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new fit: partial residuals and plots

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This commit is contained in:
Antonin Portelli
2016-04-04 19:09:18 +01:00
parent f82b20dc73
commit 07bacf0e4b
10 changed files with 335 additions and 99 deletions
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30
examples/exFit.cpp
View File

@ -4,6 +4,7 @@
#include <LatAnalyze/Io.hpp>
#include <LatAnalyze/MinuitMinimizer.hpp>
#include <LatAnalyze/NloptMinimizer.hpp>
#include <LatAnalyze/Plot.hpp>
#include <LatAnalyze/RandGen.hpp>
#include <LatAnalyze/XYStatData.hpp>
@ -11,7 +12,7 @@ using namespace std;
using namespace Latan;
const Index nPoint1 = 10, nPoint2 = 10;
const double xErr = .1, yErr = .1;
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);
@ -25,6 +26,7 @@ int main(void)
DoubleModel f([](const double *x, const double *p)
{return p[1]*exp(-x[0]*p[0])+x[1];}, 2, 2);
cout << "-- generating fake data..." << endl;
data.addXDim(nPoint1);
data.addXDim(nPoint2);
data.addYDim();
@ -34,10 +36,10 @@ int main(void)
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);
xBuf[1] = i2*dx2;
data.x(i2, 1) = xBuf[1];
data.y(data.dataIndex(i1, i2), 0) = rg.gaussian(f(xBuf, exactPar),
yErr);
}
}
data.setXError(0, DVec::Constant(data.getXSize(0), xErr));
@ -52,7 +54,7 @@ int main(void)
vector<Minimizer *> min{&globalMin, &localMin};
globalMin.setVerbosity(Minimizer::Verbosity::Normal);
globalMin.setPrecision(0.01);
globalMin.setPrecision(0.1);
globalMin.setMaxIteration(10000);
globalMin.useLowLimit(0);
globalMin.setLowLimit(0, 0.);
@ -65,10 +67,26 @@ int main(void)
localMin.setVerbosity(Minimizer::Verbosity::Normal);
// fit
cout << "-- fit..." << endl;
f.parName().setName(0, "m");
f.parName().setName(1, "A");
p = data.fit(min, init, f);
p.print();
// 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();
return EXIT_SUCCESS;
}

30
examples/exFitSample.cpp
View File

@ -3,6 +3,7 @@
#include <LatAnalyze/CompiledModel.hpp>
#include <LatAnalyze/MinuitMinimizer.hpp>
#include <LatAnalyze/NloptMinimizer.hpp>
#include <LatAnalyze/Plot.hpp>
#include <LatAnalyze/RandGen.hpp>
#include <LatAnalyze/XYSampleData.hpp>
@ -11,7 +12,7 @@ using namespace Latan;
const Index nPoint1 = 10, nPoint2 = 10;
const Index nSample = 1000;
const double xErr = .1, yErr = .1;
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);
@ -25,6 +26,7 @@ int main(void)
DoubleModel f([](const double *x, const double *p)
{return p[1]*exp(-x[0]*p[0])+x[1];}, 2, 2);
cout << "-- generating fake data..." << endl;
data.addXDim(nPoint1);
data.addXDim(nPoint2);
data.addYDim();
@ -36,9 +38,9 @@ int main(void)
data.x(i1, 0)[s] = rg.gaussian(xBuf[0], xErr);
for (Index i2 = 0; i2 < nPoint2; ++i2)
{
xBuf[1] = i2*dx2;
data.x(i2, 1)[s] = xBuf[1];
data.y(data.dataIndex(i1, i2))[s] =
xBuf[1] = i2*dx2;
data.x(i2, 1)[s] = xBuf[1];
data.y(data.dataIndex(i1, i2), 0)[s] =
rg.gaussian(f(xBuf, exactPar), yErr);
}
}
@ -52,7 +54,7 @@ int main(void)
MinuitMinimizer localMin;
vector<Minimizer *> min{&globalMin, &localMin};
globalMin.setPrecision(0.01);
globalMin.setPrecision(0.1);
globalMin.setMaxIteration(10000);
globalMin.useLowLimit(0);
globalMin.setLowLimit(0, 0.);
@ -64,10 +66,28 @@ int main(void)
globalMin.setHighLimit(1, 20.);
// fit
cout << "-- fit..." << endl;
f.parName().setName(0, "m");
f.parName().setName(1, "A");
p = data.fit(min, init, f);
p.print();
// plot
Plot plot;
DVec ref(2);
XYStatData res;
cout << "-- generating plots..." << endl;
ref(1) = 0.;
res = data.getPartialResiduals(p, ref, 0).getData();
plot << PlotRange(Axis::x, 0., 10.);
plot << Color("rgb 'blue'");
plot << PlotPredBand(p.getModel(_).bind(0, ref), 0., 10.);
plot << Color("rgb 'blue'");
plot << PlotFunction(p.getModel().bind(0, ref), 0., 10.);
plot << Color("rgb 'red'");
plot << PlotData(res);
plot.display();
return EXIT_SUCCESS;
}