Changed a lot of things in plot_all_test_data_profit

createTestData/plot_all_test_data_profit.m

 function plot_all_test_data_profit()
 
-fitLCModel = true; %false fits profit
 
 reconOption = 5;
 truncOn = false;
@@ -13,7 +12,7 @@ truncOn = false;
 offsetScatter = 0;
 markerScatter = 'd';
 markerColor = [0 1 0];
-% 
+%
 reconOption = 2;
 truncOn = true;
 offsetScatter = 0.15;
@@ -21,16 +20,6 @@ markerScatter = 'x';
 markerColor = [1 0 0];
 
 
-if fitLCModel
-    SoftwareName = 'LCModel';
-    indexFigSoftware = 0;
-else
-    SoftwareName = 'ProFit';
-    indexFigSoftware = 50;
-    proFitIteration =4;
-end
-plotInSameFigureAllSubjects = true;
-
 exportFolders = {'0 Water References',...
     '1 Normal recon', '2 Removed averages ','3 Removed coils',...
     '4 Removed averages and coils', '5 Water Supp Off', '6 Frequency Alignment Off', ...
@@ -38,8 +27,8 @@ exportFolders = {'0 Water References',...
 pathNameExport = 'ProFit test data';
 pathBaseExportFiles = pathToDataFolder(pathNameExport, exportFolders);
 
-pathBaseExportFiles = pathBaseExportFiles(1:end-1);
-pathBaseExportFiles = [pathBaseExportFiles ' - Weighted Cost Fun R3 0.25scale m_15 trunc\'];
+% pathBaseExportFiles = pathBaseExportFiles(1:end-1);
+% pathBaseExportFiles = [pathBaseExportFiles ' - Weighted Cost Fun R3 0.25scale m_15 trunc\'];
 % pathBaseExportFiles = [pathBaseExportFiles ' - Weighted Cost Fun R3 0.25scale m_15 sinebell\'];
 % pathBaseExportFiles = [pathBaseExportFiles ' - Weighted Cost Fun R3 0.25scale m_15 matched\'];
 % pathBaseExportFiles = [pathBaseExportFiles ' - R1 0.25scale m_15 trunc\'];
@@ -110,6 +99,194 @@ for indexMet = 1:numberOfMet
 end
 indecesMainMet = logical(indecesMainMet);
 
+fitLCModel = true; %false fits profit
+if fitLCModel
+    SoftwareName = 'LCModel';
+else
+    SoftwareName = 'ProFit';
+end
+[metConcAllSubjLCModel, metConcAllSubjRefLCModel, metConcAllSubjNormLCModel] = ...
+    getAllMetaboliteConc(dataExportPathBase, dataExportPathBaseRef, truncSuffix, subjects, TEs, ...
+    namingSuffixesAve, namingSuffixesCoil, fitLCModel, reconOption, ...
+    numberOfMet, metabolitesLCModel, metabolitesProFit, metabolitesLabels, indecesMainMet, ...
+    offsetScatter, markerScatter, markerColor);
+
+fitLCModel = false; %false fits profit
+if fitLCModel
+    SoftwareName = 'LCModel';
+else
+    SoftwareName = 'ProFit';
+end
+[metConcAllSubjProFit, metConcAllSubjRefProFit, metConcAllSubjNormProFit] = ...
+    getAllMetaboliteConc(dataExportPathBase, dataExportPathBaseRef, truncSuffix, subjects, TEs, ...
+    namingSuffixesAve, namingSuffixesCoil, fitLCModel, reconOption, ...
+    numberOfMet, metabolitesLCModel, metabolitesProFit, metabolitesLabels, indecesMainMet, ...
