| [0b990d] | 1 | // | 
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|  | 2 | // gdiis.cc | 
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|  | 3 | // | 
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|  | 4 | // Copyright (C) 1996 Limit Point Systems, Inc. | 
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|  | 5 | // | 
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|  | 6 | // Author: Edward Seidl <seidl@janed.com> | 
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|  | 7 | // Maintainer: LPS | 
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|  | 8 | // | 
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|  | 9 | // This file is part of the SC Toolkit. | 
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|  | 10 | // | 
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|  | 11 | // The SC Toolkit is free software; you can redistribute it and/or modify | 
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|  | 12 | // it under the terms of the GNU Library General Public License as published by | 
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|  | 13 | // the Free Software Foundation; either version 2, or (at your option) | 
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|  | 14 | // any later version. | 
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|  | 15 | // | 
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|  | 16 | // The SC Toolkit is distributed in the hope that it will be useful, | 
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|  | 17 | // but WITHOUT ANY WARRANTY; without even the implied warranty of | 
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|  | 18 | // MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the | 
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|  | 19 | // GNU Library General Public License for more details. | 
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|  | 20 | // | 
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|  | 21 | // You should have received a copy of the GNU Library General Public License | 
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|  | 22 | // along with the SC Toolkit; see the file COPYING.LIB.  If not, write to | 
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|  | 23 | // the Free Software Foundation, 675 Mass Ave, Cambridge, MA 02139, USA. | 
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|  | 24 | // | 
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|  | 25 | // The U.S. Government is granted a limited license as per AL 91-7. | 
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|  | 26 | // | 
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|  | 27 |  | 
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|  | 28 | #ifdef __GNUC__ | 
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|  | 29 | #pragma implementation | 
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|  | 30 | #endif | 
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|  | 31 |  | 
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|  | 32 | #include <math.h> | 
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|  | 33 |  | 
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|  | 34 | #include <util/state/stateio.h> | 
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|  | 35 | #include <math/optimize/gdiis.h> | 
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|  | 36 | #include <util/keyval/keyval.h> | 
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|  | 37 | #include <math/scmat/local.h> | 
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|  | 38 | #include <util/misc/formio.h> | 
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|  | 39 |  | 
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|  | 40 | using namespace std; | 
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|  | 41 | using namespace sc; | 
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|  | 42 |  | 
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|  | 43 | ///////////////////////////////////////////////////////////////////////// | 
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|  | 44 | // GDIISOpt | 
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|  | 45 |  | 
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|  | 46 | static ClassDesc GDIISOpt_cd( | 
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|  | 47 | typeid(GDIISOpt),"GDIISOpt",1,"public Optimize", | 
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|  | 48 | 0, create<GDIISOpt>, create<GDIISOpt>); | 
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|  | 49 |  | 
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|  | 50 | GDIISOpt::GDIISOpt(const Ref<KeyVal>&keyval): | 
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|  | 51 | Optimize(keyval), | 
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|  | 52 | diis_iter(0), | 
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|  | 53 | maxabs_gradient(-1.0) | 
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|  | 54 | { | 
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|  | 55 | nsave = keyval->intvalue("ngdiis"); | 
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|  | 56 | if (keyval->error() != KeyVal::OK) nsave = 5; | 
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|  | 57 |  | 
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|  | 58 | update_ << keyval->describedclassvalue("update"); | 
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|  | 59 | update_->set_inverse(); | 
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|  | 60 |  | 
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|  | 61 | convergence_ = keyval->doublevalue("convergence"); | 
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|  | 62 | if (keyval->error() != KeyVal::OK) convergence_ = 1.0e-6; | 
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|  | 63 |  | 
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|  | 64 | accuracy_ = keyval->doublevalue("accuracy"); | 
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|  | 65 | if (keyval->error() != KeyVal::OK) accuracy_ = 0.0001; | 
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|  | 66 |  | 
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|  | 67 | RefSymmSCMatrix hessian(dimension(),matrixkit()); | 
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|  | 68 | // get a guess hessian from the function | 
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|  | 69 | function()->guess_hessian(hessian); | 
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|  | 70 |  | 
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|  | 71 | // see if any hessian matrix elements have been given in the input | 
