我有一个matplotlib图,我想在两个单独的窗口中重复,在PyQt4下。我已经尝试将小部件添加到两者的布局中,但随后小部件从第一个小部件消失。有没有办法做到这一点,除了创建两个相同的图并保持同步?
答案 0 :(得分:2)
问题在于你无法将相同的qt小部件添加到两个不同的父窗口小部件中,因为在添加小部件的过程中,Qt还会创建一个重复的过程,它会执行您所看到的内容:
......小部件从第一个[窗口]消失......
因此,解决方案是制作两个共享相同图形的画布。 这是一个示例代码,这将显示两个主窗口,每个窗口有两个画布,四个图将同步:
import sys
from PyQt4 import QtGui
import numpy as np
import numpy.random as rd
from matplotlib.figure import Figure
from matplotlib.backends.backend_qt4agg import FigureCanvasQTAgg as FigureCanvas
class ApplicationWindow(QtGui.QMainWindow):
def __init__(self):
QtGui.QMainWindow.__init__(self)
self.main_widget = QtGui.QWidget(self)
vbl = QtGui.QVBoxLayout(self.main_widget)
self._fig = Figure()
self.ax = self._fig.add_subplot(111)
#note the same fig for two canvas
self.fc1 = FigureCanvas(self._fig) #canvas #1
self.fc2 = FigureCanvas(self._fig) #canvas #1
self.but = QtGui.QPushButton(self.main_widget)
self.but.setText("Update") #for testing the sync
vbl.addWidget(self.fc1)
vbl.addWidget(self.fc2)
vbl.addWidget(self.but)
self.setCentralWidget(self.main_widget)
@property
def fig(self):
return self._fig
@fig.setter
def fig(self, value):
self._fig = value
#keep the same fig in both canvas
self.fc1.figure = value
self.fc2.figure = value
def redraw_plot(self):
self.fc1.draw()
self.fc2.draw()
qApp = QtGui.QApplication(sys.argv)
aw1 = ApplicationWindow() #window #1
aw2 = ApplicationWindow() #window #2
aw1.fig = aw2.fig #THE SAME FIG FOR THE TWO WINDOWS!
def update_plot():
'''Just a random plot for test the sync!'''
#note that the update is only in the first window
ax = aw1.fig.gca()
ax.clear()
ax.plot(range(10),rd.random(10))
#calls to redraw the canvas
aw1.redraw_plot()
aw2.redraw_plot()
#just for testing the update
aw1.but.clicked.connect(update_plot)
aw2.but.clicked.connect(update_plot)
aw1.show()
aw2.show()
sys.exit(qApp.exec_())
答案 1 :(得分:0)
虽然它不是一个完美的解决方案,但matplotlib有一种内置的方法可以保持两个独立图表的限制,滴答等同步。
E.g。
import matplotlib.pyplot as plt
import numpy as np
x = np.linspace(0, 4 * np.pi, 100)
y = np.cos(x)
figures = [plt.figure() for _ in range(3)]
ax1 = figures[0].add_subplot(111)
axes = [ax1] + [fig.add_subplot(111, sharex=ax1, sharey=ax1) for fig in figures[1:]]
for ax in axes:
ax.plot(x, y, 'go-')
ax1.set_xlabel('test')
plt.show()
请注意,缩放,平移等所有3个绘图都将保持同步
虽然可能有更好的方法。