+    offsetScatter, markerScatter, markerColor);
+
+metaboliteRef = 14;%'tCho+' 3;%'tCr(CH3)' 12;%'NAA(CH3)'
+metConcAllSubjProFitScaled = metConcAllSubjProFit ./ metConcAllSubjProFit(:,:,metaboliteRef);
+metConcAllSubjRefProFitScaled = metConcAllSubjRefProFit ./ metConcAllSubjRefProFit(:,metaboliteRef);
+metConcAllSubjLCModelScaled = metConcAllSubjLCModel ./ metConcAllSubjLCModel(:,:,metaboliteRef);
+metConcAllSubjRefLCModelScaled = metConcAllSubjRefLCModel ./ metConcAllSubjRefLCModel(:,metaboliteRef);
+
+metaboliteRef = 0;
+metConcAllSubjProFitScaled = metConcAllSubjProFit;
+metConcAllSubjRefProFitScaled = metConcAllSubjRefProFit;
+metConcAllSubjLCModelScaled = metConcAllSubjLCModel;
+metConcAllSubjRefLCModelScaled = metConcAllSubjRefLCModel;
+
+% BA plot paramters
+tit = 'Fitting Repeatability '; % figure title
+subsets = {'32 ave.', '64 ave.'};
+% subsets = {'32 ave.1','32 ave.2','32 ave.3', '64 ave.1', '64 ave.2', '64 ave.3'};
+softwareNames = {'ProFit', 'LCModel'};
+gnames = {subsets, softwareNames}; % names of groups in data {dimension 1 and 2}
+label = {'Ref. Fits','Subset Fits','ratio'}; % Names of data sets
+label_SW_comp = {'LCModel','ProFit','arb.u.'}; % Names of data sets
+corrinfo = {'n','SSE','r2','eq'}; % stats to display of correlation scatter plot
+BAinfo = {'RPC','ks'}; % stats to display on Bland-ALtman plot
+limits = 'auto'; % how to set the axes limits
+if 1 % colors for the data sets may be set as:
+    colors = 'br';      % character codes
+else
+    colors = [0 0 1;... % or RGB triplets
+        1 0 0];
+end
+numOfSimulations = length(namingSuffixesAve)*length(namingSuffixesCoil);
+
+rpc_table = cell(numberOfMet+3,3);
+rpc_table{1,2} = softwareNames{1};
+rpc_table{1,3} = softwareNames{2};
+rpc_table(2:end-2,1) = metabolitesToDisplay;
+rpc_table{end,1} = 'Mean';
+for indexMet = 1: numberOfMet
+    if indexMet == metaboliteRef
+        continue;
+    end
+    %ProFit Concentrations
+    metConcAllSubjProFitPerCr_ = metConcAllSubjProFitScaled(:, :, indexMet);
+    metConcAllSubjProFitPerCr_ = reshape(metConcAllSubjProFitPerCr_,11*3,2);%group same SNR
+    metConcAllSubjRefProFitPerCr_ = metConcAllSubjRefProFitScaled(:, indexMet);
+    metConcAllSubjRefProFitPerCr_ = repmat(metConcAllSubjRefProFitPerCr_,1,6);
+    metConcAllSubjRefProFitPerCr_ = reshape(metConcAllSubjRefProFitPerCr_,11*3,2);%group same SNR
+    
+    %LCModel Concentrations
+    metConcAllSubjLCModelPerCr_ = metConcAllSubjLCModelScaled(:, :, indexMet);
+    metConcAllSubjLCModelPerCr_ = reshape(metConcAllSubjLCModelPerCr_,11*3,2);%group same SNR
+    metConcAllSubjRefLCModelPerCr_ = metConcAllSubjRefLCModelScaled(:, indexMet);
+    metConcAllSubjRefLCModelPerCr_ = repmat(metConcAllSubjRefLCModelPerCr_,1,6);
+    metConcAllSubjRefLCModelPerCr_ = reshape(metConcAllSubjRefLCModelPerCr_,11*3,2);%group same SNR
+    
+    %ProFit&LCModel Concentrations
+    metConcAllSubjPerCr_ = cat(3, metConcAllSubjProFitPerCr_, metConcAllSubjLCModelPerCr_);
+    metConcAllSubjRefPerCr_ = cat(3, metConcAllSubjRefProFitPerCr_, metConcAllSubjRefLCModelPerCr_);
+    %ref Fits vs subfits
+%     BlandAltman(metConcAllSubjRefPerCr_, metConcAllSubjPerCr_, label,[tit metabolitesLCModel{indexMet}],gnames,...