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|  | 72 | if (keyval->exists("hessian")) { | 
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|  | 73 | int n = hessian.n(); | 
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|  | 74 | for (int i=0; i<n; i++) { | 
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|  | 75 | if (keyval->exists("hessian",i)) { | 
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|  | 76 | for (int j=0; j<=i; j++) { | 
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|  | 77 | double tmp = keyval->doublevalue("hessian",i,j); | 
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|  | 78 | if (keyval->error() == KeyVal::OK) hessian(i,j) = tmp; | 
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|  | 79 | } | 
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|  | 80 | } | 
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|  | 81 | } | 
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|  | 82 | } | 
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|  | 83 | ihessian_ = function()->inverse_hessian(hessian); | 
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|  | 84 |  | 
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|  | 85 | coords_ = new RefSCVector[nsave]; | 
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|  | 86 | grad_ = new RefSCVector[nsave]; | 
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|  | 87 | error_ = new RefSCVector[nsave]; | 
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|  | 88 |  | 
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|  | 89 | for (int i=0; i < nsave; i++) { | 
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|  | 90 | coords_[i] = matrixkit()->vector(dimension()); coords_[i]->assign(0.0); | 
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|  | 91 | grad_[i] = matrixkit()->vector(dimension()); grad_[i]->assign(0.0); | 
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|  | 92 | error_[i] = matrixkit()->vector(dimension()); error_[i]->assign(0.0); | 
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|  | 93 | } | 
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|  | 94 | } | 
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|  | 95 |  | 
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|  | 96 | GDIISOpt::GDIISOpt(StateIn&s): | 
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|  | 97 | SavableState(s), | 
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|  | 98 | Optimize(s) | 
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|  | 99 | { | 
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|  | 100 | s.get(nsave); | 
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|  | 101 | s.get(diis_iter); | 
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|  | 102 | ihessian_ = matrixkit()->symmmatrix(dimension()); | 
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|  | 103 | ihessian_.restore(s); | 
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|  | 104 | update_ << SavableState::restore_state(s); | 
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|  | 105 | s.get(convergence_); | 
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|  | 106 | s.get(accuracy_); | 
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|  | 107 | s.get(maxabs_gradient); | 
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|  | 108 | coords_ = new RefSCVector[nsave]; | 
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|  | 109 | grad_ = new RefSCVector[nsave]; | 
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|  | 110 | error_ = new RefSCVector[nsave]; | 
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|  | 111 | for (int i=0; i < nsave; i++) { | 
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|  | 112 | coords_[i] = matrixkit()->vector(dimension()); | 
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|  | 113 | grad_[i] = matrixkit()->vector(dimension()); | 
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|  | 114 | error_[i] = matrixkit()->vector(dimension()); | 
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|  | 115 | coords_[i].restore(s); | 
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|  | 116 | grad_[i].restore(s); | 
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|  | 117 | error_[i].restore(s); | 
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|  | 118 | } | 
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|  | 119 | } | 
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|  | 120 |  | 
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|  | 121 | GDIISOpt::~GDIISOpt() | 
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|  | 122 | { | 
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|  | 123 | delete[] coords_; | 
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|  | 124 | delete[] grad_; | 
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|  | 125 | delete[] error_; | 
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|  | 126 | } | 
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|  | 127 |  | 
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|  | 128 | void | 
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|  | 129 | GDIISOpt::save_data_state(StateOut&s) | 
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|  | 130 | { | 
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|  | 131 | Optimize::save_data_state(s); | 
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|  | 132 | s.put(nsave); | 
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|  | 133 | s.put(diis_iter); | 
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|  | 134 | ihessian_.save(s); | 
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|  | 135 | SavableState::save_state(update_.pointer(),s); | 
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|  | 136 | s.put(convergence_); | 
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|  | 137 | s.put(accuracy_); | 
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|  | 138 | s.put(maxabs_gradient); | 
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|  | 139 | for (int i=0; i < nsave; i++) { | 
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|  | 140 | coords_[i].save(s); | 
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|  | 141 | grad_[i].save(s); | 
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|  | 142 | error_[i].save(s); | 
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|  | 143 | } | 
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|  | 144 | } | 
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|  | 145 |  | 
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|  | 146 | void | 
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|  | 147 | GDIISOpt::init() | 
