scipy.sparse.bmat(blocks, format=None, dtype=None)[source]

Build a sparse matrix from sparse sub-blocks

Parameters :

blocks : array_like

Grid of sparse matrices with compatible shapes. An entry of None implies an all-zero matrix.

format : {‘bsr’, ‘coo’, ‘csc’, ‘csr’, ‘dia’, ‘dok’, ‘lil’}, optional

The sparse format of the result (e.g. “csr”). If not given, the matrix is returned in “coo” format.

dtype : dtype specifier, optional

The data-type of the output matrix. If not given, the dtype is determined from that of blocks.

Returns :

bmat : sparse matrix

A “coo” sparse matrix or type of sparse matrix identified by format.

See also

block_diag, diags


>>> from scipy.sparse import coo_matrix, bmat
>>> A = coo_matrix([[1,2],[3,4]])
>>> B = coo_matrix([[5],[6]])
>>> C = coo_matrix([[7]])
>>> bmat( [[A,B],[None,C]] ).todense()
matrix([[1, 2, 5],
        [3, 4, 6],
        [0, 0, 7]])
>>> bmat( [[A,None],[None,C]] ).todense()
matrix([[1, 2, 0],
        [3, 4, 0],
        [0, 0, 7]])

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