Add large matrix inversion
This PR adds large matrix inversion.
I feel it might fit here under the category of "A place to experiment with fast linear algebra routines written in Julia" It is hard to find a home for this code.
But it is really quiet useful and fast.
It was mostly written by Mahdi Jamei. (Who I do not think is on Github). I just did some cleanup, and optimisations and am handling releasing it somewhere open source
Codecov Report
Merging #46 into master will decrease coverage by
21.88%. The diff coverage is45.45%.
@@ Coverage Diff @@
## master #46 +/- ##
===========================================
- Coverage 72.77% 50.88% -21.89%
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Files 10 11 +1
Lines 1381 1411 +30
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- Hits 1005 718 -287
- Misses 376 693 +317
| Impacted Files | Coverage Δ | |
|---|---|---|
| src/inv.jl | 45.45% <45.45%> (ø) |
|
| src/eigenGeneral.jl | 34.78% <0%> (-44.1%) |
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| src/householder.jl | 39.74% <0%> (-42.54%) |
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| src/cholesky.jl | 67.64% <0%> (-32.36%) |
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| src/qr.jl | 72.54% <0%> (-25.5%) |
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| src/tridiag.jl | 53.84% <0%> (-23.08%) |
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| src/lapack.jl | 28.04% <0%> (-22.77%) |
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| src/eigenSelfAdjoint.jl | 69.44% <0%> (-16.95%) |
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| src/svd.jl | 59.1% <0%> (-16.6%) |
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| src/rectfullpacked.jl | 78.57% <0%> (-7.54%) |
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| ... and 2 more |
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@andreasnoack can you take a look at this?
I have quite a bit on my plate for the time being but will review this eventually.
bump
May I suggest we merge this so long as the tests are passing? @oxinabox In case you would be up for refreshing, that is.
Do we know anything about the error properties of this algorithm?
I don't. I know in practice it is not great, but it is usable. I didn't do the math for working this out, i just tidied up the code and made the PR