marques
8ee5980906
- Created a new module `utils/__init__.py` to consolidate utility imports. - Added `event_map.py` for mapping apnea event types to numerical values and colors. - Implemented various filtering functions in `filter_func.py`, including Butterworth, Bessel, downsampling, and notch filters. - Developed `operation_tools.py` for dataset configuration loading, event mask generation, and signal processing utilities. - Introduced `split_method.py` for segmenting data based on movement and amplitude criteria. - Added `statistics_metrics.py` for calculating amplitude metrics and generating confusion matrices. - Included a new Excel file for additional data storage.
42 lines
760 B
YAML
42 lines
760 B
YAML
root_path: /mnt/disk_wd/marques_dataset/shhs/polysomnography/shhs1
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mask_save_path: /mnt/disk_code/marques/dataprepare/output/shhs1
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effort_target_fs: 10
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ecg_target_fs: 100
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dataset_config:
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window_sec: 180
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stride_sec: 60
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dataset_save_path: /mnt/disk_wd/marques_dataset/SA_dataset/SHHS1_dataset
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dataset_visual_path: /mnt/disk_wd/marques_dataset/SA_dataset/SHHS1_dataset/visualization
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effort:
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downsample_fs: 10
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effort_filter:
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filter_type: bandpass
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low_cut: 0.05
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high_cut: 0.5
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order: 3
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average_filter:
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window_size_sec: 20
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flow:
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downsample_fs: 10
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flow_filter:
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filter_type: bandpass
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low_cut: 0.05
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high_cut: 0.5
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order: 3
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spo2_fill__anomaly:
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max_fill_duration: 30
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min_gap_duration: 10
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nan_to_num_value: 95
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