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mirror of https://github.com/aportelli/LatAnalyze.git synced 2024-11-10 00:45:36 +00:00

first stab at correlator fit utility classes

This commit is contained in:
Antonin Portelli 2020-01-23 19:11:01 +00:00
parent 51efb2a81f
commit f826f30e82
5 changed files with 566 additions and 0 deletions

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@ -54,6 +54,8 @@ libLatAnalyze_la_SOURCES = \
Numerical/Minimizer.cpp \
Numerical/RootFinder.cpp \
Numerical/Solver.cpp \
Physics/CorrelatorFitter.cpp \
Physics/EffectiveMass.cpp \
Statistics/FitInterface.cpp \
Statistics/Histogram.cpp \
Statistics/Random.cpp \
@ -97,6 +99,8 @@ HPPFILES = \
Numerical/Minimizer.hpp \
Numerical/RootFinder.hpp \
Numerical/Solver.hpp \
Physics/CorrelatorFitter.hpp \
Physics/EffectiveMass.hpp \
Statistics/Dataset.hpp \
Statistics/FitInterface.hpp \
Statistics/Histogram.hpp \

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@ -0,0 +1,331 @@
/*
* CorrelatorFitter.cpp, part of LatAnalyze 3
*
* Copyright (C) 2013 - 2020 Antonin Portelli
*
* LatAnalyze 3 is free software: you can redistribute it and/or modify
* it under the terms of the GNU General Public License as published by
* the Free Software Foundation, either version 3 of the License, or
* (at your option) any later version.
*
* LatAnalyze 3 is distributed in the hope that it will be useful,
* but WITHOUT ANY WARRANTY; without even the implied warranty of
* MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
* GNU General Public License for more details.
*
* You should have received a copy of the GNU General Public License
* along with LatAnalyze 3. If not, see <http://www.gnu.org/licenses/>.
*/
#include <LatAnalyze/Physics/CorrelatorFitter.hpp>
#include <LatAnalyze/includes.hpp>
using namespace std;
using namespace Latan;
DoubleModel CorrelatorModels::makeExpModel(const Index nState)
{
DoubleModel mod;
mod.setFunction([nState](const double *x, const double *p)
{
double res = 0.;
for (unsigned int i = 0; i < nState; ++i)
{
res += p[2*i + 1]*exp(-p[2*i]*x[0]);
}
return res;
}, 1, 2*nState);
for (unsigned int i = 0; i < nState; ++i)
{
mod.parName().setName(2*i, "E_" + strFrom(i));
mod.parName().setName(2*i + 1, "Z_" + strFrom(i));
}
return mod;
}
DoubleModel CorrelatorModels::makeCoshModel(const Index nState, const Index nt)
{
DoubleModel mod;
mod.setFunction([nState, nt](const double *x, const double *p)
{
double res = 0.;
for (unsigned int i = 0; i < nState; ++i)
{
res += p[2*i + 1]*(exp(-p[2*i]*x[0]) + exp(-p[2*i]*(nt - x[0])));
}
return res;
}, 1, 2*nState);
for (unsigned int i = 0; i < nState; ++i)
{
mod.parName().setName(2*i, "E_" + strFrom(i));
mod.parName().setName(2*i + 1, "Z_" + strFrom(i));
}
return mod;
}
DoubleModel CorrelatorModels::makeSinhModel(const Index nState, const Index nt)
{
DoubleModel mod;
mod.setFunction([nState, nt](const double *x, const double *p)
{
double res = 0.;
for (unsigned int i = 0; i < nState; ++i)
{
res += p[2*i + 1]*(exp(-p[2*i]*x[0]) - exp(-p[2*i]*(nt - x[0])));
}
return res;
}, 1, 2*nState);
for (unsigned int i = 0; i < nState; ++i)
{
mod.parName().setName(2*i, "E_" + strFrom(i));
mod.parName().setName(2*i + 1, "Z_" + strFrom(i));
}
return mod;
}
DoubleModel CorrelatorModels::makeConstModel(void)
{
DoubleModel mod;
mod.setFunction([](const double *x, const double *p __dumb)
{
return x[0];
}, 1, 1);
mod.parName().setName(0, "cst");
return mod;
}
DoubleModel CorrelatorModels::makeLinearModel(void)
{
DoubleModel mod;
mod.setFunction([](const double *x, const double *p)
{
return p[0] + p[1]*x[0];
}, 1, 2);
return mod;
}
CorrelatorModels::ModelPar CorrelatorModels::parseModel(const string s)
{
smatch sm;
ModelPar par;
if (regex_match(s, sm, regex("exp([0-9]+)")))
{
par.type = CorrelatorType::exp;
par.nState = strTo<Index>(sm[0].str());
}
else if (regex_match(s, sm, regex("cosh([0-9]+)")))
{
par.type = CorrelatorType::cosh;
par.nState = strTo<Index>(sm[0].str());
}
else if (regex_match(s, sm, regex("sinh([0-9]+)")))
