简体   繁体   中英

How to construct the following matrix elegantly in numpy?

Suppose I have a 5 dimensional matrix v and now I want a new matrix D fulfilling

D[a, b, n, m, d] = v[a, b, n, n, d]-v[a, b, m, m, d].

How do I elegantly do this in numpy?

How do you want to change the dimensionality? You can reshape it like this

import numpy as np

a, b, n, d = 2, 3, 4, 5
v = np.zeros((a, b, n, n, d))
D = v.reshape((a, b, n*n, d))

我发现einsum可以做到这一点:

D = np.einsum('abiic->abic', v)[..., None, :] - np.einsum('abiic->abic', v)[:, :, None, ...]

The technical post webpages of this site follow the CC BY-SA 4.0 protocol. If you need to reprint, please indicate the site URL or the original address.Any question please contact:yoyou2525@163.com.

 
粤ICP备18138465号  © 2020-2024 STACKOOM.COM