[SciPy-user] Sparse v. dense matrix, SVD and LSI-like analysis

Travis Oliphant oliphant at ee.byu.edu
Wed Nov 17 19:06:04 CST 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



More information about the SciPy-user mailing list