order of 10^9
> and 'B' has a condition number on the order of 10^6. I have stored
> them both as "csc" type sparse matrices from the scipy.sparse library.
>
> The part of my code using lobpcg is fairly simple (for the 20 smallest
> eigenvalues):
> ---
umber on the order of 10^9
and 'B' has a condition number on the order of 10^6. I have stored
them both as "csc" type sparse matrices from the scipy.sparse library.
The part of my code using lobpcg is fairly simple (for the 20 smallest
eigenvalues):
-
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 spa
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
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 wrote:
> I am currently dealing w
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
Is there any sparse matrix package compatible with Numeric/Numarray ? Ideally,
the implementation of
a matrix (dense/sparse) should be transparent to the application. However the
APIs of the only
packages I'm aware of -- the Sparse module in Scipy and PySparse --are both
pretty incomplete
compar
