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Commit 9da86387 authored by pospelov's avatar pospelov
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Attempt to apply fit strategies in TestMesocrystal2

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App/inc/TestFittingModule2.h
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− 0
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......@@ -22,6 +22,7 @@
#include "FitMultiParameter.h"
#include "GISASExperiment.h"
#include "ISampleBuilder.h"
#include "FitSuiteStrategy.h"
class FitSuite;
......
App/src/AppOptionsDescription.cpp
+ 2
− 0
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......@@ -20,6 +20,7 @@ void AddApplicationOptions(ProgramOptions* p_options)
("all", "run all registered functional test")
("profile", "profile specified test")
("config,c", bpo::value<std::string>()->default_value("gisasfw.cfg"),"config file name")
("fitmode", bpo::value<int>()->default_value(1), "used in TestMesocrystal2")
;
// there is no positional options (without '--' or '-' signs) at the moment
......@@ -35,3 +36,4 @@ void AddApplicationOptions(ProgramOptions* p_options)
// adding options to the main option holder
p_options->add(general_options).add(functional_test_options);
}
App/src/ROOTMinimizer.cpp
+ 2
− 1
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......@@ -7,7 +7,8 @@
ROOTMinimizer::ROOTMinimizer(const std::string &minimizer_name, const std::string &algo_type) : m_fcn(0)
{
m_root_minimizer = ROOT::Math::Factory::CreateMinimizer(minimizer_name.c_str(), algo_type.c_str() );
m_root_minimizer->SetMaxFunctionCalls(5000);
m_root_minimizer->SetMaxFunctionCalls(20000);
m_root_minimizer->SetMaxIterations(20000);
printOptions();
if( m_root_minimizer == 0 ) {
throw NullPointerException("ROOTMinimizer::ROOTMinimizer() -> Error! Can't build minimizer");
......
App/src/TestFittingModule1.cpp
+ 12
− 9
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......@@ -73,17 +73,20 @@ void TestFittingModule1::execute()
m_fitSuite->setExperiment(mp_experiment);
m_fitSuite->setRealData(*mp_real_data);
m_fitSuite->setMinimizer( new ROOTMinimizer("Minuit2", "Migrad") );
//fitSuite->setMinimizer( new ROOTMinimizer("Minuit2", "Minimize") );
//fitSuite->setMinimizer( new ROOTMinimizer("Minuit2", "Combined") );
//fitSuite->setMinimizer( new ROOTMinimizer("Minuit2", "Fumili") ); //doesn't work, Fumili wants special function with derivative
//fitSuite->setMinimizer( new ROOTMinimizer("GSLMultiMin", "ConjugateFR") );
//fitSuite->setMinimizer( new ROOTMinimizer("GSLMultiMin", "BFGS") );
//fitSuite->setMinimizer( new ROOTMinimizer("GSLMultiMin", "SteepestDescent") );
//fitSuite->setMinimizer( new ROOTMinimizer("GSLSimAn", "") );
//fitSuite->setMinimizer( new ROOTMinimizer("Genetic", "") );
//m_fitSuite->setMinimizer( new ROOTMinimizer("Minuit2", "Simplex") );
//m_fitSuite->setMinimizer( new ROOTMinimizer("Minuit2", "Minimize") );
//m_fitSuite->setMinimizer( new ROOTMinimizer("Minuit2", "Combined") );
//m_fitSuite->setMinimizer( new ROOTMinimizer("Minuit2", "Fumili") ); //doesn't work, Fumili wants special function with derivative
//m_fitSuite->setMinimizer( new ROOTMinimizer("GSLMultiMin", "ConjugateFR") );
//m_fitSuite->setMinimizer( new ROOTMinimizer("GSLMultiMin", "BFGS") );
//m_fitSuite->setMinimizer( new ROOTMinimizer("GSLMultiMin", "SteepestDescent") );
//m_fitSuite->setMinimizer( new ROOTMinimizer("GSLSimAn", "") );
//m_fitSuite->setMinimizer( new ROOTMinimizer("Genetic", "") );
// tuning minimizer
//ROOT::Math::Minimizer *minim = (dynamic_cast<ROOTMinimizer *>(m_fitSuite->getMinimizer()))->getROOTMinimizer();
//minim->SetTolerance(1000.0);
//minim->SetPrecision(0.00001);
//minim->SetTolerance(0.00001);
//minim->SetStrategy(2);
//minim->SetMaxFunctionCalls(50); // for Minuit
//minim->SetMaxIterations(50); // for GSL
//minim->SetPrintLevel(4);
......
