diff --git a/DF_processing/calculateT2ExchangeCorrected.m b/DF_processing/calculateT2ExchangeCorrected.m
index 784e75bf0063ca6df95c5d34316eea86791171c9..4c5e4390e65450bc471a072ad85a6e463280f4e2 100644
--- a/DF_processing/calculateT2ExchangeCorrected.m
+++ b/DF_processing/calculateT2ExchangeCorrected.m
@@ -4,7 +4,7 @@ pathName = 'DF data path';
sampleCriteria = {'Output'};
[localFilePathBase] = pathToDataFolder(pathName, sampleCriteria);
-localFilePath = [localFilePathBase 'Output\'];
+localFilePath = [localFilePathBase 'Output\FWHMBA Results 7.5e-3\'];
load([localFilePath 'meanT2s.mat'], 'acceptableMeanT2s', 'acceptableStdT2s', 'metaboliteNamesDisplay');
% exchangeTimes in s-1 from Fichtner 2017 Occipital ROI.
diff --git a/DF_processing/doFittingAndT2Calculations_DF.m b/DF_processing/doFittingAndT2Calculations_DF.m
index a58b3a8acb7ff7fa6352be083294db1baa218a85..c7c4941d34d99bbb5e7634512d4adb9200becf9e 100644
--- a/DF_processing/doFittingAndT2Calculations_DF.m
+++ b/DF_processing/doFittingAndT2Calculations_DF.m
@@ -16,7 +16,7 @@ pH_default_Name = '_pH_XXX';
defaultLCModelUser = 'tborbath';
if fitAllSubjects
- controlFilesBase = 'fitsettings_Subject_XXXX_';
+ controlFilesBase = 'fitsettings_Subject_newNAA_XXXX_';
controlFilesBaseTE = strcat(controlFilesBase, 'TE');
controlFilesBaseSuffix = '_df_withUF_chosen_pH_XXX.control';
outputFileNameBase = strcat(defaultSubject, pH_default_Name, '_TE');
@@ -31,7 +31,7 @@ end
if fitAllSubjects
%pH_Values per subject
- [~, ~, pH_table] = xlsread([localFilePathBase, 'Output/pH_sweep_hCs_shift_fixed_all_TE/pH_Results_Subjects.xlsx']);
+ [~, ~, pH_table] = xlsread([localFilePathBase, 'Output/pH_sweep_final_settings/pH_Results_Subjects.xlsx']);
index_pH_value = 8;
if pH_table{1,index_pH_value}~=40
error('I thought you want to use the pH value of the TE 40 for fitting');
diff --git a/DF_processing/doFittingAndT2Calculations_DF_pH.m b/DF_processing/doFittingAndT2Calculations_DF_pH.m
index 4928f86a4e38c4604b54bf2bfd052036ca9d461c..6abd34ed254c486cc7cba48ef017e2a688083e78 100644
--- a/DF_processing/doFittingAndT2Calculations_DF_pH.m
+++ b/DF_processing/doFittingAndT2Calculations_DF_pH.m
@@ -8,7 +8,7 @@ fitAllSubjects = true;
orderTEs = {'24' '32' '40' '52' '60'};
% orderTEs = {'40'};
subjects = {'1658';'1717';'2017';'3373';'3490';'5771';'6249';'6971'; '7338'; '7782';'9810'};
-% subjects = {'7338'; '7782';'9810';'1658';};
+% subjects = {'5771'; '9810';};
pH_values = [6.9 6.94 6.98 7.00:0.01:7.15]';
% pH_values = [7.05]';
diff --git a/DF_processing/evaluateFWHMT2Fits.m b/DF_processing/evaluateFWHMT2Fits.m
new file mode 100644
index 0000000000000000000000000000000000000000..ac7c57096fc91706ef9ad035e532b135231fffcb
--- /dev/null
+++ b/DF_processing/evaluateFWHMT2Fits.m
@@ -0,0 +1,268 @@
+function [figureIds, sortedIndeces] = evaluateFWHMT2Fits(downField_MM_Met, offsetPlot, figureIds, sortedIndeces)