+%         'corrInfo',corrinfo,'baInfo',BAinfo,'axesLimits',limits,'colors',colors, 'showFitCI',' on',...
+%         'baStatsMode','non-parametric','forceZeroIntercept','on');
+    %LCModel vs ProFit
+    BlandAltman(metConcAllSubjLCModelPerCr_, metConcAllSubjProFitPerCr_, label_SW_comp,[tit metabolitesLCModel{indexMet}],subsets,...
+        'corrInfo',corrinfo,'baInfo',BAinfo,'axesLimits',limits,'colors',colors, 'showFitCI',' on',...
+        'baStatsMode','non-parametric','forceZeroIntercept','on', 'diffValueMode', 'percent');
+    %ProFit ref Fits vs subfits
+%     rpcProFit = BlandAltman(metConcAllSubjRefProFitPerCr_, metConcAllSubjProFitPerCr_, label,[tit softwareNames{1} ' ' metabolitesLCModel{indexMet}],subsets,...
+%         'corrInfo',corrinfo,'baInfo',BAinfo,'axesLimits',limits,'colors',[0.75 0.5 0; 0.5 0.2 0], 'showFitCI',' on',...
+%         'baStatsMode','Gaussian','forceZeroIntercept','on', 'diffValueMode', 'percent');
+%     %LCModel ref Fits vs subfits
+%     rpcLCModel = BlandAltman(metConcAllSubjRefLCModelPerCr_, metConcAllSubjLCModelPerCr_, label,[tit softwareNames{2} ' ' metabolitesLCModel{indexMet}],subsets,...
+%         'corrInfo',corrinfo,'baInfo',BAinfo,'axesLimits',limits,'colors',[0, 0.5, 0.75; 0, 0.25 0.5], 'showFitCI',' on',...
+%         'baStatsMode','Gaussian','forceZeroIntercept','on', 'diffValueMode', 'percent');
+%     rpc_table{indexMet+1,2} = rpcProFit;
+%     rpc_table{indexMet+1,3} = rpcLCModel;
+end
+
+rpc_meanProFit = mean(cell2mat(rpc_table(2:end-2,2)));
+rpc_meanLCModel = mean(cell2mat(rpc_table(2:end-2,3)));
+rpc_table{end,2} = rpc_meanProFit;
+rpc_table{end,3} = rpc_meanLCModel;
+xlswrite([pathBaseExportFiles, 'InVivoResults_RPC.xlsx'], rpc_table)
+
+
+meanMetDeviation = mean(abs(metaboliteConcentrationsAllSubjNorm), 'omitnan');
+stdMetDeviation  = std(abs(metaboliteConcentrationsAllSubjNorm), 'omitnan');
+
+meanAllMetDeviation = mean(abs(metaboliteConcentrationsAllSubjNorm(:)), 'omitnan');
+stdAllMetDeviation  = std(abs(metaboliteConcentrationsAllSubjNorm(:)), 'omitnan');
+
+mainMetaboliteConcentrationsAllSubj = metaboliteConcentrationsAllSubjNorm(:, indecesMainMet);
+meanMainMetDeviation = mean(abs(mainMetaboliteConcentrationsAllSubj(:)), 'omitnan');
+stdMainMetDeviation  = std(abs(mainMetaboliteConcentrationsAllSubj(:)), 'omitnan');
+
+metaboliteTable = cell(numberOfMet+3,2);
+metaboliteTable(2:numberOfMet+1,1) = metabolitesLabels;
+metaboliteTable{numberOfMet+2,1}   = 'Mean';
+metaboliteTable{numberOfMet+3,1}   = 'Mean Main Metabolites';
+
+plusMinusSign = char(177);
+metaboliteTable{1,2} = SoftwareName;
+
+for indexMet = 1:numberOfMet
+    metaboliteTable{indexMet+1,2}   = [num2str(meanMetDeviation(indexMet),'%.1f'),  plusMinusSign, num2str(stdMetDeviation(indexMet),'%.1f')];
+end
+
+metaboliteTable{numberOfMet+2,2}   = [num2str(meanAllMetDeviation,'%.1f'),  plusMinusSign, num2str(stdAllMetDeviation,'%.1f')];
+metaboliteTable{numberOfMet+3,2}   = [num2str(meanMainMetDeviation,'%.1f'),  plusMinusSign, num2str(stdMainMetDeviation,'%.1f')];
+
+xlswrite([pathBaseExportFiles, 'InVivoResults' SoftwareName, '.xlsx'], metaboliteTable)
+%
+% mean(cell2mat(NAA_SNR_all(:,1)))
