Collect tools to manipulate sparse and/or mixed dense/sparse matrices.
Collect tools to manipulate sparse and/or mixed dense/sparse matrices.
author: S. Maraniello date: Dec 2018
Comment: manipulating large linear system may require using both dense and sparse matrices. While numpy/scipy automatically handle most operations between mixed dense/sparse arrays, some (e.g. dot product) require more attention. This library collects methods to handle these situations.
Classes: scipy.sparse matrices are wrapped so as to ensure compatibility with numpy arrays upon conversion to dense. - csc_matrix: this is a wrapper of scipy.csc_matrix. - SupportedTypes: types supported for operations - WarningTypes: due to some bugs in scipy (v.1.1.0), sum (+) operations between np.ndarray and scipy.sparse matrices can result in numpy.matrixlib.defmatrix.matrix types. This list contains such undesired types that can result from dense/sparse operations and raises a warning if required. (b) convert these types into numpy.ndarrays.
Methods: - dot: handles matrix dot products across different types. - solve: solves linear systems Ax=b with A and b dense, sparse or mixed. - dense: convert matrix to numpy array
Warning: - only sparse types into SupportedTypes are supported!
To Do: - move these methods into an algebra module?