+
+if ~exist('downField_MM_Met','var')
+ downField_MM_Met = 'DF';
+end
+
+if ~exist('offsetPlot','var')
+ offsetPlot = 0;
+end
+if ~exist('figureIds','var')
+ figureIds = {};
+end
+
+useTotalNAA = false;
+doMetaboliteFWHMs = false;
+
+if offsetPlot <= 0
+ plotColors = {[0 0 1], [1 0 0]};
+ plotColors2 = {[0.0 0.4 0.0], [1 0.5 0.3]};
+ plotColors2 = {[0.0 0.4 0.0], [0 0 0]};
+% plotColors2 = {[0.3 0.3 0.1], [0.2 0.5 0.05]};
+else
+ plotColors = {[0.0 0.7 0.9], [1 0 1]};
+ plotColors2 = {[0.1 0.9 0.1], [0.9 0.6 0]};
+ plotColors2 = {[0.1 0.9 0.1], [0.5 0.5 0.5]};
+end
+
+usePpm = false;
+
+if isempty(figureIds)
+ emptyFigureIds = true;
+else
+ emptyFigureIds = false;
+end
+
+pathNameMM = 'DF data path';
+outputFolder = 'Output\';
+
+sampleCriteriaMM = {outputFolder};
+data_path = pathToDataFolder(pathNameMM, sampleCriteriaMM);
+
+load([data_path outputFolder 'tableT2sSubjects.mat'],'tableT2sSubjects')
+load([data_path outputFolder 'tableConcentrationsSubjects.mat'],'tableConcentrationsSubjects')
+
+doFWHMevalutation = true;
+if doFWHMevalutation
+ load([data_path outputFolder 'tableFWHMSubjects.mat'],'tableFWHMSubjects')
+ load([data_path outputFolder 'tableFWHMSubjects.mat'],'orderMetFWHMSubjects')
+end
+
+
+metaboliteNameOrder = {'Cr-CH3' 'Cr-CH2' 'NAA-ace' 'tCho_PE'};
+metaboliteNameOrderConc = {'Cr' 'Cr_CH2' 'NAA_ac' 'tCho_P'};
+metaboliteNameOrderFWHM = metaboliteNameOrder;
+metaboliteNamesDisplay = {'tCr(CH3)';'tCr(CH2)';'NAA(CH3)';'tCho+';};
+subjects = {'1658';'1706';'1717';'2017';'3373';'3490';'5771';'6249';'6971';'7338';'7782';'9810'};
+yAxisLim_FWHM = [-3 28];
+yAxisLim_Res = [-5 5];
+
+numberOfMet = length(metaboliteNameOrder);
+TEs = [24 32 40 52 60];
+numberOfTEs = 5;
+scanFrequency = 399.719;
+numOfSubjects = length(tableT2sSubjects);
+T2s = cell(numOfSubjects,numberOfMet);
+R2s = cell(numOfSubjects,numberOfMet);
+concentrations = cell(numOfSubjects, numberOfMet, numberOfTEs);
+for indexSubject = 1:numOfSubjects
+ T2times = tableT2sSubjects{indexSubject}(2,2:end);
+ R2times = tableT2sSubjects{indexSubject}(3,2:end);
+ concentrationsSubject = tableConcentrationsSubjects{indexSubject};
+ for indexMetabolite = 1:numberOfMet
+ index = find(strcmp(metaboliteNameOrder(indexMetabolite), tableT2sSubjects{indexSubject}(1,2:end)));
+ T2s(indexSubject,indexMetabolite) = T2times(index);
+ R2s(indexSubject,indexMetabolite) = R2times(index);
+ indexConc = find(strcmp(metaboliteNameOrderConc(indexMetabolite),concentrationsSubject(1,:)));
+ concentrations(indexSubject, indexMetabolite,:) = concentrationsSubject(2:6,indexConc);
+ end
+end
+
+concentrations = cell2mat(concentrations);
+T2sNumeric = str2double(T2s);
+R2sNumeric = str2double(R2s);
+nonNegT2s = T2sNumeric;
+nonNegT2s(nonNegT2s<0) = NaN;
+reshape(nonNegT2s,numberOfMet, numOfSubjects);
