在Numpy中高效地构建“滚动"行矩阵 [英] Building a matrix of 'rolled' rows efficiently in Numpy

问题描述

我想从一维数组构造一个(n,n)数组，其中每行相对于上一行移动(带换行).下面的代码可以做到这一点:

I'd like to construct a (n,n)-array from a one dimensional array, where each row is shifted (with wrapping) by one relative to the previous one. The following code does this:

import numpy as np

r = np.array([1, 2, 3, 4, 5])
n = len(r)
MM = np.zeros((n, n), dtype=r.dtype)
for k in range(n):
    MM[k, :] = np.roll(r, k)

print(MM)

其结果是:

[[1 2 3 4 5]
 [5 1 2 3 4]
 [4 5 1 2 3]
 [3 4 5 1 2]
 [2 3 4 5 1]]

对于Numpy中的大型r，是否有一种方法可以更快地执行Numpy，即避免for循环?

Is there a way to do this Numpy faster, i.e., avoiding the for-loop, for large r in Numpy?

推荐答案

看看或 scipy.linalg.toeplitz

In [257]: toeplitz(np.roll(r[::-1], 1), r)
Out[257]: 
array([[1, 2, 3, 4, 5],
       [5, 1, 2, 3, 4],
       [4, 5, 1, 2, 3],
       [3, 4, 5, 1, 2],
       [2, 3, 4, 5, 1]])

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