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## PDL::Opt::Simplex Free Download

### PDL::Opt::Simplex Ranking & Summary

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License: Perl Artistic License
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Publisher: Chris Marshall
Homepage: http://gempire.sourceforge.net/

### PDL::Opt::Simplex Description

Simplex optimization routines
PDL::Opt::Simplex is a Perl module with Simplex optimization routines.SYNOPSIS use PDL::Opt::Simplex; (\$optimum,\$ssize) = simplex(\$init,\$initsize,\$minsize, \$maxiter, sub {evaluate_func_at(\$_[0])}, sub {display_simplex(\$_[0])} );This package implements the commonly used simplex optimization algorithm. The basic idea of the algorithm is to move a "simplex" of N+1 points in the N-dimensional search space according to certain rules. The main benefit of the algorithm is that you do not need to calculate the derivatives of your function.\$init is a 1D vector holding the initial values of the N fitted parameters, \$optimum is a vector holding the final solution.\$initsize is the size of \$init (more...)\$minsize is some sort of convergence criterion (more...) - e.g. \$minsize = 1e-6The sub is assumed to understand more than 1 dimensions and threading. Its signature is 'inp(nparams); [ret]out()'. An example would be sub evaluate_func_at { my(\$xv) = @_; my \$x1 = \$xv->slice("(0)"); my \$x2 = \$xv->slice("(1)"); return \$x1**4 + (\$x2-5)**4 + \$x1*\$x2; }Here \$xv is a vector holding the current values of the parameters being fitted which are then sliced out explicitly as \$x1 and \$x2.\$ssize gives a very very approximate estimate of how close we might be - it might be miles wrong. It is the euclidean distance between the best and the worst vertices. If it is not very small, the algorithm has not converged. Requirements:
· Perl

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### PDL::Opt::Simplex Company

Chris Marshall

WebSite:http://gempire.sourceforge.net/
Company Information: