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Module « scipy.sparse »

Fonction bmat - module scipy.sparse

Signature de la fonction bmat

def bmat(blocks, format=None, dtype=None) 

Description

help(scipy.sparse.bmat)

Build a sparse array or matrix from sparse sub-blocks

Note: `block_array` is preferred over `bmat`. They are the same function
except that `bmat` can return a deprecated sparse matrix.
`bmat` returns a coo_matrix if none of the inputs are a sparse array.

.. warning::

    This function returns a sparse matrix -- not a sparse array.
    You are encouraged to use ``block_array`` to take advantage
    of the sparse array functionality.

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

Returns
-------
bmat : sparse matrix or array
    If any block in blocks is a sparse array, return a sparse array.
    Otherwise return a sparse matrix.

    If you want a sparse array built from blocks that are not sparse
    arrays, use ``block_array()``.

See Also
--------
block_array

Examples
--------
>>> from scipy.sparse import coo_array, bmat
>>> A = coo_array([[1, 2], [3, 4]])
>>> B = coo_array([[5], [6]])
>>> C = coo_array([[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]])

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