From: pp on 19 Apr 2010 02:03 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 19 Apr 2010 03:38 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 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 19 Apr 2010 15:14 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 21 Apr 2010 04:14 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