Update signal processing configurations and improve event mask handling
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@ -28,7 +28,7 @@ import numpy as np
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import signal_method
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import os
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from matplotlib import pyplot as plt
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os.environ['DISPLAY'] = "localhost:11.0"
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os.environ['DISPLAY'] = "localhost:10.0"
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def process_one_signal(samp_id):
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signal_path = list((org_signal_root_path / f"{samp_id}").glob("OrgBCG_Sync_*.txt"))
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@ -112,7 +112,7 @@ def process_one_signal(samp_id):
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sampling_rate=resp_fs,
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**resp_low_amp_conf
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)
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print(f"resp_low_amp_mask_shape: {resp_low_amp_mask.shape}, num_low_amp: {np.sum(resp_low_amp_mask == 1)}")
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print(f"resp_low_amp_mask_shape: {resp_low_amp_mask.shape}, num_low_amp: {np.sum(resp_low_amp_mask == 1)}, count_low_amp_positions: {len(resp_low_amp_position_list)}")
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else:
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resp_low_amp_mask, resp_low_amp_position_list = None, None
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print("resp_low_amp_mask is None")
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@ -125,7 +125,7 @@ def process_one_signal(samp_id):
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sampling_rate=resp_fs,
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**resp_movement_conf
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)
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print(f"resp_movement_mask_shape: {resp_movement_mask.shape}, num_movement: {np.sum(resp_movement_mask == 1)}")
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print(f"resp_movement_mask_shape: {resp_movement_mask.shape}, num_movement: {np.sum(resp_movement_mask == 1)}, count_movement_positions: {len(resp_movement_position_list)}")
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else:
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resp_movement_mask = None
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print("resp_movement_mask is None")
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@ -137,7 +137,7 @@ def process_one_signal(samp_id):
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signal_data=resp_data,
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movement_mask=resp_movement_mask,
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sampling_rate=resp_fs)
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print(f"amp_change_mask_shape: {resp_amp_change_mask.shape}, num_amp_change: {np.sum(resp_amp_change_mask == 1)}")
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print(f"amp_change_mask_shape: {resp_amp_change_mask.shape}, num_amp_change: {np.sum(resp_amp_change_mask == 1)}, count_amp_change_positions: {len(resp_amp_change_list)}")
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else:
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resp_amp_change_mask = None
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print("amp_change_mask is None")
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@ -151,7 +151,7 @@ def process_one_signal(samp_id):
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sampling_rate=bcg_fs,
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**bcg_low_amp_conf
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)
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print(f"bcg_low_amp_mask_shape: {bcg_low_amp_mask.shape}, num_low_amp: {np.sum(bcg_low_amp_mask == 1)}")
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print(f"bcg_low_amp_mask_shape: {bcg_low_amp_mask.shape}, num_low_amp: {np.sum(bcg_low_amp_mask == 1)}, count_low_amp_positions: {len(bcg_low_amp_position_list)}")
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else:
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bcg_low_amp_mask, bcg_low_amp_position_list = None, None
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print("bcg_low_amp_mask is None")
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@ -163,7 +163,7 @@ def process_one_signal(samp_id):
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sampling_rate=bcg_fs,
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**bcg_movement_conf
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)
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print(f"bcg_movement_mask_shape: {bcg_movement_mask.shape}, num_movement: {np.sum(bcg_movement_mask == 1)}")
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print(f"bcg_movement_mask_shape: {bcg_movement_mask.shape}, num_movement: {np.sum(bcg_movement_mask == 1)}, count_movement_positions: {len(bcg_movement_position_list)}")
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else:
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bcg_movement_mask = None
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print("bcg_movement_mask is None")
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@ -173,7 +173,7 @@ def process_one_signal(samp_id):
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signal_data=bcg_data,
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movement_mask=bcg_movement_mask,
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sampling_rate=bcg_fs)
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print(f"bcg_amp_change_mask_shape: {bcg_amp_change_mask.shape}, num_amp_change: {np.sum(bcg_amp_change_mask == 1)}")
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print(f"bcg_amp_change_mask_shape: {bcg_amp_change_mask.shape}, num_amp_change: {np.sum(bcg_amp_change_mask == 1)}, count_amp_change_positions: {len(bcg_amp_change_list)}")
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else:
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bcg_amp_change_mask = None
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print("bcg_amp_change_mask is None")
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@ -220,4 +220,4 @@ if __name__ == '__main__':
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all_samp_disable_df = utils.read_disable_excel(disable_df_path)
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process_one_signal(select_ids[0])
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process_one_signal(select_ids[2])
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@ -25,7 +25,7 @@ resp_filter:
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resp_low_amp:
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window_size_sec: 30
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stride_sec:
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amplitude_threshold: 5
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amplitude_threshold: 3
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merge_gap_sec: 180
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min_duration_sec: 30
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@ -52,7 +52,7 @@ bcg_filter:
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bcg_low_amp:
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window_size_sec: 1
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stride_sec:
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amplitude_threshold: 10
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amplitude_threshold: 5
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merge_gap_sec: 20
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min_duration_sec: 3
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@ -1,6 +1,6 @@
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from utils.operation_tools import timing_decorator
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import numpy as np
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from utils.operation_tools import merge_short_gaps, remove_short_durations
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from utils import merge_short_gaps, remove_short_durations, event_mask_2_list
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@timing_decorator()
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@ -159,14 +159,10 @@ def detect_movement(signal_data, sampling_rate, window_size_sec=2, stride_sec=No
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movement_mask[start:end+1] = 1
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# raw体动起止位置 [[start, end], [start, end], ...]
