184 lines
8.5 KiB
Python
184 lines
8.5 KiB
Python
import matplotlib.pyplot as plt
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import os
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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_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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# 创建一个字典来存储所有的特征点(用于测试)
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features = {
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"P_peaks_values": P_peaks_values,
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"Q_peaks_values": Q_peaks_values,
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"R_peaks_values": R_peaks_values,
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"S_peaks_values": S_peaks_values,
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"T_peaks_values": T_peaks_values,
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"P_onsets_values": P_onsets_values,
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"P_offsets_values": P_offsets_values,
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"T_onsets_values": T_onsets_values,
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"T_offsets_values": T_offsets_values,
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"on_values": on_values,
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"on_toArea_values": on_toArea_values,
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"sp_values": sp_values,
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"dn_values": dn_values,
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"dp_values": dp_values,
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"u_values": u_values,
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"u_toArea_values": u_toArea_values,
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"v_values": v_values,
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"w_values": w_values,
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"a_values": a_values,
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"a_toArea_values": a_toArea_values,
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"b_values": b_values,
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"c_values": c_values,
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"e_values": e_values,
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"f_values": f_values,
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}
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# 遍历 features 字典并打印每个键对应的时间序列长度(用于测试)
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for label, times in features.items():
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print(f"{label}: {len(times)}")
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# 设置保存目录
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save_directory = "D://python_study//big_boss//doc//output"
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# 文件名
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file_name = "coordinates.txt"
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# 文件名及路径
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output_file = os.path.join(save_directory, file_name)
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# 清空文件（如果存在）
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open(output_file, "w").close()
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# 状态变量：是否按下空格键
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space_pressed = False
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def on_key_press(event):
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"""处理键盘按键事件，检查是否按下空格键。"""
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global space_pressed
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if event.key == ' ': # 检查是否按下空格键
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space_pressed = True
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def on_key_release(event):
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"""处理键盘松开事件，松开空格键时取消按下状态。"""
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global space_pressed
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if event.key == ' ': # 检查是否松开空格键
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space_pressed = False
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def onclick(event):
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"""处理鼠标点击事件，记录横坐标到文件，只有在按下空格键时才触发。"""
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global space_pressed
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if event.xdata is not None and space_pressed: # 判断是否按下空格键
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x_coord = int(event.xdata*fs)
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print(f"{x_coord},")
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with open(output_file, "a") as f:
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f.write(f"{x_coord},") # 将横坐标写入文件
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#--------------------------------------------------------------------------------------------------------
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#--------------------------------------------------------------------------------------------------------
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#--------------------------------------------------------------------------------------------------------
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#--------------------------------------------------------------------------------------------------------
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#----------------------------------- 创建绘图函数 ----------------------------------------
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#--------------------------------------------------------------------------------------------------------
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#--------------------------------------------------------------------------------------------------------
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#--------------------------------------------------------------------------------------------------------
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#--------------------------------------------------------------------------------------------------------
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def create_plot_with_draggable_points(save_path = None):
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fig, (ax1, ax2, ax3, ax4) = plt.subplots(4, 1, sharex=True)
