Python identity shift matrix

Question

Is there any inline command to generate a shifted identity matrix in python with numpy?

A=[ ...
    0, 1, 0, 0, 0, 0, 0, 0, 0, 0
    0, 0, 1, 0, 0, 0, 0, 0, 0, 0
    0, 0, 0, 1, 0, 0, 0, 0, 0, 0
    0, 0, 0, 0, 1, 0, 0, 0, 0, 0
    0, 0, 0, 0, 0, 1, 0, 0, 0, 0
    0, 0, 0, 0, 0, 0, 1, 0, 0, 0
    0, 0, 0, 0, 0, 0, 0, 1, 0, 0
    0, 0, 0, 0, 0, 0, 0, 0, 1, 0
    0, 0, 0, 0, 0, 0, 0, 0, 0, 1
    0, 0, 0, 0, 0, 0, 0, 0, 0, 0]

Dani Mesejo Dani Mesejo · Accepted Answer · 2018-12-21T17:28:05

If I understood correctly you could use the k parameter of np.eye:

import numpy as np

result = np.eye(10, 10, 1)
print(result)

Output

[[0. 1. 0. 0. 0. 0. 0. 0. 0. 0.]
 [0. 0. 1. 0. 0. 0. 0. 0. 0. 0.]
 [0. 0. 0. 1. 0. 0. 0. 0. 0. 0.]
 [0. 0. 0. 0. 1. 0. 0. 0. 0. 0.]
 [0. 0. 0. 0. 0. 1. 0. 0. 0. 0.]
 [0. 0. 0. 0. 0. 0. 1. 0. 0. 0.]
 [0. 0. 0. 0. 0. 0. 0. 1. 0. 0.]
 [0. 0. 0. 0. 0. 0. 0. 0. 1. 0.]
 [0. 0. 0. 0. 0. 0. 0. 0. 0. 1.]
 [0. 0. 0. 0. 0. 0. 0. 0. 0. 0.]]

from the linked documentation:

k : int, optional Index of the diagonal: 0 (the default) refers to the main diagonal, a positive value refers to an upper diagonal, and a negative value to a lower diagonal.

Python identity shift matrix

1 Answers