from scipy.stats import pearsonr
import matplotlib.pyplot as plt
import seaborn as sns

from ecg_peaks_val import ecg_peaks_val
(P_peaks, Q_peaks, R_peaks, S_peaks, T_peaks,
P_onsets, P_offsets, T_onsets, T_offsets,
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) = ecg_peaks_val()

from ppg_peaks_val import ppg_peaks_val
(on, on_toArea, sp, dn, dp,
on_values, on_toArea_values, sp_values, dn_values, dp_values,
u, u_toArea, v, w,
u_values, u_toArea_values, v_values, w_values,
a, a_toArea, b, c, e, f,
a_values, a_toArea_values, b_values, c_values, e_values, f_values) = ppg_peaks_val()

from PAT import pat_val
RT_PAT = pat_val()

from ecg_time_interval import compute_interval
intervals_ecg, ratio_pp_tt = compute_interval()

from ppg_time_interval import ppg_time_interval
differences_ppg = ppg_time_interval()


print('on-dn:', differences_ppg['on-dn'])
print('R-T',intervals_ecg['R-T_offset'])
print('RT - PAT :', RT_PAT)

n = len(RT_PAT)
pearsonr_corr_1, p_1 = pearsonr(RT_PAT, differences_ppg['on-dn'])
print("RT - PAT 与 on-dn 的皮尔逊相关系数:", pearsonr_corr_1)
print('p_1:', p_1)

pearsonr_corr_2, p_2 = pearsonr(intervals_ecg['R-T_offset'], differences_ppg['on-dn'])
print("RT 与 on-dn 的皮尔逊相关系数:", pearsonr_corr_2)
print('p_2:', p_2)


# 创建上下两个子图
fig, (ax1, ax2) = plt.subplots(2, 1, figsize=(5, 8))

# —— 图1 ——
sns.regplot(x=intervals_ecg['R-T_offset'], y=differences_ppg['on-dn'],
            scatter_kws={'alpha': 0.7, 'color': 'dodgerblue'},
            line_kws={'color': 'red',
                      'label': f'r={pearsonr_corr_2:.3f}, n={n}, p={p_2:.3f}'},
            ax=ax1)
ax1.set_xlabel('RT')
ax1.set_ylabel('on-dn')
ax1.set_title(rf'$\it r$={pearsonr_corr_2:.3f}, $\it p$={p_2:.3g}, $\it n$={n}')
ax1.legend()
ax1.grid(True, linestyle='--', alpha=0.4)

# —— 图2 ——
sns.regplot(x=RT_PAT, y=differences_ppg['on-dn'],
            scatter_kws={'alpha': 0.7, 'color': 'dodgerblue'},
            line_kws={'color': 'red',
                      'label': f'r={pearsonr_corr_1:.3f}, n={n}, p={p_1:.3f}'},
            ax=ax2)
ax2.set_xlabel('RT-PAT')
ax2.set_ylabel('on-dn')
ax2.set_title(rf'$\it r$={pearsonr_corr_1:.3f}, $\it p$={p_1:.3g}, $\it n$={n}')
ax2.legend()
ax2.grid(True, linestyle='--', alpha=0.4)

plt.tight_layout()
plt.show()