Matplotlib:如何使imshow从其他numpy数组中读取x,y坐标? [英] Matplotlib: how to make imshow read x,y coordinates from other numpy arrays?
问题描述
当您想用imshow
绘制一个numpy数组时,通常会这样做:
When you want to plot a numpy array with imshow
, this is what you normally do:
import numpy as np
import matplotlib.pyplot as plt
A=np.array([[3,2,5],[8,1,2],[6,6,7],[3,5,1]]) #The array to plot
im=plt.imshow(A,origin="upper",interpolation="nearest",cmap=plt.cm.gray_r)
plt.colorbar(im)
这给了我们这个简单的图像:
Which gives us this simple image:
在此图像中,只需从数组中每个值的位置提取 x 和 y 坐标.现在,假设A
是一个值数组,这些值引用某些特定的坐标:
In this image, the x and y coordinates are simply extracted from the position of each value in the array. Now, let's say that A
is an array of values that refer to some specific coordinates:
real_x=np.array([[15,16,17],[15,16,17],[15,16,17],[15,16,17]])
real_y=np.array([[20,21,22,23],[20,21,22,23],[20,21,22,23]])
这些值是根据我的情况而编造的. 是否可以强制imshow为A中的每个值分配对应的一对坐标(real_x,real_y)?
These values are made-up to just make my case. Is there a way to force imshow to assign each value in A the corresponding pair of coordinates (real_x,real_y)?
PS:我不是要在基于数组的x和y中添加或减去某些东西,以使其与 real_x 和 real_y 匹配,但对于从 real_x 和 real_y 数组读取的这些值.然后,预期的结果是在x轴上具有 real_x 值且在y轴上具有 real_y 值的图像.
PS: I am not looking for adding or subtracting something to the array-based x and y to make them match real_x and real_y, but for something that reads these values from the real_x and real_y arrays. The intended outcome is then an image with the real_x values on the x-axis and the real_y values on the y-axis.
推荐答案
设置范围
假设您有
real_x=np.array([15,16,17])
real_y=np.array([20,21,22,23])
您将图像范围设置为
dx = (real_x[1]-real_x[0])/2.
dy = (real_y[1]-real_y[0])/2.
extent = [real_x[0]-dx, real_x[-1]+dx, real_y[0]-dy, real_y[-1]+dy]
plt.imshow(data, extent=extent)
更改刻度标签
另一种选择是只更改刻度标签
Changing ticklabels
An alternative would be to just change the ticklabels
real_x=np.array([15,16,17])
real_y=np.array([20,21,22,23])
plt.imshow(data)
plt.gca().set_xticks(range(len(real_x)))
plt.gca().set_yticks(range(len(real_x)))
plt.gca().set_xticklabels(real_x)
plt.gca().set_yticklabels(real_y)
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