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|  | 148 | { | 
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|  | 149 | Optimize::init(); | 
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|  | 150 | maxabs_gradient = -1.0; | 
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|  | 151 | } | 
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|  | 152 |  | 
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|  | 153 | int | 
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|  | 154 | GDIISOpt::update() | 
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|  | 155 | { | 
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|  | 156 | int i,j,ii,jj; | 
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|  | 157 |  | 
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|  | 158 | // these are good candidates to be input options | 
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|  | 159 | const double maxabs_gradient_to_desired_accuracy = 0.05; | 
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|  | 160 | const double maxabs_gradient_to_next_desired_accuracy = 0.005; | 
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|  | 161 | const double roundoff_error_factor = 1.1; | 
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|  | 162 |  | 
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|  | 163 | // the gradient convergence criterion. | 
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|  | 164 | double old_maxabs_gradient = maxabs_gradient; | 
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|  | 165 | RefSCVector xcurrent; | 
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|  | 166 | RefSCVector gcurrent; | 
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|  | 167 |  | 
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|  | 168 | // get the next gradient at the required level of accuracy. | 
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|  | 169 | // usually only one pass is needed, unless we happen to find | 
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|  | 170 | // that the accuracy was set too low. | 
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|  | 171 | int accurate_enough; | 
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|  | 172 | do { | 
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|  | 173 | // compute the current point | 
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|  | 174 | function()->set_desired_gradient_accuracy(accuracy_); | 
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|  | 175 |  | 
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|  | 176 | xcurrent = function()->get_x(); | 
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|  | 177 | gcurrent = function()->gradient().copy(); | 
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|  | 178 |  | 
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|  | 179 | // compute the gradient convergence criterion now so i can see if | 
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|  | 180 | // the accuracy needs to be tighter | 
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|  | 181 | maxabs_gradient = gcurrent.maxabs(); | 
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|  | 182 | // compute the required accuracy | 
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|  | 183 | accuracy_ = maxabs_gradient * maxabs_gradient_to_desired_accuracy; | 
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|  | 184 |  | 
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|  | 185 | // The roundoff_error_factor is thrown in to allow for round off making | 
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|  | 186 | // the current gcurrent.maxabs() a bit smaller than the previous, | 
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|  | 187 | // which would make the current required accuracy less than the | 
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|  | 188 | // gradient's actual accuracy and cause everything to be recomputed. | 
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|  | 189 | accurate_enough = (function()->actual_gradient_accuracy() <= | 
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|  | 190 | accuracy_*roundoff_error_factor); | 
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|  | 191 |  | 
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|  | 192 | if (!accurate_enough) { | 
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|  | 193 | ExEnv::out0() << indent | 
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|  | 194 | << "NOTICE: function()->actual_gradient_accuracy() > accuracy_:\n" | 
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|  | 195 | << indent | 
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|  | 196 | << scprintf( | 
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|  | 197 | "        function()->actual_gradient_accuracy() = %15.8e", | 
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|  | 198 | function()->actual_gradient_accuracy()) << endl << indent | 
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|  | 199 | << scprintf( | 
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|  | 200 | "                                     accuracy_ = %15.8e", | 
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|  | 201 | accuracy_) << endl; | 
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|  | 202 | } | 
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|  | 203 | } while(!accurate_enough); | 
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|  | 204 |  | 
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|  | 205 | if (old_maxabs_gradient >= 0.0 && old_maxabs_gradient < maxabs_gradient) { | 
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|  | 206 | ExEnv::out0() << indent | 
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|  | 207 | << scprintf("NOTICE: maxabs_gradient increased from %8.4e to %8.4e", | 
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|  | 208 | old_maxabs_gradient, maxabs_gradient) << endl; | 
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|  | 209 | } | 
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|  | 210 |  | 
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|  | 211 | // update the hessian | 
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|  | 212 | if (update_.nonnull()) { | 
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|  | 213 | update_->update(ihessian_,function(),xcurrent,gcurrent); | 
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|  | 214 | } | 
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|  | 215 |  | 
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|  | 216 | diis_iter++; | 
