%single gene L based interaction shift display
function EZinterAgingDev0
  global Exp
  global matFile

  [matFile,scansDir]=uigetfile('.mat','Open Experiment folder and data storage .mat file name','MultiSelect','on'); 
  AgMPDM=load(fullfile(scansDir,'MasterPlateFiles','MPDMmat.mat'));

  for i=1:size(matFile,2)
    ExpOutmat{i}=fullfile(scansDir,matFile{i});
    EScan{i}=load(ExpOutmat{1});
  end

  % single gene L based interaction shift display
  % function EZinteractDev3
  % expN=1;
 
  % User Input decode for application
  prompt={...
    'Enter LeftSide Central Boundary in Percent:',...
    'Enter RightSide Central Boundary in Percent:', ...
    'Enter Perturbation Numbers for set intersect:' ...
    'Remove No Growth Infinite Interactors:' ...
    'Number of Bins for Histograms'...
    'Subplots(Y), Multiple Plots(N), Suspend Plots(S)'};
    % 'Select Experiment(zone) number:'
         
  name='Interaction User Input';
  numlines=1;
  defaultanswer={'80','60','1','N','39','Y'};
  answer=inputdlg(prompt,name,numlines,defaultanswer);

  negPercent=str2double(cell2mat(answer(1)));
  posPercent=str2double(cell2mat(answer(2)));
  DMstr=cell2mat(answer(3));
  DMcomas=strfind((cell2mat(answer(3))),',');
  removInfinL=answer(4);
  numBins=str2double(cell2mat(answer(5)));
  subplotX=answer(6);
  % expN=str2double(cell2mat(answer(7)));
  n=0;
  for i=DMcomas,
    n=n+1
    DMsel(n)=str2double(DMstr(i-1:i))
    if i==max(DMcomas)
      DMsel(n+1)=str2double(DMstr(i:end))
    end    
  end

  Rn=Exp(expN).RFmean;
  Rs=Exp(expN).RFstd;
  dmN=length(Exp(expN).DM.drug);
  mpN=length(Exp(expN).MP);
  % Intc1=3; IntcLst=5;
  % Calculate Interaction values (with and without
  % standardDeviation/Upper-Lower boundary compensation
  for j=1:dmN
    for m=1:mpN 
      scnN=j + (dmN*(m-1)) % 1,6,11..; 2,7,12 ..; 3,8,13..;
      Xn{m,j,:}=Exp(expN).scan(scnN).plate(1).CFout(:,5);  % Exp(expN).scan(DM{j}(m)).plate(1).CFout(:,5);
      Xn{m,j,:}(Xn{m,j,:}==0)=140;
      Xln{m,j,:}=Exp(expN).scan(scnN).plate(1).CFout(:,11);  % Exp(expN).scan(DM{j}(m)).plate(1).CFout(:,11);
      Xhn{m,j,:}=Exp(expN).scan(scnN).plate(1).CFout(:,12);  % Exp(expN).scan(DM{j}(m)).plate(1).CFout(:,12);
      intL{m,j,:}=(Xn{m,j,:} - Rn(j)); 
      intL{m,j,:}(Xn{m,j,:}==140)=100;
      intLhw{m,j,:}=((Xn{m,1,:}-Xn{m,j,:}) - Rn(1)-Rn(j));
      intLhw{m,j,:}(Xn{m,j,:}==140)=100;
      deltaXR{m,j}(Xn{m,j} >=(Rn(j)+Rs(j)))=( Xln{m,j}(Xn{m,j} >=(Rn(j)+Rs(j))))- (Rn(j)+Rs(j));
      deltaXR{m,j}(Xn{m,j} < (Rn(j)-Rs(j)))=( Xhn{m,j}(Xn{m,j} < (Rn(j)-Rs(j))))- (Rn(j)-Rs(j));
      Xneg=Xhn{m,j}- (Rn(j)-Rs(j));
      Xpos=Xln{m,j}- (Rn(j)+Rs(j));
      deltaXR{m,j}=zeros(1,384);

