[Pysparse-users] transpose operation

[Toine B. <tb...@db...>]

Hi,

What is the most efficient way of transposing a matrix using PySparse?  
A search of the website doesn't yield any results and I don't see any  
transpose method in the list of methods. I must be missing something  
here; I can't imagine there is no fast transpose method available!

I've tried two different ways of calculating the transpose myself:

1) looping through the entries of a matrix M with .items() and then  
simply filling a new sparse matrix with the same values, but transposed.

     def T_ver1( self, M ):
         (rows, cols) = M.shape
         t = spmatrix.ll_mat(cols, rows, M.nnz)
         for (x, y), value in M.items():
             t[y, x] = M[x,y]
         return t

2) I've noticed that using the .dot() method to multiply a matrix with  
the identity matrix is a faster way of getting the transposed matrix M.

     def T_ver2( self, M ):
         (rows, cols) = M.shape
         I = spmatrix.ll_mat(rows, rows, rows)
         for i in xrange(0, rows):
             I[i, i] = 1
         return spmatrix.dot(M, I)):

Method 2 is faster, which I suspect is because the  .dot() function  
using either the C or Fortran code directly. But why is there no  
direct M.transpose() or M.T method to give me the transposed matrix?

Thanks in advance for the help!


Kind regards,
Toine Bogers