Numpy:将每一行除以一个向量元素 [英] Numpy: Divide each row by a vector element

问题描述

假设我有一个 numpy 数组:

Suppose I have a numpy array:

data = np.array([[1,1,1],[2,2,2],[3,3,3]])

我有一个相应的向量:"

and I have a corresponding "vector:"

vector = np.array([1,2,3])

如何对每一行的 data 进行减法或除法运算，结果是:

How do I operate on data along each row to either subtract or divide so the result is:

sub_result = [[0,0,0], [0,0,0], [0,0,0]]
div_result = [[1,1,1], [1,1,1], [1,1,1]]

长话短说:如何使用与每一行对应的一维标量数组对二维数组的每一行执行操作?

Long story short: How do I perform an operation on each row of a 2D array with a 1D array of scalars that correspond to each row?

推荐答案

给你.您只需要将 None(或np.newaxis)与广播结合使用:

Here you go. You just need to use None (or alternatively np.newaxis) combined with broadcasting:

In [6]: data - vector[:,None]
Out[6]:
array([[0, 0, 0],
       [0, 0, 0],
       [0, 0, 0]])

In [7]: data / vector[:,None]
Out[7]:
array([[1, 1, 1],
       [1, 1, 1],
       [1, 1, 1]])

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