constraint, resample until we get exactly `size` locations. + + Parameters + ---------- + horizon : Horizon + Horizon to base sampler on. + crop_shape : tuple + Shape of crop locations to generate. + threshold : float + Minimum proportion of labeled points in each sampled location. + ranges : sequence, optional + Sequence of three tuples of two ints or `None`s. + If tuple of two ints, then defines ranges of sampling along this axis. + If None, then field limits are used (no constraints). + Note that we actually use only the first two elements, corresponding to spatial ranges. + filtering_matrix : np.ndarray, optional + Map of points to remove from potentially generated locations. + field_id, label_id : int + Used as the first two columns of sampled values. + randomize_depth : False or sequence of two floats + Whether apply random shift to depth locations of sampled horizon points or not. + If two floats, then the first one is the max location of the horizon labelling in the crop in [0., 1.] range, + and the second is the min location of the horizon labelling. + spatial_shift : False or sequence of sequences of two floats + Same logic, as with `randomize_depth`, but applied to spatial point location (inline/crossline). + """ + def __init__(self, horizon, crop_shape, threshold=0.05, ranges=None, filtering_matrix=None, + randomize_depth=True, spatial_shift=False, field_id=0, label_id=0, **kwargs): + field = horizon.field + matrix = horizon.full_matrix + + self.locations = self._make_locations(field=field, points=horizon.points.copy(), matrix=matrix, + crop_shape=crop_shape, ranges=ranges, threshold=threshold, + filtering_matrix=filtering_matrix) + self.kwargs = kwargs + + self.field_id = field_id + self.label_id = label_id + + self.horizon = horizon + self.field = field + self.matrix = matrix + self.name = field.short_name + self.short_name = horizon.short_name + + if randomize_depth: + randomize_depth = randomize_depth if isinstance(randomize_depth, tuple) else (0.9, 0.1) + self.randomize_depth = randomize_depth + + self.spatial_shift = spatial_shift + super().__init__() + + def sample(self, size): + """ Get exactly `size` locations. """ + if size == 0: + return np.zeros((0, 9), np.int32) + if self.threshold == 0.0: + sampled = self._sample(size) + else: + accumulated = 0 + sampled_list = [] + + while accumulated < size: + sampled = self._sample(size*2) + condition = spatial_check_sampled(sampled, self.matrix, self.n_threshold) + + sampled_list.append(sampled[condition]) + accumulated += condition.sum() + sampled = np.concatenate(sampled_list)[:size] + + buffer = np.empty((size, 9), dtype=np.int32) + buffer[:, 0] = self.field_id + buffer[:, 1] = self.label_id + buffer[:, 2:] = sampled + return buffer + + def _sample(self, size): + idx = np.random.randint(self.n, size=size) + sampled = self.locations[idx] # (orientation, i_start, x_start, d_start, i_stop, x_stop, d_stop) + + if self.randomize_depth: + shift = np.random.randint(low=-int(self.crop_depth*self.randomize_depth[0]), + high=-int(self.crop_depth*self.randomize_depth[1]), + size=(size, 1), dtype=np.int32) + sampled[:, [3, 6]] += shift + + if self.spatial_shift: + shapes_i = sampled[:, 4] - sampled[:, 1] + shift_i = np.random.randint(low=-(shapes_i*self.spatial_shift[0][0]).astype(np.int32), + high=-(shapes_i*self.spatial_shift[0][1]).astype(np.int32), + size=(size, 1), dtype=np.int32) + sampled[:, [1, 4]] += shift_i + + shapes_x = sampled[:, 5] - sampled[:, 2] + shift_x = np.random.randint(low=-(shapes_x*self.spatial_shift[1][0]).astype(np.int32), + high=-(shapes_x*self.spatial_shift[1][1]).astype(np.int32), + size=(size, 1), dtype=np.int32) + sampled[:, [2, 5]] += shift_x + + np.clip(sampled[:, 1], 0, self.field.shape[0] - self.crop_shape[0], out=sampled[:, 1]) + np.clip(sampled[:, 4], 0 + self.crop_shape[0], self.field.shape[0], out=sampled[:, 4]) + + np.clip(sampled[:, 2], 0, self.field.shape[1] - self.crop_shape[1], out=sampled[:, 2]) + np.clip(sampled[:, 5], 0 + self.crop_shape[1], self.field.shape[1], out=sampled[:, 5]) + + np.clip(sampled[:, 3], 0, self.field.depth - self.crop_depth, out=sampled[:, 3]) + np.clip(sampled[:, 6], 0 + self.crop_depth, self.field.depth, out=sampled[:, 6]) + return sampled + + + def __repr__(self): + return f'' + + @property + def orientation_matrix(self): + orientation_matrix = super().orientation_matrix + if self.horizon.is_carcass: + orientation_matrix = self.horizon.matrix_enlarge(orientation_matrix, 9) + return orientation_matrix + + +class FaultSampler(BaseSampler): + """ Generator of crop locations, based on a single fault. Not intended to be used directly, see `SeismicSampler`. + Makes locations that: + - start from the labeled point on fault + - don't go beyond cube limits + + Locations are produced as np.ndarray of (size, 9) shape with following columns: + (field_id, label_id, orientation, i_start, x_start, d_start, i_stop, x_stop, d_stop). + Location is randomized in (-0.4*shape, 0.4*shape) range. + + For sampling, we randomly choose `size` rows from `locations`. If some of the sampled locations does not fit the + `threshold` constraint or it is impossible to make crop of defined shape, resample until we get exactly + `size` locations. + + Parameters + ---------- + fault : Fault + Fault to base sampler on. + crop_shape : tuple + Shape of crop locations to generate. + threshold : float + Minimum proportion of labeled points in each sampled location. + ranges : sequence, optional + Sequence of three tuples of two ints or `None`s. + If tuple of two ints, then defines ranges of sampling along this axis. + If None, then field limits are used (no constraints). + Note that we actually use only the first two elements, corresponding to spatial ranges. + field_id, label_id : int + Used as the first two columns of sampled values. + extend : bool + Create locations in non-labeled slides between labeled slides. + transpose : bool + Create transposed crop locations or not. + """ + def __init__(self, fault, crop_shape, threshold=0, ranges=None, extend=True, transpose=False, + field_id=0, label_id=0, **kwargs): + field = fault.field + + self.fault = fault + self.points = fault.points + + self.direction = fault.direction + self.transpose = transpose + + self.locations = self._make_locations(field, crop_shape, ranges, threshold, extend) + + self.kwargs = kwargs + + self.field_id = field_id + self.label_id = label_id + + self.field = field + self.name = field.short_name + self.short_name = fault.short_name + super().__init__(self) + + @property + def interpolated_nodes(self): + """ Create locations in non-labeled slides between labeled slides. """ + slides = np.unique(self.fault.nodes[:, self.direction]) + if len(slides) == 1: + return self.fault.nodes + locations = [] + for i, slide in enumerate(slides): + left = slides[max(i-1, 0)] + right = slides[min(i+1, len(slides)-1)] + chunk = self.fault.nodes[self.fault.nodes[:, self.direction] == slide] + for j in range(left, right): + chunk[:, self.direction] = j + locations += [chunk.copy()] + return np.concatenate(locations, axis=0) + + def _make_locations(self, field, crop_shape, ranges, threshold, extend): + # Parse parameters + ranges = ranges if ranges is not None else [None, None, None] + ranges = [item if item is not None else [0, c] + for item, c in zip(ranges, field.shape)] + ranges = np.array(ranges) + + crop_shape = np.array(crop_shape) + crop_shape_t = crop_shape[[1, 0, 2]] + n_threshold = np.int32(np.prod(crop_shape) * threshold) + + if self.fault.has_component('sticks') or self.fault.has_component('nodes'): + nodes = self.interpolated_nodes if extend else self.fault.nodes + else: + nodes = self.fault.points + + # Keep only points, that can be a starting point for a crop of given shape + i_mask = ((ranges[:2, 0] <= nodes[:, :2]).all(axis=1) & + ((nodes[:, :2] + crop_shape[:2]) <= ranges[:2, 1]).all(axis=1)) + x_mask = ((ranges[:2, 0] <= nodes[:, :2]).all(axis=1) & + ((nodes[:, :2] + crop_shape_t[:2]) <= ranges[:2, 1]).all(axis=1)) + nodes = nodes[i_mask | x_mask] + + # Transform points to (orientation, i_start, x_start, d_start, i_stop, x_stop, d_stop) + directions = [0, 1] if self.transpose else [self.direction] + + buffer = np.empty((len(nodes) * len(directions), 7), dtype=np.int32) + + for i, direction, in enumerate(directions): + start, end = i * len(nodes), (i+1) * len(nodes) + shape = crop_shape if direction == 0 else crop_shape_t + buffer[start:end, 1:4] = nodes - shape // 2 + buffer[start:end, 4:7] = buffer[start:end, 1:4] + shape + buffer[start:end, 0] = direction + + self.n = len(buffer) + self.crop_shape = crop_shape + self.crop_shape_t = crop_shape_t + self.crop_depth = crop_shape[2] + self.ranges = ranges + self.threshold = threshold + self.n_threshold = n_threshold + return buffer + + def sample(self, size): + """ Get exactly `size` locations. """ + if size == 0: + return np.zeros((0, 9), np.int32) + accumulated = 0 + sampled_list = [] + + while accumulated < size: + sampled = self._sample(size*4) + condition = volumetric_check_sampled(sampled, self.points, self.crop_shape, + self.crop_shape_t, self.n_threshold) + + sampled_list.append(sampled[condition]) + accumulated += condition.sum() + sampled = np.concatenate(sampled_list)[:size] + + buffer = np.empty((size, 9), dtype=np.int32) + buffer[:, 0] = self.field_id + buffer[:, 1] = self.label_id + buffer[:, 2:] = sampled + + return buffer + + def _sample(self, size): + idx = np.random.randint(self.n, size=size) + sampled = self.locations[idx] + i_mask = sampled[:, 0] == 0 + x_mask = sampled[:, 0] == 1 + + for mask, shape in zip([i_mask, x_mask], [self.crop_shape, self.crop_shape_t]): + high = np.floor(shape * 0.4) + low = -high + low[shape == 1] = 0 + high[shape == 1] = 1 + + shift = np.random.randint(low=low, high=high, size=(mask.sum(), 3), dtype=np.int32) + sampled[mask, 1:4] += shift + sampled[mask, 4:] += shift + + sampled[mask, 1:4] = np.clip(sampled[mask, 1:4], 0, self.field.shape - shape) + sampled[mask, 4:7] = np.clip(sampled[mask, 4:7], 0 + shape, self.field.shape) + return sampled + + def __repr__(self): + return f'' + + +class SyntheticSampler(Sampler): + """ A sampler for synthetic fields (and their labels). + As every synthetically generated crop is completely valid from a sampling point of view, + we just return placeholder random locations of the desired `crop_shape`. + """ + def __init__(self, field, crop_shape, field_id=None, label_id=None, **kwargs): + self.field = field + self.crop_shape = crop_shape + self.field_id = field_id + self.label_id = label_id + self.kwargs = kwargs + self._n = 10000 + self.n = self._n ** 3 + + self.name = self.short_name = field.name + super().__init__() + + def sample(self, size): + """ Get exactly `size` locations. """ + buffer = np.empty((size, 9), dtype=np.int32) + buffer[:, 0] = self.field_id + buffer[:, 1] = self.label_id + buffer[:, 2] = 0 + + start_point = np.random.randint(low=(0, 0, 0), high=(self._n, self._n, self._n), + size=(size, 3), dtype=np.int32) + end_point = start_point + self.crop_shape + buffer[:, [3, 4, 5]] = start_point + buffer[:, [6, 7, 8]] = end_point + return buffer + + +class WellSampler(Sampler): + """ !!. """ + def __init__(self, well, crop_shape, log='AI', field_id=None, label_id=None, threshold=0.0, + spatial_randomization=(0.0, 1.0), depth_randomization=(0.0, 0.0), **kwargs): + self.well = well + self.crop_shape = crop_shape + self.log = log + self.field_id = field_id + self.label_id = label_id + self.kwargs = kwargs + + self.name = self.short_name = well.name + self.field = well.field + super().__init__() + self.locations = self._make_locations(well, crop_shape=crop_shape, log=log, + spatial_randomization=spatial_randomization, + depth_randomization=depth_randomization) + self.threshold = self.crop_shape[-1] * threshold + + + def _make_locations(self, well, crop_shape, log, spatial_randomization, depth_randomization): + location = well.location + crop_shape = np.array(crop_shape) + crop_shape_t = crop_shape[[1, 0, 2]] + + bbox = well.bboxes[log] + mean_depth = bbox[-1].mean().astype(np.int32) + depth_ranges = [max(bbox[-1][0] - crop_shape[-1] * depth_randomization[0], 0), + min(bbox[-1][1] + crop_shape[-1] * depth_randomization[1], well.field.depth - crop_shape[-1])] + + if depth_ranges[1] <= depth_ranges[0]: + depth_ranges[0] = max(depth_ranges[1] - 1, 0) + + # inline-oriented + arange_i = np.arange(max(location[0] - crop_shape[0]*spatial_randomization[1] + 1, 0), + location[0] - crop_shape[0]*spatial_randomization[0] + 1) + arange_x = np.arange(max(location[1] - crop_shape[1]*spatial_randomization[1] + 1, 0), + location[1] - crop_shape[1]*spatial_randomization[0] + 1) + + m_i, m_x = np.meshgrid(arange_i, arange_x, indexing='ij') + points_i = np.stack([m_i.reshape(-1), m_x.reshape(-1)]).T + + # crossline-oriented + arange_i = np.arange(max(location[0] - crop_shape_t[0]*spatial_randomization[1] + 1, 0), + location[0] - crop_shape_t[0]*spatial_randomization[0] + 1) + arange_x = np.arange(max(location[1] - crop_shape_t[1]*spatial_randomization[1] + 1, 0), + location[1] - crop_shape_t[1]*spatial_randomization[0] + 1) + + m_i, m_x = np.meshgrid(arange_i, arange_x, indexing='ij') + points_x = np.stack([m_i.reshape(-1), m_x.reshape(-1)]).T + + # (orientation, i_start, x_start, d_start, i_stop, x_stop, d_stop) + buffer = np.empty((len(points_i) + len(points_x), 7), dtype=np.int32) + + buffer[:len(points_i), 0] = 0 + buffer[:len(points_i), 1:3] = points_i + buffer[:len(points_i), 3] = mean_depth + buffer[:len(points_i), 4:7] = buffer[:len(points_i), 1:4] + crop_shape + + buffer[len(points_i):, 0] = 1 + buffer[len(points_i):, 1:3] = points_x + buffer[len(points_i):, 3] = mean_depth + buffer[len(points_i):, 4:7] = buffer[len(points_i):, 1:4] + crop_shape_t + + self.n = len(buffer) + self.crop_shape = crop_shape + self.crop_shape_t = crop_shape_t + self.crop_depth = crop_shape[2] + self.ranges = [None, None, depth_ranges] + return buffer + + def sample(self, size): + """ Get exactly `size` locations. """ + if size == 0: + return np.zeros((0, 9), np.int32) + sampled = self._sample(size) + if self.threshold == 0.0 or self.well.vertical: + sampled = self._sample(size) + else: + accumulated = 0 + sampled_list = [] + + while accumulated < size: + sampled = self._sample(size*2) + condition = np.array([self.well.compute_overlap_size(mask_bbox=location[1:].reshape(2, 3).T, + log=self.log) >= self.threshold + for location in sampled], dtype=np.bool_) + + sampled_list.append(sampled[condition]) + accumulated += condition.sum() + sampled = np.concatenate(sampled_list)[:size] + + buffer = np.empty((size, 9), dtype=np.int32) + buffer[:, 0] = self.field_id + buffer[:, 1] = self.label_id + buffer[:, 2:] = sampled + return buffer + + def _sample(self, size): + idx = np.random.randint(self.n, size=size) + sampled = self.locations[idx] # (orientation, i_start, x_start, d_start, i_stop, x_stop, d_stop) + + depths = np.random.randint(*self.ranges[-1], size=size, dtype=np.int32) + sampled[:, 3] = depths + sampled[:, 6] = depths + self.crop_shape[-1] + return sampled + + +@njit +def spatial_check_points(points, matrix, crop_shape, i_mask, x_mask, threshold): + """ Compute points, which would generate crops with more than `threshold` labeled pixels. + For each point, we test two possible shapes (i-oriented and x-oriented) and check `matrix` to compute the + number of present points. Therefore, each of the initial points can result in up to two points in the output. + + Used as one of the filters for points creation at sampler initialization. + + Parameters + ---------- + points : np.ndarray + Points in (i_start, x_start, d_start) format. + matrix : np.ndarray + Depth map in cube coordinates. + crop_shape : tuple of two ints + Spatial shape of crops to generate: (i_shape, x_shape). + i_mask : np.ndarray + For each point, whether to test i-oriented shape. + x_mask : np.ndarray + For each point, whether to test x-oriented shape. + threshold : int + Minimum amount of points in a generated crop. + """ + shape_i, shape_x = crop_shape + + # Return inline, crossline, corrected_depth (mean across crop), and 0/1 as i/x flag + buffer = np.empty((2 * len(points), 4), dtype=np.int32) + counter = 0 + + for (point_i, point_x, _), i_mask_, x_mask_ in zip(points, i_mask, x_mask): + if i_mask_: + sliced = matrix[point_i:point_i+shape_i, point_x:point_x+shape_x] + present_points, running_sum = np.int32(0), np.int32(0) + + for value in np.nditer(sliced): + if value > 0: + present_points += 1 + running_sum += value.item() + + if present_points >= threshold: + d_mean = round(running_sum / present_points) + buffer[counter, :] = point_i, point_x, np.int32(d_mean), np.int32(0) + counter += 1 + + if x_mask_: + sliced = matrix[point_i:point_i+shape_x, point_x:point_x+shape_i] + present_points, running_sum = np.int32(0), np.int32(0) + + for value in np.nditer(sliced): + if value > 0: + present_points += 1 + running_sum += value.item() + + if present_points >= threshold: + d_mean = round(running_sum / present_points) + buffer[counter, :] = point_i, point_x, np.int32(d_mean), np.int32(1) + counter += 1 + + return buffer[:counter] + +@njit +def spatial_check_sampled(locations, matrix, threshold): + """ Remove points, which correspond to crops with less than `threshold` labeled pixels. + Used as a final filter for already sampled locations: they can generate crops with + smaller than `threshold` mask only due to the depth randomization. + + Parameters + ---------- + locations : np.ndarray + Locations in (orientation, i_start, x_start, d_start, i_stop, x_stop, d_stop) format. + matrix : np.ndarray + Depth map in cube coordinates. + threshold : int + Minimum amount of labeled pixels in a crop. + + Returns + ------- + condition : np.ndarray + Boolean mask for locations. + """ + #pylint: disable=chained-comparison + condition = np.ones(len(locations), dtype=np.bool_) + + for i, (_, i_start, x_start, d_start, i_stop, x_stop, d_stop) in enumerate(locations): + sliced = matrix[i_start:i_stop, x_start:x_stop] + valid_points = np.int32(0) + + for value in np.nditer(sliced): + if (d_start < value) and (value < d_stop): + valid_points += 1 + if valid_points >= threshold: + break + else: + condition[i] = False + return condition + +@njit +def volumetric_check_sampled(locations, points, crop_shape, crop_shape_t, threshold): + """ Remove points, which correspond to crops with less than `threshold` labeled pixels. + Used as a final filter for already sampled locations: they can generate crops with + smaller than `threshold`. + + Parameters + ---------- + locations : np.ndarray + Locations in (orientation, i_start, x_start, d_start, i_stop, x_stop, d_stop) format. + points : points + Fault points. + crop_shape : np.ndarray + Crop shape + crop_shape_t : np.ndarray + Tranposed crop shape + threshold : int + Minimum amount of labeled pixels in a crop. + + Returns + ------- + condition : np.ndarray + Boolean mask for locations. + """ + condition = np.ones(len(locations), dtype=np.bool_) + + if threshold > 0: + for i, (orientation, i_start, x_start, d_start, i_stop, x_stop, d_stop) in enumerate(locations): + shape = crop_shape if orientation == 0 else crop_shape_t + mask_bbox = np.array([[i_start, i_stop], [x_start, x_stop], [d_start, d_stop]], dtype=np.int32) + mask = np.zeros((shape[0], shape[1], shape[2]), dtype=np.int32) + + insert_points_into_mask(mask, points, mask_bbox, 1, 0) + if mask.sum() < threshold: + condition[i] = False + + return condition + + +class SeismicSampler(Sampler): + """ Mixture of samplers for multiple cubes with multiple labels. + Used to sample crop locations in the format of + (field_id, label_id, orientation, i_start, x_start, d_start, i_stop, x_stop, d_stop). + + Parameters + ---------- + labels : dict + Dictionary where keys are cube names and values are lists of labels. + crop_shape : tuple + Shape of crop locations to generate. + cube_proportions : sequence, optional + Proportion of each cube in the resulting mixture. + uniform_labels : bool, optional + If True, labels will be sampled inside of the cube uniformly. + If False, labels will be sampled proportional to the len of it. + threshold : float + Minimum proportion of labeled points in each sampled location. + ranges : sequence, optional + Sequence of three tuples of two ints or `None`s. + If tuple of two ints, then defines ranges of sampling along this axis. + If None, then field limits are used (no constraints). + Note that we actually use only the first two elements, corresponding to spatial ranges. + filtering_matrix : np.ndarray, optional + Map of points to remove from potentially generated locations. + randomize_depth : bool + Whether to apply random shift to depth locations of sampled horizon points or not. + kwargs : dict + Other parameters of initializing label samplers. + """ + LABELCLASS_TO_SAMPLERCLASS = { + Field: GeometrySampler, + SyntheticField: SyntheticSampler, + Geometry: GeometrySampler, + Horizon: HorizonSampler, + Fault: FaultSampler, + Well: WellSampler, MatchedWell: WellSampler + } + + @classmethod + def labelclass_to_samplerclass(cls, labelclass): + """ Mapping between label classes and used samplers. + Uses `issubclass` check in addition to getitem. + """ + samplerclass = cls.LABELCLASS_TO_SAMPLERCLASS.get(labelclass) + if samplerclass is not None: + return samplerclass + + for class_, samplerclass in cls.LABELCLASS_TO_SAMPLERCLASS.items(): + if issubclass(labelclass, class_): + return samplerclass + raise KeyError(f'Unable to determine the sampler class for `{labelclass}`') + + + def __init__(self, labels, crop_shape, cube_proportions=None, uniform_labels=True, + threshold=0.05, ranges=None, filtering_matrix=None, randomize_depth=True, **kwargs): + # One sampler of each `label` for each `field` + names, sampler_classes = {}, {} + samplers = AugmentedDict({field_name: [] for field_name in labels.keys()}) + + labels_weights = [] + + for field_id, (field_name, list_labels) in enumerate(labels.items()): + list_labels = list_labels if isinstance(list_labels, (tuple, list)) else [list_labels] + if len(list_labels) == 0: + continue + + # Unpack parameters + crop_shape_ = crop_shape[field_name] if isinstance(crop_shape, dict) else crop_shape + threshold_ = threshold[field_name] if isinstance(threshold, dict) else threshold + filtering_matrix_ = filtering_matrix[field_name] if isinstance(filtering_matrix, dict) else filtering_matrix + ranges_ = ranges[field_name] if isinstance(ranges, dict) else ranges + + # Mixture for each field + label_classes = [type(label) for label in list_labels] + if len(set(label_classes)) != 1: + raise ValueError(f'Labels contain different classes, {set(label_classes)}!') + sampler_class = self.labelclass_to_samplerclass(label_classes[0]) + sampler_classes[field_id] = sampler_class + + for label_id, label in enumerate(list_labels): + + label_sampler = sampler_class(label, crop_shape=crop_shape_, threshold=threshold_, + ranges=ranges_, filtering_matrix=filtering_matrix_, + field_id=field_id, label_id=label_id, randomize_depth=randomize_depth, + **kwargs) + + if label_sampler.n != 0: + samplers[field_name].append(label_sampler) + names[(field_id, label_id)] = (field_name, label.short_name) + + if uniform_labels: + labels_weights.append([1 / len(list_labels) for _ in list_labels]) + else: + weights = np.array([len(label) if hasattr(label, '__len__') else 1 for label in list_labels]) + weights = weights / weights.sum() + labels_weights.append(weights) + + # Resulting sampler + n_present_fields = sum(len(sampler_list) != 0 for sampler_list in samplers.values()) + if n_present_fields == 0: + raise ValueError('Empty sampler!') + + cube_proportions = cube_proportions or [1 / n_present_fields for _ in labels] + final_weights = AugmentedDict({idx: [] for idx in labels.keys()}) + + sampler = 0 & ConstantSampler(np.int32(0), dim=9) + + for (field_name, sampler_list), p, l in zip(samplers.items(), cube_proportions, labels_weights): + if len(sampler_list) != 0: + for label_sampler, label_weight in zip(sampler_list, l): + w = p * label_weight + final_weights[field_name].append(w) + sampler = sampler | (w & label_sampler) + + + self.sampler = sampler + self.samplers = samplers + self.names = names + self.sampler_classes = sampler_classes + self.final_weights = final_weights + + self.crop_shape = crop_shape + self.threshold = threshold + self.proportions = cube_proportions + + + def sample(self, size): + """ Generate exactly `size` locations. """ + return self.sampler.sample(size) + + def __call__(self, size): + return self.sampler.sample(size) + + def to_names(self, id_array): + """ Convert the first two columns of sampled locations into field and label string names. """ + return np.array([self.names[tuple(ids)] for ids in id_array]) + + def __len__(self): + return sum(len(sampler.locations) for sampler_list in self.samplers.values() for sampler in sampler_list) + + def __str__(self): + msg = 'SeismicSampler:' + for list_samplers, p in zip(self.samplers.values(), self.proportions): + msg += f'\n {list_samplers[0].field.short_name} @ {p}' + for sampler in list_samplers: + msg += f'\n {sampler}' + return msg + + def show_locations(self, savepath=None, plotter=plot, **kwargs): + """ Visualize on field map by using underlying `locations` structure. """ + data = [] + title = [] + xlabel = [] + ylabel = [] + + for samplers_list in self.samplers.values(): + field = samplers_list[0].field + + if isinstance(field, SyntheticField): + continue + + data += [[sampler.orientation_matrix, field.dead_traces_matrix] for sampler in samplers_list] + title += [f'{field.short_name}: {sampler.short_name}' for sampler in samplers_list] + xlabel += [field.index_headers[0]] * len(samplers_list) + ylabel += [field.index_headers[1]] * len(samplers_list) + + plot_config = { + 'cmap': [['Sampler', 'gray']] * len(data), + 'title': title, + 'vmin': [[1, 0]] * len(data), + 'vmax': [[3, 1]] * len(data), + 'xlabel': xlabel, + 'ylabel': ylabel, + 'augment_mask': True, + **kwargs + } + + data.append(None) # reserve extra subplot for future legend + + plotter = plotter(data, **plot_config) + + legend_config = { + 'mode': 'image', + 'color': ('purple', 'blue', 'red', 'white', 'gray'), + 'label': ('ILINES and CROSSLINES', 'only ILINES', 'only CROSSLINES', 'restricted', 'dead traces'), + 'size': 20, + 'loc': 10, + 'facecolor': 'silver', + } + + plotter[-1].add_legend(**legend_config) + + if savepath is not None: + plotter.save(savepath=savepath) + + return plotter + + def show_sampled(self, n=10000, binary=False, savepath=None, plotter=plot, **kwargs): + """ Visualize on field map by sampling `n` crop locations. """ + sampled = self.sample(n) + + data = [] + title = [] + + field_ids = np.unique(sampled[:, 0]) + for field_id in field_ids: + field = self.samplers[field_id][0].field + + if isinstance(field, SyntheticField): + continue + + matrix = np.zeros_like(field.dead_traces_matrix, dtype=np.int32) + + sampled_ = sampled[sampled[:, 0] == field_id] + for (_, _, _, point_i_start, point_x_start, _, point_i_stop, point_x_stop, _) in sampled_: + matrix[point_i_start : point_i_stop, point_x_start : point_x_stop] += 1 + if binary: + matrix[matrix > 0] = 1 + + field_data = [matrix, field.dead_traces_matrix] + data.append(field_data) + + field_title = f'{field.short_name}: {len(sampled_)} points' + title.append(field_title) + + data.append(None) # reserve extra subplot for future legend + + plot_config = { + 'matrix_name': 'Sampled slices', + 'cmap': [['Reds', 'black']] * len(field_ids), + 'alpha': [[1.0, 0.4]] * len(field_ids), + 'title': title, + 'interpolation': 'bilinear', + 'xlabel': field.index_headers[0], + 'ylabel': field.index_headers[1], + 'augment_mask': True, + **kwargs + } + + plotter = plotter(data, **plot_config) + + legend_config = { + 'mode': 'image', + 'color': ('beige', 'salmon', 'grey'), + 'label': ('alive traces', 'sampled locations', 'dead traces'), + 'size': 25, + 'loc': 10, + 'facecolor': 'silver', + } + + plotter[-1].add_legend(**legend_config) + + if savepath is not None: + plotter.save(savepath=savepath) + + return plotter diff --git a/seismiqb/synthetic/parameters.py b/seismiqb/synthetic/parameters.py new file mode 100644 index 0000000..870c6c0 --- /dev/null +++ b/seismiqb/synthetic/parameters.py @@ -0,0 +1,95 @@ +""" Pre-defined parameter generators. """ +import numpy as np +from batchflow import Config + + +class ParamGeneratorFactory: + """ Create a `param_generator` function with desired behavior. + Allows to easily change parts of the sampled configs by passing `config` variable, + which takes priority over default created parameters. + + Each of the values in `config` can be a callable: in this case, it will be called with no arguments to make config. + + Parameters + ---------- + config : dict, optional + Additional paramers for adding into generated configs. + Each value can be a callable that returns value instead. + Takes priority over options, generated by calling the instance. + attribute : str + Value is added to a generated config under the `attribute` key. + Used by the `SyntheticField` to refer to an attribute. + horizon_frequency : int + Average distance between horizons in pixels. + faults_p : sequence of numbers + i-th element is the probability of adding exactly `i` faults to the image, starting from 0. + (0.7, 0.3) means that there is 70% change to make no faults, and 30% to add one fault to the synthetic. + faults_config : dict, optional + If provided, then updates default fault creation configuration. + """ + def __init__(self, config=None, attribute='labels', horizon_frequency=25, faults_p=(0.7, 0.3), faults_config=None): + config = config if config is not None else {} + self.config = Config(config) + self.attribute = attribute + + self.horizon_frequency = horizon_frequency + + self.faults_p = faults_p + self.faults_a = np.arange(len(faults_p)) + self.faults_config = faults_config if faults_config is not None else {} + + + def make_fault_params(self, rng): + """ Create parameters for fault adding. Works only for 2d distortions. """ + return {'coordinates': 'random', + 'max_shift': rng.uniform(20, 40), + 'shift_sign': rng.choice([-1, 1]), + 'width': rng.uniform(1.0, 4.0), + 'update_horizon_matrices': True, + **self.faults_config} + + def __call__(self, shape, rng=None): + rng = rng if isinstance(rng, np.random.Generator) else np.random.default_rng(rng) + + num_horizons = shape[-1] // self.horizon_frequency + rng.integers(-3, +3) + + num_faults = rng.choice(a=self.faults_a, p=self.faults_p) + fault_params = [self.make_fault_params(rng=rng) for _ in range(num_faults)] + + config = Config({ + 'attribute': self.attribute, + 'make_velocity_vector': {'num_horizons': num_horizons, # scales with depth + 'limits': (2000, 6000), + 'randomization': 'uniform', 'randomization_scale': 0.3, + 'amplify_probability': 0.2, 'amplify_range': (2.0, 4.0), + 'amplify_sign_probability': 0.8}, + 'make_horizons': {'shape': shape, + 'interval_randomization': 'uniform', + 'interval_randomization_scale': 0.3, + 'interval_min': rng.uniform(0.2, 0.6), + 'randomization1_scale': 0.25, 'num_nodes': 10, + 'randomization2_scale': 0.25, 'locs_n_range': (3, 5), + 'output_range': (-0.2, 0.8)}, + 'make_velocity_model': {}, + + 'make_fault_2d': fault_params, + + 'make_density_model': {'randomization': 'uniform', + 'randomization_limits': (0.95, 1.05)}, + 'make_impedance_model': {}, + 'make_reflectivity_model': {}, + + 'make_synthetic': {'ricker_width': rng.uniform(4.7, 5.3), + 'ricker_points': 100}, + 'postprocess_synthetic': {'sigma': 0.5, 'clip': True, + 'noise_mode': 'normal', 'noise_mul': rng.uniform(0.1, 0.3)}, + 'cleanup': {'delete': []}, + }) + + self_config = Config({key : value() if callable(value) else value + for key, value in self.config.flatten().items()}) + config += self_config + return config + + +default_param_generator = ParamGeneratorFactory() diff --git a/seismiqb/utils/__init__.py b/seismiqb/utils/__init__.py new file mode 100644 index 0000000..db75f02 --- /dev/null +++ b/seismiqb/utils/__init__.py @@ -0,0 +1,13 @@ +""" Utility functions and classes. """ +# pylint: disable=wildcard-import +from .accumulator2d import * +from .accumulator3d import * +from .cache import * +from .charisma import * +from .classes import * +from .decorators import * +from .dtype_conversion import * +from .format_conversion import * +from .functions import * +from .groupby import * +from .storage import SQBStorage diff --git a/seismiqb/utils/accumulator2d.py b/seismiqb/utils/accumulator2d.py new file mode 100644 index 0000000..c09a3f9 --- /dev/null +++ b/seismiqb/utils/accumulator2d.py @@ -0,0 +1,215 @@ +""" Accumulator for 2d matrices. """ +import numpy as np + +try: + import cupy as cp + CUPY_AVAILABLE = True +except ImportError: + cp = np + CUPY_AVAILABLE = False +from .classes import augmented_np + + + +class Accumulator: + """ Class to accumulate statistics over streamed matrices. + An example of usage: + one can either store matrices and take a mean along desired axis at the end of their generation, + or sequentially update the `mean` matrix with the new data by using this class. + Note the latter approach is inherintly slower, but requires O(N) times less memory, + where N is the number of accumulated matrices. + + This class is intended to be used in the following manner: + - initialize the instance with desired aggregation + - iteratively call `update` method with new matrices + - to get the aggregated result, use `get` method + + NaNs are ignored in all computations. + This class works with both CPU (`numpy`) and GPU (`cupy`) arrays and automatically detects current device. + + Parameters + ---------- + agg : str + Which type of aggregation to use. Currently, following modes are implemented: + - 'mean' works by storing matrix of sums and non-nan counts. + To get the mean result, the sum is divided by the counts + - 'std' works by keeping track of sum of the matrices, sum of squared matrices, + and non-nan counts. To get the result, we subtract squared mean from mean of squared values + - 'min', 'max' works by iteratively updating the matrix of minima/maxima values + - 'argmin', 'argmax' iteratively updates index of the minima/maxima values in the passed matrices + - 'stack' just stores the matrices and concatenates them along (new) last axis + - 'mode' stores supplied matrices and computes mode along the last axis during the `get` call + amortize : bool + If False, then supplied matrices are stacked into ndarray, and then aggregation is applied. + If True, then accumulation logic is applied. + Allows for trade-off between memory usage and speed: `amortize=False` is faster, + but takes more memory resources. + total : int or None + If integer, then total number of matrices to be aggregated. + Used to reduce the memory footprint if `amortize` is set to False. + axis : int + Axis to stack matrices on and to apply aggregation funcitons. + """ + #pylint: disable=attribute-defined-outside-init + def __init__(self, agg='mean', amortize=False, total=None, axis=0): + self.agg = agg + self.amortize = amortize + self.total = total + self.axis = axis + + self.initialized = False + + + def init(self, matrix): + """ Initialize all the containers on first `update`. """ + # No amortization: collect all the matrices and apply reduce afterwards + self.module = cp.get_array_module(matrix) if CUPY_AVAILABLE else augmented_np + self.n = 1 + + if self.amortize is False or self.agg in ['stack', 'mode']: + if self.total: + self.values = self.module.empty((self.total, *matrix.shape)) + self.values[0, ...] = matrix + else: + self.values = [matrix] + + self.initialized = True + return + + # Amortization: init all the containers + if self.agg in ['mean', 'nanmean']: + # Sum of values and counts of non-nan + self.value = matrix + self.counts = (~self.module.isnan(matrix)).astype(self.module.int32) + + elif self.agg in ['min', 'nanmin', 'max', 'nanmax']: + self.value = matrix + + elif self.agg in ['std', 'nanstd']: + # Same as means, but need to keep track of mean of squares and squared mean + self.means = matrix + self.squared_means = matrix ** 2 + self.counts = (~self.module.isnan(matrix)).astype(self.module.int32) + + elif self.agg in ['argmin', 'argmax', 'nanargmin', 'nanargmax']: + # Keep the current maximum/minimum and update indices matrix, if needed + self.value = matrix + self.indices = self.module.zeros_like(matrix) + + self.initialized = True + return + + + def update(self, matrix): + """ Update containers with new matrix. """ + if not self.initialized: + self.init(matrix.copy()) + return + + # No amortization: just store everything + if self.amortize is False or self.agg in ['stack', 'mode']: + if self.total: + self.values[self.n, ...] = matrix + else: + self.values.append(matrix) + + self.n += 1 + return + + # Amortization: update underlying containers + slc = ~self.module.isnan(matrix) + + if self.agg in ['min', 'nanmin']: + self.value[slc] = self.module.fmin(self.value[slc], matrix[slc]) + + elif self.agg in ['max', 'nanmax']: + self.value[slc] = self.module.fmax(self.value[slc], matrix[slc]) + + elif self.agg in ['mean', 'nanmean']: + mask = np.logical_and(slc, self.module.isnan(self.value)) + self.value[mask] = 0.0 + self.value[slc] += matrix[slc] + self.counts[slc] += 1 + + elif self.agg in ['std', 'nanstd']: + mask = np.logical_and(slc, self.module.isnan(self.means)) + self.means[mask] = 0.0 + self.squared_means[mask] = 0.0 + self.means[slc] += matrix[slc] + self.squared_means[slc] += matrix[slc] ** 2 + self.counts[slc] += 1 + + elif self.agg in ['argmin', 'nanargmin']: + mask = self.module.logical_and(slc, self.module.isnan(self.value)) + self.value[mask] = matrix[mask] + self.indices[mask] = self.n + + slc_ = matrix < self.value + self.value[slc_] = matrix[slc_] + self.indices[slc_] = self.n + + elif self.agg in ['argmax', 'nanargmax']: + mask = self.module.logical_and(slc, self.module.isnan(self.value)) + self.value[mask] = matrix[mask] + self.indices[mask] = self.n + + slc_ = matrix > self.value + self.value[slc_] = matrix[slc_] + self.indices[slc_] = self.n + + self.n += 1 + return + + def get(self, final=False): + """ Use stored matrices to get the aggregated result. """ + # No amortization: apply function along the axis to the stacked array + if self.amortize is False or self.agg in ['stack', 'mode']: + if self.total: + stacked = self.values + else: + stacked = self.module.stack(self.values, axis=self.axis) + + if final: + self.values = None + + if self.agg in ['stack']: + value = stacked + + elif self.agg in ['mode']: + uniques = self.module.unique(stacked) + + accumulator = Accumulator('argmax') + for item in uniques[~self.module.isnan(uniques)]: + counts = (stacked == item).sum(axis=self.axis) + accumulator.update(counts) + indices = accumulator.get(final=True) + value = uniques[indices] + value[self.module.isnan(self.module.max(stacked, axis=self.axis))] = self.module.nan + + else: + value = getattr(self.module, self.agg)(stacked, axis=self.axis) + + return value + + # Amortization: compute desired aggregation + if self.agg in ['min', 'nanmin', 'max', 'nanmax']: + value = self.value + + elif self.agg in ['mean', 'nanmean']: + slc = self.counts > 0 + value = self.value if final else self.value.copy() + value[slc] /= self.counts[slc] + + elif self.agg in ['std', 'nanstd']: + slc = self.counts > 0 + means = self.means if final else self.means.copy() + means[slc] /= self.counts[slc] + + squared_means = self.squared_means if final else self.squared_means.copy() + squared_means[slc] /= self.counts[slc] + value = self.module.sqrt(squared_means - means ** 2) + + elif self.agg in ['argmin', 'argmax', 'nanargmin', 'nanargmax']: + value = self.indices + + return value diff --git a/seismiqb/utils/accumulator3d.py b/seismiqb/utils/accumulator3d.py new file mode 100644 index 0000000..b15c1d8 --- /dev/null +++ b/seismiqb/utils/accumulator3d.py @@ -0,0 +1,712 @@ +""" Accumulator for 3d volumes. """ +import os +import shutil +from copy import copy +from multiprocessing.shared_memory import SharedMemory + +import blosc +import h5pickle as h5py +import hdf5plugin +import numpy as np + +from sklearn.linear_model import LinearRegression + +from batchflow import Notifier + +from .functions import generate_string, triangular_weights_function_nd, take_along_axis + + + +class Accumulator3D: + """ Base class to aggregate predicted sub-volumes into a larger 3D cube. + Can accumulate data in memory (Numpy arrays) or on disk (HDF5 datasets). + + Type of aggregation is defined in subclasses, that must implement `__init__`, `_update` and `_aggregate` methods. + The main result in subclasses should be stored in `data` attribute, which is accessed by the base class. + + Supposed to be used in combination with `:class:.~RegularGrid` and + `:meth:.~SeismicCropBatch.update_accumulator` in a following manner: + - `RegularGrid` defines how to split desired cube range into small crops + - `Accumulator3D` creates necessary placeholders for a desired type of aggregation + - `update_accumulator` action of pipeline passes individual crops (and their locations) to + update those placeholders (see `:meth:~.update`) + - `:meth:~.aggregate` is used to get the resulting volume + - `:meth:~.clear` can be optionally used to remove array references and HDF5 file from disk + + This class is an alternative to `:meth:.~SeismicDataset.assemble_crops`, but allows to + greatly reduce memory footprint of crop aggregation by up to `overlap_factor` times. + Also, as this class updates rely on `location`s of crops, it can take crops in any order. + + Note that not all pixels of placeholders will be updated with data due to removal of dead traces, + so we have to be careful with initialization! + + Parameters + ---------- + shape : sequence + Shape of the placeholder. + origin : sequence + The upper left point of the volume: used to shift crop's locations. + dtype : np.dtype + Dtype of storage. Must be either integer or float. + transform : callable, optional + Additional function to call before storing the crop data. + path : str or file-like object, optional + If provided, then we use HDF5 datasets instead of regular Numpy arrays, storing the data directly on disk. + After the initialization, we keep the file handle in `w-` mode during the update phase. + After aggregation, we re-open the file to automatically repack it in `r` mode. + kwargs : dict + Other parameters are passed to HDF5 dataset creation. + """ + #pylint: disable=redefined-builtin + def __init__(self, shape=None, origin=None, orientation=0, dtype=np.float32, transform=None, + format=None, path=None, dataset_kwargs=None, **kwargs): + # Dimensionality and location, corrected on `orientation` + self.orientation = orientation + self.shape = self.reorder(shape) + self.origin = self.reorder(origin) + self.location = self.reorder([slice(start, start + shape) + for start, shape in zip(self.origin, self.shape)]) + + # Properties of storages + self.dtype = dtype + self.transform = getattr(self, transform) if isinstance(transform, str) else transform + + # Container definition + if format is None: + format = os.path.splitext(path)[1][1:] if path is not None else 'numpy' + self.type = format + + if self.type in ['hdf5', 'zarr']: + if isinstance(path, str) and os.path.exists(path): + if os.path.isdir(path): + shutil.rmtree(path) + else: + os.remove(path) + self.path = path + self.dataset_kwargs = dataset_kwargs or {} + + if self.type == 'hdf5': + self.file = h5py.File(path, mode='w-') + else: + import zarr #pylint: disable=import-outside-toplevel + self.file = zarr.group(zarr.LMDBStore(path)) + + elif self.type == 'shm': + self.shm_data = {} # placeholder name -> shm_instance, dtype + + self.placeholders = [] + + self.aggregated = False + self.kwargs = kwargs + + def reorder(self, sequence): + """ Reorder `sequence` with the `orientation` of accumulator. """ + if self.orientation == 1: + sequence = np.array([sequence[1], sequence[0], sequence[2]]) + if self.orientation == 2: + sequence = np.array([sequence[2], sequence[0], sequence[1]]) + return sequence + + + # Placeholder management + def create_placeholder(self, name=None, dtype=None, fill_value=None): + """ Create named storage as a dataset of HDF5 or plain array. """ + if self.type in ['hdf5', 'qhdf5']: + placeholder = self.file.create_dataset(name, shape=self.shape, dtype=dtype, + fillvalue=fill_value, **self.dataset_kwargs) + elif self.type == 'zarr': + kwargs = { + 'chunks': (1, *self.shape[1:]), + **self.dataset_kwargs + } + placeholder = self.file.create_dataset(name, shape=self.shape, dtype=dtype, + fill_value=fill_value, **kwargs) + + elif self.type == 'numpy': + placeholder = np.full(shape=self.shape, fill_value=fill_value, dtype=dtype) + + elif self.type == 'shm': + size = np.dtype(dtype).itemsize * np.prod(self.shape) + shm_name = generate_string(size=10) + + shm = SharedMemory(create=True, size=size, name=shm_name) + placeholder = np.ndarray(buffer=shm.buf, shape=self.shape, dtype=dtype) + placeholder[:] = fill_value + + self.shm_data[name] = [shm, dtype] + + self.placeholders.append(name) + setattr(self, name, placeholder) + + def remove_placeholder(self, name=None, unlink=False): + """ Remove created placeholder. """ + if self.type in ['hdf5', 'qhdf5', 'zarr']: + del self.file[name] + elif self.type == 'shm': + shm = self.shm_data[name][0] + shm.close() + if unlink: + shm.unlink() + self.shm_data.pop(name) + + self.placeholders.remove(name) + setattr(self, name, None) + + def clear(self, unlink=False): + """ Remove placeholders from memory and disk. """ + if self.type in ['hdf5', 'qhdf5', 'zarr']: + os.remove(self.path) + + if self.type == 'shm': + for name in self.placeholders: + self.remove_placeholder(name, unlink=unlink) + + def __getstate__(self): + """ Store state of an instance. Remove file handlers and shared memory objects. """ + state = copy(self.__dict__) + if self.type in ['hdf5', 'qhdf5', 'zarr']: + for name in self.placeholders: + state[name] = None + + elif self.type == 'shm': + shm_data = {} + for name in self.placeholders: + shm_instance, dtype = self.shm_data[name] + shm_data[name] = [shm_instance.name, dtype] + state[name] = None + state['shm_data'] = shm_data + + elif self.type == 'numpy': + for name in self.placeholders: + array = state[name] + compressed = blosc.compress_ptr(array.__array_interface__['data'][0], array.size, array.dtype.itemsize) + state[name] = (array.dtype, array.shape, compressed) + return state + + def __setstate__(self, state): + """ Re-create an instance from state. Re-open file handers and shared memory objects. """ + self.__dict__ = state + if self.type in ['hdf5', 'qhdf5', 'zarr']: + for name in self.placeholders: + setattr(self, name, self.file[name]) + + elif self.type == 'shm': + for name in self.placeholders: + shm_name, dtype = self.shm_data[name] + shm = SharedMemory(name=shm_name) + placeholder = np.ndarray(buffer=shm.buf, shape=self.shape, dtype=dtype) + self.shm_data[name][0] = shm + setattr(self, name, placeholder) + + elif self.type == 'numpy': + for name in self.placeholders: + dtype, shape, compressed = state[name] + placeholder = np.frombuffer(blosc.decompress(compressed, True), dtype=dtype).reshape(shape) + setattr(self, name, placeholder) + + def __del__(self): + if self.type == 'shm': + self.clear() + + + # Store data in accumulator + def update(self, crop, location): + """ Update underlying storages in supplied `location` with data from `crop`. """ + if self.aggregated: + raise RuntimeError('Aggregated data has been already computed!') + + # Check all shapes for compatibility + for s, slc in zip(crop.shape, location): + if slc.step and slc.step != 1: + raise ValueError(f"Invalid step in location {location}") + + if s < slc.stop - slc.start: + raise ValueError(f"Inconsistent crop_shape {crop.shape} and location {location}") + + # Correct orientation + location = self.reorder(location) + if self.orientation == 1: + crop = crop.transpose(1, 0, 2) + elif self.orientation == 2: + crop = crop.transpose(2, 0, 1) + + # Compute correct shapes + loc, loc_crop = [], [] + for xmin, slc, xmax in zip(self.origin, location, self.shape): + loc.append(slice(max(0, slc.start - xmin), min(xmax, slc.stop - xmin))) + loc_crop.append(slice(max(0, xmin - slc.start), min(xmax + xmin - slc.start , slc.stop - slc.start))) + loc, loc_crop = tuple(loc), tuple(loc_crop) + + # Actual update + crop = self.transform(crop[loc_crop]) if self.transform is not None else crop[loc_crop] + self._update(crop, loc) + + def _update(self, crop, location): + """ Update placeholders with data from `crop` at `locations`. """ + _ = crop, location + raise NotImplementedError + + def aggregate(self): + """ Finalize underlying storages to create required aggregation. """ + if self.aggregated: + raise RuntimeError('All data in the container has already been cleared!') + self._aggregate() + + # Re-open the HDF5 file to force flush changes and release disk space from deleted datasets + # Also add alias to `data` dataset, so the resulting cube can be opened by `Geometry` + # TODO: open resulting HDF5 file with `Geometry` and return it instead? + self.aggregated = True + if self.type in ['hdf5', 'qhdf5']: + if self.orientation == 0: + projection_name = 'projection_i' + elif self.orientation == 1: + projection_name = 'projection_x' + else: + projection_name = 'projection_d' + + self.file[projection_name] = self.file['data'] + self.file.close() + self.file = h5py.File(self.path, 'r+') + self.data = self.file['data'] + elif self.type == 'zarr': + self.file.store.flush() + else: + if self.orientation == 1: + self.data = self.data.transpose(1, 0, 2) + elif self.orientation == 2: + self.data = self.data.transpose(1, 2, 0) + return self.data + + def _aggregate(self): + """ Aggregate placeholders into resulting array. Changes `data` placeholder inplace. """ + raise NotImplementedError + + @property + def result(self): + """ Reference to the aggregated result. """ + if not self.aggregated: + self.aggregate() + return self.data + + + # Utilify methods + def export_to_hdf5(self, path=None, projections=(0,), pbar='t', dtype=None, transform=None, dataset_kwargs=None): + """ Export `data` attribute to a file. """ + if self.type != 'numpy' or self.orientation != 0: + raise NotImplementedError('`export_to_hdf5` works only with `numpy` accumulators with `orientation=0`!') + + # Parse parameters + from ..geometry.conversion_mixin import ConversionMixin #pylint: disable=import-outside-toplevel + if isinstance(path, str) and os.path.exists(path): + os.remove(path) + + dtype = dtype or self.dtype + transform = transform or (lambda array: array) + dataset_kwargs = dataset_kwargs or dict(hdf5plugin.Blosc(cname='lz4hc', clevel=6, shuffle=0)) + + data = self.data + + with h5py.File(path, mode='w-') as file: + with Notifier(pbar, total=sum(data.shape[axis] for axis in projections)) as progress_bar: + for axis in projections: + projection_name = ConversionMixin.PROJECTION_NAMES[axis] + projection_transposition = ConversionMixin.TO_PROJECTION_TRANSPOSITION[axis] + projection_shape = np.array(data.shape)[projection_transposition] + + dataset_kwargs_ = {'chunks': (1, *projection_shape[1:]), **dataset_kwargs} + projection = file.create_dataset(projection_name, shape=projection_shape, dtype=self.dtype, + **dataset_kwargs_) + + for i in range(data.shape[axis]): + projection[i] = transform(take_along_axis(data, i, axis=axis)) + progress_bar.update() + return h5py.File(path, mode='r') + + + # Pre-defined transforms + @staticmethod + def prediction_to_int8(array): + """ Convert a float array with values in [0.0, 1.0] to an int8 array with values in [-128, +127]. """ + array *= 255 + array -= 128 + return array.astype(np.int8) + + @staticmethod + def int8_to_prediction(array): + """ Convert an int8 array with values in [-128, +127] to a float array with values in [0.0, 1.0]. """ + array = array.astype(np.float32) + array += 128 + array /= 255 + return array + + @staticmethod + def prediction_to_uint8(array): + """ Convert a float array with values in [0.0, 1.0] to an uint8 array with values in [0, 255]. """ + array *= 255 + return array.astype(np.uint8) + + @staticmethod + def uint8_to_prediction(array): + """ Convert an uint8 array with values in [0, 255] to a float array with values in [0.0, 1.0]. """ + array = array.astype(np.float32) + array /= 255 + return array + + @staticmethod + def prediction_to_uint16(array): + """ Convert a float array with values in [0.0, 1.0] to an uint16 array with values in [0, 255]. + Useful for accumulators that need to keep track of sum of values. + """ + array *= 255 + return array.astype(np.uint16) + + + # Alternative constructors + @classmethod + def from_aggregation(cls, aggregation='max', shape=None, origin=None, dtype=np.float32, fill_value=None, + transform=None, format=None, path=None, dataset_kwargs=None, **kwargs): + """ Initialize chosen type of accumulator aggregation. """ + class_to_aggregation = { + NoopAccumulator3D: [None, False, 'noop'], + MaxAccumulator3D: ['max', 'maximum'], + MeanAccumulator3D: ['mean', 'avg', 'average'], + StdAccumulator3D: ['std'], + GMeanAccumulator3D: ['gmean', 'geometric'], + WeightedSumAccumulator3D: ['weighted'], + ModeAccumulator3D: ['mode'] + } + aggregation_to_class = {alias: class_ for class_, lst in class_to_aggregation.items() + for alias in lst} + + return aggregation_to_class[aggregation](shape=shape, origin=origin, dtype=dtype, fill_value=fill_value, + transform=transform, format=format, path=path, + dataset_kwargs=dataset_kwargs, **kwargs) + + @classmethod + def from_grid(cls, grid, aggregation='max', dtype=np.float32, fill_value=None, transform=None, + format=None, path=None, dataset_kwargs=None, **kwargs): + """ Infer necessary parameters for accumulator creation from a passed grid. """ + return cls.from_aggregation(aggregation=aggregation, dtype=dtype, fill_value=fill_value, + shape=grid.shape, origin=grid.origin, orientation=grid.orientation, + transform=transform, format=format, path=path, dataset_kwargs=dataset_kwargs, + **kwargs) + + +class NoopAccumulator3D(Accumulator3D): + """ Accumulator that applies no aggregation of overlapping crops. """ + def __init__(self, shape=None, origin=None, dtype=np.float32, transform=None, path=None, **kwargs): + super().__init__(shape=shape, origin=origin, dtype=dtype, transform=transform, path=path, **kwargs) + + self.create_placeholder(name='data', dtype=self.dtype, fill_value=0.0) + + def _update(self, crop, location): + self.data[location] = crop + + def _aggregate(self): + pass + + +class MaxAccumulator3D(Accumulator3D): + """ Accumulator that takes maximum value of overlapping crops. """ + def __init__(self, shape=None, origin=None, dtype=np.float32, fill_value=None, transform=None, path=None, **kwargs): + super().__init__(shape=shape, origin=origin, dtype=dtype, transform=transform, path=path, **kwargs) + + min_value = np.finfo(dtype).min if 'float' in dtype.__name__ else np.iinfo(dtype).min + self.fill_value = fill_value if fill_value is not None else min_value + self.create_placeholder(name='data', dtype=self.dtype, fill_value=self.fill_value) + + def _update(self, crop, location): + self.data[location] = np.maximum(crop, self.data[location]) + + def _aggregate(self): + pass + + +class MeanAccumulator3D(Accumulator3D): + """ Accumulator that takes mean value of overlapping crops. """ + def __init__(self, shape=None, origin=None, dtype=np.float32, transform=None, path=None, **kwargs): + if dtype in [np.int8, np.uint8]: + raise NotImplementedError('`mean` accumulation is unavailable for one-byte dtypes.') + super().__init__(shape=shape, origin=origin, dtype=dtype, transform=transform, path=path, **kwargs) + + self.create_placeholder(name='data', dtype=self.dtype, fill_value=0) + self.create_placeholder(name='counts', dtype=np.uint8, fill_value=0) + + def _update(self, crop, location): + self.data[location] += crop + self.counts[location] += 1 + + def _aggregate(self): + #pylint: disable=access-member-before-definition + if self.type == 'hdf5': + # Amortized updates for HDF5 + for i in range(self.data.shape[0]): + counts = self.counts[i] + counts[counts == 0] = 1 + if np.issubdtype(self.dtype, np.floating): + self.data[i] /= counts + else: + self.data[i] //= counts + + elif self.type in ['numpy', 'shm']: + self.counts[self.counts == 0] = 1 + if np.issubdtype(self.dtype, np.floating): + self.data /= self.counts + else: + self.data //= self.counts + + # Cleanup + self.remove_placeholder('counts', unlink=True) + + +class StdAccumulator3D(Accumulator3D): + """ Accumulator that takes std value of overlapping crops. """ + def __init__(self, shape=None, origin=None, dtype=np.float32, transform=None, path=None, **kwargs): + if dtype not in [np.float32, np.float64]: + raise ValueError('Dtype should be float32 or float64 for `std` accumulator!') + super().__init__(shape=shape, origin=origin, dtype=dtype, transform=transform, path=path, **kwargs) + + self.create_placeholder(name='data', dtype=self.dtype, fill_value=0) # sum of squared values + self.create_placeholder(name='sum', dtype=self.dtype, fill_value=0) # sum of values + self.create_placeholder(name='counts', dtype=np.uint8, fill_value=0) + + def _update(self, crop, location): + self.data[location] += crop ** 2 + self.sum[location] += crop + self.counts[location] += 1 + + def _aggregate(self): + #pylint: disable=access-member-before-definition + if self.type == 'hdf5': + # Amortized updates for HDF5 + for i in range(self.data.shape[0]): + counts = self.counts[i] + counts[counts == 0] = 1 + self.data[i] /= counts + self.sum[i] /= counts + + self.data[i] -= self.sum[i] ** 2 + self.data[i] **= 1/2 + + elif self.type in ['numpy', 'shm']: + self.counts[self.counts == 0] = 1 + self.data /= self.counts + self.sum /= self.counts + + self.data -= self.sum ** 2 + self.data **= 1/2 + + # Cleanup + self.remove_placeholder('counts', unlink=True) + self.remove_placeholder('sum', unlink=True) + + +class GMeanAccumulator3D(Accumulator3D): + """ Accumulator that takes geometric mean value of overlapping crops. """ + def __init__(self, shape=None, origin=None, dtype=np.float32, transform=None, path=None, **kwargs): + super().__init__(shape=shape, origin=origin, dtype=dtype, transform=transform, path=path, **kwargs) + + self.create_placeholder(name='data', dtype=self.dtype, fill_value=1) + self.create_placeholder(name='counts', dtype=np.uint8, fill_value=0) + + def _update(self, crop, location): + self.data[location] *= crop + self.counts[location] += 1 + + def _aggregate(self): + #pylint: disable=access-member-before-definition + if self.type == 'hdf5': + # Amortized updates for HDF5 + for i in range(self.data.shape[0]): + counts = self.counts[i] + counts[counts == 0] = 1 + + counts = counts.astype(np.float32) + counts **= -1 + self.data[i] **= counts + + elif self.type in ['numpy', 'shm']: + self.counts[self.counts == 0] = 1 + + counts = self.counts.astype(np.float32) + counts **= -1 + self.data **= self.counts + + # Cleanup + self.remove_placeholder('counts') + + +class ModeAccumulator3D(Accumulator3D): + """ Accumulator that takes mode value in overlapping crops. """ + def __init__(self, shape=None, origin=None, dtype=np.float32, + n_classes=2, transform=None, path=None, **kwargs): + # Create placeholder with counters for each class + self.fill_value = 0 + self.n_classes = n_classes + + shape = (*shape, n_classes) + origin = (*origin, 0) + + super().__init__(shape=shape, origin=origin, dtype=dtype, transform=transform, path=path, **kwargs) + + self.create_placeholder(name='data', dtype=self.dtype, fill_value=self.fill_value) + + def _update(self, crop, location): + # Update class counters in location + crop = np.eye(self.n_classes)[crop] + self.data[location] += crop + + def _aggregate(self): + # Choose the most frequently seen class value + if self.type == 'hdf5': + for i in range(self.data.shape[0]): + self.data[i] = np.argmax(self.data[i], axis=-1) + + elif self.type in ['numpy', 'shm']: + self.data = np.argmax(self.data, axis=-1) + + +class WeightedSumAccumulator3D(Accumulator3D): + """ Accumulator that takes weighted sum of overlapping crops. Accepts `weights_function` + for making weights for each crop into the initialization. + + NOTE: add support of weights incoming along with a data-crop. + """ + def __init__(self, shape=None, origin=None, dtype=np.float32, transform=None, path=None, + weights_function=triangular_weights_function_nd, **kwargs): + if dtype in [np.int8, np.uint8]: + raise NotImplementedError('`weighted` accumulation is unavailable for one-byte dtypes.') + super().__init__(shape=shape, origin=origin, dtype=dtype, transform=transform, path=path, **kwargs) + + self.create_placeholder(name='data', dtype=self.dtype, fill_value=0) + self.create_placeholder(name='weights', dtype=np.float32, fill_value=0) + self.weights_function = weights_function + self.crop_weights = None + + def _update(self, crop, location): + # Weights matrix for the incoming crop + if self.crop_weights is None or self.crop_weights.shape != crop.shape: + self.crop_weights = self.weights_function(crop) + + self.data[location] = ((self.crop_weights * crop + self.data[location] * self.weights[location]) / + (self.crop_weights + self.weights[location])) + self.weights[location] += self.crop_weights + + def _aggregate(self): + # Cleanup + self.remove_placeholder('weights', unlink=True) + + +class RegressionAccumulator(Accumulator3D): + """ Accumulator that fits least-squares regression to scale values of + each incoming crop to match values of the overlap. In doing so, ignores nan-values. + For aggregation uses weighted sum of crops. Weights-making for crops is controlled by + `weights_function`-parameter. + + Parameters + ---------- + shape : sequence + Shape of the placeholder. + origin : sequence + The upper left point of the volume: used to shift crop's locations. + dtype : np.dtype + Dtype of storage. Must be either integer or float. + transform : callable, optional + Additional function to call before storing the crop data. + path : str or file-like object, optional + If provided, then we use HDF5 datasets instead of regular Numpy arrays, storing the data directly on disk. + After the initialization, we keep the file handle in `w-` mode during the update phase. + After aggregation, we re-open the file to automatically repack it in `r` mode. + weights_function : callable + Function that accepts a crop and returns matrix with weights of the same shape. Default scheme + involves using larger weights in the crop-centre and lesser weights closer to the crop borders. + rsquared_lower_bound : float + Can be a number between 0 and 1 or `None`. If set to `None`, we use each incoming crop with + predictions to update the assembled array. Otherwise, we use only those crops, that fit already + filled data well enough, requiring r-squared of linear regression to be larger than the supplied + parameter. + regression_target : str + Can be either 'assembled' (same as 'accumulated') or 'crop' (same as 'incoming'). If set to + 'assembled', the regression considers new crop as a regressor and already filled overlap as a target. + If set to 'crop', incoming crop is the target in the regression. The choice of 'assembled' + should yield more stable results. + + NOTE: As of now, relies on the order in which crops with data arrive. When the order of + supplied crops is different, the result of aggregation might differ as well. + """ + def __init__(self, shape=None, origin=None, dtype=np.float32, transform=None, path=None, + weights_function=triangular_weights_function_nd, rsquared_lower_bound=.2, + regression_target='assembled', **kwargs): + super().__init__(shape=shape, origin=origin, dtype=dtype, transform=transform, path=path, **kwargs) + + # Fill both placeholders with nans: in order to fit the regression + # it is important to understand what overlap values are already filled. + # NOTE: perhaps rethink and make weighted regression. + self.create_placeholder(name='data', dtype=self.dtype, fill_value=np.nan) + self.create_placeholder(name='weights', dtype=np.float32, fill_value=np.nan) + + self.weights_function = weights_function + self.rsquared_lower_bound = rsquared_lower_bound or -1 + + if regression_target in ('assembled', 'accumulated'): + self.regression_target = 'assembled' + elif regression_target in ('crop', 'incoming'): + self.regression_target = 'crop' + else: + raise ValueError(f'Unknown regression target {regression_target}.') + + def _update(self, crop, location): + # Scale incoming crop to better fit already filled data. + # Fit is done via least-squares regression. + overlap_data = self.data[location] + overlap_weights = self.weights[location] + crop_weights = self.weights_function(crop) + + # If some of the values are already filled, use regression to fit new crop + # to what's filled. + overlap_indices = np.where((~np.isnan(overlap_data)) & (~np.isnan(crop))) + new_indices = np.where(np.isnan(overlap_data)) + + if len(overlap_indices[0]) > 0: + # Take overlap values from data-placeholder and the crop. + # Select regression/target according to supplied parameter `regression_target`. + if self.regression_target == 'assembled': + xs, ys = crop[overlap_indices], overlap_data[overlap_indices] + else: + xs, ys = overlap_data[overlap_indices], crop[overlap_indices] + + # Fit new crop to already existing data and transform the crop. + model = LinearRegression() + model.fit(xs.reshape(-1, 1), ys.reshape(-1)) + + # Calculating the r-squared of the fitted regression. + a, b = model.coef_[0], model.intercept_ + xs, ys = xs.reshape(-1), ys.reshape(-1) + rsquared = 1 - ((a * xs + b - ys) ** 2).mean() / ((ys - ys.mean()) ** 2).mean() + + # If the fit is bad (r-squared is too small), ignore the incoming crop. + # If it is of acceptable quality, use it to update the assembled-array. + if rsquared > self.rsquared_lower_bound: + if self.regression_target == 'assembled': + crop = a * crop + b + else: + crop = (crop - b) / a + + # Update location-slice with weighted average. + overlap_data[overlap_indices] = ((overlap_weights[overlap_indices] * overlap_data[overlap_indices] + + crop_weights[overlap_indices] * crop[overlap_indices]) / + (overlap_weights[overlap_indices] + crop_weights[overlap_indices])) + + # Update weights over overlap. + overlap_weights[overlap_indices] += crop_weights[overlap_indices] + + # Use values from crop to update the region covered by the crop and not yet filled. + self.data[location][new_indices] = crop[new_indices] + self.weights[location][new_indices] = crop_weights[new_indices] + else: + self.data[location] = crop + self.weights[location] = crop_weights + + def _aggregate(self): + # Clean-up + self.remove_placeholder('weights') diff --git a/seismiqb/utils/cache.py b/seismiqb/utils/cache.py new file mode 100644 index 0000000..317502c --- /dev/null +++ b/seismiqb/utils/cache.py @@ -0,0 +1,488 @@ +""" Thread-safe lru cache class and cache mixin. """ +import os +from copy import copy +from functools import wraps +from inspect import ismethod, signature +import json +from threading import RLock +from collections import Counter, defaultdict, OrderedDict +from weakref import WeakSet + +import numpy as np +import pandas as pd + + +class _GlobalCache: + """ Methods for global cache management. + + Note, this class controls only objects which use :class:`~.lru_cache`. + So, for properties you need to use both `property` and `lru_cache` decorators for proper cache introspection. + """ + #pylint: disable=redefined-builtin + def __init__(self): + """ Initialize containers with cache references and instances with cached objects. + + Note, the `cache_references` container is filled on the modules import stage.""" + self.cache_references = {} # for tests and debugging, helps to get cache info such as maxsize or stats + self.instances_with_cache = WeakSet() + + @property + def size(self): + """ Total cache size. """ + return self.get_stats(stats='size', level='total')['size'] + + @property + def nbytes(self): + """ Total cache nbytes. """ + return self.get_stats(stats='nbytes', level='total')['nbytes'] + + def get_size(self, level='total', format='dict'): + """ Get cache size grouped by level. For more read the doc for :meth:`~.get_attr`""" + result = self.get_stats(stats='size', level=level, format=format) + result = result['size'] if (level == 'total' and format == 'default') else result + return result + + def get_nbytes(self, level='total', format='dict'): + """ Get cache nbytes grouped by level. For more read the doc for :meth:`~.get_attr`""" + result = self.get_stats(stats='nbytes', level=level, format=format) + result = result['nbytes'] if (level == 'total' and format == 'default') else result + return result + + def get_stats(self, stats='size', level='total', format='default'): + """ Get cache statistics grouped by level. + + Parameters + ---------- + stat : str or list of str + Statistic to get values. Possible options are: 'size', 'nbytes' or both. + level : {'total', 'class', 'instance'} + Result groupby level. + If 'total', then return a total stat value for all instances. + If 'class', then return a dict with stat value for each class. + If 'instance', then return a nested dict with stat value for each instance. + format : {'default', 'dict', 'df'} + Returned data format. + If 'default', then return data as it is. + If 'dict', then convert data to the dictionary. + If 'df', then convert data to the pandas DataFrame. + """ + stats = (stats, ) if isinstance(stats, str) else stats + + # Init result accumulator/container + if level == 'total': + result = Counter({}) + elif level == 'class': + result = defaultdict(Counter) + else: + result = defaultdict(lambda: defaultdict(Counter)) + + # Fill accumulator/container with attribute values from instances with cache + for instance in self.instances_with_cache: + instance_stats = {stat: getattr(instance, f'cache_{stat}') for stat in stats} + + if level == 'total': + result += instance_stats + elif level == 'class': + result[instance.__class__.__name__] += instance_stats + else: + result[instance.__class__.__name__][f'id_{id(instance)}'] += instance_stats + + # Prepare output + if format == 'dict': + result = json.loads(json.dumps(result, default=lambda x: x.__dict__)) + + elif format == 'df': + if level == 'total': + result = pd.DataFrame(result, index=['total']) + elif level == 'class': + result = pd.DataFrame(result).T + elif level == 'instance': + result = pd.concat({k: pd.DataFrame(v).T for k, v in result.items()}, axis=0) + + return result + + def get_cache_repr(self, format='dict'): + """ Create global cache representation. + + Cache representation consists of names of objects, that use data caching, + information about cache size, nbytes, and arguments for each method. + + Keys (for 'dict') or index columns (for 'df') are: class name, instance id, method or property name. + Values are: size, nbytes and arguments. + + Parameters + ---------- + format : {'dict', 'df'} + Return value format. 'df' means pandas DataFrame. + """ + cache_repr_ = {} + + # Extract cache repr for each cached object + for instance in self.instances_with_cache: + instance_cache_repr = instance.get_cache_repr() + + if instance_cache_repr is not None: + class_name = instance.__class__.__name__ + if class_name not in cache_repr_: + cache_repr_[class_name] = {} + + cache_repr_[class_name][f'id_{id(instance)}'] = instance_cache_repr + + # Convert to pandas dataframe + if format == 'df' and len(cache_repr_) > 0: + # Dataframe index columns are (class_name, instance_id, object_name), expand values for them: + cache_repr_ = pd.DataFrame.from_dict({ + (class_name, instance_id, object_name): object_data + for class_name, class_data in cache_repr_.items() + for instance_id, instance_data in class_data.items() + for object_name, object_data in instance_data.items()}, + orient='index') + + cache_repr_ = cache_repr_.loc[:, ['size', 'nbytes', 'arguments']] # Columns sort + + return cache_repr_ if len(cache_repr_) > 0 else None + + @property + def repr(self): + """ Global cache representation. """ + df = self.get_cache_repr(format='df') + if df is not None: + df = df.loc[:, ['size', 'nbytes']] + return df + + def reset(self): + """ Clear all cache. """ + for instance in self.instances_with_cache: + instance.reset_cache() + +GlobalCache = _GlobalCache() # Global cache controller, must be the only one instance + +class lru_cache: + """ Thread-safe least recent used cache. Must be applied to a class methods. + Adds the `use_cache` argument to the decorated method to control whether the caching logic is applied. + + Under the hood, the decorator creates `cache` attribute with dict of all cached elements. + The `cache` keys are cached objects names and values are OrderedDict with all saved items. + + Parameters + ---------- + maxsize : int + Maximum amount of stored values. + attributes: None, str or sequence of str + Attributes to get from object and use as additions to key. + apply_by_default : bool + Whether the cache logic is on by default. + copy_on_return : bool + Whether to copy the object on retrieving from cache. + + Examples + -------- + Store loaded slides:: + + @lru_cache(maxsize=128) + def load_slide(cube_name, slide_no): + pass + + Specify cache size on class instantiation:: + def __init__(self, maxsize): + self.method = lru_cache(maxsize)(self.method) + + Notes + ----- + All arguments to a decorated method must be hashable. + """ + #pylint: disable=invalid-name, attribute-defined-outside-init + def __init__(self, maxsize=128, attributes=None, apply_by_default=True, copy_on_return=False): + self.maxsize = maxsize + self.apply_by_default = apply_by_default + self.copy_on_return = copy_on_return + self.func_signature = None + + # Parse `attributes` + if isinstance(attributes, str): + self.attributes = [attributes] + elif isinstance(attributes, (tuple, list)): + self.attributes = attributes + else: + self.attributes = False + + self.default = Singleton + self.lock = RLock() + self.reset() + + def reset(self, instance=None): + """ Clear cache and stats. """ + if instance is None: + self.stats = defaultdict(lambda: {'hit': 0, 'miss': 0}) + else: + if hasattr(self, 'cache') and (self.cached_attr in self.cache): + del self.cache[self.cached_attr] + + instance_hash = self.compute_hash(instance) + self.stats[instance_hash] = {'hit': 0, 'miss': 0} + + def make_key(self, instance, func, args, kwargs): + """ Create a key from a combination of method args and instance attributes. """ + # pylint: disable=unsupported-membership-test + # Process args + args = list(args) if not isinstance(args, list) else args + + if 'self' in self.func_signature: + args = args[1:] + + args_and_defaults = [name for name in self.func_signature.keys() + if (name not in kwargs.keys()) and (name != 'self')] + + # Process default values + for default_param in args_and_defaults[len(args):]: + default_value = self.func_signature.get(default_param).default + args.append(default_value) + + # Create key from args and defaults + key = list(zip(args_and_defaults, args)) + + # Process kwargs + if kwargs: + for k, v in sorted(kwargs.items()): + if isinstance(v, slice): + v = (v.start, v.stop, v.step) + key.append((k, v)) + + # Process attributes + if self.attributes: + for attr in self.attributes: + attr_hash = getattr(instance, attr).__hash__() + key.append(attr_hash) + return flatten_nested(key) + + @staticmethod + def compute_hash(obj): + """ Compute `obj` hash. If not provided by the object, rely on objects identity. """ + #pylint: disable=bare-except + try: + result = hash(obj) + except: + result = id(obj) + return result + + def __call__(self, func): + """ Add the cache to the function. """ + @wraps(func) + def wrapper(*args, **kwargs): + # if a bound method, get class instance from function else from arguments + instance = func.__self__ if self.is_method else args[0] + + use_cache = kwargs.pop('use_cache', self.apply_by_default) + copy_on_return = kwargs.pop('copy_on_return', self.copy_on_return) + + if os.getenv('SEISMIQB_DISABLE_CACHE', ""): + use_cache = False + + # Skip the caching logic and evaluate function directly + if not use_cache: + result = func(*args, **kwargs) + return result + + # Init cache and reference on it in the GlobalCache controller + if not hasattr(instance, 'cache'): + # Init cache container in the instance + setattr(instance, 'cache', defaultdict(OrderedDict)) + + GlobalCache.instances_with_cache.add(instance) + + key = self.make_key(instance, func, args, kwargs) + instance_hash = self.compute_hash(instance) + + # If result is already in cache, just retrieve it and update its timings + instance_cache = instance.cache[self.cached_attr] + result = instance_cache.get(key, self.default) + + if result is not self.default: + with self.lock: + instance_cache.move_to_end(key) + self.stats[instance_hash]['hit'] += 1 + return copy(result) if copy_on_return else result + + # The result was not found in cache: evaluate function + result = func(*args, **kwargs) + + # Add the result to cache + with self.lock: + self.stats[instance_hash]['miss'] += 1 + + if key in instance_cache: + pass + elif len(instance_cache) >= self.maxsize: + instance_cache.popitem(last=False) + instance_cache[key] = result + else: + instance_cache[key] = result + + return copy(result) if copy_on_return else result + + self.is_method = ismethod(func) + self.cached_attr = func.__qualname__ # used as a cache key in instances + self.func_signature = signature(func).parameters + + wrapper.__name__ = func.__name__ + wrapper.stats = lambda: self.stats + wrapper.reset = self.reset + wrapper.reset_instance = lambda instance: self.reset(instance=instance) + + GlobalCache.cache_references[func.__qualname__] = self + return wrapper + + +class SingletonClass: + """ There must be only one! """ +Singleton = SingletonClass() + +def flatten_nested(iterable): + """ Recursively flatten nested structure of tuples, list and dicts. """ + result = [] + if isinstance(iterable, (tuple, list)): + for item in iterable: + result.extend(flatten_nested(item)) + elif isinstance(iterable, dict): + for key, value in sorted(iterable.items()): + result.extend((*flatten_nested(key), *flatten_nested(value))) + else: + return (iterable,) + return tuple(result) + + +class CacheMixin: + """ Methods for cache management. + + You can use this mixin for cache introspection and cached data cleaning on instance level. + """ + def get_cache_size(self, name=None): + """ Get cache size for specified objects. + + Parameters + ---------- + name: str, optional + Attribute name. If None, then get total cache size. + """ + cached_values = self.get_cached_values(name) + return len(cached_values) + + def get_cache_nbytes(self, name=None): + """ Get cache nbytes for specified objects. + + Parameters + ---------- + name: str, optional + Attribute name. If None, then get total cache nbytes. + """ + cache_nbytes_accumulator = 0 + cached_values = self.get_cached_values(name) + + # Accumulate nbytes over all cached objects: each term is a nbytes of cached numpy array + for value in cached_values: + if isinstance(value, np.ndarray): + cache_nbytes_accumulator += value.nbytes #/ (1024 ** 3) + + return cache_nbytes_accumulator + + def get_cached_values(self, name=None): + """ Get cache values for specified objects. """ + cached_values = [] + if hasattr(self, 'cache'): + names = (name,) if name is not None else self.cache.keys() + + for cached_attr in names: + cached_values.extend(self.cache[cached_attr].values()) + return cached_values + + @property + def cache_size(self): + """ Total amount of cached objects. """ + return self.get_cache_size() + + @property + def cache_nbytes(self): + """ Total nbytes of cached objects. """ + return self.get_cache_nbytes() + + def _get_object_cache_repr(self, name): + """ Make object's cache repr. """ + object_cache_size = self.get_cache_size(name=name) + + if object_cache_size == 0: + return None + + object_cache_nbytes = self.get_cache_nbytes(name=name) + + cached_data = getattr(self, 'cache', {}).get(name, {}) + + # The class saves cache for the same method with different arguments values + # Get them all in a desired format: list of dicts + all_arguments = [] + for arguments in cached_data.keys(): + arguments = dict(zip(arguments[::2], arguments[1::2])) # tuple ('name', value, ...) to dict + all_arguments.append(arguments) + + # Expand extra scopes + if len(all_arguments) == 1: + all_arguments = all_arguments[0] + + object_cache_repr = { + 'size': object_cache_size, + 'nbytes': object_cache_nbytes, + 'arguments': all_arguments + } + + return object_cache_repr + + def get_cache_repr(self, format='dict'): + """ Create instance cache representation. + + Cache representation consists of names of objects that use data caching, + information about cache size, nbytes, and arguments for each method. + + Parameters + ---------- + format : {'dict', 'df'} + Return value format. 'df' means pandas DataFrame. + """ + #pylint: disable=redefined-builtin + cache_repr_ = {} + + # Create cache representation for each object + for name in self.cache.keys(): + object_cache_repr = self._get_object_cache_repr(name=name) + + if object_cache_repr is not None: + cache_repr_[name] = object_cache_repr + + # Convert to pandas dataframe + if format == 'df' and len(cache_repr_) > 0: + cache_repr_ = pd.DataFrame.from_dict(cache_repr_, orient='index') + cache_repr_ = cache_repr_.loc[:, ['size', 'nbytes', 'arguments']] # Columns sort + + return cache_repr_ if len(cache_repr_) > 0 else None + + @property + def cache_repr(self): + """ DataFrame with cache representation that contains names, cache_size + and cache_nbytes for each cached object. + """ + df = self.get_cache_repr(format='df') + if df is not None: + df = df.loc[:, ['size', 'nbytes']] + return df + + def reset_cache(self, name=None): + """ Clear cached data. + + Parameters + ---------- + name: str, optional + Attribute name. If None, then clean cache of all cached objects. + """ + if hasattr(self, 'cache'): + if name is not None: + del self.cache[name] + else: + self.cache.clear() diff --git a/seismiqb/utils/charisma.py b/seismiqb/utils/charisma.py new file mode 100644 index 0000000..c7100e0 --- /dev/null +++ b/seismiqb/utils/charisma.py @@ -0,0 +1,182 @@ +""" Charisma mixin for saving and loading data in CHARISMA-compatible format. """ +import os + +import numpy as np +import pandas as pd + +from .functions import make_interior_points_mask + +class CharismaMixin: + """ Methods for saving and loading data in CHARISMA-compatible format. """ + #pylint: disable=redefined-builtin + + # CHARISMA: default seismic format of storing surfaces inside the 3D volume + CHARISMA_SPEC = ['inline_marker', '_', 'INLINE_3D', 'xline_marker', '__', 'CROSSLINE_3D', 'CDP_X', 'CDP_Y', 'DEPTH'] + + # REDUCED_CHARISMA: CHARISMA without redundant columns + REDUCED_CHARISMA_SPEC = ['INLINE_3D', 'CROSSLINE_3D', 'DEPTH'] + + @property + def field_reference(self): + """ Reference to Field for applying methods. """ + return self.field if hasattr(self, 'field') else self + + # Load and save data in charisma-compatible format + def load_charisma(self, path, dtype=np.int32, format='points', fill_value=np.nan, + transform=True, verify=True, recover_lines=False, **kwargs): + """ Load data from path to either CHARISMA or REDUCED_CHARISMA csv-like file. + + Parameters + ---------- + path : str + Path to a file to import data from. + dtype : data-type + Output dtype. + format : str + Output array format, can be 'points' or 'matrix'. + If format is 'points' then return data as ndarray of (ilines_len, xlines_len, depth) with shape (N, 3). + If format is 'matrix' then return data as ndarray of (ilines_len, xlines_len) shape. + fill_value : int or float + Value to place into blank spaces. + transform : bool + Whether transform from line coordinates (ilines, xlines) to cubic system. + verify : bool + Whether to remove points outside of the cube range. + """ + _ = kwargs + path = self.field_reference.make_path(path, makedirs=False) + + # Load data as a points array from a file + with open(path, encoding='utf-8') as file: + line_len = len(file.readline().split()) + if line_len == len(self.REDUCED_CHARISMA_SPEC): + names = self.REDUCED_CHARISMA_SPEC + elif line_len >= len(self.CHARISMA_SPEC): + names = self.CHARISMA_SPEC + else: + raise ValueError('Data must be in CHARISMA or REDUCED_CHARISMA format.') + + df = pd.read_csv(path, sep=r'\s+', names=names, usecols=self.REDUCED_CHARISMA_SPEC) + if recover_lines: + df = self.recover_lines_from_cdp(df) + df.sort_values(self.REDUCED_CHARISMA_SPEC, inplace=True) + points = df.values + + # Transform and verify points + if transform: + points = self.field_reference.geometry.lines_to_ordinals(points) + + if verify: + mask = make_interior_points_mask(points, self.field_reference.shape) + points = points[mask] + + # Set datatype + if np.issubdtype(dtype, np.integer): + points = np.round(points) + + points = points.astype(dtype) + + if format == 'points': + return points + + # Make a matrix from points and return + matrix = np.full(shape=self.field_reference.shape[:2], fill_value=fill_value, dtype=dtype) + matrix[points[:, 0].astype(np.int32), points[:, 1].astype(np.int32)] = points[:, 2] + + return matrix + + def dump_charisma(self, data, path, format='points', name=None, transform=None): + """ Save data as (N, 3) array of points to a disk in CHARISMA-compatible format. + + Parameters + ---------- + data : ndarray + Array of (N, 3) shape or (i_lines, x_lines) shape. + path : str + Path to a file to save array to. + format : str + Input array format, can be 'points' or 'matrix'. + If format is 'points' then input data is a ndarray of (ilines_len, xlines_len, depth) with shape (N, 3). + If format is 'matrix' then input data is a ndarray of (ilines_len, xlines_len) shape. + name : str + Dumped object name. + transform : None or callable + If callable, then applied to points after converting to ilines/xlines coordinate system. + """ + path = self.field_reference.make_path(path, name=name or self.name) + os.makedirs(os.path.dirname(path), exist_ok=True) + + if format != 'points': + # Convert data to points array + idx = np.nonzero(~np.isnan(data)) + + data = np.hstack([idx[0].reshape(-1, 1), + idx[1].reshape(-1, 1), + data[idx[0], idx[1]].reshape(-1, 1)]) + + points = self.field_reference.geometry.ordinals_to_lines(data) + + # Additional transform + points = points if transform is None else transform(points) + + # Dump a charisma file + df = pd.DataFrame(points, columns=self.REDUCED_CHARISMA_SPEC) + df.sort_values(['INLINE_3D', 'CROSSLINE_3D'], inplace=True) + df = df.astype({'INLINE_3D': np.int32, 'CROSSLINE_3D': np.int32, 'DEPTH': np.float32}) + df.to_csv(path, sep=' ', columns=self.REDUCED_CHARISMA_SPEC, index=False, header=False) + + @classmethod + def is_charisma_like(cls, path, bad_extensions=None, size_threshold=100): + """ Check if the path looks like the charisma file. + + Parameters + ---------- + path : str + Path of file to check. + bad_extensions : list, optional + If provided, then list of extensions to consider file not charisma-like. + size_threshold : number + If file size in kilobytes is less, than the threshold, then file is considered not charisma-like. + """ + bad_extensions = bad_extensions or [] + bad_extensions.extend(['.py', '.ipynb', '.ckpt', + '.png', '.jpg', + '.log', '.txt', '.torch']) + + try: + if os.path.isdir(path): + return False + + if max(path.endswith(ext) for ext in bad_extensions): + return False + + if (os.path.getsize(path) / 1024) < size_threshold: + return False + + with open(path, encoding='utf-8') as file: + line = file.readline() + n = len(line.split(' ')) + + is_reduced_charisma = (n == len(cls.REDUCED_CHARISMA_SPEC)) + is_charisma = (n >= len(cls.CHARISMA_SPEC) and 'INLINE' in line) + return is_reduced_charisma or is_charisma + + except UnicodeDecodeError: + return False + + + def recover_lines_from_cdp(self, df): + """ Fix broken iline and crossline coordinates. + If coordinates are out of the cube, 'iline' and 'xline' will be infered from 'cdp_x' and 'cdp_y'. """ + i_bounds = [self.field.shifts[0], self.field.shifts[0] + self.field.shape[0]] + x_bounds = [self.field.shifts[1], self.field.shifts[1] + self.field.shape[1]] + + i_mask = np.logical_or(df['INLINE_3D'] < i_bounds[0], df['INLINE_3D'] >= i_bounds[1]) + x_mask = np.logical_or(df['CROSSLINE_3D'] < x_bounds[0], df['CROSSLINE_3D'] >= x_bounds[1]) + + _df = df[np.logical_or(i_mask, x_mask)] + + coords = np.rint(self.field.geometry.cdp_to_lines(_df[['CDP_X', 'CDP_Y']].values)).astype(np.int32) + df.loc[np.logical_or(i_mask, x_mask), ['INLINE_3D', 'CROSSLINE_3D']] = coords + + return df diff --git a/seismiqb/utils/classes.py b/seismiqb/utils/classes.py new file mode 100644 index 0000000..54c9657 --- /dev/null +++ b/seismiqb/utils/classes.py @@ -0,0 +1,355 @@ +""" Helper classes. """ +from ast import literal_eval +from collections import OrderedDict +from functools import wraps + +import numpy as np +try: + import bottleneck + BOTTLENECK_AVAILABLE = True +except ImportError: + BOTTLENECK_AVAILABLE = False + + +from .functions import to_list + + + +class AugmentedNumpy: + """ NumPy with better routines for nan-handling. """ + def __getattr__(self, key): + if not BOTTLENECK_AVAILABLE: + return getattr(np, key) + return getattr(bottleneck, key, getattr(np, key)) +augmented_np = AugmentedNumpy() + + + +class LoopedList(list): + """ List that loops from given position (default is 0). + + Examples + -------- + >>> l = LoopedList(['a', 'b', 'c']) + >>> [l[i] for i in range(9)] + ['a', 'b', 'c', 'a', 'b', 'c', 'a', 'b', 'c'] + + >>> l = LoopedList(['a', 'b', 'c', 'd'], loop_from=2) + >>> [l[i] for i in range(9)] + ['a', 'b', 'c', 'd', 'c', 'd', 'c', 'd', 'c'] + + >>> l = LoopedList(['a', 'b', 'c', 'd', 'e'], loop_from=-1) + >>> [l[i] for i in range(9)] + ['a', 'b', 'c', 'd', 'e', 'e', 'e', 'e', 'e'] + """ + def __init__(self, *args, loop_from=0, **kwargs): + self.loop_from = loop_from + super().