import statistics

from global_var import global_var_init
cycle, fs, record_name, data_path = global_var_init()

from processing import processing
(signal_dwt , waves_dwt , rpeaks , ecg_signal,
 signal, signal.v, signal.fs, rows_to_extract, t_ecg, t_ppg,
 on_column_list, on_column_list_toArea, on_values, on_values_toArea,
 sp_column_list, sp_values, dn_column_list, dn_values, dp_column_list,
 dp_values, u_column_list, u_column_list_toArea, u_values, u_values_toArea,
 v_column_list, v_values, w_column_list, w_values, a_column_list, a_column_list_toArea,
 a_values, a_values_toArea, b_column_list, b_values, c_column_list, c_values,
 e_column_list, e_values, f_column_list, f_values,
 signal.ppg, signal.vpg, signal.apg, signal.jpg) = processing()

from ecg_clean_nan import ecg_clean_nan 
(waves_dwt['ECG_P_Onsets'],waves_dwt['ECG_P_Offsets'],waves_dwt['ECG_T_Onsets'],
 waves_dwt['ECG_T_Offsets'],waves_dwt['ECG_P_Peaks'] ,waves_dwt['ECG_Q_Peaks'],
 rpeaks['ECG_R_Peaks'],waves_dwt['ECG_S_Peaks'],waves_dwt['ECG_T_Peaks']) = ecg_clean_nan()


directory=f"D://python_study//big_boss//doc//points_coordinates_update//{record_name}//ECG//"
data_ECG = {
    'ECG_P_Onsets': waves_dwt['ECG_P_Onsets'],
    'ECG_P_Offsets': waves_dwt['ECG_P_Offsets'],
    'ECG_T_Onsets': waves_dwt['ECG_T_Onsets'],
    'ECG_T_Offsets': waves_dwt['ECG_T_Offsets'],
    'ECG_P_Peaks': waves_dwt['ECG_P_Peaks'],
    'ECG_Q_Peaks': waves_dwt['ECG_Q_Peaks'],
    'ECG_R_Peaks': rpeaks['ECG_R_Peaks'],
    'ECG_S_Peaks': waves_dwt['ECG_S_Peaks'],
    'ECG_T_Peaks': waves_dwt['ECG_T_Peaks']
    
}

from txt_update import update_dict_from_files
data_update_ECG = update_dict_from_files(data_ECG, directory)

#--------------------------------------------------------------------------------------------------------
#--------------------------------------------------------------------------------------------------------
#--------------------------------------------------------------------------------------------------------
#--------------------------------------------------------------------------------------------------------
#------------------------              得到点的横纵坐标及基线          ------------------------------------
#--------------------------------------------------------------------------------------------------------
#--------------------------------------------------------------------------------------------------------
#--------------------------------------------------------------------------------------------------------
#--------------------------------------------------------------------------------------------------------
def ecg_peaks_val():

    P_peaks = data_update_ECG['ECG_P_Peaks']
    P_peaks_values = [ecg_signal[idx] for idx in P_peaks]

    Q_peaks = data_update_ECG['ECG_Q_Peaks']
    Q_peaks_values = [ecg_signal[idx] for idx in Q_peaks]

    R_peaks = data_update_ECG['ECG_R_Peaks']
    R_peaks_values = [ecg_signal[idx] for idx in R_peaks]

    S_peaks = data_update_ECG['ECG_S_Peaks']
    S_peaks_values = [ecg_signal[idx] for idx in S_peaks]

    T_peaks = data_update_ECG['ECG_T_Peaks']
    T_peaks_values = [ecg_signal[idx] for idx in T_peaks]

    P_onsets = data_update_ECG['ECG_P_Onsets']
    P_onsets_values = [ecg_signal[idx] for idx in P_onsets]

    P_offsets = data_update_ECG['ECG_P_Offsets']
    P_offsets_values = [ecg_signal[idx] for idx in P_offsets]

    T_onsets = data_update_ECG['ECG_T_Onsets']
    T_onsets_values = [ecg_signal[idx] for idx in T_onsets]

    T_offsets = data_update_ECG['ECG_T_Offsets']
    T_offsets_values = [ecg_signal[idx] for idx in T_offsets]
    
    # PQ基线
    average_P = statistics.mean(P_peaks_values)
    average_Q = statistics.mean(Q_peaks_values)
    PQ_baseline = (average_P + average_Q) / 2  


    return (#横坐标
            P_peaks, Q_peaks, R_peaks, S_peaks, T_peaks, 
            P_onsets, P_offsets, T_onsets, T_offsets,
            #纵坐标
            P_peaks_values, Q_peaks_values, R_peaks_values, S_peaks_values, T_peaks_values,
            P_onsets_values, P_offsets_values, T_onsets_values, T_offsets_values,
            PQ_baseline)
    

if __name__ == "__main__":
    
    ecg_peaks_val()