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2-pt fit: linear perturbation model

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This commit is contained in:
Antonin Portelli 2019-01-07 11:55:00 +00:00
parent 8b9494029c
commit 005158e2ed
1 changed files with 48 additions and 11 deletions
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49
physics/2pt-fit.cpp
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@ -30,7 +30,7 @@ int main(int argc, char *argv[])
opt.addOption("s", "shift" , OptParser::OptType::value , true,
"time variable shift", "0");
opt.addOption("m", "model" , OptParser::OptType::value , true,
"fit model (exp|exp2|exp3|cosh|cosh2|cosh3|<interpreter code>)", "cosh");
"fit model (exp|exp2|exp3|cosh|cosh2|cosh3|explin|<interpreter code>)", "cosh");
opt.addOption("" , "nPar" , OptParser::OptType::value , true,
"number of model parameters for custom models "
"(-1 if irrelevant)", "-1");
@ -117,7 +117,7 @@ int main(int argc, char *argv[])
// make model //////////////////////////////////////////////////////////////
DoubleModel mod;
bool coshModel = false;
bool coshModel = false, linearModel = false;
if ((model == "exp") or (model == "exp1"))
{
@ -174,6 +174,15 @@ int main(int argc, char *argv[])
+ p[5]*(exp(-p[2]*x[0])+exp(-p[4]*(nt-x[0])));
}, 1, nPar);
}
else if (model == "explin")
{
linearModel = true;
nPar = 2;
mod.setFunction([](const double *x, const double *p)
{
return p[1] - p[0]*x[0];
}, 1, nPar);
}
else
{
if (nPar > 0)
@ -210,20 +219,36 @@ int main(int argc, char *argv[])
mod.parName().setName(p, "E_" + strFrom(p/2));
mod.parName().setName(p + 1, "Z_" + strFrom(p/2));
}
if (linearModel)
{
init(0) = data.y(nt/4, 0)[central] - data.y(nt/4 + 1, 0)[central];
init(1) = data.y(nt/4, 0)[central] + nt/4*init(0);
}
else
{
init(0) = log(data.y(nt/4, 0)[central]/data.y(nt/4 + 1, 0)[central]);
init(1) = data.y(nt/4, 0)[central]/(exp(-init(0)*nt/4));
}
for (Index p = 2; p < nPar; p += 2)
{
init(p) = 2*init(p - 2);
init(p + 1) = init(p - 1)/2.;
}
for (Index p = 0; p < nPar; p += 2)
{
if (linearModel)
{
globMin.setLowLimit(p, -10.*fabs(init(p)));
globMin.setHighLimit(p, 10.*fabs(init(p)));
}
else
{
globMin.setLowLimit(p, 0.);
globMin.setHighLimit(p, 10.*init(p));
globMin.setLowLimit(p + 1, -10.*init(p + 1));
globMin.setHighLimit(p + 1, 10.*init(p + 1));
locMin.setLowLimit(p, 0.);
globMin.setHighLimit(p, 10.*init(p));
}
globMin.setLowLimit(p + 1, -10.*fabs(init(p + 1)));
globMin.setHighLimit(p + 1, 10.*fabs(init(p + 1)));
}
globMin.setPrecision(0.001);
globMin.setMaxIteration(100000);
@ -264,7 +289,10 @@ int main(int argc, char *argv[])
double e0, e0Err;
p << PlotRange(Axis::x, 0, nt - 1);
if (!linearModel)
{
p << LogScale(Axis::y);
}
p << Color("rgb 'blue'") << PlotPredBand(fit.getModel(_), 0, nt - 1);
p << Color("rgb 'blue'") << PlotFunction(fit.getModel(), 0, nt - 1);
p << Color("rgb 'red'") << PlotData(data.getData());
@ -285,6 +313,16 @@ int main(int argc, char *argv[])
}
}
}
else if (linearModel)
{
FOR_STAT_ARRAY(effMass, s)
{
for (Index t = 0; t < nt - 1; ++t)
{
effMass[s](t) = corr[s](t) - corr[s](t+1);
}
}
}
else
{
FOR_STAT_ARRAY(effMass, s)
@ -302,7 +340,6 @@ int main(int argc, char *argv[])
p << Color("rgb 'blue'") << PlotHLine(e0);
p << Color("rgb 'red'") << PlotData(effMassT, effMass);
p.display();
p.save("test");
}
if (doHeatmap)
{