问题描述
我正在尝试以图形方式分析二维数据. matplotlib.imshow
在这方面非常有用,但我认为,如果我可以从矩阵中排除某些单元格(感兴趣范围之外的值),则可以利用更多的信息.我的问题是这些值在我感兴趣的范围内展平"了颜色图.排除这些值后,我可以拥有更高的色彩分辨率.
I am trying to analyse graphically 2d data. matplotlib.imshow
is very useful in that but I feel that I could make even more use of that if I could exclude some cells from my matrix, values of outside of a range of interest. My problem is that these values ''flatten'' the colormap in my range of interest. I could have more color resolution after excluding these values.
我知道如何在我的矩阵上应用蒙版以排除这些值,但它在应用蒙版后返回一个 1d 对象:
I know how to apply a mask on my matrix to exclude these values, but it returns a 1d object after applying the mask:
mask = (myMatrix > lowerBound) & (myMatrix < upperBound)
myMatrix = myMatrix[mask] #returns a 1d array :(
有没有办法将掩码传递给 imshow
如何重建二维数组?
Is there a way to pass the mask to imshow
how to reconstruct a 2d array?
推荐答案
您可以使用 numpy.ma.mask_where
来保留数组形状,例如
You can use numpy.ma.mask_where
to preserve the array shape, e.g.
import numpy as np
import matplotlib.pyplot as plt
lowerBound = 0.25
upperBound = 0.75
myMatrix = np.random.rand(100,100)
myMatrix =np.ma.masked_where((lowerBound < myMatrix) &
(myMatrix < upperBound), myMatrix)
fig,axs=plt.subplots(2,1)
#Plot without mask
axs[0].imshow(myMatrix.data)
#Default is to apply mask
axs[1].imshow(myMatrix)
plt.show()
这篇关于Matplotlib imshow:如何在矩阵上应用掩码的文章就介绍到这了,希望我们推荐的答案对大家有所帮助,也希望大家多多支持!