[英]Issues with python matplotlib and subplot sizes
I am trying to create a figure with 6 sub-plots in python but I am having a problem. 我试图在python中创建一个包含6个子图的图,但我遇到了问题。 Here is a simplified version of my code:
这是我的代码的简化版本:
import matplotlib.pyplot as plt
import numpy
g_width = 200
g_height = 200
data = numpy.zeros(g_width*g_height).reshape(g_height,g_width)
ax1 = plt.subplot(231)
im1 = ax1.imshow(data)
ax2 = plt.subplot(232)
im2 = ax2.imshow(data)
ax3 = plt.subplot(233)
im3 = ax3.imshow(data)
ax0 = plt.subplot(234)
im0 = ax0.imshow(data)
ax4 = plt.subplot(235)
im4 = ax4.imshow(data)
ax5 = plt.subplot(236)
ax5.plot([1,2], [1,2])
plt.show()
The above figure has 5 "imshow-based" sub-plots and one simple-data-based sub-plot. 上图有5个“基于imshow的”子图和一个基于简单数据的子图。 Can someone explain to me why the box of the last sub-plot does not have the same size with the other sub-plots?
有人可以向我解释为什么最后一个子图的框与其他子图的大小不同? If I replace the last sub-plot with an "imshow-based" sub-plot the problem disappears.
如果我用“基于imshow的”子图替换最后一个子图,问题就会消失。 Why is this happening?
为什么会这样? How can I fix it?
我该如何解决?
The aspect ratio is set to "equal" for the 5
imshow() calls (check by calling
ax1.get_aspect() ) while for
ax5 it is set to
auto which gives you the non-square shape you observe. I'm guessing
"equal" for the 5
imshow() calls (check by calling
,纵横比设置为"equal" for the 5
calls (check by calling
ax1.get_aspect()进行calls (check by calling
) while for
ax5, it is set to
auto which gives you the non-square shape you observe. I'm guessing
which gives you the non-square shape you observe. I'm guessing
imshow()` defaults to equal while plot does not. which gives you the non-square shape you observe. I'm guessing
imshow()`默认为相等,而情节没有。
To fix this set all the axis aspect ratios manually eg when creating the plot ax5 = plt.subplot(236, aspect="equal")
要手动修复此设置所有轴纵横比,例如创建绘图时
ax5 = plt.subplot(236, aspect="equal")
On a side node if your creating many axis like this you may find this useful: 在侧节点上,如果您创建这样的多个轴,您可能会发现这很有用:
fig, ax = plt.subplots(ncols=3, nrows=2, subplot_kw={'aspect':'equal'})
Then ax
is a tuple (in this case ax = ((ax1, ax2, ax3), (ax4, ax5, ax6))
) so to plot in the i
, j
plot just call 然后
ax
是一个元组(在这种情况下ax = ((ax1, ax2, ax3), (ax4, ax5, ax6))
)所以要绘制在i
, j
图中只是调用
ax[i,j].plot(..)
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