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)>