+
+acceptableT2s = nonNegT2s;
+acceptableR2s = R2sNumeric;
+
+acceptableT2s(R2sNumeric<=0.51) = NaN;
+acceptableR2s(R2sNumeric<=0.51) = NaN;
+
+reshape(acceptableT2s,numberOfMet, numOfSubjects);
+acceptableMeanT2s = mean(acceptableT2s,1,'omitNaN');
+acceptableStdT2s = std(acceptableT2s,1,'omitNaN');
+acceptableMeanR2s = mean(acceptableR2s,1,'omitNaN');
+acceptableStdR2s = std(acceptableR2s,1,'omitNaN');
+
+
+
+plusMinusSign = [' ' char(177) ' '];
+tableT2Summarized = cell(numberOfMet+1,4);
+tableT2Summarized(2:end,1) = metaboliteNamesDisplay;
+tableT2Summarized(1,3) = {'Std'};
+tableT2Summarized(1,4) = {['T2' plusMinusSign 'Std']};
+tableT2Summarized(1,5) = {['R2' plusMinusSign 'Std']};
+tableT2Summarized(2:end,2) = cellstr(num2str(acceptableMeanT2s','%.2f'));
+tableT2Summarized(2:end,3) = cellstr(num2str(acceptableStdT2s','%.2f'));
+tableT2Summarized(1,2) = {'T2 Summed'};
+tableT2Summarized(1,3) = {['T2' plusMinusSign 'Std']};
+tableT2Summarized(1,4) = {['R2' plusMinusSign 'Std']};
+for index=1:numberOfMet
+ tableT2Summarized{index+1,4} = [num2str(acceptableMeanT2s(index), '%.2f') plusMinusSign num2str(acceptableStdT2s(index), '%.2f')];
+ tableT2Summarized{index+1,5} = [num2str(acceptableMeanR2s(index), '%.2f') plusMinusSign num2str(acceptableStdR2s(index), '%.2f')];
+ tableT2Summarized{index+1,3} = [num2str(acceptableMeanT2s(index), '%.1f') plusMinusSign num2str(acceptableStdT2s(index), '%.1f')];
+ tableT2Summarized{index+1,4} = [num2str(acceptableMeanR2s(index), '%.2f') plusMinusSign num2str(acceptableStdR2s(index), '%.2f')];
+end
+
+save([data_path , outputFolder, 'meanT2s_met.mat'],'acceptableMeanT2s', 'acceptableStdT2s', 'metaboliteNamesDisplay');
+exportFileXlsx = [data_path , outputFolder, 'T2_Results_Mean_std_met.xlsx'];
+xlswrite(exportFileXlsx, tableT2Summarized, 1, 'A1');
+
+%% plot the T2 Box plots
+if emptyFigureIds
+ figureIds{1} = figure;
+else
+ figure(figureIds{1});
+end
+
+positionsTicks = [2.2:1.5:1.5*numberOfMet+1.5];
+positions1 = positionsTicks + offsetPlot;
+boxPlotT2 = boxplot(acceptableT2s, metaboliteNamesDisplay,'colors',plotColors{1},'symbol','+','positions',positions1,'width',0.18);
+ylabel('T_2 (ms)')
+axT2 = get(figureIds{1},'CurrentAxes');
+axT2.XAxis.TickLength = [0,0];
+axT2.YColor = 'k';
+
+set(boxPlotT2(:,:),'linewidth',1);
+
+set(gca, 'YLim', [-5,200]);
+set(gca, 'XLim', [positionsTicks(1)-abs(offsetPlot)-0.8 positionsTicks(end)+abs(offsetPlot)+0.8]);
+
+set(gca, 'YGrid', 'on');
+set(gca, 'XTickMode', 'manual');
+set(gca, 'XTick', positionsTicks);
+set(gca, 'XTickLabelRotation', 90.0);
+set(gca, 'FontSize', 16);
+% title('T_2^\rho Relaxation Times');
+title('T_2 Relaxation Times');
+
+%% FWHM
+fwhmReshaped = zeros(size(tableFWHMSubjects,1)*size(tableFWHMSubjects,2), numberOfMet);
+for indexMetabolite = 1 :numberOfMet
+