App/src/TestFittingModule2.cpp
+ 3
− 21
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......@@ -75,27 +75,27 @@ void TestFittingModule2::execute()
//m_fitSuite->addFitParameter("*SampleBuilder/m_cylinder_ratio", 0.5, 0.1, AttLimits::limited(0.1, 0.9));
m_fitSuite->addFitParameter("*SampleBuilder/m_cylinder_ratio", 0.2, 0.1, AttLimits::fixed());
// Applying fit strategy4: fixing/releasing parameters
// FitSuiteStrategyAdjustParameters *strategy0 = new FitSuiteStrategyAdjustParameters("strategy0");
// strategy0->fix_all().release("*SampleBuilder/m_cylinder_ratio");
// m_fitSuite->addFitStrategy(strategy0);
// FitSuiteStrategyAdjustParameters *strategy1 = new FitSuiteStrategyAdjustParameters("strategy1");
// strategy1->release_all().fix("*SampleBuilder/m_cylinder_ratio");
// m_fitSuite->addFitStrategy(strategy1);
// FitSuiteStrategyAdjustParameters *strategy2 = new FitSuiteStrategyAdjustParameters("strategy2");
// strategy2->release_all();
// m_fitSuite->addFitStrategy(strategy2);
// Applying fit strategy: resizing real data
// m_fitSuite->addFitStrategy(new FitSuiteStrategyAdjustData(3));
// m_fitSuite->addFitStrategy(new FitSuiteStrategyAdjustData(2));
// m_fitSuite->addFitStrategy(new FitSuiteStrategyAdjustData(1));
// m_fitSuite->addFitStrategy(new FitSuiteStrategyDefault());
// Applying fit strategy: disturning data to get out of local minima
m_fitSuite->addFitStrategy(new FitSuiteStrategyBootstrap());
initializeExperiment();
generateRealData(0.1);
......@@ -110,24 +110,6 @@ void TestFittingModule2::execute()
m_fitSuite->setExperiment(mp_experiment);
m_fitSuite->setRealData(*mp_real_data);
m_fitSuite->setMinimizer( new ROOTMinimizer("Minuit2", "Migrad") );
//m_fitSuite->setMinimizer( new ROOTMinimizer("Minuit2", "Simplex") );
//m_fitSuite->setMinimizer( new ROOTMinimizer("Minuit2", "Minimize") );
//m_fitSuite->setMinimizer( new ROOTMinimizer("Minuit2", "Combined") );
//m_fitSuite->setMinimizer( new ROOTMinimizer("Minuit2", "Fumili") ); //doesn't work, Fumili wants special function with derivative
//m_fitSuite->setMinimizer( new ROOTMinimizer("GSLMultiMin", "ConjugateFR") );
//m_fitSuite->setMinimizer( new ROOTMinimizer("GSLMultiMin", "BFGS") );
//m_fitSuite->setMinimizer( new ROOTMinimizer("GSLMultiMin", "SteepestDescent") );
//m_fitSuite->setMinimizer( new ROOTMinimizer("GSLSimAn", "") );
//m_fitSuite->setMinimizer( new ROOTMinimizer("Genetic", "") );
// tuning minimizer
//ROOT::Math::Minimizer *minim = (dynamic_cast<ROOTMinimizer *>(m_fitSuite->getMinimizer()))->getROOTMinimizer();
//minim->SetPrecision(0.00001);
//minim->SetTolerance(0.00001);
//minim->SetStrategy(2);
//minim->SetMaxFunctionCalls(50); // for Minuit
//minim->SetMaxIterations(50); // for GSL
//minim->SetPrintLevel(4);
m_fitSuite->attachObserver( new FitSuiteObserverPrint() );
m_fitSuite->attachObserver( new FitSuiteObserverDraw() );
......
