matplotlib：颜色条及其文本标签

我想为创建colorbar图例，以heatmap使标签位于每种离散颜色的中心。从这里借来的示例：

import matplotlib.pyplot as plt
import numpy as np
from matplotlib.colors import ListedColormap

#discrete color scheme
cMap = ListedColormap(['white', 'green', 'blue','red'])

#data
np.random.seed(42)
data = np.random.rand(4, 4)
fig, ax = plt.subplots()
heatmap = ax.pcolor(data, cmap=cMap)

#legend
cbar = plt.colorbar(heatmap)
cbar.ax.set_yticklabels(['0','1','2','>3'])
cbar.set_label('# of contacts', rotation=270)

# put the major ticks at the middle of each cell
ax.set_xticks(np.arange(data.shape[1]) + 0.5, minor=False)
ax.set_yticks(np.arange(data.shape[0]) + 0.5, minor=False)
ax.invert_yaxis()

#labels
column_labels = list('ABCD')
row_labels = list('WXYZ')
ax.set_xticklabels(column_labels, minor=False)
ax.set_yticklabels(row_labels, minor=False)

plt.show()

这将生成以下图：

理想情况下，我想生成一个图例栏，该图例栏具有四种颜色，每种颜色的中心都有一个标签：0,1,2,>3。如何做到这一点？

import matplotlib.pyplot as plt
import numpy as np
from matplotlib.colors import ListedColormap

#discrete color scheme
cMap = ListedColormap(['white', 'green', 'blue','red'])

#data
np.random.seed(42)
data = np.random.rand(4, 4)
fig, ax = plt.subplots()
heatmap = ax.pcolor(data, cmap=cMap)

#legend
cbar = plt.colorbar(heatmap)

cbar.ax.get_yaxis().set_ticks([])
for j, lab in enumerate(['$0$','$1$','$2$','$>3$']):
    cbar.ax.text(.5, (2 * j + 1) / 8.0, lab, ha='center', va='center')
cbar.ax.get_yaxis().labelpad = 15
cbar.ax.set_ylabel('# of contacts', rotation=270)


# put the major ticks at the middle of each cell
ax.set_xticks(np.arange(data.shape[1]) + 0.5, minor=False)
ax.set_yticks(np.arange(data.shape[0]) + 0.5, minor=False)
ax.invert_yaxis()

#labels
column_labels = list('ABCD')
row_labels = list('WXYZ')
ax.set_xticklabels(column_labels, minor=False)
ax.set_yticklabels(row_labels, minor=False)

plt.show()

你很亲近 引用颜色条轴后，就可以对其进行任何操作，包括将文本标签放在中间。您可能需要使用格式使其更加可见。

要添加到tacaswell的答案中，该colorbar()函数具有可选cax输入，可用于传递应在其上绘制颜色条的轴。如果使用该输入，则可以使用该轴直接设置标签。

import matplotlib.pyplot as plt
from mpl_toolkits.axes_grid1 import make_axes_locatable

fig, ax = plt.subplots()
heatmap = ax.imshow(data)
divider = make_axes_locatable(ax)
cax = divider.append_axes('bottom', size='10%', pad=0.6)
cb = fig.colorbar(heatmap, cax=cax, orientation='horizontal')

cax.set_xlabel('data label')  # cax == cb.ax