+% std(cell2mat(NAA_SNR_all(:,1)))
+% mean(cell2mat(NAA_SNR_all(:,2)))
+% mean(cell2mat(NAA_SNR_all(:,3)))
+% mean(cell2mat(NAA_SNR_all(:,4)))
+% mean(cell2mat(NAA_SNR_all(:,5)))
+% std(cell2mat(NAA_SNR_all(:,5)))
+
+end
+
+function metaboliteConcentrations = matchFittedMetabolites(fitLCModel, currentConcentration, metabolitesNames,  proFitIteration, activeMetabolites)
+metaboliteConcentrations = zeros(size(metabolitesNames));
+
+if fitLCModel
+    activeMetabolites = currentConcentration(1,:);
+    currentConcentration = currentConcentration(2,:);
+else
+    activeMetabolites = activeMetabolites{proFitIteration};
+    currentConcentration = currentConcentration{proFitIteration};
+end
+for indexMet = 1 : length(metabolitesNames)
+    indexMetFit = find(strcmp(activeMetabolites,metabolitesNames(indexMet)));
+    if fitLCModel
+        metaboliteConcentrations(indexMet) = currentConcentration{indexMetFit};
+    else
+        metaboliteConcentrations(indexMet) = currentConcentration(indexMetFit);
+    end
+end
+%     metaboliteConcentrations(1) = metaboliteConcentrations(1) / 1e6; % adjust the MMB to be within range
+end
+
+function [metaboliteConcentrationsAllSubj, metaboliteConcentrationsAllSubjRef, metaboliteConcentrationsAllSubjNorm] = ...
+    getAllMetaboliteConc(dataExportPathBase, dataExportPathBaseRef, truncSuffix, subjects, TEs, ...
+    namingSuffixesAve, namingSuffixesCoil, fitLCModel, reconOption, ...
+    numberOfMet, metabolitesLCModel, metabolitesProFit, metabolitesLabels, indecesMainMet, ...
+    offsetScatter, markerScatter, markerColor)
+% settings
+plotInSameFigureAllSubjects = true;
+scalingFactorColor = 1;
+yLimValue = 50;
+NAA_SNR_global_ref = 700;% 650; for truncOn true
+
+
+if fitLCModel
+    SoftwareName = 'LCModel';
+    indexFigSoftware = 0;
+else
+    SoftwareName = 'ProFit';
+    indexFigSoftware = 50;
+    proFitIteration =4;
+end
+
+% prepare arrays etc
 numberOfSubjects = length(subjects);
 dataExportPathRef = cell(1,numberOfSubjects);
 dataExportPath = cell(1,numberOfSubjects);
@@ -117,18 +294,12 @@ for indexSubj = 1:numberOfSubjects
     dataExportPathRef{indexSubj} = [dataExportPathBaseRef subjects{indexSubj} '\\'];
     dataExportPath{indexSubj} = [dataExportPathBase subjects{indexSubj} '\\'];
 end
-
-numberOfTEs = length(TEs);
 figId = figure();
 colormapVect = colormap();
 close(figId);
 colormapVect = colormapVect(end:-1:1, :);
+numberOfTEs = length(TEs);
 numberOfColors = size(colormapVect,1);
-scalingFactorColor = 1;
-yLimValue = 50;
-NAA_SNR_global_ref = 700;% 650; for truncOn true
-
-%% do the actual plotting
 NAA_SNR_all = cell(numberOfSubjects, numberOfTEs);
 meanPercentualChange = 0;
 iterator = 0;
@@ -136,7 +307,10 @@ nansIterator = 0;
 meanFQN = 0;
 meanFQN2 = 0;
 numOfSimulations = length(namingSuffixesAve)*length(namingSuffixesCoil);
-metaboliteConcentrationsAllSubj = zeros(numberOfSubjects * numOfSimulations, numberOfMet);
+metaboliteConcentrationsAllSubjNorm = zeros(numberOfSubjects * numOfSimulations, numberOfMet);
+metaboliteConcentrationsAllSubj = zeros(numberOfSubjects, numOfSimulations, numberOfMet);
+metaboliteConcentrationsAllSubjRef = zeros(numberOfSubjects, numberOfMet);
+%% do the actual plotting