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|  | 217 |  | 
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|  | 218 | int howmany = (diis_iter < nsave) ? diis_iter : nsave; | 
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|  | 219 |  | 
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|  | 220 | if (diis_iter <= nsave) { | 
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|  | 221 | coords_[diis_iter-1] = xcurrent; | 
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|  | 222 | grad_[diis_iter-1] = gcurrent; | 
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|  | 223 | } else { | 
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|  | 224 | for (i=0; i < nsave-1; i++) { | 
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|  | 225 | coords_[i] = coords_[i+1]; | 
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|  | 226 | grad_[i] = grad_[i+1]; | 
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|  | 227 | } | 
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|  | 228 | coords_[nsave-1] = xcurrent; | 
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|  | 229 | grad_[nsave-1] = gcurrent; | 
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|  | 230 | } | 
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|  | 231 |  | 
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|  | 232 | // take the step | 
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|  | 233 | if (diis_iter==1 || maxabs_gradient > 0.05) { | 
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|  | 234 | // just take the Newton-Raphson step first iteration | 
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|  | 235 | RefSCVector xdisp = -1.0*(ihessian_ * gcurrent); | 
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|  | 236 | // try steepest descent | 
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|  | 237 | // RefSCVector xdisp = -1.0*gcurrent; | 
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|  | 238 |  | 
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|  | 239 | // scale displacement vector if it's too large | 
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|  | 240 | double tot = sqrt(xdisp.scalar_product(xdisp)); | 
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|  | 241 | if (tot > max_stepsize_) { | 
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|  | 242 | double scal = max_stepsize_/tot; | 
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|  | 243 | ExEnv::out0() << endl << indent | 
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|  | 244 | << scprintf("stepsize of %f is too big, scaling by %f",tot,scal) | 
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|  | 245 | << endl; | 
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|  | 246 | xdisp.scale(scal); | 
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|  | 247 | tot *= scal; | 
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|  | 248 | } | 
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|  | 249 |  | 
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|  | 250 | RefSCVector xnext = xcurrent + xdisp; | 
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|  | 251 |  | 
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|  | 252 | conv_->reset(); | 
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|  | 253 | conv_->get_grad(function()); | 
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|  | 254 | conv_->get_x(function()); | 
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|  | 255 | conv_->set_nextx(xnext); | 
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|  | 256 |  | 
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|  | 257 | // check for conergence before resetting the geometry | 
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|  | 258 | int converged = conv_->converged(); | 
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|  | 259 | if (converged) | 
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|  | 260 | return converged; | 
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|  | 261 |  | 
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|  | 262 | ExEnv::out0() << endl << indent | 
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|  | 263 | << scprintf("taking step of size %f", tot) << endl; | 
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|  | 264 |  | 
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|  | 265 | function()->set_x(xnext); | 
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|  | 266 |  | 
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|  | 267 | // make the next gradient computed more accurate, since it will | 
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|  | 268 | // be smaller | 
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|  | 269 | accuracy_ = maxabs_gradient * maxabs_gradient_to_next_desired_accuracy; | 
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|  | 270 |  | 
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|  | 271 | return converged; | 
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|  | 272 | } | 
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|  | 273 |  | 
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|  | 274 | // form the error vectors | 
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|  | 275 | for (i=0; i < howmany; i++) | 
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|  | 276 | error_[i] = -1.0*(ihessian_ * grad_[i]); | 
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|  | 277 |  | 
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|  | 278 | // and form the A matrix | 
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|  | 279 | RefSCMatrix A; | 
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|  | 280 | RefSCVector coeff; | 
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|  | 281 | int ntry=0; | 
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|  | 282 |  | 
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|  | 283 | do { | 
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|  | 284 | int num = howmany-ntry; | 
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|  | 285 |  | 
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|  | 286 | RefSCDimension size = new SCDimension(num+1); | 
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|  | 287 | Ref<SCMatrixKit> lkit = new LocalSCMatrixKit; | 
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|  | 288 | A = lkit->matrix(size,size); | 
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|  | 289 | coeff = lkit->vector(size); | 
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|  | 290 |  | 
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|  | 291 | for (ii=0, i=ntry; i < howmany; i++,ii++) { | 