      for i=1:length(Xpos(:))
        % deltaXR{m,j}(i)=Xpos(i);
        if deltaXR{m,j}(i)==0
          try
            if abs(Xpos(i))<abs(Xneg(i)), deltaXR{m,j}(i)=Xpos(i);end
          catch
          end
        end
      end

      for i=1:length(Xneg(:))
        if deltaXR{m,j}(i)==0, deltaXR{m,j}(i)=Xneg(i); end
        try    
          if abs(Xpos(i))>abs(Xneg(i)), deltaXR{m,j}(i)=Xneg(i); end
        catch
        end   
      end
    
      deltaXR{m,j,:}(Xln{m,j,:}==0)=100;
      deltaXR{m,j,:}(isnan(Xln{m,j,:}))=120;
      deltaXR{m,j,:}(Xhn{m,j,:}==0)=100;
      deltaXR{m,j,:}(isnan(Xhn{m,j,:}))=120;
      
      % Compile all gene related L values for the each pert-DM (j).
      addend=(1+((m-1)*384))  % ((((m-1)*j)*384)+1);
      intLcmp(addend:addend+383,j)=cell2mat(intL(m,j,:)); % ((addend:addend+383),j)=cell2mat(intL(j,m,:));
      intLadjcmp(addend:addend+383,j)=cell2mat(deltaXR(m,j,:)); % ((addend:addend+383),j)=cell2mat(deltaXR(j,m,:));
    end
    % Remove RFs and Blank (or non annotated ' ') orf data Then
    % Filter data per user intput
    intLc{j}=intLcmp(:,j);
    intLwoRFs{j}(1,:)=intLcmp(Exp(expN).mutSpotIndx.woRFs,j);
    intLwoRFs{j}(2,:)=Exp(expN).mutSpotIndx.woRFs; % index of non-RF non-blank spots %Crude early intLcmp(385:(mpN-1)*384,j);
    if strcmpi(removInfinL,'Y') 
      intLwoRFs0{j}(1,:)=intLwoRFs{j}(1,(intLwoRFs{j}(1,:)~=100)); % intLcmp(Exp(1).mutSpotIndx.woRFs,j);
      intLwoRFs0{j}(2,:)=intLwoRFs{j}(2,(intLwoRFs{j}(1,:)~=100)); % intLcmp(385:(mpN-1)*384,j);
      clear intLwoRFs
      intLwoRFs{j}(1,:)=intLwoRFs0{j}(1,:);
      intLwoRFs{j}(2,:)=intLwoRFs0{j}(2,:);  
    end
    
    intLwoRFsorted{j}=sortrows(intLwoRFs{j}',1);
    clear intLcmpSortGT0 intLcmpSortLT0
    tempIntL=intLwoRFsorted{j}(:,1);
    intLcmpSortGT0=tempIntL((tempIntL) >=0);
    intLcmpSortLT0=tempIntL((tempIntL) <0);
    centPosCnt=round(posPercent/100 * length(intLcmpSortGT0));
    centNegCnt=round(negPercent/100 * length(intLcmpSortLT0));
    intLposSel{j}=intLwoRFsorted{j}((length(intLcmpSortLT0)+centPosCnt): end,:);
    intLnegSel{j}=intLwoRFsorted{j}((1:(length(intLcmpSortLT0)-centNegCnt)),:);
    posIntboundryCentralVal(j)=intLcmpSortGT0((centPosCnt),:); % For Histogram use
    negIntboundryCentralVal(j)=intLcmpSortLT0(((length(intLcmpSortLT0))-(centNegCnt)),:); % For Histogram use
    
