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
- Adense or sparse 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 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>