绘制多个子图需要一个 colobar [重复]

Question

每个子图都有多个 colobar，我想要一个。

for i in range(6):
     plot.subplot(2,3,i)
     im=plot.contourf(xlon[:],xlat[:],rain[i,:,:])
     plot.colorbar(im)
plot.show()

Answer 1

您可以通过在其自己的轴上添加colorbar 来做到这一点。这可以通过手动创建一个附加轴并根据需要使用subplots_adjust() 和add_axes() 移动现有图来完成，例如

import matplotlib.pyplot as plt
import numpy as np
import random

fig, ax = plt.subplots(figsize=(10, 6), dpi=300)
for i in range(1,7):
    # This simply creates some random data to populate with
    a = np.arange(10)
    x, y = np.meshgrid(a, a)
    z = np.random.randint(0, 7, (10, 10))

    plt.subplot(2,3,i)
    im=plt.contourf(x, y, z)

# Tight layout is optional
fig.tight_layout()
fig.subplots_adjust(right=0.825)
cax = fig.add_axes([0.85, 0.06, 0.035, 0.91])
fig.colorbar(im, cax=cax)
plt.show()

在这种情况下add_axes() 的参数是[left, bottom, width, height]。这将产生类似

编辑

要删除图间轴标签、刻度线等，需要对上述方法进行一些重要的修改，其中plt.subplots() 用于填充子图对象的2x3 数组，然后我们对其进行迭代。例如

import matplotlib.pyplot as plt
import numpy as np
import random

nrows = 2
ncols = 3
# Create the subplot array
fig, (axes) = plt.subplots(nrows=nrows, ncols=ncols, figsize=(10, 6), 
                           dpi=300, sharex=True, sharey=True)
for i in range(nrows):
    for j in range(ncols):
        a = np.arange(10)
        x, y = np.meshgrid(a, a)
        z = np.random.randint(0, 7, (10, 10))
        im = axes[i][j].contourf(x, y, z)
        # Remove the tick marks but leave the superleft and superbottom alone
        if i != nrows-1:
            if j != 0:
                axes[i][j].tick_params(axis='both', which='both', 
                           left=False, bottom=False, top=False)
            else:
                axes[i][j].tick_params(axis='both', which='both', bottom=False, top=False)
        else:
            if j != 0:
                axes[i][j].tick_params(axis='both', which='both', left=False, top=False)
fig.tight_layout()
# Some additional whitespace adjustment is needed
fig.subplots_adjust(right=0.825, hspace=0.025, wspace=0.025)
cax = fig.add_axes([0.85, 0.06, 0.035, 0.91])
fig.colorbar(im, cax=cax)
plt.show()