From: pp on
I am currently dealing with sparse matrices and have doubts on whether
we can use
1.) dot (for matrix multiplication) and inv (inverse) operations of
numpy on sparse matrices of CSR format.

I initially constructed my sparse matrix using COO format and then
converted it to CSR format now I want to know whether normal inverse
and matrix multiplications work with sparse csr matrices.

Also can these operations be applied directly to csr matrices


Thanks a lot
From: pp on
I tried csr_matrix.dot(A,N) where A and N are two sparse matrices.
is it correct for multiplication of two sparse matrices ?
I still do not now how to perform matrix inversion for a sparse
matrix. Can anyone please help.

Thanks!!

On Apr 19, 12:03 am, pp <parul.pande...(a)gmail.com> wrote:
> I am currently dealing with sparse matrices and have doubts on whether
> we can use
> 1.) dot (for matrix multiplication) and inv (inverse) operations of
> numpy on sparse matrices of CSR format.
>
> I initially constructed my sparse matrix using COO format and then
> converted it to CSR format now I want to know whether normal inverse
> and matrix multiplications work with sparse csr matrices.
>
> Also can these operations be applied directly to csr matrices
>
> Thanks a lot

From: Robert Kern on
On 4/19/10 1:03 AM, pp wrote:
> I am currently dealing with sparse matrices and have doubts on whether
> we can use
> 1.) dot (for matrix multiplication) and inv (inverse) operations of
> numpy on sparse matrices of CSR format.
>
> I initially constructed my sparse matrix using COO format and then
> converted it to CSR format now I want to know whether normal inverse
> and matrix multiplications work with sparse csr matrices.
>
> Also can these operations be applied directly to csr matrices

You will want to ask scipy questions on the scipy mailing list.

http://www.scipy.org/Mailing_Lists

--
Robert Kern

"I have come to believe that the whole world is an enigma, a harmless enigma
that is made terrible by our own mad attempt to interpret it as though
it had
an underlying truth."
-- Umberto Eco

From: Helmut Jarausch on
On 04/19/10 08:03, pp wrote:
> I am currently dealing with sparse matrices and have doubts on whether
> we can use
> 1.) dot (for matrix multiplication) and inv (inverse) operations of
> numpy on sparse matrices of CSR format.
>

I don't know of any use of the inverse of a sparse matrix.
Note, in nearly all cases the inverse of a sparse matrix is a full matrix.
Instead of inverting a matrix solve a linear system with that matrix.
What do you need the inverse for?

Helmut.


--
Helmut Jarausch

Lehrstuhl fuer Numerische Mathematik
RWTH - Aachen University
D 52056 Aachen, Germany