通过指定行和列从另一个数组创建NumPy数组 [英] Create NumPy array from another array by specifying rows and columns

问题描述

如何通过指定要包括哪些行和列(分别由x和y指示)来创建NumPy数组B，它是NumPy数组A的子数组?

How can I create a NumPy array B which is a sub-array of a NumPy array A, by specifying which rows and columns (indicated by x and y respectively) are to be included?

例如:

A = numpy.array([[1, 2, 3, 4, 5], [6, 7, 8, 9, 10], [11, 12, 13, 14, 15]])
x = [0, 2]
y = [1, 3, 4]
B = # Do something .....

应提供输出:

>>> B
array([[2, 4, 5], [12, 14, 15]])

推荐答案

做到这一点的最佳方法是使用ix_函数:请参见

The best way to do this is to use the ix_ function: see the answer by MSeifert for details.

或者，您可以通过x和y使用链式索引操作:

Alternatively, you could use chain the indexing operations using x and y:

>>> A[x][:,y]
array([[ 2,  4,  5],
       [12, 14, 15]])

第一个x用于选择A的行.接下来，[:,y]选择由y的元素指定的子数组的列.

First x is used to select the rows of A. Next, [:,y] picks out the columns of the subarray specified by the elements of y.

在这种情况下，链接是对称的:如果愿意，还可以先使用A[:,y][x]选择列.

The chaining is symmetric in this case: you can also choose the columns first with A[:,y][x] if you wish.

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