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more code cleaning
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@ -9,7 +9,7 @@
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using namespace std;
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using namespace Latan;
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const Index nPoint1 = 5, nPoint2 = 5;
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const Index nPoint1 = 10, nPoint2 = 10;
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const double xErr = .1, yErr = .1;
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const double exactPar[2] = {0.5,5.};
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const double dx1 = 10.0/static_cast<double>(nPoint1);
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@ -1,54 +0,0 @@
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#include <iostream>
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#include <cmath>
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#include <LatAnalyze/CompiledModel.hpp>
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#include <LatAnalyze/MinuitMinimizer.hpp>
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#include <LatAnalyze/Plot.hpp>
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#include <LatAnalyze/RandGen.hpp>
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#include <LatAnalyze/XYStatData.hpp>
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using namespace std;
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using namespace Latan;
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const Index nPoint = 20;
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const double exactPar[2] = {0.5,5.0}, dx = 10.0/static_cast<double>(nPoint);
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int main(void)
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{
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// generate fake data
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XYStatData data(nPoint, 1, 1);
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RandGen rg;
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double x_k, y_k;
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DoubleModel f = compile("return p_1*exp(-x_0*p_0);", 1, 2);
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for (Index k = 0; k < nPoint; ++k)
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{
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x_k = k*dx;
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y_k = f(&x_k, exactPar) + rg.gaussian(0.0, 0.1);
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cout << x_k << " " << y_k << " " << 0.1 << endl;
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data.x(0, k) = x_k;
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data.y(0, k) = y_k;
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}
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data.yyVar(0, 0).diagonal() = DMat::Constant(nPoint, 1, 0.1*0.1);
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data.assumeXExact(0);
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// fit
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DVec init = DVec::Constant(2, 0.5);
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FitResult p;
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MinuitMinimizer minimizer;
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data.fitAllPoints();
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p = data.fit(minimizer, init, f);
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cout << "a= " << p(0) << " b= " << p(1);
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cout << " chi^2/ndof= " << p.getChi2PerDof();
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cout << " p-value= " << p.getPValue() <<endl;
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// plot result
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Plot plot;
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plot << LogScale(Axis::y) << PlotData(data);
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plot << Color("rgb 'blue'") << PlotFunction(p.getModel(), 0.0, 10.0);
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plot.display();
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return EXIT_SUCCESS;
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}
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