[SciPy-user] Sparse v. dense matrix, SVD and LSI-like analysis
Travis Oliphant
oliphant at ee.byu.edu
Wed Nov 17 20:06:04 EST 2004
Nick Arnett wrote:
> Travis Oliphant wrote:
>
>> So, while the SVD is not an eigenvector decomposition it is related
>> to one.
>
>
> Right... but I still don't understand the statement, "In any case, all
> of the linalg.* functions only operate on dense arrays, not sparse
> matrices."
>
> Why would linalg.svd not operate on a sparse matrix? I was working
> from the example (below) from your Scipy tutorial, in fact. Would the
> results not be meaningful if the matrix is sparse?
Sparse matrices and dense matrices are very different objects and
linalg.svd is a wrapper around LAPACK which only works on dense matrices.
Getting all linear algebra operations working for sparse matrices is a
very tall order and has not been done yet.
-Travis
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