For years, I've been struggling to get efficient live plotting in matplotlib, and to this day I remain unsatisfied.
I want a redraw_figure
function that updates the figure "live" (as the code runs), and will display the latest plots if I stop at a breakpoint.
Here is some demo code:
import time
from matplotlib import pyplot as plt
import numpy as np
def live_update_demo():
plt.subplot(2, 1, 1)
h1 = plt.imshow(np.random.randn(30, 30))
redraw_figure()
plt.subplot(2, 1, 2)
h2, = plt.plot(np.random.randn(50))
redraw_figure()
t_start = time.time()
for i in xrange(1000):
h1.set_data(np.random.randn(30, 30))
redraw_figure()
h2.set_ydata(np.random.randn(50))
redraw_figure()
print 'Mean Frame Rate: %.3gFPS' % ((i+1) / (time.time() - t_start))
def redraw_figure():
plt.draw()
plt.pause(0.00001)
live_update_demo()
Plots should update live when the code is run, and we should see the latest data when stopping at any breakpoint after redraw_figure()
. The question is how to best implement redraw_figure()
In the implementation above (plt.draw(); plt.pause(0.00001)
), it works, but is very slow (~3.7FPS)
I can implement it as:
def redraw_figure():
plt.gcf().canvas.flush_events()
plt.show(block=False)
And it runs faster (~11FPS), but plots are not up-to date when you stop at breakpoints (eg if I put a breakpoint on the t_start = ...
line, the second plot does not appear).
Strangely enough, what does actually work is calling the show twice:
def redraw_figure():
plt.gcf().canvas.flush_events()
plt.show(block=False)
plt.show(block=False)
Which gives ~11FPS and does keep plots up-to-data if your break on any line.
Now I've heard it said that the "block" keyword is deprecated. And calling the same function twice seems like a weird, probably-non-portable hack anyway.
So what can I put in this function that will plot at a reasonable frame rate, isn't a giant kludge, and preferably will work across backends and systems?
Some notes:
But at least on my system, that does not redraw the plots at all.
So, if anybody has an answer, you would directly make me and thousands of others very happy. Their happiness would probably trickle through to their friends and relatives, and their friends and relatives, and so on, so that you could potentially improve the lives of billions.
Conclusions
ImportanceOfBeingErnest shows how you can use blit for faster plotting, but it's not as simple as putting something different in the redraw_figure
function (you need to keep track of what things to redraw).
Question&Answers:
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