有没有一种方法可以分离Matplotlib图表，以便计算可以继续进行？

import matplotlib.pyplot as plt

plt.scatter([0], [1])
plt.draw()
plt.show(block=False)

for i in range(10):
    plt.scatter([i], [i+1])
    plt.draw()
    plt.pause(0.001)

在我的系统上，show()函数不会阻塞程序执行，虽然我希望脚本在用户与图形进行交互并使用'pick_event'回调收集数据之前等待。

为了阻塞执行直到绘图窗口关闭，我使用了以下方法：

fig = plt.figure()
ax = fig.add_subplot(1,1,1)
ax.plot(x,y)

# set processing to continue when window closed
def onclose(event):
    fig.canvas.stop_event_loop()
fig.canvas.mpl_connect('close_event', onclose)

fig.show() # this call does not block on my system
fig.canvas.start_event_loop_default() # block here until window closed

# continue with further processing, perhaps using result from callbacks

请注意，canvas.start_event_loop_default() 产生了以下警告：

C:\Python26\lib\site-packages\matplotlib\backend_bases.py:2051: DeprecationWarning: Using default event loop until function specific to this GUI is implemented
  warnings.warn(str,DeprecationWarning)

#!/usr/bin/python3

import time
import multiprocessing
import os

def plot_graph(data):
    from matplotlib.pyplot import plot, draw, show
    print("entered plot_graph()")
    plot(data)
    show() # this will block and remain a viable process as long as the figure window is open
    print("exiting plot_graph() process")

if __name__ == "__main__":
    print("starting __main__")
    multiprocessing.Process(target=plot_graph, args=([1, 2, 3],)).start()
    time.sleep(5)
    print("exiting main")
    os._exit(0) # this exits immediately with no cleanup or buffer flushing

from contextlib import contextmanager

@contextmanager
def keep_plots_open(keep_show_open_on_exit=True, even_when_error=True):
    '''
    To continue excecuting code when plt.show() is called
    and keep the plot on displaying before this contex manager exits
    (even if an error caused the exit).
    '''
    import matplotlib.pyplot
    show_original = matplotlib.pyplot.show
    def show_replacement(*args, **kwargs):
        kwargs['block'] = False
        show_original(*args, **kwargs)
    matplotlib.pyplot.show = show_replacement

    pylab_exists = True
    try:
        import pylab
    except ImportError: 
        pylab_exists = False
    if pylab_exists:
        pylab.show = show_replacement

    try:
        yield
    except Exception, err:
        if keep_show_open_on_exit and even_when_error:
            print "*********************************************"
            print "Error early edition while waiting for show():" 
            print "*********************************************"
            import traceback
            print traceback.format_exc()
            show_original()
            print "*********************************************"
            raise
    finally:
        matplotlib.pyplot.show = show_original
        if pylab_exists:
            pylab.show = show_original
    if keep_show_open_on_exit:
        show_original()

# ***********************
# Running example
# ***********************
import pylab as pl
import time
if __name__ == '__main__':
    with keep_plots_open():
        pl.figure('a')
        pl.plot([1,2,3], [4,5,6])     
        pl.plot([3,2,1], [4,5,6])
        pl.show()

        pl.figure('b')
        pl.plot([1,2,3], [4,5,6])
        pl.show()

        time.sleep(1)
        print '...'
        time.sleep(1)
        print '...'
        time.sleep(1)
        print '...'
        this_will_surely_cause_an_error

plt.figure(1)
plt.imshow(your_first_image)

plt.figure(2)
plt.imshow(your_second_image)

plt.show(block=False) # That's important 

raw_input("Press ENTER to exist") # Useful when you run your Python script from the terminal and you want to hold the running to see your figures until you press Enter

这是我找到的最简单的解决方案（线程阻塞代码）

plt.show(block=False) # this avoids blocking your thread

plt.pause(1) # comment this if you do not want a time delay

# do more stuff

plt.show(block=True) # this prevents the window from closing on you

show(block=False)
draw()

# stuff

numFig = 1

plt.figure(numFig)
numFig += 1
plt.plot(x1, y1)

# other stuff

plt.figure(numFig)
numFig += 1
plt.plot(x2, y2)

# more stuff

plt.show()

虽然没有直接回答OP的问题，但我发布这个解决方法，因为它可能会帮助到处于这种情况下的某些人：

• 我正在使用pyinstaller创建一个.exe文件，因为我无法在需要生成图形的地方安装Python，所以我需要使用Python脚本生成图形，将其保存为.png格式，关闭它并继续下一个，实现为循环中的多个图形或使用函数。

为此，我使用：

import matplotlib.pyplot as plt
#code generating the plot in a loop or function
#saving the plot
plt.savefig(var+'_plot.png',bbox_inches='tight', dpi=250) 
#you can allways reopen the plot using
os.system(var+'_plot.png') # unfortunately .png allows no interaction.
#the following avoids plot blocking the execution while in non-interactive mode
plt.show(block=False) 
#and the following closes the plot while next iteration will generate new instance.
plt.close() 

在循环中，"var"用于标识绘图，以防止其被覆盖。