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Highlights from
ProcessNetwork Version 1.0 Software

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ProcessNetwork Version 1.0 Software

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Functions for the delineation of Dynamical Process Networks using Information Theory

[C,nCounts]=getCountMat(tupleMat,nBinMat,sX,sY,NoDataCode)
function [C,nCounts]=getCountMat(tupleMat,nBinMat,sX,sY,NoDataCode)

%This function takes only classified signals, where the signal has already
%been re-classified as integer positives representing the "bin" or
%vocabulary character that each portion of the signal is classified as.
%This will also require information as to the size of the vocabulary used
%to classify the variables.

[nData,~]=size(tupleMat);
C=zeros(nBinMat(sX),nBinMat(sY),nBinMat(sY));
nCounts=0;
for i=1:nData
    dimXt = tupleMat(i,1);
    dimYw = tupleMat(i,2);
    dimYf = tupleMat(i,3);
    if (dimXt~=NoDataCode) && (dimYw~=NoDataCode) && (dimYf~=NoDataCode)
        C(dimXt,dimYw,dimYf)=C(dimXt,dimYw,dimYf)+1;
        nCounts=nCounts+1;
    end
end

%removing the if statement would speed things up if we could ensure
%there were no gaps in the data...

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