问题：在matplotlib中将x轴移动到绘图的顶部
基于关于matplotlib中的热图的问题，我想将x轴标题移动到图的顶部。
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的set_label_position（如上所述）似乎没有达到预期的效果。这是我的输出：
我究竟做错了什么？
Based on this question about heatmaps in matplotlib, I wanted to move the x-axis titles to the top of the plot.
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()
However, calling matplotlib’s set_label_position (as notated above) doesn’t seem to have the desired effect. Here’s my output:
What am I doing wrong?
回答 0
用
ax.xaxis.tick_top()将刻度线放在图像的顶部。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()
Use
ax.xaxis.tick_top()
to place the tick marks at the top of the image. The command
ax.set_xlabel('X LABEL')
ax.xaxis.set_label_position('top')
affects the label, not the tick marks.
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()
回答 1
您想要set_ticks_position而不是set_label_position：
ax.xaxis.set_ticks_position('top') # the rest is the same这给了我：
You want set_ticks_position rather than set_label_position:
ax.xaxis.set_ticks_position('top') # the rest is the same
This gives me:
回答 2
tick_params对于设置刻度属性非常有用。可以使用以下命令将标签移到顶部：
ax.tick_params(labelbottom=False,labeltop=True)回答 3
如果要让刻度（而不是标签）显示在顶部和底部（而不仅仅是顶部），则必须做一些额外的按摩。我可以做到的唯一方法是对unutbu的代码进行较小的更改：
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.xaxis.set_ticks_position('both') # THIS IS THE ONLY CHANGE
ax.set_xticklabels(column_labels, minor=False)
ax.set_yticklabels(row_labels, minor=False)
plt.show()输出：
You’ve got to do some extra massaging if you want the ticks (not labels) to show up on the top and bottom (not just the top). The only way I could do this is with a minor change to unutbu’s code:
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.xaxis.set_ticks_position('both') # THIS IS THE ONLY CHANGE
ax.set_xticklabels(column_labels, minor=False)
ax.set_yticklabels(row_labels, minor=False)
plt.show()
Output: