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mask_indices(n, mask_func, k=0)

Assume :None:None:`mask_func` is a function that, for a square array a of size (n, n) with a possible offset argument k, when called as mask_func(a, k) returns a new array with zeros in certain locations (functions like triu or tril do precisely this). Then this function returns the indices where the non-zero values would be located.

Notes

versionadded

Parameters

n : int: The returned indices will be valid to access arrays of shape (n, n).
mask_func : callable: A function whose call signature is similar to that of triu , tril . That is, mask_func(x, k) returns a boolean array, shaped like :None:None:`x`. k is an optional argument to the function.
k : scalar: An optional argument which is passed through to :None:None:`mask_func`. Functions like triu , tril take a second argument that is interpreted as an offset.

Returns

indices : tuple of arrays.: The n arrays of indices corresponding to the locations where mask_func(np.ones((n, n)), k) is True.

Return the indices to access (n, n) arrays, given a masking function.

Examples

These are the indices that would allow you to access the upper triangular part of any 3x3 array:

>>> iu = np.mask_indices(3, np.triu)

For example, if a is a 3x3 array:

>>> a = np.arange(9).reshape(3, 3)
... a
array([[0, 1, 2],
       [3, 4, 5],
       [6, 7, 8]])

>>> a[iu]
array([0, 1, 2, 4, 5, 8])

An offset can be passed also to the masking function. This gets us the indices starting on the first diagonal right of the main one:

>>> iu1 = np.mask_indices(3, np.triu, 1)

with which we now extract only three elements:

>>> a[iu1]
array([1, 2, 5])

See :

Back References

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

numpy.tril_indices numpy.triu_indices

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