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LatAnalyze/examples/exFit.cpp

63 lines
1.9 KiB
C++

#include <iostream>
#include <cmath>
#include <LatAnalyze/CompiledModel.hpp>
#include <LatAnalyze/Io.hpp>
#include <LatAnalyze/MinuitMinimizer.hpp>
#include <LatAnalyze/RandGen.hpp>
#include <LatAnalyze/XYStatData.hpp>
using namespace std;
using namespace Latan;
const Index nPoint1 = 5, nPoint2 = 5;
const double xErr = .1, yErr = .1;
const double exactPar[2] = {0.5,5.};
const double dx1 = 10.0/static_cast<double>(nPoint1);
const double dx2 = 5.0/static_cast<double>(nPoint2);
int main(void)
{
// generate fake data
XYStatData data;
RandGen rg;
double xBuf[2];
DoubleModel f([](const double *x, const double *p)
{return p[1]*exp(-x[0]*p[0])+x[1];}, 2, 2);
data.addXDim("x", nPoint1);
data.addXDim("off", nPoint2);
data.addYDim("y");
for (Index i1 = 0; i1 < nPoint1; ++i1)
{
xBuf[0] = i1*dx1;
data.x(i1, 0) = rg.gaussian(xBuf[0], xErr);
for (Index i2 = 0; i2 < nPoint2; ++i2)
{
xBuf[1] = i2*dx2;
data.x(i2, 1) = xBuf[1];
data.y(data.dataIndex(i1, i2)) = rg.gaussian(f(xBuf, exactPar),
yErr);
printf("% 8e % 8e % 8e % 8e % 8e\n", data.x(i1, 0), xErr,
data.x(i2, 1), data.y(i1), yErr);
}
}
cout << endl;
data.setXError(0, DVec::Constant(data.getXSize(0), xErr));
data.assumeXExact(true, 1);
data.setYError(0, DVec::Constant(data.getYSize(), yErr));
cout << data << endl;
// fit
DVec init = DVec::Constant(2, 0.1);
FitResult p;
MinuitMinimizer minimizer;
minimizer.setVerbosity(Minimizer::Verbosity::Normal);
p = data.fit(minimizer, init, f);
cout << "a= " << p(0) << " b= " << p(1) << endl;
cout << "chi^2/ndof= " << p.getChi2PerDof() << endl;
cout << "p-value= " << p.getPValue() <<endl;
return EXIT_SUCCESS;
}