App/src/TestMesoCrystal2.cpp
+ 89
− 14
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......@@ -27,6 +27,7 @@
#include "TRange.h"
#include "FitSuiteHelper.h"
#include "AttLimits.h"
#include "ProgramOptions.h"
#include "TCanvas.h"
#include "TH2D.h"
......@@ -68,48 +69,122 @@ void TestMesoCrystal2::execute()
std::string file_name = Utils::FileSystem::GetHomePath()+"Examples/MesoCrystals/ex02_fitspheres/004_230_P144_im_full_phitheta.txt.gz";
OutputDataReader *reader = OutputDataIOFactory::instance().getReader(file_name);
OutputData<double > *real_data = reader->getOutputData();
OutputData<double > *real_data_half = doubleBinSize(*real_data);
OutputData<double > *real_data_quarter = doubleBinSize(*real_data_half);
// OutputData<double > *real_data_eighth = doubleBinSize(*real_data_quarter);
delete reader;
// OutputData<double > *real_data_half = doubleBinSize(*real_data);
// OutputData<double > *real_data_quarter = doubleBinSize(*real_data_half);
// OutputData<double > *real_data_eighth = doubleBinSize(*real_data_quarter);
c1->cd(1); gPad->SetLogz();
IsGISAXSTools::drawOutputDataInPad(*real_data_quarter, "CONT4 Z", "experiment");
IsGISAXSTools::drawOutputDataInPad(*real_data, "CONT4 Z", "experiment");
c1->Update();
// initializing experiment using real data to have detector axises like in real_data
initializeExperiment(real_data_quarter);
initializeExperiment(real_data);
mp_experiment->printParameters();
// setting fitSuite
FitSuite *fitSuite = new FitSuite();
fitSuite->setExperiment(mp_experiment);
fitSuite->setRealData(*real_data_quarter);
fitSuite->setRealData(*real_data);
fitSuite->setMinimizer( new ROOTMinimizer("Minuit2", "Combined") );
ROOT::Math::Minimizer *minim = (dynamic_cast<ROOTMinimizer *>(fitSuite->getMinimizer()))->getROOTMinimizer();
minim->SetStrategy(2); // 0- not accurate, 1 - normal, 2 - acurate (maximum FCN calls)
fitSuite->addFitParameter("*/lattice_length_a", 6.2*Units::nanometer, 1.0*Units::nanometer,
AttLimits::limited(4.0*Units::nanometer, 8.0*Units::nanometer) );
fitSuite->addFitParameter("*/nanoparticle_radius", 5.7*Units::nanometer, 1.0*Units::nanometer,
AttLimits::limited(2.0*Units::nanometer, 8.0*Units::nanometer) );
// fitSuite->addFitParameter("*/sigma_nanoparticle_radius", 0.1*Units::nanometer, 0.05*Units::nanometer,
// AttLimits::limited(0.01*Units::nanometer, 2.0*Units::nanometer) );
fitSuite->addFitParameter("*/sigma_nanoparticle_radius", 0.1*Units::nanometer, 0.05*Units::nanometer,
AttLimits::limited(0.01*Units::nanometer, 2.0*Units::nanometer) );
fitSuite->addFitParameter("*/meso_height", 500.0*Units::nanometer, 100.0*Units::nanometer,
AttLimits::limited(100.0*Units::nanometer, 2000.0*Units::nanometer) );
fitSuite->addFitParameter("*/meso_radius", 1000.0*Units::nanometer, 100.0*Units::nanometer,
AttLimits::limited(100.0*Units::nanometer, 5000.0*Units::nanometer) );
// fitSuite->addFitParameter("*/sigma_meso_height", 5.0*Units::nanometer, 1.0*Units::nanometer,
// AttLimits::limited(10.0*Units::nanometer, 200.0*Units::nanometer) );
// fitSuite->addFitParameter("*/sigma_meso_radius", 50.0*Units::nanometer, 10.0*Units::nanometer,
// AttLimits::limited(10.0*Units::nanometer, 500.0*Units::nanometer) );
// fitSuite->addFitParameter("*/sigma_lattice_length_a", 1.5*Units::nanometer, 0.5*Units::nanometer,
// AttLimits::limited(0.01*Units::nanometer, 4.0*Units::nanometer) );
fitSuite->addFitParameter("*/sigma_meso_height", 5.0*Units::nanometer, 1.0*Units::nanometer,
AttLimits::limited(10.0*Units::nanometer, 200.0*Units::nanometer) );
fitSuite->addFitParameter("*/sigma_meso_radius", 50.0*Units::nanometer, 10.0*Units::nanometer,
AttLimits::limited(10.0*Units::nanometer, 500.0*Units::nanometer) );
fitSuite->addFitParameter("*/sigma_lattice_length_a", 1.5*Units::nanometer, 0.5*Units::nanometer,
AttLimits::limited(0.01*Units::nanometer, 4.0*Units::nanometer) );
fitSuite->addFitParameter("*/surface_filling_ratio", 0.25, 0.1,
AttLimits::limited(0.1, 0.4) );
