Alan I posted this on the scipy list:
I have a working program with b=Ax, where A is a large sparse matrix. However, I need the int8 support in the sparse library to utilize much larger matrices. I managed to get hold of a numpy svn 5066 and scipy svn 4167 build, and b=Ax now returns garbage results. Nothing was changed in the program except replacing getrow with .todense() and I checked these to make sure the right rows were being picked up. Wish I could point out where exactly the problem lies but there was no Traceback just the wrong results but it can safely be assumed it is with the numpy/scipy matrix support. Any ideas? Dinesh ----- Original Message ----- From: Alan G Isaac To: Discussion of Numerical Python Sent: Friday, April 25, 2008 11:03 AM Subject: Re: [Numpy-discussion] Does Unreasonable Matrix Behavior affectScipy Sparse On Fri, 25 Apr 2008, Dinesh B Vadhia apparently wrote: > where A is sparse using scipy.sparse. ... I'm now using > the latest svn and b = Ax 1. Please post a small example. 2. Do you have the *very* latest SVN (post r5084)? Cheers, Alan Isaac
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