使用wxPython清除matplotlib中的背景

Question

我想用matplotlib创建一个动画来监视聚类算法的收敛.它应该在第一次调用时绘制我的数据的散点图,并在每次更新绘图时绘制误差椭圆.我正在尝试使用canvas_copy_from_bbox()并restore_region()保存散点图,然后在我更新绘图时绘制一组新的省略号.但是,代码只是将旧椭圆绘制在旧椭圆之上,而不先清除先前的绘图.我怀疑,不知何故,这种方法Ellipse()与add_path()命令不兼容,但我不知道如何解决这个问题.

这是代码:

import wx
import math 
from math import pi
from matplotlib.patches import Ellipse
from matplotlib.figure import Figure
from matplotlib.backends.backend_wxagg import \
     FigureCanvasWxAgg as FigureCanvas

TIMER_ID = wx.NewId()


class _MonitorPlot(wx.Frame):
    def __init__(self, data, scale=1):
        self.scale = scale
        wx.Frame.__init__(self, None, wx.ID_ANY,
                          title="FlowVB Progress Monitor", size=(800, 600))
        self.fig = Figure((8, 6), 100)
        self.canvas = FigureCanvas(self, wx.ID_ANY, self.fig)
        self.ax = self.fig.add_subplot(111)

        x_lims = [data[:, 0].min(), data[:, 0].max()]
        y_lims = [data[:, 1].min(), data[:, 1].max()]

        self.ax.set_xlim(x_lims)
        self.ax.set_ylim(y_lims)
        self.ax.set_autoscale_on(False)

        self.l_data = self.ax.plot(data[:, 0], data[:, 1], color='blue',
                               linestyle='', marker='o')

        self.canvas.draw()
        self.bg = self.canvas.copy_from_bbox(self.ax.bbox)

        self.Bind(wx.EVT_IDLE, self._onIdle)

    def update_plot(self, pos, cov):
        self.canvas.restore_region(self.bg)

        for k in range(pos.shape[0]):
            l_center, = self.ax.plot(pos[k, 0], pos[k, 1],
                                     color='red', marker='+')

            U, s, Vh = np.linalg.svd(cov[k, :, :])
            orient = math.atan2(U[1, 0], U[0, 0]) * 180 / pi
            ellipsePlot = Ellipse(xy=pos[k, :], width=2.0 * math.sqrt(s[0]),
                                  height=2.0 * math.sqrt(s[1]),
                                  angle=orient, facecolor='none',
                                  edgecolor='red')
            self.ax.add_patch(ellipsePlot)

        self.canvas.draw()
        self.canvas.blit(self.ax.bbox)

Answer 1

发生的事情是,您每次都要在绘图中添加新的补丁,然后在调用时绘制所有补丁self.canvas.draw().

最快的解决方法是self.canvas.draw_artist(ellipsePlot)在添加每个补丁后调用并删除调用self.canvas.draw()

作为一个简单的独立示例:

# Animates 3 ellipses overlain on a scatterplot
import matplotlib.pyplot as plt
from matplotlib.patches import Ellipse
import numpy as np

num = 10
x = np.random.random(num)
y = np.random.random(num)

plt.ion()
fig = plt.figure()
ax = fig.add_subplot(111)
line = ax.plot(x, y, 'bo')

fig.canvas.draw()
bg = fig.canvas.copy_from_bbox(ax.bbox)

# Pseudo-main loop
for i in range(100):
    fig.canvas.restore_region(bg)

    # Make a new ellipse each time... (inefficient!)
    for i in range(3):
        width, height, angle = np.random.random(3)
        angle *= 180
        ellip = Ellipse(xy=(0.5, 0.5), width=width, height=height, 
                facecolor='red', angle=angle, alpha=0.5)
        ax.add_patch(ellip)
        ax.draw_artist(ellip)

    fig.canvas.blit(ax.bbox)

但是,随着时间的推移,这可能会导致内存消耗问题,因为轴对象将跟踪添加到其中的所有艺术家.如果你的轴没有长时间闲置,这可能是微不足道的,但你应该至少知道它会导致内存泄漏.解决此问题的一种方法是通过ax.remove(ellipsePlot)在绘制每个椭圆后调用每个椭圆来从轴中删除省略号艺术家.然而,这仍然是效率低下的,因为当您可以更新它们时,您不断创建和销毁椭圆艺术家.(创建和销毁它们根本没有太多开销,但是,它主要是一个风格问题......)

如果椭圆的数量随时间保持不变,则更新和更容易更新每个椭圆艺术家对象的属性,而不是创建和添加新的椭圆.这将避免从轴中删除"旧"椭圆,因为只有您需要的数字才会存在.

作为一个简单的,独立的例子:

# Animates 3 ellipses overlain on a scatterplot
import matplotlib.pyplot as plt
from matplotlib.patches import Ellipse
import numpy as np

num = 10
x = np.random.random(num)
y = np.random.random(num)

plt.ion()
fig = plt.figure()
ax = fig.add_subplot(111)
line = ax.plot(x, y, 'bo')

fig.canvas.draw()
bg = fig.canvas.copy_from_bbox(ax.bbox)

# Make and add the ellipses the first time (won't ever be drawn)
ellipses = []
for i in range(3):
    ellip = Ellipse(xy=(0.5, 0.5), width=1, height=1, 
            facecolor='red', alpha=0.5)
    ax.add_patch(ellip)
    ellipses.append(ellip)

# Pseudo-main loop
for i in range(100):
    fig.canvas.restore_region(bg)

    # Update the ellipse artists...
    for ellip in ellipses:
        ellip.width, ellip.height, ellip.angle = np.random.random(3)
        ellip.angle *= 180
        ax.draw_artist(ellip)

    fig.canvas.blit(ax.bbox)