+ indexTable = find(strcmp(orderMetFWHMSubjects(:), metaboliteNameOrderFWHM(indexMetabolite)));
+
+ fwhms = tableFWHMSubjects(:,:,indexTable);
+ fwhms(fwhms>100)= NaN;
+ fwhmReshaped(:,indexMetabolite) = fwhms(:);
+end
+
+%% T2 corrected FWHM
+for i = 1:size(fwhmReshaped,1)
+ fwhmReshaped3(i,:) = fwhmReshaped(i,:) - 1./(pi*acceptableMeanT2s*1e-3);
+end
+
+fwhmReshaped3 = fwhmReshaped3 - fwhmReshaped3(:,1);
+
+T2RelaxationLinewidth = 1./(pi*acceptableT2s*1e-3);
+
+%% plotting of FWHM
+if emptyFigureIds
+ figureIds{2} = plotFWHMs(fwhmReshaped, [], metaboliteNamesDisplay, numberOfMet, scanFrequency, plotColors, '\Delta\nu_{1/2}', usePpm, yAxisLim_FWHM, offsetPlot);
+ figureIds{3} = plotFWHMs(fwhmReshaped3, [], metaboliteNamesDisplay, numberOfMet, scanFrequency, plotColors2, '\Delta\nu_{residual}', usePpm, yAxisLim_Res, offsetPlot);
+else
+ figureIds{2} = plotFWHMs(fwhmReshaped, [], metaboliteNamesDisplay, numberOfMet, scanFrequency, plotColors, '\Delta \nu_{1/2}', usePpm, yAxisLim_FWHM, offsetPlot, figureIds{2});
+ figureIds{3} = plotFWHMs(fwhmReshaped3, [], metaboliteNamesDisplay, numberOfMet, scanFrequency, plotColors2, '\Delta\nu_{residual}', usePpm, yAxisLim_Res, offsetPlot, figureIds{3});
+end
+
+%%
+if emptyFigureIds
+ figureIds{4} = plotFWHMs(T2RelaxationLinewidth, [], metaboliteNamesDisplay, numberOfMet, scanFrequency, plotColors2, '\Delta\nu_{1/2} vs. (\pi T_2^{app})^{-1}', usePpm, yAxisLim_FWHM, offsetPlot);
+else
+ figureIds{4} = plotFWHMs(T2RelaxationLinewidth, [], metaboliteNamesDisplay, numberOfMet, scanFrequency, plotColors2, '\Delta\nu_{1/2} vs. (\pi T_2^{app})^{-1}', usePpm, yAxisLim_FWHM, offsetPlot, figureIds{4});
+end
+figureIds{4} = plotFWHMs(fwhmReshaped, [], metaboliteNamesDisplay, numberOfMet, scanFrequency, plotColors, '\Delta\nu_{1/2} vs. (\pi T_2^{app})^{-1}', usePpm, yAxisLim_FWHM, offsetPlot, figureIds{4});
+
+
+tableFWHMSummarized = cell(numberOfMet+1,4);
+tableFWHMSummarized(2:end,1) = metaboliteNamesDisplay;
+tableFWHMSummarized(1,2) = {['FWHM' plusMinusSign 'Std']};
+if usePpm
+ meanFwhmReshaped = mean(T2RelaxationLinewidth./scanFrequency, 'omitnan');
+ stdFwhmReshaped = std(T2RelaxationLinewidth./scanFrequency, 'omitnan');
+ writePrecision = '%.3f';
+else
+ meanFwhmReshaped = mean(T2RelaxationLinewidth, 'omitnan');
+ stdFwhmReshaped = std(T2RelaxationLinewidth, 'omitnan');
+ writePrecision = '%.2f';
+ writePrecision = '%.1f';
+end
+for index=1:numberOfMet
+ tableFWHMSummarized{index+1,2} = [num2str(meanFwhmReshaped(index), writePrecision) plusMinusSign num2str(stdFwhmReshaped(index), writePrecision)];
+end
+exportFileXlsx = [data_path ,'Output\FWHM_Results_Mean_std_met.xlsx'];
+xlswrite(exportFileXlsx, tableFWHMSummarized, 1, 'A1');
+
+
+end
+
+function [figId] = plotFWHMs(fwhmReshaped, FWHMSummedNumeric, metaboliteNames, numberOfMet, scanFrequency, ...
