portelli/LatAnalyze
1
0
Fork 0
mirror of https://github.com/aportelli/LatAnalyze.git synced 2025-06-19 07:47:05 +01:00
Code Releases Activity

XYStatData: various fixes and improvement, fit is now working

Browse Source
This commit is contained in:
Antonin Portelli
2016-03-16 13:05:56 +00:00
parent 9f67ead605
commit 9bc9288dfb
5 changed files with 87 additions and 51 deletions
Download Patch File Download Diff File Expand all files Collapse all files

73
examples/exFit.cpp
View File

@ -1,46 +1,51 @@
#include <iostream>
#include <cmath>
#include <LatAnalyze/CompiledModel.hpp>
#include <LatAnalyze/MinuitMinimizer.hpp>
#include <LatAnalyze/RandGen.hpp>
#include <LatAnalyze/XYStatData.hpp>
using namespace std;
using namespace Latan;
const Index nPoint = 30;
const double xErr = .01, yErr = .1;
const double exactPar[2] = {0.5,5.0}, dx = 10.0/static_cast<double>(nPoint);
int main(void)
{
XYStatData f;
// generate fake data
XYStatData data;
RandGen rg;
double x_k, y_k;
DoubleModel f([](const double *x, const double *p)
{return p[1]*exp(-x[0]*p[0]);}, 1, 2);
f.addYDim("q1");
f.addYDim("q2");
f.addXDim("x1", 6);
f.addXDim("x2", 5);
f.addXDim("x3", 5);
f.y(f.dataIndex(0,0,0), 0) = 2;
f.y(f.dataIndex(1,1,1), 0) = 4;
f.y(f.dataIndex(2,2,2), 0) = 5;
f.y(f.dataIndex(2,3,3), 0) = 10;
f.y(f.dataIndex(0,0,0), 1) = 1;
f.y(f.dataIndex(1,1,1), 1) = 2;
f.y(f.dataIndex(2,2,3), 1) = 4;
f.fitPoint(false, f.dataIndex(2,2,2), 0);
f.fitPoint(false, f.dataIndex(1,1,1), 1);
f.assumeXXCorrelated(true, 0, 0, 1, 0);
f.assumeXXCorrelated(true, 0, 1, 1, 1);
f.assumeXXCorrelated(true, 0, 2, 1, 2);
f.assumeXXCorrelated(true, 0, 0, 1, 2);
f.assumeXXCorrelated(true, 3, 2, 4, 2);
f.assumeYYCorrelated(true, f.dataIndex(0,0,0), 0, f.dataIndex(2,3,3), 0);
f.assumeYYCorrelated(true, f.dataIndex(0,0,0), 1, f.dataIndex(2,2,3), 1);
f.assumeXYCorrelated(true, 0, 0, f.dataIndex(1,1,1), 0);
f.assumeXExact(true, 0);
f.assumeXExact(true, 1);
f.assumeXExact(true, 2);
cout << f << endl;
f.setXXVar(0, 0, DMat::Identity(6, 6));
f.setXXVar(0, 2, DMat::Identity(6, 5));
f.setXXVar(1, 1, DMat::Identity(5, 5));
f.setXXVar(2, 2, DMat::Identity(5, 5));
DEBUG_MAT(f.makeCorrFilter());
DEBUG_MAT(f.getFitVar());
DEBUG_MAT(f.getFitVar().cwiseProduct(f.makeCorrFilter()));
data.addXDim("x", nPoint);
data.addYDim("y");
for (Index k = 0; k < nPoint; ++k)
{
x_k = k*dx + rg.gaussian(0.0, xErr);
y_k = f(&x_k, exactPar) + rg.gaussian(0.0, yErr);
printf("% 8e % 8e % 8e % 8e\n", x_k, xErr, y_k, yErr);
data.x(k) = x_k;
data.y(k) = y_k;
}
cout << endl;
data.setXError(0, DVec::Constant(nPoint, xErr));
data.setYError(0, DVec::Constant(nPoint, yErr));
cout << data << endl;
// fit
DVec init = DVec::Constant(2, 0.5);
FitResult p;
MinuitMinimizer minimizer;
minimizer.setVerbosity(MinuitMinimizer::Verbosity::Debug);
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;
return EXIT_SUCCESS;
}