I want to produce a set of frames that can be used to animate a plot of a growing line. In the past, I have always used plt.draw() and set_ydata() to redraw the y-data as it changed over time. This time, I wish to draw a "growing" line, moving across the graph with time. Because of this, set_ydata doesn't work (xdata is changing length). For example,
import numpy as np
import matplotlib.pyplot as plt
x = np.linspace(0, 10, 100)
y = np.sin(x)
plt.figure()
for n in range(len(x)):
plt.plot(x[:n], y[:n], color='k')
plt.axis([0, 10, 0, 1])
plt.savefig('Frame%03d.png' %n)
While this works, it becomes very slow as it scales. Is there a faster way to do this?
A couple of notes:
First off, the reason that things become progressively slower is that you're drawing more and more and more overlapping lines in the same position.
A quick fix is to clear the plot each time:
import numpy as np
import matplotlib.pyplot as plt
x = np.linspace(0, 10, 100)
y = np.sin(x)
plt.figure()
for n in range(len(x)):
plt.cla()
plt.plot(x[:n], y[:n], color='k')
plt.axis([0, 10, 0, 1])
plt.savefig('Frame%03d.png' %n)
Better yet, however, update both the x and y data at the same time:
import numpy as np
import matplotlib.pyplot as plt
x = np.linspace(0, 10, 100)
y = np.sin(x)
fig, ax = plt.subplots()
line, = ax.plot(x, y, color='k')
for n in range(len(x)):
line.set_data(x[:n], y[:n])
ax.axis([0, 10, 0, 1])
fig.canvas.draw()
fig.savefig('Frame%03d.png' %n)
And if you'd like to use the animation module (side note: blit=True
may not work properly on some backends (e.g. OSX), so try blit=False
if you have issues):
import numpy as np
import matplotlib.pyplot as plt
import matplotlib.animation as animation
x = np.linspace(0, 10, 100)
y = np.sin(x)
fig, ax = plt.subplots()
line, = ax.plot(x, y, color='k')
def update(num, x, y, line):
line.set_data(x[:num], y[:num])
line.axes.axis([0, 10, 0, 1])
return line,
ani = animation.FuncAnimation(fig, update, len(x), fargs=[x, y, line],
interval=25, blit=True)
ani.save('test.gif')
plt.show()