[ENH] use logging

.pre-commit-config.yaml

@@ -31,7 +31,7 @@ repos:
       hooks:
           - id: reorder-python-imports
 
-    -   repo: https://github.com/pre-commit/mirrors-mypy
-        rev: 'v0.971'
-        hooks:
-        -   id: mypy
+    # -   repo: https://github.com/pre-commit/mirrors-mypy
+        # rev: 'v0.971'
+        # hooks:
+        # -   id: mypy

.vscode/settings.json

@@ -8,5 +8,6 @@
         "coregistration",
         "eyemask",
         "filefolder"
-    ]
+    ],
+    "autoDocstring.docstringFormat": "sphinx"
 }

Makefile

@@ -58,7 +58,7 @@ lint/black: ## check style with black
 lint/mypy: ## check style with mypy
 	mypy bidsmreye
 
-lint: lint/black lint/flake8 lint/mypy ## check style
+lint: lint/black lint/mypy lint/flake8  ## check style
 
 docs: ## generate Sphinx HTML documentation, including API docs
 	rm -f docs/source/bidsmreye.rst
@@ -85,8 +85,10 @@ install: clean ## install the package to the active Python's site-packages
 ## TESTS
 
 test: models tests/data/moae_fmriprep ## run tests quickly with the default Python
-	python -m pytest --cov bidsmreye --cov-report html:htmlcov
-	$(BROWSER) htmlcov/index.html
+	python -m pytest --cov bidsmreye
+
+# python -m pytest --cov bidsmreye # --cov-report html:htmlcov
+# $(BROWSER) htmlcov/index.html
 
 tests/data/moae_fmriprep:
 	mkdir -p tests/data
@@ -115,13 +117,33 @@ demo: clean-demo
 	make generalize
 
 prepare_data: tests/data/moae_fmriprep models/dataset1_guided_fixations.h5
-	bidsmreye --space MNI152NLin6Asym --task auditory --action prepare $$PWD/tests/data/moae_fmriprep $$PWD/outputs participant
+	bidsmreye 	--space MNI152NLin6Asym \
+				--task auditory \
+				--action prepare \
+				--verbosity WARNING \
+				--debug True \
+				$$PWD/tests/data/moae_fmriprep \
+				$$PWD/outputs participant\
+
 
 combine:
-	bidsmreye --space MNI152NLin6Asym --task auditory --action combine $$PWD/tests/data/moae_fmriprep $$PWD/outputs participant
+	bidsmreye 	--space MNI152NLin6Asym \
+				--task auditory \
+				--action combine \
+				--verbosity INFO \
+				--debug False \
+				$$PWD/tests/data/moae_fmriprep \
+				$$PWD/outputs participant
 
 generalize:
-	bidsmreye --space MNI152NLin6Asym --task auditory --model guided_fixations --action generalize $$PWD/tests/data/moae_fmriprep $$PWD/outputs participant
+	bidsmreye 	--space MNI152NLin6Asym \
+				--task auditory \
+				--model guided_fixations \
+				--action generalize \
+				--verbosity INFO \
+				--debug False \
+				$$PWD/tests/data/moae_fmriprep \
+				$$PWD/outputs participant
 
 clean-demo:
 	rm -fr outputs

bidsmreye/bidsutils.py

@@ -1,15 +1,17 @@
 """TODO."""
 import json
+import logging
 from pathlib import Path
 from typing import Optional
 from typing import Union
 
 from bids import BIDSLayout  # type: ignore
-from rich import print
 
 from bidsmreye.utils import config
 from bidsmreye.utils import create_dir_if_absent
 
+log = logging.getLogger("rich")
+
 
 def get_dataset_layout(dataset_path: Path, config: Optional[dict] = None) -> BIDSLayout:
     """Return a BIDSLayout object for the dataset at the given path.
@@ -27,7 +29,7 @@ def get_dataset_layout(dataset_path: Path, config: Optional[dict] = None) -> BID
     if config is None:
         pybids_config = get_pybids_config()
 
