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Merge pull request #14 from AndrewYongZhenNing/develop

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Develop
This commit is contained in:
Antonin Portelli
2019-11-28 16:21:45 +00:00
committed by GitHub
parent 6fe58aba18 ae77d9a2fd
commit d30303bb54
3 changed files with 263 additions and 48 deletions
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162
physics/2pt-fit.cpp
View File

@@ -16,7 +16,7 @@ int main(int argc, char *argv[])
// parse arguments /////////////////////////////////////////////////////////
OptParser opt;
bool parsed, doPlot, doHeatmap, doCorr, fold;
string corrFileName, model, outFileName, outFmt;
string corrFileName, model, outFileName, outFmt, savePlot;
Index ti, tf, shift, nPar, thinning;
double svdTol;
Minimizer::Verbosity verbosity;
@@ -30,7 +30,7 @@ int main(int argc, char *argv[])
opt.addOption("s", "shift" , OptParser::OptType::value , true,
"time variable shift", "0");
opt.addOption("m", "model" , OptParser::OptType::value , true,
"fit model (exp|exp2|exp3|cosh|cosh2|cosh3|explin|<interpreter code>)", "cosh");
"fit model (exp|exp2|exp3|sinh|cosh|cosh2|cosh3|explin|const|<interpreter code>)", "cosh");
opt.addOption("" , "nPar" , OptParser::OptType::value , true,
"number of model parameters for custom models "
"(-1 if irrelevant)", "-1");
@@ -48,6 +48,8 @@ int main(int argc, char *argv[])
"show the fit plot");
opt.addOption("h", "heatmap" , OptParser::OptType::trigger, true,
"show the fit correlation heatmap");
opt.addOption("s", "save-plot", OptParser::OptType::value, true,
"saves the source and .pdf", "");
opt.addOption("", "help" , OptParser::OptType::trigger, true,
"show this help message and exit");
parsed = opt.parse(argc, argv);
@@ -71,6 +73,7 @@ int main(int argc, char *argv[])
fold = opt.gotOption("fold");
doPlot = opt.gotOption("p");
doHeatmap = opt.gotOption("h");
savePlot = opt.optionValue("s");
switch (opt.optionValue<unsigned int>("v"))
{
case 0:
@@ -117,7 +120,7 @@ int main(int argc, char *argv[])
// make model //////////////////////////////////////////////////////////////
DoubleModel mod;
bool coshModel = false, linearModel = false;
bool sinhModel = false, coshModel = false, linearModel = false, constModel = false;
if ((model == "exp") or (model == "exp1"))
{
@@ -144,6 +147,15 @@ int main(int argc, char *argv[])
+ p[5]*exp(-p[4]*x[0]);
}, 1, nPar);
}
else if (model == "sinh")
{
sinhModel = true;
nPar = 2;
mod.setFunction([nt](const double *x, const double *p)
{
return p[1]*(exp(-p[0]*x[0])-exp(-p[0]*(nt-x[0])));
}, 1, nPar);
}
else if ((model == "cosh") or (model == "cosh1"))
{
coshModel = true;
@@ -183,6 +195,15 @@ int main(int argc, char *argv[])
return p[1] - p[0]*x[0];
}, 1, nPar);
}
else if (model == "const")
{
constModel = true;
nPar = 1;
mod.setFunction([](const double *x __dumb, const double *p)
{
return p[0];
}, 1, nPar);
}
else
{
if (nPar > 0)
@@ -214,26 +235,43 @@ int main(int argc, char *argv[])
data.addXDim(nt, "t/a", true);
data.addYDim("C(t)");
