Currently CDF and RDF matrices wrap GSL matrices and use GSL algorithms for part of the computations. After talking with a few lead developers on IRC, it seems that the consensus is that numpy is generally better and has a much, much stronger community. What do people think of moving the RDF and CDF matrices to a numpy backend?
If we do this, then I think that much of the code in RDF and CDF becomes simple calls to numpy, and the current functions that fall back to generic algorithms (like inverse()) also become easy calls to numpy functions which do proper numerical linear algebra. Josh, apparently you did lots of work in this area; I'm particularly interested in hearing your comments. Thanks, Jason --~--~---------~--~----~------------~-------~--~----~ To post to this group, send email to sage-devel@googlegroups.com To unsubscribe from this group, send email to [EMAIL PROTECTED] For more options, visit this group at http://groups.google.com/group/sage-devel URLs: http://www.sagemath.org -~----------~----~----~----~------~----~------~--~---
