// Copyright (c) 1997-1999 Matra Datavision // Copyright (c) 1999-2014 OPEN CASCADE SAS // // This file is part of Open CASCADE Technology software library. // // This library is free software; you can redistribute it and/or modify it under // the terms of the GNU Lesser General Public License version 2.1 as published // by the Free Software Foundation, with special exception defined in the file // OCCT_LGPL_EXCEPTION.txt. Consult the file LICENSE_LGPL_21.txt included in OCCT // distribution for complete text of the license and disclaimer of any warranty. // // Alternatively, this file may be used under the terms of Open CASCADE // commercial license or contractual agreement. //#ifndef OCCT_DEBUG #define No_Standard_RangeError #define No_Standard_OutOfRange #define No_Standard_DimensionError //#endif #include #include #include #include #include #include #include #include // l'utilisation de math_BrentMinumim pur trouver un minimum dans une direction // donnee n'est pas du tout optimale. voir peut etre interpolation cubique // classique et aussi essayer "recherche unidimensionnelle economique" // PROGRAMMATION MATHEMATIQUE (theorie et algorithmes) tome1 page 82. class DirFunctionTer : public math_Function { math_Vector *P0; math_Vector *Dir; math_Vector *P; math_MultipleVarFunction *F; public : DirFunctionTer(math_Vector& V1, math_Vector& V2, math_Vector& V3, math_MultipleVarFunction& f); void Initialize(const math_Vector& p0, const math_Vector& dir); virtual Standard_Boolean Value(const Standard_Real x, Standard_Real& fval); }; DirFunctionTer::DirFunctionTer(math_Vector& V1, math_Vector& V2, math_Vector& V3, math_MultipleVarFunction& f) { P0 = &V1; Dir = &V2; P = &V3; F = &f; } void DirFunctionTer::Initialize(const math_Vector& p0, const math_Vector& dir) { *P0 = p0; *Dir = dir; } Standard_Boolean DirFunctionTer::Value(const Standard_Real x, Standard_Real& fval) { *P = *Dir; P->Multiply(x); P->Add(*P0); fval = 0.; return F->Value(*P, fval); } static Standard_Boolean MinimizeDirection(math_Vector& P, math_Vector& Dir, Standard_Real& Result, DirFunctionTer& F) { Standard_Real ax, xx, bx; F.Initialize(P, Dir); math_BracketMinimum Bracket(F, 0.0, 1.0); if(Bracket.IsDone()) { Bracket.Values(ax, xx, bx); math_BrentMinimum Sol(1.e-10); Sol.Perform(F, ax, xx, bx); if (Sol.IsDone()) { Standard_Real Scale = Sol.Location(); Result = Sol.Minimum(); Dir.Multiply(Scale); P.Add(Dir); return Standard_True; } } return Standard_False; } //======================================================================= //function : math_FRPR //purpose : Constructor //======================================================================= math_FRPR::math_FRPR(const math_MultipleVarFunctionWithGradient& theFunction, const Standard_Real theTolerance, const Standard_Integer theNbIterations, const Standard_Real theZEPS) : TheLocation(1, theFunction.NbVariables()), TheGradient(1, theFunction.NbVariables()), TheMinimum (0.0), PreviousMinimum(0.0), XTol (theTolerance), EPSZ (theZEPS), Done (Standard_False), Iter (0), State (0), TheStatus (math_NotBracketed), Itermax (theNbIterations) { } //======================================================================= //function : ~math_FRPR //purpose : Destructor //======================================================================= math_FRPR::~math_FRPR() { } //======================================================================= //function : Perform //purpose : //======================================================================= void math_FRPR::Perform(math_MultipleVarFunctionWithGradient& F, const math_Vector& StartingPoint) { Standard_Boolean Good; Standard_Integer n = TheLocation.Length(); Standard_Integer j, its; Standard_Real gg, gam, dgg; math_Vector g(1, n), h(1, n); math_Vector Temp1(1, n); math_Vector Temp2(1, n); math_Vector Temp3(1, n); DirFunctionTer F_Dir(Temp1, Temp2, Temp3, F); TheLocation = StartingPoint; Good = F.Values(TheLocation, PreviousMinimum, TheGradient); if(!Good) { Done = Standard_False; TheStatus = math_FunctionError; return; } g = -TheGradient; h = g; TheGradient = g; for(its = 1; its <= Itermax; its++) { Iter = its; Standard_Boolean IsGood = MinimizeDirection(TheLocation, TheGradient, TheMinimum, F_Dir); if(!IsGood) { Done = Standard_False; TheStatus = math_DirectionSearchError; return; } if(IsSolutionReached(F)) { Done = Standard_True; State = F.GetStateNumber(); TheStatus = math_OK; return; } Good = F.Values(TheLocation, PreviousMinimum, TheGradient); if(!Good) { Done = Standard_False; TheStatus = math_FunctionError; return; } dgg =0.0; gg = 0.0; for(j = 1; j<= n; j++) { gg += g(j)*g(j); // dgg += TheGradient(j)*TheGradient(j); //for Fletcher-Reeves dgg += (TheGradient(j)+g(j)) * TheGradient(j); //for Polak-Ribiere } if (gg == 0.0) { //Unlikely. If gradient is exactly 0 then we are already done. Done = Standard_False; TheStatus = math_FunctionError; return; } gam = dgg/gg; g = -TheGradient; TheGradient = g + gam*h; h = TheGradient; } Done = Standard_False; TheStatus = math_TooManyIterations; return; } //======================================================================= //function : Dump //purpose : //======================================================================= void math_FRPR::Dump(Standard_OStream& o) const { o << "math_FRPR "; if(Done) { o << " Status = Done \n"; o << " Location Vector = "<< TheLocation << "\n"; o << " Minimum value = " << TheMinimum <<"\n"; o << " Number of iterations = " << Iter <<"\n"; } else { o << " Status = not Done because " << (Standard_Integer)TheStatus << "\n"; } }