__init__(*args, **kwargs) + + def __getitem__(self, idx): + if idx >= len(self): + pos = self.loop_from + len(self) * (self.loop_from < 0) + if pos < 0: + raise IndexError(f"List of length {len(self)} is looped from {self.loop_from} index") + idx = pos + (idx - pos) % (len(self) - pos) + return super().__getitem__(idx) + + +class AugmentedList(list): + """ List that delegates attribute retrieval requests to contained objects and can be indexed with other iterables. + On successful attribute request returns the list of results, which is itself an instance of `AugmentedList`. + Auto-completes names to that of contained objects. Meant to be used for storing homogeneous objects. + + Examples + -------- + 1. Let `lst` be an `AugmentedList` of objects that have `mean` method. + Than the following expression: + >>> lst.mean() + Is equivalent to: + >>> [item.mean() for item in lst] + + 2. Let `lst` be an `AugmentedList` of objects that have `shape` attribute. + Than the following expression: + >>> lst.shape + Is equivalent to: + >>> [item.shape for item in lst] + + Notes + ----- + Using `AugmentedList` for heterogeneous objects storage is not recommended, due to the following: + 1. Tab autocompletion suggests attributes from the first list item only. + 2. The request of the attribute absent in any of the objects leads to an error. + """ + def __getitem__(self, key): + """ Manage indexing via iterable. """ + if isinstance(key, (int, np.integer)): + return super().__getitem__(key) + + if isinstance(key, slice): + return type(self)(super().__getitem__(key)) + + # list comprehensions have their own `locals()` that do not contain `self` and therefore `super` is unable + # to resolve zero argument form in the expression below, so we provide `type` and `object` arguments explicitly + return type(self)([super(type(self), self).__getitem__(idx) for idx in key]) # pylint: disable=bad-super-call + + # Delegating to contained objects + def __getattr__(self, key): + """ Get attributes of list items, recusively delegating this process to items if they are lists themselves. """ + if len(self) == 0: + return lambda *args, **kwargs: self + + attributes = type(self)([getattr(item, key) for item in self]) + + if not callable(attributes.reference_object): + return type(self)(attributes) + + @wraps(attributes.reference_object) + def wrapper(*args, **kwargs): + return type(self)([method(*args, **kwargs) for method in attributes]) + + return wrapper + + @property + def reference_object(self): + """ First item of a list taking into account its nestedness. """ + return self[0].reference_object if isinstance(self[0], type(self)) else self[0] + + def __dir__(self): + """ Correct autocompletion for delegated methods. """ + return dir(list) if len(self) == 0 else dir(self[0]) + + # Correct type of operations + def __add__(self, other): + return type(self)(list.__add__(self, other)) + + def __radd__(self, other): + return self.__add__(other) + + def __mul__(self, other): + return type(self)(list.__mul__(self, other)) + + def __rmul__(self, other): + return self.__mul__(other) + + +class DelegatingList(AugmentedList): + """ `AugmentedList` that allows nested mapping and filtering. + + Examples + -------- + 1. Let `indices` be an `DelegatingList` of intergers, representing image layers indices: + >>> indices = [0, 0, [0, 1]] + And let `choose_opacity` be a function that sets different opacity levels, depeneing on layer index: + >>> choose_opacity = lambda index: 1.0 if index == 0 else 0.7 + Than the following expression: + >>> indices.map(choose_opacity) + Is evaluated to: + >>> [1.0, 1.0, [1.0, 0.7]] + + 2. Let `attributes` be an `DelegatingList` of strings, representing possible `batch` objects attributes: + >>> attributes = ['inputs', 'targets', 'predictions', ['inputs', 'targets', 'predictions']] + And let `present_in_batch` be a function that returns True if an attribute with such name is present in `batch`: + >>> present_in_batch = lambda attribute: hasattr(batch, attribute) + Than the following expression: + >>> attributes.filter(present_in_batch) + Is evaluated to following (if attribute 'predictions' is absent in `batch`): + >>> ['inputs', 'targets', ['inputs', 'targets']] + + 3. Let `configs` be a `DelegatingList` of dictionaries: + >>> configs = [ + {'cmap': 'viridis', 'alpha': 1.0}, + [ + {'cmap': 'ocean', 'alpha': 1.0}, + {'cmap': 'Reds', 'alpha': 0.7} + ] + ] + That the following expresion: + >>> configs.to_dict() + Will be evaluated to: + >>> {'cmap': ['viridis, ['ocean', 'Reds]], 'alpha': [1.0, [1.0, 0.7]]} + """ + def __init__(self, obj=None): + """ Perform items recusive casting to `AugmentedList` type if they are lists. """ + obj = [] if obj is None else obj if isinstance(obj, list) else [obj] + super().__init__([type(self)(item) if isinstance(item, list) else item for item in obj]) + + def map(self, func, *other, shallow=False, **kwargs): + """ Recursively traverse list items applying given function and return list of results with same nestedness. + + Parameters + ---------- + func : callable + Function to apply to items. + other : iterables of same nestedness as `self` + Contain items that are provided to `func` alongside with position-corresponding items from `self`. + shallow : bool + If True, apply function directly to outer list items disabling recursive descent. + kwargs : misc + For `func`. + """ + result = type(self)() + + for main_item, *other_items in zip(self, *other): + if isinstance(main_item, type(self)) and not shallow: + res = main_item.map(func, *other_items, **kwargs) + else: + res = func(main_item, *other_items, **kwargs) + + if isinstance(res, list): + res = type(self)(res) + + result.append(res) + + return result + + def filter(self, func, *other, shallow=False, **kwargs): + """ Recursively apply given filtering function to list items and return those items for which function is true. + + Parameters + ---------- + func : callable + Filtering function to apply to items. Should return either False or True. + other : iterables of same nestedness as `self` + Contain items that are provided to `func` alongside with position-corresponding items from `self`. + shallow : bool + If True, apply function directly to outer list items disabling recursive descent. + args, kwargs : misc + For `func`. + """ + result = type(self)() + + for main_item, *other_items in zip(self, *other): + if isinstance(main_item, type(self)) and not shallow: + res = main_item.filter(func, *other_items, **kwargs) + if len(res) > 0: + result.append(res) + else: + res = func(main_item, *other_items, **kwargs) + if res: + result.append(main_item) + + return result + + def to_dict(self): + """ Convert nested list of dicts to dict of nested lists. Address class docs for usage examples. """ + if not isinstance(self.reference_object, dict): + raise TypeError('Only lists consisting of `dict` items can be converted.') + + result = {} + + # pylint: disable=cell-var-from-loop + for key in self.reference_object: + try: + result[key] = self.map(lambda dct: dct[key]) + except KeyError as e: + raise ValueError(f'KeyError occured due to absence of key `{key}` in some of list items.') from e + + return result + + @property + def flat(self): + """ Flat list of items. """ + res = type(self)() + + for item in self: + if isinstance(item, type(self)): + res.extend(item.flat) + else: + res.append(item) + + return res + + +class AugmentedDict(OrderedDict): + """ Ordered dictionary with additional features: + - can be indexed with ordinals. + - delegates calls to contained objects. + For example, `a_dict.method()` is equivalent to `{key : value.method() for key, value in a_dict.items()}`. + Can be used to retrieve attributes, properties and call methods. + Returns the dictionary with results, which is itself an instance of `AugmentedDict`. + - auto-completes names to that of contained objects. + - can be flattened. + """ + # Ordinal indexation + def __getitem__(self, key): + if isinstance(key, (int, np.integer)): + key = list(self.keys())[key] + return super().__getitem__(key) + + def __setitem__(self, key, value): + if isinstance(key, (int, np.integer)): + key = list(self.keys())[key] + + if isinstance(value, list): + value = AugmentedList(value) + super().__setitem__(key, value) + + # Delegating to contained objects + def __getattr__(self, key): + if len(self) == 0: + return lambda *args, **kwargs: self + + attribute = getattr(self[0], key) + + if not callable(attribute): + # Attribute or property + return AugmentedDict({key_ : getattr(value, key) for key_, value in self.items()}) + + @wraps(attribute) + def method_wrapper(*args, **kwargs): + return AugmentedDict({key_ : getattr(value, key)(*args, **kwargs) for key_, value in self.items()}) + return method_wrapper + + def __dir__(self): + """ Correct autocompletion for delegated methods. """ + if len(self) != 0: + return dir(self[0]) + return dir(dict) + + # Convenient iterables + def flatten(self, keys=None): + """ Get dict values for requested keys in a single list. """ + keys = to_list(keys) if keys is not None else list(self.keys()) + lists = [self[key] if isinstance(self[key], list) else [self[key]] for key in keys] + flattened = sum(lists, []) + return AugmentedList(flattened) + + @property + def flat(self): + """ List of all dictionary values. """ + return self.flatten() + + + +class MetaDict(dict): + """ Dictionary that can dump itself on disk in a human-readable and human-editable way. + Usually describes cube meta info such as name, coordinates (if known) and other useful data. + """ + def __repr__(self): + lines = '\n'.join(f' "{key}" : {repr(value)},' + for key, value in self.items()) + return f'{{\n{lines}\n}}' + + @classmethod + def load(cls, path): + """ Load self from `path` by evaluating the containing dictionary. """ + with open(path, 'r', encoding='utf-8') as file: + content = '\n'.join(file.readlines()) + return cls(literal_eval(content.replace('\n', '').replace(' ', ''))) + + def dump(self, path): + """ Save self to `path` with each key on a separate line. """ + with open(path, 'w', encoding='utf-8') as file: + print(repr(self), file=file) + + + @classmethod + def placeholder(cls): + """ Default MetaDict. """ + return cls({ + 'name': 'UNKNOWN', + 'ru_name': 'Неизвестно', + 'latitude': None, + 'longitude': None, + 'info': 'дополнительная информация о кубе' + }) diff --git a/seismiqb/utils/decorators.py b/seismiqb/utils/decorators.py new file mode 100644 index 0000000..7f4d273 --- /dev/null +++ b/seismiqb/utils/decorators.py @@ -0,0 +1,122 @@ +""" Collection of decorators. """ +from functools import wraps + +import cv2 +import numpy as np + +from . import to_list + +class TransformsMixin: + """ Methods to transform given array. """ + @staticmethod + def matrix_fill_to_num(matrix, value): + """ Change the matrix values at points where field is absent to a supplied one. """ + matrix[np.isnan(matrix)] = value + return matrix + + @staticmethod + def matrix_normalize(matrix, mode, subset_values=None): + """ Normalize matrix values. + + Parameters + ---------- + mode : bool, str, optional + If `min-max` or True, then use min-max scaling. + If `mean-std`, then use mean-std scaling. + If False, don't scale matrix. + """ + values = subset_values or matrix[~np.isnan(matrix)] + + if mode in ['min-max', True]: + min_, max_ = np.nanmin(values), np.nanmax(values) + matrix = (matrix - min_) / (max_ - min_) + elif mode == 'mean-std': + mean, std = np.nanmean(values), np.nanstd(values) + matrix = (matrix - mean) / std + else: + raise ValueError(f'Unknown normalization mode `{mode}`.') + return matrix + + @staticmethod + def matrix_dilate(matrix, dilation_iterations=3): + """ Dilate matrix to increase area of non-zero objects. + + Parameters + ---------- + dilation_iterations : int + Number of dilation iterations with (3, 3) kernel. Corresponds to added size for each boundary point. + """ + dtype = matrix.dtype + kernel = np.ones((3, 3), dtype=np.uint8) + dilated = cv2.dilate(matrix.astype(np.float32), kernel, iterations=dilation_iterations) + return dilated.astype(dtype) + + +def transformable(method): + """ Transform the output matrix of a function to optionally: + - put the matrix on a background with spatial shape of a cube + - change values at absent points to a desired value + - set dtype of a matrix + - normalize values + - reduce dimensionality via PCA transform + - view data as atleast 3d array. + By default, does nothing. + + Parameters + ---------- + on_full : bool + Whether to put the matrix on full cube spatial-shaped background. + fill_value : number, optional + If provided, then used at points where the horizon is absent. + dtype : numpy dtype, optional + If provided, then dtype of a matrix is changed, and fill_value at absent points is changed accordingly. + normalize : bool, str, optional + If `min-max` or True, then use min-max scaling. + If `mean-std`, then use mean-std scaling. + If False, don't scale matrix. + n_components : number, optional + If integer, then number of components to keep after PCA transformation. + If float in (0, 1) range, then amount of variance to be explained after PCA transformation. + atleast_3d : bool + Whether to return the view of a resulting array as at least 3-dimensional entity. + """ + @wraps(method) + def wrapper(instance, *args, dtype=None, on_full=False, channels=None, normalize=False, fill_value=None, + dilation_iterations=0, enlarge=False, enlarge_width=10, + atleast_3d=False, n_components=None, **kwargs): + result = method(instance, *args, **kwargs) + + if dtype and result.dtype != dtype and hasattr(instance, 'matrix_set_dtype'): + result = instance.matrix_set_dtype(result, dtype=dtype) + + if on_full and hasattr(instance, 'matrix_put_on_full'): + result = instance.matrix_put_on_full(result) + + if channels is not None: + if channels == 'middle': + channels = result.shape[2] // 2 + channels = to_list(channels) + result = result[:, :, channels] + + if normalize and hasattr(instance, 'matrix_normalize'): + result = instance.matrix_normalize(result, normalize) + + if fill_value is not None and hasattr(instance, 'matrix_fill_to_num'): + result = instance.matrix_fill_to_num(result, value=fill_value) + + if (dilation_iterations > 0) and hasattr(instance, 'matrix_dilate'): + result = instance.matrix_dilate(result, dilation_iterations=dilation_iterations) + + if enlarge and hasattr(instance, 'matrix_enlarge'): + result = instance.matrix_enlarge(result, width=enlarge_width) + + if atleast_3d: + result = np.atleast_3d(result) + + if n_components is not None and hasattr(instance, 'pca_transform'): + if result.ndim != 3: + raise ValueError(f'PCA transformation can be applied only to 3D arrays, got `{result.ndim}`') + result = instance.pca_transform(result, n_components=n_components) + + return result + return wrapper diff --git a/seismiqb/utils/dtype_conversion.py b/seismiqb/utils/dtype_conversion.py new file mode 100644 index 0000000..c989d61 --- /dev/null +++ b/seismiqb/utils/dtype_conversion.py @@ -0,0 +1,24 @@ +""" Utils for dtype conversion. """ + +from functools import partial +import numpy as np + +def proba_to_int(x, dtype='int8'): + """ Convert float probability values in interval [0, 1] to integer values of defined type. """ + min_ = np.iinfo(dtype).min + ptp = np.iinfo(dtype).max - min_ + return (x * ptp + min_).astype(dtype) + +def int_to_proba(x): + """ Convert integer values to float probability values in interval [0, 1]. """ + min_ = np.iinfo(x.dtype).min + ptp = np.iinfo(x.dtype).max - min_ + return (x.astype('float32') - min_) / ptp + +proba_to_int8 = partial(proba_to_int, dtype='int8') +proba_to_int16 = partial(proba_to_int, dtype='int16') +proba_to_int32 = partial(proba_to_int, dtype='int32') + +proba_to_uint8 = partial(proba_to_int, dtype='uint8') +proba_to_uint16 = partial(proba_to_int, dtype='uint16') +proba_to_uint32 = partial(proba_to_int, dtype='uint32') diff --git a/seismiqb/utils/format_conversion.py b/seismiqb/utils/format_conversion.py new file mode 100644 index 0000000..51f4cdf --- /dev/null +++ b/seismiqb/utils/format_conversion.py @@ -0,0 +1,36 @@ +""" Utils for format conversion. """ + +import os +import h5py +import hdf5plugin + +from batchflow import Notifier + +def repack_hdf5(path, dst_path=None, projections = (0, ), transform=None, dtype='float32', pbar='t', inplace=False, + **dataset_kwargs): + """ Recreate hdf5-file with transformation and type conversion. """ + dataset_kwargs = dataset_kwargs or dict(hdf5plugin.Blosc(cname='lz4hc', clevel=6, shuffle=0)) + transform = transform or (lambda array: array) + + with h5py.File(path, mode='r') as src_file: + from ..geometry.conversion_mixin import ConversionMixin #pylint: disable=import-outside-toplevel + + total = sum(src_file[ConversionMixin.PROJECTION_NAMES[axis]].shape[0] for axis in projections) + dst_path = dst_path or os.path.splitext(path)[0] + '_tmp.hdf5' + with h5py.File(dst_path, mode='w-') as dst_file: + with Notifier(pbar, total=total) as progress_bar: + for axis in projections: + projection_name = ConversionMixin.PROJECTION_NAMES[axis] + data = src_file[projection_name] + projection_shape = data.shape + + dataset_kwargs_ = {'chunks': (1, *projection_shape[1:]), **dataset_kwargs} + projection = dst_file.create_dataset(projection_name, shape=projection_shape, dtype=dtype, + **dataset_kwargs_) + + for i in range(data.shape[0]): + projection[i] = transform(data[i]) + progress_bar.update() + if inplace: + os.remove(path) + os.rename(dst_path, path) diff --git a/seismiqb/utils/functions.py b/seismiqb/utils/functions.py new file mode 100644 index 0000000..9f6b135 --- /dev/null +++ b/seismiqb/utils/functions.py @@ -0,0 +1,286 @@ +""" Utility functions. """ +import os +import string +import random + +import numpy as np +from numba import njit, prange + + + +def file_print(*msg, path, mode='w', **kwargs): + """ Print to file. """ + with open(path, mode, encoding='utf-8') as file: + print(*msg, file=file, **kwargs) + +def select_printer(printer): + """ Select printing method. """ + if isinstance(printer, str): + return lambda *msg, **kwargs: file_print(*msg, path=printer, **kwargs) + if callable(printer): + return printer + return print + + +def generate_string(size=10, chars=string.ascii_uppercase + string.digits): + """ Generate random string of given size. """ + return ''.join(random.choice(chars) for _ in range(size)) + + +@njit(parallel=True) +def filtering_function(points, filtering_matrix): + """ Remove points where `filtering_matrix` is 1. """ + #pylint: disable=consider-using-enumerate, not-an-iterable + mask = np.ones(len(points), dtype=np.int32) + + for i in prange(len(points)): + il, xl = points[i, 0], points[i, 1] + if filtering_matrix[il, xl] == 1: + mask[i] = 0 + return points[mask == 1, :] + + +@njit +def filter_simplices(simplices, points, matrix, threshold=5.): + """ Remove simplices outside of matrix. """ + #pylint: disable=consider-using-enumerate + mask = np.ones(len(simplices), dtype=np.int32) + + for i in range(len(simplices)): + tri = points[simplices[i]].astype(np.int32) + + middle_i, middle_x = np.mean(tri[:, 0]), np.mean(tri[:, 1]) + depths = np.array([matrix[tri[0, 0], tri[0, 1]], + matrix[tri[1, 0], tri[1, 1]], + matrix[tri[2, 0], tri[2, 1]]]) + + if matrix[int(middle_i), int(middle_x)] < 0 or np.std(depths) > threshold: + mask[i] = 0 + + return simplices[mask == 1] + + +def make_bezier_figure(n=7, radius=0.2, sharpness=0.05, scale=1.0, shape=(1, 1), + resolution=None, distance=.5, seed=None): + """ Bezier closed curve coordinates. + Creates Bezier closed curve which passes through random points. + Code based on: https://stackoverflow.com/questions/50731785/create-random-shape-contour-using-matplotlib + + Parameters + ---------- + n : int + Number more than 1 to control amount of angles (key points) in the random figure. + Must be more than 1. + radius : float + Number between 0 and 1 to control the distance of middle points in Bezier algorithm. + sharpness : float + Degree of sharpness/edgy. If 0 then a curve will be the smoothest. + scale : float + Number between 0 and 1 to control figure scale. Fits to the shape. + shape : sequence int + Shape of figure location area. + resolution : int + Amount of points in one curve between two key points. + distance : float + Number between 0 and 1 to control distance between all key points in a unit square. + seed: int, optional + Seed the random numbers generator. + """ + rng = np.random.default_rng(seed) + resolution = resolution or int(100 * scale * max(shape)) + + # Get key points of figure as random points which are far enough each other + key_points = rng.random((n, 2)) + squared_distance = distance ** 2 + + squared_distances = squared_distance - 1 + while np.any(squared_distances < squared_distance): + shifted_points = key_points - np.mean(key_points, axis=0) + angles = np.arctan2(shifted_points[:, 0], shifted_points[:, 1]) + key_points = key_points[np.argsort(angles)] + + squared_distances = np.sum(np.diff(key_points, axis=0)**2, axis=1) + key_points = rng.random((n, 2)) + + key_points *= scale * np.array(shape, float) + key_points = np.vstack([key_points, key_points[0]]) + + # Calculate figure angles in key points + p = np.arctan(sharpness) / np.pi + .5 + diff_between_points = np.diff(key_points, axis=0) + angles = np.arctan2(diff_between_points[:, 1], diff_between_points[:, 0]) + angles = angles + 2 * np.pi * (angles < 0) + rolled_angles = np.roll(angles, 1) + angles = p * angles + (1 - p) * rolled_angles + np.pi * (np.abs(rolled_angles - angles) > np.pi) + angles = np.append(angles, angles[0]) + + # Create figure part by part: make curves between each pair of points + curve_segments = [] + # Calculate control points for Bezier curve + points_distances = np.sqrt(np.sum(diff_between_points ** 2, axis=1)) + radii = radius * points_distances + middle_control_points_1 = np.transpose(radii * [np.cos(angles[:-1]), + np.sin(angles[:-1])]) + key_points[:-1] + middle_control_points_2 = np.transpose(radii * [np.cos(angles[1:] + np.pi), + np.sin(angles[1:] + np.pi)]) + key_points[1:] + curve_main_points_arr = np.hstack([key_points[:-1], middle_control_points_1, + middle_control_points_2, key_points[1:]]).reshape(n, 4, -1) + + # Get Bernstein polynomial approximation of each curve + binom_coefficients = [1, 3, 3, 1] + for i in range(n): + bezier_param_t = np.linspace(0, 1, num=resolution) + current_segment = np.zeros((resolution, 2)) + for point_num, point in enumerate(curve_main_points_arr[i]): + binom_coefficient = binom_coefficients[point_num] + polynomial_degree = np.power(bezier_param_t, point_num) + polynomial_degree *= np.power(1 - bezier_param_t, 3 - point_num) + bernstein_polynomial = binom_coefficient * polynomial_degree + current_segment += np.outer(bernstein_polynomial, point) + curve_segments.extend(current_segment) + + curve_segments = np.array(curve_segments) + figure_coordinates = np.unique(np.ceil(curve_segments).astype(int), axis=0) + return figure_coordinates + + +def trinagular_kernel_1d(length, alpha=.1): + """ Kernel-function that changes linearly from a center point to alpha on borders. """ + result = np.zeros(length) + array = np.linspace(alpha, 2, length) + result[:length // 2] = array[:length // 2] + result[length // 2:] = 2 + alpha - array[length // 2:] + return result + +def triangular_weights_function_nd(array, alpha=.1): + """ Weights-function given by a product of 1d triangular kernels. """ + result = 1 + for i, axis_len in enumerate(array.shape): + if axis_len != 1: + multiplier_shape = np.ones_like(array.shape) + multiplier_shape[i] = axis_len + result = result * trinagular_kernel_1d(axis_len, alpha).reshape(multiplier_shape) + return result + + +def to_list(obj): + """ Cast an object to a list. + When default value provided, cast it instead if object value is None. + Almost identical to `list(obj)` for 1-D objects, except for `str` instances, + which won't be split into separate letters but transformed into a list of a single element. + """ + return np.array(obj, dtype=object).ravel().tolist() + +def make_savepath(path, name, extension=''): + """ If given replace asterisk in path with label name and create save dir if it does not already exist. """ + if path.endswith('*'): + path = path.replace('*', f'{name}{extension}') + + dir_path = os.path.dirname(path) + if dir_path: + os.makedirs(dir_path, exist_ok=True) + return path + + +def make_ranges(ranges, shape): + """ Make a `ranges` tuple, valid for indexing 3-dimensional arrays: + - each element is clipped to `(0, shape[i])` range, + - None elements are changed to `(0, shape[i])`, + - None at the first place of tuple-element is changed by 0 + - None at the second place of tuple-element is changed by `shape[i]` + If `ranges` is None, then treated as a tuple of three None's. + + Example + ------- + None -> (0, shape[0]), (0, shape[1]), (0, shape[2]) + None, None, None -> (0, shape[0]), (0, shape[1]), (0, shape[2]) + (-10, shape[0]+2), (0, 100), (0, None) -> (0, shape[0]), (0, 100), (0, shape[2]) + (10, 20), (10, 20), (10, 20) -> (10, 20), (10, 20), (10, 20) + """ + if ranges is None: + ranges = [None, None, None] + ranges = [(0, c) if item is None else item for item, c in zip(ranges, shape)] + ranges = [(item[0] or 0, item[1] or c) for item, c in zip(ranges, shape)] + ranges = [(max(0, item[0]), min(c, item[1])) for item, c in zip(ranges, shape)] + return tuple(ranges) + +def make_slices(slices, shape): + """ Fill Nones in tuple of slices (analogously to `make_ranges`). """ + if slices is None: + ranges = None + else: + ranges = [None if item is None else (item.start, item.stop) for item in slices] + + ranges = make_ranges(ranges, shape) + return tuple(slice(*item) for item in ranges) + +def make_interior_points_mask(points, cube_shape): + """ Create mask for points inside of the cube. """ + mask = np.where((points[:, 0] >= 0) & + (points[:, 1] >= 0) & + (points[:, 2] >= 0) & + (points[:, 0] < cube_shape[0]) & + (points[:, 1] < cube_shape[1]) & + (points[:, 2] < cube_shape[2]))[0] + return mask + + +@njit(parallel=True) +def insert_points_into_mask(mask, points, mask_bbox, width, axis, alpha=1): + """ Add new points into binary mask. + + Parameters + ---------- + mask : numpy.ndarray + Array to insert values which correponds to some region in 3d cube (see `mask_bbox` parameter) + points : numpy.ndarray + Array of shape `(n_points, 3)` with cube coordinates of points to insert. + mask_bbox : numpy.ndarray + Array of shape (3, 2) with postion of the mask in 3d cube + width : int + Dilation of the mask along some axis. + axis : int + Direction of dilation. + """ + #pylint: disable=not-an-iterable, too-many-boolean-expressions + + left_margin = [0, 0, 0] + right_margin = [1, 1, 1] + left_margin[axis] = width // 2 + right_margin[axis] = width - width // 2 + + for i in prange(len(points)): + point = points[i] + if ((point[0] >= mask_bbox[0][0] - left_margin[0]) and + (point[1] >= mask_bbox[1][0] - left_margin[1]) and + (point[2] >= mask_bbox[2][0] - left_margin[2]) and + (point[0] < mask_bbox[0][1] + right_margin[0] - 1) and + (point[1] < mask_bbox[1][1] + right_margin[1] - 1) and + (point[2] < mask_bbox[2][1] + right_margin[2] - 1)): + + point = point - mask_bbox[:, 0] + left_bound = max(0, point[axis] - left_margin[axis]) + right_bound = min(mask.shape[axis], point[axis] + right_margin[axis]) + + if axis == 0: + for pos in range(left_bound, right_bound): + mask[pos, point[1], point[2]] = alpha + elif axis == 1: + for pos in range(left_bound, right_bound): + mask[point[0], pos, point[2]] = alpha + elif axis == 2: + for pos in range(left_bound, right_bound): + mask[point[0], point[1], pos] = alpha + + +def take_along_axis(array, index, axis): + """ A functional equivalent of `np.take` which returns a view. + Unlike `np.take`, should be used only with indices that are ints or slice. + """ + if axis == 0: + slide = array[index, :, :] + elif axis == 1: + slide = array[:, index, :] + elif axis == 2: + slide = array[:, :, index] + return slide diff --git a/seismiqb/utils/groupby.py b/seismiqb/utils/groupby.py new file mode 100644 index 0000000..9edbbe7 --- /dev/null +++ b/seismiqb/utils/groupby.py @@ -0,0 +1,186 @@ +""" Faster version of groupby operations for numpy arrays. """ +import numpy as np +from numba import njit + + + +@njit +def groupby_mean(array): + """ Faster version of mean-groupby of data along the first two columns. + Input array is supposed to have (N, 3) shape. + """ + n = len(array) + + output = np.zeros_like(array) + position = 0 + + prev = array[0, :2] + s, c = array[0, -1], 1 + + for i in range(1, n): + curr = array[i, :2] + + if prev[0] == curr[0] and prev[1] == curr[1]: + s += array[i, -1] + c += 1 + else: + output[position, :2] = prev + output[position, -1] = round(s / c) + position += 1 + + prev = curr + s, c = array[i, -1], 1 + + output[position, :2] = prev + output[position, -1] = s / c + position += 1 + return output[:position] + +@njit +def groupby_min(array): + """ Faster version of min-groupby of data along the first two columns. + Input array is supposed to have (N, 3) shape. + """ + n = len(array) + + output = np.zeros_like(array) + position = 0 + + prev = array[0, :2] + s = array[0, -1] + + for i in range(1, n): + curr = array[i, :2] + + if prev[0] == curr[0] and prev[1] == curr[1]: + s = min(s, array[i, -1]) + else: + output[position, :2] = prev + output[position, -1] = s + position += 1 + + prev = curr + s = array[i, -1] + + output[position, :2] = prev + output[position, -1] = s + position += 1 + return output[:position] + +@njit +def groupby_max(array): + """ Faster version of max-groupby of data along the first two columns. + Input array is supposed to have (N, 3) shape. + """ + n = len(array) + + output = np.zeros_like(array) + position = 0 + + prev = array[0, :2] + s = array[0, -1] + + for i in range(1, n): + curr = array[i, :2] + + if prev[0] == curr[0] and prev[1] == curr[1]: + s = max(s, array[i, -1]) + else: + output[position, :2] = prev + output[position, -1] = s + position += 1 + + prev = curr + s = array[i, -1] + + output[position, :2] = prev + output[position, -1] = s + position += 1 + return output[:position] + +@njit +def groupby_prob(array, probabilities): + """ Faster version of weighted mean groupby of data along the first two columns. + Input array is supposed to have (N, 3) shape. + """ + n = len(array) + + output = np.zeros_like(array) + position = 0 + + prev = array[0, :2] + s, c = array[0, -1] * probabilities[-1], probabilities[-1] + + for i in range(1, n): + curr = array[i, :2] + probability = probabilities[i] + + if prev[0] == curr[0] and prev[1] == curr[1]: + s += array[i, -1] * probability + c += probability + else: + output[position, :2] = prev + output[position, -1] = round(s / c) + position += 1 + + prev = curr + s, c = array[i, -1] * probability, probability + + output[position, :2] = prev + output[position, -1] = round(s / c) + position += 1 + return output[:position] + + +@njit +def groupby_all(array): + """ For each trace, compute the number of points on it, min, max and mean values. + `array` is expected to be of `(N, 3)` shape. Trace is defined by all points with the same first two coordinates. + """ + # iline, crossline, occurency, min_, max_, mean_ + output = np.zeros((len(array), 6), dtype=np.int32) + position = 0 + + # Initialize values + previous = array[0, :2] + min_ = array[0, -1] + max_ = array[0, -1] + s = array[0, -1] + c = 1 + + for i in range(1, len(array)): + current = array[i] + + if previous[1] == current[1] and previous[0] == current[0]: + # Same iline, crossline: update values + depth_ = current[-1] + min_ = min(depth_, min_) + max_ = max(depth_, max_) + s += depth_ + c += 1 + + else: + # New iline, crossline: store stats, re-initialize values + output[position, :2] = previous # iline, crossline + output[position, 2] = c # occurency + output[position, 3] = min_ # min_ + output[position, 4] = max_ # max_ + output[position, 5] = s / c # mean_ + position += 1 + + depth_ = current[-1] + previous = current[:2] + min_ = depth_ + max_ = depth_ + s = depth_ + c = 1 + + # The last point + output[position, :2] = previous # iline, crossline + output[position, 2] = c # occurency + output[position, 3] = min_ # min_ + output[position, 4] = max_ # max_ + output[position, 5] = s / c # mean_ + position += 1 + + return output[:position] diff --git a/seismiqb/utils/storage.py b/seismiqb/utils/storage.py new file mode 100644 index 0000000..837d94c --- /dev/null +++ b/seismiqb/utils/storage.py @@ -0,0 +1,245 @@ +""" Dict-like disk storage, based on HDF5 with compression. """ +import os + +import numpy as np +import pandas as pd + +import h5py +import hdf5plugin + + + +class SQBStorage: + """ Dict-like disk storage, based on HDF5 with compression. + Unlike native HDF5, works with sequences, dataframes and np.arrays with dtype object. + + Under the hood, we don't store an open file descriptor and re-open the file in read/write mode at each operation. + """ + def __init__(self, path, cname='lz4hc', clevel=6, shuffle=0): + self.path = path + self.loaded_items = [] + + self.dataset_parameters = hdf5plugin.Blosc(cname=cname, clevel=clevel, shuffle=shuffle) + + # Scan all available keys and store them in the instance for faster check + self.keys = set() + if self.exists: + with h5py.File(self.path, mode='r', swmr=True) as src: + for key in src: + self.keys.add(key) + + @property + def exists(self): + """ True, if the storage exists on disk and it is HDF5 file. """ + return os.path.exists(self.path) and h5py.is_hdf5(self.path) + + @staticmethod + def is_storage(path): + """ True if `path` exists on disk and it is HDF5 file. """ + return os.path.exists(path) and h5py.is_hdf5(path) + + def file_handler(self, mode='r', swmr=True): + """ A convenient file handler for using in with-statements. """ + return h5py.File(self.path, mode=mode, swmr=swmr) + + + # Store + def store(self, items, overwrite=True): + """ Store items from dict-like iterator. + + Parameters + ---------- + items : dict or iterable + Dictionary or iterable with key-value pairs. + overwrite : bool + Whether to overwrite keys in a storage. + """ + iterator = items.items() if isinstance(items, dict) else items + for key, value in iterator: + self.store_item(key=key, value=value, overwrite=overwrite) + update = store + + def store_item(self, key, value, overwrite=True): + """ Save one `value` as `key`. + Unlike native `h5py`, works with sequences, dataframes and arrays with `object` dtype. + """ + key = (key + '/').replace('//', '/') + + with h5py.File(self.path, mode='a') as dst: + if overwrite and key in dst: + del dst[key] + + # Sequence: store length and type separately, then dump each item to its own group + if isinstance(value, (tuple, list)) or (isinstance(value, np.ndarray) and value.dtype == object): + dst[key + 'is_sequence'] = 1 + dst[key + 'length'] = len(value) + + types = {tuple: 0, list: 1, np.ndarray: 2} + type_ = types[type(value)] + dst[key + 'type'] = type_ + + for i, v in enumerate(value): + self.store_item(key=key+str(i), value=v) + + # Dictionary: store keys / values separately + # TODO: current implementation works only with numeric keys and values + elif isinstance(value, dict): + dst[key + 'is_dict'] = 1 + + key_, value_ = next(iter(value.items())) + dst[key + 'keys'] = np.fromiter(value.keys(), dtype=np.array(key_).dtype) + dst[key + 'values'] = np.fromiter(value.values(), dtype=np.array(value_).dtype) + + # Dataframe: store column/index names and values separately + # TODO: would not work correctly with arbitrary index. Can be improved by dumping index values directly + elif isinstance(value, pd.DataFrame): + dst[key + 'is_dataframe'] = 1 + dst.attrs[key + 'columns'] = list(value.columns) + + index_names = list(value.index.names) + if index_names[0]: + dst.attrs[key + 'index_names'] = index_names + values_ = value.reset_index().values + else: + values_ = value.values + self.store_item(key=key+'values', value=values_) + + # String: use ASCII encoding with removed zero bytes + elif isinstance(value, str): + dst[key+'is_str'] = 1 + dst[key+'encoded'] = value.encode('ascii').replace(b'\x00', b' ') + + # None: store as flag + elif value is None: + dst[key+'is_none'] = 1 + + # Numpy array with numerical dtype: compress for efficiency + elif isinstance(value, np.ndarray): + dst.create_dataset(key.strip('/'), data=value, **self.dataset_parameters) + + # Fallback for native types: int, float, etc + else: + dst[key] = value + + self.keys.add(key) + + def __setitem__(self, key, value): + self.store_item(key=key, value=value, overwrite=True) + + + # Read + def read(self, keys): + """ Read keys from a storage. """ + result = {} + for key in keys: + result[key] = self.read_item(key) + return result + + def read_item(self, key): + """ Read one `key` from storage. + Unlike native `h5py`, works with sequences, dataframes and arrays with `object` dtype. + """ + key = (key + '/').replace('//', '/') + + with h5py.File(self.path, mode='r', swmr=True) as src: + # Sequence: read each element, reconstruct into original type + if key + 'is_sequence' in src: + length = src[key + 'length'][()] + type_ = src[key + 'type'][()] + + value = [self.read_item(key=key + str(i)) for i in range(length)] + + types = {0: tuple, 1: list, 2: np.array} + value = types[type_](value) + + # Dictionary: read keys/values separately, zip + elif key + 'is_dict' in src: + keys = src[key + 'keys'][()] + values = src[key + 'values'][()] + + value = dict(zip(keys, values)) + + # Dataframe: read columns and index separately, impose on values + elif key + 'is_dataframe' in src: + values = src[key + 'values'][()] + columns = src.attrs[key + 'columns'] + + value = pd.DataFrame(data=values, columns=columns) + + if key + 'index_names' in src: + index_names = src.attrs[key + 'index_names'] + value.set_index(index_names, inplace=True) + + # String: decode back from ASCII + elif key + 'is_str' in src: + value = src[key+'encoded'][()].decode('ascii') + + # None + elif key + 'is_none' in src: + value = None + + # Fallback for Numpy arrays and native types + elif key in src: + value = src[key][()] + + else: + raise KeyError(f'Key `{key}` is not in storage!') + + self.loaded_items.append(key) + return value + + def __getitem__(self, key): + return self.read_item(key=key) + + def get(self, key, default=None): + """ Get item, if present in storage, or return `default` otherwise. """ + return self.read_item(key) if self.has_item(key) else default + + # Check for item(s) + def has_items(self, keys): + """ Check if all of `keys` are present. """ + if self.exists is False: + return False + for key in keys: + if self.has_item(key) is False: + return False + return True + + def has_item(self, key): + """ Check if `key` is in storage. """ + if self.exists is False: + return False + return key in self.keys + + def __contains__(self, key): + return self.has_item(key=key) + + # Reset + def reset(self, keys): + """ Delete `keys` from storage. """ + with h5py.File(self.path, mode='a') as dst: + for key in keys: + if key in dst: + del dst[key] + + def remove(self): + """ Remove storage file entirely. """ + os.remove(self.path) + + + # Introspection + def print_tree(self): + """ Print textual representation of storage. """ + if self.exists: + with h5py.File(self.path, mode='r', swmr=True) as src: + src.visititems(self._print_tree) + + def _print_tree(self, name, node): + """ Print one storage node. """ + if isinstance(node, h5py.Dataset): + shift = name.count('/') * ' ' * 4 + item_name = name.split('/')[-1] + shape_ = f'shape={node.shape}' if node.shape != tuple() else 'scalar' + print(f'{shift}{item_name}: {shape_}, dtype={node.dtype}') + if isinstance(node, h5py.Group): + print(name) diff --git a/setup.py b/setup.py new file mode 100644 index 0000000..0500f55 --- /dev/null +++ b/setup.py @@ -0,0 +1,102 @@ +""" seismiQB is a framework for deep learning research on 3d-cubes of seismic data. """ + +from setuptools import setup, find_packages +import re + +with open('__init__.py', 'r') as f: + version = re.search(r'^__version__\s*=\s*[\'"]([^\'"]*)[\'"]', f.read(), re.MULTILINE).group(1) + + +extras = [ + 'psutil>=5.6.7', + 'bottleneck>=1.3', + 'numexpr>=2.7', +] + +extras_nn = [ + 'torch>=1.7.0', + 'torchvision>=0.1.3', + 'cupy>=8.1.0', +] + +extras_cupy = [ + 'cupy>=8.1.0', +] + +extras_vis = [ + 'plotly>=4.3.0', + 'ipython>=7.10.0', + 'ipywidgets>=7.0', +] + +extras_test = [ + 'py-nbtools[nbrun]>=0.9.8', + 'ipywidgets>=7.0', + 'plotly>=4.3.0', + 'pytest>=5.3.1', +] + + +setup( + name='seismiQB', + packages=find_packages(exclude=['tutorials']), + version=version, + url='https://github.com/GeoscienceML/seismiqb', + license='Apache 2.0', + author='GeoscienceML team', + author_email='rhudor@gmail.com', + description='An ML framework for research on volumetric seismic data', + long_description='', + zip_safe=False, + platforms='any', + install_requires=[ + # General Python libraries + 'dill>=0.3.1.1', + 'tqdm>=4.50.0', + + # Numerical + 'numpy>=1.16.0', + 'numba>=0.43.0', + 'scipy>=1.3.3', + 'scikit-learn>=0.21.3', + 'scikit_image>=0.16.2', + 'connected-components-3d>=3.10.2', + + # Data manipulation + 'pandas>=1.0.0', + 'segyio>=1.8.3', + 'lasio>=0.29', + 'h5py>=2.10.0', + 'h5pickle>=0.2.0', + 'hdf5plugin>=3.3.0', + 'blosc>=1.11', + + # Working with images + 'opencv_python>=4.1.2.30', + 'matplotlib>=3.0.2', + + # Our libraries + 'batchflow>=0.8.0', + ], + extras_require={ + 'extra': extras, + 'nn': extras_nn, + 'cupy': extras_cupy, + 'test': extras_test, + 'vis': extras_vis, + 'dev': extras + extras_nn + extras_test + extras_vis, + }, + classifiers=[ + 'Development Status :: 4 - Beta', + 'Intended Audience :: Developers', + 'Intended Audience :: Science/Research', + 'License :: OSI Approved :: Apache Software License', + 'Operating System :: OS Independent', + 'Programming Language :: Python', + 'Programming Language :: Python :: 3', + 'Programming Language :: Python :: 3.8', + 'Programming Language :: Python :: 3.9', + 'Programming Language :: Python :: 3.10', + 'Topic :: Scientific/Engineering', + ], +) diff --git a/tests/README.md b/tests/README.md new file mode 100644 index 0000000..445f29b --- /dev/null +++ b/tests/README.md @@ -0,0 +1,141 @@ +# A short instruction for adding new test notebooks + +## Notebook preparation + +Before adding a new test notebook to the list of automatically executed tests, make the following **preparations**: + +1. If the test notebook saves any files, it is highly recommended to use relative paths and create a test's **own directory** for saving files. + +The `TESTS_ROOT_DIR` (`'seismiqb\tests\test_root_dir_*'`) is a directory from which all relative paths start. `TESTS_ROOT_DIR` is shared between all test notebooks and creating separate test directories inside it prevents from mixing up files from different tests. + +2. All **externally parameterized variables** must be initialized with default values in the first or second notebook cells. All of the actual testing must be done after the cell number 2. + +This is because the `run_notebook_test.py` inserts a new cell with parameters initialization between cells number 2 and 3. + +So, the recommended notebook structure is: +* **Cell #1**: necessary imports. +* **Cell #2**: parameters initialization. +* **Cells #3+**: tests and additional code. + +## Adding a new notebook to the list of automatically executed tests + +Once the notebook is prepared, it can be added to the list of automatically executed notebooks. + +In order to do that provide a `(notebook_path, params_dict)` tuple into the `notebooks_params` variable inside the `run_notebook_test.py`. + +The `params_dict` is a dictionary with optional `'inputs'` and `'outputs'` keys: +* If the test notebook must be executed with **new parameters values**, just add them in the `'inputs'` in the dictionary format `{'parameter_name': 'parameter_value'}`. +* If it is important to **print into the terminal** some variables values from the executed notebook (such as log messages or timings), add them in the `'outputs'` in the list format `['notebook_variable_name_1', 'notebook_variable_name_2']`. + +```python +notebooks_params = ( + ('path/to/the/test_notebook.ipynb', {}), + ('path/to/the/test_notebook.ipynb', {'inputs': {'FORMAT': 'sgy'}}), + ('path/to/the/test_notebook.ipynb', {'outputs': ['message', 'timings']}), + ('path/to/the/test_notebook.ipynb', {'inputs': {'FORMAT': 'sgy'}, 'outputs': ['message']}) +) +``` + +That's all, now you know how to add new tests! + +# Additional information + +## Good practices for test notebooks + +Some recommended optional practices for creating good test notebooks are recorded in the `seismiqb/tests/template_test.ipynb`. + +## More about the `TESTS_ROOT_DIR` + +`TESTS_ROOT_DIR` is a directory for saving files for **all running tests**. A new `TESTS_ROOT_DIR` is created for each tests run. +If tests executed locally (**not** on the GitHub), then it is a directory in the format: `'seismiqb/tests/tests_root_dir_*'`. + +* If all tests are executed without any failures and `REMOVE_ROOT_DIR` is True, the `TESTS_ROOT_DIR` is removed after all tests execution. +* If there are any failures in tests and/or `REMOVE_ROOT_DIR` is False, the `TESTS_ROOT_DIR` is not removed after all tests execution. +In this case saved notebooks can be checked to find out the failure reason. + +## More about the `notebooks_params` variable + +The important details are: +* Notebooks are executed in the order they are defined in the `notebooks_params`. +* For the notebook execution with different parameters configurations, all of them must be provided into the `notebooks_params`: + +```python +notebooks_params = ( + ('path/to/the/test_notebook.ipynb', {'inputs': {'FORMAT': 'sgy'}}), + ('path/to/the/test_notebook.ipynb', {'inputs': {'FORMAT': 'blosc'}}), + ('path/to/the/test_notebook.ipynb', {'inputs': {'FORMAT': 'hdf5'}}), +) +``` + +```python +notebooks_params = ( + *[('path/to/the/test_notebook.ipynb', {'inputs': {'FORMAT': data_format}}) for data_format in ['sgy', 'blosc', 'hdf5']], +) +``` + +## More about terminal output message + +The `run_notebook_test.py` provides in the terminal output next information: +* Error traceback and additional error info (if there is any failure in the test notebook). The additional info is: the notebook file name and the failed cell number. +* Notebook's `'outputs'` (if any is provided for the notebook into the `notebooks_params`). +* Test conclusion: whether the notebook with tests failed or not. + +One noticeable moment, the message `Notebook execution failed` is printed in two cases: + +1. There is any **failure** in the notebook. Then there must be an error traceback above this message: + +```python +run_notebook_test.py --------------------------------------------------------------------------- +AssertionError Traceback (most recent call last) +/tmp/ipykernel_38767/262262589.py in +----> 1 assert False, "Test failure for the example" + +AssertionError: Test failure for the example +Notebook execution failed + + +`example_test.ipynb` failed in the cell number 6. +``` + +2. The notebook **wasn't executed**. In this case there are no traceback above this message. The reason for this situation is some internal execution error such as out of memory. + +```python +run_notebook_test.py --------------------------------------------------------------------------- +Notebook execution failed +``` + +## Correspondence between output file names and test configurations + +Output file names processed from the execution count, the executed notebook name and passed inputs into it. +Correspondence between out file name and its test configuration is saved in `seismiqb/tests/tests_root_dir_*/out_files_info.json`. + +Note, this file contains information only about **saved** executed notebooks. If the `REMOVE_EXTRA_FILES` flag is True and notebook is executed without any failure, then it is not saved. + +Example of `out_files_info.json`: + +```json +{ + "02_geometry_test_01_preparation_out_FORMATS_sgy_hdf5.ipynb": { + "filename": "geometry_test_01_preparation.ipynb", + "inputs": { + "FORMATS": [ + "sgy", + "hdf5" + ] + } + }, + "03_geometry_test_02_data_format_out_FORMAT_sgy.ipynb": { + "filename": "geometry_test_02_data_format.ipynb", + "inputs": { + "FORMAT": "sgy" + } + }, + "04_geometry_test_02_data_format_out_FORMAT_hdf5.ipynb": { + "filename": "geometry_test_02_data_format.ipynb", + "inputs": { + "FORMAT": "hdf5" + } +} +``` + +In this example executions number 2,3 and 4 was executed with failures. Other executions did **not** fail and therefore, they weren't saved. diff --git a/tests/notebooks/cache_test.ipynb b/tests/notebooks/cache_test.ipynb new file mode 100644 index 0000000..ba106ef --- /dev/null +++ b/tests/notebooks/cache_test.ipynb @@ -0,0 +1,559 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "tags": [] + }, + "outputs": [], + "source": [ + "# This file contains tests for cached methods\n", + "import sys\n", + "import gc\n", + "import warnings\n", + "warnings.filterwarnings('ignore')\n", + "\n", + "import numpy as np\n", + "\n", + "sys.path.insert(0, '../../../seismiqb')\n", + "sys.path.insert(0, '../../../batchflow')\n", + "\n", + "from seismiqb import Field, Horizon, Geometry\n", + "from seismiqb import GlobalCache" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "tags": [] + }, + "outputs": [], + "source": [ + "# Defaults for run this notebook directly\n", + "# Data paths (note, we use other tests data, no need in data creation)\n", + "GEOMETRY_PATH = './horizon_test_files/test_cube.sgy'\n", + "HORIZON_PATH = './horizon_test_files/test_horizon'" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "tags": [] + }, + "outputs": [], + "source": [ + "def cached_objects_ids():\n", + " \"\"\" Get ids of instances which use cache. \"\"\"\n", + " return [id(x) for x in GlobalCache.instances_with_cache]" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "tags": [] + }, + "outputs": [], + "source": [ + "# Import stage check\n", + "assert len(GlobalCache.cache_references) != 0, 'Cache references weren\\'t saved on import stage!'\n", + "assert len(GlobalCache.instances_with_cache) == 0, 'GlobalCache must be empty!'" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Geometry tests" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "tags": [] + }, + "outputs": [], + "source": [ + "%%time\n", + "# Initialize geometry\n", + "geometry = Geometry.new(GEOMETRY_PATH)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "tags": [] + }, + "outputs": [], + "source": [ + "%%time\n", + "# Initialization check\n", + "# Using cache creates 'cache' attribute, now it doesn't exist, because we doesn't use cache\n", + "assert id(geometry) not in cached_objects_ids(), \"Geometry cache must be disabled by default\"\n", + "assert not hasattr(geometry, 'cache'), 'Geometry cache must not exist'" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "tags": [] + }, + "outputs": [], + "source": [ + "%%time\n", + "# Load some cached data: by default cache is disabled\n", + "_ = geometry.load_slide(geometry.shape[0]//10)\n", + "\n", + "assert id(geometry) not in cached_objects_ids(), \"Geometry cache must be disabled by default\"\n", + "assert not hasattr(geometry, 'cache'), 'Geometry cache must not exist'" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "tags": [] + }, + "outputs": [], + "source": [ + "%%time\n", + "# Enable cache and load some cached data\n", + "geometry.enable_cache()\n", + "\n", + "_ = geometry.load_slide(geometry.shape[0]//10)\n", + "\n", + "assert id(geometry) in cached_objects_ids(), 'Geometry object must have cached data'\n", + "assert geometry.cache_size > 0, 'Geometry object must have cached data'" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "tags": [] + }, + "outputs": [], + "source": [ + "%%time\n", + "# Load more slides: they must be saved in cache while maxsize is not reached\n", + "maxsize = GlobalCache.cache_references['Geometry.load_slide_cached'].maxsize\n", + "\n", + "for i in range(maxsize + 1):\n", + " _ = geometry.load_slide_cached(i)\n", + "\n", + "assert geometry.cache_size == GlobalCache.size == maxsize, \"Invalid cached objects amount\"\n", + "\n", + "FIFO_error = \"The first added element wasn\\'t replaced: the FIFO logic broken\"\n", + "assert geometry.get_cache_repr()['Geometry.load_slide_cached']['arguments'][0]['index'] > 0, FIFO_error" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "tags": [] + }, + "outputs": [], + "source": [ + "%%time\n", + "# Clear cache\n", + "GlobalCache.reset()\n", + "\n", + "assert len(geometry.cache) == geometry.cache_size == GlobalCache.size == 0, 'Cache wasn\\'t properly cleared'" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "tags": [] + }, + "outputs": [], + "source": [ + "%%time\n", + "# Remove geometry object and check reference on it in the GlobalCache\n", + "geometry_id = id(geometry)\n", + "\n", + "assert geometry_id in cached_objects_ids(), 'Geometry object must be saved in the GlobalCache'\n", + "\n", + "del geometry\n", + "gc.collect()\n", + "\n", + "assert geometry_id not in cached_objects_ids(), 'Broken reference on unexisted object in the GlobalCache'" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "tags": [] + }, + "outputs": [], + "source": [ + "# Check that GlobalCcahe was cleared after geometry tests\n", + "assert len(GlobalCache.instances_with_cache) == 0, 'GlobalCache wasn\\'t cleared'" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Horizon tests" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Data loading" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "tags": [] + }, + "outputs": [], + "source": [ + "%%time\n", + "field = Field(geometry=GEOMETRY_PATH)\n", + "horizon = Horizon(storage=HORIZON_PATH, field=field)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "tags": [] + }, + "outputs": [], + "source": [ + "%%time\n", + "# Initialization check\n", + "# Using cache creates 'cache' attribute, now it doesn't exist, because we doesn't use cache\n", + "assert id(horizon) not in cached_objects_ids(), \"Horizon cache must be disabled by default\"\n", + "assert not hasattr(horizon, 'cache'), 'Horizon cache must not exist'" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Cache manipulations checks" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "tags": [] + }, + "outputs": [], + "source": [ + "%%time\n", + "# Cached property check\n", + "_ = horizon.binary_matrix\n", + "\n", + "horizon_cache_size = np.sum([len(x) for x in horizon.cache.values()])\n", + "\n", + "assert horizon_cache_size == horizon.cache_size == 1, 'Invalid cache length for the object with one cached property'\n", + "\n", + "assert len(GlobalCache.instances_with_cache) == 1, 'There is must be one reference on instance in the Global cache'\n", + "\n", + "assert id(list(GlobalCache.instances_with_cache)[0]) == id(horizon), 'GlobalCache has invalid instance reference'" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "tags": [] + }, + "outputs": [], + "source": [ + "%%time\n", + "# Check reset cache for object\n", + "horizon.reset_cache()\n", + "\n", + "assert len(horizon.cache) == horizon.cache_size == GlobalCache.size == 0, 'Cache wasn\\'t cleared'" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "tags": [] + }, + "outputs": [], + "source": [ + "%%time\n", + "# Cached object check\n", + "_ = horizon.get_fourier_decomposition()\n", + "\n", + "assert horizon.cache_size == GlobalCache.size > 0, 'Invalid cache length'" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "tags": [] + }, + "outputs": [], + "source": [ + "%%time\n", + "# Check global reset cache\n", + "GlobalCache.reset()\n", + "\n", + "assert len(horizon.cache) == horizon.cache_size == GlobalCache.size == 0, 'Cache wasn\\'t cleared'" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "execution": { + "iopub.execute_input": "2022-10-21T15:57:38.101160Z", + "iopub.status.busy": "2022-10-21T15:57:38.100627Z", + "iopub.status.idle": "2022-10-21T15:57:38.103736Z", + "shell.execute_reply": "2022-10-21T15:57:38.103306Z", + "shell.execute_reply.started": "2022-10-21T15:57:38.101122Z" + } + }, + "source": [ + "## Remove instances" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "%%time\n", + "# Check cache removal after object deletion\n", + "horizon_id = id(horizon)\n", + "\n", + "assert horizon_id in cached_objects_ids(), 'Object haven\\'t cache'\n", + "\n", + "del horizon\n", + "gc.collect()\n", + "\n", + "assert horizon_id not in cached_objects_ids(), 'Broken reference in the GlobalCache'" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Multiple cached instances check" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "%%time\n", + "horizon_1 = Horizon(storage=HORIZON_PATH, field=field)\n", + "horizon_2 = Horizon(storage=HORIZON_PATH, field=field)\n", + "\n", + "_ = horizon_1.binary_matrix\n", + "_ = horizon_2.get_fourier_decomposition()\n", + "\n", + "assert len(GlobalCache.instances_with_cache) == 2, 'Broken references in the GlobalCache'\n", + "assert horizon_1.cache_size + horizon_2.cache_size == GlobalCache.size > 0, 'Invalid cache length'" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# Check cache representation call\n", + "_ = display(horizon_1.cache_repr), display(horizon_2.cache_repr), display(GlobalCache.repr)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "tags": [] + }, + "outputs": [], + "source": [ + "%%time\n", + "# Clear one object cache\n", + "horizon_1.reset_cache()\n", + "\n", + "assert len(horizon_1.cache) == 0, 'Cache wasn\\'t cleared'\n", + "assert horizon_2.cache_size == GlobalCache.size > 0, 'Invalid cache length'\n", + "\n", + "# Return cache to the previous state for next tests\n", + "_ = horizon_1.binary_matrix" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "tags": [] + }, + "outputs": [], + "source": [ + "%%time\n", + "# Clear global cache\n", + "GlobalCache.reset()\n", + "\n", + "assert horizon_1.cache_size == horizon_2.cache_size == GlobalCache.size == 0, 'Cache wasn\\'t cleared'\n", + "\n", + "# Return cache to the previous state for next tests\n", + "_ = horizon_1.binary_matrix\n", + "_ = horizon_2.get_fourier_decomposition()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "tags": [] + }, + "outputs": [], + "source": [ + "%%time\n", + "# Check cache removal after object deletion\n", + "horizon_id_to_remove = id(horizon_1)\n", + "\n", + "assert horizon_id_to_remove in cached_objects_ids(), 'Object hasn\\'t cache'\n", + "\n", + "del horizon_1\n", + "gc.collect()\n", + "\n", + "assert horizon_id_to_remove not in cached_objects_ids(), 'Broken reference in the GlobalCache'" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "tags": [] + }, + "outputs": [], + "source": [ + "# Clear cache\n", + "del horizon_2\n", + "gc.collect()\n", + "\n", + "assert len(GlobalCache.instances_with_cache) == 0, 'Cache wasn\\'t properly cleared'" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "execution": { + "iopub.execute_input": "2022-11-11T09:57:27.802732Z", + "iopub.status.busy": "2022-11-11T09:57:27.802271Z", + "iopub.status.idle": "2022-11-11T09:57:27.807968Z", + "shell.execute_reply": "2022-11-11T09:57:27.806958Z", + "shell.execute_reply.started": "2022-11-11T09:57:27.802681Z" + } + }, + "source": [ + "# Field" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "tags": [] + }, + "outputs": [], + "source": [ + "field.load_labels(labels=HORIZON_PATH, labels_class='horizon')\n", + "\n", + "assert len(field.attached_instances) == 1, 'Horizon wasn\\'t loaded'" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "tags": [] + }, + "outputs": [], + "source": [ + "# Load cached data and check field and global cache\n", + "_ = field.attached_instances[0].binary_matrix\n", + "_ = field.geometry.load_slide_cached(field.shape[0]//10)\n", + "\n", + "assert field.cache_nbytes == GlobalCache.nbytes > 0, 'Invalid cache size'" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "tags": [] + }, + "outputs": [], + "source": [ + "# Check cache reset\n", + "field.reset_cache()\n", + "\n", + "assert field.cache_nbytes == GlobalCache.nbytes == 0, 'Cache wasn\\'t cleared'" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3 (ipykernel)", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.8.10" + }, + "widgets": { + "application/vnd.jupyter.widget-state+json": { + "state": { + "4cedc8ae223640208a0acdf8b338aa47": { + "model_module": "@jupyter-widgets/base", + "model_module_version": "1.2.0", + "model_name": "LayoutModel", + "state": {} + }, + "fc0453b4076f4f98bebbe970aa8ac2e5": { + "model_module": "@jupyter-widgets/output", + "model_module_version": "1.0.0", + "model_name": "OutputModel", + "state": { + "layout": "IPY_MODEL_4cedc8ae223640208a0acdf8b338aa47" + } + } + }, + "version_major": 2, + "version_minor": 0 + } + } + }, + "nbformat": 4, + "nbformat_minor": 4 +} diff --git a/tests/notebooks/charisma_test.ipynb b/tests/notebooks/charisma_test.ipynb new file mode 100644 index 0000000..05f7063 --- /dev/null +++ b/tests/notebooks/charisma_test.ipynb @@ -0,0 +1,207 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# This file contains tests for `CharismaMixin`\n", + "import os\n", + "import sys\n", + "import shutil\n", + "import warnings\n", + "warnings.filterwarnings('ignore')\n", + "\n", + "import numpy as np\n", + "\n", + "sys.path.insert(0, '../../../seismiqb')\n", + "\n", + "from seismiqb import Field, array_to_segy" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "tags": [] + }, + "outputs": [], + "source": [ + "# Defaults for run this notebook directly\n", + "# Data creation parameters\n", + "CUBE_SHAPE = (100, 100, 100)\n", + "SEED = 42" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "tags": [] + }, + "source": [ + "# Preparation: workspace and fake data creation" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "**Storage structure:**\n", + "___\n", + "\n", + "\n", + "\n", + "**charisma_test_files** (charisma tests directory with temporary files)\n", + "\n", + " ├── **test_array.npy** (Test cube data, now it is a random noise)\n", + "\n", + " ├── **test_cube.sgy** (Test cube data in the sgy format)\n", + "\n", + " ├── **test_cube.meta** (Meta data of the test cube)\n", + " \n", + " ├── **test_matrix** (Saved test matrix)\n", + "\n", + " └── **test_points** (Saved test points)\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# (Re)create the test directory\n", + "OUTPUT_DIR = './charisma_test_files'\n", + "\n", + "if os.path.exists(OUTPUT_DIR):\n", + " shutil.rmtree(OUTPUT_DIR)\n", + "\n", + "os.makedirs(OUTPUT_DIR)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "%%time\n", + "# Create a fake cube\n", + "CUBE_PATH = os.path.join(OUTPUT_DIR, 'test_cube.sgy')\n", + "\n", + "rng = np.random.default_rng(SEED)\n", + "data_array = rng.normal(0, 1000, CUBE_SHAPE).astype(np.float32)\n", + "\n", + "with open(os.path.join(OUTPUT_DIR, 'test_array.npy'), 'wb') as outfile:\n", + " np.save(outfile, data_array)\n", + "\n", + "array_to_segy(array_like=data_array, path=CUBE_PATH, zip_segy=False, pbar='t')" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "%%time\n", + "# Init a field\n", + "field = Field(geometry=CUBE_PATH)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Tests" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "%%time\n", + "# Test dump_charisma, load_charisma and is_charisma_like (matrix case)\n", + "# Create and dump a random matrix\n", + "matrix = rng.integers(low=0, high=10, size=CUBE_SHAPE[:2])\n", + "\n", + "matrix_path=os.path.join(OUTPUT_DIR, 'test_matrix')\n", + "\n", + "field.dump_charisma(data=matrix, path=matrix_path, format='matrix', name='saved_matrix')\n", + "\n", + "# Check is_charisma_like\n", + "assert field.is_charisma_like(matrix_path), \"Dumping matrix test: the dumped matrix file is not charisma-like.\"\n", + "\n", + "# Open saved data\n", + "opened_matrix = field.load_charisma(path=matrix_path, format='matrix')\n", + "\n", + "assert np.array_equal(matrix, opened_matrix), \"Dumping matrix test: saved and loaded matrices are not the same.\"" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "tags": [] + }, + "outputs": [], + "source": [ + "%%time\n", + "# Test dump_charisma, load_charisma and is_charisma_like (points case)\n", + "# Create random points in the field\n", + "i_lines, x_lines = np.mgrid[0:CUBE_SHAPE[0], 0:CUBE_SHAPE[1]]\n", + "\n", + "points_column_shape = (i_lines.size, 1)\n", + "i_lines, x_lines = i_lines.reshape(points_column_shape), x_lines.reshape(points_column_shape)\n", + "\n", + "depths = rng.integers(low=0, high=10, size=points_column_shape)\n", + "\n", + "points = np.hstack([i_lines, x_lines, depths])\n", + "\n", + "# Save points as charisma\n", + "points_path=os.path.join(OUTPUT_DIR, 'test_points')\n", + "\n", + "field.dump_charisma(data=points, path=points_path, format='points', name='saved_points')\n", + "\n", + "# Check is_charisma_like\n", + "assert field.is_charisma_like(points_path), \"Dumping points test: the dumped points file is not charisma-like.\"\n", + "\n", + "# Open saved data\n", + "opened_points = field.load_charisma(path=points_path, format='points')\n", + "\n", + "assert np.array_equal(points, opened_points), \"Dumping points test: saved and loaded points arrays are not the same.\"" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3 (ipykernel)", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.8.10" + }, + "widgets": { + "application/vnd.jupyter.widget-state+json": { + "state": {}, + "version_major": 2, + "version_minor": 0 + } + } + }, + "nbformat": 4, + "nbformat_minor": 4 +} diff --git a/tests/notebooks/fault_test_01_preparation.ipynb b/tests/notebooks/fault_test_01_preparation.ipynb new file mode 100644 index 0000000..1ea343c --- /dev/null +++ b/tests/notebooks/fault_test_01_preparation.ipynb @@ -0,0 +1,185 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "tags": [] + }, + "outputs": [], + "source": [ + "# This notebook contains preparation for Fault tests\n", + "# It creates and saves a fake cube with a fault\n", + "import os\n", + "import sys\n", + "import shutil\n", + "import warnings\n", + "import numpy as np\n", + "\n", + "warnings.filterwarnings('ignore')\n", + "\n", + "sys.path.insert(0, '../../../seismiqb')\n", + "sys.path.insert(0, '..')\n", + "\n", + "from seismiqb import Fault, Field, array_to_segy\n", + "from utils import generate_synthetic" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "tags": [] + }, + "outputs": [], + "source": [ + "\"\"\" You can manage notebook execution kwargs which relates to cube and fault for the test:\n", + "\n", + "SYNTHETIC_MODE : bool\n", + " Whether to create a synthetic data (cube and fault) or use existed, provided by paths.\n", + "CUBE_PATH : str or None\n", + " Path to an existed seismic cube.\n", + " Notice that it is only used with SYNTHETIC_MODE = False.\n", + "FAULT_PATH : str or None\n", + " Path to an existed seismic fault.\n", + " Notice that it is only used with SYNTHETIC_MODE = False.\n", + "CUBE_SHAPE : sequence of three integers\n", + " Shape of a synthetic cube.\n", + "\"\"\"\n", + "# Synthetic creation parameters\n", + "SYNTHETIC_MODE = True\n", + "CUBE_PATH = None\n", + "FAULT_PATH = None\n", + "CUBE_SHAPE = (500, 500, 200)\n", + "\n", + "# Visualization parameters\n", + "SCALE = 1\n", + "SHOW_FIGURES = True" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Prepare a workspace\n", + "\n", + "Create directories for files and create a fake cube with faults and save cube and one fault.\n", + "\n", + "**Storage structure:**\n", + "___\n", + "\n", + "\n", + "\n", + "**fault_test_files** (fault tests directory with temporary files)\n", + "\n", + " ├── **test_cube.sgy**\n", + "\n", + " ├── **test_cube.meta**\n", + "\n", + " └── **test_fault**\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "tags": [] + }, + "outputs": [], + "source": [ + "OUTPUT_DIR = './fault_test_files'\n", + "\n", + "# (Re)create the test directory\n", + "if os.path.exists(OUTPUT_DIR):\n", + " shutil.rmtree(OUTPUT_DIR)\n", + "\n", + "os.makedirs(OUTPUT_DIR)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Create a fake cube and a fake fault" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "tags": [] + }, + "outputs": [], + "source": [ + "%%time\n", + "if SYNTHETIC_MODE:\n", + " CUBE_PATH = os.path.join(OUTPUT_DIR, 'test_cube.sgy')\n", + " FAULT_PATH = os.path.join(OUTPUT_DIR, 'test_fault')\n", + "\n", + " # Create a cube and a fault\n", + " synt3d, _, fault_sticks = generate_synthetic(shape=CUBE_SHAPE)\n", + "\n", + " # Dump data\n", + " array_to_segy(synt3d, CUBE_PATH, zip_segy=False, delay=300)\n", + "\n", + " # Check cube\n", + " field = Field(CUBE_PATH)\n", + "\n", + " geometry_loading_error = \"Synthetic geometry creation error: saved and loaded data are different\"\n", + " assert np.allclose(field.geometry[:, :, :], synt3d), geometry_loading_error\n", + "\n", + " # Choose one fault and save it\n", + " fault = Fault({'sticks': fault_sticks}, field=field, name='test')\n", + " fault.dump_fault_sticks(FAULT_PATH)\n", + "\n", + " # Check fault\n", + " opened_fault = Fault(FAULT_PATH, field=field)\n", + "\n", + " fault_loading_error = \"Synthetic fault creation error: saved and loaded data are different\"\n", + " assert np.array_equal(\n", + " np.concatenate(fault.sticks),\n", + " np.concatenate(opened_fault.sticks)\n", + " ), fault_loading_error\n", + "\n", + " opened_fault.show(axis=2, centering=True)\n", + " \n", + " opened_fault_without_transform = Fault(FAULT_PATH, field=field, transform=False, verify=False)\n", + "\n", + " assert ((opened_fault_without_transform.nodes - opened_fault.nodes)[:, :2] == [1, 1]).all(), \"Wrong ilines/xlines offset\"" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3 (ipykernel)", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.8.10" + }, + "vscode": { + "interpreter": { + "hash": "31f2aee4e71d21fbe5cf8b01ff0e069b9275f58929596ceb00d14d90e3e16cd6" + } + }, + "widgets": { + "application/vnd.jupyter.widget-state+json": { + "state": {}, + "version_major": 2, + "version_minor": 0 + } + } + }, + "nbformat": 4, + "nbformat_minor": 4 +} diff --git a/tests/notebooks/fault_test_02_base.ipynb b/tests/notebooks/fault_test_02_base.ipynb new file mode 100644 index 0000000..a6708a8 --- /dev/null +++ b/tests/notebooks/fault_test_02_base.ipynb @@ -0,0 +1,340 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "tags": [] + }, + "outputs": [], + "source": [ + "# Tests for base Fault functionality: initialization, dumping, visualizations, etc.\n", + "%load_ext autoreload\n", + "%autoreload 2\n", + "\n", + "import os\n", + "import sys\n", + "import warnings\n", + "import numpy as np\n", + "\n", + "warnings.filterwarnings('ignore')\n", + "\n", + "sys.path.insert(0, '../../../seismiqb')\n", + "\n", + "from seismiqb import Field, Fault" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "tags": [] + }, + "outputs": [], + "source": [ + "def compare_arrays(a, b):\n", + " return all([(item[0] == item[1]).all() for item in zip(a, b)])" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "tags": [] + }, + "outputs": [], + "source": [ + "\"\"\" You can manage cube and fault for the test:\n", + "\n", + "CUBE_PATH : str\n", + " Path to an existed seismic cube.\n", + "FAULT_PATH : str\n", + " Path to an existed seismic fault.\n", + "\"\"\"\n", + "# Tests parameters\n", + "OUTPUT_DIR = './fault_test_files'\n", + "\n", + "CUBE_PATH = os.path.join(OUTPUT_DIR, 'test_cube.sgy')\n", + "FAULT_PATH = os.path.join(OUTPUT_DIR, 'test_fault')\n", + "\n", + "# Visualization parameters\n", + "SCALE = 1\n", + "SHOW_FIGURES = True" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Initialization" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "tags": [] + }, + "outputs": [], + "source": [ + "%%time\n", + "field = Field(CUBE_PATH)\n", + "fault = Fault(FAULT_PATH, field=field)\n", + "\n", + "fault.show()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "tags": [] + }, + "outputs": [], + "source": [ + "%%time\n", + "# from_points init\n", + "new_fault = Fault(storage=fault.points, field=fault.field, name='tester')\n", + "\n", + "assert (fault.points == new_fault.points).all(), f\"`from_points` initialization test failed: original and initialized fault points are unequal\"" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "tags": [] + }, + "outputs": [], + "source": [ + "%%time\n", + "# from_object init\n", + "new_fault = Fault(storage={'sticks': fault.sticks}, field=fault.field, name='tester')\n", + "\n", + "assert (fault.points == new_fault.points).all(), f\"`from_objects` with 'sticks' initialization test failed: original and initialized fault points are unequal\"" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "tags": [] + }, + "outputs": [], + "source": [ + "%%time\n", + "# from_object init\n", + "new_fault = Fault(storage={'sticks': fault.sticks, 'points': fault.points}, field=fault.field, name='tester')\n", + "\n", + "assert (fault.points == new_fault.points).all(), f\"`from_objects` with 'sticks' and 'points' initialization test failed: original and initialized fault points are unequal\"\n", + "assert (fault.sticks == new_fault.sticks), f\"`from_objects` with 'sticks' and 'points' initialization test failed: original and initialized fault sticks are unequal\"" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Storage convertation" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "tags": [] + }, + "outputs": [], + "source": [ + "%%time\n", + "# from_object init\n", + "\n", + "fault_from_points = Fault(storage={'points': fault.points}, field=fault.field)\n", + "\n", + "assert not fault_from_points.has_component('sticks'), f\"Fault created from 'points' has 'sticks'\"\n", + "assert not fault_from_points.has_component('nodes'), f\"Fault created from 'points' has 'nodes'\"\n", + "assert fault_from_points.direction == 0, f\"'direction' is wrong\"\n", + "\n", + "assert len(fault_from_points.sticks) > 0, f\"'sticks' was not created from 'points'\"" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "tags": [] + }, + "outputs": [], + "source": [ + "%%time\n", + "# from_object init\n", + "\n", + "fault_from_sticks = Fault(storage={'sticks': fault.sticks}, field=fault.field)\n", + "\n", + "assert not fault_from_sticks.has_component('nodes'), f\"Fault created from 'sticks' has 'nodes'\"\n", + "assert not fault_from_sticks.has_component('points'), f\"Fault created from 'sticks' has 'points'\"\n", + "assert fault_from_sticks.direction == 0, f\"'direction' is wrong\"\n", + "\n", + "assert len(fault_from_sticks.nodes) > 0, f\"'nodes' was not created from 'sticks'\"" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "tags": [] + }, + "outputs": [], + "source": [ + "%%time\n", + "# from_object init\n", + "\n", + "fault_from_nodes = Fault(storage={'nodes': fault.nodes, 'simplices': fault.simplices}, field=fault.field)\n", + "\n", + "assert not fault_from_nodes.has_component('points'), f\"Fault created from 'nodes'/'simplices' has 'points'\"\n", + "assert not fault_from_nodes.has_component('sticks'), f\"Fault created from 'nodes'/'simplices' has 'sticks'\"\n", + "\n", + "assert len(fault_from_nodes.points) > 0, f\"'points' was not created from 'nodes' and 'simplices'\"\n", + "assert fault_from_nodes.direction == 0, f\"'direction' is not defined\"" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Dump" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "tags": [] + }, + "outputs": [], + "source": [ + "dump_path_npz = os.path.join(OUTPUT_DIR, 'tmp_fault.npz')" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "tags": [] + }, + "outputs": [], + "source": [ + "%%time\n", + "# dump npz\n", + "fault.dump_npz(path=dump_path_npz)\n", + "\n", + "dumped_fault = Fault(storage=dump_path_npz, field=field)\n", + "\n", + "assert (fault.points == dumped_fault.points).all(), f\"`dump_npz` test failed: original and dumped 'points' are unequal\"\n", + "assert compare_arrays(fault.sticks, dumped_fault.sticks), f\"`dump_npz` test failed: original and dumped 'sticks' are unequal\"\n", + "assert (fault.nodes == dumped_fault.nodes).all(), f\"`dump_npz` test failed: original and dumped 'nodes' are unequal\"\n", + "assert (fault.simplices == dumped_fault.simplices).all(), f\"`dump_npz` test failed: original and dumped 'simplices' are unequal\"\n", + "assert (fault.direction == dumped_fault.direction), f\"`dump_npz` test failed: original and dumped 'direction' are unequal\"\n", + "\n", + "os.remove(dump_path_npz)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "tags": [] + }, + "outputs": [], + "source": [ + "%%time\n", + "# dump fault sticks\n", + "dump_path_sticks = os.path.join(OUTPUT_DIR, 'tmp_fault.char')\n", + "fault.dump_fault_sticks(path=dump_path_sticks)\n", + "\n", + "dumped_fault = Fault(storage=dump_path_sticks, field=field)\n", + "\n", + "assert compare_arrays(fault.sticks, dumped_fault.sticks), f\"`dump_fault_sticks` test failed: original and dumped 'sticks' are unequal\"\n", + "\n", + "os.remove(dump_path_sticks)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Visualizations" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "tags": [] + }, + "outputs": [], + "source": [ + "savepath = os.path.join(OUTPUT_DIR, 'tmp_fault_3d.html') \n", + "\n", + "fault.show_3d(sticks=False, show=SHOW_FIGURES, savepath=savepath)\n", + "\n", + "os.remove(savepath)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "tags": [] + }, + "outputs": [], + "source": [ + "fault.show_3d(sticks=True, show=SHOW_FIGURES, savepath=savepath)\n", + "\n", + "os.remove(savepath)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "tags": [] + }, + "outputs": [], + "source": [ + "savepath = os.path.join(OUTPUT_DIR, 'tmp_fault_2d.png') \n", + "\n", + "fault.show(show=SHOW_FIGURES, savepath=savepath)\n", + "\n", + "os.remove(savepath)" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3 (ipykernel)", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.8.10" + }, + "widgets": { + "application/vnd.jupyter.widget-state+json": { + "state": {}, + "version_major": 2, + "version_minor": 0 + } + } + }, + "nbformat": 4, + "nbformat_minor": 4 +} diff --git a/tests/notebooks/fault_test_03_sticks_processing.ipynb b/tests/notebooks/fault_test_03_sticks_processing.ipynb new file mode 100644 index 0000000..2330a16 --- /dev/null +++ b/tests/notebooks/fault_test_03_sticks_processing.ipynb @@ -0,0 +1,263 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "tags": [] + }, + "outputs": [], + "source": [ + "# Tests for base Fault functionality: initialization, dumping, visualizations, etc.\n", + "%load_ext autoreload\n", + "%autoreload 2\n", + "\n", + "import os\n", + "import sys\n", + "import warnings\n", + "import numpy as np\n", + "\n", + "warnings.filterwarnings('ignore')\n", + "\n", + "sys.path.insert(0, '../../../seismiqb')\n", + "\n", + "from seismiqb import Field, Fault" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "tags": [] + }, + "outputs": [], + "source": [ + "\"\"\" You can manage cube and fault for the test:\n", + "\n", + "CUBE_PATH : str\n", + " Path to an existed seismic cube.\n", + "FAULT_PATH : str\n", + " Path to an existed seismic fault.\n", + "\"\"\"\n", + "# Tests parameters\n", + "OUTPUT_DIR = './fault_test_files'\n", + "\n", + "CUBE_PATH = os.path.join(OUTPUT_DIR, 'test_cube.sgy')\n", + "FAULT_PATH = os.path.join(OUTPUT_DIR, 'test_fault')\n", + "\n", + "# Visualization parameters\n", + "SHOW_FIGURES = True" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Initialization" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "tags": [] + }, + "outputs": [], + "source": [ + "%%time\n", + "\n", + "# ilines sticks\n", + "field = Field(CUBE_PATH)\n", + "\n", + "sticks = np.array([\n", + " [[100, 100, 25],\n", + " [100, 130, 175]],\n", + " [[120, 100, 25],\n", + " [120, 130, 175]],\n", + " [[140, 100, 55],\n", + " [140, 130, 200]]\n", + "])\n", + "\n", + "fault = Fault({'sticks': sticks}, field=field, name='tmp')\n", + "\n", + "assert fault.direction == 0, f\"wrong fault direction\"\n", + "assert (fault.sticks == sticks).all(), f\"sticks are not the same\"" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "tags": [] + }, + "outputs": [], + "source": [ + "fault.show_3d(sticks=True, show=SHOW_FIGURES)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "tags": [] + }, + "outputs": [], + "source": [ + "%%time\n", + "# crosslines sticks\n", + "\n", + "sticks_2 = sticks[:, :, [1, 0, 2]]\n", + "\n", + "fault = Fault({'sticks': sticks_2}, field=field, name='tmp')\n", + "\n", + "assert fault.direction == 1, f\"wrong fault direction\"\n", + "assert (fault.sticks == sticks_2).all(), f\"sticks are not the same\"" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "tags": [] + }, + "outputs": [], + "source": [ + "fault.show_3d(sticks=True, show=SHOW_FIGURES)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "tags": [] + }, + "outputs": [], + "source": [ + "%%time\n", + "# mixed sticks\n", + "\n", + "sticks = np.array([\n", + " [[100, 100, 25],\n", + " [100, 100, 175]],\n", + " [[200, 100, 25],\n", + " [220, 130, 175]],\n", + " [[200, 200, 55],\n", + " [200, 200, 200]]\n", + "])\n", + "\n", + "fault = Fault({'sticks': sticks}, field=field, name='tmp')\n", + "\n", + "fault.show_3d(sticks=True, show=SHOW_FIGURES)\n", + "\n", + "assert (fault.sticks == sticks).all(), f\"sticks are not the same\"" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "tags": [] + }, + "outputs": [], + "source": [ + "%%time\n", + "# mixed sticks\n", + "\n", + "sticks = [\n", + " [[100, 100, 25],\n", + " [100, 100, 175],\n", + " [100, 200, 175]\n", + " ],\n", + " [[200, 100, 25],\n", + " [220, 130, 175]],\n", + " [[200, 200, 55],\n", + " [200, 200, 200]]\n", + "]\n", + "\n", + "sticks = [np.array(item) for item in sticks]\n", + "\n", + "fault = Fault({'sticks': sticks}, field=field, name='tmp')\n", + "\n", + "fault.show_3d(sticks=False, show=SHOW_FIGURES)\n", + "\n", + "assert (fault.sticks == sticks), f\"sticks are not the same\"" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "tags": [] + }, + "outputs": [], + "source": [ + "# sticks on bounds\n", + "\n", + "sticks = np.array([\n", + " [[0, 100, 25],\n", + " [0, 100, 175]\n", + " ],\n", + " [[100, 0, 25],\n", + " [100, 0, 175]\n", + " ],\n", + " [[field.shape[0]-1, 100, 25],\n", + " [field.shape[0]-1, 100, 175]\n", + " ],\n", + " [[100, field.shape[1]-1, 25],\n", + " [100, field.shape[1]-1, 175]\n", + " ], \n", + "])" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "tags": [] + }, + "outputs": [], + "source": [ + "fault = Fault({'sticks': sticks}, field=field, name='tmp')" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "tags": [] + }, + "outputs": [], + "source": [ + "fault.show_3d(show=SHOW_FIGURES)" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3 (ipykernel)", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.8.16" + }, + "widgets": { + "application/vnd.jupyter.widget-state+json": { + "state": {}, + "version_major": 2, + "version_minor": 0 + } + } + }, + "nbformat": 4, + "nbformat_minor": 4 +} diff --git a/tests/notebooks/fault_test_04_mask_creation.ipynb b/tests/notebooks/fault_test_04_mask_creation.ipynb new file mode 100644 index 0000000..a5f00df --- /dev/null +++ b/tests/notebooks/fault_test_04_mask_creation.ipynb @@ -0,0 +1,227 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "tags": [] + }, + "outputs": [], + "source": [ + "# Tests for base Fault functionality: initialization, dumping, visualizations, etc.\n", + "%load_ext autoreload\n", + "%autoreload 2\n", + "\n", + "import os\n", + "import sys\n", + "import warnings\n", + "import numpy as np\n", + "\n", + "warnings.filterwarnings('ignore')\n", + "\n", + "sys.path.insert(0, '../../../seismiqb')\n", + "\n", + "from batchflow import C, Pipeline\n", + "from seismiqb import Field, Fault, SeismicDataset, SeismicSampler, plot" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "tags": [] + }, + "outputs": [], + "source": [ + "\"\"\" You can manage cube and fault for the test:\n", + "\n", + "CUBE_PATH : str\n", + " Path to an existed seismic cube.\n", + "FAULT_PATH : str\n", + " Path to an existed seismic fault.\n", + "\"\"\"\n", + "# Tests parameters\n", + "OUTPUT_DIR = './fault_test_files'\n", + "\n", + "CUBE_PATH = os.path.join(OUTPUT_DIR, 'test_cube.sgy')\n", + "FAULT_PATH = os.path.join(OUTPUT_DIR, 'test_fault')\n", + "\n", + "# Visualization parameters\n", + "SHOW_FIGURES = True\n", + "\n", + "np.random.seed(42)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Initialization" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "tags": [] + }, + "outputs": [], + "source": [ + "%%time\n", + "\n", + "# ilines sticks\n", + "field = Field(CUBE_PATH)\n", + "\n", + "sticks1 = np.array([\n", + " [[100, 100, 25],\n", + " [100, 130, 175]],\n", + " [[120, 100, 25],\n", + " [120, 130, 175]],\n", + " [[140, 100, 25],\n", + " [140, 130, 175]]\n", + "])\n", + "\n", + "sticks2 = sticks1 + 30" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "tags": [] + }, + "outputs": [], + "source": [ + "dataset = SeismicDataset({field: [{'sticks': sticks1}]}, labels_class=Fault)\n", + "\n", + "ppl = (dataset.p\n", + " .make_locations(batch_size=16, generator=C('sampler'))\n", + " .load_cubes(dst='images')\n", + " .create_masks(dst='masks', width=C('width', default=3), sparse=C('sparse', default=False))\n", + ")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Check width" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "tags": [] + }, + "outputs": [], + "source": [ + "sampler = SeismicSampler(labels=dataset.labels, crop_shape=(1, 64, 64), mode='fault', threshold=0, extend=False)\n", + "\n", + "for width in range(1, 10, 2):\n", + " ppl.set_config({'width': width, 'sampler': sampler})\n", + " batch = ppl.next_batch()\n", + " assert (batch.masks.sum(axis=2) <= width+1).all(), f\"mask is wider then {width}\"" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Check 3D crops" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "tags": [] + }, + "outputs": [], + "source": [ + "dataset = SeismicDataset({field: [{'sticks': s} for s in [sticks1, sticks2]]}, labels_class=Fault)\n", + "sampler = SeismicSampler(labels=dataset.labels, crop_shape=(64, 64, 64), mode='fault', threshold=0)\n", + "width = 2\n", + "\n", + "ppl.set_dataset(dataset)\n", + "ppl.set_config({'sampler': sampler, 'width': width})\n", + "batch = ppl.next_batch()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "tags": [] + }, + "outputs": [], + "source": [ + "plot(batch.masks[0, ..., 20], show=SHOW_FIGURES, colorbar=True)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "tags": [] + }, + "outputs": [], + "source": [ + "ppl.set_config({'sampler': sampler, 'width': width, 'sparse': True})\n", + "batch = ppl.next_batch()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "tags": [] + }, + "outputs": [], + "source": [ + "plot(batch.masks[0, ..., 20], show=SHOW_FIGURES)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "tags": [] + }, + "outputs": [], + "source": [ + "for i in range(len(batch)):\n", + " loc = np.where(batch.masks[i][:, 0, 0] != -1)[0] + batch.locations[i][0].start\n", + " assert np.isin(loc, np.concatenate([sticks1[:, 0, 0], sticks2[:, 0, 0]])).all(), \"There are unlabeled slides with points\"" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3 (ipykernel)", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.8.10" + }, + "widgets": { + "application/vnd.jupyter.widget-state+json": { + "state": {}, + "version_major": 2, + "version_minor": 0 + } + } + }, + "nbformat": 4, + "nbformat_minor": 4 +} diff --git a/tests/notebooks/geometry_test_01_preparation.ipynb b/tests/notebooks/geometry_test_01_preparation.ipynb new file mode 100644 index 0000000..91f27e6 --- /dev/null +++ b/tests/notebooks/geometry_test_01_preparation.ipynb @@ -0,0 +1,269 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "tags": [] + }, + "outputs": [], + "source": [ + "# This notebook consists of actions for preparation for `SeismicGeometry` tests\n", + "# It creates a fake cube as random noise and convert it into available data formats\n", + "import os\n", + "import sys\n", + "import shutil\n", + "import warnings\n", + "warnings.filterwarnings('ignore')\n", + "\n", + "import numpy as np\n", + "\n", + "sys.path.insert(0, '../../../seismiqb')\n", + "\n", + "from seismiqb import Geometry, array_to_segy" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# Data creation parameters\n", + "CUBE_SHAPE = (1000, 200, 400)\n", + "SEED = 42\n", + "\n", + "# Data formats for which running tests\n", + "FORMATS = ['sgy', 'qsgy', 'hdf5', 'qhdf5']" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Prepare a workspace\n", + "\n", + "Create directories for files and create a fake cube and save it.