关于python：使用matplotlib中的colorbar更新contourf

Update contourf with colorbar in matplotlib

这是我的测试代码。

1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30

import os
import matplotlib.pyplot as plt

import numpy as np

a = np.arange(10)
bb, cc = np.meshgrid(a, a)
u = np.random.randint(2, 4, (10, 10))
v = np.random.randint(2, 4, (10, 10))

fig = plt.figure(figsize=(10, 10))
ax = fig.add_subplot(111)
plt.subplots_adjust(left=0.07, bottom=0.01, right=0.95,
top=0.94, hspace=0.0, wspace=0.0)

for i in range(10):

u = np.random.randint(2, 4, (10, 10))
v = np.random.randint(2, 4, (10, 10))
ws = np.sqrt(u**2 + v**2)
cf = plt.contourf(bb, cc, ws)
cb = plt.colorbar(cf)

fig.canvas.update()
fig.canvas.flush_events()

plt.savefig('test_barb/%i.png' % i, dpi=200)
for c in cf.collections:
c.remove()
cb.remove()

我在这里感到困惑的是，我画的帧越多，输出图像就越小。有没有办法防止这种情况发生？

。

氧化镁氧化镁

相关讨论

您需要确保颜色条始终位于同一个轴上。为此，您可以在循环外部创建一个颜色条轴(cax，例如使用axes_divider，并始终将颜色条绘制到该轴上，fig.colorbar(cf, cax=cax)。

1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34

import matplotlib.pyplot as plt
from mpl_toolkits.axes_grid1.axes_divider import make_axes_locatable
import numpy as np

a = np.arange(10)
bb, cc = np.meshgrid(a, a)
u = np.random.randint(2, 4, (10, 10))
v = np.random.randint(2, 4, (10, 10))

fig = plt.figure(figsize=(6, 6))
ax = fig.add_subplot(111)

# create axes for the colorbar
cax = make_axes_locatable(ax).append_axes("right", size="5%", pad="2%")

for i in range(10):
# clear colorbar axes
cax.clear()
u = np.random.randint(2, 4, (10, 10))
v = np.random.randint(2, 4, (10, 10))
ws = np.sqrt(u**2 + v**2)

cf = ax.contourf(bb, cc, ws)
# draw new colorbar in existing cax
cb = fig.colorbar(cf, cax=cax)

fig.canvas.update()
fig.canvas.flush_events()

#plt.savefig('test_barb/%i.png' % i, dpi=200)

plt.show()