def diags(self, format='dia'):
"""Return a regular sparse matrix of specified format
Parameters
----------
format : str, optional
Choice of matrix type (see scipy.sparse.diags)
- dia - Sparse matrix with DIAgonal storage
- csr - Compressed sparse row
Note
----
This method does not return the matrix scaled by self.scale. Make sure
to include the scale if the returned matrix is to be used in further
calculations
"""
if self._diags is None:
self._diags = sp_diags(list(self.values()),
list(self.keys()),
shape=self.shape,
format=format)
if self._diags.format != format:
self._diags = sp_diags(list(self.values()),
list(self.keys()),
shape=self.shape,
format=format)
return self._diags
def diags(self, format='dia'):
"""Return a regular sparse matrix of specified format
Parameters
----------
format : str, optional
Choice of matrix type (see scipy.sparse.diags)
- dia - Sparse matrix with DIAgonal storage
- csr - Compressed sparse row
Note
----
This method returns the matrix scaled by self.scale.
"""
#if self._diags.shape != self.shape or self._diags.format != format:
self._diags = sp_diags(list(self.values()), list(self.keys()),
shape=self.shape, format=format)
scale = self.scale
if isinstance(scale, np.ndarray):
scale = np.atleast_1d(scale).item()
self._diags = self._diags*scale
return self._diags