flopscope.

flopscope.numpy.diag_indices

fnp.diag_indices(n, ndim=2)[flopscope source][numpy source]

Return the indices to access the main diagonal of an array.

Adapted from NumPy docs np.diag_indices

Areacore
Typefree
NumPy Refnp.diag_indices
Cost
0
Flopscope Context

Return indices to access main diagonal of n-D array.

This returns a tuple of indices that can be used to access the main diagonal of an array a with a.ndim >= 2 dimensions and shape (n, n, ..., n). For a.ndim = 2 this is the usual diagonal, for a.ndim > 2 this is the set of indices to access a[i, i, ..., i] for i = [0..n-1].

Parameters

n:int

The size, along each dimension, of the arrays for which the returned indices can be used.

ndim:int, optional

The number of dimensions.

See also

Examples

>>> import flopscope.numpy as fnp

Create a set of indices to access the diagonal of a (4, 4) array:

>>> di = flops.diag_indices(4)
>>> di
(array([0, 1, 2, 3]), array([0, 1, 2, 3]))
>>> a = flops.arange(16).reshape(4, 4)
>>> a
array([[ 0,  1,  2,  3],
       [ 4,  5,  6,  7],
       [ 8,  9, 10, 11],
       [12, 13, 14, 15]])
>>> a[di] = 100
>>> a
array([[100,   1,   2,   3],
       [  4, 100,   6,   7],
       [  8,   9, 100,  11],
       [ 12,  13,  14, 100]])

Now, we create indices to manipulate a 3-D array:

>>> d3 = flops.diag_indices(2, 3)
>>> d3
(array([0, 1]), array([0, 1]), array([0, 1]))

And use it to set the diagonal of an array of zeros to 1:

>>> a = flops.zeros((2, 2, 2), dtype=int)
>>> a[d3] = 1
>>> a
array([[[1, 0],
        [0, 0]],
       [[0, 0],
        [0, 1]]])