Update signal processing configurations and improve event mask handling

HYS_process.py

@@ -28,7 +28,7 @@ import numpy as np
 import signal_method
 import os
 from matplotlib import pyplot as plt
-os.environ['DISPLAY'] = "localhost:11.0"
+os.environ['DISPLAY'] = "localhost:10.0"
 
 def process_one_signal(samp_id):
     signal_path = list((org_signal_root_path / f"{samp_id}").glob("OrgBCG_Sync_*.txt"))
@@ -112,7 +112,7 @@ def process_one_signal(samp_id):
             sampling_rate=resp_fs,
             **resp_low_amp_conf
         )
-        print(f"resp_low_amp_mask_shape: {resp_low_amp_mask.shape}, num_low_amp: {np.sum(resp_low_amp_mask == 1)}")
+        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)}")
     else:
         resp_low_amp_mask, resp_low_amp_position_list = None, None
         print("resp_low_amp_mask is None")
@@ -125,7 +125,7 @@ def process_one_signal(samp_id):
             sampling_rate=resp_fs,
             **resp_movement_conf
         )
-        print(f"resp_movement_mask_shape: {resp_movement_mask.shape}, num_movement: {np.sum(resp_movement_mask == 1)}")
+        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)}")
     else:
         resp_movement_mask = None
         print("resp_movement_mask is None")
@@ -137,7 +137,7 @@ def process_one_signal(samp_id):
             signal_data=resp_data,
             movement_mask=resp_movement_mask,
             sampling_rate=resp_fs)
-        print(f"amp_change_mask_shape: {resp_amp_change_mask.shape}, num_amp_change: {np.sum(resp_amp_change_mask == 1)}")
+        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)}")
     else:
         resp_amp_change_mask = None
         print("amp_change_mask is None")
@@ -151,7 +151,7 @@ def process_one_signal(samp_id):
             sampling_rate=bcg_fs,
             **bcg_low_amp_conf
         )
-        print(f"bcg_low_amp_mask_shape: {bcg_low_amp_mask.shape}, num_low_amp: {np.sum(bcg_low_amp_mask == 1)}")
+        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)}")
     else:
         bcg_low_amp_mask, bcg_low_amp_position_list = None, None
         print("bcg_low_amp_mask is None")
@@ -163,7 +163,7 @@ def process_one_signal(samp_id):
             sampling_rate=bcg_fs,
             **bcg_movement_conf
         )
-        print(f"bcg_movement_mask_shape: {bcg_movement_mask.shape}, num_movement: {np.sum(bcg_movement_mask == 1)}")
+        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)}")
     else:
         bcg_movement_mask = None
         print("bcg_movement_mask is None")
@@ -173,7 +173,7 @@ def process_one_signal(samp_id):
             signal_data=bcg_data,
             movement_mask=bcg_movement_mask,
             sampling_rate=bcg_fs)
-        print(f"bcg_amp_change_mask_shape: {bcg_amp_change_mask.shape}, num_amp_change: {np.sum(bcg_amp_change_mask == 1)}")
+        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)}")
     else:
         bcg_amp_change_mask = None
         print("bcg_amp_change_mask is None")
@@ -220,4 +220,4 @@ if __name__ == '__main__':
 
     all_samp_disable_df = utils.read_disable_excel(disable_df_path)
 
-    process_one_signal(select_ids[0])
+    process_one_signal(select_ids[2])

dataset_config/HYS_config.yaml

@@ -25,7 +25,7 @@ resp_filter:
 resp_low_amp:
   window_size_sec: 30
   stride_sec:
-  amplitude_threshold: 5
+  amplitude_threshold: 3
   merge_gap_sec: 180
   min_duration_sec: 30
 
@@ -52,7 +52,7 @@ bcg_filter:
 bcg_low_amp:
   window_size_sec: 1
   stride_sec:
-  amplitude_threshold: 10
+  amplitude_threshold: 5
   merge_gap_sec: 20
   min_duration_sec: 3
 

signal_method/rule_base_event.py

@@ -1,6 +1,6 @@
 from utils.operation_tools import timing_decorator
 import numpy as np
-from utils.operation_tools import merge_short_gaps, remove_short_durations
+from utils import merge_short_gaps, remove_short_durations, event_mask_2_list
 
 
 @timing_decorator()
@@ -159,14 +159,10 @@ def detect_movement(signal_data, sampling_rate, window_size_sec=2, stride_sec=No
             movement_mask[start:end+1] = 1
 
