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

Notes

versionadded

Parameters

n : int

The row dimension of the arrays for which the returned indices will be valid.

k : int, optional

Diagonal offset (see tril 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 of arrays

The indices for the triangle. The returned tuple contains two arrays, each with the indices along one dimension of the array.

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

See Also

mask_indices

generic function accepting an arbitrary mask function.

tril
triu
triu_indices

similar function, for upper-triangular.

Examples

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

>>> il1 = np.tril_indices(4)
... il2 = np.tril_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[il1]
array([ 0,  4,  5, ..., 13, 14, 15])

And for assigning values:

>>> a[il1] = -1
... a array([[-1, 1, 2, 3], [-1, -1, 6, 7], [-1, -1, -1, 11], [-1, -1, -1, -1]])

These cover almost the whole array (two diagonals right of the main one):

>>> a[il2] = -10
... a array([[-10, -10, -10, 3], [-10, -10, -10, -10], [-10, -10, -10, -10], [-10, -10, -10, -10]])
See :

Back References

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

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

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GitHub : /numpy/lib/twodim_base.py#894
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