SciPy

scipy.sparse.triu

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

Return the upper triangular portion of a matrix in sparse format

Returns the elements on or above the k-th diagonal of the matrix A.
  • k = 0 corresponds to the main diagonal
  • k > 0 is above the main diagonal
  • k < 0 is below the main diagonal
Parameters:
A : dense or sparse matrix

Matrix whose upper trianglar portion is desired.

k : integer

The bottom-most diagonal of the upper triangle.

format : string

Sparse format of the result, e.g. format=”csr”, etc.

Returns:
L : sparse matrix

Upper triangular portion of A in sparse format.

See also

tril
lower triangle in sparse format

Examples

>>> from scipy.sparse import csr_matrix, triu
>>> A = csr_matrix([[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]])
>>> triu(A).toarray()
array([[1, 2, 0, 0, 3],
       [0, 5, 0, 6, 7],
       [0, 0, 8, 9, 0]])
>>> 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]])
>>> triu(A, k=-1).toarray()
array([[1, 2, 0, 0, 3],
       [4, 5, 0, 6, 7],
       [0, 0, 8, 9, 0]])
>>> triu(A, format='csc')
<3x5 sparse matrix of type '<class 'numpy.int32'>'
        with 8 stored elements in Compressed Sparse Column format>

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