fitSuite->addFitParameter("*/roughness", 1.0*Units::nanometer, 0.1*Units::nanometer,
AttLimits::limited(0.01*Units::nanometer, 50.0*Units::nanometer) );
fitSuite->addFitParameter("*Beam/intensity", 8e12, 100, AttLimits::limited(8e11, 8e13) );
// fitSuite->addFitParameter("*/ResolutionFunction2D/sigma_x", 0.0002, 0.00001,
// AttLimits::limited(0.0, 0.002) );
// fitSuite->addFitParameter("*/ResolutionFunction2D/sigma_y", 0.0002, 0.00001,
// AttLimits::limited(0.0, 0.002) );
// // decrease number of bins in fit
// FitSuiteStrategyAdjustData *strategy0 = new FitSuiteStrategyAdjustData(3);
// strategy0->setCallMinimize(false);
// strategy0->setPreserveOriginalData(false);
// fitSuite->addFitStrategy(strategy0);
typedef std::vector<std::string > parnames_t;
std::vector<parnames_t > fixplan;
parnames_t pars;
pars.clear(); pars.push_back("*/lattice_length_a"); pars.push_back("*/nanoparticle_radius"); fixplan.push_back(pars);
pars.clear(); pars.push_back("*/meso_height"); pars.push_back("*/meso_radius"); fixplan.push_back(pars);
pars.clear(); pars.push_back("*Beam/intensity"); fixplan.push_back(pars);
pars.clear(); pars.push_back("*/surface_filling_ratio"); fixplan.push_back(pars);
pars.clear(); pars.push_back("*/roughness"); fixplan.push_back(pars);
pars.clear(); pars.push_back("*/sigma_lattice_length_a"); pars.push_back("*/sigma_nanoparticle_radius"); fixplan.push_back(pars);
pars.clear(); pars.push_back("*/sigma_meso_height"); pars.push_back("*/sigma_meso_radius"); fixplan.push_back(pars);
// here we are fixing specific parameters before fit
for( size_t i_plan=0; i_plan<fixplan.size(); ++i_plan) {
std::ostringstream ostr;
ostr << "strategy" <<i_plan;
FitSuiteStrategyAdjustParameters *strategy = new FitSuiteStrategyAdjustParameters(ostr.str());
strategy->fix_all();
int fitmode = (*mp_options)["fitmode"].as<int>();
if(fitmode==1) {
strategy->setPreserveOriginalValues(true); // initial values of parameters will be restored after each fit
} else {
strategy->setPreserveOriginalValues(false);
}
for(size_t i_par=0; i_par<fixplan[i_plan].size(); ++i_par) {
strategy->release(fixplan[i_plan][i_par]);
}
fitSuite->addFitStrategy(strategy);
}
FitSuiteStrategyAdjustParameters *strategy_all = new FitSuiteStrategyAdjustParameters("strategy_all");
strategy_all->release_all();
fitSuite->addFitStrategy(strategy_all);
// // Applying fit strategy: fixing/releasing parameters
// FitSuiteStrategyAdjustParameters *strategy1 = new FitSuiteStrategyAdjustParameters("strategy1");
// strategy1->fix_all().release("*/lattice_length_a").release("*/nanoparticle_radius");
// strategy1->setPreserveOriginalValues(true);
// fitSuite->addFitStrategy(strategy1);
// FitSuiteStrategyAdjustParameters *strategy2 = new FitSuiteStrategyAdjustParameters("strategy2");
// strategy2->fix_all().release("*/sigma_lattice_length_a").release("*/sigma_nanoparticle_radius");
// fitSuite->addFitStrategy(strategy2);
// FitSuiteStrategyAdjustParameters *strategy3 = new FitSuiteStrategyAdjustParameters("strategy3");
// strategy3->fix_all().release("*/meso_height").release("*/meso_radius").release("*/roughness");
// fitSuite->addFitStrategy(strategy3);
// FitSuiteStrategyAdjustParameters *strategy4 = new FitSuiteStrategyAdjustParameters("strategy4");
// strategy4->fix_all().release("*Beam/intensity");
// fitSuite->addFitStrategy(strategy4);
// FitSuiteStrategyAdjustParameters *strategy5 = new FitSuiteStrategyAdjustParameters("strategy5");
// strategy5->fix_all().release("*/sigma_meso_height").release("*/sigma_meso_radius");
// fitSuite->addFitStrategy(strategy5);
// FitSuiteStrategyAdjustParameters *strategy6 = new FitSuiteStrategyAdjustParameters("strategy6");
// strategy6->release_all();
// fitSuite->addFitStrategy(strategy6);
// IsGISAXSTools::setMinimum(1e2);
// std::string tree_file_name = Utils::FileSystem::GetHomePath()+"Examples/MesoCrystals/ex02_fitspheres/mesofit.tree";
// FitSuiteObserverWriteTree *writeTreeObserver = new FitSuiteObserverWriteTree(tree_file_name);
......
