diff --git a/createTestData/plot_all_test_data_profit.m b/createTestData/plot_all_test_data_profit.m
index 350d7c6d2db2d8425abf8b3fc90ae68cd5f8bc71..ac80b7430f4fcc8c610c89e8c1aab8eca12dbbc1 100644
--- a/createTestData/plot_all_test_data_profit.m
+++ b/createTestData/plot_all_test_data_profit.m
@@ -1,6 +1,5 @@
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