    % Find potential Interactors within selected range
    if j==DMsel(1) % Intc1,
      InterslstPos{1}=intLposSel{DMsel(1)}(:,2) % intLcmpposInd{Intc1}
      InterslstNeg{1}=intLnegSel{DMsel(1)}(:,2) % intLcmpnegInd{Intc1}
    elseif sum(ismember(DMsel,j))==1   %Intc1 && j<=IntcLst
      InterslstPos{1}=(intersect(InterslstPos{1},intLposSel{j}(:,2))); % ,intLcmpposInd{j}))
      InterslstNeg{1}=(intersect(InterslstNeg{1},intLnegSel{j}(:,2))); % ,intLcmpnegInd{j}))
    end
    
    % Convolute experiment spot index to get scan#, MP# and plateIndx needed
    % later to obtain genename and other descriptors and correlate data
    intLposDIndx{j}(:,2)=ceil((intLposSel{j}(:,2))/384); % mp plate numb  column
    intLposDIndx{j}(:,3)=(rem(intLposSel{j}(:,2),384));
    nn=(intLposDIndx{j}(:,3)==0);
    intLposDIndx{j}(nn,3)=384;
    intLposDIndx{j}(:,1)=j + (dmN*((intLposDIndx{j}(:,2))-1)); % scan numb  column  %intLposDIndx(:,2)* intLposDIndx(:,3); 
    
    intLnegDIndx{j}(:,2)=ceil((intLnegSel{j}(:,2))/384); % mp plate numb  column
    intLnegDIndx{j}(:,3)=(rem(intLnegSel{j}(:,2),384));
    nn=(intLposDIndx{j}(:,3)==0);
    intLnegDIndx{j}(nn,3)=384;
    intLnegDIndx{j}(:,1)=j + (dmN*((intLnegDIndx{j}(:,2))-1)); % scan numb 
    
    % ADJUSTED L for Reference Standard deviation(More conservative) Interaction List compilation
    intLadjwoRFs{j}(1,:)=intLadjcmp(Exp(expN).mutSpotIndx.woRFs,j);     
    intLadjwoRFs{j}(2,:)=Exp(expN).mutSpotIndx.woRFs; % intLadjcmp(385:(mpN-1)*384,j); %intLadjcmp(Exp(expN).mutSpotIndx.woRFs,j);
    
    if strcmpi(removInfinL,'Y')     
      intLadjwoRFs0{j}(1,:)=intLadjwoRFs{j}(1,(intLadjwoRFs{j}(1,:)~=100)) ;   %intLcmp(Exp(1).mutSpotIndx.woRFs,j);
      intLadjwoRFs0{j}(2,:)=intLadjwoRFs{j}(2,(intLadjwoRFs{j}(1,:)~=100)) ;   % Remove Index where spots are infinite (=100);
      clear intLadjwoRFs
      intLadjwoRFs{j}(1,:)=intLadjwoRFs0{j}(1,:);
      intLadjwoRFs{j}(2,:)=intLadjwoRFs0{j}(2,:);  
    end
  
    intLwoRFsortedAdj{j}=sortrows(intLadjwoRFs{j}',1);
    clear intLadjSortGT0 intLadjSortLT0
    tempIntLadj=intLwoRFsortedAdj{j}(:,1);
    intLadjSortGT0=tempIntLadj((tempIntLadj) >=0);
    intLadjSortLT0=tempIntLadj((tempIntLadj) <0);
    centPosCntAdj=round(posPercent/100 * length(intLadjSortGT0));
    centNegCntAdj=round(negPercent/100 * length(intLadjSortLT0));
    intLposSelAdj{j}=intLwoRFsortedAdj{j}((length(intLadjSortLT0)+centPosCntAdj): end,:);
    intLnegSelAdj{j}=intLwoRFsortedAdj{j}((1:(length(intLadjSortLT0)-centNegCntAdj)),:);
    posIntboundryCentralValAdj(j)=intLadjSortGT0((centPosCntAdj),:);
    negIntboundryCentralValAdj(j)=intLadjSortLT0(((length(intLadjSortLT0))-(centNegCntAdj)),:);

    if j==DMsel(1) % Intc1
      InterslstPosAdj{1}=intLposSelAdj{DMsel(1)}(:,2)   % intLcmpposInd{Intc1}
      InterslstNegAdj{1}=intLnegSelAdj{DMsel(1)}(:,2)   % intLcmpnegInd{Intc1}
    elseif sum(ismember(DMsel,j))==1 % j>Intc1 && j<=IntcLst
      InterslstPosAdj{1}=(intersect(InterslstPosAdj{1},intLposSelAdj{j}(:,2))); % ,intLcmpposInd{j}))
      InterslstNegAdj{1}=(intersect(InterslstNegAdj{1},intLnegSelAdj{j}(:,2))); % ,intLcmpnegInd{j}))
    end
    
