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LatAnalyze/examples/exFit.cpp

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#include <iostream>
#include <cmath>
#include <LatAnalyze/Functional/CompiledModel.hpp>
#include <LatAnalyze/Io/Io.hpp>
#include <LatAnalyze/Numerical/GslMinimizer.hpp>
#include <LatAnalyze/Core/Plot.hpp>
#include <LatAnalyze/Statistics/XYStatData.hpp>
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using namespace std;
using namespace Latan;
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const Index nPoint1 = 10, nPoint2 = 10;
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const double xErr = .1, yErr = .3;
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);
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int main(void)
{
// generate fake data
XYStatData data;
random_device rd;
mt19937 gen(rd());
normal_distribution<> dis;
double xBuf[2];
DoubleModel f([](const double *x, const double *p)
{return p[1]*exp(-x[0]*p[0])+x[1];}, 2, 2);
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cout << "-- generating fake data..." << endl;
data.addXDim(nPoint1);
data.addXDim(nPoint2);
data.addYDim();
for (Index i1 = 0; i1 < nPoint1; ++i1)
{
xBuf[0] = i1*dx1;
data.x(i1, 0) = xErr*dis(gen) + xBuf[0];
for (Index i2 = 0; i2 < nPoint2; ++i2)
{
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xBuf[1] = i2*dx2;
data.x(i2, 1) = xBuf[1];
data.y(data.dataIndex(i1, i2), 0) = yErr*dis(gen)
+ f(xBuf, exactPar);
}
}
data.setXError(0, DVec::Constant(data.getXSize(0), xErr));
data.assumeXExact(true, 1);
data.setYError(0, DVec::Constant(data.getYSize(), yErr));
// set minimizers
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DVec init = DVec::Constant(2, 0.1);
FitResult p;
GslMinimizer min(GslMinimizer::Algorithm::bfgs2);
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// fit
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min.setVerbosity(Minimizer::Verbosity::Debug);
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cout << "-- fit..." << endl;
f.parName().setName(0, "m");
f.parName().setName(1, "A");
p = data.fit(min, init, f);
p.print();
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// plot
Plot plot;
DVec ref(2);
XYStatData res;
cout << "-- generating plots..." << endl;
ref(1) = 0.;
res = data.getPartialResiduals(p, ref, 0);
plot << PlotRange(Axis::x, 0., 10.);
plot << Color("rgb 'blue'");
plot << PlotFunction(p.getModel().bind(0, ref), 0., 10.);
plot << Color("rgb 'red'");
plot << PlotData(res);
plot.display();
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return EXIT_SUCCESS;
}