scipy.sparse.bmat#

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

Build a sparse matrix from sparse sub-blocks

Parameters:

blocksarray_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”). By default an appropriate sparse matrix format is returned. This choice is subject to change.
dtypedtype, optional: The data-type of the output matrix. If not given, the dtype is determined from that of blocks.

Returns:

bmatsparse matrix

See also

block_diag, diags

Examples

>>> 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]]).toarray()
array([[1, 2, 5],
       [3, 4, 6],
       [0, 0, 7]])

>>> bmat([[A, None], [None, C]]).toarray()
array([[1, 2, 0],
       [3, 4, 0],
       [0, 0, 7]])