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# 绘制归一化后的ECG信号
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ax1.plot(t_ecg, ecg_signal)
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ax1.set(xlabel='', ylabel='ECG')
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# 绘制归一化后的PPG信号
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ax2.plot(t_ppg, signal.ppg)
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ax2.set(xlabel='', ylabel='PPG')
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# 绘制归一化后的一阶导数
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ax3.plot(t_ppg, signal.vpg)
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ax3.set(xlabel='', ylabel='vpg')
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# 绘制归一化后的二阶导数
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ax4.plot(t_ppg, signal.apg)
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ax4.set(xlabel='Time (s)', ylabel='apg')
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# 存储并绘制这些点对象
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points_1 = [ax1.plot(x, y, 'o')[0] for x, y in zip(t_ecg[P_peaks], P_peaks_values)]
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points_1 += [ax1.plot(x, y, 'o', color='cyan')[0] for x, y in zip(t_ecg[Q_peaks], Q_peaks_values)]
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points_1 += [ax1.plot(x, y, 'o', color='purple')[0] for x, y in zip(t_ecg[R_peaks], R_peaks_values)]
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points_1 += [ax1.plot(x, y, 'o', color='blue')[0] for x, y in zip(t_ecg[S_peaks], S_peaks_values)]
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points_1 += [ax1.plot(x, y, 'o', color='black')[0] for x, y in zip(t_ecg[T_peaks], T_peaks_values)]
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points_1 += [ax1.plot(x, y, 'x', color='red')[0] for x, y in zip(t_ecg[P_onsets], P_onsets_values)]
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points_1 += [ax1.plot(x, y, 'x', color='magenta')[0] for x, y in zip(t_ecg[P_offsets], P_offsets_values)]
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points_1 += [ax1.plot(x, y, 'x', color='black')[0] for x, y in zip(t_ecg[T_onsets], T_onsets_values)]
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points_1 += [ax1.plot(x, y, 'o', color='red')[0] for x, y in zip(t_ecg[T_offsets], T_offsets_values)]
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points_2 = [ax2.plot(x, y, 'o', color='red')[0] for x, y in zip(t_ppg[on], on_values)]
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points_2 += [ax2.plot(x, y, 'o', color='blue')[0] for x, y in zip(t_ppg[sp], sp_values)]
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points_2 += [ax2.plot(x, y, 'x', color='orange')[0] for x, y in zip(t_ppg[dn], dn_values)]
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points_2 += [ax2.plot(x, y, 'o', color='purple')[0] for x, y in zip(t_ppg[dp], dp_values)]
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points_3 = [ax3.plot(x, y, 'o', color='cyan')[0] for x, y in zip(t_ppg[u], u_values)]
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points_3 += [ax3.plot(x, y, 'o', color='magenta')[0] for x, y in zip(t_ppg[v], v_values)]
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points_3 += [ax3.plot(x, y, 'o', color='black')[0] for x, y in zip(t_ppg[w], w_values)]
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points_4 = [ax4.plot(x, y, 'o', color='black')[0] for x, y in zip(t_ppg[a], a_values)]
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points_4 += [ax4.plot(x, y, 'o', color='blue')[0] for x, y in zip(t_ppg[b], b_values)]
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points_4 += [ax4.plot(x, y, 'o', color='green')[0] for x, y in zip(t_ppg[c], c_values)]
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points_4 += [ax4.plot(x, y, 'o', color='orange')[0] for x, y in zip(t_ppg[e], e_values)]
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points_4 += [ax4.plot(x, y, 'o', color='purple')[0] for x, y in zip(t_ppg[f], f_values)]
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# 绑定事件
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fig.canvas.mpl_connect('button_press_event', onclick)
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fig.canvas.mpl_connect('key_press_event', on_key_press)
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fig.canvas.mpl_connect('key_release_event', on_key_release)
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# 如果指定了保存路径，则保存图像
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if save_path:
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plt.savefig(save_path)
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plt.tight_layout()
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plt.show()
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# 将图形嵌入到 Qt 的 canvas 中
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# canvas.figure = fig
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# canvas.draw()
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#--------------------------------------------------------------------------------------------------------
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#--------------------------------------------------------------------------------------------------------
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#--------------------------------------------------------------------------------------------------------
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#--------------------------------------------------------------------------------------------------------
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#----------------------------------- 调用绘图函数 ----------------------------------------
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#--------------------------------------------------------------------------------------------------------
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#--------------------------------------------------------------------------------------------------------
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#--------------------------------------------------------------------------------------------------------
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#--------------------------------------------------------------------------------------------------------
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if __name__ == '__main__':
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create_plot_with_draggable_points()
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