This is a Python package to help with analysis of the potential impacts of climate hazards and other perils on infrastructure networks.
Install using pip:
pip install nismod-snail
This should bring all dependencies with it. If any of these cause difficulties, try using a conda environment:
conda env create -n snail_env \
python=3.11 geopandas shapely rasterio python-igraph
conda activate snail_env
pip install nismod-snail
If all worked okay, you should be able to run python and import snail:
$ python
>>> import snail
>>> help(snail)
Help on package snail:
NAME
snail - snail - the spatial networks impact assessment library
Once installed, you can use snail
directly from the command line.
Split features on a grid defined by its transform, width and height:
snail split \
--features input.shp \
--transform 1 0 -180 0 -1 90 \
--width 360 \
--height 180 \
--output split.gpkg
Split features on a grid defined by a GeoTIFF, optionally adding the values from each raster band to each split feature as a new attribute:
snail split \
--features lines.geojson \
--raster gridded_data.tif \
--attribute \
--output split_lines_with_raster_values.geojson
Split multiple vector feature files along the grids defined by multiple raster files, attributing all raster values:
snail process -fs features.csv -rs rasters.csv
Where at a minimum, each CSV has a column path
with the path to each file.
A note on transform
- these six numbers define the transform from i,j
cell index (column/row) coordinates in the rectangular grid to x,y
geographic coordinates, in the coordinate reference system of the input and output files. They effectively form the first two rows of a 3x3 matrix:
| x | | a b c | | i |
| y | = | d e f | | j |
| 1 | | 0 0 1 | | 1 |
In cases without shear or rotation, a
and e
define scaling or grid cell size, while c
and f
define the offset or grid upper-left corner:
| x_scale 0 x_offset |
| 0 y_scale y_offset |
| 0 0 1 |
See rasterio/affine
and GDAL Raster Data Model for more documentation.
Clone this repository using GitHub Desktop or on the command line:
git clone git@github.com:nismod/snail.git
Change directory into the root of the project:
cd snail
To create and activate a conda environment with snail's dependencies installed:
conda env create -f environment.yml
conda activate snail-dev
Run this to install the source code as a package:
pip install .
If you're working on snail itself, install it as "editable" along with test and development packages:
pip install -e .[dev]
Run tests using pytest and pytest-cov to check coverage:
pytest --cov=snail --cov-report=term-missing
Run a formatter (black) to fix code formatting:
black src/snail
When working on the tutorial notebooks, it is recommended to install and configure nbstripout so data and outputs are not committed in the notebook files:
nbstripout --install
The C++ library in extension/src
contains the core routines to find intersections of
lines with raster grids.
Before working on the C++ library, fetch source code for Catch2 unit testing library (this is included as a git submodule):
git submodule update --init --recursive
Build the library and run tests:
cmake -Bbuild ./extension
cmake --build build/
./build/run_tests
Run code style auto-formatting:
clang-format -i extension/src/*.{cpp,hpp}
Run lints and checks:
clang-tidy --checks 'cppcoreguidelines-*' extension/src/*.{cpp,hpp}
This may need some includes for pybind11
- which will vary depending on your
python installation. For example, with python via miniconda:
clang-tidy --checks 'cppcoreguidelines-*' extension/src/* -- \
-I/home/username/miniconda3/include/python3.11/ \
-I./pybind11/include/
Or with C++ headers installed on a Linux machine:
clang-tidy --checks 'cppcoreguidelines-*' extension/src/* -- \
-std=c++14 \
-I/usr/include/x86_64-linux-gnu/c++/11 \
-I/usr/include/c++/11 \
-I{$PWD}/extension/extern/pybind11/include \
-I/usr/include/python3.10
The snail.core.intersections
module is built using pybind11
with
scikit-build-core
(see docs)
extension/src/intersections.cpp
defines the module interface using thePYBIND11_MODULE
macropyproject.toml
defines the build requirements for snail, which includes pybind11 and scikit-build-core
MIT License
Copyright (c) 2020-23 Tom Russell and all snail contributors
This library is developed by researchers in the Oxford Programme for Sustainable Infrastructure Systems at the University of Oxford, funded by multiple research projects.
This research received funding from the FCDO Climate Compatible Growth Programme. The views expressed here do not necessarily reflect the UK government's official policies.