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root/group/trunk/OOPSE/libmdtools/Minimizer1D.cpp
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Comparing trunk/OOPSE/libmdtools/Minimizer1D.cpp (file contents):
Revision 1002 by tim, Mon Feb 2 20:29:41 2004 UTC vs.
Revision 1015 by tim, Tue Feb 3 22:54:52 2004 UTC

# Line 1 | Line 1
1   #include "Minimizer1D.hpp"
2 < void Minimizer1D::Minimize(vector<double>& direction), double left, double right); {
3 <  setDirection(direction);
4 <  setRange(left,right);
5 <  minimize();
2 > #include "math.h"
3 >
4 > GoldenSectionMinimizer::GoldenSectionMinimizer(NLModel* nlp)
5 >                               :Minimizer1D(nlp){
6 >  setName("GoldenSection");
7   }
8  
9 < int Minimizer1D::checkConvergence(){
9 > int GoldenSectionMinimizer::checkConvergence(){
10  
11    if ((rightVar - leftVar) < stepTol)
12 <    return
12 >    return 1;
13    else
14      return -1;
15   }
15 –
16   void GoldenSectionMinimizer::minimize(){
17    vector<double> tempX;
18    vector <double> currentX;
19  
20    const double goldenRatio = 0.618034;
21    
22 <  currentX =  model->getX();
22 >  tempX = currentX =  model->getX();
23  
24    alpha = leftVar + (1 - goldenRatio) * (rightVar  - leftVar);
25    beta = leftVar + goldenRatio * (rightVar - leftVar);
26  
27 <  tempX = currentX + direction * alpha;
27 >  for (int i = 0; i < tempX.size(); i ++)
28 >    tempX[i] = currentX[i] + direction[i] * alpha;
29 >
30    fAlpha = model->calcF(tempX);
31  
32 <  tempX = currentX + direction * beta;
32 >  for (int i = 0; i < tempX.size(); i ++)
33 >    tempX[i] = currentX[i] + direction[i] * beta;
34 >
35    fBeta = model->calcF(tempX);
36  
37    for(currentIter = 0; currentIter < maxIteration; currentIter++){
# Line 42 | Line 46 | void GoldenSectionMinimizer::minimize(){
46        alpha = beta;
47        beta =  leftVar + goldenRatio * (rightVar - leftVar);
48  
49 <      tempX = currentX + beta * direction;
49 >      for (int i = 0; i < tempX.size(); i ++)
50 >        tempX[i] = currentX[i] + direction[i] * beta;
51  
52        prevMinVar = minVar;
53        fPrevMinVar = fMinVar;
# Line 56 | Line 61 | void GoldenSectionMinimizer::minimize(){
61        beta = alpha;
62        alpha = leftVar + (1 - goldenRatio) * (rightVar  - leftVar);
63  
64 <      tempX = currentX + alpha * direction;
64 >      for (int i = 0; i < tempX.size(); i ++)
65 >        tempX[i] = currentX[i] + direction[i] * alpha;
66  
67        prevMinVar = minVar;
68        fPrevMinVar = fMinVar;
# Line 71 | Line 77 | void GoldenSectionMinimizer::minimize(){
77      
78   }
79  
80 < /*
81 < *
80 > /**
81 > * Brent's method is a root-finding algorithm which combines root bracketing, interval bisection,
82 > * and inverse quadratic interpolation.