\n", + "\n", + "**Storage structure:**\n", + "___\n", + "\n", + "\n", + "**geometry_test_files** (geometry tests directory with temporary files)\n", + "\n", + " ├── **test_array.npy**\n", + "\n", + " └── **test_cube.{DATAFORMAT}**\n", + "\n", + "---\n", + " * **{DATAFORMAT}** means each data format from **FORMATS** list" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "OUTPUT_DIR = './geometry_test_files'\n", + "\n", + "# (Re)create the test directory\n", + "if os.path.exists(OUTPUT_DIR):\n", + " shutil.rmtree(OUTPUT_DIR)\n", + "\n", + "os.makedirs(OUTPUT_DIR)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Create a fake cube" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "CUBE_PATH = os.path.join(OUTPUT_DIR, 'test_cube.sgy')\n", + "\n", + "rng = np.random.default_rng(SEED)\n", + "data_array = rng.normal(0, 1000, CUBE_SHAPE).astype(np.float32)\n", + "\n", + "with open(os.path.join(OUTPUT_DIR, 'test_array.npy'), 'wb') as outfile:\n", + " np.save(outfile, data_array)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "tags": [] + }, + "outputs": [], + "source": [ + "%%time\n", + "array_to_segy(array_like=data_array, path=CUBE_PATH, zip_segy=False, pbar='t')" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "%%time\n", + "geometry_sgy = Geometry.new(path=CUBE_PATH, collect_stats=True, pbar='t')\n", + "\n", + "loading_error = \"Saved and loaded sgy geometry files are different\"\n", + "assert np.allclose(data_array, geometry_sgy[:, :, :]), loading_error" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Check data loading" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "tags": [] + }, + "outputs": [], + "source": [ + "%%time\n", + "geometry_sgy = Geometry.new(path=CUBE_PATH)\n", + "\n", + "assert np.allclose(data_array, geometry_sgy[:, :, :]), loading_error" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Conversion" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "tags": [] + }, + "outputs": [], + "source": [ + "for data_format in FORMATS:\n", + " if data_format != 'sgy':\n", + " _ = geometry_sgy.convert(format=data_format, quantize=False, store_meta=False, pbar='t')" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Create new sgy from array with spec from the existed sgy" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "tags": [] + }, + "outputs": [], + "source": [ + "NEW_CUBE_PATH = os.path.join(OUTPUT_DIR, 'test_new_cube.sgy')\n", + "\n", + "array = np.random.normal(size=geometry_sgy.shape)\n", + "array_to_segy(array, NEW_CUBE_PATH, spec=CUBE_PATH, zip_segy=False)\n", + "new_geometry_sgy = Geometry.new(NEW_CUBE_PATH, collect_stats=True)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "tags": [] + }, + "outputs": [], + "source": [ + "assert geometry_sgy.equal(new_geometry_sgy), 'Unmatching geometries after export'" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Creation with origin" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "tags": [] + }, + "outputs": [], + "source": [ + "NEW_CUBE_PATH = os.path.join(OUTPUT_DIR, 'test_new_cube2.sgy')\n", + "\n", + "array = np.random.normal(size=(500, 100, 200))\n", + "array_to_segy(array, NEW_CUBE_PATH, spec=CUBE_PATH, origin=(5, 10, 15), zip_segy=False)\n", + "new_geometry_sgy = Geometry.new(NEW_CUBE_PATH, collect_stats=False)\n", + "\n", + "assert geometry_sgy.shifts[0] + 5 == new_geometry_sgy.shifts[0], 'Wrong ilines offset'\n", + "assert geometry_sgy.shifts[1] + 10 == new_geometry_sgy.shifts[1], 'Wrong xlines offset'" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "tags": [] + }, + "outputs": [], + "source": [ + "index_headers = ['INLINE_3D', 'CROSSLINE_3D']\n", + "\n", + "index_ = new_geometry_sgy.headers.set_index(index_headers).index\n", + "df = geometry_sgy.headers.set_index(index_headers).loc[index_][['CDP_X', 'CDP_Y']]\n", + "new_df = new_geometry_sgy.headers.set_index(index_headers)[['CDP_X', 'CDP_Y']]\n", + "\n", + "assert (df == new_df).all().all(), 'Unmatched `headers`!'" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3 (ipykernel)", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.8.10" + }, + "widgets": { + "application/vnd.jupyter.widget-state+json": { + "state": {}, + "version_major": 2, + "version_minor": 0 + } + } + }, + "nbformat": 4, + "nbformat_minor": 4 +} diff --git a/tests/notebooks/geometry_test_02_data_format.ipynb b/tests/notebooks/geometry_test_02_data_format.ipynb new file mode 100644 index 0000000..17307ed --- /dev/null +++ b/tests/notebooks/geometry_test_02_data_format.ipynb @@ -0,0 +1,272 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# This notebook contains tests for the `SeismicGeometry` in specific data format\n", + "# Data format is specified with the `FORMAT` parameter in the cell number 2\n", + "# Note that `FORMAT` must be one of available `SeismicGeometry` data formats\n", + "import os\n", + "import sys\n", + "import warnings\n", + "warnings.filterwarnings('ignore')\n", + "\n", + "import numpy as np\n", + "\n", + "sys.path.insert(0, '../../../seismiqb')\n", + "\n", + "from seismiqb import Geometry" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "tags": [] + }, + "outputs": [], + "source": [ + "\"\"\" You should pay attention to the following parameters:\n", + "\n", + "FORMAT : str\n", + " `SeismicGeometry` file format. Possible options are: 'sgy', 'hdf5', 'qhdf5', 'blosc', 'qblosc'.\n", + "CUBE_PATH : str\n", + " Path to an existed seismic cube.\n", + "DATA_PATH : str\n", + " Path to an original data array.\n", + " It is a path to a file in 'npy', 'sgy', 'hdf5' or 'qhdf5' data format.\n", + " \n", + "Note, this notebook runs tests only for a specified data format.\n", + "\"\"\"\n", + "# Tests parameters\n", + "FORMAT = 'sgy'\n", + "\n", + "OUTPUT_DIR = './geometry_test_files'\n", + "CUBE_PATH = os.path.join(OUTPUT_DIR, f'test_cube.{FORMAT}')\n", + "DATA_PATH = os.path.join(OUTPUT_DIR, 'test_array.npy')\n", + "\n", + "ATTRIBUTES_NAMES = ['snr', 'std_matrix']\n", + "\n", + "LOAD_N_SLIDE = 10\n", + "LOAD_N_CROP = 5\n", + "\n", + "BENCHMARK_N_SLIDES = 1000\n", + "BENCHMARK_N_CROPS = 300\n", + "\n", + "SEED = 42\n", + "\n", + "# Visualization parameters\n", + "SCALE = 1\n", + "SHOW_FIGURES = True\n", + "\n", + "# Output parameters\n", + "VERBOSE = True" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# Geometry original data (to check data consistency)\n", + "if DATA_PATH.split('.')[-1] == 'npy':\n", + " with open(DATA_PATH, 'rb') as infile:\n", + " data_array = np.load(infile)\n", + "else:\n", + " geometry_data = Geometry.new(DATA_PATH)\n", + " data_array = geometry_data[:, :, :]\n", + "\n", + "rng = np.random.default_rng(SEED)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Tests" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "%%time\n", + "geometry = Geometry.new(CUBE_PATH)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "tags": [] + }, + "outputs": [], + "source": [ + "# Check data\n", + "geometry_data = geometry[:, :, :]\n", + "\n", + "if not geometry.quantized:\n", + " error_msg = \"Check saved and loaded data failed: data is not the same\"\n", + " assert np.array_equal(geometry_data, data_array), error_msg\n", + "else:\n", + " corr = np.corrcoef(geometry_data.ravel(), data_array.ravel())[0, 1]\n", + "\n", + " error_msg = \"Check saved and loaded data failed: data is not correlated\"\n", + " assert corr >= 0.9, error_msg" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# Attributes loading\n", + "\n", + "for attribute_name in ATTRIBUTES_NAMES:\n", + " # `__getattr__` test\n", + " attribute = geometry.__getattr__(key=attribute_name)\n", + "\n", + " error_msg = f\"Attributes loading test failed: can't load the `{attribute_name}` with the `__gettattr__` method\"\n", + " assert attribute is not None, error_msg\n", + "\n", + " # `load_attribute` test\n", + " attribute = geometry.load_attribute(src=attribute_name)\n", + "\n", + " error_msg = f\"Attributes loading test failed: can't load the `{attribute_name}` with the `load_attribute` method\"\n", + " assert attribute is not None, error_msg\n", + "\n", + " if VERBOSE:\n", + " print(f\"Attribute `{attribute_name}` was successfully loaded\")" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "tags": [] + }, + "outputs": [], + "source": [ + "# Slides loading\n", + "for axis in range(2):\n", + " for _ in range(LOAD_N_SLIDE):\n", + " index = rng.integers(geometry.shape[axis])\n", + " data_slice = (*[slice(None) for i in range(axis)], index)\n", + "\n", + " geometry_slide = geometry.load_slide(index=index, axis=axis)\n", + " data_slide = data_array[data_slice]\n", + "\n", + " if not geometry.quantized:\n", + " error_msg = f\"Slide loading test failed: axis={axis}, index={index}.\"\n", + " assert np.array_equal(geometry_slide, data_slide), error_msg\n", + " else:\n", + " corr = np.corrcoef(geometry_slide.ravel(), data_slide.ravel())[0, 1]\n", + "\n", + " error_msg = f\"Slide loading test failed: axis={axis}, index={index}.\"\n", + " assert corr >= 0.9, error_msg" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "tags": [] + }, + "outputs": [], + "source": [ + "# Crops loading\n", + "for _ in range(LOAD_N_CROP):\n", + " point = rng.integers(geometry.shape) // 2\n", + " shape = rng.integers((5, 5, 5), high=(200, 200, 200))\n", + "\n", + " locations = [slice(start_, np.clip(start_ + shape_, 0, max_shape))\n", + " for start_, shape_, max_shape in zip(point, shape, geometry.shape)]\n", + "\n", + " geometry_crop = geometry.load_crop(locations=locations)\n", + " data_crop = data_array[tuple(locations)]\n", + "\n", + " if not geometry.quantized:\n", + " error_msg = f\"Crop loading test failed: locations={locations}.\"\n", + " assert np.array_equal(geometry_crop, data_crop), error_msg\n", + " else:\n", + " corr = np.corrcoef(geometry_crop.ravel(), data_crop.ravel())[0, 1]\n", + "\n", + " error_msg = f\"Crop loading test failed: locations={locations}.\"\n", + " assert corr >= 0.9, error_msg" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "tags": [] + }, + "outputs": [], + "source": [ + "# Visualizations\n", + "axis = rng.integers(3)\n", + "index = rng.integers(geometry.shape[axis])\n", + "\n", + "geometry.show_slide(index=index, axis=axis, scale=SCALE, show=SHOW_FIGURES)\n", + "geometry.show_histogram(hist_log=True, scale=SCALE, show=SHOW_FIGURES)\n", + "\n", + "geometry.show(matrix='mean_matrix', scale=SCALE, show=SHOW_FIGURES)\n", + "geometry.show(matrix='snr', scale=SCALE, show=SHOW_FIGURES)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "tags": [] + }, + "outputs": [], + "source": [ + "# Timings\n", + "timings = geometry.benchmark(n_slides=BENCHMARK_N_SLIDES, n_crops=BENCHMARK_N_CROPS, seed=SEED)\n", + "\n", + "for obj, obj_timings in timings.items():\n", + " for timing_name, timing in obj_timings.items():\n", + " timings[obj][timing_name] = round(timing, 3)\n", + "\n", + "timings = {FORMAT.upper(): timings}\n", + "timings" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3 (ipykernel)", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.8.10" + }, + "widgets": { + "application/vnd.jupyter.widget-state+json": { + "state": {}, + "version_major": 2, + "version_minor": 0 + } + } + }, + "nbformat": 4, + "nbformat_minor": 4 +} diff --git a/tests/notebooks/geometry_test_03_transforms.ipynb b/tests/notebooks/geometry_test_03_transforms.ipynb new file mode 100644 index 0000000..c2e1ecc --- /dev/null +++ b/tests/notebooks/geometry_test_03_transforms.ipynb @@ -0,0 +1,131 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": null, + "id": "7b056c59-c2e7-462f-b1a9-6035f79dc3f5", + "metadata": { + "tags": [] + }, + "outputs": [], + "source": [ + "import sys\n", + "import warnings\n", + "import numpy as np\n", + "\n", + "warnings.filterwarnings('ignore')\n", + "\n", + "sys.path.insert(0, '../../../seismiqb')\n", + "sys.path.insert(0, '../../../batchflow')\n", + "\n", + "from seismiqb import SeismicDataset, SeismicSampler\n", + "from batchflow import B, F" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "ece2e7a0-13cf-4ec7-be5f-f90918cdbbdb", + "metadata": { + "tags": [] + }, + "outputs": [], + "source": [ + "cube_path = 'geometry_test_files/test_cube.sgy'" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "54c14a5c-944a-4e48-92fa-fa86258baafd", + "metadata": { + "tags": [] + }, + "outputs": [], + "source": [ + "ds = SeismicDataset([cube_path])\n", + "sampler = SeismicSampler(ds.fields, crop_shape=(1, 128, 128))\n", + "for item in ds:\n", + " item.make_normalizer()\n", + " item.make_quantizer(clip=False, ranges=0.)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "928ecc7e-9df4-4ab3-8c4b-ddbb92fd0589", + "metadata": { + "tags": [] + }, + "outputs": [], + "source": [ + "for stats_src in ['field', 'images', 'biased_images']:\n", + " bias = np.random.normal(size=16)\n", + " p = (ds.p\n", + " .make_locations(generator=sampler, batch_size=16)\n", + " .load_seismic(dst='images')\n", + " .update(B('biased_images'), B('images') + bias.reshape(-1, 1, 1, 1))\n", + " .normalize(src='biased_images', dst='biased_images_normalized')\n", + " .normalize(src='images', dst='images_normalized', stats=stats_src if stats_src != 'images' else None)\n", + " .denormalize(src='images_normalized', dst='denormalized', stats=stats_src)\n", + " .update(B.diff, F(np.abs)(B.denormalized - B.images))\n", + " )\n", + "\n", + " batch = p.next_batch(1)\n", + " normalized = batch.images_normalized.mean(axis=(1, 2, 3))\n", + " images = batch.images.mean(axis=(1, 2, 3))\n", + " \n", + " if stats_src == 'field':\n", + " stats = (ds[0].normalization_stats['mean'], ds[0].normalization_stats['std'])\n", + " else:\n", + " src = getattr(batch, stats_src)\n", + " stats = (src.mean(axis=(1, 2, 3)), src.std(axis=(1, 2, 3)))\n", + "\n", + " assert batch.diff.max() / np.abs(batch.images).max() < 1e-5, 'images reconstructed incorrectly'\n", + " assert np.abs((images - stats[0]) / stats[1] - normalized).max() < 1e-5, 'images normalized incorrectly'" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "aabd407c-2ba6-4991-ac03-03d476b1b372", + "metadata": { + "tags": [] + }, + "outputs": [], + "source": [ + "p = (ds.p\n", + " .make_locations(generator=sampler, batch_size=16)\n", + " .load_seismic(dst='images')\n", + " .quantize(src='images', dst='images_quantized')\n", + " .dequantize(src='images_quantized', dst='images_recovered')\n", + " .update(B.diff, F(np.abs)(B.images_recovered - B.images))\n", + " )\n", + "batch = p.next_batch(1)\n", + "\n", + "assert batch.diff.max() < ds[0].quantizer.estimated_absolute_error, 'images reconstructed incorrectly'" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3 (ipykernel)", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.8.16" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +} diff --git a/tests/notebooks/horizon_test_01_preparation.ipynb b/tests/notebooks/horizon_test_01_preparation.ipynb new file mode 100644 index 0000000..3a37571 --- /dev/null +++ b/tests/notebooks/horizon_test_01_preparation.ipynb @@ -0,0 +1,177 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# This notebook contains preparation for Horizon tests\n", + "# It creates and saves a fake cube with a horizon\n", + "import os\n", + "import sys\n", + "import shutil\n", + "import warnings\n", + "import numpy as np\n", + "\n", + "warnings.filterwarnings('ignore')\n", + "\n", + "sys.path.insert(0, '../../../seismiqb')\n", + "sys.path.insert(0, '..')\n", + "\n", + "from seismiqb import Horizon, Field, array_to_segy\n", + "from utils import generate_synthetic" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "\"\"\" You can manage notebook execution kwargs which relates to cube and horizon for the test:\n", + "\n", + "SYNTHETIC_MODE : bool\n", + " Whether to create a synthetic data (cube and horizon) or use existed, provided by paths.\n", + "CUBE_PATH : str or None\n", + " Path to an existed seismic cube.\n", + " Notice that it is only used with SYNTHETIC_MODE = False.\n", + "HORIZON_PATH : str or None\n", + " Path to an existed seismic horizon.\n", + " Notice that it is only used with SYNTHETIC_MODE = False.\n", + "CUBE_SHAPE : sequence of three integers\n", + " Shape of a synthetic cube.\n", + "\"\"\"\n", + "# Synthetic creation parameters\n", + "SYNTHETIC_MODE = True\n", + "CUBE_PATH = None\n", + "HORIZON_PATH = None\n", + "CUBE_SHAPE = (500, 500, 200)\n", + "\n", + "# Visualization parameters\n", + "SCALE = 1\n", + "SHOW_FIGURES = True" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Prepare a workspace\n", + "\n", + "Create directories for files and create a fake cube with horizons and save cube and one horizon.\n", + "\n", + "**Storage structure:**\n", + "___\n", + "\n", + "\n", + "\n", + "**horizon_test_files** (horizon tests directory with temporary files)\n", + "\n", + " ├── **test_cube.sgy**\n", + "\n", + " ├── **test_cube.meta**\n", + " \n", + " └── **test_horizon**\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "OUTPUT_DIR = './horizon_test_files'\n", + "\n", + "# (Re)create the test directory\n", + "if os.path.exists(OUTPUT_DIR):\n", + " shutil.rmtree(OUTPUT_DIR)\n", + "\n", + "os.makedirs(OUTPUT_DIR)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Create a fake cube and a fake horizon" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "tags": [] + }, + "outputs": [], + "source": [ + "%%time\n", + "if SYNTHETIC_MODE:\n", + " CUBE_PATH = os.path.join(OUTPUT_DIR, 'test_cube.sgy')\n", + " HORIZON_PATH = os.path.join(OUTPUT_DIR, 'test_horizon')\n", + "\n", + " # Create a cube and a horizon\n", + " synt3d, horizon_matrix, _ = generate_synthetic(shape=CUBE_SHAPE)\n", + "\n", + " # Create zero traces in the cube\n", + " FILL_VALUE = -999999\n", + " points = (slice(0, CUBE_SHAPE[0]//10, None),\n", + " slice(CUBE_SHAPE[0]//10, CUBE_SHAPE[0]//5, None))\n", + "\n", + " synt3d[points] = FILL_VALUE\n", + " horizon_matrix[points[:2]] = FILL_VALUE\n", + "\n", + " # Dump data\n", + " array_to_segy(synt3d, CUBE_PATH, zip_segy=False)\n", + "\n", + " # Check cube\n", + " field = Field(CUBE_PATH)\n", + "\n", + " geometry_loading_error = \"Synthetic geometry creation error: saved and loaded data are different\"\n", + " assert np.allclose(field.geometry[:, :, :], synt3d), geometry_loading_error\n", + "\n", + " # Choose one horizon and save it\n", + " horizon = Horizon(horizon_matrix, field=field, name='test')\n", + " horizon.dump(HORIZON_PATH)\n", + "\n", + " # Check horizon\n", + " opened_horizon = Horizon(HORIZON_PATH, field=field)\n", + "\n", + " horizon_loading_error = \"Synthetic horizon creation error: saved and loaded data are different\"\n", + " assert np.array_equal(horizon.full_matrix, opened_horizon.full_matrix), horizon_loading_error\n", + " assert np.array_equal(horizon.points, opened_horizon.points), horizon_loading_error\n", + "\n", + " opened_horizon.filter()\n", + " opened_horizon.show(show=SHOW_FIGURES, scale=SCALE)" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3 (ipykernel)", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.8.10" + }, + "widgets": { + "application/vnd.jupyter.widget-state+json": { + "state": {}, + "version_major": 2, + "version_minor": 0 + } + } + }, + "nbformat": 4, + "nbformat_minor": 4 +} diff --git a/tests/notebooks/horizon_test_02_base.ipynb b/tests/notebooks/horizon_test_02_base.ipynb new file mode 100644 index 0000000..a686788 --- /dev/null +++ b/tests/notebooks/horizon_test_02_base.ipynb @@ -0,0 +1,408 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# Tests for base Horizon functionality: initialization, dumping, visualizations, etc.\n", + "import os\n", + "import sys\n", + "import warnings\n", + "import numpy as np\n", + "\n", + "warnings.filterwarnings('ignore')\n", + "\n", + "sys.path.insert(0, '../../../seismiqb')\n", + "\n", + "from seismiqb import Field, Horizon" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "\"\"\" You can manage cube and horizon for the test:\n", + "\n", + "CUBE_PATH : str\n", + " Path to an existed seismic cube.\n", + "HORIZON_PATH : str\n", + " Path to an existed seismic horizon.\n", + "\"\"\"\n", + "# Tests parameters\n", + "OUTPUT_DIR = './horizon_test_files'\n", + "\n", + "CUBE_PATH = os.path.join(OUTPUT_DIR, 'test_cube.sgy')\n", + "HORIZON_PATH = os.path.join(OUTPUT_DIR, 'test_horizon')\n", + "\n", + "# Visualization parameters\n", + "SCALE = 1\n", + "SHOW_FIGURES = True" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Initialization" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "%%time\n", + "field = Field(CUBE_PATH)\n", + "horizon = Horizon(HORIZON_PATH, field=field)\n", + "horizon.filter()\n", + "\n", + "horizon.show(show=SHOW_FIGURES, scale=SCALE)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "%%time\n", + "# from_points init\n", + "new_horizon = Horizon(storage=horizon.points, field=horizon.field, name='tester')\n", + "\n", + "assert horizon.equal(new_horizon), f\"`from_points` initialization test failed: original and initialized horizons are unequal\"" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "%%time\n", + "# from_matrix init\n", + "new_horizon = Horizon(storage=horizon.matrix, i_min=horizon.i_min, x_min=horizon.x_min,\n", + " field=horizon.field, name='tester')\n", + "\n", + "assert horizon.equal(new_horizon), f\"`from_matrix` initialization test failed: original and initialized horizons are unequal\"" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "%%time\n", + "# from_full_matrix init\n", + "new_horizon = Horizon(storage=horizon.full_matrix, field=horizon.field, name='tester')\n", + "\n", + "assert horizon.equal(new_horizon), f\"`from_full_matrix` initialization test failed: original and initialized horizons are unequal\"" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "%%time\n", + "# from_dict\n", + "horizon_dict = {}\n", + "for k, v in zip(horizon.points[:, :2], horizon.points[:, 2]):\n", + " horizon_dict[tuple(k)] = v\n", + "\n", + "new_horizon = Horizon(storage=horizon_dict, transform=False, field=horizon.field, name='tester')\n", + "\n", + "assert horizon.equal(new_horizon), f\"`from_dict` initialization test failed: original and initialized horizons are unequal\"" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Dump" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "dump_path = os.path.join(OUTPUT_DIR, 'tmp_horizon')" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "%%time\n", + "# dump\n", + "horizon.dump(path=dump_path)\n", + "\n", + "dumped_horizon = Horizon(storage=dump_path, field=field)\n", + "\n", + "assert horizon.equal(new_horizon), f\"`dump` test failed: original and dumped horizons are unequal\"\n", + "\n", + "os.remove(dump_path)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "%%time\n", + "# dump_float\n", + "max_depth_difference = 2\n", + "horizon.dump_float(path=dump_path, max_depth_difference=max_depth_difference)\n", + "\n", + "dumped_horizon = Horizon(storage=dump_path, field=field)\n", + "\n", + "error_message = \"`dump_float` test failed: original and dumped horizons are not close\"\n", + "assert np.allclose(horizon.points, dumped_horizon.points, atol=max_depth_difference), error_message\n", + "\n", + "os.remove(dump_path)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Base methods" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "%%time\n", + "horizon_points = Horizon.matrix_to_points(matrix=horizon.matrix)\n", + "\n", + "# Shift (it exists in methods that call `matrix_to_points`)\n", + "horizon_points[:, 0] += horizon.i_min\n", + "horizon_points[:, 1] += horizon.x_min\n", + "\n", + "error_message = \"`matrix_to_points` test failed: original and extracted points are not equal\"\n", + "assert np.array_equal(horizon.points, horizon_points), error_message" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "%%time\n", + "horizon_matrix = Horizon.points_to_matrix(points=horizon.points, i_min=horizon.i_min, x_min=horizon.x_min,\n", + " i_length=horizon.i_length, x_length=horizon.x_length)\n", + "\n", + "error_message = \"`points_to_matrix` test failed: original and extracted matrices are not equal\"\n", + "assert np.array_equal(horizon.matrix, horizon_matrix), error_message" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Evaluate" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "%%time\n", + "_ = horizon.evaluate(scale=SCALE, bad_color='black')" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Get values" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "tags": [] + }, + "outputs": [], + "source": [ + "%%time\n", + "for axis in range(2):\n", + " index = horizon.shape[axis] // 2\n", + " _ = horizon.load_slide(index=index, axis=axis)\n", + "\n", + " horizon.show_slide(index=index, axis=axis, width=5, combine='separate',\n", + " cmap=['gray', 'viridis'], grid=False,\n", + " scale=SCALE, show=SHOW_FIGURES)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# get_cube_values" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "tags": [] + }, + "outputs": [], + "source": [ + "%%time\n", + "# Make a flat horizon in the cube\n", + "depth = field.shape[-1] // 2\n", + "window = 2 * (field.shape[-1] // 40) + 1 # must be an odd value\n", + "\n", + "constant_matrix = np.ones_like(horizon.full_matrix) * depth\n", + "\n", + "constant_horizon = Horizon(constant_matrix, i_min=0, x_min=0,\n", + " field=horizon.field, name='const')\n", + "\n", + "# Get values along constant horizon\n", + "horizon_values = constant_horizon.get_cube_values(window=window)\n", + "horizon_values = np.nan_to_num(horizon_values, constant_horizon.FILL_VALUE)\n", + "\n", + "# Get values from the cube\n", + "geometry_values = field.geometry[:, :, depth-window//2:depth+window//2+1]\n", + "\n", + "error_message = \"`get_cube_values` test failed: original and extracted values are not equal\"\n", + "assert np.allclose(horizon_values[constant_horizon.mask],\n", + " geometry_values[constant_horizon.mask]), error_message" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Operations with FILL_VALUE" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "tags": [] + }, + "outputs": [], + "source": [ + "%%time\n", + "# Change fill_value to a new one\n", + "horizon_copy = horizon.copy()\n", + "new_fill_value = -10\n", + "\n", + "# New and old fill_values amount before filling\n", + "n_fill_value = np.sum(horizon_copy.matrix == new_fill_value)\n", + "n_absent = np.sum(horizon_copy.matrix == horizon_copy.FILL_VALUE)\n", + "\n", + "horizon_copy.matrix_fill_to_num(matrix=horizon_copy.matrix, value=new_fill_value)\n", + "\n", + "# New fill_values amount after filling\n", + "n_new_fill_value = np.sum(horizon_copy.matrix == new_fill_value)\n", + "\n", + "error_message = \"`matrix_fill_to_num` test failed: unexpected amount of points with new fill value\"\n", + "assert n_new_fill_value == n_fill_value + n_absent, error_message" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "tags": [] + }, + "outputs": [], + "source": [ + "%%time\n", + "# Reverse filling: new fill_value to old\n", + "horizon_copy.matrix_num_to_fill(matrix=horizon_copy.matrix, value=new_fill_value)\n", + "\n", + "n_restored_fill_value = np.sum(horizon_copy.matrix == horizon_copy.FILL_VALUE)\n", + "\n", + "error_message = \"`matrix_num_to_fill` test failed: unexpected amount of points with restored fill value\"\n", + "assert n_restored_fill_value == n_new_fill_value, error_message" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Matrix normalization" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "tags": [] + }, + "outputs": [], + "source": [ + "%%time\n", + "# Min-max\n", + "horizon_copy = horizon.copy()\n", + "\n", + "normalized_matrix = horizon_copy.matrix_normalize(matrix=horizon_copy.full_matrix, mode='min-max')\n", + "\n", + "error_msg = \"'min-max' matrix normalization test failed: matrix values are not in [0, 1] interval\"\n", + "assert np.isclose(np.nanmin(normalized_matrix[horizon_copy.mask]), 0), error_msg\n", + "assert np.isclose(np.nanmax(normalized_matrix[horizon_copy.mask]), 1), error_msg\n", + "\n", + "# Mean-std\n", + "horizon_copy = horizon.copy()\n", + "\n", + "normalized_matrix = horizon_copy.matrix_normalize(matrix=horizon_copy.full_matrix, mode='mean-std')\n", + "\n", + "error_msg = \"'mean-std' matrix normalization test failed: matrix values are not in [0, 1] interval\"\n", + "assert np.isclose(np.nanmean(normalized_matrix[horizon_copy.mask]), 0), error_msg\n", + "assert np.isclose(np.nanstd(normalized_matrix[horizon_copy.mask]), 1), error_msg" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3 (ipykernel)", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.8.10" + }, + "widgets": { + "application/vnd.jupyter.widget-state+json": { + "state": {}, + "version_major": 2, + "version_minor": 0 + } + } + }, + "nbformat": 4, + "nbformat_minor": 4 +} diff --git a/tests/notebooks/horizon_test_03_attributes.ipynb b/tests/notebooks/horizon_test_03_attributes.ipynb new file mode 100644 index 0000000..a913bf7 --- /dev/null +++ b/tests/notebooks/horizon_test_03_attributes.ipynb @@ -0,0 +1,180 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# Tests Horizon attributes and properties: loading and show\n", + "import os\n", + "import sys\n", + "import warnings\n", + "import numpy as np\n", + "\n", + "warnings.filterwarnings('ignore')\n", + "\n", + "sys.path.insert(0, '../../../seismiqb')\n", + "\n", + "from seismiqb import Field, Horizon" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "\"\"\" You can manage cube and horizon for the test:\n", + "\n", + "CUBE_PATH : str\n", + " Path to an existed seismic cube.\n", + "HORIZON_PATH : str\n", + " Path to an existed seismic horizon.\n", + " \n", + "Also, you can change attributes to check with:\n", + "\n", + "ATTRIBUTES_LIST : list of str\n", + " List of attributes names to use in tests.\n", + "\"\"\"\n", + "# Tests parameters\n", + "OUTPUT_DIR = './horizon_test_files'\n", + "\n", + "CUBE_PATH = os.path.join(OUTPUT_DIR, 'test_cube.sgy')\n", + "HORIZON_PATH = os.path.join(OUTPUT_DIR, 'test_horizon')\n", + "\n", + "ATTRIBUTES_LIST = ['amplitudes', 'depths', 'instant_phases',\n", + " 'instant_amplitudes', 'fourier', 'wavelet', 'mask']\n", + "\n", + "# Visualization parameters\n", + "SCALE = 1\n", + "SHOW_FIGURES = True" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "%%time\n", + "field = Field(CUBE_PATH)\n", + "horizon = Horizon(HORIZON_PATH, field=field)\n", + "horizon.filter()\n", + "\n", + "horizon.show(show=SHOW_FIGURES)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Properties" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "%%time\n", + "_ = horizon.binary_matrix\n", + "_ = horizon.mask\n", + "_ = horizon.borders_matrix\n", + "_ = horizon.boundaries_matrix\n", + "_ = horizon.filled_matrix" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Get attributes" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "tags": [] + }, + "outputs": [], + "source": [ + "%%time\n", + "for side in [-1, 1]:\n", + " _ = horizon.get_zerocrossings(side=side)\n", + " print(f\"`get_zerocrossings` with {side} side was successfully checked.\")" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "%%time\n", + "_ = horizon.get_median_diff_map()\n", + "_ = horizon.get_gradient_map()\n", + "_ = horizon.get_spikes_mask()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Loading attributes" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "%%time\n", + "metrics = horizon.load_attribute('metrics', metric='local_corrs', normalize='min-max')" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "tags": [] + }, + "outputs": [], + "source": [ + "%%time\n", + "horizon.show(ATTRIBUTES_LIST, combine='separate', ncols=2, scale=SCALE, show=SHOW_FIGURES)" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3 (ipykernel)", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.8.10" + }, + "widgets": { + "application/vnd.jupyter.widget-state+json": { + "state": {}, + "version_major": 2, + "version_minor": 0 + } + } + }, + "nbformat": 4, + "nbformat_minor": 4 +} diff --git a/tests/notebooks/horizon_test_04_processing.ipynb b/tests/notebooks/horizon_test_04_processing.ipynb new file mode 100644 index 0000000..a2a931f --- /dev/null +++ b/tests/notebooks/horizon_test_04_processing.ipynb @@ -0,0 +1,434 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "tags": [] + }, + "outputs": [], + "source": [ + "# Tests for methods that process horizon surface (filtering, creating carcass, holes, etc.)\n", + "import os\n", + "import sys\n", + "import warnings\n", + "import numpy as np\n", + "from cv2 import dilate\n", + "\n", + "warnings.filterwarnings('ignore')\n", + "\n", + "sys.path.insert(0, '../../../seismiqb')\n", + "\n", + "from seismiqb import Field, Horizon, plot" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "\"\"\" You can manage cube and horizon for the test:\n", + "\n", + "CUBE_PATH : str\n", + " Path to an existed seismic cube.\n", + "HORIZON_PATH : str\n", + " Path to an existed seismic horizon.\n", + "\"\"\"\n", + "# Tests parameters\n", + "OUTPUT_DIR = './horizon_test_files'\n", + "\n", + "CUBE_PATH = os.path.join(OUTPUT_DIR, 'test_cube.sgy')\n", + "HORIZON_PATH = os.path.join(OUTPUT_DIR, 'test_horizon')\n", + "\n", + "SEED = 42\n", + "\n", + "# Visualization parameters\n", + "SCALE = 1\n", + "SHOW_FIGURES = True" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "%%time\n", + "field = Field(CUBE_PATH)\n", + "horizon = Horizon(HORIZON_PATH, field=field)\n", + "\n", + "horizon.show(show=SHOW_FIGURES)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Filtering" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "%%time\n", + "# from_subset\n", + "# Cut horizon by i_line and check its filtered and non-filtered parts\n", + "# Create filtering matrix\n", + "i_line_cut = horizon.shape[0] // 3\n", + "\n", + "filtering_matrix = np.zeros_like(horizon.full_matrix)\n", + "filtering_matrix[i_line_cut:] = 1\n", + "\n", + "# Horizon filtered by matrix\n", + "filtered_horizon = Horizon(storage=horizon.full_matrix, field=field, name='filtered')\n", + "filtered_horizon = filtered_horizon.from_subset(filtering_matrix)\n", + "\n", + "filtered_horizon.show(show=SHOW_FIGURES)\n", + "\n", + "not_empty_traces_error = \"`from_subset` filtering test failed: filtered traces are not empty\"\n", + "assert np.all(filtered_horizon.full_matrix[:i_line_cut] == filtered_horizon.FILL_VALUE), not_empty_traces_error\n", + "\n", + "empty_traces_error = \"`from_subset` filtering test failed: non-filtered traces was changed by filtering\"\n", + "assert np.array_equal(filtered_horizon.full_matrix[i_line_cut:],\n", + " horizon.full_matrix[i_line_cut:]), empty_traces_error" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "%%time\n", + "# filter\n", + "filtered_horizon = Horizon(horizon.full_matrix, field=field, name='filtered')\n", + "filtered_horizon.filter(inplace=True)\n", + "\n", + "filtered_horizon.show(show=SHOW_FIGURES)\n", + "\n", + "# Check that dead traces filled by FILL_VALUE\n", + "dead_traces = filtered_horizon.full_matrix[field.dead_traces_matrix == 1]\n", + "\n", + "not_empty_traces_error = \"`filter` test failed: filtered traces are not empty\"\n", + "assert np.all(dead_traces == filtered_horizon.FILL_VALUE), not_empty_traces_error\n", + "\n", + "# Check that other traces didn't change\n", + "nonzero_traces = filtered_horizon.full_matrix[field.dead_traces_matrix == 0]\n", + "original_nonzero_traces = horizon.full_matrix[field.dead_traces_matrix == 0]\n", + "\n", + "empty_traces_error = \"`filter` test failed: non-filtered traces were changed by filtering\"\n", + "assert np.array_equal(nonzero_traces, original_nonzero_traces), empty_traces_error" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "%%time\n", + "# filter\n", + "# Cut horizon by i_line and check its filtered and non-filtered parts\n", + "i_line_cut = horizon.shape[0] // 3\n", + "\n", + "filtered_horizon = Horizon(horizon.full_matrix, field=field, name='filtered')\n", + "\n", + "filtering_matrix = np.zeros_like(horizon.full_matrix)\n", + "filtering_matrix[:i_line_cut] = 1\n", + "\n", + "filtered_horizon.filter(filtering_matrix, inplace=True)\n", + "\n", + "filtered_horizon.show(show=SHOW_FIGURES)\n", + "\n", + "not_empty_traces_error = \"`filter` method test failed: filtered traces are not empty\"\n", + "assert np.all(filtered_horizon.full_matrix[:i_line_cut] == filtered_horizon.FILL_VALUE), not_empty_traces_error\n", + "\n", + "empty_traces_error = \"`filter` method test failed: non-filtered traces was changed by filtering\"\n", + "assert np.array_equal(filtered_horizon.full_matrix[i_line_cut:],\n", + " horizon.full_matrix[i_line_cut:]), empty_traces_error" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "tags": [] + }, + "outputs": [], + "source": [ + "%%time\n", + "# Filter spikes with median_diff, gradient and spikes maps\n", + "# Create constant horizon with a spike\n", + "spike_point = (horizon.shape[0] // 2, horizon.shape[1] // 2)\n", + "\n", + "horizon_matrix = np.ones_like(horizon.full_matrix) * horizon.field.shape[-1]//2\n", + "horizon_matrix[spike_point] += 5\n", + "\n", + "horizon_with_spikes = Horizon(horizon_matrix, field=field, name='constant_with_spike')\n", + "horizon_with_spikes.filter(inplace=True)\n", + "\n", + "# Get mask of areas with spike cut\n", + "dilation_iterations = 1\n", + "\n", + "spikes_mask = np.zeros(shape=horizon_with_spikes.full_matrix.shape, dtype=np.float32)\n", + "spikes_mask[spike_point] = 1 \n", + "spikes_mask = dilate(spikes_mask, kernel=np.ones((3, 3), np.uint8), iterations=dilation_iterations)\n", + "\n", + "spikes_mask = spikes_mask > 0\n", + "\n", + "spikes = {\n", + " 'median': horizon_with_spikes.get_median_diff_map,\n", + " 'gradient': horizon_with_spikes.get_gradient_map,\n", + " 'spikes': horizon_with_spikes.get_spikes_mask\n", + "}\n", + "\n", + "# Check despiking\n", + "for mode, get_spikes_method in spikes.items():\n", + " spikes_map = get_spikes_method(dilation_iterations=dilation_iterations)\n", + " spikes_map = spikes_map > 0\n", + " \n", + " despiked_horizon = horizon_with_spikes.filter(spikes_map, inplace=False)\n", + "\n", + " not_empty_traces_error = f\"Despike with mode '{mode}' test failed: filtered traces with spike are not empty\"\n", + " assert np.all(despiked_horizon.full_matrix[spikes_mask] == despiked_horizon.FILL_VALUE), not_empty_traces_error\n", + "\n", + " empty_traces_error = f\"Despike with mode '{mode}' test failed: despike changes traces without spikes\"\n", + " assert np.array_equal(despiked_horizon.full_matrix[~spikes_mask], horizon_with_spikes.full_matrix[~spikes_mask]), empty_traces_error\n", + "\n", + " print(f\"Despiking mode '{mode}' was successfully tested\")" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "%%time\n", + "# filter_disconnected_regions\n", + "# Split horizon in two parts by i_line_cut\n", + "i_line_cut = horizon.shape[0]//3\n", + "filtering_matrix = np.zeros_like(horizon.full_matrix)\n", + "filtering_matrix[i_line_cut, :] = 1\n", + "\n", + "splitted_horizon = Horizon(horizon.full_matrix, field=field, name='splitted')\n", + "splitted_horizon.filter(filtering_matrix, inplace=True)\n", + "\n", + "splitted_horizon.filter_disconnected_regions(inplace=True)\n", + "\n", + "not_empty_traces_error = f\"`filter_disconnected_regions` test failed: disconnected region wasn't filtered\"\n", + "assert np.all(splitted_horizon.full_matrix[:i_line_cut+1]==splitted_horizon.FILL_VALUE), not_empty_traces_error\n", + "\n", + "empty_traces_error = f\"`filter_disconnected_regions` test failed: wrong traces were filtered\"\n", + "assert np.array_equal(splitted_horizon.full_matrix[i_line_cut+1:], horizon.full_matrix[i_line_cut+1:]), empty_traces_error" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Specific manipulations" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "horizon = Horizon(horizon.full_matrix, field=field, name='filtered')\n", + "horizon.filter(inplace=True)\n", + "\n", + "frequency = 100\n", + "\n", + "def calculate_grid_coverage(horizon, frequencies=100, width=1, **kwargs):\n", + " \"\"\" Approximate calculation of coverage of regular grid.\n", + "\n", + " horizon : :class:`Horizon`\n", + " Seismic horizon instance.\n", + " frequencies : int or sequence of two integers\n", + " (iline, xline) grid frequencies.\n", + " If int, then ilines and xlines frequencies are equal.\n", + " width : int or sequence of two integers\n", + " (iline, xline) grid width.\n", + " If int, then ilines and xlines grid widths are equal.\n", + " \"\"\"\n", + " if isinstance(frequencies, int):\n", + " frequencies = (frequencies, frequencies)\n", + "\n", + " i_min = kwargs.get('i_min', horizon.i_min)\n", + " x_min = kwargs.get('x_min', horizon.x_min)\n", + "\n", + " amount_of_ilines = (horizon.i_length - i_min) // frequencies[0]\n", + " amount_of_xlines = (horizon.x_length - x_min) // frequencies[1]\n", + "\n", + " # On borders we have a line with half of grid width\n", + " if (horizon.i_length - i_min) % frequencies[0] > 0:\n", + " amount_of_ilines += 0.5\n", + " else:\n", + " amount_of_ilines -= 0.5\n", + "\n", + " if (horizon.x_length - x_min) % frequencies[1] > 0:\n", + " amount_of_xlines += 0.5\n", + " else:\n", + " amount_of_xlines -= 0.5\n", + "\n", + " # Count amount of traces for grid with width = 1\n", + " intersection_traces = amount_of_ilines * amount_of_xlines\n", + " grid_traces = amount_of_ilines * horizon.x_length + amount_of_xlines * horizon.i_length\n", + "\n", + " # Apply width\n", + " intersection_traces = width * width * intersection_traces\n", + " grid_traces = width * grid_traces\n", + " grid_traces -= intersection_traces\n", + "\n", + " # Calculate approximate amount of traces in grid in horizon area\n", + " coverage = grid_traces / horizon.size\n", + " return coverage" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Carcass" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "%%time\n", + "carcass = horizon.make_carcass(margin=0, frequencies=frequency, regular=True, interpolate=True)\n", + "\n", + "carcass.show(show=SHOW_FIGURES, load_kwargs={'enlarge': True})\n", + "\n", + "approximate_coverage = calculate_grid_coverage(horizon=horizon, frequencies=frequency, width=3, i_min=0, x_min=0)\n", + "\n", + "assert np.isclose(carcass.coverage, approximate_coverage, atol=2e-3), \"`make_carcass` test failed: resulted coverage is not expected\"" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## thin_out" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "%%time\n", + "thined_horizon = Horizon(horizon.full_matrix, field=field, name='thined')\n", + "thined_horizon.thin_out(factor=(frequency, frequency), threshold=np.min(horizon.shape)//10, inplace=True)\n", + "\n", + "thined_horizon.show(show=SHOW_FIGURES, load_kwargs={'enlarge': True})\n", + "\n", + "approximate_coverage = calculate_grid_coverage(horizon=horizon, frequencies=frequency, width=1,\n", + " i_min=horizon.i_min, x_min=horizon.x_min)\n", + "\n", + "assert np.isclose(thined_horizon.coverage, approximate_coverage, atol=2e-3), \"`thin_out` test failed: resulted coverage is not expected\"" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Interpolate" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "%%time\n", + "interpolated_horizon = Horizon(thined_horizon.full_matrix, field=field, name='interpolated')\n", + "interpolated_horizon.interpolate(inplace=True)\n", + "\n", + "interpolated_horizon.show(show=SHOW_FIGURES, load_kwargs={'enlarge': True})\n", + "\n", + "approximate_coverage = calculate_grid_coverage(horizon=horizon, frequencies=frequency, width=3,\n", + " i_min=horizon.i_min, x_min=horizon.x_min)\n", + "\n", + "assert np.isclose(interpolated_horizon.coverage, approximate_coverage, atol=2e-3), \"`interpolate` test failed: resulted coverage is not expected\"\n", + "\n", + "# Existed traces mustn't be changed\n", + "nonbad_traces_mask = thined_horizon.full_matrix != thined_horizon.FILL_VALUE\n", + "nonbad_traces_thined = thined_horizon.full_matrix[nonbad_traces_mask]\n", + "nonbad_traces_interpolated = interpolated_horizon.full_matrix[nonbad_traces_mask]\n", + "\n", + "assert np.array_equal(\n", + " nonbad_traces_thined, nonbad_traces_interpolated, equal_nan=False\n", + "), \"interpolate test failed: surface values were changed\"" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Holes" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "tags": [] + }, + "outputs": [], + "source": [ + "%%time\n", + "filtering_matrix = horizon.generate_holes_matrix(seed=SEED)\n", + "filtering_matrix = horizon.matrix_put_on_full(filtering_matrix)\n", + "\n", + "horizon_with_holes = Horizon(horizon.full_matrix, field=field, name='holed')\n", + "horizon_with_holes.filter(filtering_matrix, inplace=True)\n", + "\n", + "if SHOW_FIGURES:\n", + " plot(filtering_matrix, cmap='viridis', scale=SCALE, title='Holes matrix')\n", + " horizon_with_holes.show(scale=SCALE)\n", + "\n", + "assert (horizon_with_holes.coverage < horizon.coverage), \"`generate_holes_matrix` test failed: no traces was filtered\"" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3 (ipykernel)", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.8.10" + }, + "widgets": { + "application/vnd.jupyter.widget-state+json": { + "state": {}, + "version_major": 2, + "version_minor": 0 + } + } + }, + "nbformat": 4, + "nbformat_minor": 4 +} diff --git a/tests/notebooks/horizon_test_05_extraction.ipynb b/tests/notebooks/horizon_test_05_extraction.ipynb new file mode 100644 index 0000000..4d72886 --- /dev/null +++ b/tests/notebooks/horizon_test_05_extraction.ipynb @@ -0,0 +1,429 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# Tests for methods that merge horizons\n", + "import os\n", + "import sys\n", + "import warnings\n", + "import math\n", + "import numpy as np\n", + "\n", + "warnings.filterwarnings('ignore')\n", + "\n", + "sys.path.insert(0, '../..')\n", + "\n", + "from seismiqb import Field, Horizon, plot" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "tags": [] + }, + "outputs": [], + "source": [ + "\"\"\" You can manage cube and horizon for the test:\n", + "\n", + "CUBE_PATH : str\n", + " Path to an existed seismic cube.\n", + "HORIZON_PATH : str\n", + " Path to an existed seismic horizon.\n", + "\"\"\"\n", + "# Tests parameters\n", + "OUTPUT_DIR = './horizon_test_files'\n", + "\n", + "CUBE_PATH = os.path.join(OUTPUT_DIR, 'test_cube.sgy')\n", + "HORIZON_PATH = os.path.join(OUTPUT_DIR, 'test_horizon')\n", + "\n", + "# Visualization parameters\n", + "SCALE = 1\n", + "SHOW_FIGURES = True\n", + "\n", + "# Output parameters\n", + "VERBOSE = True" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "tags": [] + }, + "outputs": [], + "source": [ + "%%time\n", + "field = Field(CUBE_PATH)\n", + "\n", + "horizon = Horizon(HORIZON_PATH, field=field)\n", + "horizon.filter()\n", + "field.load_labels({'horizons': horizon})\n", + "\n", + "horizon.show(show=SHOW_FIGURES)\n", + "\n", + "message = \"\"" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Merge two horizons" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "configs = [\n", + "# (first horizon border, second horizon border, verify_merge code)\n", + " (len(horizon.points)//2, len(horizon.points)//2-len(horizon.points)//10, 4), # overlapped\n", + " (len(horizon.points)//10, len(horizon.points)//10, 3), # close without overlap\n", + " (len(horizon.points)//10, len(horizon.points)//2, 1), # spatially far\n", + " (len(horizon.points)//10, len(horizon.points)//10-len(horizon.points)//20, 0) # for height-wise far\n", + "]" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "tags": [] + }, + "outputs": [], + "source": [ + "%%time\n", + "# Horizon.*_merge methods\n", + "\n", + "for (border_1, border_2, code) in configs:\n", + " # Create new horizons\n", + " horizon_1 = Horizon(horizon.points[:border_1, :], field=field, name='horizon_1')\n", + " horizon_2 = Horizon(horizon.points[border_2:, :], field=field, name='horizon_2')\n", + "\n", + " if code == 0: # Make horizons height-wise far\n", + " horizon_2.points[:, 2] += 50\n", + "\n", + " # Check merge code\n", + " verified_code = horizon_1.verify_merge(horizon_2, adjacency=1)\n", + " error_message = f\"Merge two horizons with code {code} test failed: verified code {verified_code} wasn't expected\"\n", + " assert verified_code == code, error_message\n", + "\n", + " # Merge and check horizons if they are mergeable\n", + " if code == 4:\n", + " merged_horizon = Horizon.overlap_merge(horizon_1, horizon_2)\n", + "\n", + " assert horizon.equal(merged_horizon), \"Overlapped horizons merge failed: merged horizon unequals to original one\"\n", + "\n", + " elif code == 3:\n", + " merged_horizon = horizon_1.adjacent_merge(horizon_2)\n", + "\n", + " assert horizon.equal(merged_horizon), \"Close horizons merge failed: merged horizon unequals to original one\"\n", + "\n", + " if VERBOSE:\n", + " current_message = f\"The two horizons merge test with merge code {code} successfully passed.\\n\"\n", + " # print(current_message)\n", + " message += current_message" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Merge multiple horizons\n", + "\n", + "We split a horizon in multiple parts, merge them into one horizon and compare it with original one." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# Create new horizon with much more empty traces\n", + "zero_traces = np.tril(horizon.full_matrix).astype(bool)\n", + "horizon.filter(zero_traces)\n", + "horizon.filter_disconnected_regions()\n", + "\n", + "horizon.show(show=SHOW_FIGURES, scale=SCALE)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "tags": [] + }, + "outputs": [], + "source": [ + "def split_and_merge_horizon_test(horizon, crop_shape, overlap, adjacency):\n", + " \"\"\" Split a horizon in crops with overlap and merge them.\n", + "\n", + " Merged horizon compared with the original.\n", + "\n", + " Parameters\n", + " ----------\n", + " horizon : :class:`Horizon`\n", + " Seismic horizon instance.\n", + " crop_shape : sequence of two integers\n", + " Crop shape (ilines, xlines).\n", + " overlap : sequence of two integers\n", + " Crops overlap by (ilines, xlines).\n", + " adjacency : int\n", + " Margin to consider horizons to be spatially close.\n", + " \"\"\"\n", + " current_message = \"\"\n", + " params = f\"crop_shape={crop_shape}; overlap={overlap}; adjacency={adjacency}\"\n", + " borders = []\n", + "\n", + " # Get splitting borders\n", + " for axis in range(2):\n", + " stride = crop_shape[axis] - overlap[axis]\n", + " n_crops = math.ceil(horizon.full_matrix.shape[axis] / stride)\n", + " axis_borders = [(i*stride, i*stride + crop_shape[axis]) for i in range(n_crops)]\n", + "\n", + " borders.append(axis_borders)\n", + "\n", + " horizons = []\n", + "\n", + " # Split a horizon\n", + " for i_border_num, horizon_i_borders in enumerate(borders[0]):\n", + " for x_border_num, horizon_x_borders in enumerate(borders[1]):\n", + " cutted_horizon_matrix = horizon.full_matrix[horizon_i_borders[0]:horizon_i_borders[1],\n", + " horizon_x_borders[0]:horizon_x_borders[1]]\n", + "\n", + " if not np.all(cutted_horizon_matrix == horizon.FILL_VALUE):\n", + " horizon_ = Horizon(cutted_horizon_matrix, format='matrix',\n", + " i_min=horizon_i_borders[0], x_min=horizon_x_borders[0],\n", + " field=field, name=f\"A_horizon_{i_border_num*x_border_num}\")\n", + "\n", + " horizons.append(horizon_)\n", + "\n", + " # Calculate horizons summation for additional checks\n", + " merged_ = np.zeros_like(horizons[0].full_matrix)\n", + "\n", + " for horizon_ in horizons:\n", + " merged_ += (horizon_.full_matrix > 0)\n", + "\n", + " # Horizon merge: inplace\n", + " horizons, _ = Horizon.merge_list(horizons, adjacency=adjacency, mean_threshold=5.)\n", + " merged_horizon = horizons[-1]\n", + "\n", + " # Take a look at horizon parts summation\n", + " if SHOW_FIGURES:\n", + " plot([merged_, merged_horizon.full_matrix], combine='separate',\n", + " scale=SCALE, suptitle_label=params, colorbar=True, fontsize=14)\n", + "\n", + " # Asserts\n", + " error_message = f\"`merge_list` test with params {params} failed\"\n", + " if (overlap[0] >= 0) and (overlap[1] >= 0):\n", + " n_missing = 0\n", + " assert horizon.equal(merged_horizon, threshold_missing=n_missing), error_message\n", + "\n", + " else:\n", + " n_missing = len(horizon) - (merged_ > 0).sum()\n", + " assert horizon.equal(merged_horizon, threshold_missing=n_missing + 1), error_message\n", + "\n", + " if VERBOSE:\n", + " current_message = f\"`merge_list` test with params {params} successfully passed.\\n\"\n", + " # print(current_message)\n", + " \n", + " return current_message" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "scrolled": true, + "tags": [] + }, + "outputs": [], + "source": [ + "overlaps = [(i, j) for i in range(-3, 4) for j in range(-3, 4)]\n", + "\n", + "SHOW_FIGURES = False\n", + "\n", + "crop_shapes = [\n", + " (horizon.full_matrix.shape[0]//20+1, horizon.full_matrix.shape[1]//20+1), # Split horizon into small square crops\n", + " (horizon.full_matrix.shape[0]//10+1, horizon.full_matrix.shape[1]//10+1), # Split horizon into medium square crops\n", + " (horizon.full_matrix.shape[0]//5+1, horizon.full_matrix.shape[1]//5+1), # Split horizon into big square crops\n", + " (horizon.full_matrix.shape[0], horizon.full_matrix.shape[1]//20+1), # Split horizon by i_lines\n", + " (horizon.full_matrix.shape[0]//20+1, horizon.full_matrix.shape[1]) # Split horizon by x_lines\n", + "]\n", + "\n", + "for crop_shape in crop_shapes:\n", + " for overlap in overlaps:\n", + " min_ = min(overlap)\n", + " adjacency = 0 if min_ > 0 else -min_ + 1\n", + " message += split_and_merge_horizon_test(horizon=horizon, crop_shape=crop_shape, overlap=overlap, adjacency=adjacency)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Extract" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "tags": [] + }, + "outputs": [], + "source": [ + "%%time\n", + "valid_traces = field.dead_traces_matrix == 0\n", + "\n", + "mask = np.zeros(field.shape, dtype=np.int32)\n", + "for horizon in field.labels:\n", + " mask[horizon.points[:, 0], horizon.points[:, 1], horizon.points[:, 2]] = 1\n", + "\n", + "origin = np.array([0, 0, 0])" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## No chunks" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "tags": [] + }, + "outputs": [], + "source": [ + "horizons = Horizon.from_mask(mask.copy(), field=field, origin=origin)\n", + "extracted_horizon = horizons[-1]\n", + "\n", + "assert horizon.equal(extracted_horizon), \"`from_mask` test failed: original and extracted horizons are unequal\"" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## With chunks" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "tags": [] + }, + "outputs": [], + "source": [ + "def chunked_extraction_test(mask, true_horizon, valid_traces, origin, step, overlap):\n", + " \"\"\" Split a horizon in chunks using mask and merge them.\n", + "\n", + " Merged horizon compared with the original.\n", + "\n", + " Parameters\n", + " ----------\n", + " mask : np.ndarray\n", + " Horizon presence mask in the cube coordinates. \n", + " true_horizon : :class:`Horizon`\n", + " Seismic horizon instance.\n", + " valid_traces : np.ndarray\n", + " Mask of valid traces in the field.\n", + " origin : sequence of three integers\n", + " The upper left coordinate of a `mask` in the cube coordinates.\n", + " step : int\n", + " Chunk size along i_lines and x_lines.\n", + " overlap : sequence of two integers\n", + " Crops overlap by (ilines, xlines).\n", + " \"\"\"\n", + " current_message = \"\"\n", + " params = f\"step={step}; overlap={overlap}\"\n", + " i_step = x_step = step\n", + " i_stride = x_stride = step - overlap\n", + "\n", + " # Create horizons from subvolumes\n", + " horizons = []\n", + " for i_start in range(0, mask.shape[0], i_stride):\n", + " for x_start in range(0, mask.shape[1], x_stride):\n", + " i_end = min(i_start + i_step, mask.shape[0])\n", + " x_end = min(x_start + x_step, mask.shape[1])\n", + "\n", + " slices = (slice(i_start, i_end), slice(x_start, x_end), slice(None))\n", + "\n", + " if valid_traces[slices[:2]].sum() > 0:\n", + " subvolume = mask[slices].copy()\n", + " subvolume_origin = origin + [slc.start or 0 for slc in slices]\n", + "\n", + " horizons_, _ = Horizon.extract_from_mask(subvolume, field=field, origin=subvolume_origin,\n", + " minsize=0, verbose=False)\n", + " horizons.extend(horizons_)\n", + "\n", + " # Merge horizons from chunks\n", + " horizons, _ = Horizon.merge_list(horizons, mean_threshold=0.5, max_threshold=0.2, adjacency=0)\n", + " extracted_horizon = horizons[-1]\n", + "\n", + " assert true_horizon.equal(extracted_horizon), f\"Extraction with chunks test failed with params: {params}\"\n", + "\n", + " if VERBOSE:\n", + " current_message = f\"The extraction with chunks test with params {params} successfully passed.\\n\"\n", + "\n", + " return current_message" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "scrolled": true, + "tags": [] + }, + "outputs": [], + "source": [ + "for step in [30, 50, 100]:\n", + " for overlap in [5, 10, 15]:\n", + " message += chunked_extraction_test(mask.copy(), true_horizon=horizon,\n", + " valid_traces=valid_traces, origin=origin,\n", + " step=step, overlap=overlap)" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3 (ipykernel)", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.8.10" + }, + "widgets": { + "application/vnd.jupyter.widget-state+json": { + "state": {}, + "version_major": 2, + "version_minor": 0 + } + } + }, + "nbformat": 4, + "nbformat_minor": 4 +} diff --git a/tests/notebooks/template_test.ipynb b/tests/notebooks/template_test.ipynb new file mode 100644 index 0000000..2922f73 --- /dev/null +++ b/tests/notebooks/template_test.ipynb @@ -0,0 +1,192 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# This file contains the template and good practices for creating new test notebooks\n", + "# First recommendation is to write a comment with a short notebook description and important notes on the top of the first cell\n", + "# Under the comment write all necessary imports\n", + "import os\n", + "import sys\n", + "import shutil\n", + "import warnings\n", + "warnings.filterwarnings('ignore')\n", + "\n", + "import numpy as np\n", + "\n", + "sys.path.insert(0, '../../../seismiqb')\n", + "\n", + "from seismiqb import SeismicGeometry\n", + "from seismiqb.geometry import export" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# The second cell contains all changeable parameters\n", + "# Overwritten values are placed between the second and the third cells, so we need to set defaults here\n", + "\"\"\" If there are some important parameters in the notebook, then you should write a docstring with them here. \"\"\"\n", + "# Data creation parameters\n", + "CUBE_SHAPE = (100, 100, 100)\n", + "SEED = 42" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "tags": [] + }, + "source": [ + "# Preparation: workspace and fake data creation" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Usually, tests start with preparation steps: we **create a workspace and fake data** for running tests on it.\n", + "\n", + "It would be good if you add with a **short description of the storage structure**. It is useful in the case when a test operates with a large number of files.\n", + "Also, the description clarifies what is stored in each file." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "**Storage structure:**\n", + "___\n", + "\n", + "\n", + "\n", + "**template_test_files** (TESTS_NAME tests directory with temporary files)\n", + "\n", + " ├── **test_array.npy** (Test cube data, now it is a random noise)\n", + "\n", + " ├── **test_cube.sgy** (Test cube created from the `test_array.npy` data)\n", + "\n", + " └── **test_cube.meta** (`test_cube.sgy` meta file)\n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "If the test saves any data, then it must start by creating its' **own saving directory**: it helps to avoid mixing up files between different tests.\n", + "\n", + "The next cell is placed in every test notebook that works with data dumps.\n", + "\n", + "**Note**, that it is important to **use relative paths**: all directories and files created in tests are saved in a new directory which is created by the `run_notebook_test.py`." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# (Re)create the test directory\n", + "OUTPUT_DIR = './template_test_files'\n", + "\n", + "if os.path.exists(OUTPUT_DIR):\n", + " shutil.rmtree(OUTPUT_DIR)\n", + "\n", + "os.makedirs(OUTPUT_DIR)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "**After that you can do everything you need.**\n", + "\n", + "Some examples and other good practices:" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "%%time\n", + "# Example of fake data creation\n", + "CUBE_PATH = os.path.join(OUTPUT_DIR, 'test_cube.sgy')\n", + "\n", + "rng = np.random.default_rng(SEED)\n", + "data_array = rng.normal(0, 1000, CUBE_SHAPE).astype(np.float32)\n", + "\n", + "with open(os.path.join(OUTPUT_DIR, 'test_array.npy'), 'wb') as outfile:\n", + " np.save(outfile, data_array)\n", + "\n", + "export.make_segy_from_array(array=data_array, path_segy=CUBE_PATH, zip_segy=False,\n", + " sample_rate=2., delay=50, pbar='t')" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Tests" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "The following code is a **simple test** that checks that saved and loaded data are the same." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# Test example\n", + "geometry = SeismicGeometry(path=CUBE_PATH)\n", + "\n", + "error_message = \"Fake data creation test failed: original and loaded data are not the same\"\n", + "assert np.allclose(data_array, geometry[:, :, :]), error_message" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Advice for tests is to **write quite clear and detailed error messages in assertions**. In the error case all of them are printed in the cell output in the notebook and in the terminal output if you run tests from the `run_notebook_test.py` script.\n", + "These messages are helpful in finding out the reason for tests failure.\n", + "\n", + "\n", + "The last advice is to **split huge test notebooks** into separate notebooks for convenient tests usage." + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3 (ipykernel)", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.8.10" + } + }, + "nbformat": 4, + "nbformat_minor": 4 +} diff --git a/tests/run_notebook_test.py b/tests/run_notebook_test.py new file mode 100644 index 0000000..ae5a47b --- /dev/null +++ b/tests/run_notebook_test.py @@ -0,0 +1,230 @@ +""" Script for running tests notebooks with provided parameters. + +Each test execution is controlled by the following constants that are declared in the `common_params` dict: + +REMOVE_EXTRA_FILES : bool + Whether to remove extra files such as executed notebooks without failures. +SHOW_FIGURES : bool + Whether to show additional figures in the executed notebooks. + Showing some figures can be useful for finding out the reason for the tests failure. +VERBOSE : bool + Whether to print in the terminal additional information from tests. + +Other noteworthy variables for tests control are: + +TESTS_ROOT_DIR : str + Path to the directory for saving results and temporary files for all tests + (executed notebooks, logs, data files like cubes, etc.). + Note that the directory will be removed if `REMOVE_ROOT_DIR` is True and no one test failed. +REMOVE_ROOT_DIR : bool + Whether to remove `TESTS_ROOT_DIR` after execution in case of all tests completion without failures. + +Another important script part is the `notebooks_params` variable which manages notebooks execution order, +internal parameter values and outputs variables names for each individual test. +To add a new test case you just need to add a configuration tuple (notebook_path, params_dict) in it, where +the `params_dict` may have optional keys 'inputs' and 'outputs': + - 'inputs' is a dict with test parameters to pass to the test notebook execution, + - 'outputs' contains names of variables to return from the test notebook. + +After all parameters initializations the `test_run_notebook` function is called. +Under the hood, the function parses test arguments, runs test notebooks with given configurations, +catches execution information such as traceback and internal variables values, and provides them to the terminal output. + +Output file names processed from the execution count, the executed notebook name and passed inputs into it. +Correspondence between out file name and its test configuration is saved in +`seismiqb/tests/tests_root_dir_*/out_files_info.json`. +""" +import os +import json +import re +import shutil +import subprocess +import tempfile +import pytest +from nbtools import run_notebook + + +# Base tests variables for entire test process +pytest.failed = False +pytest.out_files_info = {} +BASE_DIR = os.path.normpath(os.getenv('BASE_DIR', os.path.join(os.path.dirname(os.path.realpath(__file__)), '../../seismiqb'))) +TESTS_DIR = os.path.join(BASE_DIR, 'tests') +git_hash = subprocess.check_output(['git', 'rev-parse', '--short', 'HEAD']).decode('ascii').strip() +pytest.TESTS_ROOT_DIR = os.getenv('SEISMIQB_TESTS_ROOT_DIR', None) +REMOVE_ROOT_DIR = bool(int(os.getenv('SEISMIQB_TESTS_REMOVE_ROOT_DIR', '1'))) + +# Parameters for each test notebooks +common_params = { + 'REMOVE_EXTRA_FILES': bool(int(os.getenv('SEISMIQB_TESTS_REMOVE_EXTRA_FILES', '1'))), + 'SHOW_FIGURES': bool(int(os.getenv('SEISMIQB_TESTS_SHOW_FIGURES', '0'))), + 'VERBOSE': bool(int(os.getenv('SEISMIQB_TESTS_VERBOSE', '1'))) +} + +TESTS_NOTEBOOKS_DIR = os.path.join(BASE_DIR, 'tests/notebooks/') # path to the directory with tests notebooks +# TUTORIALS_DIR = os.path.join(BASE_DIR, 'tutorials/') # path to the directory with tutorials + +geometry_formats = ['sgy', 'qsgy', 'hdf5', 'qhdf5'] +notebooks_params = ( + # Tests configurations: + # (notebook_path, {'inputs': dict (optional), 'outputs': str or list of str (optional)}) + + # CharismaMixin test + (os.path.join(TESTS_NOTEBOOKS_DIR, 'charisma_test.ipynb'), {}), + + # Geometry tests + (os.path.join(TESTS_NOTEBOOKS_DIR, 'geometry_test_01_preparation.ipynb'), + {'inputs': {'FORMATS': geometry_formats}}), + + *[(os.path.join(TESTS_NOTEBOOKS_DIR, 'geometry_test_02_data_format.ipynb'), + {'inputs': {'FORMAT': data_format}, 'outputs': 'timings'}) for data_format in geometry_formats], + + (os.path.join(TESTS_NOTEBOOKS_DIR, 'geometry_test_03_transforms.ipynb'), + {'inputs': {'FORMATS': 'sgy'}}), + + # Horizon tests + (os.path.join(TESTS_NOTEBOOKS_DIR, 'horizon_test_01_preparation.ipynb'), {}), + (os.path.join(TESTS_NOTEBOOKS_DIR, 'horizon_test_02_base.ipynb'), {}), + (os.path.join(TESTS_NOTEBOOKS_DIR, 'horizon_test_03_attributes.ipynb'), {}), + (os.path.join(TESTS_NOTEBOOKS_DIR, 'horizon_test_04_processing.ipynb'), {}), + (os.path.join(TESTS_NOTEBOOKS_DIR, 'horizon_test_05_extraction.ipynb'), {}), + + # Fault tests + (os.path.join(TESTS_NOTEBOOKS_DIR, 'fault_test_01_preparation.ipynb'), {}), + (os.path.join(TESTS_NOTEBOOKS_DIR, 'fault_test_02_base.ipynb'), {}), + (os.path.join(TESTS_NOTEBOOKS_DIR, 'fault_test_03_sticks_processing.ipynb'), {}), + # (os.path.join(TESTS_NOTEBOOKS_DIR, 'fault_test_04_mask_creation.ipynb'), {}), # TODO: re-enable after updating BF + + # Cache test + (os.path.join(TESTS_NOTEBOOKS_DIR, 'cache_test.ipynb'), {}), + + # TODO: add tutorials + # (os.path.join(TUTORIALS_DIR, '01_Geometry_part_1.ipynb'), {}) +) + + +@pytest.mark.parametrize("notebook_kwargs", notebooks_params) +def test_run_notebook(notebook_kwargs, capsys, finalize_fixture): + """ Run tests notebooks using kwargs and print outputs in the terminal. """ + # Parse kwargs + pytest.TESTS_ROOT_DIR = pytest.TESTS_ROOT_DIR or tempfile.mkdtemp(prefix=f'tests_root_dir_{git_hash}_', dir=TESTS_DIR) + + path_ipynb, params = notebook_kwargs + filename = os.path.basename(path_ipynb) + + outputs = params.pop('outputs', None) + inputs = params.pop('inputs', {}) + inputs_repr = str(inputs) # for printing output info + out_filename = create_output_filename(input_filename=filename, inputs=inputs) + pytest.out_files_info[out_filename] = {'filename': filename, 'inputs': inputs.copy()} + + inputs.update(common_params) + + # Run test notebook + out_path_ipynb = os.path.join(pytest.TESTS_ROOT_DIR, out_filename) + exec_res = run_notebook(path=path_ipynb, inputs=inputs, outputs=outputs, + inputs_pos=2, working_dir=pytest.TESTS_ROOT_DIR, + out_path_ipynb=out_path_ipynb, display_links=False) + + if not exec_res['failed'] and common_params['REMOVE_EXTRA_FILES']: + os.remove(out_path_ipynb) + del pytest.out_files_info[out_filename] + + pytest.failed = pytest.failed or exec_res['failed'] + + # Terminal output + with capsys.disabled(): + notebook_info = f"`{filename}`{' with inputs=' + inputs_repr if inputs_repr!='{}' else ''}" + + # Extract traceback + if exec_res['failed']: + print(exec_res.get('traceback', '')) + print(f"\n{notebook_info} failed in the cell number {exec_res.get('failed cell number', None)}.\n") + + # Print test outputs + for k, v in exec_res.get('outputs', {}).items(): + message = v if isinstance(v, str) else json.dumps(v, indent=4) + print(f"{k}:\n{message}\n") + + # Provide test conclusion + if out_filename in pytest.out_files_info: + print((f"Execution of {notebook_info} saved in `{out_filename}`.\n")) + + if not exec_res['failed']: + print(f"{notebook_info} was executed successfully.\n") + else: + assert False, f"{notebook_info} failed, look at `{out_filename}`.\n" + +@pytest.fixture(scope="module") +def finalize_fixture(): + """ Final steps after all tests completion. + + When the last test is completed, this fixture: + - Dump information about correspondence between saved out files and test configuration + (the executed notebook file name and its inputs). + - Removes `pytest.TESTS_ROOT_DIR` in case of all tests completion without failures (if needed). + Note, if `pytest.TESTS_ROOT_DIR` is removed, then there is no need in dumping information about deleted files. + """ + # Run all tests in the module + yield + + # Remove pytest.TESTS_ROOT_DIR if all tests were successful + if REMOVE_ROOT_DIR and not pytest.failed: + shutil.rmtree(pytest.TESTS_ROOT_DIR) + + # If pytest.TESTS_ROOT_DIR exists, then dump information about out files + else: + dump_path = os.path.join(pytest.TESTS_ROOT_DIR, 'out_files_info.json') + + with open(dump_path, 'w') as dump_file: + json.dump(pytest.out_files_info, dump_file, indent=4) + + +# Helper function +NUM_ITERATOR = iter(range(1, len(notebooks_params)+1)) + +def create_output_filename(input_filename, inputs): + """ Creates output notebook filename. + + Output notebook filename consists of: + - Executed notebook basename + - Numeration prefix (which is equal to the test configuration execution order) + - Processed input parameters as suffix. + + `inputs` dict is converted to a string in the following format: + `'____<...>'` + + Where values are processed depends on their type: + - If value is a path string, then we add only basename without extension to the suffix. + - In other cases we remove all non-string literals from its string representation + and replace spaces with underscores. This is useful for cases when inputs contain lists, tuples, or dicts. + + Parameters + ---------- + input_filename : str + A basename of notebook for execution in tests. + inputs : dict + Dict of input parameters which were passed into the `input_filename` notebook. + """ + # Prepare filename prefix which is a file num + file_num = str(next(NUM_ITERATOR)).zfill(2) + + # Prepare filename suffix which is a short params repr + inputs_short_repr = "" + + for param_name, param_value in inputs.items(): + param_value = str(param_value) + + if os.path.exists(param_value): + # Cut long paths + param_value = os.path.splitext(os.path.basename(param_value))[0] + else: + # Create a correct filename substring for lists, tuples, dicts + param_value = re.sub(r'[^\w^ ]', '', param_value) # Remove all non-letter symbols except spaces + param_value = param_value.replace(' ', '_') + + inputs_short_repr += param_name + '_' + param_value + '_' + + filename_without_ext = os.path.splitext(input_filename)[0] + + out_filename = f"{file_num}_{filename_without_ext}_out_{inputs_short_repr[:-1]}.ipynb" + return out_filename diff --git a/tests/utils.py b/tests/utils.py new file mode 100644 index 0000000..448c554 --- /dev/null +++ b/tests/utils.py @@ -0,0 +1,33 @@ +""" Utility functions for tests.""" +import numpy as np + +def generate_synthetic(shape=(500, 500, 300), i_scale=5, i_frequency=0.02, x_scale=5, x_frequency=0.05, + sticks_direction=0, n_nodes=4, n_sticks=10): + """ Create synthetic data cube and horizon for tests.""" + i_shape, x_shape, depth = shape + synthetic = np.empty(shape, dtype=np.float32) + matrix = np.empty(shape[:2], dtype=np.int32) + + arange = np.arange(depth, dtype=np.float32) + trace = np.sin(0.1 * arange) + + for i in range(i_shape): + for j in range(x_shape): + + offset = i_scale*np.cos(i_frequency*i) + x_scale*np.sin(x_frequency*j) + offset = int(offset) + + synthetic[i, j, :] = np.roll(trace, offset) + matrix[i, j] = offset + + sticks = [] + for loc in np.linspace(0, shape[sticks_direction]-1, n_sticks).astype(np.int32): + start = int(0.4 * (shape[1-sticks_direction]-1)) + end = int(0.6 * (shape[1-sticks_direction]-1)) + nodes = np.linspace(start, end, n_nodes).astype(np.int32) + depthes = np.linspace(0, shape[2]-1, n_nodes).astype(np.int32) + array = np.stack([nodes, depthes], axis=1) + array = np.insert(array, sticks_direction, loc, axis=1) + sticks.append(array) + + return synthetic, matrix + depth // 2, np.array(sticks) diff --git a/tutorials/01_Geometry_part_1.ipynb b/tutorials/01_Geometry_part_1.ipynb new file mode 100644 index 0000000..3df63ef --- /dev/null +++ b/tutorials/01_Geometry_part_1.ipynb @@ -0,0 +1,692 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Geometry tutorial: part 1\n", + "\n", + "One of the crucial parts of our framework is a `Geometry` class that holds information about the underlying cube of amplitudes in different data formats (**SEG-Y**, **HDF5**) and their versions with compression using quantization (**QSGY**, **QHDF5**). The main capabilities of `Geometry` are:\n", + "\n", + "- infer information about traces in the cube based on one or more headers\n", + "- collect spatial and integral statistics about amplitude values\n", + "- provide methods for loading actual data from the desired location\n", + "- convert **SEG-Y** cubes to more efficient file formats that take less disk space\n", + "\n", + "To create a `Geometry` instance for a **SEG-Y** cube, we need to supply a path to the cube and the headers that would be used to uniquely identify each of the traces: those headers are used as an index to access underlying data. Note that we only load more than one trace into memory when we specifically ask for it: all information collection is done sequentially, without requiring too much RAM.\n", + "\n", + "The `Geometry` tutorial is split into two parts. The **first part** demonstrates a number of methods and properties that help us to **examine the geology**:\n", + "\n", + "* [Post-stack cube with INLINE_3D/CROSSLINE_3D headers](#headers)\n", + "* [First look at geological properties](#stats)\n", + "* [Loading cube data slices](#cube_slices)\n", + "\n", + "And in the [**second part**](./01_Geometry_part_2.ipynb) you will learn more about **different data formats** and **saving processed data**." + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "metadata": { + "execution": { + "iopub.execute_input": "2022-09-28T12:36:07.334569Z", + "iopub.status.busy": "2022-09-28T12:36:07.334020Z", + "iopub.status.idle": "2022-09-28T12:36:09.061705Z", + "shell.execute_reply": "2022-09-28T12:36:09.060733Z", + "shell.execute_reply.started": "2022-09-28T12:36:07.334428Z" + }, + "tags": [] + }, + "outputs": [], + "source": [ + "# All the necessary imports\n", + "import os\n", + "import sys\n", + "import numpy as np\n", + "from time import perf_counter\n", + "from matplotlib import pyplot as plt\n", + "\n", + "import warnings\n", + "warnings.filterwarnings('ignore')\n", + "\n", + "sys.path.insert(0, '../..')\n", + "sys.path.insert(0, '..')\n", + "from seismiqb import Geometry, plot\n", + "\n", + "FIGURE_SCALE = 1.5" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "\n", + "# Post-stack: INLINE_3D/CROSSLINE_3D headers\n", + "\n", + "First of all, we instantiate a cube. Besides cube location on the disk, we need to specify:\n", + "\n", + "- headers to store for each trace\n", + "- which of the headers are used as a unique identifier of a trace: it must be a subset of `headers`\n", + "- whether to collect amplitude statistics and spatial stats\n", + "\n", + "Post-stack is a cube after multiple processing steps: it is already summed, and each trace has a dedicated `INLINE_3D` and `CROSSLINE_3D`.\n", + "\n", + "By default, we load `INLINE_3D, CROSSLINE_3D, CDP_Y, CDP_X` headers and use the first two for indexing." + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": { + "execution": { + "iopub.execute_input": "2022-09-28T12:36:09.062791Z", + "iopub.status.busy": "2022-09-28T12:36:09.062648Z", + "iopub.status.idle": "2022-09-28T12:36:27.764926Z", + "shell.execute_reply": "2022-09-28T12:36:27.763390Z", + "shell.execute_reply.started": "2022-09-28T12:36:09.062773Z" + }, + "tags": [] + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Collecting stats for `001_YETYPUR.sgy`: 100%|\u001b[38;2;76;175;80m████████████████████████████\u001b[0m| 2563/2563 [00:07<00:00, 354.02it/s]\u001b[0m\n", + "Processed geometry for cube /data/seismic_data/seismic_interpretation/001_YETYPUR/001_YETYPUR.sgy\n", + "Index headers: ['INLINE_3D', 'CROSSLINE_3D']\n", + "Traces: 3_611_267\n", + "Shape: (2563, 1409, 1501)\n", + "Time delay: 50 ms\n", + "Sample rate: 2.0 ms\n", + "Area: 1522.4 km²\n", + "\n", + "File size: 21.000 GB\n", + "Instance (memory) size: 0.141 GB\n", + "\n", + "Number of dead traces: 1_175_447\n", + "Number of alive traces: 2_435_820\n", + "Fullness: 0.67\n", + "\n", + "Value statistics:\n", + "mean | std: 0.03 | 1887.17 \n", + "min | max: -47429.45 | 39240.19 \n", + "q01 | q99: -5459.50 | 5118.29 \n", + "Number of unique values: 214\n", + "CPU times: user 1min 35s, sys: 11.1 s, total: 1min 46s\n", + "Wall time: 18.7 s\n" + ] + } + ], + "source": [ + "%%time\n", + "geometry = Geometry.new(path='/data/seismic_data/seismic_interpretation/001_YETYPUR/001_YETYPUR.sgy',\n", + " collect_stats=True, recollect_stats=True)\n", + "\n", + "print(geometry)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "A ```Geometry``` instance contains some information about the cube.\n", + "The following properties are available through the ```print``` call:\n", + " * **Base info**: cube name, index headers, shape;\n", + " * Info about **data acquisition**: time delay, sample rate;\n", + " * **Сomputed info**: approximate area in squared kilometers;\n", + " * **Storage** parameters;\n", + " * **Traces info**: total amount, amount of meaningful traces and their proportion;\n", + " * **Cube statistics** based on subsample of traces.\n", + "\n", + "Moreover, this is not all what ```SeismicGeometry``` stored inside. We can save and get other things from an instance of this class:\n", + " * Other **geometry properties** like depth, ranges, dead traces and area;\n", + " * **Statistical matrices**: mean, std, min, max;\n", + " * **Signal-to-noise** ratio matrix;\n", + "\n", + "A regular `pandas` dataframe describes cube structure, storing all required headers:" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": { + "execution": { + "iopub.execute_input": "2022-09-28T12:36:27.768319Z", + "iopub.status.busy": "2022-09-28T12:36:27.768026Z", + "iopub.status.idle": "2022-09-28T12:36:27.968816Z", + "shell.execute_reply": "2022-09-28T12:36:27.968165Z", + "shell.execute_reply.started": "2022-09-28T12:36:27.768282Z" + } + }, + "outputs": [ + { + "data": { + "text/html": [ + "