{
par.type = CorrelatorType::sinh;
par.nState = strTo<Index>(sm[0].str());
}
else if (s == "linear")
{
par.type = CorrelatorType::linear;
par.nState = 1;
}
else if (s == "cst")
{
par.type = CorrelatorType::cst;
par.nState = 1;
}
else
{
par.type = CorrelatorType::undefined;
par.nState = 0;
}
return par;
}
DoubleModel CorrelatorModels::makeModel(const CorrelatorModels::ModelPar par,
const Index nt)
{
switch (par.type)
{
case CorrelatorType::undefined:
LATAN_ERROR(Argument, "correlator type is undefined");
break;
case CorrelatorType::exp:
return makeExpModel(par.nState);
break;
case CorrelatorType::cosh:
return makeCoshModel(par.nState, nt);
break;
case CorrelatorType::sinh:
return makeSinhModel(par.nState, nt);
break;
case CorrelatorType::linear:
return makeLinearModel();
break;
case CorrelatorType::cst:
return makeConstModel();
break;
}
}
DVec CorrelatorModels::parameterGuess(const DMatSample &corr,
const ModelPar par)
{
DVec init;
Index nt = corr.size();
switch (par.type)
{
case CorrelatorType::undefined:
LATAN_ERROR(Argument, "correlator type is undefined");
break;
case CorrelatorType::exp:
case CorrelatorType::cosh:
case CorrelatorType::sinh:
init.resize(2*par.nState);
init(0) = log(corr[central](nt/4)/corr[central](nt/4 + 1));
init(1) = corr[central](nt/4)/(exp(-init(0)*nt/4));
for (Index p = 2; p < init.size(); p += 2)
{
init(p) = 2*init(p - 2);
init(p + 1) = init(p - 1)/2.;
}
break;
case CorrelatorType::linear:
init.resize(2);
init(0) = corr[central](nt/4) - corr[central](nt/4 + 1, 0);
init(1) = corr[central](nt/4, 0) + nt/4*init(0);
break;
case CorrelatorType::cst:
init.resize(1);
init(0) = corr[central](nt/4);
break;
default:
break;
}
return init;
}
CorrelatorFitter::CorrelatorFitter(const DMatSample &corr)
{
setCorrelator(corr);
}
CorrelatorFitter::CorrelatorFitter(const std::vector<DMatSample> &corr)
{
setCorrelators(corr);
}
void CorrelatorFitter::setCorrelator(const DMatSample &corr)
{
std::vector<DMatSample> vec;
vec.push_back(corr);
setCorrelators(vec);
}
void CorrelatorFitter::setCorrelators(const std::vector<DMatSample> &corr)
{
Index nSample = corr[0].size();
DMatSample tVec(nSample);
std::vector<const DMatSample *> ptVec;
nt_ = corr[0][central].rows();
tVec.fill(DVec::LinSpaced(nt_, 0, nt_ - 1));
for (auto &c: corr)
{
ptVec.push_back(&c);
}
data_.reset(new XYSampleData(corr[0].size()));
data_->addXDim(nt_, "t/a", true);
for (unsigned int i = 0; i < corr.size(); ++i)
{
data_->addYDim("C_" + strFrom(i) + "(t)");
}
data_->setUnidimData(tVec, ptVec);
model_.resize(corr.size());
range_.resize(corr.size(), make_pair(0, nt_ - 1));
thinning_.resize(corr.size(), 1);
}
void CorrelatorFitter::setModel(const DoubleModel &model, const Index i)
{
model_[i] = model;
}
const DoubleModel & CorrelatorFitter::getModel(const Index i) const
{
return model_.at(i);
}
void CorrelatorFitter::setFitRange(const Index tMin, const Index tMax,
const Index i)
{
range_[i] = make_pair(tMin, tMax);
refreshRanges();
}
void CorrelatorFitter::setCorrelation(const bool isCorrelated, const Index i,
const Index j)
{
data_->assumeYYCorrelated(isCorrelated, i, j);
}
DMat CorrelatorFitter::getVarianceMatrix(void)
{
return data_->getFitVarMat();
}
void CorrelatorFitter::setThinning(const Index thinning, const Index i)
{
thinning_[i] = thinning;
refreshRanges();
}
SampleFitResult CorrelatorFitter::fit(Minimizer &minimizer, const DVec &init)
{
vector<Minimizer *> vecPt = {&minimizer};
return fit(vecPt, init);
}
SampleFitResult CorrelatorFitter::fit(vector<Minimizer *> &minimizer,
const DVec &init)
{
vector<const DoubleModel *> vecPt(model_.size());
for (unsigned int i = 0; i < model_.size(); ++i)
{
vecPt[i] = &(model_[i]);
}
return data_->fit(minimizer, init, vecPt);
}
void CorrelatorFitter::refreshRanges(void)
{
for (unsigned int i = 0; i < range_.size(); ++i)
for (Index t = 0; t < nt_; ++t)
{
data_->fitPoint((t >= range_[i].first) and (t <= range_[i].second)
and ((t - range_[i].first) % thinning_[i] == 0), t);
}
}

