Skip to content
Snippets Groups Projects
Commit 02559a6c authored by Tamas Borbath's avatar Tamas Borbath
Browse files

Changed a lot of things in plot_all_test_data_profit

parent e401d52a
No related branches found
No related tags found
No related merge requests found
Hide whitespace changes
Inline Side-by-side
createTestData/plot_all_test_data_profit.m
+ 246
− 116
View file @ 02559a6c
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
0% or .
You are about to add 0 people to the discussion. Proceed with caution.
Finish editing this message first!
Please register or to comment