    % Convolute experiment spot index to get scan#, MP# and plateIndx needed
    % later to obtain genename and other descriptors and correlate data
    intLposDIndxAdj{j}(:,2)=ceil((intLposSelAdj{j}(:,2))/384); % mp plate numb  column
    intLposDIndxAdj{j}(:,3)=(rem(intLposSelAdj{j}(:,2),384));
    nn=(intLposDIndxAdj{j}(:,3)==0);
    intLposDIndx{j}(nn,3)=384;
    intLposDIndxAdj{j}(:,1)=j + (dmN*((intLposDIndxAdj{j}(:,2))-1)); % scan numb  column  %intLposDIndx(:,2)* intLposDIndx(:,3); 
    
    intLnegDIndxAdj{j}(:,2)=ceil((intLnegSelAdj{j}(:,2))/384); % mp plate numb  column
    intLnegDIndxAdj{j}(:,3)=(rem(intLnegSelAdj{j}(:,2),384));
    nn=(intLposDIndxAdj{j}(:,3)==0);
    intLnegDIndxAdj{j}(nn,3)=384;
    intLnegDIndxAdj{j}(:,1)=j + (dmN*((intLnegDIndxAdj{j}(:,2))-1)); % scan numb 
  end  

  % Get interaction values for each DM drugmedia agar type
  IntersValsPos=intLcmp(InterslstPos{1},DMsel);
  IntersValsNeg=intLcmp(InterslstNeg{1},DMsel);
  IntersValsPosAdj=intLadjcmp(InterslstPosAdj{1},DMsel);
  IntersValsNegAdj=intLadjcmp(InterslstNegAdj{1},DMsel);

  % Build 'genelist' data sheet for interactors
  selIntPx{1}(:,6)=InterslstPos{1};
  selIntPx{1}(:,2)=ceil((InterslstPos{1})/384); % mp plate numb  column
  selIntPx{1}(:,3)=(rem(InterslstPos{1},384));
  nn=(selIntPx{1}(:,3)==0);
  selIntPx{1}(nn,3)=384;
  selIntPx{1}(:,4)=ceil(selIntPx{1}(:,3)/24); % row numb
  selIntPx{1}(:,5)=rem(selIntPx{1}(:,3),24);
  mm=(selIntPx{1}(:,5)==0);
  selIntPx{1}(mm,5)=24;
  selIntPx{1}(:,1)=j + (dmN*((selIntPx{1}(:,2))-1)); % scan numb  column  %intLposDIndx(:,2)* intLposDIndx(:,3); 
  selIntP=cell2mat(selIntPx);
  selIntNx{1}(:,6)=InterslstNeg{1};
  selIntNx{1}(:,2)=ceil((InterslstNeg{1})/384); % mp plate numb  column
  selIntNx{1}(:,3)=(rem(InterslstNeg{1},384));
  nn=(selIntNx{1}(:,3)==0);
  selIntNx{1}(nn,3)=384;
  selIntNx{1}(:,4)=ceil(selIntNx{1}(:,3)/24); % row numb
  selIntNx{1}(:,5)=rem(selIntNx{1}(:,3),24);
  mm=(selIntNx{1}(:,5)==0);
  selIntNx{1}(mm,5)=24;
  selIntNx{1}(:,1)=j + (dmN*((selIntNx{1}(:,2))-1));  % scan numb
  selIntN=cell2mat(selIntNx);

