如何“扩展"一个numpy数组? [英] How to "scale" a numpy array?

问题描述

我想将一个形状为 (h, w) 的数组缩放 n 倍，从而得到一个形状为 (h*n, w*n) 的数组.

I would like to scale an array of shape (h, w) by a factor of n, resulting in an array of shape (h*n, w*n), with the.

假设我有一个 2x2 数组:

Say that I have a 2x2 array:

array([[1, 1],
       [0, 1]])

我想将数组缩放为 4x4:

I would like to scale the array to become 4x4:

array([[1, 1, 1, 1],
       [1, 1, 1, 1],
       [0, 0, 1, 1],
       [0, 0, 1, 1]])

即，将原始数组中每个单元格的值复制到结果数组中的 4 个对应单元格中.假设任意数组大小和缩放因子，最有效的方法是什么?

That is, the value of each cell in the original array is copied into 4 corresponding cells in the resulting array. Assuming arbitrary array size and scaling factor, what's the most efficient way to do this?

推荐答案

您应该使用 Kronecker 产品, numpy.kron:

计算 Kronecker 乘积，一个由第二个数组的块组成的复合数组，由第一个缩放

Computes the Kronecker product, a composite array made of blocks of the second array scaled by the first

import numpy as np
a = np.array([[1, 1],
              [0, 1]])
n = 2
np.kron(a, np.ones((n,n)))

提供你想要的:

array([[1, 1, 1, 1],
       [1, 1, 1, 1],
       [0, 0, 1, 1],
       [0, 0, 1, 1]])

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