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// ************************************************************************************************
//
// BornAgain: simulate and fit reflection and scattering
//
//! @file Fit/Suite/SimAnMinimizer.cpp
//! @brief Implements class SimAnMinimizer.
//!
//! @homepage http://www.bornagainproject.org
//! @license GNU General Public License v3 or higher (see COPYING)
//! @copyright Forschungszentrum Jülich GmbH 2018
//! @authors Scientific Computing Group at MLZ (see CITATION, AUTHORS)
//
// ************************************************************************************************
#include "Fit/Suite/SimAnMinimizer.h"
#include "Fit/Suite/GSLMultiMinimizer.h"
#ifdef _WIN32
#pragma warning(push)
#pragma warning(disable : 4267)
#else
#pragma GCC diagnostic push
#pragma GCC diagnostic ignored "-Wdeprecated-declarations"
#endif
#include <Math/GSLSimAnMinimizer.h>
#ifdef _WIN32
#pragma warning(pop)
#else
#pragma GCC diagnostic pop
#endif
SimAnMinimizer::SimAnMinimizer()
: MinimizerAdapter(MinimizerInfo::buildGSLSimAnInfo())
, m_siman_minimizer(new ROOT::Math::GSLSimAnMinimizer())
{
addOption("PrintLevel", 0, "Minimizer internal print level");
addOption("MaxIterations", 100, "Number of points to try for each step");
addOption("IterationsAtTemp", 10, "Number of iterations at each temperature");
addOption("StepSize", 1.0, "Max step size used in random walk");
addOption("k", 1.0, "Boltzmann k");
addOption("t_init", 50.0, "Boltzmann initial temperature");
addOption("mu", 1.05, "Boltzmann mu");
addOption("t_min", 0.1, "Boltzmann minimal temperature");
}
SimAnMinimizer::~SimAnMinimizer() = default;
void SimAnMinimizer::setPrintLevel(int value)
{
setOptionValue("PrintLevel", value);
}
int SimAnMinimizer::printLevel() const
{
return optionValue<int>("PrintLevel");
}
void SimAnMinimizer::setMaxIterations(int value)
{
setOptionValue("MaxIterations", value);
}
int SimAnMinimizer::maxIterations() const
{
return optionValue<int>("MaxIterations");
}
void SimAnMinimizer::setIterationsAtEachTemp(int value)
{
setOptionValue("IterationsAtTemp", value);
}
int SimAnMinimizer::iterationsAtEachTemp() const
{
return optionValue<int>("IterationsAtTemp");
}
void SimAnMinimizer::setStepSize(double value)
{
setOptionValue("StepSize", value);
}
double SimAnMinimizer::stepSize() const
{
return optionValue<double>("StepSize");
}
void SimAnMinimizer::setBoltzmannK(double value)
{
setOptionValue("k", value);
}
double SimAnMinimizer::boltzmannK() const
{
return optionValue<double>("k");
}
void SimAnMinimizer::setBoltzmannInitialTemp(double value)
{
setOptionValue("t_init", value);
}
double SimAnMinimizer::boltzmannInitialTemp() const
{
return optionValue<double>("t_init");
}
void SimAnMinimizer::setBoltzmannMu(double value)
{
setOptionValue("mu", value);
}
double SimAnMinimizer::boltzmannMu() const
{
return optionValue<double>("mu");
}
void SimAnMinimizer::setBoltzmannMinTemp(double value)
{
setOptionValue("t_min", value);
}
double SimAnMinimizer::boltzmannMinTemp() const
{
return optionValue<double>("t_min");
}
std::map<std::string, std::string> SimAnMinimizer::statusMap() const
{
auto result = MinimizerAdapter::statusMap();
result["functionCalls"] = std::to_string(rootMinimizer()->NCalls());
return result;
}
void SimAnMinimizer::propagateOptions()
{
ROOT::Math::GSLSimAnParams& pars = m_siman_minimizer->getSolver().Params();
pars.n_tries = maxIterations();
pars.iters_fixed_T = iterationsAtEachTemp();
pars.step_size = stepSize();
pars.k = boltzmannK();
pars.t_initial = boltzmannInitialTemp();
pars.mu_t = boltzmannMu();
pars.t_min = boltzmannMinTemp();
}
const MinimizerAdapter::root_minimizer_t* SimAnMinimizer::rootMinimizer() const
{
return m_siman_minimizer.get();
}
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