From e6e9e593a451d6e01094c45fb22a15d465ed415b Mon Sep 17 00:00:00 2001
From: Remco Renken <r.j.renken@umcg.nl>
Date: Thu, 24 Nov 2022 14:10:27 +0100
Subject: [PATCH] see previous comment

---
 TestCREClass.m | 61 ++++++++++++++++++++++++++++----------------------
 1 file changed, 34 insertions(+), 27 deletions(-)

diff --git a/TestCREClass.m b/TestCREClass.m
index 70ed77b..ba3e425 100644
--- a/TestCREClass.m
+++ b/TestCREClass.m
@@ -2,31 +2,36 @@
 % show some default behaviour
 % and test the error handling. 
 %% set some constants
-A=randn(100);
+% A=randn(1000,1);
+% A=rand(1000,1);
+A=cat(1,randn(1000,1),randn(200,1)+10);
 %% create instance of CRE class
-S1=CREClass;
-%% Calculate by setting labda equal to each of the (unique) values in the data. 
-S1.UseHistProxyFlag=false;
-S1.EqualSizeBinFlag=false;
-S1.Data=A;% set gaussian data
-S1.Calc;
-disp(S1)
-%% use histogram aproximation with unequal bin sizes in the histogram
-S2=CREClass;
-S2.UseHistProxyFlag=true;
-S2.EqualSizeBinFlag=false;
-S2.Data=A;% set gaussian data
-S2.nBin=numel(A);      % set nbin to npoints; This is fine as we use the cummulative distribution and the formulas as defined in Zografos
-S2.Calc
-disp(S2)
-%% use histogram aproximation with equal bin sizes in the histogram
-S3=CREClass;
-S3.UseHistProxyFlag=true;
-S3.EqualSizeBinFlag=false;
-S3.Data=A;% set gaussian data
-S3.nBin=numel(A);      % set nbin to npoints; This is fine as we use the cummulative distribution and the formulas as defined in Zografos
-S3.Calc
-disp(S3)
+% % % S1=CREClass;
+% % % %% Calculate by setting labda equal to each of the (unique) values in the data. 
+% % % S1.UseHistProxyFlag=false;
+% % % S1.EqualSizeBinFlag=false;
+% % % S1.Data=A;% set gaussian data
+% % % S1.Calc; %get RB based on the CRE
+% % % S1.CalcRBShannon; %% get RB based on shannon entropy
+% % % disp(S1)
+% % % %% use histogram aproximation with unequal bin sizes in the histogram
+% % % S2=CREClass;
+% % % S2.UseHistProxyFlag=true;
+% % % S2.EqualSizeBinFlag=false;
+% % % S2.Data=A;% set gaussian data
+% % % S2.nBin=numel(A);      % set nbin to npoints; This is fine as we use the cummulative distribution and the formulas as defined in Zografos
+% % % S2.Calc
+% % % S2.CalcRBShannon;
+% % % disp(S2)
+% % % %% use histogram aproximation with equal bin sizes in the histogram
+% % % S3=CREClass;
+% % % S3.UseHistProxyFlag=true;
+% % % S3.EqualSizeBinFlag=false;
+% % % S3.Data=A;% set gaussian data
+% % % S3.nBin=numel(A);      % set nbin to npoints; This is fine as we use the cummulative distribution and the formulas as defined in Zografos
+% % % S3.Calc
+% % % S3.CalcRBShannon;
+% % % disp(S3)
 %% Check recalculation of edges
 S4=CREClass;
 S4.UseHistProxyFlag=true;
@@ -34,13 +39,15 @@ S4.EqualSizeBinFlag=true;
 S4.Data=A;% set gaussian data
 S4.nBin=numel(A);      % set nbin to npoints; This is fine as we use the cummulative distribution and the formulas as defined in Zografos
 S4.Calc
+S4.CalcRBShannon;
 disp(S4)
-S4.nBin=numel(A)/10;
+S4.nBin=round(numel(A)/10);
 S4.CalcEdges ; % force a recalculation of the edges
 S4.Calc;
+S4.CalcRBShannon;
 disp(S4)
-
-
+%%
+return;
 %% Show effect of scaling or ofsett the data
 % Scale
 S.Data=100*A;