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Fixing Bayesian tools

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This commit is contained in:
darksnake 2017-06-14 21:44:12 +03:00
parent 693dd09a1c
commit 8e8d5fb055
2 changed files with 3 additions and 3 deletions
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2
numass-main/src/main/groovy/inr/numass/scripts/OldTest.groovy
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@ -98,7 +98,7 @@ res.print(out);
//sp.setCaching(true); //sp.setCaching(true);
//sp.setSuppressWarnings(true); //sp.setSuppressWarnings(true);
// //
//BayesianManager bm = new BayesianManager(); //BayesianConfidenceLimit bm = new BayesianConfidenceLimit();
//bm.printMarginalLikelihood(onComplete, "U2", res, ["E0", "N", "bkg", "U2", "X"], 10000); //bm.printMarginalLikelihood(onComplete, "U2", res, ["E0", "N", "bkg", "U2", "X"], 10000);
// PrintNamed.printLike2D(Out.onComplete, "like", res, "N", "E0", 30, 60, 2); // PrintNamed.printLike2D(Out.onComplete, "like", res, "N", "E0", 30, 60, 2);

4
numass-main/src/main/groovy/inr/numass/scripts/TritiumTest.groovy
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@ -20,7 +20,7 @@ import hep.dataforge.data.DataSet
import hep.dataforge.stat.fit.FitManager import hep.dataforge.stat.fit.FitManager
import hep.dataforge.stat.fit.FitState import hep.dataforge.stat.fit.FitState
import hep.dataforge.stat.fit.ParamSet import hep.dataforge.stat.fit.ParamSet
import hep.dataforge.stat.likelihood.BayesianManager import hep.dataforge.stat.likelihood.BayesianConfidenceLimit
import hep.dataforge.stat.models.XYModel import hep.dataforge.stat.models.XYModel
import hep.dataforge.tables.ListTable import hep.dataforge.tables.ListTable
import inr.numass.data.SpectrumGenerator import inr.numass.data.SpectrumGenerator
@ -104,7 +104,7 @@ res.print(out);
beta.setCaching(true); beta.setCaching(true);
beta.setSuppressWarnings(true); beta.setSuppressWarnings(true);
BayesianManager bm = new BayesianManager(); BayesianConfidenceLimit bm = new BayesianConfidenceLimit();
// bm.setPriorProb(new OneSidedUniformPrior("trap", 0, true)); // bm.setPriorProb(new OneSidedUniformPrior("trap", 0, true));
// bm.setPriorProb(new GaussianPrior("trap", 1d, 0.002)); // bm.setPriorProb(new GaussianPrior("trap", 1d, 0.002));
// bm.printMarginalLikelihood(Out.onComplete,"U2", res); // bm.printMarginalLikelihood(Out.onComplete,"U2", res);