73 lines
2.4 KiB
Python
73 lines
2.4 KiB
Python
from scipy.stats import pearsonr
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import matplotlib.pyplot as plt
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import seaborn as sns
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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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from PAT import pat_val
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RT_PAT = pat_val()
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from ecg_time_interval import compute_interval
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intervals_ecg, ratio_pp_tt = compute_interval()
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from ppg_time_interval import ppg_time_interval
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differences_ppg = ppg_time_interval()
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print('on-dn:', differences_ppg['on-dn'])
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print('R-T',intervals_ecg['R-T_offset'])
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print('RT - PAT :', RT_PAT)
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n = len(RT_PAT)
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pearsonr_corr_1, p_1 = pearsonr(RT_PAT, differences_ppg['on-dn'])
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print("RT - PAT 与 on-dn 的皮尔逊相关系数:", pearsonr_corr_1)
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print('p_1:', p_1)
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pearsonr_corr_2, p_2 = pearsonr(intervals_ecg['R-T_offset'], differences_ppg['on-dn'])
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print("RT 与 on-dn 的皮尔逊相关系数:", pearsonr_corr_2)
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print('p_2:', p_2)
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# 创建上下两个子图
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fig, (ax1, ax2) = plt.subplots(2, 1, figsize=(5, 8))
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# —— 图1 ——
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sns.regplot(x=intervals_ecg['R-T_offset'], y=differences_ppg['on-dn'],
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scatter_kws={'alpha': 0.7, 'color': 'dodgerblue'},
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line_kws={'color': 'red',
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'label': f'r={pearsonr_corr_2:.3f}, n={n}, p={p_2:.3f}'},
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ax=ax1)
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ax1.set_xlabel('RT')
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ax1.set_ylabel('on-dn')
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ax1.set_title(rf'$\it r$={pearsonr_corr_2:.3f}, $\it p$={p_2:.3g}, $\it n$={n}')
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ax1.legend()
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ax1.grid(True, linestyle='--', alpha=0.4)
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# —— 图2 ——
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sns.regplot(x=RT_PAT, y=differences_ppg['on-dn'],
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scatter_kws={'alpha': 0.7, 'color': 'dodgerblue'},
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line_kws={'color': 'red',
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'label': f'r={pearsonr_corr_1:.3f}, n={n}, p={p_1:.3f}'},
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ax=ax2)
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ax2.set_xlabel('RT-PAT')
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ax2.set_ylabel('on-dn')
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ax2.set_title(rf'$\it r$={pearsonr_corr_1:.3f}, $\it p$={p_1:.3g}, $\it n$={n}')
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ax2.legend()
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ax2.grid(True, linestyle='--', alpha=0.4)
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plt.tight_layout()
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plt.show()
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