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first commit for the new fit interface

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Antonin Portelli
2016-03-08 19:37:51 +00:00
parent 352caf30b6
commit 917031747f
6 changed files with 243 additions and 44 deletions
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8
examples/Makefile.am
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@@ -26,7 +26,7 @@ noinst_PROGRAMS = \
exRootFinder
if HAVE_MINUIT
noinst_PROGRAMS += exMin
noinst_PROGRAMS += exFit exMin
endif
exCompiledDoubleFunction_SOURCES = exCompiledDoubleFunction.cpp
@@ -37,6 +37,12 @@ exDerivative_SOURCES = exDerivative.cpp
exDerivative_CFLAGS = -g -O2
exDerivative_LDFLAGS = -L../lib/.libs -lLatAnalyze
if HAVE_MINUIT
exFit_SOURCES = exFit.cpp
exFit_CFLAGS = -g -O2
exFit_LDFLAGS = -L../lib/.libs -lLatAnalyze
endif
exInterp_SOURCES = exInterp.cpp
exInterp_CFLAGS = -g -O2
exInterp_LDFLAGS = -L../lib/.libs -lLatAnalyze

49
examples/exFit.cpp
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@@ -1,54 +1,17 @@
#include <iostream>
#include <cmath>
#include <LatAnalyze/CompiledModel.hpp>
#include <LatAnalyze/MinuitMinimizer.hpp>
#include <LatAnalyze/Plot.hpp>
#include <LatAnalyze/RandGen.hpp>
#include <LatAnalyze/XYStatData.hpp>
#include <LatAnalyze/FitInterface.hpp>
using namespace std;
using namespace Latan;
const Index nPoint = 20;
const double exactPar[2] = {0.5,5.0}, dx = 10.0/static_cast<double>(nPoint);
int main(void)
{
// generate fake data
XYStatData data(nPoint, 1, 1);
RandGen rg;
double x_k, y_k;
DoubleModel f = compile("return p_1*exp(-x_0*p_0);", 1, 2);
for (Index k = 0; k < nPoint; ++k)
{
x_k = k*dx;
y_k = f(&x_k, exactPar) + rg.gaussian(0.0, 0.1);
cout << x_k << " " << y_k << " " << 0.1 << endl;
data.x(0, k) = x_k;
data.y(0, k) = y_k;
}
data.yyVar(0, 0).diagonal() = DMat::Constant(nPoint, 1, 0.1*0.1);
data.assumeXExact(0);
// fit
DVec init = DVec::Constant(2, 0.5);
FitResult p;
MinuitMinimizer minimizer;
FitInterface f;
data.fitAllPoints();
p = data.fit(minimizer, init, f);
cout << "a= " << p(0) << " b= " << p(1);
cout << " chi^2/ndof= " << p.getChi2PerDof();
cout << " p-value= " << p.getPValue() <<endl;
// plot result
Plot plot;
plot << LogScale(Axis::y) << PlotData(data);
plot << Color("rgb 'blue'") << PlotFunction(p.getModel(), 0.0, 10.0);
plot.display();
f.addXDim("a", 3);
f.addXDim("b", 4);
f.addXDim("c", 3);
f.addYDim("y");
return EXIT_SUCCESS;
}

54
examples/exFit.old.cpp Normal file
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@@ -0,0 +1,54 @@
#include <iostream>
#include <cmath>
#include <LatAnalyze/CompiledModel.hpp>
#include <LatAnalyze/MinuitMinimizer.hpp>
#include <LatAnalyze/Plot.hpp>
#include <LatAnalyze/RandGen.hpp>
#include <LatAnalyze/XYStatData.hpp>
using namespace std;
using namespace Latan;
const Index nPoint = 20;
const double exactPar[2] = {0.5,5.0}, dx = 10.0/static_cast<double>(nPoint);
int main(void)
{
// generate fake data
XYStatData data(nPoint, 1, 1);
RandGen rg;
double x_k, y_k;
DoubleModel f = compile("return p_1*exp(-x_0*p_0);", 1, 2);
for (Index k = 0; k < nPoint; ++k)
{
x_k = k*dx;
y_k = f(&x_k, exactPar) + rg.gaussian(0.0, 0.1);
cout << x_k << " " << y_k << " " << 0.1 << endl;
data.x(0, k) = x_k;
data.y(0, k) = y_k;
}
data.yyVar(0, 0).diagonal() = DMat::Constant(nPoint, 1, 0.1*0.1);
data.assumeXExact(0);
// fit
DVec init = DVec::Constant(2, 0.5);
FitResult p;
MinuitMinimizer minimizer;
data.fitAllPoints();
p = data.fit(minimizer, init, f);
cout << "a= " << p(0) << " b= " << p(1);
cout << " chi^2/ndof= " << p.getChi2PerDof();
cout << " p-value= " << p.getPValue() <<endl;
// plot result
Plot plot;
plot << LogScale(Axis::y) << PlotData(data);
plot << Color("rgb 'blue'") << PlotFunction(p.getModel(), 0.0, 10.0);
plot.display();
return EXIT_SUCCESS;
}