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/* -------------------------------------------------------------------------- *
* Simbody(tm) Example: Parameter Constrained Optimization *
* -------------------------------------------------------------------------- *
* This is part of the SimTK biosimulation toolkit originating from *
* Simbios, the NIH National Center for Physics-Based Simulation of *
* Biological Structures at Stanford, funded under the NIH Roadmap for *
* Medical Research, grant U54 GM072970. See https://simtk.org/home/simbody. *
* *
* Portions copyright (c) 2006-12 Stanford University and the Authors. *
* Authors: Jack Middleton *
* Contributors: *
* *
* Licensed under the Apache License, Version 2.0 (the "License"); you may *
* not use this file except in compliance with the License. You may obtain a *
* copy of the License at http://www.apache.org/licenses/LICENSE-2.0. *
* *
* Unless required by applicable law or agreed to in writing, software *
* distributed under the License is distributed on an "AS IS" BASIS, *
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. *
* See the License for the specific language governing permissions and *
* limitations under the License. *
* -------------------------------------------------------------------------- */
#include "SimTKmath.h"
#include <iostream>
using namespace SimTK;
const static int NUMBER_OF_PARAMETERS = 25;
class ProblemSystem : public OptimizerSystem {
public:
ProblemSystem( const int numParameters ) : OptimizerSystem( numParameters ) {}
int objectiveFunc( const Vector &coefficients, bool new_coefficients, Real& f ) const override {
const Real *x = &coefficients[0];
f = .25 *(x[0]-1.0)*(x[0]-1.0);
for(int i=1;i<getNumParameters();i++) {
f = f + pow(x[i]-x[i-1]*x[i-1], 2.0);
}
f = 4.0* f;
return( 0 );
}
int gradientFunc( const Vector &coefficients, bool new_coefficients, Vector &gradient ) const override {
const Real *x;
Real t1,t2;
x = &coefficients[0];
t1 = x[1]-(x[0]*x[0]);
gradient[0] = 2.0*(x[0]-1.0)-16.0*x[0]*t1;
for(int i=1;i<getNumParameters()-1;i++) {
t2=t1;
t1=x[i+1]-(x[i]*x[i]);
gradient[i]=8.0*t2-16.0*x[i]*t1;
}
gradient[getNumParameters()-1]=8.0*t1;
return(0);
}
};
/* adapted from driver1.f of Lbfgsb.2.1.tar.gz */
int main() {
int n = NUMBER_OF_PARAMETERS;
Vector results(NUMBER_OF_PARAMETERS);
Vector lower_bounds(NUMBER_OF_PARAMETERS);
Vector upper_bounds(NUMBER_OF_PARAMETERS);
ProblemSystem sys(NUMBER_OF_PARAMETERS);
/* set initial conditions */
for(int i=0;i<n;i++) {
results[i] = 3.0;
}
/* set bounds */
for(int i=0;i<n;i=i+2) { // even numbered
lower_bounds[i] = 1.0;
upper_bounds[i] = 100.0;
}
for(int i=1;i<n;i=i+2) { // odd numbered
lower_bounds[i] = -100.0;
upper_bounds[i] = 100.0;
}
sys.setParameterLimits( lower_bounds, upper_bounds );
Real f = NaN;
try {
Optimizer opt( sys );
opt.setConvergenceTolerance( .0001 );
f = opt.optimize( results );
}
catch (const SimTK::Exception::Base& e) {
std::cout << "ParameterConstrainedOptimization.cpp Caught exception :" << std::endl;
std::cout << e.what() << std::endl;
}
printf("f = %f params = ",f);
for(int i=0; i<NUMBER_OF_PARAMETERS; i++ ) {
printf(" %f",results[i]);
}
printf("\n");
return 0;
}
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