+ plotColors, titleName, usePpm, yAxisLim, offsetPlot, figId)
+%% plot the FWHM Box plots
+if ~exist('figId', 'var')
+ figId = figure;
+else
+ figure(figId);
+ hold on
+end
+positionsTicks = 2.2:1.5:1.5*numberOfMet+1.5;
+positions = positionsTicks + offsetPlot;
+fwhm_plot_limit = 150;
+
+if (usePpm)
+ fwhmReshapedPpm = fwhmReshaped ./ scanFrequency;
+ fwhm_plot_limit_ppm = fwhm_plot_limit ./ scanFrequency;
+ %set yyaxis left active, hence both
+ yyaxis left
+end
+
+boxPlotFWHM = boxplot(fwhmReshaped, metaboliteNames,'colors',plotColors{1},'symbol','+','positions',positions);
+
+if (usePpm)
+ yyaxis right
+ boxPlotFWHMPpm = boxplot(fwhmReshapedPpm, metaboliteNames,'colors',plotColors{1},'symbol','+','positions',positions);
+ set(gca,'YColor','k');
+ yyaxis left
+end
+
+ylabel('\Delta\nu (Hz)')
+if usePpm
+ yyaxis right
+ ylabel('\Delta\nu (ppm)', 'Color', 'k')
+ yyaxis left
+end
+
+ax = get(figId,'CurrentAxes');
+ax.XAxis.TickLength = [0,0];
+ax.YColor = 'k';
+
+set(boxPlotFWHM(:,:),'linewidth',1);
+set(gca, 'YGrid', 'on');
+set(gca, 'XTickMode', 'manual');
+set(gca, 'XTick', positionsTicks);
+set(gca, 'XLim', [positionsTicks(1)-abs(offsetPlot)-0.8 positionsTicks(end)+abs(offsetPlot)+0.8]);
+set(gca, 'XTickLabelRotation', 90.0);
+set(gca, 'FontSize', 16);
+title(titleName);
+
+if usePpm
+ set(gca, 'YLim', [yAxisLim(1),yAxisLim(2)]);
+ yyaxis right
+ set(gca, 'YLim', [yAxisLim(1)/scanFrequency,yAxisLim(2)./scanFrequency]);
+else
+ set(gca, 'YLim', [0,yAxisLim(2)]);
+end
+end
diff --git a/DF_processing/evaluate_pH_fit.m b/DF_processing/evaluate_pH_fit.m
index c1c91dec6b65243448a3be6e12a05ce35847b6e2..debc067b228b5a3b368ae7f2f9ed9af7ae58d90e 100644
--- a/DF_processing/evaluate_pH_fit.m
+++ b/DF_processing/evaluate_pH_fit.m
@@ -3,16 +3,18 @@ use_hist = false;
if use_hist
outputFolder = 'Output\pH_sweep_hCs_hist_shift_fixed_all_TE\';
else
- outputFolder = 'Output\pH_sweep\';
+ outputFolder = 'Output\pH_sweep_final_settings\';
+% outputFolder = 'Output\pH_sweep_hCs_shift_fixed\';
end
pathName = 'DF data path';
sampleCriteria = {outputFolder};
data_path = pathToDataFolder(pathName, sampleCriteria);
-pH_values = [6.9:0.01:7.1]';
+pH_values = [6.9:0.01:7.15]';
doSubjects = true;
if doSubjects
subjects = {'1658';'1717';'2017';'3373';'3490';'5771';'6249';'6971'; '7338'; '7782';'9810'};
+% subjects = {'3373'};
else
subjects = {'Summed'};
end
diff --git a/DF_processing/lineBroadeningExchangingPeaks.m b/DF_processing/lineBroadeningExchangingPeaks.m
new file mode 100644
index 0000000000000000000000000000000000000000..7b3cee705daa589155ab1cbf5ceab7b95b884a2f
--- /dev/null
+++ b/DF_processing/lineBroadeningExchangingPeaks.m
@@ -0,0 +1,138 @@
+function lineBroadeningExchangingPeaks()
+
+%sample data and the equations from "Spin Dynamics - Malcolm Levitt
+% page 520 chapter 19.5.2 and Lorentzian lineshape: pag 97 Chapter 5.8.2
+gamma = [-3000:0.1:3000]*2*pi;
+gammaA = -1000*2*pi;
