From 8e8d5fb05570ce50b2bc4f2b0555c3f0c519a8fd Mon Sep 17 00:00:00 2001
From: darksnake <darksnake@daetron>
Date: Wed, 14 Jun 2017 21:44:12 +0300
Subject: [PATCH] Fixing Bayesian tools

---
 numass-main/src/main/groovy/inr/numass/scripts/OldTest.groovy | 2 +-
 .../src/main/groovy/inr/numass/scripts/TritiumTest.groovy     | 4 ++--
 2 files changed, 3 insertions(+), 3 deletions(-)

diff --git a/numass-main/src/main/groovy/inr/numass/scripts/OldTest.groovy b/numass-main/src/main/groovy/inr/numass/scripts/OldTest.groovy
index 2f4c4498..731ea3d7 100644
--- a/numass-main/src/main/groovy/inr/numass/scripts/OldTest.groovy
+++ b/numass-main/src/main/groovy/inr/numass/scripts/OldTest.groovy
@@ -98,7 +98,7 @@ res.print(out);
 //sp.setCaching(true);
 //sp.setSuppressWarnings(true);
 //
-//BayesianManager bm = new BayesianManager();
+//BayesianConfidenceLimit bm = new BayesianConfidenceLimit();
 //bm.printMarginalLikelihood(onComplete, "U2", res, ["E0", "N", "bkg", "U2", "X"], 10000);
 
 //        PrintNamed.printLike2D(Out.onComplete, "like", res, "N", "E0", 30, 60, 2);
diff --git a/numass-main/src/main/groovy/inr/numass/scripts/TritiumTest.groovy b/numass-main/src/main/groovy/inr/numass/scripts/TritiumTest.groovy
index e9b06e1f..08c7e022 100644
--- a/numass-main/src/main/groovy/inr/numass/scripts/TritiumTest.groovy
+++ b/numass-main/src/main/groovy/inr/numass/scripts/TritiumTest.groovy
@@ -20,7 +20,7 @@ import hep.dataforge.data.DataSet
 import hep.dataforge.stat.fit.FitManager
 import hep.dataforge.stat.fit.FitState
 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.tables.ListTable
 import inr.numass.data.SpectrumGenerator
@@ -104,7 +104,7 @@ res.print(out);
 beta.setCaching(true);
 beta.setSuppressWarnings(true);
 
-BayesianManager bm = new BayesianManager();
+BayesianConfidenceLimit bm = new BayesianConfidenceLimit();
 //        bm.setPriorProb(new OneSidedUniformPrior("trap", 0, true));
 //        bm.setPriorProb(new GaussianPrior("trap", 1d, 0.002));
 //        bm.printMarginalLikelihood(Out.onComplete,"U2", res);