data.setUnidimData(tvec, corr);
for (Index p = 0; p < nPar; p += 2)
// set parameter name /////////////
if(constModel)
{
mod.parName().setName(p, "E_" + strFrom(p/2));
mod.parName().setName(p + 1, "Z_" + strFrom(p/2));
mod.parName().setName(0, "const");
}
else
{
for (Index p = 0; p < nPar; p += 2)
{
mod.parName().setName(p, "E_" + strFrom(p/2));
mod.parName().setName(p + 1, "Z_" + strFrom(p/2));
}
}
//set initial values ////////////////
if (linearModel)
{
init(0) = data.y(nt/4, 0)[central] - data.y(nt/4 + 1, 0)[central];
init(1) = data.y(nt/4, 0)[central] + nt/4*init(0);
}
else if(constModel)
{
init(0) = data.y(nt/4, 0)[central];
}
else
{
init(0) = log(data.y(nt/4, 0)[central]/data.y(nt/4 + 1, 0)[central]);
init(1) = data.y(nt/4, 0)[central]/(exp(-init(0)*nt/4));
// cout << init(0) << "\t" << init(1) << endl;
}
for (Index p = 2; p < nPar; p += 2)
{
init(p) = 2*init(p - 2);
init(p + 1) = init(p - 1)/2.;
}
// set limits for minimiser //////////////
for (Index p = 0; p < nPar; p += 2)
{
if (linearModel)
@@ -241,20 +279,32 @@ int main(int argc, char *argv[])
globMin.setLowLimit(p, -10.*fabs(init(p)));
globMin.setHighLimit(p, 10.*fabs(init(p)));
}
else if(constModel)
{
globMin.setLowLimit(p, -10*fabs(init(0)));
locMin.setLowLimit(p, -10*fabs(init(0)));
globMin.setHighLimit(p, 10*fabs(init(0)));
}
else
{
globMin.setLowLimit(p, 0.);
locMin.setLowLimit(p, 0.);
// locMin.setLowLimit(p, 0.);
globMin.setHighLimit(p, 10.*init(p));
}
globMin.setLowLimit(p + 1, -10.*fabs(init(p + 1)));
globMin.setHighLimit(p + 1, 10.*fabs(init(p + 1)));
if(!constModel)
{
locMin.setLowLimit(p+1, -1);
globMin.setLowLimit(p + 1, -10.*fabs(init(p + 1)));
globMin.setHighLimit(p + 1, 10.*fabs(init(p + 1)));
}
}
globMin.setPrecision(0.001);
globMin.setMaxIteration(100000);
globMin.setVerbosity(verbosity);
locMin.setMaxIteration(1000000);
locMin.setVerbosity(verbosity);
// fit /////////////////////////////////
for (Index t = 0; t < nt; ++t)
{
data.fitPoint((t >= ti) and (t <= tf)
@@ -278,69 +328,86 @@ int main(int argc, char *argv[])
fit = data.fit(locMin, init, mod);
fit.print();
}
// plots ///////////////////////////////////////////////////////////////////
if (doPlot)
{
Plot p;
DMatSample effMass(nSample);
DVec effMassT, fitErr;
Index maxT = (coshModel) ? (nt - 2) : (nt - 1);
double e0, e0Err;
p << PlotRange(Axis::x, 0, nt - 1);
if (!linearModel)
if (!linearModel and !constModel)
{
p << LogScale(Axis::y);
}
p << Color("rgb 'blue'") << PlotPredBand(fit.getModel(_), 0, nt - 1);
p << Color("rgb 'blue'") << PlotFunction(fit.getModel(), 0, nt - 1);
p << Color("rgb 'red'") << PlotData(data.getData());
p << Color("rgb 'red'") << PlotData(data.getData());
p.display();
effMass.resizeMat(maxT, 1);
effMassT.setLinSpaced(maxT, 1, maxT);
fitErr = fit.variance().cwiseSqrt();
e0 = fit[central](0);
e0Err = fitErr(0);
if (coshModel)
if(savePlot != "")
{
FOR_STAT_ARRAY(effMass, s)
cout << "Saving plot and source code to " << savePlot << endl;
p.save(savePlot);
}
// effective mass plot //////////////////////////////////////////////////////
