00001 // 00002 // Copyright (C) 2004-2008 Greg Landrum and Rational Discovery LLC 00003 // 00004 // @@ All Rights Reserved @@ 00005 // 00006 00007 namespace BFGSOpt { 00008 const double FUNCTOL=1e-4; //!< Default tolerance for function convergence in the minimizer 00009 const double MOVETOL=1e-7; //!< Default tolerance for x changes in the minimizer 00010 const int MAXITS=200; //!< Default maximum number of iterations 00011 const double EPS=3e-8; //!< Default gradient tolerance in the minimizer 00012 const double TOLX=4.*EPS; //!< Default direction vector tolerance in the minimizer 00013 const double MAXSTEP=100.0; //!< Default maximim step size in the minimizer 00014 00015 //! Do a Quasi-Newton minimization along a line. 00016 /*! 00017 See Numerical Recipes in C, Section 9.7 for a description of the algorithm. 00018 00019 \param dim the dimensionality of the space. 00020 \param oldPt the current position, as an array. 00021 \param oldVal the current function value. 00022 \param grad the value of the function gradient at oldPt 00023 \param dir the minimization direction 00024 \param newPt used to return the final position 00025 \param newVal used to return the final function value 00026 \param func the function to minimize 00027 \param maxStep the maximum allowable step size 00028 \param resCode used to return the results of the search. 00029 00030 Possible values for resCode are on return are: 00031 - 0: success 00032 - 1: the stepsize got too small. This probably indicates success. 00033 - -1: the direction is bad (orthogonal to the gradient) 00034 */ 00035 void linearSearch(unsigned int dim,double *oldPt,double oldVal, 00036 double *grad,double *dir,double *newPt, 00037 double &newVal, 00038 double (*func)(double *), 00039 double maxStep,int &resCode); 00040 00041 //! Do a BFGS minimization of a function. 00042 /*! 00043 See Numerical Recipes in C, Section 10.7 for a description of the algorithm. 00044 00045 \param dim the dimensionality of the space. 00046 \param pos the starting position, as an array. 00047 \param gradTol tolerance for gradient convergence 00048 \param numIters used to return the number of iterations required 00049 \param funcVal used to return the final function value 00050 \param func the function to minimize 00051 \param gradFunc calculates the gradient of func 00052 \param funcTol tolerance for changes in the function value for convergence. 00053 \param maxIts maximum number of iterations allowed 00054 00055 \return a flag indicating success (or type of failure). Possible values are: 00056 - 0: success 00057 - 1: too many iterations were required 00058 */ 00059 int minimize(unsigned int dim,double *pos, 00060 double gradTol, 00061 unsigned int &numIters, 00062 double &funcVal, 00063 double (*func)(double *), 00064 void (*gradFunc)(double *,double*), 00065 double funcTol=TOLX, 00066 unsigned int maxIts=MAXITS); 00067 }
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