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