240 lines
12 KiB
Python
240 lines
12 KiB
Python
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import numpy as np
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from matplotlib import pyplot as plt
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plt.rcParams['font.sans-serif'] = ['SimSun'] # 使用宋体
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plt.rcParams['axes.unicode_minus'] = False # 正常显示负号
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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 = 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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#--------------------------------------------------------------------------------------------------------
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#--------------------------------------------------------------------------------------------------------
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#--------------------------------------------------------------------------------------------------------
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#--------------------------------------------------------------------------------------------------------
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#----------------------------------- 创建拖动类 ----------------------------------------
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#--------------------------------------------------------------------------------------------------------
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#--------------------------------------------------------------------------------------------------------
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#--------------------------------------------------------------------------------------------------------
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#--------------------------------------------------------------------------------------------------------
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class DraggablePoints:
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def __init__(self, ax, points, signal_type, signal_name):
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self.ax = ax
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self.points = points # 这里是 Line2D 对象的列表
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self.signal_type = signal_type
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self.signal_name = signal_name
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self.selected_point = None
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self.press = None
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self.new_x = None
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self.real_y = None # 最终获得的点，其纵坐标数值应在信号线上
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self.point_x = None
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# 连接鼠标事件
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self.cidpress = ax.figure.canvas.mpl_connect('button_press_event', self.on_press)
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self.cidmotion = ax.figure.canvas.mpl_connect('motion_notify_event', self.on_motion)
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self.cidrelease = ax.figure.canvas.mpl_connect('button_release_event', self.on_release)
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def on_press(self, event):
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if self.ax == event.inaxes:
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for point in self.points:
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point_x = point.get_xdata()
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point_y = point.get_ydata()
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distance = np.hypot(point_x - event.xdata, point_y - event.ydata)
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if distance < 0.05: # 可以根据需要调整这个阈值
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self.selected_point = point
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self.point_x = point.get_xdata()
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self.point_y = point.get_ydata()
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self.press = (point_x, point_y, event.xdata, event.ydata)
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break
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def on_motion(self, event):
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if self.selected_point is None or event.inaxes != self.ax:
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return
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if self.signal_name == "ECG":
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# 计算点的新的位置
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self.new_x = self.press[0] + (event.xdata - self.press[2])
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self.real_y = self.signal_type[int(self.new_x*fs_ecg)]
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self.real_y = np.array([self.real_y]) #格式转换，从float64 转换成了 ndarray，为了set_data（）能读取
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# 更新选中点的位置
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self.selected_point.set_data(self.new_x, self.real_y)
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self.ax.figure.canvas.draw() # 使用 draw 更新
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else :
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# 计算点的新的位置
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self.new_x = self.press[0] + (event.xdata - self.press[2])
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self.real_y = self.signal_type[int(self.new_x*fs_ppg)]
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self.real_y = np.array([self.real_y]) #格式转换，从float64 转换成了 ndarray，为了set_data（）能读取
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# 更新选中点的位置
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self.selected_point.set_data(self.new_x, self.real_y)
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self.ax.figure.canvas.draw() # 使用 draw 更新
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def on_release(self, event):
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if self.selected_point:
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if self.signal_name == "ECG":
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print(" 点所属的信号 ：",self.signal_name)
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print(" 点的坐标(t) ：",self.point_x, self.point_y)
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print(" 更新后点坐标(t) ：",np.round(self.new_x, 3) , "[", self.real_y, "]" )
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print(" 点的位置 : ",int(self.point_x*fs_ecg))
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print(" 更新后点的位置 ：",int(self.new_x*fs_ecg) )
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print("------------------------------------------")
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else:
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print(" 点所属的信号 ：",self.signal_name)
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print(" 点的坐标(t) ：",self.point_x, self.point_y)
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print(" 更新后点坐标(t) ：",np.round(self.new_x, 3) , "[", self.real_y, "]" )
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print(" 点的位置 : ",int(self.point_x*fs_ppg))
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print(" 更新后点的位置 ：",int(self.new_x*fs_ppg) )
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print("------------------------------------------")
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self.selected_point = None
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self.press = None
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self.new_x = None
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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, 'x', color='gold')[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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draggable_points_1 = DraggablePoints(ax1, points_1, ecg_signal, signal_name = "ECG")
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draggable_points_2 = DraggablePoints(ax2, points_2, signal.ppg, signal_name = "PPG")
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draggable_points_3 = DraggablePoints(ax3, points_3, signal.vpg, signal_name = "VPG")
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draggable_points_4 = DraggablePoints(ax4, points_4, signal.apg, signal_name = "APG")
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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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print(len(P_peaks))
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print(len(Q_peaks))
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print(len(R_peaks))
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print(len(S_peaks))
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print(len(T_peaks))
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print(len(P_onsets))
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print(len(P_offsets))
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print(len(T_onsets))
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print(len(T_offsets))
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print(len(u))
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print(len(v))
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print(len(w))
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print(len(a))
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print(len(b))
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print(len(c))
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print(len(e))
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print(len(f))
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create_plot_with_draggable_points()
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