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Makefile
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Makefile
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FOLDER_PATH= .
SRC_PATH=./src
TEST_PATH=./tests
DATA_PATH=data
EXPORT_PATH=./output
# UTILITIES
# ---------
clean:
rm output/db/*csv
flake8:
. $(FOLDER_PATH)/env/bin/activate; \
flake8 --ignore=E402 src/usecase
flake8_all:
. $(FOLDER_PATH)/env/bin/activate; \
flake8 --ignore=E402 src/ tests/ dags/
test:
. $(FOLDER_PATH)/env/bin/activate; \
pytest -s -vvv $(TEST_PATH)
coverage:
. $(FOLDER_PATH)/env/bin/activate; \
pytest --cov=$(SRC_PATH) --cov-report html $(TEST_PATH)
# FETCH DATA (FOR AIRFLOW PREPROCESSING)
# -------------
fetch_data:
. $(FOLDER_PATH)/env/bin/activate; \
python3 src/usecase/fetch_database.py --data-folder $(DATA_PATH) --export-folder $(EXPORT_PATH)/fetched_data
# PREPROCESSING
# -------------
# (chose between individual files scripts or all candidate scripts)
# PYTHON SCRIPT ON INDIVIDUAL FILES
individual_detect_qrs:
. $(FOLDER_PATH)/env/bin/activate; \
python3 src/usecase/detect_qrs.py --qrs-file-path $(DATA_PATH)/tuh/dev/01_tcp_ar/002/00009578/00009578_s006_t001.edf --method hamilton --exam-id 00009578_s006_t001 --output-folder $(EXPORT_PATH)/individual/res-v0_6
individual_compute_hrvanalysis_features:
. $(FOLDER_PATH)/env/bin/activate; \
python3 src/usecase/compute_hrvanalysis_features.py --rr-intervals-file-path exports/individual/res-v0_6/00009578_s006_t001.csv --output-folder $(EXPORT_PATH)/individual/feats-v0_6
individual_consolidate_feats_and_annot:
. $(FOLDER_PATH)/env/bin/activate; \
python3 src/usecase/consolidate_feats_and_annot.py --features-file-path exports/individual/feats-v0_6/00009578_s006_t001.csv --annotations-file-path $(DATA_PATH)/tuh/dev/01_tcp_ar/002/00009578/00009578_s002_t001.tse_bi --output-folder $(EXPORT_PATH)/individual/cons_v0_6
#WIP
example_ecg_qc:
python3 src/usecase/apply_ecg_qc.py --filepath data/tuh/dev/01_tcp_ar/002/00009578/00009578_s006_t001.edf --output-folder . --sampling-frequency 1000 --exam-id 00009578_s006_t001
# BASH SCRIPT WRAPPING PYTHON SCRIPTS OVER ALL CANDIDATES
bash_detect_qrs:
. $(FOLDER_PATH)/env/bin/activate; \
mkdir -p $(EXPORT_PATH); \
./scripts/bash_pipeline/1_detect_qrs_wrapper.sh -i $(DATA_PATH) -o $(EXPORT_PATH)/res-v0_6
bash_compute_hrvanalysis_features:
. $(FOLDER_PATH)/env/bin/activate; \
./scripts/bash_pipeline/2_compute_hrvanalysis_features_wrapper.sh -i $(EXPORT_PATH)/res-v0_6 -o $(EXPORT_PATH)/feats-v0_6
bash_consolidate_feats_and_annot:
. $(FOLDER_PATH)/env/bin/activate; \
./scripts/bash_pipeline/3_consolidate_feats_and_annot_wrapper.sh -i $(EXPORT_PATH)/feats-v0_6 -a $(DATA_PATH) -o $(EXPORT_PATH)/cons-v0_6
# CREATION OF THE DATASET
# -----------------------
create_ml_dataset:
. $(FOLDER_PATH)/env/bin/activate; \
python3 src/usecase/create_ml_dataset.py --input-folder $(EXPORT_PATH)/cons-v0_6 --output-folder $(EXPORT_PATH)/ml_dataset
# TRAIN OF THE MODEL
# ------------------
train:
. $(FOLDER_PATH)/env/bin/activate; \
python3 src/usecase/train_model.py --ml-dataset-path $(EXPORT_PATH)/ml_dataset/df_ml.csv