if (!constModel)
{
DMatSample effMass(nSample);
DVec effMassT, fitErr;
Index maxT = (coshModel) ? (nt - 2) : (nt - 1);
double e0, e0Err;
effMass.resizeMat(maxT, 1);
effMassT.setLinSpaced(maxT, 0, maxT-1);
fitErr = fit.variance().cwiseSqrt();
e0 = fit[central](0);
e0Err = fitErr(0);
if (coshModel or sinhModel)
{
for (Index t = 1; t < nt - 1; ++t)
FOR_STAT_ARRAY(effMass, s)
{
effMass[s](t - 1) = acosh((corr[s](t-1) + corr[s](t+1))
/(2.*corr[s](t)));
for (Index t = 1; t < nt - 1; ++t)
{
effMass[s](t - 1) = acosh((corr[s](t-1) + corr[s](t+1))
/(2.*corr[s](t)));
}
}
}
}
else if (linearModel)
{
FOR_STAT_ARRAY(effMass, s)
else if (linearModel)
{
for (Index t = 0; t < nt - 1; ++t)
FOR_STAT_ARRAY(effMass, s)
{
effMass[s](t) = corr[s](t) - corr[s](t+1);
for (Index t = 0; t < nt - 1; ++t)
{
effMass[s](t) = corr[s](t) - corr[s](t+1);
}
}
}
}
else
{
FOR_STAT_ARRAY(effMass, s)
else
{
for (Index t = 1; t < nt; ++t)
FOR_STAT_ARRAY(effMass, s)
{
effMass[s](t - 1) = log(corr[s](t-1)/corr[s](t));
for (Index t = 1; t < nt; ++t)
{
effMass[s](t - 1) = log(corr[s](t-1)/corr[s](t));
}
}
}
p.reset();
p << PlotRange(Axis::x, 0, maxT);
p << PlotRange(Axis::y, e0 - 20.*e0Err, e0 + 20.*e0Err);
p << Color("rgb 'blue'") << PlotBand(0, maxT, e0 - e0Err, e0 + e0Err);
p << Color("rgb 'blue'") << PlotHLine(e0);
p << Color("rgb 'red'") << PlotData(effMassT, effMass);
p << Caption("Effective Mass");
p.display();
if(savePlot != "")
{
string savename = savePlot + "_effMass";
cout << "Saving effective mass plot and source code to " << savename << endl;
p.save(savename);
}
}
p.reset();
p << PlotRange(Axis::x, 1, maxT);
p << PlotRange(Axis::y, e0 - 20.*e0Err, e0 + 20.*e0Err);
p << Color("rgb 'blue'") << PlotBand(0, maxT, e0 - e0Err, e0 + e0Err);
p << Color("rgb 'blue'") << PlotHLine(e0);
p << Color("rgb 'red'") << PlotData(effMassT, effMass);
p.display();
}
}
if (doHeatmap)
{
Plot p;
@@ -359,6 +426,7 @@ int main(int argc, char *argv[])
}
}
// output //////////////////////////////////////////////////////////////////
if (!outFileName.empty())
{

7
utils/Makefile.am
View File

@@ -7,6 +7,7 @@ endif
endif
bin_PROGRAMS = \
latan-plot \
latan-sample-combine \
latan-sample-element \
latan-sample-fake \
@@ -14,7 +15,11 @@ bin_PROGRAMS = \
latan-sample-plot \
latan-sample-plot-corr\
latan-sample-read \
latan-resample
latan-resample
latan_plot_SOURCES = plot.cpp
latan_plot_CXXFLAGS = $(COM_CXXFLAGS)
latan_plot_LDFLAGS = -L../lib/.libs -lLatAnalyze
latan_sample_combine_SOURCES = sample-combine.cpp
latan_sample_combine_CXXFLAGS = $(COM_CXXFLAGS)

142
utils/plot.cpp Normal file
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@@ -0,0 +1,142 @@
#include <LatAnalyze/Core/OptParser.hpp>
#include <LatAnalyze/Functional/CompiledModel.hpp>
#include <LatAnalyze/Io/Io.hpp>
#include <LatAnalyze/Statistics/MatSample.hpp>
#include <LatAnalyze/Core/Math.hpp>
#include <LatAnalyze/Numerical/MinuitMinimizer.hpp>
#include <LatAnalyze/Numerical/NloptMinimizer.hpp>
#include <LatAnalyze/Core/Plot.hpp>
#include <LatAnalyze/Statistics/XYSampleData.hpp>
