64 lines
1.9 KiB
Python
64 lines
1.9 KiB
Python
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from processing import processing
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(signal_dwt , waves_dwt , rpeaks , ecg_signal,
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signal, signal.v, signal.fs, rows_to_extract, t_ecg, t_ppg,
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on_column_list, on_column_list_toArea, on_values, on_values_toArea,
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sp_column_list, sp_values, dn_column_list, dn_values, dp_column_list,
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dp_values, u_column_list, u_column_list_toArea, u_values, u_values_toArea,
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v_column_list, v_values, w_column_list, w_values, a_column_list, a_column_list_toArea,
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a_values, a_values_toArea, b_column_list, b_values, c_column_list, c_values,
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e_column_list, e_values, f_column_list, f_values,
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signal.ppg, signal.vpg, signal.apg, signal.jpg) = processing()
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from ppg_peaks_val import ppg_peaks_val
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(on, on_toArea, sp, dn, dp,
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on_values, on_toArea_values, sp_values, dn_values, dp_values,
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u, u_toArea, v, w,
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u_values, u_toArea_values, v_values, w_values,
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a, a_toArea, b, c, e, f,
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a_values, a_toArea_values, b_values, c_values, e_values, f_values) = ppg_peaks_val()
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def ppg_time_interval():
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# 创建一个字典来存储所有的特征点
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features_ppg_1 = {
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"on": on,
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"sp": sp,
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"dn": dn,
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"dp": dp,
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"u": u,
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"v": v,
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"w": w,
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"a": a,
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"b": b,
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"c": c,
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"e": e,
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"f": f
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}
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# 计算每对特征点之间的间隔
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differences_ppg = {}
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for start_label, start_values in features_ppg_1.items():
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for end_label, end_values in features_ppg_1.items():
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if start_label != end_label:
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difference_label = f"{start_label}-{end_label}"
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# 计算对应位置的间隔
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diffs = [end_val - start_val for start_val, end_val in zip(start_values, end_values)]
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differences_ppg[difference_label] = diffs
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#输出间隔
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# for key, value in differences_ppg.items():
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# print(f" {key}: {value}")
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return differences_ppg
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if __name__ == "__main__":
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ppg_time_interval()
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