def block_diag(mats, format=None, dtype=None):
"""
Build a block diagonal sparse matrix from provided matrices.
.. versionadded:: 0.11.0
Parameters
----------
A, B, ... : sequence of matrices
Input matrices.
format : str, 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
-------
res : sparse matrix
See Also
--------
bmat, diags
Examples
--------
>>> A = coo_matrix([[1, 2], [3, 4]])
>>> B = coo_matrix([[5], [6]])
>>> C = coo_matrix([[7]])
>>> block_diag((A, B, C)).todense()
matrix([[1, 2, 0, 0],
[3, 4, 0, 0],
[0, 0, 5, 0],
[0, 0, 6, 0],
[0, 0, 0, 7]])
"""
nmat = len(mats)
rows = []
for ia, a in enumerate(mats):
row = [None]*nmat
if issparse(a):
row[ia] = a
else:
row[ia] = coo_matrix(a)
rows.append(row)
return bmat(rows, format=format, dtype=dtype)
def block_diag(mats, format=None, dtype=None):
"""
Build a block diagonal sparse matrix from provided matrices.
.. versionadded:: 0.11.0
Parameters
----------
A, B, ... : sequence of matrices
Input matrices.
format : str, 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
-------
res : sparse matrix
See Also
--------
bmat, diags
Examples
--------
>>> A = coo_matrix([[1, 2], [3, 4]])
>>> B = coo_matrix([[5], [6]])
>>> C = coo_matrix([[7]])
>>> block_diag((A, B, C)).todense()
matrix([[1, 2, 0, 0],
[3, 4, 0, 0],
[0, 0, 5, 0],
[0, 0, 6, 0],
[0, 0, 0, 7]])
"""
nmat = len(mats)
rows = []
for ia, a in enumerate(mats):
row = [None] * nmat
if issparse(a):
row[ia] = a
else:
row[ia] = coo_matrix(a)
rows.append(row)
return bmat(rows, format=format, dtype=dtype)