 for indexSubj = 1:numberOfSubjects
     if fitLCModel
         load([dataExportPathRef{indexSubj}, 'concentrations' truncSuffix '.mat'], 'concentrations');
@@ -144,11 +318,15 @@ for indexSubj = 1:numberOfSubjects
         load([dataExportPath{indexSubj}, 'concentrations' truncSuffix '.mat'], 'concentrations');
     else
         load([dataExportPathRef{indexSubj}, 'concentrations' truncSuffix '_profit.mat'], 'concentrations', 'activeMetabolites', 'FQNs', 'FQNs2');
-        concentrationsRef = concentrations;        
+        load([dataExportPathRef{indexSubj}, 'concentrations', truncSuffix '_H2O_profit.mat'], 'concentrations_H2O');
+        concentrationsRef = concentrations;
+        concentrations_H2ORef = cell2mat(concentrations_H2O);
         activeMetabolitesRef = activeMetabolites;
         FQNsRef =  FQNs;
         FQNsRef2 =  FQNs2;
-        load([dataExportPath{indexSubj}, 'concentrations' truncSuffix '_profit.mat'], 'concentrations', 'activeMetabolites', 'FQNs', 'FQNs2');
+        load([dataExportPath{indexSubj}, 'concentrations' truncSuffix '_profit.mat'], 'concentrations', 'activeMetabolites', 'FQNs', 'FQNs2'); 
+        load([dataExportPath{indexSubj}, 'concentrations', truncSuffix '_H2O_profit.mat'], 'concentrations_H2O');
+        concentrations_H2O = cell2mat(concentrations_H2O);
     end
     % load stats (SNR, FWHM, etc)
     load([dataExportPathRef{indexSubj}, 'stats' truncSuffix '.mat'], 'stats');
@@ -178,8 +356,11 @@ for indexSubj = 1:numberOfSubjects
         
         if fitLCModel
             metaboliteConcentrationsRef = matchFittedMetabolites(fitLCModel, currentConcentrationRef, metabolitesLCModel, [], []);
+            metaboliteConcentrationsRef(end) = metaboliteConcentrationsRef(end) .* 1e-8;
         else
-            metaboliteConcentrationsRef = matchFittedMetabolites(fitLCModel, currentConcentrationRef, metabolitesProFit, proFitIteration, activeMetabolitesRef);
+            metaboliteConcentrationsRef_notScaled = matchFittedMetabolites(fitLCModel, currentConcentrationRef, metabolitesProFit, proFitIteration, activeMetabolitesRef);
+            %scale the concentations similarly as LCModel
+            metaboliteConcentrationsRef = metaboliteConcentrationsRef_notScaled * 40873 / concentrations_H2ORef * 2;
         end
         if ~fitLCModel
             currentFQNRef = FQNsRef{indexTE,1, 1};
@@ -188,14 +369,14 @@ for indexSubj = 1:numberOfSubjects
             FQN_Ref2 = currentFQNRef2{proFitIteration};
         end
         %scale with the MC water reference amplitude
-        metaboliteConcentrationsRef = metaboliteConcentrationsRef ./ water_ref_amplitude;
         metaboliteConcentrationsRefNormalized = (metaboliteConcentrationsRef-metaboliteConcentrationsRef) ./ metaboliteConcentrationsRef *100;
         scatter([1:numberOfMet]-offsetScatter,metaboliteConcentrationsRefNormalized,[],'d', 'MarkerEdgeColor', currentColorRef);
-
-%         cb = colorbar;
-%         cb.Limits = [0 NAA_ref_SNR*scalingFactorColor];
-%         cb.Color = colormapVect
-
+        
+        metaboliteConcentrationsAllSubjRef(indexSubj, :)  = metaboliteConcentrationsRef;
+        %         cb = colorbar;
