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Module « numpy »

Fonction triu_indices - module numpy

Signature de la fonction triu_indices

def triu_indices(n, k=0, m=None) 

Description

help(numpy.triu_indices)

Return the indices for the upper-triangle of an (n, m) array.

Parameters
----------
n : int
    The size of the arrays for which the returned indices will
    be valid.
k : int, optional
    Diagonal offset (see `triu` for details).
m : int, optional
    The column dimension of the arrays for which the returned
    arrays will be valid.
    By default `m` is taken equal to `n`.


Returns
-------
inds : tuple, shape(2) of ndarrays, shape(`n`)
    The row and column indices, respectively. The row indices are sorted
    in non-decreasing order, and the correspdonding column indices are
    strictly increasing for each row.

See also
--------
tril_indices : similar function, for lower-triangular.
mask_indices : generic function accepting an arbitrary mask function.
triu, tril

Examples
--------
>>> import numpy as np

Compute two different sets of indices to access 4x4 arrays, one for the
upper triangular part starting at the main diagonal, and one starting two
diagonals further right:

>>> iu1 = np.triu_indices(4)
>>> iu1
(array([0, 0, 0, 0, 1, 1, 1, 2, 2, 3]), array([0, 1, 2, 3, 1, 2, 3, 2, 3, 3]))

Note that row indices (first array) are non-decreasing, and the corresponding
column indices (second array) are strictly increasing for each row.

Here is how they can be used with a sample array:

>>> a = np.arange(16).reshape(4, 4)
>>> a
array([[ 0,  1,  2,  3],
       [ 4,  5,  6,  7],
       [ 8,  9, 10, 11],
       [12, 13, 14, 15]])

Both for indexing:

>>> a[iu1]
array([ 0,  1,  2, ..., 10, 11, 15])

And for assigning values:

>>> a[iu1] = -1
>>> a
array([[-1, -1, -1, -1],
       [ 4, -1, -1, -1],
       [ 8,  9, -1, -1],
       [12, 13, 14, -1]])

These cover only a small part of the whole array (two diagonals right
of the main one):

>>> iu2 = np.triu_indices(4, 2)
>>> a[iu2] = -10
>>> a
array([[ -1,  -1, -10, -10],
       [  4,  -1,  -1, -10],
       [  8,   9,  -1,  -1],
       [ 12,  13,  14,  -1]])

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