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" + ], + "text/plain": [ + " CROSSLINE_3D CDP_Y INLINE_3D CDP_X TRACE_SEQUENCE_FILE\n", + "0 19 7150315 24 717115 1\n", + "1 20 7150315 24 717140 2\n", + "2 21 7150315 24 717165 3\n", + "3 22 7150315 24 717190 4\n", + "4 23 7150315 24 717215 5\n", + "... ... ... ... ... ...\n", + "3611262 1423 7214365 2586 752215 3611263\n", + "3611263 1424 7214365 2586 752240 3611264\n", + "3611264 1425 7214365 2586 752265 3611265\n", + "3611265 1426 7214365 2586 752290 3611266\n", + "3611266 1427 7214365 2586 752315 3611267\n", + "\n", + "[3611267 rows x 5 columns]" + ] + }, + "execution_count": 3, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "geometry.headers" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "***Note that our class can work with any indexing headers, not only the `INLINE_3D`/`CROSSLINE_3D` pair. Though, it is much preferred: those headers are represented by integer values, and their usage as an index is much more robust. A common flaw of a `CDP_X`/`CDP_Y` index is that multiple `CDP_X` can correspond to one `CROSSLIN_3D`. For example, `10.25`, `10.2501` values can be labeled as the first crossline, which makes the unique indexing much harder to impose.***" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "\n", + "# First look at geological properties\n", + "\n", + "`INLINE_3D`/`CROSSLINE_3D` index provides a clear spatial structure, so we can collect spatial (lateral) stats at initialization. It takes some time and creates several additional attributes:\n", + "\n", + "- `min_matrix`, `max_matrix`, `mean_matrix`, `std_matrix` store minimum, maximum, average, and variance values for each of the cube traces\n", + "- `min_vector`, `max_vector`, `mean_vector`, `std_vector` store minimum, maximum, average, and variance values depthwise\n", + "\n", + "Each `*_matrix` has the same dimensionality as the spatial range of the cube: we can see that the cube has 2563 inlines and 1409 crosslines, and each matrix has the same shape. Most of the cubes are padded with zero traces on the edges to have a rectangular shape:" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": { + "execution": { + "iopub.execute_input": "2022-09-28T12:36:27.970072Z", + "iopub.status.busy": "2022-09-28T12:36:27.969926Z", + "iopub.status.idle": "2022-09-28T12:36:28.705271Z", + "shell.execute_reply": "2022-09-28T12:36:28.704596Z", + "shell.execute_reply.started": "2022-09-28T12:36:27.970054Z" + }, + "tags": [] + }, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "geometry.show(matrix='snr', scale=FIGURE_SCALE)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "To speed up the instance initialization, we keep all of the collected stats near the cube in a ```*.sgy_meta``` file in HDF5 format and use it for subsequent initializations. To force re-creation of ```*.sgy_meta``` file (instead of loading stats from it) during processing, pass `recollect_stats=True` at initialization, just as we did." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "\n", + "# Loading cube data slices" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "One of the main usages of `Geometry` is to load slices of amplitudes. We use the `load_slide` method, which takes a number of a slice that we want to load. The loading acts along the specified axis (0 by default), corresponding to a `INLINE_3D` in our case. " + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": { + "execution": { + "iopub.execute_input": "2022-09-28T12:36:28.706504Z", + "iopub.status.busy": "2022-09-28T12:36:28.706166Z", + "iopub.status.idle": "2022-09-28T12:36:28.715453Z", + "shell.execute_reply": "2022-09-28T12:36:28.714792Z", + "shell.execute_reply.started": "2022-09-28T12:36:28.706475Z" + } + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "CPU times: user 5.89 ms, sys: 394 µs, total: 6.28 ms\n", + "Wall time: 4.64 ms\n" + ] + } + ], + "source": [ + "%%time\n", + "slide = geometry.load_slide(index=30, axis=0)" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": { + "execution": { + "iopub.execute_input": "2022-09-28T12:36:28.716741Z", + "iopub.status.busy": "2022-09-28T12:36:28.716457Z", + "iopub.status.idle": "2022-09-28T12:36:28.764132Z", + "shell.execute_reply": "2022-09-28T12:36:28.763368Z", + "shell.execute_reply.started": "2022-09-28T12:36:28.716717Z" + } + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "CPU times: user 19.3 ms, sys: 23.9 ms, total: 43.2 ms\n", + "Wall time: 42.6 ms\n" + ] + } + ], + "source": [ + "%%time\n", + "locations = [slice(0, 100), slice(600, 800), slice(600, 1000)]\n", + "crop = geometry.load_crop(locations)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "For convenience, the square brackets allow working with an instance of `geometry` like with any regular 3D array and load data into memory. As you can see, loading an entire ~20GB cube takes just a few seconds!" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "metadata": { + "execution": { + "iopub.execute_input": "2022-09-28T12:36:28.765383Z", + "iopub.status.busy": "2022-09-28T12:36:28.765100Z", + "iopub.status.idle": "2022-09-28T12:36:43.652303Z", + "shell.execute_reply": "2022-09-28T12:36:43.651164Z", + "shell.execute_reply.started": "2022-09-28T12:36:28.765359Z" + } + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Entire cube:\n", + " [2563 1409 1501]\n", + " (2563, 1409, 1501)\n", + "\n", + "CPU times: user 7.78 s, sys: 7.1 s, total: 14.9 s\n", + "Wall time: 14.9 s\n" + ] + } + ], + "source": [ + "%%time\n", + "print(f\"Entire cube:\\n {geometry.shape}\\n {geometry[:, :, :].shape}\\n\")" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "metadata": { + "execution": { + "iopub.execute_input": "2022-09-28T12:36:43.653910Z", + "iopub.status.busy": "2022-09-28T12:36:43.653740Z", + "iopub.status.idle": "2022-09-28T12:36:46.073236Z", + "shell.execute_reply": "2022-09-28T12:36:46.072523Z", + "shell.execute_reply.started": "2022-09-28T12:36:43.653890Z" + }, + "tags": [] + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Crop:\n", + " (200, 400, 30)\n", + "\n", + "Slide:\n", + " (1409, 1501)\n", + " (2563, 1501)\n", + " (2563, 1409)\n", + "\n", + "CPU times: user 2.27 s, sys: 150 ms, total: 2.42 s\n", + "Wall time: 2.41 s\n" + ] + } + ], + "source": [ + "%%time\n", + "print(f\"Crop:\\n {geometry[700:900, 200:600, 0:30].shape}\\n\")\n", + "print(f\"Slide:\\n {geometry[100, :].shape}\\n {geometry[:, 10].shape}\\n {geometry[:, :, 0].shape}\\n\")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Visualization\n", + "\n", + "Method `show_slide` acts exactly like `load_slide` does and works with the same parameters, but displays the data instead of returning it.\n", + "\n", + "***Note:*** just like any other plot in our library, it automatically parses `matplotlib` arguments and uses them in right places. To learn more about it, check out our [plotting tutorial](./plotters/01_image.ipynb)! " + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "metadata": { + "execution": { + "iopub.execute_input": "2022-09-28T12:36:46.074657Z", + "iopub.status.busy": "2022-09-28T12:36:46.074317Z", + "iopub.status.idle": "2022-09-28T12:36:46.678737Z", + "shell.execute_reply": "2022-09-28T12:36:46.677989Z", + "shell.execute_reply.started": "2022-09-28T12:36:46.074634Z" + } + }, + "outputs": [ + { + "data": { + "image/png": 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\n", 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" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "geometry.show_slide(index=800, axis=1, scale=FIGURE_SCALE)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "As the bottom of the slide is very noisy and does not provide much insight, we would like to zoom in. `zoom` parameter does exactly that:" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "metadata": { + "execution": { + "iopub.execute_input": "2022-09-28T12:36:46.680135Z", + "iopub.status.busy": "2022-09-28T12:36:46.679679Z", + "iopub.status.idle": "2022-09-28T12:36:46.946554Z", + "shell.execute_reply": "2022-09-28T12:36:46.945505Z", + "shell.execute_reply.started": "2022-09-28T12:36:46.680109Z" + } + }, + "outputs": [ + { + "data": { + "image/png": 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\n", 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" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "geometry.show_slide(index=800, axis=1, scale=FIGURE_SCALE,\n", + " zoom=(slice(None), slice(900, 1300)))" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Sometimes, change of colormap helps to distinguish reflections such as horizons and faults:\n", + "\n", + "***We also zero-center the image by passing `vmin` and `vmax` values.***" + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "metadata": { + "execution": { + "iopub.execute_input": "2022-09-28T12:36:46.947731Z", + "iopub.status.busy": "2022-09-28T12:36:46.947561Z", + "iopub.status.idle": "2022-09-28T12:36:47.233941Z", + "shell.execute_reply": "2022-09-28T12:36:47.233292Z", + "shell.execute_reply.started": "2022-09-28T12:36:46.947711Z" + } + }, + "outputs": [ + { + "data": { + "image/png": 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9ouvdUjrssMOsK1O6u7vx8MMP47rrrsPatWtx7bXX4ogjjrAy8Xry5MnTq408MPTkydMORy8m8yfDQjeXNJxyc85kjR49etht2ppULpfN35tzt+KqVasalt3adXl6ZdPFF1+MSy65ZIvKjhgxwvwdRdFmldHnNhUqDiQRB42A+cc//nHMnz8fTz75JI4//njcf//92GuvvTarDZ48efL0SiMPDD158rTDkXqylixZ8pJePq7v2pzrLtatW/eStWVzaNdddzV/q2d1KGLSELfs1q7L045LGr65uWHWfX195u8XY2SYPHkyrr/+euy3336oVqt497vfjQcffNACq548efL0aiGfldSTJ087HE2dOtX8zWskXiqaMmWK+Xvx4sUbfTaOY3NH3PaiOXPmmL//8pe/bPTZlStXGjA3YcKEuhDK4dRVq9Xw4IMPAkg8PLvtttuw2u3p1UttbW3m73/+85+bVUafY9bYLaV58+bh1FNPBQA88sgjWLBgwYuqz5MnT55eruSBoSdPnnY40ku59f60l4L0Lj5eZTAU/fnPf7Y8HduDDj30UDQ1NQEAfv/731vn/lz61a9+Zf4+6qij6r7fY4890N7eDiC5IHxjIPzee+81fX/961//ijtj6OmlI11DmjhqY6TPMXHOi6FPfvKTxkv46U9/etgh5Z48efL0SiAPDD158rTD0THHHGPu1fva176G5cuXv2TvOvbYY016++uuu26jyWuuvPLKl6wdm0ulUsncI9fX1zfknXlxHOOaa64x/5944ol1z+RyObz97W83z1999dVDvvcrX/nKRuvytOPSUUcdhZEjRwIAbrvttk16DQcGBnDttdea/4877rgX3YaZM2cavuzs7HzVXEfiyZMnT0oeGHry5GmHo9GjR+Piiy8GkFzcfdRRR+HJJ5/caJn7778fH/3oR4f9rgkTJuCUU04BkCRgOemkkxp64a655hrceOONw67/paCLLroIuVwOQJJ84+GHH6575tJLL8X9998PILlm49hjj21Y13nnnWeS7nzxi1/EHXfcUffMddddh5tuuglAcoH4GWecsVX64enVQZMnTzahnAMDA3j7298+pDHnhRdewPve9z784x//AADsvvvueMtb3rJV2nHBBReYdfHf//3feOGFF7ZKvZ48efL0ciGffMaTJ087JH3wgx/En//8Z/zv//4vHn74YaNAHnLIIZg8eTIGBwexcuVKPPLII7jjjjvw1FNPYeedd8bnP//5Yb/rc5/7HG677TZ0dnbil7/8JebMmYPTTz8ds2bNwurVq/GjH/0Iv/71r/Ga17wGY8eO3a7XVQDAPvvsg49+9KP43Oc+hzVr1uDAAw/Ee9/7Xuy3336oVCr44Q9/aEJwS6WS5Z1xacqUKbjyyitx1llnIYoiHH300TjllFMwf/58RFGEX/7yl7j55psBJFcYXHvttQjDcMj6vv3tb+Opp56yPuvt7TV/X3jhhdZ348aNw0c+8pHhDsF2oU3dp6l07LHHGi/ajkBXXnkl7r77bvzjH//Agw8+iF122QXveMc7cMABB6ClpQXr1q3DI488ghtuuMGELI8ePRrXX3/9ZmUl3Rzac889ceyxx+LnP/+58RoO97obT548eXpZU+zJkydPL1MCYH62tOz8+fOHfKZWq8Wf+cxn4qamJutdQ/0MVdfmvOsf//hHPGPGjCHrbm9vj//617/G8+fP3+I+b02q1Wrxhz70oTiXyw3Z5okTJ8Z33HHHZtV3xRVXxCNHjhyyrjFjxsQ/+MEPNlmPjs/m/EyfPv1FjsTm0amnnmreuWDBgs0uN5y+6M/q1as3WfeCBQvM86eeeuoW9+2pp57aovG8+OKLTbmLL754i99PWrlyZXzUUUdt1vjsuuuu8UMPPbTR+rZkfP7whz9Ya7Zarb7ofnny5MnTy4V8KKknT552WMrlcrjwwgvx1FNP4dJLL8X8+fPR1taGQqGAMAzR3t6ON77xjbjooovwxz/+EXfdddcWv2vXXXfFo48+is9+9rOYO3cuSqUSxowZgzlz5uCiiy7Cgw8+iL333nvrde5FUi6Xw5e+9CX84Q9/wGmnnYaZM2ciDEOUy2XMmzcPl156Kf72t7/h8MMP36z6zjvvPDzwwAP4wAc+gF133RWjR482/f/Yxz6GRx55BO985ztf4l55eiVTa2srfvnLX+Kee+7Bf/7nf2LvvffG+PHjEQQBmpubMWvWLPz7v/87rr/+ejz22GMvyX2DBx54IA455BAA/qyhJ0+eXn2Ui+M43t6N8OTJkydPnjx58uTJkydP24+8x9CTJ0+ePHny5MmTJ0+ednDywNCTJ0+ePHny5MmTJ0+ednDywNCTJ0+ePHny5MmTJ0+ednDy11V48uTJk6cdgh544AE888wzW1z++OOP33qN8eTJkydPnl5m5JPPePLkyZOnHYJOO+00LFy4cIvL++3SkydPnjy9msmHknry5MmTJ0+ePHny5MnTDk7eY+jJkydPnjx58uTJkydPOzh5j6EnT548efLkyZMnT5487eDkgaEnT548efLkyZMnT5487eDkgaEnT548efLkyZMnT5487eDkgaEnT548efLk6WVP/f39uOiii7Dbbrth1KhRyOVyyOVy+Otf/7q9m+bJkydPrwrywNCTp1cwDQ4O4sYbb8Qpp5yCXXfdFeVyGYVCARMnTsRBBx2Ej3/843j00Ufryi1dutQoVfozYsQIlMtldHR04GMf+9iw7nxbvnw5PvOZz+Cggw5CW1sbCoUCJkyYgI6ODlxwwQV48sknN6uexx57DOeccw723ntvjB07FoVCAVOmTME+++yDk046CV//+tfxxBNPDFn+/vvvx3vf+17stttuGDNmDJqamrDTTjuho6MDp59+Oq677jo8++yzdeWuu+46Mw5Lly7d7H5vqtyMGTPM95u6B++SSy5BLpfDjBkz6r4bas6G+rnuuus2uw9D0c9+9jOcd955OOyww7DzzjujubnZzMfRRx+NBQsWIIqiIctr3/kzcuRIjB8/HjvvvDPe/OY341Of+tRWVex//etf4x3veAemT5+OMAwxatQozJw5EyeddBJ+97vfbbL82rVrcckll2DPPfdEqVTC2LFj8brXvQ5XXnklBgYGNll+xYoV+MhHPoLXvva1GDVqFFpaWnDwwQfjW9/61iv2uosvf/nLuOSSS7Y7ADvxxBPxX//1X3j88ceRy+UwadIkTJo0CSNHjtys8l1dXbjxxhtxwQUX4IgjjsD48eMNX951111b1KYNGzZgr732MvWcdtppmyzzwAMP4N3vfjfa29vR1NSEyZMn49/+7d/w29/+dpNl+/r68NnPfhYdHR0YO3YsisUidt11V5x77rno7Ozcoj548uTJk6HYkydPr0j64x//GO+6664xAPMzcuTIuKWlJc7n89bnb33rW+MXXnjBlH3qqafMd83NzfGkSZPiSZMmxS0tLVa5UqkU33rrrZtsyxe+8IW4WCyacrlcLh43blw8YsQI81kQBPF5550XR1E0ZD2f//zn4yAIrDaUy+V41KhR1mfz58+vK1ur1eJzzz3Xeo7taGpqsj4/9dRT68ovWLDAfP/UU09tzhRsVrnp06db77733nuHrOviiy+OAcTTp0+v+26oORvq5/rrr9/sPgxFe+yxh9X2MWPGxGEYWp/Nmzcv7urqaliefQ/D0LRr4sSJdXUAiA844ID4oYce2uK21mq1+P3vf79V56hRo+p458Mf/vCQdSxdujSeMWOGebZYLFq8s88++8Q9PT1Dll+0aFE8fvx4a/0oP7/pTW+y1uErhTiPCxYs2G5t+Pvf/27G8YYbbtiiOri+Gv3ceeedW6XORrJF6Zvf/KbFE2PHjo1zuZz5/+KLLx6y7N///neLP5uamuJyuWzJhd/+9rdb1A9Pnjx5iuM49sDQk6dXIP30pz81Cuv48ePj//7v/46feOIJ830URfGf//zn+IILLoibm5tjAPHq1avN9woyXGVv3bp18YIFC4zCMXbs2HjVqlVDtuXss882de2///7xrbfeGlerVdOOu+++Oz722GPNM8cff3w8ODhYV88Pf/hD88whhxwS33777fH69evN952dnfEPfvCD+G1ve1t8xBFH1JW/8sorTfnjjjsuvvfeey0lfMmSJfG3v/3t+KijjopPP/30uvLbChgefPDBQ9a1ucBwWynoF198cXzttdfGf/vb3+L+/n7z+XPPPRd/+tOfNgaIN73pTQ3Ls++NlOU1a9bEv/3tb+P3ve99hpcLhUL8s5/9bIva+p3vfMeMz9ve9jZrPTz++OPxcccdZ77/0Y9+VFd+w4YN8Z577hkDiCdPnhz/+te/juM4jgcHB+Prr78+HjNmTAwgPuaYYxq+v7e3N25ra4sBxLNnz47//Oc/x3Ecxy+88EJ8zTXXxCNHjowBxGedddYW9W970ssBGN54441G3m0pXXLJJfFOO+0UH3fccfGll14af/Ob33xRwPDhhx+OR44cGc+cOTOeNGnSJoHhvffea4xlxx9/fPzss8/GcRzH3d3dllGjEfDt7++PZ86cacbghz/8Ybxhw4Y4juP4ySefjI8++mgDDlmvJ0+ePA2XPDD05OkVRk888YQBe7vvvvsmlYBVq1bFxx133GYDQ9L//u//mme+8Y1vNHxm4cKF5pmTTjppo97ACy+80Dx76aWX1n1/4IEHxgDiOXPmGIVnKFKQEseJt2jq1KkxgPioo47aaNlG5eP4pQeGxx57rPEMDAV+Xm7AcFP08Y9/3LSpER9uDBgqPfTQQ/FOO+0UA4hHjx5tgbrNpUMPPTQGEM+aNash/wwMDBjF+p3vfGfd99/61rc26tX9/ve/b77/zW9+U/c9+XvUqFHxkiVL6r6/7LLLYgDxiBEj4n/84x/D7t/2pJcDMLzuuuuGXBubS6580jU1XGAYRVHc0dERA4hvv/32zeL1gw46KAYQ77nnnvHAwEDd929605tiAPGMGTPq2nr11Vebtv74xz+uK7t+/XrThkaGL0+ePHnaHPJnDD15eoXRhRdeiL6+PoRhiFtuuQXt7e0bfb6lpQU//vGPMXbs2GG956ijjjJ//+1vf6v7fmBgAB//+McBALNnz8a3vvUtjBgxYsj6PvOZz+ANb3gDAODyyy9Hd3e39T3PLx1zzDEIgmCjbRs1apT1f3d3N5577jkAwFve8paNlm1UfltQR0cH3va2twEAPvGJT6BWq23zNmxtOuCAA8zfHP8tob322gs333wzcrkc1q1bh0svvXTYdSxfvhwAsPfeezfkn5EjR2Lu3LkAgEqlUvf9woULAQCHHXYY/uVf/qXu+3e+8514zWteAwD43//937rv+Zk+p3T22WejVCphcHAQ3/ve9zazVzYNDg7iO9/5Dg4//HC0traiqakJU6dOxdvf/vaNnpHjWc+NnTs97bTT6s7I8czr008/DQB4z3veU3dmdLhUrVbx5S9/GQceeCDGjRuHMAwxffp0nHLKKQ3PMLINbNfTTz9tvX9zzvSRNiafhktXXnklFi1ahFNOOQVHHHHEJp9fsmQJ7rnnHgDAeeed1/BcJOXp0qVL8fvf/9767he/+AUAYJdddsFxxx1XVzYMQ5xzzjkAgBtuuAHr168fXoc8efLkCT75jCdPryhasWIFbr75ZgDASSedhF133XWzyw5XiYslUcbg4GDd97fccguWLVsGALjgggsQhuEm6/zUpz4FIMku+J3vfKfhMy82gcLLOQHDZz/7WQRBgEceeQT/93//t72b86Lp7rvvBpDw1syZM19UXfvttx+OOeYYAMBNN900bMWW73/ooYcaJsTZsGGDAR4dHR3Wd/39/fjDH/4AADj66KMb1p/L5Yyx5Pbbb7e++8c//mESNQ1VvlQq4eCDD25YfnNozZo1eOMb34gzzjgDd955J3p7e1EsFrF8+XLcfPPNOOyww3D++ecPu96NUalUwqRJk5DPJ6pCc3OzSfjCn+HQc889h9e97nX48Ic/jD/+8Y9Yt24dwjDEM888g+9+97vYd999cfXVVzdsQ3NzMwAgn89b7x+uwWtr0BNPPIGLL74YEyZMwBe/+MXNKvPrX//a/K1GN6WDDjoIY8aMAVDPIwTnu++++5Dv2G233QAA69atM/zsyZMnT8MhDww9eXoF0Z133mk8Tf/2b//2kr7rtttuM383UvqZQS+fz292Ww455BCMHz8eQNIXpf322w8AcOONN+L73//+sDxqEyZMMF6aq6++2lLCXk60yy674L3vfS+ABCS/8MIL27lFw6dKpYJHH30UH/3oR3HllVcCAE4++WRMmDDhRdd97LHHAgBeeOEF3HfffcMqe9ZZZwEAFi9ejHe9611YvHix+e4f//gH3vGOd2DJkiXYeeed8eEPf9gq+/e//93w25w5c4Z8B7/r6upCT0+P+Vwz/25O+ccee2xzu2XojDPOwF133YVCoYCvfOUr6Ovrw+rVq7Fs2TKcfvrpAIAvfOEL+PrXvz7suoei8847D11dXdhpp50AAFdddRW6urqsn82lwcFBnHDCCXj00UcxduxY/N///R8qlQp6e3vxz3/+E29+85tRq9Vw7rnn4pe//GVdG6666ioAwE477WS9n59vK4rjGGeccQaq1Sq+9KUvGXm2KSKPTJw4ERMnTmz4zIgRIzB79mwAjaM0gMZGukbfPfLII5vVLk+ePHlS8sDQk6dXEKmysM8++7wk7+jv78fChQtx7rnnAgCamprwrne9a8i2zJw501jzN4cYzudeo3HJJZcgCAJEUYSTTjoJU6dOxYknnogrrrgCd955J9atW7fRej/zmc8ASK4bOPLIIzFjxgyccsopuOqqq3Dvvfe+bEDYxRdfjGKxiKeffhpf+9rXtqiOc889F21tbRv92Zp03333mdC9MWPGYM8998QVV1yBfD6P008/fauBkb333tv8/c9//nNYZf/1X/8VX/rSl1AoFHDzzTdjl112QbFYRLFYxOzZs3HXXXfhrLPOwp/+9Kc6fqXnGwCmTp065Dv0Oy0z3PJ9fX0Nw1mHovvvvx8//OEPASSGj7PPPhvFYhEA0NbWhm9/+9s44YQTAAAXXXQRqtXqZte9rejmm2/G/fffDyAx/px00kkoFAoAEhlyyy23YP/990ccx/joRz+6PZu6Ubrmmmtwzz334E1vehNOOumkzS5HHtkYf+j3ylMAzBU2f/vb34a89kRlqlvekydPnjaHPDD05OkVRKtWrTJ/t7S0bJU6FWSMHz8eo0ePxmmnnYbe3l6MHDkSCxcuxOTJk4dsy+ZazEmtra1WedL8+fNx22234bWvfS2A7M6xj370ozj88MMxbtw4HHvssXVnb0gnnXQSrr/+enPm8umnn8Z3v/tdfOhDH8LrX/96jBs3Du985zvx0EMPDau9W5va2tqMx+qyyy5DX1/fsOvo6+vDihUrNvqzNalQKJjQPSrzAPD+978fF1988VY7s6k8rR65zaUPfehD+NGPfmQ8MuvXrzchqQMDA6hUKlizZk1dubVr15q/CbgakX6nZV5s+U3RDTfcAABob283HmeXaBjp7u5+WXrM2Yd/+Zd/wZFHHln3fRAEuPjiiwEkAOfl6PFaunQpPv7xj6NYLOJ//ud/hlWW870x/tDvXf5gmPVTTz2F73//+3XlKpUKvvKVr5j/t0SuePLkyZMHhp487eCkIEOV8WnTpuHhhx/GiSeeuM3a8oY3vAGPPfYY7rrrLnz84x/H4YcfbsDChg0bcOutt2L+/PnmrKJLJ554IpYsWYJbb70V/+///T/rzM769etxww03oKOjA9/85je3WZ8a0fnnn4/x48eju7sbV1xxxbDLL1iwAHGSVXrIn61J8+bNM6F769evx5NPPokPfOAD+PrXv4499tgDP/3pT7fq+7aE+vv7ceKJJ+LNb34zpk2bhttvvx0rV67EypUrcfvtt2P33XfHd7/7Xey33354+OGHt3dzh0WLFi0CkCTG4Xk/l3bbbTfjbeLzLydim974xjcO+cxhhx1mEsS8HPvwvve9zyRHapRg6KWk97znPead73//+/H1r38dq1atwgsvvIB7770XRx55JJYvX24SLw3FJ548efK0MfKSw5OnVxCpd25LPCqNSEHGmjVrcOedd+L1r389nnnmGbznPe8ZMuSNbXE9f5siZiMdytOYz+cxf/58XHbZZbjjjjuwatUq/P3vf8enPvUpjB49GkDiHfn5z3/esPzIkSNx9NFH48orr8Tdd9+N3t5ePPDAAzj33HNNqOpZZ521XT2HY8eOxSc+8QkAwJe+9KVhndXa3pTP5zFr1ixcc801uOKKK1CpVHDSSSeZrKAvhpSnh+uJPv/883HjjTfita99Le6++24cccQRaG1tRWtrK4444gj8/ve/x6677oru7m584AMfsMrSeAAkAHMo0u+0zIstvyl6/vnnAWw6DJHecj7/cqLN6UMYhiai4OXWh29961v4zW9+g3nz5uFDH/rQsMtzvjfGH/q9yx+jR4/Gz3/+c0yfPh3r1q3DWWedhdbWVoRhiNe//vW477778PnPfx7lchkAMG7cuGG30ZMnT548MPTk6RVEe+yxh/n7wQcf3Or1Nzc349BDD8Xtt9+OPfbYA/fddx8++MEPNnyW2fGWLFnSMDxvKGJmSO3Lpmj27Nn49Kc/jZ/+9Kcmu+q3vvWtzSqbz+exzz774Mtf/jKuvfZaAEmShgULFmz2+18K+sAHPoBp06Zt8fUMLwf6z//8TzQ1NaFSqeAHP/jBi65PwfrOO++82eXWrl1r5vYDH/hAwwy5o0aNMrx8zz33WMBjypQp5u+NXbuh32mZ4ZZvbm5GqVQa8jlPLy9as2YNzjvvPOTzeXz5y1/G+vXrUalUrB966aMoMp9pAi3yyKaudeH3ylOk3XffHY888giuuOIKHHrooXjNa16DXXbZBe94xzvwu9/9Dueeey56e3sBYFgZqz158uSJ5IGhJ0+vINJQsltuueUle0+xWDRp4xcuXIh777237hneSVir1Ta7Lb/73e+Mh/Hwww8fdrsOP/xwzJo1C0CSaXK4dMopp5jzcFtSfmtSU1OTAYTf+ta3rCyarxQKw9CE+m6N9vOutqamJuuOxE3RE088Ya6o2Big3GWXXczfTz31lPl7t912M+vKTYqkxO/a2tqs85CaiXRzym/syoFGxDOTm7qKhd+7WS8ZXrixpDTDMe5sCW1OH6rVqpEPQ2Xu3B60evVqrFmzBrVaDYcccgjGjBlT98PrSr73ve+ZzzRkmTzy/PPPY+XKlQ3fMzg4iMcffxzA0IazMWPG4LzzzsOdd96JJUuW4IknnsANN9yAgw8+2Lqq5cADD9xq/ffkydOOQx4YevL0CqJJkyaZ7IPf//738cQTT2x22eGeOzvssMMwf/58AMk9hS4df/zxJvvl5z73uc3K+skEGaNGjcJ73vOeYbWHRE9LU1PTsMuOGDHCeJO2pPzWppNPPhlz5szBhg0b8MlPfnJ7N2fYtHbtWqPkDic0shH96U9/wq233goguSR+c+7FJOl5Kt731og0KY+2t1gs4vWvfz0A+5oWpTiO8atf/QoA6pKn7Lrrrpg2bdpGy69bt87c+9go+crGiPcu6nU1Lj3++OPG2/S6173O+o5hhc8++2zDsrVabaNn+ji+L+bsKvtwxx13DPnMXXfdZYCN24dXOh1xxBHm76F45A9/+INJOjNcHgFg7kbdf//9vcfQkydPW0QeGHry9Aqj//qv/0KpVML69evx1re+dZOhSatXr8YJJ5ywRR4BgpW77767LtNhU1MTLrvsMgCJUvre9753o3dsfepTnzJK4cc+9rG6e+9uv/32TSqeDz30kAk3nDdvnvl8YGCg7l7ERvSzn/0Mq1evriu/vSifz5sxvOmmm/CXv/xlO7coo0aXxLt0xRVXmOcOPfTQLX7XI488gre97W2I4xijR4/GRRddNKzys2fPNp7gb33rWw3bPjg4aMJNx40bZ7Lfkk499VQACfjitQpKN910E5YsWQIg8Twr5XI589n111+PpUuX1pX/6le/ikqlghEjRgzrmgMgAcpAEmY4VAg1EzK1trbWJXjhNSC33HJLwzW2cOHCjXryeL0HwxS3hNiHP/7xj3WXtwMJv9GDPmfOnI3eB7mtacaMGZtM9jR9+nQACR/xM17NAyRXchx00EEAgCuvvBIbNmyoe8/ll18OAJg+fToOOeSQYbXxvvvuM5lSL7zwwi3ppidPnjwBsSdPnl5xdMstt8SFQiEGELe2tsaXX355/OSTT5rvoyiKH3jggfiiiy6Ky+VyDCBevXq1+f6pp56KAcQA4gULFmz0Xa973etiAPEBBxzQ8PuzzjrL1HXAAQfEv/zlL+MXXnghjuM4HhwcjO+55574zW9+s3nmzW9+czw4OFhXz/jx4+Ndd901vvTSS+M//elPpo44juPly5fHX/ziF+PW1tYYQBwEQfzXv/7VfL927doYQLzPPvvEV155ZfzQQw/FURSZNixdujS+5JJL4mKxGAOIm5ub4+eee856/4IFC0wbH3jggXjlypVD/qxataphuaeeeqquX9OnT48BxBdffPGQY3zQQQeZOgDE06dPr3tmOHO2Nei6666L//Vf/zX+4Q9/GK9YscJ8Pjg4GD/00EPx+973PtOe17/+9XGtVqurg30/9dRT677r6+uL77zzzvjMM8+MwzCMAcSFQiG+9dZbt6i9Z599tmnPUUcdFT/88MPx4OCgae+RRx5pvv/0pz9dV37Dhg3xnnvuGQOIp06dGv/mN78x/b3xxhvj5ubmGEB89NFHN3x/b29v3NbWFgOId99993jRokVxHMfxCy+8EH/ta18z6/Wss87aov6dcMIJZoyuvvrqeN26dXEcJ2vjve99r+nb//zP/9SV/c1vfmO+f+973xt3d3fHcRzHa9asib/4xS/GhUIhbmlpGXKuTjrppBhAfOCBB8Y9PT1b1P4oiuL9998/BhCPHTs2/t73vhcPDAzEcRzHS5Ysid/ylreYNjbiAa6zRmtjc2lwcNBaxw888IB5549//GPru2q1Oqy6N8brpD/84Q/xiBEjYgDxW9/61rizszOO4zhetWqVJUdvuOGGhuW//OUvx9/73vfirq4u89mKFSviL3zhC3GpVIoBxGeeeeaw2u3JkydPSh4YevL0CqV77rknnjVrlgUoqODl83nzWS6Xi9/1rncZJSyOhwcybrnlFvPsz3/+84bPXH755fGoUaPMc/l8Pm5paYmDIDCfjRgxIv7Qhz4Ub9iwoWEdVKq1jnHjxsVNTU3W52PGjIlvuukmq+y6deuMwqXva2lpiUeOHGl9PnHixPj3v/993fsV4G3qZ+zYsQ3LbSkwvOeee4YFDJubm+NJkyZt9Oecc84Z8n2bQ+54jB49Om5tbTUAhz+HH364BZQb9T0MQ9OuiRMnGoCuPwceeGD8yCOPbHF7+/v746OOOsqqs6mpqY5/3vWudxmjgUtPPfVUPGPGDPNssVg0oJWGh40Bo0WLFsXjx4+3eFX578gjjxw24CD19vbG8+fPN3UFQRCPGzcuzuVy5rPzzjtvyPInn3yyNQ7lctnIibPPPjs+9dRThwQ2v/vd78x7RowYEU+ePDmePn36sEFaZ2dnvMcee1jyioYrrvmrrrqqYdmtAQx1DW3qZ7jGl80BhnEcx9/85jctuVgul6053JicOO6448xzYRgaYwXl/Nlnn93Q6ObJkydPm0seGHry9AqmKIriH/zgB/FJJ50Uz5o1K25ubo5HjhwZt7a2xgcddFD8yU9+Mn788cfryg0HGNZqNaPMzZs3b8jnnnvuufiSSy6JDzzwwHjixInxyJEj4/Hjx8fz5s2Lzz///IbtUOrr64tvuumm+D//8z/jAw44IJ4wYUIcBEFcKBTiSZMmxYceemj82c9+1rKWK3V3d8f/+7//G7/3ve+N991337ilpSUeMWJEHIZh3N7eHr/pTW+Kr7rqqnjNmjUNy29PYBjHseUx2RQw3JyfTSmom6Lnn38+/uY3vxmfdNJJ8R577BG3trbGI0aMiEulUjx79uz45JNPjn/xi19stA72XX8IaGbOnBkfe+yx8UUXXWR5f18M1Wq1+KabboqPO+64uL29PS4UCnFTU1O80047xSeccMKQhg2lvr6++FOf+lQ8Z86cePTo0fGYMWPifffdN/7CF75gebGHoq6urvjDH/5wvMsuu8RhGMblcjk+6KCD4m9+85svWmmPoij+9re/HR966KHxuHHj4pEjR8aTJ0+OTzjhhPjOO+/caNnBwcH4qquuiufOnRuPGjUqbm5ujg8++OD4xhtvjOM43igwjOM4vvXWW+M3vvGN8fjx4y3D03Bp/fr18Re/+MX4gAMOiMeOHRsXCoV4p512ik8++eT4wQcfHLLcqwUYxnEc/+Uvf4n//d//PZ46daqRb8cff3x8xx13bLTcrbfeGp988snxa1/72ri5uTkOwzCeOXNm/J73vCf+4x//OKz2evLkyVMjysXxVr4J2ZMnT548efLkyZMnT548vaLIJ5/x5MmTJ0+ePHny5MmTpx2cPDD05MmTJ0+ePHny5MmTpx2cPDD05MmTJ0+ePHny5MmTpx2cgu3dAE+ePHny9NJRW1vbsMt0dXW9BC3x5MmTJ0+ePL2cySef8eTJk6dXMeVyuWGX8duCJ0+ePHnytOOR9xh68uTJ06uYPMjz5MmTJ0+ePG0O+TOGnjx58uTJkydPnjx58rSDkweGnjx58uTJkydPnjx58rSDkweGnjx58uTJkydPnjx58rSDkweGnjx58uTJkydPnjx58rSD08saGF511VWYM2cO9thjD3z5y18GAPT09OCII47ALrvsgiOOOAKrV68GkCRYOOecczBr1izstddeeOCBB7Zjyz158uTJkydPnjx58rQj0rPPPovDDjsMu+++O/bYYw9cddVVALYMxyxcuBC77LILdtllFyxcuNB8/pe//AV77rknZs2ahXPOOWerJJt72QLDRx99FN/85jfxpz/9CQ899BB+/vOfY/Hixbj88svxhje8AU8++STe8IY34PLLLwcA/PKXv8STTz6JJ598Etdeey3OOuus7dwDT548efLkyZMnT5487WgUBAGuvPJKPPbYY7jvvvvw1a9+FY899tiwcUxPTw8+/elP4/7778ef/vQnfPrTnzZg8qyzzsI3v/lNU+6222570e1+2QLDv//979h///1RLBYRBAHmz5+PH/3oR/jJT36CU089FQBw6qmn4sc//jEA4Cc/+QlOOeUU5HI5HHDAAejt7cXy5cu3Yw88efLkyZMnT548efK0o9HkyZMxb948AMCYMWOw22674bnnnhs2jvnVr36FI444Ai0tLRg3bhyOOOII3HbbbVi+fDn6+vpwwAEHIJfL4ZRTTjF1vRh62QLDOXPm4O6778aqVavQ39+PW2+9Fc8++yxWrFiByZMnAwDa2tqwYsUKAMBzzz2HnXbayZRvb2/Hc889t13a7smTJ0+ePHny5MmTJ09Lly7Fgw8+iP3333/YOGZjn7e3t9d9/mLpZXvB/W677YaPfexjOPLIIzF69GjMnTsXI0aMsJ7J5XLI5XLDqvfaa6/FtddeCwB4/PHH8drXzkYcA3EM5PNADjGQ1slQ3cHBrHw+n/xoGcRJmcFB82fyOYBaLfkhjRiR/J/Pm9cglwOiKPk9YkRaH1/KCoMAg4Pp90JWO7TR/MJ0LIcYOcRx8q5CAaaBg3Eeg4NJu0aMAEaOqAHValJ25Eggn8cLgwFqtayNbHscA0EA5Aaj5B92lh1Mf+JcHjnEGKzlUKtl5aIoeUUOMTZEOVN0cDBtIwcriuThbIB1TKIoG++BAWDDhqw5bPPIkcl7w7C+uXEM5Gvpe0g6eYUCEGTjYJ5PB4Wf52qDyR8syzkcMaJuTvg155+/OZ9B4PBZyjCsksODWi0bDI774GBSIfmJgx4EGMwFiKLskUIh65OOl+FJh+dyOeExToSuRXZAn9EKRowA8hnfDQ4mRTi97Fetlo4xywlfxchl7dC6q1WzZqxxV17K55Pv6zolZAbXHkKXZzhe7DLbzyU8cmTCi5wenW+tI593eF5flBKXQVMTkItTRlfixPE3mZLdRM6w98iRyBYM+68L2yUKP8Po2bPRYM78y2aPHJmNa60G5FHL5r7BmHO8+BH5Os7lTRPJAhw38o3KW1arLMnhUPGYzztjyMqUp2u1ZFIGB2EJePKXzo8yBz/nS3UT4WccC9bHRunYcy5Fhisf6n7DYjrlKoZHjADMomdhPsR362KX9SGiJ3tJun7NnpV+SZYy6zdvl9VlVrfshF+UVVgP+85HzfDFtaxyl4fdl3Cs+RkXxKbkAex1zaFzH1f21mHmlLvLU7/TJurcuc3SOeaYKGu6a1E/29jwmL2HDXeFmnZa14PL3/x+wwb7M3Zexzp9aYyc+ZfVcgy1zdpeFV9smq71ESPkISWXoZ2NTt9r6VYpb2p3XVZhNWZJ5+L6QXZJhFmcS16Yi2uZUubISW7r1Bm4pNlebn0qNzkeOl7KLypHVCy5vKTjrlNIasS3jZ5V1srlkHUEwNLly9Hd3V0/Ti8R7ZLLoX8Ly5Z33x2jRo0y/5955pk488wzrWcqlQpOOOEEfPnLX0Zzc7P13ZbgmJeaXrbAEADOOOMMnHHGGQCAT3ziE2hvb8ekSZOwfPlyTJ48GcuXL8fEiRMBAFOnTsWzzz5rynZ2dmLq1Kl1deqk7bNPB/74x0WoVhOgEEVAb28KjkYCpVKywPKoob+aR7Wa/F8qJc8GAUxZfsffrI/fF5AoH7WggHyU/N0fFainI4qA1auBF15Iyowdm6yRMMzeF4ZAvtoPhCEGojwKQQ09vXmUy0kba8gjX+nLOhuG6I8KZt9rDvqzxgIYCIro7ga6uoDWVmBa+DyweDFQqQBz5qC/PAXd3cmYhGHWlnIZSR8qleRLIBP05TIGwmbT97QZFtZqLtWSculg9ZcmoqsLGD0aGDcOKAS1pO4oSl7Y2wuUSuhH0YxndzewfHkmoEeMSMYOSIrMnZuOVXd38p7WVpjOsmGlUvJ5FCWdqlTsvrDhOumVSvI/6ymXgRkzMo2dz6f114ICVq5M2lkuZ1WMGAGsWWOPaaWS/J2PBpI6OLZA8mW5jFqp2fAjae1agHJJdZz165MxIe+0tQH5rmXA0qXJWIwYkQx4ayvQ1ob+oNnMt3aDQ8XmkBc4PFwnzaVU+ler2ViEYTJWWqBcxgAK6O4GprTVkraEIQbCZqxenfSFa6mlNICeSgG9vUkzm0spn0cDppEDKGD16mTN6pTx9QUMmLVWqPTAdDIIskkplw1oNh3Vxa0MTP7RxRuG2Xf8nBNC3lH+EB5BqWTWIllQ1w/nUvYerF+f/Cb/R1Eyv2EItLcD+d6erP3lMlaszGPChOTZfLUftbCYGASi/mQNpnKCzQqCdB1GEQZQMCxYKqWfA6ghj0olaxv5rbU1mweWCQK7bwTKra1Zn/huipUgSFiU/VZ+1HayH7WwaMpXKtmUVCoJkCaIGTkymW6KIOXnfKUvE+DVarbew9CSWQjDxEhUbknen44Vf2qlZjPWAMx4V6sJDw9E+Uymp+udMt3wNweN79TOl0qoIW/NmY43i0RRwu78O4qSMef/GzakMjfqzxiuWk3WLPlTSWVjGGbt42ecbNbDzYM8r98HAfqreaxdm/BNUxMwZgxQDLLxYL9YPQCsXGk3ifzRHA6YCSXPsp8kjrnuzWYeUMseogDS/9mAKEItKFhtY3dJHLZ8NFCnFLhl3Tby1WvX2jxbrWZbDoe0gAFTn5GJrnxCwn+GpwDDO9oOvk9FNcedbXJFHeXQyJHJb92yyuVEfps9uFpN/taOjRplL0B2TgdEJ072YtNvnTckOpaqJaUSkO9+Pqsjrac/KmDtWuE5RwByjApBzd4DXMWGkx1FGAiKZlwUPHIOVbSwyVxuui0ohWGiGwH1srAY1rI1yPUIAK2t6KkUjBrFethUto9GxlGj7OfcNmq7+Nz69VmfdDjWrk10m0olkS8vvJBNa6mUAecxY9L2A5mcTeeo48AD6wfiJaT1AD64hWV/OGoUFi1aNOT3GzZswAknnICTTjoJb33rWwFg2Dhm6tSpuOuuu6zPDz30UEydOhWdnZ11z79YysVbI4XNS0TPP/88Jk6ciGeeeQZHHnkk7rvvPnz2s5/F+PHjccEFF+Dyyy9HT08PPv/5z+MXv/gFrrnmGtx66624//77cc455+BPf/rTRuvv6OjAn/6UTCgVCWuDd1YqBUUUJQxNsKhyoqVsb/qkPGpQSTwQJEoMBS4XSF8lbwFOA+rCRHBRwaAC3RwkisdAUEw2d7Y1LFp7e3PJVsA7O5MNdvJkYFqwDHjwweTh3XbDsnAmurszmdfamiqE1b56bSoFbKoztbYCRfTbA+NqijIGhUgAHADMmGEBaFQqeKyrBWvXAjvtlCjAUZQq+Sqwe3szVEP0NWqUjbra21FrnZiMeTBga1CqAFDAcjOi8K1Wgc5Oo/3WZsxM5jcF7D29eWzYAKxalVWrOoYKU46rPheGtuJDQFmMEoW1H8mYUecqlzPcwWkhX7lK89Kl2VC1tqabdmdnNvbcmFMgbojIlaBJN3JkAIHvJG7mECobjB0LTJpQy+aouxsGEQVB8ne5nFmagWQO29uTHy5UzomCuVIJ/WGLqXLGjPrx7ezMWIRd4t9sI6dZ52TDhnQji/qy9wMYiPJ1LMh1QyzBYQWSTXPChFRRIfBwB0rXjDZIX1QuJwuhXEZfVESplFWzfn2i7AdBypd8T1tbYvhxFceUiQbCBMwUghr6Knk0B/3oR9ECYXnUDIDpq2RyjvKLvGAB+HSN1cJiIgeptZVKGEDB8LJrr7FkcTomK1bmMWqUGFBc0MTx6u1NJluBfWtrwhRpZwaiPFavBtIoHjOGs2Zl1UWRrUQRrBplUtFua6uR3wQaBD5AZqRhX9vakuYY+V+tohYWrT2FU8QpJD8HQbYHkcf4vA6D9oO83tsLC9CTZ8aMyeQJxyNf7bfRAIABFBJDJy365bLhEwMwie51kXGs2CASB4yLRC1TitzUCMOOpPX3RM3G/qfrHai31Zh9RdawkgJtUyYFH/3VvBkKA0j4kmrVGAN1/mgU1gotMMfvFJgrEFVhzv/TcRiI8kn9KT+7INq8Q8feAblqaKY8U95oBFwVKDaS9yNGJGuGwxKGmcGIU22APPcBXUtqRNCJ1PknqX7BhrmbaiOkUy7bBrK0czp/2n8VNRy+QtSf7UMk1R3DED2VgjUuxMIuOFRn/eAgrHWtXVNbo9ZDgxDVICBbUlyG/G0MUoDpbzHM5l8BJdvukmuU4jjRUO0CUr63VErXhO5pYYhauQVdXck4HHtsx0bB1tam9lwO525h2Rv23XfItsZxjFNPPRUtLS3mZgUAOP/884eFY3p6erDvvvuaLKXz5s3DX/7yF7S0tGC//fbDV77yFey///445phjcPbZZ+OYY47Zwt4k9LIGhgcffDBWrVqFkSNH4otf/CLe8IY3YNWqVXjHO96BZ555BtOnT8eNN96IlpYWxHGMD37wg7jttttQLBaxYMECdHR0bLT+jo4O/OIXi/DCC9miomVHcYz7mStz1NGkBiTVYSlUqKQbZUCFimvqZuEwRF+1YCn/LaWBzBycaqEDQQIGuSDb24FC5xKDQB5+NNkAUwcR8p3PJN6jahWYPRvLgml4/PHkla99bWpJrvTYXsF05+2PCqbvVKzzlb5sU29rQz+KRrEiGOLfRjhwV0kHrlZuMUPRXEqUz0cfzXABkHq9+GJKRk5gqlUu6SyYcU+dMhZA41w2l7I56EfRKPMbNgDr1mVy69FHLVyPcjn5rr09GUv1rJI4rU1NCaBNcTnGjk3GgM+TzxQUjhmTtXXpUuMwRGurvcfrhutuEEGQWRotr0AQGO8crZrGeNDZmY2tKiTq7qQGppt0W1vGnARq6XtYRJ0HrK6rK8OhpVLSXm6cQGZJnVJO2j5QajGKCy2RxlNJ1wgnUReqWiQB20OoCklbG/qreaOos4/9ke2B0PVvPNMkHYd0kgZKLaYcFXPVeQkki1FfNpGu2TtVcAZQSOaytzcD1lzYM2YAQYAVa4uGj4qBKJ9hiL5KIgfMuFGT0Pkmc1cq6C9NtKa6GNZszYPMxkmmnEg/N6ABYpVXsKtWMI45f9MYoGOr6IXjo4vbVXz5OZVPlmcdQYCBoGjmhzL/hRcynmUEB9eKLgW+kkPhEtdma6tjBCuVUGubYryKrKgWZLKeALBuXEqlzCuZAlAVhxxO177p6tP5KPM4rVyZyDwOM59h/6rVxCAJZB4i2m/U8cPhDwIxENCggAEbQfA3haMrqPVvhi3InqdeplqpGStXZvuL4VVkBhwl49VDrc4ow4gMZSMaKtTjpw5lGk5M5E468LWgUGcYtow86frWei0vlQJkeSG9ovQy83HXk+OS7lFmTXIenLpJLtDm+GnkhgF4fElqqOOWwj2VIoLeRkaIzJiRLHfVs4wHneNXrWb6AhEMx1BlrjJwEABtbUa3yFf6bEHMxct61Bilg8i6Um+9voaP6RbjAnY+wz5Zc+2iLFYmLyB/8L2cRzdwi4FACszyvT3ZwLvGFhp4Uz5Vb7I2SfVPy+AhBpYgcIyRimTZGBd1A9n4p591HHjgNgWGO+Vy+H9bWPZ7GwGG99xzDw4++GDsueeeyKexs5dddhn233//YeOY73znO7jssssAAJ/85Cfxnve8BwCwaNEinHbaaVi/fj2OPvpoXH311S86NPVlDQxfatpjjw789reLzCYXhjDWXUY6mNBGFxGqR4lanlqyZLFQyNM6BQwhkFlvqogPBEUjG4rBgAFjBoAFAVaMmIJ167JIySAAprUNJGiitzcJCUURixcnr5oxA2juXpIJ8fZ29LTuikWLkrIdHUBz1xNZW8IwkdZBYIHTclmArQjX/qhg2tHamnoZ+a5SKftNNAMApRKe6cxCdWe29Zv30XLZXH3ePEvPQ09v3tIxVq9OFOF0H8isekGmOAHZ3sVo0I1FTamVi7+XL0/aNGlSojwqK8ycUcsUULroWFF3tx23QdSqPMSdnbslB1K9qJ2dWXhmayvQ3o4VK/MmNBWwHZwc17a2zEvJZxiGrKGp1Wqyia9Zk4FLNocyPl/tN6G9QPI811FLWRStrq6kvQwfSttrgFk60CtWFwwQ1/EHsnkdPz4Z72ltA+irFixPKVAfbqkbmdZZKqVriAPjKmVRv/HMqmUVkFBwR3GtlVusTdWEQ7MSdYmJ2VYt9Ow/HSGcBxqllCddw7nic6N8l0pmXMkqnZ3J8NPCz/GoVlPe5ZiogUrBYopwBlDIIgjK5YS3uei03xzUdI5feCHTd0aPzsK/W1ttJZ6K5JgxwnPpPAyggEJQw7KuvPFMqJNJgw+oh6xenXhq99jD5hEDvJApNpwq1Wc4JMIyCZBHvxWdEYYw0RYc8yhK1gSVd/Ik26y8yvc1NdnKXRH92RiTSdgwampq4NDFocaQMDRhhQawcM/RxeTWLeiyFhSMxxFIPeDRgJHX69Y1NqJp33V+VE9lGbWNqgwj6fhbngd+kf5twKgQQY+7/XLIDCgTZVyrN0BeFyIr0QXpkqJ97Qzbr51v4HnUJRhFWXg0x9jFRS6Yc7GoGrw5ZIWo37Ye6Mu1H7o5uiBNX+yCLwm75N7W05vHk09mRyvU5qs4LQyz4yYmiokeO9fL7DKK6C+cHhMxxA/UMtSoLzp3OocqiDleKqgVNSrSUv4B6gAkf9Oo4k4HfyzPPsdX+YmT746/8p0yjxu+rszHZ/m5ThLr1b6xTbr4dXEjWY8cBh6F6jj88G0KDKflcjh/C8su3AgwfKXSDg0MOzo6sOjee22rUyMrHRe0Cn9usKlSrXKAOlUxFEURA5n5WXciWo5hn6cIgkQg9FXyWciFfLlifTMGB7PwolIJaK4sg0GAs2djWTQRS5dmx+CKf703US5mzQLa2jBQajGPt7en4EvBSupdoAWypVyzhWbqXSGWMWGPwUAGjtxYPmpKQWDCcox1Ne1jTzDRYJ+ODqBl6QPJ9ymgYLiWi6Up+/iZfh5FGXDmWRYqZ8SplIMm7JaFqtUE5HHuNmwAXvMa28rV25uZ04miqBlS43BdCpxPAmZq66yXgHr9+iQ2lZtfa2sm5PUzMoIruEsl9IRT0NVlH7lUHYqKBWDLf3qbjFGCFvE0dFYt67Tq8ozHhg2p0kiPmoaWifLWj2LiKeN6oJbNCUkNGNbaUfejag4aU8mGkfdSBhlAwfBHqZSBLwUiDK3T/Yzn4hTDRxHM+UYgq4PTq+KDTVDPKLts1oHMnWVVdg1JojkpiCUxzE3lz7LuAqa0pTKllBlLNGyIrAhkxqZSKT0LmjIG38eQIYa5qxDsjwrG20uQU+h9PpN76frXcVLRy9/03LGNDJMdOzZpI6M92PYgSMeRnRAmp/eC7DelrWbaGgSZAanINATq0VKEGIYmZDYMs3NebLPl3eDaR2pUqPZbgMOc+1L5znanAzMQFLF6dSICOO6TJ2e2tXy1P5MbXB+q2LmImWNCxkvXhHo4jFJKj5AyirrJZEzqQFKpZJ1dZVHVD1mFgmT32KLqpfRQ0iNGg1e5nHpFyHSNkJK+WBXZ9EUDQdGcn60DBLKYec7bdIjzxXKK5hQMpGuazdDprjvCwjFWy5auMbYr7Q9BhYtPtIuunh8EMFEjlG8cV+u8uP7Wl2hFsq4BmH4GQRp15EahcNIdfYJynqCYhrkBFEx0CQ03Oszy6rotlufaaIQiuyp7KGDU+sIwO1NtecAE0JlK+Z02QMdJX0jSjYTjk4a4ujLcHXYWZ585tGbN6rEfJ8baCvPXfjj9IiDV+tUQq8Q91I2uM8bVRjq0rAc1wG5rj+H0XA6f2MKy3/TA8NVFHXPnYtFPf2oLdV28KeMC9fu2YXi1HqqSSq1TzV8ixAFYyqmzf2Rhf6nmOBA2W2fF0v0cxe5n7BPfs2fjscUF45zaZRegJewHfvObpK7Zs1Frm2IcigSN+d5UeLe2Jop6WLPPy1SyM25c3+vXp4o/rc5qHWxrQ63UbHk/VDE2QqlUMgpid3eCvzo7gTlzgL3ae5IP5s41nhUOcXd3Iuss0Nrba+LUNTcMQzCN5ZjAg4JTAbumj6Q5tlSyM3soymS5SgVob0cfmg2m5FxGUaLI8ozR6NEJeKDSXSrZHhwgY510SiysyHFQA2C+a1nWDtWyyby9vUnbW1tRm7WrYRkOBeeIx/s0mQA3SlXYxo5N517Dh9Uqwne3tSWW+1S5Ve88DSd6VofeIo4DDQ5hmBkmBsLmuv01isRLpzunoh5ulmwAfzcyBqkio6QoxH2W46+ah1pqBSSQmDDFjebkZkk2VFztOnH0fCSjrBQnk5rDAeMtIQ8ZEBQkFnXNu1OpmOmzlAB6iDREbsXqgkmQMWIEMGlcGrXAteNqFqlsNXJAedUdZ50HjcNVNwgRH+ecBwHd+SOachVsrnMZUMq/Ypgp7TwGQHYy8ieUEFG1UAF2GDbPOzvoiGctOY88w8khYIj5pAkJeJXjfRa/cO5NqD4yizx5woQhN0oM42rLAmaM4kkgymfYDxcwhqEdYs2G8dnUQmWFWqpireOoyJLfpYZJ3f64L5okbK7hiKCrkaKuQptWQ1XYacVhP/is/lb54wJDlUnOhq9zZPZcCDjTsdH61ajtIgYJ39tY6CObpmIyiuxj3hqaqq/RcddlGgSZp4v5EEqlzLDIZcJhNfoHYOcKCALrTDJaWxOeaZuClSuzZH2KrVwxPGJEIrNok+a+unatbWBQJ7vrMGNdGsGs4cGNwjyNbHONNDrIOpj8X+WhMgSVJ1fX1MlQa4uuxbReAzhTRuD+oyDUfK+hExwgbja67+kgKY/Key0HgbbNkTXUjQ88cNueMZyRy+GiLSz7Px4YvrqoY968ZEKrVXPGxF1vuh6VdP1agI6W/VRSDiA768aMp0CmXBnhrlqhhEtSG6whbxTDfPfzdZa2ZdFE/PWvibDbZZfEKdjc+4yVZZRJZYIg9RCWslj3fKUPfUjOg01pyxR2DTHUvSwfDdjCm57PcktmKUxj6SuVRG+LoqT9TU1ZuBGTP3R1JWBjn32AXXv/lBQolxOEmCZ1aI56gHIZz3Rm52mefTaxnjc1ydnFal8WbklBxbgZpuHjTpYqGBbaShN6UM/TbG1Tp2Z4keFv9KpOmpAKVCpDruVYlV4iLVEOOdbUh7inaFgox49eKXfPUWdZEEg4dLUPBjEzFRtRRmsretBi3sW9RG0brF8xp+4TqkfpXhQEWcgTN+ZiMGDHS2pMo45T2rm+oCVR0IMkXC0MM+cssxkScAIZtie5OJnKo4bUms2+tydrfKNwPB1gVqYbsAoRtSBrn9RKqxsmNQ9XOdBNmtZf8hDbqh4GtofJptJzmarD56MBoKsLtfZpyd884xUEGcBRZZfhvwRIqddEz6No940HRBlX+813KIBKPQVWghogS4ikynwUoT9otmQ0lVkqi5wqvkKHjG3VjL6aLVSPFCiGayk7/RKZ3dObRTIUgwGj7DNUlYBO9w2KHNWr6IU0L5ZNiYmGoih5htl91QnoZqwlRgayfgEwYb10JpgkJQRAgSQMiiIzN5otlNNpvN0p2CR/MFkQZT8BW3/QXOcl4F5p9hbV2AErKZYVBpuugX4Ujazm+1y9mwYpi1kFVbueXO6DlPFAKk8ly7jqCupUVdZWHJA21/xt1kr6hQJxa4w1WkMrUdnCz12kBFheaAvpBHbiGiW3Cv1cidVZ8kX75HrIkXkVo8g+PWEM7i5o1w1R508NESSVvdysVOa4LkPdBMplExYNZPwkal1dn13QzN9WkhWRc1b7+H8jYAXYxkxlKFq80880cz4gkRw0wEeFuqqt8WYnXWODGnK0k66VgeSCUydqjDoh5TXlg3qsDz982wLD1+RyuGQLy17tgeGrizr23Rd/+vNfLGurLhzd3KtVSfgSBFYyCkDO9aShjnqwmnKpUE2tmK4SllrB3A3XshjyCy7cUgkDpRbcd1+2X86aBUzDM7b7IU19t6wrbxSI9nag0L0MpgOpRycIUsU4FSIm6YGiEyKiVGCYxBJBpvywqcwTQMeBGpDVOF8uAzPLPcCiRcCTTyaZWubMQX/bzGTco+eTSogstH9EurNmZW2lG4y58GfMSMYhyNLyE4ur7sWhZqjfpDFyfkE1OiBDFvyeKIljTsGdjgkzfjFci2cCOQasWj0ALUGf+VDPXZmMk1Sq2AkXFaYhynSyMGxy0sge20VJfuSmqSGyugumE1drm2LsEvRkqfOGNHVqIuiJKzo7ExA3YYLt9GG/Nco0CBIviTnjC2BZV+ZBoa64ciUsxVM3cFo+1ctDDBWGmcVY8R83Kt3rCB6U7TjdOuycBrYDkPNKfCDlHa51871mjWL6adVqORcaRsw6uQYovNgQyeTQH7aYMVnWlUdbm20EMAYtfqhn2ESJtBKIpJ9bACjtY081OXfn2j9GjEiMQuxae3sGZnjlBROg0HDkOv4Y/qZZ/GhoqlbtG2hchxj/prOMGEg902GYJgHSRBo62W5ItDAXwY3qVkCWbNdES3DulGHd6zBUoeJ8yNmBgVKLGacwlKQaQZZcioYTIFl3UQSTfdKNUGBd+lubo8CGz/CqCcqxKEozZatA1YFQMM3PJSmGJixjm4F0X2KjSiUDkDmPRfRbskoNvYoN3CaxXxwTxVMceiqspZL9nI6FAicD7JWk3xYAJgWZt0R1f/c3+dnKyCvjqXVYyj6Z0jVWqrUozDzXjZR2JSrwKp4Ul+krdAgUWGlwiQLDRsNmjW3QwJPqrsVG4Re64bAB7p7poj5d52Fo6WhcltoE18jDfhmeCBono1HSvcF48LSdalXi/2yzNo5zm+oB+Wp/vfWWz+sCD0OzZ+qrrEzE/EKtq/w/zM7OkxhZwTqZaqFUahCBUC6j45BDtinYmpnL4dItLPtlDwxfXbTPPh34wx8WWXsU4KShBsxiqrUmd43Q2m4pUdRW1XOg2oF6AtIkLUCWn0TvA9KEj9QPmE65L8quHaCOMHs2UFz6WJI6s1xOLvErJWe3qG+GITCtvZaBnPZ2KxW93lnGRA357udta1VrK/qiLPRNu8sjhWvXZpnHgASTzZoFNEOyLbJj3d3A44/b5xHnzEH/jN0BpJs9LdDl5DxkayvQgp5sXngJI4X/jBlY0lkwQ0/BzDEtlVLAxU1STbvq7WMb05BYCjSGdnLcOjuTYsxa6O7BCnJ0k6VQJAuNHSsbSHo/pYIQym11pKjRLgxTMDuqL/tCXY1BkCSwKbeYNodhBtTy3c9nKE83WvVYkJdp7lN0ryFinMswyaa7dGlSlJimEY7RI1LERRwTPZop0VGZ97y11QBgfqdKIbuipDqVjqEqYdKNRNFClqSEz6jiCWSZ9/g+ToHOYVNTGmrJzVs1JgFiqqjqub9SyUmeozLHzcaqWouEs3IdM/OvAjOGrnL6WZxriGxQjPpst5yroJFH0mf6kHj4eKWPKh5mjFNvCBMbtZTszHeWMshDR4r+SORDARPWZLqKsZ4VSztqEg1JpzXskefymAzHCnlT1M36uXZosJJ36jkiBa0G9OlZPzKny9ipQmedseRclEoYKE80/KqeNV0DxL/k2UJVrmfROSXfqheY4CQ1MkaRZJ5W44ijhA5E+cRQyYXPzrNeF1wyHJf1trVZdwIbz6cLFkSW0ZgBZF5UDXPXYhpyyGaobNHPNEOsNjkIbC96rdRsPdMwlNYFfZIpVJc3Q/IBJ8NqGFqf65nlundq6DxlhYtMdQyRefw4Rbo1KEZxl50FWEXRce935FC4xjgrw6sLhvTvBuucY8A2azECf7MhuY2Psggw47V1wKK+nmCaUQfMEE7SpGKNhrhRhtAoapCplQOv4DHdIE24vh530Mr4MgG+WhWjcTjMakRnW0hsk3qCVU0AnPBa1U00RDUMt3nymZ1zOVy+hWU/54Hhq4s6Ojqw6Pe/zwQBhaFq9aowKIfreYN0oxsImzPLe7pga2HRrEmei9cFM3q0JOhwwqeYch6wM70FgYAAugzb2hJQFSZW5LVrgeeeS3QQo4im1u6B9pmmuxRy1gXMQb/pEzPQ0QnHpA+0/hBncpjGj0/PNQZ9CVBlrmpKGJU4Y8ZkZ5BmzcIzXUmmyZbo+QwphCGWdBXR2Wky8Vs6liYJoTeNx4h4UbJpoN4Poegt1bZr7dOsa/14lpP3Eq5dmyW+oBdDDZIugOFmxlBK99wDrdCrVyf1ul5MzjXrag4TJfmZroLxAkrzAWSOJ9Whxo8XHuN4iLWvL8p4lJswy2hb8qhlhzcp0BW1ALZWRQVYXHy8EiRf6as7j0dea0bqWSevOIPBzZ19LZdtPmCVPOtJjwn5lqGmqhSog4bLkGMB2OAOyPZYruOmpiyEkd/rPc5r1mT16CY7enSytplAg/ymFnkX75RKaXIIaUBPb3aIn201SatoQOH5WBUkra3Z5ddsuFBflCj5moRIAbhJMEQw4lrZ9DwX5awuYr7TBTm0MnHSHPBhaYqcDOVD4W9rwN0BVY2VRj45zDkQNluhmixueU1TOa/hb1byjFS+cv5dvMNznlYWanpfWT/yWLkykUPjxzvZslOgz8Q8rpcPqG+vCq6+aqHOhqR6NYdQDQRhCAsgq1JsvDrV5IgGIx30GhplQ149Y/apILAMB1SwmWioBT12ll/OdZot1zX0KIhj5Ib2z7ouRAZPr4NQA46JplGDgRy9cMdfdWBlTyWV82pQNACObROeoPFE2dxZvtacaBsophUwmnOZLiBUEEdyEQJlc8rnKh+V3L2NP4UoS8rkGuZ7epP2UW4boyAcgMQXqHxzN2llhiH4DMh4VcdfQVod/4gMc5PF6LhrlIObHXkorKtrxhWvJNUprfHTCUgrczOc6tcWv6XEKDDuZ8pvZh3IGjAd1g65rl82tlQyhkkNAd/WoaSzcjlcsYVlP+uB4auLOvbeG4t++cv6w0bOKqXHSL0AapBWvYLZr4gv1QDX1paUz/f22CEPgG2iFPfWivXNBhSaS8kZnwkkHq0ZMxta6oxHpVpNPIRyUJ9KqGZVLUT9CZDjgk3PHDIBhva7tTW7rHvGDLkT8dlnE02XGmNbGzB3bt2ZJHpAGfJTDLLMfhqtVakk10PstlsKGKh8BkFSN4EKJyAIMhTLCWttNe/nYfjnnrOHX42MTI7WEvRl98TxAb3zgSArDLFifTNWrMjKm2QULEckp1lkOBGcXN3BNV6SzKcaJZX9chn9bTOxdm2WtZAgGcjuS2xryxTKILDvL8tX+oyA5sZCBccNiZNItkQB5L1s1IK4a0dRdkcmEdasWZnxhZuFvkSRltt/vlhdcCQFuhwjOWDkhpKaMK/0Q/UIk23Mhi+KeRRl1x4Acl7GVaAU4KS8qaFtvMGDui3PxelU81kNTQKyMErFVbz2Qc9aBkEWvtPamhzVbak8k427ePIMiHcVQo29VE0vnWM3HJZ9DMNUHqgmrIok50qFZAO5C4h8oAKSCgbjpQOsc9DsTnc3TCglq6THmrKPyZAoZxgFoUYAvWqI891XyVtyQ+W+Yt40eh3d3dk5v2IghsOUh3ntjpYj8dyjUdhE0TPei65lWcNJra0Zg5XL9lVJ9G5yPnUzI/NRJnFu0jnvr+YtkasGRhrqxo3LpnD06MwYwxBhek7GjMmwP6NM3CPgQJZ4B8iUR6VyOYmaKVR6bGTLhqXKcBAkddFYQ+Xf8JeWVa+3bg7CTGZeCKjYac0MpPVog1Pm0Tsr3f0bsL1OCio0tJXZvQHbk2UAHxNFSUZcXcrGq6svbuAJNqRo10VKfF49junaVsCkYl+rJW+43lstM1ReKW2++78+y2l0RbXudWR7EsfQtSsBjufVfXlaCcvyY/64Ibp6LljPzTuBAaZNCm6VGgFNoN47rlNm1asTpQBbgK/KLPKm8mUjz7XyurIPj7nwbuJtDQx3yeXwxS0s+2kPDF9dtM8+HfjJTxYZJlWL/bp1NvBz9RY6Q0gsH0WpNZ9KDL1UJFaiB29I1AKpSFNTCYIsZpGNbWtDbfbudZtmb296NUWUJhtJNZxaucUkmAFs/dxcSFoqWZkJ2UwqmOWyeCp7exPFnyAMSPqSAsEVqwtYsyYbF3abyq4OQbkMS+liWO26dclGvv9ufZYHEUgyBnLPZcJNzX7N8yd6Zsk9U8P9q7UVmFLqS/pDkMP5IEAhM7S2mkvbacGc0ip3C9JDyiwxvIwsDJP6N2xIzlDqbhcEicTu7bXz72vWDFXO1ZhAAwGVjSDIXKvp4fSBoIgHH8zAB3HU7NnJdFmpyavV7I5ETpKOQfqugXJ26Xm1mt2zKfqupVtEUXquleBadseBUkt2nUtraz34YyVyFsnaiNUbxfFUkKnPamgQmYJ1uNqCWplJtIqIFjEQNpuvLdCpioIeqCFyUcQ3a1bijUiNN+yOnrXiHV5UwileGAaqXXSHh+Bk8uQMB/b2puuZYa1crIAdmuZqc+m6YBKB9esTjyhFHpUEelDpjZ0xoz66Xu/802FThUV1E65h4qBqNXs/h5ihfyRdQuRFVUA5pfTgErAwYVKh0pMpRc69djrFbE9rq0Rd8IXCS+qxMgoUs3Ol/Mn1xf6rQc/KxJzOVb7aj4Eg8daYOtVKr4MchibjqvKIdfm8htJp9mY1/jBpl4JKDib7kYJXIDt9EUWZuNK79ICsn1PaUvDKfY9ULid371aLRlysXw9jlLOMX3p2SZnIdbOl8+oCMx0fV4mlh8vUwQIpE+rdbKqgR1HmgdTQSVZleYv5ZalkebZYF5DxAtcF61Lgq8+bc6jppNNgoOtM73Gs4530YQ3J1D40BEmKQrUxYvB0QaMayyiyKeZ5rtVtN6tlhA75C7CNAdoEbQq3O46fG7WhBjuSxQdaofa/kWFBGxyIt81FpzSQ8T5sLiBduI3QasozDDvVPiowJjAl0Ob4N2iCqYMefu0ux1q9oHo8ik1lHXqtBesw0XbBtr/gfpdcDl/ZwrIXeWD46qK99+7Az36WTCgtFprNEMisUxo6YyEMIFtN1FaITty0ZIBR2CmQ9fJ11VHDECj2LgMefDD5cPLk5MP0SgS3emZpnDS4zKzwWtsUs7fuNcc5sE3tMd30a+3TzD13aswPwxRo9i5LQkMZv8cwrvZ2oK0NfUELuruzs3T0kAaBk+gGsCz+VC6Jb/huAm/j9QQwUJ5oxquRxZFKE+89U+FPnBQEYrUHTAiYhuVoWeIiCrVCtS/J9Lp8eaKtU3FavTqZo/RKCL3/Echw9OjRCS5UhTmK7Eu52V6OXxBkgEPP7FExmjEDKFaezwbRdWeTianMtbbimc48li9PPKe9vQkuAbJD4Ux4Vgxr9uVR6lUnD3Bz0sODCmb5o1l2eC6U4wckxovu5xPFSq5nyVf6jFePSoCVURdZeJiOYXPQn1kLyFzqKXFjRzkhXCfsp6IR9k9dexwXV5FSwMr69XstR0RFhlFlWABDHeohsT1Opjoah/rad8fSpVlTiLHb25Pfei+gijO15PI17e2J4WkgbDYY16x1DKCnUrASm3Z22g5ldoki0cX3bDq7QUyibMVsu5xrDveGDWl2YBbQ6AHyf6qUm2gKGhT4nDZM+Vu1GPKVgj6di/b2en5RYyD5imuUPEB+oHuTg6LtC0Pr+hfFZSRldTa5vV2UL9Ypnvm+St4AdSqA6lUDkiZNaR2wK+cEqBuRAFHfpYYd1yhKAQ2Y4xfsgzlXxjHQkGG6e6MI/a3TsHixPaSuo7pcTuW/ujpTA6x7xs1cGQVYc1crNZt/9Xn+bcL5FG1w7hQccKJE+ec+7no1rfsV3RfytyQpIxuq2sHXG8O1C1Iahe4DlrdHp0vFoAIIxSmNMhebsdXK3IIqzF1Q1dpqdCZ+zL2W7XCxkvu/i6c0866KXqP3SSV1ZzVTb6Iai9z6rdBjFg7tM49WQqGUkfS8ngI1FTnGsK+NlrXF8Sdw1zq1OXpNlQJhji9Js8dy7PTaKTfDraqbgGO4Ynv5YDou2zr5zK65HL66hWU/7oHhq4s65s3DottuyxiU50oYpqRWffc+JpK6wygRSiXrmgoSdT969nThqZ66eHFS7dSpmQWGr1QdVgVyMUoBS1sbam1TDH5rakoUpRUr81i1KnnHtNZ+07da2xRzBRg9eb29wLS2gaS+++7LpO6cOUkCk7YpxnK3apVtUWtvd0J6SkkGOdWjgiCx7DLEiEBOgVAYAvnHH0u0yrlz0RNMtPaGUim9MJuDRy0yRUs15JNwtkoFeOqpbKfVHO2kMLQP6ulmq39TynPw00OjtRkzsXSpvadxX+NnPJ9IRVpxgVpENZRKZSeVtFIpAZc0YPCMp+aMocOwVEoTDhF5d3UlWV+p5be2JhM2axZWNE3DihVZXeQfKkCcpyBIchu1t1tJLxNlI1Wwa60TsyyCvGqAHV++PDsoQheSam68L1JBk2qm6tFlAzlv9ORFUbIOwqJx4GrkqckOmYZWaSY+Dc8Sg3Z2RQxgu8Fda7gq/a6XUBUddwED9ZYON45XFUsVHqxXGYouRWZ/qlQw0DYNQGLcGAibEyNHqYRnOvNW+LY6rHUqWLVienaR2RpNWBorpGsyPf/lgkMqK2awCSA4PjRKkFRDIqBj/3UhqVCiQYLPk28kAsGK+1SPtqJRBW6NDIMEKe7iZVvSBWPGKYqsM1mabdWAW75PhQnRm15bosaPMAudJOWjBLDTQ0APc0tJrh0irzXgZ6a6r1SyJSyRmgjDzK7BJk9pq9nt53yqVst2Kx8Lo9Xap2HlStsWwimhg5JT2dz7TPKAE86jl4XreSYl1qfspWetrOMW1AuUf1RYsg+udkwZyDnjZ7qe2bk0UznvsqTiTmJgCVm7GNZs66JuLIwaSgGBG06o0859w9Sp7W9k2WFBNZTpXpl6rgDnrKZbvtFk6PpWROTKRV3rKldZr2vgEx63PHWNwLJ+xnUtIfbq6WwUqdDob2URbaoL1gB731VdkqSGUA6dftcIIJdKdlgyYINq7T7rt3hBxtw1Guj6Aezzma7hW5/Xs64AsN9+2zaU9LW5HK7dwrIf8cDw1UUd++6LRXffbW9eukGpiUasOAiSZAOaQRywF6Hu45RJajUZPToDfbqYTfhLFKEnnIInn8yyalKQ8AxKEMBKQdzfOs1KlABklipjIef1GOWySTpQqWQXsLe2AsXFD2dK/J57JtddVJrR1WXf/87cMeWyeGfCJGxVnVZM1U7i/kF9ZM4coPD4w9kAEoTPnYv+sCUBvUCCVvRaimrVeEXDMO0r3SIEJfydTkCtdaKVyRqQe/UElQ6gYOnY6gzr7s6SjWhKfIb6qd6jCSIs6c8BkY2WyQ6iKO2LACOeIzFeDjIex6y1NQFkaUgZEx3Rgk7WLZeB3Well493dmbjxUan15sAyLSOMEzAY3rFxuLFWTbdSZOSZEMbNsBcv6HhXdxLNRx51qzMM6lhKaVSdom9tXsSXKbKMDOQ8kpGnmuYNUvO2DCMWkFGtWoyGKoDQ5wmFqBXUE+jCuddLaZc37rZUvHUDZPKM1B/RsZ4BFzXGOdX50hBBxugrpG0A7W2KQCcM81sNO8JTcMBGR7dUnKyxmlcalub2eCLgSS24aRzkZC/Q/uck2krSZWwtN3m2pz03CuveqEM0+h8NwxVMaBiMpJiNg4TnYpkkbVrE48+sSH1fzaRSY7IjqozKo5VBRuwr+lRRxn7QueaqxgCWXZeTrORdxXxeJJxGbIxe3amXKthRQyX9DiqR1ixTqHaZxstuDDIa45nqa4DKofTBUVvApumCqhusxZ/cYNVIywND6nMWhFPTML6y5IIhG3R8SGAZ7vD5J5PxQA6Z4pfFLuZM+guA1ar6IdtCK1W7asfKG+M91IRgXpXpY2mH5IBuj9otu6l1LnkKQYTfqgIhOGuQdFE7ejr2V+9t5Gf1d1P6raRlShPsO3CNwNB0b7jzwVl3LtJ7t+ucYzkgsJG6Ez3Y5Wbjd7llm0U6qntCLOwWDXqcj9o9Dr3tS5ocpvDbUA9fK4NSu1jOp/qEXRxr75bQSHrM56+MLtzWdVmraOR8YX9B+xrochXCh4POWTbAsPZuRy+tYVlP+SB4auLOubOxaLf/hYDpZZkMyIAiSLUyi1W5ndVSKinqcGWFiPe0QVkse4jRkjmPtcrANiSgMpsyb4snjqaORisLqK2NqxYmc/OxEgIHkFOYekTZmOpzZhpeYTK5dRK/cIzwF//mrxs7lz0t+9qEnpGUboZyrkWIAtjYFuZmIDdKZdTrxURVbWaHejhuRrdcaklpaE9+WjAStNN6xKvczDp+xmGIRsUs1yq08E9+rd2bQJomKiCuWWo2NFazSaGoYTBiOWRY2IsYJEdrqqWWr2vKQyzUEhN/awhQbxUuz8qWIoAgRWQ3rmoO4seFE07zgQ5ixdndZRKybzuPis9J/noo5lGpLuHSvooSlBYep70ma6ClZmWfMVoOG4+DKdlVno1aDOk0V1vgH3nkSpvaljm3KpTeOedZd2pNUIBFgEYG+x6J93Q2TA7Z2aFGDVSGLhw041U9RBVhAnmWUWjDI5stnqL29qcBDi607NPbFMYZheKioGrTh65IEK1A+UJoh6eg3aNOiS60jnRisC50FgWMHPC7IR6D6e5WqW3J3sXhbJqtGw/s5mQIejm5nM89EYKAmD2bKxY32xSzLMKZmFWfiPPUcaowi9Tb56rCzEEDN/1VAoZKE95zM0PozYBNTKyyzwXGYbpFUahKPFE0iSOgRg63ZBU3Y6UpU00DV3MqRbKM8au4S+K0rOs9IKqNqneF2fONTqGuFRlRRRJwjQaPGfNMuBTIylUftMhZyXhUZchB4KucYLvdG/qqxbQ1ZVlk3adhBQjen5LRaiee9O9UjENk3YzG7A5a6lWDQ4O2y6onlEQGgIIZKHi3GYpfyxEwPoJdFJ55zrqXPzFvbnu6gzObZR5yVWOq9HYus6gEXDTTUL3es2IqTzOBiqvaaO5NpwFqyCFxTncPNbBcTF9Va+ji5RKJSsBFMfKqjyQs4Yix03iIAXf2i93bHT+XPmqRlddhwruRc7z7G2j1xgdR9sFWNcsabVW5mvdS1hpWjYItr3HcLdcDtdtYdkPeGD46qJ99unAHXcsMsdQNNRTo5KY7p5nWoDUmuoqTZpoRncjsUwC9iW5QFJNS9k+JMyIJhOWSZMyLf2lElasLRqvVRAAxWpPskGjmIBcNX3OmIGBoGiyIbLJbW1p4pVFi8A7IQYOOMRgNkb2GTDE/lDgl5qNflWtJnihGAxk2TzVq6U7nyomaTITgjPKCm7ey7qyhBzEPMwcqpiSmyABspkrsUYVw5rJvgnIuVG+oK3NeFKBTBlTAyab3hxm4VmTJmRpmxmuxKQ37DKzRxIwE2QDmUDU7GfsF8n1UKnl0M2IyHaTh8MwTYufDhiVuCiCdbaUv3m+hX2dMSO9/oAa25NPJko/3YCqYJXLCfoMgmwiqN3xUKTGLbe1GeMGr3Wg/s7+Ui+ift9cfd5SLgfKE/H441myIVUM02s7LY8dE1Qo/5DXlXT/YnkqdGwPlXIgs9YT/LMPkyYlv1etssM1jbJNeUJFT0MDGygOTEahNiU+nq/02Zuu7uwEB0GQoRr+djW/VHOsBYUk8yVBHlN7ugPV2pqB5qoYKlS5TjPpAqg3XrhK2/r12TPqVqbGXS7bB2LZ51Qg8vyyWa/oyxCchjBTWQrDzMWuRgJVXhQ4q7LpGlN0ctN2a5QJ5dhQBo5SKQXABF3VvHWfnkbZ8bUKxMhGfAeX4dSpKeBgghMVMAo21PriLIIBFKx7LpUFOBQaSanJgUqlLDqF64RtJa5xFWNTuQg1yljWM2ECkF/8hL25CWjl3kMArOnxKaYsDyn5VQwpljebAF4yGrtbvwIh68qJdE2pgUHZStlSsYYr18k31t7MdvN/8rsAR56n172CRKOUsq8CPkZkcBy1z43Yn3PJe5uBLCzRBRDafzWCuG1RnOi+V8+56fsBWPsqly6pERjTCHagHlfqXJl69N5TXQTuwLibO2B5VA0Y1AarDqUvpzFD6yCpZcldT2yDW6aRW5P/c2JUkOkz7r7jfh4E5kiByiqXZzr222+bgq3dczl8dwvLvt8Dw1cX7b13B265ZRFmtg9Ym125LNm7uGOryRLIdjIlx6deKyXZCrkuebEzPUN6nwypLqthNQmX5JqmB4sWdCsFulrOqXADQBCgv5o3Og8X4q7l5xMPIQHtUUfh4ccTAa7KK50DWj3BSKmUXs2wdKmt6HEgW1sNIFZ5Uaj2mUt+6eGkEs+zNpSbs2Ylir1JCy5hhTzDEEUp8EmFOsFqEGQZCFmnHkUDMh1Qhz0MJWwGSdIX1ZeATKcmTtYQspZyzfbq0qKtSqTrndEBj6LMw5Mqu+pBZTY09aZybHlXlxogosjOcKl3V2piG/aLv7XP/NHbIebMSe+dJM+xPwSLnHRmuOnsTIwQGzZksciVSnLodNQouwzTz9E1zLXIlxNt9/Zmcb204kyenGVNJLIPAtRaJ5p70elh4TLRfZO8UK1mvK4KBc9TaRQUM1qyDvKxsiynn+/jd2GYRfFynRHjqFjhkOi1oGzn+vUJ8FQDSlNTUueee2ZYnJ4tnqXUsOV+FI1jn8AayLI9sh2MNgbEM6WXqpO/qZA73nQNm2407kAWnqyKA59X3RfI+sS+c3zYZyrClGNajzitjBOMuEKTWuixMGbypZGJ9em1MRoBLfjQwv2cY9Latfa5cvJCSznzNDLpD4faRIjQk5q+iJmbgQSP6/Fe90xda2sqP1MGqQsZ5ss08qO9Pfmc+yMrVVcfhWO6HyzrLlhOeC5njitlFI9PMAJAQ88ZDsd5Y1g7t2e1EQRBenUKB9QN0eQ+JeOlmRzJq1EkSWtYvpGw4HsabSoCTJUH2X/1KFpp/yPbkKdgTPmTdWk9Y8akIcc8D0H3O407rlElijAQFC3dX5yl1palId7K43qujESDp3qlFWTp/jRmTDZsjcIlgaxvLilo063VvW9Pn1N9TP928Rjr1LFWmWY9oKQWREeY6blrE/2hjdeGApbXEciWF//Wz83F9vyAoFM9usjOz7qg16pHwW4qDFWGa1fZRY6lOjwsAO96NQXhb+vkM3vkcvj+FpY9wwPDVxd17LUXFt18c/KPa77TsKd0QfVVC9YiUEsbmZ7KRxTZ4XHWpp3WxzhtvXSXipuuQ7XMUm9uDuz7ihiCwWyOy3qLSfa4IPFg8TaF9nZg19Ye4De/SSqfNAnYbTcswUysXJklr6RypBuPudaACJreI2pR5bIJweVwUkFTD0sQZB4pVWY5NPzZdVbNFrR6ufqsWdmGnSq2PVECxHkO0oTKQBRgzVKYSlU9d8iuqMJvCTo3NkkbToXJdfO5UretzTbXUrrzGSIvmvnVssdxUMWG75dziy5vFSo95llzNxz67R2PP9p2d6dIn68huc+M3sZKxT7foqF45XKWjbVUys50cXlRNzPngzgZcjbJoLl0/PrD5FzQ6tUJ/7S1AS3VZVl4YFcXrKwVRAvqJgBsMzA/p8WFc635z/k/iWhJc/GzzWraV+RCam83C62vNMWsUcA+n9SIhdh8eng1Zw+Q5Z0Jgsx5O2dOxnpcn6KzW9PNetavT7zhfZW8ObbJYADi7VIpiwqn7KAiaTJKppX2RYnXxTr7HGWhWVZIVhpSGkXJPFMRtEIkKYtc1wo7oKGr/K1IkJ+pktLWZgxO7tK0PFoU+KrsqZuHd+hohihXIyYS1AnmM3rgj7yj3s5y2QA4NSYUglrmYlf0FwTmTLZGlapocflMv+O5eDN/KRlPkh7KcxQ9M0787R46d9wGlO3sj5FhAPrDFiNmS6U0kgFAT6VghkajJfR8OGC/ulwGil1LLLRs3e9KGcDxV3lP+aybBRtNVy2JPKcuPxL7zTFIz9a6opfY20S7UPFPO6rGFz6vR2B0ftvbU52EvKoHPlV+cZDSTKCaD0nrYxcJStlN49WkwTsI6gAjkN3J6W5BumwV+KgcVAOKAkndj3gcxBg6XEYPs4vfzdlHnVM1cslRAg051TYaOaFf6oCp7HE7rogTyNpLCrIQTz7u4j+KNAZX6H2uvFuUz3PuGgF6JbKJNKOuqS4gNKBSx5Oka4Djmz6zrYHhnFwON21h2ZM9MHx1UcfcuVh0++3oL03MLDbIzqapAkOLHRcAL2QHEl4uQC6RpbDV+MMwOYPBtWClGKZiKaEEABIFuJo371IsYYSOhPswwx33CuIo3mJwZEcPcM89WXjJoYdixYYW/OMf2bm7VCcyOQwAoDnqydqnO2+5DLS3Y1l3wcJLGrmiMhjI/tdskfyuXJZwRXrYOD4CFMxF7KnXS+s1h+01DEhA3EB5Ijo7s7NaevaQbbEUT9bjxmlRg2cYHudBf0j6PaUrBaGe9RJl2CRRUa2UFs9ySzL/erBPLfV8f5jdU8V77IDs+hXAtuRyeqtV+5qWKMrua2JabjNGqiWwr/zd1majwCC58091avWeMVSObaAnT0H74sUZ4CB+Y9dZH50Z1N24BOlNsBI+cB7dHQ7ICqtmqYod+Yy8SSCbhg0akFOt2vG6PLi2YkWmSVF7o/YdRckAqGtS46nZmUoleaa3104RzA5zPubMMVfLDITNxiuS7+2xNUdV7nl2C8gO3+pAlstYsbaINWuS8EBmtaWNhEPDM9ajRye/FfuEYabM8f5YYvNRo1J5kM4N+dTlVU4NMZbbFbaBUaccFnaby8Ws/cWLM9nqpsR0gR1frsBUL0McN84Wcq4XTd2NfEbP4bGhnHPKBFfTV/DF+WFH+SznU0FKiuB7evOWR5XKtCaVYjVcZyrjOZZTp9aH8gdBul9pJiwuTvVG6hjTiJUChjoPQ9qvWqk54WE9zKxGA/KruIGZ6ZP4jcnRiMPJtxx616bDfuc7n8n2QRU0utnxe7ZLGVhDAVSzVwuP8g7HLAVXihc4RnXn3NMvOb8a1MOgDYqdSePkfJ8CRUWXas2jgE5JdRSCEsoGzXqpNlU+S/bWayNICg5dY7wOt+ETZx7csHt3+SpL8h0GHKaNNgYsLeCAPffKCso1rVd1IcDOfMtGuO21jFHuF67sSF+k0WjKG5ZRS9eKC1aVgsDsZ3VnOZXX9YXSHwuppgxgndOnXiPt29b3GO6Zy+FHW1j2XR4Yvrpo3rwO3HXXIjSjD/1BFvapgoFhO8Zbph4y13wCNLYScgFqbIZKi9TTZoFF2exrrROzBaSAhM+FobVREAzSaDx7NrB7773J1ROzZgEHHIAllYlGz9x55+zMFRWsSaPkwne6JNraDAik4B81KnE66p1iHEf1TAC2o8XdKIxHleeY3MQUfFA31dRibsatUjHxLuZzFeJU3Jl5R8Ef50KvKNFNmoiZg8RNsVpFLSxi5Ur7YL/K6+5uOysdlY5q1b60nPsuwc348XZoou5FPEunTbMyximviXECgAEHVN4J5MNQwsmUl3U350+phH4U69aUhqNZoYV61sUN51LNwNlU6OmltXpKWQwv1FD5PirDQYAV65vNHY0EieRtHldjhlHVzXgtiA5XV5d9/pBAgyCGzVZrOZenNpUsyGHVLKZjxiRL06TDJzBTg4MozEZZo8I2Y4YNHLjwCETTc8YcjFpQSBTbMMSyaKIlO1IWSRS17udRa50IQM4NdncnSj6Zx1WMU9DYX80bR+/SpfWOEtWZyQrUQ1WRoiGAbEHvNJ24xFZ6fFKTxvAZJk5lPYrxVq5MQCvnjtfp9PZmRqQwzM6Cu3oQz0dzmig+mDRCvRFGKUqt6X1R0eD7UaPqDWYKTkyiqt7n7TtlldRLqh7GUM65U/F1j0m41j2Vv7IeKYd5tVNfJW/YjMXUERhFtiEn39tjG0oYBaFaNbO2KO/zedWuGdIaZGf39HJtIxvV4+cqxLqfVqsmGZSCCA4lq1EeGjEiAUGuns4q1RBSrdo2T86xOWOpYYkKGFmxGgvZfo4LYL2MhmXzEmX+MLsPk1E7iv1onAHk7kOOH2WPA0gMH/GzVDYs68pnSfjEAK9VulkzlXcs0OcCF5m3OvSokxHYnmidK3PmFtn1JgyxVMc7X+VWDQiPCcO49xByelR+NGim9Ruwwz4toAiJtHDRruo1JOV/9dJxwLVBOs46v5yYRnW6FAQmQolFjPdY28p6UtC4rZPP7JnL4adbWPbtHhi+umjffTvw5z8nE6rx3bRcWL/pCdTFxAXB3ZCLS5U31/JXLqOnN28pQMQrPEzPBWRlTtP721Lww8yV6h1cvDhryh57AJNWPJyEjUYR8O5344nKFKxenYX1UYbTMN5SrmVhe6lWtmJDi3Fu0CJPg2EB2XkhV8Cr/FA5o3feWTsj+0bFmF4nueBwxcp81k49L5EKFHPfnAuwqZFr6Bdj4qg1hqE5z6mKnm7oTKSgRjDB95bSwNe78rRaTayojGpsasoS1aiep+eTFKeq8kkliKGbDBPhHBnvHhnEteIBZjJ5dx+t46qfsW3sk0lu5Oxi5txoekdeT2+iEPN+RvIJm1CI+i0gXwuLZq31lxJAYs7QUklK0QTPw0WRZD2kK1rd60SGaV/dBC7sm8kK6U5sFNnWcdf6qfJBB0o1Cipv6cS5CgPPpnEZaLtKpQw0uPsxu8iEHtpk1fU53e3tEoKWyiLlNfIxbVD8zLX6c8oLlZ7Mw8ZDm5wrLh49zMmDSvydKk9RJJevOxoY0/+rgs42q4OV/E7AaZTsKMuEyDXDPvB5JhUC7MRLDIXVy8fpDNRMuUpRlPDsAAoWEASysa+VE4BmrhtSrTEdEyBhZ/ZXvTEUabSVGfDDTuk6Z2FXOyW5QMuVnZqFI3WtsW8ArHBgMh35iq+uVu1thU0IQ9ubayXe4bvZce57QdE0zxgF3TWXhj5yvhvJYNZhkqUFAfpLE81zjIrg/lbAgDlO4how2B+9a3DdOtswyv2TZSnLdXtSMKSedBMK6d4t6AIiMrTK9xT0MlMp32GypMvC12tM9Fn2Q41Z7t2SKqOMbNfwae7RCmKoI3HRlkoGlGv/GRLK30ygpFdDaJddGwNlo259/E2xDAhA3BgK1HWlFaXfWWf49PtGioG8w0qYgywHBV9lAWPdu9Wq51qlKaDUWKg6LPugdXFC+Rn/Z/2q42o9QpbM601CwK226H5MniBF295juFcuh19sYdl/88Dw1UUdHR1Y9Pvf23fquNYTCi5dEOki7EfRcoZwPfLMA61Tquy58d1cz7oe1eimlmPAPn7GNbl0aXbWat99U2/fffdld9QdeiiWtc3Ds89m4aK68QAp0KKHsLcX6OjAM5UWLF+eWPlaW7N+qWCipxWww2uttNXM4qYWTdfMT4snvX6trehBiwEU3LsYxsAQUpLKOG7oK1YXrMygpVLS51WrsrHTTKjc2KgIE2xx8+CPWpK52VP5MdlG2V9OaGenPWlqflYXgyJJV4NKX8DwKhJ1chKVWhYlb1FpmTRuwA6hVJBODxAtysiy59FLoxgtDLPIORNeGkXoqRaTbK3jEoMLsypSmVZwmEctM5mn47FiZT4pq9lAALPmVEkulWAuVn+mM28808Y7wbBcDpaG1+mmpvFinAcuYDJQ2mgra1xqFdVx0uyzpn36LmqHOs+qIAG2m0wVC22bhqunE6LhPv2wrbUqyqrVFODr+Te6MsjgkrnUzaTMoaxWE28nIBdt8wuNy3OFnCodfLea0qkxp/LAzAXLMykR61eDEseLdwgB9VmGaJUZNcpOPU2rl7pxyOz0wtBrxjXjKHeqqykQYXgdm8dpVECg7NjWJp7aUnLusVBNrl9Z1p0lCqMnnKzBtcU1x0REk0b22DGS9LJzHhQMKuBQRZhzo0zFButcu+tHZDv3xmo1k8k8pqsZnVWOETiq51Gnh5EFBuipAtzITRMkIXJ8rxrdKGPUyNnbm0V2K0Zg9ZqszAIDorT3Rcm+RSMwl4juKdpPAi0Opy4dBb3aPTUGFTBghy04lkW9oNwYoWUvIijW/UblP79TceriBAP01WKjvKU8FARZyIxbaWurdY2YYiBlU+4p5oybUKOM30FgG1fZV4oENYhxuZPMGToH8NWNq7ZBHA5arG5PTMdFr/cwwHUoQ44ykuoTqiC5Akc6RTCqjmpVQ+oS5ARBXX90/AHYkVtBYIzHLq+ox/jII7etx3DvXA63bWHZf/XA8NVFHfvsg0V/+EOdkqhnrrhH0jpIy7k68AB7LTYKG1PlgHiIgof36DHxC+WmAhUqwJph89ln7TvbJj33QHIP3dq1SWVtbeg/6EiTIV6tpdQLyuU0zTc7NHs2HltaxNq12bkgPWsWBA3ScOvq1tVerdqHjdTSxI2BSWtKzVi6NLMq09HDTY46Y0vYb9JtEzSq5XrlyuSsE+eAY8yQGG66Mt2maayHqbXZVJ7DY5Ob0YeBsNmUzUdyLlKFLjdhVqaWdzZAjQ2q1FLrUQ+WKmIaapsyVq3UXGehdi2/nEcFCGYOVXnnQxoiyEXA+UwVy/6wxdwHqV4qYl83QR+71EjxMWOeXrnAOyDduTAblHv+Ssc2bcxAlM/OAOv5CJ2DtE/9QbMF+DmObkgv9Regfp2qEsHxpfeCPCP7ZHbeD5K1mAq1AsFSybrWRDVBU64Rj5XL6I8KliGK8ocKOA0/emdZFCVGDiYy0r6rIhOGybrVcDoar/TcIA0zJptxacCOqtAFqWH4nZ2ZsAPsFJW0VLiNYywsgY/KItUKybAKambMQH9pojkeS16mx4YAWTEqx0OPBBLXEgy6/EL2pZhQgyCQfc4wU/JgGGZnANPpt1ia64/ngslsA2Gz8QZxmIOgwZlqjr+rvSmDu5+xAalhoRYWG6fu5zxoXYpkONCpwYNyl/KeZ1TdgBNVXl1x4BpGGsoaIAMkLKBnPRX90HBA+Zi+xDpXrDzGBmp/OzuzfqaTpnsM+Uiz1Go1yh8cA7HnmSHnc4Djkdf5S+eTspZjZc7ru4JPB7zR5+n/XCeUcZZBxrGC6D2HFr+wXv6ve6MCf43WUAHs8qvyOdsrRxAQhiaSxIB92AlZOEdRZN9xyj1No6XYfDexi9XXRmi6EWPzcxdMK0J25oD9UVJ5pbb6Rk1QR4Z7DFbXWd0ZyLRCZvtXwwbraMRW7Nq2BoZzczncsYVl3+SB4dan008/HT//+c8xceJEPProowCAnp4enHjiiVi6dClmzJiBG2+8EePGjUMcxzj33HNx6623olgs4rrrrsO8efMAAAsXLsR//dd/AQAuvPBCnHrqqZt89957d+CmmxZh7NhEeWHCFWX85cuz1NmALWybmmDuXVMnBJNoAJngpoNG9wbqLVPaasDjj9uoUKzoTFqjRnEmE9ltN6C564mkfHd3YrqfNStJDd6beFdaSgNY1l0wCkmpJBnXFi82lwLyAnTuezzT0tObN3LTbKKp0m4uXqWUYdu1D6nVn5YijiGPlaihi5lTadzX5BOoVDBQasmy7nEi0h3ShPRRyhDRUxrRfUNNjy9W5KSbCL+X7+hBaykNZJPBXYHW8CgLE3QN1rqJq1zX7GwkvZIiikSBI+khTgVsGvaYKlgrVif1Uo+mMukqEaqTV6vZXYvmjFQglliOr5qtlenVopGOofF4KOik1TEaMF5ePcLLECK2T/VQNc6ky8UaHndNKjBxDdI0NNDi2dObN6G0HCv1ilovhpOFLczO/WpuFyAbElVW1fCi/WT1CiTJovQS06JNGaH9p97JEGjKLT3vWiplkcZqQOI79E5G8o62tasrG3f3rj0Ok0ZA8ExaEMAYFNRopcT+sjyfIeBspJNS2dELxrVd/CFIol7Y1WUnsFE9lHyiDmzyjBoQ3LJsC2Uax88KgeRE8WWlkjlTqzo0+UjFmeqAum5ZdtYsAYlqtRAFmH3jmK1bl925as0bo2oU+bIg5SwzuVAeEL2kRhfLoEfg4Qoh1qPMw85rpuIwNDkA3OMLKtvYbt45qJjGnHeipVQNcWoVUEONGJIaWnu4F6i2rUzBhcY+c2NXGaqMyjGR/jMslHPn/k15oDKkWs1C7vWKgnw0kMWNq/LD30BduJ96xBR7WYaGtB80WtV58IIGHsvUGNAIsBjjrWuVV7TBB6Ugo4vqLmTXZG1Sh2XUCIJ6g2IjQZUa58iLgO1ZdtmAupW1JuVvveKB5c3Y8gMVUATjDa4BYsgtDZT0fDN0nkNAHglDuRuTxLFwIrX0nkp2QUOmtS1cMtZ1LBD9ThSkjiOP3KZga59cDndtYdk3bAIYvtQY5y9/+QtOO+00rF+/Hscccwyuuuoq5HK5LexNQtsdGP7+979HqVTCKaecYgbtox/9KFpaWnDBBRfg8ssvx+rVq/G5z30Ot956K66++mrceuutuP/++3Huuefi/vvvR09PTxIWumgRcrkc9t13X/zlL3/BOL2RvgHtvXcHbr99kcWk5jxBes8ekO1TVAqALIO9eu6jKLvvi+WY4n0KliWVMMd/FGXxJEBSsfrSmeN/zJgs+0KqSA8ERRS6lyXeQW4s5TJw6KEm6yP3OSpfVIonTahl5shKBZg1C0s6C2avb29P7yVMpVcNeeSXLslWOS2lFEZ62Zla38IQPb15k4zRVV5ci1G5jOR6jZQHUC5nZws7O21trFRCrdRsKbP8uhDIeToOvoZt6gE91YB1J1WpygknGqHyoqba1lasWF0w96YZ0CRWdHM5curp4jlT3bx5VojVk9z7hggSzf2NoQPWNMSNxL6Xy2bjDYKMBdUxyDnh/sl38dwHnTV6v1hzOGBvlor2OZbqSieT8kK8KLW4dy1L/g9D+0CSO1hkIEWQYZL5l7prW5tzZkQYzw2ZCcMMFHDoqKj0VTNvG8HS4KDtDGYz6fVjEzmmrmLAzxRgUA4p+3HqGgFG1We4r3LD57qQo8K2Z0grFxd6f1Qw3sRRozIdTDPakjeUn9VwoFn11Ljtgt1GoMS9o45TR+8dLfJaN+sHbHBWiJzkU6VSXbQB3x8EtufWspSk8s5VMI1hjGNJBZ8WL/K53u+hF/MBmdXRdeESBKjA5NpJ1zHBteaZUuMAtxgg4QniNSv0m0InigzYUL7lViF6vmkCeZWilV2b1l6r9wRz/XNyU+WdXjY9w2nJUTXCSFut6AaR5f2liWZ9Kl+wKGWCJmsrBDWTtZPNXbnS5neOMY+8m2R0S5faVh31AirpnukMMvWMhiHvGopdqdhnBtKoIB1P9zyuvpp9I2519XHdGo3xzq2EQm8owKsWNyH3+g3XEKRgXY0hYeiEJQpgMxPLBxVUK6mQ18Hgs2ocDrPjEy7f8xWazdXwULXPNphwPqIsFFdBI1CfiZl9Zqi0NpFToNeHuYYjPkcxoiKIBlGVy65+qAFK7Dfnh/JfjYTaL5IMo2uHyuSqGmBUeZaB3tZnDOflcrh7C8vO3wQwfKkxzn777YevfOUr2H///XHMMcfgnHPOwdFHH72FvUlok8BwhJ42Hm7luRwilQZD0NKlS/HmN7/ZDNprX/ta3HXXXZg8eTKWL1+OQw89FP/4xz/w/ve/H4ceeije9a53Wc/x5xvf+AYA1D03FO21Vwduu22RlX8EyHRrlYXlchJCCMDeqBYvzgq5h9C4alauzNJ+aYo9IjHNKEhSyyUbQpSlq69cBmbMQE/UbNYblaPmUrLhMUnDpJGSCS4I0BNMNGcWmUqeio4J7dADlNQ69PxQ+v5nOvMmVEozBtKL43oULGuR3lHnph9sazMSa1lv0bI8cSiZEZTvoBBasTJfd38Pw7EaZsZKNStLAXTBjlhQOTXlssTRh6H5DrBv3XCVejdaprlkp5TWTUXlplpfGT6riQD4nAVYuKFy8+K8AkBbm0nhDmShkzyzo23Q9nJP1fnm+GsiHr6GY255Rat99s7HeeAgKVHzLZfrPQouUYkGMlDOKz50gLgAgGxsdGdjXRQE+jk7y2cUMenOqjKQg+YqMmlZ97Jh1xrPx/lKY0FWeUFGc0P0UrnhAle9iiRf6bNfpg/qeHMdOIm6VqzM1yVl0VBvthuQszdRZIcHu1qt9ss1EHDNpWHUYShhaykf1cotFggwkQWsn7+10SrjOafkFfcZF6jQNcgb5bkvzJpVv5iBeg8c63PDgt3oBlXUyde8O5Hfp8CBgF+PRVCGkg15TGHSOEkk47avXEZftWBFe7BpBBzEwVwObDK3unz382bOjAeJxjzyF9ca5xfJPmbOb4dylpZt5PiQ39k4idNlFADD/4AM0FIs6lbOv9kPxWm6LSru1XHh/3yutTW7G1T5uh9Fw5+ARGggu4uYIs0kj6IhQj1fLigKAqCtDbXWieZxZV32k4CF+6WydqmUgZUgcLzPOgDKoxwE5Xc+F2TJt0hRlIFthstrOxuJVxdXuOLJvaKB5wvNXkAeV2CrOSV0LBVJpd5BFmFkgonGUr2BL9T3KALX/Y5ENKeoWffE9P06PmqsVP5zRSm7MhQZ42E6RzrGeiLIFdNW4isdMxfE68amBntGAqTreltnJd03l8O9W1j29ZsRSvpSYZxDDz0Uhx12GB5//HEAwA9+8APruS2lYFMPvBiH4paWXbFiBSZPngwAaGtrw4oVKwAAzz33HHbaaSfzXHt7O5577rkhP98UFQpZKGdfJW+U+GltAli6u4HF3ckmD2RxZbrbJQ3NzrC0t9uWtN12A+bOxZKl9gW0XV1ACABL7cVcrQJtbYVkzy8BpTY59Dt7dmaRbm3NzgUgC43itWhLlyYhoDPbswPoAzN2NR5QblQtITMqthrltFjpsW9BJigMAvSVpyUbaBXo7QTQmVmjx4+XS5CDgUzBWZoIxqJu3IqONAkCB4HCAsBjS4tGIM2YkV6LAKCGIiZNsM9orVwJDA7mLQDJhAZZ2FohM25GQBQVEAUtCJDOCZBmoCsYbxI9xJTtFMKJdblYZ/mLokTZUuzBcF69J5LCNsuwljfvBeqFe3cln4ZjFIytgQoEN1XdLMMw6QtQQFBOQ0FKE7P7/BYvRjNggFRzDgBK6K8Wk2fSja1gNvgk1G316szrYi6hRpZsRvFIEACVapYsw+x7YXMGGEstiUIZTEw2oi7b+B5hIoIIaAuA1U3TMLJUb5w3ykAa8lwLiyhEA6ihkPEZMkDT3zotG9twioU96KXiT5212gF5lrcpZRINXzPrO2iu35yD7FyrgphCCVbSF9aTjwZQQJRwK9tE5SU92KnZFBmKR8s7ARKzwiKKkv6p15wMp14CemhT5sqnC4xGiklj+utS/a9eX7CS8VA0rl6fTw0KBbMmE+t2wRgaKhU570slsReIoqKlO6kntlRK1k8UtST1SlsArg/ef1o0Cj/XM+emXAY2jJ6IceMS2YrxEzFhAttl4RYzPATrK1bmMXKGrVSVg0wOWaCq2mzEXVMTMKoEBK123Wrpt+7H1PBxGn7o/q9UTARGMQgwrVzGtFIIhMlEDJQnGlwRRVl0/j9SvmlqKqTn3puNp2RkOk67tssRgmoVoOgOQ0xpzYQgE2XxCPZf/wpUqxON/OTcI5iGUlsaeUDFNCggX60CXV3IV6toAbKBqVSQVwUzCJJ9l5+pR4LG1O7upA5FGFlDgCjClKAXKLFPZaBVGKsswqGaJAXp7c0MY1QF+AozX3JlSVdXMsdLluZTfi8Y7x1gJy8CgKok6alUgCefTMZscLAFYdgCYBpaZwHTWvvt6yjIH+nVMvkgQHO1imaO04wZZv71SCRBIAOZyFJAcnY/oSKCoGi8z6MCIKrSk9YChJn8skCXGOXy1AV0HlCyw05RAyR7M8dgKKIPIzsWSQNYMtZUdpP+5tN+ZRlum5qAMTOmZJ50BXeklB+T3TQtnRpMUGKCrgKilO/DUtp2NGegUY1OXNhpJI9eYROkBuowBFBqztZ9pZKs0N5eFNLOFo11QgYkCFAQZaDI9uuAqvFJjnYAQD4MUUjrLQBoccCu0QfUC8vfrkdflSYKT90YWUcUwT4RuW0oB4i5+qWnrYVxnnvuObSL4Nlc7LMp2iQwfOqppxp+HscxZs6cibe97W244oorXnRDhqJcLvei42WVrr32Wlx77bUAgJWdnSjcdTvQ1YXmUikRmlEEy/U1ZkzCzLvtZh0Up+UUyNz7euQLABAAa0cD63qB4J7sLjTFQmr05RophjUs68pb8iMICqgGE1HpBoJwpqVg8bnBwczyWa2mYaGlzLpYa5+GqJrpEbQO9UdFVIMiWlJLV5GagmRqWbG6YK6sYCgDvaxTWuWMwjoALwTZogfqM98AWaPb2izLFGVVpZIJxQQop9biSgVAkgVS9ZF89/NAuYxCtYpJ45IQjimtA+Z83oQJdugYLcOA3SRVxjgnbIc6jTgvesUIN3gqeYohNEdKtZolUSCgYmY8vcYiCOy78ahoWOcuS0mynK5uKnOZR1ates1hygdBUtEACgYsrh/bnHgIIfdoVqsoVntt7ZfCvrMTRSDZ2AfbzKBwk6qVmrMrJsIQhTBRVIrGIxMCyBuLvAIB7k1RBMyckZ2FobLA+Zo0qi+1pGdZSpPwwOT5nqgZpRAooGY8Vf1RAYgy5bqGvJnLfDSAYjmwwnWnlPps86gCwpRq5RazYefJRDLp+TBMlYfQAJtiVE02cGU02SSLIQF+BuIKSOcuilALignoCwppnaknrsp9vxmoZMtuICqgGrSgFCaXchfSc2B5MmSqhANpKGzYbMZzZAiEqUziWNTKLbZ3LzVU5dPFWoh6E4UiSsajOQcgiIBSiFq5xfCkprZXaz/1FipS6oHX4dKMxTo1mu5dATWJ/EUPvQZ4sK5CkPAe13GW5Crz3lCX0TOkQQA805k3JwMYek08TVsigag6j3t7M+OTtpPTtH49IxfzCMNmRFEzqtFEhEEyvCNGABg/xXh2VNkvRP12ZEalgkJnJ6YAmKIgihEaYWjuV+zqsjPtJv3mWaMioqiIWbMy2U2nfmtrwdx/11LtRks5ANpC2zOLxJPc2Zk6v1KwlOGJZrS2NqNCYNybGdwGAYTl1IvWtcz2lIqXotY2JTO2dC/LNlwiDW4IOmjc65cuzY5PkFHS8nn0ooUROGEIoJxNHOsFzCZWqFYxLQAwrhWYENQrxkEKOIOi8Z4xXNjss+0ZQ/NIQGcn8PjjCVijjlEFgBAIZ6SJpdCXzX9vL3DXXShUq5jCcChOGsrAmDJqE7JENNWqvc+p82vNGjv6WR2/BGRhmEKoIF37UWoAKQPNQb8BW0CmnBMcFAhuVJdgIxRUOecXNZGPkkyfWdurV2e6U2K0yQNI1pdOYZTydpje68q6jAe3qwuFKEoAk5GtpaQPpcQY2VMpYMOGQgq8U1AKIKxwXAtoaioYfZJVJffm5hFFiZGmqQlAUzPGtIqxCJnMU72wVHbu8dR1AiQeyDSqplq1z64DEqE1I5uGfDSA/qhgziuOG2ezM1UG6jiAGr6z+eD/I2IA64HBysY9mi8Z5XLI6SYxDFq5ciU6OjrM/2eeeSbOPPPMYbx662KcrUGbHInp06dv9PtSqbTJZ4ZLkyZNwvLly42bdeLEZCFOnToVzz77rHmus7MTU6dOxdSpU3HXXXdZnx966KEN69ZJ69h990Rq0tLI3bqjIwF+iR/FgCENQakszRZBqZSFE3CT59/cX3gnod5xY93f1dubrOAgUTza2rIQSe6jpZLctRaEWLEyU6i5N5VKaXhe1At0V4Hu5OUrmqYBK20PT6IEJxbbYtQHdPVmYzBjBpYszWPlU4nQ5DAZ76IxMwbA0qgeCUlcJ4VVGABRmIWTBUGizFKAdHUl+zDHc6edkq6OHQu0BH1AlCQbCAKgEA2ggCrQG2UINUoy7xUwkPQHAQrV1LoWlJLfUYRCECBoTZSPtWvt9OdKPBzu3ptVCzLQGoYSehUl5454Jo/9LET9aKn2GqtoGCYeLW6ChSjClBBAVAFGloCRHKASmkdWgRcqSCBwkO74sHboYqmEae1ZspO1azPvcWbULwBoQTlMvU29zyfvD0M0jwJqYTP6q0Ws3VDMsham4HLtWmAUgPUjmvFCAERhZjMwyYgEXZs7/aj5lkoYKLWkSns6B+ku0oJqYnJmHdXUSokI6K2iGARANWGWfMpbRWTncppTgNJSSnZBApyWMJknBQe6YYZhFq6URy25ly0aQLHSa1sDVBMqlbJrKkRZqSGPaprNFIohRUdlllVLQLg7pCCCAlB/nidV6vNBkI6R8EH6WRHVBCUEKa9UkroKYZisFT2QyzpSj4x5dxCgxSzQ9N20eqQA0ISFooBqaUp2lU0QZFECHEe+q7cX+c7OpD2qmGh/KkgMU+JNyIdhwgdSpogqkIuACsty4EOjJBbSvph2pX0JwmQOa0iSTDQHUTaG4oIsAkAUJoqe8EAzIqCazhVKaAmzpAzVahJxUkvlKo8cjh2bGT24NnWNElBRCRsxwg4Lq1QSgLn7LDscW8MX2UyCZiDbr6ooIirPRNgmiiSVRHpzenuBv//dsGQzgOYXXsAUxuwPVhKNYVa7ySTd6M41tinxQCYelCCYknij4qSaKLLPM44da0fY8ZQCwx/J5mPHJn8z8RCPkXd3T2EOtWT/43qpVJDv7k74B7CiUMweRctjajDTSAiUJyagmmuGz6d19YRTkj1ZQbeuLbUGsrMM10nXdw15REER1QoQRcXEhlJKxpMe1FpQRF+FfiqgOawhHw2gJepFS3uAvWaXTIIxGh3ZzM5OYOnSZgMqxo4FJs9Oz4IuXZrd/UqXMRIZU2xqAsaNQ6FUQrNaRMthZiRyjjKMGJGC9sGMFxVgckg4VOvXFzFqVBGldH/g+VUgNfYqClWG1/+7u+u8TPlqNTFEUt5qHWxEGKIAYNIoJJFSAnTcO2MV6ERRohPSVlCtFhCGLUbXszyOYn3ORxFajNIY2oC2UgFQTZQkg6wCm5fGJCHHbM/69XrrlG0EU8Pw6tUElUWEYRHVqAXVShZ9rZES7m86+TZssE9vVOU+z2o1u9uZY0RPdKJbZbMzfnzym/q0ZvsulSS76bamXG6LEemECROGHfa6tTDO1KlT0Snrls+/WHpRyWfy+TxOO+00fOc733lRjXDjb88//3yMHz/eHMzs6enB5z//efziF7/ANddcYw5mnnPOOfjTn/6Enp4e7LvvvnjggQcAAPPmzcNf/vIXtLS0bPS9++7bgbvvXmTOETBznxp8VJkk4zN1uK5Z6jGFqN82A1M4lMsGtFgACjBg0JTXitPvNV2yLugwlMuUq332+cb0bAmt46hUrHT8kyaIFYlUKuGZroK5v7C9PbWyUnGghZG/xaSmaZG5MbnCVQ2kFEB0NmpUkEY1FDCAnkohs9BVnWydaf/dzScBIrW6eHzrDjJKd3XdivLOe7H0/iPjZWJmQT0X6W4+bqf5jI6dGiVcU78OXjrGzEjLHBYTJtjZYpVZNfMgvY+sjgJ/zBhkIaPSST3vBtjGDBrZU5YBkHRhxIikPRqhooYStSBaIShpaJa501BfzIKut5lldRxTJhmI8tlZGP0+3en0CgY2RTOW6jCSVXSazTmWKF17cl6O86BjpWxA3UbHRZeg4V3yV/oyTaMOZONoZRhEfTtMB6MIfWi2EiCyn5p9lh4Cbtpsm8uOauiichgEGZ/R0eKKM/5vLPwaUiUNM4YzWrtdhVs1Tv7o9wpsVbNLB12vQqlW7WQsKm8V/Chf8LeOed1VN7Ct5Vzm2l2KnywEzjZG6tkhdpOZ/XQOVVdW5VYVOE1y5JYLAkk6wkHhQudD3Af0bNDo0UAaFmUJBgpyapfpAuJ1ULoNupgLyEID9ZaSVauycWtthZVohtc7DA5m/V+/PpFHao8plVKe0qxomQXNbozyE3+zMsaat7Zm53P1/hGV+ek6rpWakzv9uruzxDEUCCrzdZPkpKY8Tb7Vva5USu8KLJXQVy0Y3cW6wiZtN5PC6TTqtr7rrFqSO0HvI3322YzhOLhMoKTECCv9SUFXEGQyg8NCTyTXhov7OO9MKMV1AmSeLc6vYu8gsKNnlK+aS5IciS/mQtB2q0FIERMHPciygKpXle8aOzb5zXXMv8vldK64p6dXXxk5l86VAY3kA7X8sMPlcpZFVXlNETmQTW66rwPIonqUVHHjOymg0nbRUG5kBRkwpX7nGAyTSrlXPrm/KdfGjAEOOWTbnjHsGDkSizaRrHLIstOmDfuM4dbEOG7ymbPPPhvHHHPMFvWFtN2B4bve9S7cdddd6O7uxqRJk/DpT38axx9/PN7xjnfgmWeewfTp03HjjTeipaUFcRzjgx/8IG677TYUi0UsWLDAuHC/853v4LLLLgMAfPKTn8R73vOeTb577twO3HtvMqGadZ/MygQa3IRpwXRltm5w7sbEcCUgC4tiGUtBShfYQFDMwCO1CCrK5bLJuugawnieb6CUhGvwwmMaSIvoN1btKAIKlR5bykYRBlqnYNGi5JWzZgHF3mXJBiFZUa3EIZK1Eaj3rGr7KLD1DLUKiSBIw10kzIFheuaKAz3gJ8Kov5rPrOD0UKVnFQi4gyADTyYLnKTfBmBPqk4SGcTVcBX8k8gc3FiM9S8bDCPI0+fVq6Xy33VY8VW6P+lmGIZpH1PF1tz51yDNOD2Lbqp9dtsk1OEH7BsVBd081IqSjm++t8ceJ/nNRDeqGANZiCw3LlVoda1Rz+HGL3tpFm4cOGnHudFyQ3a1Yg6g9sk90KIhcKogALZBptGupwtWDUek9FkCC1IjOdOoyWyKghQaS9zNWV+bR3a+mvXxuJoCQpVxbtt4rlTBlHZTMb4FpkRx0bayfy5Qs6zJQZYG3zK4iHyoSzahQNLVSMjD/F5dcdwIUqW70diTdH54dybHioqxFWbId5HvAFumsF0NDDWAfVxH15ICdA4JbVEMEwbqMyNy7ZfLmVGNBpA6xqOnUa0H3LP4tyrWaujRhuqGphuDrhmZI828yZ/WVtu4oQlwtAk0ADNRCIe8tTULKeR0c4wAibRJM5ebxGlUHFKPOg2YzUF/1od0LRYqPbb8UHDCzxwl3EyIWgVUnrjPwJbx9Cjp1Salkp0ITKdJE+hyvBgsQDXAAFvygm5KHI9G+6UaXt0QVsoBSeqixoMgsA3yKo90GDlvmvxO51GTpJXLWU4ENi/f/XyGUHUxc0B08emaZX/S/Yugl8aJNWts3YfFG8lGNYgw+71iU3ftEjS746H36+o5c+tlrnXG3cPEcGt4TeVTuq/qEmU1NDYzAzv5S18ZhlnElu43Bx64jYFhoYBFes3XcMpOnLjRtr7UGGfRokXmuoqjjz4aV1999fa9rmJreQy3F+21Vwd+/vNkQqkMuRu+uacvytJ5R1G6CUWRBfQKGLA3Q36hsaBqpaKABKwFS+BSqdjAUpUm9b5QQXqmM480+sMCQgDMHVJhWJ/CvxYWsXhxsjHuuWcKCDs7TUgpz/PpHs7xocIJ2CmWXVBI0ruKVJc24T/c/NSSqmMI2ChT0+qpUGPlrluLu50Itv5qPsvuqIqOarWqtaqZXzVo17rM/oirSbMvaviV5R1S14HWRVTEzzTUUD9zNzFRMnn2whgkZBNQ66d6/FwsxPLcC032WraDyqELvDj2OieKfqnQ63kRzmGanj8ME6/6QFDMlGxSKck6yKkIgow/G6XZLobZfXqAc/9WFJlzF4CEuDgKDN/lnlfl5q4hMxwGlTE6dXUKeBjanitmvnV3VtnQ1TtueYEZm6dz4vJIus4M4EpJIwEsb69qj3IPnF7zw6bRuq9GWY6DKvhh6FjOtZ36oBqJGnl1XBSNjL8N8JRIA8sIEob1WVJ1zNl3PRAr41+XtVHlmAt++Iy6PBRRq7ak+wpJDDTk16GAKUWb6uqAfcyOSifPNbOpvOjaEWeJMp2eN9L1wKMKOn35ar+dFZgPA7aXkQ3mXuoCTDVGsUGzZxtPmXXtgzRAPdD91TyWLrWHvFyuv1eTfVy6NKmK51pVdEVRlj+AzWeTSdwy2ORqNbuNSSMI+GPCC3WdNUIS/HGvSuD37H97u5GNHEq9+kXbyfYTYJGFXXsJYJ8gcZepyQugMocN4Etc9KfyTBuk67mRDGM9anBzx0MMED29eeMQZXEuO3oodZiBbC00NQGTxvRn3nN3jrQ/BL3u3KVhpFq/ddTI0RF0G2U7FfCSGMKrYonDwhBfEvcoBdFsoq4Lfudu6QS+VIGojljHCogGyfCqK7EQFQ4yWVsbOt7ylm0LDEeNwqLXvGbLyhaL/oJ7pVc6MNxzzw786leLjLwg3/KeI8C+raEYOiEIunIAe9NSq58q+qn1m6m3a8ibA9sUOjzIq8VVDwGS383hgFFgnukq2PH5Ev5UrcoVFjyEnpqFn1iapDHfeWdg0mAKCKMocRm2tmJZVzIOI0ZkVi+3e21tNuADbL3NWFfZcCBTvIDknSo0FcQ5sS5uf0xcuu7CbmhaqkRYZzop4SRsTI30apjVOwP5GWCH8qlgBJB5OLnR8UvxklgvlaxkRsFRcJQyqYJJQMCd9t/dqNIG18KifdYtJeMVcMNRZVNm+Airdy32UZSlPCcIYtfHjs2USuWbMJS5U5DN/3USyDuqRIepV1kvC+dYayhQCnbcYV+7th6ouIZRPut6VBt50YLAvnMLsMNvFStEkX1mmaTKpavAsy2cPvd8l/bBtaNUq9n1NTz7QeXfvaR9zRr7/Xwfn9Ox0Xk2V49QyybIlytweD+chjSrIqbjSeWUXk43LJPjT+OY6mM6j/q5jqNRwAEDbDTqgRZ7hrqpc4PlrRBiGjE0TtPV+lWB1Yao4kwgk3o8zcXypZLVT+vd7ppX2eMo3GrwYP18F8edPMnPCAqIP8g/mmwmCOx72saNS/YG5REgTXKl5/EUTfEzIi9XjutZOD1TsXJlEs46d26mbIqnuVFYN42BenVCMchkrpYh/3Gt8ZYq7Rvz0Cj/MrReVQU6yphwx71DVo1LDIUEsiGxojnEoFZ3gaE2hGNG/qBBNd0bB4IiVq9OQnUVX+nQG7mThs9TLgJZdFRfJW9AlrJ+dhYuW+/s0+jRafmgP3MpNbrCRQeXFROxcFNSQ4IKKVcwqIJCYZkqMwNB0ahBHGJdE9w7GBnG6ySnTpUrv7geKQP0mjEFibpG+SLd+zjprtzQ6AYyBcupfsp3pIZVdziCIItk06VoDKHi5rR0Ns6L7rucEzXuk0ql7MyQzikboUbucnmb32PYUSxi0ezZW1Y2n/fAUOmVDgw79toLi267zQoFMem+1UUG2HcOhKF5nqFF/IoCQ+Uz+Z8WOj5vgEckIZS6wKlgpQXMdQDpohoIm00Cg3I5DYOgoJfkBJQdLdHzpq99aEZnZ3KGsLn3maR/KVjsC1qwdGmm4+iGNmuWeFYoGFLrF/tpQmMpNFTzZf9cz5da2lQA9vYmyn+lD7VSs2VY1s3dtEeUUr1029IKUuGsoWi8rNqcc2P73Ul0fxwwHAQwZxLdou69SvSuqGBWgG3dtRTWnxdUL5TyID8LQ1Eqw9AO/+FmwoaXStY5EMs7ocYN3S3T8w36fipInD4NU9M2NtJfFKy4SibXDa3YeoaqWs1AS6kE+y4+RWSK+NyNTPulXijlA1fRaARa3b/dzqr1wUVXqadKWZVfNZIn2i0LJKRrmWeRGDJMcOvyCf9n103IG8eG7eUGXq2aKyn0ETXW57ufz15CxU3Ppen4iXHGBdau8YGk4VQ6Je70EOip/sy/KTu1exZoUMWHTKkATOdN5V8lyWbL9WSAHAbq+Yyd1PdQjrkTxfexvCqVQWArn27aai3HOdF61SDjGDfVsOFiUJeHVOdT3TaKYIBHeioBpVIGfjinNBi0tTU+H861ruF1ra3p2fzFi+1QTO23rjfyH/cKysYwOe9Vd7eq8io7leoJzLIbRQng5X2Ehg+CAD3VosGvNAZxKVlnlNNOMqqDCUT1TnvyPKeqVEoMb6NGZV1vCfutxWKOTjAaQT2ROqkcUBph26aliUuybKMcQgIiF7uR9RiKzLDK5urz9h2BaeN5RRHPPKq4GTvWznbpTiOPOKoM4JZm9ljdBxQcKlKn3qdGflfgkKijpR7Y3t7EJrFmjZ2che1tbU36QeNWW1t2l3NLWRwN5bIxvtIAQ0O/4Q0yhIIx9bgqEFNZ4soWNlANCpTLroHZtQqoDNS9VX+4uGXSrOMzyizk+XSvYle2+RnDUgmL9tpry8oODHhgqPSKB4Z7741Fv/51veDQUB4AiCL0BS3G4AHYFnldH4zJL0Z99ZYeSjT1aLW2mpTpzaUsCyY3Bgq6MEw21kkTasZDFYbI7qJLNzlzMDjInmupLgMefxyYMQN9rTPx978ngmr38rLMW9fWhlrbFHN1I3XjKErAY777+fqL3VTZVhMzN1ACNGTWKHOxfNDAIqsHqDlOqQAmdi/CTs7DUDAOs1pbmbSB7yaYUk+BtTnwQbF61VonWjqTEtnD9Cktr0DRDb+gYqNnMYMgmXsDZJmAKFWYySrGC6lCN6WBoGgBBrbPKPtypsQkJHABkyqDKTBlqKXur6zbSuLDD7nRqIGDDWHbBaCRRzk2GpWoVSqpR1/DxghW9IyrdlGmyALq/FzZV88D83Pj+Xa1YjGOqFeLfWI/NDyzzgTtKjAsBNhKvc4T16AqgbLBGsDobvbKHPybxhoXeLj8oQqz8Ch1FFXuVc/QrvEKA0ujVAqdy8uRgRMzBy7gkTG3DCr8HQTZhepRlJ3lhp0swZ0/A/bIZ6ET3ivnw9lRrjG3Pf3VvJUsRfcQ9doGQaY8cgqs8FR3DhQlaIQFSTetBmNbh7x1Q2ttNQYpsoI5u5zKUD0WoECQY6DigYYK3onneuK1W2ooAjJ9U68pIQsQXMyalYayVaswdwBxg+C46Q32Mi7W3u96Xji27e2olZIEboUo9XzSLaoyLuUDV3byyAebwPA+BdPsL6s1xk8k0QE0aBDL6NLkMmbTW1uzTJC8coVzR68fE9OZMVNE6lrhmPo1zeiqx2vcIQuCVHeI5FymTjStz1yn5bK5LmUgKFpeRjZPDcPcBjm2avfkFhQEGYBkVzR8VnBwZlTkXAKZ7JNrXuosH1x7kpSPa33Nmqzd7tYBZDxOfUWPcOiJF/aLr3FsN8Y4wj1Qm18qwc7R4CoKehwH2T6qaqqOt7aHxMgOV0QB2TVYelURy1POOdsYjjxyGwPD5mYskisnhlW2r2/HA4YzZ84c8runn34ao0ePRivTPruV53L45z//+eJa+BLSPvt04Be/WGQECh2BNLwC2frnXS0a4TKlTQSqHuBIr7qgsq+bqoZZcP92jZHlciYoKAxoXRootViLrxBlCsuyrryR4exPYekTRqAv6Spi9Og0G+njjycPzZiBvqhoBBJ1w7Fj07CIzmcy4d3eXn8uTH+nwoVCkR4tCxCSXDAZBOgLWozsampKLJXpXmwZfilEmFacWTqZpls3YwWMikk4rtbZIi0chlayHiUVYqtXZ/1UT6FRGIl01FqpCi0nPKW6UDFH0hqlTpV4VWTUspc+z4yRVKgotGlVNees6GmjRk+GBWxrKpBl4msQhkLdyigh1X70pReSu2DNeDQVxQaZd9wAWXl/rdRsvLuqdOo5QAWcnC8Os4uvtO0anskQRZc9dNNThY/jrfq18msjJ5AacU0YuJ4lZIMVCJLUqKFAQMdTG+KGvat2JI2tmTvqGvfNGmt3p2d9YWidMdOm6WPuOOpvi08CB8ggu5rEeOIj2+ikiYfMeGlItzZILeNBYHnnGRLoeqipCNF7SbnLJirw037ye5ZlyCpgZyLVPYH1jB5tv9dVdtevlzPmEplgNh1qd/yb4xGG9tlSVXxdxKZyR2Uan2lrQz+StemGliovqePGle9sgir8rq5eLtuZhMtlWMZbVwmfMcMWp/lqCuyWLrXBH7VpbQjDIBiuyUwsUZSVZ5ZRd5HT3aaAnagpjSPVUN7Vq5M+6bbBdcA9zD0D7B7DJFUqdh4ARlUA2W0dUWSfLWUd5XKq1DMUknrA+vXJ37zYkJOixu9SKbsTMzXKKE6ngYB3fJZK6ZVUtEwzE5DymV6irPsnn+HY8++0oyb6Jn2WV5LovYy8GkyvrlLxqEDMWiPkB/XCarvEQK77vGFgtRyr4OP+Lv1hKD4z87qy1BXnfI0aD3iukMSMv/pqvlaT/eh3/F4juVVlIH+psYtT5Noi1ThrEg0GNXTst9+2BYZjx2LR61+/ZWWff37HA4b5vHtDzDAqz+UwqKddX2Y0Z04Hbr99URK2Uu23wqMsr1K1mgApbh405Yjppl8u5QWSRbFqVbaBjxtnR67o3mqFZjpelv6g2QIzYZhmBUvf34+iCWGYMUO+o9Roa8OK9c345z+BOXPSkI7FixMPx+zdzaO8KDc9WphdUcE+t7fbyhbBU7qh6ebODKmmH9SSFODIBbS6+auCANhRvUAW8UoBXUPeZOJsdL2CtRNJAhPVl9jEKEoUL0DAXlizhT37AmQSt7UVqFSssNBKJdvH2C/iLOMxUSVLgZ2gWBM+nIKdOm+n6+FR6Suog15bx7lh2JhkQCdgNiN2nRQESC6UBuywLF0A5BuOl5xVsHYtYe6+KLsvMggy3SAM6zMEkg8A27Ct1mBdN4qTlEe4/womrVOuWMYdB/7vvo/P67uBTKHQc6KKTxp5kvkO7X+j8Elu1iZZlno+0jEnD7h9YKSClcVVtQu+RNeBZiABoILTnCtUpY2klyu7Wo2LCJRRYYNubZY7D+rJ0u+V3Tj2XV2ZzqbNNTLZYQidO1fuqbHBnP1NyT0GUIeWG1kM+BIFbdWqucsMyLJPu3YAd9h5jMEcOVCjj861rlllYjVE8SWuIYrPuu4KmWM1lLoABqgPEeZ88dWuV4j1sMn0wOgW6M4N61NeCMM0BDPdyzn/GpFCJbg5HMiAUhgmAEjP8emekxqKrdBdAixFbC+8kKFoxt7TRcp06EDyGX90/aTyl14Zc21WOo991UJdnhRON6vQ6WU39NinihOdXovn9SXuHuf+n/aNUQ7u9RnKanyfi6WCwDn6wE2dvwFb8KsA1HDrFMj2RUUztcqf3MsrFTtpD/moXJZ9nf1XPtAG8zN3M9bx4f+6lvRHEZwYsfMVuW5GmJtgmKReaso/M4/MKN7AWmMdhUkLq4EOsBOzkdgN1TWUjLxM+bjjyCO3LTBsacGiN75xy8ouWbLjAcPf/e53L+oF8+fPf1HlX0rq2GcfLPrJTzIJp0BGtYhqFbW2KWYtqy6uglPlNLO4ERSqbDJgg1ZI1UxUGaHmQuskkFgn29rQHzRbOkuh93lbiJTLWNZdMCEr00o9VqaAnmrRGECffTZp466zUlDAdF1haEJngOzsjJXZkgqgaripwO2rZqmw3U2HjxOIjRvnZCbVHbtSscJ1rHOAjsavIZWFKMsoa8Jgg8A6F8I54d8a6qWARO/gqQsTEwXCiqMP7VTOQHZAXwWnGgqsZDIKElNywxWjKEuhbt6vyrqCWABobTXZ6VSpYjt0PNSbZzae1MJHgOuGYrK86Yuzjox1RJVjbsz8XsF3CkLqQgmrVRM2bQBRkGVdte5ocjsZRdlzYRbupsqpm8XU1eX1vJ4uWy5n6gQso846BSFqxHCT1Oi4CkZo2C2+X68g4XvVuKL6P3mN8+kaZRpRHX+mlVrnpIT3rcRQqdLNabBCPtlxNdU3MomL0qRGC465TLH1Hd+ndxEahTIMjdFF+ZjjbYHl9Au9A9FSlKgsUUal/eDxAB1fF0Aa8KcAS4W8KpWqbCtAU+YJs1BtN5KSMqfOA8WF4GYJVQHOOXCRnaILVdAbAF3LgMU65bNaqTk7s52u0XxV7giWOnnOn6JDxQur1H2IXhPiLw2927AhSxaj61jXHvmMZ+mCIIsyohjj3squSaoAiy+tKAHd9wk0ic6oI7BD3KhoqNZInra2+uMbauRN54jn/3S50QMbBHZmZZ1ijpWeIlAgp1MaRZmXW9nAApG6QXLSeM5RvNjuGXttl6pNGp6r/QAyA6LRN6iv9PbCygLoImUZ/1pYNIbfdetsR6FrJNKlG4Z24h0VdYBkonUr4m9VWtzvXeOMAlS1gujEcOzVCKQhcfxeveg6RyKb1YDtXs/W2ZkBZz0+BDhOEdYNbPvkM+PHY9Gxx25Z2cce2/GA4auZOubNw2/vegBAtk40mgRIBCXTV+u60Lveo0jOhelOQgHf1mZf4MKYbi5A3dwpvHXRsp4wRA9arEuKC5WeTDKmFi+G05RKwLS2gSxcJg3tWLG+GevWZccLd945Tb/86KNmFxtom2Yyppk7cFRYitBkKAuQPcYN2tHlzFhbnjiVjqL0WQIkGLCvORAQAEh9AoCoBHIom0s1ewd3NUhVVFT4iQLiGvPCUJJKSD9qQSHz3rL+Bgey+ZUa790mGCugIpD0fhUmuACSR3jJLnmVSQDMS0QjMWAyVZh1T1IQbJUVrctKmEMShV0VcZIJ3aUynCowxWAg2ZhpDuY6Ug9jo3njulEgmT5nzkGpsusyZAOrqPJhQ+TsagHaDt2cpS49d6ZfscmsjuPpZt5U3lDdX5NWGHAG1ClUJOvCa+EBV+/ge/Wie/3crGF+qGPprmsX5Upb3cuu+S5XVzAKbqPxlYdcg401V6qlaYdV/irIUnL50rXkp31k2JoaTNSA786f20cdY5bRcnyWXl5ESRIyE27Ntikg0wrl3LL+RFF2ITeVambIrrt7URvtyk1lZterTFJlVcdd63dkPUrp5fCMaNB3az/dte3OVcojbIIadukN4iXlOgeu7hxFWQLvUik7gqJ2L8uLFCXGBJ6bS4NM6qaKw6N8o8PERCbmKhoertR9hm5VNkQVFbUGCI/3Ve3rRnQpuMvGFZNqLORzWlajsFw+Z5OMEYWhmYq2OOAEtzqn2iiVwQqkWV74gNFhypLkeTO+rhzTNqmlQcFsqWTOgarhwfXs832NjITaLbaH09louwqCxtEoluFNrR9uYTXGNtrjgiCL0eZEqsLCZ+k55/fsmEYLuaCUxmvlSwAdhx++bYHhhAlY9G//tmVlH3hgxwOGp59+Og466CCcfvrp26pN24z23rsDf/zjIsO/BIXNoX2XmKXspl4zswuQuWmWB7KyjHvo7s48XoC9kaaLwVjXaSFUKZACADYn3/18FneRLtSe8kyz9mfNShVwBvVXKsDs2UC5jGc68+jsTKxmM2YAk3JZaCk9k7WgkPRTrMB9aDZhV3rOhUNAS6x72SpQf18eN0nznQr0VNiaC4F1R0qVGmNdFUWQ7WgpDWSKhexEtbCIlSsTpWdK64BlzmUygUZKmgVkuMFTQUnHh5noqOiqsqF32FEGl0r2WRsgU2QV7Or4sk3G2kkwSq+zCu0wtDwjQHZuxVwtQuVBD7lqP9MO0CtHOa46l+ug0DlnGXrumCKf/bdCR9LCaok1WdvIL5qlVdOequLrTKCCDs6HFnOTm9Tdf8ZOuJZjV/NxtSW+TBlJG6Ln3Ny603J1CUJQn1xFz6Oyb8ZQouddRUHgOnDP02iztTv0RmsTlT91SLRLqperN9eyirtngBpUqOcaXQXKPZ9izYk+mDbaCpXV7xW4NOAjPmPGU707it44d25IripfLlAT0ODOgYtRXTys4EHPObo8QZ3PutZFK+FL0gmjkYgZhQHbA07M5+rkOmRGsaYxR4FetWq7LVWZ13lQhlIBpGPIZ+j5AbJEJ643SjcmnRvWl+6n5lofGQ9nigEkoK+/mjdgr73dPkuvxs3u7sxbFIaJPKbnqNFdxcqGvb129lbV81WkaGCRieSpVDJjKH/Yb8oh3QOCIDNcy340lCgjb2q0BQ2TYZjxAfdYTq2b/Mi6DzqQM8OOHNWrRRRYqljmZ5axXs/W8jPWzRBgBSjqgXWNQI3InRRtiA5ems2+FhSsRDOc72rV9nCuW2eLF65ldx4AG2Qqn2oz+ByJV55FkW14Uz2Ezbfknk6+Nk5BI1/KbIaushCGJmybeSlIxx67jZPPTJqERSeeuGVl7713xwOGr/TMoxujjnnzsOg3v6nf1VQg6N1AKlgpPHiCW0JcqODqAlb5AmSggZnnuK7cdPzNQX+2MWrwe3u7ua7Cer76fOYd4e7d3m4yoTGJ2q6zagkg7O422V36SxMBpAfOgyTsi0nKAPtsAePsw1CyU5J0gyfojbINE4CdfkutVBpSSyFTrSYewNTLQG8Ilfl+JGGx+Wo/VqwtmgP2nD4mpmHGsSXdSWjs6NHp5xpTHwR1mdb0PqkgyMJF+6q2t446jHs8R+e9peQIYi0owNjSAuXgOa2Qrp4EpBng6KXkDkLvqhOmyLJWKIdulq75WtdHEGSZ+YKadT8SH2P4FxPfGM+6hJsY5Svtc1+1kBhlUsOIlf2R56IArFjfnMwb6i/RBhqEKLq7ZDqm1ninA+N6qo2SoedYAjtUkGdbVaHTYaSCY8q44UJCei4OEMMJO+mC0CDLfsj2amixGnb5OuvaFAjgdBUx6dBQ3mG9FocGD9dbxuHW9PUcUzdpTJ22w47pmkj/5ruN11TaasYP9e2lDNFlx1cOZbCxjAGipLrXa1SrEr2g86RtdzVrt25pkAvuOV4azs/xd3lP9xiSq6daZ8ZZkY5/KtAUuJKn1q/Pwu6ZLI1/K4jR4+XWnKsi7SqbKn9cr6Bmu9DJcw2usp4LEIOEMqWOtWQb5ZEEyysubh7DH5U+s9cOhM1mm25gLzD39fX22hlX6anU8QOyoyiNQtYVz1ardgJWBUk8tqiJ81rC/uzIiDv3Ov5kFiIJjd5IPWN8B6NaOcScWo5FGuBiqSYagcWxaWQb0Cnm9KkY1HFwtyvlS5VHuk/zf3Mu0wV4LExSXqWVhBnYG9wRagZEeU95kA9zvDkPjeSHlmEn00XGIyquCqu6ZaMjEhRJ5B+1GdPgr3c2ch61W7yrmE3W+2BXrbKbGkWZWs13U1UBEpX6LW/ZxsCwrQ2LTjlly8r+9rceGL6aqGPOHCy69dZMAGh+dbUOyW9e4MoiLvjjQqFXndhMkxlYyRl0U1OJxncy/j3dkHoqBbPZaz6AKaW+BOjpCqtWgRkzsKwrj6VLkyoOOAAodGX3Fg60zzQLNN+beOgGwmZ0dyePrF+f3Bs8rb1mX9TDdurfHDMVqHo/o5ZJB6+GvJUAhM5VFVYUduqUBTJLK++LojcESIRRGAIzZzQIp6v21SXkUAXeUtzFEMCzLLoBKggC6sNqSJwnhu+OGJFlBCORBdS5HASpcYDtSkEyG619XrMmE7ajR6eeRaa55086uNxE9AwlLXZUWFSJNBlLFUC6h/cBS3vRZE58RJXZ3l47A6PqemaOUsTBpEFAolzynCS9igoQVXmilZNgPwzlbEmq8LqJQiwgxv9djSudVFXUyfaN9nTXOajV61k/8hBQn2xFr3qxdnY3hktD+GRu/j97fx8l11WficKPS1ulo9JRqVQqqcvtstKItmjLwpbtNiiMw3iIFxBCCDATMJmZfDAZyExWPmaSmTA377pDZm4uN3kZFsMkM1m8N0wWIYEkLEiCQxwwgwYcMKZjNLawFbsRHdFud6tLrXKrXDouHZXfP/Z+9n727pINSiIYzFmrV3dXnbPP/vjt3/49v08fB6JjlH3g35E8pwkHxpUmUO8hXmoVV4FFZUsqWfhu3dtsX5XSCmh4qfdA1Fc34bT2bADFAkbTpFXqWcV+cU1Js5HVnsoSAYopYNR36/j9GDjIlHgUYKoSifcDkXRFfsaP2T09s9LMhJq4iR4Ofv+kte90gcb1WTbgKK/7LnOfk3XRM42PM89KpEDknCafbYh/1O908fSQzuIaoXzUZ/XWszit56YHrRJKlmGtZ2mnnolXjNYmEAXUqNGMLVom0ArLAqVDAsL21pqcvCisE8BqtlclG57npAsdiuIbH/unZST0MEuVF+NAOemBrpWNPX6K6VJJcmIzOlVlacf6xBP2M6VXVdDq8UNwmsZFUoagMpsgUWWLtH4igSr3AxCHc3qFciEAO1VCEnmyg7xSUKffu/8vVsc1nV7PN9IQCVl88vxxCk+NkdQlTV3KSTd67IwLN1QyYVe4HsyyS53OmGFbvu3M77Ovec3lBYZXXYW5t7710p79kz/5DjD8drpuumkWR47MRcVbldCV2PV8lnI10eUPMG5UHmAUyBV0quSTMg9VtVGoy+qRIqvRcIBB1WRkxsZgqWeFco6t0wEOtE4FJjYzE1naWNeLwcLscr1ci1VI2n/+rZcAPv6rDImPzs8HANTMLINjHwZlcF+hzMOkLTpVKpNwrZq5uCgWhbeC6jmWZfBuqqkbqcpdKlipYFyWIlCYONZOAahMxwamTFDGDHpc6nPnAqhVZQMPQ2rwfNZUDOL1dzTAOAemtmax4GrvVGjcDXJg6r6ekLrBssl07XhAVvrrcZpAPRCNCRZuTrq6R6viRYlEE82UQej3NR4Z75SaexTMiHSlMXTsKq3r3r1OB5lKVUoIukfTi9+p1j0VllOhXwlO50D3lJzYmnY9cr0SsDfM6pHMboxT+AjI1tT43gIoVuY0JjFNJ65DYveVtsn6ytIKY7t3h+80dNS7FTvFTjpHG6x2MjcKvtIlozsyENfIU9kpXcrUUKmJINOl4DuAOCX7uOXl+kRlbFxjKa8QTOWfTQEx+UzEizRhTdrRcqMFNS0az/Er3uLjBIwKKDVcINqnOhBK3twPTkjWpCj6W0PwWbqDF2Ozsiy4tzqPvGgtU5rUdygIGXd0RfOYWnQdgfsYXjZGIteDSs9hvoBEr9YojfNT3qUDGUcAcihRoaH6Ws3Kqt1vNGKXbu6Rp57aeC5xm1HGifIBUN7QlLBKRMoHOZd0U+L4qDF3OQ8GZdUDRoIHZZ3atNKM0i+nXK/0XsVMqVVbuwwEAKvvUNrhcnKOebRRNsxzx3dTE6q+KO0U/be19gwQ/P31AKbFQTtzMW00EHkOaVIkLz9ov3QyVUaVBYm8THifrjmROyeY/IB94edcIGU+rRZmX//6ywsMOx3M/czPXNqzf/AH3wGG307XgQOzuPPOOX/I1LKRtwjqHvQaaG4+PQxSiYgae+GuPuZBNpUeZmoh4F5hDAIZP5kZNVd8tpY5S57LNtnvA48/bnkJE5p2OkCzPBUYUAJECcgemq+i27Wxh3tbA3gzI7ldckBtKChdlpFb2waXPmWC9Dt3nw9NzVpyXP8Y5+ItD8pYOHhjvPuOJmPgg0zKkCZAodafAo4KWqyPp1YRP9fMdJmFLIYcngodGzILptY0/g3EMaVk8DyVRYpmn3hwElRq/0jH3hpNM06WYa2wiQ8aDVd/kx3XRqUeKWMglG9znCqI8zD01lt1leRD9CPi+PgeKil0v/AQoeCkBx7voelYkxFww6pEpFYDsRCmIRBqkUiTh/CKLPwK3hKkoaBLryhxiiNGBQbaZFTqIZWQUtTXD2VShqgGIV1pzdHfhnIn+mK3qNp/TqfX5ur4ST/jEBYFAveb1hC2o26cqTFC3TA1rnQDr0EinOja69h0rpT3mdi92vMPvZ9zk0qhKnBx7wBRRmSmhmeZIo6PP956bZ7ZwqjAToEw29Pf/hnV7iRKIHYgjd1U+lMAX5aBV1JOVc+EVKeZ9gcQcKE8j4KgCsjc20rjgHdjFd2FZ5OpEVP5b5Q9W11mpYNptmW+lu1qJsW0xiP3HdulhTR6H+/Xxdf9w/2SWoOBGEilqDelSeFtyvaUb+vxneeO5oEohlIximIZ/Y5unzo3ylN9Yhx9mCZLLiJRaZqmk26ZShv8W2WQLPP7jbSY1kpOebEq91Oa93Sjzyf0oMunZ2JRhL2hXkDERpwfDo/fMZRzAz9OkXpq2kzPBnWlSrUiqeGA6bR5tVobEwsCG/2Sx/ES1d7zMwrNShQp8fE+/d5NDLMoX/YC93v3Yu4XfuHSnn3/+78DDL+drtkbbsDcn/1Z2DhZttEsn2oPqRoiUZOgy5gJ0bWhKOze436kHMFDlZq7NFZjnMyVZUHGrmUhO9vA1H0sIF2Bdu1ymUaLIqRPc1o6bymUmJ+FBdvPyXw9MHD6dGoHBEABiE8MIDAi3j9OVSugGWXpA5C9q5sCFj7T6fiC5tVCYtPUhOoOj5XVik1eYtaDGxCZldNa65JTO6iujjx7VVjSDOEkDfXbV4FI7ycpCU4DEHijMSEIvNez7pHjakaOEwZUSlwvqv6A8vGfTALhBLFhey8WF8Ph7oExzcukaabZY0cp/DqNP91On3giHIy7d8dYRDEez3+mrubypTIRkxd0OvGBGgHvIpRNGQtY5P9RezLaF6klOpX3PQjSdox1RVVDpbpKqvAObIxrgzFxXOwYEMBb9Xq27KR8xsfdppYbd7O+k+1oUqUotb1mLU0tl44ON7j3qfDCe1WBxoNfQBkFayAWulSGSfVuCc6NhXV+oDzB8etBUYmFVeVVqsV2L1Wlj7qGq85GljYotPghaVOt0cYgzQCr8pbKYTrlvBSgp669bC+qvYgkoVIq+ae8hC8Us6daFmXZNpCYNkueqOUCuBzkBYqNOP5WS+rf6uTo4JVYgI0mP63YThpUxZwx0T5Nj6QoVlUJkW2IHMC5VXBSL9fivqbPJkqkiA7loImSHPHS8XNj6GGyuBgH9KkQ7/j3ADV/Jo3bnum0pvxK9a6UU3ivWs7ZjXSv6HxnGUKCO1W46826UONoVeUyNTOOm990Y/FMUxlFP1dgpWtAGcLxc63Zx1vpfkqLY7rf+UPSUDdYlSXInpScSEJ0yVavI107hqrwmSxDkLFMzCdWVit+7bw7d9qgm1cvgyUx91pbVdNHjLPMqgjNe9VgmOfA619/mYHhd30X5n7ply7t2fe+97kJDPM8R0usCV9341dcga985SuX3Lm/62v2hS/E3Kc+5bVt5A+RZtDE2Q25uUnUJHBqgpiUhfybLkl5HnDOuFgBXvxMg7XbbdmsDvyohMv4qqIQMKRmfABotfw4KECw6O2WLQ5ELiyEznY69rk8x1qv4pnYOFcPnnlkFsxkCcTKTpZO0H5EQpv2F/BjS5PfMDtqUVjrptYe5AFXxdADpShmhrFyqRZLDg4VxpU/qqC6wSqoCQnU95/vIjccl6FLYuiqGGKtH8piRMka3CLQ4uLjWgBvFa301yN3QHV5274dqJUhvk4zjmZZksVNwTtjThIAHs2dCTGFWoydAiJpn7G3OnWcV8ozZ89ad7Esi93XgHhNePhFafV5E4lOQU7qxpWaHhR9JsKpJtsZZykfqwDRz3TudNI5fyLMUDBUEtF05PwsBXs6dA2LUpDj13ec25q831uexoFDzmFRRCVX+FszogIiALIzis5TlAB4Lwt+pF1IQXXKkyko8eK+VdmPQ0mVBFwSxmspXy2KWMhJp4TtABJ7qJ3U38pI3IPjYg+VrIhzuI/TdyZLGP3WmMto4ylI5ED5YErLrt9a4iYtUWBMsN5GAqhcrG2rZETSSF/PqdL5oJupKlJ37nTvLgbxzSphJ/MfufZycl0IhMYce75sxrst+3c6RUfqaQKIN0Wq6MPG5EJ66TnkLemqlBZNZlSmoLe2kQ8pLyLvyzKv0NYwFTU6AaHWsLoQXyyWnkcDFd7MqqlLkRwb/nvvgqmeRryRY2AD7KwSfbrOHAzjJNKOaqY/DlC19krYqjFWrb6jJyoOOR6NTSTd6qt4MZmcsmH+r3G/vDcdaqqDUP1DqgPTZxQwppiZrslCJpFYRuWzKn/Uc5qWW1WEpRnbuQT83ita3dpd9jqG+/Zh7v/6vy7t2Xe967kJDC+58SuuwAU9pb/FrhtumMUnPjEXWU5oytYzlEKWCqJpunfNPKgMQonf15TjC5TJpQ+pD4K6VmgymlbLW/zqucsyquokp6mkwN7MbaHbUXsSx4/br32dQw7SuY0yo+TFEhPoOaMxdOTB5LnUiNHFgs+xjhMQGJQmSSMjIrDrdMbLKpT7J9sbBUYySi3aCwSMFsU2sWHlgCq9qLUDCKdfKpmqmlSEfArlmhWRj2oWSd6bWoo8g6W1FMFVhiSSyByRVUGMhhF4Zn8GhS1jsmOHcxOSki0+QQsQa3bTWAH1YVJ3ErfAPlGQupGR5gBf9oNf8WvNvJuGX9DFjVpTPVSZ7MJnJEzNUSQ+cQeMiEv7mBKeCiu6CbTzCp5T4KgMhv1QAV2FODMmCcc4sKECjKpt2V8KM6L5Js+Ksm8mCCPKDiulZ2gVG5padKgzW6/fY05RYUz4H4DnOetlLZoWBRjROFWiTIHXRcBVmmQmvegtQG95LgmXz1voXEbjaF6y0G+VPynIqSyqVpgNG1vpMl1bvU/G6vuRAiGEkAQlL/JuWh39enB+lOb03emlwjovrqeiVDc/vN1n99SOuUnmfQpQUjasS6/CrGKF1HCk3eTvarEev59zqN4X6jri7hnnyqwJY8aBHvZdl5dKYZ55Y90IU+QkczoW0JMna9IDbcsBF2/lobyhJinOgTE2KZ14hjBBScpq3K0byIHsX49WJSVldewqq3/psPV5vfidWse476i4URp5RmUeO6xzlvrR6uB08DoA3egpUhI5QF+rvIr0wxhaFTO06ZRVeAsfx5Hyh1SA4H1OOaJADYjJAYjDHHWo6TGpr2df9djkuLVtLwtL6Roqq1/ykstsMZyextyv/dqlPft//9/PTWD4yle+Er/4i794SS/4+3//71/Sc5fjuuGGWfzZn9kFVTN+WcZaEQ2BMkY076KWV22ht8qIZj1Sz6hFJt247rDULIFRoonSZcKSWAx1U/N9kPpBWnNv5WwNTz5prTO1/qnItElwQkCYKs0iV7XksByXSAEIeDeVrTUMhvfoIeNBEw/yPMdav2o1S5Jsg+PjHKysVjyIYHyPKlo5/Tt2WAbM7J26HJHGn0J2qjEEfJkG1YCnMR4pFmDGLy3h4EJEo/lShqokw/NGcUPkLibxZFoqTGO31CLJ+U7rMqaacbqOUtgljenhUs+G4+sqFkXImEuzoAo11Na39mzQQKuFOsVRmkWV/aXSpixjb1ilq1QTylBFPVPL0rZFLS215uoexHZS4x8QBECdQ90DzGQKhINd4xu9AJOYZNL6lGmM3tmzG+lehWm61VKA0r3JMaRrn8qr/IzPq8srIG5GQAQao/HyhdxbbkG8C6bySAXRZBjjBLS089wP4yTTtE2VNEl4/F//VvCQPqPvcLxJdYDavZQfRiBtnMSoDGEcYNPxaKPCt8YBY06xrqF355d96mv7KXBUZYRuinFKD9lYaamNyJLG/us86/jGzbUxPoEJLypu1WLDvcuMk2xWycif7TrnuuHcQ77WrxtzND/uIFOX32hcTvGqgrS+QmlD3f7oKaJdis7KJEuuH4eeXcAGkOLlGu47RWhcA1GkrfcrPmuoZjrlLaovpKIxpbkUR0X1go2JFKO8VFkwDlzpkunc0vVVvbRSyx0QA3aGWrBtD+IVMKoVM913MhZ/r8ZIagdT3/TkcKbiLnVbLYq4lIRa0amIZ5P0ZEstmakHLkM7yLP0b3aLMim9mJjngXRLZUI6Ba1WnKDPy3E6d25eZl/+8ssLDK+5BnP/+T9f2rP/5//53ASG37YxhjfeiLn/+T/9ZoxicDCKuY9yYaIMJ80Py0pIge8kUgrMdaxjYOoWLLodNsxsbA0ZubpjkX94RpllocaBe++wvRdnzoSNPrHd1jr07jtFgQFqFhwuL3vgt9StYtMmYGLzWhSPMCirXsjn7UDgVyroqRaYB9darxKFUeiUpTJX9CxBrjJCldbbbQxNzTMdAlO1rgExmMrz4C46zJv2GfqeclDGYB11/ywQDgoFGerySGGahsLz520ZD50nQFJ+p51Txkf/Yj0g9DRVjsxGXUeGuU15zphVWmNJNz4BjdakcwtDazhfzwOTF5UBzYaNMxtkzSCcUMuIkBRIE9Nx2VTA0YNdk63pvPM+wJVESbPdiSS91g/rfu6cBUBAOGA0zpduTI1G7F6oQLso7HzpoZp6aSlN65nNpdPM9KkyQAFBCjwpfACxkMorAv4qXMpNkSVPrEBpXCb7QGVXut4a56kypdI9+5TuZRXWdE8qMFZZ9ezZQLc7dwq/K63rN4cYWZjYMbdHWCJAyWRDnTrd7+wcX6aTopKkCsRpbZwUrClxp8kyUsGc+5fvRwANKuwrzbAZNUSnMa2eLjjmFJAl9AIggANx60oBgk4Lp7BSDKK2IoujESVhMYjnLZ1jJSLdIPrCdB71szxk1dX3b1AkIK4vytdo/CNvp3CsHodK+ymIJ0iISh05yzkwRuBNQOyGMSvoFdoZB+B0StOpJd3QI0Zf7csWyTz69yVKA536CDDqurLPuqbKAAjwnHJEv9bcBmlMfMovtD/jSsF4OU0AJRBcWVMPUp1PXjq3nB5O1Tg+pmCK7q8brLG6SClgTC91ndJOpciffCnd39p5rksaRHox/qX8gm2lwpUuYGrs0P6z33wP368hFPruVEEstHnZy1W84AWY+2//7dKe/bf/9jvA8Nvpmr3xRsz9xV/Yf3SzAbGqREyGWnOLvFW1/xq+w88r/fWNmQMBL2hH8YO6QcjlHdCslEMsda3VrJ4NfRIVJv7w8Q7Ot5CpiVkzamoKqPdO2u87nSjW7eRy1fMdlclrxRoAYNRoRhiOjDqtH6cymTEh4JnTGsUTljbxjL6PZSkA+zeTalBrxsQyKmBHNfYYX8kgUB68KrzpumYhA2qaNCG1AnF8k61hTABFYS1iejIrqvja18Lp0unYBeHpokBQhWAuBNEHENR+KQonzUxPY9jZF2W05bRoQptBGeK/UsFegSbLiejhrfOSZtrlHCkdUKhUd8EowJ3roEK7ZhvVA0WDern4qolV8xiRL/1mpX11dbxYibLUpYZzxTFQiASCm56nRyespAoflQmV1qgj0CLBlN1UpizLJPurdMxnV1QXTGN8IhUNFyRr4zRym9DCooqO1L0yPd9TD1qO8WKZyrdsCQWP8zxWUpB1qbKGbv68mO1z+/a4n9x2ZGnUBakcRUUAL3UxAwI/Kwq7Xzh3KT70/D2x7o4TWn0mWI2bUkFsHNM0cXZYPjYOtBFoK6/l/To/G5QLKh27d5IX80xJLRFcM2/lUbc8XmknU20RO6fvTrUtKdpRIVOJThEbP9MsFqk50F3q3aKJMunNoWEH3CcaI5YWCedckU4VUOo+02eUt3g5IbWcpgBAF17HpXMO65I/jsS0CZ+UTN0mUx7KSzbRhrIrY9Y+svqnjHQcWHFERSUJL22ac6pu2vp5+rd2SV+XAk4gtmKl32k76dIoGDcmVvQpXttQszrtiG5UZdTaGYYPpftKO5a2zclUl5tUQ69hMnxnqqzXSeA7UjStf6sMS6YOxPKKCnCuf3peXnZX0pkZzF0ixpn9mZ/5DjD8drpmZ2cxd999AOJDXWO8zpyJXQ295jSVklItoGqNqFYCLr6hRZNcFMFNTgPryfDz3Lp70h0xCrpHcElbWraAZ2oKqHaXfCabgal7gYcCrmBEGBMSkbB+IruoZ1M6FGM21kVj5sHIAusOAQoX3oVJ4ueYqRTdbhxAp26dmi+aaa6NCQledA16PQvKmCNaBbKyDGCNV2oC63btpG/daieUn1ET0GgEQNPvhyxxKp3Sn4n0wlOOPisKAHu9WEpXrZsWIOb3ExPBf6TV8jWi+P5RZ68/xOrZMKZX0cLrOmq8LZdUD2gFMbz0rKOwLyGx3s1Eq3NMtobevUxIxH/faACV7qnwIqIOp+k2xoFUDVLlyUzCVi2nxt+p4kcFrdQHmnMlByZjjHw2yGROI6swP9f2SbNlGbnkpixE3aA0UW+6DznvmtmYwgoTlvCeshSXILU8AV5xwC0QWS11HmCtd808WE9Ufuff9VwynTolwCir+bHUjSQ94lqJ2xUVRV6gda70tDrwPcvLlgRY55PNkBRYSFznd5yxT1mHZncfpziIhD/H1yKXPvc7BXppVr9oMXmlgECEdSrkalkAogpAFCTyszSjafQefbe+N8uiWEotBk760AyVxmysIenPlJTeTMiYu+H8VOE2Bc7sn+5nPWeVlsYhgnQx3W+le10+nRJaooAQb592OwUQ6inIddEE0KQxZSFpUffUm8ADc+VbXMNxc4gQE6skJsO3fEyDPJVf6aXv1Hu4IcrShqaUlbHzmPIvryjXvqfXmAlg+0qPCYuO3pmWvgFEQZl2yv2durSOG0dZxgnXgNhDRafImDhWXrcaY5oBRMp0fR/3kY8ZTecrXbMytjxzHjTzcvodATr7pGPQplXJqZZ1Kn6511XWY31lnZ9xY3zNay4zMLzuOsx98IOX9uyb3/wdYPjtdM3OzuJzn5sL2Rgdc1OXzAj98FIVOBmvSgmZTahAdzbKpykDUY3sxTZfWVrh7okngqsgsYh3n3K7kcAxyyQesNcLgQCdjo/Jo4CkLpJVM9oQUN/vO8FOhQflvGk8AjudSbyQm1MycYJZn9TEzfOotSfOYEhQtbwcLID9vi3UyIndtcuiZxX4CcRojiAHW1wM7U5NxUI/rVbK9fh8WfpyGZXFk+Ez+t12u3EhI7avYC7Pg/supdVWC0NT88v06KP2VrrYcX2YfKduXOZYAlGVPorCtk9AqhZoApBGAzh0CKPO3lixwCQ8jnaB4GrG814tISneUT0JaVM1u7qcCviAOKETwYsK7mr84/JozK9iul5vo5BaNxK7onWgKESSrsZlrVChknPM5/k/v9MAWdWGEugkoGG9rNkDlBkEeaXmSzPGTU95Df8nakz72W7HzET9rnWs4wJ8U4SXjpltKrrSz3h/lsVudom07ZVAy8sbiSq1Drnv0nqUHH6jYd33WRdl1J60cwcp6eH6RHCqZKDCEoXzJ54IU8NpnZgIwrwqzFQAUuGdpWhSQUsxDhBbPciT/XnkrhR8+jq5sp68RzPcKomlwjKQ1IXkOutm1weJoNmHMk78wzGq+3KaPj/lK6kFNlVMse9pfK6nH8cwtP5llBk6leZ1D7BxYVJ+3pWBiSzAMXMcGv+rn6sygiCQIIDn7cUu7abKDiqIs+u835iN+QAiBEWidd+zD2QPGrfm+6oxgNqpNMkVB67zpR1LLJMEq7yda7oBMejvdGLGocB0YtI+8lJ+nfZXLk0ip+us+Dm1WKbTn3YhTZbDz/VvPpe6xepvPU/TIaSkr32hGKvxh2mdbLahek61kOuW0HZVgZzWW+aVAnglj5e97DIDw4MHMfeRj1zasz/8w98Bhn/b15vf/Gbceeed2LNnD44dOwYA+MM//EO8/e1vx8MPP4z77rsPs7Oz/v53vOMd+K3f+i1s2rQJ73nPe/CKV7wCAHDXXXfhZ3/2Z3HhwgX8xE/8BN72trc967t9jCGFYQaUp2byVGh22v1UDuNFOUsFYb1SjOlBnr5XzPkD1FCDxAhwh+Y51k3TMxNfB6rfx6izN1hZWi2s9YOA0OtZPLV9e4jlibIeujEz9jA97dKU3nyGVgOO0ZgksUAqYAAW0BaVUJdRhW6CHXI+qqdptSMoU+kMsMDQLcBar0JDqZ3j+Xl4/1oNxlCOyvldXbX/b99u3UFp6iJSef7zQ6q/qSmsPL0HX/kKcPx4jB05H1zrsgxYXQ1/xoSSk0yKozoIJtRRQZRMnJ7BnY4d61VXARO73ZweO2YBJed3YsL6Hk9N2X6fqYZMpHpwu7kdtSf9xxtS0Jdl7MYoBD6C1Yy328GiohaLQVn1gh4BEIX7KHuvu9QCom6QisNI4yQTYnEm8+X3arHk/7rllYZJx7RqprKDCvyq8U81/SzPUpZxcWgK6BsyjyoIBYLVU6tWazCkWtpSq7isqybq2LzZxZSmgrIKY7pvxymF2Cf1DVVJRJEPJ1YUWgSSyj94u7IYNfpWikFYUPo8uy/X+3H8HC9N2kjBXDXYKtAT11IgGyf0laXtApOZqLCoeht+Ps7tTWkslaGZKIiuiylm1mcUr3OJUiyXCmd6tAEXsSi6ByNLnypYdNCqXEnPzzz3oQ9KHhrbzT2rMr1a6dJkTvxNhWaWYUOiI7a1IRusfqkgmFcKgBU5JYugXjHRHjZxDVGNh9NyLtoFLYvBMaZYjPeTNtLtRVoDNlqm/JxBeLWOW27Swvecf14U+NVzlz/krR6gpqiInVSGCcT0ozxM1yxdu/R73pMwcQVzqmQZa0FPkVWyF6L363w5/qV7Ua1p6b7TEkQ6LenvlPeMc6vleqjeL50S7jdNyKSWanpapPwCiPefnnW6RDp1Sr/k23qlfItKFPKV2Ze97PICw+uvx9ydd17as69//TP29VKwyTf7elZgqNfKygr++q//Glu2bMHMzAy2sKjQ3+D6zGc+gzzP8SM/8iMeGD788MOoVCp461vfine+850eGD700EN405vehPvuuw9LS0u4/fbb8cgjjwAA9u/fj09+8pPodDq45ZZb8MEPfhAHDhx4xnffdNMs7p+7zwsHdNfSShFpDBLg5ZjoXq/9540qUAGx6UN9S/idqmXSl6mVzrlQ0QW02RDXTSdVr5ytBRdUhINGN2G/L8/yeWO1zxqjpmBABTcVwnn5za1jS5GzSvFaH8+YIMXzb04y4FHPytN7fDY09Txj6N7iYjCSFIXFQyq3ttvAoUPA9DRQPf5A6JuihiyL/T2Uq7fbQLvtlQPz88A99wBHj4YaW8SKamwuCutGySLrnAYCdMrU/MnzQHukxYUF+z4g0N358zZmSzPy0U2DgtWuXcCNNwK33grUjt1ngSKvVitM4NRU+NyE9P4+y24qXeg6c41S0JACDBVCGg0MTD3QmFuDUaPp8y0B4cCiGxbdu5W++Qp2UemdGk7eo9lGFSCq9VI1uRSMdu8OSScojHJ4GhbJ9aaln7FLWpvxYkJuSjOyHBsOa36u1uWnnooNoBwLjcjOUA0gTsqjfEwFGwW9fGZc9mbqTAi+uMyRsoEd5aYlzZDA0wEyAQwZlmpElE+SGZA/Zk2/dlFNtzz3tU2BpC6bxrwag1HDtlEpBpap6GZkvzmGMapzdb8EYj6s7vuMbU7pTd2xeKWWssgyJi9Ls0WngqIKcqlcrYoMjSFOrzT9f5RpUIE/1w6IzwA3V0xOwr6kbEP7vmlTqIun4Jd0zksVnlr308+jxueOk2rpqqBaIP2ez3Gc6dmmJpcETESlfxS9q7UzUbBFF63diGtsplhIL52vlB3r8kRgLkWaaVy77mdlYu7c4HvUAqnv1b5GlklVTo8DfXqNQ8y6Dko8SRuaRVlv2QASeYNeinouBkplI9GNPM3ezKXX8lW6Vqk1P527cWdBim99HWRINlB1Y08RW57Hil51G3KX1pilTJMaZtNzWRU2qghO63eyj5c9xvDQIcx94hOX9uyrXnXRvl64cOGSsMk3+7rIjouvv/qrv8I//+f/HH/BRC0AsizDW9/6Vvzqr/4qNqcRv9/A9dKXvhQLCwvRZ9dee+3Ye//4j/8Yd9xxB7Zs2YLnPe95mJ6exn0uRnB6ehr79u0DANxxxx344z/+42ed/KefBk4uVnyBbPI6CnnOEOQP6yh+zhig6AIFpdBYMPD3UfIsSwxMHWc3xfE+3FD9PoASMHndG2v4fa8Atm0C8DRwYdky0ond1N46rp7nOFlOoly2r7QawdjFx1sVATSLLtA1wc3NZf9k3UAf3wdYlyxTRb/nrJv9NaC0Y60pk+yVsaAHhL/5OU1o/K0ToAFBrRbQ6fh4jOPHgWNHYs8/PRSNsZjt/HkLoAgmpqdt82fOWAA1P29/bKjh9WF9G7Hnqcet3XB4kkyLAvjSl2L33le+0gon114bMl3u3OnWgRr2btd2iC5z6oJKteLZs0C5FUDL7s4+0TzwktkcuDXbeAK4NRhO7cfx47bJxx6zzS8sAP/rfwFf+AJw993AzMyLcN11L8KLn3fKTurysv05etRaEq+91iPrGtdPuT7deUXYjoC9Cs5sP89D1pHl5YAutmxBbffuEPvpEu5UigH2Zn1BejmGxgrqVTPCxPYCKO1+Qb+PiqObKkpUMzs3NQPUGsZ1ZYwVZGfphRhjQtIjJpE5e9YKM6qVXVgASmfl7PcrkcF5/3Q4+MrSrvugrGJidzj0d+8O5/G5c3HqcG4FlU25zFqHWes26kUgeOFCCIFVa9H+qWD596VwkqLdXF4VFifbG4UWKiG2bg1jItBlv1kHc1DWUMLyDjhX9y1bgJ2uv0zMVbgalkXhXNe7XUs/BIds3A3KW2mojGu3becXFlAr5+396h7rBlhfXrb5iFsty8O6Reyr7KyPFe7RsrT3Tk+HQ0EZhAJdUZ5UigGqugi9HipliZoxqJUl8GQJmBaaeVh0tRTZkkEh5s0OI2TjJB2WHvhVo21qp6riAVIVJXjcVw3/B5CZKGENzwB7pIfEYAnuBUDaksLqGGFEoTGrB9bBOpnsmCSnqHS79gxxc1v36JVEaezfRSrEivCfN3ycNIH38nLFsydeAfyqy2cVRWHnLnPfF06xACcg+xhik1gAy2F0vkeSuyovBGRWemsxDakmoCzj2rqqiODf7tmKW4AagJrhAtnfWlhccYsC8EjuQLy2RVnDufM171aYN8IcRvVslWFx8xaFpW/3ojr7dqEIfVRCzUJxeOugU3UK+mqIsxzjcslXlrAkot3YEA+dgteyRKUsLaW6c8NNntsL1egdlVSjomeevkdlIVGAVgBUHX2z9ZEJJaOovAh7qOL3llqbqyiB0rVVlqi6bgUQDctzFMiVQMXRXlXvzbI4Jld+KstLYbJdEsNKf92vd9WFAVXLAWrb/UJ6/sW+Kz8foQKwHJP7rTGfqmO4mB7g7/S64oqN6PZv4brvvvsuCZt8s69nXYKVlRW89KUvRbfbhRoXz507h//8n/8zut0u3v/+9/+ddpLXY489hsOHD/v/O50OHnvsMQDA1VdfHX3+hS984Vnbq1SsTAqEfVHLRtjb6McHfR+oEriIOp7xK3y2KBx7yYQ39Hk4WbfM2k5ElE+hS3PTMCEHClvagskdAJegBQCQByZlbIIGWgJq5ToGZR2F402Uw+tmgJFxGst2O7gwlIHPT1xxygK8LMOotcdOgTvDmsUSUCBW1wLx31Z6DpPMg3N+PjrYvFTtfgaNSR8eh74zHh63yvqFhcBnDx4EXvACWypiejpYeWgZ3LEDuPrqYAGpl2uuhl4JfHcHg9ZeHDlicVC/D3zxiyH2hUZKNdyy+6wPl+f2Ha97nf39whcCBzrrAWD1APRNkLDSQpif/WzsL0WNBAnpmmvC30URspPmuW2fJsPUtAOgevw4rufc5gAaBphtAO02HupN4o/+yFo377oLyPM9mJ3dg9tuA2ZmYA+DY8eAz3/equUFvEXmLfVF4X6gr5eqhem/S4Gd1uCrrrL3EOEsL9vFMyZYL5kgiGNfXkYVy3EcKAUltq+WZ9Kku7yjTmqpL0vUvAXfoF72rQAKoHYFrKQoQYx5LnFjqUa9sO+rlCWqro+1sg+UBlVj7GfIvCKlTkFJ2mdWSJU9VPnNYW7ZEj4nuKQyq90ObmbMwWSbp6BVldjmSpTYhnoZlUk15pgCcm0nIktWLRuhZuwYKOSs96sgsDDG8TPAuxOWJfUIdbSzoLCq5nbvrGd7YKb2xC7m3JgiGNPaPUIFZd5EtS0u93nuY3gBByKnpsJm54AVPYjlMRIAda+5tUK+J8IBVBx60KBWJy6MtpcEz1aKAjX3zrrSa4rK3OJTqQEEMM+tQfbAxD1lWfUeInaNQswU49GqsESQ50FZkBpymRUW2OgKOy7GjstUlhakDrM6kNWjo8OXJlGFIgmQhKnCrq4Hib/XQyXLUCtL1LLM8j4Bi0BQaJBVsVk9e1O5P2Sqrfrjil2F86AxIDCPLbiR1TmNw1W38PGIO0w+/04lZ+VnfLYoUC3tYV41xoIJd/8wUiyER/TVbF49gtTJwxjHo0wVTgcX6F6s5CoCpO1HrrX9PqplH82yBDbLy7NAQGrxSvEe/1cl26ZNCu4s0DTu3eC6uf9rZhQB/nGZtoOrZxUmc0m2YMcP2UfMPB8QdhGvrdBspSytTJllQYHkBlYx9sxAv/D3RhtNJ1UnWv9Oz6dxZyM1QaqgYE4CXv2+BcbccwSPaQxHr2f5F9vPcwtU4c5Gp2TRxD9qBfV1lssSXwcs+du/Nm2Kz4G/peuxxx67JGzyzb6edQX+03/6T1hdXcULX/hCvPvd78bs7CzW19fxkY98BP/H//F/4Hd/93fxtre97VseAfN673vfi/e+970AgO7qKRuHl+d2I+opn1RupYa6j7rnXdRMVWG1sDX04TVPqKGZ0b9epC3Eqf0B0UiWJapFEFRHeR3VvgWCVVP6UyuK8StsIeW6GXjGsd6ve5lW3YmGZc22l4UitTzcWbtu1NoT+lY6N0IKZhR09AAfd6Apo2OylEOHLAAsqzzH0euGg0fPSE49rW6HDll57qbp9WB96/eB+b5/994sA1quf90cWHSMsdWyaNL1pda9H69qlXjVT05jmDf9u4mnNOkpa7Fb7b1YAZdPAg8+aM1yxxrAV7dZ00mnE5BknmOtF7TpGqsE2PY0Fw2NbS2SipOBc6u0s3UmZw4AMwe816vW0NuxI2TJqxbrwb1ueRl4/HEc2HocB27PgV84hM/cW8XcnB3C3BynaBIveMEkrnnTy9E067Hwqqpmz/TLMFEcAA++Xs9O3tSUpz3iP4Y65hcssJ/9Idff48ctMH388eAPzOQ+dHFlXCjNxsbYAZBY6Kerk/7kk0HIV7et9IAVJUVE02LZJuDz+wCI56gs47SNCgI4T2ybWhxaqTIHGlstz4vs79CfpinQzERQBsJYLrj9WOSoliXqm4EJ0wNMDhT9QFBcN6JM+jBnmVVqpNpwzocKAf2+FVb4v/teyzvU8wQkOdBYLdZRNQZDU/OY2JbTqWKb20YFar6dYVmBoYCNkXUTdV05e9YaIhqy5FGfiwLV0lokyxIoMxuPXc9GGDQmffx0VHIiD1mY685d005xDSiBLHNWPAShuFoWQAmvdKs4hV4VoxjgGClWbWpAHgTlaM5J2+SzCjBFwKtxLzp6a/rv7ARVha6HZcXXf4zxRQVAzYIbU0WtHNpPHHk1c/j3jTC+fMfZsyHxk9a8TK1RCmSVPvh5UVQB0wzHDGAVXAgG2iyjzsoK5v0+cH7LXmxtiCsiGXq368bi5usKRPVKCDTSfioQyvOKVejmwSWwLMM8qFHPsgALuouiCoezAVOztIDghmcMUGbVZC1CW1UM4wKjqozlAnBCUsudCvGAH1DVA46+ALAs8gjg2UJrHT0oyjLONqvYXEtWJSQaHRN6eZ7gLMu82EZFGqIirgpH03qZ5Lc2pJdFc/bKMozcPo7j+yoRuFfrHZtIgTOvUO4iWMWQV4NLpQBI36CjxXEulexnNA5Opm7AcZ1JJ1R/Z1nkzknFGfvcN03H5xwN6obnu3Rx2ScgzgSnmoAssxbHpD9eicrPlXAu8/X00zEtfCPX6upqlAflLW95C97ylrf8bXXtm3I96yrcddddyPMcf/Znf4bJSWsh2759O376p38aTz/9NH7u534Od91112UBhldddRW+9rWv+f8XFxdxlbNAXOzz9NJFm7355uCqpARujM0YKZnluHHplkZwRy2/MdYFpSisMF/tr3l/7Uo5tIIAmb5z4fIJZ/hOY2xmzmJg2wVQZXKW3lIAhbrJqD12h7tBUHwwDsVmsAOAKgamjtIJblnmsq51u0ABrGd7UHfZx6oUHtWExhOTAiawwS3EAyN3rWzbZz0I50I9RR4+rJkHhPikLVsCIGu3rTXLA52FfgxOZmbs/92utaTRCsDvHNrzjJBunN0ucPfdqAJoUmDPMmChQFMzvSxa5/kJJquhtSzPLVi55RbAGKzBCq7nzwNbHS2YMtQOpBYagNeSwhhMFsv+cJ5sy8lMQb3sO62h7V/FSSHNws5DE6UFDg3jDjsr1C736ijKOkoDoHM9DsyM7PwsLwN/9Ed46fnzeOmt1wA/N4v7j1bw6KPW3fTIEZJUHTMzQJ7XYEzTJ4XlxRg9GvYsLmx6Ievxx+PKGbRg8TMGvR8/Dnz4w0Ce19HpvAg7drwI1xwCbpoZWNPmwoJ98NFHgzTCwm1a/oCp/r7ylY3R9Y1GqDGp0fVlGayi7DjplvdROqLl9HnPs/cRxdMVmIj/qafiLA0EyUBwH6YFhH3Pc2u+3rbNmsGPH48lRQVk6qatheZOn46lcu7PVivWHmh/9HBnkTYe+potgN8DFrWpJZdaHDefNbfgtVYL6FuiV9chlqNhLVfr2lSgnpU23rSs+mnSMp5UoIjt13eLWZqzzMZGraPuPRxMZnlzpRjAZMFyyPCBcmvVL4W6U7J8xtC1RfZnTFwmiEJxWdbcvAPnzlWxdWsVuYlBsXefcsm4qlyDotwgbA0bYokURZ2PF2KcqyQQIeD054MxwYJRFKj2epbXmQw0n2iJGmLI9X5Vj5VIkK24d9XcdzwDo6zVbhzj0u2r0aRfxpboESre/diGVNT8elA2bbfdPIhVp9mAb3RYVlGWVZSoojR1ZLlYItgYlU1ZZoFGliHLNrqykfbo3rh9O1AK1ipLO27G06XybKMRx4RG7oKlDfMwJmSXHRm7flVHN8OyirIAgBpKU0NZMBa15nVFxkhstp7HaYe4p7kISXHPaq/nlVF1E5QJMMYrkHmpK/vFQJ8xMTs6fz4oDmwbFoBVnbW6KhOv4BuoepBSiuU/xT3p3tgAXDgvvLksrXslENwrCZpdiMwGa1ZZAlnIEK0Ga73Yd35XNYhi6kaobHBNjf6/GLrm/OR1b5zwc1FufDRaD6GXMH92bo30r1IOUc8gfaV1tOZpLYotdi8dNZrR3uY7i8I63VRZ4k07p+uilmFNvnYZr1HiBPSNXLt3775ojOEzYZZv5etZk89s374dhw8fxic/+ckN3y0tLaHT6eCnfuqn8F/+y3+55E4sLCzg1a9+tU8+w+u2226Lks98+ctfxg//8A/75DPf+73fi0cffRRPP/009u/fj0996lO46qqrcMstt+D3fu/3cN111z3je2dvumnDgqpWkxfBoU8TLoefd+3kznNa+AFqUY0pQOJhlHknGiG6Y1R7LqOos5CsPL3HJ7+AMb7Q+9ji2u6ihli9Dvt9oJlLggAnBfixiB+lFywWF2MXPrV+GBPVveEUPP44sLIS8Aj70WqFZBw7d1qs1mjAWlcXF2MAKvOCsgwWOV5ZhlGj6YVJGoM6nZCohOA7LdNhjBNo1FypB2bKSTkvee4zvAIu5rIcxCpt1dSqhk81amoJ4OQRWNNkyn6Q62riIiKutH/af4e218q6F67bbaA6/5Bze+3Zew4exMrTe7CyYj8+cwb4q78KwhGXnNbOJ54Iy5SeXeT/09M26Q09Y42x69LMbHzC6qp9x9xcCCejF0u7bZ/vdIDZWWBvZxQDK5p3AaDTwVI3xKOkyWOauSRy0PhIIHbtA+IERMyasHmzlQ57vQDAACsZ7dpl+7F5s7VKO6A3yutYXLT9eOKJWGnLvjUbIwt8OS6WYNH83gRsSk9qdVQgq88wA40CwokJ++JWK9xDCW/XrhDjSrCrGhvAfnb6dCAEtsV+qavc44/bhSd9k3B27w59VldyzrlI5etO+DHG7i+t4arynpL78rJdqu3b7ZC4TF7PQkFoeckr4fTq90OsKRDA5gbNSCpsKrATy7MWzS6KoNMgae3cGZrTsfkMmqJE2GB5ZbkKRU6kC0Wy+pnyC30xeU8e6pmqFY2/xx1ZvNg055nC9LgaapwXvlrD1Uh6VB6ph3qqg+SQoxIQTrBM60YqnUSlqFIlZ+pu7g4uWsMJ7LVcSvoI/9YlGXdxvYEAjv36X6zBLPPJQcSzL1qndI0qGG10WZUbafHz8oOeSekA1N1u3FmJ2M087ee4z1Q3y2bGWdBUltKxjftcSZtd5KVzxXtJmxs6erErmUe1LI7rSypOpOuzobYi36GWX23EmA38RdtNZUFALJPqBZROSvp3ypz0HmN8QkLv8j9moD6ZjZY80Xa0L26Tz77oRZc1+cyhQ7P4xCcu7X2vetXFE+WUZXlJ2OSbfY1h8fH15JNPRj6yetGCOBgMLrkDb3rTm3DkyBF0u110Oh388i//MprNJn76p38aq6ur+P7v/34cOnQIf/7nf47rrrsOb3jDG3DgwAEYY/Abv/Eb2OQEtV//9V/HK17xCly4cAFvfvObv66Jv/B0BcOyEh1MNQy89k4v1jQaIWQNqwJYR90fWMYAPbMHGWx7CjKrGGLdNK1BgY2WcUY6Y6rI4dJvZ3vsvQVw/ukatm6lsrMayYfKCGybdvOuS0xEWTqXUBg0UYDxiXSPBZyFk+p5x/Qqn/2s3ezXXgvMzOBkt4bFxZA/BAjyI88Syt7s18wMcNttPpeMBcdaoL1rgJ6QYa8XTnpjLEro94M7oLrRlSUqvTVMNmzynLK0sUyDsor1fsUFPVdRmCqsJ24l8oJcWq5g06Y6Nm+uA609GsJkXXGdLNXtAegDZdkEenZON21yWSoxsjdQONYK5Owv10UnhqehSq3u82Fr0s8pEIxQSmdVDLFe2APYa9pVWqK7ZbeLJrpolgWQt7FypomV8gAa0wewtz20yOzIEUz0ephotXD9zAxGt1vrPw1TO3dK2vGyDGNstTBAzcumtcyBHY5tYcFaVj1IAdAvUZmfx4QxmADw0lszC0zP1nD6tDWe3Xsv8KEP2Vft2gVMTVVw5ZWTEU6ip6wmC+LcsPyAxXVVb91pNJrIsqaPk2I2NS4J+QDX98ornZViJ7BrOrjq0kOXoZOLi0B2LOC8ft8qP06fjpUyfIfdXhWU5T4Ysw+Nhp2mQ4csfpuasuR/8KDULqSSiKe/SgJu8Gv9qt9/vZ7db4y9PXvWej4X3cjDGFu3WhDO/EBAiDksS6DRj+tWtTKgMx2S2FbNCCurFUsj3SU7GQcPhkyeFCoAi9oISPkbsBtp27aQntcY1Gk2dICzVnKxcxc7JRvEKXX2tXPsM90o2y2nqlIOg9uS609l4YT1KHCuqvVyDegbG99HLwHdz4patKgYLwqLbj2qZRm5Cdfcd3XAmRwbkRsfM/HSWmJMFegHdsGEHLt3A8OyCpgqTMPuP2S1WLBXwK3EnQp3/Iyxm0WBap5bHwjG0rs4Pb2Vzascff58YN1rvQrOn69GRe7t7wBq6RZYb2Ve0OU7OJZ60YUL4rP8g5NRGp90Jd9d8xgPcEl5inh52K4H3VlmlQ3OdTUCi2QK3ASLi37tSFSVfh91P5eWnqqiSasCNu42RQtuzhlrS5KhoteyyZBQKLy2ipJr7OSPWuGYSeYn17uq6tqUZQV00d0AvIoiJJArXd9MDaYRxwuOK1O0wVToPvfxv+53TYnGx80G3qV7IGCEONwmpiHId3G2zhQUp2OOABjirL22Lbvv0q2dAswKRuGlRWHdIhPATcA4jk3EYLkS4a6y1FIrtZAJGvaHa+HdakvnLu32g23YfqWZi33pMHsY+j2XKjBSZRDnUYGnWgOrxljrYt6M58c97N+bhWy66qbrfE3sezBeKfB3ff1NLIbPdBljLgmbfLOvv3Edw7/rOod/l9fs7Czm7rsvuCA6DW1azFTTDBsTYs7UOk6BMc0XoB5cGkMfaakQkgQwLIrCLEEBE9AwVb8WNNYsgyurlY1FaSP3RKlJRcsUgRfvJWibnsb9C00f/qWMmzKb4huWXmi3naVGs8ZoIVxOgjHRvNNNbWSqoe+Az5hKGTOR7yzYpFmSE6vImZkxlavxYWrKybD662GxeI/GY2lWPS5kp+NdgKMD02mWdY35CI1ePDNV5tdL5TmmuefwvAVa06kmrry+v+y7m4vR9H7Mz1sQdfXVLjnI/Dzw1a9aAlTrAl+oa0e3LF60djIlpjEYHbw+cr3juJnkp9kYWWlYs5caY1HHwYO4/1gVR44EjKECaVFYerv66hBCqopNJpo4fTrcT4O0Fi6Xs92ToFovTp8erzhnEhgggPbpaUv7nU6YDi4Lp0qxXL8fMt0yZBWIPVxTr5MnngjTz3FxWTl1VDYtLwdjoNZpZNm/bdsszqGAouBV10pJX4UyvrvVCm260FJMTNi10bmlUZGeA+22owECMMC+kPyY2idOBnmUKlm4KXo9y5i3bg1KJJVwWMOmLDGashnifC1EHbwxwc1hyxY7COep4K12nDBOjoL0gFACMSaKH78QXEh+R9di1egxfEAEKQ6d60QDsF762i1bXKZpMxzPZJwAG5UKYL+0f6rhSEGBErYKxyL4U2nDi7zMu6IqUSsPd2cWp1X1hsaE8goE+CkWS8EFX8PndXi6bHyWc0mrXuTupguhc6vnwDiUofOqnaGFWKxuyor5KEnHx71rnUZF8W6t1IKqJQw2TNDF+pUiLneNUAnnXgKI0iFH4NIDmHL8+/RK2rvY+mpT2kRK8il+u9iVgqX0vby0LuJYJDtuTvVe7UTSKR23NhMUBrEcqXLquNfq/xozqsrnyCV0zPwYY+VPVW7offSqo2Fk3HDHDZ1XBaPLbjE8eHAWf/AHl/a+H/mRy1ta43Jcz2lgePPNs/j0p+dQlhvjvIHYFUQ/V5lD3Xv0Xt24CVbwNROBIIBqYdEoKULfuneurFawe7d7Zz8kVACctQ+2/hvvR1n6emtrPasVmmwNsdYPlsRIENDMkXmOR/qT+OhHrTuo8zbE1JQVfq1mvR+kW024wZOfJzcngcIaBSw9lNwEDctKcMtEAFJnzrjyHHoAcxCaxU4PRI4lzZ5F4MmxM+aQknyjEWpNUcjjGDRFH3+323Y83VMbNc16L/tKhARgraj5YdAFTm/nWm/gnu5LHwOrKc6BMCduLP2+WBXZv8VFD2rX0PRy+bZtwMTmtTC/ReHdm0mvKpMz3I/CP4WqPHd0yQr3ehK7dSJ9elDePWXX4qtftY2y8N/tt/t18/FkdOFW92MVvhn7dv68Nf0lcTUeQCsdUcvhhHGSGo1H58/bLhljH5+YACZ2Dq3WpCgsoTLFrRbvIvhQdKxagakpvzeGnX04diwkuSV5sprHjh22D1rthYBQa6sS/FLJdNVVzsLNun5kbo2GjX9GmBq2WenZOGkqpAD4GqJf+1oAI52Opd+vfCXUElWWwFBH4jbJz+T7vGNHWKZ2Gzh8GJjEUuzupypd1bY5hQQVSPVsGBB3loXJ4h6haY7BzEoHCwtAo4GT+QF8/vM29vbYsTAeLdVBfqi1SFutoLBotyUZCvlr6l5OItu2Dd68xn6TRrihOAZ+n0q8Ci7kc8aJUQnAV0V8BiMvyEXZVRm3SEVdKsin5nB+ppcqAQFLc85Th7eTXvVc5PbQ/6mMoeeAsBOvNzDGgX4Br+Qx5F0a5sF2GBOYAkcqiPVz9ls90Z0nIgAA1TtJREFUK7UtXqxR5+UFaUuxtVf0pgo57UiKCgBf6oE6FF4RcGb4i3teQefFQJYfe28t7kfaL+W5F2tUx0WiE0QRFZkfB7D1eiaUMe5K94f7nSYATIeW1hDkdTGro3ZBp0Jdp6O20zGqvJCOK9VeqEB5sTlQ9Kv3uf+j+GdReKWZZdO/x8nGqf7DKwHcNS6py7j51nl90YsuL9g6cGAWH/jApb3vLW95jgLDK6644tIav+IKlM+0ab/J1803z+Kzn52LeBvrjwHxvorSEPPLssRav7rBGMX02z5mACHuQc3q0cnGh9l2mh3QbdrK8hJG7cmoHQ2Ar5lhFF+0lk3CGFeqIqtZ4ZtjoHaapgtn9vjEkSruuccKfLffDuwrH4GvJWFMcKViPBQlIvZbk1MAXqgjmFUNF0pnweyvB6mWgiADBmnx4rwxLkvnSuJjfPv9vs8yWDeDNN2cb0/X0AtyShQifRCcRHEty0v2u0bTC48UmvUcZB06TokuOZkrhy/T5gUiPktN34ULQc7kVGu4WJY50EhrXKuF9SK4yWQZUFk8aRtptz1ATA2snGL2pdWyS79zp4tZbYziAUkpgGFWD+vB7EN5HqywzGBjjM8SC4glaX7eWhS3bQtrRxXnk09axEOrDtt20t+o0QzvZZwsJ1ktO6SrVHhR3kUUrPF3NMXQXNZqeRqowcbFEUg3GvCadU0K4jL3BBS4umpNh9xbWWb/ZuIX9uXJJ0PfVLLmMwLsAQQQxD3PzxkQ3GiEZ9V0srAQB4CmQolTjvjnZmYCunPzsu5qUFKZQADJYQO2C5q1Fwh1SPM8WCJpdez37ZIePWq7t7gYLLb8oS6KU8SlJ+bi5ZVERYEHFur4oz+yHtYLC7ad224L5EVgURT2vcePhwo9ysp37Qr8gVe7HRRsBJXtthO+6aM/zp+Jsa5aVFPr5+lZkvoup0DRhKLyZRmXUeVtRRGsi6ThiwEe/g2EhDNZNiZWLY3R5B6T4LIoOyz/VqCkf4uCDVmG9aIauTyr0dW7icoAWOtPBVztlsrffkwu6Y8eDUoTnO5UnmeSmqg/ZRm5+RGUR/OnnTImsryy/Q2lc7jGSYxlKoCrbsiXC5FLFWM6LwTPG/qng5bB6xg3rH/SwdTNkH/7Z8aBRAXL+u50PsYpoy8CnsZmCR0zmRsALZ8X4K30rM3oK8dhYTUkpMNL9+K4/8cBVZVROXVq8VNDvQJB7UOqONC9zz2jR5e+O112ZVsp8LzcwHBmZhbve9+lve9nfuY5Cgz/JtdodPn9hb/ey7uSliUGZdUXtablQ7VB4xRVxgTr3QamQ2p3wq93j9QdycvtoAjgZbHGim6Dw7wZNU9ldJY5Dfs4DVlZWlfH/vpGbuBqyI0OXo+777ZF0Hs94J/8E+ClnRNWXU7JTE1CYj5d68U+8sYE955I2lBBQWvSpZzNSW1eU02LnjFxplSCZWqz5UQf5XWsrgbXOzK8KOEMgYSumQZwqsVRrYa0uBkDdDpYOd/Eyoq1IJEhpgkJqKGWfD8AHHAjEOa40nly860aNW85E4tbrxeYsrobUXavF6eC0sBJxytna9YVafFEbOlUiShVb7MD2hFV2/N5ncPSZluk9ppzUc9HEm/aDTTWaHhL1e7dCJl4uVatli8H0u/HiTU114nqXDh0TqnG92oReQJrWod27rT3cw1VqD59OpA3M+tS18KstJVigLUiCNjpVLKtp54Ky+/rcKZudnkeeSdwS5BkuK24jfidr0jRi4WGft+Ok3PFWEOG0gF2D+3YAUxsHwQlEglZCZ0WN3aGe5WfEY2dP2//lphCv+6dDkbtSRw5Yutt8lHNx6R8b2oq1J/Pc/u71YozIN95ZzAsLi7a351OYGlqEST+feMbgTf+wAD49KeBL385TCrpvdGwLyJaNcabdU8uVnD0aLCcAtbC+r/+V5g69ZJlUzMztv/T08Dzn2/1HcRN1WI9NNbvh/Iw6sWQZnFhYiRqcVRhpwzbrcGgrHoa8KDBxPUneTYxAQ4tbMr7qUNJ95hXVpXDKJtt5GagSDq1EKcKVD6v2rXM1t8lSx2DEfytG0CV25jcs6MsxE+n1kIeBXpWp+6O6bLwc75Kh6Q8ge9UEBlJ5c6jgfPOrce+PaOrqM6fowVVhI/jT1p3UK1f+rnmU9A5T4GRfj7WkuaucSAxvWfDuPhZiqBS1JR0MpqrZEE0qQznR8/ctLm09IyGJaWA86JlKlKTtXuRgn0l+3EiJRB0hUBgA3Tfpuzg36dzmSLAi10qyKhcmT7HcaSysX4u18hULzswfMELZvHf/tulve/f/tvnIDD867/+67/RC77ru77rb/T83+V16NAs7rtvzjNudS/RMDJ1t9mgyQKCAOQInMxAtY5VM/LZv9STiP+rG5ief4qHaKjjOUo5ulkseRcoSkvD1iSKQgRLcS/0GUhd6u6T2Iu777b/zswAr79tzarMjQEOHfKxG9pfPZMpF/kDqbcW3lNa0DY0tZDAhKcqECbXWeP0qhSDWEXfbmO9X/HTTWGRQm/NhDhMrTtIIZIYb8cOSRxDS5ICGh2kBoqZkJr5+PG4DuH0tBPkjbhcibrNj18zl4ow5LPeIYAPYxBKmmjfVNrn3JAo3N/jalNt2SLxqep+2Wp5y15ZOhdQ93l04ihjN8HyQCBUlhYMkc5rxVoYb6sVMpiV69Hc0CpRFM4NMMkoM8iaHqTxgNu9G0HRQrOTJgpRUE1BWP3S+KMHm1iEGTvHuN1QFN7e6uO2eksxkCdNp6c2iVb2IYBA35yPTsfPbQUjLC3HmnsJlYuGoa5AtEwOs3qwljjFgo9L1XdqrKh6EWjf220/n2v9qsca5Gtnz1p3b+8lUayHZxMlVIRQafkFguTCYvDGePPaWq+C48eD9yjnf2oKqB27z5oOGw1gehpL7ZswP2+39qZNwI032qZWV+2raAQ1xnr/MtmPMdZDYn/3c9ZSzbIl09NhTrjhFxftz+OPB7dnXrr23JtZxkxKFvFNT+PEcg1Hj9r+0EJ55oxtiuxDwuy8UoPx3XQfpoHW6anQ6bg9zmxIvV7sA0tmoNmX2EeJcbSF3UPMKy96S5B9yfaxa+8AYypbKkACkuyrvJQu3eWFa8k4ykvr+UZgk+04ED/OHXCDwE9lpioBdQCuzTR7qPJrHVdkWUsEYLU8Ksvi/yrsp9jGu53KGUoQCyDilTqt2m7U19QNn7wCGwGQ5ltIZfx0mMoGU/CqfUhB98WucTgwbSsFthdrc4Nl+mKNuyt1v9VxjsNxBM4RHYxpIKJtmUTmttgA2NK/dcAkltQMrm7o2vF0oYyJMt76s2UceB0DwH1oiya5McECmyoCtAlepLnLDQynp2fxrndd2vv+w394DgLDb+dr9sYbMfeFL8RWDyA+FPi/+qZws5VlFPeUMkggDrvw2t/UDUela1UlsqC3ezc3Hm+vdE/FxefZL2ai0GJgavlyDQzbe3HkiM0CaQzw2tcCB/r3WYHH1QrQWo4AYhUl0SkllkTQr5aDMBGq8gcixD1AzcdVeobY62HUsK6NLGfH68or7W+6V7I0FRXoEs4YrKQiWS0tV/xZyNwV9AbU2CwdLhDL8lRu141LZ+8CXIZZPbpHDZMqZ2i5O8B+n8aeqszUaoVYEbpt1LNgfQOSkipq/XP90jw0WeYAGlEjXTq7XQwbeyyAM4kLtLEB5b6uU2oFpmsoF4KWFU4E474kQY3fa1wAwNe5gzGhXhstJAr2BAgjz73mO9K2a9/UryUt58DPxqEwPktgR1pW8KwCLfvF3yzAxneRGKiQUCLhOFVLpAc+Xas5bhbyY384PsC2dfZsqIuQSuZ0kRB33g11Djk3jz9u21EGxzVjH1VxIdloVs5UsXlzbIxXGcXTk7ZFwPrww8F8qSZdvoful1NT