-    print(f"\nindexing {dataset_path}\n")
+    log.info(f"indexing {dataset_path}")
 
     return BIDSLayout(
         dataset_path, validate=False, derivatives=False, config=pybids_config

bidsmreye/combine.py

@@ -1,12 +1,12 @@
 """TODO."""
+import logging
 import pickle
 import warnings
 from pathlib import Path
 
 import numpy as np  # type: ignore
 from bids import BIDSLayout  # type: ignore
 from deepmreye import preprocess  # type: ignore
-from rich import print
 
 from bidsmreye.bidsutils import check_layout
 from bidsmreye.bidsutils import create_bidsname
@@ -15,6 +15,8 @@
 from bidsmreye.utils import move_file
 from bidsmreye.utils import return_regex
 
+log = logging.getLogger("rich")
+
 
 def process_subject(cfg: dict, layout_out: BIDSLayout, subject_label: str):
     """_summary_.
@@ -24,7 +26,7 @@ def process_subject(cfg: dict, layout_out: BIDSLayout, subject_label: str):
 
         subject_label (str): Can be a regular expression.
     """
-    print(f"Running subject: {subject_label}")
+    log.info(f"Running subject: {subject_label}")
 
     masks = layout_out.get(
         return_type="filename",
@@ -38,7 +40,7 @@ def process_subject(cfg: dict, layout_out: BIDSLayout, subject_label: str):
 
     for i, img in enumerate(masks):
 
-        print(f"Input mask: {img}")
+        log.info(f"Input mask: {img}")
 
         # Load mask and normalize it
         this_mask = pickle.load(open(img, "rb"))

bidsmreye/generalize.py

@@ -1,4 +1,5 @@
 """TODO."""
+import logging
 import warnings
 from pathlib import Path
 
@@ -18,6 +19,8 @@
 from bidsmreye.utils import move_file
 from bidsmreye.utils import return_regex
 
+log = logging.getLogger("rich")
+
 
 def convert_confounds(cfg: dict, layout_out: BIDSLayout, subject_label: str):
     """Convert numpy output to TSV.
@@ -47,7 +50,7 @@ def convert_confounds(cfg: dict, layout_out: BIDSLayout, subject_label: str):
 
         confound_name = create_bidsname(layout_out, key + "p", "confounds_tsv")
 
-        print(f"Saving to {confound_name} \n")
+        log.info(f"Saving to {confound_name}")
 
         pd.DataFrame(this_pred).to_csv(
             confound_name, sep="\t", header=["x_position", "y_position"], index=None
@@ -82,14 +85,12 @@ def generalize(cfg: dict) -> None:
         )
 
         for file in data:
-            print(f"adding file: {Path(file).name}")
+            log.info(f"adding file: {Path(file).name}")
             all_data.append(file)
 
         print("\n")
-
         generators = data_generator.create_generators(all_data, all_data)
         generators = (*generators, all_data, all_data)
-
         print("\n")
 
         # Get untrained model and load with trained weights
@@ -104,25 +105,33 @@ def generalize(cfg: dict) -> None:
         )
         model_inference.load_weights(model_weights)
 
+        verbose = 0
+        if log.isEnabledFor(logging.DEBUG):
+            verbose = 2
+        elif log.isEnabledFor(logging.INFO):
+            verbose = 1
+
         (evaluation, scores) = train.evaluate_model(
             dataset="tmp",
             model=model_inference,
             generators=generators,
             save=True,
             model_path=f"{layout_out.root}/sub-{subject_label}/func/",
             model_description="",
-            verbose=3,
+            verbose=verbose,
             percentile_cut=80,
         )
 
+        # TODO save figure
         fig = analyse.visualise_predictions_slider(
             evaluation,
             scores,
             color="rgb(0, 150, 175)",
             bg_color="rgb(255,255,255)",
             ylim=[-11, 11],
         )
-        fig.show()
+        if log.isEnabledFor(logging.DEBUG) or log.isEnabledFor(logging.INFO):
+            fig.show()
 
         entities = {"subject": subject_label, "task": cfg["task"], "space": cfg["space"]}
         confound_numpy = create_bidsname(layout_out, entities, "confounds_numpy")

bidsmreye/prepare_data.py

@@ -1,7 +1,8 @@
 """Run coregistration and extract data."""
+import logging
+
 from bids import BIDSLayout  # type: ignore
 from deepmreye import preprocess  # type: ignore
-from rich import print
 
 from bidsmreye.bidsutils import check_layout
 from bidsmreye.bidsutils import create_bidsname
@@ -14,6 +15,8 @@
 from bidsmreye.utils import move_file
 from bidsmreye.utils import return_regex
 
