更新函数中的matplotlib映像 [英] Update matplotlib image in a function

问题描述

我有一个处理图像的循环，我希望在第100次迭代(例如)中使用matplotlib在单个输出窗口中显示图像.因此，我正在尝试编写一个函数，该函数将以numpy张量作为输入并显示相应的图像.

I've got a loop that's processing images and I want, on every 100th iteration (say) to display the image in a single output window using matplotlib. So I'm trying to write a function which will take a numpy tensor as input and display the corresponding image.

这是我所无法使用的:

def display(image):
  global im

  # If  im has been initialized, update it with the current image; otherwise initialize im and update with current image.   
  try:
    im
    im.set_array(image)
    plt.draw()
  except NameError:
    im = plt.imshow(image, cmap=plt.get_cmap('gray'), vmin=0, vmax=255)
    plt.show(block=False)
    plt.draw()

我一开始试图通过 FuncAnimation 传递它，但这似乎旨在让动画调用一个函数来执行更新，而不是在 matplotlib 上调用函数来显示结果.

I was trying to pass it through FuncAnimation at first, but that seems designed to have the animation call a function to do the update, rather than having a function call on matplotlib to display the result.

上面的代码打开了一个窗口，但它似乎没有更新.任何人都可以在这里指出正确的方向吗?

The code above opens a window but it doesn't seem to update. Can anyone point me in the right direction here?

非常感谢，

Justin

推荐答案

也许你可以使用以下组合:

Maybe you can use a combination of:

• fig.canvas.draw_idle()和
• plt.pause()

第一个将重新绘制您的图形，而第二个将调用 GUI 事件循环来更新图形.

The first one will re-draw your figure, while the second one will call the GUI event loop to update the figure.

您也不必一直调用imshow，只需在"im"对象上调用"set_data"方法就足够了.这样的事情应该可以工作:

Also you don't need to call imshow all the times, it's sufficient to call the "set_data" method on your "im" object. Something like that should work:

import matplotlib.pyplot as plt
import numpy

fig,ax = plt.subplots(1,1)
image = numpy.array([[1,1,1], [2,2,2], [3,3,3]])
im = ax.imshow(image)

while True:       
    image = numpy.multiply(1.1, image)
    im.set_data(image)
    fig.canvas.draw_idle()
    plt.pause(1)

这是改编自 这个答案.希望有帮助.

This was adapted from this answer. Hope it helps.

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