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

Notes

versionadded

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
versionadded

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 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 a ndarray of shape(n, n).

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

See Also

mask_indices

generic function accepting an arbitrary mask function.

tril
tril_indices

similar function, for lower-triangular.

triu

Examples

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)
... iu2 = np.triu_indices(4, 2)

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):

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

Back References

The following pages refer to to this document either explicitly or contain code examples using this.

numpy.mask_indices numpy.triu_indices_from numpy.tril_indices dask.array.routines.triu_indices

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