numpy.mask_indices¶

numpy.
mask_indices
(n, mask_func, k=0)[source]¶ Return the indices to access (n, n) arrays, given a masking function.
Assume mask_func is a function that, for a square array a of size
(n, n)
with a possible offset argument k, when called asmask_func(a, k)
returns a new array with zeros in certain locations (functions liketriu
ortril
do precisely this). Then this function returns the indices where the nonzero values would be located.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 x. k is an optional argument to the function. k : scalar
An optional argument which is passed through to 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.
See also
Notes
New in version 1.4.0.
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])