dpnp.triu_indices_from

dpnp.triu_indices_from(arr, k=0)[source]

Return the indices for the lower-triangle of arr.

For full documentation refer to numpy.triu_indices_from.

Parameters:

arr ({dpnp.ndarray, usm_ndarray}) -- The indices will be valid for square arrays whose dimensions are the same as arr.
k (int, optional) --
Diagonal offset (see dpnp.triu for details).

Default: 0.

Returns:

inds -- The indices for the triangle. The returned tuple contains two arrays, each with the indices along one dimension of the array. Can be used to slice an ndarray of shape(n, n).

Return type:

tuple of dpnp.ndarray

See also

dpnp.triu_indices: Return the indices for the upper-triangle of an (n, m) array.
dpnp.triu: Return upper triangle of an array.
dpnp.tril_indices_from: similar function, for lower-triangular.

Examples

Create a 4 by 4 array.

>>> import dpnp as np
>>> 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]])

Pass the array to get the indices of the upper triangular elements.

>>> triui = np.triu_indices_from(a)
>>> triui
(array([0, 0, 0, 0, 1, 1, 1, 2, 2, 3]),
 array([0, 1, 2, 3, 1, 2, 3, 2, 3, 3]))

>>> a[triui]
array([ 0,  1,  2,  3,  5,  6,  7, 10, 11, 15])

This is syntactic sugar for triu_indices().

>>> np.triu_indices(a.shape[0])
(array([0, 0, 0, 0, 1, 1, 1, 2, 2, 3]),
 array([0, 1, 2, 3, 1, 2, 3, 2, 3, 3]))

Use the k parameter to return the indices for the upper triangular array from the k-th diagonal.

>>> triuim1 = np.triu_indices_from(a, k=1)
>>> a[triuim1]
array([ 1,  2,  3,  6,  7, 11])