88 lines
4.1 KiB
Matlab
88 lines
4.1 KiB
Matlab
classdef CCREClass<CREClass
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%CCRECLASS calculate the Conditional Cummulative Residual Entropy
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% This class uses the CREClass options
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%
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properties
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%the data field inherited from the CREClass will contain the data
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%to calculate the CCRE on.
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%the nBin field inherited from the CREClass will contain the number
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%of bins if UseHistProxy is set.
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end
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properties
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DataRef %This parameter will contain the reference set.
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nBinRef %number of "bins" to use for the reference distribution
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CCRE %parameter containing the conditional Cumulative Residual Entropy
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EquidistantBinFlag=true; % set to true to get equidistant bins, set to false to get equi-content bins,
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% if set to false: each bin will contain (aproximately) an equal
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% number of pixel values.
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end
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methods %constructor
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function obj = CCREClass()
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%CCRECLASS Construct an instance of this class
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% Detailed explanation goes here
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obj@CREClass;
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end
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end
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methods %set and get functions
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function set.DataRef(obj,val)
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if isnumeric(val)
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obj.DataRef=val;
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else
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error('please enter numeric array/matrix as reference');
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end
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end
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function set.nBinRef(obj,val)
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nBinFromCRE=obj.nBin; %park the current value of nBin
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obj.nBin=val; %use the check system from CREClass
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obj.nBinRef=obj.nBin;
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obj.nBin=nBinFromCRE; %restore the current value of nBin
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end
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end
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methods %user callable functions
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%% CCRE A|B
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%
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% $$CCRE = \varepsilon (A) - E[\varepsilon(A|B)]$$
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%
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% $$\varepsilon(A) = -\sum_{\lambda}F_c^A(\lambda)logF_c(A^(\lambda)$$
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% $$F_c^A(\lambda)=\int_{\lambda}^{\infty}p^A(l)dl$$
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%
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% $$E[\varepsilon(A|B)]= \sigma_{\kappa} p^B(\kappa)*\varepsilon(A|B)$$
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%
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% $$\varepsilon(A|B) = \sigma_{\lambda}F_c^{A|B}(\lambda)log
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% F_c^{A|B}(\lambda)$$
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%
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% $$F_c^{A|B}(\lambda) = \int_{\lambda}^{\infty}p^{A,B}(l,k)/p^B(\kappa)dl$$
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%
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% see equation 7 in wan and Vemuri
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function Calc(obj)
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Calc@CREClass(obj); %calculate the CRE for the data.
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if isempty(obj.DataRef);return;end %if no refdata given, return;
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%calculate histogram for RefData
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EVarEpsDataGivenRef=0; %clear previous calculations
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if obj.EquidistantBinFlag
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[pDataRef,E]=histcounts(obj.DataRef(:),obj.nBinRef,'Normalization','probability');
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[JointHist,E1,E2]=histcounts2(obj.Data(:),obj.DataRef(:),[obj.nBin,obj.nBinRef],'Normalization','probability'); %obtain bin edges for Target
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else
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prc=linspace(0,100,obj.nBinRef+1); % define the edges of the bins as a precentile
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Edges=prctile(obj.DataRef(:),prc);
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[pDataRef,E]=histcounts(obj.DataRef(:),Edges,'Normalization','probability');
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[JointHist,E1,E2]=histcounts2(obj.Data(:),obj.DataRef(:),[obj.nBin,obj.nBinRef],'Normalization','probability'); %obtain bin edges for Target
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end
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for k=1:numel(pDataRef) %loop over the bins in pDataRef NB: must be equal to the bins in JointHist for the Ref
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if pDataRef(k)==0;continue;end% if no data at this line go to the next
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ind=E(k)<=obj.DataRef(:)&obj.DataRef(:)<E(k+1); %get an index to all points in Ref data inside the current bin
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CRE_DataGivenDataRef=CREClass;
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CRE_DataGivenDataRef.Data=obj.Data(ind);
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CRE_DataGivenDataRef.nBin=E1; %force the same bin definition for all itterations. This value is ignored if UseHistProxy is set to false
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CRE_DataGivenDataRef.Calc;
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EVarEpsDataGivenRef=EVarEpsDataGivenRef+pDataRef(k)*CRE_DataGivenDataRef.CRE; % I really have to check this line on merit.
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end
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obj.CCRE=obj.CRE-EVarEpsDataGivenRef;
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end
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end
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end
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