  for i=1:size(selIntP,1)
    IPgene(i)=Exp(expN).MP(selIntP(i,2)).genename{1}(selIntP(i,3));
    IPorf(i)=Exp(expN).MP(selIntP(i,2)).orf{1}(selIntP(i,3));
    IPstrain(i)=Exp(expN).MP(selIntP(i,2)).strain{1}(selIntP(i,3));
    IPspecifics(i)=Exp(expN).MP(selIntP(i,2)).specifics{1}(selIntP(i,3));
    IPorfRep(i)=Exp(expN).MP(selIntP(i,2)).orfRep{1}(selIntP(i,3));  
    
    % Bad this is the L data for only the last selected DM perturbation
    % Would need to calculate each scan# for each DMsel value
    ipL(i)=Exp(expN).scan(selIntP(i,1)).plate(1).CFout(selIntP(i,3),5);
    ipLlower(i)=Exp(expN).scan(selIntP(i,1)).plate(1).CFout(selIntP(i,3),11);
    ipLupper(i)=Exp(expN).scan(selIntP(i,1)).plate(1).CFout(selIntP(i,3),12);
  end
 
  for i=1:size(selIntN,1)
    INgene(i)=Exp(expN).MP(selIntN(i,2)).genename{1}(selIntN(i,3));
    INorf(i)=Exp(expN).MP(selIntN(i,2)).orf{1}(selIntN(i,3));
    INstrain(i)=Exp(expN).MP(selIntN(i,2)).strain{1}(selIntN(i,3));
    INspecifics(i)=Exp(expN).MP(selIntN(i,2)).specifics{1}(selIntN(i,3));
    INorfRep(i)=Exp(expN).MP(selIntN(i,2)).orfRep{1}(selIntN(i,3));    
    
    % Bad this is the L data for only the last selected DM perturbation
    % Would need to calculate each scan# for each DMsel value
    inL(i)=Exp(expN).scan(selIntN(i,1)).plate(1).CFout(selIntN(i,3),5);
    inLlower(i)=Exp(expN).scan(selIntN(i,1)).plate(1).CFout(selIntN(i,3),11);
    inLupper(i)=Exp(expN).scan(selIntN(i,1)).plate(1).CFout(selIntN(i,3),12);
  end

  % ADJUSTED with STD and curve fit boundaries to produce more conservative interaction values 
  % Build 'genelist' data sheet for interactors
  selIntPxAdj{1}(:,2)=ceil((InterslstPosAdj{1})/384);  %mp plate numb  column
  selIntPxAdj{1}(:,3)=(rem(InterslstPosAdj{1},384));
  nn=(selIntPxAdj{1}(:,3)==0);
  selIntPxAdj{1}(nn,3)=384;
  selIntPxAdj{1}(:,4)=ceil(selIntPxAdj{1}(:,3)/24);  %row numb
  selIntPxAdj{1}(:,5)=rem(selIntPxAdj{1}(:,3),24);
  mm=(selIntPxAdj{1}(:,5)==0);
  selIntPxAdj{1}(mm,5)=24;
  selIntPxAdj{1}(:,1)=j + (dmN*((selIntPxAdj{1}(:,2))-1));   %scan numb  column  %intLposDIndx(:,2)* intLposDIndx(:,3); 
  selIntPAdj=cell2mat(selIntPxAdj);
  selIntNxAdj{1}(:,2)=ceil((InterslstNegAdj{1})/384);  %mp plate numb  column
  selIntNxAdj{1}(:,3)=(rem(InterslstNegAdj{1},384));
  nn=(selIntNxAdj{1}(:,3)==0);
  selIntNxAdj{1}(nn,3)=384;
  selIntNxAdj{1}(:,4)=ceil(selIntNxAdj{1}(:,3)/24);  %row numb
  selIntNxAdj{1}(:,5)=rem(selIntNxAdj{1}(:,3),24);
  mm=(selIntNxAdj{1}(:,5)==0);
  selIntNxAdj{1}(mm,5)=24;
  selIntNxAdj{1}(:,1)=j + (dmN*((selIntNxAdj{1}(:,2))-1));   %scan numb
  selIntNAdj=cell2mat(selIntNxAdj);