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@ -0,0 +1,79 @@
/*
* CorrelatorFitter.hpp, part of LatAnalyze 3
*
* Copyright (C) 2013 - 2020 Antonin Portelli
*
* LatAnalyze 3 is free software: you can redistribute it and/or modify
* it under the terms of the GNU General Public License as published by
* the Free Software Foundation, either version 3 of the License, or
* (at your option) any later version.
*
* LatAnalyze 3 is distributed in the hope that it will be useful,
* but WITHOUT ANY WARRANTY; without even the implied warranty of
* MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
* GNU General Public License for more details.
*
* You should have received a copy of the GNU General Public License
* along with LatAnalyze 3. If not, see <http://www.gnu.org/licenses/>.
*/
#ifndef Latan_CorrelatorFitter_hpp_
#define Latan_CorrelatorFitter_hpp_
#include <LatAnalyze/Global.hpp>
#include <LatAnalyze/Functional/Model.hpp>
#include <LatAnalyze/Statistics/XYSampleData.hpp>
BEGIN_LATAN_NAMESPACE
enum class CorrelatorType {undefined, exp, cosh, sinh, linear, cst};
namespace CorrelatorModels
{
struct ModelPar
{
CorrelatorType type;
Index nState;
};
DoubleModel makeExpModel(const Index nState);
DoubleModel makeCoshModel(const Index nState, const Index nt);
DoubleModel makeSinhModel(const Index nState, const Index nt);
DoubleModel makeConstModel(void);
DoubleModel makeLinearModel(void);
ModelPar parseModel(const std::string s);
DoubleModel makeModel(const ModelPar par, const Index nt);
DVec parameterGuess(const DMatSample &corr, const ModelPar par);
};
class CorrelatorFitter
{
public:
CorrelatorFitter(const DMatSample &corr);
CorrelatorFitter(const std::vector<DMatSample> &corr);
void setCorrelator(const DMatSample &corr);
void setCorrelators(const std::vector<DMatSample> &corr);
const DMatSample & getCorrelator(const Index i = 0) const;
const std::vector<DMatSample> & getCorrelators(void) const;
void setModel(const DoubleModel &model, const Index i = 0);
const DoubleModel & getModel(const Index i = 0) const;
void setFitRange(const Index tMin, const Index tMax, const Index i = 0);
void setCorrelation(const bool isCorrelated, const Index i = 0,
const Index j = 0);
DMat getVarianceMatrix(void);
void setThinning(const Index thinning, const Index i = 0);
SampleFitResult fit(Minimizer &minimizer, const DVec &init);
SampleFitResult fit(std::vector<Minimizer *> &minimizer, const DVec &init);
private:
void refreshRanges(void);
private:
Index nt_{0};
std::unique_ptr<XYSampleData> data_;
std::vector<DoubleModel> model_;
std::vector<std::pair<Index, Index>> range_;
std::vector<Index> thinning_;
};
END_LATAN_NAMESPACE
#endif // Latan_CorrelatorFitter_hpp_

