Source code for openmdao.matrices.csc_matrix

"""Define the CSCmatrix class."""

import numpy as np
from scipy.sparse import csc_matrix

from openmdao.matrices.coo_matrix import COOMatrix

[docs]class CSCMatrix(COOMatrix): """ Sparse matrix in Compressed Col Storage format. """ def _build(self, num_rows, num_cols, system=None): """ Allocate the matrix. Parameters ---------- num_rows : int number of rows in the matrix. num_cols : int number of cols in the matrix. system : <System> owning system. """ super()._build(num_rows, num_cols, system) self._coo = self._matrix def _pre_update(self): """ Do anything that needs to be done at the start of AssembledJacobian._update. """ self._matrix = self._coo def _post_update(self): """ Do anything that needs to be done at the end of AssembledJacobian._update. """ coo = self._coo # this will add any repeated entries together # NOTE: The CSC matrix was created in the following way instead of using self._coo.tocsc() # because on older versions of scipy, self._coo.tocsc() reuses the row/col arrays and the # result is that self._coo.row and self._coo.col get scrambled after csc conversion. self._matrix = csc_matrix((, (coo.row, coo.col)), shape=coo.shape) def _convert_mask(self, mask): """ Convert the mask to the format of this sparse matrix (CSC, etc.) from COO. Parameters ---------- mask : ndarray The mask of indices to zero out. Returns ------- ndarray The converted mask array. """ coo = self._coo csc = csc_matrix((mask, (coo.row, coo.col)), shape=coo.shape) return
[docs] def set_complex_step_mode(self, active): """ Turn on or off complex stepping mode. When turned on, the value in each subjac is cast as complex, and when turned off, they are returned to real values. Parameters ---------- active : bool Complex mode flag; set to True prior to commencing complex step. """ if active: if 'complex' not in self._matrix.dtype.__str__(): = self._matrix.dtype = complex = self._coo.dtype = complex else: = self._matrix.dtype = np.float = self._coo.dtype = np.float