netneurotools.utils.get_triu

netneurotools.utils.get_triu(data, k=1)[source]

Return vectorized version of upper triangle from data.

Parameters:

data ((N, N) array_like) – Input data
k (int, optional) – Which diagonal to select from (where primary diagonal is 0). Default: 1

Returns:

triu – Upper triangle of data

Return type:

(N * N-1 / 2) numpy.ndarray

Examples

>>> from netneurotools import utils

>>> X = np.array([[1, 0.5, 0.25], [0.5, 1, 0.33], [0.25, 0.33, 1]])
>>> tri = utils.get_triu(X)
>>> tri
array([0.5 , 0.25, 0.33])