scipy.sparse.

triu#

scipy.sparse.triu(A, k=0, format=None)[source]#

Return the upper triangular portion of a sparse array or matrix

Returns the elements on or above the k-th diagonal of A.

k = 0 corresponds to the main diagonal
k > 0 is above the main diagonal
k < 0 is below the main diagonal

Parameters:

Adense or sparse array or matrix: Matrix whose upper trianglar portion is desired.
kintegeroptional: The bottom-most diagonal of the upper triangle.
formatstring: Sparse format of the result, e.g. format=”csr”, etc.

Returns:

Lsparse array or matrix: Upper triangular portion of A in sparse format. Sparse array if A is a sparse array, otherwise matrix.

See also

tril: lower triangle in sparse format

Examples

>>> from scipy.sparse import csr_array, triu
>>> A = csr_array([[1, 2, 0, 0, 3], [4, 5, 0, 6, 7], [0, 0, 8, 9, 0]],
...                dtype='int32')
>>> A.toarray()
array([[1, 2, 0, 0, 3],
       [4, 5, 0, 6, 7],
       [0, 0, 8, 9, 0]], dtype=int32)
>>> triu(A).toarray()
array([[1, 2, 0, 0, 3],
       [0, 5, 0, 6, 7],
       [0, 0, 8, 9, 0]], dtype=int32)
>>> triu(A).nnz
8
>>> triu(A, k=1).toarray()
array([[0, 2, 0, 0, 3],
       [0, 0, 0, 6, 7],
       [0, 0, 0, 9, 0]], dtype=int32)
>>> triu(A, k=-1).toarray()
array([[1, 2, 0, 0, 3],
       [4, 5, 0, 6, 7],
       [0, 0, 8, 9, 0]], dtype=int32)
>>> triu(A, format='csc')
<Compressed Sparse Column sparse array of dtype 'int32'
    with 8 stored elements and shape (3, 5)>