1q34lltsPzT2lBocBap5brVgjYY1GWrCGK6LQ1yRRwj7l8dJyvyc8Hu+m7yXJmFmUeJ96l/O1M2dDoZT+7GwEPRWvZ61Oj75ZEju+vjjcekYTgl5C0u/zMwA110HfM/32My3NQxCaMCZM/YhImMyNhUmSWcct4AqLnuq+KSi1e9px9fjLJDhKInS6Ku0mKIl3WOCNCKwpp1T0CPW6dS6VxTBrZbln1S+Nka8TQQBeKFflC+qI0rbBNx41XtINoPWltT9cbHi214QV3mFL0n6k7IHnUpOjxfqdXG0j7om2gkddMoP9T79rW2ZuHbgmK+jprXf47o07nl2E4i9sseBRz0qgDjL5gbA7640SRS/1r2hfUjJOZ3mdBzp52q5BBJApoNPHxbAlt6Szv24edWt52N55R1puxF/d+/1MmyiCOdtL33p5QVbz3/+LN7xjkt736/92neA4bfVdfPNs/jLz3/OU6Rm9+RGVqUKEBu6CCqoURXFi5fbPDiiVsXFNvigbuVYvM8JcIPMWupqRqwo+psXBcipKR/PUzeDWIPKdl3axC98sYJPfco+dtttwMumTlitu8v8cGKhgnbbgQflDipIc3erEEEpJhW4pcabyrEUFimvtdshh0d6/rdadj59QhUTSiiwyHwzG0SCNRO8kEFrZj8gLl3H+4hz9RmVz328ohP61/pV7zbIcdFS6onFrb8ywejQUTCgmRKdIMMEEpQhBd97Bk1tX5ojxwtojsbVwDYxAUxsXbdrDwQwpHFJocJ4DBzUnEE6cIqCUdtarPVQGJTVSCji/4AkRXGCuY8PVMUHCaUsgUYD64UVos6fd26OCkhJPG4ho4RCam1V9K3SAAGFCjMKdvm3ErNKXOKeV+ufil3kXFrWUV4PSYtIhETtXEhebJ99Yp/VEsl3qJJLtRNKFBwH38u542cq1CloVMt0mmmY/dRnGUgYaoaE92gWGo6Xm1MVAV/7WjD5MxaS9RZf+ELg9tsxNDWbpGqnK8FCV2++Q4udEpA9+WQ8ZiKqV74So87eIHCnQb9sl5eCYs5vkgDGf6e/VRFBkHb6dLDwjTP5iBXMa7/o6p/ZhE5M7Prww7ZWKOMgqc9wHruYnrb7/9prgRe/2CWdIhqlMkR9QTVrKi8NLyD9Oma93o9dnnXokWCZgiwN2lPachdLMbEtrQGo5Jdikqj2Iz/UdXP8R5WhBLS0itPdm+/QrTYOQ6XZZFU/oSTCbmidZOAibo7AhmzX+v5IccexOauiknB60TocxahLdvB0nbTYu5/j1Aqs/FN5ULqu6d7Q51JUmD6jl977LMAoTRqj83CxLqTdT11dqZxQegTiLaPXhrXli3SR5HcKPsdNhyZ+2VCQPt0k48y1ulYCIrXPquBRALyBF7p3pYmtvHGCBhJawV0/LndW0uc9bxa//MuX9r73vOc5CAxPnjyJPM/RbDaf6bYN19GjR3Hy5Em85jWv+Rt18O/yuvnmWXz+83MR2FNZj3GGFOaBWHvniVnjthS4qYVOrYIULLhB+/2NFg0CBBVeVUBRga8sgZkZPNCdxNyc1Shfc411i6r3lzwgu/de2+SDD1rmPztrs/9VP/mn9sSbncWwvTe41DAgZxwQlEMqAqwU8iSpwHpZ81/z4rRs22Zd0HgA022PMsnu3YkWU4XtRiNo7ZeXYnSpsXpuHby7JuP6KOxLzKIfjxvzALX4gCxLDEzdY+5Gw4FR9stZPjkODbH0hy1ioKbzQmNSUmEkwg4KtjSLngeAbmxDU/OMWIEl8QVxFsuvTE0Bk41BDOzLMlh/ytInEFJdQ2osoqy4uGg/o1Gt27VryuyrzmvSb52ikJT6ejA6gZfzSPL3NTG73dBHRcycTBUQSM8Xs06kqmJOLmlbtRlqgVOBWRU9BLl04SwKmzyqELc1gr10gOmG4ee8tB9qSVWNgevPWi8kv2Bzmq2QSjFODRCyJfMzxVDpFOV58ISggDDKalGW5Ahss+BjCuLZMPcwgIGphzXvngIAjFp7vPGt03Gfs+yJy1Lq+RK1SlRcEJDxt9YXabdDZhz2RUH0uA3JNVEhi+Nlx1OBVyUqWStmiI1c/AjC1f2bEnxRBMuvgl5udP7dagEHD+Kh4xU8+KAFjEeP2mEyeU67bcHizIw9G2ZnXXKceZd8jEG1pC/NvMuLLheMb9SkZI6hjbKat4Ry2em1m2XBrY7ZtJWHAmE6ffmIxGLn/081iyk40e91n6cKonHoL1UE8N2avZXvTL2PeGUhfEKPHv6vYEJBhupSAMSFw0WI51kRlVlxF+v+piwwJU91I/Zg/iKxgPxfj9300s8uWq/uYqAu/VsnJAWd+nmKoPR5AT+RogCxBfBi3dRmNSeFp2P2YwzaVEXyOIXCM/aXn/H3Rax24xQAbD8Fr6kuivtMZZZx1r2LzUkKoi8Wm6lbkZ9dbovhd33XLH7ply7tfe9973MQGG7atAk/9mM/ht/6rd/a8N1NN92EH/zBH8S///f/fsN3P/7jP473v//9uJAeHN9C1+yhQ5j73OfiQ4S51VlsDYg1+ARypGIKZxQ0LrYTjQlAC7Dta6HkRsP6BgHBXMZDf/fuwBA00UGWYdDaiwcfBL7wBR9ig0YjJBJkCm+W5mKWvetnhiHrglMfr6xWbNxUuQ50u77eFy8y/GYep/Uuy1AEW5VQKjux6/p5DVY4ppWTbjcT2wdRzISe7doXlasqhc0CqQaVRsPVU6SmzWmnNTMn4MYrFhfN2kf5nAkVgASUAECn461fLDtBZkptrsqKmzaFGnpcSjZVloEsVMZTDKJewRSaVJkBIBKWvICcCLCjhs0CurxsjRVM1ENAumNHqL6QYkWOqdWK5cNNm+wzjYazrLr59lZWB+Y5N8aELK70FqRlOPK9peVJwROzYbqUkQNTjzLCqlGQ76G8zCuV+TxgK4og1Korojw4QC1KEKoHnLICrjdZB/UQvEgTV14Z1p56Ia45+0kMwHlWD8sLF8LabYibIWLn+st41sq6dbvmM+pmy8RZvbXYYlqW3kIdpT13rkXUKKvOjPPMZSUYUNmcwqiPhZW1WOtVIhl7yxZnIaQ10E2sd2Uv1r1iisZALcvCxEEq67daQHX5ZPhgXDIUVfBx4VVRx80JxMmx1JQPhGd4nnAjs1Op1VGZYKrwUC2NKCUi9E5tFhnL9u0+c8+J/h7cc481tj76qE2Uw24wUU+nY/G2Zn3tdCQZDePWgdgCqsG5BIgMjsxzDBs2Wcz585amOQV5HnsOexp141LLlbc0ZhkGZdVPs1cECti7mNDMKWw24ozZ/M4Y4Q+K3FQ7Nk4qpnygwr0SsgZqcp3lc+1vmlWUr9I+qoeIhgH4/akKE0dn6sKqZKXtKy/lz7j6eSkp6zyzTVWwp3gHuEgMYAoMx10KknQudWDp/ePaHoeWRblAi61XhGFj8iHtDkmGn6muKL1fjfT6epV3lBZSkKf36aV6uHFTkJKhkvS4/TIOo+t3ol/fwNvZvk6tuppf7hjDvXtn8Qu/cGnve//7n4PA8JnqFD7Td//bAMNPfCKOE9KibCrJcJeo7yF3jKo+NYhLucGZM0H9rvfqrlHkZIw9dQFfyGypV8OmTaEQ9qOPhrpirRZw663AgcaS14SvTFyPv/zLoKS/9VZgL04Gbb074ZnptFasBVOSq8/H4bKGW7ttm1fBFAiZMBUAcuiNRkhzrVNHBXir5Q4zd2CNWnustrO3FBrhGnG+aSFx43jouNVkTU0FuWx1NYS1MXW8McDe9jDi2ApCgcCkvFTr1mnU2gPAjoXp0Z96ynZneto+W+meCmuqgYWp+peKBxUwxqni1JVS72NcGLm5MzEOy0qUfIfJijT2JqrjyDl07Z9crnrLXpr6naBDu0owTxpQObosHTAvy2B5TesyupNKaxrOz4fp29cZ+tjFtV4FzYYFlJwSLRyvhh0FnArQ2E/tI7Nwsg0uGY2QNEiq/M0lZhWNcZkXfbIdDMIJKdZctqfYXRUEDOvi/2xfD1w9tLUdbZtsi2ysLEM9RCDQruIKNUBSp8WtNzER6Ip94zMU6CMh3nWEwqd3s85CJmb2lWtV7S4FZExLo/JIWtHyHJiawmhqn39VPbOAch3WbX2yHWffG2Z1H8/baACVhROxNDQzgxOLVZ+shsYxjf+l4iSycvFLdRFNBdn0N9/JwY+TIsdZJSWmO7KIqQZKxhy1RTrkdyyVQheNmRng4EGc7Ddxzz3AZz9r8V23axWOjz9+AcB5AJsAcDNtRpZtwubNITMsM6vOzNifA9NDa6ZcXrbuwWRSgH1vpxMsu1xzFtCk+zAQn818Znrau0qqWxoVc5GFrbfm52xc6QUFg7oH+H+a3IWAlkodNd6owKvtUUmVZcKb+RKlH9JUSiNKQ+5gU5CgOgzVe5Nna3kS783AtrhfxbqT8iGStRpX0+8VkPJzDc1IsZe+hxef+3piAtO+jdtqCkR8P0XZsOHF6bmd/q17fIyJVOPpgBic8bd3wXQdotJdwfK4Layv5P+eD7GtxNqZDsEDfIZZ6IGiB4t+lj6coMZnLDWiz/Gw4QCkc7OvetVlBVtXXTWLn/qpS3vfRz7yHWD4dX/3vwUwvOEGzH3sY8H9CAjEqRq9fh+RH57udKr/+TkQS9OOAwxQizCl4knWPabwxoNj9277PWPuGg1r+WOzjYZNJjAzA+xvrYUkKOyfgtRjx2zh8GuuCUEmmuzCNcismxrr4DWN6kumgEIHQ2To5kNjCje4oihjSN3KFFxr//K6lwcpG7bbLpOmA0x0i2O3aDVc71dQz0LGPB7Y5IdcUvZvZbXiLXdc6loWJ1kwBqj3TtobCPYoyGlGRgqMfFEqAPIztsFnCIiJorU9Va0rohFJe9RoelfRRsOBFADrZc0LJVruotEQ1yQxm9I6pAf8BuGXFkFx5xqgFlxfZaxpMgXvhoiQHr8sLb2THHQKaaFuty04S4GZgg3N+EYAGu0RUW8yeRDlM1psNSsw29f6ZGOLFrs5GeZNH980QC0CQUURl8FQN2Efj0xrCCdCD1PSQZZFxYmVjn18RynWDiatcR4D0TjcM5xD4gUOibK6WkpVZ8a5YpkPVSqUZRBMsyx4DfiXkV/me7yOisNttdw+pzIhq3sg3Gg4RRL5CAsPstPqPqp8J8tCFtSiCKYw7mdaTbOaLwdDyyOPBSAWWJ9JVtyxIy4uH1kTU+FJiVj/Vp6rQhZfqD5g2jY7pffqu2hVXFy0wA0AVlY8+Ma2bcEt1c3TI/PBivvooxZA0luFyXEU6zQawD/6R1ZJefiwUwCwhiPN4bxR1wKw2baZmKoo4nhIyX7sTZscr/o/l6VPUlXLgpURRhKfqacCf5P5cP40rl7vKzfWJ+RXjFXkNlb8znvGKdpSMBNl9+bk8gaN+04VDcJ4tOavGg8jhaHcl4Iu3sIrpXO2HSmHUqQj/48r5cBLP9e4wASPjAWMijeEzW94JmXd6d+RB4buzRR9qiChKFfjcHkf26F3gcyBgmnersllVMbRpaYCPsV26dx6QCr91vM3ermuX8qPdCw8U/U7XrreuiiqsZFr9iUvuaxga3JyFj/xE5f2vo9//NsPGI7ZSs+h68kn7Sl2/nwItMqyYO+mVMJ4F2OAdtszey0rVTgZS2tXGRNc9Pg/5RL1rlHDkTH2jOx07CHL/cR4rFe/2gJBny4fLsnMYs/fNGzssZvemGAya7eB2dmo7lS9eyocvGUJLC9bdpw3sdStei25j6HL96DX5V6uolfUgMJZDTe5HwBbS+DcWXvP7txp8MsSMFnMHBVgdzoYlqHOXz137hGmhkJwB/qxAXfLFnr6NZE1gLNnghvmZGuI2tF7fNBbvd8HZmbQR9WtUcULsEDIbgpUvCWT60Mhbr1fQx3rQFGgRmnHWe/WG3utjFICeQn0yr3IDJC7de3nQYA2pV2S1AW0aE16OsjzkFRmsd9EWTbRatjvamaIQdaMgA+TFXkBwoxQWTyJCYL1LMOgsBlg68sn7AtaLe9e1CwKoJd5QWqtqOH808DmAsgD/kCWMcuge5EC4G4XFQZ+ZRlq3VNAmVkFgbOy7jQhiZCdbSs8VI3xiXyq5RAwVczMILKASpLe2N2o5xQDJgeQo2qAatEHCmudQwlUjUG1eypCKYxfO3e+hq0GqDuhq1qWqJnSZ2jd24ljLPLcCn0WaGcbDkK6s/XRRNOMMCyr6Bd2bLaflu5r/S6Q2T3IeT1zphq5vJZlBTB1wAA1M/J9NgAyA/TQhCkBU8i8lGXkMl01IwzKGrKGs6oUA5upNq/D9IP8CATBlXvu/PlYd8ZSBTRak+bIShwZeHk9NYTzGQu6awBq/vOytHsc3SD7k9fZ7db0pKYGlFo2siV6cgdMV4GtW6swFGxdwqpuuRd5wwI07vtuFygzoF8CjRLIek6ZJBl2K8vLaIow2FQmT5djlSgZaOuuoQleCazQYZuqufmp+T2/ZYuU07EEEAugYoWNQK4isFQoVWTOfisY5aai3+itt4a2u91wPjKrzenTAID9BGTG4CZujBaAF7jSHFdeCczM4JHFGo4dswbDO+8E/t//l+s6iZmZSUxP21fOzNjuLCxYbPqVI7abrLxRFMCZMzXs3l3D6moTO3fehBtusCVJXv1qYLL3kO3jPffEWgkqQlst1JwSaoQKKrROGmNF7X6hGy+eL02cpNpOVdrluT1D3XM1FZazzJ4ZjQbQN6gWBZqcd/dMndlL3Wda+N7rmopaXIN1Sz1OGENFmPQxir0sClSKnh2vMah7OjVBceZeVikGqMLyTpUd2JfUkkhyU95VFDX/nddboAqUAAIuiixNG1zh3UurgO13lj2z9OqVJW5dAaAoHacJSFutq6lhXvUoxlRQOp5e1fi/1G2Ce5ADZQMKCNMJKwrvmsp14rz7Z0pEQLrqACCHGV4fuz4HvhuSv1QwQhVlaNPNvdYlzbJqSL5FJsv9pIqTVIHFiRMFBZWh9VzOa0k6pQroSKF1Ga/RKGaZz/XruW0xvP56zN11V+x/Bpv1TAsk8/xkcC49XC5cCOewCviqTCxLq2ilqxpjAOn+yQLN6lHjYyK427k56V5DaxT9t6amQokBiDaxKKy1gplRKbGp9tNtSNY9VIUXtYcnl6veSkfXOSDUMUuDmIExQe/sP/tsDE4uxwkvduywc8rbJiaCxvnsWTtXu3cDlcWTQcvP+C+ia2ZSEDcz/wKu8/Kyd5dFWQbLjJt3H1NFZqXZF+mCKwLV0NS8S2Ong5Bww1n/fLbbwq0riYt+uWoWUebqLM2cMmoDvZVBA9nIUFNrglizB6h54coYOzXV5ZPWIthoehAavYfEQOuJHhBcPOmzzxgLOwcrqxVfIJ2uU7SA7+3EdUPz3AoFHnCNU0+nB4ej5WEeQLFq6yNBCfBxjZxqNkk6Xl0NTW/d6sahWhvVnIp7l9YlS5eRY9ODl/cwJtUn3eF4GnvGDl2zGZZlsGBRl8W9cvp0MJql08j/yRLSGJkIkFCooWDMxVKBgHRWxtYYbW+tV/HuYNzj7Cs/43bLc0svEztjwURr47F7tPqsnKtjYSHEclKXl+YaSpX53Fv8m3pAhrPyPRwmw+N8xlw2KnFagNvr6gWRmoZSpJxl3ruCZ4quV7qOY0jQx5vy8h4C6kes79cG9WXkR4rAdSJ4sU3yR+WVjNNnJ+k72WoBMzNYn3kR7r7b6mWPHg3VM7j+NPrNzIQqOBozvLxsWf38PPClL9m/6UHw/d9vq5YcPgwcmBnZF8zPh0wq9PKZmsKotccvk5aR4nuikksOOdA9lTHU3NPeApnnkcVd92tZyl7nHGr8N1+uRJqul6xJmo2VU719e0zvKd0rS2Pd04geiThSVMqHeV/ynMbnp6TF8IRxBmstxg4ERSCVUFquikoz3Ze6Zno0javFaExsfUsTAKVZPUUfFL2Png/pvrTgcTh+/vRc5qXAMZ3fNBhRF1LkPM9DpHyKz1yrTEQnygHjSEYToqU3FR/RRxV4sstKUzoUb+HXWFsdR5Z5GYnzf7mzkk5MzOKNb7y0933uc99+FsPnNDB83vNm8W/+zVyUO4ZZGnfvDvuV8rYq99TKx7AIPdR8zByFAh6UlFIWFgKgYQcoJVI60c3Ejhw8GAmj3Lj1fBRAkjs4lpYryHN3gDFFZKfjpZ5he6/vjiaPoXKZcUVeSFN3LLqiGRPH/6USjAjUo6wWAe6JifgAyzIX70OUxarxRRHAXCrV0gSnpw3f2W5jqWsZDr0tq6UDO3SZotmDTFNLRXCM7XYcv2KMt26eP2+zqnophcShHJUDJEjNcwzNxkytrZYVKAem7h+j1ZAS7Hq/gm7XAnRaPLz7E63Dyp05T7R+OGSxhiYefVSKhJfr9v5gNrUX6ZdE4cxCaRwLHyNAobBFV9803szHRCLEUwDBlXK9qFpLMxBniOTcSh/X+tVIlqUwxjg/Lwi4l/DAY1dYrzEVlFngO8uCXKsC2PnzccIeThebodWbn3MoqmTO86Bk4v8AfPkTpY8ss0oHZobVS93UjLGAgElYUmCh8b4E4uPu03XxcYGiLBk1mkGo0Ji2dIDKG3gp8bjNycy5mglV0+czqYYmuRmh4rNr7thhDVTtdogzWy+q3ju72Rh5RRCwMTkGefZ6WfNrR822JjphHUE1GqnMxb6P02FQJlSBPSpXo/MigFhLE+g0UthmzDf5xjjcQXBVz0cBLHKdUqDI9VKAqBYQ8mIOtNEIfFt5j1olCRQZsK5ArdXC+tT1mJsLSqtOx8W/8bnlZeufqp49Tz3la+5+7njT1+V99NFQWoKJc267zWbqnsSS5dWa3UmS4UTSLs82Nx6fZAc2SRkgICPLoqyUSur0kk2Vxjx3eT+/j8pWpGvBAzR1G9WGU5Sk36kG2J3LSnZRiQq+X3/rwPi5CvppX7QdPZtc/8lneZGmx4FGfg7E+Q1SsEKPrFQZlOpk6I2gn2+ohakNc87G5EtIp1hFERUHytLtQQFnQDgz2S6VFd71E6JQUAUwG1bmo3SgA9bO6T1ZKCnBJvv9EFvNrZYutTzu51wBPedAdUPsAisGKe2zvZe97PKCrd27Z/G6113a++6//zvA8Ov+7n8HYHjVVbP4xV+c85iDREwhU92N+DnrHtfM0AILWqhUHQ5ssMhFp7Oqsp3QPspq3lsHiEMFyzKcjZoEA3CWiOWT4R8HHrj5JluWmQxNzQt3a0XNM7KFBeAFL3C17Ny1cq6OJ54A9k87sDk/H1nfmGlvvax5mcAnFaHQD/h4M+JigsGtW4F6uRZr0TlInuQUKMh52+0IMNXLNaDR8Gn42QSZGZdisjWMNPfDrO6ZLb16eBjwMwI2zrWeCaurkjFRk2JMTeHEcg3z88G4trBgC0szyQXBHHFO6pVRFEE3wHnNc1u3mzFexGirq96bK8pjo6GZgMXWvpSHpsN0CH04fcDrE5oNa9nJ86A1VUGUc6BAa71f8a7PRWHbiEDz9oFPh8s4LW9x4USLoKAxLbo+FKAUF3rQImUX+Pzyckgqo15/al0hjagCaNu2MP/cttSDcE4pzxoDX55kvV+JlMBlCZ/ghOtBkJyOTfvFvvR6ti9c9yqGwc0rTW7Ch0WdO8zqfl7onsR1cVvTH9YTu8W6Vww2ChOwAIt8sYYB1oqanx81HBSFTfbiNdGsJ6imOUXA5BdsgGNxfIz91X3CjK1A0O3MzCRlaPLcZyNNgSazC9PFfb0M9T8Vw5KveH4vQhmz51E4orUbwIb42RQPq5Cln6snFX+8gpEv0s2YgoVUISfgcq1X8Z4ufDfpq9WS4u2puUdoKnIr44ahwqjfD7VHlSg4SZxcdbFJQYxaHvkeZZLK6Em8Tz0VMhaTaXc6ASzeW8FnP2uzdpM3dzpWv3r4sAWL+6dHlpAWF2MFh/5mnR0G/2vgrQItxpNwTFoLlcS4a5dlDGQ2ZNri8kvlRQooOHzF6ZHbJcE550piKCO6AKJY+4hQTZy0RF320yt6N4lXAYt+N+6+9HARcx/BlzbDy5iNcX9pVtCL4Vnls2UZZ3YmCNL/FWOPw+H6zvRsJNnzvNFkaNRtaNiAAmSdFv1OaSHtG7281Hth3NQDiDJ4E0zzvFI9Ueo5qpZ1XQu1MPJ95HXaV50znXOCxCwDXv7yywu2du2axStecWnve+SR5ygw/Ef/6B/hne9854bvpqamLvrdz//8z+MjH/nItzQwvO66WXzyk3NBkKFLRb8f3P2AWLvKVJR5bqmZ9ZpI9Z2OF8CHWd1vBMbcqNKVm5SxOWrRUjesqD6SZqkUdfBoap9XgJIRNLMBlno1byBTJkNhplme8pYbniG1Yi20XdrspqdPW1wIBCxEY5sxceIc9bAqCtFU95diKV00cDAG6/mkF8IpOGtiQoZ2sF1mXFdgBMDHB9aKtUjSGpmqzRqqJ4VK56q1J5CntMb/6b7JCe10cKKYxD33WLcoWi3cVxvy0TgM6cEJLbFrZo8HDgokaNh0+gM9Nz3NbNlic0TogcF1YYkSn93TLZy3GHVPYdTa42N4nGeyF2Andge3FNIsq65weqJkNexEv+9vHM0ciBLAjEzV04pPPsJJ0vkHLKDM61boV0sFlQhOiOKra2YYnqfPNgmCqILWej393OZkfTwORxMOcU6YiZL7KNLk8mTkJuBGo7BEcJRq/Fst70pIa+fIVD258XbOm76KyXcUK1DWVMWGCg30iqgUgyhDKpUEpCFfOsKVfogYmoI7Xhxjad1KSf/9vlPS6BqzgyQkfm5MbI2Bjdkk+TKOm3vp+ulBDNpQ9bTMrnFcqr/j63btCkJJv+9crCVTJNeePEeFxtSSyW6MS2E/TsDW2mdUgDDT8TgcyOlWWV/7oroCn2lQicV9Se8NzcVDZdTEhONLBGu6r/UF/Dt1LeaCp8xIkpKh2w0aMl0g9lNNa/xclSBqiQZsYrVezy4O/ZOBuFp7p4Ph7Evw0Y/aOo5zc+GYn5iwfJs0UxRWqaZsQjNeA5a/13NJmuX2xDpCAivPQxVAUktKOUMZDn+I2oHwty68aLKV/ym25kXLkz/T2Y5qQMZZ/FINiY5BfqKYMUcT6pHgr7KMwagSuYLJ1BTFd0s7nnemygXlRbxXkci4tnSRTciiquSl+y3VnWh3NMKnlo2CACN9VdCfZVZZo2E5aUkWTs04fQ15PRVT9DJR7M37ufVovdYk+Ho+65wNUQ0Jadw1KKtRkjSUZfCo0gy72FhPkfTJvqVnFJt8yUsuL9jauXMW/+AfXNr7Tp58jgLDK6644pJf8K0MDGenpzH3vvcFQUczwjA92NatIRuA1F8alhWvYCRxawrqft9aegArdCifrxSDOG6NyI3CbHoQEyExqQcQXtxq4WSv7mPbRnndgh8JklnvHPAJD1hQngyLQiEQBOBaZl0jl7J9OHYsjoskQGGtY2VWqvj0wgmBGCVEYZLDrO61+HSnaeZDrPWrGxiHj5WhADE9HQJTsszGWbI4dO8U1rM9vo9U8hLYekvJdom/4dpSYOEgOI9EbI67rpk9OHbMgsEzZ2zyg8OHXYZS1QJkWXALVjNwevhRuKJQlWrWNXOiazcq/O1cAs+eteVMqIlkE0UB3HADMPHkCZs8wqWlH2Z1m+kR8OUuaCDmXCnjNsYlYtHTSg9kzmVZ+ngTwK0fy6S4cY7ak/Yw0WyZgAVJtDipJUBOOm8BVyDKflBopCsAvwd8Fk4AsUKAbasgrAStQkty0Eenm5u4SPhnzCnHqCc3Nw6FRMawakIfnqpqotNL6YfCHxHOxfwdSZ8qrHOexNLE99L6pvE9xmCDgBDxJnU1B7yrKBOvMKGWB9ZG4rWMxBeyf86KmGUumyV55tQURu3JoNgT5sHyLVpqgvuh37eAgADZAxbZr8xUSfBGzMF4TrapNbhIJvxbhThddiU9at030M6YGKmiCBZ0Xqov5KXyML0V/Fyr8iXL7NwWVSwsBNxC0qBCasuWUPYHEOCpsRjsDPergkauF7/j9yQmTZxD2uRAyBeVf6p1ShUunFiOb3ExTD7B6NSUfcfsLE4sVnH0aKik0evB81HK9XTVLctYEdPrxRl4VWlKYMhSFjx/aSG58srY1ZX5Btpte7zVi1OhQ5w71R4oUKaMQp7FxWPSsbLqaZdrGCXvouKNZ5QqEvTS/xVU8f/0We0j79EDxV1RfLMSur5T0ZqiCL0naXdDn42JrP3Ky4xBnBSF70xvTs1inGcg8ligQomPqVu8B2Pu+ZXVSly+RMer/UjGpQBcy5V4XsjLMQbvls5+JgoX8jlfm5T8wu01Pq9JkbIszsod1d2U8hm+TNa4uVRTaZZd9nIVO3bM4u/9vUt736lTz1FgeMmNX3HFtzYwvP56zP3RH9lafqYWuV5RRgOCsUh5DyAxENxYqglUJsvDSgU7dS91/w+yphcy0O9bkOcyQw3zpr9dvV3KEtjbEsFaA9fo38eb3Smv9cR8fTlu7G4Xg8Ykjh+3B9RYLT8QBHYFNkAsgALxASXClp7xxjhXpvn5IDTwHanJMMu8AD269aWYn7dWOq+9N0OsuKyOCwsBzJZlsLzdeqtdGk0wwVqKa72Kj5dTMEzh4IknbOUPeuw0GsD3fq8DXAsLcbCpMrt226LIFPHyXi3SzZeT2NSKpmDRSdfD1qR/jWpiaYGiXMQlarVcTbF777Uf0ERIAAYE6ygXiECLJl2nlIAxWDlTjYqsq1Dc6bi40amp0J66WbdaPmsZdTFUoFDQYswC6Z9B/14zC4l/44ZttbDWt4emugZduBAnkaSLJi89i+smtkRtEEpprTfB2u5jWFOhhQKpKgPIF1LrKOdLBSSuOxlACsZ0nZR4xQQydJkvNd7Sr6v6yupE6N4HYp9l9ps8TIQyr0Hur8VCHOk5z7HUC67obFKnbEPmOo57cTG8z9WvqywvAXmOlXN1rw33fI3xZHyJrp9TKkUKC3F5Ji17bT4zABcBBCqoo4tVlPY9EYY1wZPKuJHFQNdWEV+67lz75NIatHo0cRkpnJJUfA1bUa4MG3u8l6YmxKEBni54bEeN4J2Oc9VVZQV5GsMvOHk8GzVQOKV5dYXXvUSexTXl/mTb/K3aAGZZ3bw5/AbCoHjt3BnabLUwau2JsCUB5JNP2mbPnQuuuYD9/4knYn6o3q/MZ/DEE0EXyP8VrNDjhh6yxMwEk50O0MSapXMGwBKJkAiYmYcPtNtRTG9qqNXYNl6ed3DeUwDFBrh+6RpAAKDW/dT9oVf6XQpAFdWl/GXMvov6SZrLsshiz1tSPRrXTUsW8fJJh7S/OnYdDxBomRf5KO9xCjDqWzwvSeNO+D61nqrCJJmPUV6PEw25s2tDBlhtG4gVn67NSJmQ8ib2RXk3v6NwpXOVxvXmOWZf9rLLCrbq9VnMzl7a+9bXn4PA8Nv5uuGGWXziE3M2K6CzlpGPtlpiydA4ASD2FyCR6yncboeNQWHY7fK1fjXCUrTsnDtnzyG+hufhwkJQCD7xRDh0z5yRbIYaq5VlWIe1JDXzIU4uV7HXLIVBuYyHTHhBHECGMTChTmAd68Eip5pEan1V43MxVXVhM6OWZRhLp+MEETW5ZhnW2ge8kafVsvdzmhcWAiDrdm39Rs5jWdpYvt274YujZ5mNI5ls2PqLg3yPZ+7Hj/uayOj3Q0zi6dNBgHJd92thTLiPLkcTE8DEY/eHjHdXXmkPXvVHolBiDNazPV62VV5e6y1h1J5Ev+8sjpq8xoEnavM5tTRweqss55/WZ77XWT+H0wewuGjHDoS60JOtYQzI1YWaAjMZuwNxfFVleSm8j5PeatmXKLB0Dwymr49jtQBfsgKwwoKWWODaeq0kS00QRPOdLv2mZsSrG3G9TiyAA4R3qkBEAZ9WorE1CnVNebAyQYY2pJYQfqb+zqV1v6ksnoz3T1HY8czPx/tI3U4bDftexvWqFZGSHTexCmgJL6KgMWrtQaW35muY6tykfImup8yw65VMzMLHPrDtvB5rsTl/LKpOmlHLrBvPqD3pBdFRVrPjdeNfWa34Env7OkMMyuBO58vjiPAauenSVSsLCRcYk7p5sytVQSSkvrWpGVDdHVWwUbSb/q33kIEBkbKO7RFkqvtwKourDBYVamd/uf84H2KupIcBgQgQcrBUi/XYSkX6pTeAq48KhCyz1G9xy/V6sZsrM8VyqZuNUQzY9ByTeDvfuExAVOqGAnNZxpZ2BQca0899rDVVzp+3hwyl/9QllRovphinBZOHAmMG1SSUonAg1p4R8dELKav7LjHrKoEilZwcDoGksiQgWBu5jq2WPQdf8AJg4vRD4RAty2AC5s20omaZ9xAAQmilJoRJASOHqhZRWlW1jxe1iKUgSsEJ51L3TApCUiuebhClj1ThRUQPxBlrVdHFdzp+ofOtrEFFIK+g1Xezj9RMah/HASz3mYYkRRY8d2/ktuveQU+wsbyBz6oRIeUZ6R5SsE3+nmZcS8Cjv3JbB7nSW/N5J4CQHE49MnhEXe4YwzyfxfXXX9r7hsPvAMNvq2v2hS/E3B//sf2HhK2lBEjcEkvD2Bc9L4Gw32iF2rLFumyurFYiawXlO7o3+pIAcogMy0oApQzo4mnATZ3GTk1NYalf9+9nl/e1BzixXMO+qZG3GlQxjF1Z3SG1craGxx4DbpoJrq7D1qRlLBRCAd8GLSVes2VitycKlhz/xFMnbWDHli3ANddg0NmP48dDDh/GwxFn8Dp71mKu6elgeFpYAP7hPwzlPZb6FtAemB7G2UHpovfgg5bxT08Dhw/jM/dW8fjjIX/AmTPBKsXpNcb2p90OVqtWyybXwMIC8PnP21OT2QwofKvLKxAGpYyZ0h4BBSdyZiZYHvVeBV6OTrz0Ra03i4BR4+9qp9WzoY+rG3X2emGDt5alpRNvOeJB5Sw7/qI0wr6q5oL96XbtHBPgGIM1NP1UaOLULAMmzalwgDILLIFx6r8MeCIZlNXonPLgkQlIUos814YbhJ/xNxsBoswwUTZaFU74s7AQCxMk/DyP4kUGqIVSMk5QHRQVT+t0KQPsGIaZTbTk+YMKvG5tRu1JXwqCF7tAw64qfdl9KqPYZJaFz/LczSH5gjEYNZooiiAcTraGPhkN+8u+DcoqasZ+7y2obsyDzLZz/rxVwhjjMh7TtR2w73NgMg3K1mys1XJg9zmVVEq3KrmWpVcKkf8KNoozgooQSGvKU0+FpiMBKw2k5jtVY6+Cnr6URJteWRanj+elgtcYQKluZLzU2qMy2tjaiG5wI1S8d35RxGdWoyHZXlWw1gNQFQ6JCyPdh4GgENXkosDGXC5AnJCYdEzFoXTd7v3SKgg8H9D9mh7YajLVuWUoAXmHWuC4J5hOMZUPuPZaZJCbTGlA11UUowDibBxAACsE5uS7Li/A8nI4P7/2Nfv79OmgO6NL7NmzFwCMcM01m3H4MPDa1wKvfKVT0M7P2zSuKyv2nbSaMmuaAlidN54/Oi72z8210iWzJnNf6UWMqmuqFnSVK/w+hBSF17VF7I6tHulsg+8pS7H4Uf4jQ07RnipayEjc9wQ22m82p/IYvV3U2UL1dyQTxYrGIPJUqMEp54zwLnejB4maWVbAWson2OnUZV7xnUZpaHMqnvC7yLNCByD8NS1vlmJk4PLHGNZqs5ievrT3VavfAYY4deoUPv3pT+PLX/4yTp8+jUqlgmaziRe+8IW47bbb0CLH/t/guvHGWXzqU3No5kN/wDImZefO8XKgKka8AGWMdz9q5sMgzFLAHaddUUFENTK6C8mM1edRYoPoGkYtbbsNNM26928HQmKEQVFBrX8qgEyp/3dyOSSJ2NdaD/3Pc3topJkcCJzpknPttRGjZC2zLHMM6t57fSzQF85dj099ysZz8ICfmbEY4uW3uSyGBCg6F92ufYhgKs8tAAHCmMSyFWWnmJrCILPWkHq5Bs2JPpra562U9WxoNaqUjvhujes8exZ43vMCSGu3bWkFI0A+VSny8CwKO2+8hwcuM9XS1ZSuURq3QJ8ujX9kH42xJ87KSjB7ENxwcmnxXV7G6OD1OHo08GzWj2y1nOsf380SJ6Q7zq1TmgxQw/Hj4Wwis9+1y3bl3DngK18J5+fMTIyNCch37rSvarctvuYhytDaRsPS0VKvFpXx7PWshlpTmNM4wCkkpqRHAJUPXhjguEjvepCptZQWcgo97mflfNPXMwUCeOLFJphwiN9rhRfOD7e2AjqerdyCquTevj3ME8lLldJUhGumvUbDlibZ4FbkGlg3zSjMkH3yVrQ8tyA3C0IbY3YqxSDE6LmFWy9CjTCSM4X2UWuP1yVwCSj7ekuQSg/8n5PtFtonQ1AidOs5QsVqqrVQHgW7TieqQTdO+BwUlQ1bWrugXlC8+ArNjlyWIRaN91d6a7FEqMoJICwCx6+d41g5DyL9+lieBCCzzTRmkc17ME6Q72qo6g/vTWlXhcOisDxAywBoYgzeo/F3tDrqcAX/+v8JWvXY1KlhHLkerYDEqHOe1e9VD/Vc6hRmQ6+A0nmKlATqBqiKAa4RmRi/I4HQQkpiosKt2714gTxOhmZQIpDcts0iq3Y7bDTn/rq6GpLt3HuvPWYefdTeQtdXWhYPHbK/Z2aAWvekvZlaW0VYxgRtqfaRhK4FCNO6EURDDHzVhH1SSkivFNTx4lRo8q10ncbRirZFPsmkTzt2hMzUqofxGaH5MBsnPRmDtbLuSaLRiEsW6WP0jgFCTWtVnKhHM119U5pWz+tUrKSiJM08m4Iy7kN1J9b2dJj0ACDZMWO/Wq8pfrBtIPAI1gHnuhEg65bhOXG5y1Vk2Sz27r2099Xrz2FgeObMGfz8z/88PvCBD1w0bnDz5s340R/9Ufzar/0aduzY8XV14M1vfjPuvPNO7NmzB8eOHQMA/Jt/82/wsY99DNVqFc9//vPx3//7f0fDMbt3vOMd+K3f+i1s2rQJ73nPe/CKV7wCAHDXXXfhZ3/2Z3HhwgX8xE/8BN72trc967tnb7oJc3ffHSSu0qZ5B+TwdkXPfap4UrIG2AORWX7UnvTE7ouFd0/Fwn56AgLWQiFZqJjxTAVp1bZyg/d6Llg9kxIKPKnd2Fa27bPWwGnrjrWGJno9i/ump4F9Dac5bDQwmt5vBYsjR4L0ffXV8aFTFBgY67rnXYKAcMDxECkK4PBh/I8jFXzgA/ajQ4eAH/sxoHb0c7avZ8/a56iFpaqNqupz5+yJf801AUwxCFJRSauF0dQ+K3A5dxjGuaz3K6FERqtlAaBKpcCGwvURp+Va04pFYFgU8Bkb3H20yq2sBEElyywImthpYyAJnGg5ITBQL1LiRdIDhSKGjrLrvZ7Hvzb1fDYMIPX4cTvmmZlg/nRa0ZUd+30CIeJwWq4qvTXvAmyMHSI9RAF4NzLmQJiZib3BFNTRu5bts980OPb7VhgBLPZ3WwGAfY7eW5QfsswJeokL9TBvYm7OtkGLmbIhZp782tfs/1SI6/KTvCjsKmBRoZYYXY3CZAPc0mpwpeckx60giGvZ6dixrqxYN2UCSOomigIbXHEjqwMJSd1a1cVdLagywcOygmrPuSMzfq/RsOUHnMVyrRdKR3DK6YHHhDTGWBq/+mpxxdc4VUfMHshpWn+VwFzfWaBZXY+YqVVBxcTuUexu6P6mqyRjVkmzFE7yPFg0feZbRTwEoyr8q3o/z33stxqJ1EOLv3npELkslO29OzNdblOVOv9W1brOnZ4lvDeVqBV9pSA0C2U4GNsevVOBqvRrvV+xMeK8iiJyZSN9y2uipiLXQj6g/df6iGQu7kzm3NMiqXtSw7VJatQJnDvnko8p4gVihqud1RgAIC7IzThaB2w21MFzn3uZAqMNtfsi8ME1JcMgDSooIZoBNp6diizUnzPLLIO55hrg4EF87mgNx47ZY//BBy0vfuwx+xjpmfrXQ4cCnhOP0+i4ZPUNxkF6QEKGQUJYWLD1KJkZjuZD9vnKKwPC0L4rj0vRXsI7onvZURPcs5XE0hqTqvDQ+DufoZMPq+xAZCdyl7o7q1eHMUndaSCSO6PYav4WYL3eD7Sk7J1D1/FxPPqdWgb1HpUzdV39POjNJmRrzvNgKUxDLbU9gngqNI0JfYlc17MMsz/8w5cVbFWrs2i3L+19e/ZcOjD8wz/8Q7z97W/Hww8/jPvuuw+zs7P+u28U63z1q1/FHXfcgdOnT+Pmm2/G7/zO76BareKpp57Cj/zIj+Av//IvsWvXLvz+7/8+piiYXuT6uoDhysoKbrvtNjzyyCN4+umn0Ww2cdNNN6HVamE0GqHb7eJLX/oSzpw5gyuuuALXXnstjhw58nVZDz/zmc8gz3P8yI/8iAeGn/jEJ/Cyl70Mxhj84i/+IgDgV3/1V/HQQw/hTW96E+677z4sLS3h9ttvxyOPPAIA2L9/Pz75yU+i0+nglltuwQc/+EEcOHDgGd89e/31mLvzTr+RB2XVWtWowgFi64zjjMOy4i1s6TlJfFA3IQ18lgVvP92c/nK7OMoQaoZegFK/dmZBA4JSrpkPfTp3GqWyDDZ+iQlGZmaAmRms9av+jNu2DZi44lTQaNJ99vhxK13fdhs+192PX//1IC9yfLfdZoXu3bvtocG4/dOn7Rgff9weMkeOBG+vn/1ZYGLuT23bFy7YPtHkk2XAwYPedZUWJMA+38wlZXJR+Gya66bptUxlaTOSrpk9fukAFy9z7Fh0WIym99v76bLrBjdsTXo5hJnkWi1XasMYG49FTTH9IqemcKJbx5EjgSHv2hXXHswy+xlgP9f7GLLCs7OZDWJhxPnlUzBeXo4T6NKozO6kiuvDh4H6/P0BiRC1ARjke3D0aFgj0ph6i5JfU0ZbXQVe+EIrMOxvB0VDWpS9lo3gTZNqTlAVo1iuPfriaeKA7NJyxcaK0mrKPUkUx3ZpVQaCdNLpYGhqHpR7VMfJkdId7BbHzyXg3uZr+MqpKaDZPxkEk34/uDHzFAQsEVHQ5wam8MMAnu3bgcOHcXK56ueZa9HtBq0uDR0TE7ZpWivJZ2ZmgnGs0wnAmzoUjoXd5TSwgkdZ2nWlYZjrrrKWT7ilBWDz3LuPlmUQxJmNOcqE1+th1J70j/MiLkgtnZrpWUPN6C5FyxZ5xIlF24/J9sibWlfO1nxRepaR05qb3BJcJho9Fhdj/RSFGm+BSq2aCigFDPvBSeYjVQIC8Blb+T/pTOVgFdh5JrCW5lhpUL0u5DyOSmvQPTQxt6wX1Ui4Y1Fun7BCzBVeCKYVmoBLzQ1uv6ZWC+ItKgG0GxWMvCDMOeCc0CrK+FUqEugtQ6FZrZnqAajRFB6Ul+IyTubNG8Qy5CeGkrFK6jo4IHY90vXRdoCgBXL/K3hUBUyqCwAcr9UsQWqN1LFwc1G5T0R39dU2S3VjjzcSzs/b30ePxsCaQ9Z9ynkle2fTJAN1OOK2YC6cgwctz5mZcTILC06qJkeVGbq30jlNlR1pR7QD1MqwlqR6EwgwI22zCd2PzERfz4Zh/amcVw0QEDa0uhuwTxwTG+ffqjBT8Nt3dUOVXnXMbENNijoP2pYCd57JnM9nalM3JO/jGujm5qXnvsYgUYNMT5NWC7NveMNlBYabN89i585Le9/evZcODB9++GFUKhW89a1vxTvf+U4PDC8F67zhDW/A61//etxxxx34yZ/8Sdxwww34F//iX+C//tf/igceeAC/+Zu/iQ996EP46Ec/it///d9/xn59XcDwB3/wB/Gxj30M09PTePe7341XvepVY++788478a/+1b/CiRMn8LrXvQ4f/vCHv67JWVhYwKtf/WoPDPX66Ec/ig9/+MP43d/9XbzjHe8AAPy7f/fvAACveMUr8Pa3vx0A8Pa3vx1//ud/DgAb7rvYdeONs/jTP52zCTgEVa2cqXrTuh4iyhC4V5S/F4VjEC7BC2t/8cBCGWrYMIW6gj1l/BRI2H6exyZ/MlumFT5zBpjYvBYyq7hDmLEyE9tDEhae0dWFR7yLJ+PAaov2s7Wpm/DOdwJ33WWZ92232Wyehw7Zw/oLX6xg82bLQ1gPiv3kQdxq2edumlqz8Xi9XjAn8BB0p8xaYZlvMxvEhy0tX0SJtIgQTCwvY9iaxMJCyE5K4amJtbCmqxVff86X86D0TCZnjAWQZF4cDPOJk2k6AYuWYQKnAzOjOGMObIwmtWKay0HPDArmzDo3P2+FV3VB277dCaNsRGPlqAkQ4UsFms/cY4XfV926bpF6uw3MzgZw2+sBhw/jE0dCfaU0X4YK+fta657gR+1J71LN8hn10tWPXFgI5kIeNkSvMzMBpOmhrMRNyzyVMjMzeGQxKE9IItx7O3a4Q5pp3imlPP54QPgzM/ZBSjo8xOmKxXXn4UfhhO7DZArHjgW/T/bTAVE0Gj5OjlarnTutEmLlrKVzprcniddLt0doGmXsJjUGtPYWtlSKlmL0Vt7SJpui6+eJxapdKwCPLNeRZcDetmTL5BjzPFhlWi3vWk78zNtJB6yByO6xjMXUlNR1652yYLGsqTE9uDgSgavQwxeMCWrxxdMR4ofYv2ZD4o1YCihR4pGP17IRlpYr2LQpWEf4apXP2S1mblbjAFmQyjwKaOmGpjoLvkNzoGwoXs+JznOfiITuqBqjx/eJjOhJU6dPwbx3E0/NAW79aUkxJokxpQCngrh70RBVv/8IqtIMv+zj6qqz7AIeuOk96rUNBIMR9Ssa0sd3er6owDg5oPkuTjPZoq4P55hrx/vULW4cmCTdReZhY6JYWL0iS+I4F1S+WGlBLbx6ZqpQLooyxkTr+309PcZP8j3q965JuoAoKQ6yzIcjrBdVr8DQtSAeYrfVqq/4ml4yVDCurISu9fvA00+fR5Zt9vHO27aFdSGGZbJYCUv2Ok/+zf81/Jjt7d7tACgz/bAwKomBKa+J+tTleNeuOFutewndQtVbQLNfA06xUhSen1Cm4xKo90qWwedxUEUAED7XurSRRc8tgo83LGPFEbMiR7G0vBT5ksmk9+ihywVXHs7POBBRjDCRjpI4eRbXdNs24Pu///K6Z1Yqs8iyS3vfgQN/877edtttETD8RrHO2972NuzevRvLy8swxuDzn/+8v4/Pfvd3fzfKskS73cbq6uozliE0F/3GXQ8++CA+9rGP4fnPfz6++MUvPqOL6Ktf/Wr8vb/393DLLbfgox/9KB566KFntdo92/W+970Pb3zjGwEAjz32GA4fPuy/63Q6eMyd7ldffXX0+Re+8IVnbXvTJpu18uRyDcbsQZYDWWktC9xUNTPECNVo09bKdcAxuqpDb1UAVVNiiBrOPL0H20ugQN1OcAFkWQWlHJoT20Na+3onuDjQknhgKmwmr43trwP9ArUsA4ougDbW+zXUzQATpxcst6UgvryMYd7Eu99t9+VP/mQNe1v2kMjaFVSOPeCFbfT7aHYfskWCb7wRf3J8P379bbaZt78deM3UA8Bv/zawaIA/2wE0Gnjx6dP22YMH8fIpkQ54CtBs8fnzwIKr+H7ttWESnYQ0MHUfUlgvTmGU7UGvqKHZX8Mammg0aig6+4Pr4PHjwPS0jYVaBrJsEs3uEva3hDEtLgCtFk4Uk979sdGwh5DFdXvQ6exBPiOFuwlAZ2aCZl0AHgWMMp9E3VhhseyHc/vA9BBYtqBxHVYIX14GOiZo59vtUFC+LANQ2LoVeOnMKdy/aAX+mRl7eJJvBy+SGhYX9zr3SLuvnnwSOPYhHoR7fOa/fr+ORsNqY196q6WpldU6njr0GuztPwTcfbellelpuyZzc3h5jpBEh5IlEPtBHl0MEtnBg/aAdYdHrXT3tFoh1qzbtUh3agpYXsbg0EvQ6wGT2QDDvIljy5PISuBA27rWjNqT1roOoNEGKq0WRjMHrCHwePDY8S6zQIiDXTbA1BTWG3vRa+zxwgCNeFlmu3H2LLCwaS+2ZkDWAPqNgPGa+TCOrZyeDmZTgvFuF7j9dn/orZc1PPyws5aXgXSyrOKFg5UVoN+vecUoFRmM11h+oonl7d+PzrUOFzZehKII7rOVhRP+/c35o2gSVDFH/oIFQnsp4ExPY193Ecg6QJZhf/9+x7NasTTOA54H+Je+hL1PPYW9Pla177S5rSDlTxmg0/HCELePrQpRcQf8Hk9elC2tYtjVwcqaOLutaXlhwwouBHG9Xj0yHJelrQl74UIlstjaxEUl0LN7v1fWcf58DbvbwQVVE+ay5uJkZsc9kfcigQnGIT7j9r+TWGplib1qfchyTLaKCHySd9OditO6aVMAzxcu2OaZEbrbraAsawAsXdDIPZkNUe0uYVI196l02GoBJaXO0m4W3pPDu+ISf8/NAf1+069FowFMNkIinapqPjnBeY5Ry3pfRGUKHK1UCzt/Vc5ho+HPr8h1shxiYnMfI1hwz+QZZWnnhULhpk22GdXRAEFm7/WCfo7TYgFGFZs3A+12zcnwVdSc0Fwr7GLUACvtdGxSLnV75341xioLOPzHH9/ozcj3GgMsL7OWW80pce05ve1cHGIX4qoq2LrVWrPPnG/6GEy+vyyBIg9kxstbM+nqrDSrmsnPfhaVzZtR5ZrwXipi220MOtZTpp4nYTFlac9/IrnV1ZDlzRifobW+dSvqGgBHVEPaoz+patXPnwfMhcBk1ce30cBSt+rzgs3Pb8b8vOUlDz8c3OmBoA8lyKQimDxejVGqlOD9irmBvdiyZS927gwKlHbbnr1k+dsm7HnhXeN7p+zZsLgY0K8D2/U8BzZtQv2pp+zDV11llYnUBGUZ0Le/a2Ufe1F4GdIvcr+M91ijgQosPRujCXcIFgNoPH/e8qBAr1XU1I0XksmXe5luIW79KPPy9b6kiCsx5lkQAKCKrFHzMebpkUK6P38G2Lq1CuOOlxyiFCMwB1B3GeqbvV5wrbqM19NPxw4X3+zrG8U6p0+fRqPRgHFrrfc/9thj/hljDHbs2IHTp08/o0fnswLDD37wg7jiiivwrne96+uKG9y5cyfe9a534bWvfS0++MEP4j/+x//4rM9c7PqVX/kVGGPwj//xP77kNtLrve99L9773vcCAFZXV7FW1Hw+kH7fMptst3W3rJsBRqbmg/KrQPDVhIutYEY+x4SrxTomNpdAtx9URi6ZS1WTBADeglgtnZ61LDFyRdormc2MhxKouw06zOpY7NYx1QKW+3U04CwNi8uWM87O4oHuJOaPAr1eE+0F60Z45owd39577wSyDJUsCyk+u90A4r7v+/Dxuyq4+27gn/0z4HWvA6q/+R6gmwNve5tPFlEzTmO1eNJaoOivRgZIJEYLDeC573q2B8vLwI4z9uOtW118Y7cH5Dkq3VNoZhmGWRPNxRNAmaPWamFltYbHHquh19+DqR6wz5xE3RisnJ/EQ71JHGgs+WC7tc71PpTw9tutwPbQcSsksjs0FJVlHZ0OcO58DV9YaHo8xAOfyrIbbrCZPLMMWHQCPnluu23X7v7lSTz6KPDd3227MjEBn3W104EXmClTNss+Jh47bhvpdHBT9hAwnQOtNiZbALLFwNQ7e7G4aDPJ0chHkPTmV5+ydft6oT4kvTaOHbMC6MxMsDqczA9g75QJlldjMDr8ElSOPxQsYdwUpHkKqbOzATBqsCDBIK1BrI3ICWw0sIRJTC4+glpZAot9VMsSNzkku97fA5PvQa23hokn3Lt6BoP2PvS6wE0ddyh3YSW27duDZZS0XBTAwgLqc3Ool6UD+TO4aaofhKk+UHuyj4mtfX8w0gLV6wEPzVexvLyP2zOsLybRKyatnPM0sNthxPl5mwDqBS8AXrz7RJBcaIGbd5LIuXO2v08+CUxP2wOQKmMAE5s3Y//sLIa5zdw5PW0FgZVVW0Knb/bBuIPXTO/zchWFZgKm8xOSffPQpJ/+6sHcuyF3e/aAhgG27QgK8m4X6G4FtrWsp2unY99XL9ditf65c8DDD6PObDYAalmGJpUMThg6sVDB3Fwcb/roo8D27RV0OhbP9vvAF75UxenTdhwEwp1OsERy6XbutIocZoYeFBa0kBT35mvAFSVQ2vcT60z2HgIWS6Boxf5uyovJt1qtoACgtJP6u2ohu17PCuGujYoxqHNthdHU1by71Ums7dwnwGFmyV4POHeuis2bJ5Flk/6VBHR81ZT8XymlvAbfefw4Kr0emgCaZYl9DA6bmsJ6YQXxB45VcO5cFdu3N5HnTWzZBOxuIZRQabVQ4SYYZ0GgS0thEwl5196yapWnxmBkavaMy/Oo6Ha1exJVYywvIFAoS2C7HTDXuGaGVplQDt26NCJrdzMH9hn7N+u59vtA4eIPgaZP+sN4t2p/Dc1+H00AaGQewDAREZMN0eVfAWriZRjRH/9XD0h1TQZCDUMOmZ6M47z11Jpip63up6ko6p5Ey2wvTA5kU1JyRa2ZTOh2/LhVKpO/O3PaILeKyrJ9wCf6Uvoe6x7LzqmrtJqHeV24YMEiTYraHgCcP4/JrVsxmec4AOBlxgC3toDbs0BvYdD2GX6mWlO1asu+pfX2zJmQXMYdE16fuLBgce/KCvCBDwBnzlwAUAAYAjgPq6asAtiGLLsJ27ff5PXHTNpz223OYyIbhjSxx46FAFhl1OrSSoIFgoeSWigBVHTcxqAyNYVqlll5MrUe8zmGJ3Ct8jykwEldVN3cVtx3NfZHao5Uz51DlWZiPgMAW7ag+uSTqLpzoc41p0aM8aPGoKbxpBwvFVFTUzaUoltz0/PvcXmvp/H00+ef/bYx1+rqahQb+Ja3vAVvectb/P+33347likPyPUrv/Ir+MEf/MFLeuff9fWswJBWwh/4gR/4uhv9gR/4ATQaja/Lanex67d/+7dx55134lOf+pQ3eV511VX4GjNHAFhcXMRVV10FABf9PL100WYPHbJZPBe72EdmckUGoIV62QNgQiIAboZ22weY1xHSyvf7QF0y9XlpKMswaFiXw2Y/1Ao7cwZgPq8z56ymZvPmKprOvWiU1XyB7ZGxhe6r5QD7sh5QNDDZnQfme16Nen/nNTjyoZCok0Hls7PAG79vHWtlHUtTb8Dkl/40uO8dO2Y38NVX4zPZy/H5/6/lYb/wC8De4hHg594dXOXuvReVVsse5HmOCt0X77gDQ1SjhH/UnBeFTYc9yJpW6Fm038/M2Np96PeBv1oGOh2sNfbh2DFfyQLdBaAo9qHsAee/Gg7ULLPjumd5r49RMAZ4312TACbRXrDj73Sc29y99wJliQPe/fR2PDBvAR8Tejz8sH1mZoaa4CDfsibU8rIvl+f5OWPyquUAjyzWcNPBIW4q5oBejr1lCfxVHxNliQNFH8gOOvfIZSBrWencFRrmAVahXy4QJAnnT1o5ehR7222gl2EfBdcis1reCxeAhQU0d+1CU1XV11wDHJ7FyX4Ti4vA/mkbr7O4CPyP5f04fHi/TQAEoMIBEthp0cROB0vtm6zrcvekpRvV/LLmHlE3zUdOATEyVVQWTmCy1QLa08DRoxjNvsjGqn3wg8DWraiz8PL0dHRw1Y7fj9rCQojLM8ZqYtX1FPAHzPr0TagfOmSfX1wE7rknLsbHtnkIHz9uhd+yRDPL0Ox0cKBVWLcsVHztRGbaBeA17uv9Cl520AHWv+qHWmBFESyvDr3T9YeunpqN3hjnhXD33ajmOarMBFQUmHBJrpp8+fx8JNjVKEHSvEFl1Je+BmzfjiZBTKeDSlFgsiwxWZbBPPUUgAtWmJg0XaBVig9UA3U4wWNqCmuNfd7VJ0rgUrgSIXNzIblRWWKfMdjXaTiLo41DpZ5sYSFkoX3xlSeBrY7mujmAFtA3Fkw9YYWWWqcDFNYVCWVYB8b97S1PYJjvs1ppt4cnGwNgYQHrHVvDc9cmYCIPWnC/2YFY0HQA0deKpNlRpXUKoYyLUW8JFU5pilBLD2n2a18D7rkHlSzD3m3bsHf7dmCqYZU82aTHpxRqgYDPjx4NRgtjqsiyPb55S+L70W5b5dSVVzpeuLAA3Hsv6kWBujHY22gA2zPLf8u6X5cnn9xrc5Q47OcTbvAFHpEEYbSyvOTdv2tFL+wfp/Rc61eR51XAjQdb6n5L+lT8LqZ+WFqFqDGubQJVp5BlAiLikJqzOFfnH7FgEQAaDTRbGUZZzXusA9ZCu21bDU/BWk9rJoDqSmG9cfZnfcC4DjRMoAnTDxYWI5+TLojUEwBF904d6wiVSNeSZmwEQtZHxVwEp2R9+krtxiPztNjWYLL9MNP7bcmo3aOgCHa076u6Ukh3WohhaxJnNk3iNGKDdarf1qnYsgXAd4VkpcpqvdWeShm6rxIsnjtnfx8/HhdCZJZWTo6moda+a6kP92zFGFSzDBMKZozB9b0ecO4s0NoMtAMI45nlFR/tNpBtwdDUMD9v9x1LQS4sWNnht38bOH/+DOA8wq64Yh/yfB8ajZfhuutCCGMaRq/5gch6ChP0UxMT4dnpaWAyX7f8//HHwxlNXsLGqYC8+upglRVDRERQXMw8x9JycO8mTXa7AC649X0KaLXjsHiWvMo7gSYpFvjkVcb42tjUl1I8OH7MDmN1Ffjyl4MS5Lbb8E24noZVBHzj1+7du5/RlfTuu+/+htv8RrHOrl270Ov1UJYljDHR/Wyr0+mgLEs88cQT2PUsVtlnjTHcu3cvrrnmGnzqU5/6hgZ2++2349FHH8Vf//VfP+u9aYzhXXfdhX/9r/81/uf//J/YzZRyAL785S/jh3/4h31A5vd+7/fi0UcfxdNPP439+/fjU5/6FK666irccsst+L3f+z1cd911z/je2Ztvxtyf/RkG+R5bzyfdQIC1cjkXEWqw6+XaRp8FxqIFnylfPLlqrNl8kO+J/f01pkCL6ZK57dxpv1dnfUpmV14JzM7iRLeO48ftV1NTdsO1WtZSWO0uWWGtLIFXvxr/+m1VdDrAHXcAk/1HsLJjP/7iL4A777SvmZmx2UL3zf2BZTrXXWf7MDPjMxT6TJ+SNXS9X/EyEQ+MlAe1227eXAdPwALBubnAUIhLisLGMtIjlVq56if/1HKlqSmsODcQn/nQCdAoS8u5+33g4EE80N+HsnS1GbvdUDrj0CGsTd3kD9M8B5rFUoi7o9YzLXqb+vi02zixULGxXKw/SNdDWh90YpjRw7U5ak9aoWpxEaPZF2F+Htg/FZLMFIVd10pvLUjTFExVS0jaAIL1jpJlu421xj5fqoEhdsR+hw4B9cWHbBudDtZNEOBJF5XjD9m2Gw0MGpNWoBLV9wgVOw4KxlmGUaOJ5WV4q9FLZwe4/3gNR4/GmQIPHQrxlZXlJW/F0/IHK2eqXpBk8p2tW0MZQS3/YExIlAHjajSxdidfyrhHFfR7PSusa9Zlmno1T/6WLTb7DgUYl4FJ42+odBXFL4CguKGgRKGf8z097cB3p+NTt/P5GpwmnzExFApcbKOPa2ZMbmlr+AFAbeGhAFTZAZoZ+RJauY4dC5Yxxk0WhRVIaCVUd2vSnyITFZj5N9/p+rGU7/c6BdIDm+31LPuh9bOOUCvRt0HhstHAytN7fBz1UrlnQ+hnc/mhkMl4aspbl3ixsPygrHr3c74iy0J2261bg5ya5y5uTxKq+PYw9AvnXU3LQeAFlOw5RyxTwERc/BwIUr9mo2GGaMdHNEEZaZDyP40WbIpLOjuLkGxNO+94ANkqyYIunmrJ5fk2LCt2Lrj/uQFIC2puI6rLc6z1rWtlDYkClgeH0qgK9+Snxnh3fMblk8yr5SBoE0UYpjWScjX1RUDQF3gQJ5rAkalaPszDjhuTE6SAWVGbZofSvccFUUWDAJRRa4+fNooBQBDIFRBqhQs9FjiFfAUBidb0rGIYW/PU7YSAi9YnTpL61erY1DKegjdnlV1dDW7VapTnj3fZJPESFKp8plmp1LQKxIF7DCClZoX3cq/pOAH4opscCy1fJHyadxmyQ4WkafrzmtETX/qSLRNCUmCIJ4fCdeG5TBxHkZDrRfBUFHZMV165CZ1OUIrzh8nyVGkAhO0mywAgPv50WjlEFW0p+qjXAq803xGXgjidS7KyEm8N8votW+xYmNDu4EHgNa+5vDGGV1xxI4BPX9KzN998+996jOGlYJ0f+qEfwj/8h//QJ5+5/vrr8S//5b/Eb/zGb+DBBx/0yWc+8pGP4A/+4A+esT/PCgzr9Tpe9apX4UMf+tA3NNA3velN+PjHP44nyMWe4b4jR46g2+1iYmICv/zLv4x3vOMdeOqppzyqPXz4MH7zN38TgDW/vu9974MxBu9+97vxfd/3fQCAj3/84/i5n/s5XLhwAW9+85vxS7/0S8/ax4MHZ/EnfzKHTifUkdfsX9y43h+fzLPTwSive1dz8kFuJhVWa2YYCzKqZQQCA3VAktYqMkviQ27iY8esC/ZjjwXLFoFTngP7cMKqsWhiW162knejgc/gpbj7btuVD384yLq33mqthC+dOhmSkwDA9DQeKvZpQlbvfVoULs4L64ETuXFRS1vDIHA+19GHFuu+huHMjAVBXj1FzbvGTxw7Zpn11VfbcZCRf/7zIQCA/XVuvuvZHs+A220rDx45EgTQ174WqM/9j2DVosB1+HCUHpTjIGa/cMFmOqQQRprZ27LF4U9gny+VQItknofsrUzASlK66qoAbvp9O5xeL9TtJiOmV8iuXcCNNzqhpW9d6lZXAxBhGnF+VykGIVOdM9U+Mm9jwPY27Lqt9au+ptUtt7jEPK5sief0kvhn0Jj0OQuIQ2nEYskKAkomg7l+yvbn6FHgpkOjSHj6k3ua3qBXFLGWNM9Dva0rr4xLRKpCNy0azMOH/WBmZgXDnU6ooQhEeBbGAM9/vv1882ZXG9TYum7c49WFR6wltWc/a+ZDvwd8+u3UXUetUppC1pmmh6j6WJmpqXCAUy9EwYIevmyOByyXTOtyveAFdow8t1iSk2MltqBAWctGuP+ope9NmyzdcntounGvSMuklA8QAKu3sri91J708SjV/lpIedjpWCVNUfPydbW7FBiMSk0qhPb7ONFrYnXVWcQa61iHjVfePyUCfVnaeNpWCyfaL4n0AppbglmjOTdAXOrkiSdigyHBEfdpagFW/MI2Sa81M/TKIV9nkWYtBYRqDlKXum43lPghUKfJiYcYP3dJQ5gOf3nZ4vsnngg6EvaLHhLVxROBZ1PjSKWWgN0zZwLvMSbMpyb/8BZXEqu6oNKqT6SqEirPAQXFpS0npaDbo38FkcZg5UzVG5a4BfnDOpqk0VGj6Y8cFXJV/6ZKJ7VU68Uuq/5Dh6NHG7/jXHl3V/IN3UvaCY6Z9MFNnGUY5XV/XinmGXdxTri3le6NQcg6C4QDiu/UdVGFkiqDeHHN03FQHqLXiZjUVMnB+WO/VAelSjfvpqyohX2hV0C6iLqneCjzOncudnukeU/TBlM7qUibNaaoEHCC4NDULN0CUZ1n7TJjCLWUBLtMnSYrfVjLvuVbtM6qN60COE2mpYZaJubJ8yCLiF4i6h9ZzFNPxYkY2RbbphinU62xoGVp5ZhrrnHJASmfzM0FQevqqzH7nvdcZmB4A4C7LunZm2/+gUvu60c/+lH89E//NFZXV9FoNHDo0CGfWOYbxTonTpzAHXfcgbW1Ndx44434wAc+gC1btqAoCvzTf/pP8aUvfQnNZhMf+tCHsG/fvmfs17MCw02bNuFHf/RH8b73ve8bGvCP//iP43d+53dQplqjb6Fr9oYbMPfZz3qqHubNcOgkTGaECt30o3A6aj4Y6kT3TwaBMVU+kyJSoHj4YfsZa7RRM8iNToGPm41MftMme6g7l2xrYTAiCB0/HqeRZ1+cpeqB/CX4f/4f2/bsLPCKVwATpx+y6q3HHguxB9PTWNm2z5ef2IuT3nJDgDQsK944EdUlU2sEgEFrr4+fabeBfdmSdfF79FF7zzXXBAneuXI8NF/1zGdx0RpyGIfUaARtFA21atAjIGi3Xd3Go0e96e1kth8f/KCd84MHLUPUevBFYafw+HHbnV27LPak4nFlxc4b4LTS3SUgz/Hxe+peoGffNAkctwENUMYE/HX+vBVuKX/xnKyW1kK0VtR8W5qMVEJ8vEaZgq4YZnDTwWEEEIdT+7G87GKyHKGd7FpXmZkZ2Cy9ND0DGLX24N577RpMTcWuMfXM0h5dbbIsyHj9PlA/9rlgPWXHFxbsJD31lN0It9wSJElRg37hi5UImDQb4gZFemFiHNUMHzoUEt8AGLb32qy92yWrq0Ndo6l9IZNlu+2LW9P4S3oCLGh98slg3Tp3zoHpfoh7q3RPBUDNhSfDUKsHJXFaqIl6syzUOqHkpqYv/s/O8XMKb1/7WvD1uXDBLgYRO5+j2Si32S9p1KZ3ycTWdS84rZc1n2mUshMzKOe5E2Yo+KvAqCY3Y4J1GfB8BHCZlOfnw9gdkEFZhjIUjVAmgYLvU08Be7NTYXGmp3Fiserpfv/0yAobCwsYvvYNuOsuu367d8dGdxVsAAH4bl+wZAMNF1wKAmzAWV1Y9gYI43baofWy5g0UGmqibTIPRN0MgpeBmnoULPFc4rxSswJs9CKg4kFRC7WJ7bYvz0NlFgU7wZTWDZWAFAgmLNKe+6EijfuHJMi2jJH6o+wn94B63+g4Oh3nhmr/9fU2VXJ2oDGywo1DYFnms3QD8MlforUDYtOHoiX14zQ2K6saxdn9Sn89KDn1R/pNL6ReLyRN5v+pMYw0RqsQk2JyH3rFNc967T871Wp5CyTxj2I9JTG6C2ZZKCHis16qkptoQGmLPEvfr3TMiwPTDGtUdijSATZaDZX++Zv3KlhVXsR3Kj1QMUDeDVFaZpl3hQ5+nkXQONLriwBSJ48JaFLzn/phcsG3bbP3kRh5eJN/qjKRfeN4NDZX36NzrCia88Pv+LdaTLmWuqe4rsqLuD6qsEhRu64z/UjVTJ8+yzPk8GHM/of/cJmB4fUA7rykZ2+++fXPvQL3lUoFP/ZjP3ZJwPD9738/Lqhb1rfYNXvoEOY+85mYieU5Vs5UPWij5o203OkAteUTQXU/Px8sKoyT6vWwPn1ThI+MCR6OtDRqVkImYpiYsPiM3oiA/Z5udAQS11zjXB+d/9kANdTu/pNwCj/8MHDttRi09+FDH7JjeeONjwBTU3hovmqTtdx9t92ou3ZZxuSCfpjN8+xZ4Hu+J1jdgDjDdbsN7JsKmfj0vFdeRetpvXDWqDNngOc9D4OpA0wy6kHvk08CX/xiAB/Hj9t5uuaa2ApUFPDuFEAwLjQawCSWYjMWpTmb9gxoNDB85WswN2ffydC1sgT2dkahZAXj3fI8cp09sVDBvqmRt3j83octiD182GUeveczIRuBup0wYwwlUf4+ejSAYg5ifn5jHSdq7XloKDNtNLByvhm5MVJZS0A+NQVUl08CZYmlbB+OH7d08eIbbfzRaHo/7rmHCWsCltuxI2RmyzLbVrUcBKJI/TkBe+P8vA0oL/Z4TGCMLaZMy8LefM0qCVjhXjcbza4UgCmxcg4AfOHBGhYWLGDnWXbHHc6i1WhgrVexwv6xY2E92V6/H+iE60MzIgUqAlb+T/N5t2sluquvDmZ0d/9aUfO1v7gPiHmYB0LlGE7X9LRVOkw2pBYcBUyNFXEPaykM4kpO0a5dwa2o3YYvVB+hIMf3GEs5bOzxNEMXV61NyvXX7O60FD3xRFCOdTrOyqoCYZ4HAMixOaJc71c81qhnw8A4FheBQ4f8ODdvtu/38clubzKG9iUz4m6d5xiYOu691y7PvsaaX8O1su6FbyC4HbNgumrKyRfUa4De4MBGFz7y+yyTpDBiGaGikMCaFt7Tp2NNOxVINEaQRuhB4l2jVfBSV0RVTqjPHjeJMmjuCWo5Gw2snKvjscdiD+rUAgHY82pi9yh2yVM6M9Z6R6WeyqcTEwHPAuJqm+cYoOZpjN1kbqNauR7MFmrOc5rBYd70ce4e2NAFVPmTmy+6+gLWLZYhIIC4BBMUcsP6OO8iHHKypzYAXF46P7oXOMlcC7fh2Dcql4nPNZyOhi3lJWyKFslmYxRKNHHsVA6VIWmZdgmwt7BkBOmcQ1Ndlw7BZ4tOrXfG+NIKEdhMLzbGNVZQwnbduqkVX6eYsaopTvIlQ9KB6sSpAoW8n3uYvJgN8jtqmNQNlwIcL/p0U/kH2OdWVsKBwMnNshDMnWVhwTkfMg86v/5ZBcPcSFQkFgUiN51EaRGBQYJydWNXZpcqIVQQ1EKXCtBJ33SpcocUy3gY881wJX0hgI9e0rM333zHcxMYvvKVr8Tb3va2b6jhd7zjHfjEJz7xrQ0Mb7oJc0eOBGYJbLTvk5lSm9XrBf+qgwfxuYVJH7TPoORjx/zXvlkgHKiNhrVUPfFELPNRiKOwRT98nvcEQXtze8jRZXLf1MgK19REGWMlTGPwkXsn0WpZd9HKsQds2i0KT5RuGg3ge78X+J7v8fXOul1rbfMuiUAwp505A1xzDdbb+7GwECuxduwIB1WrJYV3nd/lWms/jh+3hg3A+pVT+TYxYeXsyeKE/XJqKki8/b6d2KKwkwfYB//qr+yDr3tdsIrR9awosN45gCNH7O0TE/Z9tbnPRBYxz/w1AQsFfyb0mJ6OtXYzM3iktwfHjgGvf+3IzmuvZ9fgh37IzumxY3YMND9RS9lqBReqdhuDrIla/xTWzB7fHeIgys+kEe9mx4OdSIBog4zZ+YhQwLvqKku2AEKGv04Ha70KHn3UuXx21gJNqDRIUK1ufS7Ok2X3Kgsn/NwPWzbZ0rFjllyIrVQZefx4yDPQalkwxzFyKJ2OtYYPyqrH9HS15DRyuaicPXs2eGmyth6X1hhLuhR4Odfc9rTcMuax3XZF0rlWTrA3xsZ8EpBs2hRqc9HNk33j/i8K+/2OHdbKSE8BAi+6IKuVmaE9xNyqSKLbD4Uy5kDhUjFejyRelqEGGD9vNBwoIg25w37lXN2n2wesULnWC3U4CXxUYc55pOGS9z3/+W7PletYOVf3FtdmY2QXn8mTaPWkAEL/RlpARfDndw8s1DE/b7fm9eYhqyArq7YWa6fj14psAXCukt2lQABFEWedSrXjQKwlV01fbjO9VopBZJ1Z71c8ZlP9DZsivRkT4tjWy1ArkT8EnapTYjdoWdLEg+wWjefbt4cSHd41lBOhgJD/A2H/s9PUaGQZlpaDi18qjOtxwotNVHun/Lpq7DTJjjI0Y8/YLZ84p2Et2IOs6Y+CxcWwZ8nX9nWcZZOBq6Qhgmb3fo6hWohLKRdFgDNdM7nHamboazeSR2m8qWK81GDJdeH46O2rS8D5qmAUuwqlFwF4KmiTRwlgUn6iyu1OR5QwlHlI2wgJfoh5eHHdaQFXHSW/H2dQopux0gy7Lg4cG/AJL80/w7Hp/JLmNbRQ44GVV7JvfJb8zJjEhTYdDBlJqilRoM3PVRnDtkhMjQYGIeWP9fjiAcVNxInm/0zOQ1fWPA/WSSZmU4R+xqV912KgGhicMiK2SUai5mTOA4VTZUI6/tRaaAwGRSUklEJgQaq8YLZg5U+zr7+8VrgrrjgI4A8v6dmbb/6nz01g+EyFEJ/t+pYGhjfeiM994UtRrbtGQ4LOyxIDU/da/oWFYGQ7fhxYXT2PmZnN2L07eGzNzlrhY3///lhrQ6awuBiSO1DdNzVlNzc1R2m+627XvuCqq+zGufLKUCCsLFmkCpidxUM44F0UGw3g+vxE0NSfPWul4nvuse0cPmzrOUxNAe02lvp1zxfqRz9j38l38zCi9Emmx1Sd1Bapho2MYnoaS6UFUVQStdvOesXneZgvL4fc0a1W4Pi7dwcrAgOCDh3CUudF1iJy7AFvdhmhgrvuCrFaNEY9/HCwxt5wg3OZE1eMQb4HZ89arHn8eDDQ7doVwC7j+Fje5CVTS8FyxsCTBx+0CHdmxrbNZDAUtAg0KB0Bvni5txwWha31djYoEDitJImJCcvraQir9Gzc18DUQ6IS54ryyLJ1GZyedhZVB+JWzjfx2GNhSV9+2zAIyAo08xzrnQPeyKbyxPHjgTxZ0oOA59ZbLfhYWa0ES8fx48FKevgwPn63ddfjOmksJs8g1rqcmXEJP9jhhYUQiMh4j1tuCfPsaHTU2mPdPNXclefBDOH+p0utWvtotOPSNBrWqk2hnUbegwddIp/uCTs+ItWnngqBRIClDfIGIBzkN94YI0ln/VAhyFtMVEghIuA+1+QQrv4D07YT3HFrsqaegk26SXIKVe6s9k6FuVPXcWqHqOwoLJBkiPC117p07vkIJxYqXjFAIZX6E7rpcihcIuLFTZtsBjvAZq+rHPkfQL+PlRe/BoB1TR1kTdSyka89aoyLCaVCjMyx38d6PmnBMQOGlVdrxlIVFskLuTCkIQVbqkVXYcxZTTh1lOPUCME+U/7csiVW6rCIPL2QFXwyZkh1WCrIA2LRZLIo3WhshGNUqxg7pEKgG++wsSdY/DgQJzAudasen/nEZdy/WidUzdDcdKQ1tb5QC6LBsZ0OPndvxStpGAIw2RjEqEj6xTqcHHqjgVgJqu6gnBt1u9N5YL9JKzqW1LKpbbJd95vZvIGg5+XXxB26VIAkj1FEyvco6G23MTQ1H5JAkM1YcMr35HG+jp0iNVpOORZ1fUjnQq90/JxwY+s0kwz5kzajzamiJX1F+ip+BgSvJC0jwnYVyGuZRk3EwosK/jyXeFW+TM8W8kYyMvIGKrsFzEfBnjxcyYdUe5BaJVVhxsGrJ4F2nu9i27qHKdeRNnn2UwOoE5sugmoFUqWaLozSo/JRtXC6/y8/MLwOwO9d0rM33/zPnnvAcGpq6m8EDL/61a9e8rN/19dVV83irW+d8/Ilma7yVP2b6dUPHXIWuD/6SJCSKZgtLloEcs018SajFonp4MgIqA4uSyvpM0UhVcY0yVBwYTpijS53Pmj3H69Fe6zfBw7kJ63rZFb32eT3ZUtYz21sCS0o/b4d1/Uda41ceXqPd18tSxuCePXVwTJqjB3G9e1TXrIZZlb4rGXWRWRpOQiAxlhBrp4NY7dAmhwPHvRumlNTFvtNPHnCuhXltvahqzzBWz3PYvtqqbj1VtutOtajmMs1NHHPPT7ZJQB7ANPiMzUVl5+kIH34cOCVi4tu7OX9gcFJoOMg3xOAmmYo4qLwZObf1MYBdjDUAHJgmzZZs4sKIouLwRxGU5PG2vV6dsE6HZ+ZaICaT6R5zTVAc/GBcJDdeiseOFbBPfcEmfjWWwMWJzBST85qd8nT+P0L1no2PQ0cmHEaQMmOieVlDKcPhNT3tAAz/vOf/BMM2rbcQDMbBBc8br75+TDWft+aorZvB2ZmMGxYS2t18URwD9XiraQxaiWAWFFD8xkB2tat3krMVPPsAmns4EEXe9XvW8XMo48CX/lKYBTtdihyTEGX3+nBy7lot61CgfuaG2911fZt9267cI89FpcKabXgTb4cM627euBTa0yPAhL68nJwF3KKFSKxIarWqiKC8QPHAtgqipBtjq+jd0K9XAub89AhPDRf9UqOgwddHGtZ4qGFmleyUI/S6QDN8pR3k//Cl6pYWAjuly87PPBuGaPp/Th2LLglUkheN010u1bJMPHkCWBqCvcfrXi2QwzY6Vh+xczKGs/NZSHZcEmYwTS6URt1//tyF7xHXbT4o5YalgkoK5H1UL1CKWOpOycQg0EVctUQoDhP8cKuXYl7Kq2L5CPq0sJO0Q1ALA4s3VQpBiGmyBhLS61JVDHEUrfqp8IY4MC0uA7zTOTeZGedX/vQ1Lw3TlmGpBbGuHOFpggAa2U9CkfOspAEbF9nGIM3wO8nFvlWcMJ5UqwMhBjwSEhwEz7K60HBnC4CF1XRjZoaVWDXheJ8u/81SQlvU4Mvw7jdEliFkk4+59i53Gu+IbZZlhtD4xSHZFnIe5QCNtUZ8dLkfvSo8JnF+RB/K/DQDcDBqu81aUYXDNgAOHQuB0XIps6mVU/C/msX2D1NTEW+lMqMfDXBaJ6LdYznmNKBKtd0E+s4lRHxhZw7sUj68SrR8vzU//UZpTeduxT86xzzf07aOFRORaWuEZUz/UqkCyUGfcMbLrcr6bUAfvuSnr355p967gHDb+dLs5JWF0/Em04DHPr9kJGEAipgCf7FL46zl8zOYnToJnzxi8HKDwRtLYWNiYnYlaSeDTe6UqnmpyisMETBkvXRpvd74LayYsHd3r4rLdDrYeX5L8HEziG+8KUq/uIvgvb4qaeC3H777VZYaxZLtt1eD8OGrYtFYxiNh6JwxaOPAn/5lxu8q6K0zDMzFlRN9h4KCSg6HTzSbWJ+PjYOtttWkDt9OgASZrCamgKa/ZMYdfZ6d90dO4AXv9AKaSeXq9Z1tXDukA8+aBvi6UOhjEJ1q4VHenv8eNptoPbpPw2BR0SGZJ633RbMRzxBOZnOZLzUOODjSCknXnUVQlkN1956a19kdF1YsOvm3W75BS2NR46EoG2mz969O6g3afIhCKGAQTBSlmHcMzNY6la9m2KtdLWRPv952+b0NEaHbkKlsKUlGNPEOaoWrixHlmE0vd8rkL3WmrSrVheC3uVlrDf24t57LV1lmaWN62eGIdYvy7Bm9ngsv7cTamJyrpjMkuckzyC6XQPx/tK2eICNGk1U+ra+ZzMbBPBIbUO3a2mI5lpV1dMvtyisq+Pu3cDBg1ibeQnuvTd2k1NX1YWFYNGhBYUkdOONgez07Oa4a0bidri+Ylkmy0rleL82jg7WTdMKY71T4UU84LPMmkJZkJk8cNu2kBb39Gl7H/1SSa+U+F79anz87qrH5kySpTGO66UF283GKGjkGg0MTN3PVaV7KkgKzLLM8R88iJWrbsJjj9nXTk0BE0884pEeYwgnnngEWF7GYPalXumjxdvXy5qnD24jziPd9hcWNqaYP3Mm5Irg55wiCpMqd5HtUKBm2Ycsc/tJ55oNKgBLJU0VEN39LPsABPLQBF3sR6qgB+Jjhq/xYQCqjGGfVJBVQZFu/O58ortcltn1H2X2fwKmUVbDPfcERZOWnFHvfg3Xnp6OsxNTH8sjsdFwSgcCU/bPucCvwwJGxowy1pnr4y2GXDxRikT7hZ+lk6hWIr1X54/P6o9zS2YT3qVR2+Tcp33TNdBLFdNZhrVeJfIqjJLW6LsU/WbWfV4BEl/JLV/PQ8wgwaqyTJYz4fNsS4Eoh0Z8wqvZGI0fozH+XWUZl1DhrfV8FGQOZaxqmuRa6Lrobw7ErdFaL8RjKjbj+9WbNF3u1Jiu9+k5kT6vOJDvo/LdJ8hRIOmUBlVjFV46TI2tZt/o1qyeoRSZVEfJd2ufKYKk+XeAODZa22JXyUdV+UVyffObLzcwnAHw/7ukZ2+++V99Bxh+O12zBw5g7m1vCwF9PACBQM0Uclstm/v9xhtt6vPFqneN5GYmjmg0nLCr5n5aC+jDAQTuQhDQ6fh6WNXeqdCYk6JHMwfCgVEUGDUsuDpyxLpGvni3tZisda4HYIezb8rGBzUaViha2bIXf/EXFohQ+PE18g4exMhYoW5/vmQL3J6xwM3l1LEgmi5DVK/zFCdnB8L3dN1rt4FDh3Cy2IP5eXvL9LQDGwuPWJRJSf7w4SANMD6P4EZ98SkNSFIZ7/51++32f5oGCeoefjgOPuP69HqhyBzzQs/MhHcTAFD6YD86HXxuYRKf/WzIFsvSIQ8/bJu55poAfGlBnZsLDFld+1l+ghpVGrIOHw7Tkucue2Kvh1Frj4+927UrHE5l6dL2z8/bOC5m2CHnFUHcW+k+/WnbYVqpgaBudn6c60XVKzd89j3GX+jpRmscTzcKjFnmtemDsop77rHvn5mxr2iadb8mw/ZeP64LF2JPwDx3LqXURLg9utSv+/1NjXme27nWyjlMflpZtlllB6buBWEKaPPzwU00z60iYvt22Bg2R9NLZq8vNk4g5OdGtb2SJdWfqL2etaSYEU4uVvx0sW+cWj00OZ1qTGW8Io2AGlfU68VhuhqrSB7BbcvQErI8Kq8pTN54o+NLPOW5N+lr3+3C16Jptawy5bWvxf1HK56eSSJnzgQFEIUmdd9lpka6mTLEl4boRsO5RZtTnnd53t1oAPPzGE4fwL33yn1FgUFrrxckt2+34580p2LBU9vhHuCmcvRNQZhxd6mhhwoAzUlRlvDJghQvqMHQGCf0qcuVaPK9JUqRnhKEWi0V1LhDaoCa924mGCZQTHVKCiQVTOZ5cFvnzxB2z9TK9dA3NsbBCw/wc+s8H0ZZLSQjKUsMShvLV0UAkZXemv2eBK6aSMefGDNN+u50giuuj63m/Dgl5cpqxYdupSFk6nhw5kyIc1O8roLzli1xrjC9aFnT7NHeoqyWGtKcWpX5w40JBOUQaZNtqHVSiZMDazQwajT9Gisd8HXsv8/YOm5/AFGK3xEs+NOyCx4cFhK2MU7+cQTI84WX4t+LTRNJXL8zJnjxcyo57wrEeJwTwEZeALqAqSWt1fI1Gal8IS/lPldjAPukPFx1LDo1ahhWQx6/5716Nui4VWek+gjV1xZFUI6QJknbfE7PFyqydEoUhHNsGuupuq1mw4aTcD2AkGxQL/LOl7zkcgPDFwD4r5f07M03/+J3gOG30zV74IBNPtNq4eRiJdrcquEA4kMxz22BeG8eYMH5c+dCFU9KWlrXRrJqDPOmF44okBEzKnNuNOxrsixoZvTMvfVW4KUzp6wJzalUCRZ27LDtF4UrpVGuhfi2qSmLTno94OBBnzDEGGt1e2Cx6RMeMN9ILbPxQWRoviA5zT9MZajxIocO2cyUvTqOH7d9eeUrXbH6Xi/k/2esSbsdQJ5WLHZufd6SwDlWNdzRo7admZkolbha59ptoDr/kAVLTz4ZYjWBAGaA+P3KmcUHba2s48gR+9XsLLC/JQWeRRlwcrnqw0AB+7rDh+2wzp2zZRTWipoXeL32ur+Oganjrrvs8i4uBg9KAhEauPr9ADQJiNptpzC4ZRQK2eU51toHPJ01G1ZrfKJb913fts2VdnBmn1HbFgOnRphT0TTrHjmNWtb6qsmSqGRvlqfCvHa7tqPf/d1+3egqTJrm1jHGpe9XrYtzq2YJFNKmMS5mlUiOZggVnrPMC7BaNoCHJo2GFJQajQBKdZ6Zo4jg4sDMKNA86YWCjtPYerAo6vBBWQ2CdK8XTIoSZ+otfOUgqqOoQK9aDsIprIWkOAdqaSqttXR11XqlAhu13wRopBG1flHPwjCvLVuCUXXbNtv1F195MrjV05wzNWV5AbME80fdEbmgTtoY5tYddG4usIRWC3jN7QMb7O34xqAxacF6q4WT/SY6HatgWViw3tSR1dgsRXOBbtfGZh+vBM8BF59Yy0ZxWk5lykVhs1+q4EwpSceniEoRliggNM6TvzW2jDiG08TlZbKkVNhUKwXl9mo5CKVe2PDMjI85I85S8E4r7wgVrK7GbolMJqJgmNubOkHu48m2E7h5AJDQuNYkZGoqdf74Am46ToiaNfjiRx8N3jvGAIcOYb21z1sI6aVNRc/+6VGoP6WMgO90WZrIM5RfaFJSKjaY6FH3EhCxHz889XSgokKT2BA769ZlO1F5KlUCsJPaMJlxChaJGMj0c1vPkY+prpwAAggCP19DpZQCBrah4Jh8VWuF8h6yqDyXeoScOJ1A/dGG9cVq/dP72I6bD2Y6VkcETofia33Njh3O+8eMwo1ZtqG2prfiARuysFLxr7oTBYyMzS+KANa4vARdwEYLncaJ6/SpXoH8Q6dI9y63kwLPSm8No0bTv1fXZ5TX/VbjUUsZmmPi3qDoRB7H91MZ5j2O3EOzL3nJZQaG+wG855Kevfnm/893gOG30zU7O4tPfGLOgp7CaSN5GCnjBAKF93qhvkSn4wEVNxO9gnhAqtaRTW/ZYgWWRsMKISurFWuJMEMvXI6ymm+LWYtpPSKzqi484k+owaGX+HAtwAIPIHYPaJp1K2WRK8/OBiHM1Gx77TZOdOseeDQXHwgohNI7d32ng0Fj0svsvCjHEyT0+6HkRPPzfxqKOrbbGM0ciHI8eO3d4gk80N/nE3tOTVkXoZPLVb80lJ/JIO+5x76LGSVbLSt0TWxe80CceUDq/aUQGPXVr9oF4ZhMPQIpxsSa/Vq5DgA42bMxNZMNV3vs4YetYsDFRqHTiYVfWo1Ua8qBc+IoeVFYonW4PYm77w7yPoVDxs1s2xYEdGq95+bs62ZmgFe/Wsbc72Mw+1IsLloX5N27Lb2cPRtAZ90McLJbC3MlWv5hWfHuvFQezMyE/Dn0iCZNON2DBeTz88HHbXY2Vnv2+xh29vlDk+G3BGUsZn/6tItNEiC23q94g9y2bS6FPj/Q05GbJ9W2Az7ekAJStbDrPMrrXjPMw47VL+pm4F2tKCyqQKQhIzwwSQKKNWgl9HyIJ7mCTeclQG0v+8PEIsQ5xlhXWgphvjafo0XWB+Q0pAaFAzOjgJKlNMiwrKBaDrBytubLDwDBw5T7ZG4uaH6np4H9HedhcOyYBXSkcWZy4iCe9zy7F7dutSbDlZVQv4cEkeeWbg4dCvy538cDvb04d84Cpfl5V4Zl94lg+mL2oulpDFp7o48ZR6iZEz2Y0v3JS30bU3MGaYkbQNdP433cswQdSpoEVXw1P/flL7RPeoNrhEl3FMCQP1BAazSAWv9UdEgNTU3Lnfo4Kl/TzrlZDk0twh1A4vroCP7Ecs2Hu/I+eonUzDAoQsisuAA0k7TbGE3t80a+vW3nAUFQqFZDSpgkYtYGJWJj/aM8t0nLulXv9s+POx3nbq68WWUAts1wAiCY03lApwUutR3+Loo4XTBgLW5O0KaCj3uTF8EC97rqVKg4Zqgwwdzu3c66m1qQ3e9RVgsxoam5VJmCItmE3jYAMDeeseBNv3Md13GzTJhe5HM6lamFUJeBLKUsHYgD4vIYGiak4JO/HX0RxPErLrvqd+pmELuopuMcN/4U4BoTH+r6Qsd/GeuuGBkIc6DJq1IDL5dP9Vc+xEDXmQ3qmvMzXWelGyfkjRrNkKxIDxUnN7AEDPtVy0axKRUIbZYlZl/2sssMDKcBvOuSnr355stbc/FyXM9tYHjoEObe+944ABgIO4fWDboe0gWvrPrYO8o0ypD4M9kaBmDQ71s3oN6aPxhGphoKqPLSgBC6Qq6uWqGJG+7YsZCr/PBhnMz2e+0dff4Z1FsUzlLIUg9EUzxERYL/k3ut5cZbmZaXgzaewhzBIX36igInek0vwwLBW8dNFw5MuRgu+nXNzGDl6T2RW06lsALnk08Gl8uZGSu8rDy9xyf75Dxrghh6q9K6uboaXB8ojx2YCfEUa2j6Ydx00IJNlfX0YoK+Tgc+Lf1D8zarIOv7TTbswbqe7fHAxRjnylnaQt3sa5ZZQX29sK5STMjBRArMhaKGhiocwx0nFHGRGftKYZSC1e0vx2/+pv33la8EJsuTIYuKSwM67OxDv2/dSZkhjhlMK721gNC4T/Ic62Ut0pjTyrRrFzCx0x44Jxcr3lBAMLRjB/DGf3DKfkiFA/cIrbQaQJjnPgnKOuq2FmaWWddPlz6+KGyM7hBVP8c0jigtcEvxDCzLUPudMsLBgyGN+8l+01v7mo0gMI6yGip92x/K/XTV9pIDNQqp1psES6nOmd7vn6/77c+6njt2uLksSy8YVMtBWH8Ao9YeL6PqOChTcHo3bbJ0xr1T7Z0K1kXOOSVk5+XAOJWo3+SDTnAiWdCayDId///23j88qurOH38xXIfLMAzDMIYhDHEMIQSMMZJoUzel1AXR1qLbdi1uu8pX2+62T5/a7X7a6q5ttbWl7na72uqu61etuP2BrV1/rLJIrUuVtYBA87GAEQJkQwgJhGEI0zAM15nPH+e+znnfAbSiBSvn9Tw8QDJz77nnnvM+79f7J1MHGZXNS+zcqUJSW1uBWc0lo7w7jmEQlC8UKnyIeNy0z6EBLRrDxo3B+gbVqZJZXz4TGhhTi1de0bVwVAsEKUBooEinkY3WaMMeO1nQi3LggCH5rKgaRhElx4TAUQbwvchwRLYK4d7RChKVL9+IUXRjei3z/dEbIBugU/ENWOekcse9lcnoXF2+dhkxyzXnOOr86OsP6bVd6YBh1WCCP+fno1F/v8jF4edcbOkKBQr8NDerj8miMgw+GT/eL1QUV2fDpk1qP0+aZN43deqA19x1MXAwEmj7FurvMwowPZd8wQ0NGHJUWsbgoAl84d6Px41njHPBFFsSMiAYUsi5IGRInyQ5JOmZjC9rZaGRSrLFyZZs0L/IsBeWdhI9LgbwyFzxZBKqarUkgpwoSWb48uVF+RmuLclA5OHpONojLodOTyQJOUUlo1HYf5LfqwzDlIRQ7x3JOCpkrvTe6ffvsygWnwnsI64LvhwJ4friWSPlP/cmEEzp0Nf2PF3cyPNMmDTHXElEQwVRUVc6LPic/H9lZBoQdNvxuaQxyVPtWAjeguRcflV+RkLaYYBgRWQZSiuDVnQYvCSdnFsmyLvuKSCGUwEsPqHvtrT8gyWG7yS0zpyJdX5I0jCMFZR7T4ZUyRYu5EjUayOOUoSZDE3Pi5S7g4OqZgVDF4BANILe0zt3ms8wr4Z7nLKa7TV6e5Xwf/e7RWEQad13TLU9CtRVq1TqjyjUia1bjRMvmfTbGch4VccxuXkMypcD4sWkJKHpmaw5mQSamzFwJIEzzjC90fJ55Rw4fNgQO8qHBLIYchL6FtXxYRUu2tyM7f0RrSTURNXnYoPbtWI7lA/pyF5ZOJYEiecvC03EnGH05SLYuVMVl6SDj3/LomnJpFJkAGB281Awl07OD2AOLCq5viWOISac3yLCpkiI/znmn8HzgglY1L4rrdDUzHmgMX61uRk/Xq4Un8ZG9f4T3h7TEyCdxnC6Hr/9rV/I40x1SFO5TyZFNVmGBvIPrfv0LtFNwTEVCsDeveg7/wNa8YpGgUvqtquCN6NH656bekGSHXueaYzHlimplAlLZfwnNws1Msnm+eL5WRIAKjiNjca9nU5j+6Ahe/XJbPAQ4z1hvGcBs340iqwX0x/THidqzTLEmol/I0cq6wKFTDqNLBJ6O+3dazw2gK88dnYGm/N5nvogq9CyfwmVHClg+EcW26G1m9YSvlOyaBohyGg4pzLc2tf0sukmbN1qlNBo1I9U8N1gxWgCv/mNajnBqF9yzVGj1PdYKdnnM6iP7wl63OJxDBXCuoWQLLAajQI1vS+ocTc3oxhNYN06Nc3vmtJnQlAZtphMYnOuWldcHDNGdTthX85i4yydW5bPqzGSoHH6pW7N183hci1Q4eIWloVgAeMMjbm+DJBFqLi/5GHhqqIgJFAkobKIDhWycD5r3qGMgPHfcyka0441jjGTUecJe/lJ+4YMDaNCD5giI1zuUqfNZHxFnoYA/7m2F6r5GnQxNMfxoxR8A1cpU6tkpedpAsStLs9Q1xXFviRhpvLszxk9shEMm7AHhgQQdM3RkEoZwMMpldKVb6mzM4I9XBgKHjhy0jiJviIxHK1Cb68RB9zOXDeuG6xqyVcnt2EmI0L8ZKEgIPiy/KT1bM7kxUpjsiaAUnZLmSHPG7nQJfuTZJFrjSyQv+P3yIp5bghyxLWkjaKV9xZ7gwYPx0GAWGpjgePowke8vcyD5HLkJXmUs6hO4DuUh3wR/uLlHmBRaxp92UuRIcZ8RY4TzLFzHOPxpQiWhhm+ez0ODorrqBAK7FOCa4XTxnmVX+f9Qvmh4Be5BvhvqdPIM1S8U12ZGEYW6LXJNeDPm5wzGmIosy655GTnGNYC+PoJfbel5Q5LDN9JOOecVjzwwDqd5zdyJHSLBupGBw+aFnqUc7LkMq0s3NDykJIWLioKvCb7vcnYbHqZhgphvY+onNdmlBVXRiNFo0rBH46a/C6SmGRSfbc+7Xvr6urw3Oqw1rPb2xXXW7PG5Lxd3NCnyERjo3mI3l4UG5rw5JNBPZStO2rTRejqG0yWkabjdBoDE2bq0BiGG1LfjmHIxB7SQ+qTu6IXUi0ReELSE0YXIUlWw0yEBvfgpf4qHTHGYiOZjFLwi9GE1oU7O5Wl2nWNQsVql4AyIk+YYEIzqTPI9JwrrwRiXRuUVy5VjY4OM2W0ynZ1+QrRYI8p78oPcKBS4MqTX5JvXyEnkU6llIDf0hXSX2V+Iq3tgHoVbW1A6JkVQCaDNfvrsXKlIobnnuuHkkWjRosD0OPUBhTb3bv9Eu+ZkpmAfN6QSppIp01T/+/oMIo3Nw2LkrzrXcBll+GhH6qWJLPbisDy5WouSND4vFxDZOdUKjo7lTbDahG8DxOJpkwx64Qk2vOg4wwB9e/ublP9RFYg4OLOZFBqbNJKirY8+5u+6ChFQ5KCUH+f0fBoHaLplGZl33OS9WLKq9Lfr+J5AeOSkAoatWzZ7Z5ePWoybIMjySeFFGNKo1FTBo4bkcKHlitubpkoBpiFNWECdClQQP07lTLPWlkfv7kZaGzE9u6Q3u81SZ8s+9r59sGYlnFSLsiqoKtWGWt0MmnC5C64AKjFduWdRo0KNXzsMeDSS3X1ye5uv31G72YMZ2bivvuMAkJCenG7vw75/Pm8IexSodm505jBqcVz7fD9Sm+K/A7XNuPkmBQUj6u5840CRceE+cacinwrCh/pYYzHdZhcZbgWXyXB5cS5DHVvD+bGAnqSh+PVAeeV1PUZrMLlx2gHLpVQYdj0uPFlNPNFJV+Kx4FI/3bzLLLakpxTHqCS9PC9+IcoCSx5J9eR5GajRqm0Ak04U9XamOB5IiqA+4gTKAkQGZkkThxHpVem0lsjlWheh7KXyoeo6soQdeks4m0lmZFtIeVyYQQteyzX1flRDTxjUykMIRbIbqDXS0bmVBLRQ4fUPWj8lmsLMLlwNHBXRlCnUsI7eqx3Ki8oFSlpJJGQE1JptJR7WlpuuM5IHKOxYDg0ybQkun4UheTLOt9QKntSBgCB98g9wuVM0cKvkFhKscNlw5QBzu/48eb3Eado1qo/Vka2HEXw5UX5f//zgCHNjAiR7455x9oYROLOeT3WQozHdXQcI6VcV91nKB9CLFoKOFVGjwYuvvhkE8MMgK+d0HdbWu62xPCdhPPOa8WLL65DuPMlTUyGnVhg00oLCxdzwPLl7+ChfEhZewHA85AtRAIb23WVG31gfxivvmoS8ocRUZZLX7iU4gkdvvfSxhDSabPf6CypzRhrGpsHsziALq5Chdr3AgxnZmqS29FhQqoS7rAJu/KT84peSFcffKJDVfFjk+lCQSkCAwNGB2aejjw75ZlIJa+uzngJ6DGsMDjhN7/xLfa0Xgnl9LmNCXR0GCsp701FMZMxDqhq9KkPvPyyIasTJgDnn48+VOs2gq2t0KRuFjao/wwOqotRQRk1ShEfmTS5f79SHBsbkc2FkIiXsKEjpPM8XVc9L8N5yHGYV9rXH0J1Sv3NqQ95RU2+skjo+Y70bw8q7zxZ6EXkBznRIoZtOKp6/EXWPadCeefMwUvuhapXHLKmCbz0bNIb2dGhrpGu1862mnTJ9MnbvVvNKz3C1CLq6pDNhXQ0di6nFJPQurXqfo2N+NJ99ejtBW64AXjXtKyxatBy4ThBl5I0bfrKYE9/WK8x6gTVKZFHIhU3+bNkEsNOTBv/AXHI9/er/UCiyeoeXGA7d6q1QI+ObKWQTJr8Y7+oUdaLaSWVChhlSXe30Y3a2tRXdMVfEX84sDeklzBDZGUkAQ0RjChiqw7Anw9+ieEGDBuVMaAkilxPUpGVpm6/Mi1FC/UK6kSZjN90nvGUrF7h75Xhhlno7jY/0q0FxLtBLmcKWvH9NTdr2YqNG9XfjY3Y0h9Dfz8w23lBfaetDWhowJaukCou4seZrtlZjYEBRRJ10aRo9OgQe2pk6bQmWuHcHqP8S42cWjENEXIh8nkyGZSSag/qXC75h4uCgoJ/cy/xmbk3pXYpDRnxuFHs/JD3oUJYR5ZQlDEkVb4/vvKYM2zCK/hD36Mz7IW1zJT6d2Ukn0yprK8rmX4f/LBfLIi6PB3ODM2lbZAkz3/NqM2YXHxpS3Nd3yMqz2OxqVn8iUc2X3s8XmHsAgKhdfqc5zvwwUI8VNBZ0XHs2MDH9B4n5BzRo8LzD/A9dpxgaRiikYLMWyYg0vjD9+QLgVI0ppdGZ6cpXEYROm6cMgzqfqNU5iV8wy7D5WXghOuqW2t9wzG6jJwy3e7E9wTysSTv9jxT7XnCBD83XD4796OcQHle+QKQVWylyGKRnpIbCebnSkt85Zdo0Ob9JSmVc+MzdOZ8S++b5JL8uPyb0F5RPyqoiHDg34xUoN2gsmooECzoIx+Ha4xFdhidIMfFYC7AcGspwjjVgBHjkpiyzhO9zpWeTRmJKyuwS4cKHSy60Jc/Ua2zZ59kYngWgL87oe+2tPz/lhi+k9A6YwbW3X13MOSMLMhxUHQieoNIKwp1KSq9NG7m8yqU5YwzfOWj0h3I61eWRJTaqS/YAUUUmF9VdGOqkMroIQwcUr8fPTpYgDDSvdkkv/f3q55kU6ZguHU2Dh7085V48LNbua/8Z+O1AHyLb+dmHVZXmxo2PfQAE/fJCg/nngs0N+sCHQcOGKsyoG5DL2xXl/JgltyI5l+8LIuXuK5qv5HJqNt2duq0RNQmFVncPhjTEY2Ab/Gn8rt8uZF+3d2qxQhLE7LqYSqFbOslOHLEL2SSHjKxodKcx9hWwAgteiszGfRF65FKqa9u3Khet8xZ49cyGaOX85DN59V3eO6MGqU8eQcOmJQvWuKPHFHTzOXCvxPRYqDqGQ8mLjPtcXBdDOwPq0IEnZuRTc3EunWiIJDjk/BCwayPdBrDmZmI5Pp0o8Unnono4oFSwQwP+iF6ngcsXIjN3RHMzKjiNVwy//M/ioTPbjP9Op/rrMIPf6imeOFCU3OHkUVUFsP5LOC6GPIigfdO3TifN3V/Jk5UrzsaVf+eOL5ovLOepw0/BL3BDKVh4SHAN5pIV/CqVWrN79pl1odf0CTbcJEu9gOYfcmDcPduNW/Mr6F1lNEKfA5WQZUeAoYwTpqkrsFKoORRPKj5PugxBtRWLRTUHqKtg54yz1OfZfN4joNbwHWhlWDJQQKFugCz4H0XebbuwoDxPOYMq0iEnTtNyb1MBrj8cvTlInqu+vtNJWWKSMdR66auzqyJ1as1x1Ae8Tu+q67X3o5ivEqRa5/1ZKOq72lDAxB68gn1ZcdRcsHP0e7zqnRY3e9+ZwIYKI9oIAz0DBMvt+iF1BqVsp6D5QV84j2UN3mZ5EqDg6aFCOtVjRtneCL7I2rjZH7ItAcZHDRmdplzQM2soSHwQhmKyT1EyJ95niAqg4OGsFCTZJIhmZwksQCy+bC2HfF8bG31ZUXnS0ZB9wl4MV6FcD6LgSMJHXr36qt+6gAvQCug4yj57cW0opvPi8qn3Hy8PjV1ChfXxcCRBF591QRxpFJq340fb/JFeQl+jWsx4oiecRyAXA88O+QZT1QalOm69iMJSOzlx3jfQA5lJfNgnuzOnUoIAsFmclzczc3A2WdjKD0TK1caUc9XyFY7fJ1hFI2SI3Mv+K5JSDnPPNBlyFTl/MhnEFFFw4joW7HPMh+RxEOGOgNHhxFLhxhDwzl/cj55Wz5vLFrhKZRuWWn1ogWOG1EKOX6H4P6T3jO5L+X/eT1+1n8QGVbL1BhZ0ZNzwEvRhlAZ6i49fhLSIZvJwORiVo6NF6p8r+JCjHIjieU5B5iWbgBM1A1g1hSfnfGzAFovueQkE8MaAH97Qt9tafl3SwzfSWhtbcVPf7pOOyko1+mNoqIgOR33firl50EwZAY4Ou5aenRY492v6sFQNFqImKgdzu1R15ImNbINqWg4jiqTPNgXtGT7zceRz6uDgA/W24uBcfUA/FYEHR3KEpxSVSATUT8RursbpYaZePFFpQPQiUO5TlnHdLb61JAJH6QQkXkDnFR/8w/sD+uQzXfN8KukvvyyYUD/+7/qO3PmmEM2Hlca6vr1RgFlflNHhynbynKkf/InwGWXYThVq62T8bjv7WIllM5OEzLrx8wMHEnoXICIWzIKHw+FeBxbukLa6tzQAN2TkYdrBMPmHv54tudUuWcSZ8Bwzur4sB7LfzwZ1kK6qbGkk+PpmaUzhfeSB+m+fcFzFxDED4pYvdSlqozWpJSnmQUi29pMngqNISGUggqW/9DLVid05CCjnjjHnE6G0dIu0tCg1vWWXJWu5tmEl4B8Hs8WVFP4jg71Ob8bBdLpYBcRrjnyMhr6mbvLsBrmjNLRRCWjrs6kR0o7jeT9hYJqf8nn6upSa58WbTpXHcfkh1C5ika1PQmjRqkxMAR9/371b+YLsqqtvkE8jmL7xXpfSL4lm3dzW8t9yFdT6bTiocyzV0a4nnmmcXjK6/Jn1FukoZxLQYZ0SgcjP3/J3JIiX1yIrmv6gUom1NtrqknRKsTFzWQz30qwYbBGdyKoqwOaUnsUSac2NHeuZlSs5jw4CCxdqvjfvHlAon+zbk0x5EVUCHs0qi3q27aZtZBKQRlE+BJoBiejJwGT4d7Usijv+OxkgfL5pRebk+tPZjGa0EtDKrPS2cH1Ickdu/0AJioxPNhnqnNKDZoe42QSw25CW+9lT8NCwYQiRrwhM9c8h6THmRqrlPs+YShFVUgvjWAk9Mmk7y1+8kk16LY2Zfzxc8p1kTZ5LT+0LREtmjxkf0ylunqd1yTzvLj+qc/HoiXT2skXqgwplZ5F2feUlZ8pX/ja6WSnh5aEkn+4JwCzHeTPSU5iXtYYX6WSwXUiX4pUyLnGRMyn7iXoFc0N+c5oPJWbubERaG7G5q4wVq8O2oClE41LWRq7OEQZ9c7nlXxHkmypR7DLFwmaLNIiidGxQF4ZWCeVH/YjQyK5vgARHfIiePllteelIZXj5fnqeSanmBFAod6e4APzy2Sb8h1yIjmBnCyOhVYHCuvKqARpqamcYPmS5OfkguN1ueC45kl6pdu/kvBVGjs4Bh68fF5CLmxeV45PEkBev5Jc00rhnoriM2kAN5zQd1taHrbE8J2E2tpWLF68TikO0YrKVVzAMuadZm1p+eHpww3koxhN6OKhPHAdR52hsmKV4ygByXSkbdsMD5Ryn9bKIsKqX5u8P5M3OMZ4HAOjanR4SwTKSxfa+JLp2ySbt8v4h/Z2bO+PBIxDMccnL7t3K9eV3xR41y6jLMvHz2RUqGigRHRB5WV1dgJNDb5CwM1ERsBkI8aL0mWWzysN733vg65cwcM9lVIE2Le6bkG99s7R2M2KjL29KnxGK69s/H7okHqHLK5D86m0QMv4fccBGhow7KmKmImcX0jl//5fI3DJTjKZYEgiBSigFGPef+xYEwpK7UMK5rq6gEJbQkiXj9fClYeBfxoPp2q1LnBRW4VC5Htt1uyowrZtioezIEPRiagCCoWC7jEYjwOJjmcBx8Fw62z89rfAww8bAjd9ujJWU0dMpdRr1ZZ8GaKWTmNgTC0mjtgDLF+O0sevwerVaokx0pHTkM+b1gz0dFH3TKWAixqyJlbOX4wD71qAV14x75/borXVkGuejZziceMU0aMCG40qvsFcXfYc5ZJg9ULmCre2mldOpTHiDZmbAMYw5DjB2K583hTGoRssnzdFZoRyrP/2PN1nUq8r3jyZVMYWsmW6YX2ylU3N1LKIRV48T81zZYi4rA/BAioyFExyHxm9wDlpbwdqo3uOXvt89t/+Vgk9Mu1cDjjnHLUXATUHnBs+2+TJqrSpv0+HPRVSLMnU6tXARz4CJLrW6j1UTNdi/371jCweO326X3yjd7PpocqSyIzPpSLnzy/vR+OR5EZS1+E6ozdKKtpcEmFH9EqUnhQa+ChUpfeCSpnPzhneODBgSDr3DcfEvRMuDJmJ2rvX9JH1XUXFZLU2jJFoc67oeOPrkyTgqEbtVPb8sRbdmP71zp3qI3RyptNArdMDHWM8frzyIiVr0NVliJaMKKRo5f3JEeNx36hVGYYIkzNFW248DlRHh4INhDl2oqJEtKx8LHPzJKGQZInbj2KaREPaR5gKwRRieebLFA2GFgo7q5r7XDaY/82J4HnFwUkXKw0GtCpxb44Zoz575pkmJ7qhAX39oYD3PMB0ZfldLm4KBXnecMByTuNxbO824bkcrgxV5c+47EkgmeJzLMNGuL9HyZZcTj0LX0zlXvJZadFT1XJZa4AG38rlzMiLdNqvH1DIGo+hJEGV3oRK4koSyfckCRvfI6/B30v9g9eo1N8qySSVOC4a6f6W4Hj4sFwvleXapUGIz1NJJgl57jFGXJJG+TnXVWlUvpHl5PcxnAzgMyf03ZaWRy0xfCehddo0rLv9dkUs5KJmPI88qCmphdWj5ChiQHLEw1j2wsrnDdfQXqjcnoC1OZsPa1nO6pgEFS3uxeqoapI9sD+sEukBo4E0NOCF1aqaZDqtwva2dIf1kGvTivz29IdVEYjly9XgScySSRTjVeqwGdxjnj+nqvMtX24Ery7r7zgY2BsKNDuuVH6oJAFAbf8Lhpy6rom9bWzEhv5qrZi3t5tCNS+/bJRyhsLR8Ll6tVFOWaySfQ+pQ5PjSeslBTz70FEJJqjoSTnoOH7xDP+w07kLLH9O1kFzo+epcF4mGbpusHMwa+HTs/v880o7kG4ZEglqHVwUgLKGuj7h4+dkfG40CrS1YSharR2YWnnKD+lcrWzjbDz2mCm/P2GC7ynAsDn0Mxk8tyqE5mZldd/erQ5ltgpgVBkAJAp96mRtbdUtDrb3hrF3rwhddRwMHIxg4uEe4DvfMUYBPyRQExkqMuw9wZ52HNdZZ6mDn0qo45gKujTq0GvFfb1unbEYTJqktDWGBmQyGKqbhY4OxfVZhKFQUGuGyiBf85VXArFcj9nogDn4SIjpXpfm6UwGxUy9rgfjujB9odatO7a5nWU4uXfOOiuYYMLPMX4ZMAqRjCJg2DTnluuVJZHJBkkouR4ZJ+srd1S0Ab9wRz6PNS/HsGaNMS7v36+mNp1WbXB8u5Ky9ntFDHth/exs6xLOZ/V7072t1q3TC42tSrRBIJPBCxtjGDlSyYneXuBTl/cBjzwCTJ2qnqmhAQMTZuLAAT/3jTIzHjfEE0A2WoM77oCOmGAYqx90oR9//341xTNmmCUGmBBQRtYxpFm/Y5IWWcnZF9CleCJQRIaFHUpOWCn/nA/mIlNhpPGAJUo5SK6hZDLQu5E1wpJJ0RKFxkUKCP6hHBNGR22UotLPCZAsiVYCqbRSBvr5kBwPI2J5fowbZ1r4nHmmf27565v9SqXDhCF048erW1Sn1BzqHDfOh1C8i64qeiQ5ISMF+H+KXRmix3NdkyMOwr9HoNo07yujf6Tnh3PjvyP28+PSlFPLcfHZ2Zw9GjXFYkRxz0BYeDzuF3njWP37F6EMHGHH3w9MeuaBR3Ymjc6uqw6I0aPNmiHbzeXUv+NxE59PsF8GlSKOhfdgzHSlJ0oSFuBoAiaJiDSk8IX6sjebC+lcUP3+GO8sQzQKBbOYGIbtz8lQvAYrV5oaDYDa20yXEY7bQO6fnAIeM9RNQnl1FlL28XEOHqzIt+RClw4LucaEUyJwIT4X/88b8+fCksUUJhmRzlvIgkIy6IFrjss40PbDdQO1N3RUnFMKFPHxPBOlznc0e/bJLj5TDeBTJ/TdlpYnLTF8J6F11iyse/JJIBpFX15V5zp0SB1GMlqI4fq6+bdPiAL5JNL1T9LAMAfAbEaaSGX4gP+dgEVPCivZGL2uTm22we3m1HIcDIys1onK1Y4iddsL1VpBY4heZ6fK54p0vKDya/pDqE6qvAqG/1UnVfWoWK4HxVSNzp+TUVX0hk6bZnpNS0sew3lonU0mgcQzP4WMw9yeugirVpn6BLLhMGBCTDjF48apKqodHWbqGhuNgT2VUpyCfIuE5eBBvxqd5+l8oq4uU1mVRlPZe42vcvdu0zeL7UNIGjMZoLrzWe3RGyhXYeVKY7mUHqpqNxuwYGfzYa0XylLskbwKJS7GVcGK/n6fjHZ0GA8nWRhjD6Wbgko+f79zJzBlCgYmNmHTJjVm9uRyHH+trFwJtLdjzc5qnbtGyChonuMTD/vW/eXL1S8uvRQvDNYjl1OtQEIdG0yVURIS3w24oUMdCBc1qJysl3I1OrfsXRf4nlx+j4pKPB6oYMS+i3QSdncHC2I2NKg1GcpljWdOWj6bm9GXU8WhYl4WiEaRzYdV1EBXl/pDCw8X4MaNxiIxZowaF+MPeUPKA5548bg28iSTStHXfRedYe3BHco06W2uyWEyiWEoz31ocE8w1p2LtFAwViPHMZVJqTRQRvlyohRPIJQfMr0AZZUPajqyUA3JKKtnTppkyAxPciqG06ahmKnXLTyySGjHxOCgaomzbRv0XGQyplKifm5JrguqmAWgqvoWUzWKKOXziiTu3Qtcdhme7VA9SVtbzddren3j09y5em9s6Iqp3xW2GOHgr4c1L4Zw553GkZJMqusVCuoyO3ca24MM5eX+AIy8oK2BupgQ0Rg3LtjGgx5m5uBEClnzPqTiJ8MxfI+7zOmhnlwomKKnJA260iZlhedpS2U2H9Zkg2KEerkOkXRNBUJ5L861VgSBgJdjqBA2Oc480/glxj37WvRwIaR5JOetqaFoCHQuZ+Kx6Xk+dMjkjkejGI6rytDSUcj3RI6g85vo8uY6b2hAEWF9K+mYoUiVjweY7cJju9Jhw/kkZNQg9XHuBYakarIpPUzygmSM8sJ8UNfFwN6QzvGXzk+qE3SAjxnjN75nxUr58uULpl4jFwkPAv7OdbUHndCRTezTB1WZUxPQaFSvXxLtiDdkLMi0vNGCIb2d0jtHGSRdqCRA0ispDRTSCyd1Nu4NWRFMvgfmFflnPVIpFNO1WL3alF2Q00KeyyFTp5FOXA4hGjXnl/yctCEQeg757v0Ps+2GXLvSaanXllzA8Xggd5HrRU6PXG58Dp1n7Tjoy0UC600GO/E5KQdlwIiUl7KPM7fkggUnmxhOAvD/ndB3W1pWWGL4TkJDQytuvXUdpk0zRnHAGLcoD+Nx/4CF6XsjPf+AcUZQD6bh3nVN7j51ESoIOqFc9kGgpJAmQxmWI2/qm6h6ekPaMNlUp4p+UB/OZFSfP818/AIRa8Zdgv/5H/Wd9nbd6xw1aVUtLYGsMZNzF993n0lCYEhXc7MymzNkyD8AdOJ0we/z98wzapKam7G5UIvHHlM5QFu3KqE0darqxzh3rtL7SNxEoUvk88rr8MorRghTubq4dUjdg52SmbNE5aKuTpdWHW6Yha4u9eONG03Bw95eJeSnTFH3Pe889XPqVL/7nWkXF48DM+uKyObDgfOawpTnSH+/KXjIxvaDg6oi3pauUOAQiXhDunw4YJooS2e2zgXlGojHj6pgJg3RtckhY+Jsa0PWqVIew1wWpbhq4TFmDDBx4CV1wNTNVOvScdA3qJSlI0fUK451rjUPyVK0K1eaUN/zzzcVHbhW6a7lgTtmDPC+92FLrypkk/D2oM+r0u+CPdSPoX8EQrLIf5saS0bR9MnfwMhqrF9/tPeeBT5IdIFgP/qDB003hilTfDIvvFKaFYhqqawYSuOK1E14Dlc2+2W5d/bz1FU2fYV9yIsgVthjLiItw4D5TLSkNgofQCpvMjxRKgSSIPuhYgP7w0FLOmA8nXT57d2rJnPUKMXw6L1kOARJpJzc9nbVSsZXJAYOxbB+PY7pqZkwwehdMl2lrk7tz1jnWi1Yt0Rn4ZFHdJAE5swx73KW85ISIO3tyhKfqtXpxOH+HiCdxopnQtrBzsjRj39cvZv2diD02H+Yxdjerv64rvqgNG3PmIE+tzagO776qsnJZjFd5pYODir5cuCAGiujq3lJhjRnMmorOY6ZUor/ujqotSGVaCq/1DYFo2GPQjpzDh/2c60pGwHDeOJxlJJVekyM5qVBCAiG69FhNG6cycPShq6CqVLpOMqYWnLCysjBvcqX7HnG0MF1y41CQ5gcJ73v0ntO12Njo87t7hsMB3gG55A8OxoVaRJyf0mtln9LgiHIRymuckJDvT1GVgDG9SHCdPXZLa4/7CaO8hLKCpTSBiOdWVLxDxB5SRqkV803ItFTw4gbigHOSYBAyHPGcXS1Uwn5GuNxUzCP/Jt2o7FjRZVSWvQoh/hl/4FoiJDyn0WB5NBopK2suFlJjjQxkhZPMnQpG7mAuWB27FBCidYrwIS2M3k9HlcCymf3LMLHqHjuGxbCIcflFuVQOA2iMKcGl5+s8aRzSOUf+XzJpHJOMEJBXtQ3QgN+MSVONj/Hm0qLgiTQHCTnkPtVpjoIgxLXggxDJ/r7TcAOj9cxY4APfOBkE8OJAD52Qt9taXnOEsN3EpqbW/Hss+qFVjr+qBwD0M2UAaO4yAT0EEro6Q2pPlr8JTeNJHNS8FBCFAooukrgRlxjUeO92SRUe/Mq2lyU3IhOR2GhGMDP65EhPPm8UnYOHsRzUz6Gxx5TZ+iVVxoZ3dBgFLbauGoa77pA+LGfmguTQbMrL6AuxBOKk0gTGJMo3v1uFNsvxtKlqtVYb68igVdc4TdV3/SsHp9OKOOBGo8rgfzyy0pRoBtCZonzQGSzdBlqFY8bCQ3o/InNnirG47d5RL3bY4rhHD6syA67Xp9/vmnj4Lqq+IXjAM3NuppeDMLqWSgAjY3aeyobuNJ7m0wa8sJlEnGEN9rXqobdhO59SaIJGHnMDglsWRKPK0Usm1cktL7Oz2Pq6NAet7BT0m1KhuuaUCj4Te87O40Xiu+cyo1/44GDEZ1O2d2tUuIuSm5R3r72dmwu1AacV0eOqHA1VtjFxo0otV2kaxbVDq5FoAb8+eebzea6JheG65i9DM88Uynt/mSU4glTnILJSdLSTNeMPARliA3D8vzDcGBcPQYGTNgoh8StnEr5Hkd5mvOQZsEMJxy4Fc9Z2Z+e+hFb04T6+442Gft7eShaHdDZpGLOn8e8rJZBRVeFB4V7t5tno9eT9cb5ML77ouRG9Foln3cc34sDk2fF95tK+dUm+aBdXcrNtm2bGhAT+Wgxa20FGhvRl4/h+edVai65Njk4vf6ep2wPBKejsVFdhqnJg4PA7PhLao1feqlWToYLIeWN6O/HUKoe3/mOutfUqep68+YBs/7rm6qwFV+IH5kB11U5zdJrIWRzwL1EOUv5uHq1KaLD4joMs2N/ST8UIRtVxXX27VPP8tvfqn9TNjCUUTpoZ8ww+qpsWXnggBrKhAnq8rq9jPQM+Roawzm5dIFg6wdNevy8n4BG5yt+VM4PHzY8lWJZVzblvEFVLAXMmHWLDFr+yDgdR/dS5DHW329ymskfUynfuMIPMK+MTIoyxD9PmDPN85zPzXVM8RCG8C6SQFRq8jQ6AkdVaNVFvBj2K91jPK84PsoenqHCmyW9tTzOpBeH+giHQSOA9PLwyEqnK7yF/i9YEVQSKz5uNKrWGw1bslUBQ1ip8HMMkti6rsmhBExnH8BsqXBB5KdSqFR6zOPxgOFNzgHDaoHgEiWkx04aOAhpT+E2ZiEj7aGTeZT8Qj6v1u6OHcGL8p1KmSGVS5HiQIJW6amTedt0LHDsnPtJk4KGU9pMqHox0o0tf+W7lGeS55k6aK6rZAfvwc9ya0ajSrQzJJb7kdOic5lRDFQRlnoQn7dySmSV9dYLLzzJxLAKwFUn9N2WltWWGL6T0NrUhHU//GHQuhaPoxRP6AgqbemSSoNMNpGmHxm/IRtIVxzK2UJEbzqpl1Fnq68r6epi3ECxgspL3NwV1huKG5YhjvSkhH/4gNmpTBzzPGzPJXDXXUpezZ+v9O8wDIHgEGs6nkDx0gV62Gxztnw58ItfqIPlAx/wvUiszMrB+pZnLUmSSQy5qhplV5fiU+3twDUL/QI0K1cqRZ/9Kfj3zp3qBsmkKdLC+aVySbP24KBSvvya6AyZg+tiw8Ywtm5Vl9X5bc8/rx6CY9y719TILxRMkh0l6cCAMfU7jjpdp01TjEjmUYgQvp7+MOJxNTX0hkjnDfkq7Qi9veZAbWjw1xwhCY6ncpH27vUPeD8nie+KwpUks28wrMNsa1N+SKrf/83z1NKI9W856vAqRk1/JjoIK61+JDirVqnf8dVxWzDnnIdcc7PfNiA/pN57NIpi+8VYty5ocEzke4KKlJ+TRN724otGV6ceSS8/i1Aw7YU6VzKp2k8wn5TOBhn2QiSTfk+t0SIvhxuMCihDwjMZ9PSaMB7JGaRzn5Fw3d1qubF1Bb1L7J7A11BZHZBihNyW3h/qmLT4M1JP8lOpnLFSKnNJWaJfu6eEZbjPqwqENrEgAyul0gvFFg+uq94xFYu6OiDW7Re84sIpFEzTd2lwoNFFejkBbPdqsHevqjdF0TJ3rt/bMxpFn1cFzwNqup8D7rlHxcm3tQGOgywSSMSV0e6xx5Td6fLLgQXx50xYwq9/rRIf58wxWhV7wwCmryVjP5NJE9YqvXact3xekUn2TKk0UtHAkcsh0PSUz5xKqbmYM8d4wVxX5zsNFcJ4+WUVNUFlLpUy71emfvGyjY3qD4tEjR7tp0NwUXEzO44y3jCSRXrHqL35Fy5FY9prwZBfSU64lKisplK+7GUoSzqNYjSBsKP6E04cr86hRFzJMxok6DiknQ4wXkvei+FnQNBQBoiiOKwUzbMZ0HnHstebVIYpzisdMyS18riX/JEkk/KMtcU4H7K9kPZkSeItPZaV3iAKFekyJFvkJMg15ZPVnt6QdmhSHtL2qkPVpcCXzJITwRBcGcEg14+omyD3cIC9cIL8c6bkhHXLIDpZWYuBjy0JkXBgBsgFSRBgjKO0p0lnlxy6XOIkTLmcIZpsC8T3SN6vQ9p9w1/AUyvPBw5Wut85lxwg55mD4ibiQqM7tK4OWbdaR/1TlOzebeaOc3TkSLCKLmUB8x65bGREjXSKSkMUA0BIlLnXKP87O9V5xntLgk1vLm2OVJ34uZh7jNxmf15br7rqJBPDMwF86IS+29Ky3hLDtxrXXXcdnnzySVRVVWGjXxThK1/5Ch5//HGEQiFUVVXhwQcfRHV1NcrlMm644QYsW7YMkUgEDz74IGbNmgUAWLJkCW677TYAwM0334xrr732de89a1YrVq5cZ+KmARNjwQNZKoVUUuvqtVCnJWTieBUmSO8CwyZo5ZKyWodUCMHJMI2wU9LNwXURBhmHms+jGE3A8wxho14S9oYV2Zo7F1sGE5pwhgf7gGQSW7rDOvUmsmqFCr38xCdUqe/8kHru558H/vzPdY4hPA/PdtfiZz9TRnUq+zwEWSAwlVIWayZhU+DyvMnnlRF94UKgfvAF6B4FlDCXXqoYIzX1zk6j7Tc06LLqjgMTQgcYRiE8K0Unout3sHXArl1GsEejQOiRnypGE4+rgZ9/vlLyvepA2BGFJeAf6nlFFmTISG1Gkbi+/pDWnShYE1D9ufbtCzoX2D4hHjeKNqNfGTK0b58hAjzMo1H/+f08tKF8SK8F6ZxmFFaNu0cPviefUOuhd7uyaiertbJAbxV1CV6T5zh1Dt4nBtVPk0VqtvSqHoPpNNAU71GkL5rA4CBQDdVSpRhN6B57E1/t0x5LNDSgmKrRhx4PM/atAkyYHpXMiRN9Bbewx3g2+dJcF0PxGm1ppW5Ofp3JqDBgrUzRIJBK6TBsaeNwHMNtpGIio8QOHTLeGmmhj2BYe/ezhYgK0c7lgpUuPA8v9Sa0k5Pvg3uI6zGdNo4mriUufRqVWIeElY7lHmSoNL3LUsGu7JXNqnuyAiNgDOBUlkL5oUDF3lJaFWhggU+CvUh1ufd83lTF5ACozcfj6sPMA5Mm/XweaGjA5m4VKdHeDsT+80eqUeZtt+HZjoT2qLPKLY1nf9G8WZFH5lHW1QE334wnNtbqME2CRgcShFB/n1H66NZMp014JBeF74EBjJGERVRoxHFdEQrGhcmFk88rucg8QzJv6Z3kecDCS/RuSm+m6yKLhO4Fy0KkVBIZuUBOnkz63jtaf6RVgrJVEpJK4ljpxnEcFFM1+hVyi7GjUHWyGAh9Htgb0sYz3prnie4hWRjWBiLKCccxERThfFafE1xSMjyZxqtqr8fMO+eLhFxE7LDQjy4oI59Zrkv+f/dus4CkS4oHiSRyUuBKUsZNJiIdWBQEMByQBJY941zXj5SofG9kziyA5QvQzZ0hdHUZ0s3zhxyPTi8dbuuDXmb5KNwjCWTNPnAcDHkRfX5weR86VGGMqlg3LIgj+S7/r/U0yfQ49+K+AaOi/D/h/5v53lyylfYd3p/Eh8YAGh/GjhV9LYVVsOSETR4eJ6eSLBMynJUKilQWuU55UNPiyQFTcPPQocLCe/He4rn1uujvNwtARthwUclxyOfgy6Cx78gR9e+xY41QEetWe6dl6Kl0ltB6xGdNp08BMUwC+OAJfbel5bcnPNYvfvGL+M///E+Ew2FMnToVP/jBDxD353Xx4sW4//77MXLkSHzve9/D/PnzAQDLly/HDTfcgFdffRWf+MQncOONNwIAduzYgYULF2Lfvn1oaWnBv//7vyMcDuPw4cO45pprsH79ekyYMAEPP/wwMhSax8EpJ4bPPfccotEorrnmGk0Mh4aGEIupRfW9730Pmzdvxj333INly5bh+9//PpYtW4Y1a9bghhtuwJo1a5DNZtHaqmKSR4wYgZaWFqxfvx7jWaHtOJg1qxUbVr8QtILJyoL+QchQPgpQKsmyzxOJHb8Wi5aCQoD/ls3QmBckBQPhuugbDAfCAhiekRhUHh6WFnddILTyWaWJzJ2LFZ01aGz0D19f8AyUq/DUU8B1i0rAXXcpUvjRjxoTE2OBLr8cLwzW46LGIaC7G9l0E1xXXXrCBNUDsS8XwfPPK6LIw4XemsmTTQ6e65pCkrkc8IlPADXP/0iFmOXzysM3dy6eWJXQegeNZLQeyp50DGNhzz6GH2zYqHIamjIqR89xFPkeLoSU4PaFZE/OlEynHlqbVJ7FIlQfJ16XFm+mQ0ilkchkfOLlurrhMkM9Q/2GDDmO/3+6BlMpDByKKY8U45qSSaUMV7qaXBeldA2AIGmk56cyxN/zfAMBVMgne3FJBUoX+nBVdT5asXmTYTehKpLyMJDCnNZeThKto2w+SPMjLajUxnwto+iFEEYRz60Oq/nzthuGTKWLyVmeZ3KPRo402t2uXcZNksmYBC4+KEOdqexxzHyZZD80SnDySBgoB1iO0tcsS8kqVdAmHtchXlS0I64fmssDnMo+Nw9gShvK2Dt6Hnk4ssM9Xa0NDUbx4DxSXvAZpeySrovKGCnfKjtwJIEzzjC5fuQf+/YZXiAdYdL2MmqUKc7FZRCP+5EDjgPNRFiMp7kZRSeiST91E76WcO924zal9YNGMBroWltRjCYC9XYS0aIy7DzyiDKQ/J+vo6NDEcVCQf2KIbZNjSVV+RYA5szBwFkX4umn1ecyGeCS5j0mntzXSIejVbrIFaA+y6JNnBcRjKGVXoKhVvQ6SANLIqqU26G8WkMxDAXDE/k3DxrAnBMk4dx7Mo5OWgikm6OtTYWQ+4YaluQnx5WGMHZLkQaxXM4YurikACNnAuSQF6U1gSTHZ5/sA0vk88bDzFQIGkZmNojKkYDZC9JilU5jS5eKmOjuVsuOPFbnY/ua/3AhpFtEeJ7yQE4cO2ysL0xPoD7AB5ed0vlOmMLAn/kN6ilHh/KhgAexkgNSVtNTxb0ULgyZ8UhvEhcZH44X5IWiUWRz5p4Ub3RWHTrkV5/lc8rw91QKw/FqvQ0puit5P0ljNGqIKYckh8zKvCSY5ANcQ5QtnFKSULm2qO9wuo/lPeTnKf5ibkXeHSG9n/KheMZK4lZJ0OWE+mdBZQ4kRaz0/mpyKK8rZDfzMOkMOOre/niHvbC5Nt8bJzqfV9EXsiQ8J47PzMlmiAk3PM89LkC2L2O8Z2UYrNRJpIWb/5cHBl2FHCeFfaWVmWOhjpFKAXV1KCGECy882TmGEwBcekLfbWl55YTHumLFClx88cVwHAdf/vKXAQC33347Nm/ejKuvvhpr165FX18f5s6diy1btgAA6uvr8Ytf/ALpdBoXXHABfvKTn2DmzJm46qqr8KEPfQgLFy7EX//1X+O8887Dpz/9afzLv/wLXnrpJdxzzz1YunQpHn30UTz88MOvOa5TTgwBoLu7G5dffrkmhhKLFy9GT08P/vVf/xV/9Vd/hTlz5uDqq68GAEyfPh0rV67Uf/7t3/4NAI763PHQ2tCAdU88odz0uZCWGXJvci9QyLmu8RoFpD6gN7bc9AAMMZCuAJ8EsioUrWjZfFgLv4EB9TerNrIXFuVbU0PRFHZJpdDTvABPPqkIWLh3uw7l3NAR0kVWmhqKusn8mWcCtW6fbh63rKse3d3AZ9o2AJ6HNeULtc4xu72klDCaYcmsmptRqqvX4XkMLWAycV2dCmOa3ZhV3kzfXVZqn42f/Ux9Z9o0dbk5c1SJ5r5+c8A5jp8jl88bMpXLYSheo2XkrIwqlLO9N6zTCSeeWTra5Cishy90RLB6tfo12yA2Nxt5yxLLWtFhbJB/rRJCCHnKS8yOH6Fev3cST0WaYHfsMIKS2iXzvGSlPR5ArH7C8AqyTZIxP6xNl4JmQ3HZ3sIX6sWGJv0Vyn3Ar9JKl0ZdnbaODxXCKkcN0KEyVKTGjPErkuZypjoQFVAmQ7BSDZO/kkn05BP6FVBfrK/zQ8jGDpuqmDxEGWLnOMptwDnyPOOyBkxfwHQa2ZzyxERyfSY8pb/fWMql5ZhzVSgY8kdlOpUy7QE6O82CoLuQGjPXU2+vWvC5nBqn7xJhUQmer6H8ULBEr+tq4l5X51dy3b3b5LTS1cGSmLSQcA5cF8V4lSqoQsHU2RlUXqmFyp4YBA97sgKZ59TQYL5PpVwaBvjHDxPn+uBt+cyAH/Ip3Y3+/A1Hq7QCGqhKSvbHCzU0GNcjFYmuLlOwZ9EirClfqAhgZgjbB2M6KiK8coWqcOW6wKJF6EldqHLu/JD1LV0h1KcVMRg4FMOmTeryW7cqMsflRVuFDL2SCiHPCIrEMWPULVhtj5VIaeznK5S6IAtNMSIvBJFvDugzpVDwKzhysqUxgwOhm4NCmOtO/kmnlWBmYl00ip7BCH79a2Ug8Dyz9ehRFE4sRFwV2SIvqUNQ6aWSCiVJv1AA4bro61fnbm08q0JL/aq2msDQGyoZFZ+bTGbUKODss4G6On0GcE0y2oKRwGwBAs/D9v5IIEWQRVIq8+0Yqk4itHt3cB1I4sd1T95IMsOuOPTiu26QWNOwLKN7pY4v7NQBIsJzSMtOXkC6wXgBX05wzsl1wv09wZYagHkon/SyhYrkXVofkgVOoKJp9Prl9UgS5CJyHG2sYAinzNYAgrmNnHM+lny/MuqW763y73Hj1L9pYI9Gg7UkNGSoBr/sV4mWkby8dyXv4tRL3ZHrhA6+aNSXeYWCyeXNiWgSPqSMVpP7QL4jfo7vkC+W64EylYYiX3brZ5WT55rcYb4mySNzOUPOp0wRzgeeydKIzEXLF8WQJn8dDDsxPWSmTtBp+hd/cbKJ4XgAF5/Qd1ta/vctGeujjz6KRx55BD/60Y+wePFiAMBNN90EAJg/fz5uueUWAMAtt9yCp59+GgD052688UaceeaZ6O/vh+M4+PWvf60/x++++93vhud5SKVS2Lt3L0aMGHHcsTjH/c0pxt///d/joYcewrhx4/Df//3fAIBdu3ZhypQp+jPpdBq7du067s9fD6VIFD1uPQY7jKGa7QJ0uAc9APkokPOC8ZuVpMH/f9gXJGEq6SytTUsvoPPyYvE4Yr7gDXsFJPL9WrpNzPUC0Sia8t3AkVHAGZPU/efOVWRwdbfaZAsX4sdPxpDuBj6zaBh47EnV+DlViw6f/LS1AfUr7wWeyWPi3LkYGN2Ezk5g1WA18vlqdD6mPvOZOZuBArDBuRA4onSHxOAWYJVSwHVPCTZ1++EPEfI8VMfjqE4mcVE0CjTXBU+yrVuB1bvUv+fMQV9qFjY+o1J5PvpnRcMoDzcD+TiqvRyQTmrJms1VYePGGFIp4Je/jCGViuHiOSXEkEcxHUNPfwK7t5qD23WBzZ0hpFIROH4RAMDvy+cLp4u853BRo3rHxTrV8Fu1FwFingf0DgY9S1AhItSjY9ESNncpJWRmZhjoz6mbv/vd2DKowpkmjlMW6WxqpvYSFL0Qwp7KdeNYu7qAujn+/QH0FRI6ytL1gHhyJpqcHnWINDYpx0G/X4goX0CpfbaxVGea9NkQymUR/sVTqBk9GqU5F2s9KpkEevIJRDMJJHLbgc5OFBpmoasrjHQaGDiSUApMQRUyqfH8hx4dBw5DDXrOHCAaxcD+sGphhRo4ySbNGUK5LIbT9Th40G+34R8QWVSrIoP5PCaOBrb3xwCnHrWNw3rfFdtmB3qD8nm4nDz/zHH6gXy+BhNE1cfu7mo4TjVcF0i2qs9Vez26gkwxWY1CwffoSy2MBpvOToR4QrW1GWZAdy09joxPo+IUr9ZK4PgoEEERETcPwAU8f/2wQqevPUz0hjDxcA7wUuhJzoIXN0U7il5IhYCzFySrk0SjmrCGSbSoSMv4T8D8jn1aK5+FIUCHDikCyoIduZz62b59wXxbajh79+oGlrF0GjMpE+Mqb4yFZAoFYChZi5f31mL8eF9/8N9hjTuECPL+flSyopSsghdXOYMRV+UGJgtARMpaz1NzsnAhNvfG0NGhHvuCC4ANHTHt9Ak7JWDuXAy3X4KDB/2Q74IvxzIZoKsL9Z6H7f0z8cwzSpxefrm6xfjxann7fdZ1tVp9RnhD2rs05CR05IjnmVY2H/1z4z1gn1q+Ah4v8bjxKLLSMkByGEKhkAgoaCYfVkUnKHtHDXKoUb+LBkN9w4N9Zt5k5c2uLpVjuWqV8Yh7HmocBzWNjcDCy9GTT2DjRujccL7+ceOYL2cansMXCcNeBIM5wHFicNPVSgYN7jH7ZnBQTWhnpzKgzZiBauanNzQgvG5d0HjhGyiKTgThuC/EuXa51gF1vd/8Bli9GrV+65QEJ8wXIsPpenR2Arlc2H+WMGpTw6hNK4KSzSlP5sCA8fxKD3o8rsiJDDlmxF08bvLi6B2TtQMA4zUj6VayP4J4XMnxUNcWhAEkIDCYN+TMcZAgu3BdoF9p1CFfdhXdGMJuCUU3ptdMoQCMHAWMdn1Dp08eqr0CSpkaLVYGBmoAfw1Juw9vFc4PqT0YjcJxVagnQzpVcbwQQlT6PU/n9zOyolAADo2rUsbvgm9U91lGuHsLqgFUuw4Qd4FpKspGki9N5glB5NjqRAZokGhyXdIoMzgYjJJUe1C1BGKkUjQKjBunqjTn3IRJCXGKiOT2IAIg4apNSmMkh8MWxFyi3Bs7dxr5wD3seUDBiwBOBFH4/3cSODQmgfGOiAh2YnAAxLwhlZfqxuCw3ZAIYS3FEyi4iWCaEgfW2Gg8lW5MVTD31+fBgxG8mgOAMHK5cID4el4wYpqk13WN8auzM4xCIaFf6ahRMZxxRiwQwQoAUQfw8oYsy6AaLmvafKUIOHkoAzjyup/6Q+KBBx7ARz/6UQCK67S1tenfSU5TyXXWrFmDffv2IR6Pw/Hfufy85EeO42DcuHHYt28fkjQOHANvW2L4zW9+E9/85jexePFi3HXXXbj11lvfkuvee++9uPfeewEAmzb9Fh/6UOtbct2Tir/7u+D/v/e9N/b9H//4mD9+4QXguyc4pDd77z9W7N27F2cyN8rC4gRg19DbA29UjL6d8JatoWef/eOeCIsThpVDFm8Gb+X66Wb6xUnC/PltGBzsO6HvHjp0CK2thkd86lOfwqc+9Sn9/7lz56Jfxs/7+OY3v4krrrhC/9txHHzsYyfWMuOtxtuWGBIf+9jH8P73vx+33norJk+ejJ07d+rf9fb2YvLkyZg8eTJWiprmvb29mMPmVhWQL415iRYWJwq7hizeLOwasnizsGvI4s3CriGLN4M/5vWzfPnyP9i1n3nmmdf8/YMPPognn3wSv/zlL3V45/G4DoBj/nzChAnI5XLwPA+O4wQ+z2ul02l4nocDBw5gwoQJrzmm0Ak96R8YW7du1f9+/PHH0eCHlCxYsAAPPfQQyuUyVq9ejXHjxmHSpEmYP38+VqxYgf3792P//v1YsWKFruBjYWFhYWFhYWFhYWHxdsHy5cvxD//wD3jiiScQiUT0zxcsWIClS5fi8OHD2LFjB7Zu3YoLL7wQF1xwAbZu3YodO3agWCxi6dKlWLBgAUaMGIH3ve99eOSRRwCoLg30Ri5YsABLliwBADzyyCO4+OKLXzO/EHgbeAyvvvpqrFy5EoODg0in07j11luxbNkyvPLKKwiFQjjrrLNwzz33AADe//73Y9myZairq0MkEsEPfvADAEAikcBXvvIVXHDBBQCAr371q0gkEse9p4WFhYWFhYWFhYWFxanAZz/7WRw+fBjz5s0DALS1teGee+7BOeecg6uuugozZ86E4zi4++67MdIvy3/XXXdh/vz5ePXVV3HdddfhnHPOAaCqmS5cuBA333wzzj//fFx//fUAgOuvvx5/+Zd/ibq6OiQSCSxduvR1x/W2qEp6qnDvvfcGYoEtLN4o7BqyeLOwa8jizcKuIYs3C7uGLN4M7Pp55+C0JoYWFhYWFhYWFhYWFhYWb9McQwsLCwsLCwsLCwsLC4uTh9OWGC5fvhzTp09HXV0dvv3tb5/q4Vi8jZHJZHDuueeiublZlyXOZrOYN28epk2bhnnz5mG/3zm+XC7jc5/7HOrq6tDU1IQNGzacyqFbnCJcd911qKqqQmNjo/7ZiayZJUuWYNq0aZg2bZpOILd45+NY6+eWW27B5MmT0dzcjObmZixbtkz/bvHixairq8P06dN182PAnnOnM3bu3In3ve99mDlzJs455xzceeedAKwcsvj9cLz1Y+XQaYDyaQjP88q1tbXlbdu2lQ8fPlxuamoqb9q06VQPy+JtirPOOqu8d+/ewM+++MUvlhcvXlwul8vlxYsXl7/0pS+Vy+Vy+amnnipfeuml5VKpVP71r39dvvDCC0/6eC1OPX71q1+V169fXz7nnHP0z97omtm3b1/57LPPLu/bt6+czWbLZ599djmbzZ78h7E46TjW+vna175W/sd//MejPrtp06ZyU1NTuVAolLdv316ura0te55nz7nTHH19feX169eXy+VyeWhoqDxt2rTypk2brByy+L1wvPVj5dA7H6elx3Dt2rWoq6tDbW0twuEwFi5ciMcff/xUD8vijwiPP/44rr32WgDAtddei8cee0z//JprrsGIESPQ1taGXC6H3bt3n8KRWpwKzJ49+6jKyG90zTz99NOYN28eEokExo8fj3nz5v1B+y1ZvH1wrPVzPDz++ONYuHAhRo0ahbPPPht1dXVYu3atPedOc0yaNAmzZs0CAIwdOxYzZszArl27rByy+L1wvPVzPFg59M7BaUkMd+3ahSlTpuj/p9Pp11zwFqc3RowYgUsuuQQtLS249957AQADAwOYNGkSACCVSmFgYACAXVsWx8cbXTN2LVlU4q677kJTUxOuu+46HQJo14/F66G7uxu/+c1v8K53vcvKIYs3DLl+ACuH3uk4LYmhhcUbwapVq7Bhwwb813/9F+6++24899xzgd+PGDHidRuGWlhI2DVj8Ubx6U9/Gtu2bUNHRwcmTZqEv/3bvz3VQ7L4I0A+n8eHP/xh3HHHHYjFYoHfWTlk8XqoXD9WDr3zcVoSw8mTJ2Pnzp36/729vZg8efIpHJHF2xlcG1VVVfizP/szrF27FhMnTtQhort370ZVVZX+rF1bFsfCG10zdi1ZSEycOBEjR45EKBTCJz/5SaxduxaAXT8Wx8eRI0fw4Q9/GB/72MfwoQ99CICVQxa/P463fqwcemfjtCSGF1xwAbZu3YodO3agWCxi6dKlWLBgwakelsXbEL/73e9w8OBB/e8VK1agsbERCxYs0NXZlixZgiuuuAIAsGDBAjz00EMol8tYvXo1xo0bp8N2LE5vvNE1M3/+fKxYsQL79+/H/v37sWLFCsyfP/9UPoLFKYTMVX700Ud1xdIFCxZg6dKlOHz4MHbs2IGtW7fiwgsvtOfcaY5yuYzrr78eM2bMwBe+8AX9cyuHLH4fHG/9WDl0GuCUlr45hXjqqafK06ZNK9fW1pZvu+22Uz0ci7cptm3bVm5qaio3NTWVZ86cqdfK4OBg+eKLLy7X1dWV//RP/7S8b9++crlcLpdKpfJnPvOZcm1tbbmxsbH84osvnsrhW5wiLFy4sJxKpcqO45QnT55cvu+++05ozdx///3lqVOnlqdOnVp+4IEHTtXjWJxkHGv9fPzjHy83NjaWzz333PIHP/jBcl9fn/78bbfdVq6trS3X19eXly1bpn9uz7nTF88//3wZQPncc88tn3feeeXzzjuv/NRTT1k5ZPF74Xjrx8qhdz5GlMvl8qkmpxYWFhYWFhYWFhYWFhanDqdlKKmFhYWFhYWFhYWFhYWFgSWGFhYWFhYWFhYWFhYWpzksMbSwsLCwsLCwsLCwsDjNYYmhhYWFhYWFhYWFhYXFaQ5LDC0sLCwsLCwsLCwsLE5zWGJoYWFhcZogk8lgxIgRWLlypf7ZLbfcghEjRmDEiBH4yEc+ctzvfuc738GIESOwaNGiwM+7u7v199/MON7qsbzenxPF5s2b8fnPfx7vec97MGXKFIwePRqRSAQNDQ347Gc/i+7u7mN+Tz4b/7iui6qqKsyaNQvXX389fv7zn+PIkSMnPDYLCwsLC4s3A+dUD8DCwsLC4u2Bn//853jxxRdxwQUXnOqhvOmxXHvttW/xiBReeOEF3HnnnZg0aRLq6+vxJ3/yJzh48CA2bNiAu+++Gw8++CCWLVuG2bNnH/P7U6dORXt7OwDA8zzkcjm8/PLLeOCBB/DAAw8gnU7j/vvvxyWXXPIHGb+FhYWFhcXxYImhhYWFhQUikQiGh4dx00034ZlnnvmjH8uDDz741g7Kx9y5c9HZ2Ynp06cHfn7kyBF8+ctfxj//8z/j2muvxfbt24/pmWxvbz/m2F555RV87Wtfw8MPP4zLLrsM//Ef/4ErrrjiD/IMFhYWFhYWx4INJbWwsLCwwFVXXYVUKoVf/vKX+MUvfmHHchxkMpmjSCEAnHHGGbj99tvhui66u7uxdevWN3Td6dOnY+nSpfjCF76AUqmEa6+9Frlc7i0atYWFhYWFxevDEkMLCwsLC4wZMwZf+cpXAAA33XQTyuWyHcsbRCgUQiikjtVRo0ad0DW+/e1vo7q6GgcOHMB99933Vg7PwsLCwsLiNWGJoYWFhYUFAOCTn/wkpk6divXr1+NnP/uZHcsbQKlUwje+8Q0MDw/jvPPOQ01NzQld54wzzsBVV10FAG87b6mFhYWFxTsblhhaWFhYWABQpOQb3/gGAODmm2+G53l2LMfB/v37sWjRIixatAhXXHEFzj77bNx6662YNm0afvKTn7ypyqetra0AgE2bNr1Vw7WwsLCwsHhdWGJoYWFhYaGxcOFCNDc3Y+vWrbj//vv/aMfyWq0qrrzyyjc9tt/97ndYsmQJlixZgieeeAI9PT1obm7Gz372M8yYMeNNXTuZTAIA9u3b96bHaWFhYWFh8fvCViW1sLCwsNAYMWIEFi9ejMsuuwxf//rXcc0112D06NF/dGN5rXYVs2bNetNjS6fTOvdx9+7dWLt2Lb761a+ipaUF3/3ud/G5z33uhK9dKpUAQOcrWlhYWFhYnAxYYmhhYWFhEcCll16K9773vfjVr36FO++8EzfeeOMf3Vj+UO0qjoVJkybhiiuuwOzZs3Heeefhb/7mb/Ce97wH559//gldb3BwEACQSCTeymFaWFhYWFi8Jqw50sLCwsLiKHz7298GANx+++3Yv3+/HcvvgfHjx+OKK65AqVTCY489dsLXWb9+PQDg3HPPfYtGZmFhYWFh8fqwxNDCwsLC4ii0tbXhyiuvRC6X08TMjuX1ceaZZwIA9uzZc0LfLxaL+OlPfwoAmDdv3ls2LgsLCwsLi9eDJYYWFhYWFsfEt771LYwcORLf//73sWvXLjuW3wPPPvssAGDatGkn9P2bbroJu3fvxvjx43H99de/lUOzsLCwsLB4TVhiaGFhYWFxTMyYMQPXXHMNDh06hHvvvdeOBcAdd9yBnTt3HvXzoaEhfOlLX8KvfvUrjB07FgsXLnxD192yZQuuvvpqfPe738XIkSPx0EMPIRaLvVXDtrCwsLCweF3Y4jMWFhYWFsfFrbfeih//+McYHh5+3c+2tbUd93eTJk3Co48+etLGsmjRotf8/de//vUTakJ/xx134Atf+AJmzpyJ6dOnY9SoUdi1axc6OjowNDSEsWPHYunSpaiurj7m91etWqXH9uqrryKXy+Hll1/Gtm3bAAA1NTW4//77MXfu3Dc8NgsLCwsLizcDSwwtLCwsLI6LKVOm4LOf/Sz+6Z/+6XU/u2bNmuP+7qyzzjqpY1myZMlr/v7zn//8CRHDb33rW3j66aexbt06rFy5EgcOHMDYsWMxffp0XHLJJfjMZz5zXFIIANu2bdMkMBwOY9y4cUin07j++uvx/ve/Hx/84AdxxhlnvOFxWVhYWFhYvFmMKLMRk4WFhYWFhYWFhYWFhcVpCZtjaGFhYWFhYWFhYWFhcZrDEkMLCwsLCwsLCwsLC4vTHDbH0MLCwsLitMR9992HVatW/V6fbWhowI033vgHHpGFhYWFhcWpg80xtLCwsLA4LbFo0aLXLVJDvPe978XKlSv/sAOysLCwsLA4hbDE0MLCwsLCwsLCwsLC4jSHzTG0sLCwsLCwsLCwsLA4zWGJoYWFhYWFhYWFhYWFxWkOSwwtLCwsLCwsLCwsLCxOc1hiaGFhYWFhYWFhYWFhcZrDEkMLCwsLCwsLCwsLC4vTHJYYWlhYWFhYWFhYWFhYnOb4f8bJBLhjh7tqAAAAAElFTkSuQmCC\n", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "geometry.show_slide(index=800, axis=1, scale=FIGURE_SCALE,\n", + " zoom=(slice(None), slice(900, 1300)),\n", + " cmap='seismic', vmin=-20000, vmax=20000)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Conclusion" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "This concludes the **first part** of the `SeismicGeometry` tutorial: it showed how to dive into geological data with the `SeismicGeometry` class. Specifically, you have learned how to:\n", + "\n", + "- infer geological properties like SNR of seismic cubes\n", + "- load actual slices of seismic data, as well as visualize them\n", + "- display simple amplitude distribution statistics\n", + "\n", + "The [second part](./01_Geometry_part_2.ipynb) shows data loading optimizations and saving new data cubes." + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3 (ipykernel)", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.8.10" + }, + "widgets": { + "application/vnd.jupyter.widget-state+json": { + "state": { + "283e4f8eedd347eb90ff1cce05057146": { + "model_module": "@jupyter-widgets/base", + "model_module_version": "1.2.0", + "model_name": "LayoutModel", + "state": {} + }, + "de77a81f28754b63aa7ae819ebd95a90": { + "model_module": "@jupyter-widgets/output", + "model_module_version": "1.0.0", + "model_name": "OutputModel", + "state": { + "layout": "IPY_MODEL_283e4f8eedd347eb90ff1cce05057146" + } + } + }, + "version_major": 2, + "version_minor": 0 + } + } + }, + "nbformat": 4, + "nbformat_minor": 4 +} diff --git a/tutorials/01_Geometry_part_2.ipynb b/tutorials/01_Geometry_part_2.ipynb new file mode 100644 index 0000000..f85c332 --- /dev/null +++ b/tutorials/01_Geometry_part_2.ipynb @@ -0,0 +1,579 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Geometry tutorial: part 2\n", + "\n", + "In the [**first part**](./01_Geometry_part_1) of the `Geometry` tutorial you found out methods and properties which help to **examine geology**.\n", + "\n", + "This notebook is the second part of the `Geometry` tutorial which shows methods that help to **work with seismic data**, specifically:\n", + "\n", + "* [Optimizing seismic data loading](#formats)\n", + "* [Saving processed data](#saving)" + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "metadata": { + "execution": { + "iopub.execute_input": "2022-09-28T14:18:43.495019Z", + "iopub.status.busy": "2022-09-28T14:18:43.494319Z", + "iopub.status.idle": "2022-09-28T14:18:45.227662Z", + "shell.execute_reply": "2022-09-28T14:18:45.226831Z", + "shell.execute_reply.started": "2022-09-28T14:18:43.494936Z" + } + }, + "outputs": [], + "source": [ + "# All the necessary imports\n", + "import os\n", + "import sys\n", + "\n", + "import warnings\n", + "warnings.filterwarnings(\"ignore\")\n", + "\n", + "import numpy as np\n", + "from time import perf_counter\n", + "from matplotlib import pyplot as plt\n", + "\n", + "sys.path.insert(0, '../..')\n", + "sys.path.insert(0, '..')\n", + "from seismiqb import Geometry, plot" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": { + "execution": { + "iopub.execute_input": "2022-09-28T14:18:45.228855Z", + "iopub.status.busy": "2022-09-28T14:18:45.228607Z", + "iopub.status.idle": "2022-09-28T14:19:04.605292Z", + "shell.execute_reply": "2022-09-28T14:19:04.603569Z", + "shell.execute_reply.started": "2022-09-28T14:18:45.228835Z" + } + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Collecting stats for `001_YETYPUR.sgy`: 100%|\u001b[38;2;76;175;80m████████████████████████████\u001b[0m| 2563/2563 [00:07<00:00, 339.09it/s]\u001b[0m\n", + "Processed geometry for cube /data/seismic_data/seismic_interpretation/001_YETYPUR/001_YETYPUR.sgy\n", + "Index headers: ['INLINE_3D', 'CROSSLINE_3D']\n", + "Traces: 3_611_267\n", + "Shape: (2563, 1409, 1501)\n", + "Time delay: 50 ms\n", + "Sample rate: 2.0 ms\n", + "Area: 1522.4 km²\n", + "\n", + "File size: 21.000 GB\n", + "Instance (memory) size: 0.141 GB\n", + "\n", + "Number of dead traces: 1_175_447\n", + "Number of alive traces: 2_435_820\n", + "Fullness: 0.67\n", + "\n", + "Value statistics:\n", + "mean | std: 0.03 | 1887.17 \n", + "min | max: -47429.45 | 39240.19 \n", + "q01 | q99: -5459.50 | 5118.29 \n", + "Number of unique values: 214\n", + "CPU times: user 1min 38s, sys: 10.9 s, total: 1min 49s\n", + "Wall time: 19.4 s\n" + ] + } + ], + "source": [ + "%%time\n", + "geometry_sgy = Geometry.new(path='/data/seismic_data/seismic_interpretation/001_YETYPUR/001_YETYPUR.sgy',\n", + " collect_stats=True, recollect_stats=True)\n", + "\n", + "print(geometry_sgy)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "\n", + "# Optimizing seismic data loading\n", + "\n", + "**SEG-Y** format is, essentially, a 2D container of traces. That is not very efficient for slide loading, and we can reshape and rewrite this array into an actual 3D cube of values. As we keep the meta information about the cube right next to it in a `CUBE_NAME.meta` file, so all of the optimized storages need only to keep the array itself.\n", + "\n", + "***By default, a cube in another format is stored right next to its SEG-Y counterpart.***\n", + "\n", + "***Creating a 3D volume requires a strict and clear spatial structure, so converting is restricted to `INLINE_3D`/`CROSSLINE_3D` indexing headers.***\n", + "\n", + "As alternatives to the **SEG-Y** format, we have **HDF5**, **QHDF5**, and **QSGY** formats:\n", + "\n", + " * [**HDF5**](https://www.hdfgroup.org/solutions/hdf5/) is a scientific format designed to store and organize large amounts of data\n", + " * **QHDF5** is quantized version of **HDF5**, that stores int8 values instead of float32. Quantization process is based on cube statistics, but still loses some accuracy\n", + " * **QSGY** stores int8 values in accordance to SEG-Y standard\n", + "\n", + "Let's compare data formats from a speed and storage efficiency points of view:" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": { + "execution": { + "iopub.execute_input": "2022-09-28T14:19:04.610617Z", + "iopub.status.busy": "2022-09-28T14:19:04.610069Z", + "iopub.status.idle": "2022-09-28T14:20:10.608772Z", + "shell.execute_reply": "2022-09-28T14:20:10.607964Z", + "shell.execute_reply.started": "2022-09-28T14:19:04.610566Z" + } + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "100%|\u001b[38;2;76;175;80m██████████████████████████████\u001b[0m| 3611267/3611267 [00:40<00:00, 88215.53it/s]\u001b[0m\n", + "Collecting stats for `001_YETYPUR_f8.sgy`: 100%|\u001b[38;2;76;175;80m█████████████████████████\u001b[0m| 2563/2563 [00:05<00:00, 479.86it/s]\u001b[0m\n", + "CPU times: user 1min 27s, sys: 5.74 s, total: 1min 32s\n", + "Wall time: 1min 5s\n" + ] + } + ], + "source": [ + "%%time\n", + "converted_path = geometry_sgy.repack_segy()\n", + "geometry_qsgy = Geometry.new(converted_path)" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": { + "execution": { + "iopub.execute_input": "2022-09-28T14:20:10.610382Z", + "iopub.status.busy": "2022-09-28T14:20:10.610047Z", + "iopub.status.idle": "2022-09-28T14:45:51.225253Z", + "shell.execute_reply": "2022-09-28T14:45:51.224478Z", + "shell.execute_reply.started": "2022-09-28T14:20:10.610355Z" + } + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Converting to 001_YETYPUR.hdf5:d: 100%|\u001b[38;2;76;175;80m███████████████████████████████████\u001b[0m| 5473/5473 [25:38<00:00, 3.56it/s]\u001b[0m\n", + "CPU times: user 25min 32s, sys: 11 s, total: 25min 43s\n", + "Wall time: 25min 40s\n" + ] + } + ], + "source": [ + "%%time\n", + "geometry_hdf5 = geometry_sgy.convert('hdf5')" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": { + "execution": { + "iopub.execute_input": "2022-09-28T14:45:51.226576Z", + "iopub.status.busy": "2022-09-28T14:45:51.226301Z", + "iopub.status.idle": "2022-09-28T15:03:31.647431Z", + "shell.execute_reply": "2022-09-28T15:03:31.646563Z", + "shell.execute_reply.started": "2022-09-28T14:45:51.226556Z" + }, + "tags": [] + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Converting to 001_YETYPUR.qhdf5:d: 100%|\u001b[38;2;76;175;80m██████████████████████████████████\u001b[0m| 5473/5473 [17:29<00:00, 5.22it/s]\u001b[0m\n", + "CPU times: user 17min 21s, sys: 21.8 s, total: 17min 43s\n", + "Wall time: 17min 40s\n" + ] + } + ], + "source": [ + "%%time\n", + "geometry_qhdf5 = geometry_sgy.convert('qhdf5')" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": { + "execution": { + "iopub.execute_input": "2022-09-28T15:03:31.649041Z", + "iopub.status.busy": "2022-09-28T15:03:31.648715Z", + "iopub.status.idle": "2022-09-28T15:03:31.653525Z", + "shell.execute_reply": "2022-09-28T15:03:31.652784Z", + "shell.execute_reply.started": "2022-09-28T15:03:31.649014Z" + } + }, + "outputs": [], + "source": [ + "names = [\"SEG-Y\", \"QSEG-Y\", \"HDF5\", \"QHDF5\"]\n", + "geometries = [geometry_sgy, geometry_qsgy, geometry_hdf5, geometry_qhdf5]" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "metadata": { + "execution": { + "iopub.execute_input": "2022-09-28T15:03:31.654603Z", + "iopub.status.busy": "2022-09-28T15:03:31.654362Z", + "iopub.status.idle": "2022-09-28T15:05:15.239949Z", + "shell.execute_reply": "2022-09-28T15:05:15.238958Z", + "shell.execute_reply.started": "2022-09-28T15:03:31.654582Z" + } + }, + "outputs": [], + "source": [ + "timings = {}\n", + "sizes = {}\n", + "\n", + "for geometry, name in zip(geometries, names):\n", + " timings[name] = geometry.benchmark(slide_allowed_axis=(0, 1))\n", + " sizes[name] = os.path.getsize(geometry.path) / (1024**3)" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "metadata": { + "execution": { + "iopub.execute_input": "2022-09-28T15:05:15.241606Z", + "iopub.status.busy": "2022-09-28T15:05:15.241082Z", + "iopub.status.idle": "2022-09-28T15:05:15.515031Z", + "shell.execute_reply": "2022-09-28T15:05:15.514672Z", + "shell.execute_reply.started": "2022-09-28T15:05:15.241587Z" + }, + "tags": [] + }, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "def plot_ax(dct, unit, title, ax):\n", + " bars = ax.bar(dct.keys(), dct.values())\n", + " ax.set_title(title, fontsize=20)\n", + " ax.set_xlabel('Storage format', fontsize=16)\n", + " ax.set_ylabel(unit, fontsize=16)\n", + " return ax\n", + "\n", + "fig, axs = plt.subplots(1, 3, figsize=(20, 4))\n", + "axs[0] = plot_ax({key: value['slide']['wall'] for key, value in timings.items()},\n", + " \"Time, ms\", \"Slide loading timings\", axs[0])\n", + "axs[1] = plot_ax({key: value['crop']['wall'] for key, value in timings.items()},\n", + " \"Time, ms\", \"Crop loading timings\", axs[1])\n", + "axs[2] = plot_ax(sizes, \"Storage, GB\", \"Storage using\", axs[2])\n", + "\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Note the bigger cube size in **HDF5** format: it is almost 3 times the size of the original **SEG-Y** cube! That is because we store not only the `(iline, crossline, depth)` projection but also the `(crossline, depth, iline)` and `(depth, iline, crossline)` ones: that is done to make slide loading along all the dimensions as fast as possible. As we can see, the converted version is much faster." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "So we have that:\n", + " * **QBLOSC** is more efficient in terms of data storage;\n", + " * **QHDF5** provides the best load data timings." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "***The entire functionality is the same for all formats:***" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Straightforward quality estimation of the seismic data can be done by looking at the signal-to-noise ratio for each of the traces: in our case, it is defined as:\n", + "$$ log_{10} \\frac{E(trace)^2}{Var(trace)^2}$$" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "metadata": { + "execution": { + "iopub.execute_input": "2022-09-28T15:05:15.515851Z", + "iopub.status.busy": "2022-09-28T15:05:15.515686Z", + "iopub.status.idle": "2022-09-28T15:05:16.096490Z", + "shell.execute_reply": "2022-09-28T15:05:16.095861Z", + "shell.execute_reply.started": "2022-09-28T15:05:15.515835Z" + } + }, + "outputs": [ + { + "data": { + "image/png": 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\n", 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" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "geometry_qhdf5.show(matrix='snr', cmap='viridis')" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Obviously, all of the previous visualization functions are still available." + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "metadata": { + "execution": { + "iopub.execute_input": "2022-09-28T15:05:16.097471Z", + "iopub.status.busy": "2022-09-28T15:05:16.097258Z", + "iopub.status.idle": "2022-09-28T15:05:16.637337Z", + "shell.execute_reply": "2022-09-28T15:05:16.636768Z", + "shell.execute_reply.started": "2022-09-28T15:05:16.097455Z" + }, + "tags": [] + }, + "outputs": [ + { + "data": { + "image/png": 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\n", 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\n", 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" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "geometry_qhdf5.show_histogram(histogram_log=True)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "\n", + "# Saving processed data\n", + "\n", + "When all work with a cube is done, we can easily save results.\n", + "For example, we have an array with a processed cube and want to dump it into memory as a new **SEG-Y** cube:" + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "metadata": { + "execution": { + "iopub.execute_input": "2022-09-28T15:05:18.734692Z", + "iopub.status.busy": "2022-09-28T15:05:18.734466Z", + "iopub.status.idle": "2022-09-28T15:05:19.430635Z", + "shell.execute_reply": "2022-09-28T15:05:19.428816Z", + "shell.execute_reply.started": "2022-09-28T15:05:18.734675Z" + }, + "tags": [] + }, + "outputs": [], + "source": [ + "from seismiqb import array_to_segy\n", + "!rm processed.*" + ] + }, + { + "cell_type": "code", + "execution_count": 13, + "metadata": { + "execution": { + "iopub.execute_input": "2022-09-28T15:05:19.433661Z", + "iopub.status.busy": "2022-09-28T15:05:19.433237Z", + "iopub.status.idle": "2022-09-28T15:05:25.098085Z", + "shell.execute_reply": "2022-09-28T15:05:25.096972Z", + "shell.execute_reply.started": "2022-09-28T15:05:19.433609Z" + }, + "tags": [] + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Array to SEG-Y: 100%|\u001b[38;2;76;175;80m██████████████████████\u001b[0m| 1000/1000 [00:02<00:00, 449.87it/s]\u001b[0m\n", + "CPU times: user 2.47 s, sys: 9.2 s, total: 11.7 s\n", + "Wall time: 5.66 s\n" + ] + } + ], + "source": [ + "%%time\n", + "processed_data = geometry[1000:2000, 500:1000, :] * 2\n", + "processed_data = processed_data.copy()\n", + "\n", + "array_to_segy(array_like=processed_data, sample_rate=2.0, delay=50,\n", + " path='processed.sgy', zip_segy=False)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Let's check processed cube:" + ] + }, + { + "cell_type": "code", + "execution_count": 14, + "metadata": { + "execution": { + "iopub.execute_input": "2022-09-28T15:05:25.100578Z", + "iopub.status.busy": "2022-09-28T15:05:25.100085Z", + "iopub.status.idle": "2022-09-28T15:05:28.519073Z", + "shell.execute_reply": "2022-09-28T15:05:28.517834Z", + "shell.execute_reply.started": "2022-09-28T15:05:25.100528Z" + }, + "tags": [] + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Cubes have same values: True\n" + ] + } + ], + "source": [ + "geometry_processed_sgy = Geometry.new(path='processed.sgy', collect_stats=False, pbar='t')\n", + "print(f\"Cubes have same values: {np.all(geometry_processed_sgy[:, :, :].ravel()==processed_data.ravel())}\")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Conclusion" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "This concludes the `Geometry` tutorial: now you know how to work with various cubes with the help of our framework. To sum up, you have learned how to:\n", + "\n", + "- infer geological properties like SNR of seismic cubes\n", + "- load actual slices of seismic data, as well as visualize them\n", + "- convert SEGY-cubes into HDF5, BLOSC, QHDF5, QBLOSC-formats for faster data loading\n", + "- display simple amplitude distribution statistics\n", + "- save processed cubes\n", + "\n", + "The [next tutorial](./01_Horizon.ipynb) shows how to add 2D surfaces, also known as horizons, to the cubes." + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3 (ipykernel)", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.8.10" + }, + "widgets": { + "application/vnd.jupyter.widget-state+json": { + "state": { + "1d553a4d1b374cdf81a2dae4fde6ae83": { + "model_module": "@jupyter-widgets/base", + "model_module_version": "1.2.0", + "model_name": "LayoutModel", + "state": {} + }, + "8bcfb69c63ff4b11b9672399534a82c9": { + "model_module": "@jupyter-widgets/output", + "model_module_version": "1.0.0", + "model_name": "OutputModel", + "state": { + "layout": "IPY_MODEL_1d553a4d1b374cdf81a2dae4fde6ae83" + } + } + }, + "version_major": 2, + "version_minor": 0 + } + } + }, + "nbformat": 4, + "nbformat_minor": 4 +} diff --git a/tutorials/02_Horizon.ipynb b/tutorials/02_Horizon.ipynb new file mode 100644 index 0000000..d468f6f --- /dev/null +++ b/tutorials/02_Horizon.ipynb @@ -0,0 +1,837 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Horizon tutorial\n", + "\n", + "Seismic data is, essentially, a stack of event layers. Each of such layers is a change in rock properties, and these surfaces are called horizons. In this notebook, we demonstrate our methods to work with them. \n", + "\n", + "Before proceeding, make sure to check out our [previous tutorials on Geometry](./01_Geometry_part_1.ipynb).\n", + "\n", + "Contents:\n", + "\n", + "* [Horizon initialization](#initialization) from a storage\n", + "* [Horizon representations](#representations) as matrices and points clouds\n", + "* [Geological attributes and basic data manipulations](#attributes) as amplitudes, phases, decompositions, surfaces quality evaluations, etc.\n", + "* [Caching](#cache) for faster repeated data loading\n", + "* [Additional manipulations](#add_manipulations) as creating carcasses, creating holes on horizons and cutting sharp discontinuites" + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "metadata": { + "execution": { + "iopub.execute_input": "2022-09-28T14:57:50.072162Z", + "iopub.status.busy": "2022-09-28T14:57:50.071634Z", + "iopub.status.idle": "2022-09-28T14:57:51.764604Z", + "shell.execute_reply": "2022-09-28T14:57:51.763841Z", + "shell.execute_reply.started": "2022-09-28T14:57:50.072034Z" + }, + "tags": [] + }, + "outputs": [], + "source": [ + "# All the necessary imports\n", + "import sys\n", + "import warnings\n", + "warnings.filterwarnings('ignore')\n", + "\n", + "sys.path.insert(0, '../..')\n", + "sys.path.insert(0, '..')\n", + "from seismiqb import Field, Horizon, plot\n", + "\n", + "# Constants:\n", + "FIGURE_SCALE = 1.5" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Horizon initialization\n", + "" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "To create an instance of `Horizon`, we must provide a **storage** and a reference to a **field**. Storage can be one of:\n", + "\n", + "- path to a csv-like file. We support CHARISMA and GENERAL PURPOSE geological formats\n", + "- array of shape (N, 3), where each row is a point in *(iline, crossline, depth)* format\n", + "- matrix of shape *(n_ilines, n_crosslines)* and left-upper point in the cube coordinate system\n", + "- matrix of the same shape as the cube spatial range\n", + "- mapping (dictionary) from *(iline, crossline)* pairs to *depth*\n", + "\n", + "So, let's load a horizon from disk. Note that we use the `~` symbol to use the same [dirname](https://docs.python.org/3/library/os.path.html#os.path.dirname), as in the field." + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": { + "execution": { + "iopub.execute_input": "2022-09-28T14:57:51.765843Z", + "iopub.status.busy": "2022-09-28T14:57:51.765598Z", + "iopub.status.idle": "2022-09-28T14:57:56.437274Z", + "shell.execute_reply": "2022-09-28T14:57:56.436670Z", + "shell.execute_reply.started": "2022-09-28T14:57:51.765823Z" + } + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\n", + "Horizon etp_BP10_anon for 001_YETYPUR loaded from file\n", + "Ilines range: 0 to 2559\n", + "Xlines range: 1 to 1403\n", + "Depth range: 908 to 1076\n", + "Depth mean: 983.258\n", + "Depth std: 42.3661\n", + "\n", + "Length: 2902207\n", + "Perimeter: 8646\n", + "Coverage: 1.1915\n", + "Solidity: 1.0\n", + "Num of holes: 0\n", + "\n" + ] + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "CPU times: user 4.51 s, sys: 753 ms, total: 5.26 s\n", + "Wall time: 4.66 s\n" + ] + } + ], + "source": [ + "%%time\n", + "field = Field(geometry='/data/seismic_data/seismic_interpretation/001_YETYPUR/001_YETYPUR.sgy')\n", + "horizon = Horizon(storage='~/INPUTS/HORIZONS/FINAL/etp_BP10_anon', field=field)\n", + "\n", + "print(horizon)\n", + "horizon.show(scale=FIGURE_SCALE)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "After the loading, we can print some key stats on horizon location and its depth.\n", + "\n", + "**Coverage** metric shows the ratio of labeled non-dead traces to all: being more than `1` means that the horizon does not match the geology. Probably, that is an artifact of the auto-picking procedure. We can remove unnecessary labeling with the `filter` method:" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": { + "execution": { + "iopub.execute_input": "2022-09-28T14:57:56.439489Z", + "iopub.status.busy": "2022-09-28T14:57:56.439133Z", + "iopub.status.idle": "2022-09-28T14:57:57.670642Z", + "shell.execute_reply": "2022-09-28T14:57:57.669828Z", + "shell.execute_reply.started": "2022-09-28T14:57:56.439459Z" + } + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\n", + "Horizon etp_BP10_anon for 001_YETYPUR loaded from file\n", + "Ilines range: 0 to 2559\n", + "Xlines range: 1 to 1403\n", + "Depth range: 908 to 1076\n", + "Depth mean: 980.459\n", + "Depth std: 43.4773\n", + "\n", + "Length: 2424324\n", + "Perimeter: 8242\n", + "Coverage: 0.99528\n", + "Solidity: 1.0\n", + "Num of holes: 0\n", + "\n" + ] + }, + { + "data": { + "image/png": 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\n", 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" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "CPU times: user 1.34 s, sys: 456 ms, total: 1.8 s\n", + "Wall time: 1.23 s\n" + ] + } + ], + "source": [ + "%%time\n", + "horizon.filter(inplace=True)\n", + "\n", + "print(horizon)\n", + "horizon.show(scale=FIGURE_SCALE)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "The `show` method, used in the previous cells, allows us to look at the depth map of a horizon from above.\n", + "\n", + "Additionally, the `SeismiQB` library has the `show_slide` method for visualization of axial projections (with or without labeling)." + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": { + "execution": { + "iopub.execute_input": "2022-09-28T14:57:57.671982Z", + "iopub.status.busy": "2022-09-28T14:57:57.671761Z", + "iopub.status.idle": "2022-09-28T14:57:58.360291Z", + "shell.execute_reply": "2022-09-28T14:57:58.359620Z", + "shell.execute_reply.started": "2022-09-28T14:57:57.671945Z" + }, + "tags": [] + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "CPU times: user 111 ms, sys: 63.1 ms, total: 175 ms\n", + "Wall time: 97 ms\n" + ] + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "%%time\n", + "horizon.show_slide(200, width=10,\n", + " cmap=['Greys_r', 'red'], scale=FIGURE_SCALE)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Horizon representations\n", + "" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "In `SeismiQB`, each horizon can be represented by multiple underlying storage containers: `points` or/and `matrix`.\n", + "\n", + "- `points` is an array of shape *(N, 3)*, where each row is a point in *(iline, crossline, depth)* format;\n", + "- `matrix` is an array of shape *(n_ilines, n_crosslines)*. Essentially, that is a depth map of a horizon." + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": { + "execution": { + "iopub.execute_input": "2022-09-28T14:57:58.361357Z", + "iopub.status.busy": "2022-09-28T14:57:58.361224Z", + "iopub.status.idle": "2022-09-28T14:57:58.368367Z", + "shell.execute_reply": "2022-09-28T14:57:58.367676Z", + "shell.execute_reply.started": "2022-09-28T14:57:58.361341Z" + } + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Points representation:\n", + "\n", + "[[ 0 737 1020]\n", + " [ 0 738 1020]\n", + " [ 0 739 1020]\n", + " [ 0 740 1020]\n", + " [ 0 741 1020]] \n", + "\n", + "Shape: (2424324, 3)\n", + "Stored elements: 7272972\n", + "Memory: 0.03 GB\n", + "\n", + "\n", + "Matrix representation:\n", + "Shape: (2560, 1403)\n", + "Stored elements: 3591680\n", + "Memory: 0.01 GB\n" + ] + } + ], + "source": [ + "horizon_points = horizon.points\n", + "print(\"Points representation:\\n\")\n", + "print(horizon.points[:5], '\\n')\n", + "print(\"Shape: \", horizon.points.shape)\n", + "print(\"Stored elements:\", horizon_points.size)\n", + "print(f\"Memory: {horizon_points.nbytes/(1024**3):4.2f} GB\\n\\n\")\n", + "\n", + "print(\"Matrix representation:\")\n", + "horizon_matrix = horizon.matrix\n", + "print(\"Shape: \", horizon.matrix.shape)\n", + "print(\"Stored elements:\", horizon_matrix.size)\n", + "print(f\"Memory: {horizon_matrix.nbytes/(1024**3):4.2f} GB\")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "**The reason to support multiple storages** is simple: speed and efficiency. Some operations can be done faster using the `points` array, while others work better with the `matrix` storage.\n", + "\n", + "\n", + "**Note** that most of the attributes of `Horizon` instances are loaded **lazily**. If the horizon is initialized from `points`, then the `matrix` attribute is created only at the time of the first access, and same goes for statistics and geological properties. Keeping track of accessed attributes is important when we work with thousands of model-generated horizons, as we want to avoid any unneccessary loadings and cachings." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Geological attributes and basic data manipulations\n", + "" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "We can learn a lot by looking at geological transformations of the horizon depth map and the amplitudes along it. For example, visualizations of transformations can provide information about facies or possible geological fault locations. `SeismiQB` provides a number of pre-defined attributes that can be loaded and displayed by `load_attribute` and `show` methods.\n", + "\n", + "By default, the `show` method displays the depth map of a horizon surface. We can show other geological attributes by using the `src` positional argument:" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": { + "execution": { + "iopub.execute_input": "2022-09-28T14:57:58.369846Z", + "iopub.status.busy": "2022-09-28T14:57:58.369324Z", + "iopub.status.idle": "2022-09-28T14:59:39.675148Z", + "shell.execute_reply": "2022-09-28T14:59:39.674658Z", + "shell.execute_reply.started": "2022-09-28T14:57:58.369818Z" + } + }, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "CPU times: user 2min 10s, sys: 2min 4s, total: 4min 14s\n", + "Wall time: 1min 41s\n" + ] + } + ], + "source": [ + "%%time\n", + "horizon.show(['amplitudes', 'instant_phases',\n", + " 'fourier_decomposition', 'wavelet_decomposition'],\n", + " ncols=2, nrows=2, combine='separate', scale=FIGURE_SCALE)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "We also provide a few metric maps of horizon quality: for each trace, we compare the labeling to a set of reference traces. The comparison function can differ: usually, we use the correlation coefficient. The computation of metrics can be speed up by using `gpu` instead of `cpu`.\n", + "\n", + "The `evaluate` method prints several key characteristics and displays a map of support correlation. If traces correlate with supports, then they are green. The closer the color to red, the more complex a region (more it differs from reference traces)." + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "metadata": { + "execution": { + "iopub.execute_input": "2022-09-28T14:59:39.676102Z", + "iopub.status.busy": "2022-09-28T14:59:39.675956Z", + "iopub.status.idle": "2022-09-28T14:59:58.237568Z", + "shell.execute_reply": "2022-09-28T14:59:58.236793Z", + "shell.execute_reply.started": "2022-09-28T14:59:39.676082Z" + } + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\n", + "Number of labeled points: 2424324\n", + "Number of points inside borders: 2424324\n", + "Perimeter (length of borders): 8242\n", + "Percentage of labeled non-bad traces: 0.995\n", + "Percentage of labeled traces inside borders: 1.000\n", + "Number of holes inside borders: 0\n", + "\n", + "CPU times: user 16.4 s, sys: 1.77 s, total: 18.2 s\n", + "Wall time: 18 s\n" + ] + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "%%time\n", + "_ = horizon.evaluate(bad_color='black', device='gpu', scale=FIGURE_SCALE)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "To access the amplitude values along the `Horizon`, we use `get_cube_values` method. The `window` is used to change the thickness of extracted data." + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "metadata": { + "execution": { + "iopub.execute_input": "2022-09-28T14:59:58.238934Z", + "iopub.status.busy": "2022-09-28T14:59:58.238752Z", + "iopub.status.idle": "2022-09-28T15:03:00.443068Z", + "shell.execute_reply": "2022-09-28T15:03:00.442466Z", + "shell.execute_reply.started": "2022-09-28T14:59:58.238909Z" + } + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Shape of cut subcube: (2563, 1409, 777)\n", + "Size of the array: 10.45 GB\n", + "\n", + "Shape of cut subcube: (2563, 777)\n", + "Size of the array: 0.01 GB\n", + "\n", + "CPU times: user 2min 49s, sys: 12.5 s, total: 3min 2s\n", + "Wall time: 3min 1s\n" + ] + }, + { + "data": { + "image/png": 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" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "%%time\n", + "cut_volume = horizon.get_cube_values(window=777)\n", + "\n", + "print(f'Shape of cut subcube: {cut_volume.shape}')\n", + "print(f'Size of the array: {cut_volume.nbytes/(1024**3):4.2f} GB\\n')\n", + "\n", + "cut_line = cut_volume[:, 777, :]\n", + "\n", + "print(f'Shape of cut subcube: {cut_line.shape}')\n", + "print(f'Size of the array: {cut_line.nbytes/(1024**3):4.2f} GB\\n')\n", + "\n", + "plot(cut_line, colorbar=True, scale=FIGURE_SCALE)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Caching\n", + "" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "In the [geometry tutorial]() we described the caching logic that significantly speeds up the data loading. Here we use the same [LRU cache]() strategy to avoid re-computing of geological attributes. \n", + "\n", + "Cache API is the same as in the case of `SeismicGeometry`:" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "metadata": { + "execution": { + "iopub.execute_input": "2022-09-28T15:03:00.444436Z", + "iopub.status.busy": "2022-09-28T15:03:00.444245Z", + "iopub.status.idle": "2022-09-28T15:03:00.511389Z", + "shell.execute_reply": "2022-09-28T15:03:00.510771Z", + "shell.execute_reply.started": "2022-09-28T15:03:00.444410Z" + } + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Cached memory: 0.75 GB\n", + "Cache representation:\n" + ] + }, + { + "data": { + "text/html": [ + "
