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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.

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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