using namespace std;
using namespace Latan;
int main(int argc, char *argv[])
{
// parse arguments /////////////////////////////////////////////////////////
OptParser opt;
bool parsed, imag;
string plotFileName, outFileName, xName, yName, title, save;
vector<string> inFileName;
double xLow, xHigh, spacing;
opt.addOption("i" , "imag" , OptParser::OptType::trigger, true,
"plot imaginary");
opt.addOption("o", "output", OptParser::OptType::value , true,
"output file", "");
opt.addOption("x", "xAxis", OptParser::OptType::value , true,
"x-axis name", "");
opt.addOption("l", "xLow", OptParser::OptType::value , true,
"x-axis lower bound", "0");
opt.addOption("y", "yAxis", OptParser::OptType::value , true,
"y-axis name", "");
opt.addOption("", "spacing", OptParser::OptType::value , true,
"spacing between points", "1");
opt.addOption("s", "save", OptParser::OptType::value, true,
"saves the source and .pdf", "");
opt.addOption("t", "title", OptParser::OptType::value , true,
"plot title", "");
opt.addOption("", "help" , OptParser::OptType::trigger, true,
"show this help message and exit");
parsed = opt.parse(argc, argv);
if (!parsed or opt.gotOption("help") or opt.getArgs().size() != 1)
{
cerr << "usage: " << argv[0] << " <.h5/manifest file> <options> " << endl;
cerr << endl << "Possible options:" << endl << opt << endl;
return EXIT_FAILURE;
}
plotFileName = opt.getArgs().front();
imag = opt.gotOption("i");
xName = opt.optionValue("x");
xLow = opt.optionValue<double>("l");
yName = opt.optionValue("y");
spacing = opt.optionValue<double>("spacing");
save = opt.optionValue("s");
title = opt.optionValue("t");
outFileName = opt.optionValue<string>("o");
if(plotFileName.find(".h5") == string::npos)
{
inFileName = readManifest(plotFileName);
}
// load and plot file(s) /////////////////////////////////////////////////////////
DMatSample tmp;
Index nt;
Plot p;
DVec tAxis;
if(inFileName.size() == 0)
{
tmp = Io::load<DMatSample>(plotFileName);
nt = tmp[central].rows();
if(imag)
{
tmp = tmp.block(0, 1, nt, 1);
}
else
{
tmp = tmp.block(0, 0, nt, 1);
}
xHigh= xLow+spacing*(nt-1);
tAxis.setLinSpaced(nt, xLow, xHigh);
p << PlotData(tAxis, tmp);
}
else
{
tmp = Io::load<DMatSample>(inFileName[0]);
nt = tmp[central].rows();
xHigh= xLow+spacing*(nt-1);
tAxis.setLinSpaced(nt, xLow, xHigh);
for(unsigned long i = 0; i < inFileName.size(); i++)
{
plotFileName = inFileName[i];
tmp = Io::load<DMatSample>(plotFileName);
if(imag)
{
tmp = tmp.block(0, 1, nt, 1);
}
else
{
tmp = tmp.block(0, 0, nt, 1);
}
p << PlotData(tAxis, tmp);
}
}
p << Label(xName, Axis::x);
p << Label(yName, Axis::y);
p << PlotRange(Axis::x, xLow, xHigh);
p << Caption(title);
if(save != "")
{
cout << "Saving plot and source code to " << save << endl;
p.save(save + "/" + title);
}
else
{
cout << "Displaying plot..." << endl;
p.display();
}
// output //////////////////////////////////////////////////////////////////
if (!outFileName.empty())
{
Io::save(tmp, outFileName);
cout << "File saved as: " << outFileName << endl;
}
return EXIT_SUCCESS;
}