Free Python optimization framework

Thursday, August 7, 2008

Updates in 1) oofun doc 2) ralg

1. Some changes for NLP/NSP ralg solver have been made. A personal wiki page for ralg has been committed.

2. I have added new entry to openopt doc page about how to use oofun to prevent recalculating same parts of code.
(This is rather common problem, mentioned for example here and here).

Let me note once again that calling df(x1) doesn't guarantee that f(x1) (i.e. in same point) was called immediately before the df call (and same to c, h, dc, dh). Still in 90-95% cases it's true, so it would be convenient to check and (if input, according to dependencies, is same) substitute already calculated values automatically.

So oofun is an implementation of possible solutions to the issue. There are some other convenient tools based on oofun usage, already available in OO code. Still lots of other oofun-related work in Kernel remains to be done (recursive 1st derivatives, implementation of oovar etc).

Of course oofun concept isn't something new, for example, something like this is present in YALMIP (free MATLAB toolbox for some numerical optimization problems, translates YALMIP scripts to MATLAB). Also, there is some similar work involving in our dept using Visual C and Rational Rose.

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