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cache_lengthcache_size
binary_matrix10.003345
full_binary_matrix10.003363
get_cube_values10.672651
get_fourier_decomposition10.026906
get_instantaneous_phases10.013453
get_wavelet_decomposition10.026906
\n", + "
" + ], + "text/plain": [ + " cache_length cache_size\n", + "binary_matrix 1 0.003345\n", + "full_binary_matrix 1 0.003363\n", + "get_cube_values 1 0.672651\n", + "get_fourier_decomposition 1 0.026906\n", + "get_instantaneous_phases 1 0.013453\n", + "get_wavelet_decomposition 1 0.026906" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\n", + "Cached memory after reset: 0.00 GB\n", + "Cached representation after reset: None\n" + ] + } + ], + "source": [ + "# Cache inspectation:\n", + "print(f\"Cached memory: {horizon.cache_size:4.2f} GB\")\n", + "\n", + "print(\"Cache representation:\")\n", + "cache_repr = horizon.cache_repr\n", + "display(cache_repr)\n", + "\n", + "# Cache nullification:\n", + "horizon.reset_cache()\n", + "\n", + "print(f\"\\nCached memory after reset: {horizon.cache_size:4.2f} GB\")\n", + "print(f\"Cached representation after reset: {horizon.cache_repr}\")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Additional manipulations\n", + "" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "We use neural networks to label the entire horizon starting from a part of its labeling. To validate this technique on real examples, we artificially reduce the coverage of horizon by:\n", + "\n", + "* cutting a sparce carcass from the full horizon\n", + "* adding holes to the full horizon" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "metadata": { + "execution": { + "iopub.execute_input": "2022-09-28T15:03:00.512581Z", + "iopub.status.busy": "2022-09-28T15:03:00.512307Z", + "iopub.status.idle": "2022-09-28T15:03:01.507204Z", + "shell.execute_reply": "2022-09-28T15:03:01.506632Z", + "shell.execute_reply.started": "2022-09-28T15:03:00.512557Z" + } + }, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "carcass = horizon.make_carcass(frequencies=100)\n", + "carcass.show(load_kwargs={'enlarge': True, 'enlarge_width': 10}, scale=FIGURE_SCALE)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "The next option is to add holes to the horizon surface. It is used to validate the postprocessing procedures of horizon detection." + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "metadata": { + "execution": { + "iopub.execute_input": "2022-09-28T15:03:01.508201Z", + "iopub.status.busy": "2022-09-28T15:03:01.508002Z", + "iopub.status.idle": "2022-09-28T15:03:03.422686Z", + "shell.execute_reply": "2022-09-28T15:03:03.422113Z", + "shell.execute_reply.started": "2022-09-28T15:03:01.508177Z" + }, + "tags": [] + }, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "CPU times: user 1.91 s, sys: 579 ms, total: 2.49 s\n", + "Wall time: 1.91 s\n" + ] + } + ], + "source": [ + "%%time\n", + "horizon_with_holes = horizon.make_holes(seed=13)\n", + "\n", + "horizon_with_holes.show(scale=FIGURE_SCALE)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Sometimes model predictions contain sharp discontinuities, which we eliminate using the `despike` method. This helps to make better predictions in these areas." + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "metadata": { + "execution": { + "iopub.execute_input": "2022-09-28T15:03:03.424346Z", + "iopub.status.busy": "2022-09-28T15:03:03.424187Z", + "iopub.status.idle": "2022-09-28T15:03:05.816901Z", + "shell.execute_reply": "2022-09-28T15:03:05.816123Z", + "shell.execute_reply.started": "2022-09-28T15:03:03.424329Z" + }, + "tags": [] + }, + "outputs": [ + { + "data": { + "image/png": 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uuOPQo0cPzJ8/H1OmTMHTTz+N0047rV72GxM6pfbrX/96NC09p6SpuJXYGjZsGKqqqlBbW4s33ngDxpgGz5xYl4wcORJnnXUWbr75Zrz//vv40Y9+hIkTJ+K+++5zfXTnnXf2Hh3TUkiSBJMmTcL222+PL774Aj/96U/xjW98AwMGDMApp5zi+vGtt95a8XkXwkbrAayT34SGQp9XyqemK4qyDmlqdawoGwJPPvmkF1F7/vnnU2nefPNN06tXL++KsXRl9/PPPzf9+vVztmbPni2WOXfuXLPFFlsYoO4RHPxq93XXXefKufbaa4O+F4tF8+STT4r7qK8AzM0335xKs2LFCjNy5MjMaEpDIqe/+c1vvIjGW2+9lcpfW1trdt55ZwPAtGvXztxzzz1iOR999JGLrBYKBfPaa6+l0lxxxRXOl2HDhpklS5ak0tx7772mqqrKa5+miJzW1taaoUOHOh/OOeccU1tbm0p3+eWXuzT9+vUzq1atSqWhkVMAZvTo0eJCITfccINLc8ghhzTIfx6tDZEnmnnEEUcYACZJEnPjjTeKaVasWGEOPPBAZ+vhhx+uuKyamhqzzTbbuDRSFP6rr74yxx57bDASvD6hMzCy+ujatWtdv66urjbFYtHbv99+++WOnBlj3HcUAPPBBx/k8repIqfGGLNy5Uqz1VZbeRE/+9ietm3bmn//+9/R/M01cmq57bbbvMg+Pf+OP/74zPx5I6dvvfWW1/fnz5/v7af78tKYkdO//OUvLl2hUHCPrFIUZd2j4lRR1gOHH364+6GbPHlyMN2DDz6YKU5/+ctfuv0PPPBAtNwnnnjCpb3qqqu8fePHj3f7+MqceaG+jhkzJpjuo48+Mp07dzYAzEYbbWSWLVuWSlNfcfqzn/3MbR86dKhZsGCBmP++++5z6X7zm99E6/XWW2+5Afh3v/tdb99XX33lDUbffvvtoJ3zzz+/ycXpjBkzXPm77757SkxQDj30UJf2d7/7XWo/HahusskmwX5TW1vrREe7du3M2rVr6+1/Y4nTF154we0/77zzomUuXbrUdOnSxQnwSsu6//773f6RI0cGy1m5cqUnzppKnHbr1s35EFuJNk96OtU9S6jVJ70xTStOjam72ChNZ+ffsRL1fc5p3u+OhopTY4wZPXp0qvxevXqZTz/9NDNvHnG6fPlys9dee7l0w4cPT6VpCnG6Zs0a89Zbb5krrrjCbLTRRi7dcccdl9sHRVEaji6IpCjrmK+++goPP/wwAKBnz574zne+E0x76KGHYsiQIVF7d955J4C6BSW+9a1vRdPuv//+2HzzzQEAjz76qLdv4403du/p9KX68qMf/Si4j9Z71apVDV4sB6h7/uF3v/tdt8ronnvuiaeeegp9+vQR09t269y5s7cQi8TWW2+NXXfdFUC63Z555hl8/PHHAIBvfetb3qIenPPOOw+FQtN+zf75z3927y+44ILotEn6DFGaT+Lkk09OrehqKRQKGDFiBIC6/m+n0TYl9vgnSRLtqwDQrVs3t5DPk08+6a0YnAf6HMpYWRtvvDHOOuusimyvC+zUfqBuVd4sNtpoI/d+xYoV68xWc2WfffbBD37wA2/bLrvsggsvvLCJPGpcJk2alJpm+9vf/hbdu3evyM7TTz+N6dOnu9fUqVPxs5/9DEOGDMEzzzwDoO5ZsNdff32j+V4Jp556qrfAWtu2bbHNNtvgoosucrdA7L333vjd737XJP4pyoaK3nOqKOuYV155xS2/P2LEiMxHIYwaNQr/+c9/xH3Lly93D5/v2bMnpk+fnll+x44dASBlc/To0fjVr34FoO5h6j/96U9xzDHHoG/fvpk2OV26dMm8v2z//ffH//7v/wKoW1HXrvpZH1avXo1jjjnGiYBvfOMb+NOf/uQJbo5dcbh37965xLE9Tu+//z5WrVrlBtHPPfecSzNq1Kiojd69e2PbbbcNPiZjfTBnzhwAdaJs9OjR0bR77rknOnbsiC+++ALPPvtsNC1dyVKCXiRYtmxZTm/XHfb4d+3a1bVJDCtIv/rqK7z33nuZF40oto8UCgXst99+0bRZfUhpnlx99dW44447sHTpUgDAzTffXPFjboYOHYorr7wyV9r6PralPvTr1w8/+9nPnNg+5JBDcNhhh1VsJ+tROl27dsWkSZPchazmRPv27XHbbbfhO9/5TpM8vkhRNmRUnCrKOubDDz907wcNGpSZPpbmgw8+QLFYBFA32A494kWCC4RDDjkEJ5xwAu666y588sknOO+883Deeedh8ODB2HPPPbHvvvvim9/8Zq5B0VZbbZW5kAmtF22T+vCTn/zELdL0ne98B7fffjuqq8NfZ1988YV7JuNbb72Fb3/72xWVt2zZMidO63M8m1KcLlq0CADQq1cvdOrUKZq2UChgq622wiuvvIKlS5dizZo1aNu2rZg2a1EU+kzS1atXV+h142Mfq7Rs2bJ6Hf9KsH2kV69e7vmRIfL0oXVNx44dXR1Xr17tLmiFoI+F4n2K5s1z3GO2mjMbbbQROnXq5MRpfcTjpptummsBvKaA1qexhHG7du3QvXt3DB06FAceeCBOPfXURltcqT58//vfd4u1FYtFfPjhh3jyySdx3333YfXq1bjqqqswYsQIDBgwoMl8VJQNERWnirKOodPcYpE9S2wwm7Vqbgy72iLlD3/4A/bff3/86le/clN7586di7lz52LKlCmoqqrCsccei1/+8pfugeQSldaLtkl9oM+HXLlyZeqZfJyGtBsAF/kGGvd4rg/sVMm8flBxsWLFCmyyySZiuqaerlwpDekD9PjnwfaRltA/gLoIlhWnS5YsiYrTmpoafP755wDqngXJ/e/atat7b1fFjmEvGvG8Sstn1qxZmat+hygUCu5CbE1NTfTio4X+LuSJdu68886piwNnn302nn76aYwePRpz587FQQcdhBdeeCHzgo2iKI1HyxpdKEoLhP6offnll5npV65cmcvWySefDFO3qFnuFydJEpx++ul47bXX8O6772LKlCkYP368u4+ytrYWU6dOxW677YbFixcH/aq0Xg39ob/mmmuw5557Aqi7v++4444TxbdU3r777ltxu9Er5415PNcHNhqV1w8qvltSJCsLe9y22GKLio9/pQNsW1ZL6B9A3T3WFhthDrFgwQLU1tYCqIv68hkTldiqqanBwoULAdSJ9ND94sqGB73nNe+9yPaiCdCwCx177703rr32WgDA22+/3WruJVaUloKKU0VZx9gFiQDgnXfeyUwfS0MHbwsWLGiYY4yBAwfi5JNPxm233Ya3334bL7zwAnbaaScAddOJr7vuumDed999NzN6SetF26Q+dOrUCTNnzswtULt06eIEQ0PbrTGP5/rARrw/+uijzIi1McYtXrTJJpsEp/S2ROy58/HHH0cvZDQGto989NFHmeKzqfsHAO/ZsS+88EI07fPPPy/mq4+tl19+2Qndbbfdtlk/41RZv/Tq1cu9z7ugGk3Xs2fPBpV/1llnuQstEydOxJtvvtkge4qi5EfFqaKsY3bccUc3yP/73//uBmMhnnjiieC+TTfdFNtuuy0A4F//+pd3pbix2Xnnnd0Kp0Ddyoshli9fjhdffDFqb9asWe79Lrvs0mD/rEDda6+9ANQJ1GOPPTYoPPbdd18AwHvvvdcgQWBX8QWAv/3tb9G0ixYtCi5utb6w/hpj8Pjjj0fT/uMf/3ACltazNWAXXVm9ejWefPLJdVqWbbtisYjZs2dH08bO9/XFQQcd5N4/8sgj0bR0MbGDDz54ndpSNlzo90/etRVout12261B5VdVVeFnP/sZgLoI/8UXX9wge4qi5EfFqaKsY9q1a+ceS7F48WLcddddwbQPP/xwppgZO3YsgLopgxMmTGg8RwXodFZ6P4/EDTfcENz3ySef4A9/+AOAuvvwGmsgagXq3nvvDQCYPn16UKDadgPQoIHGXnvt5RYIeeCBB6JX9W+88cbMixHrmqOOOsq9v/7666MRbjuVjedrDZx88snu/WWXXbZOjwtdcMmuiC2xatUq3HrrrevMj7zst99+2GyzzQAAjz/+ePDRUh9//DGmTZsGoG4108MPPzyVZvDgwW7Gxdy5c91jtDirV6/2HtFx7LHHNqgOSuuCrg48ceLEzNkO77zzjrvY0a5du0b5jTnhhBPQv39/AMC9997bKI9cUxQlGxWnirIeoM86POecc/Dyyy+n0sydOxenn356pq2zzjrL/WBOmDAB1113nVs4QmL58uX4zW9+k4qaXX755Xjssceiee2jX4C6CHCMu+66C7fddltq+8qVK3H88ce7BWlOO+20Rl34pGPHjnj44Yc9gXrMMcekBjNHH320i9hOnToV5557bnShm1WrVmHy5MluMG5p06aNe8bhmjVrcOyxx7oVOynTp0+PCvb1xaGHHoqhQ4cCqHtG6wUXXCAe86uvvhp/+ctfANQ9SuLEE09cr36ua3bbbTcnuJ966imceOKJ0ZkHNTU1+POf/4xbbrml4rK++c1vYptttgFQFxm9/PLLU2nWrl2L008/PfO+zPVBdXW1ixIZY3DyySenVihevXo1xo4d66Ypn3322cHFsi655BL3/swzz8R///tfb3+xWMRZZ53lth999NHiFGFlw+WII45w59Cbb76JM844I/i84UWLFnnf+aecckqDp/UCdefF+eefD6DuvLjssssabFNRlGx0tV5FWQ/svffe+N73vof//d//xbJly7D77rtj7Nix2HvvvVEoFDBnzhxMmjQJK1euxBFHHBF9fmmHDh0wffp0jBgxAp9//jl+/OMf47e//S2OOuoobLvttujYsSM+//xzvPfee5gzZw5mz56NNWvWeFN0gbopqZdccgl69eqFgw46CMOGDUOvXr3ckvoPPPCAmybVrl07nHfeeUGfhg0bhs8++wxnnnkmpk+fjm9/+9vo2rUr3n77bUyaNAnvv/8+AGDLLbfEVVdd1fAGZViB+o1vfANPPfUUZsyYgWOOOQZ/+tOf0KZNGwB1qz/ed9992GOPPbBw4UL8+te/xj333INjjjkGO+64I7p06YIvvvgC//3vf/H888/jiSeewMqVK3HFFVekyrvgggtw77334uWXX8aLL76IbbfdFt/97ncxdOhQrFy5EjNnzsR9992Hrl27Yscdd8yc2rkuKRQK+MMf/oA999wTq1atwi9/+UvMmjULJ554Ivr27YvFixfjnnvucdO227RpgzvuuAPt27dvMp/XFb///e/x9ttv49///jfuvvtuPPLIIzj22GMxfPhwdOvWDatWrcLChQvx0ksv4bHHHsOyZctyXTDiVFVVYdKkSdhvv/2wdu1aXHLJJXjsscdw3HHHoUePHnj//fcxefJkvPHGG/j2t7/tntfblJx55pm477778NRTT+HFF1/EjjvuiPHjx2PQoEFYsGABJk2a5GZ1bLvttvj5z38etHX44YfjuOOOw9133433338fO++8M8aPH4/tt98en376Ke644w73rNnevXtnXsThZdGVl+fNm5fav/POO+PII4+sqP5NwZIlS3I9qxqou28+65m5rYmqqipMmzYNe+21F7788kvccccd+Nvf/objjjsO22+/PTp06IClS5fi2Wefxd133+0ummy77ba4/vrrG82P008/HZdffjk++eQT3HvvvXjttdf0QoqirGuMoijrhZqaGnPSSScZAOKrUCiYX/ziF+b22293226//fagvTfffNPstNNOQXv01a5dO/Pwww97+UeOHJkr76abbmoeeeQR0QebZsSIEeall14yffr0CdrZaqutzLvvvhusz4gRI1xaiTzt8sUXX5h9993XpTvssMPMmjVrvDQffvihGTVqVK66V1VVmd/97ndiWYsXL462f9euXc1jjz1mxo4d67bNmzcvWP91zT/+8Q/Tu3fvaH27d+9uZs6cGbRxySWXuLSzZs2KlldJ2sawM2vWLJfukksuCaZbvny5Oe6443IdfwDmoosuqndZf/7zn02HDh2CtvfZZx+zbNky7zxqSpYuXWr233//aHvsvPPO5v3338+0tXr1ajNmzJiora222sq88sormbbyHiv7Gjt2bCO0Rjb9+/ev+NymfaeS14477pjLPv2+if1+ZEG/bytpT/o93pDz3vLiiy+awYMH52qjQw45xHz66adRe/Vpn6uuusrlOfrooxtcJ0VR4ui0XkVZT1RVVeGOO+7AX/7yFxx66KHYbLPN0K5dO2yxxRY4/vjj8fTTT+OCCy7IbW+bbbbBCy+8gBkzZmDs2LHYeuut0blzZ1RVVbmI3cknn4zJkydj0aJFqXtwHnjgAfz5z3/GOeecg7333hu9evVCmzZt0LZtW/Tq1QujRo3C9ddfj7lz5+LAAw/M9GfYsGF46aWX8POf/xzbbbcdOnXqhI4dO2KnnXbC1VdfjVdffRUDBw6suN0qoUOHDnjooYfc4kcPPPAAjj76aG/6bu/evfH4449j9uzZGD9+PIYOHYquXbuiqqoKnTt3xrbbbovjjjsOt956Kz744AOcccYZYlk9evTAs88+i5tuugm77747OnfujI033hjbbLMNfvjDH+Lll1/GAQccsE7rWwl77LEH5s6dixtuuAEjRozAZptthjZt2mCTTTbBHnvsgauuugrvvvuut6BNa6Rz586YNm0aXnzxRZx77rnYaaedsMkmm6C6uhodO3bE4MGDccQRR+CGG27Au+++K07Jzcu3v/1tvP766zj77LMxcOBAtGvXDptuuin22msv3Hrrrfjb3/7WrJ7t2a1bNzz++OOYNm0aDj30UGy++eZo27Ytevbsif333x8TJ07Es88+iy222CLTVrt27TB16lQ8/PDDOOaYY9CvXz9X/z322AM33HADXnnlFeywww7roWZKS2WnnXbCf/7zH0ybNg0nnHACBg0ahM6dO6O6uhrdu3fHDjvsgDPPPBNPP/00HnroIXTv3r3RfTjrrLPco23uu+8+/Pvf/270MhRFKZMYk/H8B0VRlAD20Q8jRoxo0qmriqIoiqIoSstHI6eKoiiKoiiKoihKk6PiVFEURVEURVEURWlyVJwqiqIoiqIoiqIoTY4+SkZRFEVRlFbJo48+ii+//LJeeTfddFP3/GRFURRl/aDiVFEURVGUVsm4cePcc5YrRRd6UxRFWf+oOFUUpd7oYt+KoiiKoihKY6GPklEURVEURVEURVGaHF0QSVEURVEURVEURWlyVJwqiqIoiqIoiqIoTY6KU0VRFEVRFEVRFKXJUXGqKIqiKIqiKIqiNDkqThVFURRFURRFUZQmR8WpoiiKoiiKoiiK0uSoOFUURVEURVEURVGaHBWniqIoiqIoiqIoSpOj4lRRFEVRFEVRFEVpclScKoqywVBbW4sbbrgBO+20Ezp06IAkSZAkCaZPn94o9gcMGIAkSTB58uSK9ilxTjnlFCRJglNOOaWpXamIdd3fAGDkyJFIkgSXXnppo9lsKi699FIkSYKRI0em9jXXPhDzWVEURamc6qZ2QFEUZX1x7rnn4uabbwYAtG3bFj179gQAtG/fvindanXceOON+Oyzz3DEEUdg2LBhTe1Ok6H9TVEURVEqQ8WpoigbBCtWrMBvf/tbAMAvfvELnH/++UiSpIm9ap3ceOONeP/99zFgwIBGEae9e/fGNttsg969ezfcufWE9rfK2XTTTbHNNttgiy22aGpXFEVRlCZCxamiKBsEb775JtauXQsAOPPMM1UotCCuueYaXHPNNU3tRkVof6ucs88+G2effXZTu6EoiqI0IXrPqaIoGwRffvmle9+xY8cm9ETZEND+piiKoiiVo+JUUZRWzeTJk1MLltiFaULbZ8+eHbTXHBag4YuwPPDAAxg1ahQ22WQTdO7cGXvuuWdq0Z0777wTe+21F7p164aOHTti3333xRNPPBEs47XXXsOll16K/fffH1tttRU22mgjdO7cGTvttBN+/vOfY8mSJUG/3n//fQDAqaee6rU1jR7Onz/fbZs/fz7effddjBs3DltuuSXatWuHAQMGuLShxXCuvfZaJEmCtm3bYs6cOWI9HnroIRQKBSRJgj/+8Y+RVpWpra3F73//e+y///7YdNNN0a5dO/Tp0wfHHHOM2E8q6W95y7/pppuw8847o0OHDujevTtGjhyJe++9N7eNZ555Bt/5znfQv39/tG/fHl26dMGuu+6Ka6+9Fl988UUw3yOPPIIjjzwSffv2Rdu2bdG5c2cMHDgQBx54IK6//nosXbrUS8/75T333IMRI0age/fu6NChA77+9a/j5ptvRm1trVheQxYXevTRR9GpUyfXT2pqahqlDQDg4YcfxujRo9G1a1d07NgRO+64I37xi1+4yLiiKIrSiBhFUZRWzLRp00zPnj1Nt27dDAADwPTs2dO9vv3tb7u0dv+sWbOC9kaMGGEAmEsuuSS1r3///gaAuf322yvaVymXXHKJAWBGjBhhLr74YgPAFAoF06VLF1cHAOa2224zxWLRjB071gAw1dXVplOnTm5/VVWVefDBB8UyrL8ATPv27U337t1NkiRuW58+fcybb77p5bnuuutMz549TaFQMABM586dvbbu2bOnSztv3jxn649//KPp2LGjAWA23nhj06FDB9O/f3+X1vo/duxYr7xisWgOOOAAA8AMHDjQfP75597+Dz/80Gy22WYGgDn55JMrbufPPvvMjBw50muvrl27eu1w/vnne3kq6W9ZrF692hx00EHOTqFQ8Mq/8MILo/2xtrbW/OAHP/D6RMeOHU1VVZX7vM0225j58+en8l522WVevo033tgdo9B5Qvvlj3/8YwPAJEliunXr5voEAHPQQQeZ1atXp8qk+TmhPmCMMXfeeadp06aNa5PGagPqk3117drVVFdXGwBm3333NT/96U+DPiuKoiiVo+JUUZQNglmzZrkBZoiWJk67dOliqqqqzFVXXWU+++wzY4wxCxYscIKmU6dO5uKLLzYbbbSRue2228zKlSuNMca8/fbbZvjw4QaA2WKLLUxtbW2qjJNPPtlMnjzZvP/++27bV199ZR5//HGz6667GgBm5513Fv3LU1cqTjt27Gh2220389xzz7n9b731lnsfEyaLFi0yPXr0MADMiSee6LZT4Tpo0CCzYsWKoC8hjjrqKAPAtG3b1vzmN79x7bdo0SJz2mmnOf9vvfXWVN48/S2LH/7wh07gXXnllWb58uXGGGMWL15szjzzTNcHQv3x5z//uQFgevToYW655Rbz6aefGmOMWbNmjZk1a5bZaaed3HGkfWD+/PlOTJ533nlm4cKFbt9nn31mnnrqKfO9733PPP/88155tF8CMGeffbb5+OOPjTHGLF++3FxxxRVOWP/whz9M+VsfcXrdddeZJElMkiTmxhtvbLQ2MMaYGTNmuGN4zDHHmP/+97/GGGO+/PJLc8stt5i2bduarl27qjhVFEVpRFScKoqyQdAaxSkAc+WVV6b2L1++3HTo0MGl+cMf/pBK884777j9Tz31VEXlr1ixwvTs2TOYt1Jx2r9//6h4jIlTY4x56KGHnOiZPHmyMcaYa665xgAwbdq08URvXv71r385/37729+Kaax43XTTTc2qVau8fQ0VpwsXLnQRuosuukhMc/zxx7syeH+cN2+eqaqqMhtttJF5+eWXxfyff/656du3rwFg7r//frf97rvvNgDM1ltvXZHPtF+edNJJYhorFqurqz3RS/PnEafFYtGJ97Zt25pp06al8jSkDYwxZtttt3X+SBdwbrvtNldfFaeKoiiNg95zqiiK0kJp3749zj333NT2zp07Y4899gAAbLHFFjjhhBNSabbaaisMGjQIAPDqq69WVG7Hjh0xYsQIAMDTTz9doddpzj777AYtGnTIIYfghz/8obP1hz/8ARdffDEA4Oqrr8bw4cMrtnn33XcDAPr27YszzjhDTHPFFVcAAJYsWYLHHnusPq4Huffee1FTU4ONNtoI559/vpgmdt/z5MmTUVtbi4MPPhg77rijmKZTp0444ogjANTdX2rp2rUrgLrH4axcubJe/tv251xwwQXYaKONUFNTg/vuu69ettesWYMTTzwRv/rVr9CpUyc89NBDOO6441LpGtIGr776Kt544w0AwM9//nMUCunh0ne/+1306dOnXnVQFEVRZPRRMoqiKC2UbbfdFh06dBD39ezZEwAwfPjw4GNMevbsiXfeeQfLli0T9z/44IO488478dxzz2Hx4sXeCrSWBQsW1NP7MnvttVeDbVxzzTWYPXs2XnzxRZx00kkAgAMPPBA/+tGP6mXv+eefBwDst99+ojABgCFDhqBPnz5YuHAhnn/+eXzrW9+qn/OR8ocPH47OnTuLabbeemtXPueZZ54BULdQUK9evYLl2MWA7CJWALDrrrti0003xaJFi7Dbbrvh//2//4cDDjgA22yzTa5H4vTr189d+OB07twZX//61/H000+7OlbCihUrcOihh+Lxxx9Hz5498fDDD2OnnXYS0zakDaxv1dXV2GeffcR8hUIBI0eOrNdCW4qiKIqMilNFUZQWSqdOnYL7qqurc6fhq44Wi0V85zvfwdSpU7203bp1Q9u2bQEAy5cvx+rVq+sdWaP06NGjwTbatm2LKVOmYPvttwcAdOnSBVOmTKn380U//vhjAMiMjPXt2xcLFy506RuLSsvnfPjhhwCAlStX5jpG9MJD165dMXXqVJxwwgl4/fXX8f3vfx9AXZvuu+++OPbYY3HcccehTZs2oq0sn+3++rTZn//8Z/f+L3/5S1CYAg1rA+ubXaE5RN++fTPtKoqiKPnRab2KoiiKx6RJkzB16lRUVVXh4osvxty5c/HVV19h6dKl+Oijj/DRRx/h6KOPBgAYYxpcXlVVVYNtAMDEiRPd+88//xwvv/xyo9htidjHtVx44YUwdetLRF/8sTgHHHAA5s2bhzvuuANjx47F4MGDsXz5cvzlL3/BSSedhJ122kkUxeuaESNGoF+/fgCAM844A5988kkwbUPbQFEURVn/qDhVFEUpYUXS6tWrg2mWL1++vtxpMqZNmwagbvB/2WWXYdCgQamprR999FFTuBbkwQcfxE033QQA2GGHHWCMwdixY7F48eJ62bPR3Kxpy3Z/Y0R/pfKzBGBov53GSqeqVkqHDh1w0kknYfLkyXj77bexYMECXHvttWjfvr0XUc3rE99fnzYbMGAAZs+ejf79++PVV1/FfvvtF4zANqQNrG9LlizBmjVrgumaQqAriqK0ZlScKoqilOjWrRsA4IMPPhD3r1ixAv/5z3/Wp0tNgq1/aMrkF198gWeffTaY3wrZxoiq5mHRokU49dRTAQCnnnoqnnzySQwYMAAff/wxxo4dWy8/7CJKs2bNQrFYFNO8+eabTpzssssu9fQ+Xv7zzz/v7onkzJ07Nyie7X28jz/+ePRiSyX06dMHP/7xj919vKFFoD744AO8++674r4VK1bghRdeAIB6LVQFAAMHDsTs2bMxYMAAvP766xg5cqR4saQhbWB9q6mpwVNPPSWmKRaLGm1VFEVpZFScKoqilLAreoZWEb3++uvx1VdfrU+XmoQuXboAAF555RVx/xVXXIEVK1YE89sFfD777LNG941TLBZx0kknYcmSJRg8eDBuuukmdOnSBXfddReqq6vxyCOP4IYbbqjY7pgxYwDURcb+7//+T0xjV6TddNNNccABB9S/EgJHHXUUqqqqsGrVKlx//fVimssvvzyY/7TTTkN1dTWWLFmCSy65JFrWmjVrPAGc1cc32mgjAAguFAWUVzLm/PKXv8SqVatQXV2No446KlpOjAEDBuDvf/87Bg4ciP/85z8YOXIkFi1a5KVpSBvssMMOGDJkCADgqquuEi9Q/P73v2+UBcEURVGUMipOFUVRShx//PEA6h4pcckll+Dzzz8HUDe173/+539w5ZVXusdstGYOPvhgAMDvfvc7TJw40U1r/Oijj/DDH/4Qv/jFL7DJJpsE82+33XYA6h6HEloJuLH4xS9+gSeeeAJt2rTB1KlT3erFe+yxhxMk//M//4MXX3yxIru77rqrE0/f//73cfPNN7sFcz766CN897vfxZ/+9CcAdUKsffv2jVUlAHVRyrPOOsvZv+aaa9wFgU8++cQ9MsdeSOBstdVWuOiiiwDUtdHJJ5+M1157ze2vqanByy+/jMsvvxyDBg3y7s+99tprccghh+DOO+/0xNdXX32Fe+65B9dddx0A4NBDDxXLtotRnXPOOViyZAmAuojp1Vdf7QT1WWedhc0337w+TePYYost8Pe//x2DBg3CW2+9hREjRnjTbBvSBkCdKAXqoucnnHCCa4vVq1fjtttuw9lnn71BfB8oiqKsV9bnQ1UVRVGailmzZhkAJva1V1NTY/bbbz+XLkkS061bN5MkiUmSxFx33XVmxIgRBoC55JJLUvn79+9vAJjbb7+9on2VcskllxgAZsSIEcE0Y8eONQDM2LFjg2lCdVm2bJn52te+5tqhUCiYrl27miRJDAAzfvz4qP2///3vLm1VVZXp3bu36d+/v+nfv79LM2/ePGd/3rx50fqGynr22WdNmzZtDABz3XXXpfLV1taakSNHGgBm6623Nl988UW0HM5nn33m2giAqa6udv3Bbjv//PPFvHn6WxarVq0yBxxwgLNTVVXllX/hhRdG+2OxWDQXXXSR5+9GG21kNtlkE1NVVeW2ATBPP/20y2f7F83TvXt3z86QIUPMokWLvPJov/zxj3/snUO0vAMOOMCsWrUq5W+sX8f628KFC80222xjAJitttrK/Pe//21wG1h+9rOfeWm6detmqqurDQCzzz77mJ/+9KeZ56KiKIqSH42cKoqilKiqqsJf//pXXHbZZfja176Gtm3bIkkSHHjggXjsscdw/vnnN7WL64WuXbviH//4B84991wMGDAAVVVVqK6uxsiRIzF16lTcdttt0fz77rsv/vrXv+KAAw5A165dsXjxYrz//vsNWpyHs2LFChx//PFYu3YtRo8eLT7PtFAo4M4770T37t3x9ttv4+yzz66ojC5duuCJJ57ApEmTMHLkSHTq1AlffPEFevXqhaOOOgqzZs1yUcR1Qfv27fHwww/j17/+NYYNG4a2bdvCGIN99tkH99xzDyZMmBDNnyQJLr/8crz66qv43ve+hyFDhqCqqgrLly9Ht27dsOeee+KCCy7AP/7xD+9Zs+PGjcPEiRNx/PHHY7vttsPGG2+Mzz//HN26dcM+++yDG2+8ES+++GL02aHXXnstpk2bhr333hvGGLRt2xbDhg3Dr3/9a8ycObNRI82bb745Zs+ejSFDhuDdd9/FiBEjXF+rbxtYrrzySjz44IPYf//90blzZ3z11VcYMmQIJkyYgCeeeMI9WklRFEVpHBJj1tOKFYqiKIqitFouvfRSXHbZZRgxYoQuFKQoiqLUC42cKoqiKIqiKIqiKE2OilNFURRFURRFURSlyVFxqiiKoiiKoiiKojQ51U3tgKIoyobI9ddfH3x+ZYjzzz9/g1mUSVEURVGUDQ8Vp4qiKE3AF198gcWLF1ecR1GaK5deeikuvfTSpnZDURRFacHoar2KoiiKoiiKoihKk6P3nCqKoiiKoiiKoihNjopTRVEURVEURVEUpclRcaooiqIoiqIoiqI0OSpOFUVRFEVRFEVRlCZHxamiKIqiKIqiKIrS5Kg4VRRFURRFURRFUZocFaeKoiiKoiiKoihKk6PiVFEURVEURVEURWlyNmhxOnPmTGyzzTYYNGgQJkyY0NTuKC2UAQMGYPvtt8ewYcMwfPhwAMDSpUsxevRoDB48GKNHj8ayZcsAAMYY/OAHP8CgQYOwww474MUXX2xK15VmymmnnYYePXpgu+22c9vq06emTJmCwYMHY/DgwZgyZcp6r4fSPJH616WXXoo+ffpg2LBhGDZsGB566CG375prrsGgQYOwzTbb4JFHHnHb9TdUCfHBBx9gv/32w7bbbouhQ4fi17/+NQD9HlMah1D/0u+xVoLZQKmpqTEDBw407777rvnqq6/MDjvsYF5//fWmdktpgfTv39988skn3rYLLrjAXHPNNcYYY6655hrz4x//2BhjzF//+ldz8MEHm2KxaP75z3+aXXfddb37qzR//v73v5sXXnjBDB061G2rtE99+umnZssttzSffvqpWbp0qdlyyy3N0qVL139llGaH1L8uueQSc91116XSvv7662aHHXYwq1evNu+9954ZOHCgqamp0d9QJcqHH35oXnjhBWOMMZ9//rkZPHiwef311/V7TGkUQv1Lv8daBxts5HTOnDkYNGgQBg4ciLZt22LMmDGYMWNGU7ultBJmzJiBsWPHAgDGjh2L6dOnu+0nn3wykiTB7rvvjs8++wyLFi1qQk+V5si+++6L7t27e9sq7VOPPPIIRo8eje7du6Nbt24YPXo0Zs6cub6rojRDpP4VYsaMGRgzZgzatWuHLbfcEoMGDcKcOXP0N1SJ0rt3b+y8884AgE6dOmHIkCFYuHChfo8pjUKof4XQ77GWxQYrThcuXIh+/fq5z3379o12bEUJkSQJDjzwQHz961/HxIkTAQCLFy9G7969AQC9evXC4sWLAWi/U+pPpX1K+5pSKTfffDN22GEHnHbaaW66pfYvpaHMnz8fL730EnbbbTf9HlMaHdq/AP0eaw1ssOJUURqLp59+Gi+++CIefvhh3HLLLXjyySe9/UmSIEmSJvJOaY1on1IamzPPPBPvvvsuXn75ZfTu3Rs/+tGPmtolpRXwxRdf4KijjsKNN96Izp07e/v0e0xpKLx/6fdY62CDFad9+vTBBx984D4vWLAAffr0aUKPlJaK7Tc9evTAt7/9bcyZMwc9e/Z003UXLVqEHj16uLTa75T6UGmf0r6mVELPnj1RVVWFQqGA7373u5gzZw4A7V9K/Vm7di2OOuoonHjiiTjyyCMB6PeY0niE+pd+j7V8Nlhxussuu2Du3LmYN28e1qxZg2nTpuGwww5rareUFsbKlSuxYsUK9/7RRx/Fdttth8MOO8ytKjhlyhQcfvjhAIDDDjsMd9xxB4wx+Ne//oUuXbq4KU6KEqPSPnXQQQfh0UcfxbJly7Bs2TI8+uijOOigg5qyCkozht77fv/997uVfA877DBMmzYNX331FebNm4e5c+di11131d9QJYoxBqeffjqGDBmC8847z23X7zGlMQj1L/0eayU06XJMTcxf//pXM3jwYDNw4EBz5ZVXNrU7Sgvk3XffNTvssIPZYYcdzLbbbuv60ZIlS8z+++9vBg0aZEaNGmU+/fRTY4wxxWLRfO973zMDBw402223nXnuueea0n2lmTJmzBjTq1cvU11dbfr06WP+7//+r159atKkSWarrbYyW221lfn973/fVNVRmhlS//rOd75jtttuO7P99tubb33rW+bDDz906a+88kozcOBAs/XWW5uHHnrIbdffUCXEU089ZQCY7bff3uy4445mxx13NH/961/1e0xpFEL9S7/HWgeJMcY0tUBWFEVRFEVRFEVRNmw22Gm9iqIoiqIoiqIoSvNBxamiKIqiKIqiKIrS5Kg4VRRFURRFURRFUZocFaeKoiiKoiiKoihKk9MqxenMmTOxzTbbYNCgQZgwYUJTu6MoiqIoiqIoSitHNUjDaXWr9dbW1mLrrbfGY489hr59+2KXXXbB1KlTse222za1a4qiKIqiKIqitEJUgzQOrS5yOmfOHAwaNAgDBw5E27ZtMWbMGMyYMaOp3VIURVEURVEUpZWiGqRxqG5qBxqbhQsXol+/fu5z37598eyzz3ppJk6ciIkTJwIA3nzzTXzta19brz4qiqIoiqIoitKymD9/PpYsWSLuy6NBGptkUD/gy9UV5ztoh69j5syZ68CjhtPqxGkexo0bh3HjxgEAhg8fjueff76JPVIURVEURWnZ3PPaeABAktS9ACBB+T0ltF1KJ1Gfe9JCN7JRX4N+kJ2hdKH6FJJynjxlUQzSftuPRbJdSkO3ZbUX94f7yetWiBxfWy4v06bNe+y5PWsz1B7UX+tzIrwfvdVv8xfOGD58eL3zrhO+XA2MP7LibEv+8sI6cKZxaHXitE+fPvjggw/c5wULFqBPnz5N6JGiKIqiKErr5k+vj0+JUiAtQiRhUoFOaViePGK4ASJUosDEmJQ1ZM+Ycl5Pj5m6z4WkLFCTxBdtPF+CsDiXfKlElErC1pT85NupQA2RErWkblJ7iG3KyuTv1wVNpUHWZZ2aglZ3z+kuu+yCuXPnYt68eVizZg2mTZuGww47rKndUhRFURRFabUkSVmIFZJy9DRB+WW3uzwgYiXHCyxtIWe+vC8nJMEEjeAHSvWJvaqoj8Qmt+u1hdBeCbFp24u2tWRTsltI4m0mHT9eT2eTtpVkT/A/gdxOUl7vGET6TqjtPVus7f42b3ykJ9cf1SCNQ6uLnFZXV+Pmm2/GQQcdhNraWpx22mkYOnRoU7ulKIqiKIrSKrnvjfG+SLL/EzF5Kk0kmZ8nSX+2m7yooWAwtt8YeTulwMuOesrEYc52iO03XgjUf08jqJIPKYSIpgQVozwdFajcNK0zj3BK0VM+VZfmTVj+UPA3FTkO+Gq3z54/HiMH1H96r0STaJAk3r9aIq1OnALAN77xDXzjG99oajcURVEURVFaNff/Z3wqeufes7SGba/k/sMs8RmafloUhCcXmkUhn2dbKIsKq5j7Uh1DYjjLjpsqyws3st9AftFKBW6ee2RpJDPWFtLnVJuwjJJoteKTT+mV6sXbO4Hs67oQqE2hQVqZNm2d4lRRFEVRFEVZt0x/c3xUjHK8KFgFwtSmp6QEpklH+qR0UpncL7F8+BoqJNqkfFLEt9LyqQ9OtFGnmHi3oq6KR4kjtrkoDdVV2kf3c0EppfOiriwC64lTup0KdGS3VTR6XZ8VtZT1gopTRVEURVGUFsgfXq27d066F/C47Ro3IiQhRRSlfaFVWymVRP4kEVoVmN4YitxRuABy25kIcoJMdjVddoZ4ktKFtqem9ZL/TJt6eaW2lxZG8gSntE3oYyG8egtp+YUJLkypqLVRbeeyiVxAyIiWEhOtaipsa6oLoOJUURRFURSlRXDnK36kMjT9MkF59dyjt113IjXvtNSQ4AoJUkpsmm3WfZ1chIUifkFxGthOfeDpJILtEhBP0WnLkjANCDaXNOc9ppJfkijNuj/Wlm23SSJfEuR24SK7sWjqVm6l9eDTerNEvuhr4FE3SvNAxamiKIqiKEoz5o5Xxrt7/GL3AzoBkSEiGos8okpCinyGkCJ/tiwumKh+s9NerTCS7pHM8jsa+WRCKM9jWnjevEIvtYNP5Y3YyLpPM1aW1LaxqGmoTbztgsi32+iKxO5Zrih/sPUICd5QGZKflRyv5oy9GNWaUHGqKIqiKIrSzJj88ng3cLdizk5dpWIUIAN0Msi3+6a/OR5HfG39RU9jSCv6UhtccNjnfErl8fy0zvZexSKJLjamYBdNsDpwf6X8eYWeBxGmVKzxsum0XumZo9EySkj3oPKLAJ69VAGRfcwH/qgcGKT6t7XDI8VSPaQLILWB+3JbOjqtV1EURVEURWl0bn9pfFkEICxMaYTUEosorisqnaILyGIzITuTSGJJ0Cbw28Rus7rD/i9w21l+Comjj5whUUyaLk9UMugDS28EYRqa40rbNLQabrAuJJ10f6jXzpE2ydve4kJM9r/x0wH+6sqSLVo29auKmCsKFz6U5oGKU0VRFEVRlCbg9y/VLWgkCUu63U5JtSKsUEgLm1iE68G3x+ObWzd+9DTr2Z8Zs05T4i0lXIX0dLtXV0HY2vsVeZ6s55pmRfk4doEdF+kVonax+yEls8H7TrkwFaKKNi31J6ttpbJ4P/LuCS0RE4r1QZqObVdipudDURCtgCxKQbeRVYxrG9f1JqO1iWwVp4qiKIqiKOuJSS+OF0WW/cwFqpvqiLQwlYTs+rrflJZpy7U4gRTLG4gq5onkUdt0Sq+Xl0zpDZUREr+hsoOzQFnUVGqX2LZKjpUkOk0oekrKCT0nNs+FA5ueTyuXnmsKsk+Cr77MI9r2fmHah+zjcGjdpWm7sbZOTRkHUN3aVF0rQcWpoiiKoijKOsRGSAEhWphDmFLxFfpPbdi8rozGr1LKd76dapDYqrnclmRPKi9r+jKNkoXspLbnKJfWxZD9PGrKbcYip5TY9OgiE1hSaDolVgNl8WMXe9yP1w+tIC5l4scakO8VtlSx9FK60L2gnsBm9QhtQ2BbqJ1aInrPqaIoiqIoihLkdiJGgfJAPxa9CkZMSdSITl+NiTMpkvjIO+Nx0KDGndoriWxAECcBwcbzRsWFkDYUPQbYVNuM8qU6hODHzTCBaLfFyoyJUl5P2messOMilfqR5xmeIWEnTXf2LoyQiwquT1dYPu0bwYsEge2xFXpj21N2Sv/z3ifd3Gkl1XCoOFUURVEURWkgVpDaQTwlz2DcDvZTohTwhRhLHxW0kTIbgyxxkXd6r01TiSiNva8r3DeQdQzqiyQQ6QWFGDy6HYoCegE+40cfQ9HU0P2+0anLbF8qYk/eO594QSwamZr6Gys/4oso+DPOM+5Snv6oND0qThVFURRFUerB5Jf96bpA/USQJEytGAD9TKJXLtJW+m/vB6T2qD/rglBdeTSRR4yp0OB1TJURSCdFnqV8EKKBDYEKSn7/ZCgimrV4j80b7DvCPFgrhrlQzXPceZRWmt0augiSwM+bMiL4zi8aWMGauogR6APcbihNcLp4oD+2humw9HuitaDiVFEURVEUpQKmvOyvskupjygMCdPUlF6ynQ6svcfMCAJ1XfD4e+mFnRxEsEjTPLmwtlmyIqdSZEyyXWRiOIR7NImgziQRyaOAVeRDSODZdNLiQXkuJqTaLyJUed05hUC72fxg20PPOU05WNqeerSNlF4QuLmiucIxDR0XbtNdECE+QMijNA9UnCqKoiiKokS44xV2D2lsMJ2xP4YkQKlgpQvSAPGFkrhPAPDEe+MxamDj3HdKiwhG+hJf+PC0ktj0ykjC6UJTUO17IC46E2Eb9yuUV8IJpQpWxY2J0mC+gKi0c2153UOPWckSc9S/JJCHGpUWhBIjlDkWaxLMe9ObU6JWsBlb7Ki1idLWEAGmqDhVFEVRFEVhTHk5EhmMUJ+BIn+cBp++m0d8SpHTdUm0HC4acgjSmL3YlGnxkSJsH98ecjeE5Bv1ISRIs2xm1T0UjRUfHUMenWOn+/LyaPKQn7wP8QsiKd9IdDz0GB3uR2gGsOhPIt8rKolpSZDGHnfTKkhUnCqKoiiKorRKJr88PleULos89/RRPHFJ3zNhwKN9XEhkRuEacRArRRG5iLBCJG/UMCaY8uzPu11Mm5E41r5ZeaXHtNh8McGbdRy9lXITBKdRS2VKgk66wJF6fAyxZ4ggtve7Zj3GJiZgeRnO7yTspzHlZ6NKxA5NaxN1rQUVp4qiKIqibLBMoYsa2f8NFKYp8ZKRJyhMJZ8SIV8CUTitqyjq3+ePF21S0eS2lf5L0cX6CurYokK8rJidvNDjwe1JgooSEmOZgjuHv1YgJklpGm/EGSn6bvPSCwhSOtfewv2k9tE2tuiYMLb7Y33HiV5qy/iPf/HakAlXGpVdV/2hudGKqgJAxamiKIqiKBsQt7+Unq4bG1DnRZxemtMIj1DRKb2Av92WlbD8UtlS8bPnj8fIAQ2775Taji0EJE4/hSxK87aVJP55/qwpq7H7EYG0uJaEqdT+YplS3xKEbX0FhhWIBRCBKvgmiU33iBWSlk83tu8LCVArXGDw7jU16f5AjzVdPClaX9Y3Yn0sgd+O1iewMkKP3FGaHypOFUVRFEVp1XiCNBABk8gSTJIgDeULmXKCQIhYQfhMp/PyBZFo2SHR1xhRFklcAukIVmrKJhMnlUSvssQ/ra8xvuDijy7h4ixFJPoY84H7EitDEr15SekrIsZsO/O2ESOhrHDpkS40PY22er7QRhaiq1JflC5weP0nx82i7ngS32rJNF8rSG1/SEqF1bfdmyutKQoMqDhVFEVRFKUVcvtL/jNIcwvSSJrQdNKY3YAO8H0ThKkkVGOPm4nVIW/d8/D0f8cHbYTEqLif2aAR0VikTConJcD58RZsSJ+doA2I3ryitJJ2iPljfQr1NSpEi6WVelPikfQBHp2XHMh6Bijdnme6LO2vgUB6+X0iCFSSj04hTlAWpW6FYpQFaW2xJFRJe9DpybFH7rQkbFu0JlScKoqiKIrS4vm/F8dnTsHMEmahdKGppCGbQTEkiCibrmJhmiGguG2a9qn3x2Of/pVP7X36v+PF7VS0533GKM2XJRole0GBFcqb4RO9N1S6BzPkh+RLqogKxGgoTdC+7R8oRQxLm7PuIwXSi1oVTWVt6rlA1CefqixNs7V+eZTSpUQpiYa6KDgpg9eDp+fPgC0aP7quNC9UnCqKoiiK0mL53Qvjg9P0glMKWZoY4gJHGWIjZj807TYkTAsZ+/MK00rFXBYhYUlFQFb+vO3qpQmkzcoqRZElA1ak5m23TGGaw7eK/AzZtuKQ9y9il/Ypap8uNgSkj5+NyvL9diqtKyeJrzLsXA2dP4IwdT4SoeldRDBAsVSfYiki6iKsQh+j9rPuPW4p6LReRVEURVGUJmTiC+UInjfVNodYo59j5F3gKAm9T9LvJTHG/aWrkYbuKeUCldpeV8L0Hx+MTz07k9YDKAuHLIFaSCo7Fq6cQPqYiTxtQAVP6GJCXv9sHiqgsqbKSvmpb1m+hBYlkvqOFZnUVNH4YjDP8UstMAS4+zlD07Il/6kvdsGl1HNNS2nsdju1t5b4QMWr3S6J7aTURlbLK80PFaeKoiiKojR7bntefgap/V9JFDGLvFG9BOl0XpmCHZqG+22FqSRKeR7uR8qvQL3tgP2fH4TvHaX36aWEAvOHf84rUHl+bp9PDaXpk4z9kr3QsTBI14PftxlDujjg+STYz7IV2xYUXEBqUSJ6ocN+LiRAVZI+vtSeQXqqrCuLlMePLz3+Uh34Pdu2HLe9SEQv8d9Ow6UCnArqYrFcF9ovinIV6s6xwL6WSAXXT1oEKk4VRVEURWl23DxnfFCkxQjdk9nYwtTalcqnfoTy03pJUy7zRkZj4jVU76ym8MpkIoanCdqALFALGfXK8jEJ7Jf6SK4+QFdyRVmsJn6SqC8xH8R8GYlCwpCWWZX4frn7RYmw5hF4m9/zs/TeijVT+kPbhPueoHx8afmiv0yYpoQ72WaFqknSfdkkvm+8TH4faULSUgFMF09qLQJVp/UqiqIoiqKsA26e40/XDQkwQBagfHtMHNJyaFpejkRQOAnCNJQ/Nj03tC9Wfh5hGppOG7IHQA5R5oQLmFQbCz7Wh1AfoWUGLzDwYyVMV02QvhdS6mfcLoBc03KB7JWgJRvuEJmyWKXRQn4hIMsHZzPSf609+1xVqkkb4x7OKqKUPfGbAAldWEm46FEsbTfwp1Mb6zjSEWKl+aHiVFEURVGUJuOmZ/3ppdICQEA4Cua9D6QJUZ/nlFYqTGNTNbmgtNMtQ6KV28gjvqO+ZuRN3B94EasQ4qNFIuWHonM8byxdrB1CFzCszZA9yYckyfY3jz0Lj47mPZZS37JiDCWRysvPFOjEcNaCRimhy/pF6l7UUiRXiqzayDptVxrltAsbSY+XSRKgiqRx9uD7RC8S0PdcWLdkGuH6TrNCxamiKIqiKOsVGiENTfuTBtWxfdxe6F49L62QL5Qm7wAwlxAo/W+IMJXsxiJkscfhhHy07+lU19AjOELTfqPPOs0oO7bN2sq6eBGyYesVQ+p/qamjGb5ISFHSSqYE83IMe1HbeewmtDEC7WZ3x6KjhqVzZo2QjojMgvAC6u4ltc8rLbJ2LyRlYVpF3ntVYecRXTSpNYnT1oaKU0VRFEVR1im/eXZ8SjCEpjHmEaKScPPSEXtZoqwxRCkXxDGb0lRdu/CLV6+AME35J9SPfw5O582pVvmAn47q6XZpVdpKoroVJM3sF3nsxgQqF+gWHj3NEykPYZMW2DHPyiOV6ab0MtFn84RmZ9OLDyjlt3WUpjYXIUxVZo3Io6Rc0FohacVkdQGoKvjitGiAmpI45cLU/U/KfvF6SYtaWWHKp/22ZEJ9viWj4lRRFEVRlEbnxn+N9wbSNEKaGiALQtPtY/tDaUPCL0Qsgidlp+IraDNjHxfQVkBIdQnaCYjt2PTRxh67emUJUyjrCxdFofbOI0zzuhITqNQ+/UxFeKVVTk3nJcLU1kGqdyga6Pw3JduRc8cKNl5nu48alNrSsP+uOJuH+kvu9/Sm5cKPXCaoE6H82K+tLT8Sxj5nNXSOe3VhlZP6ZOhZqi2VVqZNVZwqiqIoitI4/PIf4z3BFRKmIRERE572c9a+VERSsE/LzjOwy4qIhtKEfI1NMQ6J6zzCNZaf+1YpdszPhYoVA9J0Ui5KuD2pDO9zQCDFhGl9qpiqU4a92MUUi/TIF15mcBq3VKhJ5wN5z6f0Sr5HL8gkZApuoO5JAiRGrre939PuF6d+Iz0t2pZbWyR9yQBri+nVeGlZdhq8jcC6Mkhk1EWBk9YjRDcEWssqyoqiKIqiNAHXPTMe1z0zHtf/Y7y3XRKm3vRVkIE23y589gQv2QdAHswzPCGDugGQN8CPvLLsxiJoUuTN/pfEupeWloF0GaLYFrZVgihIBLGS8DSCD+KxBekHbLtXD4T3Wdup8mL1Svxpo9Kx9fqfVMeAv3mRFkGSIqHiK0nXOXXOoDL/Un2d2UmlQ/re0NB2+oxVHuXkCxzZSKp92Yip3V5bmt5rp/na+1BriuUFk9wLflnWJt/fGqb0AgAyvrvq850GAKeddhp69OiB7bbbzm1bunQpRo8ejcGDB2P06NFYtmyZ2zd79mwMGzYMQ4cOxYgRI9z2mTNnYptttsGgQYMwYcKEXFVScaooiqIoSkX84unxTpSGBrb2cyGpu6esQAaxfJAUFCzcdoaNUNRUHPjz/IHBW2gwJ4nkGJIQie2jvkv28wgyTt5pybZuhSTdXlJ66mdQaEttG0gX9C9yzLPagQsXWi9qu9J7lCV/7T2TWVHTSuD+SnaybIaiq56gREC0knRVpXtE6Xb73u6j95CGjpNhLypQDRGodh99b+9FtdODuRDNqnvsgpICnHLKKZg5c6a3bcKECRg1ahTmzp2LUaNGObH52Wef4Xvf+x4eeOABvP766/jTn/4EAKitrcVZZ52Fhx9+GG+88QamTp2KN954I7NsndarKIqiKEomv3jaX2HXi5YxsUAH+nT1TZef2c4SG1JZUhog/Sga915Iy8uWfAp9lqgkTyxqmlVU3nKk6cNSGdJxDKVPErbaamm7nT4Zym/TiOUHjnmm342kLioVKvVp75gd6YIEIIushPyn+U1AlHFMadouLcu5nZSfXyr5CZSjWlTsGdRNsy2Y8iJH1Fe7iFICMs2WfJZEvCdcWcTTin9P6Ar3kbrvI2bb9eF0sS2SdSGy9913X8yfP9/bNmPGDMyePRsAMHbsWIwcORLXXnst7rrrLhx55JHYYostAAA9evQAAMyZMweDBg3CwIEDAQBjxozBjBkzsO2220bLVnGqKIqiKIqIjYwCQKGQXggmKFBL22hEBSwdJSZK6bbQZwuPlmaJUlGEJfWb8heLaIXS5bGZJZorITMqmTefCYtUeoz4FMrYRYk82yVfpIsYfOqoc9v4+W26qIjP2d7chhVQ0n7vvBHKo2KR+pzHFeme3NTqugKJU451ApTeF+rZAhGGzC8rPBNT9yoalJYQLotia5uv+uvVITBV17aFtWV30ONtd2V9V9D+2dJprIs0WSxevBi9e/cGAPTq1QuLFy8GALz99ttYu3YtRo4ciRUrVuCcc87BySefjIULF6Jfv34uf9++ffHss89mlqPiVFEURVEUAOHoKB2Yun1I7wfKn6tomgxBaj8jY1teUersC2mp/3yb9J4jPaLCsxPJL4otkj4mnusTYaV5gyvfCmXFyqT2eF1TwogoHEkgeX3L+PuyfJDS1GeMniXYLXmiolSk2TypKCSxLYmoLNsWw7YlkIWp9z4g2EF9MWmB55VvLwCYtE/2ggWlmABVAFAoT8ENLXRE68Yjp/w4GVLZ1L2kpDGceUHkry9R1xz55JNPMHz4cPd53LhxGDduXO78SZIgKTVgTU0NXnjhBTzxxBNYtWoV9thjD+y+++719k3FqaIoiqJswFhBykVkNDoaEafSwkVAWmiFhFdsuzSY5BEpl5b5SwkNTunHUFQlJjyzonrU56A4D5Sbq7wcQitrYJ53wC4JXqmfOBEj1TVwQYALuOCxiL2X/IscH7qfiyFpWjr3SRKKUl6pXFq+d1zZFNwsQucR38/vvQz5IaZhx5O2FY2Q23pXF8oR1ASliCmApCQouYD37jVlFyx4W/KosiRQiyD+0vStRJja77pK2WyzzfD8889XlKdnz55YtGgRevfujUWLFrnpu3379sUmm2yCDh06oEOHDth3333xyiuvoG/fvvjggw9c/gULFqBPnz6Z5eiCSIqiKIqygeItaFR6Satuxl42T1XpxRdX4XCxS6f+Zi2WRCmwvDFhmsB/AUgN5G0eL2IMuQ5enoB/fHDviQ4hjbc9Ig54/UK2Uo/zgd++oXIrIW9UM3UM2DYvPeI+SniPDwnY4f0ub8Q05Rt7H+ojoW2hCHglfYSKQS8iTV9J+kXPV+63NGU/tVAStRuoD62LW0ApqROpdJGk2HdE6F5bWgcpLfXP9YnY/9Yyr3c9cdhhh2HKlCkAgClTpuDwww8HABx++OF4+umnUVNTgy+//BLPPvsshgwZgl122QVz587FvHnzsGbNGkybNg2HHXZYZjkaOVUURVGUDZDr/1G+n5QLNjrAhPDeYiMZoRU5pcgetxkarEv5aZlSGj5gjkaAMsrhdnPdtydtY/VMtVWkHSQ/pPJ5fmnQnyWK6kslkVapbPs+NK2XT18N4Y4P7WNC2aH3EtLiWl5ZGSRI37tZCVn+xaashmy5thbamU7VTvWNhN07TD7H2qOQkIgmAJOU7lklAtcuwsRXVJaI7ef7rD0rlN2HvJ2qhbAuosDHH388Zs+ejSVLlqBv37647LLL8JOf/ATHHnssJk2ahP79++Oee+4BAAwZMgQHH3wwdthhBxQKBZxxxhnuETQ333wzDjroINTW1uK0007D0KFDs+tjzIZ93WD48OEVh7UVRVEUpSXzy3/495YCabEgvQ8JQ2lAmyUEeZqYULRw0ZUSw2y78zcizCQf8w6MYmNCSainoplC+0F4z+1k1UO6WBA7HlGRXvofa5Nc4lHIk1vY5ktWlzYitisZxHNhmreOsVG1dKFCKiPLTyp6ef7YMaR+FpmwTF3kEeyFHutCRaC1z9vBgDyr1LDnmpa22eeacrtSHWLQCCmtj7Rg2ogBv63AcvPTDW37bYbNfnhkxfl63/VCs6oHRSOniqIoirIB8UsSMQWyRRIgD+rAPkvRllxTFANpLVwQ07QhUeqlyRB3km+VCDJJYHvpWBum2k/wO9h+OcR81nM6Y/B7LT3fAlGt3CKT5V8X0R7rT0PKKEhtXEnZpcTS/a6h488Rp7UKx5mnpba5qPPuxyTv+XZXB7ugkPFt1BbL4q/IXihnSy2qZExJgNpy+UwE4b7TGLHvltItrmmBzBX0OuqD65tWUg2HilNFURRF2YAIRVikRXpCojQkUN09jWS7REoEBQbePHseUSr6F/FFEjN0oM4jVLFyJF8BP4LL2zBrOqbdFxSNBGnV4pC9EPbYSKKZ399Hy+HiIEYlg+k8acVoYQOFaX3tJKk35Xaj90s6gdaAiwkxeETUmPTKuFKE0VOWRHDa/7WmLFCBOps1RV+gUhFO+w0VslSkSkJeupfU1kM67xLWAUXRTyuzjtq9KVhXF3qaChWniqIoirIBIUXW6EIpFB7piYlAbiM6XiJpsiJ/KVEm7AtFL0PRKtElmibxBWoe8kR+uRiVorqS6KtUmNaHPANcKtZjEWP7ORUpzbinMCRwpeMnTR3lbSc9ymV9kbAPkv9efXMIVbqvaOTt1rb9z99T0Uqn0VJNmqC0YioRhLbMmtLUXFumFat2qq7N5qbRUiHK/ot1LDlChTI/N/k5YAWu931g/P6qtBxUnCqKoijKBkTovtEqKjYCaSih6bwh8eTBojoxv7xt3L8MPyVhmneqcZLIUVPpHrhcwjTg6/oSptKzIkNR9DxkPe/VKwcl4RPxMyRwgz4ydReyyy+4hMSqdGGmsZD8r8Q+b7eUuCvttwJXejSLi1iasjB1fgltUjTEJvz7QIE6MUrt0n0GpUWO4AtEKoZD9XTPWSVqWTx/SFuEbCWQ2znPxaqWRGuqC6DiVFEURVE2KPggPHgvJBsMcrgwlaYFh8gjSj1f+L48eSLCMMunWNQ070BQWuwmSQKiWxgs5xWmIbznTwq+SxcXbL4QfLpltHyeV9hG94XKo77ZNrWrvUoGs9qI9v/GiqryMmPPV6UCjgosKi4BoT8INtw+nhYsYkqmz9rPCcmY8p/k4T7bbDYqLa3g6/lKfPam87J6WHtJUl69l0dOxYtkkPuV9VFqb6V5o+JUURRFUTYgJDEYEnDR+xYjwjQUraLTLPOuvOvti4jSUGQq8/40gSyxEUvLF9Th7UR9C9mTjse6uq8sJYIbUE6W1ssyHTpW0gWVoon7GmprI6QJ+Zl3OnjWNvoxq424uOP3cdttRVae12dKis0TgrwcwRlrh94XWomAtwJVajPrQ2gVXip4qUCl3yniBaQEXoHeysGlN3RRJ35RpqUTEu0tGRWniqIoirIBEYrocSRRJD7wnrwPCQIqRKXpw155bF8o0kh94GWGIqX1HcTlyRe7X5cOrCWfQgI0NvDMErp5LyzQsjihiFRj38eX58JIJQJPysO3ZQrpeooXal88fkSYWYHI+46NoFJhav/bPFxscRFbRHnqLVB+3miRl8/8Jm46IcntAH7UlOaR7p2lkVu6cJK159rJ+AI1gS9CU5FzAWtH6qetTcRZWlu1VJwqiqIoygYEF3QpURURSDb6QcVoSORkCR9nm2/LEHJSHULl5YmsAfH7ECuOHJGyY8I0WEeSV/I/b/Q15FslA1lJsHAfpfQx0UP9i+2zhO6njd1Lyvul+GgWhMV3ffGOGbuQ49qu9KFIRJf9H/KTT8/28qGuvlycGgAJEYpO8CI9vdbZKb3xpgKzdNI9qHQfnTZcIL4YlBdNotHhoilfsOI2aRSU308rPZ/ViVfbbiWjofOhtYrVlo6KU0VRFEXZgOCPNcmaPhobHNN90mNMogIqVF5EmHF/JP+pnRDSNFEgLXBC+yR7Ut2p0Jaoz9g4K0+eiwJ58oeEElj98t6DKtoKlJ2HIos48gsJnnjO6WcSeF8feNuExDAVdl7/Y05I95nGztUkUl/qm7OblBdBKhp/9V0qGmn/MCQ/nQpM60vt1RbZir4lX2oNEc1CdDXUL6x93gb0Ak6RpOVt0CrI+I5piag4VRRFUZQNCCpOgbDYkz5LI/bYgkZeViZ6QtN280bVnPgL7Ke+pewI20wkvbXFBZHkXyK852Vm+R3zIVRualvEbqw4UZSSY5c6RsyYTUOFQ2yKLi8jL6G2qO8jdbKOR0y0h/LFpgZbgchXuQXKU3AtXkSSXLyRLsjQNneLFhE7Li0pj0Y7wcShi2TSaCbzlwpKL7qOsg3+fNME/qtI6xloL9s2dEEs+n1iz08nUBOgitaBtKHSfFFxqiiKoigbEJKAksQpX9gnj12a3rObyOm47ayoKU0vCQFKruetBvzgUNGQJ2+eetC01EZDB86SHXFbTt9ioo0KEVqYtABNfYhdCMhK76aEJrKgDGnMWLvEVuGtbx25ILOi0aAu0miE8yUBmYJbEls2ullgx5iufFuw5ZQ+W1ue+ERazFFRabPz9zRvuXLpOvKIa4HUCWR7QurG25kKVD6VuAgyzZm0a5HUG6j/8WqOtKa6ACpOFUVRFGWDImu13th9pHmQRGlW/ljkNpaWfrbEnpca8pfDI02JsI/nj0bJ6Psk7Zv0Oa9IjUW6Q+WG0sf8plBxIfkQCS6mywgcvxAx2+KxZBnEqBzxJVjngDCNXQyQypGml/Ip41bkpe6jTeCm63rirbS/quDfv+nNUiCC1Nq3opAKYjq1VhKT/H0IUbwK0VV6f2joIo/Fiu9KHwHkHSPaJq2E1lQXoHyvcrPkgw8+wH777Ydtt90WQ4cOxa9//WsAwNKlSzF69GgMHjwYo0ePxrJlywAAxhj84Ac/wKBBg7DDDjvgxRdfbEr3FUVRFKXZ4QaCib+QSiGpG9jabQWQVyK/6KDSbS+U7dEBZ5L4ZbrBtiDIpHzuxfZRgsI78spqo+A+oRzJJ9A0AWEaagdet5TYDJXFfMsz1dWQF90mpssQfNQvb9EdfiwzhGnsGNWH+gpTtz/QZ3m/lerp9V/a/5E+V6yv7l5NU75ns6b0WlMLrC0Ca+3/0ja6vdY4TZo67/hnoCyI7f2mPGIqtqmQhkdK+bRe6XhIEWR6LtDVflPHBeljF1vMaV2KOdUuDadZi9Pq6mr88pe/xBtvvIF//etfuOWWW/DGG29gwoQJGDVqFObOnYtRo0ZhwoQJAICHH34Yc+fOxdy5czFx4kSceeaZTVwDRVEURWleeMIyCYjSksh0r4CozJOGDsr5dmmALIkqUQwmgTrRNCx9SBRBSGd9Eesi1M3mt/lSAob45sqD7wv/TOsXqntW3hjeFE76svsFEcpXa6Vl8/bIgvcZZwthG3yftHiOJ/4izjSWRpH6XehF+yo/F1N9njhohZkVqlRI1hSB1TV1ry/XAivXAKtq6oRqbWlFIN7GgH+8JCEpCspI1DS10q4Vx4E+wbfxmQr8OyEklEPntS2fryq8Llnf2iXW12Kv5kyzFqe9e/fGzjvvDADo1KkThgwZgoULF2LGjBkYO3YsAGDs2LGYPn06AGDGjBk4+eSTkSQJdt99d3z22WdYtGhRU7mvKIqiKM0OOpCzorSKvLdCkw+mqwp1r1AUVRp0p8Qq2IBceAHhKGEo2kYH8zxClYpqSWkFuynRGHnR9Al7L9mk/nn2hVGjFPXkx6bA/OeROQqNaKW2pYvPHNDT/VQAeWmYkVC6SgbNsbQJ+R9qV6lNg/Zifcj+p/2a9alQ9NT+ly6s0PIAf9ptbbG88m2xJE5rS5HTVTWl19o6sbqmtrSfRF5rTboPcEFaK5RDfeCLJFFiCxtltXdqwTTIxy9GbNpvViS4oah2aTgt5p7T+fPn46WXXsJuu+2GxYsXo3fv3gCAXr16YfHixQCAhQsXol+/fi5P3759sXDhQpfWMnHiREycOBEA8Mknn6ynGiiKoihK0zLttfHunjSAiMnSpWo+EKSDZbvPRdUgT5OjNqT7EhOaUIAP0EOEpvDy8rhPDibOqJ2sxXRo/ULlxPzyPku+CfVL1Smj/fj72DaKbQuTkTYp/eF1ppGySqZRVqg/chGKAOclSyAl/H+STitNY5UEku1rPC+NUAPpyDa9j5Ou/JskQFKKmtrFg+x9pvzigOH/iV1bv0KS3i7VUSK6wrGUvvRHavOsftmcaEztEqNS8d7caRHi9IsvvsBRRx2FG2+8EZ07d/b2JUmCpMKjMm7cOIwbNw4AMHz48EbzU1EURVGaMzRiA/s+kbdLeZJSKMcNkNnPbyoaRcRsal/Mz8hOvoqwJAZ5GaKwENJ5+4hAzfIzjxCN+UkJrTJcqTDNQ+ixGnkft0Hbv9KVdbmdxsKU1EslgigUNZeOa+y4idNX6YUMyFE929+yGiJ0H6UVpnyl3Jpi3f7aYjlfkgDVhbqXPWZUhJLs5f+m/LxQ6680vZtXm29OyMZKBVUiGcyTrxHKrg+NrV1itDJt2vzF6dq1a3HUUUfhxBNPxJFHHgkA6NmzJxYtWoTevXtj0aJF6NGjBwCgT58++OCDD1zeBQsWoE+fPk3it6IoiqI0J/70+vjUvZ2xqaixAbk4CA8hRE8rJWsKqOR/qDw+xg2NeaXBrHS/XagdqS+hqC5PL07hjVwACDVnJc9yjD0epRJ4dM+zGckn7XORV8EWJ880YiC/rglepEnSx8vtQ1qcuvLI1Rn32BepH9k6m3T/kuoi3UPJn+Vp790rsu2WqsT3J0ngVgMGyQug/MgXkp8KU1onFwVG2sfYRSHnAwLtXEHfpDMA6pO/Iah2aRjN+p5TYwxOP/10DBkyBOedd57bfthhh2HKlCkAgClTpuDwww932++44w4YY/Cvf/0LXbp0qSgsriiKoiitFXvfaGoBpMS/VzSh29hnaQEbqRxv8RViJ+ZbyEZMmPKoL1+8yKalr9S2JL0f1D4XKKS9UvkFW56PGe0QLVvwL5ZXshWMuFLBIYgez4cMMUgXtXGinqTNirCGLnxIdZCObR7yCNVYdFo6F6pK0cgq4Z7tmOCyU2Wlcu3bWJvx+1X5gkTuflFShrQSr3T/stRO9F5TKkwN0kKQ1zt0vNx+KX0lB5ZAVx1enzSFdqHnRt5Xc6ZZR06feeYZ3Hnnndh+++0xbNgwAMDVV1+Nn/zkJzj22GMxadIk9O/fH/fccw8A4Bvf+AYeeughDBo0CBtvvDFuv/32JvReURRFUZoP0rTDWLSxwAaIUjSK3r/qoiV2YGvq9ttBLI0KSuPFvNNCRdGHdN14fSjUT1c/Yp8vFsTLt9Eh7otUXmiAzbfzFXltmlAdQs0VOsYhqDDIc28mbS8bHQPSbeYECLFv6xgUvzFhSm0L6aQoYkOQ+ioVXPYzkL6QUkRd9IdHfqlwZzNw3T2WYiRbikQTUUqPIUxZFEvwZ47aC1VuGi85Ti5qyto7NJXX+QYySzmhH8o+ePVD+pg2ZJo4JyT+18XCSKpdGk6zFqd77703TKDnPPHEE6ltSZLglltuWdduKYqiKEqLYvqb46PilOOtOpqR1gkRp0bK2+2g204fdOUG/Mw7WJQippKPwfGtIG6S0AdBLFgBK0V6pLT0c9YjLaSoUUzUx8qrBG8AX08bWSSh96H2EzbyfFT7BEVI6Y/UfrzNsqZE8+PCV0qmfocucrgyja/bvEepJET8hwSq4AsK6f6SEu5sH/fNRoLphSYLXVTJ3asqiWrrG5lf6y4ABdLbfVLzc7EqieNc07kzjm9DaQrtsg6r0yQ0a3GqKIqiKErDkaJydJ9FGiBmRt7Yf7qDjqmz7Lj78YTtziQTbu5/hihLlZ01QPVG68wWsRkT+8HtSbp8ejHA5o1FS0OiNVSmJbpIUM4RrhM1pvw5JvQls9ELAzn38QsURnLEUtqXxxebnHeBBOl6pVa9DYgjSfh70Uq2z4rp3FclSkmriD/FUiVCWd0qvwYoCt8JbQrlol06U/bb2PckEkvbLU93ohFjIP2f+sPtUXFs65M3EBp7VmtLg/fL1oCKU0VRFEVpxfzlrfG5ppACYfGTRUhIVbIwjxcpyrBt7WdFgmPCJssXIO4PF5OV2I9N/c1jN3XspKmgOcrlZUj6zoo+e6GhPlMhXQQO6eMlCsZQf2I+S6JfdiCyT4A+SsiKUOlevSIRRFIk3W6n6TxBXXrvygM8YSo9ukV6piiILbeIV0aVrei0ApP6XSCKxy1slABVpG3o/1orcAWBmJDttA+5vsTPYcFXO/04RkyEU19agyBt7ag4VRRFUZQK+L8Xx3sDTEkw2O2xiKXN42xlpLXw+yX5dN2U8BFEaZYQyj09NoPYVGBxI0svCSEeMeP/Y+XmhQprKYiaFeGshNijcfJEYqXPnJTgBFL9NRZ45GV5q7vmKB9IT8uUhGnsQgndxt8DRJxJBKLybncg4pk6HuSze7ZosSy23OJIpXOytlj3OBcrLu1iSfTe1CIV/0Ro2kWL6IJGQf8hi8ZYfW2U0/odu6BRlfjfO5aiqatjUhKwsQWIbL9JSo0p3Vsb6ku2vTyBj3L01LUb6ZdefeGf062N1lYnFaeKoiiKUgHS/ZhAWPC5QRdJmxIHAaErwdPzAV3oOZmA73PoPa8PtSUJtbxIeQ3byAfoMXEWEqgh/1ID1kgIhZbNB7V5BDAVYnlWCw1e6IiUQ/fxaYpZ4lG0H4m+Jvx/wCf+3Ey6LQYvK+s8EMs3gT6G9LEkWZy9vFOeE5TFY02xTpDVlh4CyhdGqjVlcVqVAG0AFKrS5UmHgK60y8VpSpibsk9Zqy3z+tC0sX5rRSoVsrXF0udS/RNSvie07RtSUTs9mF7Ey+rrdpEpWu8YtC2oQFWaNypOFUVRFCUnt780Xow+Wui0uARMyBIhkRJONk3ALh9087RZK71yscLTZUWs+D7+Oc94TxoYetEsA1+QBiIrku+83fJEEqJpAkItb4QwYZ9jApWL31Aa6hatt9hmgtgK9SfnAyD2PSAu3rypoEi/l8qP9XXpoo/kD8WbeszbkolRLuhdUrad2rb53Hlsyo8qWVMrtw19lEmCuqhpbUm81RTKQrKq4N8ravN4opQJPlcHUq9YOvddxOpofQOA6kA/jR3LqgIRpIkfyTT8+474bNMkBb+MWNSVrirMpzrTOsXOI3r+tCaNmuNrqUWh4lRRFEVRclJFVsIMDYLslL4CgEJp8EUH4gbkKj7KA0dpxVk3iKJRFpI2JJSlz7FBfkig8nSh1VAl4SkiiAoqjKwdT3DxekhmKxCmeaKaldigdsQIUKRduC8FkpfXiYopT6h7jpMyiR0u9mDS+yTxD54vUg+uj1O+BcrLEqN5xKkV4zZKR9uMXgDh/cszI0Qc6fRXd4yryp9txNSQtHTxIBs5LSRAVRGoLdR9trYLCdCuGmhfXa6XKZbzepE/K3SJQGPuB+HPLy1Sf4tlYckXd3LpmXHrB+3v9DvJe64q+e4xqGsz73xJynXj5dPjZlcQLhoSiWXkuXhEs7aKKGqSv94tBRWniqIoipKD218a7z1eITR91kVNC+k0dKBs9QMXpzadg0WCeLQ04XlJmpgYpdtS4oV+ZvuI7vGjwQlSwiQ19mMbqD06mA1GLgUfqUiTBmmxac5ZUU0pfcgO9YGKI1NBOV7bWltUrJr48bLtyAVZSohJ4hPp9ss7PZn3OSkSzI8dbyvJDiD4HnPCyOeR3eRW9BWEnRPtib/dmJKAA1uYiBVv93vCrERNsW7BoFoDJLXl7dWF8vnbpvTeThf27qUk5Rnji0uvbqzegL+YE+1bVFBb0WiY0DFCXaz7BbKtkNTlpd9phrS99cE9eqZ0nKpLF/vs9Gi3v5SfPqoG8IW/912TlP2h21uVCN2AUHGqKIqiKDlIDfiQHvDZdDyqwPdzEZK1IAnHmzYcKSdli/oovI+VyW1I6VP7+KAw4JMnqIiwkYSw5GtMWMX8pWKGi6/QI3Y4dJp26ljYthUGxyGh6/IF+paXRsjnpk8S8ZLymw36uV+0TEtVIlYjGP0M2eeiVBKnkq1MAsLTKzspizEafXS6tPSGihoaOa0plv2zAslNpyW2bAWsYLJ9vMj9McDaktpbk5QvYlhxatuDTtl1fhHhGqwve3mRyZJ/tt/b+iSkb/DmdNFo+HWxkdTUuYxyHfhsD9r/3f2nQjmGlEHbwV4I4L659sGGI0o1cqooiqIoGxhTXh7vD5jhX62nYkKarhiNRsIfvMWg9mLiNyp6AnlCSFNYuYChA0henuQ/hQ5m6WCUC3huL894LKt+CSkw9KgK6TiGolT0sxM8KEdPuW+hY5eQ/bF7/kL1KiTl6a2hOtG0ee2GplJWKippemm16ZidkCiTIp+8PBp1c9tI3UIClUKn8nqPiOEHvPS2ulAWUtK5tLZYFne2PGuzQL5jJF84npC0+cmL9rcC6vqIXWTIPhfV1qWA9HRtbxq+/UxEIY30U2eMKU1Tpm3F/KXPfaXHxU5vtisb2+8YqS2sj/wRP65N2PmmNE9UnCqKoihKBnQAbgd59v7AkCjNmo5IB91WGPEpdVJaT9Qk/jYuLqTyQ5FGQBYqHMlXO1C1+6QgVtb9nd5gVyg/r/AB5AWiUuVKhgPpJMEU0gkJe08Fj83LbaXEKRdsvIyIKLXp81zssGnzin5JVIT6PO+DoTxeRC3jnLGZpZVu3QeTFj1UiBrmjH3OJz+efJsVT04c+UWWI6am7KP7noB/PHj0r4aVi5K/1YW6FxVuPCIpiTRbXkJeMWik0UZUrR0aiefl0w0JeUnQSLPNIC0OZ1CeRu1tM7I4Tdjxk6ZV03rasluLQI21eUtFxamiKIqiZGAHlvYeKSog+BTfmPiT7Hpik+4UBIOUTrqvNVQ+3c6ns/Jppln+S4KJRqHoND9ankUSqylBY/zteeDCNFPYBS4C0PsmxXaJ+G/z830hoWvLoMdGSiv6HyDkJt0eEpR5bPAVoGMRUEkQSuk9IckKdeJJ2O5sOOf87W7hHciPufGEUCRqatNKMwRiItEKMSfOSHp+nyqNmjrfWRtwwZk6Pvy7idWHCski2eem+MJPB5afHk/v+NE6M79suxmWj76nIpS2Z+qY0wsHTFi7lYAD33/OXitSdJV8P7YEVJwqiqIoSgZ2kFdN5thxgcGFaShylSVMxMGbIECpXyFbIWHD7/fi+aS8QHjAxweKnqgKKBypfbKmBWflp8VliXRaBhVqQHpwGxWpEKJJzK6NEEn9Ina8vHQZA9CUXSaYUn0BsmD2xF7ALzu4p32ILurF29P2EbpdWqHaiVagboEdJoZs3+JipSgdL+E8omXZ8qh9r47svy0nC1c26/dJ4kcPvXsomcByPhj/cS9uP2kLCSq+pH4stR9ffMi5bvzPUuSSil0XoTbptrMrFXPRS5uKruYrlev6Ejvp6MUL63eqvrQ/5jiWStOg4lRRFEVRMiiQQQ4fUNNBGR14Z4m7oACIiC5pGm9ommhs6qe3nwtCVo4kvCTfbNmpMV/IgDA4pNOCOTzilRKCXKAg3TY0vfeZ/0/SbsfEYXCXFaXEl5BYCh1fqezYlF0vLz2AzH5KQAaEKN1G21kSmrRL8TwhMUttVpFtABFw8O+PdC9ykAwTI3aX6zel/1T81BpfqPCFdFI2CHnFTeqCRyCfdLy4KJNsSj7RNud57HvXF0lb8YXZ6KJMtp0kAZ2gdGyoMGWCm0ZEkwRu4SVeH3q/aGh2hfWdllNbFEQr89UK1tamS2PfzS0RFaeKoiiKkgM3GErkaCN/D7ABobBN2u7KCfghrhQcKdfmie232yS7lQx8pHvIQtGK6CBR2JG1cE/oESKh9k65mTedkCc0/dNNeYXfvpLNULtnHcuULV4PItzorlAfDtmL+RO7X9RF+Ihw4pHWQqHsB7VH7zNMUHqECnlZUZp6j7LQ4T57q7wWyTEUfLfprT2eTqyvcO7yfm/7hF20yopu20zuvSmJ6aR8SwG/uMSFtfXZth9N66LSxLcq6wCrDxV6oXrShqBC2vpAxabX7vxCE2lbekGCpqE4YZ2UnzfLHy/Dv4toRDf2Pag0PSpOFUVRFCUDb1Ve+558ThJ/AMjT2s8geek2UdAJg1wuXuorSr1kTNTVV5hyW6HpydLg3ru/DOl62LT8HtRYvST/8wrQENIxpNt5lMbAX8xGtCn4xe1Kg/Msn+hnaWqnJIhjeaUyU+dAaT8ViFYM0brQxXokXwwxYgWZtWEvELnIHMnjxA15zwUqFa2ubFqvkjKkfVK6J5SLPE4osmrrQynS+rL+YoWq3Sd1FSvUuM8J4D1/lPtgX22Iz5LbXkRTEI+gbU7s2HarNb4tWjdpYSPv3lThHEiSuu/kWsFZLpr5dwxt39Yytbe1iWwVp4qiKIqSgR1IS4NxOmAUH/sRGdzb7anBBQmjGJYmQbpcaXASe9SM5x/8yFpIMPN8oQVgaHpp7EdFpiFpJRvSokL8fR4RFfJP2u7KDuSTkKLeVujExHZWBBvIXkE5Vl9AjtplvZd85H0u5C+PTHlCM/GFUepYJ6WptsYXK9wfg/KUXK8Ma5P1G/qYFJLU+0/rQ6dj0zxZF1FC04Kp/xDasLzTt2M3e9OgA/54fpB6OZGK8kJHVeSYVSXltuZT56sKddtrinUvU4riQkhLo6LWN1s+rxP3FahboZfWy5AEptQQtv6SKJUuLHj33oJsa2W0Mm2q4lRRFEVRsnCPjxEEUUhkULJEXyp74gtGm48/qzAkSun+PAKVisQsUSptj0WJojsyBoqZ7cr8zYr+SW6EjosdJAej2/AFhB3g08ExFahZPknHi4sRL31G3S38HmnuA7chfZb+A349XT7pGJA24SvIWgzKjxCRopRUSEkRUdv+9jypK6wkdE1ZfNkIoLeYGPMjhBTpi53/qfOClFkg+ekzdq2ITFDuf4WkfD8ub6vYKWL7o3u2q6mzUVsq04k3dhGlQNratVVSFsg2GutW9w2I8dC9utxvw/ZL/rubjkkee88phfc3aTEkm7+1ibrWgopTRVEURcmA3yNHSZJ0dItGiABZIEjRSm8f2c7FRB5Ryn2RtpFgh+cfn1JHffD8RDodrYOEK7vC0SEXaTFhiYx93BeexxYkRWoln4BS9KiUjwqfIuR7H3l+epz4RZAsYcrt2aaNXcgQRSZLJ0Xf6SJGISFHFw7jziVJXUTOijN+T6L0KBGbz5qRoopcOFYlQIHYqzV1kT9bJj0PUv6TMqyfdJ+toxVCtN1T91VHonzixaDSq5YJU/q801obZSRCW7JBhTutl21DGlFO3csK//jYNO4e1ZIP/D7TGK7tE78dvTTw24QK4KLxBbqtA293bo++MdK+Fkzo96Alo+JUURRFUTKg98lJ+ySR4UU5pUFwYGBc2hXMG5r2GROiofdcJLpyBGEnDoAiAsVFlgKVdNPwInnFsokA4QOzmEhNbc/an3PAR49/VVIXlbLHHwBQlKsp+W7FSEDXBYkJz5AIk4S3F6kXfJEuXrjolSDEpOh6Ql+l/W7qKROmVHh4opCcY6l7EWm/SFCOnBbL5dJ7XqnQ5tFV6wOHrwhrI5158NraOBOpNFUoCzW+6FSRCDTXfuzYcX/d+ULyePeogkVw2UUD6puddi11bHs8aJ7U/cGm3O5g2+sKSUdQeVEVCVNopLQloeJUURRFUTKITeuln0G2Z0XuqA1JuNp/IeEREsVSJJf7mpqGafw0qc/Mlk1CB6iiAMsYDcb2S6LTIFyPrMhmpb5xxKh5IJ31zU3LhCzcJOGXx0cpX6yvhNJb+MA95lvoYgSdrimJI88fei4lcALeEz4lakMCFb44sdFSG2Gk/ZI+wsTeR8nPH/sczlpyMYEKOamefFosb5+s+xtd36BtRPoNbU/bZnwxJyf6DILnBoeKQhrlpv2AP5MVZLtrT2aX3r/qlcfawrg/srgMRVMlQRqKatu0lqyFyVoyrU10qzhVFEVRlAz4VEcgPgCsKGoV2Cbd70ijpVwE0LJigk0iJWoiojS1jfgYWghGspN3oOjVk0dwhPde3hz1lyI9EnZ/5qNcAvZp5ChLlNrtecU1bSN+7EOik0ZBJaHKBY/oA8oiylsIiZQVa1Z7cYNe5EiJ7VLEs4i0+Kgt1olXe2zaVsFNc6XRUC5UqgrkgochU3/twj9ItwlfpIj6atNYe5SULX5e0zZAWYhS+zaimYpglgoQLwyB2YR8LKkItv7ZhZNo1JRGtQ3JW8X9KRVeQPickrqUdG4Y9j4mYj3BKpRNz9+sc71FkcjHNYvm3AQqThVFURQlBzYq4InAiFAJiQMvTcSGNO0SkKd9ivYidhOWJ4+Y5HmpIKGDVWeTDZpTg2MmZGP1z9pWqRiXkCKjlkoGszapvS8w9GihvD5kRp/ht3tUiAh+WHFC4dOxafuKiyAB7vEuWfWk93zSqCFd3Mbzky1qZEU+vxcxQSnqacp+UuFqqS4tqkPbmgsbLsD4Z9omPD8V5dSmJFClY2W32dka1t/Q/biewKdtl6O/BUUiE/TSucxFtfWFHkOaPrGiMEm3dV5i03djwpTSqoRpK6WQnURRFEVRNmwKbCDp/QcZDJZe0QWU4OdDwAZ9eX4gvV0a4Ep2eX5vgCy8PL8FUeuVw/J45TH/nD3STqE6B9uObKN1ptDjEHqF7HM79D8v05AXkBYQVaysmC9S1Z1YEfZ5vifycbEL2diFiKTjD6QFlhTFs9usverSq02hLnLZpsDKgV8GjVCuLZYfU2KFpI2GWl+8x6gIbVZF9tWWBGlNEVhTC6wtvdbUAl/VlD/XFOv+1xb9xaoSYstr20j/kS440dVu+TlDocelugC0qar7bz+3q6pr0+pSpNcKeFGgMruSf+I5TdLw+20lpO+40HcdXwhO7J+sr3KiglTYJqYN2WglQpV/L+Z5ZXHaaaehR48e2G677dy2pUuXYvTo0Rg8eDBGjx6NZcuWeXmee+45VFdX495773XbpkyZgsGDB2Pw4MGYMmVKrvqoOFUURVGUnIgCNfHFgzQATOVN5AFaaJBn9/HBnFeO8J8LTwjbuAhJ1VcYZNuBIfWH+8FthPbnRcrHhRMlJjzzDNJ4Gn58xagX880TCfDf8xcX6aJPSf72o34HhVUpTWxQL642C1+AFZKyoKJTZmkfpNOna40vTOlrbUk4ri1GpoWSdqoqlAWqnbJpBS4VvM42sW99sJFXe89qVdZxoD6QtvZ8KhBxBvk84cfBYgWru/hhyL238IUZtSOKdmZbEnUcvjKuV28I/Zn4mWU71KYcQ/6LdTB+efTCkGjPpF9KmFNOOQUzZ870tk2YMAGjRo3C3LlzMWrUKEyYMMHtq62txYUXXogDDzzQbVu6dCkuu+wyPPvss5gzZw4uu+yylKCVUHGqKIqiKBUQipwC/sCLRzZSeVheKlpCAtUTwhnlp/KRPKntxE4oompJRW2Ecnkeur0+cJ9jhARgKC8/FpIokQQIFWBZUU2XTygnFWFm5Ul2eGSM9q1UmWx/LJptsdE5KvD4cbfTJ/m9nXTqrU3O77utLS08ZCOZtURQegK1tiwe6QI4dEEeK4xdGcxf66ezXZu278pgx0psf+FY8v32Pz9G/LhI7c6x7ULth8QoFddW3PKLEDFhFttn6+rKK8jfKaF6cFt5kO5hl6YC11dothZ9mvrezvHKYt9990X37t29bTNmzMDYsWMBAGPHjsX06dPdvptuuglHHXUUevTo4bY98sgjGD16NLp3745u3bph9OjRKcErofecKoqiKEoGlYiqJEkPlrwBrWCMDiCTBICpG2BSMynhEbAV9Iv5mJUmaCcJ+BOod0PhwjJW79C0W88XyU+pTmxQn7JD7dPwjhBxcvkkf+AP8CsZMNO2sPnpVEpvGrfgNxVSRVIHKgDsY1KcYDZ1+Yu15TLc/cPGz8sv1oRELt9XNHWPS7HCkopbHhmzYg1kH42m0eeoujKL5XwGpXON+Sr1Z4phaWm0J3WPKmuPPOeFXZiILkpk+1A1841e4AL8KcW1gH9vb8mOoZUQyk4Sua1B62Pthk01CNt2kiClvoaQ9pnIvg2JTz75BMOHD3efx40bh3HjxkXzLF68GL179wYA9OrVC4sXLwYALFy4EPfffz9mzZqF5557zqVfuHAh+vXr5z737dsXCxcuzPRNxamiKIqi5MQN7oRoARc2/G2WMOXiyw0iycA2JnKlAW8i7OP5gpGSQLpYOZLw42SNCUX7QnvTfaHtecV2tE4Rn7z3VJCEyhLyS+IbEASOYMuL4Ar9I5aGQsUc7eO2HCtknBAp+uIXKEcnATI9nUQv+X8O32dMaVGpgi+opFVzxbYhL+sTXVTIClOUyrDPCuV2UratUCZCWIooU3HLL5J4NoTvCtfORKxbO1ZU07TULr0wYvfVgrWt/RPoV9a3UD+RfJSOb+gZsVnfAaH9tK0zbQSEKT9WLR3axyths802w/PPP1//cpMESamDnHvuubj22mtRKDTOhFwVp4qiKIqSgR3MiSKBDf75CrYuDYlu0P0hwckHn2DpYgNnT+xyERUhtp8PyutDpcI0JOAkYgsK8TKo6JNsZ05LDAniDB+l4xsU0UTwSkKBCxEqTrzjz8qRFvHxxITNz/alhAm7WMEfO2KScjq+yA4XXFW0XzPRZCOIzq7fPM6fokmLOPcy4X5hUCeCbdl5IvRcRPN99CKNJFBp2amwPKkvFdYg7+m96TQayu//LCJNkbSF2M8j50HWFG46jVrKFyPP10pS+hM6P4uszbldKWLfGqhkBk1D6NmzJxYtWoTevXtj0aJFbgrv888/jzFjxgAAlixZgoceegjV1dXo06cPZs+e7fIvWLAAI0eOzCxH7zlVFEVRlEZAEoMcb/ou/AEzH1DHFrDx8pCXs1vBYCXmtzg9NTDI5tM1M8sVXrSM0AJTko9501L7IWHq7ReEnFh/od7chhQ98y42JKTeTGBKzSrdH+jakrUHF6a8f3l+gm1n9uliO6k6kzJplNLd/0kigTVF4CtyTylIXloPKnDtval0VVlrq6aY9oUTWiyI26kt5uvPWfduitNiERdPvL5UjIcW2Kpix0s6l2LniBWX1HfxRXzzBCr5HBOmkkjNI1xD8D5G7dHvJH6uUCGt5Oewww5zK+5OmTIFhx9+OABg3rx5mD9/PubPn4+jjz4a//u//4sjjjgCBx10EB599FEsW7YMy5Ytw6OPPoqDDjoosxyNnCqKoihKBlxAuO1cuJT+G54Pfp7YvZliesiDSp5fjMwJ++wUx1A9bBopbX3gdY7WJZH3RyOS9fGJ2U2QHqwm5I0UvaTYYyQdg1Q6Jox5uoSWKfjl7om0ZQb85hcspCm/zh4pN1RNF61N5MeZ8HsbRTFCXjSv7SM2n/WRih43bRilablEBPL+RQWR1C68/lRo2Xs2nS8kH03LoX2ATj+V8vOZGPwcofd9hmYF0HaiWOHuZnIkcFFheoxChHbxqcFUCGbB6xYqh0eaua/S+cD940KUtg/vn62B+nz/ZXH88cdj9uzZWLJkCfr27YvLLrsMP/nJT3Dsscdi0qRJ6N+/P+65556oje7du+Oiiy7CLrvsAgC4+OKLU4ssSag4VRRFUZQMpIiEhDcQlewQe3wQxoVslsjh9qLbmDCNIe2nAlUclAcGed7U0tioMoP6TFurVMxHy45cHRCjphH7th8FpwYTwQTITRaa7ixGelEWlTRaSC8+2MWAbDXFiGySjtrRCBq9MTQmAOh0YBrBpBGu2pLiqSJ+0egYID/qxJUhbJPOM3ceUtGIst92MSh6sSkvCc2Y4ZuF1yd0QcRN5RWEaci+FaZFmyjxj0WWyJSm9GbBL06kLlQIfcMEEvN7gkNTeKXzJiaCFZmpU6eK25944olovsmTJ3ufTzvtNJx22mkVla3iVFEURVFyImkULjTomIcOglPPDGSDZfue74v5EBOlUhp+71reiGgsXWwwTP23AjU2KJSixjFij9zJgqfxjhtLQ6N4qbQ2OgX/eFM7Utl56xmz4flKXxE/ePSUizxDXjS6Z6eN8qnpJilH6gz81X1T4oO8p9FAusquE4gGqGHCgwoSG1W0n2n9+NRT1z5MYBti1/ps7XmrFLsdSMGjz9I+W773P6OP0gsFRZDVu0mdbBQ0Fu2ulNCUY7uP3j9shPZvSLmSoMyaFizaYukTYR9/35Kpz8W75oyKU0VRFEXJgA7mgezBgCQ8+fZQOi4sJF+k9zSv5GNWxFRCun8MYAO8CkZ4ifuTLVJD1KceeW3H2t3mDd1fyvPnEam8bIsdUCd8B/vI+xadulvg+0h+unAOX3zEE4isLvS/KeWlK99ykcft0v/UZ1cuETs0SgcgLZpYX+R19vYRgc3FaZEkpMeX1sWJbWKLCtlUXVmUj/aF0H3cqXOZ2yz9oT64aCJRYOL0WVMWlhJZ4o+2SSg6WSlSf+Dl2f28vKyoqd0nlUFttZboaSvTpipOFUVRFKUSKhkIeFEnCGKVpJPsxgb5XKSEREtMzPHoKU0bE6ZSpCqEF1U2fp3ddrstbCbln7OfkSfkS6705H2oiomwr+KLGTxdSWy4yJjdLByTlAhCekVeu40vgmR3Jk6llSNx1HbIfTdVlPvL/WT+x/qLt4gS2xe6zxNg92WWDooVZXRaPhXP3jkp+WzKItxGJ717SQPnLUW6SCFNvabbpXra89E+osdLy/ynwp6KNGm2BBemoTbOc8HAe5ZshtDl28S0QFCYxtJFL2rQtK1EnLY2VJwqiqIoSoSZ74zPJTJCu/ijPWJpefSUbpMWduFpafq8EcaGRCK9e/cCPnoiJyBkU1EiE2/rdYUVJLxNsyJLgC9IC+w4xkSHE+a0fyRlvcEXrkoJNkT6E8lXSICqQtkfPj0XBcAUqUNpoRsSMFbcWV8SK3hRTm+jpNSGE9Mlv4oJySOUw/HSJOUywNqM1iPWr6xv/IIN7Rd5yJqynylo2XlCzwc3Ddv4513qHAJSgjIYOWXHVRJ2NB3fF7PN82UhXQSThKnUF0PCNCRKW4M25b8trQEVp4qiKIoSgYqO2DZAHiTQtFx00qgOTU/tJWSHJAokYSrZqnQgFronNSGGud+S0ErlDwjUPMQWwVnXSINeSSxa4Sd9LsIXGl4kWSpUEjJMePFd9LEsbuAaULC0/9QU/XpZ8WNFbdH4i+nA+HWnxz4hO/gFi6S0rdYAVQCSQnnho2Lipw31eWPkNFaEFlGOEBuUV9/l9XZimogVMTJHhGCkOZ1tV1fh/MzKJ322EWC7nU6ltn1IOqXo43ZCSMI0dhEFbH+WfV5W1n4uMC0xYVpfUdoaxGlrRMWpoiiKouREukodu0dUemYlzUPFR8wO90HcTnaIz0Qt/Y8NyEKDXGvfEwURH1JRHCHqxAffoX0UqV6Sfw1BKjsr8uNdgIAsTg0RFHY7fTSnWGfj9w8ukiQ/iyiLF9pexVqgypBnlBbKvvNnRdLpuQm/KdWWzdo7JRRZZ0qEbZ6gDdTJKzfxy6HHhB4DuwJxdcHPZ0g6utqw9cV+pseiaMri2aur4C+/+JRVn4ZCo8Z8qj0gC8eYAOSCL5SPpg+J+ZAwpOUY9jnLbsj/LIHtbUd6e0tnXfez9Y2KU0VRFEXJgRSVjAnJmEDkn7kwDQ1+uT80Py03RkyANnSsVskgyQmtnIWGhCmPVIWEW56pb1HRTQbDqfs8yfGjj2gB28cHxwVmR3KI9gVev9RFAJQFKt1oB/uFItC2qk60GXuPaUmU1hTLC+zYMgoFf9VbGpXlZTofURZ+1mcnfJkgKhqgtgjUJuVyrZ0isvuG9cv2aXpfZpKkRWUVEa/WL3vRwCa19eHntxPriX/uUZ/B8lAaIlal88Q7BkR8JUgfr1g7ciFnt9WXrKhrNG8gP7VthP98H/eDnnfSPagtmiTfd1tLQsWpoiiKokTImr5LB7FcbESjpmS7JEyBtBDhA/hKabD4lAbJEUdC981J+yV7kniLTV0WPzdw4EYFqR34c/tUmNL/tA84ezaqJUSurP9uu2EL/cDPI22jNugjWux7O33XirPaYt0UWxrxtNNgawWRBpQjwVLEy9qg02qtAOY2bJ5aAyQlX6T6WJuhfUWSPykwcQ7/vm/rl8VOWfYep1M68ayQ5cLU2uOPtqHNtK71QugijG0fLky5OBNFqSQsjZyXlhHyISRUpb4D+H1ferayJExT+5iPdF8e35WmR8WpoiiKogSY+c749PNJIQ/Y6f4827OEaYiY+OLPq2wovO4uskaETAx6byX9z/dL+7x0qCzyFL3nlX0OCcQQUhvzKb10ein1x4vOwR80ez6TKxDcF2GWrTdYD/Ul+5lHQqk4tX7XsD7FL8AU2HH1hLgV8VScJuWyaXrrl93uptVafwN1oe1OI/D2masF5i8XplTwmwQoFoDqUpvYCDJQFum2/EJSF3W24hyoazsQ+5Kf9kNDLpRI5zkVqJLokoQoFY5cwHGkyGSloi6UXBK9lDzC1NvO64d0/tAK5C2ddX0hZH2j4lRRFEVRArgBNBt80/18EAyyTRKxMZEa9aURRiBZA8vYlGArttyzFXPYoGKk0oEgb89Y9fPcpxtMQ/zKa4cLAts2/JFBIb+d8CLqgtpMeAHEP1GoGVkEeHaYQLTRTE+sFktlEBEgRU2puOPPDqX/C0lZvFF/qDC1253wCNSVa3f7suI2IfUTZztAsJfURU5ptK66UCfYrW27wrHdX1VawKnWwK1uXEjqtlUVyu3qXTBAuh2psATktqb7bJvwtqCEBJ19b/d5opQLtsB7yT6/+JSHLFEq5gmkpRe9aN/h5eR5XrPSfFBxqiiKoigR+ICWChRpMBkVpgGhur6ufIdW4I3B6x+zwcWtW6WWRLdiQlUS+nwfUNlgOPMCQeiYsIG3E17s2NOIozftk2yL1ddGCkWXEl8IhJ7zWrR5AiLVpgtFnyxW6LqIbVIWr/S5o7ZeVsxVlwReVWmnJ+C5wCZ1B4iI5XNxhbIstcWyj56YJ2Xa7dKCRnR/gtIiUVWAKdSJzppi3cvWr01B6EOsX7StqktTUwRgo6/WQVtWEm73hLVVSKhKfSDrdJCOd577eel7UdxGRF5sOjCPfMZ84MKU999ikVysoOkQjiLz+rV09J5TRVEURdkAoFN6qfAICdNKxgeVDiZCU3f58xipH3nHXlZshoRP3vzWn1D0NTQY5NFY/tgP7k8lY0p6nJyQQfkY8gV+eFSc70vdXwrAJCwN22+NhO6vC9WJinlXFyGdofuI2I31MXoPqCQgeFaDOtHmPaYmKQtLNx23ABRMeTEjJxpYvawNWq9gtJOU4wR24otlao+W5y6G0H3kYoCdIk2f5Voo+mW3r64Tp7aeNCpaXYqqVhV8gW39pFFpb4q3FMlj9Q/do11E3TnCxRdNw0VgnmgpF4C0HpUSEqYh3zi03UQxz/bRtgitTkx9of60dELfCy0ZFaeKoiiKEkESB9JUR4sb8JRGdg26zyxjv3Q/LH/Px1+SGI3ZCZUbEqKhATN/T6Nh1F7mFN7Sn/oMLLkIoo92cbZ5niS9j77nFwXEaLpg3JsaSQbQMUHN7TuhZetk/PshaTl8ME+3caFnxZK9l4/bc9FgKkyTsoi104K9yFW6Cdx2+kgX+5xSe+54Ijbxt3OxQX0skvQ2smzvRbW+0La15VSVFKt95I797/qmFemJL0yNgVO79hE2xtS1B40KG/gLNtGpqVyghqileVDuE9Jx58SEqWHbxfzC+9DU4ND9olTgc5tStJN+prbpc1zzRElDn5XmhYpTRVEURWE8PHd8+p7HwKgx9IgTO9iMCdSYcE2JkHqKXEmkVipGnR8RG8E8wgiQ3h9IBWrMpGvPBhCKzkm+2TLzFCkJU/ooFXthwxMRRJRK0TRq25s2zHbSKBftb6HIUCiSxffRKZtUOFsH+L23VGS66avEt9Bjc6hgtveo8nJoND1LcNgC7MJIdPqvE6MIt6kTnFYEJ2mhbcWorSd97I0VtwnKqwi78k25nlRQee1F2zVy/LK2eW0jpOP9g6aJiTbeVUVhK5Tj/RfK4eJS8l20ZfxIa8ivUF1bAzqtV1EURVFaMQ++Pd67R80OZoH0QDZLUMXwBujsc1b0ULJRaXkQPq+PMU5syq7kgx2A8ns3ucCJ2ZeKlNKlpt4SMVnJANCb/mpfGcc0dv+y+8y3lzqO1D4SeQbltC9yAcOjzjSCaeDf+0ptUZs8Kkzfm5IQrUX5wgCNWtKLBbH60qhuAWXf+OrJNC0XqDyN85WU6wRVRru7qe/0gkQgbVYEtRLh6OwJNvIKU3dsA6I4Jv4km1Q0xmzyab90m7vPlInYSgVpK9GmrQ4Vp4qiKIpS4sG3x5cH3Yk/QK1UuIVEUpbIWRfCVMorDcxCg2YpLRUwsUWSGnJV3xtwZghQN/YPCElviigRSH6i8HbvAgWLbkn3BlKf7CsWuRLvdyVCiPfH1OA9EK0KIQ3s6X2omf0U2X2FTzulIp3eU2tFY01Sl7+2tpzGroKboE68oshWACZvQkIstc2KeZLI1jl1cUQQi5Jocm4kSB3/SkVQVpnBfEL6rLIlYVppRDGvKIzZj4lSaT+d0hs6r3h5Ut9sDayPi4rrExWniqIoigLgL2+Nl+8vrMcvvyc0hGhNTKSua2Eq2QgJ1ay8dDoqXZnXIonWvNOBJV8S9r8+pBbkERoiGLGELHKzyBIWNiJIhZZ7JIvwYFO6gi5x2ysrVKYhL2rLLnjkjg+xLR1DKpapYKdJ+f3aNo33+JmkvJrumlq46a3WlzZV5f1Fg/LzU0tt5k1tFgSqLdd7NivNDyLGjew/jHBxAAHBxY5JIqTPIxop0rHk+XnbhyKW9H2wDswWfYRMSCzGIqdSWdI0Xk94CvW1/YIKU2475E9MQLd0dFqvoiiKorRiPCGSNw8bIFM7/H2WnRhZws4bWOcs06bNO1bjAo0P9EOPk5H8SolOIS0dhNIVW8WoUsKOX5L+79kXhKohee1Al+6X3sfgUTTqs/1cNHVTFZ1oK+0vkGdsigNw+P2OCju7j05Ndnmp2KADfuMv1hO6uECfdWrhbUGjonz6e1Xp8TM2KkqpNX5UtZosOERXZC2W2im1ai8VxFxQlmza+4ENzWOPNTmXnWukX9g2C0075VPBU0KJCSvqd4J0ek5oV0iYhkQtt8PFrDQTgi9wFYpySvYkYS5O2TUBcUr7POQVfUPiPxaNVZofKk4VRVGUDZ4H3x7vRVc4ea5M542MinkrsF0f+OI1QHpglumDYCuzXFYmz+cJeMEuHzvawXEV0kIiVH5ImJrSn1jbWtEiidpQtmC0kqlTHkWyr6oCqXexHF2kg/aUsLD2mDC1tu1/SQzYl91Oo8c0YsajoLzOdnVcMXIJJuxZXhqBbUPEqD0nk1Im+sghoDS9t5gW/rYMT/SgTgxzG9YHa4D6T5/PS/e5dpOEFhOiNn0MqS8Zyc+IjTzCKySUeV/Ja18SgkCgXch26TFGtA9T8U8vInDxKtrMEKgQ8rR0Gvjz0OxQcaooiqJs0Dz49ngAZBpl4kdcuCgLLaQjTeWl+UM05sCCD+QkMZCQN1nCjotK3gYuYkpsSfXJI76DYk/YVmvSj0xxiYmP9IJDwpJllUF9iyGJF2tTiv5wqDgESARTaGtqM/eUYiJ8bT56zHjk1Fjbgu8uElhy3PlG6isef1YX22ZF+I8QAvz3JTfTVNX9qzVAbeJHT0Orvlo/C8wXl44kpPWy9SySulHxw8VXYxITml46QYhxO7xv0v9Ztp0N/jlQbqhdqCDkF1r4hRVXHisnGDEVxGdIULcWUdpaUXGqKIoS4aG5472r/lk/clk/ipTQYFm8ik7s2M/SgCUkqApJ+Xl8PBpC7xWsLco+S4MdWkaIVBSFRSfsbu6vVBdevmc3sN3ui91nSAerkpiLkSXEpHo5P8lg3/lPxYFg3w7kjbAv5lMwXQ6Byj/TcyErchktP3J8gcoG+3zab+rFhAg/l7lfXHxxP22kLUH63K7kYoMkGtxnUx6wS0hTlr3+Gzg2rj2YYKDlxL6bnEhznaDufxF+v6B2+MUb2342MlksqRBblvTcYHtvasHAPZ6laABT5X8fh6JqXv2S8sUNqXlp1A6kXWPiRxJ/obYMHdOUnYBNvt8I27L8kr7TY7ZDAjCYlqWhdebHyPkKshIvyU9/s8D2SaJW8o/a4ftbMnzqemtAuM2++VFbW4uddtoJ3/zmNwEA8+bNw2677YZBgwbhuOOOw5o1awAAX331FY477jgMGjQIu+22G+bPn9+EXiuK0tJ5mAlTOsXMvrcPaLdQMejy8bzwo3MF9kqkF/PN+cXscNs0HSU06OfisBCwwUUXrZcnEAL+2VdV4j/kviCkTRKhXViZUjt5PghtXpWU73vjx5VGeLx2Y21n30qDg9B4IY/g4gNBirQIDm0b0V6gHFvnvITsxPpTaLs9PqFyaP3pOWaPHe8DeaHCybBXJXjRHZOOBNHyPGEWKM/V2ZQvFNWUXmuLdYsF2ddasq+26E8LtmWGFi3yzjXE7++zuLoFxJAnFlj6ovHbyasrfN/5Cqw0L1A+1vbcbVMFtK0C2lUD7Urv21bVbW9T2m/vWeX1oNFW7ketYUKXCSvJV3psU8eVbM8rTHl+r72FtrH7QlCh5tU9Zx7vPTnm/PjS40rb0Ss71meQPg7UB9r2YrQ1sJ/7wC9YNCbrW7ck9Xg1Z1qEOP31r3+NIUOGuM8XXnghfvjDH+Kdd95Bt27dMGnSJADApEmT0K1bN7zzzjv44Q9/iAsvvLCpXFYUpYUz8x1/5Vb63hNgpf9UZFGhJIlUuo+LsdCPiDSlNJVWssMEG8fwH3/j2+bwqatenVgb0XrzAbEkxEVBKrWhYI/Xl7YHtSeJYc8XdqxpW8egA7z6XMU27H1qgBsZ0LpyAe94VIokZHg5dGDHB+00H7+wQfdnPRuWDjQpseNn+wQQFtze8aR1E+oR8iu1jbcH28dJCbEMYUAH/bXkZUUpHdhTwcGrz7/L+AUifkz4YF+KDtN25lEwXgcuKKjQkES+FSa1tp4sD5DuD6mLTgW5r3n+kGNgQNq4VG5twDealx4nS0z8SBdSaNsZyDa9dpa2S21PbNL8NB9tE16OVybdxsrgbcEFqSRoaTvS/1liUkob+iwda9631wWqWxpGsxenCxYswF//+lecccYZAABjDP72t7/h6KOPBgCMHTsW06dPBwDMmDEDY8eOBQAcffTReOKJJ2DWVc9TFKXV8ui749NROaSFYkjcuEEy2yZGSSEIVzZ44eWKaZK0DW9bKR2NrFDodi40uTD0xEeGCOIRTdG/QPtQP4IRZcGeFIVNRWcROB4Jq6fQVtH6ZmznApASGnRKxK74V+CuS8+j3UC47pIQlyLa1L4U2fbyCeWk0iLdL6T+yn2Tmior0punDbm4yhIsVORwwUfrxv2L+RIb9GcJYHduECFHxRwXJPSciV3IyOUra7uUcKDiBkiJnixxJvVBb6owwu3CBSD1JyWmWd6QIA2JVUlQhnyS6i3ZSO2n9RDyUSHI03ERx/fZ/Lxv82gnPXZ5ouSpbYF+TffR91LkO+RDY9MUuiWpx6s50+zvOT333HPxi1/8AitWrAAAfPrpp+jatSuqq+tc79u3LxYuXAgAWLhwIfr16wcAqK6uRpcuXfDpp59i00039WxOnDgREydOBAB88skn66sqiqK0AB5/b7y7p4//RHgDV/Le/VgDdY9hMJF8AZvOgLDdlP4Yu90IeQPlUIFVVRpEuh9q+EItNZhNyu9DftLyDC87nTSdPiCEpOgC3RYaVHhiFmmBGWobui+UhgrMLCSRJImzWD5eljHhsk2p8b06JOU8WeWSQy73U8EfT2RnjKcy+z5Pa31HuV9xEWT7Ms0npaH9DWCDapYfyDdF2A3EmQ0+SAfg7sWkaWh53C/rNwzcd5Gl1oR9tN8TRWYzKj6ILwltbN4uVIwS32P91fOt1A9t27hktEzIQsu1EzluPI/4PZOg7t7UpNyO/Lx01Y30X/pbQMvKK2x4OircnH1WB96ngr4JOyVfJftSPSTxKfkhidbMNHSbfc8/wxemqXwBmzzaGqr/+oicrgvdsqHRrCOnDz74IHr06IGvf/3rjWp33LhxeP755/H8889js802a1TbiqK0XJ54b3w6Sgl2DyLK//l+ty1JR+TyEIsgpSJ6wov659UhSUd2C0n5Xixpqi0vP+RnEknnfA/VF377ZU3bpEjTcqX89jmKPHpKI0VS9DQ03beSKKrULqFIYaydQtDBW6jcrCm0Nn8wuoayvzS6mkpXj3aJ2Ugg9zFj5Pde/w34SEkJ03r6HxqUZ6YXBsfeBRDymfZD27/peUMH+jZqxO9FFaOWpbKy+rp4PrB0/DshYfWxbUT9pMKCXhRLSF2pXU8kwo9+0brSsmgb0u8C3k/4BQ163kiRvoZE3EKizNsPtj/wou0iHWtE7ItTb0ka2o6eX4H/qWglK8sr1x4v4kctycvbOhRxDUVg87x4tL0xWFe6JYvQmCD2as4068jpM888gwceeAAPPfQQVq9ejc8//xznnHMOPvvsM9TU1KC6uhoLFixAnz59AAB9+vTBBx98gL59+6KmpgbLly/HJpts0sS1UBSlJTBr3ngXPbTwwTLdxgddCUqRSNTZSOAPCKoCPwb8t7FoAj8cpUK8qEMAHo2UprOmBoMoDyYKSSn6QtuC+CpFU3m7hH7zue800kkHhDxiaB2wdhOEf2BpvfkgOSTiQ8TKkeoRTUP+Z42JJD+B8oDbUjQkulZqp5ArPNJI/cpqA8k3us9AOGZC+tBgMO8g0dUzAK+LIecN9Zf7JYmprD7v+cQ+U3tOXLFBPgLneuw4gfQLr57EvnVIutDkyi5Vzgq3ui+uujR09ocXHUf6HOXfg2D7XF3Id5fzyZB+k9F3eSSRpqNCl/thfbGRGMP203yuLZD+Hm7o9E8pCsn9reRCB88T28ftWSHHt8WitUZIS//HosGptEUiJlneWL48ZUvR1pRtuj3dfA2iqXRLM9eaFdOsxek111yDa665BgAwe/ZsXH/99fjjH/+IY445Bvfeey/GjBmDKVOm4PDDDwcAHHbYYZgyZQr22GMP3Hvvvdh///2RNPfLA60c+/xAC12wAogPDmIRJL4tZIvu9/KQH1puo5KBGv9xDuYJ1JuXlXfATAn9wHlpIvuyypPaJjRQy/MjJxH7kZZ+7Ggau4/+2IYildIPqP1sB0iF0MAw1p9IuXYKXwHhutMBPU9UlaTr48rno7KI7VBkjk5vswNDu71I2sHlScouJoJfIDYkP6S0FHusYkLStQfdF7BH/aaDzSRiH4gfc+6rdwEjkCfHoRLJ+51C4QI1JHjsfx5JqeQ7jOehQgPkbVBgke1ZgpR0xej5J/noRdtYf87TxrSf2UG0V2faH/m5WvpP+7TFJOX+I/pCz3P7fSrYBhD8nuXfL/ZCDcUQ/933AjnXi0hDZx5Iv7G2rXnk0ftN8A6q8F1I9heFLIblte0TEo/0t6pA0hu2j7c5z98YhH67QqI6dHzzCNaQLS7mQnmk30jabiFh6aU16foVi+ULn7UmnD72n+aRorTB8lkdeLs2BqpbGodmLU5DXHvttRgzZgx+/vOfY6eddsLpp58OADj99NNx0kknYdCgQejevTumTZvWxJ5uuEiilIscDheGfMyTCGkAP21IBMbgfoUGQfTqd33LqVSMWySxRQc41p71jX/hCuNH8XPIl5TvoUF7Ka03sIl8+7sBn3SwS59dfdjAhV+yD0UmJTdSA2o20LFX+UODQorXL1BuC/4jKOWxdbJpqMCwYjGVL+PXlB4bvgDI6K1+C6BuwSf6w33woPJ2W0RVabAK+AMQeg9cKtIUaCSpDeiFIS4cpYiMrXvWucfPYX6OFVj78PMohCRMOUngvdd1DYKdKUs0xXy0AjVURGhAbJ3N6t+lZPJ5xH0TBsfcZiWD/twXAUla3v5SOkAeyNs8tN/wWQT2e8l+34WqY6eQA3VTT1Eotz+9cGLtGpQjl7bfG/aeQqfnSr+NdLv7jjN+X/R+AwMVkW4FcH4h3U/s56L7UvWhbWC/O7k45F/5IcQLsqHv3cDx5hdt6HcDP19it2mItsHanfiY+k1mG0K/IaE2ybpAnCUmpXINSyMJ02LEnstv/Gm8MfGZZz8tS0rPfZME+vpiXeqW0Hnfkmkx4nTkyJEYOXIkAGDgwIGYM2dOKk379u3xpz/9aT17plCsKOURSW8b+TFk4yPvSz81CGV2pDR0W4iC8CPq/TgH7CTkjZQm72CIv8/ymbelYdstdBqSZM5eKfc3Mj9Z3XiElC9Iw32zP+gFlpcOnuiPBndHEo184ELFqmH5Kr3KzYV9Svxm2KMDvoT4aoWdjfZJQpcWExp5i5G6nD9CYqSkhH0EBS+aH2967hmULz54dcnhj3QxI3TuhaJ+ocF8LF8oDe23NFJt/eIDIAQ+hwapeccJ9EJXFnnSFU2pPqbcJ6k/9NwT/bFlCWW69gv0kVSfYN83UroQ/EJgnu9J7if/nXG22D5JEEE4Lp5d1v9s/5HuRfQuiBRQt0AP2U99sxvsd0JS+lwg7UEz04E5EL6/2NaJfhd533d2uz22kGcVVRXK920mqPuOoxfWpOPD+zj/vjF0hyH1DhD6jaPlhC44NBb0MPD3MSHJhROy0ht5eyyfFBHkfTIk4iQbXGjae0MlO0Hha9OhLBZD4pOXy+9VDdWBpuPlSoslhdqwMVHdUn9ajDhVWgahCGlwAGkHUSj/uNEfRW/AE7ODtOjMQyhSIw2I7GcpYinVi5fD6yD5b+tMBxu8PjwvH7jzNNaeE1KG5eX2E/k9H/iI9weWBse1bKAg+k8GNnzgyiOLofcJGu8KaGpATQZtofT2ePLpYja/E+m8f7H0CdkOlCMx9sc1dE6IftH6wB88WqoKpSiOsN1GOuixt33Im/obQLpowre7dkv85g4dbpqf24+dU9L3hTTV0vZbmwfEZ9q/olOuuU0BqS9Usj8PXhu6E8r/zDZ7g7qQKIOwP/S9xPto6NhEZxXAPxaxC280vTvmKL/3zktelknvM/YP84W2F++/Mez3s/WLT633BCf5nwDuIleC9PcCy+rK4n3IbqMClOehx79A3tPvEz6tN9Su1i9jbUS+tOj3JReovG78PKeChh5rXjean9uTjj/g35NPz5sE6faigsirE/PDZKSRfDbCdl6elxfx38QsQUjf875mjC9Mi4ItmpaLUuubt4/ZoeXH7kkN+SmVS33Oar+WSt6LnC0FFadKo/Hw3PGZU/U49gvE/mDz1QIB/8cHkEWYNDjlgx9ePh20SxGQ1JV3pL/MQvWKfVHwq9/2x066x4dGJyXcPjaI8/w24emLVjiG/KWRUI7U9vaH2i4KRMuT2o6Lv1QxZPBAB6redro5MODN+sF2xQllWB9j9aDCNiE7jIGLLthjQduLTwek9S+yyqUiVUJ9xAF8Ut73xHvjyxeACuW+8bd55ee6JikDMtK0Yz5YNwhcYBEGuSBtxH2nH2OuVRRZI+nt+Z2yY5D6TqNCltuV/BH7fQX+xghNNaZdGJB9CJ0O/LyuxEd+UYkP5IPpc9hM2OdUOrDfHN536HEkaamfIP+li2f0e8dekErZJeXx73YDv69RIUj3235jvx8S1H2PJHQgD//+dq+NmE37RvoO8ny1SUk70lkwVQW/Xfl3uCSabXlZosz5xvz3jlUgH7ch/VZz//jnvEKF/XyL0c1QXWO+cRvUNvdZsg1kRwapXamt+Hspainl9UQqbVPI+Ys8DysrT5mSv1nClNqQ2qcl08CfkmaHilOlUZj5DhGmCdIDBciDCu9Hmg1YHfTHUPiRkqKcYt6AD9LgmdqiX6a8zNBAyX4B2h98m5YOFOhb++Mt1UMSh2wM6AkKqQkMfBt577PLEnTBiBVk8VIprl6m3E5A+bOXDv6PIoVPB4qWmcjppM88ysOFtj3m9h4yHmELLZpUKKUpGn9RECkSxAdLqWNq2ODT+H0mFE0A0u1JBws1Qn+NXUzhflo7TsSTz14mUoYdsPABssvHGpPXTbolwNkOHO/Y94JUBk3njlXJv9DplhrsCuIhRugikvt+zSiTl5P6Hy/epaX9wTuekQE1b8eYX1m+S0LG+pFVJ/ddbfsj8dml5edSwAeKPVdT0XbIF0bpwJ3/Btnz1t63Z23YNDGMkIa2V+K+FMrt5X6LSdvx32e7PyW8QucF/N9E7p/9jnLpk7rvw9ACS1zsSMc+1BZcpKTaJ/H7Ac3Pq0htSeLH8zntUjkd/+4V8uSJjOaxa9h/6qf9n2fRIk9YCmVx4VkU3ucVwpJ9SZRSO7H7UTNOG6WJUHGqNJhH3x3vprsB5R8dfl+ZNChIyGVjKk5DUDt0UMMHJWI0k/mQOyJgRwNI15Enc1967D+HbneDa5ABifHthyJUqcE8KyM0YKlUOIoCWRjoW4FtTUsR20quUNv0sR9UaSBgffbs5f0hyshHB7p8O70owS+M0AgDJTTQ5rb5uUGjKqGu7PoT22bLcKKB9CPua2iw5OzDb5PYqsm0u/KBBt0u+U/7lldntp+e4/R42L5YRdOHzp1AR/G+cyKDb+o/zWuPayKk5eXkEaSxz549+N+R/LtB/G4W8ocQL9YZ1teQPsa8f/Lv8Riiz8JvQSpR2b2ULy5pUh44033UFH00iS2TXmB05Zh0Pe33N70YS+/Do+lsoQVD7vcj02ycaE38Ab89v+1spNDCSdYP79gFfiele8UNaQSvLQ05T0gHki7C0u9O+9nu97oU64iGv/j+wHe+KEyFdBZbB56Gn9/OJ+F9KL21HxO1WSsRx2ynfGa+8f90nxWmWSvi8iiozUPLlAQpFZF5hXDquNl98D9LwtSbqh1p15ZI7vFsC0HFqdJgvPtPTFmYSvef8h86oLyd5uFf1jSdhf7g0x/MYDQvUDZH/DFL2A8u8dErw/oVKNvuD5F3YOYt3sIM2nYRB10kTWwwK/pGfJQ+2/fcHy6EaRqpPfiPrHg8+Ge2ISZMY+KYisLYlWDbD4wpT63zBpbsOKaOB+83bIBu+5B9FeFPew8d21TVDLGVcbxj7SIJGUjbGLzPhQidh7Z/04sBSWQ/yGfpPKRpbENLfbYSpPPA28eOV97TLpY26wIetSHtS8iHdTmmkWYT0Dfi9zR80RK1H8hrBZdFGohmfScY9j9haeniYPRYSd/99kUvoNhzm0Y+a4r+xbyE2i29oesH0Be9eGO/YwqFyMwgkNtoknJeup9/L/F6uQYqZS4k/iwR911WemOE/LHvWVo/iye8TPkl7kcaSYjxfKF7HGk67j/fL/5uCOnFOjE/xHTCNqksaV+W6KPniyTuXB5y7PjsMkkE8wsw1GYtt83+u/QsUMD9Ty2aJPjemkRpa0XFqdIgnnjPv8/U/hBVkR88oPxFLi1GYj+nIqdJ+ctEGgAask2yS+/HEhfvIXjjbeGLq6oAmGK5fnyQ5Xwy/sBPSBIVznlERB6kASGPavC3sWJjgj80GKaDnZBANeS9BN/sosrCPopUHh8cpWwj/eOfKdgSslgJa3MumlKDv0Af4VGJJIFb4dP1k6S8KqtXH7FSfv+SklF/vD7M2ix07zLfZz97A1TmlrMRaGPeb0Of86S370ORXC+KjHifDJUn+eS20fM7kC4v0j33ecda/DhkpYVJH2cxLUsX+v6h/ooX1Vg6+xvAxWrsIp6zQdLYc9SVy3xNnZfsO8bm4b8TbrGixD9v6G8iPQ+8fsDqVFssi9MkKU3tZ3lc3clvmtemzjnyu0jz8+9EUj/v/M/o02K6UoPZxZ7oNkPe899G/p2ckO20/ehxoher3EvoTyFxFhJRdF9ImNI+4fUpXhf+eyOk4cTEU+jWlNjvVKwNYgI1JkylKbzUZzG6ibIw5eKUCtNKFliibVFLN4TqxtLlOR4tiYb8pjRHVJwqDUKa6mlfdF9oii/dzyOnQHgwX7eh/I8KVJrWGH8VTnHwSDfagQYpgn/Be/7zbzY6SBHss6JS20MDfmngL/rP7Bn2meYJ7QtuC9QjJXpL7Ux/vGldvHzECTfwFPzm/cANtNiAx7A2kn7kE+EYSf0sdkWa+pFa2AfpQTYfrPG+GBKxsYEH98W2A08vXvggjnJfuQ3a3gbpe5f5eV4kx9H1a8lf4b1YNykPsxU6f6iYj9n20qI88A41fcLSp/bz40u20wtw0uBVspUF7zN5iJn16s/6SswnqQ7B/sdtCOeb4edKoM2988WWRcpz93ZnDE7Ffkq+03h6Q865xBoonSe8jUK/Zd49d8RPg9KMCZbefufQQbpNS8Wh7cdF+9+URbp08D0xIHxHeWnJd6/U37xzg7Udbz96IUg6Z2h7GFph6rORbx+hwoZffPP8KP3PuyqsLUfaTu1J2/h2iu0Hqe2G/efbQ+kj27iAS0UcUW5X7z3pp8GIqlBmkecv7aslaSRb4DYFu7ws/r7IfJKOT0vGjrlbEypOlQbDoyP0R41GUPkgkg8MJXHqiZbIyVeVQBwschGWOUhlA9RUGmHwKwlXWmaIrO8SO4C1//l9vbb8PGXEBGwI3u7cFs3Pv+NtW1ERaBARjCQ9L4sOtKwdOhDkA0I6+EhF+kg6v7KCsGH14v3KDhLtlX0eyXRlUqeN/0PCbVJ/pPvdQnjtFhrsRQb5qUEhaVs+8KY+SVE8fg7nEYYhsvptSJhm2ea+8fQpYSblDfgole19B7Lj7/qM8F3CiS021dh451vkuztGsI34yQX/e5MP9rk9z0+UxYcbeArleY97MuE2k/aF6mv7iNRPrYBzgpDYsvbtraOpKZHkRRdCcl2FnJ8Jyve/2qnGNmGxZMTeq2rbqWD8NrN9j0dDpTq5789AG6bOJfaB93krqK3/XNDVFn2fpKgh7Tf8Oyok7CihBXh4Pq9sLqAC/kl+Z/nB8+TxSbLH+7JkLyRK+X8XOSVp+T2iVFhK9mKLHkniNY8o5eXw+kl+tkaB2tqoWJwWi0XMnz8fn376KQqFArp3744BAwYgaW2yXcmFKDxLn+l0JvpeGtzQyGco+iENhOn+vIPF0ODR7vN+OIG6wQfxOyhAKDm/8EKnDb9PSBQzkfxeGZGyYl/MVBjaz0FbwkBFEkoGacHIhRX3zY3DyPHgwjQkUCGUR4+hO9QhAZXIx1sSGoXSCDJ2P0tWX5XKjqWVBm28HYWPQVEcFASl9s0j2grsc+x8y0MoaZbojZXvpQvZo/UN2M9TDf69J3335RkgScI0z9dMnr62Lgkeh9IGSZDT8z3mNhcMEvZRKPZ+SPGiI/HVuyhHvgClCz4c/p3sxBxLJ01DpDMOnCCweY3fHrYca9t+x9lnF9eywXctGfjTxyBJUUZ3UQqy76n0CP+mpzPaneS7zX63oPzZE5Tse9CaCQo35ifdxoVjTJjxegZFaqCs0DZL1oq7Qb8FIZZKk+GT/RxbFdfud9tN+fwxLG9oOm4eUUrzu3S0rVk9KhGlUnl0WrH0fdBSaaKv93VGbnH65JNP4vrrr8fs2bOxcuVKb1+nTp2w//7744ILLsAee+zR6E4qzRc66ALKP0j2Yd10YEZXKKRpqR0gLcy88lierO18Xx6oCDJkm312p61LHhFSKXlEqd2ed2As5ef7Q1VJ2PtY1JQONPjgoyKBSnzjAwHnsx01sWNEBSpQ9kGcUmxNMPu8LWgd+EUYC5/Wa7cB/j1pNh/tH6FH/HiDN1ae5C+vM90WI5E+kPYFqZuh+wQ7FYnv0Pac5450/vO2TZ03EMRi5BxzzRDoO5K/nrgRylxf8Pap5HuR1zfh+xK5/W259DwIpQPt6ykHwv7lGUwaA5iEXSgxvgACO052s/e9k5DjT84vSupilbVB0kkrl/Kype8h7ziY8gUwWwZdedqtrVCs20+nSzr7pd+uqgJQXaj7T/PzpqX1Tm2n/gt9IpWGpU99z9r85PfD2uEXSm16KVKX8pVst7uzFu6B8F5Kj6y0iI8TuE1ql28LCTH+nufhvuaJlNJ9xWL5u59H+KXpvFysUuFJy5dELS2L+iD5LbWLZ8v4Njz/hPZSmhe5xOkFF1yAG264AQBghCP6+eefY/r06ZgxYwZ+8pOf4KqrrmpcL5VmixVqlKrSj590n2noUTGpqYAZZcbSxAaneTHWjv1FLA1sQtOH+VkRuj80eN+o/Z9zm91eSf1C6V0VhR9I7oOU3w72pIiDJFBDvoV+oOmPrKsDKcMOaOgxM8xugvg9qB7EVkhQSgNnHg2h92PyutnsNIrBXaP3ldkBGodHFKxvtIxE8IGnTzmRlJvYkF2GbRPtId5fxHIz0sYQI8rCvtT98UifE1wsSHZi5fLtUhnWtuQz7bd5kPqzuA5ABTZ5+VLfj30v2P38nOVROpcO6e+fVN9g3y/unCgV7qItSbxvSnW05xZds8Dr6+R7xpVh0u3AV6h3fpG6cQHAVx71fCB56e8s7VP2e83Wu8rUic7aoj+VkU7rrSoAbauANvY3uuRnrSnnky6wSP7biwim9N4Aqb7DbXkCiH2m5wBtF/6DlCA8BdbbBr/tgbA488oT7HK/+PYsISj5yXeHbNIyeZtVKoxD4lackmvK+/jUWEAWp9SeOFU39N/IkdlY20i28orS2DFviazPC5/rg0xxeuONN+KXv/wlkiTBUUcdhe985zsYPnw4Nt10UxSLRSxZsgQvvPAC7rzzTtx///2YMGECevfujbPPPnt9+K80MQXhR9OKU/vDKUVPLU485BxAZaWRBuqVQMWIfWMHQIXSl5ydJubuvXB//EEGtWPrKUWFQ5GYWF2y2oH/UEcjJ3zwQCuSkTdVDur/ZW/bKPbjK1XZtoX9YeKDYzqyovfthq5oU4FLB790Px9s0x9Vyt5b/BYA8Pf546NihtrnEVc7AAzmlbaz//xDSOxKfcKQ9AblF7XFbUj9k5kOR9SY7TzncOrcYXmyFmST8uT5Lor1S8kfmi4rbx4f8pDne1XKA/jHmfcpSaTy/fYcsr8HQN25kusiUcCec8z+dqD83p2Dgj+G2hHKp79lRfv9TspxRbPvAreN9z32fUDLt/vcoNn+fjAfXD7jC1R+PhaSuihxdaHcL2uLafu2jvbiMZ3xUVME1tYCa0urBifwL3RwUcOPF/2+pm3Ov1MkQZEXz4eM/Ial5xE/apP6Xqmt0PaY77ws/n0qfb/yduPbpHpJtnmZVNS5izzWdml/1mNeJCFpt2eKU3IupO69FtqC+y2JWV6n1L3MrB1bA43wU9GsKMR2Ll++HD/72c/Qpk0bTJ8+Hffccw8OO+wwbL755mjbti3at2+Pvn374vDDD8e9996L+++/H1VVVfjpT3+Kzz//fH3VQWli7I8YXRyGbqODo1RaCAPHwCtom7xg7QT2x142L7VB99F7FaQr2ZDsJnL9wPcFPkt1KZBtqVWOhbwhcRlLWxDy0jTUDm8DXk6I0OIuQOAHyPg/TtxXHrmQ/He+onQRJYn7QcUMr7uzlfh9027nq9jSPACLwidlnxKWn7c39yXUl1N54Nvmn6U+Ruso9Tl+3kfPZeZHyLdUntA+wTZtX9vukjClx4m3cQzePt53HnnFvp8odgBnB2d54YO4oL856+XlYflC7/k22o/oq6rgz6ahbUbrQi8M8nZO9ZNE6KfsvOA+hvoa7/eSjwnYwNj+FwbhIGkkAUXbl+a10Sn7on0iYfW09mm5SVInTtuUoqJtq+pe7aqBjdoAG7cBOrSte21UDbSvLqeh6atLU36l3xR+zFPfzUzY0Dbi7cGFQUwo0HandkJp6bGw99t6vrDfE34eSr5623h+hM9Hqf50qqsTUEb+TNNJ22pZPm6L56Pt42wU66L49qIMtVkbsCn5xftykZdBt5HyUlHWCupUG0nnzqUMO4rMaaedhh49emC77bZz25YuXYrRo0dj8ODBGD16NJYtWwYA+OMf/4gddtgB22+/Pfbcc0+88sorLs/MmTOxzTbbYNCgQZgwYUKusqPi9K677sKqVavwP//zP/jWt76Vaeywww7Dz372M3z55ZeYNm1aLgeU1gEfSALyYCElhOjAIrCfDnq9SCzSg5eQuMt6uTpAtmF9BNIiFRm+0DYSB/Gxz8wuF/TSYEoagAWPl5CWtwetJ3hati8Et2uRhGHoinJs0Jk6Zsx3qR7Ut9BUSJrG1YPWhbR9FfUlqRvgPbtgPP61YHxqYO2tYp12KeVXrkE3O/4Flier/6fS0HoK7cnPkZhgk86prHMVvMwM//mx4faltvP+83qyV4GVJ5FqpyR88YP6RQf2WayvwRQ/B/g+7zPYuVAonxPi7BlmOzUzgZ0fqWMgvKflWZt8MG7LkQQ0/44D/ONJ/UyIfTpQrzV1UUc7EOcX1yT4IJ8O4m1Zrk7EB/o/1CVsXuniAP3Oou1YRdKLx1nw33sFvr+lNjBkH0/PoWklsQiw9hHK9+zAF1qp8lj7csFo4AswzzcihKifXHzyYx8VlcyPWmYrJfCQT9y5F2uPWmZL8lWqhxWEkoDkIjgkZPMIYF5/nrammK675Be/HaclEvoNzfO7GeOUU07BzJkzvW0TJkzAqFGjMHfuXIwaNcqJzS233BJ///vf8e9//xsXXXQRxo0bBwCora3FWWedhYcffhhvvPEGpk6dijfeeCOz7Kg4nT17Ntq0aYMf/OAH2bUo8YMf/ABVVVX429/+ljuP0jqgfV0a2HhRLZI+6yTxTjyWjw9gQttDUVSwPKE68QEK/eELCTduWxxwC/WTIoHS9lTUlLzn4gDMH/5ZEiU0nRfVENKn2i2wPYY0hYf77H6khR+UkKji/oiiDGGBKtmin2l6OziuYnklYZPq1zl/MPJA7dB+IhHalxIBgWMa7I9knyhUA/3TK1/qv8Ir1L60LVyZUlkQfIydQ4GX5zfksqRyQ9B+Xp+r/FzI5IH7wwf+RtgG+MfbO+7wv0d5+0qRd95vpPShF21TO0itKbIIE6mrdIHA7jcIf9e7PCgPvOnU2FpSprNDypbErRTNkb6HeflOsFBhzOtB9lNfXL7SZ3pxwTu3aJtBJqu/x9pB6qLcXur4MOEkCSmej0dDnR32Essxsu1o5JWJJ+lYS4IsJColURqKxqY+83RF2XaW6JUiuwbh/O49S5MSmKz+obrXFtP7a4tAjSmf6yFB7r4LiHhVZPbdd190797d2zZjxgyMHTsWADB27FhMnz4dALDnnnuiW7duAIDdd98dCxYsAADMmTMHgwYNwsCBA9G2bVuMGTMGM2bMyCw7es/pq6++iu22284VmIdu3bph++23x6uvvpo7j9KySQ0KEzYIYdu8AZkp53H5S5tpOvojFRILxJy4TxpYpH5MhYEA9Yf+WMVsB82yeoYGztJgGEIaajchfhmSx5Q+VDRARclGIB87fMG8IGUn8N/X9zchdYzJdlsGL9fzh6YnA1MJWgdvO8mbNSDjSGLPHjPDyzJl4VipMHFlkc9VEWel+3H5eQqhPaRzk8OqFDyvQ1EXaiePgKcR51A+6fuI+ymVT/3l20KEziPqhzv+DaAQqAf9bqDl0jR8G91nSD807NxC4rdV7GKDd5GLvhL/90LML5RhgPLjVoS0dpAr2UpIOu97Uxh4uzKNf6xMoAw+a8GVmdTZt75R0UDbmfpXYO0iHSvqJxe2tm6eO8XS8TTlhZC8fNY+67fe96Eplx36DpD6GBeFEN5LSBcvDdvOvyNDEdWY3dA+erzz2g75yi/y0LypCxCsbiFxLdng7ZXym9UrVKeUADfpvNy3oCBmxzzWLtQ2T099Cz3HlPsH2mZCW7dkKh2HAMAnn3yC4cOHu8/jxo1zEc8QixcvRu/evQEAvXr1wuLFi1NpJk2ahEMOOQQAsHDhQvTr18/t69u3L5599tlM36Li9JNPPsG+++6baYQzYMAA/P3vf684n9Jy4YM/+oMqXXkFe8/3UeEhDXYkWwC8b+PQ4NGw/aH8qQG48MOXZzCeEt5Grncqcsfyhz5L+6i7hrzy4AY0LI/nd4LgD6L1J095kuCix8e2Vy6/S3/oANgbRLuN5YK8vmDqjgH3SfJDOu70h7dgB+ymvI+m4xdtbFo78OUDYqAsHvOIVCpSpAs/gNyuNikXqrTPcf+yfhTznKPiZ8k/oTDpmNG0CXsfS+dtR3rgTfNUOhjwxJkVVxnHMibEY9OFs/Km9hvIX330PC81Bj0XDOqmXxnUiUQUAZP4tjzBnJTLShJ4j3qRBBj9zuHfm/ac4cffqxYbzILk4+kLSV1lEpSjNDa/O1epg0l58M3TSlOXbT2pCRpxsj4kpDxJrLu6kLR2e61hv7X2vynbs78Ftky6Qq8n+lmf4ETPKe4z8TH0XoKn5ccxJT6YPcPec9uS3WDZSIuwUD1SZRnZXym9+Jto0nWRRHXKL94ukH3lUVGp3ekFm5goFesPIdoc+c8FKa+z3eYWIozZIcePt9GGzmabbYbnn3++3vmTJEHCfmhmzZqFSZMm4emnn26Qb1Fx+vnnn6NLly4VG+3UqRNWrFhRb6eUlgOdvlhdAIb1qlud9LWPx8vRitBAkP0ISwPLkDjwxgu8PGEbjPdP9I+Ls7wDUWlgmMqbpNMm6d1im0htFIQ6b8rCR/I3tT0pt0Hq6nmkKA69ch+yl0WeSJmXnjpp/PJ4X7EDbdpUfNCfiiIyag3cM3BpnqKpOz9i97S4/kmPj2FtzPyng33+Q84Hs+JFIeOfK6Fj4Q3aURbVNlJlj2fFxydn+rwRUtsmkkBxoiJUBv+flNvVmHBbcj8bcgWenxvUH05WFF08N0vnQFDkoNwHvc/Irpftfwlpf3oxw/qUFMpl0HMPCVAwZeFkyyyyPkp9osfUlY90Ol4/a9f6zS8uGsA9S5QO2G2hyf9n7++jbTuqMmH8qX1uAgZoJJCEkA9GYwARRIVgGH5gFCIICkpj6LQKSmgiNqDYtDBslQ5/KLRjIAo0Pz4iXBwi5Ae2vKIgTRBCCxECSgZ+9Ijd4TXQIUBIpJWW5OxV7x97zVpPPTVnrbXP/ci94cwx9jlr1aqaNWtW1az5VNWqhSnPajIrbdJl4jPkCbSzbfHqIJPeAHpPV8rC+vDqudgp0lFlN4BywnwlA5V1JeFa/6WNdhz8qO1uA0x7YMxbVVMbrrJ7ZVG+PZm57fQAqgcGPT5qt708IzlUb1njsc4CPh6YV/m8cO4/EaDlMbY8y378HmjXurZw/RyM9tX1mHGGXw6g7QcX/z+X4LInvhbHM207Du+VTjvtNNxwww04/fTTccMNN+DUU08tz6655ho885nPxLvf/W7c8573BACcccYZuP7660ucz3zmMzjjjDNm8+m+c7q7u9ug4iWUUsLu7u7W6fbp+CObTTZndVEajwddN+8d0TP+b7xYhioc9WCenPjhz+Fp1BuUq9l15aX58r1kpDrheNF7fd52MEun73+xo9Rzur0yzJVdHajIgphcXvheyKuXpvzSHjiO21YCGZl2Av1Znr2ttJWcqdWjG4Zat1r/WvamTSoP1U3QXq2ceojM3DutR4qiLaC6aqxxvD4Kias69/Lq9Yel5Nm0JbRXXXvOq+tU5zpsFqTS8zkboWE7ejJsauut6pNOXN0qr3y4jlnOarU2O+UGKgeb1WDp7YTc6oRb7kvMK8tPwqv3+yCrVZC6k+us15189NerN08XVidcNxzW5eOAL83Du/faacNXQQ8EFMHRRcCnAmnBM64zBkq9n54uq/XexNdTbimsHDCkBw05cvB715UdkLJwGfjbt7zKHwJNuR4GlPdMGaD2dBLpTN8VbXSR6V1Up/zVSdjO7xnvvCRuXMcBqd+y5LcXeuITn4iDBw8CAA4ePIgnPelJAIC///u/x5Of/GT8zu/8Dh7wgAeU+I94xCNw7bXX4rrrrsOtt96Kt771rXjiE584m8/sd073aZ/myBr5kIGP/+9LyoCdE2ArQk2ajnO4ZLXHlcNzIAN5Z3lhNN5j5EGeeXkomIvyh1P28D75+vHy5ZWAMuCOYVmvnXz0QaUjpx5tZr7oUwoSORJJntuql870B8lbXnqdpvrTMqhsVVuQQlSrDsmf6eZTdyWL4jBbmK2g6mFJVXlGOVasPypPU2jOlHh6bbLOaErLxer1VdWHsgJa0MS3ls+Sbck98t6rTGhBqZKnGw9EMM+Ix7bkgT/mpQ5/FM9Wr7fN0+sLVf6o88+UjuN4Opqzo8ZnQAtw1E7M2dYmzzzZk6qt5alNWJ68/dji8nMrYyUf88QUkdvLgdUm/ioBaTxwqCqDI5uFr0yWFZDHdOuMzTZcahP2M4NV2Xnpw2qQverR4lmS7IRZfE8nS5ritt3dW4VcOvHN6fVa+cyFM/hnMKbPvNXDaBJBQV1PFi2DTiz10nnbYlUeZmDhDE61XD27XZXJ4g8TSKxAvPD06svsRVUuSevx6KVnHhpu9PT/egkO/sjxvYJ6OOmiiy7CBz7wAXzxi1/EmWeeiUsvvRQvetGLcOGFF+Kyyy7Dfe97X1x++eUAgJe85CW46aab8DM/8zMAgAMHDuDqq6/GgQMH8KpXvQqPfexjsV6v8YxnPAMPfvCDZ/OeBadvf/vb8YEPfGCrAn3xi1/cKv4+Hb8UOSfDOLjyu3ferHm5Joed/1eRdRBGzJv5L3ECWY4ST/J0Z/MDp8krgxnNxgHznGbnv8rQyEMOCzuZrCN+VspJ6Sv9yjP+z2XOlnbGgVDw6SFQC2fQuy2xTAbqejJy/MY7wyQLA1QFZ+ZoZgljqtL0HHpxLkPkIHLypTf5o0m4zBHLSP/a7rhevbJxu1/y7izrinXutXdPJnve6yvJSaO8t3GKl5Jnjw4XaVNpnls9BREqW+H0f4vj6nr8rSRtxmbVQ8ttebFMavesLF59VGURp50nzsrkDlpwb7yrlTDU7blyZsmm6CSYxbcxr9iFNLXdMgakDai1MDvp99Z1nZ8BaePrVZtX52rzrY/zPcdVW8nkvXva5OVcVzIGDzzg1IzxTljveXgtbcQDlRpvCOTLkr55HvHIfjyVq+JH8qnsQGtHvXL27plfD5RWk99aDk5Lfcg7NZd5an7c9yJ9lfROXfDBSJ4+5sDp8Ux7nTjt0e/93u+54VdccUUT9oY3vAFveMMb3PiPf/zj8fjHP36rvGfB6T/+4z/iH//xH7diCgB72Q68T8cfuQc2oDZANkjbgM1hQOycLCUeiI0ipxSSZ/WI45LTnhI2M9nwHRtl75WjOAQMeMj5YhkiXhrHzYP4McDmWXTP6SxBZMh7gD9yJOao4jnKZasO3F4YoHo0ly87lYuAM8elTEwPJktvi64CPa0XfqeMidtCVyZl7N/OhvPzUs+inyTtZZByeavo3bwEmFhf8gDq3AnDc6A0y3XvBNg5WtJ2IvKqa05PnJUX9WhsnVan2cjL2puws3Be8RhGxmo/7Br0vGwZR71dXB1yV6/cTtXmJXoPlMac7soSUNkStglqz3Ucsx1E/K1XI3umNmI9AF9djyCVHHHP7jSAPdVt3cpS7Knl4+goInX+q/GR4zn2I9KrggMPLLjgTfh5q4Ne/fXyieSZA5QRaPJAowIijR/KYXGEB/OOyudda9wIVHvye+l1KzODUC/MttZ6OtD3SFWu8r6r6MTiGd9IHx6/iP7NOy7BW/7V/urp7U1dcPqnf/qnR0uOfTpOiQddNarl4JQ0DWzqiNvAmeCDsQZIibH1iB0kHXtdECLPVC6TOVoZU9/enlWOZJaIqZbFk09lqp6j1VVxwqSMvI2tmv1kxlyw5qFfH0qH4sgrD9N/CUc92Dh4KiQdtObyr3Qxtjd14tgR9eQHamfuENWiTafLcy/4ZclcIoNrbdqaf7R6yrr06mMOSOpqqEtbKJvrqArPy3Qyy7/DZ85phuiiB0y9Ff1tKWrTSj37OpsHWgdR+8uBVX1IUllpH5+Xw09o3Cj16BiG0uayRm7lqsrp9XkaEzLGbbkecMRGbganRvwd0aa97wB3OrABp1/d3QDVgdIZH16J5Tyrvuc58lnGDR2PLUzKw/XmTWZp0/UAourYu/fict6ADxy9eJ78Kqv6LBH/Ckg51xxXQamCRcujSqe2QOT1Vkc1X0gaL1yfab4uIEVrx/Q9WwahtnrJcRiYersUPF2ZHHbA0YC2TN7hSBEA98rGZWT612+/BG99yvEDUK3v35GoC06/53u+52jJsU/HKe2s6kHrYafXHfqaG6eXzG1wN0PQAC0ZqM3ZYDCiA6MalSZ9h+acYBukE6ZTSm0wVwecgaG7ZZAcgUx87FEXoEo8D5hC0hTKohNH/1YvFr96CD+952x45DmMBuCipBVA5TKRbNuA5BkRm4mAaqVylJ3VkuHomfmhTq/5V4MwObtLVh8tXpZ67ZWryluEUV890pUXrpMixsdb2TSdaVzdKj3XJz3+kVyW99zzvYCsHk+A6idg7K1GbJ2npacw27bKdTrHg/vx3Aq+y2MMzxnlnAGWy7OFdnAJx2vGhxSDbW4L1YQcC0xh9k57Qrttt9lK2FxM/c4DbWofufxefTRjltMeDZQfWE1bfe3AJYvH4wjzLHpBvaLEW4R5XOu1kwIcHBvoxdXy9Np2NIZ4AIPBhZfeG5N4nOkBtbIq5zxXEKnAVLep9uRi3iXc4ki8OTCqutE4KofF53Bv9dDK5dl2SL58rSuj0burZRWVeYheKx0wH4uregjqn8sY6S+ivdrk243S/Lh4vNH+gUj7dMTJtmCpE5NBjg/Fr1ZHxj+VA8KRAyPSzAbvkYosUgbPUWZRdEW5cprGgrPT1zg4qB3nuTLYe17N6mWaVnwZiGgcBkgcpwAKE90b0Bx51IFZUgfV1l4tB4UVXToZRyucKlsEvj1qVhgcudT5TvVtWUkx3e61TZa8SD9aRxHraLyt5BHHrfAfb/RUVIvnrsJIHsyPG2TvXVIG7VX/26KMqm/uV0tWGqO68t6L9fKOeB6KAxTx1c/+ePEjmxXl4+nOuwZQAGaS+PbfVkJKEyDbw3bITuHUOuL7RIGVPhwnnf9L1OZaJ4pYTm/ixfpjKpE3z4Y8vmsLAAQscwZuW28mdnfS5pmVi/vVzgo4Ae2qq+lxGMdRc+J7ZE67ybsaK8CSsg0JfzS+NPUu+bgyOLYlmqTU594qOz/3gG4EDiMAEz1XcKXX3iFHc3lo2bSMqpMIhM4BUA+IQ8KjdNweNI4H0td0rfoB8eL3Qlm/unWXZTZQGgFScHpHb9FECIDmszJGT37bJfj9px4/q6d3NNoHp/t0SMTv/uQMXP2/L6kcEps1Xo9xLKykY8c6t4M/k4cNtllFmSN2PsxZYjDE313ynGQFxImurXyWiJ23iKc6REvCVQ4FwiZDKScmh1DlNBBiET0ngilyShiYzJEC1IYXNwLvOdr2EQLUDhXn2f5L3XK8BqgJrwH1BEHlIG5BSa55IoGfRyummqbSE10U0EvPCyBIDpj0BOzIb/osTq7T772yLFnh1OfchrX/6HuAc2CxdyCNfn80mlxxZWabIzLas94Kl9eW+B1Fcwo1vYIwDevZHq88bD8yfD58z1tiLa3pYJ2BPH4iwt4/LTqRPDks80+c6EpWiuM6+GLvXFskZeSTfzk/O33XyPJbZ+DEHQAD1V+u/m3CV229VGDCAxoiP5fNvndanVSca54KMorTT+NJsSe5zSci1bP1f86beRk44fslK1+cl/cfDl/NN/pveuHtqxEQruQQuS08AmtVWZRXEKZl4HJq+NxkTQP0HP0075JSm+FyWT/0dOa9T6r5RLo2ubzJCy2rd3qvR3PPj1Xa0p045mkROP1f/+t/4f3vfz/udKc74TGPeQxOP/10AEDOGa9+9avxjne8A5///Odx//vfH5dccgl+4Ad+4IgKvU/HDrHTwIaFB242JHZ0fgamLWAzTmca/6jT7NmQjL11Ug9kNHHEwdIwDvfim34SamcjSqdOnT3zQIry4AiWn6WvykYVxgDG42PChyA01YODJtdwdkzY4YoOytG8Iu9kiXxzVMnZkwFtfTTxxj9z7XKpbM2KPJx2wnzleWl/W8jAYEL7vMqi6bx4XOfRJEvDS55XgETkbnhKWDXxIqR9VL+7zHnm8WbOXvSoZ3OA+tuZYdwFbWedaYeFyZd9XXh2pQdMXVHMXlAg93Gt+0w/oAZH/C1dBuI5t2Hl8xWBXLz64r07V5VBym1tgutDJ8y4vfPKsPbDnMfV4VXtYDNZu2v0IrpS8voEP2OZzGnnYjDoWA91vUVVP9cEPcBQPXeAhemE64jjVhOyND4pjzlQqnmrHFVbQdtmvG2pCkiVd/RuagNinftefKaorBq3Gi/keTVhQOWyMkQn8lr+DFbn9Fj1O+NBvPjHFE0ORJ+TAepx1MqmcZ/0e5fgnRftr57eHjQLTl/+8pfjRS96EdbrzdrXSSedhN/93d/FE5/4RPzYj/0Y3va2tyGPtfk3f/M3+MM//ENceuml+KVf+qUjK/k+HRPEjoF9x04BTmWQ6TkDNLu29EoJ9QN2htWgeVuwen5itAqqjrSm8cI0vwoQkaPirnJKGXqya/qofKm5mGSwmx4gAWo9RHlUgxlinlE+Wp9zq4r2XsySfNRZxJbyqazGk+8jKnUt+S0FLlH+EQ9tOxamDoanB61DJV49ZdBnYT2Hh9thqWuvPwR5l+Rev3Pyj+pHQZ7yZlul9kBXYYtzNcaZm1CZy8+TM5LZsz2RQ8myremTLjuSB/OK5NDnnixFBlDbk/bW2Dg2tOLQmzPK4FR1k1Fvm2dlqBMfyaqObQM6nXGl0gPXkeiQx0m23b12741HWha1bRmo9Mfpla/pV+27hdnWagMVpXxO+WdXoxCDkCheBayitAEjBabr7D/n6wgEettUFZBW4JR5S169Fb4IYHkyqY4i8srWA6devtmTGfXEDgNPXeXULb9DBoahbn9FjySTrfAr8J3TISid6kF1o3z4/nijvfoUxyqteg//7M/+DC94wQuQc8b3fu/34oILLsCtt96Kpz3tafiv//W/4q1vfSt+8Ad/EG9/+9vxwQ9+EL/yK7+CO93pTrj00kvxl3/5l0epCPt0e9LOqnXcAN+RaIyDhDUGWOIn+jUOiv08ZxS1jPrbhpKUqyonycZhHJdl0TQcVx0ay7vnoHqyJuKXKE0VLk5Xk0acKs7fdW6duD2ZG0fV+Smpo1fxE5lY1xynu/ojjc/TiadXj9z2F+UrP28FqPCUn25TdeXv5D1Xb54ejbcnk+ZrcbQ/VCeXJrj65HbKfJs4mvdMuQC/j3H0MrufJ0deeW4LTJW0vdlt836lUNRv9N1gXW20tJUNSA6/VF/32ldULnbovXS6MqztI2Pj3O4O0//b1pv/+quADJY5nA0wIOdatwVH+uEwO8yo/Kh976ymH7ezCCxUenTAi1tvnk3kn7SFZtVLwJW3Kmj5eEBKSQFOkxfJ4AFTBoXajtReVnXvgA5d2fOAT/SzVWQv3ADXmu6b/0Odn/EL+Tphmmc1iTDUaYw3b6nl/Kq4uQaQRd8sA6Z4u0Mriz3jMu5K+XctX9RxrG8Pw/S7bQB215QmtyvB2pZMRm1XQ/br2vhy2dfye/zvTod6Hsvk+QRzv2OZuiunr3zlK5FSwlve8hb86I/+KADg3e9+N57whCfgp3/6p/EjP/IjeMc73lHif/d3fzfud7/74Sd/8ifx2te+Fq95zWuOrPT7dLtTdKS9HZ9fjAnI4ZBeUWbW8xRPVxs9SuOfBkigdroOlTyHxDtsJEucivhhnvhytAocBvnzcw8YeuktzAbs6pnJM/6PHBvVc9K0mK73vGraq6tc/Wt4AIHzy6JRG9O0mr7IFdURHF05MlblmyGrn6gMlt/cqnLU9IDYwazSUhj3Jch1pMdQLqonLZPGy2MG1rx0IsUrm/Lg+GqfjDxdqk68fKwteXE98vLR1f9IRnumei8TBVqHVGazreaM2Lv/Zp91soHNFMuiNlBliiiXP5McJiNEPibL05zqAv5p5RdjO7JnBv6AGsRk1P+1DAxGgaDu0xTH6/vaP3ZW7RjBbdfqfglp+3WGkiJXNWmX23RJy9exnRYeAfNoNZPrVm1aRpvGyqETPN6KJcsV2QEGJZA4Wk6dgLB8uJ4yaoBj9+V6oDCnHNHKaG/1FECjNy2/guyiT2rPajdMVma8CtqA1pUHDHVl1J7pd0ctTgUQUcfxyujlqzqNTu/lMPZD+b4KdG617+3T0aPuyumHP/xhfOM3fmMBpgDwAz/wA/iWb/kWfPGLX8Qv/MIvNGl+/Md/HGeccQY+9KEPHX5p9+mYoyT/dUXRTiTcoe+9JYrvbrdYkq+ABF0FWCo7/4yvrp5U8ehZtdqT2hWAJl2SdCp7J1zLrbrQlScvbuRUbQvgK71smXaOL/9UT5y3m17ahMvbcYQ1fXRvfKIVSq7DXh1HdXs4thNFdd9NozIhbuPalrWeWA7vp/l1ZZA2rTsWlpSz6cNBOn2fUeWrnFgnDYM93fEQ6aM3ycBOVXHC2AF0nOoqL6cdrtL03c3KHnO5IfXEOqNnkHi9MqiT2zynchXekndvBWR3XGX56nrz2RVeaWEQYHx0dY2vdeWE65vTcrmrtoq6TRxYjTpfST9a2H5ZH9peWGZvHOW0nKaklTI1QI11Izw5fZMfpJ1Iv7b0vJrGK3HN6ioEqEp5K3lFZi6Xx9NbSbP2dJuzqsn3a1oFXOc2Lq9eRqugzXZXecYrmtzvl6SrZMyoViy9Fd4BUpZMK5qin13Sk/W3Nd0PQ11+k5/z1JVN1tGupGvqiGT0Vkl1VbTUwfir0qAuu+okA3js7xzbq6dL/Iye73EsUnfl9MYbb8S3f/u3N+EPeMADcM011+BBD3pQ82y1WuHBD34wPvzhDx8+KffpmCUbIHh2q9rqCyB1pkDy+IdPD7QVCcAHEs3Anp1IHVKe3qqAzebbKav8fCvZgHqWN00DegSUlH92ZAzTBnLwShjLoPn2ZtCbMD+qnx6+vB41+k0obcL45FyvzHNabyVWHV8W3itHr41EcTxeVk+6UqBxt9Jl9uXRPEG6yPRMV1R6PLSd9SZKesB/El76U5CA9cZtuZGlU5Y5+aJVw+hAroxpVcX65CoBJ/BqHSbniPNxyzpTCVb2IftAlleHTCaNV2wq24HkvHJh9ht9+6I01w4j0lUhEjHk5a6uSJwG5KIuG+ffgFZMdcd2vpLR+kUgczOJg1jHSG0+c2R5mzyZ+JZwp7yurJK+8CRH37X7eZJdx5JS1iDPajdVnvpM1c9RA1J7zmW2C7WhDdDOLS8tY7Q6CtT5uzwDOV2dOjw1rrdyCInjrsQ6+qkmLIhvY9vIvugzr2wVyM8TmOvFN2CqoNSL55XBQKT22UgnVVkC3ahqyoQglX/ltP99OjrUBad3vvOdkRzLedJJJwEA/sW/+BduulNOOQW33nrrYRBvn451um0tgzEN3mXLr4CExkCMo5EZBXOoKqe6I8O2g7umTXKdgWKwB0xCZEnXyzs5NwYUXKCjjjSH5Tauytzj1aPI9jJQdcay6TpgwI6LDgx7oQp0WgbBoNrEJVkYWEyFoHaW2jLpCklXTifM8mue5XmdePnZIJw6cYosUu4Sv5cxt68O/70Q5z1bdsp7qz6ufUl079Un6zOjBnkKDjP9eDXMZuuNH5dDV9sLSATKIXHqMJkdMt5zZI6/2mDVgepj4PbvPGeZIPH4XuPoM4/UCdXJHGvroHjcPm2cUJ4ljeOEaluotkHmNo8ij6OXTM9Z755ubHLN6lR1tbSJ86SM1nEvTQPa0Tr4RgzajIrznyYdsTxlnBNenizRgTglLwdsKDXjUpZVOUrvgU4rpz1X0JWFrwdKAR+Q9UCWyqVlYB2qDjyArXrkMpi+e31E24aXt+qRV2k9HQ+jUCYbx2X5ep/RYbCYnXhaDs630r1TB0YMRL02uyb9fN/BS/D+px+7J/cexmH6mKAuOL3Xve6FG264oQk/9dRTcb/73S9Md8stt+Dkk08+dOn26Zinf96dti3tgK5XBE4pPhurzIE04DJIZY9i286Xxz/RSqfnsNl/A6UFoFJ6dUCWgAQbzD0DGDky3nON45VpW/JmvqN4PaeDeczFW7KC13vG/lBGu9rlOWMM1Ji/AqbuRAHzW0hzWHARDydD7j9L6r1y6HuOLGrHZQnPRibneaXvMSDSy5zO1ZHpydXImCdwsKQe9VCikq+AAgMKGSgTcra6yqu0AzVctSmVrRSbMdfXrf2vxnT2WgXbNZOHHbWUNmnUGfXskkdVXUmFzNWhlZPbMjuVDAxKGtFLac+5djaNN09A0HAyu2rfyJvrHT6Jnnv2mtsZOL7T/pfakwoIjvx10iOyv7qCW9LAAUkk10p0bXrg8ldpBRwArR7tf7g6ixYkGp9mkofkqg71cdq0B1R41Y/BV0mTJ3kiMNXLy4s/CB/VX9X2RWelvJJeVzJ74NR42IVnxyNZmT9vnYUjW9kaK3qMVraXrI6q3hgIc9yqjPD5e/kw2Vh4OCdojxQdDzJuQ11w+sAHPhAf/vCHkXOuVlBf9rKX4WUve1mY7pprrsFZZ511+KTcp2OWvrqeOvTOTv1ek+eE2uAa9aM8/mFAqKdpWniVZoY8x05BXuOMjbJ6J2Zqmlm7wE4FWoPn8VKnSuXdC7HhnhVZnRK0g8Q2pM53M+MuA/ChkjpjVqfq7GeKq7OubrvYiyzYm84MoMw5/W5a+LrUvuOy6oCKJiq36V48tPWvTqunoyMx5pqjovx7dWS2Cal22phHSuNBDuNknQJD6/fmtNlrA/qpC5aT5apsQ651P+QNGM2YgKl3urL2BwZMtvrb292hkz5LJtIiapx4CXeddzjt2upFwrM6zeyw5wk8ms4MdOnp6Vqm8iObzUDR+m3ZIkzKiMDYNu28AWmUp903eQT5MnDQ9mqTfp66bVzXccq139S++F1ED3yqTFxnlq/1JW4jZTVuqGVugDXFh4QVQJVrMGPxw63GIoOGQ/Lj565+jR+tMDfPiJ+Wr3q1ILfb/Tmt1Z/uQjK+Kp+dqqvvhWoZvC28ESj1QL+VScuoq6NRfG9V1JuYUf5GPF6VPrxPR4264PRhD3sY3vOe9+Dqq6/GIx7xiEUM/+Iv/gLXX389fuRHfuSwCLhPxzbdtp467U73eK2JilOaJ+NYsME4QvYcaB2YGfwWHhrHyx/1QFxFZ+CU2zQcjcNCEELlsjIbew+Uqixa/oj2MssXrWJ6M5hAUD6PbyduoovK+VjIXKP1tj1GKwa9uFxPlbyHibyZ9rm4kWzaPyysAhFOn2Iwac8zR1hIzCNK5k0INHyCdhjx8/TmTTSVNCRvHgOqXRpL8sUkY/VukuWLCdRYXhU4RV2+ARNIWsF3VHXbbeGL6UTD4owO4/c+2Rmjsg1DqyM+rTPSXWMbpWwRRbZoSV9c2jcYtDTPKb3u1lmNOue2uWNlS23dWRymZlwiuUs7oHGE5TL5LT+3T1AZerpI4x8DA0rbrBaZPKnznG2StRuTz7PFpqd1ng4aUlDjbZ3XdzC5nIAPdph3JTNq0Batrq6D03d7236Zh8efy8Ckq5w6zqoMzIfDSz/IdRmN31r4snzWxodU8y46VrnydMDQrsgP0MRBruXvrZTqBAGXvy741Da4DZicLKOnzyXglMeoJbt8jhW6o4HnLjh94QtfiJ/6qZ/Cve9978UM//Zv/xZPf/rT8dSnPvWQhdunY592aZb9wKo2zNFAzk7RMN7PbTPkdHOkICfJswZQBnx5Zc9zxJY4LFVgJvkwOTORXIUihyQAcwrOlwK+4kAHA+pSPiojDyhRvtuw1gFsK3m2SHOktskscbpLXO/GgGSu63grEF7+0D22rwuXb/DA65OHkpcHTPl/mM7SjoW1lUzvhN2efDw7b/pkPYayZQGEahuobasTquC0cZAxnbKZMZ3IqwqoVgYt3zpKp+Cbf7OfNBIQW9WXgDbNjycwre149aF1Xeyq9AV1fHW11yYIVG4vrpcf3/NNprJ6Os10Ua2Ein1TR10ndTnNEgr1Tbwim03V1tQL67mqgzFcT+VtbDkBmwjoWvtV0MjAbD00SdztqbplXEGuAqU5cMorgNrmVH/ABPKYl8rctAXi27we5ZTTG28qwDnWlR3+o2CUwW4i3fD3TrlfpRzrK1op1TjcX7wmwHl6u07mtk3raj+nAdrP69zRgN/xQF1were73Q13u9vdtmJ40UUX4aKLLjokofbp+CHb1puwWUW9dZzK5w+Ps7NQZqIxfaRcKXnptpSrmfGeAZYewMySzgOSys+ocZxRO4BJnilf3R7m0Zwzso2zEm3j2wsgdfmP/w+VXePMoL9qWsmQpoFJgVKPhbabQ9FJNFi6cfU5K9FpgxFFq1tRegNaS8vZaaIVz7JyKLo3HiZr46gLf46rYEP7lbfLob1pZeXr7DxjmQyk6sneIX8rIyZnzibqBjpQSR1LzjPRz8jkMMd8nafPxpS8QHaIGCYAq9XGQS0OJfFt5Jd71lNkG/cyWVaB2FFmTe6NE9V/a/+5lqX65M+qbUtalsp+YJzQoEjlfhK1kSUcJ4L+pvWvMmleS4id/tk8cx2nyCH9k695MjNLOnb2B0lvE9oN6CIeRs17oqjBkAdYFDAWIMRlhbR91ABrEB4cR/OItruqfjg/nYDQuldgzWFsmyoAK7qD8CxAmWTgiQHvfVIG71zOslVedGBlrD79IjpiUMrlBd0XHTt6bPQ7w8NocJ5b+zmeQOmRmky/vagLTg8n/dRP/RR+53d+B7u7u0cry306CrQ71E5Sxmbbzok7m5+9f9p8A3R0yozUWCYs/5ahR01eFp78OPrMZoQrnp4DHMgWyiyDRG+Wvtw7xjNizbOCbpw5Jg5PliVawShxxmccN1pa6DkfR5LmwKibRtoJOydLKIo6W6c88OYp7+KNUJj68UsndrwVm65MnHY+ep0X5vXntV91LLIT1wMpPTmUbPU0y3OvvzMwZbASAbW5FbtEz72VEXWwkvy0HBg22/SGNJWrnCycgWz3ebKzq5FZymOcPJXJSB0+b/JujnhHCk+0NO0hEYjhglO8ZhKSkmdMW5x5JcSyZtlXniKlrMzXmBigMjvH+mL96bbvuTwsiwbUcV+3slCbKfJ1eLplovZV8nRkZPvTsxvaZqOtvhUYs7xznUbBGcdXcOOBNq9sVZmpn0VAVMM9+fR/kU36bqQbtw4cniozT44ZRSfcenpk+2PxvFN4me+QW31XFWNysC5ZbtUjtTlPzmjLbq9cTpNrt0eHNzGPY5E65uu4paMGTgEgHy3vc5+OGuU8bSGzD1ffaQcYTpgOR9IPwQNTp9fZxeI0eA5qMDjy1lGPPGfdA4XJS+TfurPrs9sJcxynl7Y865SxGvAWdrO5aB6fLjAV8FoBVGYgsrLsR5J0QI7y9IDENrRkhWhpuVNH4TmjBqhO+9oGmNo9Tyq4jvlC3ppHpX/h7xWTw3pOB/dnlWuJjFzf3tau0EZ0yGQ3W6UArNg7AqhaMF3lqdol1T1ILmsTlm/GZkXEnEArgx2YBJtcHFdNDUgVsVOrewZF27avKlz0wjtLig4znYCMqd1A4nVlofKoU8/lYB7c7hgQMmWpg+q/xFubbonPkvFCbUS5DoBh1+YQT+Xv5WNl53ZbrRZLW/Z4u9tmPRBAaXurhx7g9MCOhnn2g8vEaflAJY8Ph0eyZaAcZuTpfgmAjkC6/dd3VZuTqoFGL54PUfWpLADU8ss1P141rXilqWmonM0kQudzQtFqr5bN1RNiW5Cbi1Yf+3Rs0FEFp/t0xyMzPsO4J+TWNbA+AJywg+LkVqumOvrbrd3zYOhcG0UrjGaYmhn11KbtOZ09MKrxes96PHIQz4vTXOc6TO97sriDU/CMB9RGNm+gmwHS6rtFjoPKxXlyvKVbepdSpjYUycByKFVtqQPueuW2fJlPk6869Xk7ML0krldX25LX74DJNkQAlfXvbfGL5N2GvLbONiFaSQ3zV5vj5MflypzO8iJnE/C3BhpgQ6fOdSKvOK65PoF1kPRlCzCVw4RmJ35pm5udkNMK9zpCRtsYEevbsyFldTFhs6qc66zLqjLHxeQkR/XqjU1KaqMLr8A2WNws1xWo3bK/sxPPPPV/k25sf7pNNrLNFUhweJcw/kk6i2dyzwFBbxutvuuooJjtsIJZfg80AkCz4JTL6eiF81ZdVYcXUfkYgCrY07phXlE92GprtTsrIzykiOVinZUtsGlzQrkRg2fVrzd50fueqU5wql6zBWJ6XpQhgawDSdYk8Z4fk5S2swfHA+2D0306ZGJDcuFDNh8p/vD1l0zbmZxO0xgEceSNnzkOESW5UQCr4FFBh27X7JE6LlGaCPRymdUR5nCP1Gk1ftFsosrRM7AZDhDJcu+EzZGCjznS8mh9Hsog0ZNBy0nZ1+llgPQo6bUHUPWewi0bnchRGVUvyQunAO0HSyjSi+a7lzFxboWW46iT4vj1lTxMvM1SdeblmVE7/wZQl+TF8ukKghfHgtm55JXUOQeUy1U9Np1hWqnjerJVvDxMgHjgNKk9L0DLsBaZ1Wnkcvao2V0hZSo6pB/zdMcXcWiNnzfhYOOLgXKWy7bsWvu0SQHjW+okT+0mq4CYHHB7zlt8HbHdyQi26QVQoHXeOY1Sz4aX8TbVOlcwkbBZifcO5teJlAj48nZXV05J17yXKHE8AMbbTfVzLCyPB2h55dTL1wPDSwAp940MX2aWyeLt0nvoXF8VOOQGQuUsZco+jzXaPs66YBDK6YyXnYwMoLwuoPlzefU7tAy2o3Te8yI/l72+DALaNgpMcti5Ady/dEV6n44O7YPTfTokYsdoRSOWGfnbhtqhUCcAoJm7Bc6M5dkLz504mu+2wFTTRXJ5wJgNZbRVzMLVGHsDm7LVeNFqxJLJAuY3R142vW2zmi4idfR0pnPbVdO56D2AFD3neLP5BwOs3Sv7ymEnx0fz7WVtDudeaUk9HirvCGxGxDrzdiM0Tj/1BwWMjk+3KH9rm9WKG6Y+bwBkGOMxiOBvQO+OAHEYQanFYYAVAg3+5ansXCbTEW8n5Wf8Xqrx2RnPCYB9rxp12zN+5aR1kaORVeyektpI3V6rP45uny/TSS3Ar9NSV3mqKzu8j+XlsurkUFO2VOuHwbbpxIBuGeqonJUjTO1SeVihXF3L2KDy9sYOBlag8jCosfZRtWsnD16RVtDFfW+QuAriettpNZ6COd42CtBKIOWlwFD5DUF+KrvpzstD07HuozIxqAbi74gyKGUe3A68A4s8v8HaIOfLevA+FaPylomNoB3aluICTkWWOV151MiFuo1x+ZSHglK7X1MaDj8e6BCG+WOS9sHpPh0S6Tukb//rS3DiDnCXEzaOjTlfwMZ4nbgDnLCa3kU1R85dYZrJ2wODmcIVHDZgcUv+HJYXxFPgkERXkROdxj/RLKvmHzoeeQK7Ubk80rJF9aBONES2yLFWZ7cryyEODpFuyvNe2rkIIy1aIXJY5eCaw5rJiyCuOvTJCd+WPHDsPj8MpCto2p+L75XrdpUpQil3UObGwZPryG5weuuXS/XKE2/M21YseZVyGOOak7USnTAZ2Km2wqGOm+jHMrP+Up4AqpXxQAbyauwzaYrPdktPU2dlZsrTWx6c3W0ius2pBjLguHTt6UCJJwlYN6Dy9/LSFUu7zqhXWDwnOVPdAihbuR0VNWVpxh9nrPR2GvBzLnsll+TJgCYqq8fHA0GeLlnHEYiLwKnmF4LTYeobumrI/FVWBaYeYNKVP86Dy6j61HrwyqnvkZbyEA+zdSxXU0ZJw7pu6hF+XfK7omWCIaE9yNLRo9oD1q9XHyyTgnblowE8ceP5Z95Eih6wVKJkTL6Xk+5Ypv1tvfu0T0QHxpnrQQzUbQPwlds2n5qx5wdWwJ0PAF93ALjTgQ1QXYEG6NQaKnYYI6qcFAkHhbsDvDnBeR7IquPXlUOdN0nrgUwFc8VQOwOkpgXqtBzmbfmKDNkcGFTAUOlMRoZSf+LQbWvz9zpGbANMXeBC7WOvFIHJOWIdz/GP2umhANM5Wsp3SVtbUj8KSLNGJHCiYHAbUll1S28PmJo/o3aismNiI8z+2W8njdsmR1uYx/87aB3gdfa3V5b8TVargzy1l0qeDGA17XIxx3Ani6yjfKvV9AmwygF2HFJ3RoPahLZfla9Kltp24rX9XlvSulGwaWXP9Dysb8qHV0aNj9euC99RgCGoQy1TVB5PnqZ/dKiML5SmjDNOXqafAmYIkOgYxf8hvHsri/Y/4snbXxWcMmisQKRXviDP6J1IjqNAS7e+MikQV5CoK5QqE6+QZuaZfaCXRTbPzpZ4qLeJA+2KK+uOV/wLH0yr1NpWVN+qW5WP9dUwVP6SDrl9Hm3J7doq4bPXMXyfDo32wek+HRKduDMdsHHbMHV6e09il97fODBu6T2wAk4Y47FjZpSz74gY9WaItp09igBqD5iGeZMMntPlRs6t4SuD08yAupQs7tzqgudQlEFp/GM66uVfrcywZZ9J18gj90u28XrO4LbAdE4O1V2ZSHGc2GqQC8ofObDm8O6FXFn2MML29LcNQD2U59GkzRRhbJcWd4wUbZ03HlUeThw9rddk4b4d6SBTxl07MIaZDTQwihWQB5R3uPSbkEazfSLT4UlOGcqnZCivnIFhVYNhA6Z5hbI1mWWInLlqxQW1jbVwS9PIRs/t+6u2isoU2laVKU/tIQXxuF01K7gUh+0j28QI8FblNiGojbI4fDBWVQYBhB6pjCp/F4SS/Z8FEQ4Q0PFJ89Nto+54I2FDIIfdMwDl8OY7qI5cqhPmF279Ha+bdyepDJ7OWZ+sS97iqvlGemJQ6oFnfdbkqWVB639VK8iDU7ZEB6s5eZg8HLYmOd16Jb0h4Km8vbAIlHrjbMSMbZiX17FIe/UVjlXaB6f7dEj0deMnY9YDsDNsTuutBjOaebbVAHvOqwW8Pbj5BdZhZF9or9saGKACbSdfBEzJEY2AKTstZvyaLYqonQY1/LpCvc3qmDlIPWA6R9U2RW9QkXhaxibe+GcOoCwBpkq9tlPiOIPgXDvynBDm5W3925YKMBWnoZLVAWJV3WzRNuboSA7QXvuonJzsx2NdJH1Ozv9s/iRHr+8yaALF0/DMdSD8rF+zQhkk8oEi9t4ne1raVs1B5DBWZYLjqOXpXVITs6QZQeo6T+/GJqB6N9VolTaTj3aATAPmpL3aDhlus0w8Tqi+c9oAVF4NUvvfFFNlojInUhRPjqZRYRki7xifdcv2RUF3Tx5gKlvVFqRtdfvElKQJ8yYXLXwQvTFIsftq5Uz4Mf/I2Y8ApsVRMLcEMMLhM+TxVN2M6p1PBT4R2ISThkGZB0oHhy/zrtoL2rje9ttKllyvlDIPLqeuGButiQfHB+pxacjjwsGwEXon1e9veyu5WtlD6jwHmq2zXEbWcymk6C3ySXrjqnvAEj1PHBbwieIfyni+T9vTPjjdp0Oik07YdODbBgC7k9Hj75pG7+skTIdRrHigFgDEs8s9ihwEztsbzHs+xTbOfW9VRZ2kyPHIzn3kHGwr3xLyBk2gdZYYVPKAzMZcV03VuQPHof/cPg7HeNDTlerbrpeAmojvkkEsRfpgmezeiWd9ZfQtpq2B3Gcy1QPqutE8G9m2KQddV23EaedLKGrrPV5Z0nFbct/rE4dtKSl41e83qwh2UTmGDp/CP031OaTx9EgBt/bfc7DUsbI4mpdtCS5ATdJbuysrl2l6L5ZtvDnOGGXeEVkbJ9EBsJ4evNOCB3q2Htp2rHajWaGl53rKr93nDCTZZ6srw1WeiG0wr3R6bYF5mPzeJ4K8OuVJGA7TvuNNjGQSWvuNZ5e8/rgEsHoreD2AOAcaNX0FDhGDUI4H1NcKdpu87Fr4K0+uG8vD+A8Z2M3CT/7zZIUH1vWzLNYHI+C5zqi22mqf2x2A29bTpNKQaLwBqnd2tZ719QILXzI5U+nRhCO9eaBS7X7v9FwX0DJPGgSdYrT8enyPIVI7fkegfXC6T4dEdz4wGZrdFbAa6hl373ReM7zlPSY5cZHxSuhR06O5TrnXFdWe0zEXdw7weobOG6D1ecnf00cnUwUNXt5LibewRfXDDmKTN4+CVeTp/55Ajeor4BHpd6+kbKImO5cfO+JL0lh74U9jmOPJK1nqOCRJH62wunUVlG0pcd+fmyxgB62KEzgK7MwxIF3iOM3tQOjxSAR0uvVFZTJnIqEtj4XzoUmFB6Y6s7pZYapvc7oK+BUnkGUe8gSGMsTpyxOPhI1TN4z2eo32oLsVxYv0yG3UBWgzOrb3c41PtLJnOuS0OqaYfjW+1mUFPtIkO49V3opxVI5MP26flR6ov3EfYPBS4pK99BzpyJZ411F/WxF/1ndvAlVB4iDXmh/zUGAX8bC4cwCW43nbSSF5Kyj1gLKuhFpb8sDxWtJZmfUTMCugbKHVlVLlaa9L2Q4ba0sMTHVSxQ4yshVnA8zW79jWqAyVnnIldmXTdHswU1U3XPcip6ZXMOoB2GqI8pjJM23rYX+d6RvHEu3Vzz1W6aiB02c+85k4//zzj1Z2+3SU6MBqYyjN6eBtQ3qiIxtR+9A1QAaRDFez+ph8I9bMjjvEzoLJ1qNeJ4+cWG9LYJSGyzAHoCo+qB0s+xc6dHKTnGeucd+CikwB0ijPMuoC2IBIwfyzQXmpXBGQNxn3QtpWdJa7l25Ovh5xmaNkOkBnS2gBpGvrm24bmAFlXHfVYL6gHL06yaRcb3Y+cgYW+B0Vj6jf6/bcOUBl13m8aMBVroGNEjvcpQ2xrOS0Vj5rmuImEihhdNpy7RhbfUWrcxzAANXK1WwDJKeTbZzlWV7JkM+xwORlu23/KT+IvFb29bi9mEFpWU1N2LwTO0zjyEBt1KtPK38pK6aylDjZv/YmjFhHrunrNNQCduDLWfX/XF+r3dZ+oiCmlAF+uJcWTjqOq3yWgD3dLgvE6bcBm6BrL020/TYE2CJLdS3582qm9z4lA0td4bW+UFQmZeDVSS2bF2/VyY/J0vJJvOUZxSv6Rh3H01v5n/1VTQ9MIre8tnpPVG5yFCcgrx8ELowbf5+OPHXB6ZVXXol73/veeMADHrAV0/e9733467/+azzvec8rYd/5nd+J7/zO79yblPt0zFLl4KXJkTmwmhwX7tTmDAx5837q6raNc8EzduwAqWOoBmKRkzz+UYdNHfW51ZMjTTyTaKSAtMhH5Ylk9lbLNO5ewR+vLkRGvVrJcYApx7UfO9ylvnP9bt2cbN1yBNdhfKfd2IC6uO0JP/7v5bcXyuUPmkmAWYC6gFL5c2iyewDAcwA8h8brF6GsIJ2IHjiO9vloV4Hpj7dR89Zpr11zes+xTxoH9coKy1rAKRV8lab+YnZ3EBmW7rLIpCfudxaNgaF9fiYBZT/5ipzdotPUlkXLbWGQ/GFlYR2M+du4kgDYcaMpTwDVA506dkRycP1oX9VVozliXpbeJuR4xUvtuOvMW3inw3rAi5u/yuOl8d5jZDnmgCU/90Aj8zceCkpNHl1p9N4rjbb0KijtAtNcy8LlUR3xiqlX9kH4MljWU3e9tsSgUWXVQ56qT71QPTEArRSNKW+gtQEDxdVylLRSd/y8TA7BJ9ahybl2dKB2scmwvW1l6ZC2ZTdj1GWN+sWxRLen73okqHuK+fnnn4+Xvexl7rOTTz4Zz33uc91nv/u7v4vnP//5hy7dPh0XZIca3WkHuMuJwF1P3Hzn9OtO2Jzme2BVz3znvHnf4Su3Af/wVeDmf978/6fb6gOVzOGyj8LvEOCtnCVymkPHGfGzbbZDsHGN0quzu43R8ERUkKkOTUr+r4qPWl+NzFtaNpYjypfjal42+VDVJcuI+n9EewZznXRLdZEX/Lw8w4E1SNcjc3aZrzo2h0rezgejw5VHD5j2+jWTyjdXx967qEyDykFyqqOmwJll8dKU8EyO80wZk9dHQH0P9eFyVbpO3zcncXfYnB1w21A7wPafTyhtVrVQP6t0MQeoHF7aHnQrpeVhY8+B1eb72SesgBPGMcd+J+xM4XzGgU6QzVHTBjqJXHCEts14fHp2YK6deH3fBWmO3j0HnPtfUwZJ5wHDpk7H+9KuBvmfpxXxwYvv6FV/66H/zH7arvnayue1O2+VdNdkHt8DLav6eTo0zECk8uR4ahMUiEb3rLsiI9cJpry5/iH1uSbeWqfexEBpE9JO5iYHhlEXGSRnrq+r+6BPab2qTKEcOe5b3NZNp8c6ML0j0twntpCDWrnlllvwT//0T4ddIC+fpzzlKfjGb/xGPOhBD8JHPvIRfOlLX8IFF1yA+9///rjgggtw8803F1mf97zn4ZxzzsFDH/pQfOITnzji8n2tU8bGATlhZwNG/8WdgHvcefP/pBM276SeuCOz3dh0/q+ugX+6FfiHfwb+z1eB/3vbBrTqJwwMoKpDwQ5gtD1rjg7HamkP9C7lvURkdkQ9B6uKh1o3uj1QAS7/h3PPzjyDXM/Br/JzgLvnVOvKu4JWC19K29ap57ir/NsC+GqAJ4dGQepexr1oIiCUw7nec36S4VKerkOg/yVOF2DKj3l6uq36wwJ5gRpoFd6Oc+NNFil5espOuG6f5X7mTex4fcYDqUbu4U3k2HpObwW+k6Nzx4H0KNJ7ODlBfAuAXk9gII/y7KTNGHTiCERt5075ORObS8grRtWHgzrlZ9uASbUZ6kyz061x7ZnX3xugKHEHzUP0zqtdXjqt+wbAkEzWNhhQ7Qq4sHcmB5Uh1wDMBSoZLkBdOzx3CUR6bd/jDdTl8lY0q37g6McFgawvyH9J6wFYztvy9OrFdGDto7QTkcNtNx2+JY7zYxBufFj+ZgJE2ijLo/ErIBnI3eTvhPPP2ov2u23oaGOXaJGi9zuWaRac3t70sz/7s3jc4x6Hv/3bv8UnP/lJPOhBD8JLX/pSPPrRj8a1116LRz/60XjpS18KAHj3u9+Na6+9Ftdeey1e97rX4dnPfvbtLP0dn9gxOmE1Ogc7wJ0OTOD0hFU9k31gNXUM6/BmKNS5bf/vgAABAABJREFUSY4joQBpaR/zVgtT8GyODmUmrTiZEtbEcxxedcjdnxohCl8sYxBXwVtTrqAsltYFgR2QdShG9FCNbwT8jbwZaA1jsoG2CjuEdrQtlb7WyXNOZ9GkgzrpOpgvKaYnV5PPHA+VoVcXC2WYo6bfWbjoip07jwdfM+i0A+YUgFa7R+A/U0BmfHdSC2DndiqojWFiJ3KgMqps7oov9fGmf6AGF7v0qwCaJ+tM29G+HMWz55Ej7oHxqBmxDeD+GDnhDVjpOfLZ59WATtGbB0y9MjOY0JXNCMwV/qjBXXZ4lVXN3K5ozoFGDxg2YHeUoQBSWan0gKz935WJG0vnycY68eq+2o4rutJ4Wi5bXa1kwbRqC24D0rbWeaODZuuw1948PlLX5Rlq/42p1J9T59xJmI8LPqWsCiK9uqxkDXRe1Y/EgyPPNnS0scs+OD2K9A//8A+48sorcfHFFwMATjzxRHz913893vnOd+LpT386AODpT386/uAP/gAA8M53vhNPe9rTkFLCIx/5SNxyyy244YYbbi/xv6aIAZc5P7aVyrZZ2Qz2AZrZ5m1XO2k0PuP3Uu/xda/FXU98bWV4IPmY41PJovdwgFRqw/Zc9oBR5IhGaatVRNQOXLRqqdubq3jCo8mvJ5fI4T1340tezGeOh8rn0VxdHy6K2BYHggavMoBh5pdbPuXeGRiXEvNm+dQ5qZ4v5L3NSpPnzLDTdag0x8d7rnVQ5CRnq0njBEZttVlp9+IE6TmO/ff6ckrThB7bPBek9sCgyGF5mF3mHSoMbj2Aq69UGF9WXWWvWZbU14vnLCtoYCeXV1RvXberYOrEDlL3/F/7qAfsuGwRSIx04fIlPg2okjBvtVAd8qrvZ3GwUf/YQY/kqmTLU5oeeI3CgPaZB3x09arUX6dNeCCVAe8SoKuAcN1Jw+GlXUFAmrSFCpwHuijgjZ6XnQKiU95KbFt3q7rD9MwDaA0IlbbhgVi7rvovlbMB3CI38wPqiakItGt7aPoh8bOwQeKAnnu/qt1Lf9iW9rHLodMx/SmZ6667Dqeccgp+6qd+Cp/85Cfx8Ic/HL/5m7+JG2+8EaeffjoA4N73vjduvPFGAMBnP/tZnHXWWSX9mWeeic9+9rMlrtHrXvc6vO51rwMAfOELXzhKpblj0pDpMCOzWETsKAGTA2TXOddOUc4bB2P3tonHP+9OzlnOPiBJ5Y9PzSokfD5LqZfWUUObHmScKU1J63l74ggqP30WrRyYHvW6eRbJofkG9aFJQsCX62s3LcmlhyN5q3iWX0rbDzJR23AHxD0MXtm51nqY5SH9wJwAK6+Kz88tPUfSMs+BUXbuk4R7cVWWpV1vr86B8uBvZKq8GfEEyhLSeoj4WF9JGmYXWdJb3FEHOwlYS74J2HwiYrzO1AaQp4PFenKzs+k9NxvOE2L6XMtT2ldu4/X0bHIj6A+piUxlGPOqxiQIMHPaok7kmPwKMlNC+WyPVwi1YxrWjQ/pm20RCxU92ngYlEXDgNpushxePAUt7OxbfBcQS3oFs5xWQTWDslAe4hsB9LkwbQvKN9INb3FXgOhR0Z+TzpXB0V21WhromHXFsuvBRr24kfymf74PI6u9cdoHvw/r5cU09OJROUocsoNzvN0iLI04Q0cKu0QUTfQdz3RMr5zu7u7iE5/4BJ797GfjL/7iL3CXu9ylLIMbpZSQtkQZz3rWs3D11Vfj6quvximnnHI4Rf6aIzXmFmY/YHJudlZ0uFGaVk3twCSMvOxQjmtuvAT/44uX4Kvrzf3uUBt0b5XOo9620SoexbVyeLw0rzkHJHqsWwA9WXnVoVoNRbya4a6mLHC+dWXD5OCwSt8L9OrxnJOBqQLOFL7N+6cebTsG9Zy+uV+PKsd+yzK5s76efJHMkn5xvttFr9JpWgYsc9sw52hOfd6sffXM+HjAI+BX/Rc+lWwzfdDK773CwPnzcyuPa0dQ9z1+d99+zRZgCe/ZmB3a+cLvvtt4MAcIq5UV1Svqtsk/AwP8rqBt8+X3F/XnvYcYvZtYASaSv7KDXK8sN+p0VlbVg2cnFEiVw4HkEJ+5X0/f3G4UIFbgjeuQ0no6imSIVrD12luJrMJ5u6/Uc6gH51CvBqiizV9BrSefqzegWbmMqGmD9PPyrNqLxbMVRG43Dr8ImGq/itqkyeuVqYRlJ3D8aZ5DG6Wrc+0zUXvJ8jziH9mVaBzs1WOPjhR2+VqiY3rl9Mwzz8SZZ56J8847DwDwlKc8BS996Utx2mmn4YYbbsDpp5+OG264AaeeeioA4IwzzsD1119f0n/mM5/BGWeccbvI/rVCQ55WsnigtsHMHJkTsOn8vS2CbFx4wL9tXC7g7cDqFPD/hm+uHc5tzEF24jf35JghTysXS/NJiTLihLn6B6B9R2yWOPHIP6Oeda+yljgenypc+GiZmGeRAbXDx3KpyBx3KXkrEIvTotWrAo7shPWo1xasHfOECz8DnMkfbxCdaXc8s6ztilfaNM9F23nno4RpvL7EbcPj3dXnjDxmW0q7c3ipvWjySHUbY/2pACVunlYxrf3Y86pgqPmVPqFtUO61j1UTeFNwPfnmyJApfaY0ZQuwY38rGYgP6zoRr6rvk64Dc9NQ6kQyNXiAUJMx6PKe6X3ET+1N7sRf4gAzH5UPeaN/oK5XbRvMuwKlTh7RJJZOIHgrdZXjL+FA/awBCQiede712pUjo6wY6kpsJCfrR/Wx+PMwpL+5sdmtW69s8rP8+LM6XN4mH6lToLZ9Gm+WFsSL2liRkcs0xvUmVZhf2J+8BKmOp/0B8P1BlZsjbAshjzp2SfNt7nijWXD6uc99DldeeeVWzz73uc8dumTYLHufddZZ+B//43/ggQ98IK644gp80zd9E77pm74JBw8exIte9CIcPHgQT3rSkwAAT3ziE/GqV70K//pf/2v8+Z//Oe5+97svXhbfp72TAVRzsjNQ9eZyCBLqwa6acc6TM6Pb19YZWA0TCN5xOmFkjLbpsItW9pazK5QzugaOAZq3Pa8Hjrvbi4nHJmDKh+2vbg/TrTE62Fb6hV+fTRk7gDtKU6UNZO+RAvBDJW+ArHSEuD64Hj15umCI4veciFLfuXaYq/pz9GePVmNGLIvnQHly7ZXm0lt5vPayDUDNnIDaUrgNmvRg9g1OvFIG4qkoi1fbBgpr5E4lyeTw8jPtt1pYAUmJ0zoU7XzIkLzhr566PIWPyVxkMdk47zzpx5t0rMpEjqfX9xIlHHL9TEn7s/YZzUP7nvbLHKQt107ZFASb3Cqj5ZfSOB6KbYvSM58hKJdXTm4DzaqqlFdXIVUf1fOhBlYmL+cZrcJ6es7C266z8NVrT84ir+gEiPlA0nN8r915fNz+l2tgXa3cUnoFpQrEEvGzMKMq387Yan5XaStOnCh/C6veeQWquvbSKE+tG49WFN8oir9yFBGC4zzZ8KV0e2CXOxg2nQenf/Inf4I/+ZM/acJTSuGzw0mvfOUr8WM/9mO49dZbcb/73Q9vfOMbMQwDLrzwQlx22WW4733vi8svvxwA8PjHPx5//Md/jHPOOQcnnXQS3vjGNx5R2fZpoiUdgwdZc3CKsUW9x1zfa+IBpZuHNzCj9hu9AcHS7mX2qQID4x8GhQXoOQMVKI4HTNVa91aA2XGrIjgDE8e3QbQ8t0HT8RI53HMYLdsFVVX46eA6l34b/gzWPBk9HbIsUT7eQB21K3TC5+KZvqN2DbSTQzrRYXEAX3fc7xL/Aod+jjyH2sub62VpfS6lEKDyQweMA+09A9Pe1lzNx+ur3jugTb/EBGLnyOwG9xu2JZqHTtx5Zcqos+YVUz5kqVcGdYatTfF9CZf60D6lfCNgZau7xs62wfK25kbuXPOJAKfmp+2YHe2w2nKt27nxzICdlY0pStsD3N5qsqdfb8urhiv45M+/aV7uFtjcyuFt65wDxuV/RvUNUa8sFah0ygHUILjSi8jH7dTq1ANPO6DJHOKtZWA/R4FpRgtMvS27HmV5btfee+PZia/M9LnrR1Fepg8F8lyv2iZVdsAHmZpmSPVYNszEBTbx58DsCmRXt6B97HJo1AWnZ5999u2+J/pbv/VbcfXVVzfhV1xxRROWUsKrX/3qoyHWPo3EA76BTt26q4aBt4mZsTWHaidNs1q6xbFyoMhaeIbUHi8BnIuBg8jTgCoHoKosS+Twtln2ZOH0ESgu8hVhWr05WLTNqzMQujLKwMj8lQ/fq6z83/jowUjbUA9keIOzO3juMe+lVOkDrUxcdgWoCvo8p6O0lwzktPnxu4ZzFe32O8mD27HXDsLZatTtsWwR7fSH4mCZ/eiLX/UND7gA/RVTldPuOb7Xj3XFcsixqnvOW+HFfdwYiw3ttVXWKzupFman9kYgvgIaHVBc2bdcd21rb03bcSgCh8iTrBnTO4nJwlLtlCdK38hL4dp3CqCguBVwWUBeX7R7WxWt2kWu69Ly1zBNl5wyzK1UMdj0gKm3CukBRg+grnMrB6fbGpzaNTb1rbrIaOVVGQG4W3dL3SSRwWkLBsQUMOa02TVmeZTyouVj/xWIugciOXo0Wcs155fb8KWuva64D3kqi4FBtb+VLsY/UZ1EYJjBrQeIOU2xpaNMzXdcG+ZjvQZl5smdAZtJhm3H+6ONXb6mtvV++tOfPkpi7NPxSjZAquPIYE23Gib6IW2MSQX2KJ3yYiOdyFj0DPCSPrtkm1oDjoU8gMqJt7UdS4xNJR87mKzLPPOfqAKxaI06A05debX47Hgy30VlSW3cKk8Rv/dOZLXqwIlItgUYrJC2sW2IVa0OSdVvFsrkPWeAak4558OrAgV4UH7228FmQFbQYvmqUxVth/T6gsqtjpU6zovaDfWtqA1V8SV/BvJqq5YQ84jSWb16datbVVnH1TNJU12PGTRxWZ+Og2cThZXDKrabV0tZLuPJ5dNrLVNKdZszWeyZ53gyebqIJpNKm6Y0XA+ebJ7MDY/clpdBVCUHXUd9SNuEvk+o/UhlUNmqbcHEO1rZ1T7ggTkPnHon6zY8cr2i6a2WeXnOglOpXwW93n8PmC45zdZO4uUDeLhuGYx5PHYJAXk6UCClOub/Cvqa9ibtuEdeW2W5q3KSvlmGNcY+ndtnmRgPwtfTuZLLS66rMNOfMx714ns7k1j28vwOBv6OdTqmD0Tap2OfdmgfRa/vVsA0tfcAkAXA8aqO0ToDeUCZbV8KPqu8HXmi+Cr/HDHgqOydGLc5dnMARdM3ehBPscg1x1ccXc0nUxy73gawRQNRI8ckxuTEEQDwALBS88mZ8qdOqHy8FV91piKaAygcj/kzONhCnQ1ZefWdNN7qZgOzrQjwqpU5GCugRRBano5jUcrFjrU843B2su2eZS5xHf2a46AAdVuy8jNYMv3M+SaaLorjiRY5aofqCymQZJ7FDkoY4MvPzllxNJ16V3uqZfPA5zCM8nQavgeGG/nQArsGeJkMTttVQG35dIEq2r7FPCu7Aj+8WaUb6jjWjz351E6xzJxXZMMG4mP3Xnmjrb7ZSaPP9N3JJSAyBKdkpxggN+CVdMJ1VIWxPgJZSh0NlC+l81bomMc6TwDO7nWrruZfdD1MwL4Bpp02Vto8WtI2BdT9o5SX77We7VlG8RM4rabz6lflZvJWS5fQKE780EjGpG38l2OZ7mjY+Zj+lMw+HftkgyZ/xmSbVQf+hMGBVf9TB7yNzAa9agtTcn6Y/m9brnK9h/RmxMs9nPstZOjGS/VAw45nj1evXBX47zi3ds3PD9f2El0d4rrc9lMyqhevbEzq3CwBpva8N9hlabNVOtQOgCeP0dz2Qe0jEZ9GPv6pk+fI5fKYidM4co4+5hwYj6f6H9GPyQO66rREus7033PQumCBfhHvYtfkmdpFK0fU93jCjL8pzTZV0yl/a5vWpvTTJlrnPFGwShvbfuLOdNo6b0H3wAh/Lkbz4HZj5csiowfM7Tl/toProQJD8OUyvsyjkqGTlvOzNJpX+VSK5FmeDXUcrYu1w1Pzj3jftq4/1aI2xPt8S/N5HrsnHWWnvUQ/7/MwDEx5FZZXMr3PsKj9U2A7B0yHPALEAU3bKp+NydPP/VRRrj9pVOmR7pt0BEy3+iwMta0mDG0+FmZxuJ1YIssDVmYNZ73as6Au1oMvv/HWFeiq8y4kNz0b/0rYZRSdhnxHp2c84xk49dRT8ZCHPKSEfelLX8IFF1yA+9///rjgggtw8803AwByznje856Hc845Bw996EPxiU98oqQ5ePAg7n//++P+978/Dh48uCjvfXC6T4dE6vRXW7M6ndlzZvQ7nsafD7PwZpC3MRpLMI3mfShYqwdQLWxPfJ2wZqsffGd1jhpwH/DZC2iv0nfy9+I1q94L8m++GyllU7JB1a65zpqBP8hTnZ+Iojg2bi4Fqj1eSlqfq9TWL5cvKqel0f7RyJrbX8Un1UCJZ/yHGT0rn8M0J7IVeXUT1qmUf64deeQ54EwRCAeCb5YG8Xr5KcBjMLSm51ZWBqcnCDBmsMyTRbrKUsYWSQO0dR/5ndoOI/DpAsrxfwN2pK94zngEyjSNgk0GnN73MA3kVN96ddIyyDdwwKBoPdT1VuUrYDjL86pMAuK2/el3Thvdjv81Xw/cdesz90//5YaUMYFElYNBKdcDfy9VJytY1ypzBWApbgVKA3lN7AqAo447OM+a76Jy32FdUP6ml/rh9Ct6kjbVTA6Q/N5pvhVvyaPkxffyGAh8RtFNw1fjNoU99ojt4za/OfrJn/xJvOc976nCXvrSl+LRj340rr32Wjz60Y8u329997vfjWuvvRbXXnstXve61+HZz342gA2YvfTSS/Hnf/7n+OhHP4pLL720ANoedbf13u9+95uXPqCUEv7n//yfe06/T3csahzYNNkCfsanWdrMOjB2JHGgmZSPK4MD2PL4h7f5Wpwj4exqfiXsCBPnwVtx5/Iuclqd7VFYznNuK3CJhynPhLYMNhDqM0hYdHAS89BZZ6Ad/JfqjONwWRh4KUjxaOkW3wrgSIIG6DvA3xukhjwN6rbFN6FeSXOdFKGorivnwelr7CdU6cc681bVo/wbHg7N2Y8h12AuZ6ofbYQkYyZZtY603VXy5L7MXls02XgbctWXnLiqH54AKo6jtGEm7lfWXkrbSXU+azl9RHfZFH2k6R0241ut8mJqH+Zwe+2ssjfwn1m+HnHd6ISVx6MCVvK8DF+51nlkY2aFw1R+r0wqV3TPfDzg4z1rQDvHI5k80K/8gXhrbuE31MAUqHlyvtqftL68rbxeuoqnk5blZWA9184UOBd90fXg5MXtzytbL08uz2JnwxsTMPW7yi/jOKQvBtbe+Mt8VV4lrVNP1ua1ALKDzMf1Hdn/k0R2Gx2edKzQkfBXH/WoRzVnD73zne/EBz7wAQDA05/+dJx//vl42ctehne+85142tOehpQSHvnIR+KWW27BDTfcgA984AO44IILcPLJJwMALrjgArznPe/BRRdd1M37iB2IdHuf8rtPR48UeFpnN+eIHQseGDhhtSpGg3W0XS1P0YrRNeMRxV/aIqMtqyz/UqfXI5P3cHaRSM6ek9uTnR3UPRSxrhvhaxd70R0DSrtX8Jrov4VFALVqR9Tuek5ORFoebxLE4xU1gyxtpHJmojROQNTOPHDAOjO9AnRoGcnrDfTKi4nbU+bKGmWsJk1yW37lPTeBVD1f0F8zK4Dsl/Fi0FXxojQsYMnK6QSeDlnv7ASyg2nPh4y2DaVp8mCFtp0osPZ0y6uaA4A8TMCc41iRGYhwIco3czECU7rmVVs+N2DI2JwaHRhrbT9e3+2R57T3JpwU+A0U1wN8meJx/ST6qR3gvHv9muXgeuM0DHi0fSkghsTxwCnXrQK5Kv6YRj8nU+ki18CFy6ztOQKeKo/3XHVooNKuVQd8zyAxY9paiyB9VP5EYUBrpypAP9Q8hlyDdZWx4g+fuO7svvKpgnQNEydv5PYeqZbJA6ZVX0hTHTZ5cKGszVIcjVIFSMHSKFsoOyWxPlL0I4qKxqKvRbrxxhvLN1jvfe9748YbbwQAfPazn8VZZ51V4p155pn47Gc/G4bPURecfuxjH9tK6N///d/Hb/7mb+IrX/nKVun26Y5HmYwWE68mmHPCWwvNyWLHWAEqO5HFcIHSkMO7DW0DXr1rz0Fig3skjZs6IJTt1sS6LpMFpO8KwOwxj8NFLIvd63PAl5OBu7YjHRC9tHPUTGTIc3MgvPdnedCcy6MXxdrf0rbnzUoPXA4b8J2Bfo6fN2NtfZb7eOqkaXgHAFVtRqL40ay/8o6AsfpCbI94NbUcvsP2guRrJjMw3+5UhojU+bN0fM3F050jLIPpjuPwZI83qVNtF6d2vpMArMjOjwmrPkwglOvQ8lgPU14czvUatTuOZ8ERKPRAlOco87VuGzWqvr/ojRPR2AGpE85PymXbW1lvRY+OvApYFdwpoOSVzEy8uNysr2jl1MtDgStvEVb+3vZcXcGMyAOmll7BlLdSas9Nlyo7f8qE+w+HFQCa6zIyqNN2VrWZ1IZ73082GRmYNs/g2zpv3PTsfeFPMmV5XvVVx+55Mie+Qc3bG6OajC08y0QNpQ/9OGNZCXLs0178yy984Qs499xzy/2znvUsPOtZz9oiz3TEFiK74PThD3/4IiZXXnklXvSiF+HP//zPkXPGQx7yEPzar/3aYRFwn+44VIFN+6F998lz6BpDMhqO4nQy7y1lYvDATuy2XU63y7JBZgfvSNk7HWSaWUJ2zO2PODgWLyJd3QrlAOnTiat1pgAYQTqW05NpKUUANJqtjmTvyhXEVwfNc1b1+5rZicsz+B5VoNhxQFQ2b/tjqT9MK2hLgGnUhEzexslx2uoKnTaQqd7VfhymDhb5JtqvOT7rmUHrJBzZAuexJ8OiyRJMfFVnbGvnqLTN3AKsJo4jZ7l3yl4+T0Rlb7YFp8mBH0Zd8jdWdYWs16a9NubJ3+tHWZ577VfDvf48ty1Y81SqHOwg/yHXW6e5Hbo7feg6egfT29LrlTVaefWA5FweBvI0TbRKWm2TpfiqU20XbNu0jN7JuF4bqEC4yVxnXcK4DKD4GQRKg7ZWgVApmze5qTuFvPKrjBXJxAX7DU37pXG7lJHrOk8r0Csvcxayc++1fcuDfUYdd4u8aMsZjRWlaBnVJNodjU455RT3W6w9Ou2003DDDTfg9NNPxw033IBTTz0VAHDGGWfg+uuvL/E+85nP4IwzzsAZZ5xRtgFb+Pnnnz+bzyEdiPTJT34Sj3/84/G93/u9uOqqq3Df+94XBw8exCc/+Uk84QlPOBTW+3Sck7cd15wkWy3lUxsZsAKT86I8Gv5oD/io+IjBOhSaA2Vz6ZiWONA82Dbpt8hrTg6tFy/OnJx7JY911QZSGzcSpweIqvuF8kYOvbdl3Dvkojg+qAfIJcQrAcyby6AOR5PXgsw4jbvapk4GO1gSrzdzrnqZk6X0Y7QTLhy/5D1eR21nDkyX/Gfisfy9uKqD6hm1DZa510aiLaUahw+0yRLf+vjOagKGBmj4cBw71KUBQZjagB3g4oJhKSfbFwvnA2BuW29+ds2nm+pBP9rHtF0pIOJ2y/20lMPhqSfhFh3R/0p3OTgIR/kOsbx8suva++VWH56+LN5tA3DrqNfqwCQtX65PkV3L/yJvdKJsoENPp6oPK78HDL00FofbmoJfD8SuRY7S7gZgd+2cEIy23Xjl8cqn9jJLnLXpUvoSA1OvLTKI5XFAx+tKnsiYcH92fpX8JmfMxtWDhWv2g/OrJmw82XL9X/MEx9P2AqedRfro6IplO1Yp7eG3F3riE59YTtw9ePAgnvSkJ5XwN7/5zcg546qrrsLd7353nH766XjsYx+L9773vbj55ptx8803473vfS8e+9jHzuazp++cXnfddfilX/olvO1tb8MwDDjllFPwH//jf8Szn/1snHDCCXthuU/HIV170yV94Cj/Aeddoz2AoSXxUnA9R1nih7PbOZZdZ/K8PJZYuiwXPV2HaTvhyQnbhrx03iAD0CpXcN+jKO4SHj09LAEsh0LDEWLurQrshTz5yruCBJiqdhL1B7rWVR7OS+PxipjOePfIZFEwWiYwpG2w0wW69iYarNA9u2F6yeUC9TtLEH2lNr491hUkTqaye2BQ1dXESZN+V6spDTv2RuU9ZGFqsnOZ1FYuJdvSqGmrco7y2ez5kKc61QmC5PCwNErRyhTk2u6NZ+QgK19Op2Xrxek95/qIVtTsGYM4S7tC1eTC8qkc0fZdLy/9HwFQTs9xGThwu4zy0EkABnBhXVEeCrzULoQ6yRM/Bowmq6VnfVflF2DqAeGqjCyb8R37s56q3TQ7p369+yDZxNuJo7bD2zUW6dcoXLUkPnrvjSOmiwx/7GnylbRV36DyHG90JGS+6KKL8IEPfABf/OIXceaZZ+LSSy/Fi170Ilx44YW47LLLcN/73heXX345AODxj388/viP/xjnnHMOTjrpJLzxjW8EAJx88sn45V/+ZTziEY8AAPzKr/xKORypR1uB089//vN4yUtegje84Q249dZbcbe73Q0///M/j3//7/897nrXu25b7n26A1AFAlNtrLzPVFTAdA/5ZLnnvLvpHaBc+GXHSR0tXddBnTFkc87tUmLDGb0bwnFDo0xW2Bxpde6Wyho5V704lSzCVwc0jldd5Clx1RYcoKoDGMvU05E6F54IR5q2cR5MVgVb+h5NBTqzHy+UJbXlzw6/ufc01UniGVwPnDbtQcAok9mWSsaoTCCwyDz2MMA3ALVjT6rMIU5cnpwl1qs67z1A5YblycHMw4Z/+byDpgXK+4lswzVOFV/uq7Yw5p2A5mCaEsdhbHHWGRhMjqAyw+3HjpOr1x4Q0bQRENTnzNdzkiPbHMnURABccMfRNLxsjZfnbN8a+am8Fu6BYA84WlxbRbP7SN9LgCnHaWRBC0xL3lwuyXvJtl1Vv4JsjqN9V3mZPAOljYBpWfWkzEteYz8wgFpFC9qW10YiwMiUxEYxD1stN1rRMy6fl54ZlQUKJw+vzlUvtuWWASrHL/LJWMi2X/NdkQ3PiO3O1wL93u/9nht+xRVXNGEpJbz61a924z/jGc/AM57xjK3yXgRO/8//+T/4z//5P+MVr3gFvvKVr+CEE07A8573PPzSL/0S7nWve22V4T7dcajZsgsUJzZJuG6zVfIcusIbAnwdPtHseeRr6kxf5bhDVjlmeM0Z+SjuNo6wW2Z1gNEZCCTNNjJXeeggooMn+vl7cZbI4oFFoAaTHkCdy3tOhkNZ8V1CEa+lWTQrhLk9hbfi6bUPp+/1AJbmp/w94NXIgamPZdQTJ3Nl9/qCUtQPKnk84FU6P6qHrA93pl7sRwGqmvmYr+qw9N08yRVN9mg/j/qe2rc1HNA7ibR5T43KZJ8QUt5WVs/mqlw2FvCYwOX1Ji7N2TSae/coApZeWHau9T+nbSa1nDJ4ZYcTT9OrLe7lx6TAyGyAlqOAJLT1zXl44SZLF7Q7emBwqKALThp3tVDDc3sSsMm9Jr4ViM01yGvAkqNze9ab7NCtv6UOqAz8rnxGvQKtW19Z/xUwdfRlAfoaQAXCc92nvPrTrbQRWf81ebSdKwAs7ZB03eVPgnmyWJi7KsyRxGZEfcZIgaoXVwEqEPt/xwKxfb2jUBec3nrrrXjVq16FX/u1X8NNN92E1WqFH//xH8dLXvIS3Pe+9z1aMn5N0jv++pLiAOhHy/Udy+o+1YepVB+4H3nrqiaHA/VsOX/oXInBaOW4kuPG4cXnU+NJPLpbdR1g4EXnMK98lm81II9/XIecGB9OA1DA9kKmPf14jkKiZ176bQCdl1/vOgKxPT5HmpaCYNWJ134Olyw9kZq2HkwsZCxvS1onZfAdr21grsARgzXHUeCJA5YlInMUdGcFZ9es+pIIvTK6Tk7H2dQOzTaLdcEUOTe2DVV12sTt1J/JNThRDcAnShPpW+uZ81YApDbBdDxkIOXxhF3UaSL5m7IwT5GZnVPL28Apy7yTgJw6ts/RA9shvddrz9memwjwwjWOpxtwPtoOcrtluSmr8GO96goj8kZvmXWqdln4eSuzUbl0RVRXOnV1tdIbx5V8NZ13gm2G805qnlYoyzuhKnckz/hc+4bGYWDJcdbCo5SJZPDSZ0g5rd5E3koWoD7R3CkjJE3RLfN02pcFN74D8Sh6l0SWRj+/kyWeTnil8aKql/F/F5gKkyaeBcgz3RLthZlc7DPNyrFPh5W64PT+978/PvOZzyDnjB/6oR/Cr/7qr+LBD37w0ZLta5rMePDspxk6c04G0GAucSDPrPNXWyjI6dRxP9ePZ4ERMA06HM3eYcOYH8ujwDbyOXuGlGnpqmD0uMonVf8mvhQuUV3ekd6UbwSKvVlSdn69VSodcFm2YRDArsKIDDqQs2zRc4/PkjCjw706qTO8TXkiOUB9RtKyjN67bR55zvNcXG5jnp6X6KkXRwGogRKABmsyBsqqWR0U3j1ZPfBnwIhPaFWnvcpjEq1sq4vyy16YE4dtZDlh1tGP0or6ZdVHuXyOvthJ9eTiFc2BeIb9XNqZtxpXARy2P3nUveXrlJWbRcST8yt1kv34hS/l59kudoCrcLS2yHvuxY9046XrXUf5zNkeDveAnKbTa2CyRdaGwvoXWT35LGxuPPGAPb+PGa2AFjkkbXTtPePtsBxPQbF3OjDrwdWR1CVf8zZlrociA287yG05m8OCSC4Fppq3faKmTBqhHSedqqzSs8zVc3nWtVEit9HADpGkmaMmryWRtqGMxnA0/RKyNXhMw+Pu4ZycPuzUmbw7XqkLTq+//nqklHDSSSfhuuuuw0UXXbSYcUoJn/zkJw9ZwK91YoNVOguF6/aJ5kATSmsMG3CTJ0PHqyeWPtpmhigvNsyUdxGB0wChQ+muOlDZyzsBTloWkXl7QIPzK0EOf07TyBOQGfHGbjg6cdOLPkq9jYkZKPZAEg94BZimQDbKwnMaIvkgacLnjkw9cp0FJ54B7R5PTb8NCF4k60wdbJMuamORQ8ITPVyvi4pIbcMcH29rZQUkpf978nObs/bGoIfzsPozJ6ys4KbNJwh4RUXzYfnDIi6sa9NhcQJBW1w75eW0pv/SVaUy1GbOOZkrkqdsKe70R+uzFqYrcpxnSijvsa3SZvvvDiYQYNuBE/938gtB1UK7wbplFdt7epHaPfsAJ8wDip7cPTDjxenx1zR8r3IUG6t8nHICbZtSwG3PbCyf2zKs5dYtt148zs8DpM1KbCcdp8kBP15FVTCsK6hzADvSSSULP3P6kaWxrbucwRDw8cC/MfLyL/zGOGaL1MZw/VRpHHnB16jbjPoE2bn22nYzNmgiNhwOLQWzfmLKI3qe6qhelMj3PR7oeJFzKc2+c5pzxle+8hV86lOf2orxkfow69cKKYCzLWMZ0yy6WaYIoA4Yt0SNTLx3okp+aBu3hUWdlB2xsByUV3FURaZiLLcwBE36kaKZ9TkQyM88+fbamqvJBE8OKbMaf3bWeEDQWVMe8Bh8cp5AvRXcHnoTAo0zsWCgh4RvA/wi8nhtw7cL2KksnN8c4J7jNxcnfLaHuI2jSmGeUwEEbZkdXWoTFrx28lmhnQxLFIdXLwDgAIWrU2/pdoDNNkSzByNYzSOAStkHtrm5qG9z9vuDF7fEx/SzdNVOENFH9a4Spn5aMWfHpyND1G7Lqx5A2eqqznp1nWtQ7/VjW6k2sjGDwQUAHFhNJ7+qc7vEHizZYcAny5Z2tOQFNvTz8fp4r+97cbSsvW3AKpPGUdm8LbDebprqfchc7zwwmRqQ6fDxyurJ29ODN/nRAC+7Jj7R1mF3lZTieJ+KAafTOI7c1YRbMEFU2r6WQf4XHVAZPd0pwHXLzWkpHfMzslVK8weVtLtE7ZFJQa7XbpXy+CdzemqM/BxA+Waox4jbSE9Ofdawi/KYYyrAtZQp9ycj9+nIURec/umf/unRkmOfHMrlD3XwcTBa52kgX8EHqIl5pPq/t3qqW/v40I8eQG2206bJ2Ch/L7xKz4PtjGEwPt4KqwcC58gFtqyrZWxcvmz0ND9vIMh0nziyho9x7fQ8XuHw0pqDzdtXPJvN+vNWrHgg8cgrR49cQLggnRe/chyIvz5X1tvk13M0ta00OwsW8g6fB3GiZNWkhv13GnsK2gS335Qnp85OUj3AXtLY/oY8fY/R2uWajJS2CwOm6zGPhPGD7Wlq01omy6fyR3gyB6JzKuNc32OTaHGtmNE2b6B1fhWocr/1qLIVwpvjJGz0bmW0fPUwlwxZVULdF4wf0ypP44ml49VudWS13FH4nOOZUI9j/BkZr71Hu2B6NofLrf1IdbPEnnjXLEMkG1C3Ue9bxmUiAFM9Wl1bn9Bx3wNlnsKZH0dRnbEOovJHW3j1tFYPlFZ55FquPD7T74Bym2b/SLf19uQ23a2S/04rf+7FA5OsoEH4cp1qvrPAdLyJtuFa2oT6gLMqjpOmvmjJ2pOOUdGYxa8+lLKbPwcgy/Nid7UDoK1zJqsfLkJkFz3i/D3/Ljk3je+Lvs0+VuiOBqK74PR7vud7jpYc+yTEoIqdXDYE7DSYw5IxGTY2wB5IVGDHeUcAtRghymMbh76MJ45MDIKX8NYVziov1AZlkYwkQ7TKTNWymKKss/NQB+3IOFo4b9myCQtva3eV1gHzjb5Q15fK5cnolW9bcOnJq8+rMJGpF6cX5snK8iwtRjMYi4yc9xLHgtN148gAbqQgjScu7HkVkeV0+OsBaQYQi+0Zjc+QJ2DKTqt3QJvRkDerduqorHZqWSsAR2ntmfe8XEtfjkCN2TkFk+WdL8cGan2a/VznesWV32OtbE2e0nmg2qPCh+ONepwDqtWqW6axwsmD4+rKVeHvtOs5EFfyMP7EIwIznMajHgj2nG+Lq+BjbmVUbY7r2EvdVe2UbDcDqhJXZK/ijHz5fWHWk4IetdFeHC2rlTFa6eSwIU99P8PXowdoS/xcvyNqsikwLboaaj/H0mf6MT/Lh+U5kOq2bO91eicNl/IILwtnf62SRXSq/DIzw9juhzoN10WVP1Wq7qSK0ugYX8WV9q5lKzY/0adjnH7B/biwJP0Y6Uqq1s8cZS0Q36rugn5YLbg4/Pbp9qOtvnO6T0ePBqBsYyudaqhP4jXwCUzvCAHTSmqiawWoZtyK8XJAogLUQrm1NfqOQSYZyi9NBo/f4WoQmBg2z5EVcYoTObdVuUdZym95s4GP3pVVebxnnnOVneds6MsWbh0gnPTMx3PcUmodcxuEzPl0HRFnoOVB1gO1h5t6LFkWo8ZxljheWbz8PGDK9eRuLcVUB17aZsB2qOc42HO3jUncLOGWjrsaz4JHMihPW9XRd6l2h82PV3eUJ0+mGRkAYmdonafwxgahrSOzK55edLJJ9RLxTaNwBVSYPSRHzHQYAVnTTXPAkPBSGdTh9YjjsZ2t4oy641UL76T3Vdqsxu6spnLpawA2CRZN7kSvG1gcwO9TUPtNdojTNpnCb2OazgNnKhPQHqITxc3yn+MVGUROTsvtPwKnSdLopIX5BonkU4AKtJMFGncODERbZHWM6K2U9uTTstkzXb0sQHIEpt5KfqYfJL+qX6f6v4Wv7T/VCfsjXpvgssPKIeUDpSvl1YcjJWmsHI/bM/Kmb7M8DTm6dx5X8lm4tkft12ZHI/tp12ZDm4faKUF6cYRz89ICOP0hYHeHozsart4Hp8co7Q70qYUxLGcgj1u5zEkyx8EMpxlE3urrAVQzeBlwQSI39LnBi7evAS1/BqgWPwSoQNvLjE+qH+uMnhkjBsxLDVIINLPwyT7wW8LLZKx4U5g3iDe8qcx2iAmTOcF8nzntqh7oefCu3m+1NNYWHOdBxxkt59zAMAf8PMfUcxqVvG1crrPppPfqIpLPW1nx4ip/5tGswHXSNjJ6z2Z0ahdcvx6octNh+lSDycvfVDWnzhw7A18Mbgo/kdNsFLdDW8XYHTaAyfJotsKhXaVZdWxFpGO7rbZWis00h630C9EV2x6zFRbf254aHVgy186juLwqnQGkMQPeKm36MzC4M4LSAyt6D4/KwsCU2547CdLpe0v67txW3SUO2FweGtyzFxGILXH43onTHTvJDql+SnhHh2aXvZVT/s9jhidbNNaEQFRlc3gokI5kYxl4TPLeL9Vtu+rfsM50W2+W+Fou3ca+O/TbgLfttqevSi9jpLl2WvKU/Pk6ddKqzF5ZmKKdEF5/2R2It6TX3ReWL0/kJeHPO2zc8s6Uk+NFUZXH3KLHXPpjibxJyeOduuD0JS95ySEx/5Vf+ZVDSv+1TOwEmZOXAeQB5VRFoD4kCWhn53nljwFqlmcMSHVGMXJWrUM0q6sZ1da14unQQKCnT7I3xEbAHEA2Zgqes1deK4foda4DZ9EF89ftcySyz6ufVT14A+HgZmG9srAO1gB2uT5Rz86bM2p1vM7T+4DmoOr2zSx8dBBQ49gbBFXe5lmQ3gWYaGXp5eXp1XM+PH5zTqc6q3OyNLJFBeD4vWdSNk6j+WifrsCpXGs7sjYDTO2FbQc7J9wuvO3k3qCqel6zgRM5zBGtykI2icndRo1gVVPjke1KqE/M5LIW3eb6uefEWhrmr89NRpWFwxWcrtJ0qJHx3x2m7dHs9Jv+U5qALQMPzU/7f9Te54Apx6+cWmG0dIvfNuSCffhlcnXNz4Wn2oY5e1B4ilyeHJG++dRmBX1NIZ08PZvRlSNPZfdAplfPXhvScOO3ljDexlvAKaVdsy7S1D95my9vcefTqIEaCK+H9vupQJ0f61B1VOmJ9UIPtT8oRe3TnnG/nkNXXhuKQKibXuJlTDtj1gPZYoqnrxPoJFflf2bhEeh0iXwe7QWvKU/PJ9ynI09dcPqf/tN/wl5O3c05I6W0D04PgW5bT85CWZk0gErxFCRZR2LDzgCPgWQxBgz+aNZ9TOYO0NPD2BlkeSwfWzHlLb+g63JPoMgDz56lYFn1HdFJIIofNO0yAJhTTeHeu61LSAejyBGKwkDhnDdvbeKZQK4iYHLyDZxyffEgvDu0fKoBhOTRbVWRpegNtp4uenEifo5f64L/JfXlDk70bHZlNpDxSFAP3Kocqs+E9lmzkkr2QO2A2aU8xrP0yC1AXVwW6nOm6/X4MpjXJrlNlPJlclJZjuTEHSkCQdZPtI2bXXLf386tPeM4VdvInWfC0wuzNLxaWnaujJRQn8brrQID9aq4bsflNrDERkVxPVBiNDc5sA1p+aNnyt8rmz33+rcn/xLg7snTm3TwriN9zQHiXh01cS0O9bcIkHq2kPOM0lg++h3Q8qNtvAo0dUzmXVxmy/jAIoszYDr4qwKmlBfLMzdGqc697alev9XVXEDkjdoAlx8+9bpMb6wF6vG0sj1Uj1Znc4NqJvtS2WThBdLL0nKwfNHko5XHTaegcwxjP5l942OZjnHxtqYuOH3a0562J3C6T4dOBhJ4Jtw6yWBTg0DZrsUrp8gT+IN0sHKgBzA5lRnNtl81qB55YK2k8Tr+SJa/FUNXIxRkenYhAjy6ZcR4VLLJzVwezJeKVuIsWY3Nzn1vUI8cvmgrVuQMl9Xo8dbdokeM9B0bW1HVlTZjzWNTNFDODS4aN9KD5r8tefpsBsLOPeufZfP+e/oCBESILCXOjPy9sKhsS9JyYJZ7bv/VyrrDwuuDJltzcIeL+qZwA6bV+/YErnhihUVWWaP21CO2l82OE7GTXv5uf4Tf7vQ54NelXpeykzOFYTNGVICC+JtcO2ladcoZ2KVxwWuXEXjqAdaovyzRw5xOrCxePATPl/DXfqPljXZNlPgLyun2R8cmqz309BnxiPirfSp5UF/3dDAHSr0dNUbe9t1yz+UlngpMm1N7TV77qW1BbYcaAJmmfPhk8bJbI5CX7YtbL3QRtVt9b5tXfz3y2gbnF+2i0nierdQ0vVcfLJHpZZExJYWZDCuy4dl4om0/UVm4/fL7vjtBh4/sRU9kFf9QfI992p664PRNb3rTURJjn5Ruo3dOd1Yos0+rtLnftdWEscPwASXaQUuHHz2PagU2T+EWx/O5ug5zFifO4e05oWww+NMm1eoJG3USYs7IMG8PIEhWi4kdbB6EmK/G9waoOYDaOAc0SPZmCkOZUR++onlwXJUREtcdHPl6gVw6+eCWe+FAZfkCgeNIacMyOfn1eLuOIab2UVQgukj0PyqODqRe+3FBT6eOetT0Wwo3slOgQzuQ23rXd9ysL3p1Wj5Rk+p4Zes5yfYdZ74WAPDf//6SCpyqvnZSDU4rsJbJORLZtY2YXeUdJ8WupDo9O6+sDr7OEi8irw82J/ASn7K6lGoeDAxMzp20uV6h3soYyaBhnLcHUox0BTa61jJ5W721vx4OavoY4vJGW1c5Xs9+R/deXhG4N/LGAg8UWxn5nediowicsThJ7rndRePUIPLqGKXjl75rrTrl7bAMTLU9DRnV+RuRDS95QWxRnlZM17ldvWVZOE++9zLx+rjXZjhcbYQH2LR8Beg5guiuDw+Y9nwAT8aSjmRpxjyJnyQwJ9nu7LSp6NPGltfK6ojkTY4ttnCVq9TJWEGVueFKi4OOObqjrSMekQORbrzxRnz1q1/F2WeffSTYf02QHYi0Kp7RJjwD02pp3sws2pa3zMAyT0ZAgZ+lTUAFGnXLLSCrBELsoCG3nUOTFRnsmeRpPO1ncTRtidheVg5j85BkVr48W9jjW5WZy0UX3qw0R1kCSJmvDuxcNK4nxf9Fbi6PyNaUk9KoPrpgMRqZAmIHweM/52QsJXZ8GKDOpWE5vXd0lsrpjRe8ddYGes07mr3O8l+f6zPv3khBhB6kpcR9wFuliEjbrfe8eQcdU/uwb58yQAU2rz5wvTar0iAbkqe65Pcmq23xxFv5IE92sfrkCrWtUp9jGG/Vq2xZrp2zudcLtD829gu1DLwaWvEbw3g8UH2EdRTYMJbTA6JDjtNU/0VOG+O89u6lUwAAtG1aSR9Z2qjth2UI4rEcXpxIhrnXBiyc+SaOJ3G5v/Iqk6Wx+lddeXJwO1GQCNRtwPJmsKeTK1wW41XyGqY0FkdtVum/qc6nAj+SVzbBSCY7eI3jsI5NP1qXXodp2gnl7cVl0MYJItl1AmBNOtB81tkP99pUI5voVrdAN1uXU20DCyU0BzdZuVmOUn8iW9O38/SNV54AyHmzGs7AFdjc93zTwkNBquqj8+xYoDsYNj0y4PSHf/iH8bGPfQy7u7tHgv3XBK3Hg4+wqt85BcbO5HS2ZoacQC1Qb/kt399DDQjB92Twi6FC7Rhph9BBTmemGsNOTmmVN92XmUEBQJEcCngqYoBpZSTBoi3AlsaMGD9s3m/lgUkGmsZhXGjxFAwkeVYNCqlRVUnDgMgD8J7zxXyylNsDfFmehc63HxyCdU2nz+dWNr08mZfmyX2qJyfLss2qscVnHXIbit5n5Hxc4LrHUZQdMFdu1AP64aTSvzOqVxRs65g5kbsD8P/8j0uQsNlBUn1ai66x2tjQXdLhetjsSDHniuvXXp3g04cTWl2YrTCgmjlcaJipZ7PTBiqbfChus2oX2BF9pivCClIYnDKw8FYul8jV/a88At5KvT4YkTruTL0+6tkNBdyqA00b6QpYVhYvP+XJq6CVDI5caXzQs2c5B8BRZOD/3go5yzqwwIDbBkq48G2ucx3OeeqrSgyUAarvPF03K3dRO7Z8QPrhMjl6ZL3RWwluPPYVksM30g3HK/6e5F3KLkJ67YqpOYmYdKP2oriYlo8ARpec9qSfIerqWHw45Dps0EkWzANUy5vj8NiwT0efjtinZPLh9l6+xqgcApJpRQHYdH6QoUg0azr+zFDYigOTAtQCJseeaiuZZmQUBJnh8A4ssnBvFtZzejSt913UYrzJyHpyLCWdJVOAZmX2DBnzsDjGowckokGAKZEMrBOTFVkOskItQ1helkUADT/TyYM5h3GOXOAmeWhYlnQNT+Gn4b00c/yyhPecuKg+tx3DPD5LecxNenAe29Cc86yTRL3BXSculHWS/+yYWDbsTO4OwK3rcVcJgBN2aoAKyG6TMd2t1O75+4X2M6CLVduf1Ldje+mpKprcsj7GdV45YR0w6K7kOfGatpTqfDk+r5rxKoj2VZbHePRW9tyVNbvXskdl65Q3ihuBaaPK6Rz68TUvD5B6wNTS9nTFcTy5I15NmOi0l1/F2wmfsxERKPVAq3eqLcfVa74vE1HGK7fbeaP8vbwqAC/1WwC02Rrq01V5WFanjUS6ZMC1dtIxkHTYu20gAqZcZo+89qwy2hpG+X5sbm2C9u9ST2lcrUytfI5Ls8knw20vmQRWuRNFylXAGBb4Y1YuW1HtbvOVa5P1eACo+9t69+mo0DpvHIiU6VAQTGAzjde79MyIDxbiGUUzKHpoEhso3l5XMKsAt8ZjI3BrgLGadcqTPM3AxSDM+TXfRAUqi7IEmCmZHFY2lqsHfHNQZrdcJIM3gHmDSeIL5S1hmsYbqJqDLXIbl2XSMkaDmlG1MqRxSY6eI6by9+RYOt/lOS2ek8fhfN1zmNWZmJPJczi8VU8O98qi15p+oWr2tApl6arXA4yWTo7M8GdHAPB1VWzKGG6fmLFPa7HdAYBhvVk5Vb1V2/6snw8tyG1WTcd7XgXpnUrM9cOycRvrvSu3tK6ivlYBYpHJ4vK2xSq/HK+iR2CNnVkGTxwvAmvKn8umYR55bTBLeeqHPh+vf3lljexU1Ga8OrIH7vu1Tj4VL7R1Ftm46PlS8upNy8PvpHJ5mQenb3hLO2SAqu3U0w9QT/5kOAcoSRrOV8vb9EenLWjZOKw65IkizrVnPc9iDpgqmzLh54wxWgcGRBOm1UbTl9WDncbLaRtZMqrttFVZKGOuA926qwJ66rGwFEXKmAWoFs/GEGZVpaPMmnz36ajQPjgVuvD/f0mzcmb3J6wmJ8M+0gyKyx+cN9CTUr1drIAu+p7kauS9s5r+r9IIRHlfCP/HdM3bYo34+6dJwnmF0sAjO08JU5h+ey4Tv6Kn0rOn/7zioce7g3hkYlji0M/0qkZOVy1dYxYNwqyQPPGz+yUgoegPy/KPni8xfNWL/g4jdQS8/HsyePyiONHgynViz3Xm1RJr3/L4zg3inO+c4xQ5H951s31S0y5wMHryczvWeLrqGLH3wBZTNMu7DTD1gHMFUEtElErUSZqoXfJzT65emlUCVjsL2gXVv+fYJYm7BnBgjLdaUbjZVrEZuj3QZLNnvYkE3Q65cnh55THZuXx8XW3LRT256Dn1ChhVp2vJU+Vwga7xFhmj1a5IR1pWjauUnP6zDc3J4dmTuVVR5uuBVB5HmU+Jw3WMyUZofc/ZO+Y7t7Jq5O6AkHyiU3a9MuvqkwHDwheTX2VpB+GpQJUPL7IDvixtAaZcftYBtdOerqp2ITpj3nrAEz+vyhnUj6Zt5JB8tR6MdmQM9uqq4pFrv5TroddXvQOLqkk7LhPJo5/JcXXA16Qv8x/5vnUgUABqxXN83t3Sj0kHhfUYOOT4JOBjgdhfvqPQPjgl+tHLLymn3arhXgE4+CObUyL/zTsu2Wrws3cvePVvGIC0otXLvJl5GjLK6qitiuY1kFejoRg7544ho2FsmLJ6ynJbGgaflLwCWZWzhSk+0M7GMYjk9w70fUNeJTBgl1EDTKMsvKp3uxxQ2azi1lHq+9wCPJODLVIFnB0e5b/pI4rrpONwG/wUTCjeX9LWOIpnpHqDsMvPkbcXXgLIedLB2NNrU0eObJHR9erXcwB6DpwHTOdWTiNnmcfJJWX05NOxVtPNAdMorOElcXrOaKJ+3duyrxW1BFT0ZK0mMdJkjxjIz73P7Dnw5tQ0Dsz4s/dR7fMSdkI6T64pwACmXSlW7t7WcJZ9yVZMfW7tVcES22b7b+MLP9fTVyMZo7aq18PQ9vm5SaOIP4cvaUNG3jt7cw5bL3+2v6xjoNUDnLj8jPMzUADUYw/bTeVbdKlxSdc9ez63FbYhR5cRII3kqeSFtAcK8z4R4/EyYKorq0YVKMvT+GphvAoYtcFqhVYU0AOmbjt12nKk9l6/9/qE6YBBfgFuiXRA+bK+spSvnGpOddGzXzwpHwLVXINUlne2+Tlx8vhHJ7c9XtFElY0dA4AdL9/yB9Ok62gM5mS+XSnFY+HxSvvglCgl2peO/gDHDcE7lMOoOCrm4I3x9ECiNfXyjBEgp4l/tsHfOgmtotr2Xx7YWM4KHFoGcm1bZ3svhDcOLer3YJkXr0R6ctizDB/MKoAu+qXMOU+PQnDpeKUmR6WbDhkbNmaNMXUGFU7P4UmMSwPao4HCebYXwx/x9vLmWy1TBOwZUCgvD9RliRPR3GqTOgZzwJQdR5VT0/A9MBXEy4P5yByLm8+RoEh23f7Nz8q1AFSjVa8wC8jbOhoNst7nbiy+1W3CBBKr5wvao60Y7I7XBlIP0HdW+X18rcvuwSccJhcsn9efNa3rbEp4BE6tnF5/8OT2+nrVT2nc0ckdr//1diY09lHuOY5Xp73XBiKKbDOTB+y8dLrSps8rHiafU2bWE/PQutBt4tEKeJW/I3/02Y6oHAz8IgDNZYz6gAHGqD1qeUo7s3i5jr9CzYff9TRQxGCteheU+On2dvrX1oHIxxG8Nsztl/mobnrAkIEpj1crjCd1a7nG6wLsHXnXqR6HrX63wTtef2xWlDt9ZAm4Mh2ar606Z557BWtW7lKeOxjoO15oH5wSJWy2dJWGT40+JeBp//US7KTN1lvtD1775c6d83hAEabZpBVGIMbfK83TdQaQh2mVNNsJviPpqWQ7zBytI1nAVKLOJ4CscmwIKLpExoHfZXWRPRkg3h7ogrBUy2FkW5WTJ/8W1AyWLKPnLHNa4ZMlQs+h0sG8kknyWVIsHfyW0JL4ESj2ysPxqlUASRsNFHPA1Fup42eu/PCdnagMrjOtPDt60DhevipfxFspej/VqHu6buAYefk78zVtANWvrvo12323oKgM3nbXNP4JJ25GGdXhTvQMmOTXybhb1/UKY8kjTXaHX02otrKjef2/9IvIQS/bNKVuor6jwNSisYNvE42ckbeK6Tn/HMcL0z4SgU4PmHphWtZemJWzCXQibnOAyVz/0b7D5VGZXb0Jz6ifzK3KKg+1YZ6eI79EgVVEbhnH/7YSWT0P0pQyShiv6HM74rz4mldZS1qTR8rIq4qWt6Xjbb+mI13Z1bFMyxMBU6+Nqx484r7spalkx6QHTlf5KiIP68seuNdcBpUxlzWRcu3l5SX2iu9NBGjcCLxmoDnwU2U9nLRkR9LtSXc0DN0Fp1deeeWemH75y1/eU7rbk/712y+pPiMAYHrnEnQKJPqOWOmkuZ3RNxrUScooH5IeMmCHfAxjnsMYvrNC/QmZ1bTimsb7spqK6RrY3K8pv2yBGZVDV5w4jHKl9oh5/Q4hAp46+2T33ioqg7GiL9MfpsFG5fccazVigo8bqvLLk4wqV0NSv54hL9donQqT1QY2fT+Yy9oDKUttZuQQLkrb4RHxTPrfKQPrwxucvftGNnUicqvvKp/c5uU5jT0dRc5zxGuO35J8jLSt9Q7v0XrzZFs0v6NtURyGZlfElqRlmPs+JdtWluNQBmh18Fkula38SB7rwyZH00/cRuFe1lFy35bYf7bTa0Ln3sqs1+9cMMZhLA98IBH2uQX5Wtg2TmDUp/j7jkvSZydMZdT+44HRyDbO7fCwuEvsq8eT224zXqOd4Ohtzy3xHDlL/Zg+HPkBZ8UsKCtvo41kKXHtOedN8lSy6n+TK7eycdymzI5MLiBbUG8VX0feEJRavllOL3biJSc9yzInB+fn0SD/m/7D8szOeMYT/55s7JdZWbnMFaOFfX/x6mp2yrNPR5S64PT8889H2sPaeM55T+luT6owX6odaq8k/G4R4Bu1YZh4WB42o73GpoMfwGSY7FRe2w+f8gaYJgDDePBRlql5BqUZmN4vTfQC9whWd1K9atn08PE/g60Ecr5GKjw0ncfTbivLOemlkkf0xwOgrszy1t8s8kUDVY9YvCTXSrxyq987jPL0HAGLmFR3ki/rRx2CphwyWBRHPhiEeunnwFlGm5/Vp4H9nhXQgd/Sz9ES53Hu/9wMfU9fnkPr8YpkdstEcTygNVcfXd7izCgb7d8qRxGA2n3pcxL3UEBqbxW4yBq0ZaAth/fcW3V136V39KFt3F69sPaexkjemGG6j177YP7e8+hZ5NwrOI4mK/g6AqR8vxSQen3FyxNo67xXZk8H8cPNv/C9ZCefOcDu6cYToQc0PLmjerFnPXtl+TWH3oztzbZ6mj8wSDrP5oVlym3ZPcCmZdd2pHa413Y8IG1y8y6HJfWoOuIDpirZA3mi73Fq+VSOHnn1qzwNmHK5Na36pEyDysblcuTtbfV2266XrxOmQXM7gyI6HOgi/P7pqJvI9z9W6TiDXLPUBadnn332cQcyD4V01RSoHRV1WrhjsTOgDkPZxpumT8SY87aLsRLGA5LK+6NpyqOcvCt5W1zvRN88ImH3OcnjAlRMnZPDPYDKzxVAml6apUu6163HTNV3Pc2YSp4mZ8mL+fu3odOjoNzSqgHlT/VkkWGO2KEv9ywX6Yh1xwC/OLm5LovnKFW6k3ghwKVnUTrdUsg0ZP9ku8hhMJVEDp0nn8ZhR+JwAdNGl5JfL3zpYOvVQ7l3ANI2VJUdogfTfZraezPJwjfUMUr35Y5C/AAfpC5dGdW429AcAKzCqA8zdd8Hy1Nft22E1sfMVtgnuUxlrPfGFjl9dk728gx1e662I4vN0natbZYPNFLZIkDKvLz/Xv5RP5+zYxEt6hdOm9B85vo29yO+163ROlZ4eliUH2K9238FbZZOQRbL5fFTfyVSvtoR/XwM843y6pWLVzXnQC6Dw0h/zKNZ6ZvpV02Y6psiaptX/hyu831AH5hqXfMuDgWc3dV5uYj6aQRKXRvq8FTyyuvxXdrfC1/xmzy76k30c572Tix/Aqc6cdh4jP97W4iPBbqjIbUuOP30pz99lMQ4tsgDJr1Z+erwHwNq3ODp2gCHrfytsAGoOwCSbMWyz8lkA6Kg75/Kud2ZAKid3Ft9BzUAqCZDs22PyjPX6DOXG/WpvLMgNfdnfCrwxyxYVuYHyg91eCWvI4rdJ5U5kJEN+5yOuE15kdmp5MdajgpAW9xcy92T0+57g0IEXnVA81Y8eCu8R95Arjw0LuADBnUGdEDXPCLHyMs/Kn9PBpV/jrw8erw0agMmZ/gUvXC5AyfKMljU9ymu1lfkMO0FfEZtw5419qBDs7Zc7hsb5siR4Pdda3dqJ3r9oFeManKAeQX1ynl5TrTreI80CN+l4JT5eEDOs0nohHHZvbhzxHUTyaj8sv53bJ8BBs1Hdb0ECHv21NO1fgPUKwfzt8lCPaPC4uu7oz3brDJwnqHdnal/S+eC3aBMGZsJlXICLOr61a3N2ldU3lngLPl7IC8ae5mnTdp6eXlp16KL5r1RiR/aDZGX8422YM/uuAracSf7xeFzZL7GkkxLHqm1v3poExOf6Mtgd5+ODu0fiITN+6Z7aXfNdjAGMnmaPV9nOWmSrMiACYAWkInJyd8ZZ+Lte3spb7b/VmAHk9FLq8mgGaDdFeDKM0C2lc4GVQV7Pb3wFk4FqC4wJWOhq7KsT+a/k2jANKOcUDkAJjc7f5n4NU4hX4sBYz4mXtm2p3VIMngAVoGlDhzqxISglMJMl6Zz1m1vcHKdQAqHE656UofCe+Y530tWyTgO56Pye3G0CD2nP4pTlU/zlngaFj3zgDVQ1/tS2usgbvlrXp6Tv3STjDdOMzgsbfMwDuZdYOoItyTrbcRrdmeMVG1jR+3sKTgdMtzPnXD7T/IsSxhPTDFfda6r/pQnh9bAaFUG4qMUTfosAadc9oiX6gJAt48ddnCqdsDhy/XE+VrZKod+/OmqlgdsmSKQbrIqGOT6Yh17gMF47Kza9sFbdVk2S9N7V7UHNpk8IM91sA6emx6NX9Wfhqnc9tWDUgbirRS12x7NbeXV5HzPZdcJdlc+zovaFk/2MX/PXkRMWV7tR3s9aXyOeuXdZvw7LGS6I1sbjVNVf1QlH4PE/ukdhb7mwen/uvn/xTl4eBUWdaioIavzt0rAiTt0gNJQG5Vi4AgBGYgtQRkFsGK8H4BqBbQcVsRhY/ry8vZqM/tjANTiV7xRr55yZ8ygDsqDMA9u6G8RZpDaW5VtHOg06cpkGGQgUv6Z0+a+XXHDbDAY7/VTNpy29y6TtqEk95x/JJvFr7aSc4JE9wRQI1IHYg6Yeo6okTocUb62NZu3OXoOztxWP8AZiCVf757LpOXUdL3y9sKUrwdSo8mROVpSn0vIJllMkMapDtpytHOEmmAtEzVcD8zN5dfw0jD4dVHJZf0v+W3mcLxLpH2SJ8LMidfJp95qMdtRtmNeGtuZMtBP26536EumeJA8dIVUgZy+s9wDqSp3BHAh6aFhMw18q/Yf9P9ee9p2O7Plw+8xRnyAunys96JzjUPtaMgTQPNkd+0dNYoKJDplHKqENc9effbeHy7vS3b4uVtVnbJYe7QDgsphj8JXySsr58X2w5NRn3nteNtdIU1d5brI9qrAgM1k/Zrz1YIFTkbT7yiKLWwcAJDTpNNGTk3o8PKo19f3SiZLtWDQoUotJgdNpDqPi79cvod6BwN/xzodMjh9xzvegT/4gz/AF77wBZx55pl46lOfigsuuOBwyHa7UnGybLDBwtn4scHvJAKtfGCRGUXhZx3ktjzx2QGq7bo5bT51Y2B05ZzSa/lUqCra1jvytPKVkydNNpqdZ3DFwI9BqgtQMcW1IJ3Vb0AqJqNRtgnTg4F0xLoDy6j/NU8hDbKyWdn1fTkD9LyNlQfYrLyApv3MbWf2VoBKvXCdEDD1Vsk8B2cOgHmrMQ0vTI6Sng5q9bxKwAk70zWn8cqsgydPCHmDnAcEdSA20vfDNE/l3btnHSS0+XN+fKDVNuOb8jFes+kc3SogS9j0fQ+sad0oMPVkjAKbfqVocSFxXWvyZjKI8tgmG5PN+4RNDyix08btIHJStU2xjVri2Grf9MBp49DTuMP3PDnUk1fBqfalKKzK2+mbBpir/PwiVPLsldg+ev3LyyOSPdRZYH+VD9ACNS8NJF3vxNbofesyljm21Hhsu+Ko5e/Zzh7Y1v+6mpsX8Kry6/T7qBxF7qiN0jOVvfBGbDN6Y33vvAoDpuWa6o/BdCWEY2N7/EFJzK8ZOjJxVktoW1C61/7NdaZ+H7OMqiLTRblOdPL3Idido0F3NOzcBafve9/78Iu/+It48pOfjBe96EXN82c84xk4ePAgACCPLeqNb3wjXvjCF+JXf/VXj4C4R4a0UhloFSDm1Pxch2eyLTUDUBo5AzU2MsUQJjphL20+Bs9gtZJ5dIAzG5vgQKRk23vTtBJpW7t2CFggT+DQAz8MugovQqEGoCaBaKZKgKzxLrqF39myyKFxXBlnAJtLJJc6niuqFz6m3xwG3YpkPBgEuDJSwU1PXvurACrL6ZAH5MqzII4O3N61lndN1zlv2vuB8WdpTxj7wO4w7RLgzzcpqGengOVtni+49rYWqg7KtdyzjiK96TN2UnjbZq/ZcVv2+PB9dNCQ5zR5/K29Zbp348mzJdQro/VZ7e+a75zuOTzrszyVL7IhOvGjwDSU3+HZA3Ve/KZ+qL/38vV4G7jja40f9QUN85y7yAbwM08mL9+enHP1ve1qVEgOn17ftjAXQKHWGZO2ZYu3Fn3ZfwX/xqMqv8VBvQpZtZvs99dV1BaJx1JQV20pzmjqmeNHBxGFOqUyLgXyGsZp3f4vebLd0HwHeQa0cgNtP/BolXx5gBig6neTbbw0O8qrqFUB41uXOE5Km/ZiADU7kRbx7LSnKP6hUHauqwkCueCDRzlRaXNpjIO4LR1LdKzLty11wel73vMefPzjH8fLX/7y5tnll1+ON73pTQCAhz3sYfi+7/s+/P3f/z3e/va342Uvexl+8Ad/EN/xHd9xRIQ+0mRGaUUODgOqOWctjx3bTgErjo/xHMNXq+l9Unu539IDo3FIm/ADY94HdjbgcncEnrZNd2c1vVua8nhEdp4+T2Pvn6Y8boHJU1hm2bAJsG1ptoU2wwGEjj4aYE9lUqeUVFo5Z+X9q46es/Bvntk19thpJSEPdqPKp0F0jKOrGLwCYzpWsGxAU/Xo6UYBBMdhOfU6O9e9sOIokCzrYSofA1LOaz22N0tvQPTASrb1jjpapU27tfeK1+NWdf6mMNej63g7ZeBnXBbPqejpQJ+rfpm4DSwhjaefU5rj01t59pztnlPUhM081zw5n15eVZvWhtvedsO7jvT4h+2D55QbKGRg2ltFM90umais6iH5cSu7R/2D84jam7vN1q6dfCyNJ0MBOk67Md466bZklVTDm8ktp3xRP5rrd3t1zCJbYvdmq63sPVvCcuj7e7baqeVgvfKJyRG49QBp5YAHIIe/cc6AxztcSUnrVlfqWS6Vh++9dlmtvjL/oKweqeza/rzVZM6nASVOXL33xkkum0dzbZTP4VBAXp47vNZBvloeLYe3myy0955tkHZXRRe9eXkCrf/C/Lft0x4vjy+PDdF2f/VRkbH/ndOjTF1w+pGPfAT3vOc98V3f9V3Ns9/6rd8CADz2sY/FH/3RH2G12pi817/+9bjkkktw2WWXHTfgVAcDowjgzHbkMQ6/B1E+P0KOUPlEDG35rQDX2CFy3pzom1J9uJF9yoBXRXfHrb47aep45RAl3hKcCbA68q/Qlr/ElRlAM/DeFl8FXFni27ZZ5sn67p786hi7Ki9yLra2K046ls/ktnrWfIex7v7lPV4LAPi7L11SQJoa+mr1dfwTraRyupKf/IB6cJgDo1wmwF8d0dXRaEuXrQ5n4mNbfnXgSKhXTg2UHljVIN6TV/l5zhWXKXKKdaDtAVevDEyeo6LvZs+lXfKtT48iJ1/v5/qBTqwsiduE9+SjTpSxHPx6eXjPuB9V/VcmOzyKAJcnSw9AcntlRjqOsClImk7au4KOpm1bfM27U64KWORYFnvurfopoFWQW+mjI2PDK+ifSizz3KsbEXHUpu5JZm/FkAFUlH9kw2z8Y1BqcXis0XcAI8DkjeV2z+1nLffejhhPRzo+aPl78hkPjdNbLfWAqclQjQ9Bm/Nu7JKBKdcJ68AmoEHl0X61tJ3xhLtOBkQThB5rHl/Nb7CvMkQAXeX2ALiB4B1M/lh3sKPH6pvwMy+vCmSP+fDWarveEZ0pbbujh2UrY0Og+yquhW9hU24P2qs+jlXqgtPPfOYzeNjDHtaEf/nLX8ZVV12FlBJe/OIXF2AKbLb6Xnrppfjwhz98+KU9wtQMMOOfZlYIe5upNcNi7xGsxm2OK0wfdI/kAiZAZP/LYUhAdRpvcSQGVAcjVWB1fF6MPP1WiWZBx/gGppsB2IwYgTl+d4pXC710Hghj4sGIH5bB26kfC2cjVAwMAR7lVfHJ8hCtbD3nPGOcSKC45b/TnqxOrZyV8TTnQ3RYBnP6cV5NvE6Y53jxispAeXCdaPkrFVJZI4d/yDTgJgCrerWf5at0tnDg5PJoOm8AjxyVSA6gBXLbOMZKve1hc6tpWqdRHM/MeGXW/Lz2F8nq5Vv4Ak27MGr62AJZowQ60Wf/+L3XsE85MrG582RX2RiQZy9/Jy8GGhUPJ5zzHyit11e4XMrba/dqFxTAKF8uc5i/lHfJ6r/20Sb++F+B2V76oNffeaLNdoVYHO9zKl45+L+BMWPuxeNjIfgkW08+oLbH3uSHOvc8dmrepoe5uhmc8kfyhTJLu5ijMs6NZSiT+05+OtnCk34ZU96RvS2fqJFyReUrPODb1yGPPl6eL6+Oq2HcEZg2YCrX940s4/9VXgZoytjs6CLKwwOr3qJF1W7Qtrslu+f2Srn8mc9rn44+dcHpF77wBTzqUY9qwj/2sY9hGAacfPLJeOQjH1k929nZwUMf+lB86EMfOrySHkHynFcbHLz3BLZpw14Hyhmbb46NVmJnVTu4u2aEyXgjj6ui/M5oGeXHgWnVbokxoGhAiQHwkKZ3TIe8kcPyM1DJ25vt5wGQ4sCOstqKGG/ZKacXE6BtvAAxXpiS11YwUbLcDsA62AIETGVgKp+KobLZoG6JmxVttDKy02eA/H9+6ZJilFVXlqZ5r9fkYJ1I+Sungh55bTkCqLpVjeOqU+o5APq+q04gsAPNgGDQMCpTcSBkJrjK0yGta3eLYscxKPqROB4/pR6g3OsA2gM+bny09VvVC8ghcPg2YeOfLPG8CYlIn2Gc5KfxeC/ip0wkjk5ONX1a+odX14kuItlNzgY8S5ticGC0pjRszxQwmm2o6kVkd20A0NRz9Iz7gMkVbZ3UNHyCbBRXV3JZVz2ZOB6TmsmIlgJWrw2Y/YtWMbNVEPFowJ7FtTi0Y0q3xK7pXnn1AD5v2bUxyPoty2bj5ly7Z5m4fSlojuymUQXKSY5eu7TdZuFBSh3Zc/kz1hs9UHm9T6hkiluFOXIqabDpeg1/Z8ySMcLNStoTy+TF13bGr55V6R1fqhkLAv78zGtPClC5zTAt2rkTCRLIZdQsQNFN9KrYwqxuV7qjgesuOE0p4eabb27CP/GJTwCAu6oKACeffDJuu+22wyDe0SEdAAFU3+o0MmNvcSuQsaQzUQc33jYDyMhoNRp/PpXPVlgz/8wwC3i076DatgiM2yT5nVSbnjXDuDOiJP7ETO8Ffi1XucYEShnscZh3yNI0Yk4GQvNWQ2J8VYZGPpLTc4DZYBZ54MiHWjZvdtAj3rrqtQHkqb2pLhoAT/mWNiCDgufIRP89Z5b5eoMyD7D6nkxVZ0HjMV1YeZtvMpJcHB9onS+P3O2BVC7Av9Z+5fFjvt6kk0fbgGwvPt+qk+nGjxyJQOZtBmMN82TdRg9cx1Xf6+XR6+teGUF55KndsY2K+oi2VXWSja8zf1SIJwyjSB6gtX/6zLOLutXSswWQZ3ofgZUlgJdthddGmF/PXnlyGPUmiFZSN0xz2+Sjw8U4zHYjefbEa/NcXgYRqsfe+6ORjertImGgVb1CQu1Y66s7uUbhlk6/S6rl8oBow88pGxP3KeT61RlOU62GSiZV+3L0yrsNPEG9slv6qE2xykuZEgFUkcObqOqSyFB2yeVat10Wjq53MNm7RjeOzYj49XTjyZFSa1d7sqp937as3bjjn+MR5LGvfUehLjg966yzcM011yDnjEQ19sEPfhApJZx33nluui996Us49dRTD6+kR4l4S01E3uwUO+bFCZpxQDMwDRrkpA+Y9v7b6mfpyJj+VwMeD5qJjCBt+7Xvndq2yTxM23Wr8pASigycn8kk+rByFFCHSV7r9JWxY4+OQQ4mY87v7HmzaWzgOaySicoW2SrmzyC2AouQcjh596gZhNmpFR00/yWt6rwa6FHfe86l52CorBElxAC1x4R1xk5/E8cZDBlQMPEEig6MkeMRORraryNQ6l1vS0vTRm2mCaewqF/a8x6Q2ob2CkzVmeELb0LCi6/ZJPrfk4Enl3hCiuucHXd7kLB5DSNJPJOVd4o0DpT0P5aXy6X64/g9hy8CStoOvHsP/HB+vcmrKp3oMepLHi+OzzzZkYcTD6jHB488fbLuPZui8pssVTlZP17+XDY46TgPx96xvF69RGlsfLJxm8c0JncCT3lJGMvsTYYwKPWqo9f+dPVyZZ2UqPIjMo1bXv055eLyrmfSctwsz7p9kdL1iNtGb9i0z7qwnWJ9MzBdMqYUfg5Fu9WUre6Y4vg6lno+sG1x5ngWvoS8cqo/kSm88U97vEf+7Mvv0+1DXXB6/vnn4/Wvfz1e9apX4bnPfS4A4K/+6q/w3ve+FwDwhCc8wU33l3/5lzj77LMPs6hHhkpjTNMMkjku1ewdppl2oG3w2ph7jdp7/zLlejAxWXaUT6oPjOl1oky/0vFlS7CBWfth3NrLAHUH7cyl8S9lmMSrAGk2NuO9fUiaB4ZM6cp7JKhnfs2J8FZzvcFnCekWGw/4MEhMIvc2IDVykgootQdpMo6sN10h5nbLeXhOg+tEUHz76eRHAc+kA93yY8SryxymbYTlTXKv+tEwHjSMF08qeCDTc757zjw7X1X+jqPjFLmER+XQOHPUAECnDpY0d9a/Ol89ikBiw1+ez8Xl/3zt2VeN4z3PqIFnlI7fu7dvPFdxqf/wpM1q9PZ5ZaG8FoCpL7LDbDZNeant9vqmytSUg9J5q0cheJH8OK43saN12vQf7jtOPgAaQNUDpUtkr3SwsJ2wbGzn1BH1gFozYQG0dab6dcoZHfCj5VUdRPXipTEBzH9Q0FfFE71ouYuMdN8dU/JU9l5+HOa9t5vSBMj4q3len2dg5tkqbQuDpNU4HNdrR96WdC+fhh+WjQvFVlCkFUb/K1N7RGArOrxNP7ZKGtGS790eKqk+vG30QHtqf8SLjSvbXWABIKW89dWX4waoOmPZ8U5dcPr85z8fb3rTm/BzP/dzeNvb3oZTTz0VV1xxBdbrNc4999zmfVNg8z7q5z73OTzlKU85YkIfKbIBq3o3cqRixMUIRg2XAW+Ul/FF3hjjNBoee7giEMrpDDiX018xgTZv9muQldB1RnXyWKYfhnFgoJN9Mf2r0rCDxPJVv7TJz95hNUN7QIxAAT5A2cLMW13NSBhoVSd2G5u5dIaOt/s2AFUzFb1HdoJsaFVfmRU6RjA9NGCEBiirF34/1HMePGfGI55cKYZ5BphqWi3wXsczBbRcBp5F7znV2QkvYZ34rjyoyx/FXVLejBqgbMMnksEFFPS858yH7bXjhIVxnPw1Xej8IJiwcHiqA9MgXLT1WtlrsoPKIoNWyzCdJG2HyVkfZKCj8kbbvlNC9VkxLY/FzZKOy2D2ugduynXn3nhovl7+1RZO6Ucqc1SeXhv1ZJorh07aMTFfdrhtHDIbrDtTNI+1lpflDN6xtXrpHpqEenIQaCfaSlzJf8gt8NRxGFROzrOnU6ADBp069NpgNNZU4FDahrUtq5NyIJTD0+KD0pXCSFk9mgNe2QnjcK8eM8nfI83aqxvW00qeMzCNyreErN+s83QwErsfmYStJtGET8+v6C7QEM9oWzmP7dErZpze+0LEHHGd6/ioQPWQFL5PW1MXnD7wgQ/EwYMHcfHFF1en797nPvfBm9/8ZjfNa17zGgDAYx7zmMMo5tEjbdfcSb1GuqQjNMCOrBiDkozJAbLnyt8Ab3GKRFYXeCVsDl9IKKumPDvH75kCm5k1O3zJ3kPllVUGLjy4Vds7ZbCJvhtbjAFd24qmAXEFSbzCvBRo9sgDQXZvADVneYfH5ClMKJgAbK95NKBr1Anrh9+LM7LtPLySb+E8UGr5PLKJjnKEPDrtaA/UfZ/EkS3ahsYOkbYz5akzz0A7mPOgpE5J5Bgeyqyx57gUh8YZeDU/Nz3xidJUMqfqXwjKI1DlUQ8UuDI4cTyQGWWpjoy71Rvzbdl7d9lbebF+5n2n19Ik+l9l5aRLVr7RlkbbK3uAs9Q7xYtW+nmrMYnVBcJ8PUg6BqZat942XObpAV+W1UvH+do1UE9Oaj/gV3PKu3MUL+VNhJX1vyBfS88ysI3QFSzeYqzvp6oeoXyovXmTcU29wNdbsSljG7MJ7MguRECUw1SGqs05bcGuvXrwZGVwCkw7EThv9jX4k2aefYvKwXkit8+1HUk0tx9pOeDY8iWU9b/Vj9gk03vQZRrSSTcOL20Z9TbqnOsEnl6YGvuN/sQc84xWoi2M+9Tcp2U4jubryaW2c+6MlaU6v71oL+3uWKYuOAWApz71qTj//PPxrne9C5///Odx9tln40lPehLuete7uvHPPfdcfMu3fAse/ehHH3ZhjwSZY8HETo8BKqBtxNrQU6dzesSDV0adpwHUaGZqhc23T23WywPABijtVF6g/YRMkVcy2QFw27AZ3HIGsq2g5snJYoNqq3yJfwQsPXWsQIN2nvQ6oE7DwJQBalVW4e3Vq8X1SAcsJnYsKkeUDG6VlB0Mn2Uliw5sJQ2VVwdJnm3XAch7J6Q3GOiBRFIUF5wdyvshXh7AVPdefM/B8NpVJK86EsxXdduT3XhFgz46z7w2WvLpDKrquGgcdR607A3PYALAy7sXpjLNyQf02802bYrLrOAy4qOAjYkdeAWh5mhz3ha3fL8ard7N/mV6xnY+O409AnDRhMIc4Ev0rLdV3QNC1X9pj5qm62QGPO2ZkgeINa62+ei0W+PHsq7SuOJJSo3GawNOujW5rIzmVhbv/VTP/uhOF6Mk/Lyyap1wPCadMNC2rM88fp78HjDlcpiM1TfAvXokHZqOzQfi1VQbo+wdS16Z9hTA24Ebyu2l6ljbdcSiac/Ux7keGx+hFaW1NcKXJ0SMEjbtuCxoqB3wxW/Hc4o8pxMlqytv4pDTc/iScbbhg9rW51z3S9Ox7WhhuatdcEQsh4LbHrDdpyNPs+AUAE477TRcfPHFixj+zM/8zCEJdHtR41B2OpFuLZ0jPWRJt04qWSesDGMZWcdOmSajndL0nVQFo2MSrI2FCWOHIaXxo9y5BQcrbFZQVwnYGVdSC7h1Cs+rjAxSFVByPmogEyaHrxhaAqYe2A3BKdo6cgcIC0wtX6B2evVUX3P+qokKyahZ/RZZqgGIZWZA3imDVyavbQ3Zf944nll+nJeja4+iAU0dHS1HU19OZqZ3nTRQhyHKQ+MYRQ62DuTMx6PQIfDaCeqJjohPk9Ypo1dmBUu95914bTQ3/yTPI0Dk8Yz6Kof33lFmQBblYfF6gLbY+VHHTX92hA0BfULb1ijcIwU9nF3pnzPx9ZkXrrxCgEr1q8+jFVgOU7k9UNtLY9f8DJgHWZyHN85U7crajtPHBtGBAlPm7X16xyuHAlOtT73WyVjm5VH0rnh0OnCv3uy+qjPqGxEwhaSNwGnRqT1MctCPpGUQp2M0l7NbnhnZltgtTqvbcK3vez5iZOu5TNo2cqZDnPZIjT+AttwNQN1Dnp5f0ZNjCb8IGJZddmTHd8S2zk0waFjk128r99GmOxp4XgRO7+jkARJ2HjznSJ0bOHGYGoAqF8yvPHMM4nqg+CMIXY2g1N5D3cHmno1+2SpD75Ka4bdTfEHxmq28Yxw+UETLmlBvS9KVVJ7N5K07hU+eZlpXoNnG0WKYU6kGZA6cegN1w4MCPYCkALUACr6msugAXPEkT5MHgWqlmQtKz3hwZlZKlHQxVYOhPttikIocm8gZa/IRR6TpczP5ct7dOJ0BLMvzHi2JV9XzeL10dV3T8r3y7snEjpynqyTx7JnXFvh5b8Wz63hjqt/S3FObLkm4x6vKcyasykvamrZP7buJ+q7HvwHn4iVrOTwdRMBHbYDmP1cPGj8Co/y8ii/Pe6sfIdAdw7ppAx6AD9L4WmVUPmy3Nd80JmJbb6CAGfKnrhSI9UBnBFRKnTvPtZxNeams1k+aiReHj6fb8kzzoLJVY5Yj/xwo9exOM7HiyMZ2yMtLyQPCEfDSNr3Ingf1Zn6evqoRjU3crkud5FqWtVcW5hXYBOXvhefyx5crUsW2wJP7X49yEMf0vBKbzRQtGEVfefDsZVmAkLCIz7FEx7h4W9PcV1Nm6R3veAd+4id+Ao973OPwzGc+E//tv/23wyFXod/4jd/Agx/8YDzkIQ/BRRddhH/+53/Gddddh/POOw/nnHMOnvrUp+LWW28FAHz1q1/FU5/6VJxzzjk477zz8OlPf3pRHs22XtRbutgwAu0JYgqAItKtYZpHRJl+9v1Te+9iPdT3u8O0xYJ/Fm932GzX3R3GMEtPYYPkMWh+Q33v5acOFpe3ioc6Ts5tGZVndL/kp3JU9YB2EGH5tE64Lqtnuf4xL9PZ7lDXlaefRncdOYz4feQ56m1li9pkZNQ5LcvlAdOq3e+hDteD/5ut+0DupVuMuFwaNvfz4rNc4S/IXx0+dlbZZnkyaJuM5GzKafrn3+D3S+3/Xn0YcXuvdJTba6+MS/u7197UzlTtVRTC7/mXA5JSzZvl9+TQvHeH+qfPbqPfrevxej3aaqkHrw6qeoDoA2jqSdtU1ZZE51V9UPtR3p4OtB67Y0fejJ3V+Ek8PDvu2XjTq1cXu6LnW3eB3XXdvtcZ2M00VmZgGGp7Xo2NuS6vtndtg0peG2yea1mD+KqvRs/w9VbKMGwicNylwLRpc6h1pCJX7Q+tnviAKu2vTXsef007lnwzprrGlKzVo+h07vCoqkyS/3pMb7qI7FMkizEuZQ3k035TxY3aXSdPtXOBWP7YE6TplpHy9XynMP7444UKC++l641TS+lo4JY7OnXB6fve9z58+7d/O1760pe6z5/xjGfgwgsvxFve8ha8973vxW//9m/jcY97HH7xF3/xsAj32c9+Fr/1W7+Fq6++Gp/61KewXq/x1re+FS984Qvx/Oc/H3/3d3+He9zjHrjssssAAJdddhnucY974O/+7u/w/Oc/Hy984QsX5VPNzFO4Xavh4UaqwFSdFf2pMTPjocbWmP+XH3wtXvODr8X/b/yxM1WMD4OcvBlAixOfW0Bqg7ECVDOY7Oyw4WNwsARE8KAeOQ06oBn/XZG3MfZ0r4PzHOApctD/DF/+ykETPWSRmw1sZZyFT+MMaz7KU55XOpB8uU1G79x6znR5LnKzrt34ou9KB9Km1bmNdMDE/cmrR+bF95Wj4uiu8JayRKQ6Zt0cKuXOj/PznAvtPz1+xdYEeUTEzYiBReNk82RXnvquvqMNbMJWCdhZTbs/OB8Dfy4IRF2v3TLn/jOvPZl8za+jm0ifmhfbNgOZBoi+ugb+eXfz/9b15vma4t46/nbJrleTiXKvAEnBW2Nf0PaXgWUnPqV8wqPiiTY/RPlp/Vh+kHc4g7yreqbrWXA4TKCEy2B5DxJfJ4a5LgpgzdMOJ4+M125GBersf3VCK8kEbPrKDtl2HlNCPec6bjX26Q8tIDUAVG6lnr3Dn7TuK7703DNGzTgobUCpGQdJZi1n005IRkh8YuWOa5B7lU3LwW1aFypAPFTHdeZt+T0yvfF99bzDq5cF68XqE2gP3ZqVT35L8m+ai0SsfDK0fhqHc3kamxL8ltLRwi1M7PNt81tCv/mbv4mHPOQhePCDH4xXvOIVADafC33kIx+Jb/3Wb8W5556Lj370owCAnDOe97zn4ZxzzsFDH/pQfOITn9i6LEZdcPqe97wHH//4x/Fd3/VdzbPLL78cb3rTm5Bzxrd927fhBS94AS688EKklPCyl72sOt33UGh3dxf/9//+X+zu7uIrX/kKTj/9dLz//e8vn6p5+tOfjj/4gz8AALzzne/E05/+dADAU57yFFxxxRXIh8N7RGyAvHhzZA1Dt4Mw6IxohWnbiOZXHEYCo5UDM4br6mjj0Ayts1MNzBBHyAGrakA8gOqBFnuuMjEA5cGtBwqLExCsrnmrDZynGkKt/8bwEQ91dphP5UAInwh4cJiWjx08iwcnLuRaibd1shzMy3VMhY9bt/zfKZfq0uTRyR9P31UdeW1JZADFZ0cO8izKk527pXQog95eBv1DjWOks84mT9g+UfdRS7uzAk7YmU4P5dXHndXmx9u37XmTN+UfTXC4TvfCOFpmzdvVUar7jgJnDmcgagDUwOdXdzfg9J93aZV0qO3x7rq2zbsjP88Gz+084XqycaPEQfs8oqgPaloXHNA1T5AOaHWoeTZtQvKuZOZGP173bCng6FLyqcaKSKe5LjePSUvtAMsUnfWAsf4YpLKuvHZQdD/+CthQ3ZCOK+CZpxXfxubnOs1a8jMw5tl9TxXcXjgw6/OgLWqYAmbXF3EEaWyeyODFdwEpyYAc59cgKycjb+deZ25klpJcexhmm7HvSFAzHlGfLe1K9Szx1T5vM87O0bGCWw6VPvWpT+H1r389PvrRj+KTn/wk3vWud+Hv/u7v8Au/8At48YtfjL/8y7/ES17yEvzCL/wCAODd7343rr32Wlx77bV43eteh2c/+9l7zrv7zulHPvIR3POe93TB6W/91m8BAB772Mfij/7oj7BabXDu61//elxyySW47LLL8B3f8R17FgwAzjjjDLzgBS/A2Wefja/7uq/D93//9+PhD384vv7rvx4HDmxEP/PMM/HZz34WwGbG4qyzztoU7MAB3P3ud8dNN92Ee93rXhXf173udXjd614HAPjql/+5erZ037Ya2pJ+hsFKrnU7zJDG9zFHWZ7zx5cU4zPkjRPHA3ABuXl8EXwMt0/AYIzDp/qu+bl9/3RAOWxpZfGAzbulo6XjA5fYcUwWD+0Kg2XRvD+K+t6z7FbOdfvIdZijgTs7aYrOc/2+F590y+DIk9XqZNGHom0Q5zANcMrC12n8w46KN1jOyRBu58X0XFe6evE1Xx5o5xyPKm5Qh5rWqoHD5gbLUk+OMxTK05HBu4/0eyjjTOicy7M5J/5wHJaQ0ub99DXqtmjtOFG88XEBn+Uk7lxvYeRPQgVmYCoLWieyF9dk8MLtOkncPAZWK6KcyNGjJ1OWZzwhxisOlr86/ryFWCcih6EN8w7Zi8peZNU+68jMZSwqSHU81UMla66fad/KuXba9XTXqB575ejagtzqgeWpoopsVb5oyxrJXNpZroEp51tNbqSpXJyPpeV8rO8VPnnqS7pyxu2wKoxz69m10k413Knbnl4VjFmf88jG49JPM4pfw3mHbd2Rw5uQ1HJ4k//Mm/WgPIbARqgcXQNmVByTII31ezJmPbZ8rkWOeFJ2/I691zaAtr8tKVaPNO/InvGzrjxBXR0pOlK4ZY4OwxDf0N/8zd/gvPPOw0knnQQA+J7v+R78/u//PlJK+PKXvwwA+Id/+Afc5z73AbAB2k972tOQUsIjH/lI3HLLLbjhhhtw+umnb513d+X0M5/5DB72sIc14V/+8pdx1VVXIaWEF7/4xQWYAputvve5z30Oy8rpzTffjHe+85247rrr8L//9//GP/3TP+E973nPIfN91rOehauvvhpXX3017vQv7rxnPs2MJNrBUmlJJ+FBh2mVxgOP0rQVjp9VM/ioZ494G5htJSsz8Ll9b8lmsW1vf/SuK7/7VGbbaUWV5VAdeTP4qjq7X4sMLKsOjq5OZXDWlQUezCo5iS+HgcJ5VdL7aVmMNF+Oz/fNbCDl3Ry8EOTNcdOCuF55I2e10o/cV2VxBjEvbAmxzLOrOtTeeAafZ/1VHlcfM/l4eR4JYOpRtIVbZdorscNwYDX9DHgaCNVnO6t6EmsldgvwnRv+DR3ZVde6+rWkjeu1x8eeeyu13E8MQNiKZvWO6NCm5RXLShbjF5S/AWUqU0ZjXwfKr6yOUh5qFyu+rEen3NV/0gW8OBTPWyFlHqx7r01keT43SdWUQ8s0/qp3G1UXpN+Kr+ig0imNu9q+mnEmqFdv2/Yw+G1bV0n5x0pQvbr6QO0DRP3N0yuvDsIrq5OfUuOkitxNvZLu7JmuHHv2wcnG9Ue640Dnea4itfrm9C6LXtsWP0B1xts4+TUFm2Skf1tt+9R6m+l+e6LDMbF6qOPxNjIcKdwyR0diW+9DHvIQfOhDH8JNN92Er3zlK/jjP/5jXH/99XjFK16B//Af/gPOOussvOAFL8Cv/dqvAaiBNlCD8G2pu3L6hS98AY961KOa8I997GMYhgEnn3wyHvnIR1bPdnZ28NCHPhQf+tCH9iQQ0/ve9z78y3/5L3HKKacAAJ785Cfjz/7sz3DLLbdgd3cXBw4cwGc+8xmcccYZADYzFtdffz3OPPNM7O7u4h/+4R9wz3veczafOYNjxHXJKzFmGLJcRw7j7kxexYDTypwZkp0ErHamuOXTLZ0Z/WJ0sJmZHgbggAWuNrNuu7RymlfTSbu60mo/lmmYWE0rjcOon2FyRstBwWma3fV+RYfY/BkkH2BaJa7KO/6ptgdSJ+SB1v57J++C7kH/mxVUyo8dFXW+o+pu4llE4l3KnJtH7nYeLmdkjHXw7lF3sJRn6sgvzcPjV23lpbIru8gZdcvt1NVSmeDkHeVzJIizOVTA67UZnrSYy7/iZemp7+j7o9ZvuHl738bz+Fve2s68sKZATlk1nu4+0LYXyQRpn+oA8zv7Om5E8qTmYpLJCe7L1yF9322uDzU6FnvqAQ7moXHc1cgoL+bVka+3GsjBKqddezJFcmXv3imfx08nPZIY9Gii0cq3zlPf4XJy/x1swMz1GGNpiuxoyetTvZXSnu1nYKr6gqTrNdsBtcxe/UVkuptrT1G9A2j6OhPvtKr4Uv1WZe60c9VpKKzde3Y8zeukSQNMu+yC7FyRVGfbZbsVbVsurz0C8zbUU+u24Pho4ZbDQV/4whdw7rnnlvtnPetZeNaznlXuH/SgB+GFL3whvv/7vx93uctd8K3f+q3Y2dnBa17zGvzGb/wG/tW/+le4/PLLcfHFF+N973vfYZWtu3KaUsLNN9/chNtLrt6qKgCcfPLJuO222w5ZuLPPPhtXXXUVvvKVryDnjCuuuALf9E3fhO/93u/F29/+dgDAwYMH8aQnPQkA8MQnPhEHDx4EALz97W/H933f9yEtaFlLG71rzFEPWF2HyZ4HxtJErd73cYzhKm3Ama1OHNhxDhBhfplmPofN4GWHJrEjtTtMpxHqibzNymWu42TKI5yxp3hlIJdnOtDrf8A5ECKoP9PVgRVwwmp63431x++/RS3Fc74aeUmGOafbWz1q8uvpsJOuWfVFrXdvpbr6ZTRt1HhE+oDkpzrp9ZvqnuJ6/UT5eDr20kR8VUbXEc11+ki2JaSyML/ZdFvmWZULe5Nf24amN/JWQlXnXrqe7AycKsc/x32vqWcnby2T9oNi74KVTref0H3P9nF75VWMEgYBJ9oHMTnq3m+QH7/r5vUDPSW0scdaVtJRaLPRllWBW1UuR6+Rbarik14qyvUl60blZPDlycSTmK79lHap5VN+1W4fkSFqe95q58BoDcEqCMVlHlxHagd57GhOxqWyhOM5ieWNU1nCTF/Rj3dqgWRj+a2oRVZRwVJgqvXRyC18eAKiOSxN+GUL03CSv4oL0p/olnUcGWjz/XrOvZYzlT90v0V6t64dXS6Jk+n5oVIj18wPiH2spZ+SOVq4RSla7On9TjnllLKL9Oqrr66AqdHFF1+Mj3/847jyyitxj3vcAw94wANw8OBBPPnJTwYA/OiP/mg5EMmAthGD8G2pC07POussXHPNNdCXcz/4wQ8ipYTzzjvPTfelL30Jp5566p4EYjrvvPPwlKc8BQ972MPwzd/8zRiGAc961rPwspe9DC9/+ctxzjnn4KabbsLFF18MYKPEm266Ceeccw5e/vKXh6cMLyGv0fY6izq5XtSmQ3f4sUMRGlgymjZAlS2/BrwIxPF23mGoQSgfGqRbfm3Q1MOVGNwqSDW5q9WEXINXPqiGdRc5pNVBRQ5PzyEtehp1VsDqzgawnjBe78gWRe90Th5U1Cnj+ih1mPs/JnUwdBBjvp7zHum8mjgYMDt50DinQb6NTiJZOa3w43KyvvTwDI7jkQseNO8c86jKgFqfmmYvAybXUzggO3XMss3mIfJzvr1JDXWQWGZP917dejQI30WOiuQfxg14equ/RffEM+pP2oeaduHJIHGUei5G5H8k+PJ5bVzrNiqL2htu5419zTUffsY2hflwXpXMJJeer8A8QHya8jpl17GEGWWgBfFap3kCQdU4QWVRPeqzSr+YgFxTb6jzHvIIGgc05dXXZwow1bprg2td0rWNaU3bdnTkbd3VNlXVFeUd2RpuIx5pP67aERfKKXNVH9wWKLySI+DBNqG37dHaTETsvyBP8lcTGlS2qv47PL268PTNfMwftEM0mV9T/k6ZmLxJNaA/sb8kvOs3ZJ+Pyq1xlccSYlsA1ItBS+Hi7YlbjgR9/vOfBwD8/d//PX7/938f/+bf/Bvc5z73wQc/+EEAwPvf/37c//73B7AB2m9+85uRc8ZVV12Fu9/97nt63xQAUu4cC/XTP/3TeP3rX49XvOIVeO5znwsA+Ku/+it827d9G9brNf7sz/6s2dYLAPe5z33K7MGxTid/wym44KVPrsI8hfD2NX3Xk59bnETPq0MqZEsUr3DqVsadNAImTKdZWvyc6/tEHci2/ezaIJgnAAps+B3YmVYU+dAS/tn7rfq8fPqBVx3p2u71VM6U2jyAaSWUdVx059SFyeLpnXkpz4RYhzyAekaS6wkS1ntmeUS0ErlscLX3IXco7ZLJNHVCeQJBnwFTebldKjCtHABM8VRnPfvfc2jniA/NaeQP6sxT1dx7mRGAi+JzfnDyVLlUliWDnTpOs3Epz7WTZifIlN9BipyVngxeXh6VLYkOb8/B8tqMV+dGvYNMSl5ReMDP69+axmysXSuI68kSOqwjL52xT5TWex71KbM1fCpuT4fGy+vbK9Iz173WF183QDBIw3lp+RqwlqZ7feTlEW25jWyb8eX8FaRG5Y/4WhkyWn9Cgbb3LgOXc0Vx+PUai5ewGS+B6XyIqE1y/URt1ytXie+zrUAj+0HaJnZSLR+/RtNrK3a2hfVTs3HVJ24C2Uz2dZ4ObuTuxO1gCSgdRH4b07k6PRul8rmT7cTDo2YLscpH19UzTwAJCtux8GR5VS69jkh3k6hMbP+qdBJvTm+9scLq7oAs3/2fX3wtAODcc8/F1Vdf7RfgdqCzH3QKXvjmJ89HFHrjsz8+W47v/u7vxk033YQTTjgBL3/5y/HoRz8a//2//3f87M/+LHZ3d3HnO98Z/+W//Bc8/OEPR84Zz3nOc/Ce97wHJ510Et74xjdW24a3oe47p89//vPxpje9CT/3cz+Ht73tbTj11FNxxRVXYL1e49xzz3WB6cc+9jF87nOfK0cm31Go6hS5dVaqsWSMXMaVoDP2nNOKP11XxprkWKEGfCtsKvc2G7jYKUibgcrYHhhfBh1Gw26n+O6O75masefTfTOmd0xNxEDkKb4lknhr4sXGi8Gj8UgAUq6feXF0UEOmGTAbGEc+5XCpVKfJ8Ouay1RnWBcsMyMqW5efsMpOBAtTJ9Rz/Cuwqfnx4NcZXBo5KR3/j+JqESJg6g1q6MTzBiDOp6kWb1AmnjPFbkgdpuZdwW0ZOvx7wNQr85wzxnYszHMLGXt5eTQ3GdEDLUb2nlfVxyRNJJ/rmHUFmneovEcJY38MZFpCpitPZ9zXe/3D7u1da2/yqfdebm8SyYAux9N0dq3ANIpX5WXlq4Sb2mjiQsJv/+yUa94qQwSS1Qk3GT1g2uNTeJFMKbflq4q1pO2o7tvH5b+CU89BjyYkLF5THs2T7aHoZzzawiXeMROR9sXInqg+vDKbTAw+6TgPn2+gO0//FdDHZBOicahqZ07ePHHo2fAldsat1xmbuS017/EH1xE1kxNBmIWXevB4cZ468RDIohOSSyY8b29S//twknd+0Hd913fh4x//eCtHSnj1q199WPLtgtMHPvCBOHjwIC6++OLq9N373Oc+ePOb3+ymec1rXgMAeMxjHnNYBDyaVBojYuOs5M1cK7mGG7WRZJDJYcmJ6xou6Xj2zsEB+jwMb1Eyx4IPQ+IZV/3UTB7GGVg6GMk+KZOx4WPXmcrB4HMzjVgXsmDCPMmsz7RcBv7NcTRDwu+ienpiZ4GdoMxGUOIupZ7BzyCHGrVBLe3HG+QDltVEwxhmqq3i53orkTdTGwFMkytq2l66JTPtXr8KAaYNSMKvN+Pce1ZNGM3FdUjjLwFGXV4izyhirTNqr96Ej5c/t22lXr12217gUBnPvVLkyC+ZgOjyFT4avs2KPeue+9scbQtQrZ6XjD26ElXx8PSYp3SWllc/o/bgrY4A7SqM1hM7/J4clS3OlJdX17l2zHsTUlVZ0eqnii96Ut4eKOX/Csy9sjUroSJ3Bspn2KoyxGLXZVgQZtuHvdXQbe6177gyauFGSuMfBX9NW2+U02bhHULE/NZ07eXB7d2zodF23khWtgk0x12vJmeUAy693SvNynMmnmKHtgVJOkGzLfL07FGxbYdg+7t5IiinE+ZNskUTYQpQl8hxSEh9n/ZMXXAKAE996lNx/vnn413vehc+//nP4+yzz8aTnvQk3PWud3Xjn3vuufiWb/kWPPrRjz7swh4NSnzhdEoFRnN8PGPn3a8onAFpmW0LiA1Wlvg2E7hebVYtGXSvMG75Tc4M+Ag8DxAYNWCK1eQkGJA0g8thrAdLavJmArgpbQZn0wHri79LyQbaDAa/G8JbjYtuqP54MDKDWrbB5NqJigyjaywVXXA4R9GBlmTgCQ67jupcV0uqmcPcxjV9qdPjOoYOec88/8NzADQNx/EAdjToNn1Q4ut2Jm+waoDdjLwReW0jmpWf5eXZl5m8PR4aZ85hUHDSm4CI5FjqlMzplfWp15beq6coXTNrT2nnVuotvcrHTrLOwnvtwRzxanIlbacLT85e/au+GIQCtSNpNoPbgce710fVSebnvZNvQzm5Lr1ySjrtcxEYRnAf8ezZp7LyTPw80Gq8I7C95DqSmUlXkSxN8+rQqJ/ell6WoQfUM0eshJlkKo+l/bNPNFA7sQTaxrKEUzYlL/uaQDW0UgLdJaDic10qCFRqdB3I3zzP9F/qLHq3diOQc2k8ZurRoyWTXl572kNWe6Leiqs971FUxxqnmHBn/GsA7jZI9vakNK+f441mwSkAnHbaaeXl3Tn6mZ/5mUMS6Fig0ElAvcoXUbRNaknj4ZkyW21MwXO7j2gnbWYRDyQgr1ANOtUANhqF3TF8lTdgdFeA6UAAdGeF6rMyZXXUKY+lsXxtzG6A6GoCpArabLYzYwTdTsH5/VGPNAnrMjKEc1XGDoCGG39uN+W5paGyGil40HDvvZZoUNE8oy1qHnmg1AUHkWPhyMN83dlNtGGAr18e/E2X7IwkTHVQ7UIg+ecGXp1P6A2eFjb3LstS2gaUGG0zk121s4Xpeu2liduRn+Nou/LSRm0sAiHa1vS5J1fPtveAlser4mv67bSLkr/IHYEfzVeBhNmI8t6bpOVyRvbGnrmTKLnmtwQURvbDHPscpKv40TP9zNZs33TKwDyX6H4OmJb+wbz9orhyLZE7epDlgtuGvn/ZAzeePvL4IEqWxva9ovGIDzzUV29MLuOr4NeercdKtndzuY0uLQNPmHBay3uTQQ2e5/pqkxlReX2nfVTah9ZVQ+Lj8c63pZNdh4OOdBaNnxWUa6tx0/7PCJ+dulcyH/RIrRDvU0yLwOk+TUTjaXdVM9xioGAzSj/+0dXA6jmlH7ABlRmTIS7G3A5TSsDO0B4gYMY7YZrRHDB+C3WFstJpgHVn9HayvH+aM8p7q4ZUDSCUASqjXpnNVBZykrJjFMoWYk/HmLYrc1gBJxIekckbkaatBjQnbuHnMR0j5Oy3ieiwE5t5BqYJjAjgkf2t5DTQvJcVsLkZyjnnx0vryWz3ydER51Hq1wDqMPWHnVXdXqyNh2UhnjCe8iwCOL22ENG2DkZvsmEufmRruJ1FzZTj9vLh2e9ItCWAxWsPSyZBIjkXOeYdJyWirm85tseMCaC69oMcYZ2osnBvBcir/wbsmxHy7JO0dQap+v6b6izaMhtN+Hj1ZfJnoNv/PVqSv5YvstEVyCa9Nc9Q6zWjlXfRKvC2tlFkAMbxFoGfIXyqz9sIv0jXdsntbg4MJmwmqa25NSAsTZflsy9U/5q/+SkWsM6bgjPIjSZQWXfexInlXXZRlT9tXKOqGwU69MYqFTCTLWjGsDEjLqPpq5HHaddeFdmCw9p51sRFrTs415aPt008ItfuRdcmRGrjeO2d89gLYPf8cs5+m3LenrTt2HWs01bg9LrrrsMf/dEf4eMf/zi+8IUvANh8J+fhD384Hv/4x+N+97vfERHyaFMBbXA6QCYHzGkNHBz4BNWsdc504FBG40BGDa43k8Qzy3YIkH3Xcz0At47H2KvcZnDSmHh3BKarRKumaWNc82oDdO1dVQOTK6C8W2HyF4CW6wObLC/TURrvC1DG/Pu8bEBKfgt0E1RfCewCVBkMopWWasVE6rxsyRKHIkncZqXTGcxXcg+6LzOT48QAv0e3lCKHcxtiZ4d5zoGP6loGJtZNmWTJ0+cQdkojmnQE1gemiRMPFLlAjWV0ns8NENr3S7jDJ8PXh8VfAkwd1bnkrZ5tM3ERyemFaVytf68de21kTsYe0PUToHJSDLRHtiKSo9iDLGCT7MESZ6fq65SHt+VU04U8SRRXdkzOPDtlPTDIvOd03AAop245T6bq9ZBc/49kSKjz1DGZ40bAtGmTThkbUA1fD3NAwiuTUXWaro2jTv249iXQk8rSAMu8zNZYHjbBbJPclod9ScDAovHmtJE9tfy9V2C4jsz2A/TKEdC2OaEhTz4MUj0BYDzc8gbhkd/HCZu+IrbHymgr3h54jhYtQrkW2J2FJr/IsCieFzfFY5Lnf7u7BRPCPqqkdboNrVL7Dd1jkb4mt/XecssteO5zn4u3vvWtGIYB+vWZN7/5zXj+85+PCy+8EK961atwj3vc44gIezRIDbt2dp25YcPVHPlPM2ScRsFK7wS7ih9khk2IBxFeCeFPvdihQWvq/N6Wr4wNgC2n9fKqKb1/au+kctn5gAcGp82qwICyXcfyMyDB2RgfA6tL+2Ax/pnACNefm2j65624LnG+C5sxf29102TynJwK0BNFs9g80KmxVj7Ve7ZbWts5B8L4qwOuzo0C0yXvAlo4v1/KTuyw3tzrd2/XaVxBTdMniEwfBZzyj/K2FfymDUSyLpxIacqFVq9eHlXX6dSdF5/7QY8OV5tgOVQWfua12RzEsXBPxrAPBjyVZt9nCsK9Vfi5Vz64HXNa6wu8lZbvvbzmylNsBbX7MgYBTVthe2HOvtobLbv2SY2q6ih9PtOqHurx1MtPV34aQOi0qaicLAuXxSuHN0Z6aaxMXRuh8nWod8qw3XurYV7b6PWz8EyBXI856uBHvpAHutaklJI/3TefkPFkNT1LPtY3GEA0tk8COZ2JZnKYDL1Px0Sk48eQUVZKNe9eExikIBmTXzVny/ZKS9mVtk5puIhRu6t4ZEoU+HQMUmdlGiN5IHSQ620Aqvr4+3T0aBacfvazn8WjHvUofPrTn0bOGQ9+8IPxiEc8Aqeddhpyzvj85z+Pj370o/jrv/5rvPWtb8VHPvIRXHnllTjzzDOPhvyHnXhGivpOoTknJpqRXpw/+h3Vk9NL38g9pl9h821T45HTdIJeZeRzbViGYUpnK5xsLHNG2T7MM/w2YxoBrqQ3o/UoZcgon3lJJDPLXwA4Wp2YIS2fqonyxmQI2YnLxLPnbHvEgz8D9PLMYcIrqvrYG9R4oPccEC4zp5+Tf66sVRtLvryWtnnHlORYumVGBz5Nrw59STeOLAdWwIE8Tc7wFt8CAMY0/J5J9c6woxuWLey8RNaGOUlU/Ajc92jO6TmctASYum0iaKtZnut1b6uuF87PevKUB2RjlsxCR9vDI+Ct8TiO1bG2Y+7bUdn03iuDOYMKXFjGwmO8t3GgetfNyc/rk0rVt4rJBpX+6+mG7qN3zmfr2pFFg7YBpk3b5TI7bWwbYOq9F+nRnL2ca2t2rQCDb1gP6qAXAJDrMAWllV105LD/elBTZB+QJj3rhEjDI2ismndlZ6iRl7FTgLJXHovPlFIQz4lbWEb9zKungObiJIhusjxbwN97D32JbNVCDmqbZLqOfF/Oo5fXNsCTgSqDZfbRdLw+lmnBkHVcURec5pzxpCc9Cddddx3OO+88vOpVr8LDH/5wN+7VV1+N5zznOfjoRz+KH/7hH8bHPvYxpON0nVmNwdLDcTweSuF7X6g7Sll1nZld0jwbgEU/HjDssCQGdmZ4dvJm+++a/q8ScBs2AJW3/tr7oztpBKtyEq8JYVt+I3Bq4BYJZSuxyaYG20ApDzBlC7A4KwyUvedALSfP1FWyoU3nUTTwKEAPZwSp7XnbcHRAKIOqhpksuTb6xdkQZyDMo1PYaJtQuGOA8ldiJ0H7WwbKNvTSnq3e8+ScVO8PSV7rsZGs1WH3ZA/k9uRt3onOdVudW6mP9BHl0aM5YGo24HCY5cY5mekjXhvl6ygMCFYMA76enPrM1ffYZnV3hvfedySTJ1fvnvsvt2UNZzvmiBxSD+wVO+DE4/gGmEuGnbyKnNo2MB1sw8RbP7dpP16Y9qMs/728l/Dvbemcs2O9NCHfmXJyHtvE0/bXvA+KVnZuIx7pyq7ZF09GlcXaim7N9fJv0gnDCmRibKZOm/XqTP0KoJ1ArpIE5VOyvskHGamN03w9YBzy33LC3N47HZL4NTQZTiKE/sfh9ui57Et5bwsWe4DVW0llH6SEbZflPh0G6oLTt7zlLfjEJz6BxzzmMXjXu96FE088MYx77rnn4sorr8QTnvAEvP/978db3vIW/NiP/dhhF/hIkufc9bbRMs2+GykOt2d47BAXBpi2+mjyKfhk2YdE6dmQW54WF5PhNCNoK0rmkNyWAKw3PMsBSnlznQDYJ2WK8zbuwd1JQDYAm6ZDmYp8IrjNTK3SJn05UGliOa3OoXXueBsHHwQFtA6Id+AHnw5sRjpJXqw71XkT5sThQxIMcOsgV/jPgCcN95wsHvgtk6h9RoCmF25y9+Tz+lEBbjLo8VZj+zF4ZyfaysZ67clispb6HuPuDtMnCOzQJH4v13PI5k7t897bVEW4Op3hdyjU6LmXIfYGXOdm9vcKTJeA0uh+W1mLDSJH0nvvu8t7SzkVmFpenN2cI8YO5GLnDnJ6a0cnKkv0fn0Gyvc01Ubb5JHJ26R18ue8e+Xapv7ntoNz2/PieLamaacBD+bj2ZYl4HsuvsaNdMLvk7LMXtre1uImz5m2q+1iG2Da5Kc6pvuq3eQ230g2K4Pnb/BNr40170Z69Soy6KnTwOgDBRnp4UlLwVpK9Xdms+Wd0Ww9Nv5lLKOx1j7fsyhPSss+mkcGll1fi+N4+fQmyjUPod5W34XFvN1pbjLjeKQuOL388stx4MAB/PZv/3YXmBqdeOKJuOyyy/AN3/ANeNvb3nbcgNOxT3TJm6mKeEE6WXPIUaqvK7BhgJHkWiKfyVYB1FEWBW0GQPm9VAOSGA1Y9Q4paPuVOejDBDYzUHp4BpDWE/C1T87YlmIlK6vRCpsVXRssdow1KcF7RyYD5Xupc8TpeUU1ct6jd0OjptA4FTSoka1vysAXzbvPOujRtecQGQjmlcVoa5wnP/PUdqzOTA9gMEUzsd4BLz2w0uQXDVio5VeQa/zLToBRRzaxUgArpvAlpKupS+MeKnlt1MJtEmj2HR52ULYY7KJ2pHF6bSSqa+Y/B2R6AMqTg8lWTc2eIODlkZbNk6uJlykvvnfKaNRs1Q1kAab2r/F7p7cqj9nxjuqL/9sz3RIb8nF4Vu23M7nm8TCK+peXrgoT2SPiCUBP1038BXHmwG0VNvMsep80mpiwcm+TN5z6itLbMwWmESjVraD2f+CxJNKXk7en22b3C1Cdm6H8mKfXLhnY9UBcpOdt7G7Ux1k2jVNNhFt+mR/U9o8n+4ehirZIXgb7q44+qrxJnKW2qJqoC0CujX8Gljn8eMd2x7v8Sl1wevXVV+O8887b6v3Rs88+G4985CPx8Y9//JCFu72oCwyCGRpv1cT6e68D9wYoMxrV6uGMMTAAybOGerDQ2jFgBYik6dCjO6fNu3q3rTcn/BbnhviWsq9qg15s3fjJGfuETB55FwM+CmVOmr0fqoZ7yKg+NcMDCut4RWFMkVNnoKMBqEzBAK+8vOc8CWBl4/aQnHQM2HkANgNq9dRrO5Zf9U4n8eD8IhBRHAVKoAO85+T0gLuVT5+ro648q/pOkyweby6HxWd9WpF2qK6L0zRMaXgrOk8qRNut7RnTnt47d/rnNmlcxxtTP2Hqbl/qyBHVwZJZ/LDuc13XkfOq6TTvuT5pwMwjtjvet5RVbk+WCKSqfNXpq0F73kPzadJaHmvKP9IpJI0XrmMGb+W1rbrKx62TIKzwIdtZxmJPJrpeAkY13RKApm20antku4r8vhihLJxHLw7LqfFKH4fTniSe13e6W7w7AaqXKL13voDK0iv3AOqTZNh6+XIenMx739YmKTMQevpRPtF4HAHUXn/wXn+KKMv/bU+ljVYzeYyu/Edv8EbrU5S4GG2G85zJ85Fd205xOToD7kh3+vpWRHe0Fcjjlbrg9KabbsL555+/NdOzzz4bH/vYx/Yq0+1CZth1ywTPgpV32jrAwHgx0ti2rXfBLMhw9OKxE4FaBm97YkatgwNjghNWm9/OegNS7cAk5Zcz6QfioAyygiT7KBQ82/+cUU7vZXCq+inffKMsGqDgDEaVSBnVdlug1p/l65EGR9uJOZ8UxC38vLqlQrLTpwM8bxFUEO+VR0WInGne2hM540vASURaXXP9jGWt0oG6n9P/uG2oY1V4WZgloDJG/bnq95rnzIRSxaNhuj1I9cTQMA+scl7Vo5kBnfN2n8nzyNmPVsdZngiUenl6z0N9W78ZbxP95vg37Qdw+wVPwniTOJGjvvRD8F7+DQh28p3jpbayuqbyz602euCEnxU+JC9AIDXg29NNNLHhyeGVoWuD2E7MxJ8D6GF7XcKH/nvbdjW99i3vQCMA/kyiI6+2Z52UVbm9tCxLk9dof3iCZS/A1HvXttzSJHmvg2T0fbpt7JSGRT5bk0YmiJTXADroMpDP4rl5EM9dCiyTRGWWvE3r7pBKUx16dV0+9ZaXjXWmA29s5zw9YlnuSHRHK08XnN71rnfFl7/85a2ZfvnLX8Zd7nKXPQt1rFA0IANTA9dGbkZZ+23pmEDYAXXr65wRNL6WVnl55bD7cgiSZZKnFVp7z7WckpsmY3XbmgbvNL1Tavqw7aPRFtsy5tGAkdGueK7GMgx5XAnOqFZOE6XlbZiZyuHOrJF+tC4UOO4VjC6hHoA1Yp3wdpRKljzpQMM8cKkOyxxAbcKcwTByqqJyaRDXXdNkRpmb1fIxvCe3t0psLHkW1UA3zwpXAI06IgO6XvvWIkQ0BxTUkYp2AFROkJOHpvXiATFgRaQbjrJkMqH/uJtmkbM391x01pRBeXWMsIJPrx9oP8wSVoFx6cNKcwBVy66fZVFgynlou1KbEmXG5YnaHSeJJsgKr6A/LALmM7qZA8ZADK5Ztkg/vb4cTZD0dNazqxoHJI+1216ZtX2wncleAi9vp/2zTrxDsFTnKmMETC1eMUNSFxEY0nzVnqpw1cSUZ99z21c4L20j9gkdzX/u8yQMQIHWBHljr7fav2RStGmLcj8MHaDH/DicxtTGF02TvKXfJXp1qyN3YyNpXK7kmnGcezvX9unYoC44/YZv+AZ8+MMfxu7uLg4cWPRJVNx222348Ic/jG/4hm84LAIebeo1+F4aD6Ayv0TxzLgumiHCZJAZNBkfr1PqXnqPGmM3/slp2t7C5VulzRbfVQJOGHvxKtVb38pKXW7lsDxWGZt3U+3wpIRyCFLzvVQFnHmSPaMeSPjwJP5peb2tHVx/XHceHco7guwARc9G0ZBQvycabdPZRh5vANO8WYY5BypynsqgpgOJ8FWq3hmpHmwSLlk9qrYcSgfxQLpk4Q5alpYnaeZAapV2/NOAw+zrUIuYyp8ZR9Wrxy3baxi9MkDtY9ZfL09H9Y1j6zmcka5YnG10kx05WMaSxhOYeczI1UwQyXPvuhdWnomOsjxTYDrbZ/N83RmDPF22ACXIj5L7+VOZtrWxS8BbOJHTsclzvD1+S3hEdab85tpMKEunbRjfQZ932vGcDF7/7aWLnveAqd7PjSeePsMt33JT3j3P8z6gN+HHr9NE2/Wj7bQ5j19RsDGvZFT9C/u7x09fUzOKVstdW5Tr8c/brhzZ9jKmkvBqO5FbgLqEeAy2JOxrK/XqszO8HRe0FK8cL9Tdmv64xz0Ot9xyC3791399McNf//Vfxy233IIf+IEfOGThjgZ5RtwG2UzPt3XyGn503aPiVCyUGWg7YeQsh+81Ufn5AB3+ARtweuIOcLcTgXvcGbj7nYCvOwDc6QBwws7m8COWj420fepjnceTUoeJtz4fgrTD0D4bWM6hTr8e2kGCVw+8cNNT9OtRaTfyGySf9dD+SlujutJy9uThvCIxuS2rbJauavNOmkaPWfgjkE11LzLx5AHPti5xDkpaoJmEULmbsoEGOP6lehWdeXFZOf0chU6byMN5Nbrr/OCkXyKT5zw3P6Apu5HWVeQU7GXbkRZBZfDaoVcW5bmwyhrnuOJBeplzkL10c8484Pd3rz44T/08i8rZtH+QLlHLpsJz/1Zb0KzcBGXybAbb3iLzwl/FR8vjxGH+A2p9VbJxOmkHvJ1ZdRyWVXTPYaozV0doSetCI2k+VfvAlMZk1zbg/TzbEOlaZfd8DaBuO8rbErh2qJNfpDNoGskv58mPiNqwEo837IMsTc/lYd1w+2SZS5ocA1NLa/7RgPpX9Ett2Wt/Oh7bmLuzClZGtVxzSuD2Z//3oLuIvMWKvdDScf72Ivadlv6OZeouhz7nOc/Bb/zGb+CXf/mXcdJJJ+Fnf/Znu8xe8YpX4Jd/+Zdxl7vcBc95znMOq6BHksppsIC7zp8xzWRFs1ANz/F5s322MKz5Gc/KqQYWO+lzZLx16yo/N9HslVA1erZSemC1+VmYGZYDaVrd4sFK+ZXtqnkqm53SW82WjAl3QLOJA5Aokhmd6t2FPBlQBS5lhcd+NEOaJf42xAOlhhs/Hnwq+WWmkOPxgTyu4ffCJJC3oOvAZnmxHrQ8nmMRUbTVzXPytzX2CQtXT0lGVz+St+q1ArzJKXeeni0lTWuX7KD15OOVydm8Fui150SzmEuLqP3IjSPP9jrYR32tF59lqJ4FTliVjg3DSEuAZbS1UPPntqoOahS/SkfxvNNxOX7E1yW1SZI/05KTbVVWz8ZYHI9V1a/3WP+WVleWIzm9tHtstoVfb5yI+qHRkONnVX1JPTXgj+J77WmbMrIN6/XNuboLxxcpyzbjUUTRmGR52UGNzH+JLbTJdgaXK9TvTHuAkuuj1AvZ1LKqKDS3PTgibgNh38vBwkeeViqtTy5919wdv1jPeSzrmGbJeMfjdcB6Nj1/2YDtDPtD+3R0qQtOTznlFLzhDW/ARRddhJ//+Z/Hm970JvzET/wEvv3bvx2nnXYaAODGG2/EVVddhd/5nd/Bpz71KQDA61//epxyyilHXvrDSPytqdV0WTldemAOkzo5UZzoPQZLl7lzjs+rE4Cp1yQK64Fc7mEKUD0Hih2RAp5QO8lr4zEC1gQAO8AJw3S6r67IWYHKu60D8ILvei0A4DevusTfhmu6x4aXyc/xEpXNyr6ScAV43r3+j97v88J58NQJBuarg6IHPHXWcAk47RnRnrPATkz5LJDIuNRZ8bbxRuTNgnsyH45BwQPr1XP4ulWgkh1le1vDu3JQfF4NK1vY0QJWr50iuG/ydOJ5DnCS+zJhsSCPIkvq17vbNkW+CPzsyQFl27OHtIXIIQOc+klOmhmZ+P1Ab1IyAr9qP9TRZWDq9akGmOo9tW3VHdcNn2m3xEHulaOZ0HLie6LutV49YDrnWLNMHkBkvSzhUaXt2GcjdyVpQTqgBQ5qW7WteTZIqTcGcrm8eDyR3Gw/dwqh44Snw96Ei353OupDCkjV7pnPYw8TyWK2svCWtuDZiEq/HeOYx7zmToBe8p5mxZp04fql459wZ54piXWQ28nhyi/aQ6ftjSs6kbwX3uYL2/fNi7zbs7vdKPIPj2eafZH0wgsvxGq1wjOf+Ux88pOfxDXXXOPGyznjbne7G17/+tfjwgsvPOyCHklqZoGplldmuMaOvHTlwp2BH28i0BPRkMd3Mhd2bDupjQ1sJkPiGRs1mlZWS2ZA1APBtqKa0marxyoB2N0AVKXeluMCyAUkDZhAqTrRdvASAzhd9dXVRzaiLigV3TU0M1CqgxgZ65ImTzI1xpzKBKon5rvE5jeOnZSBgb0HHL3B3z31We+dsCjukaBodrwHULMolZ0Zdki4AnpmwXOsDChUzpjUL6fXdlsl62Q+B5qLTNFEzAz/kN9hIO1Ph5OW9pltBnx3lR1tWLN1la75uaXxwKs6+p791ry9fsBNmYW0+GqrmrHSyb/JpmMTPBAeTYbpBJw3QdDL15PXs9+WF/f7Jo6j46U0l06Doy3WXtzZfLU8MlZZfnNlWjJpovGaz8N58vVkhF9fc1tAh4W6Mj+vjIGpTWsT+2wcqjFhYT5MUfxqmHEiKeD1bH0PmGq8aIFjCakv4OZLOlu64suyKss5YDonfvTqzj4dG7TolKOnPOUpOP/88/HKV74Sf/iHf4hrrrkGw/hBwNVqhW/+5m/GE5/4RDznOc857lZMPaoMquPEGvEjbwXFO1jHA61dxxYo3wjVeNbZ5zqhNxM0B3jNKETGLqM1DgUcJuDAziZO9U1VirsCsOLPyaQJAKscGf4A7QHTMm7QMz3gQIFouRbnX/9XupHrcBCQOJ6DZ5F4kGXZiuF3HAL+v3Qw8Rxia0uRs+KRNxh5TkWUf1UGcWay82yONG8vvU24eB6B17cVxDBPa+tLZggix6qK4zgMnsyVnA5gdfkG8nlOJFNvy1TEaykl0t3iraYY5enYLi++qUDLwn3GnMBefyo8ZvL3nPfqvzjUpU8GPNRBj0Bh1bcl3NrrNrrmPJm8VS83baAHvta+GupAeFcO7lIb4eh0SXKTaxvdbaOXSI7eimk4ljh5mf3o6VxBaY+1TpBFkyYqR8UjOeGBDVxaVo9yczHm3wbVn2Bx2q79bMLYbAHH9/hGtj0aizTjTPm4PMXGh6uolF/Pzh0K9YrTtIEt+G5r97chr2+bSo8Lcnzn452WHcEL4F73uhcuvfRSXHrppdjd3cWXvvQlAMDJJ5+8+CTfY5LEIHtgrBjR8sciy2qLpCmzbFN0ly/nq86SUfSuaFOcTA7rTGTtfItWhcc//E2wnKeObYNpwua9VDP0mo85Sq/880vKiitA242lTDwwrMf/q4TyiRkPpPKPqfpES3Dt/Wf5WbaiFyF9po6j8tXT72z1e5C40gSLTLMgxZFB5eWwuVVR5e3F8RzNaODeKzCN8ojKWMBeJMf4hycsvDxt0miV6i1hXb7OvRFvl0oSX7ezlzT6PwBUrlxBuPExsKYrBL0Jq57TvXiSQWypl2xmLqCKx/8BsrVRGnpe7AqNAZ597U3ERHG0L+qhR036Dm/mZ3GX6Nv0yPaI7bpHSz6D4fYveT676yLPb2XcC/Um0riew8lEGo+MlrZHtUs9e93bgs1y9Xjx60qqf+al743OkerO5OlNWLi22Avv8Ih4zVLHRnnbTW0MUD0B9XZ271WvMqHn9N2mPy8c35Sf8uWbcMyasVGeP6r6Smjtv8e/8ke8SYgOH2DaZu2NN3P2exuanWA/TPkcDTpe5FxKe0KVBw4cwKmnnnq4ZbldiAeZ7kCBeKusly4CqJwmcvTcLYdk+MuKpxnG8T+n4xnAOdnYCQN8gDyIoRnsYKLR0bdvmmXivyO858DvqhOPt9esKMy2E8+BVBOdnXxeTc0Sz/tvuuEZUpPJKAIiFqYOpJaPyZwGLgMPFqxXHQgaXtI+WJa51YA5R4PL7Dob2Q9z/6PVnaenyrHPtV4y/DBXeNRp9HGSMNWVfQ94ZwX3277V5FYgU6m3TAeMSTlYKHdCgvJomoA08AJIOvXOoLQxkDP685551724XjzPuemVYduZZG8niMcnWgUp92jvuf1Uk215mtDz3v2r/ufY+a/sitgco8GpiKq/wSdrX3NgkeWIZPDqq0yEoNbB0kNWvCjeODI3cWVxXLtusgV1H9k3Tr8UTLvbUEWfkSMdyRaV2bO/EbFt98a55tMkCygsY1DeORl7GfTqwHYC6HfmWZ5qpXdUxnq87H5+DtNhRosPDpu5L3LQcx4HVJyIX2g3gn5qY5H2LX2HvkonF3udVKp4HQZaMoHCYXe0lcljnY7IkucHPvABvPjFL8YHP/jBI8H+iJO73QSTgar8tvGmC2xza7yKfSND19uKkTE5v1X+Iou+O1it7lr5KK4CVFCchj8FcJ7OmF3Ky/8ZqNpg3wNGnB8wvZfK3ze1E34L7+yDVKC+15WoBqjSSMzGqXL+pZ1EAzeHMc2BwvI8ipfH78wG5aVolQzsICvYg6SfK4PFCZ20QPSQj+TFMrIcqpqu4wWRveO0al7RNkh2wrkfWXv3JjGAWveVOMSH+wbH5z5azdjLjEAzmGaJk9q4KqeVsXpA9sfTh/Jr+Bxm8iZCtuYhztzcRNrcKb1VXyDbqI5kOc1T2kLIN7eObc/uVP27MeIUj9LqSrBnDzSuyuOVdc72WZ+xHSIKmHq8PWIwrbbM48O8vDbFemS7E9mXucmLHs29P+nZ2mJnpP5Ke+n0zTAf4ZnkmeYdfTNzFiXNPPLKu5hm2qHyW8Gf0CgHOLH9G/uU7Z6xXU+lT9N9Ssvesdy2fpoymS9g1yBZZ/LRQyajPDmfbhzUTcBe5cpod4gdCvUAI5s9lieMzzogP/p4oeNJ1iV0WMHplVdeiRe/+MW48sorDyfbo07RYFK9MD+GVQATrRH3Ggx3cgV+c/GR6+0k2okYmA6pXT1lWTW/nrxzRoDJoiowhYRnMuIKlCveVH4+FGlF+gDqI9uRJ7nLrGhBnrXjoqupJT2k3DRIeqs2PWdRfcNoS1ukf49HHWlcxQOgo4uCoZzrAUIHOs85Y/Kc1a5DFQ1kM/GLUxjk1QVEct/bghnVCYdpH8to68V4rbRtBLpuxnrJ33sHhkGsfqYqAhGVM4VYb+rnMB8WdC/bepm/Ti6oQxeR1+d6q6deXKbeagfQ9jcPNEXPM/z2W55THFA8LU/Rj6TnfDnPNrP6v9yG5coYTyftxJ0bE5RfZL9mAb/qdaadsPPstfEKuDtU+hXHofqK7Ly3KtbYVrXFM0XRSF7e+qUBXl1XGT2amyT18CWXWfNqIkvFz5XZsyeL9BRE9Nqikq6amhxz28qteEUfTltQP+RQaOlER5aLXjKWfc4mKn9vPGN9R1twe/6Ol5dG6/mpzNsrt47lbp6OndtmkmmfDp1mwelXv/pVvPKVr8S73vUu3HjjjTjttNPwQz/0Q/h3/+7f4c53vjMA4JprrsELXvACXHHFFcg544QTTsC//bf/9ogLfzSo2b6ACaBW8RakjUgHegOWbPQSx3N6qzoQPB5k1A6zGoaB8rDZQx1TOLuE5WVj+SoedGMrour8J0xOgpWbBwN738/i8Yoqv/fB31nlFSfja/ryQGqlf5ZbnRDU8SPnp2f88/hnbhso09oGvlQ7T1X9OzJ5DnBkexuj7LQ9z3CbbotMDoBSPnzdA6Ycxl3CK4Mzv9Bce++e6KDEEyNeea3+ygoQ2nbj6cpuIycxBQWrnIlc5+M5lNoJI/DgMVCwqrrx2lCkd81/6Zi/jXPg8l7oELGuygSW/RnD1RnlfK0fejtDPMd7dgeFpKWibKVDk8vj5bX5nKfvS3uOdcWD+vn/197bR1taVHfCv+feBmK7DMKSr3SD0DQi0HyIDTIzCibaoEzSJDovaTQBhl7iR3wddcYvjBqMCjpjIqOsCSgqvjEyOqKtiNAzZjC4IrRA1AE0tgjLpmX4RhOZAfqeev+4Z9fZtWvvqnrOPbf79u39W+vce87zVO3a9fnsX+2qeqwxS7ZzzUCVpEfqztOkCTb1vd2WnkKH7EYn7rE2Lds4l9uyXFO7rU5AiXQtOVp6GVksyNFgjaEx7ZDXkfXsiEWqlH9JPoVradvZieeKDjViqo7loUJMlfi1OHNFNrGhjS1ku/Uoc3q+tJxpoqUr9ZPjAieJg2EZ8TozV6kgnzCI+ho6qWkb9VuCHAcXOsgGXkwoktOnnnoKv/M7v4ObbroJYVhD//iP/4gbb7wR119/PTZu3IiPf/zj+A//4T9g27ZtAIB169bhAx/4AFasWDH/2k8QkdAskBrOBvwufXBkR5pL42L4h4wLPggk/CqMSNl0l16r6tflgxEZcZxMJ4QvjIx3Km9OTJPlXiwcN745IQksHDegeNz4OiCkaVM+uOGp6RF1R5q2ZqDzuLwOJfnl5Uhx48Ml5Pdr4A9GaWAEQyfLQM1kK2nJ360PfS09qRPXl8spGSz8IZTMnDaUn3UEfguBl4RbGoSxnTQYC9w4kG1JPixlO028qEDSByk+79sq0Rc/VA+pkCvrzZRnhJvLg99qs0l7QVpedENOwGX68LGVXaJ4A9gTPdYeUq6TmSfR1mWb1vpKpjsHGzu1NqwauMg9tTMVnYPyX4NaJkp9yfxaEzokU30XOE9T1iuM30o/lXnSSEhLO1bHNpGmlp6WTul9qpZcM5xIW9M5sSugLOMtoKW9y7AtsmtLoFv1oPF5UAoE2zHB5ZCtkZVvQPbmhw5AqM0GMPTNaw/R+XPMaB9A/rxr2Z5Ez4xsa8Lwz3zZ3XMllq02xELAQuEuk0KRnP6X//Jf8N3vfhe77bYbzjnnHBx77LH45S9/iWuuuQbf+ta38JrXvAZXXHEFAODkk0/GX/7lX+J5z3vedlF80oh7uZBWsvYwSI4bRzoIxJl2JqPmLYvGniBIM+z7lLzPDKcgvsfkmGKDLl2SrKlkDRTarDTpzB9cqsxh+nwpYkwHwO7Ts//Jy8CXm9KgFw+iYgOFnCmivYEd+05kmB4A/EXbajmJ0Vx6d3laPG9aGLlMkcRb5S6NsZZxhj9QLFKdpGMYjxrRKEEzYFohDc0sbehEmv8e92GRlPPwWu20PnkPSNsFn+jIloZD9G3YuvN65BMgcs9rJJasX1Hacb+rSJN+c4Kq1X+SxjAc/631+VKZSZSIVUvc+F3ROQsvwsny4NCWbWnjsaYTGci8HKyDjeiaOQnEwtfKx5pk4uBjIY9jhdeWDtdQkmmNRTyffDJGPmutcUCDOe7JMTgbvNJgVr8g/VoOhIppiWQCZg8OtMbeknytj5bu83QnAV7PCTEddywWZSuvT0Jvbbyv6TJxNIz9TWIa4mZbuxri0i05Kcqh2T59wffkthYDeU1pLLaSnnT9ZfbvTkRQFxOK5PS//bf/hq7rcP311+PFL35xvH7BBRfgj//4j3HFFVeg6zq84x3vwIc+9KH51nXeoBFKiGtTtQ4ujEUrnDY7lXgjhEEUH9jdiKBSMG2PJlOFWZSpDLkPTRpg/J45IDDRRLqILGnLN7nh0bE8R1nD31NIiV22xJg9bGg/FH1IIVq+m5BhjO5FkpgoMPufdKG0eD5aCaAsJ/6Dy5dxQho0g9Sl1G4t+a0EtSRHfuc6WeFrA7yYF8h0kUawfKhSfTZ5MNC23DLTsTAJwzEzYOMG79tG2prXJ4j71r48MkQAvb0nCgujheJn5R5Y3+7y31y21oasZVfSWKJrJRIj66NUPzXEdFlji/kzdNY8qJGUhnxCLUlH+W3l3WrfzXka/taWqwbkurSQoFofz8YQ6Pni961rSfygp83DtZBReVl2B+0e10/TV/utbcPgaZG+M4N8EjYrT3pGSEWZQD6eWHktNaDSWKTlj8LKtquNAS2yLLn8GmEgyrJIjli/LvUlmV6fpbgt3tM4zrLxQ3tPvVDZhDVGx/TkPdTLXYszLtSJqeH/KRFu3HQ4QU1sw7kormBn9j7uxKqrKJLTO++8EyeccEJCTAkXXHABPv/5z+Oggw7CBz/4wfnSb7uCz65LtOxTUuwYAKlXQ/YlTkoTuy/kDy5+wFEA4utl+D7KIjkOKUGVsMhuC/mR3qRieBYmITAYldNMGC01Th5KzJiUy7DlAJYQfIVYJDOMiVJCVy6nkD9pzPDfJF4u8bTiqjDIUR9CVjKCiwaPZmQyXSyDSear1DbM2X9uoDCyZKVh6VwjQ1G/wkOvpH9ysu6wLw0wPFEZutEul3rHk0sbjMbAvmge1CADdmnYIHRJoLT5xPBiOmmGk0YAir9rBjFXrTbRwSaatPREcRSNfd53ed/hJKNkdElSHlAOz/ULQTectT7MD+5JZCh6yD2sWnlqkwlAurKIe/G1/mXlNxnzC8/bxADn+jeMdxZ43dNvTTdevoTaUt6AWQI6Q7oadS8Po7N0ywZYlMefKKMwDvPfmoe/1g+1vcCqHg11pKUn61j222Ld1/Jh5KEvaPmvdbqvpRsnqC0rT6xxokRM1aSV8FYflO2xdA4CjYMtmMJwWXMhvzK8RGYnz2Ec0KCtGJxwEo4eKJLTxx57DCtXrlTv0fXVq1ej25mnG5A+A/g7qQgZOSnMtluwTkLjafM0VI/mMHBCtoQATS96YFnXVaNVIalEFq20+AO/+hAdDry8LLthvOkO6KZmH+L0HsmpTsxGYhRHep5ILuksTzYmZTmJpQdaNFhlPmW5KWHkfc2IpDxqD7XaQBj14FY18nqw4tLDhOun6S7Ex+uZgaNUtGX0qTqxOBS+5WHH65HKV/7P0gq6QaYZ5tpDibcP7rXm6ZFnhK5PdcP+Ip60SXkLI6HolVdkyKVcEvLQJL5CwJId5aVRRm1XCct10eT1hTaxINPQwsrxSGtXVIc1I0+WN+8/RDIsEid1l2MChE5aOI0MaeWa7KlETj61OFYblHEyYoncOOTlK4lp9DAr6XcdW8nDwsgJqAC9n6poMID5uCN1krDeK8tX9wSW99gmjLFogNyeSFRXnqcWLDkSGgHUDmKSdd0hz0MMUxqnFNl9wmnEtCbLIqal/tSC0rOV24qyDVs6EkGl8y9E123SR+rG+wlBPsNknVEbaDkEKQjBlFdq6zLtUhnwlTfxmSIU0IjppGFOilm/W8efHYidnIZlKJLTwWCA3XffXb232267AQCe8YxnTF6rHYBIUgKyjev8Bcr8d4u8prTpjxgo6LpGUGPn7mYVmxr2aE64LL2497GWBxo844NQ6BTljbJgkluZ5xiW6UyD7fQUsEToyAcya4llbVl18kUZ1aUhpA38EGFIfyl+EIDBII0jDXxpAFSNMMYUTJKjZJE8PTwtXr8cllGgGhPUbwoyeFuT16VBIvNilYVVTi2GUckY10APcgorJ0uobGZYfQfMHiKzDcBu07PtWasXnrasQ1UXHkaOF2FEcPlSYHnImIRGiPnyYNmvTeO/cczT2pIaLuhhaYImBKW+RT+kupPpa79DyCcQNcM8IZGGLB43iO/WknL+u3X/ZykvMm1gtF9QlSXqVe2Hncj/sA5k/w3snvVew/isLfTxYZKxbui8B23cUNOA3ZdayUqpDUQjfZgYr99IWg25GrlsMRkyD08Pw7lW98l3IbfFa6qNv33ar3rIkTZoKvdlP+M6zcVbWiOowOggpLowZO9FnQsSchfy9s4niTgR5ZNGJENO4Gn6xcONmOwke2xMlissknfUD4VQGIuQtkzANK2kQa5XEsaIU4u3kLDA1euNib7ndLFANkY56GhHXPPObA5k3EiURhD9YQON5hWJs3Us3GBIUNEh3ePGBoDAZMbXj7Aw9J+WCZsP9MBO9WUy40Al0tfkZHvjkIfLSKsip0Z+SbfsZOPhvcDLBukgT781Y9NaBsfTjkYb0zUEoKO6FO1EGtpE1NWMDdOXdl3HvmSGpkgniGtC/Oi7GNilUTjFdLHKS37naZUOJCoRR4uw0J5lilciBVoYks3tIYob62hqVIeyfKNMjNrXtuEhKEm/Uh5+iQ1W6IMAm+hQ5EDJK93T9rrJuNJQkftYLTugxRsJMONGuacZPH2htWstjGaA8euaXtzYM2Ub7Q+w23uVMIr0Ez24HFutZmIqy0OGC9DzpulZ2ttaWoGUrVwZNpqpDglB5v1TU9jivlq+JLKTRYPIt9JWZT8CehAXBZM0iLW2qz235D3t9TQ8TDZRC708M33Eb22/dPG3uDUfxBRoq4Nepzf3GOOyZ3xhjE28qI0JhDA8iTvYcpNn4TA87wMyHH3nYtQVSg3EVHteWmFryMqrEIbb57VTnB3zgyo5/c53voPzzjuv9/2u6+JJvjsDaNBVH4oKah66SNCM8NrJnlIHTvD4QyAejgTE0St0SPagagS1Dzhx4w8kTnSpdw+GnluaVYtGMxkQHVM1CMLI0xRyuVGSeZWVa815M39gpKhyL9o/YRRMPgj5dzlYx//Dcor/kRt8U2BEVspRrnfxT/4QSAzGgnGpTp4UwvDfU7IwFPAHFjeSsrISacqHpmZI04MsvmNUPDRr+6ti+Sj6RB1Z3NjWlYduks6wT9Ipobxv8DwmcelPJ9qHaF/WJAkvJ1mGhGK/MYwUTd9O3OPGUZNRZ7QZqynVREpDuu/+xMAyIQ0wrU3w77JPWTpYhjx9t5aSVnUv3Gsx0LUxQeoh+0cr0UnSqeSLG6u0DJaPufGL7KeFNt6zKNV+ZYFWKQTofZsmgvuSpKZVCH0zpsSttZsknDJ+WuO1mqaWhqZHY75kmrLdWisQWu2hPnZT1makQvJea9oN9WS1dT7+SJsrOhWYfPnslDrz+9Te5fPSciYAo76tHZhUQolIjhO3JEs6Z2hCbC573ecbZHcvJlTJ6U9/+lP89Kc/7X1/ZyKn0qCTS0clah0qzuqKmazmZb7MMNVIGBFUoP56GCA1donYcJKrEWf+ypfkvaTsviSoXTd6VUvGRJDmySKoMf9GPvp0QNK/ZGQnMkuWt6JXyYBruV/KC3/oqg8ecT1ZMsyMuWhM0gOKfg/jWQOunDypDczWCbSJjko8jUBZRk7NEJMPWkkONGLK0+L1ps0MEwbDpRP8gZA95Lt8XElOih5ClknmCTUmHDDMlzZJoZWBJPE8vyQithvWb2U/tTyq2liljXkW8Sd9JTSDkrfpxCgiPZDrqkGODzVvAOlQbYeA2fak3BaCINvmfIO3F00XQs0LXPLUSpm8nfBDxDipk2Ufn69aGvLZU0m/BtPzw9tgh/QMCDEeyO1BVjqtUNtpoe2OCy671G5Lz22J0r7SPsS0pEdpaXytzseZzJe6tZDKFmTLdq0xiJ65wzaoTWaWJgO53ZrcY88OWc7as5rsY+6UoC8UrmZDlwhubVVOH5RIqXSqTPcV7pgTiuT0fe973/bSY4ciDiSFDkHQTmgz5SrGGpT4moHal4RFPsgfjixNSUy5IRqEEOm55fdo8IoENjDiygcedi95WIu8SSIMNiBIHdRBk8njxqtJSjU5ohz7GDTJYK3c1+5Zy7upHDW9SCavTkAx0DgxDblha3lzNL1LD7MaOLnVyLW29Jbft4hqJFcy3jBf0mCxDv5IroW0fjT5Wf5on3dg5SrlGO015iX+SdMu6SaR1JcQEAKSvcYdRq9fimHouohH1+U9nmbyHmZGerWlxi2kjhNLoJxvum+FqcZlYw2NU7y9WERI9sViGwlp2JhuT10TnTXQ+KjI4sZg5oWs1Il4lCTXq8Q/GHnl7Vk+azDSSyKrD6ZflkzHJlOgBUj1ya5V0s2ebYF5T9lzkIcLLF9zWeYr9eZlKb9qEwYl8LzlCerPoZaJGonivlLlkmU3Wc+IXktsDWh2QnNcptSYj08A9fmVxP7pRvYDpU/jf2milafFy1Hrl/I6tSu+za1IKgt5mW+UlhXH34Xr47aF7YmdQcc+cHI6RBxQFBIHsIGvY69zMQbNieqk6EVpW+lyTwcneZqHlQ6YSNKlAYeTT6QkkhMXCkf/5btE5YNc5iV5/QV7sFuGUWtx88GbHwhQfFgpTMry/lgPaCm+ZMhJopqQciFTPbgGo8FzShiEWpzSQQyawaA9pDhqbd/yullpS/0lOZOem4z8socmCtcTmRj1j9oDlNd7NhFUiJtMCBFYYla/lgZhNECM+utEeGmgDLqRfG78BMoPB++vIh2+hJ8Mc/7KnEwMK/eqQavUndkHeRtlqmqnMoPdm+5YmXYjWfQKK26Q8FUisTyZDppOst5q/U0a1skEkwgfwxbKUZtYikvqujRcSTdtvLWWKfO8a0uTNXVLBiM9SyxYfbXlBFItbWs857rxZ5kMxwkqgMSDxXWVy3znZD8U8iCzYY2jHEWCyuS2ED4tSEZMrXSUNIrttNJWLMQ6GSPufKKkj5wsscJqY1QpjWTFldFvOyUsMFrtoBE87ZnbB3wMmpTXVMqJ9rIhZMETv24n0LEnqst6t2zZgkcffRT77bcf9ttvv2LY+++/H/fffz/23ntvLF++fGJKbi9oD+LizDja1szLAZAbVOrSVv5Q4+RAIahElrknoBMDdSRlPJOKwZflL4zi08xpoIyIPNBlbT8sfaeHNHlWjWzHvJHhmE0acPFhJEsa/rK8rWXElhIx2ZDqmh0QgQrxMh6qnfieHbylPJzlQM2XWHOjMxqJWtqa4aLprxhWakZkNFHGFlEIYWTsS5EambEMLznpMM5MOU/bulYqs5IRwMNoXntJ3uLSeEU29WErLV6mGdHH7NgQ978mrH50ArFUrsVLliz5EuGbV5oImTINCqORwmTVhCKzNtZwghrHszA6IbY0CTJO/mTeaqfzatemGupGQhIjrpvsP3xVCx+r6J6mX4D9igmKR8Sfy5WoEUT+WybCJ0o0ueqKGiPN2lhCZI76JN9/yu/XCGofWGVrjY/FZ4Hym0+UyDGuFl+2E46EmBbK1aoLM3ylHIsrBAqNUNpf4xj/xWenEd7SJSvrLh+z+f7SmUGlLLvkX56mSF86bHjb53bwpEjSHB7juaw5CFtspG9nQZGc/vM//zOe//zn46mnnsKtt95aFfbrX/8ap5xyCpYuXYqf/vSneNrTnjYxRbc3zIdYGJ5uNoQ8PbdIblkYSVAJyRJXiq8YRnJ5RaZr6ckvZFF8SfS4fnRCLzeOO/pwwzBgduY4jGRwAyJZdoI0DbmHjedVJecY6SrLn4fn8WrGHPcWxzQ4UWBlVjoMxIIZjghmIV40PpiAxIPNwrfudSvqKyrDIrCarlpzTB5wdM0IpxlakqCQrID0Q2FaDHdJmCluFs66FkS6LKAkTHIChZMi/sDnXkktbVlGMj/cWCsZixp4ecj88brjZM0i3Py3lM8R61EpS63+SWbJ4JDETatnDr78OUlj+GXAwkmUiHN16SyTbRFyCx1G47JcvqpNKsUld4wYWeMDgY/LyTJlrRzEvdIEA68GrU5a9mVaelAa2bXWTlBJ3xKTERGFmfQlK1navH0ZbbEmX5v4k7+TswlCvg3DSkO7ri7jLcSdC5Hoixrx0Mbrqkwg2kDx95j6ac9Dng55zGRdPTXIw2ey2fOHh62NrTH9YbpxSS/s8mmVyXXj6TTFQZPJq8KKtzPx0p1J1xYUHX+f//zn8dBDD+Hd7343VqxYURW2YsUKvOc978F9992HL3zhCxNTcnsieh0w8j7Ih6D8nZ1oV5Atf8trpYMCrNkzHt56OPD4Us4A6QBVMgZ5+XB5lA6V20DECUKO/M71jPcK+vNw8Z7Il8xvyZjhOgzC7Oz/DM9PSO9R25D3ZJsJIhzlayCuJWWqyM7yqaQ5Mxh9gkiPt2eph6YvrwP1mqJP1l6EDEDIGX7nbVgjppK4cFmy7DTUDHAZ1iJdWVjkfcdKl4eVbZT+yzzKsFm4AAwG6SfrA0wGJ7y9jDLknlgyRLRZe02W1veI5Fr54/rLT1/ItlNcEiv1wah/Uf+he1J2i25JHy6EIdmt0Ko0Tnp0tvGi9V0Jdf+s/BTyo6U5V6gi2GTnQDQW2V57p2foLI3y7GAV6Ol23ezkQuuJpZyAyMwnYwYfr0P6vJLjL/XtZOm/SKuFmGr9SZvwiYKk7kLvSWOudU/QnpVNRK7hfi2Mmo6o22i3VMYi/szS2kUr5HOg9AwcF5ZNqoY1rpfqv7qabojH3nlZW0DHRFAcF7/+9a9jjz32wOtf//pmga973euwxx574Ktf/epcddtukLP8Gdkw4pnGsPLhcbSHOh8gSgS1hMygMQwOraNrpECGobjZgxCp7sl1QB3AtbgUX5Z9UOQmpAq67hBpWJMOpYeMJKuSlEq5mu6yjjXDn5bhzIi0Ml1FOjMDnSC3fizINGU7TtpCIZ9q3TO59FtNn92T7Uhrh1wvKUeSK36Pg+8z7GPMlIixqrcSJgkPpe5Dmm+aBBoIeR3YXmR2rUZMpW5aHcQ0Ch5IKctqO/J30m+0MrHKGHk5NXnN2UeOJ0k46mv0GYwmrpK0WRmoBJZ0w+jD0zD1VHTi+hMJa8hyLpf3Q6YHL7/a5Cbdk/nh7ajVe2a2TaaDHPei3O3gOrD6QDTSh7+neMdDSlClml0DQeVkkepce1bQ9W0D4KmZ4TuWxdiRTbQi/ci0KN/W85H6woyQq/X7LF+A2bdr8fu29+2JLv4R18TvjJSyC7yvyedb0gYGeRvQIMc6a/IayNtEDdrzXD6vLLSmMQ4sUsr1KQ0bpPvOQEwpr30+CxnFZb0/+MEPcMIJJ+DpT396s8ClS5fixBNPxPe///256rbdQMtOtcGADD2+NmOcSg1gS+xkRzUeWpPEIIz2JmpLeONeUXaNLyeW8VvT4usKA7+m/FeXdwXlNF8qPyab72EKLF36HTCq52R/nERI/kWwpNQHBo/D2w7YNWuQTAweIbNmrPGlllIPS3f1ZuFS6cGS6cV0Iv1IplzGXppI4LrK71zGVJfrxx/O2oNdpkXgXiaL7FpIlgUrbaiDqDOk3SO7z2Soso22Jz02mu5afWbLT1nfT2bFRZ/j8rRtChzae41lW4gkEaP6oUO85PjD42tI6pAX0FCGJGDZ2M/GCavPa3nh6ck4NSMsM0KVPpKkx+6X6prXnUUkLRJcC8PltUwARV3ZeN66t0+2ESBvA7ydtUxStKDPGEiI/U/piPKStgdVjiMJyWT9ReoXkF+j65x8lOrbAg+vTTiY8pQbpf4E9LOHJLmfJNnRVGzRrQOS5b1941PaWZ9nmFKuqX0Ueln3HZu0LRzWGMP/t5zPUgoj7VUNcrtXK5LHmpFHx/ZHkZw++OCDeNGLXtRb6LJly7Bp06axldrekAP7gG3YksSIOodswJNYLsS9Nn2gnbirhgv6wR7Jns4xQWWU7VOVgwojpB3SsuXkn5eJSlBZevE6kA9gkrVZFjvPR+VayVBNrgvjohvqK1XKlkyyAHKw5uqHoXFKL4nmuqnhlby1PHlrzYLnme8fpLgdU4QbViXDVRr30ijSvst+2Zdg8jgyXdlHOSiPiWEpdJuSlc6+So+KZuDX9i5GWeK3rHtNDfOBz+sMol9CaRdKGcl+rEFbeSB1JAI0xRq0NMxLM+Sx6w+/SOIq65m+J/uajfaq6cLlBYwItkyjBi6HZrsDlRGrmySOuBDbZRiNJ5zoyDiW15frw9OyiKmGZKIMaZvXCKpKdll7KaVTHPfGwKTkECqPolGaQawoQJmUyuvAaJUF3QtaJKEULz/ZPky9GwpJa3PjgtqfPABrEq/rAUblr16X4za7n0w6KhWdtH32PXk2iLrV2vtMIZN9ylcTo42rpCvPH53BMmWkSRMhgy4/OImHb13ebkE+/zOSydotvyXtYpnvX71rJ/CaYk7m+4JEkZzutttuePLJJ3sLffLJJ7FkSfUg4AWDxACiE86AeOotN641gso3hHN5pfS0hmRdLzW6jFwyIV1BqBI8Hu6UeUpC3tFbYMmmAT8g/a0ZJJS/jKBilO/EE8rqSMrKMlzTv/Dglw9sGU4atB1GA2CVnAqZGqEg2bFskKZH8aiMeX6SAdpqiGBFZZANki+NnaRYWBuSugchj8uX4QjaLLH2Ozk0RYSreaNjPCG75tHR9CFoRJWuTQPqhIAsR1mvsk3y1QOWjpp6qqE0zP/U1EjPTgmXpCUGQKm/9AjHvITRh5aqAaNDjah/0Ls6E7Gi7cl652klY4S8Z9Qb9wCU2iEPY7XJ6uSCKBsrXkmMRiITYiEMzRLh1sLMhVB0yA3SVlI6bnoWSvL7kO0Sprp0UqIETvLpdwBiv+f1wNueNWllTtIJuXQtTpAp7bzqfa61a4jJggnU7QREzD0h6muK4ReYDWIRVB7FGpfHKSsZpa+cKYyWZVv26HR8LxXis4LGluRgxkLaZFu0TiSQPdpqispJXV4OLfasJLsLHTuTri0oTlbsv//++PGPf9xb6I9//OPqa2cWCgJm92XwfRLJsiHD4JAzNLV20RnfNRmJMdjYifpAGj3Zf9hjsjqIKp0fSGd7+X0rfCndki4akQjiE8Ox8NUPRHsI+gx2sncjiHTA9vawT7avVMmP1IPrw/WQ+0ilrgPxnctN9p+I9GSd8RlzmUdOLBI9WJisfirlJuu0Rkxl2CTPEGnZUVX0HfhLBp3mHdTqOalz5XuMH0b/A/K81dp51IHpQ2nQZJ2Un7VDlo7cN8rbKG9ziY5MvlWGmky17Rjtp9SvS5D57UVM2f1iGqweLHmJrqKutXFVEh4eTtNHtimrr/TZj0bPtdKzrLUvVp9zRtnXui4v5/na+2al24pS+Vl7WZt04GNHQPI84N+rykm5/BPsvibHuSadme7bu75UPfsoL6KZ93i/R75CqDZu9bUJCTQBWLJpA9jBi+waH3OyPfXD//wafw70PhSsR3jte5RF/T7o9bszeE3nG5dccglWrVqFo446Ch/72Mfi9Y9//ON47nOfi6OOOgpvf/vb4/WLLroIK1euxOGHH47rr79+7HSL7s2TTjoJf/M3f4M77rgDRx11VJPA22+/HXfeeSde/epXj63U9oa230jepyP7EdKHxDhLEcylgTTzVHkIaUheaUP/6Z/8XYD0nib3AnvVCvPW9nkoxrhMrzipKAy06J0Lqfe0JFsuD473MJJllYU0zrTrdE+7xsNz8pfIEUYlRBiZP1q+Zy5zw6hstEE7BMULp9yT++sIalzpiVUM2Y5HFm1SfUhg1Ka0ftiHmPL48j/dl9+tCaOWh3zWFupREmj7uS0ZrfpodWnKVcqGe8xl/USPgBgTeVxJtrguvKyjQVBov8n3Lr+v9e1EfqXt8J9SNwqvLaOUca1xYcaIK5G0WyMNuZxXa9dkIFrpaZNAFHTcPZoyLX6Og7YFhtpRy8SuhkzPkN6z3gFrTYoAk/OYmjqWwlbu8zKTKy/kfS3ZuKeVe5K08hHXuy7dMhSQv8u1JkPeK0HpwmrccYlpaUwv6VYb46ttuEdbkP1S28teEq/ZIkC5vLgjlGBtk6DVhAGjyWgEqB5k/jPacci9q1CulfafqjZ0YfJLtZukXiyM3P62M2A+9L399tvxyU9+Eps2bcLuu++Ol73sZfjd3/1dbNmyBRs2bMAPfvAD7LHHHnjggQcAAHfeeSeuuuoq3HHHHfjFL36Bl770pfjJT36C6emWjYcpiuT0rLPOwuc//3m87nWvw7e+9S3svvvuRWFPPfUUXve616HrOpx11lm9ldkR0GYGtVlKaYTxMK2NovQglsS0OturdFC591Qb6JNOiZQYxv1MnUJ0WQfmL2YP4j6XBaSGN09YLjuSxi1dH4f8yuWFmcEvDMAS8UvkKtez9BU5BEmutf2SpkGjXKcBND7MjKjaM6MTXzjpsJLtjLDS0I1ylTaUyRdGpbymPZzVfAhdSF5Q4mhpB6T9s2bsTRrJxA+7LvuJlnfZTkv12MdgphN/43jHxz9eMGJCKDPklH7ICazm+ed6Z8RH5EmTacVN9BL6JcLZdU4utTjaOCGJTsuMvwyTGKdizJLtOulHilyCanBSPNH/tLKLJMeQL8NKvQl9z1XgkON4drPTy0wLWpu4sK6VrvdFTYfk8cnKdJr1p4Sows5zlrZIk2RNdaPny9QUa2uN7VjKnytkv9Da+LjLGkP8U0+7FqZjFyRZa5JTKN++pDp5FipyeHn1IfohzO4z5W0iJjgc/8P73OO4GPCjH/0IL3jBC7B06VIAwCmnnIKrr74at9xyC975zndijz32AADsu+++AIANGzZg3bp12GOPPXDIIYdg5cqV2LRpE/7Fv/gXvdMuOv5OP/10nHzyyfj7v/97vPjFL8YPf/hDM+wPfvADnHLKKfjud7+LF77whTj99NN7K7OjkLwbKkB9aBHk5dIBKfwD5EYjHXCheUyzwY7pxB8omocoKGGtEax1Nj8Z6AKqM6cctWVwsryZXWHeL+rM65H/Hn6s5YgyfR4+QNFrjCevtjSQG6FyaW6mM0uXLw+Wy4ZLS4jVJeyF+NnyYFEeWV1q15QyBFLCIustzsqKckrKhtc7jD4i4xh1x9O2iF+Q+lRkWnE1yLqhMtfCDEQYed2S3wdymfYAbKnfIH+NES9/yrPUU+1TPN8yLywcB29TElyuep1f09pLyK/zsqDlbFpfTV7HEZhMIVv9CL1i/dN3WY4iHYj4Zv7Ef8ofD9+K1vAl3qDVx5zAKnmu4rLnaClJK1APJUr5j0ukuzkQMZYf2fe2sXdkU1/kaTbJV75b7Z3SKMnQ9C8RKd4PrftZWkaC2rijpZXJEwJqchJ54ntLv9RsRCuOfEZn98RHg3zdUIz/Z5chvO8yJ6Y7CJxPtH5qWLVqFW688UY8/PDDePzxx3Httddiy5Yt+MlPfoIbb7wRL3jBC3DKKafge9/7HgBg69atOPDAA2P85cuXY+vWrWPlp3pq0Ze+9CX8y3/5L3HTTTfhec97Ho4++miccMIJkSk/8MAD+N73vof/9b/+F0IIWLFiBb74xS+OpcyOhrWUIDvJi8gkXUP54QswL+scZowp/cw7QdcC8lfCUPrDcPzEy8w7rMhJvIoiHr+m3ZPLasH0kunJ6V7rcBfufQxCXlNZyfuxcNLrWpwi+RBh+IOlBG6oE2KRsjokuZQfSxdJqrhhwWWA6dfixYhlxRVkaVGZmXUx/FNr/yS2VnaxyShtgOsj80DQ2n6C2v0eSHSR/UKUI6AvSdS8Ia1ks6UtanpQumTo0cFNyf0w+5kansjF24BGjPhqE95Web1bfS+weLIPaPVJYbSVEUH8l32Bl7c0pjutMkTa6nc7ShY+1plhTFpjgLacN4Y1vKaltjGHZp+hj0cvidfpeZ2zYIYi4dGuKW17rmlnbaUis3XbAcmOe9UDIyBgE06ij20DEAajFR1mUqwsNDJfKltrGxF/fsk8yHwBs/ZKrbxayqoWJBkXFB0teaWxiu63NqE+6bbCTH9YN9w2nsLohF4ACH/mZHQhYBxq8eCDD2L16tXx9/nnn4/zzz8//j7iiCPwjne8A6eeeiqe/vSn47jjjsP09DS2bduGRx55BDfddBO+973v4cwzz8TPfvazCeRihCo53WeffXDLLbfgT/7kT3DVVVfhhz/8IX74wx+iYz0shICpqSmsW7cOn/jEJ7DXXntNVMntBe21HfG78iDgy2jls18ziGqGubansmjwB0a+tAGe3y/IqaUzDqROtG9X3kuMWSHAIsZUThY5ScQMhZoP8uF1qUMLEdXS0e5bsvhDTsbvWH6jqoyYWupl5cDyl5AEJrOvR42We8p8SMhJB274WPFa9pbycqM2wIl8C5KJESaPl43mDWyZXKoa+4X600iEtueoNL6Ulo9baVptlud3JqR1z8cWev0WXxpdmsXnxvcgjA6lSwzkoSxOWDWZkSwKI1rO7lvjIC8fq6z4cmOtTWrjCzfUZVxrciRgREpjXOR11ExKRNpcT0tfiqfdI0O1Ke1GHWtdSurFyyderMiuqaKdBF2DHBt4OrHNFvqAdW2uKI4tGLWpUvwwDBTfqteN/sdxVhk7rTRLaH0VXkl2NhnekK42NrRAPmfkGKz1HWvskfelPO13X8h23es5OfyTbSFz7+iiAPG7EtavX4/169cDAC644AIsX74cP/7xj/GKV7wCXdfhxBNPxNTUFB566CEsW7YMW7ZsiXHvvfdeLFu2bCzdmt73sueee+Kv//qv8f73vx/XXHMNbr31Vjz44IMxc89//vPxr//1v8ahhx46lhI7GvwdWdzw6oYX+DWJZGYeqWHGXecyqnVgg4YsWGFQrsmg1+PwfaBW9GwPK0sr20takQWk5UPyZpWCOgBacSyCChEO0I34LAGIh4OSniZbC19CYigKeWodd3k4Locb4by9Sl3Vh1HFaot7LpU6sdot34uc6CyYbKx2hRyOg7kucaO0A/tOr1ToS0xb8pB5RUUb1Sap6L4cYyyjp3lsCXl7KmWT9zt+LW5NUIxEuYQopjn8np1azcaUAHtlQZIGkBV+EP/lddKdZJTyXEOJiFOaLWGSiQikdVMzUjWvqWVI0zUt/5qu/F2pLWgxqPt225YyKKUTkPY1Gi/NycO+1ws6lNrgfCGZ8DAS1lYqaB5K6te075ziAm0TlS26lvZDA/XJg75towPMV7xY4bP4Mroy/mW2hWIDaOg7aZyoUXiuA/37HgA89V4npAsVNJk7H3jggQew77774uc//zmuvvpq3HTTTZiamsL//J//E7/927+Nn/zkJ3jyySfxrGc9C2vXrsWrXvUqvPWtb8UvfvELbN68GSeeeOJY6fZ6GemKFSvwpje9aayEFiq6LjcEO/aF3+vkfdRn/Urtpbackg9kUugk22FCsENKTKRnUnINTRbAZhCVwRpsgJQEVYsby4GRUU5Qo2IFfUx9UZ9xLXnvOGoeM83IjAa0jMuM8yY5w/Lhnj9m46eiWbjArsmEeBpWnfN4VB+ascOzpS6zLJS7WUa5yln8WF70HcbstfK7lZhKQ5+nL2XLa7w9a6SOQy4n7USf6Qt1UkTqBtFPMUsmu46d8DgsWKr7wUCUMcsfGb5ESik+90xy3WTZ8vY1F+NNA69zWWfjeAtb2m1ifLMM09e5EFOCtUKg1ubpd/P+vYb64G3K0tVKqzQpWGv+chzkY2CRoFbkyjCDkF/ri/i8q+jAJ7Ose3L8k/dawd8GEOMzOVa9tfYby46aq9cQaMun9pysTfzT+JuMFSLB0vhaglnnc4grVwby5eRWnA7uJd3V8cpXvhIPP/wwdtttN1x66aV45jOfifPOOw/nnXceVq1ahd133x1XXnkluq7DUUcdhTPPPBNHHnkklixZgksvvXSsk3qBnuR0sUKbEUt+d/rMhCRyxTTY/T4nFWoPYEkYpU7ZabtgJA8wvaclo4Hfy8ghSys+qJQyyZb2UjT+I7vZRlBbn2Ealx3nAdjHmyKNzBZjM5LN4W9rgjdoPzrjfiGcDKgZroSMRLHrsly0Zeo8Dr+uLV/lv2W5cZJbKk5JdGrGXh9IvbkcTVxiFLNrgN33+CoLiq8R2iZ9Dd040aV7g6GealsnfZj+PBxdn+6Y7KHe8vTbZPJA1KV2INQkofVReY8TPz75VpJFvyUh4PezvHBdgKzNZ94sjK5rEz0ybU0v/lu7PkliSug7jxIC86rz6z3lWgS1jx48bV5eNVLK007ad3vyRYJpTaAmdcjKsET0JaidyXE/0T2M91o9Lj8RV2h7dF8kXwhc16G1GWjjZi9deqJ1YktD72XqTkJ3aowxP92EG2+8Mbu2++6746//+q/V8O9+97vx7ne/e87pLghyet555+Gaa67Bvvvui9tvvx0A8Mgjj+AP//APcc899+Dggw/GF7/4Rey1114IIeDf/bt/h2uvvRZLly7FZz/7WRx//PEAgCuvvBIf+MAHAAB/+qd/inPOOacpfcvAk8vXNIJakqkFLRHTAleYM2oEmt/npFsejNQ7XSj5IvnyXsgfgHLJLyfmnKBqUJdGGnqOY/S2GDbSyNSMQHNCIIwmESzDMtGDlQugeyg7IasT1yzIekrSB0zSNYlytcqNT1aUZEmjdhw0e1GV+pGwlppbHvwOsyQvnigeA43pMS3oxb0xIcye3kmIRBNpG+NL/fjkDx2cMcXkWcY1XQvIJyloGGhaVm1kTo41dE0jjSTHIn30Xasv2U61vmKR0hifydAIMmEm/ZnpIMXXPGZa/rMwGgkqlLkGbWJGkyXHvKy/8DCKbC1dc/yXaRtpqnGVPh/TkhPERnuyEIzvPG0rvHZdTbOgxxT0OtLahjZ5Ms3GCy2OJf/BtztRcuy82O6cZoyJ6oWOcSe7Jopzzz0X1113XXLt4osvxkte8hJs3rwZL3nJS3DxxRcDAL75zW9i8+bN2Lx5My6//HK8/vWvBzBb8RdeeCFuvvlmbNq0CRdeeCEeffTRatpk+NFnin1KD9EWuS1hJHErGdJ9DexJGeY8felBsF4hoYWVupFMFMImhp5yrQRaLli7V/XYKZ/kVRjGJ3vlA0s3kcfTg5DNwpdeE6KVC8mXYZL/4hpPT8ptyavcO8g/ps5KeWQf3g6UcpVtpC8sw93SxZRjXO+Q9/coX5Q7vdohea3DMDxvt3I1Bn36Iiv7kJe31NWUQfllenCvEr2Khb+apXRCryS1ms78WtSTpSf7D2+v8rdMQ/tu6ZC0R6Uty1cjxUjsq5TBX01TSp/yNhD6DBQdNci8aqeijktMrbjmEl6w/Is2IL3zWjzrmtqGDP1kP+dtSeoTmC5kT5D90GmKDtHi2SpOvDXE7xOe992SYTiOEVyTSXjgbZc5MXXs9NiRnGaxYEF4Tk8++WTcc889ybUNGzbghhtuAACcc845ePGLX4wPf/jD2LBhA84++2x0XYeTTjoJjz32GO677z7ccMMNWLNmDfbee28AwJo1a3DdddfhrLPOqqbPB1vueZL3MLyXLVdF6l1sGbznOsnRGp/y0vpA4Q/avmFa4o4LKneZhsyfVncl7x0/EIQb45YXWzXQYOc7M4QVQ0i2P8pnGAqmyfcsr+xaIrPL9dfKjJcpgpCH9FVJEOUqjd3MCCOjrbIcgOsmDUJ+TatCKp+sPEUYq/7ksmDeTkoHlk2P2ciTcgt53rTJCjlJJqo5aeMWMc3yLOraIocaCW6F5unkRAoYlbl1snCyp4s1lKw9iLaotSHSiZYq03VJxGgc115ab0GtRyU/qlIUX8TlemmkWcurTCqZLEDaxlvaSjXfrNx5mWbh2BftGaktz+flQDK0spTe0GQ8MnTiMq13bdJ9rXylHnI8IJ1KY4hF1unZox3UI58DvVCKMxTMk+y62b5gveplnNONuUyCE1HHYsSO4DSLzHG6MMiphvvvvx8HHHAAAGD//ffH/fffD8B+yWufl79efvnluPzyywEAT/7q/ybvzcwMavSvdE4qOLhBQA/01ueM5cWdtCtfEycfUIEpnxmgdItnkJWFPO0zMZ4CI0uGLjGOkGvN6tfKR3o9kjRkmoW0NGUz755CPpKyUsRI41lOnkh9glJ4Vrume7wdctEDqWgtPd5GYoBcRlZ+Ctkt1QWHPG206+yTbq1rmuFbO9yq1nFl25NxZLsA0r2YANJ93QxUXzNDQR2GhrChh2y7kgRwr1s8AZvFGcsbG/+k1+jDy7dU1sleWNGfgHRSxGozmdewG/WrUlssyeTghJvCxd9ZZ1f0Y3Iof+r7So2xyrom73NYpwL3OfhJy0MxDpJHQi/ZWRtRCJVMh+vVWsYEercntYe4eiGk8mn7jtx60efZnmSr6x/fmrzQ8ij7T9aP2L0B+z+XrT0cXQc8/DYnpI5dD/PJaRYjFiw55ei6Dt0EWRh/0ewzV+zD0kEyOAO6B0DC2jcRMHp4AbmhaT18arPbib6WDKbbXKAZ2TLZ5GAkQCXmXA4djGSRxyDkcCOB6oMbCoAuRxI5a0+ffGBb+pSMhUQ3xYjkpEC2r0QfzdDWIjCZlr7N14Xe/DpPtmZQ8jqy9NUwEBaxFkzNJ/QyGMA2WmOYHpaj9BDFw8QMOZJ0AjmJ0jxDMawoaG3cIA8gn9Dhfb1UXvIaIU7Sid8yfOtIrBVxLW6JYHGPazKRpZQhyVHJVkjD8HFoxii3kr4mkVIaoHZLjheTJqaE0qmuQJu3uGUslNAIqTX2JxNlVIdWYgWCSmMARwsxpeWnA4zGRBqz40ROGE2CcftAEtpRwmn6zRAZy/JY6MsA87wDuPvNTggdjoWCSXOaWZkTFbfDsWDJ6X777Yf77rsPBxxwAO677z7su+++AGC+5HXZsmXRZU7XX/ziF/dKU/Nq7agKt4hp1+V6lYgg0JYHMh76GJ+tCEw496zJ2W1ubPN40ghPp3tHYTO9BUkuEhzo9a8ZkUkSgjRopFKxU9LfMs8FSPlkOJG+WjitPmUcK93MW17RLbYhkR8ralYellFspJeVQUA8oEfW67iHM8n66wxZWt0QyHAteUSsZYDWq65iGpQ/Je35GL6Svsv6KP9tZdLKu0WaEy8PkRUWaArIMsk9gK39SU5iyb6rTiLAzo+8EeR/QTp43kpjSAsJVZLP7zO5coKnNuE1RjcaxWPjuDb29JJdq1vx+/o/doLmcDh2DOaT09ScBzsjFsSBSBrWrl2LK6+8EsDsiVVnnHFGvP65z30OIQTcdNNN2HPPPXHAAQfgtNNOw8aNG/Hoo4/i0UcfxcaNG3Haaac1pRVnRNm1cYhpS/C4j6sQXr5blX5yYtop9zhajZjWOKVDOQB931ppplgepFQyWol8SDISf4e0DrkhJ/UK7KMdWJTJU2QnH2mEsjgAMr15GC2edmCSWibadeMzUD7WPR5P5mcwyMucrsePkYeB+PA0knwhD5sdIGXkn5fBIAzzxGRa5VgqYy2ZUvqkgwxXa+cEfrARP+CI9/euG/V3Pk4l/UO0W1PXmkJWPIh8CplWX7HaPZeZ1PcwzAz7JO0KyNrFoJJWrU/Ldme2V+X3QAmo9ank3vC3eWKsEm8uKLbdShpcF+0QKU1e0jZYGtrBa1Z6pRu15+51f3QZrvsjJ6YOh2PHYXtymsWABeE5Peuss3DDDTfgoYcewvLly3HhhRfine98J84880xcccUVePazn40vfvGLAIDTTz8d1157LVauXImlS5fiM5/5DABg7733xnve8x6ccMIJAID3vve9cSNxDfLgj77EtPUVB7VwmidRekinuvRaTa5GaFt0q8kNAZlnMurO7lE4FORRWjEoNzz4EqlO3O/S+KSA3LcadRCypXFtzeAXDTDmPrGITCsSQxSpZ6ET4Xjy8ppMU1uyK2VF+V3hniI7k0d9KaQkyqxTkQYZvdl1EVYuueMw9/8JHWWZaWll+WJtK17TwivXMlnDP7J+LTl8fOJfNIKapaf01Zqu3DNobTXgfTYwPcDLi/UvXh9ywkbTKSOgTDeSLV+pAhbXyievTxknI50NfVi2M0nIpCyZb/V0XCPtcfQrHczTOkSp/ULckM8mKw61eTnO8fta37WgebGdkDocjh2BHcFpFtuy3i6ESc3H7px45op98KIPvCL+1pbNxnssDA8/LY1GGa/L4053+cNUEhC+p4UIWOvhJLR3hucncZN36cFEksRyOVJvrqssr5JMSax5+BJ5zg6oKhjaVv1p5E4aQxyJoVnpIVUSz9PEaL9gMhkC3RiTkxNcd8or15+TiVJbsZaPyiitA5409ilPkogGGPUz/D0YjMgIzx/EtVJeqBzlMtlW76UGSa7l9YQcsv9Anl/Lcybl8DBa3+Rx6Dp/1YwVRqZdIqcUzjrJmHt2rfQsslHz7GrElP7L/X48jkqIFLJMesu6s+LG3yK/MV98PDHkaGRcLkGuEdNW7yagtwWpR0Dl1Fql3/QhtX0g233Lacf085tORh0Ox3bA6tWrccstt+xoNSKec/Q++PhXX1EPKPDuP7x1QeWDY0F4TnckVu797OxaKzEdB9xLqMnnvxPSJggxyUriGLpp+zyB0cFEUTcWKDNkw8iwk15Ofl2exhv17EbyuZ7JYUqGoasRACtskg+Rdy5PI6gaavc75PUgdZFpR8N+GB+KjjEu5YPdT8gabCOu7x5LTmjpe9+pq+gFNEgWD8eCqRMFsd0IQhOgkBKWB4jvVh1ahFNCkhmVNGiEUNOz0p64Pr3LvnRPdv5S2v2SzXSIZVQgfdLrnax+aNSP93OevkyHX1e9qYU6qa04AMoH09TaikVMe8nTVSzui97RU9ItBLuFmF7rhNThcDjm9NxeiNjlySkwMqjGXZ4rCVsLrGVy2dI9eV0hqRrIS1rTR5LMGgYApmVcJR2N6AYWoS9BpfgZMbcILfsi4wTju5aeJJcaTILM/ysGMM93YoCinVi2Gpka2eH1Fj2XCrkbB0S8tTYl85rck8a5Qm45QdRIaUmeVQat7b+lSCSZ1mTUvFQc1T4c8vbWKrsm35KnLe/Nvht1JD2D5CGdKpA20lNO7FmEslZPSVkYEwjJNfZdbWsVEkz3Wic2am1I6sRRe7emReDlb3XMKJTtJAlvjZg6KXU4HI4RFtuyXienClQCCtuI4+8B60NQJbQltdzAb218kZgaBmRHP4Snk5PH4h41UT6SdEavG0tH+z8OQW3RJfmNsnFHSwYJ2fJMnkcBqm+eNU0/np48BCS+8kchh6rOIddJI5mqt1mTl31R7inyLZmc5PITao0ksnJrIcS117gkv5XrmXEuvtTyqN3Tli9z8DJo9Z7yeGr6DfFb4rX0s7HfdToEP3wMUPpc0PddatDaU2uZtpLD5D7qZKk0OaDlWSPfNa9p7Xr1BGnoee2MwavUnq1w40CbPLTgpNThcDgWP5ycYrS8lXtAJXkaXkq8NtwgHXRzf1E1kbztNgGiEFRNp+KSR+TElhPUUrxxCKrlue5bbpyYakZu1BFpmMTjzXSxiKlFvDghovJqMc4sj2+AsRS0QDqT8tI8nLydK/KsPNOEyrieV5kHWd8tBxy13NcmMmTAmkwrjWzioDJJYIHXlWzn1FXmSg5Yd5sX1Oqr6mmW9aTIaymC1nJS+4cRUJJSa/wgtL7ipkW/KLNBVhzv2DXejqZQOFiK/gc9T5perZMq2ooXmZ9rX+2E1OFwOEpYZI5TJ6eEcQw0SVIH3WjJK2GhudqbDS/kZSKX1VokMSOo7Dq/TwQVyD1ufQlqn/s8XEBu7GlhpMGU6Elhha5avEw+mLEe0t81ZMEUUqcRskRfw60pCTsRzpI8HpcO42rxJlr3tTAy3VYb3zKqLf1LHmdpXJeISfxeKF8L8hAiIqjykCy5L9cCr2ttDmNSQ1VtsovSo9/jEDaNMFlpleKX+ut0qUDE2KF57OW1Uj6tFRHWSoA+KI0p2aFsRnotxFSOdfKwLDNM0O87KXU4HI5dE05OBaoEDHWyRGHkaaPjHHJS05XkcgwwSw4skkZGVQegG37hhyORMW0RvLgUNaSERfOgcl07RX4sjoKuJDu5buRd3pdoqYPoQTeIKSFZEg3hVUXqDVXzxu6FYJ+02oqENNFKAOM+IIzRmmdPEHFLJl99wEm3DB/nH5R0W+o0I8+NkxFafMnPebloxUHtQhLDUtXxcYPClVYXqEs0kfcDrg+HrPeOXxsWfktTM+