     # raw体动起止位置 [[start, end], [start, end], ...]
-    raw_movement_start = np.where(np.diff(np.concatenate([[0], raw_movement_mask])) == 1)[0]
-    raw_movement_end = np.where(np.diff(np.concatenate([raw_movement_mask, [0]])) == -1)[0] + 1
-    raw_movement_position_list = [[start, end] for start, end in zip(raw_movement_start, raw_movement_end)]
+    raw_movement_position_list = event_mask_2_list(raw_movement_mask)
 
     # merge体动起止位置 [[start, end], [start, end], ...]
-    movement_start = np.where(np.diff(np.concatenate([[0], movement_mask])) == 1)[0]
-    movement_end = np.where(np.diff(np.concatenate([movement_mask, [0]])) == -1)[0] + 1
-    movement_position_list = [[start, end] for start, end in zip(movement_start, movement_end)]
+    movement_position_list = event_mask_2_list(movement_mask)
 
     return raw_movement_mask, movement_mask,  raw_movement_position_list, movement_position_list
 
@@ -201,7 +197,7 @@ def detect_low_amplitude_signal(signal_data, sampling_rate, window_size_sec=1, s
     stride_samples = int(stride_sec * sampling_rate)
 
     # 确保步长至少为1
-    stride_samples = max(1, stride_samples)
+    stride_samples = max(sampling_rate, stride_samples)
 
     # 处理信号边界，使用反射填充
     pad_size = window_samples // 2
@@ -255,9 +251,7 @@ def detect_low_amplitude_signal(signal_data, sampling_rate, window_size_sec=1, s
     low_amplitude_mask = low_amplitude_mask.repeat(stride_sec)[:len(signal_data) // sampling_rate]
 
     # 低幅值状态起止位置 [[start, end], [start, end], ...]
-    low_amplitude_start = np.where(np.diff(np.concatenate([[0], low_amplitude_mask])) == 1)[0]
-    low_amplitude_end = np.where(np.diff(np.concatenate([low_amplitude_mask, [0]])) == -1)[0]
-    low_amplitude_position_list = [[start, end] for start, end in zip(low_amplitude_start, low_amplitude_end)]
+    low_amplitude_position_list = event_mask_2_list(low_amplitude_mask)
 
     return low_amplitude_mask, low_amplitude_position_list
 

utils/__init__.py

@@ -1,4 +1,5 @@
 from utils.HYS_FileReader import read_label_csv, read_signal_txt, read_disable_excel
-from utils.operation_tools import load_dataset_conf, generate_disable_mask, generate_event_mask
+from utils.operation_tools import load_dataset_conf, generate_disable_mask, generate_event_mask, event_mask_2_list
+from utils.operation_tools import merge_short_gaps, remove_short_durations
 from utils.event_map import E2N
 from utils.signal_process import butterworth, average_filter, downsample_signal_fast, notch_filter, bessel

utils/operation_tools.py

@@ -206,3 +206,9 @@ def generate_event_mask(signal_second: int, event_df):
         score_mask[start:end] = row["score"]
     return event_mask, score_mask
 
+
+def event_mask_2_list(mask):
+    mask_start = np.where(np.diff(mask, append=0) == 1)[0]
+    mask_end = np.where(np.diff(mask, append=0) == -1)[0] + 1
+    event_list =[[start, end] for start, end in zip(mask_start, mask_end)]
+    return event_list

utils/signal_process.py

@@ -4,8 +4,7 @@ from scipy import signal, ndimage
 
 
 @timing_decorator()
-def butterworth(data, _type, low_cut=0.0, high_cut=0.0, order=10,sample_rate=1000):
-
+def butterworth(data, _type, low_cut=0.0, high_cut=0.0, order=10, sample_rate=1000):
     if _type == "lowpass":  # 低通滤波处理
         sos = signal.butter(order, low_cut / (sample_rate * 0.5), btype='lowpass', output='sos')
         return signal.sosfiltfilt(sos, np.array(data))
@@ -90,6 +89,7 @@ def downsample_signal_fast(original_signal, original_fs, target_fs, chunk_size=1
 
     return downsampled_signal
 
+
 @timing_decorator()
 def average_filter(raw_data, sample_rate, window_size_sec=20):
     kernel = np.ones(window_size_sec * sample_rate) / (window_size_sec * sample_rate)