64 lines
2.2 KiB
Python
64 lines
2.2 KiB
Python
import numpy as np
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import os
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from scipy.stats import pearsonr
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from global_var import global_var_init
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cycle, fs_ecg, fs_ppg, record_name, record_name_csv, data_path = global_var_init()
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from ecg_peaks_val import ecg_peaks_val
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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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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) = ecg_peaks_val()
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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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num1 = [
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np.diff(P_peaks), np.diff(Q_peaks), np.diff(R_peaks), np.diff(S_peaks), np.diff(T_peaks),
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np.diff(P_onsets), np.diff(P_offsets),
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np.diff(T_onsets), np.diff(T_offsets),
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]
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num2 = [
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np.diff(on), np.diff(sp), np.diff(dn), np.diff(dp),
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np.diff(u), np.diff(v), np.diff(w),
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np.diff(a), np.diff(b), np.diff(c), np.diff(e), np.diff(f),
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]
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# 定义保存的目录
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output_dir = f"D://python_study//big_boss//doc//output//{record_name}"
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# 定义文件名
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filename = f"{record_name}_output_2.txt"
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# 组合目录和文件名
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file_path = os.path.join(output_dir, filename)
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print("正在将相关性系数输出到文本中，请稍后。。。。。")
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# 确保输出目录存在
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os.makedirs(output_dir, exist_ok=True)
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for n1 in num1:
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for n2 in num2:
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# 检查 n1 和 n2 是否是有效的数组
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if isinstance(n1, np.ndarray) and isinstance(n2, np.ndarray) and len(n1) > 1 and len(n2) > 1 and len(n1) == len(n2):
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pearson_corr, _ = pearsonr(n1, n2)
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# 打开文件，追加输出
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with open(file_path, 'a') as f:
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f.write(str(pearson_corr) + '\n')
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else:
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print(f"Skipping invalid arrays: n1={n1}, n2={n2}")
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# 打开文件以进行追加
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with open(file_path, 'a') as f:
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f.write('##########################################' + '\n')
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print("输出完毕！") |