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|  | 292 | coeff(ii) = 0; | 
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|  | 293 | for (j=ntry,jj=0; j <= i; j++,jj++) { | 
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|  | 294 | A(ii,jj) = error_[i].scalar_product(error_[j]); | 
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|  | 295 | A(jj,ii) = A(ii,jj); | 
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|  | 296 | } | 
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|  | 297 | } | 
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|  | 298 |  | 
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|  | 299 | A->scale(1.0/A(0,0)); | 
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|  | 300 |  | 
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|  | 301 | coeff(num) = 1.0; | 
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|  | 302 | for (i=0; i < num; i++) | 
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|  | 303 | A(num,i) = A(i,num) = 1.0; | 
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|  | 304 |  | 
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|  | 305 | A(num,num) = 0; | 
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|  | 306 |  | 
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|  | 307 | ntry++; | 
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|  | 308 |  | 
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|  | 309 | } while (fabs(A.solve_lin(coeff)) < 1.0e-12); | 
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|  | 310 |  | 
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|  | 311 | RefSCVector xstar = matrixkit()->vector(dimension()); | 
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|  | 312 | RefSCVector delstar = matrixkit()->vector(dimension()); | 
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|  | 313 |  | 
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|  | 314 | xstar.assign(0.0); | 
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|  | 315 | delstar.assign(0.0); | 
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|  | 316 |  | 
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|  | 317 | for (i=0,ii=ntry-1; ii < howmany; i++,ii++) { | 
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|  | 318 | RefSCVector tmp = grad_[ii].copy(); tmp.scale(coeff[i]); | 
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|  | 319 | delstar.accumulate(tmp); | 
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|  | 320 | tmp = coords_[ii].copy(); tmp.scale(coeff[i]); | 
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|  | 321 | xstar.accumulate(tmp); | 
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|  | 322 | } | 
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|  | 323 |  | 
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|  | 324 | RefSCVector xdisp = xstar - xcurrent - ihessian_*delstar; | 
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|  | 325 | // scale displacement vector if it's too large | 
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|  | 326 | double tot = sqrt(xdisp.scalar_product(xdisp)); | 
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|  | 327 | if (tot > max_stepsize_) { | 
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|  | 328 | double scal = max_stepsize_/tot; | 
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|  | 329 | ExEnv::out0() << endl << indent | 
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|  | 330 | << scprintf("stepsize of %f is too big, scaling by %f",tot,scal) | 
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|  | 331 | << endl; | 
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|  | 332 | xdisp.scale(scal); | 
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|  | 333 | tot *= scal; | 
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|  | 334 | } | 
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|  | 335 |  | 
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|  | 336 | RefSCVector xnext = xcurrent + xdisp; | 
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|  | 337 |  | 
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|  | 338 | conv_->reset(); | 
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|  | 339 | conv_->get_grad(function()); | 
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|  | 340 | conv_->get_x(function()); | 
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|  | 341 | conv_->set_nextx(xnext); | 
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|  | 342 |  | 
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|  | 343 | // check for conergence before resetting the geometry | 
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|  | 344 | int converged = conv_->converged(); | 
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|  | 345 | if (converged) | 
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|  | 346 | return converged; | 
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|  | 347 |  | 
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|  | 348 | ExEnv::out0() << endl << indent | 
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|  | 349 | << scprintf("taking step of size %f", tot) << endl; | 
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|  | 350 |  | 
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|  | 351 | function()->set_x(xnext); | 
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|  | 352 |  | 
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|  | 353 | // make the next gradient computed more accurate, since it will | 
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|  | 354 | // be smaller | 
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|  | 355 | accuracy_ = maxabs_gradient * maxabs_gradient_to_next_desired_accuracy; | 
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|  | 356 |  | 
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|  | 357 | return converged; | 
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|  | 358 | } | 
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|  | 359 |  | 
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|  | 360 | ///////////////////////////////////////////////////////////////////////////// | 
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|  | 361 |  | 
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|  | 362 | // Local Variables: | 
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|  | 363 | // mode: c++ | 
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|  | 364 | // c-file-style: "ETS" | 
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|  | 365 | // End: | 
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