Core/Tools/inc/FitSuite.h
+ 4
− 2
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......@@ -20,10 +20,12 @@
#include "AttLimits.h"
#include "FitMultiParameter.h"
#include "FitSuiteStrategy.h"
#include "IMinimizer.h"
#include <string>
class Experiment;
class IMinimizer;
class ParameterPool;
class ChiSquaredModule;
......@@ -49,7 +51,7 @@ public:
Experiment *getExperiment() { return m_experiment; }
//! set minimizer
void setMinimizer(IMinimizer *minimizer) { m_minimizer = minimizer; }
void setMinimizer(IMinimizer *minimizer) { delete m_minimizer; m_minimizer = minimizer; }
//! get minimizer
IMinimizer *getMinimizer() { return m_minimizer; }
......
Core/Tools/inc/FitSuiteStrategy.h
+ 12
− 4
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......@@ -34,6 +34,8 @@ class FitSuite;
class IFitSuiteStrategy : public INamed
{
public:
// TODO refactor all strategies (decorator, policies?) to change the way of calling FitSuite's minimizer: simple call, clear parameters/matrices before the call, no call at all, see FitSuiteStrategyAdjustData
IFitSuiteStrategy() : m_fit_suite(0) {}
IFitSuiteStrategy(const std::string &name) : INamed(name), m_fit_suite(0) {}
......@@ -59,15 +61,19 @@ public:
//- -------------------------------------------------------------------
//! @class FitSuiteStrategyAdjustData
//! @brief Strategy modifies data before running minimizing round
//! @brief Strategy modifies data before running minimization round
//- -------------------------------------------------------------------
class FitSuiteStrategyAdjustData : public IFitSuiteStrategy
{
public:
FitSuiteStrategyAdjustData(int power_of_two = 1) : IFitSuiteStrategy("FitSuiteStrategyAdjustData"), m_power_of_two(power_of_two) { }
FitSuiteStrategyAdjustData(int power_of_two = 1, bool preserve_original=true, bool call_minimize=true) : IFitSuiteStrategy("FitSuiteStrategyAdjustData"), m_power_of_two(power_of_two), m_preserve_original_data(preserve_original), m_call_minimize(call_minimize) { }
void setPreserveOriginalData(bool preserve_original) { m_preserve_original_data = preserve_original; }
void setCallMinimize(bool call_minimize) { m_call_minimize = call_minimize; }
virtual void execute();
private:
size_t m_power_of_two;
bool m_preserve_original_data; //! if it is true, strategy will restore original data in FitSuite before exiting
bool m_call_minimize; //! if it's true, modify data and then call FitSuite's minimizer, if false - simply modify the data
};
......@@ -78,19 +84,21 @@ private:
class FitSuiteStrategyAdjustParameters : public IFitSuiteStrategy
{
public:
FitSuiteStrategyAdjustParameters(const std::string &name) : IFitSuiteStrategy(name), m_fix_all(false), m_release_all(false) { }
FitSuiteStrategyAdjustParameters() : IFitSuiteStrategy("FitSuiteStrategyAdjustParameters"), m_fix_all(false), m_release_all(false) { }
FitSuiteStrategyAdjustParameters(const std::string &name) : IFitSuiteStrategy(name), m_fix_all(false), m_release_all(false), m_preserve_original_values(false) { }
FitSuiteStrategyAdjustParameters() : IFitSuiteStrategy("FitSuiteStrategyAdjustParameters"), m_fix_all(false), m_release_all(false), m_preserve_original_values(false) { }
virtual ~FitSuiteStrategyAdjustParameters(){}
virtual void execute();
FitSuiteStrategyAdjustParameters &fix_all() { m_fix_all = true; return *this; }
FitSuiteStrategyAdjustParameters &release_all() { m_release_all = true; return *this; }
FitSuiteStrategyAdjustParameters &fix(std::string parname ) { m_pars_to_fix.push_back(parname); return *this; }
FitSuiteStrategyAdjustParameters &release(std::string parname ) { m_pars_to_release.push_back(parname); return *this; }
void setPreserveOriginalValues(bool preserve_values) { m_preserve_original_values = preserve_values; }
private:
bool m_fix_all;
bool m_release_all;
std::vector<std::string > m_pars_to_fix;
std::vector<std::string > m_pars_to_release;
bool m_preserve_original_values; //! if it's true, strategy will set back values of parameters as they were before minimization round
};
......