+gammaB = 1000*2*pi;
+lambda=0;
+
+plotPpm = false;
+[S, figId] = calculateLineShape(gamma, gammaA, gammaB, 0.5*1e3, lambda, plotPpm, []);
+[S, figId] = calculateLineShape(gamma, gammaA, gammaB, 1.0*1e3, lambda, plotPpm, [], figId);
+[S, figId] = calculateLineShape(gamma, gammaA, gammaB, 2.5*1e3, lambda, plotPpm, [], figId);
+[S, figId] = calculateLineShape(gamma, gammaA, gammaB, 3.5*1e3, lambda, plotPpm, [], figId);
+[S, figId] = calculateLineShape(gamma, gammaA, gammaB, 6.3*1e3, lambda, plotPpm, [], figId);
+legend('k=0.5x10^3s^{-1}','k=1.0x10^3s^{-1}','k=2.5x10^3s^{-1}','k=3.5x10^3s^{-1}','k=6.3x10^3s^{-1}')
+
+% -------------------------------------------------------------
+water = 0.0; %ppm
+ppmRange = [-10:0.0001:10];
+
+omega = 42.577 * 9.41 * (5.75-4.7);
+scanfrequency = 399*2*pi;
+% scanfrequency = 42.57747 * 2.8*2*pi;%3T
+gamma = ppmRange * scanfrequency;
+gammaWater = water * scanfrequency;
+lambda = 0;
+
+%values from Haris 2012, NMR Biomed
+PCr_1 = 2.5; % ppm
+PCr_2 = 1.8; % ppm
+Cr = 1.8; % ppm
+k_PCr_1 = 140;%s-1
+k_PCr_2 = 120;%s-1
+k_Cr = 950;%s-1
+
+gammaPCr_1 = PCr_1 * scanfrequency;
+gammaPCr_2 = PCr_2 * scanfrequency;
+gammaCr = Cr * scanfrequency;
+plotPpm = true;
+[S, figId] = calculateLineShape(gamma, gammaWater, gammaPCr_1, k_PCr_1, lambda, plotPpm, ppmRange);
+[S, figId] = calculateLineShape(gamma, gammaWater, gammaPCr_2, k_PCr_2, lambda, plotPpm, ppmRange, figId);
+[S, figId] = calculateLineShape(gamma, gammaWater, gammaCr, k_Cr, lambda, plotPpm, ppmRange, figId);
+legend('PCr 2.5ppm k=140s^{-1}', 'PCr 1.8ppm k=120s^{-1}', 'Cr 1.8ppm k=950s^{-1}');
+
+Urea = 5.75-4.7; % ppm
+k_Urea = 7;% k= 6.76 Hz Occ lobe GM rich; k = 8.00 Hz Parietal WM [Fichtner 9.4T, MRM 2017]
+
+gammaUrea = Urea * scanfrequency;
+plotPpm = true;
+[S, figId] = calculateLineShape(gamma, gammaWater, gammaUrea, 0.1, lambda, plotPpm, ppmRange+4.7);
+[S, figId] = calculateLineShape(gamma, gammaWater, gammaUrea, k_Urea, lambda, plotPpm, ppmRange+4.7,figId);
+[S, figId] = calculateLineShape(gamma, gammaWater, gammaUrea, 13, lambda, plotPpm, ppmRange+4.7,figId);
+legend('Urea 5.75ppm k=0.1s^{-1}','Urea 5.75ppm k=7s^{-1}','Urea 5.75ppm k=13s^{-1}');
+if plotPpm
+ xlim([5.7 5.8])
+else
+ xlim([410 430])
+end
+ylim([-0.001 0.1])
+
+%values from [Fichtner 9.4T, MRM 2017]
+DF58 = 5.8-4.7; % ppm
+DF68 = 6.8-4.7; % ppm
+DF82 = 8.2-4.7; % ppm
+DF83 = 8.3-4.7; % ppm
+DF85 = 8.5-4.7; % ppm
+NAA = 7.82-4.7; % ppm
+k_DF58 = 6.76;% k= 6.76 Hz Occ lobe GM rich; k = 8.00 Hz Parietal WM
+k_DF68 = 2.34;% k= 2.34 Hz Occ lobe GM rich; k = 2.42 Hz Parietal WM
+k_DF82 = 9.32;% k= 9.32 Hz Occ lobe GM rich; k = 10.6 Hz Parietal WM
+k_DF83 = 13.8;% k= 13.8 Hz Occ lobe GM rich; k = 13.4 Hz Parietal WM
+k_DF85 = 3.31;% k= 3.31 Hz Occ lobe GM rich; k = 4.05 Hz Parietal WM
+k_NAA = 0.74;% k= 0.74 Hz Occ lobe GM rich; k = 0.92 Hz Parietal WM
+
+gammaDF58 = DF58 * scanfrequency;
