void itsHybridContinuousInteractingAntColony::diversification()
{
if ( antsNb != getSampleSizeCurrent() ) {
ostringstream msg;
msg << "ErrorSize: antsNb (" << antsNb << ")"
<< " and sample size (" << getSampleSizeCurrent() << ")"
<< " does not match";
throw Exception_Size_Match( msg.str(), EXCEPTION_INFOS );
}
// move ants
for ( unsigned int i=0; i < getSampleSizeCurrent(); i++ ) {
antMove( i );
}
// ants -> sample
for ( unsigned int i=0; i < antsNb; i++ ) {
itsPoint p;
p.setSolution( antCurrentPoint[i] );
vector<double> val;
val.push_back( antCurrentValue[i] );
p.setValues( val );
setSamplePoint( i, p );
}
}
void itsRandom::diversification()
{
// reinit all
setSampleSize( getSampleSize() );
// draw each point in an hyper cube
for( unsigned int i=0; i < getSampleSize(); i++) {
// draw solution
itsPoint p;
p.setSolution( randomUniform( this->getProblem()->boundsMinima(), this->getProblem()->boundsMaxima() ) );
// get values
setSamplePoint(i, evaluate(p) );
}
}
void itsHybridEstimationOfDistribution::simplex()
{
// if no given NMS evaluations number
if( getSimplexEvaluations() == -1 ) {
//setSimplexEvaluations( (int)floor( pow( (this->problem->getDimension() + 1 ), 2.0 ) ) );
setSimplexEvaluations( this->getProblem()->getDimension() + 10 );
}
for( unsigned int i=0; i < getSampleSizeCurrent(); i++ ) {
itsNelderMead nms;
// problem optimized
nms.setProblem( this->getProblem() );
// no ending stopping criteria
nms.setValueMin(0.0);
nms.setIterationsMaxNumber( this->getIterationsMaxNumber() );
// used stopping criterion
nms.setEvaluationsMaxNumber( this->simplexEvaluations );
// edges from sample hypercube
vector<double> edges =
multiply(
substraction(
this->getProblem()->boundsMaxima(),
this->getProblem()->boundsMinima()
),
1 / ( pow( (double)getSampleSizeCurrent(), (double)1.0/this->getProblem()->getDimension() ) - 1 )
);
// init on current point
nms.initSimplexFromBasePoint( getSamplePoint(i), edges );
// silent launch
nms.startSilent();
// change the point to the new local optimum
setSamplePoint( i, nms.getOptimum() );
}
}
std::shared_ptr<Opm::UniformTabulated2DFunction<Scalar> >
createUniformTabulatedFunction(Fn &f)
{
Scalar xMin = -2.0;
Scalar xMax = 3.0;
unsigned m = 50;
Scalar yMin = -1/2.0;
Scalar yMax = 1/3.0;
unsigned n = 40;
auto tab = std::make_shared<Opm::UniformTabulated2DFunction<Scalar>>(
xMin, xMax, m,
yMin, yMax, n);
for (unsigned i = 0; i < m; ++i) {
Scalar x = xMin + Scalar(i)/(m - 1) * (xMax - xMin);
for (unsigned j = 0; j < n; ++j) {
Scalar y = yMin + Scalar(j)/(n - 1) * (yMax - yMin);
tab->setSamplePoint(i, j, f(x, y));
}
}
return tab;
}
void itsSimulatedAnnealing::diversification()
{
// reinit all
setSampleSize( getSampleSize() );
// draw each point in an hyper cube
for( unsigned int i=0; i < getSampleSize(); i++) {
// draw solution
p_new.setSolution( randomUniform( this->getProblem()->boundsMinima(), this->getProblem()->boundsMaxima() ) );
p_new = evaluate(p_new);
setSamplePoint( i, p_new );
// Metropolis rule
// if the value is the better than the previous point, accept
if( isValueSmaller(p_current,p_new) ) {
p_current = p_new;
} else {
// else, draw a random number and see if we accept the new point
if( randomUniform(0.0,temperature_max) < temperature ) {
p_current = p_new;
} // else the current point is kept
}
}
}
void PolyBezierCurve::generateSamplePoints( const curvedef::MapEvaluators & evalMap,
const int & rate )
{
assert( !evalMap.empty() );
mathdef::resize( m_samplePoints, rate * getNumSegments() + 1 );
mathdef::setZero( m_samplePoints );
// Evaluate the first point on the first curve, then
// Loop through all segment to sample 1st sample to last sample.
resetToFirstSegment();
int samp_i = 0; // Sample temp index
int j;
curvedef::Degree deg;
VectorX2s segCtrlPts;
while (m_iter != pointsEnd()) {
deg = getSegmentDegree( m_currentSegment );
const BezierEvaluator & evaluator = evalMap.find( deg )->second;
assert( evaluator.isBasesComputed() );
assert( deg > 0);
segCtrlPts = m_controlPoints.block( m_iter.getCurrentRow(), 0, deg + 1, 2 );
// Compute first end point if we are at first segment
if (m_currentSegment == 0)
{
j = 0;
// std::cout << "eval first t = " << computeParameterT(j, rate) << ": " << std::endl;
setSamplePoint(samp_i, evaluator.eval(segCtrlPts, j));
// std::cout << m_samplePoints.block(samp_i, 0, 1, 2) << std::endl;
++samp_i;
}
j = 1;
while (j <= rate)
{
// Sample segment point from index 1 to rate
// std::cout << "eval t = " << computeParameterT(j, rate) << ": " << std::endl;
setSamplePoint(samp_i, evaluator.eval(segCtrlPts, j));
// std::cout << m_samplePoints.block(samp_i, 0, 1, 2) << std::endl;
++samp_i;
++j;
}
advanceSegment();
}
//
// int segment = 0; // Segment index
// int samp_i = 0; // Sample temp index
// int ctrl_i = 0; // Control point temp index
// int j;
// curvedef::Degree deg; int numPts;
// VectorX2s segCtrlPts;
// while (segment < getNumSegments())
// {
// deg = getSegmentDegree( segment );
// const BezierEvaluator & evaluator = evalMap.find( deg )->second;
//
// assert( evaluator.isBasesComputed() );
// assert( deg > 0);
//
// std::cout << "CONTROL POINTS:\n" << m_controlPoints << std::endl;
// std::cout << "deg, ctrl_i, samp_i: " << deg << " " << ctrl_i << " " << samp_i << std::endl;
// std::cout << m_controlPoints.block( ctrl_i, 0, deg + 1, 2) << std::endl;
//
// segCtrlPts = m_controlPoints.block( ctrl_i, 0, deg + 1, 2);
//
// // Compute first end point if we are at first segment
// if (segment == 0)
// {
// j = 0;
// std::cout << "eval first t = " << computeParameterT(j, rate) << ": " << std::endl;
// setSamplePoint(samp_i, evaluator.eval(segCtrlPts, j));
// std::cout << m_samplePoints.block(samp_i, 0, 1, 2) << std::endl;
// ++samp_i;
// }
//
// j = 1;
// while (j <= rate)
// {
// // Sample segment point from index 1 to rate
// std::cout << "eval t = " << computeParameterT(j, rate) << ": " << std::endl;
// setSamplePoint(samp_i, evaluator.eval(segCtrlPts, j));
// std::cout << m_samplePoints.block(samp_i, 0, 1, 2) << std::endl;
// ++samp_i;
// ++j;
// }
//
// ctrl_i += deg;
// ++segment;
// }
}
