Expose solver options in LAPACK for eigh
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- Python
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Description
LAPACK has multiple algorithms for computing eigensystems for symmetric matrices, although NumPy only seems to use the default method. It would be useful to expose this option so that users can select which approach to use since some may be better than others for large matrix problems.
Contributor guide
First steps
- Read the whole issue, then the project's contributing guide.
- Comment on the issue to say you are picking it up — it saves two people doing the same work.
- Fork the repository and make your change on a branch.
- Open a pull request that references the issue number.
Research direction
Start by tracing NumPy's eigh entry point and its LAPACK integration to identify how the current default eigensolver is selected. Determine the API scope for exposing alternate LAPACK algorithms, and consider how users would select them for large symmetric-matrix problems; done means the option is available through eigh and its behavior is covered.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- python
- Domain
- data
- Issue type
- Feature
- Difficulty
- 5/5
- Estimated time
- Over a week
- Activity status
- Stale
- Clarity
- Mostly clear
- Newbie friendliness
- 35/100