How to fill specific elements of a matrix knowing their indices with values from a column vector

Question

How can I fill the elements of the lower triangular part of a matrix, including the diagonal, with values from a column vector?

For example i have :

m=np.zeros((3,3))
n=np.array([[1],[1],[1],[1],[1],[1]])   #column vector

I want to replace values which have indices of (0,0),(1,0),(1,1),(2,0),(2,1),(2,2) from m with the vector n, so I get:

m=np.array([[1,0,0],[1,1,0],[1,1,1]])

Then I want make the same operation to m.T to get as a result:

m=np.array([[1,1,1],[1,1,1],[1,1,1]])

Can someone help me please? n should be a vector with shape(6,1)

indices are found by just typing np.tril_indices(3) because in each iteration i want to replace the lower triangular part of the matrix — Wejdene, Jun 17 '20 at 11:59

score 1 · Accepted Answer · answered Jun 17 '20 at 11:47

I'm not sure if there's going to be a clever numpy-specific way of doing this, but it looks relatively straightforward like this:

import numpy as np
m=np.zeros((3,3))
n=np.array([[1],[1],[1],[1],[1],[1]])   #column vector
indices=[(0,0),(1,0),(1,1),(2,0),(2,1),(2,2)]

for ix, index in enumerate(indices):
    m[index] = n[ix][0]
print(m)

for ix, index in enumerate(indices):
    m.T[index] = n[ix][0]
print(m)

Output of the above is:

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

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

How to fill specific elements of a matrix knowing their indices with values from a column vector

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