[Scipy-tickets] [SciPy] #1897: expmFrechet would be nice

SciPy Trac scipy-tickets@scipy....
Sun Apr 21 23:19:11 CDT 2013


#1897: expmFrechet would be nice
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 Reporter:  unknown (google)              |       Owner:  pv         
     Type:  enhancement                   |      Status:  new        
 Priority:  low                           |   Milestone:  Unscheduled
Component:  scipy.linalg                  |     Version:  0.12.0     
 Keywords:  linalg matfuncs expm frechet  |  
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 I have an application where I need to compute the matrix exponential
 expm(A) and also the upper right block of expm([[A, E], [0, A]]).

 Luckily, there's a detailed explanation of a fast algorithm to do this.
 http://eprints.ma.man.ac.uk/1218/

 It is even available in R as expmFrechet.
 http://cran.r-project.org/web/packages/expm/expm.pdf

 Perhaps if I would try to independently and manually transcribe Higham's
 published algorithm into python code and paste it into this ticket, then
 it would make its way into scipy.linalg?  I would not need a sparse matrix
 implementation, and I would only need double float precision.  I would
 probably not be up to the task of making a complete pull request on
 github.

 Maybe it could become available, using a function signature like in the R
 docs, as scipy.linalg.expm_frechet(A, E, method="SPS", compute_expm=True)
 where A and E are NxN double precision numpy ndarrays, and it would return
 either the two NxN output matrices (expm_frechet_AE, expm_A) or just the
 single NxN output matrix expm_frechet_AE depending on the value of the
 compute_expm arg.  The method arg would be either "SPS" for the clever
 algorithm or "blockEnlarge" for the dumb algorithm.  Testing would be very
 simple because expm is already implemented.

-- 
Ticket URL: <http://projects.scipy.org/scipy/ticket/1897>
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