Comments (4)
I want to see SVD added for sure! Please feel free to work on it.
There currently exists some eigendecomposition. The eigenvalue decomposition works too but only for normal matrices with real eigenvalues. That in itself can probably be improved a lot.
See here for the current code. If you want to make any changes, or have suggestions, let me know!
Note: The current implementations are also just inefficient and should make use of the new MatrixSlice
structs.
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https://gist.github.com/zackmdavis/e65e295205aba03b548011c7401bf9ec
Posting this here for reference.
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I've just merged the PR that resolves #64, sorry it took so long!. @zackmdavis - are you happy to pick up this issue again?
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I found a UofTexas paper which provides pseudo code implementations of lots of SVD algorithms. These may be a little out of scope to begin with - but some of the simpler ones may still be worth a look.
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Related Issues (20)
- (feature?) More flexible inner products HOT 2
- Make `Matrix::from_fn` row-major
- Using assert_*_equal macros in all tests HOT 1
- SVD goes in an infinite loop for certain matrices HOT 2
- Matrix debug info is incorrect on docs homepage? HOT 2
- Computation of numerically stable matrix operations HOT 3
- Add serde support HOT 1
- Eigenvalues goes into infinite loop for certain matrices HOT 8
- Document that Cholesky only uses the lower triangular part HOT 1
- Variance and mean could be calculated in a better way HOT 1
- Adapt matrix factorizations from nalgebra? HOT 5
- SVD algorithm will segfault if matrix has 0 rows or 0 columns
- 'Matrix row counts not equal.' should give matrix dimensions
- Multidimensional tensors
- Hosted documentation out-of-date
- I want to help HOT 4
- Right-multiplication by permutation matrix is inconsistent with representation
- Matrix Operations on Complex Numbers
- API soundness issue in `raw_slice` and `raw_slice_mut` HOT 1
- [Question] Will sparse matrices be supported?
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