+        %         cb.Limits = [0 NAA_ref_SNR*scalingFactorColor];
+        %         cb.Color = colormapVect
+        
         metaboliteConcentrationsAll = zeros(numOfSimulations, numberOfMet);
         % do plotting for each individual case
         for indexAverageDelete = 1: length(namingSuffixesAve)
@@ -210,8 +391,16 @@ for indexSubj = 1:numberOfSubjects
                     hold on
                     if fitLCModel
                         metaboliteConcentrations = matchFittedMetabolites(fitLCModel, currentConcentration, metabolitesLCModel, [], []);
-                     else
-                        metaboliteConcentrations = matchFittedMetabolites(fitLCModel, currentConcentration, metabolitesProFit, proFitIteration, activeMetabolites);
+                        metaboliteConcentrations(end) = metaboliteConcentrations(end) .* 1e-8;
+                    else
+                        metaboliteConcentrations_notScaled = matchFittedMetabolites(fitLCModel, currentConcentration, metabolitesProFit, proFitIteration, activeMetabolites);
+                        %scale the concentations similarly as LCModel
+                        metaboliteConcentrations = metaboliteConcentrations_notScaled * 40873 / concentrations_H2O(runningIndex) * 2;
+                    end
+                    if runningIndex <= 3 %scale with coresponding averages
+                        metaboliteConcentrations = metaboliteConcentrations * 3;
+                    else
+                        metaboliteConcentrations = metaboliteConcentrations *3/2;
                     end
                     if ~fitLCModel
                         currentFQN = FQNs{indexTE,indexAverageDelete, indexCoilDelete};
@@ -220,26 +409,24 @@ for indexSubj = 1:numberOfSubjects
                         currentFQN2 = FQNs2{indexTE,indexAverageDelete, indexCoilDelete};
                         FQN2 = currentFQN2{proFitIteration};
                         meanFQN2 = meanFQN2 + FQN2;
-                    end
-                %scale with the MC water reference amplitude
-                    metaboliteConcentrations = metaboliteConcentrations ./ water_amplitude;
-
+                    end                    
                     metaboliteConcentrationsNormalized = (metaboliteConcentrations-metaboliteConcentrationsRef) ...
                         ./ metaboliteConcentrationsRef *100;
                     metaboliteConcentrationsAll(runningIndex, :) = metaboliteConcentrationsNormalized;
                     metaboliteConcentrationsNormalized(abs(metaboliteConcentrationsNormalized) > yLimValue*2) = NaN; %TODO change! This is actually stupid
-                    metaboliteConcentrationsAllSubj(runningIndex + (indexSubj-1)*numOfSimulations, :) = metaboliteConcentrationsNormalized;
+                    metaboliteConcentrationsAllSubjNorm(runningIndex + (indexSubj-1)*numOfSimulations, :) = metaboliteConcentrationsNormalized;
+                    metaboliteConcentrationsAllSubj(indexSubj, runningIndex, :) = metaboliteConcentrations;
                     if reconOption>4
                         %use this scatter if you want to check if there are structural offsets