  for i=1:size(selIntPAdj,1)
    IPgeneAdj(i)=Exp(expN).MP(selIntPAdj(i,2)).genename{1}(selIntPAdj(i,3));
    IPorfAdj(i)=Exp(expN).MP(selIntPAdj(i,2)).orf{1}(selIntPAdj(i,3));
    IPstrainAdj(i)=Exp(expN).MP(selIntPAdj(i,2)).strain{1}(selIntPAdj(i,3));
    IPspecificsAdj(i)=Exp(expN).MP(selIntPAdj(i,2)).specifics{1}(selIntPAdj(i,3));
    IPorfRepAdj(i)=Exp(expN).MP(selIntPAdj(i,2)).orfRep{1}(selIntPAdj(i,3));  
    % Bad this is the L data for only the last selected DM perturbation
    % Would need to calculate each scan# for each DMsel value
    ipLAdj(i)=Exp(expN).scan(selIntPAdj(i,1)).plate(1).CFout(selIntPAdj(i,3),5);
    ipLlowerAdj(i)=Exp(expN).scan(selIntPAdj(i,1)).plate(1).CFout(selIntPAdj(i,3),11);
    ipLupperAdj(i)=Exp(expN).scan(selIntPAdj(i,1)).plate(1).CFout(selIntPAdj(i,3),12);
  end
  
  for i=1:size(selIntNAdj,1)
    INgeneAdj(i)=Exp(expN).MP(selIntNAdj(i,2)).genename{1}(selIntNAdj(i,3));
    INorfAdj(i)=Exp(expN).MP(selIntNAdj(i,2)).orf{1}(selIntNAdj(i,3));
    INstrainAdj(i)=Exp(expN).MP(selIntNAdj(i,2)).strain{1}(selIntNAdj(i,3));
    INspecificsAdj(i)=Exp(expN).MP(selIntNAdj(i,2)).specifics{1}(selIntNAdj(i,3));
    INorfRepAdj(i)=Exp(expN).MP(selIntNAdj(i,2)).orfRep{1}(selIntNAdj(i,3));
    %Bad this is the L data for only the last selected DM perturbation
    %Would need to calculate each scan# for each DMsel value
    inLAdj(i)=Exp(expN).scan(selIntNAdj(i,1)).plate(1).CFout(selIntNAdj(i,3),5);
    inLlowerAdj(i)=Exp(expN).scan(selIntNAdj(i,1)).plate(1).CFout(selIntNAdj(i,3),11);
    inLupperAdj(i)=Exp(expN).scan(selIntNAdj(i,1)).plate(1).CFout(selIntNAdj(i,3),12);
  end


  % Plot Histogram
  % subplotX=1;
  figure
  if strcmpi(subplotX,'Y')
    for j=1:dmN
      histLdata=intLwoRFsorted{j}(:,1); % intLcmp(385:(mpN-1)*384,j);
      % histLadjData=intLadjcmp(385:(mpN-1)*384,j);
      hgLdat{j}=histfitJR(histLdata,numBins,'kernel');
      x{j}=get(hgLdat{j}(2),'xdata');
      y{j}=get(hgLdat{j}(2),'ydata');
      xb{j}=get(hgLdat{j}(1),'xdata');
      yb{j}=get(hgLdat{j}(1),'ydata');
      ybpostot{j}=sum(yb{j}(2,(xb{j}(1,:)>=0)));
      ybnegtot{j}=sum(yb{j}(2,(xb{j}(1,:) <0)));
      xbb(j,:)=xb{j}(2,:);
      ybb(j,:)=yb{j}(2,:);
      clf
    end
   