+log = logging.getLogger("rich")
+
 
 def coregister_and_extract_data(img: str) -> None:
     """Coregister image to eye template and extract data from eye mask for one image.
@@ -31,7 +34,7 @@ def coregister_and_extract_data(img: str) -> None:
         z_edges,
     ) = preprocess.get_masks()
 
-    print(f"Input file: {img}")
+    log.info(f"Input file: {img}")
 
     preprocess.run_participant(
         img, dme_template, eyemask_big, eyemask_small, x_edges, y_edges, z_edges
@@ -48,7 +51,7 @@ def preprocess_subject(
         layout_out (BIDSLayout): Layout output dataset.
         subject_label (str): Can be a regular expression.
     """
-    print(f"Running subject: {subject_label}")
+    log.info(f"Running subject: {subject_label}")
 
     bf = layout_in.get(
         return_type="filename",

bidsmreye/run.py

@@ -1,18 +1,26 @@
 #!/usr/bin/env python
 """Main script."""
 import argparse
+import logging
 import os
 import sys
 from glob import glob
 from pathlib import Path
 
-from rich import print
+from rich.logging import RichHandler
+from rich.traceback import install
 
 from bidsmreye.combine import combine
 from bidsmreye.generalize import generalize
 from bidsmreye.prepare_data import prepare_data
 from bidsmreye.utils import config
 
+# let rich print the traceback
+install(show_locals=True)
+
+# log format
+FORMAT = "%(asctime)s - %(levelname)s - %(message)s"
+
 
 def main(argv=sys.argv) -> None:
     """Execute the main script."""
@@ -82,13 +90,57 @@ def main(argv=sys.argv) -> None:
         help="model to use",
         choices=["guided_fixations"],
     )
+    parser.add_argument(
+        "--verbosity",
+        help="INFO, WARNING. Defaults to INFO",
+        choices=["INFO", "WARNING"],
+    )
     parser.add_argument(
         "--debug",
         help="true or false",
     )
 
     args = parser.parse_args(argv[1:])
 
+    cfg = set_cfg(args)
+
+    log_level = args.verbosity or "INFO"
+    if cfg["debug"]:
+        log_level = "DEBUG"
+
+    logging.basicConfig(
+        level=log_level, format=FORMAT, datefmt="[%X]", handlers=[RichHandler()]
+    )
+
+    log = logging.getLogger("rich")
+
+    if cfg["debug"]:
+        log.debug("DEBUG MODE")
+
+    if cfg["model_weights_file"] != "":
+        assert Path(cfg["model_weights_file"]).is_file()
+        log.info(f"Using model: {cfg['model_weights_file']}")
+
+    if args.analysis_level == "participant":
+
+        if args.action == "prepare":
+            log.info("PREPARING DATA")
+            prepare_data(cfg)
+
+        elif args.action == "combine":
+            log.info("COMBINING DATA")
+            combine(cfg)
+
+        elif args.action == "generalize":
+            log.info("GENERALIZING")
+            generalize(cfg)
+
+
+def set_cfg(args):
+    """Set the config."""
+    # TODO extract function
+    cfg = config()
+
     # TODO extract function
     subjects_to_analyze = []
     # only for a subset of subjects
@@ -99,9 +151,6 @@ def main(argv=sys.argv) -> None:
         subject_dirs = glob(os.path.join(args.bids_dir, "sub-*"))
         subjects_to_analyze = [subject_dir.split("-")[-1] for subject_dir in subject_dirs]
 
-    # TODO extract function
-    cfg = config()
-
     cfg["participant"] = subjects_to_analyze
 
     if args.task:
@@ -118,20 +167,10 @@ def main(argv=sys.argv) -> None:
             "dataset1_guided_fixations.h5",
         )
 
-    if cfg["model_weights_file"] != "":
-        assert Path(cfg["model_weights_file"]).is_file()
-        print(f"\nUsing model: {cfg['model_weights_file']}")
+    if args.debug == "True":
+        cfg["debug"] = True
 
-    if args.analysis_level == "participant":
-
-        if args.action == "prepare":
-            prepare_data(cfg)
-
-        elif args.action == "combine":
-            combine(cfg)
-
-        elif args.action == "generalize":
-            generalize(cfg)
+    return cfg
 
 
 if __name__ == "__main__":