83   */
84 + BrentMinimizer::BrentMinimizer(NLModel* nlp)
85 +                   :Minimizer1D(nlp){
86 +  setName("Brent");
87 + }
88  
89   void BrentMinimizer::minimize(){
90  
91 +  double fu, fv, fw;
92 +  double p, q, r;
93 +  double u, v, w;
94 +  double d;
95 +  double e;
96 +  double etemp;
97 +  double stepTol2;
98 +  double fLeftVar, fRightVar;
99 +  const double goldenRatio = 0.3819660;
100 +  vector<double> tempX, currentX;
101 +  
102 +  stepTol2 = 2 * stepTol;
103 +  e = 0;
104 +  d = 0;
105 +
106 +  currentX = tempX = model->getX();
107 +
108 +  for (int i = 0; i < tempX.size(); i ++)
109 +    tempX[i] = currentX[i] + direction[i] * leftVar;
110 +  
111 +  fLeftVar = model->calcF(tempX);
112 +
113 +  for (int i = 0; i < tempX.size(); i ++)
114 +    tempX[i] = currentX[i] + direction[i] * rightVar;  
115 +  
116 +  fRightVar = model->calcF(tempX);
117 +
118 +  if(fRightVar < fLeftVar) {
119 +    prevMinVar = rightVar;
120 +    fPrevMinVar = fRightVar;
121 +    v  = leftVar;
122 +    fv = fLeftVar;
123 +  }
124 +  else {
125 +    prevMinVar = leftVar;
126 +    fPrevMinVar = fLeftVar;
127 +    v  = rightVar;
128 +    fv = fRightVar;
129 +  }
130 +
131 +  midVar = leftVar + rightVar;
132 +  
133    for(currentIter = 0; currentIter < maxIteration; currentIter){
134  
135 +     // a trial parabolic fit
136 +     if (fabs(e) > stepTol){
137  
138 +       r = (minVar - prevMinVar) * (fMinVar - fv);
139 +       q = (minVar - v) * (fMinVar - fPrevMinVar);
140 +       p = (minVar - v) *q -(minVar - prevMinVar)*r;
141 +       q = 2.0 *(q-r);
142  
143 +       if (q > 0.0)
144 +         p = -p;
145  
146 +       q = fabs(q);
147 +
148 +       etemp = e;
149 +       e  = d;
150 +
151 +       if(fabs(p) >= fabs(0.5*q*etemp) || p <= q*(leftVar - minVar) || p >= q*(rightVar - minVar)){
152 +         e =  minVar >= midVar ? leftVar - minVar : rightVar - minVar;
153 +         d = goldenRatio * e;
154 +       }
155 +       else{
156 +         d = p/q;
157 +         u = minVar + d;
158 +         if ( u - leftVar < stepTol2 || rightVar - u  < stepTol2)
159 +           d = midVar > minVar ? stepTol : - stepTol;
160 +       }
161 +     }
162 +     //golden section
163 +     else{
164 +       e = minVar >=midVar? leftVar - minVar : rightVar - minVar;
165 +       d =goldenRatio * e;
166 +     }
167 +
168 +     u = fabs(d) >= stepTol ? minVar + d : minVar + copysign(d, stepTol);
169 +
170 +     for (int i = 0; i < tempX.size(); i ++)
171 +       tempX[i] = currentX[i] + direction[i] * u;  
172 +    
173 +     fu = model->calcF();  
174 +
175 +     if(fu <= fMinVar){
176 +
177 +       if(u >= minVar)
178 +         leftVar = minVar;
179 +       else
180 +         rightVar = minVar;
181 +
182 +       v  = prevMinVar;
183 +       fv = fPrevMinVar;
184 +       prevMinVar = minVar;
185 +       fPrevMinVar = fMinVar;
186 +       minVar = u;
187 +       fMinVar = fu;
188 +      
189 +     }
190 +     else{
191 +       if (u < minVar) leftVar = u;
192 +       else rightVar= u;
193 +       if(fu <= fPrevMinVar || prevMinVar == minVar) {
194 +         v  = prevMinVar;
195 +         fv = fPrevMinVar;
196 +         prevMinVar = u;
197 +         fPrevMinVar = fu;
198 +      }
199 +      else if ( fu <= fv || v == minVar || v == prevMinVar ) {
200 +        v  = u;
201 +         fv = fu;
202 +      }  
203 +    }    
204 +
205 +    midVar = leftVar + rightVar;
206 +
207 +     if (checkConvergence() > 0){
208 +       minStatus = MINSTATUS_CONVERGE;
209 +       return;
210 +     }
211 +    
212    }
213  
214  
215    minStatus = MINSTATUS_MAXITER;
216 <  return;
216 >  return;  
217   }
218 +
219 + int BrentMinimizer::checkConvergence(){
220 +  
221 +  if (fabs(minVar - midVar) <  stepTol)
222 +    return 1;
223 +  else
224 +    return -1;
225 + }

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