如何正确屏蔽 numpy 二维数组? [英] How to properly mask a numpy 2D array?

问题描述

假设我有一个二维坐标数组，看起来像

Say I have a two dimensional array of coordinates that looks something like

x = array([[1,2],[2,3],[3,4]])

之前在我的工作中，我生成了一个最终看起来像的面具

Previously in my work so far, I generated a mask that ends up looking something like

mask = [False,False,True]

当我尝试在 2D 坐标向量上使用此蒙版时，出现错误

When I try to use this mask on the 2D coordinate vector, I get an error

newX = np.ma.compressed(np.ma.masked_array(x,mask))

>>>numpy.ma.core.MaskError: Mask and data not compatible: data size 
   is 6, mask size is 3.`

我想这是有道理的.所以我尝试简单地使用以下掩码:

which makes sense, I suppose. So I tried to simply use the following mask instead:

mask2 = np.column_stack((mask,mask))
newX = np.ma.compressed(np.ma.masked_array(x,mask2))

我得到的很接近:

>>>array([1,2,2,3])

我所期望的(和想要的):

to what I would expect (and want):

>>>array([[1,2],[2,3]])

一定有更简单的方法来做到这一点吗?

There must be an easier way to do this?

推荐答案

这是您要找的吗?

import numpy as np
x[~np.array(mask)]
# array([[1, 2],
#        [2, 3]])

或者来自 numpy 掩码数组:

newX = np.ma.array(x, mask = np.column_stack((mask, mask)))
newX

# masked_array(data =
#  [[1 2]
#  [2 3]
#  [-- --]],
#              mask =
#  [[False False]
#  [False False]
#  [ True  True]],
#        fill_value = 999999)

这篇关于如何正确屏蔽 numpy 二维数组?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IT屋！