numpy.triu_indices(n, k=0, m=None)
[source]
Return the indices for the upper-triangle of an (n, m) array.
Parameters: |
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Returns: |
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See also
tril_indices
mask_indices
New in version 1.4.0.
Compute two different sets of indices to access 4x4 arrays, one for the upper triangular part starting at the main diagonal, and one starting two diagonals further right:
>>> iu1 = np.triu_indices(4) >>> iu2 = np.triu_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[iu1] array([ 0, 1, 2, ..., 10, 11, 15])
And for assigning values:
>>> a[iu1] = -1 >>> a array([[-1, -1, -1, -1], [ 4, -1, -1, -1], [ 8, 9, -1, -1], [12, 13, 14, -1]])
These cover only a small part of the whole array (two diagonals right of the main one):
>>> a[iu2] = -10 >>> a array([[ -1, -1, -10, -10], [ 4, -1, -1, -10], [ 8, 9, -1, -1], [ 12, 13, 14, -1]])
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https://docs.scipy.org/doc/numpy-1.17.0/reference/generated/numpy.triu_indices.html