-                        scatter([1:numberOfMet]+offsetScatter,metaboliteConcentrationsNormalized, markerScatter, 'MarkerEdgeColor', markerColor, 'LineWidth', 1);
+%                         scatter([1:numberOfMet]+offsetScatter,metaboliteConcentrationsNormalized, markerScatter, 'MarkerEdgeColor', markerColor, 'LineWidth', 1);
                     else
                         % SNR matched
                         currentColor = colormapVect(round(NAA_SNR/NAA_SNR_global_ref/scalingFactorColor * numberOfColors),:);
-                        scatter([1:numberOfMet]+offsetScatter,metaboliteConcentrationsNormalized, markerScatter, 'MarkerEdgeColor',currentColor, 'LineWidth', 2);
+%                         scatter([1:numberOfMet]+offsetScatter,metaboliteConcentrationsNormalized, markerScatter, 'MarkerEdgeColor',currentColor, 'LineWidth', 2);
                     end
                     currentNans = isnan(metaboliteConcentrationsNormalized);
                     nansIterator = nansIterator + currentNans;
-                    meanPercentualChange = meanPercentualChange + abs(metaboliteConcentrationsNormalized); 
+                    meanPercentualChange = meanPercentualChange + abs(metaboliteConcentrationsNormalized);
                     iterator = iterator + ~(currentNans);
                 end
             end
@@ -248,92 +435,35 @@ for indexSubj = 1:numberOfSubjects
         cb = colorbar('XTickLabel',num2str(round(xticksSNR)'), 'Direction','reverse');
         ylabel(cb,'SNR_{NAA(CH3)}');
         
-%         boxplot(metaboliteConcentrationsAll);
+        %         boxplot(metaboliteConcentrationsAll);
         xticks(1:numberOfMet);
         xticklabels(metabolitesLabels);
         xtickangle(45)
         ylim([-yLimValue,yLimValue]);
         xlim([0.5,17.5])
         ylabel('Concentration change c_{k,%} (%)')
-
+        
         mainMetMeanChange = meanPercentualChange(indecesMainMet);
         mainMetNaNs = nansIterator(indecesMainMet);
         mainMetIterator = iterator(indecesMainMet);
         
         title(SoftwareName)
-%         if fitLCModel
-%             title([SoftwareName  ... ' Subject: ', subjects{indexSubj}, ' TE ', num2str(TEs(indexTE)) ' ms'...
-%                 ' - mean change (main mets): ', num2str(mean(meanPercentualChange./iterator,'omitnan'),3) '%; '...
-%                 ' (', num2str(mean(mainMetMeanChange./mainMetIterator,'omitnan'),3) '%); '...
-%                 num2str(sum(nansIterator)), ' (', num2str(sum(mainMetNaNs)), ') NaNs'...
-%                 ]);
-%         else
-%             title([SoftwareName  ... ' Subject: ', subjects{indexSubj}, ' TE ', num2str(TEs(indexTE)) ' ms'...
-%                 ' - mean change (main mets): ', num2str(mean(meanPercentualChange./iterator,'omitnan'),3) '%; '...
-%                 ' (', num2str(mean(mainMetMeanChange./mainMetIterator,'omitnan'),3) '%); '...
-%                 num2str(sum(nansIterator)), ' (', num2str(sum(mainMetNaNs)), ') NaNs'...
-%                 ', FQN_{Ref}:' num2str(FQN_Ref/numberOfSubjects,3), ', FQN_{mean}:' num2str(meanFQN/max(iterator),3)...
-%                 ', FQN_{Ref}:' num2str(FQN_Ref2/numberOfSubjects,3), ', FQN_{mean}:' num2str(meanFQN2/max(iterator),3)...