YuiiitmJAnKEcdG8n1pMga76uy/9J1Xk/a5IJG1kqkVIYtXWuFdhq1dnI0142eD60TpxYx5WqXDmQrLcOfy3jncDgcjhHfWExwcjqEenLt8EuJoCbfyWgV4cdpM30aWsk4D/FPXa5FSpuNf+QEdYDUAJTsRCOs3Cspya+ZNiv7lnAl7wSMaxq0V5Zo73Eskv0wIqcaGZbGnWXgc1JAxNQigEBaXiUPYVKnMoxGFkKDQU56acROMEeNIGke0Nr+Wi4+iDSSeKIctfjxfwMxlfHGOXSKE1nRhTLIamolmBb51dKqLdvnoPbKvXR9CJnZfg0ZNY+pJKZAXg+letGIqTWOtBJTlfxpfatBR00GJ6aJPD5WGcTTIqZZ+vJ3gZQ2DeoOh8PhaMJiG0qdnDJoxplJ2Iww/DRbKbNmkLUQK43gNL+CwQpXskp7yK+JIoJT8rCW5EKRnXmtK3mRS2hrabaQB+udqFob0dKQxLTkeZHp1a6XXgdTIp0AMrLW4nEGjH4k4hIxVUUKEmMZ+Aq/LC5LpN8WyQkyEnT9pIfNukf3SyRinNlOXi/RW9YnHuy2bzUHGb5GTOVtPsFCXtwe/HSkh9FmzAkQ8bv02hf9Qn6LtymNuBHmREwrarW8h5nrS/2IwtIZCZFAGrKs1Q9VYsqvyUqwwrB7fvCRw+Fw7LpwcqpgXKORx0/X887PrEZJR21pby1f0ntMGKc8OBHVTgSWBHU2QxiR/JAeUgXoto6mX83DIo02VX+0nZzL5ZXCAEjIBE8/sPQ0ctqx/60nyQKjciRoHthqBhrSScIqcTTCJpccJ+1LVrRFYmUUoz40YmrJG+fdsH3ulzy+JWhksFQvfZbAWq+1KsUpocRF+HU58VCCRuRKpK7U7gmDhsSD9T0gGz8scaXxqERuOfgw2UpMpW7So0oENbvHwmjiB1ahWJhUGIfD4XDk6HxZ76JGRqJQWQarhKGH/jRsL4TEfLcpS4+EAwwDkZFfa+ilPUs8PTK+awRVfudyWgkqQTuIp0RYNIzzSpfkvhFHho9G+pCU0ndCsne0YZJDGtCc0FpLF8d5TUgNFinjhFlbhgwM653lO6u74X9Jbmv1UfOWN5162tOILgUfp9hbxxRLj5rXt9YWSvEhdCsRUwvWmMrjaX1Pyx+0a6LvZeNIQU+t3wLjE2xLrrymxSmmI9IqtVnp3dXyb3p0FR2pTFvHKS6C4nzTvaYOh8OxS8PJKZBYKfKkSUmYwK5bRInuVwme4akoReNyp8Q9bmjIe330KqFPfLl0NzF+w4iEWN8lodUIqlYHFjFVl941kFAOflASvy9JYbFtGLqQrgNxcWooyDKkZd6T66yQrMOH5uNQkpIhrnmy+AE0FE4jpglK5JbLwqhcJAEb53AeWX/qqdUtUNq2BbnntGr8W4RCwTiTE7U4kizKiQi5zBTKdz7JpBFTnlbTMlN2i5Oj0gICq38TtKW7Wj9T9dbInTEuzCfUNEX7LrVpSTSrY19FjsPhcDj6YZE5Tp2cWpAzunJ5bGasNHi1qmmKNPjrVqTxapHP2j2ZznzBMqDVJaXiO89ziaAmdWCkZxGT6ntYC+SqGgajvXVcqY791wwx8jhMobw/jO9jpDKxlnFapF1e67NcOOqrTa4E3cjmBqsUXyLIRRIkyl8SUr6HmxMY7RArrr+RTHI/yU+BZFj9rJWUWtAIOJetXW/BnMcw9r10SJgkplp8Xr8lkmh5Rok4lryj2m8uO4jfXC5dz1ZqyPZg9AmpwzjEVBJ4dVVGRUaWpkKkzbCGjn0JaMtKJYfD4XDoWGxjp5NTgmLh9jmRcr4hDVnaUzpO3KY4KBuqAwwJE8qypfc0xg/MWyaYS0AaR3pciycTK+lLYsJ1yHQVsiyjqURe+dLcKbBy7FJyxoom/i4Z7h3y9qgd1CUnObSKzDx/BpkswohT9BJ1uRFNpFyi5tW1PLBcroU+xLTo4RLpSUIwJeLyyZWO/zfClVAiANYEiDWeWRM78/mqD2tCRJZt7eTc9Ev+s0Q+i3vV2TWN4MUxwNBPW2HRBzJKaa9plfw2pE8ySkH7tIdSUEuf63xJr8PhcOzycHKqQCMt3IixThrNwjWml3CzoWXJPSuSX9TIpkZcLbKp2NhJOqWlh/J9p5psnie+9FLuPeThBmG0lFUSVE5mW5abcY8Nh0Y2S4aktUzS8hDKa5S/rM1gtN90EIBtg5w48nLpBKnT9E/0MliK1uasPMl8dco1Gc7yNE0FYCaIuguplxOo120HnTBYr+GJ+rUQHSW81n/4BA2PPxBhZCK0Xzu2ZaNjZv3NIOH8vnzdjMRCmGvrwN6pPFR0BrkX0Bpj43cgewdpkP8rJNTqv1b7teJp94L4LpFMTBl6jLvsfBx0TKlS36YfQV5rxDhE3eFwOBw6rAn+nRlOTjlKHsDhn/iuPmZZTMqdbtmpFkre00gcSTYjmvQ728MZkLyXtJceIU+XH1KTsWBWdtIzWiKogCCzQnzUiZFSbiQmy6ZFvNLSQQua8RygkCLoyy0HLM2ZoBDYYd5nSP9ge7+i15Zdo+XAklAmpKtABDVSbxVJi5eJSAiCIOEYtdXkECgrLZQHZGov0ttkkQEpu3Sdl7H1Cg4L9LopIqly0mYUcJSgNr70fZ0QiWxFJH6GrBZoS6e7bniKeLzA2oYIqxIzeU/0WavvttR3jZA2yVLaWI2AWr9rxLSWTq1tWtfl5Gu2fHpMcmnqMfy/8Y/da+pwOBwOJ6cjtC6jYwajuby0L8ucA/rsJ9IIKmB4PSkPIk6rHkRYs2WMjKTy35HUsjQ1ggqIfagYXdPywIkp5HcZXgmjoTWcFY8gvbpTAIJCFGkigcpUSzYI+SXvuiSwkShx3RozQfFq73SU6WvXOHFNCIxAzJdRFnziqFRXterL2ibKxLsFCQHqRn2Ei+DebDkJsz32lUhiOpetDRZB5SIHGP5mdWZ5HDWCJNs+kE/yGM7prO76TjbIsBphbF1SC1SWMBsy+5LScaCNleOOg1Kee1IdDodjbvA9p4sRSqVqywG5EWm1A04kyLMjSeEkUFumSqh5UKM81PWLZVAgPsX4pCtGxiMnGtw7Oj0MGCcEFIJa0zUxgFr0G9Og1DyigG7gl/Qmo32KhSvVC78nwzTtWWSTE5J0tRqMM23BmmRyD+4MuybBCZ30CNMPalulZZWaTjyO3Pur5bU4QVUJH0JKUJn6WR+RE0o12Rx8SXy1j1fuJ+mJeHIlAkF7ZY28b00eyEPMtAkJi5gmMrtc32ySRsYpoGU5cG0cMYm3kZZGfPnvSZDSODdoraaYI5G0yuS/n+1eU4fD4RgXi4ybOjmVSF4jg9RLV0ORSCiksHbgUh8CWPKCWroAIyM4GvtDg21ayJF5a/HmyD15FFYSiZEiozAzYZag0jJjWvrIl35meRIi6XrrDL9l/JF6MmzpPaHWO0U1PXgRTHfAtpDWJxF07q3X0ufkQJZTydso67KPgd7yGhWSKcl8FlRpw9YkTJDChBjuceQGMV8Kr3qHC/Ukr9f6moxuBdf6iWRSGUk1EmwhqKV2Y0Gmm02GGOFaUCOmGalslCHvUxnSb+vgsZJMa8Kjuc+0BcvkSlLHx6qWVQstbZYvpy9NNmhys+sNYRwOh8Ph0ODkdEyM6z3sE1caFDKeZnBYhsCgS5duzkX/PrAOhIkQpImWZHJSFpf9DT2r3EC0DCjLu6DBMvxKrzcpeUBbPSCaXtaSV9qbx1+DQnv0AiMeneKJ68AMfGoHQfcEWkugLfB2ZHopgyhjFj4gJTSybgHd20jISJ2QxfWS+0S5TIIk57VJmF7GuWisiZdWyJ7WZLJ2oIL1HQ3ahIl8v2wNXDTFVUkc2uRGLyeL10EnpVk7GgMtJDamx67JyZ0+HtHadaDfSbyt5NyaPJrEuF/KY62M5fu4+77qxuFwOBwpfFnvLgRpJNUe7B0UYwBlr6vmPZVeVv671QjRwmgE1VpuzGfOpce0byeQOse9hcOE4r5SkTB5TSNxZR+gbABLUlqyl7hXr+VVCSWvaCkN0iNbcszIUwiGt2QYZ9tg1rvKvT6cZJJ3VSN2HatQKseSp0XeKk0ElO5x8kFh+X1rXTQnq1aTS9qSwFTov9SxRM7nIoPIFc8I5UtbKi895524rtYN77T83gTJCG9XteKoEdSYl5CWGbVf1vRH7Ui0y3GyprUJy0Op3S/BjF/Sh5VDTZ4cNyxiF0oy50hQ+xDTGvEcAPiWL+l1OBwOB4OTUwZt+W7rM7wlnEUG+TK7aF8aBNVKu2Q4J0vZht9b3pFKRsxcvcS169nBMCxdflBSNObBiLOhlzToap6OkufCQh/vN9eD6yMNZXqtjFQhErygezz5clVOIDIiyDCF2bJv9ZZqhJ97ZJOwIY8j41M0zfjmkxeZ/JCGsXSu7YetetGUpLX4pTaYkAkeB3p7J8R+yvtFRVdt3CA9+vZf8s6XToaeBAbDMqJ+wA+zIi8xrRjQ2g/Pq9UeavtKZdscN2stXnQJc5WFItMiprX+qyYhJgP493HqVo6x7g11OByO7YdF5jh1ckro+/qUAlcchWGGpQyrGbby4JKSZ1PqYoHkyKXBRGY4AY37UI3MBUVeUa+K0SRJMzfEafkuZU4uBUs8TiUdpB5KGOm5sMpT9TAbRp68J4mpZlhqxDRrN4qCkch36XLQpE5ZtNqEgZV/7X7IvqQ/eZzSMmktrQ6I+ideRiNNwjiTBsWwJNcK22jMW/2G12m2FFkkKvfLTvE4GPVPjeRraZfeCzuXU3otyFc81RDoo/QNkpPsxVb6GA+byWfhY3oTIt4kT0PLgW6WnBZi2tqm+Y9JLQvrc3K3w+FwOOYGso0WE5ycoj8xJSSkD7m3ggxLWraaLL1D6jWSp9DK9372IYWJjuyLSVCR5z96TaLFmy87LOnS4o2TpJkIKoDoNdFIaGKYszyW9gRyFVpfO8MhZfODhloMsEi0WHlqeso4HW8rFFbKlXJYey4SSiV9aQTXwnOZ1t7T4vsRuwppZf2DSBzvcyp6GNs1wh7V7HISE+8h91LHOIyMJenIiRXe35GXJUEuY+aHKakeVsGs5/oA08aKUthWTCH1dEeCGYDBANk7ay2dODGtesYF2e1LTGtloYmq7Ue34lGY6jJeQyZBToYCbJzpSSRbyreGvz3Hl/Q6HA6HI4WTU0zOHZ4Zz5LQiS8JqQq54TAl4lpeUGHXjuJIC9rQLRJmTpxDuuczEmQgIT5jk2V2QV12zMqIkuD/O6RLfqM+Rpq19wcG9l9inImBmmGmHQTCCaxSdZl8dRk0EfyKrpahS2nJpY7xvkLGZbisrBUSEOuyUE7U/vgkTnUj4zAMj8OjSr2bl3EKWVrfspY2cxHJpA9FS2ZYRnE1sivl0iQTkB+ExfUl/bjcPu25dDJ1X2gTQVpbJEI6wOi/BlotQN7VGaNC5Zgn67LUFpKJR+O7FQZoI6UUz/Lw1pbK8vxY4xj9l2GTff+KDK3aSwfTucfU4XA4th8mxWMWCpyc9kQLSZFhyLtR3B+peF6kIauFsTxlLYhkRpEH5ASVDGlp7JfKpLZUVMan8MkhP2AeXmZg05JG7X2iHNIwND25yn2+LLvE+SRpr4F7dpL06A8vE0UmXZPhQxh611DeV6wZuppxmxm6ISVZNSLK5ZI8kM4Marny9ocR4YyEzoKoKJlmjYBL8DavtmfeQDCqB1mGVFbyFSm8z3HBMp8asUwIXjea1JHvN+bElBPibDVFyPtQy4FfLdD2dcd6EASx9ziGETGVcVUPtpRRS0O5pk0gamFMmUafNrpIE5onW1iaHYbbKKA2w2Y5TeFYH3E4HA6HQ4OT03mAurcL6Z5KbgRopIYv8028R2KKOgz/VI0rFtdc/irIb0BKUCkt0o9+80OT+s6YR7UqBHfACoxm+aU+QLuHgkVNl9QFsb+1VF5oMyhbCBDA0lHIlRU18PCCHJVOsuWyuY5SX8sLBQzLuhBfpiFlR2KNLMuIt2R9SE8qk9vxiEqavJI0EmRmVUlLTogkSTLZdE22S3WSSSQl+1NSXkQmRDuRh0DFNhBgnorN429P0kBlZJ2oHAn08PtU0CdVBkNhVptQ27iod6uPWR5jPtFA6EPqWzymShWZMmphaF8uV5GT0RjWGoMN+RLacmrLE+xwOByOyWCxzfc5OYVuGM8HJEHl6ZMSljdS6pgYM13yL5WbBkkIZaIXjycSI4LKjWPN6zJXg8OKnywf62Z1mWZ6cgO0RCSHapvXW5bOJXIxOsQIGJURGYEW+TE9t4XyKxmpUr4kqTVIck7/M1JnpFkqU3ktAfPmyT6RVCNr5zXPXrJPWtGV6yNJS2nva6eFY+nw/tryqiGuoiS7ST6MONQXS95U63ClSFKZQF5csoylh7xlvByXzMh4/NRgvr+WE1ptPzj3Eid6NZBCrb7GecWURGnFRsmjq41LtdUfMgwRUT4BFpCPrZrOsX1WdFT1Ce1tweFwOBwOwMkpgNwYs06w1Mif6ilTiFuUDXbozxDcC5ksPQz2UjuuQyjdL+hiXZPygVmCGsiTwfQlA0d6MPtAcOz8tyBb0aDqUh00jxqXh4b7EqrBJmSR4TgtwpTIryRIJXSiTWhREjnKBIIFSUwD+88NUsBIV9FJloudeEqUTM/58H9nyWWJDzD7HtiW5ZEq2ZTg5EgLJwiqFJHFMQisVErup463qS+MRI3IvSAjGkmNB6Gx/tPSZ1v3mhpFiABjGTjFY2WXebW72brnhBxI/5NnUMrk/0u6Zm1hAmidrLOIKd2rvatXy6cWlh/iBqTPmBjG0CPKVdIlZBMNzkodDodj/qE8/3Z2ODkdomSU8KVd/IGuElMoJFYYiZpxnXgzht+5HCmzk+FZ+jLdTBfDKK15IrU9sJSoJKklSBKq6S5/83IPQTn4h+sg86TItXTgkHs2x/UCkKEtl8hqBIob6CWjUSWjLMFkwqOiG9cl0VMYzabxrJDGFi84IOqR5VkjDhRMHqIU+D0WXltySfe1vbI8LVmknGTKoq8SGl7P2gDBIe7JCQIKw9/7y/Mu5ci+3Lp0t/baH6uceNypQvu1IImpRsDNg5EYCZ9BKkf2ea19lvamt5RZy8SXNsEpdZKTmSWSp41JJT2s8dF6ngGjNqg1xRpadHM4HA7H3ODkdBeGPMikL0qeS1qqyq9rJJITyEhQR0FNQlr0jhLZs+4P//P9p4mXklt9XXrJTLN0T7spvIEJQZU6NKSnGU0lTx+rjkSlDqOTd6MKmuGr3EvqS/G+8SWb5DHixmw2WcAV4wQVaX1w+VKXGWaI8rBavihO7Z2LUS3F6wWkBDUpQ5HnSFDyrCb9AshJHfdEll5JImVLVpMtr0ROlmNcRuQSuYX2TYSuRIa5HpyQyUrO9reLvjNNeomyK6G2ioOXbSksgV4hUxoPaElvF9rITbY6AWn5aO24BmsMrXlltbTkeC770VRANoljpcXT0VShOqFtEFra2tjAQeUfJ3CUcaPFa+rE1OFwOBwtcHI6DyCDzzJmtJM24+8uNyaBWdJgLS+OaRq/OX/hHkhVd8WAaT2dmOe7SD4NGaX70hvIjWxAIamVNCSsg1b4gUjcEKPTg3lcqUJiONKHXxP542nwyxapA3QvFZFa7nWS5SLTz35rOorwGikdCD1LHplE1pCgMk6W59loV2qZhHTCgDyWqieS0hNpEYhMyrrhcWNYnl/FWE9O/gWrp+HFgRZXpMdJM40LpX4tCQjXKRmL2EBR6vOS3E93OTHlYacNWdQu4wRPhbzQ5IQ5AcXaCyem8r68TnrWUCNXWlq87GMRa+UkvtPhT7IPaHUpxxUNM2G2HXchj6Pp34LS2MDvqwS9Z1oOh8Ph0MHtvcUCJ6c9IL2m1kO2xRgv3kdq0BAZI0+E9JK0zEhzozvadwVjFrDzqnmQOUFt6SQlQ1Hmh+RGTyL3DJJRL0mqgtbDjrjRbh3CMiPCA0DoZuNJD3RLuiUymHhQoROB5DerQKonPnhZJEvThZb4tuSJ3ktJ5cd1bl1yknjexL0pUT7UJ6LeFYObeyxrhnn0KnV5GKvoIvEQk0ha1fDfGklV9Yfet+SJ3nISx0Ky95QSY3IA3YPH0XXpcnUeVluiLe9RnraBvft3qIdFarR3BGd9kj5K4n1JWA1aOladW/2b/wfy8Va28jAAAFdFSURBVEWT0UICpSf7qZnRyetyXLH0Sg5DYmnG+0balk6lSS+Hw+FwOJycNsJazsuJjDaj3WcdeG3pbXI4UsHQzuIquhXDF0gr90BZntyBMHqyZclC5ypZ54ZyVASJ8U1hWl6fUoOMr+2l5MvxYhxBlHl4LQ0pCyh7cLIlnxqEFTsYlhWRSy1usvTSIBryRGeNIGiI3i55vVJH1mmsA0Z8NY+R1tbj5AYS52AGdcJEIQZme1XGCI30St1kuGQSwUhqrojjCcSqA0Gua8tWSwrKMUtre5QkLe/l9dN62jRPj1SqrsRgUE9TbkhXI2DateRVSFr6pTRk+6ukVVKU8jnT6c+zVs+wJKaWDIuYOhwOh2OyWGx7Tq1thrsWKg/Mln2m1v3Wh3FLRfCZbDJcJ/Ws58s06XfN+ImeMiUc14+W2XG9wa7zsDMh/0g58Tu/Jowi6zMX8PKfEfmx0k+uGTIDRmWJwmcw6EFMxfXBAJgZpN7NWC+D0YfXD3mB6UPX6DM9vD9NHuPhtemp2e9TXTpgaieq8msD9snKKKSENWtbGHlwZL/gdaFdz+qK38PoE+vd0FMUebF/lvpMzIvUkwuoTGTxfJjpGWU3UPKe5U0JE+MqOvHl3jw+9SNeli1LwS3IsaEG7RAky9ua5VNpNyTDaiMD5aOlKetcLe/CmEY6avrHSash+Cm+2ZkImuyQ5q1GQoNyzeFwOByTQzfGpwWXXHIJVq1ahaOOOgof+9jHknsf/ehH0XUdHnroIQBACAFvetObsHLlShxzzDG47bbbxs6Pe04JAWZtlTymFM2KPtfZjDAUbInhew5LL4S39OOeqRDY8lgl7UhahDC5rJBD238qDWbr5NRZAUq+lEKntFtfnTLu6ZuDMEvy6BZfZk2Gn7anuFQG2j5Ii9jEV2oATaNLEP8pbctOTF43USlP7pGk5aEDkfeS11QzrjUvO//ND+6SEypA7gmc66SR9IDJfHGPMrUDKjerWSde3sZyxlB06xNF6wtRvaCXs/oe1KhEHl5+t/Q2dcRw8km2geGfDqzMlXSkZ5XKMmnrIk7fV8XUSJXWr2sn7JqyDKIr09HIIEfpwK/Wx1FCbsOoHIp6KOOKVn7OUR0Oh2Ph4/bbb8cnP/lJbNq0Cbvvvjte9rKX4Xd/93excuVKbNmyBRs3bsRBBx0Uw3/zm9/E5s2bsXnzZtx88814/etfj5tvvnmstN1zCvawDOKjheHXgvgvws2FmJaMAKCy51D5XUpDMzarL30XmZXe3PgJaTmRARM9JtKStNIhvYShVPIMlVA0OBWDmUDkdGZYQOQhBBiJD8jahOUd4a9pGCDLblmnkhVekKWF4ekQuJdUjRtGXi7Nm0rftTzU6knz8NH3mQBsG+jEBqgvN9a8qxwt3VaS1qb0jDZQI0AdZsvRqoc4MYS64S/bo+VJ1YiI5imUbYy3hyxtpe9a+c5mdw3vntVGNaJUGxNl3gYF/XieEy+wlBP0stPuaeNmqX/SPRpHs/EUo8hyplweoGZlknTg4666xzTk3+X43NI+HQ6Hw9Ef/FnY+qnhRz/6EV7wghdg6dKlWLJkCU455RRcffXVAIC3vOUt+MhHPoKOCdqwYQPOPvtsdF2Hk046CY899hjuu+++sfLj5BSFhyZ7sNKSvtaH6zjEtLZMS2ISL4yXBhZ9T3QS35NkuZEe8g83oAJGpDTGFVZLQErSVGXFJY2gWp8kbiFMScYA+bI41SutlBsvF/7aliDCWW0hM/IKZVdrHtII1spFyw9EWA0D8V8zXmV65j2wNmTUFZAOZvwEZa2Nc9lZnvQs5eF425f6Bv13qzypT0kGtSe5zJ7LzcoMdrlQfjLCJD+KzD55s96Laz1AS0PqJEmQVdZSdjIeSD2M/lMi+RSvtF2Ah1fJqCZ0CCKoU1N5WUqSzJf414ipzJ/23eFwOBw7F1atWoUbb7wRDz/8MB5//HFce+212LJlCzZs2IBly5bh2GOPTcJv3boVBx54YPy9fPlybN26day0fVkvhg9R4f3i0N7dN8fVunka7Ht8z52iTwhzXypMciKUpbEhjJZQUvnI5b0xakjlcKinyFo6sSD8P4mltOhdq2DlhEKZJWkMBdcOn5KqxlXEVA7dcB+n0DXxYgnjjP/mrztJ7kmD1jCSS9cmaQyWCCpvixpR016FAeTLMa00NWJHdQDo7dXUXfFuq2kX7mm68zKIrxiiRij0tw7G4eMPjHKK+Q5K++7KSzmza2Hk3eRdNyOonX36tXaSMumreTFJF7VORZ7pP+nJDwKLBAs5UeL7qfuiFkfeJqKmyZDttSSHx9XS0HSrTkpa92UfsGQSQVXar1VvNWKqHjpVyoPD4XA4mjEOLXjwwQexevXq+Pv888/H+eefH38fccQReMc73oFTTz0VT3/603HcccfhiSeewIc+9CFs3LhxAlrbcHKKEbmhfYPJEqgC8SrKnAOJ5O/XjHYuI4gWwaoRL55PHiSwPMqomsFNYZF/NROWpFPGlQQu3u/KVRBYOfWqK8UYVIMpBJMvoZxRGIdm/EWPRBilXSJC2mVOxqwwlv5A2i60tDlH0vTRCCgCOwlYSZN+J/FF39CWgWYeSKYbb69cnkauCPI9uNoJ2xaRrIH3O95fomGuxJHNJssTKSTTEf1BmxySJ3qrkwGM/GkkleLwV5rIfarVcUZca5l44enE/wbZk0RpHE9dk0dbhK9ueVDi0LXSCosWvYrqlm6yhGdkOKV8pbdU6iTJdN9ydDgcDsdkoNlQLdhnn31wyy23FMOsX78e69evBwBccMEF2G+//fDVr341ek3vvfdeHH/88di0aROWLVuGLVu2xLj33nsvli1b1l8x+LJeAOn+x0giIJaXxi/60jmCJH3aR0K7lix54/Lkb0VuYHpqkHKy62H0m+vCDZJm7wRLS/NqyPxY18CuIaR1IOMly4qNcs8MzmDEQ/oBkHmRuUEnTyTm6XFvaVLOyKG2ndK9xrZmwcpv/LC2YJ1AqrVDbam35uHS8soJPclS2z/0vEoyLXWUdSg9RCrJLlyTZSSXe1r1wsPOyDJA2q60cSqWCSsc2T+s+ozlzH9D11Ve49+TZdRGH4ByTZZFcUUDWJsSMrjetdUvtfTMCRotXa098PCyzSofLZ1eYILUqBYjlu2M/rM+VSKmahsZR3+Hw+FwLEg88MADAICf//znuPrqq3HOOefggQcewD333IN77rkHy5cvx2233Yb9998fa9euxec+9zmEEHDTTTdhzz33xAEHHDBWuu45xfAhPFzCFiA8p9JDGGBbL/OgF/eSJUvvFC+nBcvj2FdOayLJ+zi5t1WmLXVSdKMb2pJdflKxZZQG6EtPpXeT79+aZg2AG5sxK4ohGDDr4SFjbkrET4ipYsyRnkpxjcIOC6C1vjI5IS8L+f5Sq26k3i1Lc6Ohy8or1hnEyctG/IzAi7bBVxXwNqDVOZAuVdfU15YuJstrRd3xH6WThrX8aZDeVytOMk4ZY1Rp+WfyrmRWVrJf8LzzatK8qPE/l9UJPY1yLyEhTCgsFx/+kWNBANreEWykTelYKwOgXJcklaN4IjWFUa6purP+wW9rzy8KyMOqkzpI89sCTZ4cH81IDofD4ZgT5ouWvPKVr8TDDz+M3XbbDZdeeime+cxnmmFPP/10XHvttVi5ciWWLl2Kz3zmM2On6+SUQS5hTZa4DcOYy7KEcZrcM+JpiIbg0EidboxnoZZuMPRuhcXVO4xeb8MJQ8mIMY3xoVGbvJ6DySUSLF+fQ8sbNeNaktbEm9fNvquT0hsMUhKnLevjS4sHLK24hK5ATJP8CtInyWMLSkYxN5r53lArDesAlNK1WG5BpMfzxeuExePkyDqBOpmMyNhU+ltbLsxfR9O0RNMgEJKsl2Ro160TbQEkr3TS9ASUyTRG2JOOqbAW+fona6m4JKydIjMS2Ak/Hckrp71TlKc9Um70n76S/hRVvnJLTbeiU+kapVkkfwYhBFLdVELdh9AZzyOpI9fJOqRKFc/GE/eWOhwOx+LDjTfeWLx/zz33xO9d1+HSSy+dSLpOTgU0gqqGC+mhPARuI40DiyhmE+AFUjmJA5MkeLlwUmce3JQoxAgqGUWGN0pD4IUqynooatZrqRjkAxEnIbCB/WOGcEfkhd2fGQB/tfYyAMBrvvba7ITepCwCEJgemkHYQmBayGMWX5Ed646loS3NJUyx36qHyiBVVHZ8uZ8kmVr+eLrc45zox/Tg3mlOPjrlt+yI8vCkWr5kHvl3yRk6JYwqRwmr6Qgg2TereYGB0TtmSXAkrLx9k2xR/lOiv+gKCeVZcNJ1SplMi/1KXGsl7xQ+WS5fKDM5+Gqe1D7jMg+rTQ7UvITyPp9ciXI1hYb5sF4LU9MVQHGiIE7GKddraGnfUp9JnCrvcDgcDgPd/Nj9OxJOThuQkTCFjSm8SIW6x2nMRqWRQg7pSRxXDiCWfmrh2cW+xkjpxNeYfsiNen6oTSSLStrRIK94TYiUdmDhhv+nWQHIcg3sC/e2lkip6gmzVRulNSwEq61pBuOUcc8yLmfE72wJrEJ6pAdFI6YSsh5L7+oNPE1RhpJgJcRUmTWxliRrhjevt6BcxzCJAfsu42mQ5I6+85utpxqrWxI6fRziRSIndLTxQva3TKYozxpJoskFjdhlXtwg0m4cV/qEldAIsDZBo+XXIm6yHxRf/yK/8/IbtukSZ431j9zzGtuwjN+zrGQZudfU4XA4diwWGTd1cgrk5LDkPW0hconsOehVJYRaegVDc1IwvbaNSnbyCzPELEOHnw4bDVYMy8giIjJNKwyTpxFl+vqGa14LYOixk2HCSH+LoNT2cM11j1cr+p5EK9OyjGN5nxvFmVyRBpWZ5s3J8soKuOt0j5S2hCE71ZldL6XJDyOyIFcVaFCbnkK6E3Kt6KfJmBmG4yTVTFdcoMkbucoASF+b1eJlnhFlwF9Fo74LlOeD3afs8ypXHOFpPngAZSyx4mpkNqn/QpoxvEIam1GKqOjVmk5c3TOMSGMWz1Of8UNbwlsiymVh7ek6HA6HY9eCk9NG1AxPDivYXL2m0nYM7MJcuGhpCbOW78yY5+lrM/7ynridkAZhKNY8RzMYkVTuNZCyE/0kiWE6SeOv6DViYUveI8sQ7FP3fGnv9vBU1LysGjmWBK6mp4wrSYK5bJLIrJgMSJYmMy9TPGjKaJtchrxO7WGGPOGBeelJXJfub7aqNZLOQlrZHkqZeQG515VIKsXhy7kpfLb0me7JtAzizz2ciZohr0Pphed5Nb2tIiwHEXBNLs9fCS37Tilt67RaIO0D2phBYZo8pexSS/fWJgq08S95dVVBz5b0NGJaIqoOh8Ph2D7wZb2LENxDOc4BNONinMakElQgkksyEKOxDN3GNQ1oisBIaQjpITIterV4UVWPTsUDIQ1DynMQOk9hZKSrBFWoKi9LY6xDvh+S7tc8K+bSzh4THi1oWSpcehepRMmmbiGenMwB1fmKjNjFQ5MEAYvCWN0Cs0upuy4lH1OiTWn7UE3l+G0++cAaUymaTCYhyFYcnieDTFvy1OXx0hPK2q659JkucTlchhhrojxDH66TJHSRlCv5i8ROlJlsw31OSa5B7Qe1OjPCqsS0IMsipn3aTGlipHW80uRr2ehNTCvt2eFwOBwOwMlphj7EtHYoUgktpGSAdFmcNAQ5SkSnxXCoeU1rBJWMn2T2XipqEQNxi4xmjUBx4xYsDn0hcjKD4eEswsulGn9MJhmTGYkLwKfPmD0Qaf3XXpvo1ALLa9qHoNZO1ZXp0InPtTatEX55v49dKYkHkc5SPhMS24nfFAajfE6DeUR5HgQRlaefWrqUPJ4d/8/aEy2DpYmLWtmY5SvS0iacKD8Q9608aESV2gOQbltoqVztICXZtXle5ARaUkfs+gzPPOmm9FnZ7/k9bfyN8RRiZb7/WYbT0lPyIO/R/T577zViqnmWzbYjxxFRXyHUiWm2kkG5r+a7INNE4VngcDgcjnZoq2Z2djg5hT3zLpfv1TBXT5gWPzEmwsgjqBqB0L2nY+kiZEk9paeWx0v04hcqxggZ/2GYz0GHzDiM6Qvx/AIZzzPMWJ/q8rCWscyXJ0ZyxfJIHjoNGRlQSDY/4VTGkSi1p9ppm5neBX1b7ETuMdSM1yw816ng2SGjeSoAU1M5CaT/M2FEtGkwlt5x7omT5SFP+eWy8x8j3SgObxtZmB79rFTWXJT00LZ4uzlLVPVEOmlh9WVLx254c4Dh+4BZPF7fyaFG7D/XJUlDIb90nYieSkwNEBmrhbH2m5bGHT5eWKS5D2rENJEtJm6yiQwoxJ7KsKCnNg5o9TUOKaW+43A4HI75gS/rXYSwDNTEM6BNWXMCGC3ikaHWt6308aaqRiQzNGvQyG28V8hDy6t2VNlzNE5qRhWQGmz8XaPbhmGmO72MKbz0gtBBOBjKWv+1144mByx9hNyakdty2E2JYLYYxVUSK++LsAm5KBinA5Yv7qnhe2WtfddT4p7se9Er2OmezxiHTSqofRaCpCr3JYgc0Yd04nni7w3loizvWWnSSNWpoVNnBNMo76gzdIKayRXllOSR5Z+rS/eS3yx9KlO1PbFy5l4//nuu4J52Srskt0+aMW/ajT66KelKvbN7ckJCxKulZ8oW1/tUgb9KxuFwOBx94ORUQLMBTQLBCOq0ZgQa8gDbcGyBtdxXk0tGszQQxvGo1ozd5Brp1iIXjUYUyeSeL+ZJSDwGgkwl4QyPUhIPI4PMOhBK88y0kFaAOZIb2sG4xrhVV/y7JA1JWBFOtiHpJSvpKgklEUkIGdFbysuY6Zl5FQuGtZYfvuc0e12RUQ+cmMZJDyLAGNWjfLVNyShv7Y8xjZY2wAmmZMnQ20Pre525PgBmX0OD0dgiPXl8cqgFgqcmEyIh5HUFjMqeE6faSoCsDUO0GZaeRgRln5D35wqNmNb2iMpl+7JPW3pa+cp0Mr5zqCdmg03wtQhxOBwOx1hYZI5TJ6c1VAnk0KgL7DsnHImdGHRDfhySmhxQElJPpyTFTSdTor1x15YEcpkclpe11VZhvCK9XjGqI8kcyuhayqNEkgVhaonDYRGsLFxDhZS8kVpY/l0ldMjDWO8bjWkrxj3pMM30IYIa7xt6ZnqLdHn5ZXWgxWf6xHagEGNtGTwtJ+VlxJcXJx0upF5ETQeenkynRlDlNQ5OSnl/DCJSyavKSa2c6OF6awQ1yZ+QVYRsP6J99X2Ni9WWrVOk+3gD50xMjb4uZUnCPC4scl8j8PKeFl56yoG8uvnKEwq72Awoh8PhcEwe2+tg2iLOO+887Lvvvli1alW89ra3vQ3Pfe5zccwxx+AP/uAP8Nhjj8V7F110EVauXInDDz8c119/fbx+3XXX4fDDD8fKlStx8cUXz1kv6elRnBERA2YISONCe9BDXJMGcB9YB3eU5GnGhYxP90veKC1Oco19BsZvrq9llM51PT0nWjPss20w+588YwkRUn7TvsMkDo+rpc3zYdyXn5h+Q3vR2k9GROVvLRwLmxmWvH5E2dSarUZ0SvnO0mN1R7pZnyA+M+LDZcn6BnJ5XE95sMwAqY4WrL4p66U0iWSVU3Zf1hFvJ0IXnhdLVysfUQ+tDhpkJRArEQaGXlmbF/95H7SSrpFRSpenw8O2ENMOs4RdnWyoTOBl7ZGna6Rn7SWP5aLoauWd6yDbTkwv6GVMdZcLLqfrcDgciwk7gtPQqsA+n4WMBUFOzz33XFx33XXJtTVr1uD222/HD3/4QzznOc/BRRddBAC48847cdVVV+GOO+7Addddhze84Q2YmZnBzMwM/uRP/gTf/OY3ceedd+ILX/gC7rzzzqb0WwwZTkyzB7MiIDMEDblamnOZNS8ZqDVjODM2FEOWvidGkxHH1I+lVTOeVRmVMKXDiiS5IYOKPvF9lkLnQZg9rffTZ1yGpwazpJY+M0xuVh7Iy52XgwWtjDKCqH2MOqPfksRlehp6yfZk6t3QdkttM8k312nY5ohkEjmUv+VHI6uS+MLSpdB3OLFrybMk+33LTMrSSDSQlmtC1kSeZZoZEeyrK6s46aXU6ri2msPymJbabSZDlA9vX/KApVpf5PHpewk0mdlCULk8KbflAR0PCeOrctCvfcp48TtGeZaTDxZK4Ra4PeRwOBxzxo7gNN0Yn4WMBUFOTz75ZOy9997JtVNPPRVLlsyuOj7ppJNw7733AgA2bNiAdevWYY899sAhhxyClStXYtOmTdi0aRNWrlyJFStWYPfdd8e6deuwYcOGienY8nwfCAMjIwsQhk7B0K/dz9LmccR3TTbXWTNok/BQroUyQbWMeguyrFqgGY30W8rlhpY06IH8PjeiB2GWhBK2DdK8kTc2854rusq8WmWlEgyeH+tjlGNQdMtkDsNq5aOVK0c8rVW5l6TP9NeQ5JvpPCPiWGTRks3LhRPXeA/pd/kpkSW61wlvmeyDyXeWJkfJK2zVC4+X5aekQ0j/awRVq9OsfFm6FJjnM3qtpdIsEG8bmsdURrP6VglW2+PlYe01nS+0JsFnuqfER9tvD7QRU14efNm2jFZaGZLIk/F5mwzKfYfD4Vhk2Bk4zULHgiCnNXz605/Gy1/+cgDA1q1bceCBB8Z7y5cvx9atW83rGi6//HKsXr0aq1evxoMPPlj0FBA0gyjIAEgNnRiuYIzzsKX7LWQvW2oovyv6afkpeQgsj0tLGUpYJL7vS+JV2ZpcYdz3OUWSH3glvSHcmJVk3yIGRd2VMs8IKHoY5VwnQybBKhNrf2ipPWlh+hj8NbJS6hNJOCFPnbwIjBArcqt9FCMZxXAyHXZ9HGT9MeQkVa17Q461lJa3Oy6DPgP5ny2XT9KBuGb0ib5thVAj8XPBPIiMiAeCVaaz+QObJkNk35TtfNyyBCplKQehoHyYPlyXlr7icDgcixGT5jT0DFhMy3oX/IFIH/zgB7FkyRK8+tWvnpjM888/H+effz4AYPXq1fF6gHLwSMgPMcoOBmHh6WAT9VASJcJ8tA/+upnA02WJcv34SYtaGRDoXswXxUf5xM/S4TzccCHdgf7GVBCKc/njGEEyXtcB5371tQhBf29fQlBRONwmiO9jNABJrrjnJMrUCBjScoEIKsuJH9ITDxDqynVjnPnSjNa4tb1t/BLlvQMSBQfdbD+hMiR0Svz4W6RB/SAACEPZnGiEMEpXi9sXWtlLzxeQ9mnKBxUC9eHs8DbWnwHlFFjWaBIZMhz7Em93OSmVsuVERJauiNZrosOQwe+X9mb2qTselpb2annX9IhtlMmZQl4uvM9rh+xp42hpolHqTONfUxEXAmljDqXhcDgcuxrmg9MsRixocvrZz34W11xzDb71rW+hGz6Bly1bhi1btsQw9957L5YtWwYA5vUWSMNLvcd+a6fx0g9JUIGcpMr4moHZpK+CSBgFGZYEhhNNYKS3Zsiq+WX3+Pss+6DVY9ridZQGqHVC51inI4eceGkEr2PhObJ3akohcwAnCRpp0DynMvnSclECJ6ia3pz8aemUJj3U6wZZsZARSSYnKsgIdheGhHJ4K77DVsittcvSCbj8dGJ+TSuL3hMyJE/E114lFcPzihB1KV/RpOWbT0KRDPkaGV6GMWhI81zgqSpp0sLI+k70ZGOajKOlNYnVGhbUuobd7jvxJYTy2KqtBIgiOj3fqj4F0mwqOgYx7ZWGw+FwLBLMJ6dZbBN+C3ZZ73XXXYePfOQj+NrXvoalS5fG62vXrsVVV12FJ554AnfffTc2b96ME088ESeccAI2b96Mu+++G08++SSuuuoqrF27tikta69VK5Lwwx+0D5EbyNKbpz245XLCccANrmwvKk9HhAfEkkAjjPwtv7eSSB7OOjGU667pkclGmZhaMqwlv7T8jC/XVffphnLezX2c5eyo4fmH50ktt0Jex1kCScRqqmPLQ/h92OTLyoums+Wp4mnKSZJ4qFXIT2BO0gyiXuk30r2taplCL/8kX7K9Kdfmgpi+zIe4TpBLfeV+Xh6P50GrD3l6rJaejBfbGdiYJPPB4kJ8D4pMGY/yCbClrtBXMJAMfpCWlgdZ5q0ovlKLlXctHuVBLsHK9pgirVeLaHfywyYttPY51diPa5B9nB9KdsLlr51ACg6Hw7GwMa+chttjPT4LGQvCc3rWWWfhhhtuwEMPPYTly5fjwgsvxEUXXYQnnngCa9asATC7gfiv/uqvcNRRR+HMM8/EkUceiSVLluDSSy/F9PTs2xQ/8YlP4LTTTsPMzAzOO+88HHXUUc06yPeGAlC9qEDF+MDIU8C9qDJwPEAmjDxOlse2dPqsdT8xTof3s/ehhlG6fTyoPD73mgw6fbZDM3y4QVTzWmiGnGZQ0U+NmA6CTpq0paxS5iCk9+SpvNwRRcan9CZheC1rDxiVp5YXkm8SISWcJov0rR10xMHblfRE8bxreeX1I5fBa+n39VxJj2SSx3hCUap/Uk88ImvfADCDvAwt8D6SXJdkjalUkh3HBObR5XEtIpGkqfRpIK37Kd5YRD8ujTdy2a8WvlTPpbyrS3qRklQuy0qHt0mwuCRLptMyebU9YPZD8UWOB63jKKD31fkA7488PdJxPj3VDofDsSOxEDjNzo4uhB31KF4YWL16NX7z/30+AGGMD/9rhKY245AYoCKsnI2OXiBD5riTG6a8brR8MerKdJKEhF/X9JTX6OAgrdyYLTz72zCqLO9Jdk+5D6ReT3mNE8OWmaNBmH29zADAl8+8DADw/3zxtaqRN8Bs/qe7EXmSvEVLc4rVBc+bpouMw+9ph6NEeQY5leVZauu0d468YXRNI4rcizNdKGdJFkrkSOoLkZ/ooWPktFQmPF9a+8/0ZGRbTjpMdcBuU2l8Tib55Ii1HxlARj61ZcE8LKXDr5X6NAcvG15GtfLiMvlYEievGiY7uN6cNCZea6Tftckoave8HVD/w/D+tsGoD0u0eEtLRLgEPjZF/QpEUta7lGGF5fL4hJAsS1mvsi9H2RBhFF21i9bkAe/jWtu47bWXaSk4HA7HgsTq1atxyy237Gg1Io5+3j7Y8Lev6B3vzDW3Lqh8cCwIz+lCAX+wlw75qRrQYMYAfxh3KYmIaYqp8OSAC9Q9La03yGCZATDNdCp5TqJ6IQ3Lvag8vlZuFomk8Jae/HvmLYBu6JinzRqErYUIdR0rL0NW14087kl+ZQWK8iOdtT2ppeW2pXut001y2SSApM7iTSB6fROjE6P6l9AmIUiOJPSZPkbb5f8pXEaqgDizRPey17sIPTms1QiUV+n9yyYUgvgNtXhUqASsQkw1+VGPLg+g7keVY5DsbEpc7kWdCul1IO/XU1Dyooyr9F9rOxY0csVXTNBS7xJKJLCmwjjTu1oR1yYE1PHOuC/DWu2c0u2VB4OYqitkQjrp4HA4HA5HDU5OFWQEbQyCCihG8FCOSVC5bIqnkJaS3jLtLrOeZ6/NhNSjldiyZHgy0sQJaiSLShmEMFreWzPsSku7NII6F1Sqqgiqq1d9eXRaLydzMQ3h7SBYhqAkqCVYpCkLBz2vlnhpVMo6C5SmILIUhg6K4rpFT82QsCf1bBiw40KS1immIxFTztEoL1ROfMmxzAdB7s+dYnEpjWlFDv2WMrU6sox7DS3BiKDyZfiA0WeZUslElJGwnMhqWaKpnQCctKNKXiyvaRaWtTfL46rFCeI3pTEJzPWVKZSH0rt2e8nTiCsfb1HIeyMxbalXh8PhcEwGC30PaV84OYVt+PMTaLcLQUVqLGcCMAqjEVE1fUYeuJWeeD249wRIiGe2HJaRssSQbSgLoLycLVv2Jwgq6TjJWXirDi0vQE0WwEgQQ0KQ+siU8QskVXpgFcdZ/lqLBnCyonq1DFLeJLdy3fToG3Fp2XriURJxJDHl4eSkSwijzyDMBqJXBVneKKsYSqsTxiGm0kvJtyLIMHzsMr32kqBmGRgp0XfvYuKxFfesyRHpSa+Nc5oMOoippCtPr+/Q0tp/JYoEUOhjEdM+/Y23bfrdEj+YP2w52fjgcDgcjnlDh7k5YBYinJzCNkq5V0C+QqFEFrKZ6aHxF41iyVC4LvKB3kiciveEUcnzS+965NZSJFcsbypJVQx00kEejlQ7hIRfayG5crZ/LsgmBsYgCoDuIYxlIMi8RhxLaXPCK9tqokMQrw5R7o8DzXCPy8SDfhAWeRZbvKUlomoto7aWMXYQ3m1F/0jGMsG5PPo61dnEdMbQk2OK1b1GMmV6ljiLrMSxSvTzmIbRX5N0gz25oo2PrYhEutBnVWKK9D9Q3zfNZdHEgpqekVYreo898rkgLlljwiTSrpFhbTwd9/3QgN1GHQ6Hw+GowckpUsNNGmAA8zKya+q6vJa0jOhaOM2DoS2jrarBEw0jw57+JwSVxeEkVXpa1GRE2Q269F4ruJxJLOk100GbF1N6DrN7hd8zwGg/qiCoMryVTc3jpf0uwdyLyxNg+ijNQfVoRvmK7KlSeRZ+lyC9oiXIZcb0PVudkCijT1J03Yj0JsFZP6nmg6fb0G+1OmjBAKM90hZB1bynPLw5SRbEd9QndWoeb8ubF8kl5auRlPK45lJYFr7P8FIjupqerdDI6STGvpa2ycu++AypyADycncPqsPhcMwvfFnvIkUQRpdmUMVXskB54BpeCU0OET7ywhC0kyczIqgZd+y7Zhhlr9GIFqhCUEV+qFxCgLoUkuuQqRoajXZNnhKH7xcEpSfktyxbTYxgUW/m3INCJiwjTNNdTgCMsyQvxuvEbwa+VzimXUlLGsUqURJ5pb2kfQmrJrcVcr9iC1RvXCOJ4m1BtouEQMgLhmxaRq/u+TQg77V6pDQSzvuzRlCBdI+5lDcSMvLM8gS0CQCV6ErZIg1JHEuvP9IILd23DuLRiFifVRuaPG3szgIJmG1pOyJrXxOSE687MXU4HA5HTzg5heItYNaodUIloBjLzCDT4vL0AKBTDM3aeze1V4hkEJY0P5VT7nWTBDWmI8g6z88gzB4AE/OsGK4xjaB/19BqGE7Sm5oY6xBtgP1uTU4LT20rmwBg4PubtT2EGmGYC/qSYxlnRsjiBxLF9lRJt28dansHx5r4UK7JiRiSLQ8kU415OWFQSFRdpbCdISc41DDD/ypJFeOj1j7MFSaaPJam/K29s1gLL3UoHrAURJ02tiGL6Mr3IBdlDP/zYZPfG2dYa9mLXdRJGbPMV8g4HA6HY8FhkTlOnZwCurHGCavl/cxelxBSImF5DhMi22oBCA9HnonCNam/9H4wPSMB1fKDNJ7WGaKxDn25n6W+9LCMu0RhIGQkHiQj8aBkprT8kMvnZJMIW2Z0GhMAme7Kb3Uvpy1iNIESFK97IzTDue9JoVQ2k17epxEgs0swA5uHpYONRsqOVheUdJTeNVlOrdmzPKg1tHpNKY1pcY03c41kAnm7qfFoizDGvFUKRaufmIcxiKl1+JG2fHeu7VGS5+ymcinYt3sR5tZD3Cz0yntD2GSOUun7DofD4Zg/+LLeRQq53A1If5f2ehYJnWJU0ZcwjBs9rUUFe2UnQ3Y68PCPRlCB8jLERC2j3KTONfUFV6gus2v1nmYH50CPVyQl7Ltc2qrtT1br3CjHliWmAOKSajmBIsNwWIazXBKp7rFU0igdQqSl0UpMa/nQZGjEsya3pEDpBF6tTmV9tC4L1caSqnpGWY6TliSbfJxqJaiW5zUhjHIsKOhIcSlt7X4tXnEZr9Ju+hJTrU8XV60ol8YZwqnt9dlr3UcuwZoUmA0MU3nrlhNTh8PhcIwLJ6cQRJJ5Rehe+sUmqpzQJUKUsERM5ZJAkVTxWsnuS+4J6zJZrsh1FUSF8jONUVi5LFj1nnL54noTlMIw97qGdqNvHKOUp1MzuLjBl6VT8MxpZIOTBYuYap5cGbekp6kr8jIl49iaFIjLKSfgMc3mOGS7M0hqCdGLjtGpuy3p84O5IK4XbPY0beUaHydqkz9WWdbqubTHlRNSrR9np3Nruim6ammUYJGiltUWHBYxBRpWTlA4GIS+hZgqYYxbuX6FsN3wDxFUwqTIn2zDvN7pe5BKCkVbJ62SZ6kyueFwOByO8bDYxlMnp0NoBltC1mTgIayDk9RDk2SaQ8N6CkjJYyE8T7evYUx7RROZ/ItBUIMoB827lBHsMUlgFleQusDCyCSqByE16NRHbW3pJKVDunCCWU1TxInLgMOojWhyrINviqRHkUGGasuSQt42ZLrjntLMw0vSZC3rHGfCoUPaDyQZjv8L5Z1NGBikvQT+6heSG3UKaRh+Dco1q64HQGw/2X7z4ZfSpAZ/D2rf/m2RnkzHArEp9Wk+FljxNWKupTHV2GZVYqqEaW0KHYq8z4Tcnz4XxC0HIa1nKpNJ7D8N8c/ogkp6HQ6Hw7HLw8kpcgMsWZKmGDsWUY33w+gVIgRt7yAXUfPCZMZ5xSjNSOTwQpbHqDgSQ7UGy2htRUI86D9LPyEliieDkxPSp5ae9t3yRraUA69T2mc1I9MSJK7kleF1wwnDDGaN0CVMYYqnncobMHrPZ20psayHuXqW5ftFq/GEDEmaJHGUYTNyrITVkBAydp3KU/OM8nBaubZ6riUiwaA6xeQ8YzwNdSKF/nR524txWV/XUCJX1gFv2sm2vC4zbznyvlpCyL4Y5J7ppS3rlmFbl/JOEk0TAUaYvtc75BMIVFdamWpys3dal+LMc9k5HA7HYkfX9bM5dgY4OcXI6JhSjOGqx6BLv0piQUhOwtV0YCSmpmuiX8FToBn2lhFmeYxVHYb3kzJjBVXrI5xUmEvCmCxZNq3EdBxPqXUIEcHyWNSW/VIb08pGEmKLwG7DLMHgnr1SeuokBPLyk8YjJwgE6+TdRFZIy1Pbjyvj8vvZBALvS5QfkT5gn2hdJBpKuVhLePtirg+JvsS070SKBr76oS+5tiYELI8ojR3yujU5EuR/qnfoRD5rRz2hTUgkxDSIGyKu1kajPMWTy9Mp6SLR2k5aykAjpRxTHTCj5BWwx4kgKs55qMPhcMwPFhk3dXJK4MZHQriQP1S5d08uQZURNAM9OVSH69BATDl5s4iOSVCHRhVfxtanQWtGKJcliaXUS5VZu87KlBtDJWI6F++fha5LPU/TpAcjpUG0n4z4iot9SFBC4Dp9OWCyzJaRf1MOv15Jn5MAyrcWh1eb5e2X16y0NYKaLe9W4sn3BC+2QZtjvmZLxyGohNqhRtoSfU1ODFeYJCntNZVpWuQ3yjImOYJyTyOlyf/KuKaN0S3DljYpZqUxSQyEkrIsi324cN/hcDgcDgknp8DogTs0GGqHgdBSQDL+My+msv7M8iLFg1E0b6ZIU+ogyQfXo4WgUh47tBui3ItpLbubpHFketXQfrJnazpk+MmDZNRJAMzeJ29C4hka/iGCFtj/hDhhVPbJPkbhYeS/reWZXC/+3zKis3jihrZMpPZ6iBD/wJw84WFLxFSGk/M+WnlqaDnYJ+uu1MaV+zsKJU9vC6zDkZK89ySkWRo1Umrck4SuxSPYZ6KjpZ1xyFPNk3xp6cLOmwX5HDDLpkDMS+nUVGhZpVOSrY7LQu8gA4hwTlgdDodjMvBlvYsQkVgJkjoTbMN0ilsvgsRIb6q2VK40gy7DSPClp5rnVk2PB+NMksmxSJEkREr0PA1d9SpklhWeX/WWcmM3kr6hMMuolYafJKadMFjJM1k7xZZDek4pzSVD2VNTswf10MRHCLPLwXlbSTztSHWylkQaKxBHYZT8S3JOZHwqjJaoR+8o05ETOq2dSHIp9SBYyx9luOwmJS5QIrH8HafqHl1F5FyJXB9MarKn6dVQ0Ce5apMAiQyDlJYIKemnxefQ+hlveyXio+llbgkgnbS2JfKh5aUkk8TUUBI3H95RkbWIuN+0RIaVMSTeE+GclDocDoejBCenGBnYoH/MwrYepIlHRhrmwmsUxBdJAun1G4n8is7a0mC55NeanZce1GicwzbC438WlzxM8rRLCFklY0QtJ0VOq0EjSVrQMjUmJLEqGWQ8HCE7BCaMwqEbeVKBNM/moVfDeC3lXNJRy4N8Zy9BElRa4qvJLRFMGbYU3yLdkuxnCU2QPE6wGfXygk6ahEiCKvOVrcho1HUcL+k4rxvSvIoaKbXaj0k6GYpE3CKzDcS0ZdLSCj+XVzOxJBP5JQxEeUIpa66POg4GPTyP53A4HI65Y5E5Tp2cEuSS3ISkauEV76rmTVWny4VBQgQ104WiVbxy9OqaJD4nLTI9pA1Ze8VMlgbKXheNoFJaJbTYJzxM6bUTplxhnJIxVXodQ2LcirRalh9ysk8Eb0YUPBEBes1HyYsOFo7uk3HLOZrmkW+FjEttW76GhIcvvWbCUoGT+xZ9ZDC5/80W0KZQMkGjzIaUiJwFi1jPhYRKmeN6b7WVEEk6sMs+TlQV4nMdZRjed4r9t9KOuX78cCWr38uwY6FHXDnsq95eNkbz1RJ8jMrkanIwvhdfI/ZZnw55/fG4qp4YlbdJTjHH+nA4HA7HooSTU4wevIkRUXjYS+IahhejMc8NOGHFWa+b4B7KTL+GB3h8Z6Jxv2bISsPbSqO03zF7X6C4Z6G0H9BCaTbeSiojOYZM9bASZoTVvHpyT67llZ4rZNKJoTi8Kd+h2yRXEHHp2W89hKY1jXgN+h7R1td3VMu4RyVw8dSXaZKhRUQfb1ELsSiRNG27AI9nXdPasPSUq+kBCbHS0i22TRa+ZYLCHBeFHEl25LjSRIRq+qBf/ZfKM5kIkZOVhrzatRaUulPplTHFsVVOZgxJaalenJg6HA7HZOB7ThcxVJJqhMsOFqGHcye8qWB2hzREBBnSvHMaxp4llwRVsbTkjH5NRov3pvXQGoJFVktyWu0cMvxqXhsiZK2kQEOtmjr2ictjuTelKx9CZC37q4XjExgt+/ykZ590C4GdTKwYrs2GPOnC9QxKgAqauoWhlPSeakuSO+V7K/jYkt1TJkUIdK3Fy99KYGJ9BuVVLMGe4Eq2BwwLQfOwyjStNqbFLZWPUDPxMkoCBOV3ErkRWpsmcF1l+ceTs42ykGUsPaZ9VhXI51Ut2zxuMjYYxFSG4zpwXaldJHWD1LMNTGaJssPhcDhmQXbkYoKTUyiEi93rlN8UJ5GB4dJMRlKB1BMUPTAkR5DUTC8rSIEg1t7TKeUm1w1iqpYPC5ukPwFjw1oirEEaTlryk7B/pIFdW2ptebOSfafSs4ORZzrOY3Sj19ZwWS2EFchJpRa3xUDUCFuyL3GoMH1t3m+KfiSiSGTkxIuFRoIK9J+IsXQtXdPGFJ4OLatuWQbbrNswL9Z+Yz0SG1uEPtZEiUVIh+K0JEi8eW9OKLQpPtbXmg/9T4wCZZKRw1ymy8qyREytslPLsUZuWZgsqLhuhpNRQkpwrfbhhNThcDgcJTg5xWg/JVA3qovPVWb0dvyB3qVLfrkxX11GZ10rEFT6XfKAFrMh9OPyiUCVCGpzGpjbUoSigWWkKY2/Fr0t0iAJg5UnfmKwNMymurSMA4svJ0aANlJ69R9eZmXFMQ/4g6tem11LyIOoRN5usgOnWBwKR178SSynTnRslMXbs1w23iq7tuw3i4+8/WsyLK+pKlD52ZfkyfFQElSNmNWgEVOToDbKKsVtJZsmGRb60rNADeNE1OFwOOYdvqx3kSIutzI8ADVvJIDEmkpIBl3rmFdQs75IjOF1k/ckOIGcorhimSipmX4x5A3/ZAaZuMYJqgUrTxaha/GeSiNLypJeTs24n1SHbiW88YRZVhdfO8vJ5M6Mr6y7TCWoHBbJiqspOj0c9aug9J/aWFDCOBNJ46AvSYtkr0v7tUUcTWJaIWmtJE+G0+qOj/U8Tp/nhySmcyGhangRJ+qoXLPC0hhaS6eG2ioAh8PhcOzacHIqYD18W14MPyVIR7IviBHRAVKCqi2jjd/Z9XE8lBLJMjQF1hJeTvjiATmclBaEasRVy1f8PZRlngAcUkMq6jX8PsXKOUtsDpB7NWteDvdg7jrgBLWPhyrer3nKWB+0lgGP462TaDll2FpJQPeylQD8PtJ7U11eTrI8ZHny6xkxrZRjiWxqcVqWxwL1cXUcTIrAaWRTPWU7jMJWhvS0zkJbWS22mX2Hw+FYKJiv4fWSSy7BJz/5SYQQ8JrXvAZvfvOb8ba3vQ1f//rXsfvuu+PQQw/FZz7zGTzzmc8EAFx00UW44oorMD09jf/8n/8zTjvttLHSbXIILnaEMPcPwJY50cOafQbi+iDMLvUdsA8PD/6fxQW712K8yJn+WhTyWNSW5WnpWB/rdSNavmRavHyy+IYuA7S9hkHTXcoZ19PqxHTXw1fWXYavrJutd97X4+8aETI+QD5hZPUZK34Jybgi9MzGIGVckPdkv+ZjHh/rYlgtP/yjpQvl0CxjjLDKwhwPWLo0lgwwO17Th19PlrcaaJncJJ1ax3ZVZ9jPieRZpESW6crybzk8jd/nwcz96g6Hw+GYM+h1hH0+Ndx+++345Cc/iU2bNuEHP/gBrrnmGvz0pz/FmjVrcPvtt+OHP/whnvOc5+Ciiy4CANx555246qqrcMcdd+C6667DG97wBszMzIyVHyenAiUjsfgZPsDJcFGJ2vB6NASQktIBC8u/R93GNFy0PKZfjHIQRgY3PrlB1mIQS2LelzRnckSEVuMvkWMY2/y/RXRLIILi2DXxVVH/k/KASfC+ZvU7fs8igGi419rPs7SDmHyT/a0Qr0ToW05zNvMtxx/5UchYabIuvqfYyEsNc91LzHXOJkfZGC4nBuINLgPpfU7Q6XcSNYi4Ij2Hw+Fw7Jz40Y9+hBe84AVYunQplixZglNOOQVXX301Tj31VCxZMrvw9qSTTsK9994LANiwYQPWrVuHPfbYA4cccghWrlyJTZs2jZW2k1MAt732spEBMuaHGwXRKwp9dp0e6vSPe1BnGgmfRdImaQhLY0OieLKkEqdkbGqeJi2Mdq+3l6FiIGceoOFv8p5IsspnoJyYOgBgw1mX4WtnXdbkaaxBJR/sMyjc09q61jeteyW5pcmpwGRyOfK7ml9BgIpjYeP4UywPpbxqr7/Rvkf9htenYD9g5XMhkSHyX8qf9gyIspSx2yq7Fm9oFkZLF6PnWQ3uPXU4HI7JoBvjU8OqVatw44034uGHH8bjjz+Oa6+9Flu2bEnCfPrTn8bLX/5yAMDWrVtx4IEHxnvLly/H1q1bx8qP7zkVmDO3C6NDMkgWNQJ+6qZsIDHdLn39TKZbQLJPla5lBwphZBgFtM/qByGLy0++B3b4klJo/ICXcdOW96I+6F9PqgEnvrfssSrdc2LqkPj6qy7D7/2NfVhSqc3TfWDYPsc05kPI23brCdW1fkayNXlyMilAf10P16fZ81YgcNlvhZBq90qvWErKI4x0DmH0uiY5DsZ3ASuyM7nG+BSMgak2nkmoWyuGD6ramGrWEztHwSLJNThBdTgcjh2DBx98EKtXr46/zz//fJx//vnx9xFHHIF3vOMdOPXUU/H0pz8dxx13HKanp+P9D37wg1iyZAle/epXT1w3J6dD/MPrLsNxf1U+cZOjZljRAUjx+T38MjP8OgVGUPlBJwHJO1JLJ9Zyw1b7bp3a24cwlsDTyW+y9zMCOQkXSA55UYzXkg7VEyQbjSatXLR61uDE1GHh66+abRsWSeV9l9n7ptfOOrSI38vSoPuGLJlOCyml+HLSSqbZgqY+qpDMVj1jeCNCy7tZOYnrxH0+DkpvqVxhYh1exfVLvreMgzJNJc40e67wyVDpQU2WKBtjMeVhXFLK03M4HA7H+GjdQyqxzz774JZbbimGWb9+PdavXw8AuOCCC7B8+XIAwGc/+1lcc801+Na3voVumPiyZcsSz+q9996LZcuW9VcMvqw3g7VsLu7XCUj2idIMv3aNL/UC+03Ld2fYw10zCCmsqqPxHcr3coZn/1mHFlEQzWjqg5oh2WRosrTnc8K9Tye/+g8vc2LqaAKRVA2l5aOlsLLfyOWXtaW9tbBW+to4Z+2fJ3QYeU01ffjvOO4xZQPyT0nvFmKabLko5F+mpZWdlMnPH7D0ijIN/frC2hqSpCd+8/rIDi4y0glMMJdHdZyFFb9b25rD4XA46piPZb0A8MADDwAAfv7zn+Pqq6/Gq171Klx33XX4yEc+gq997WtYunRpDLt27VpcddVVeOKJJ3D33Xdj8+bNOPHEE8fKj3tOGb7/ustwzH/p975C7VUKBO3dd/ydp3FJFZud5q+caW09mreRLzkj76lJukKalpqv4Z9Sfjn4kt/5WLpFyfY9rAhgy5JhGG6NOvuJvI6+IIK69guvNUmKhswryQghMCIE0jPKw6sncYulnSVkS26H4wa9FqvFoyu9cFoe0ohIlJPjr6Zfco3dqy2t7XuP7pfyLeVo42dGdJXfzVsjjAv0ju2gBrLl0GQsKRH14hMSRn2ONVnqcDgcjgWDV77ylXj44Yex22674dJLL8Uzn/lMvPGNb8QTTzyBNWvWAJg9FOmv/uqvcNRRR+HMM8/EkUceiSVLluDSSy9NlgH3gZPTAlq9CEBqPEbiFEZGBS3fjYbG8Evcs6l4FCgYX95L8eVSXZ4uJ7qcoEq5nbhA719NiLKUHxVoI3DjEFQr7T7epbmiNvHg3lLHXPC1sxZ3+9GWMMd3mnbi9VDsmgXNA1gDHzP6vFpK3g/id/xeGCtb0rBWy2RLaMtqJs+b7CL7nUyIKnpIAk/ezZkwyiPNFcjJkWKemHyS4XtNHQ6HY3KYrzH1xhtvzK799Kc/NcO/+93vxrvf/e45p+vLegV++Hp2cm8F3GCSXgX+6oRk2Rt7eGsGQZYAciOAp5l8LxhTPD2pOw+QvYOwZlwZ9+dKHKWdJWfnJwWrP0dPj/B+BzgxdThq+PqrLsuWMfMxMXrj2DV1HaoY04B0TLWi8LHVerWXBnnfGktjWJZWjGPI0OJy2RoxLY11PN+JV7SUN4zKfxCAmUG6zWQQgMFg9vq2AfDUAHhqZvh9BnhyZvb/E8PvM4NRXqOcQfrZFmbj8zR8aa/D4XA4LDg5VWAZPTKM3GvKj9Cv7rsZ/lENlCygPktN8aThpoWx8lAjqKZMqUMh3XHe4ycJvZZuK/rMKKkrC9lF+Q5Lh8Nh4+uvuiwZK4nAQIx3AYxIIiWg2mFFSRhJVoksiTgWNDLJx8aWCbqYh5DGD2CrZ9jyXylSEtMkfeNDaFmuy0kpfSeyuE0Qym3sQ+SVf/j9RCdW7pGIGvrwcnI4HA7H3DBfe053FJycKrj9DZdlxpQ0FvjsLz3UpZFTI6gkLM7wh5HchCBWCKoFTqqS96waRhCHdUASj58ZTA0Etc9secmLYHmcNQ+Jll4rYXVi6nDMDde86jJc86rLMBjMeuUyYmqRTOU+UB5ruLcURjgZJ9HFuF9DbWyz9qXWJv6aIQhydkifQkrjs4Z5T6OHczCKY+UnLtFF3dCh8NzgcM+pw+FwzB20VaLvZyHD95wakA/N4jvwkJ7bwR/WHdtLJdtCEi8gvgdVvvPF2ovKDz/ptadz+Ie/i5SjGwrX3klYfCejkBuvE0EVG2TpVTOtOnOim90f08hpieYHHzkcc8e1fzTbj07/69emnkY5toT8ACiMbiUTU5zslF4Hk8lhpLQWpihH/C6NlRa5lhN+NWirc2qTg/SdJkEjmWX/tYOMuvhnhOlu9E5XrkN8BY3yDOD1lGyVcHLqcDgcDgH3nBr40RtTQiL3FMXr4n8r5GFEJJcvgeXGQymBvocNlTyo0XtgpKfFtdLQrnOoJFPTpRZnggaOFPXlM52YOhyTBJFUOU5oY6w2FvAxYIDcU2puYwhIxz95TXxiPOTjApT4Wno8nPyuoeaFlK/rGSh50hCQP1sk4onPYlZdWw421Q0nLpUZeGlU0O+uG012LvBJe4fD4dipsNiW9brntAD+AOdeSnkPIpz1rjj+OgX+n75USWbA7ImLBchZabm0d4rd096lInXg3lOhiu4lRV5WXK7UqcXrK70lyb0xiWlpyRrd94OPHI75AfU9y0NKYWqTYE1pKZOJfeKrMrXvfPCTN41lvTXZHHKrR0LIuWxlPA2KwnIMlNGsuimN1/RIaZn11ryyDofD4XC457SAHzPv6Vycc+bDfDh9QYR2CrNLpmoP/+R/h4z8tupbm22vxofhMTDS0r7T4Rma54Jf15ZVzxcxBZyYOhzbA3yvDFCfqGrZS6p5QDVPaXK9omfibS3okI1jIt0sPHJdOOT+UQoYJ+z4d9gnE/MzB0pQ3zU7xM6wT8nhcDh2Rfie010MfP9QHy4U4p9RfH6Pk0yrkWSXpUfWIKbaNQL3ngLpbHvcLyU8paU2bHlQa+AeU18663DsWrjujy7Daf/f7LtQS5Nr3HtXI6aWh1SLoxJMsbJFyqlNxKmO04I305KjvTaMX4hkl6Uhlzpn0QwPaG2Cb5z3t7bIjWHbgjkcDoejgMU2lrrntIJ//H/T/VGtD92W17FkcTDyFmqgvT7a8iu6XyKmPB2+T4v0U1Z+qTPpk9rjGYITU4djVwf3SGbvhxbEVI0vvZTK/SwtZZzV5Iy7QkPOUJf2tpL47ITdTOmcmKr6B+UalUMhL1T+HNMdsGRq9v90V/asltApzy2Hw+FwODS453QOiHsr5e+hV3AQZh/oGmiWnZbzJu8C1fasduwwCU5Gle+ZnhWiChizFMMZ+SmWRrxV8ZZaXgQex0/BdTh2bUTSxK8phLTmLbU4V0ZMDa9ksv3emhzs0jEshPwZkIQX92QY2s9vvbYLhu7S66u9RzrLZyHflL58p3Rxe0lnl6UW1ompw+FwzB8W+jLdvnBy2gDynu7MeMnnXlsNkxySxAgpf3XBXNu/HzTkcDgA4Po/vgxrjHFJI1wWWohpLY5cNSKX9raOe3EIZZGSPfaCiM5I5pqw5NEtjZjKZc5mdhXyW4rDSXowlugWl/UO/xCRX2Q2k8PhcDjmGb6sdxfBt84uE8LkMA32H8KwIrR4bDX7xYmpw+EgaAcz9CGmUQ77QMTnS3Tpdw3Z0loeny+Vhb4clocDCxPHVPnhcYTcZmKqyWXjeetrZ3g58gOZSpDbSawtKBKLYeLX4XA4diS6MT8LGe453YVABLXFi0oIALqhFyB5Dx5G31vgpNThcEhs/OPhwUhdSro4+KF02vUSSkt5gZx0WXsqKRhfRcJ/E5Gc6nTPa5J2xTtqQUbLiGkDLA9qTKPHYUYWJiHD4XA4HI1QJnl3drjndBdEzYtK0GbYiZj2OYraianD4bBw/R9fpnoD+fe4msPw/iXOQhGH3wdGnsAZ4aW0PKDydS4Bs3FnFB0GIj1JaiPY1HULMZ00Sgc9aa8akF7QPoaQLN+BKDeHw+FwODjcc7qLopWgOhwOx3yjdKgPJ3/8kCHr9TAQ9yRBLJEiIp6lg47MiABCl8avHXik3dN431yIHO0B1faeWmlyD3InwlGepIdUcQibxDsEYPOb/BnkcDgck8Aic5w6OXU4HA7HjoX6WhclXOkdoCWyqhLEAuMLLQxRY7CcAJeIKXJPb/F0XPEjDJjcEnPVGKOhC8E6Yb4vNGJae1etw+FwOBy+rNfhcDgcOxR/e85l+ZJduYxXLsMV9zjGIabJUly53lcjU4IoZ8GtdInAFpbWSnT0KjG5mbUSP3pNC7CWM9eS6UMwkwP3AvCzf+deU4fD4ZgU5Lu1Wz4LGe45dTgcDscOh1yWy3/L5+icPG8lIkb3Wl+Bwog0h/ng79jburrZ2WGWZFmvzibiVtxItKUsI41OOdCJiOu4HlXuLXWHqcPhcEweC5xr9oZ7Th0Oh8Oxw3HDuZfZnlOMSFPp9VUSmde04DEF0hnlIO7XHKktoD2b093IG0of1TvK9RzmZSB0K4KXJcqkntLlBxbJFcvkZS2+Qzak/yXudq+pw+FwOApwcupwOByOBYFv/9vLslN2gTIZaoYho/QeOHN5cUjjc1LJX7VVYrLTw0Ra3zvHdZHZkUmo5DLk9+j+9JAw81fkyPeb1t53qunjXlOHw+GYX/A3aCyWZb0Lgpyed9552HfffbFq1ars3kc/+lF0XYeHHnoIABBCwJve9CasXLkSxxxzDG677bYY9sorr8Rhhx2Gww47DFdeeeV209/hcDgck0VGuALz6in7PXsJa0y/lRRXwxYIajdkpppX0jQgDKIsk+KeZwInnuO82qVEcq3wdN+9pg6HY7HDOc3csSDI6bnnnovrrrsuu75lyxZs3LgRBx10ULz2zW9+E5s3b8bmzZtx+eWX4/Wvfz0A4JFHHsGFF16Im2++GZs2bcKFF16IRx99dLvlweFwOBxzx9/92zKB0V4TI79XUXFVti6B1cJmYpkblggox5SIIJONHln2vc/y4pYy0jylcwG9tzYhxu46dTgcuwB2BKcprQCyPgsZC4Kcnnzyydh7772z6295y1vwkY98BB2zBDZs2ICzzz4bXdfhpJNOwmOPPYb77rsP119/PdasWYO9994be+21F9asWaM2DofD4XAsfNQeoC1cRxI/MyEjUbn8KS6J6qNXA4u08iqvFc5ZKmKcZdGl04QtcaXlu3e/2b2mDodj8WNHcBpf1rudsGHDBixbtgzHHntscn3r1q048MAD4+/ly5dj69at5nUNl19+OVavXo3Vq1fjwQcfnJ8MOBwOh2Ms3HhencjM+dlaOFUo7uHh3zudRMoDmgLzkGa81PCeRlmC+Gp7SWOaStqavLmi9MoeGS67ln1xOByOXQ/zyWkWIxbkq2Qef/xxfOhDH8LGjRvnRf7555+P888/HwCwevXqeUnD4XA4HOOjhaA6HA6Hw7GQMd+cBlj4y3T7YkF6Tu+66y7cfffdOPbYY3HwwQfj3nvvxfHHH4///b//N5YtW4YtW7bEsPfeey+WLVtmXnc4HA6Hw+FwOByO7Q3nNP2xID2nRx99NB544IH4++CDD8Ytt9yCZz3rWVi7di0+8YlPYN26dbj55pux55574oADDsBpp52GCy64IG4Y3rhxIy666KJqWvfccw+e/exnY5999pm3/Dh2bTz44IPevhzzBm9fjvmGtzHHfMLbl2O+Mck2ds899/QKP9+c5lnPej5Wr761dz6e9axn9Y6zvbAgyOlZZ52FG264AQ899BCWL1+OCy+8EOvXr1fDnn766bj22muxcuVKLF26FJ/5zGcAAHvvvTfe85734IQTTgAAvPe971U3JEs89NBDWL16NW655ZbJZcjhYPD25ZhPePtyzDe8jTnmE96+HPON7dnGtjenWYyHv3YhTOT15js1fGB0zCe8fTnmE96+HPMNb2OO+YS3L8d8w9vYzoUFuefU4XA4HA6Hw+FwOBy7FpycAvHkXodjPuDtyzGf8PblmG94G3PMJ7x9OeYb3sZ2LviyXofD4XA4HA6Hw+Fw7HC459ThcDgcDofD4XA4HDscuzQ5ve6663D44Ydj5cqVuPjii3e0Oo6dFAcffDCOPvpoHHfccVi9ejUA4JFHHsGaNWtw2GGHYc2aNfE48BAC3vSmN2HlypU45phjcNttt+1I1R0LFOeddx723XdfrFq1Kl4bp01deeWVOOyww3DYYYfhyiuv3O75cCxMaO3rz/7sz7Bs2TIcd9xxOO6443DttdfGexdddBFWrlyJww8/HNdff3287s9Qh4UtW7bgt3/7t3HkkUfiqKOOwiWXXALAxzHHZGC1Lx/HFgnCLopt27aFFStWhLvuuis88cQT4Zhjjgl33HHHjlbLsRPi2c9+dnjwwQeTa29729vCRRddFEII4aKLLgpvf/vbQwghfOMb3wgve9nLwmAwCN/97nfDiSeeuN31dSx8fPvb3w633nprOOqoo+K1vm3q4YcfDoccckh4+OGHwyOPPBIOOeSQ8Mgjj2z/zDgWHLT29b73vS/8x//4H7Owd9xxRzjmmGPC//2//zf87Gc/CytWrAjbtm3zZ6ijiF/84hfh1ltvDSGE8Ktf/Socdthh4Y477vBxzDERWO3Lx7HFgV3Wc7pp0yasXLkSK1aswO67745169Zhw4YNO1otxyLBhg0bcM455wAAzjnnHHz1q1+N188++2x0XYeTTjoJjz32GO67774dqKljIeLkk0/O3mnWt01df/31WLNmDfbee2/stddeWLNmzaJ8H5qjP7T2ZWHDhg1Yt24d9thjDxxyyCFYuXIlNm3a5M9QRxEHHHAAjj/+eADAM57xDBxxxBHYunWrj2OOicBqXxZ8HNu5sMuS061bt+LAAw+Mv5cvX15s2A6Hha7rcOqpp+L5z38+Lr/8cgDA/fffjwMOOAAAsP/+++P+++8H4O3OMT76tilva46++MQnPoFjjjkG5513Xlxu6e3LMVfcc889+Id/+Ae84AUv8HHMMXHw9gX4OLYYsMuSU4djUvjOd76D2267Dd/85jdx6aWX4u/+7u+S+13Xoeu6HaSdYzHC25Rj0nj961+Pu+66C9///vdxwAEH4N//+3+/o1VyLAL88z//M175ylfiYx/7GH7zN38zuefjmGOukO3Lx7HFgV2WnC5btgxbtmyJv++9914sW7ZsB2rk2FlB7WbffffFH/zBH2DTpk3Yb7/94nLd++67D/vuu28M6+3OMQ76tilva44+2G+//TA9PY2pqSm85jWvwaZNmwB4+3KMj6eeegqvfOUr8epXvxqveMUrAPg45pgcrPbl49jOj12WnJ5wwgnYvHkz7r77bjz55JO46qqrsHbt2h2tlmMnw69//Wv80z/9U/y+ceNGrFq1CmvXro2nCl555ZU444wzAABr167F5z73OYQQcNNNN2HPPfeMS5wcjhL6tqnTTjsNGzduxKOPPopHH30UGzduxGmnnbYjs+BYwOB737/yla/Ek3zXrl2Lq666Ck888QTuvvtubN68GSeeeKI/Qx1FhBCwfv16HHHEEXjrW98ar/s45pgErPbl49giwQ49jmkH4xvf+EY47LDDwooVK8IHPvCBHa2OYyfEXXfdFY455phwzDHHhCOPPDK2o4ceeij8zu/8Tli5cmV4yUteEh5++OEQQgiDwSC84Q1vCCtWrAirVq0K3/ve93ak+o4FinXr1oX9998/LFmyJCxbtix86lOfGqtNXXHFFeHQQw8Nhx56aPj0pz+9o7LjWGDQ2tcf/dEfhVWrVoWjjz46/N7v/V74xS9+EcN/4AMfCCtWrAjPec5zwrXXXhuv+zPUYeHGG28MAMLRRx8djj322HDssceGb3zjGz6OOSYCq335OLY40IUQwo4myA6Hw+FwOBwOh8Ph2LWxyy7rdTgcDofD4XA4HA7HwoGTU4fD4XA4HA6Hw+Fw7HA4OXU4HA6Hw+FwOBwOxw6Hk1OHw+FwOBwOh8PhcOxwODl1OBwOh8PhcDgcDscOh5NTh8PhcIyNgw8+GF3X4YYbbojX/uzP/gxd16HrOvybf/NvzLj/6T/9J3Rdh3PPPTe5fs8998T4c9Fj0rrUPuPizjvvxJvf/Ga86EUvwoEHHoinPe1pWLp0KZ773OfijW98I+655x41Hs8bfX7jN34D++67L44//nisX78eX/7yl/HUU0+NrZvD4XA4HNsTS3a0Ag6Hw+FYvPjyl7+M733vezjhhBN2tCpz1uWcc86ZsEaz+Pu//3tccsklOOCAA/Cc5zwH/+pf/Sv80z/9E2677TZceuml+OxnP4trr70WJ598shr/0EMPxQtf+EIAwLZt2/DYY4/hRz/6ET796U/j05/+NJYvX44rrrgCp5566rzo73A4HA7HpODk1OFwOBzzgqVLl+Lxxx/Hu971LvyP//E/dnpdPvvZz05WqSFe+tKX4sc//jEOP/zw5PpTTz2Fd7zjHfjLv/xLnHPOOfjZz36memhf+MIXqrr94z/+I973vvfhv/7X/4qXv/zluPrqq3HGGWfMSx4cDofD4ZgEfFmvw+FwOOYFZ555Jvbff39861vfwn//7//ddTFw8MEHZ8QUAHbbbTd8+MMfxm/8xm/gnnvuwebNm3vJPfzww3HVVVfhrW99KwaDAc455xw89thjE9La4XA4HI7Jw8mpw+FwOOYFT3/60/Ge97wHAPCud70LIQTXpSempqYwNTX7qN5jjz3GknHxxRfjt37rt/DLX/4Sn/rUpyapnsPhcDgcE4WTU4fD4XDMG17zmtfg0EMPxa233oovfelLrksPDAYD/Pmf/zkef/xxHHvssTjooIPGkrPbbrvhzDPPBIAF5zV2OBwOh4PDyanD4XA45g277bYb/vzP/xwA8Kd/+qfYtm2b62Lg0Ucfxbnnnotzzz0XZ5xxBg455BBceOGFOOyww/CFL3xhTicCr169GgBwxx13TEpdh8PhcDgmDienDofD4ZhXrFu3Dscddxw2b96MK664YqfVpfQamd///d+fs26//vWvceWVV+LKK6/E1772Nfz85z/Hcccdhy996Us44ogj5iT7Wc96FgDg4YcfnrOeDofD4XDMF/y0XofD4XDMK7quw0UXXYSXv/zleP/734+zzz4bT3va03Y6XUqvkjn++OPnrNvy5cvjXtj77rsPmzZtwnvf+148//nPx1/8xV/gTW9609iyB4MBAMT9qw6Hw+FwLEQ4OXU4HA7HvONlL3sZTjnlFHz729/GJZdcgne+8507nS7z9SoZDQcccADOOOMMnHzyyTj22GPxlre8BS960YvwvOc9byx5Dz30EABg7733nqSaDofD4XBMFD6F6nA4HI7tgosvvhgA8OEPfxiPPvqo69KAvfbaC2eccQYGgwG++tWvji3n1ltvBQAcffTRE9LM4XA4HI7Jw8mpw+FwOLYLTjrpJPz+7/8+HnvssUgOXZc69tlnHwDAAw88MFb8J598El/84hcBAGvWrJmYXg6Hw+FwTBpOTh0Oh8Ox3fChD30I09PT+PjHP46tW7e6Lg3427/9WwDAYYcdNlb8d73rXbjvvvuw1157Yf369ZNUzeFwOByOicLJqcPhcDi2G4444gicffbZ+D//5//g8ssvd10AfOxjH8OWLVuy67/61a/w9re/Hd/+9rfxjGc8A+vWresl9yc/+QnOOuss/MVf/AWmp6fxuc99Dr/5m785KbUdDofD4Zg4/EAkh8PhcGxXXHjhhfibv/kbPP7449WwJ510knnvgAMOwFe+8pXtpsu5555bvP/+978fBx10UG8dPvaxj+Gtb30rjjzySBx++OHYY489sHXrVnz/+9/Hr371KzzjGc/AVVddhd/6rd9S43/nO9+Jus3MzOCxxx7Dj370I9x1110AgIMOOghXXHEFXvrSl/bWzeFwOByO7Qknpw6Hw+HYrjjwwAPxxje+ER/96EerYW+++Wbz3rOf/eztqsuVV15ZvP/mN795LHL6oQ99CNdffz1uueUW3HDDDfjlL3+JZzzjGTj88MNx6qmn4g1veINJTAHgrrvuikR09913x5577only5dj/fr1OP300/F7v/d72G233Xrr5XA4HA7H9kYX6KVqDofD4XA4HA6Hw+Fw7CD4nlOHw+FwOBwOh8PhcOxwODl1OBwOh8PhcDgcDscOh+85dTgcDodjQvjUpz6F73znO01hn/vc5+Kd73znPGvkcDgcDsfOA99z6nA4HA7HhHDuuedWD04inHLKKbjhhhvmVyGHw+FwOHYiODl1OBwOh8PhcDgcDscOh+85dTgcDofD4XA4HA7HDoeTU4fD4XA4HA6Hw+Fw7HA4OXU4HA6Hw+FwOBwOxw6Hk1OHw+FwOBwOh8PhcOxwODl1OBwOh8PhcDgcDscOh5NTh8PhcDgcDofD4XDscPz/GfEc3Ilalc8AAAAASUVORK5CYII=\n", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "CPU times: user 6.78 s, sys: 808 ms, total: 7.58 s\n", + "Wall time: 2.39 s\n" + ] + } + ], + "source": [ + "%%time\n", + "horizon_despiked = Horizon(horizon.full_matrix, field=horizon.field, name='despiked')\n", + "horizon_despiked.despike(inplace=True)\n", + "horizon_despiked.show(scale=FIGURE_SCALE)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Conclusion\n", + "\n", + "This concludes the `Horizon` tutorial. To sum up, you have learned how to:\n", + "\n", + "- load, inspect and visualize horizons by computing key characteristics (coverage, amount of labeled and non-labeled traces, etc.) and geological attributes (amplitudes, phases, decompositions)\n", + "- apply useful manipulations to horizons as cutting carcasses, holes, and sharp discontinuities\n", + "- cache computed attributes for saving time on repeated actions\n", + "\n", + "In [the next one](./03_Cubeset.ipynb), you will learn how to work with an entire dataset of seismic cubes and horizons!" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3 (ipykernel)", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.8.10" + }, + "widgets": { + "application/vnd.jupyter.widget-state+json": { + "state": { + "4cedc8ae223640208a0acdf8b338aa47": { + "model_module": "@jupyter-widgets/base", + "model_module_version": "1.2.0", + "model_name": "LayoutModel", + "state": {} + }, + "fc0453b4076f4f98bebbe970aa8ac2e5": { + "model_module": "@jupyter-widgets/output", + "model_module_version": "1.0.0", + "model_name": "OutputModel", + "state": { + "layout": "IPY_MODEL_4cedc8ae223640208a0acdf8b338aa47" + } + } + }, + "version_major": 2, + "version_minor": 0 + } + } + }, + "nbformat": 4, + "nbformat_minor": 4 +} diff --git a/tutorials/03_Augmentations.ipynb b/tutorials/03_Augmentations.ipynb new file mode 100644 index 0000000..0d2cfa1 --- /dev/null +++ b/tutorials/03_Augmentations.ipynb @@ -0,0 +1,451 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Augmentations tutorial\n", + "\n", + "This notebook demonstrates how to work with `SeismicDataset`, which is merely a container for `Field` instances, and shows pipeline of loading actual data into batches. You will learn how to:\n", + "\n", + "- organize loads of cubes and horizons into one entity\n", + "- generate points close to one of the horizons in 3D cube space\n", + "- load seismic images and create masks near generated points\n", + "- apply augmentations for both data and labels" + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "metadata": { + "execution": { + "iopub.execute_input": "2022-09-28T15:07:26.838756Z", + "iopub.status.busy": "2022-09-28T15:07:26.838244Z", + "iopub.status.idle": "2022-09-28T15:07:28.546897Z", + "shell.execute_reply": "2022-09-28T15:07:28.546096Z", + "shell.execute_reply.started": "2022-09-28T15:07:26.838629Z" + }, + "tags": [] + }, + "outputs": [], + "source": [ + "# All the necessary imports\n", + "import sys\n", + "import warnings\n", + "warnings.filterwarnings('ignore')\n", + "\n", + "import numpy as np\n", + "\n", + "sys.path.insert(0, '../..')\n", + "sys.path.insert(0, '..')\n", + "from batchflow import D, P, R, FilesIndex, Pipeline\n", + "from seismiqb import SeismicDataset, Horizon, SeismicSampler, plot " + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Seismic Dataset\n", + "\n", + "As was mentioned before, an instance of `SeismicDataset` is merely a container to hold field (cubes, horizons, etc.) together. It is initialized from a dict of cube paths mapped to relative path to horizons (or other labels), and under the hood instances of `SeismicGeometry` are created:" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": { + "execution": { + "iopub.execute_input": "2022-09-28T15:07:28.547973Z", + "iopub.status.busy": "2022-09-28T15:07:28.547827Z", + "iopub.status.idle": "2022-09-28T15:07:29.478843Z", + "shell.execute_reply": "2022-09-28T15:07:29.477598Z", + "shell.execute_reply.started": "2022-09-28T15:07:28.547955Z" + }, + "tags": [] + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Seismic Dataset with 1 field:\n", + " Field `002_M` with processed geometry and labels:\n", + " - labels: [t0_G_anon, t0_M_anon, t0_BV8_anon, t0_B_anon, t0_J1_anon]\n" + ] + } + ], + "source": [ + "index = {'/data/seismic_data/seismic_interpretation/002_M/002_M.sgy': '~/INPUTS/HORIZONS/FINAL/*'}\n", + "\n", + "dataset = SeismicDataset(index=index, labels_class=Horizon)\n", + "\n", + "print(dataset)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "As we can see, now each field knows about its cube and labels, as well as lots of other statistics which you can check in [the very first tutorial on `Geometry`](./01_Geometry.ipynb)." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "The last but not least, sampler. Sampler is an entity that generates points in following format:\n", + "\n", + "- each point is 9-dimensional:\n", + " - the first two entries are indices of the cube and horizons that this point belongs to;\n", + " - the third is an index of axis to make a crop along;\n", + " - the next three are start coordinates of the crop;\n", + " - the last three are end coordinates of the crop;\n", + "- by default, horizons sampler generates points close to the set of the horizons for each cube.\n", + "\n", + "During the model train, we sample points and use it as anchor for crop location, that is cut from actual seismic cube. Method `show_sampled` allows to visualize actually generated crops of data given the shape of desired crops:" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": { + "execution": { + "iopub.execute_input": "2022-09-28T15:07:29.481124Z", + "iopub.status.busy": "2022-09-28T15:07:29.480791Z", + "iopub.status.idle": "2022-09-28T15:07:32.543758Z", + "shell.execute_reply": "2022-09-28T15:07:32.543066Z", + "shell.execute_reply.started": "2022-09-28T15:07:29.481096Z" + }, + "tags": [] + }, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "sampler = SeismicSampler(labels=dataset.labels, crop_shape=(1, 256, 256), mode='horizon')\n", + "\n", + "sampler.show_sampled(scale=0.8)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# CropBatch\n", + "\n", + "All of our research is organized with the help of [**BatchFlow** library](https://github.com/analysiscenter/batchflow), which allows us to:\n", + "\n", + "- define pipelines that set the sequence of actions to be performed on generated batches of data. Each action can be done in a multi-threading or multi-processing way, where different threads/processes work with various individual batch items\n", + "- create complex neural networks with just a few lines of code\n", + "- do hyperparameter research \n", + "\n", + "To load data according to sampler, we:\n", + "- create crop locations, based on generated (sampled) points of desired shape. Note that it does not load anything from disk: only positions are created\n", + "\n", + "- heavy lifting of disk I/O is performed by `load_cubes`, that takes positions (created by `make_locations`) and actually gets seismic data\n", + "\n", + "- `create_masks` action generates segmentation mask for the crop location by adding all of the horizons on it" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": { + "execution": { + "iopub.execute_input": "2022-09-28T15:07:32.544823Z", + "iopub.status.busy": "2022-09-28T15:07:32.544661Z", + "iopub.status.idle": "2022-09-28T15:07:32.570778Z", + "shell.execute_reply": "2022-09-28T15:07:32.570162Z", + "shell.execute_reply.started": "2022-09-28T15:07:32.544802Z" + }, + "tags": [] + }, + "outputs": [], + "source": [ + "demo_pipeline = (\n", + " Pipeline()\n", + " .make_locations(generator=sampler, batch_size=16)\n", + " .load_seismic(dst='images')\n", + " .create_masks(dst='masks', width=5)\n", + ") << dataset\n", + "\n", + "batch = demo_pipeline.next_batch()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "All the created components (`images`, `masks`) can be accessed via dotted notation: `batch.images` and `batch.masks`. Following visualization shows them on separate graphs:" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": { + "execution": { + "iopub.execute_input": "2022-09-28T15:07:32.571675Z", + "iopub.status.busy": "2022-09-28T15:07:32.571544Z", + "iopub.status.idle": "2022-09-28T15:07:33.780341Z", + "shell.execute_reply": "2022-09-28T15:07:33.779411Z", + "shell.execute_reply.started": "2022-09-28T15:07:32.571660Z" + }, + "tags": [] + }, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "batch.plot_roll(n=5, ncols=5, components=[['images', 'masks']])" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "In order to train a robust model, we must diversify our dataset with wealth of data augmentations: that helps to prevent overfitting and make model generalize better to unseen inputs. Many of the augmentations are already implemented as part of `CropBatch`:\n", + "\n", + "* `transpose`: by default, `crop`, `load_cubes`, `create_mask` get data in `(iline, xline, h)` format with `iline` being used as image-channel, yet most of the following augmentations can be computed way more efficiently if the channel axis is the last. Transposing allows us to permute the order before applying augmentations\n", + "* `scale`: as different cubes have different ranges of possible values, it is usually a good idea to transform each of them to a fixed range. Under the hood, minimum and maximum values for each cube are used\n", + "* `additive_noise`, `multiplicative_noise`: modify each entry in `src` by adding zero-mean noise or multiplying by values with mean at 1\n", + "* `rotate`, `scale_2d`: rotate image around its center, zoom in or zoom out of it\n", + "* `cutout_2d`: zero-out patches of first two axes\n", + "* `affine_transform`, `perspective_transform`: change basis to move 3 (4 in case of perspective transform) points to different location \n", + "* `elastic_transform`: slightly jitter the indexing grid of the first two axes of `src`\n", + "* `bandwidth_filter`: keep only desired range of frequences" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": { + "execution": { + "iopub.execute_input": "2022-09-28T15:07:33.781618Z", + "iopub.status.busy": "2022-09-28T15:07:33.781444Z", + "iopub.status.idle": "2022-09-28T15:07:34.105064Z", + "shell.execute_reply": "2022-09-28T15:07:34.104145Z", + "shell.execute_reply.started": "2022-09-28T15:07:33.781596Z" + }, + "tags": [] + }, + "outputs": [], + "source": [ + "keep_coords = ['anoise', 'mnoise', 'cutout', 'bfilter']\n", + "transform_coords = ['rotate', 'scale', 'affine', 'perspective', 'elastic_hard', 'elastic_soft']\n", + "\n", + "# masks will be transformed and [0, 1]-values will be corrupted.\n", + "to_binarize = ['masks_'+item for item in transform_coords]\n", + "\n", + "demo_pipeline = (\n", + " Pipeline()\n", + " # Load data\n", + " .make_locations(generator=sampler, batch_size=16)\n", + " .load_seismic(dst='images')\n", + " .create_masks(dst='masks', width=5)\n", + " .normalize(src='images')\n", + "\n", + " .bandpass_filter(lowcut=50, highcut=60,\n", + " src='images', dst='images_bfilter')\n", + " \n", + " # Images only augmentations:\n", + " .transpose(src=['images', 'masks'], order=(1, 2, 0))\n", + " .additive_noise(scale=0.05,\n", + " src='images', dst='images_anoise')\n", + " .multiplicative_noise(scale=0.05,\n", + " src='images', dst='images_mnoise')\n", + " .cutout_2d(patch_shape=P(R('uniform', 10, 20, size=2)), n_patches=P(R('uniform', 10, 20)),\n", + " src='images', dst='images_cutout')\n", + "\n", + " # Images and masks augmentations: \n", + " .rotate_2d(angle=P(R('uniform', 5, 30)), adjust=True,\n", + " src=['images', 'masks'], dst=['images_rotate', 'masks_rotate'])\n", + " .scale_2d(scale=2,\n", + " src=['images', 'masks'], dst=['images_scale', 'masks_scale'])\n", + " .affine_transform(alpha=P(R('uniform', 0, 30)),\n", + " src=['images', 'masks'], dst=['images_affine', 'masks_affine'])\n", + " .perspective_transform(alpha=P(R('uniform', 0, 30)),\n", + " src=['images', 'masks'], dst=['images_perspective', 'masks_perspective'])\n", + " .elastic_transform(alpha=P(R('uniform', 35, 45)), sigma=P(R('uniform', 4, 4.5)),\n", + " src=['images', 'masks'], dst=['images_elastic_hard', 'masks_elastic_hard'])\n", + " .elastic_transform(alpha=P(R('uniform', 20, 25)), sigma=P(R('uniform', 4, 4.5)),\n", + " src=['images', 'masks'], dst=['images_elastic_soft', 'masks_elastic_soft'])\n", + " \n", + " .transpose(src=None, order=(2, 0, 1))\n", + " .binarize(src=to_binarize)\n", + ") << dataset\n", + "\n", + "batch = demo_pipeline.next_batch()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Seismic data and its augmented counterpart:" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "metadata": { + "execution": { + "iopub.execute_input": "2022-09-28T15:07:34.106167Z", + "iopub.status.busy": "2022-09-28T15:07:34.106012Z", + "iopub.status.idle": "2022-09-28T15:07:34.109780Z", + "shell.execute_reply": "2022-09-28T15:07:34.109150Z", + "shell.execute_reply.started": "2022-09-28T15:07:34.106147Z" + }, + "tags": [] + }, + "outputs": [], + "source": [ + "components = ['images'] + [f'images_{aug}' for aug in keep_coords]" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "metadata": { + "execution": { + "iopub.execute_input": "2022-09-28T15:07:34.110673Z", + "iopub.status.busy": "2022-09-28T15:07:34.110552Z", + "iopub.status.idle": "2022-09-28T15:07:35.248688Z", + "shell.execute_reply": "2022-09-28T15:07:35.247720Z", + "shell.execute_reply.started": "2022-09-28T15:07:34.110658Z" + }, + "tags": [] + }, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "batch.plot_roll(indices=[0], components=components, title=['original'] + keep_coords, ncols=5)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Seismic data with masks painted over it and the augmented counterpart:" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "metadata": { + "execution": { + "iopub.execute_input": "2022-09-28T15:07:35.249949Z", + "iopub.status.busy": "2022-09-28T15:07:35.249776Z", + "iopub.status.idle": "2022-09-28T15:07:35.253727Z", + "shell.execute_reply": "2022-09-28T15:07:35.253149Z", + "shell.execute_reply.started": "2022-09-28T15:07:35.249927Z" + }, + "tags": [] + }, + "outputs": [], + "source": [ + "components = [['images', 'masks']] + [[f'images_{aug}', f'masks_{aug}'] for aug in transform_coords]" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "metadata": { + "execution": { + "iopub.execute_input": "2022-09-28T15:07:35.254797Z", + "iopub.status.busy": "2022-09-28T15:07:35.254646Z", + "iopub.status.idle": "2022-09-28T15:07:37.108691Z", + "shell.execute_reply": "2022-09-28T15:07:37.107738Z", + "shell.execute_reply.started": "2022-09-28T15:07:35.254779Z" + }, + "tags": [] + }, + "outputs": [ + { + "data": { + "image/png": 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\n", 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" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "batch.plot_roll(indices=[0], components=components, ncols=4, title=['original'] + transform_coords)" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3 (ipykernel)", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.8.10" + }, + "widgets": { + "application/vnd.jupyter.widget-state+json": { + "state": { + "68e4e6c362924ad6a8495c6e8a5671a0": { + "model_module": "@jupyter-widgets/base", + "model_module_version": "1.2.0", + "model_name": "LayoutModel", + "state": {} + }, + "acc975c6dc25442d83b2dfb0fcee5c4e": { + "model_module": "@jupyter-widgets/output", + "model_module_version": "1.0.0", + "model_name": "OutputModel", + "state": { + "layout": "IPY_MODEL_68e4e6c362924ad6a8495c6e8a5671a0" + } + } + }, + "version_major": 2, + "version_minor": 0 + } + } + }, + "nbformat": 4, + "nbformat_minor": 4 +} diff --git a/tutorials/05_Synthetic_Generator.ipynb b/tutorials/05_Synthetic_Generator.ipynb new file mode 100644 index 0000000..760109f --- /dev/null +++ b/tutorials/05_Synthetic_Generator.ipynb @@ -0,0 +1,2299 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# `SyntheticGenerator` tutorial" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "This tutorial demonstrates how to generate synthetic seismic along with horizons and faults using `seismiqb`. One can use generated data for training models for horizon/faults detection as well as models of impedance inversion.\n", + "\n", + "By the end of the tutorial you will know two ways of generating synthetic data:\n", + "- chaining methods from `SyntheticGenerator` class\n", + "- running `generate_synthetic` wrapper function\n", + "\n", + "You will also know how to control the parameters of `SyntheticGenerator` methods to generate synthetic slides that suit your needs." + ] + }, + { + "cell_type": "code", + "execution_count": 494, + "metadata": {}, + "outputs": [], + "source": [ + "# All necessary imports\n", + "import sys\n", + "import shutil\n", + "sys.path.insert(0, '..')\n", + "\n", + "from seismiqb import generate_synthetic, SyntheticGenerator, plot, Horizon, Field, SeismicDataset\n", + "from seismiqb.src.geometry.export import make_segy_from_array" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Using `SyntheticGenerator` class" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "In order to create synthetic seismic using `SyntheticGenerator` class one must chain methods for\n", + "\n", + "- generation of a range of velocities\n", + "- generation of velocity-model\n", + "- adding faults (optionaly)\n", + "- making density-model\n", + "- making reflectivity coefficients\n", + "- generation synthetic-model\n", + "- postprocessing synthetic model (optinally)\n", + "\n", + "from a class instance. For reproducibility purposes `SyntheticGenerator` instance can be initiated with a seed:" + ] + }, + { + "cell_type": "code", + "execution_count": 495, + "metadata": {}, + "outputs": [], + "source": [ + "generator = SyntheticGenerator(seed=100)" + ] + }, + { + "cell_type": "code", + "execution_count": 496, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "CPU times: user 54.6 ms, sys: 0 ns, total: 54.6 ms\n", + "Wall time: 51.8 ms\n" + ] + } + ], + "source": [ + "%%time\n", + "generator = (generator.make_velocities(num_reflections=60, horizon_heights=(0.2, 0.3, 0.5, 0.8),\n", + " horizon_multipliers=(-14, 16, -11, 10))\n", + " .make_velocity_model((200, 500), (10, ))\n", + " .add_faults(faults_coordinates=(((100, 100), (120, 220)),\n", + " ((150, 340), (190, 470))), max_shift=13,\n", + " zeros_share=0.2)\n", + " .make_density_model((0.98, 1.02))\n", + " .make_reflectivity()\n", + " .make_synthetic()\n", + " .postprocess_synthetic(noise_mul=0.0))" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "check out generated synthetic along with corresponding velocity model and computed reflectivity coefficients:" + ] + }, + { + "cell_type": "code", + "execution_count": 497, + "metadata": {}, + "outputs": [], + "source": [ + "import numpy as np" + ] + }, + { + "cell_type": "code", + "execution_count": 499, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "plot([generator.synthetic,\n", + " np.maximum(generator.fetch_faults(), generator.fetch_horizons(horizon_format='mask'))], combine='separate',\n", + " label=['Synthetic', 'Faults & horizons'],\n", + " cmap='gray', figsize=(10, 9))" + ] + }, + { + "cell_type": "code", + "execution_count": 500, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "plot([generator.synthetic, generator.velocity_model], combine='separate',\n", + " label=['Synthetic', 'Velocity model'],\n", + " cmap='gray', figsize=(10, 9), colorbar=[False, True])" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Tweaking the parameters of synthetic generation" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### *num_reflections* in `make_velocities`" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "The general \"look\" of a seismic slide is strongly influenced by the number of reflections (layers on velocity model. Increase the value of this parameter to make seismic look more interesting. Do not go overboard with the number of reflections. Default ricker frequency cannot discern large number of small jumps in velocity model. As the result, large number of reflections will only lead to more noise in synthetic:" + ] + }, + { + "cell_type": "code", + "execution_count": 506, + "metadata": {}, + "outputs": [], + "source": [ + "reflections = [10, 30, 50, 100, 200, 300]\n", + "slides = []" + ] + }, + { + "cell_type": "code", + "execution_count": 507, + "metadata": {}, + "outputs": [], + "source": [ + "for num_reflections in reflections:\n", + " generator = (generator.make_velocities(num_reflections=num_reflections,\n", + " horizon_heights=(0.2, 0.3, 0.5, 0.8),\n", + " horizon_multipliers=(-8, 8, -7, 9))\n", + " .make_velocity_model((200, 800), (10, ))\n", + " .make_density_model((.99, 1.01))\n", + " .make_reflectivity()\n", + " .make_synthetic()\n", + " .postprocess_synthetic(noise_mul=0.2))\n", + " slides.append(generator.synthetic)" + ] + }, + { + "cell_type": "code", + "execution_count": 508, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "plot(slides, cmap='gray', combine='separate', figsize=(17, 10),\n", + " label=[f'{num} Reflections' for num in reflections])" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### *horizon_heights* and *horizon_jumps* in `make_velocities`\n", + "\n", + "These two parameters control the number of horizons (sharp, most visible reflections), their heights (in shares of 1) and their magnitide. The magnitide is controlled by multiplier jumps relative to the common difference in velocities between layers. Large negative jumps correspond to black horizons, large positive - to white ones. Pick jumps that are to small - and you won't find any horizons at all (all of the reflections become horizons):" + ] + }, + { + "cell_type": "code", + "execution_count": 509, + "metadata": {}, + "outputs": [], + "source": [ + "heights = [(0.2, 0.5), (0.3, 0.8), (.1, .6), (.2, .4), (.2, .9)]\n", + "magnitudes =[(-2, 2), (-5, 4), (9, -8), (-16, 20), (35, -27)]\n", + "slides = []" + ] + }, + { + "cell_type": "code", + "execution_count": 510, + "metadata": {}, + "outputs": [], + "source": [ + "for hs, magns in zip(heights, magnitudes):\n", + " generator = (generator.make_velocities(num_reflections=100,\n", + " horizon_heights=hs, horizon_multipliers=magns)\n", + " .make_velocity_model((200, 800), (10, ))\n", + " .make_density_model((.97, 1.03))\n", + " .make_reflectivity()\n", + " .make_synthetic()\n", + " .postprocess_synthetic(noise_mul=0.2))\n", + " slides.append(generator.synthetic)" + ] + }, + { + "cell_type": "code", + "execution_count": 511, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "plot(slides, cmap='gray', combine='separate', figsize=(18, 10),\n", + " label=[f'Heights:\\n {hs}\\n Magnitudes:\\n{magns}' for hs, magns in zip(heights, magnitudes)])" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### *density_noise_lims* in `make_density_model`" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "In `SyntheticGenerator` `density_model` is given by `noise * velocity_model`. As the result, you can increase the sharpness of horizons by decreasing noise range. However, go to small (reduce the noise range to `[1, 1]`) and the synthetic will become unrealistically sharp:" + ] + }, + { + "cell_type": "code", + "execution_count": 512, + "metadata": {}, + "outputs": [], + "source": [ + "es = [0.3, 0.2, 0.07, 0.03, 0]\n", + "noise_ranges = [(1 - e, 1 + e) for e in es]\n", + "slides = []" + ] + }, + { + "cell_type": "code", + "execution_count": 513, + "metadata": {}, + "outputs": [], + "source": [ + "for noise_lims in noise_ranges:\n", + " generator = (generator.make_velocities(num_reflections=60,\n", + " horizon_heights=(0.2, 0.3, 0.5, 0.8),\n", + " horizon_multipliers=(-8, 8, -7, 9))\n", + " .make_velocity_model((200, 800), (10, ))\n", + " .make_density_model(density_noise_lims=noise_lims)\n", + " .make_reflectivity()\n", + " .make_synthetic()\n", + " .postprocess_synthetic(noise_mul=0.2)\n", + " )\n", + " slides.append(generator.synthetic)" + ] + }, + { + "cell_type": "code", + "execution_count": 515, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "plot(slides, cmap='gray', combine='separate', figsize=(16, 10),\n", + " label=[f'Noise range:\\n ({1 - e:.3f}, {1 + e:.3f}) ' for e in es])" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### *grid_shape* and *perturbation_share* in `make_velocity_model`" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "To form the layers of velocity model we use horizontal surfaces, randomly perturbed in grid-points. To control the heights' variability of a surface use parameters `grid_shape` and `perturbation_share`.\n", + "\n", + "On one hand, you can make each surface more volatile, increasing the amount of grid-points in which surfaces' heights are sampled. On the other hand, you can achieve more volatility, increasing perturbation range for surfaces' heights in a node. Note that `perturbation_share`-parameter is set in shares of typical distance between subsequent surfaces:" + ] + }, + { + "cell_type": "code", + "execution_count": 326, + "metadata": {}, + "outputs": [], + "source": [ + "grids = [(7, ), (7, ), (7, ), (10, ), (14, ), (18, )]\n", + "perturbations_shares = [.01, .1, .4, .2, .2, .2]\n", + "\n", + "slides = []" + ] + }, + { + "cell_type": "code", + "execution_count": 327, + "metadata": {}, + "outputs": [], + "source": [ + "for grid, share in zip(grids, perturbations_shares):\n", + " generator = (generator.make_velocities(num_reflections=60,\n", + " horizon_heights=(0.2, 0.3, 0.5, 0.8),\n", + " horizon_multipliers=(-8, 8, -7, 9))\n", + " .make_velocity_model((200, 800), grid_shape=grid,\n", + " perturbation_share=share)\n", + " .make_density_model(density_noise_lims=(0.99, 1.01))\n", + " .make_reflectivity()\n", + " .make_synthetic()\n", + " .postprocess_synthetic(noise_mul=0.2))\n", + " slides.append(generator.synthetic)" + ] + }, + { + "cell_type": "code", + "execution_count": 328, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "plot(slides, cmap=['gray'] * len(slides), combine='separate', figsize=(18, 10),\n", + " label=[f'Grid shape:\\n ({grid[0]}, ) \\n Pert share:\\n ({share:.2f}, )'\n", + " for grid, share in zip(grids, perturbations_shares)])" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### `add_faults`-method of `SyntheticGenerator`\n", + "\n", + "To make synthetic more interesting and for training faults' detection models, add faults on a synthetic slide.\n", + "\n", + "For now, faults are only supported for 2d-seismic. The natural way to describe faults is by their coordinates. A fault's location is set by its coordinates `([x0, y0], [x1, y1])`:\n", + "\n", + "```\n", + "coords_of_three_faults = ([(100, 100), (150, 200)],\n", + " [(80, 200), (100, 270)],\n", + " [(150, 300), (130, 400)])\n", + "```\n", + "To make faults more visible, (i) put them close to horizons and (ii) control *max_shift*-parameter. The latter is in depth units and controls how large are the faults:" + ] + }, + { + "cell_type": "code", + "execution_count": 574, + "metadata": {}, + "outputs": [], + "source": [ + "shifts = [1, 5, 15, 25, 40]\n", + "\n", + "slides = []" + ] + }, + { + "cell_type": "code", + "execution_count": 575, + "metadata": {}, + "outputs": [], + "source": [ + "for shift in shifts:\n", + " generator = SyntheticGenerator(seed=90)\n", + " generator = (generator.make_velocities(num_reflections=80, horizon_heights=(0.2, 0.3, 0.5, 0.8),\n", + " horizon_multipliers=(-8, 8, -7, 9))\n", + " .make_velocity_model((200, 800), (10, ))\n", + " .add_faults(faults_coordinates=(((100, 100), (120, 220)),\n", + " ((150, 600), (180, 720))),\n", + " max_shift=shift,\n", + " zeros_share=0.4)\n", + " .make_density_model((.99, 1.01))\n", + " .make_reflectivity()\n", + " .make_synthetic()\n", + " .postprocess_synthetic(noise_mul=0.2))\n", + " slides.append(generator.synthetic)" + ] + }, + { + "cell_type": "code", + "execution_count": 576, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "plot(slides, cmap='gray', combine='separate', figsize=(18, 10),\n", + " label=[f'Max depth-shift\\nin a fault:\\n{shift}' for shift in shifts])" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Note that each fault affects the synthetic the most at its center and the least at its origin point `(x0, y0)` and end point `(x1, y1)`. Use *zeros_share* parameter to control how fast the effect of a fault drops when moving closer to `(x0, y0)` and `(x1, y1)`:" + ] + }, + { + "cell_type": "code", + "execution_count": 591, + "metadata": {}, + "outputs": [], + "source": [ + "zeros_shares = [0.0, 0.1, 0.4, 0.8]\n", + "\n", + "slides = []" + ] + }, + { + "cell_type": "code", + "execution_count": 592, + "metadata": {}, + "outputs": [], + "source": [ + "for zeros_share in zeros_shares:\n", + " generator = SyntheticGenerator(seed=10)\n", + " generator = (generator.make_velocities(num_reflections=80, horizon_heights=(0.2, 0.3, 0.5, 0.8),\n", + " horizon_multipliers=(-8, 8, -7, 9))\n", + " .make_velocity_model((200, 800), (10, ))\n", + " .add_faults(faults_coordinates=(((100, 100), (120, 220)),\n", + " ((150, 600), (180, 720))),\n", + " max_shift=17,\n", + " zeros_share=zeros_share)\n", + " .make_density_model((.99, 1.01))\n", + " .make_reflectivity()\n", + " .make_synthetic()\n", + " .postprocess_synthetic(noise_mul=0.2))\n", + " slides.append(generator.synthetic)" + ] + }, + { + "cell_type": "code", + "execution_count": 593, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "plot(slides, cmap='gray', combine='separate', figsize=(16, 10),\n", + " label=[f'Zeros-share \\nin a fault:\\n{share}' for share in zeros_shares])" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Using `generate_synthetic` wrapper to generate seismic" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "a bit simpler way involves using `generate_synthetic` wrapper function. All parameters need to be supplied at once:" + ] + }, + { + "cell_type": "code", + "execution_count": 533, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "CPU times: user 49 ms, sys: 5.82 ms, total: 54.8 ms\n", + "Wall time: 52.6 ms\n" + ] + } + ], + "source": [ + "%%time\n", + "synthetic, mask, _ = generate_synthetic(shape=(200, 600), grid_shape=10, num_reflections=40,\n", + " horizon_heights=(0.2, 0.3, 0.5, 0.8),\n", + " horizon_multipliers=(-8, 8, -7, 9),\n", + " faults_coordinates=(((100, 100), (120, 220)),\n", + " ((150, 320), (180, 420))),\n", + " zeros_share_faults=0.2, seed=100,\n", + " max_shift=14,\n", + " noise_mul=0.2)" + ] + }, + { + "cell_type": "code", + "execution_count": 534, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "plot([synthetic, mask], combine='separate', cmap=['gray', 'gray'],\n", + " label=['Synthetic slide', 'Reflectivity coefficients'], colorbar=[False, True])" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## `dump` and `load` synthetic cube with `seismiqb`" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Let's create a 3d-synthetic cube" + ] + }, + { + "cell_type": "code", + "execution_count": 553, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "CPU times: user 525 ms, sys: 127 ms, total: 652 ms\n", + "Wall time: 650 ms\n" + ] + } + ], + "source": [ + "%%time\n", + "synt3d, hors, _ = generate_synthetic(shape=(150, 150, 200), grid_shape=(10, 10),\n", + " num_reflections=60,\n", + " geobodies_format=('heights', 'mask'))" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + 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This class allows to generate and augment data that can be readily used in model training +* [The last tutorial](05_Synthetic_Generator.ipynb) previews the capabilities of our synthetic generator, which can be leverage for making roughly realistic data for model training diff --git a/tutorials/plot/01_maps.ipynb b/tutorials/plot/01_maps.ipynb new file mode 100644 index 0000000..ca3ede7 --- /dev/null +++ b/tutorials/plot/01_maps.ipynb @@ -0,0 +1,304 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "tags": [] + }, + "outputs": [], + "source": [ + "%load_ext autoreload\n", + "%autoreload 2" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "tags": [] + }, + "outputs": [], + "source": [ + "import sys\n", + "import numpy as np\n", + "\n", + "sys.path.insert(0, '../../../batchflow')\n", + "sys.path.insert(0, '../../')\n", + "\n", + "from seismiqb import SeismicDataset, HorizonMetrics, SeismicSampler" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "tags": [] + }, + "outputs": [], + "source": [ + "GEOMETRY_PATH = 'cube.blosc'\n", + "HORIZONS_PATH = 'horizons/*'\n", + "\n", + "dataset = SeismicDataset({GEOMETRY_PATH: {'horizons': HORIZONS_PATH}}, interpolate=True)\n", + "print(dataset)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Field attributes" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "tags": [] + }, + "outputs": [], + "source": [ + "field = dataset[0]" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "field.show_points()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "field.geometry.show()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "field.geometry.show_histogram()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "To display several field attributes one over another simply provide them as a list of names.\n", + "\n", + "Plot parameters are passed in the same manner as in `plot`:\n", + "1. If parameter name can be interpreted unequivocally, than pass it \"as is\" (e.g. `'cmap'` is obviously can be meant only for `plt.imshow`).\n", + "\n", + "2. Else, if parameter name might be meant for several annotation methods, put a prefix before it to specify it's destination method
\n", + " (e.g. `'label'` is valid for `plt.title`, `plt.suptitle`, `plt.legend`, so one should provide it as `'leged_label'`). " + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "tags": [] + }, + "outputs": [], + "source": [ + "field.show(attributes=['snr', 'horizons:0/mask'], label=['snr map', 'horizon mask'])" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "To display attributes separately provide `combine='separate'`." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "tags": [] + }, + "outputs": [], + "source": [ + "field.show(['quality_map', 'quality_grid'], combine='separate')" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Horizon attributes" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "tags": [] + }, + "outputs": [], + "source": [ + "horizon = field.horizons[0]" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "One can display horizon attributes by calling `show` directly on `Horizon` instance." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "scrolled": false, + "tags": [] + }, + "outputs": [], + "source": [ + "horizon.show(['depths', 'gradient', 'amplitudes', 'spikes'], combine='separate', bbox=True, ncols=2)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Metrics" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Note that additional arguments for histogram might be provided with `hist_` prefix." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "tags": [] + }, + "outputs": [], + "source": [ + "horizon_metrics = HorizonMetrics([horizon])\n", + "_ = horizon_metrics.evaluate('support_corrs')" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "tags": [] + }, + "outputs": [], + "source": [ + "field.geometry.show()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "tags": [] + }, + "outputs": [], + "source": [ + "field.geometry.show_histogram()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Samplers" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "tags": [] + }, + "outputs": [], + "source": [ + "sampler = SeismicSampler(labels=dataset.horizons, crop_shape=(256, 1, 256), threshold=0.1, mode='horizon')" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "tags": [] + }, + "outputs": [], + "source": [ + "sampler.show_sampled()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "scrolled": false, + "tags": [] + }, + "outputs": [], + "source": [ + "sampler.show_locations()" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3 (ipykernel)", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.9.10" + }, + "widgets": { + "application/vnd.jupyter.widget-state+json": { + "state": { + "d642aa19239e4163a0a8a38834fa39a6": { + "model_module": "@jupyter-widgets/base", + "model_module_version": "1.2.0", + "model_name": "LayoutModel", + "state": {} + }, + "fdc70311f2614e0d97bee06b751ddfdd": { + "model_module": "@jupyter-widgets/output", + "model_module_version": "1.0.0", + "model_name": "OutputModel", + "state": { + "layout": "IPY_MODEL_d642aa19239e4163a0a8a38834fa39a6" + } + } + }, + "version_major": 2, + "version_minor": 0 + } + } + }, + "nbformat": 4, + "nbformat_minor": 4 +} diff --git a/tutorials/plot/02_slides.ipynb b/tutorials/plot/02_slides.ipynb new file mode 100644 index 0000000..2703348 --- /dev/null +++ b/tutorials/plot/02_slides.ipynb @@ -0,0 +1,206 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "tags": [] + }, + "outputs": [], + "source": [ + "%load_ext autoreload\n", + "%autoreload 2" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "import sys\n", + "import numpy as np\n", + "from copy import copy\n", + "\n", + "sys.path.insert(0, '../../../batchflow')\n", + "sys.path.insert(0, '../../')\n", + "\n", + "from seismiqb import SeismicDataset" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "tags": [] + }, + "outputs": [], + "source": [ + "GEOMETRY_PATH = 'cube.blosc'\n", + "HORIZONS_PATH = 'horizons/*'\n", + "\n", + "dataset = SeismicDataset({GEOMETRY_PATH: {'horizons': HORIZONS_PATH}})\n", + "print(dataset)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Slides" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "field = dataset[0]" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "scrolled": false, + "tags": [] + }, + "outputs": [], + "source": [ + "axis = 0\n", + "line = field.shape[axis] // 2\n", + "\n", + "field.show_slide(\n", + " line,\n", + " axis=axis,\n", + " width=10,\n", + " alpha=[1.0, 0.5],\n", + ")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "One can request same slide directly from field." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "tags": [] + }, + "outputs": [], + "source": [ + "field = dataset[0]" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Use `zoom` to focus on specific slide region." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "tags": [] + }, + "outputs": [], + "source": [ + "line_min, line_max = (field.zero_traces.take(line, axis) == 0).nonzero()[0][[0, -1]]\n", + "line_indent = (line_max - line_min) // 4\n", + "line_slice = slice(line_min + line_indent, line_max - line_indent)\n", + "\n", + "line_depths = field.horizons[0].load_attribute('full_matrix', dtype=np.float32).take(line, axis)[line_slice]\n", + "depth_min, depth_max = np.nanmin(line_depths).astype(np.int32), np.nanmax(line_depths).astype(np.int32)\n", + "depth_indent = (depth_max - depth_min) * 4\n", + "depth_slice = slice(depth_min - depth_indent, depth_max + depth_indent)\n", + "\n", + "zoom = (line_slice, depth_slice)\n", + "\n", + "field.show_slide(\n", + " line,\n", + " width=5,\n", + " axis=axis,\n", + " scale=3,\n", + " zoom=zoom,\n", + " alpha=[1.0, 0.5],\n", + ")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "To display seismic data and horizon mask on separate plots, use `combine='separate'`." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "tags": [] + }, + "outputs": [], + "source": [ + "field.show_slide(\n", + " line,\n", + " axis=axis,\n", + " width=5,\n", + " scale=3,\n", + " zoom=zoom,\n", + " combine='separate',\n", + " nrows=2,\n", + ")" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3 (ipykernel)", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.9.10" + }, + "widgets": { + "application/vnd.jupyter.widget-state+json": { + "state": { + "53d386b3bcd74afea7c36e53559dafe2": { + "model_module": "@jupyter-widgets/output", + "model_module_version": "1.0.0", + "model_name": "OutputModel", + "state": { + "layout": "IPY_MODEL_f93b678ea46643f4856ed298ead9c76d" + } + }, + "f93b678ea46643f4856ed298ead9c76d": { + "model_module": "@jupyter-widgets/base", + "model_module_version": "1.2.0", + "model_name": "LayoutModel", + "state": {} + } + }, + "version_major": 2, + "version_minor": 0 + } + } + }, + "nbformat": 4, + "nbformat_minor": 4 +} diff --git a/tutorials/plot/03_hist.ipynb b/tutorials/plot/03_hist.ipynb new file mode 100644 index 0000000..6913d48 --- /dev/null +++ b/tutorials/plot/03_hist.ipynb @@ -0,0 +1,264 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "tags": [] + }, + "outputs": [], + "source": [ + "%load_ext autoreload\n", + "%autoreload 2" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "tags": [] + }, + "outputs": [], + "source": [ + "import sys\n", + "import numpy as np\n", + "\n", + "sys.path.insert(0, '../../../batchflow')\n", + "sys.path.insert(0, '../../')\n", + "\n", + "from seismiqb import SeismicDataset, Horizon" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "tags": [] + }, + "outputs": [], + "source": [ + "GEOMETRY_PATH = 'cube.blosc'\n", + "HORIZONS_PATH = 'horizons/*'\n", + "\n", + "dataset = SeismicDataset({GEOMETRY_PATH: {'horizons': HORIZONS_PATH}}, interpolate=True)\n", + "print(dataset)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "tags": [] + }, + "outputs": [], + "source": [ + "field = dataset[0]\n", + "horizon = field.horizons[0]" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Field attributes" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Use `mode='histogram'` to plot histograms for desired field attributes." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "scrolled": false, + "tags": [] + }, + "outputs": [], + "source": [ + "field.show(\n", + " attributes=[\n", + " 'snr',\n", + " 'horizons:*/depths',\n", + " 'horizons:*/amplitudes',\n", + " 'horizons:*/instant_amplitudes'\n", + " ],\n", + " mode='histogram',\n", + " combine='separate',\n", + " ncols=2\n", + ")" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "tags": [] + }, + "outputs": [], + "source": [ + "field.show(\n", + " attributes=[f'horizons:{i}/depths' for i in range(len(field.horizons))],\n", + " mode='histogram',\n", + " title_pattern='Depths distribution of {label_name}',\n", + " suptitle_size=20, title_size=15, title_wrap_width=100, title_wrap_delimiter=','\n", + ")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Metrics" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Some functions, like `horizon.compare` already use `mode='histogram'` under the hood." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "tags": [] + }, + "outputs": [], + "source": [ + "def gkern(size, sigma):\n", + " x = np.linspace(-(size - 1) / 2., (size - 1) / 2., size)\n", + " gauss = np.exp(-0.5 * np.square(x) / np.square(sigma))\n", + " kernel = np.outer(gauss, gauss)\n", + " return kernel / np.sum(kernel)\n", + "\n", + "def add_horizon_anomalies(horizon):\n", + " shifts = np.zeros(horizon.matrix.shape, dtype=np.int32)\n", + "\n", + " for _ in range(np.random.randint(10, 20)):\n", + " size = np.random.randint(10, 50)\n", + " kernel = gkern(size, size * 0.3)\n", + " kernel = kernel / kernel.max() * np.random.randint(5, 10)\n", + " kernel = np.repeat(kernel, np.random.randint(1,4), axis=np.random.randint(2))\n", + " kernel *= np.random.choice([-1, 1])\n", + "\n", + " i, x, h = horizon.points[np.random.choice(len(horizon))]\n", + " i_start = i - kernel.shape[0] // 2\n", + " i_stop = i_start + kernel.shape[0]\n", + " x_start = x - kernel.shape[1] // 2\n", + " x_stop = x_start + kernel.shape[1]\n", + "\n", + " if (i_start < 0) or (x_start < 0) or (i_stop > shifts.shape[0]) or (x_stop > shifts.shape[1]):\n", + " continue\n", + "\n", + " shifts[i_start : i_stop, x_start : x_stop] += kernel.astype(np.int32)\n", + "\n", + " shifts[horizon.matrix < 0] = horizon.FILL_VALUE\n", + "\n", + " shifted_matrix = horizon.matrix + shifts\n", + " shifted = Horizon(shifted_matrix, horizon.field,\n", + " name=f\"shifted {horizon.name}\", i_min=horizon.i_min, x_min=horizon.x_min)\n", + " \n", + " return shifted" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Note that additional arguments for histogram might be provided with `hist_` prefix." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "tags": [] + }, + "outputs": [], + "source": [ + "anomalous = add_horizon_anomalies(horizon)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "One can provide parameters for those plots histograms via `hist_kwargs`." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "scrolled": false, + "tags": [] + }, + "outputs": [], + "source": [ + "_ = horizon.compare(\n", + " anomalous,\n", + " printer=lambda _: None,\n", + " ignore_zeros=True,\n", + " hist_kwargs=\n", + " {\n", + " 'color': 'lightcoral',\n", + " 'histogram_log': True,\n", + " 'histogram_cumulative': -1,\n", + " 'histogram_histtype': 'step',\n", + " 'histogram_linewidth': 3,\n", + " 'histogram_linestyle': '--',\n", + " 'title': 'Cumulative histogram of horizon depths differences'\n", + " }\n", + ")" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3 (ipykernel)", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.9.10" + }, + "widgets": { + "application/vnd.jupyter.widget-state+json": { + "state": { + "0d898d0fcdd143b5903cf40cbc03ac5a": { + "model_module": "@jupyter-widgets/base", + "model_module_version": "1.2.0", + "model_name": "LayoutModel", + "state": {} + }, + "25fe05ee9b1441f3bcc1d2483459bce1": { + "model_module": "@jupyter-widgets/output", + "model_module_version": "1.0.0", + "model_name": "OutputModel", + "state": { + "layout": "IPY_MODEL_0d898d0fcdd143b5903cf40cbc03ac5a" + } + } + }, + "version_major": 2, + "version_minor": 0 + } + } + }, + "nbformat": 4, + "nbformat_minor": 4 +} diff --git a/tutorials/plot/04_batch.ipynb b/tutorials/plot/04_batch.ipynb new file mode 100644 index 0000000..f470436 --- /dev/null +++ b/tutorials/plot/04_batch.ipynb @@ -0,0 +1,277 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "tags": [] + }, + "outputs": [], + "source": [ + "%load_ext autoreload\n", + "%autoreload 2" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "tags": [] + }, + "outputs": [], + "source": [ + "import sys\n", + "import numpy as np\n", + "\n", + "sys.path.insert(0, '../../../batchflow')\n", + "sys.path.insert(0, '../../')\n", + "\n", + "from seismiqb import SeismicDataset, HorizonMetrics, SeismicSampler\n", + "from batchflow import Pipeline, B" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "tags": [] + }, + "outputs": [], + "source": [ + "GEOMETRY_PATH = 'cube.blosc'\n", + "HORIZONS_PATH = 'horizons/*'\n", + "\n", + "dataset = SeismicDataset({GEOMETRY_PATH: {'horizons': HORIZONS_PATH}}, interpolate=True)\n", + "print(dataset)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "tags": [] + }, + "outputs": [], + "source": [ + "field = dataset[0]\n", + "horizon = field.horizons[0]" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Inline/crossline-oriented slices sampling" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "tags": [] + }, + "outputs": [], + "source": [ + "CROP_SHAPE = (1, 128, 256)\n", + "\n", + "sampler = SeismicSampler(labels=dataset.labels, crop_shape=CROP_SHAPE)\n", + "\n", + "sampler.show_sampled()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "def make_horizons_predictions(batch, q=0.95):\n", + " predictions = []\n", + " for image in batch.images:\n", + " val = np.quantile(image, q)\n", + " prediction = np.zeros_like(image)\n", + " prediction[image > val] = image[image > val] / np.nanmax(image)\n", + " predictions.append(prediction)\n", + " batch.predictions = np.array(predictions, dtype='object')" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "BATCH_SIZE = 32\n", + "\n", + "template = (\n", + " Pipeline()\n", + " .make_locations(generator=sampler, batch_size=BATCH_SIZE)\n", + " .load_cubes(dst='images')\n", + " .create_masks(dst='masks')\n", + " .make_horizons_predictions(B())\n", + ")\n", + "pipeline = template << dataset" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "batch = pipeline.next_batch()\n", + "batch.plot()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "batch.plot(dilate=[None, 1, [None, 1], None, 1])" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Depth-oriented slices sampling" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "CROP_SHAPE = (256, 256, 1)\n", + "\n", + "sampler = SeismicSampler(labels=dataset.labels, crop_shape=CROP_SHAPE, threshold=0., mode='horizon', depth_shift=False)\n", + "\n", + "sampler.show_sampled()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "def make_facies_masks(batch, threshold=0.5):\n", + " masks = []\n", + "\n", + " for image in batch.images:\n", + " val = np.quantile(image, threshold)\n", + " mask = np.zeros_like(image)\n", + " mask = image > val\n", + " masks.append(mask)\n", + "\n", + " batch.masks = np.array(masks)\n", + " \n", + "def make_facies_predictions(batch, threshold=0.6):\n", + " predictions = []\n", + "\n", + " for image in batch.images:\n", + " prediction = np.zeros_like(image)\n", + " val = np.quantile(image, threshold)\n", + " mask = image > val\n", + " min_, max_ = np.nanmin(image[mask]), np.nanmax(image[mask])\n", + " prediction[mask] = (image[mask] - min_) / (max_ - min_)\n", + " predictions.append(prediction)\n", + " \n", + " batch.predictions = np.array(predictions)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "tags": [] + }, + "outputs": [], + "source": [ + "BATCH_SIZE = 32\n", + "\n", + "template = (\n", + " Pipeline()\n", + " .make_locations(generator=sampler, batch_size=BATCH_SIZE)\n", + " .compute_label_attribute(src='horizons:*/amplitudes', dst='images', fill_value=0)\n", + " .make_facies_masks(B())\n", + " .make_facies_predictions(B())\n", + ")\n", + "pipeline = template << dataset" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "batch = pipeline.next_batch()\n", + "plotter = batch.plot()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "scrolled": false, + "tags": [] + }, + "outputs": [], + "source": [ + "batch.plot_roll(n=3)" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3 (ipykernel)", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.9.10" + }, + "vscode": { + "interpreter": { + "hash": "c6e4e9f98eb68ad3b7c296f83d20e6de614cb42e90992a65aa266555a3137d0d" + } + }, + "widgets": { + "application/vnd.jupyter.widget-state+json": { + "state": { + "5705f4ea08ab4e2b9672387f3db22226": { + "model_module": "@jupyter-widgets/base", + "model_module_version": "1.2.0", + "model_name": "LayoutModel", + "state": {} + }, + "bf8427636dc54235882bb1de4ea89adc": { + 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