Core/Tools/src/FitSuite.cpp
+ 6
− 2
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......@@ -109,6 +109,10 @@ void FitSuite::minimize()
{
if( !m_minimizer ) throw NullPointerException("FitSuite::runFit() -> Error! Minimizer is missed.");
// initializing minimizer with fcn function belonging to given class
m_minimizer->setFunction( std::bind1st(std::mem_fun(&FitSuite::functionToMinimize), this), m_fit_params.size() );
// propagating fit parameters to the minimizer
int index(0);
for(fitparameters_t::iterator it = m_fit_params.begin(); it!= m_fit_params.end(); ++it) {
......@@ -134,8 +138,8 @@ void FitSuite::runFit()
// initializing fit parameters
init_fit_parameters();
// initializing minimizer with fcn function belonging to given class
m_minimizer->setFunction( std::bind1st(std::mem_fun(&FitSuite::functionToMinimize), this), m_fit_params.size() );
// // initializing minimizer with fcn function belonging to given class
// m_minimizer->setFunction( std::bind1st(std::mem_fun(&FitSuite::functionToMinimize), this), m_fit_params.size() );
// running minimizer
if( m_fit_strategies.empty() ) {
......
Core/Tools/src/FitSuiteStrategy.cpp
+ 30
− 37
View file @ 9da86387
......@@ -32,13 +32,15 @@ void FitSuiteStrategyAdjustData::execute()
// if no data rediction was requested, just call FitSuite's minimization
if( m_power_of_two == 0 ) {
m_fit_suite->minimize();
if(m_call_minimize) {
m_fit_suite->minimize();
}
return;
}
// saving original data
OutputData<double > *orig_data = m_fit_suite->getChiSquaredModule()->getRealData()->clone();
// create adjusted data which will have doubled (4,8,...) bin size
// create adjusted data which will have doubled (2,4,8,...) bin size
OutputData<double> *adjusted_data = orig_data;
for(size_t i=0; i<m_power_of_two; ++i) {
OutputData<double> *new_data = doubleBinSize(*adjusted_data);
......@@ -59,14 +61,18 @@ void FitSuiteStrategyAdjustData::execute()
experiment->setDetectorParameters(axis0->getSize(), axis0->getMin(), axis0->getMax(), axis1->getSize(), axis1->getMin(), axis1->getMax());
// calling minimization
m_fit_suite->getMinimizer()->clear(); // clear minimizer's parameters and error matrixes
m_fit_suite->minimize();
if(m_call_minimize) {
m_fit_suite->getMinimizer()->clear(); // clear minimizer's parameters and error matrixes
m_fit_suite->minimize();
}
// returning back original data
m_fit_suite->setRealData(*orig_data);
axis0 = reinterpret_cast<const NamedVector<double>*>(orig_data->getAxes()[0]);
axis1 = reinterpret_cast<const NamedVector<double>*>(orig_data->getAxes()[1]);
experiment->setDetectorParameters(axis0->getSize(), axis0->getMin(), axis0->getMax(), axis1->getSize(), axis1->getMin(), axis1->getMax());
// setting back original data
if(m_preserve_original_data) {
m_fit_suite->setRealData(*orig_data);
axis0 = reinterpret_cast<const NamedVector<double>*>(orig_data->getAxes()[0]);
axis1 = reinterpret_cast<const NamedVector<double>*>(orig_data->getAxes()[1]);
experiment->setDetectorParameters(axis0->getSize(), axis0->getMin(), axis0->getMax(), axis1->getSize(), axis1->getMin(), axis1->getMax());
}
delete orig_data;
delete adjusted_data;
......@@ -108,8 +114,21 @@ void FitSuiteStrategyAdjustParameters::execute()
m_fit_suite->getFitParameter((*it))->setFixed(false);
}
std::vector<double > original_param_values;
