Extract upper or lower triangular part of a numpy matrix

Try numpy.triu (triangle-upper) and numpy.tril (triangle-lower).

Code example:

np.triu([[1,2,3],[4,5,6],[7,8,9],[10,11,12]])
array([[ 1,  2,  3],
       [ 4,  5,  6],
       [ 0,  8,  9],
       [ 0,  0, 12]])

To extract the upper triangle values to a flat vector, you can do something like the following:

import numpy as np

a = np.array([[1,2,3],[4,5,6],[7,8,9]])
print(a)

#array([[1, 2, 3],
#       [4, 5, 6],
#       [7, 8, 9]])

a[np.triu_indices(3)]
#or
list(a[np.triu_indices(3)])

#array([1, 2, 3, 5, 6, 9])

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Similarly, for the lower triangle, use np.tril.

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IMPORTANT

If you want to extract the values that are above the diagonal (or below) then use the k argument. This is usually used when the matrix is symmetric.

import numpy as np

a = np.array([[1,2,3],[4,5,6],[7,8,9]])

#array([[1, 2, 3],
#       [4, 5, 6],
#       [7, 8, 9]])

a[np.triu_indices(3, k = 1)]

# this returns the following
array([2, 3, 6])

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EDIT (on 11.11.2019):

To put back the extracted vector into a 2D symmetric array, one can follow my answer here: https://stackoverflow.com/a/58806626/5025009