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raw_movement_start = np.where(np.diff(np.concatenate([[0], raw_movement_mask])) == 1)[0]
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raw_movement_end = np.where(np.diff(np.concatenate([raw_movement_mask, [0]])) == -1)[0] + 1
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raw_movement_position_list = [[start, end] for start, end in zip(raw_movement_start, raw_movement_end)]
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raw_movement_position_list = event_mask_2_list(raw_movement_mask)
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# merge体动起止位置 [[start, end], [start, end], ...]
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movement_start = np.where(np.diff(np.concatenate([[0], movement_mask])) == 1)[0]
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movement_end = np.where(np.diff(np.concatenate([movement_mask, [0]])) == -1)[0] + 1
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movement_position_list = [[start, end] for start, end in zip(movement_start, movement_end)]
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movement_position_list = event_mask_2_list(movement_mask)
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return raw_movement_mask, movement_mask, raw_movement_position_list, movement_position_list
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@ -201,7 +197,7 @@ def detect_low_amplitude_signal(signal_data, sampling_rate, window_size_sec=1, s
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stride_samples = int(stride_sec * sampling_rate)
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# 确保步长至少为1
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stride_samples = max(1, stride_samples)
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stride_samples = max(sampling_rate, stride_samples)
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# 处理信号边界，使用反射填充
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pad_size = window_samples // 2
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@ -255,9 +251,7 @@ def detect_low_amplitude_signal(signal_data, sampling_rate, window_size_sec=1, s
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low_amplitude_mask = low_amplitude_mask.repeat(stride_sec)[:len(signal_data) // sampling_rate]
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# 低幅值状态起止位置 [[start, end], [start, end], ...]
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low_amplitude_start = np.where(np.diff(np.concatenate([[0], low_amplitude_mask])) == 1)[0]
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low_amplitude_end = np.where(np.diff(np.concatenate([low_amplitude_mask, [0]])) == -1)[0]
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low_amplitude_position_list = [[start, end] for start, end in zip(low_amplitude_start, low_amplitude_end)]
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low_amplitude_position_list = event_mask_2_list(low_amplitude_mask)
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return low_amplitude_mask, low_amplitude_position_list
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@ -1,4 +1,5 @@
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from utils.HYS_FileReader import read_label_csv, read_signal_txt, read_disable_excel
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from utils.operation_tools import load_dataset_conf, generate_disable_mask, generate_event_mask
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from utils.operation_tools import load_dataset_conf, generate_disable_mask, generate_event_mask, event_mask_2_list
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from utils.operation_tools import merge_short_gaps, remove_short_durations
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from utils.event_map import E2N
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from utils.signal_process import butterworth, average_filter, downsample_signal_fast, notch_filter, bessel
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@ -206,3 +206,9 @@ def generate_event_mask(signal_second: int, event_df):
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score_mask[start:end] = row["score"]
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return event_mask, score_mask
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def event_mask_2_list(mask):
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mask_start = np.where(np.diff(mask, append=0) == 1)[0]
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mask_end = np.where(np.diff(mask, append=0) == -1)[0] + 1
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event_list =[[start, end] for start, end in zip(mask_start, mask_end)]
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return event_list
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@ -5,7 +5,6 @@ from scipy import signal, ndimage
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@timing_decorator()
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def butterworth(data, _type, low_cut=0.0, high_cut=0.0, order=10, sample_rate=1000):
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if _type == "lowpass": # 低通滤波处理
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sos = signal.butter(order, low_cut / (sample_rate * 0.5), btype='lowpass', output='sos')
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return signal.sosfiltfilt(sos, np.array(data))
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@ -90,6 +89,7 @@ def downsample_signal_fast(original_signal, original_fs, target_fs, chunk_size=1
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return downsampled_signal
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@timing_decorator()
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def average_filter(raw_data, sample_rate, window_size_sec=20):
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kernel = np.ones(window_size_sec * sample_rate) / (window_size_sec * sample_rate)
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