    % Figure
    for j=1:dmN
      histLdata=intLwoRFsorted{j}(:,1); % intLcmp(385:(mpN-1)*384,j);    
      hgL{j}=subplot(2, 4, j), histfitJR(histLdata,numBins,'kernel') ; hold  %hgL{j}=histfit(intLcmp(:,j),31,'kernel')
      subplot(2, 4, j),plot(posIntboundryCentralVal(j), 1:3000,'--r')
      subplot(2, 4, j),plot(negIntboundryCentralVal(j), 1:3000,'--g')
      hold off
    end
    scnsize=get(0,'screensize')
    pos1=[round(scnsize(3)/40), round(scnsize(4)/2 +(scnsize(3)/80)),...
        round(scnsize(3) -round(scnsize(3)/80)),round(scnsize(4)/2 -round(scnsize(4)/80))]
    set(gcf,'outerposition',pos1)
    set(gcf,'Name', 'Interaction Values ');
    
    figure
    for j=1:dmN
      histLadjData=intLwoRFsortedAdj{j}(:,1);  %intLadjcmp(385:(mpN-1)*384,j);
      hgLadj{j}=subplot(2, 4, j),histfitJR(histLadjData,numBins,'kernel') ; hold   %hgLadj{j}=histfit(intLadjcmp(:,j),31,'kernel')
      subplot(2, 4, j),plot(posIntboundryCentralValAdj(j), 1:3000,'--r')
      subplot(2, 4, j),plot(negIntboundryCentralValAdj(j), 1:3000,'--g')
      hold off
    end
    pos2=[round(scnsize(3)/40), round(scnsize(4)/30),...
      round(scnsize(3) -scnsize(3)/80),round(scnsize(4)/2 -scnsize(4)/80)]
    set(gcf,'outerposition',pos2)
    set(gcf,'Name', 'Interaction Compensated by Standard Deviation and Upper/Lower Curvefit boundaries')
  elseif strcmpi(subplotX,'N')    
    for j=1:dmN
      histLdata=intLwoRFsorted{j}(:,1);     %intLcmp(385:(mpN-1)*384,j);
      histLadjData=intLwoRFsortedAdj{j}(:,1);  %intLadjcmp(385:(mpN-1)*384,j);%intLadjcmp(385:(mpN-1)*384,j);  %intLcmp(:,j);  %intLadjcmp(:,j);
      figure    
      hgL{j}=histfitJR(histLdata,numBins,'kernel') ; hold  %hgL{j}=histfit(intLcmp(:,j),31,'kernel')
      plot(posIntboundryCentralVal(j), 1:3000,'--r')
      plot(negIntboundryCentralVal(j), 1:3000,'--g')
      hold off
      figure
      hgLadj{j}=histfitJR(histLadjData,numBins,'kernel') ; hold   %hgLadj{j}=histfit(intLadjcmp(:,j),31,'kernel')
      plot(posIntboundryCentralValAdj(j), 1:3000,'--r')
      plot(negIntboundryCentralValAdj(j), 1:3000,'--g')
      hold off
      x{j}=get(hgL{j}(2),'xdata')
      y{j}=get(hgL{j}(2),'ydata');
      xb{j}=get(hgL{j}(1),'xdata')
      yb{j}=get(hgL{j}(1),'ydata')
      ybpostot{j}=sum(yb{j}(2,(xb{j}(1,:)>=0)))
      ybnegtot{j}=sum(yb{j}(2,(xb{j}(1,:) <0)))
      xbb(j,:)=xb{j}(2,:);
      ybb(j,:)=yb{j}(2,:);
    end
    if strcmpi(subplotX,'N')
      figure
      bar3(ybb); 
      % xxbb=yb{1}(2,:);
      % figure
    end
  else
  end  
  % histograms placed in subplot figure  else multiple histogram plots

  if strcmpi(subplotX,'Y')
    figure
    bar3(ybb);
    set(gcf,'Name', 'Unfiltered Interaction Histogram for all DrugMedias; NoGrowth Interactors set to 100hr (highest bin)')
    %xxbb=yb{1}(2,:);
    %figure
  end

  EZintPrint
  a=1 % TODO what is this for
end