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@ -0,0 +1,103 @@
/*
* EffectiveMass.cpp, part of LatAnalyze 3
*
* Copyright (C) 2013 - 2020 Antonin Portelli
*
* LatAnalyze 3 is free software: you can redistribute it and/or modify
* it under the terms of the GNU General Public License as published by
* the Free Software Foundation, either version 3 of the License, or
* (at your option) any later version.
*
* LatAnalyze 3 is distributed in the hope that it will be useful,
* but WITHOUT ANY WARRANTY; without even the implied warranty of
* MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
* GNU General Public License for more details.
*
* You should have received a copy of the GNU General Public License
* along with LatAnalyze 3. If not, see <http://www.gnu.org/licenses/>.
*/
#include <LatAnalyze/Physics/EffectiveMass.hpp>
#include <LatAnalyze/includes.hpp>
using namespace std;
using namespace Latan;
// constructors ////////////////////////////////////////////////////////////////
EffectiveMass::EffectiveMass(const CorrelatorType type)
: type_(type)
{}
// access //////////////////////////////////////////////////////////////////////
CorrelatorType EffectiveMass::getType(void) const
{
return type_;
}
void EffectiveMass::setType(const CorrelatorType type)
{
type_ = type;
}
// compute effective mass //////////////////////////////////////////////////////
DVec EffectiveMass::operator()(const DVec &corr) const
{
Index nt = corr.size();
DVec em;
if (nt < 2)
{
LATAN_ERROR(Size, "input vector has less than 2 elements");
}
switch (type_)
{
case CorrelatorType::undefined:
LATAN_ERROR(Argument, "correlator type is undefined");
break;
case CorrelatorType::exp:
em.resize(nt - 1);
for (Index t = 1; t < nt; ++t)
{
em(t - 1) = log(corr(t - 1)/corr(t));
}
break;
case CorrelatorType::cosh:
em.resize(nt - 2);
for (Index t = 1; t < nt - 1; ++t)
{
em(t - 1) = acosh((corr(t - 1) + corr(t + 1))/(2.*corr(t)));
}
break;
case CorrelatorType::sinh:
em.resize(nt - 2);
for (Index t = 1; t < nt - 1; ++t)
{
em(t - 1) = acosh((corr(t - 1) + corr(t + 1))/(2.*corr(t)));
}
break;
case CorrelatorType::linear:
em.resize(nt - 1);
for (Index t = 0; t < nt - 1; ++t)
{
em(t) = corr(t) - corr(t - 1);
}
break;
case CorrelatorType::cst:
em = corr;
break;
}
return em;
}
DMatSample EffectiveMass::operator()(const DMatSample &corr) const
{
DMatSample em(corr.size());
FOR_STAT_ARRAY(em, s)
{
em[s] = (*this)(corr[s]);
}
return em;
}

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@ -0,0 +1,49 @@
/*
* EffectiveMass.hpp, part of LatAnalyze 3
*
* Copyright (C) 2013 - 2020 Antonin Portelli
*
* LatAnalyze 3 is free software: you can redistribute it and/or modify
* it under the terms of the GNU General Public License as published by
* the Free Software Foundation, either version 3 of the License, or
* (at your option) any later version.
*
* LatAnalyze 3 is distributed in the hope that it will be useful,
* but WITHOUT ANY WARRANTY; without even the implied warranty of
* MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
* GNU General Public License for more details.
*
* You should have received a copy of the GNU General Public License
* along with LatAnalyze 3. If not, see <http://www.gnu.org/licenses/>.
*/
#ifndef Latan_EffectiveMass_hpp_
#define Latan_EffectiveMass_hpp_
#include <LatAnalyze/Global.hpp>
#include <LatAnalyze/Statistics/MatSample.hpp>
#include <LatAnalyze/Physics/CorrelatorFitter.hpp>
BEGIN_LATAN_NAMESPACE
/******************************************************************************
* Effective mass class *
******************************************************************************/
class EffectiveMass
{
public:
// constructors
EffectiveMass(const CorrelatorType type = CorrelatorType::exp);
// access
CorrelatorType getType(void) const;
void setType(const CorrelatorType type);
// compute effective mass
DVec operator()(const DVec &corr) const;
DMatSample operator()(const DMatSample &corr) const;
private:
CorrelatorType type_;
};
END_LATAN_NAMESPACE
#endif // Latan_EffectiveMass_hpp_