for(FitSuite::fitparameters_t::iterator it = m_fit_suite->fitparams_begin(); it!=m_fit_suite->fitparams_end(); ++it) {
original_param_values.push_back( (*it)->getValue() );
}
// calling minimization
m_fit_suite->minimize();
if(m_preserve_original_values) {
int index(0);
for(FitSuite::fitparameters_t::iterator it = m_fit_suite->fitparams_begin(); it!=m_fit_suite->fitparams_end(); ++it) {
(*it)->setValue(original_param_values[index++]);
}
}
}
......@@ -130,17 +149,9 @@ void FitSuiteStrategyBootstrap::execute()
double chi2_last = m_fit_suite->getMinimizer()->getMinValue();
FitResult fitResult;
// fitResult.chi2 = m_fit_suite->getMinimizer()->getMinValue();
// for(FitSuite::fitparameters_t::iterator it = m_fit_suite->fitparams_begin(); it!=m_fit_suite->fitparams_end(); ++it) {
// fitResult.param_values.push_back( (*it)->getValue());
// param_values.push_back( (*it)->getValue() );
// }
// fitHistory.push_back(fitResult);
OutputData<double > *orig_data = m_fit_suite->getChiSquaredModule()->getRealData()->clone();
for(int i_iter=0; i_iter<m_n_iterations; ++i_iter) {
OutputData<double > *noisy_data = generateNoisyData(100, *orig_data);
OutputData<double > *noisy_data = generateNoisyData(10, *orig_data);
fitResult.clear();
fitResult.niter = i_iter;
......@@ -198,12 +209,7 @@ void FitSuiteStrategyBootstrap::execute()
std::cout << "FitSuiteStrategyBootstrap::execute() -> Results" << std::endl;
for(size_t i=0; i<fitHistory.size(); ++i) {
std::cout << "i:" << i
<< " niter:" << fitHistory[i].niter
// << " chi2_last:" << fitHistory[i].chi2_last
// << " chi2_noisy:" << fitHistory[i].chi2_noisy
// << " chi2_current:" << fitHistory[i].chi2_current
<< std::endl;
std::cout << "i:" << i << " niter:" << fitHistory[i].niter << std::endl;
std::cout << " chi2_last :" << fitHistory[i].chi2_last << " | ";
for(size_t j=0; j<fitHistory[i].param_values.size(); ++j) std::cout << fitHistory[i].param_values[j] << " ";
std::cout << std::endl;
......@@ -252,23 +258,10 @@ OutputData<double> *FitSuiteStrategyBootstrap::generateNoisyData(double noise_fa
double current = p_result->currentValue();
double sigma = noise_factor*std::sqrt(current);
double random = MathFunctions::GenerateNormalRandom(current, sigma);
//std::cout << "XXX " << current << " " << random << " " << current/random << std::endl;
if (random<0.0) random = 0.0;
p_result->next() = random;
}
// OutputData<double> *p_result = source.clone();
// p_result->resetIndex();
// double random_factor = noise_factor*MathFunctions::GenerateNormalRandom(0.0, 1.0);
// while (p_result->hasNext()) {
// double current = p_result->currentValue();
// double random = current + random_factor*current;
// if (random<0.0) random = 0.0;
// p_result->next() = random;
// std::cout << random << " XXXXXX " << current << " " << random/current << std::endl;
// }
return p_result;
}
Macros/GitUtils/gisasfw_loc.png
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View replaced file @ f7201786 View file @ 9da86387
Macros/GitUtils/gisasfw_loc.png

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Macros/GitUtils/gisasfw_loc.png

15.8 KiB | W: | H:

Macros/GitUtils/gisasfw_loc.png
Macros/GitUtils/gisasfw_loc.png
Macros/GitUtils/gisasfw_loc.png
Macros/GitUtils/gisasfw_loc.png
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