Update a chart in realtime with matplotlib
Question:
I’d like to update a plot by redrawing a new curve (with 100 points) in real-time.
This works:
import time, matplotlib.pyplot as plt, numpy as np
fig = plt.figure()
ax = fig.add_subplot(111)
t0 = time.time()
for i in range(10000000):
x = np.random.random(100)
ax.clear()
ax.plot(x, color='b')
fig.show()
plt.pause(0.01)
print(i, i/(time.time()-t0))
but there is only ~10 FPS, which seems slow.
What is the standard way to do this in Matplotlib?
I have already read How to update a plot in matplotlib and How do I plot in real-time in a while loop using matplotlib? but these cases are different because they add a new point to an existing plot. In my use case, I need to redraw everything and keep 100 points.
Answers:
I do not know any technique to gain an order of magnitude. Nevertheless you can slightly increase the FPS with
- update the line data instead of creating a new plot with
set_ydata
(and/or set_xdata
)
- use
Figure.canvas.draw_idle()
instead of Figure.canvas.draw()
(cf. this question).
Thus I would recommand you to try the following:
import time
import matplotlib.pyplot as plt
import numpy as np
fig = plt.figure()
ax = fig.add_subplot(111)
t0 = time.time()
x = np.random.random(100)
l, *_ = ax.plot(x, color='b')
fig.show()
fig.canvas.flush_events()
ax.set_autoscale_on(False)
for i in range(10000000):
x = np.random.random(100)
l.set_ydata(x)
fig.canvas.draw_idle()
fig.canvas.flush_events()
print(i, i/(time.time()-t0))
Note that, as mentioned by @Bhargav in the comments, changing matplotlib backend can also help (e.g. matplotlib.use('QtAgg')
).
I hope this help.
I’d like to update a plot by redrawing a new curve (with 100 points) in real-time.
This works:
import time, matplotlib.pyplot as plt, numpy as np
fig = plt.figure()
ax = fig.add_subplot(111)
t0 = time.time()
for i in range(10000000):
x = np.random.random(100)
ax.clear()
ax.plot(x, color='b')
fig.show()
plt.pause(0.01)
print(i, i/(time.time()-t0))
but there is only ~10 FPS, which seems slow.
What is the standard way to do this in Matplotlib?
I have already read How to update a plot in matplotlib and How do I plot in real-time in a while loop using matplotlib? but these cases are different because they add a new point to an existing plot. In my use case, I need to redraw everything and keep 100 points.
I do not know any technique to gain an order of magnitude. Nevertheless you can slightly increase the FPS with
- update the line data instead of creating a new plot with
set_ydata
(and/orset_xdata
) - use
Figure.canvas.draw_idle()
instead ofFigure.canvas.draw()
(cf. this question).
Thus I would recommand you to try the following:
import time
import matplotlib.pyplot as plt
import numpy as np
fig = plt.figure()
ax = fig.add_subplot(111)
t0 = time.time()
x = np.random.random(100)
l, *_ = ax.plot(x, color='b')
fig.show()
fig.canvas.flush_events()
ax.set_autoscale_on(False)
for i in range(10000000):
x = np.random.random(100)
l.set_ydata(x)
fig.canvas.draw_idle()
fig.canvas.flush_events()
print(i, i/(time.time()-t0))
Note that, as mentioned by @Bhargav in the comments, changing matplotlib backend can also help (e.g. matplotlib.use('QtAgg')
).
I hope this help.