#include #include #include #include #include #include using namespace std; using namespace Latan; const Index nPoint = 30; const Index nSample = 1000; const double xErr = .2, yErr = .1; const double exactPar[2] = {0.5,5.0}, dx = 10.0/static_cast(nPoint); int main(void) { // generate fake data DMatSample x(nSample, nPoint, 1), y(nSample, nPoint, 1); XYSampleData data(nSample); RandGen rg; double x1_k, x2_k; DoubleModel f([](const double *t, const double *p) {return p[1]*exp(-t[0]*p[0]);}, 1, 2); data.addXDim("x", nPoint); data.addYDim("y"); FOR_STAT_ARRAY(x, s) { for (Index k = 0; k < nPoint; ++k) { x1_k = rg.gaussian(k*dx, xErr); x2_k = rg.gaussian(k*dx, xErr); data.x(k)[s] = x1_k; data.y(k)[s] = rg.gaussian(f(&x2_k, exactPar), yErr); } } cout << data << endl; // fit DVec init = DVec::Constant(2, 0.5); DMat err; SampleFitResult p; MinuitMinimizer minimizer; p = data.fit(minimizer, init, f); err = p.variance().cwiseSqrt(); cout << "a= " << p[central](0) << " +/- " << err(0) << endl; cout << "b= " << p[central](1) << " +/- " << err(1) << endl; cout << "chi^2/ndof= " << p.getChi2PerDof() << endl; cout << "p-value= " << p.getPValue() << endl; return EXIT_SUCCESS; }