如何更新 matplotlib 中的绘图? [英] How to update a plot in matplotlib?

问题描述

我在此处重绘图形时遇到问题.我允许用户指定时间尺度(x 轴)中的单位，然后我重新计算并调用这个函数 plots().我希望情节简单地更新，而不是在图中附加另一个情节.

I'm having issues with redrawing the figure here. I allow the user to specify the units in the time scale (x-axis) and then I recalculate and call this function plots(). I want the plot to simply update, not append another plot to the figure.

def plots():
    global vlgaBuffSorted
    cntr()

    result = collections.defaultdict(list)
    for d in vlgaBuffSorted:
        result[d['event']].append(d)

    result_list = result.values()

    f = Figure()
    graph1 = f.add_subplot(211)
    graph2 = f.add_subplot(212,sharex=graph1)

    for item in result_list:
        tL = []
        vgsL = []
        vdsL = []
        isubL = []
        for dict in item:
            tL.append(dict['time'])
            vgsL.append(dict['vgs'])
            vdsL.append(dict['vds'])
            isubL.append(dict['isub'])
        graph1.plot(tL,vdsL,'bo',label='a')
        graph1.plot(tL,vgsL,'rp',label='b')
        graph2.plot(tL,isubL,'b-',label='c')

    plotCanvas = FigureCanvasTkAgg(f, pltFrame)
    toolbar = NavigationToolbar2TkAgg(plotCanvas, pltFrame)
    toolbar.pack(side=BOTTOM)
    plotCanvas.get_tk_widget().pack(side=TOP)

推荐答案

您基本上有两个选择:

1. 完全按照您当前的操作进行，但在重新绘制数据之前调用 graph1.clear() 和 graph2.clear().这是最慢但最简单、最可靠的选项.

1. Do exactly what you're currently doing, but call graph1.clear() and graph2.clear() before replotting the data. This is the slowest, but most simplest and most robust option.

无需重新绘图，您只需更新绘图对象的数据即可.您需要对代码进行一些更改，但这应该比每次都重新绘制要快得多.但是，您绘制的数据的形状无法更改，如果您的数据范围发生变化，您将需要手动重置 x 和 y 轴限制.

Instead of replotting, you can just update the data of the plot objects. You'll need to make some changes in your code, but this should be much, much faster than replotting things every time. However, the shape of the data that you're plotting can't change, and if the range of your data is changing, you'll need to manually reset the x and y axis limits.

以第二个选项为例:

import matplotlib.pyplot as plt
import numpy as np

x = np.linspace(0, 6*np.pi, 100)
y = np.sin(x)

# You probably won't need this if you're embedding things in a tkinter plot...
plt.ion()

fig = plt.figure()
ax = fig.add_subplot(111)
line1, = ax.plot(x, y, 'r-') # Returns a tuple of line objects, thus the comma

for phase in np.linspace(0, 10*np.pi, 500):
    line1.set_ydata(np.sin(x + phase))
    fig.canvas.draw()
    fig.canvas.flush_events()

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