-%                 ]);
-%         end
-    end    
-    
-end
-
-meanMetDeviation = mean(abs(metaboliteConcentrationsAllSubj), 'omitnan');
-stdMetDeviation  = std(abs(metaboliteConcentrationsAllSubj), 'omitnan');
-
-meanAllMetDeviation = mean(abs(metaboliteConcentrationsAllSubj(:)), 'omitnan');
-stdAllMetDeviation  = std(abs(metaboliteConcentrationsAllSubj(:)), 'omitnan');
-
-mainMetaboliteConcentrationsAllSubj = metaboliteConcentrationsAllSubj(:, indecesMainMet);
-meanMainMetDeviation = mean(abs(mainMetaboliteConcentrationsAllSubj(:)), 'omitnan');
-stdMainMetDeviation  = std(abs(mainMetaboliteConcentrationsAllSubj(:)), 'omitnan');
-
-metaboliteTable = cell(numberOfMet+3,2);
-metaboliteTable(2:numberOfMet+1,1) = metabolitesLabels;
-metaboliteTable{numberOfMet+2,1}   = 'Mean';
-metaboliteTable{numberOfMet+3,1}   = 'Mean Main Metabolites';
-
-plusMinusSign = char(177);
-metaboliteTable{1,2} = SoftwareName;
-
-for indexMet = 1:numberOfMet
-    metaboliteTable{indexMet+1,2}   = [num2str(meanMetDeviation(indexMet),'%.1f'),  plusMinusSign, num2str(stdMetDeviation(indexMet),'%.1f')];
-end
-
-metaboliteTable{numberOfMet+2,2}   = [num2str(meanAllMetDeviation,'%.1f'),  plusMinusSign, num2str(stdAllMetDeviation,'%.1f')];
-metaboliteTable{numberOfMet+3,2}   = [num2str(meanMainMetDeviation,'%.1f'),  plusMinusSign, num2str(stdMainMetDeviation,'%.1f')];
-
-xlswrite([pathBaseExportFiles, 'InVivoResults' SoftwareName, '.xlsx'], metaboliteTable)
-% 
-% mean(cell2mat(NAA_SNR_all(:,1)))
-% std(cell2mat(NAA_SNR_all(:,1)))
-% mean(cell2mat(NAA_SNR_all(:,2)))
-% mean(cell2mat(NAA_SNR_all(:,3)))
-% mean(cell2mat(NAA_SNR_all(:,4)))
-% mean(cell2mat(NAA_SNR_all(:,5)))
-% std(cell2mat(NAA_SNR_all(:,5)))
-
-end
-
-function metaboliteConcentrations = matchFittedMetabolites(fitLCModel, currentConcentration, metabolitesNames,  proFitIteration, activeMetabolites)
-metaboliteConcentrations = zeros(size(metabolitesNames));
-
-if fitLCModel
-    activeMetabolites = currentConcentration(1,:);
-    currentConcentration = currentConcentration(2,:);
-else
-    activeMetabolites = activeMetabolites{proFitIteration};
-    currentConcentration = currentConcentration{proFitIteration};
-end
-for indexMet = 1 : length(metabolitesNames)
-    indexMetFit = find(strcmp(activeMetabolites,metabolitesNames(indexMet)));
-    if fitLCModel
-        metaboliteConcentrations(indexMet) = currentConcentration{indexMetFit};
-    else
-        metaboliteConcentrations(indexMet) = currentConcentration(indexMetFit);
+        %         if fitLCModel
+        %             title([SoftwareName  ... ' Subject: ', subjects{indexSubj}, ' TE ', num2str(TEs(indexTE)) ' ms'...
+        %                 ' - mean change (main mets): ', num2str(mean(meanPercentualChange./iterator,'omitnan'),3) '%; '...
+        %                 ' (', num2str(mean(mainMetMeanChange./mainMetIterator,'omitnan'),3) '%); '...
+        %                 num2str(sum(nansIterator)), ' (', num2str(sum(mainMetNaNs)), ') NaNs'...
+        %                 ]);
+        %         else
+        %             title([SoftwareName  ... ' Subject: ', subjects{indexSubj}, ' TE ', num2str(TEs(indexTE)) ' ms'...
+        %                 ' - mean change (main mets): ', num2str(mean(meanPercentualChange./iterator,'omitnan'),3) '%; '...
+        %                 ' (', num2str(mean(mainMetMeanChange./mainMetIterator,'omitnan'),3) '%); '...
+        %                 num2str(sum(nansIterator)), ' (', num2str(sum(mainMetNaNs)), ') NaNs'...
+        %                 ', FQN_{Ref}:' num2str(FQN_Ref/numberOfSubjects,3), ', FQN_{mean}:' num2str(meanFQN/max(iterator),3)...
+        %                 ', FQN_{Ref}:' num2str(FQN_Ref2/numberOfSubjects,3), ', FQN_{mean}:' num2str(meanFQN2/max(iterator),3)...
+        %                 ]);
+        %         end
     end
+    
 end
-%     metaboliteConcentrations(1) = metaboliteConcentrations(1) / 1e6; % adjust the MMB to be within range
 end
\ No newline at end of file