Comments (1)
Hi, your understanding is correct and you should be able to use the cholesky operator in order to solve the equation. However, if laplacian operator is not a sparse matrix it will be better for you to use solvers from scipy.linalg or numpy.linalg
from scikit-sparse.
Related Issues (20)
- Cannot depend on ```sckit-sparse``` in a clean environment due to early ```numpy``` import. HOT 20
- Numerical inconsistency between scikit-sparse and numpy Cholesky's HOT 11
- Scikit-Sparse Installation 'Could not find suitable distribution for Requirement.parse('cython')' HOT 1
- CholmodNotPositiveDefiniteError inconsistent HOT 5
- Working With CHOLMOD Built from Source HOT 1
- convert csc_matrix or lil_matrix to tensor form
- Python 3.9 support (regenerate with new cython) HOT 2
- xx HOT 1
- Can't find "cholmod.h" while installing using pip on macOS HOT 2
- computing selective inverse efficiently
- Support GPU?
- Support Apple silicon? HOT 8
- There is a "Process finished with exit code -1073741819 (0xC0000005)" HOT 1
- Adding citations
- Adapt package to work with SciPy's 'LinearOperator' interface
- Scikit-sparse not (default) available for Ubuntu 22 HOT 2
- Python 3.10? HOT 1
- Problems with installation
- Import Error: symbol not found when importing sksparse.cholmod HOT 2
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from scikit-sparse.