python - 在Matplotlib中将x轴移动到绘图的顶部

基于this question about heatmaps in matplotlib，我想将x轴标题移动到绘图的顶部。

import matplotlib.pyplot as plt
import numpy as np
column_labels = list('ABCD')
row_labels = list('WXYZ')
data = np.random.rand(4,4)
fig, ax = plt.subplots()
heatmap = ax.pcolor(data, cmap=plt.cm.Blues)

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

# want a more natural, table-like display
ax.invert_yaxis()
ax.xaxis.set_label_position('top') # <-- This doesn't work!

ax.set_xticklabels(row_labels, minor=False)
ax.set_yticklabels(column_labels, minor=False)
plt.show()

但是，调用matplotlib's set_label_position(如上所述)似乎并没有达到预期的效果。这是我的输出:

我究竟做错了什么？

最佳答案

用

ax.xaxis.tick_top()

将刻度线放置在图像的顶部。命令

ax.set_xlabel('X LABEL')
ax.xaxis.set_label_position('top')

影响标签，而不影响刻度线。

import matplotlib.pyplot as plt
import numpy as np
column_labels = list('ABCD')
row_labels = list('WXYZ')
data = np.random.rand(4, 4)
fig, ax = plt.subplots()
heatmap = ax.pcolor(data, cmap=plt.cm.Blues)

# 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)

# want a more natural, table-like display
ax.invert_yaxis()
ax.xaxis.tick_top()

ax.set_xticklabels(column_labels, minor=False)
ax.set_yticklabels(row_labels, minor=False)
plt.show()

关于python - 在Matplotlib中将x轴移动到绘图的顶部，我们在Stack Overflow上找到一个类似的问题：https://stackoverflow.com/questions/48470251/