diag_indices(n, ndim=2)
This returns a tuple of indices that can be used to access the main diagonal of an array :None:None:`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]
.
The size, along each dimension, of the arrays for which the returned indices can be used.
The number of dimensions.
Return the indices to access the main diagonal of an array.
Create a set of indices to access the diagonal of a (4, 4) array:
>>> di = np.diag_indices(4)
... di (array([0, 1, 2, 3]), array([0, 1, 2, 3]))
>>> 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]])
>>> 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 = np.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 = np.zeros((2, 2, 2), dtype=int)See :
... a[d3] = 1
... a array([[[1, 0], [0, 0]], [[0, 0], [0, 1]]])
The following pages refer to to this document either explicitly or contain code examples using this.
numpy.fill_diagonal
numpy.diag_indices_from
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