98 lines
4.1 KiB
Python
98 lines
4.1 KiB
Python
import statistics
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from global_var import global_var_init
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cycle, fs, record_name, data_path = global_var_init()
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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 ecg_clean_nan import ecg_clean_nan
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(waves_dwt['ECG_P_Onsets'],waves_dwt['ECG_P_Offsets'],waves_dwt['ECG_T_Onsets'],
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waves_dwt['ECG_T_Offsets'],waves_dwt['ECG_P_Peaks'] ,waves_dwt['ECG_Q_Peaks'],
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rpeaks['ECG_R_Peaks'],waves_dwt['ECG_S_Peaks'],waves_dwt['ECG_T_Peaks']) = ecg_clean_nan()
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directory=f"D://python_study//big_boss//doc//points_coordinates_update//{record_name}//ECG//"
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data_ECG = {
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'ECG_P_Onsets': waves_dwt['ECG_P_Onsets'],
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'ECG_P_Offsets': waves_dwt['ECG_P_Offsets'],
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'ECG_T_Onsets': waves_dwt['ECG_T_Onsets'],
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'ECG_T_Offsets': waves_dwt['ECG_T_Offsets'],
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'ECG_P_Peaks': waves_dwt['ECG_P_Peaks'],
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'ECG_Q_Peaks': waves_dwt['ECG_Q_Peaks'],
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'ECG_R_Peaks': rpeaks['ECG_R_Peaks'],
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'ECG_S_Peaks': waves_dwt['ECG_S_Peaks'],
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'ECG_T_Peaks': waves_dwt['ECG_T_Peaks']
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}
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from txt_update import update_dict_from_files
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data_update_ECG = update_dict_from_files(data_ECG, directory)
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#--------------------------------------------------------------------------------------------------------
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#--------------------------------------------------------------------------------------------------------
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#--------------------------------------------------------------------------------------------------------
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#--------------------------------------------------------------------------------------------------------
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#------------------------ 得到点的横纵坐标及基线 ------------------------------------
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#--------------------------------------------------------------------------------------------------------
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#--------------------------------------------------------------------------------------------------------
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#--------------------------------------------------------------------------------------------------------
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#--------------------------------------------------------------------------------------------------------
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def ecg_peaks_val():
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P_peaks = data_update_ECG['ECG_P_Peaks']
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P_peaks_values = [ecg_signal[idx] for idx in P_peaks]
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Q_peaks = data_update_ECG['ECG_Q_Peaks']
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Q_peaks_values = [ecg_signal[idx] for idx in Q_peaks]
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R_peaks = data_update_ECG['ECG_R_Peaks']
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R_peaks_values = [ecg_signal[idx] for idx in R_peaks]
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S_peaks = data_update_ECG['ECG_S_Peaks']
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S_peaks_values = [ecg_signal[idx] for idx in S_peaks]
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T_peaks = data_update_ECG['ECG_T_Peaks']
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T_peaks_values = [ecg_signal[idx] for idx in T_peaks]
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P_onsets = data_update_ECG['ECG_P_Onsets']
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P_onsets_values = [ecg_signal[idx] for idx in P_onsets]
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P_offsets = data_update_ECG['ECG_P_Offsets']
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P_offsets_values = [ecg_signal[idx] for idx in P_offsets]
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T_onsets = data_update_ECG['ECG_T_Onsets']
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T_onsets_values = [ecg_signal[idx] for idx in T_onsets]
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T_offsets = data_update_ECG['ECG_T_Offsets']
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T_offsets_values = [ecg_signal[idx] for idx in T_offsets]
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# PQ基线
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average_P = statistics.mean(P_peaks_values)
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average_Q = statistics.mean(Q_peaks_values)
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PQ_baseline = (average_P + average_Q) / 2
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return (#横坐标
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P_peaks, Q_peaks, R_peaks, S_peaks, T_peaks,
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P_onsets, P_offsets, T_onsets, T_offsets,
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#纵坐标
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P_peaks_values, Q_peaks_values, R_peaks_values, S_peaks_values, T_peaks_values,
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P_onsets_values, P_offsets_values, T_onsets_values, T_offsets_values,
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PQ_baseline)
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if __name__ == "__main__":
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ecg_peaks_val()
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