+gammaDF68 = DF68 * scanfrequency;
+gammaDF82 = DF82 * scanfrequency;
+gammaDF83 = DF83 * scanfrequency;
+gammaDF85 = DF85 * scanfrequency;
+gammaNAA = NAA * scanfrequency;
+plotPpm = true;
+[S, figId] = calculateLineShape(gamma, gammaWater, gammaDF58, k_DF58, lambda, plotPpm, ppmRange+4.7);
+[S, figId] = calculateLineShape(gamma, gammaWater, gammaDF68, k_DF68, lambda, plotPpm, ppmRange+4.7,figId);
+[S, figId] = calculateLineShape(gamma, gammaWater, gammaDF82, k_DF82, lambda, plotPpm, ppmRange+4.7,figId);
+[S, figId] = calculateLineShape(gamma, gammaWater, gammaDF83, k_DF83, lambda, plotPpm, ppmRange+4.7,figId);
+[S, figId] = calculateLineShape(gamma, gammaWater, gammaDF85, k_DF85, lambda, plotPpm, ppmRange+4.7,figId);
+[S, figId] = calculateLineShape(gamma, gammaWater, gammaNAA, k_NAA, lambda, plotPpm, ppmRange+4.7,figId);
+legend('DF_{5.75} k=6.76s^{-1}','DF_{6.80} k=2.346s^{-1}','DF_{8.20} k=9.32s^{-1}','DF_{8.30} k=13.8s^{-1}','DF_{8.50} k=3.31s^{-1}', 'NAA k=0.74s^{-1}');
+if plotPpm
+ xlim([5.7 8.6])
+ xlim([4.6 8.6])
+else
+ xlim([400 1600])
+end
+ylim([-0.001 0.25])
+set(gca,'xdir','reverse')
+xlabel('\delta (ppm)')
+ylabel('Signal (arb. u.)')
+
+% results of FWHM
+%DF58 = 2.17 Hz
+%DF68 = 0.7581 Hz
+%DF82 = 2.95 Hz
+%DF83 = 4.389 Hz
+%DF85 = 1.0374 Hz
+%NAA = 0.2394 Hz
+end
+
+function [S, figId] = calculateLineShape(gamma, gammaA, gammaB, k, lambda, plotPpm, ppmRange, figId)
+gammaDif = gammaB-gammaA;
+R = sqrt(abs(k^2-(gammaDif/2)^2));
+gammaM = 0.5*(gammaA+gammaB);
+
+% signal_L = 1 ./ ((lambda+k) + 1i*(gamma-(gammaM+R)));
+% signal_R = 1 ./ ((lambda+k) + 1i*(gamma-(gammaM-R)));
+%
+% S = 0.5 .*(1-1i*k/R) .* signal_L+...
+% 0.5 .*(1+1i*k/R) .* signal_R;
+S = 0.5 .*(1-1i*k/R) .* lorentz(gamma, gammaM+R, lambda+k)+...
+ 0.5 .*(1+1i*k/R) .* lorentz(gamma, gammaM-R, lambda+k);
+
+if exist('figId', 'var')
+ figure(figId)
+else
+ figId = figure;
+ hold on
+end
+if plotPpm
+ plot(ppmRange, real(S))
+else
+ plot(gamma/(2*pi), real(S))
+end
+end
+
+function signal = lorentz(gamma,gammaL, lambda)
+ signal = 1 ./ (lambda + 1i*(gamma-gammaL));
+end
\ No newline at end of file
diff --git a/DF_processing/plot_mean_std_of_spectra_DF.m b/DF_processing/plot_mean_std_of_spectra_DF.m
index 8bd586b63887eb919cd12710ebd325ee6d11621f..f999ab505dae381d576308e0222962e19502fc19 100644
--- a/DF_processing/plot_mean_std_of_spectra_DF.m
+++ b/DF_processing/plot_mean_std_of_spectra_DF.m
@@ -10,6 +10,7 @@ TEs = [24; 32; 40; 52; 60];
colors = {[0 0.7 0]; [1 0 0]; [0 0 1]; [0 0 0]; [0 0.5 0.5];};
numberOfTEs = length(TEs);
offsetStep = 2.7e-5;
+offsetStep = 1.e-5;
offSetBase = offsetStep * (numberOfTEs + 1);
for indexTE = 1:numberOfTEs
@@ -99,14 +100,14 @@ end
%%
figure(1)
-stdAlpha = 0.4;
-hold on
-h = area(ppmScale,[(meanSpectrum - stdSpectrum) + offset (stdSpectrum * 2)]);
-h(1).FaceColor = 'none';
-h(2).FaceColor = colorSpectrum;
-h(2).FaceAlpha = stdAlpha;
-h(1).EdgeColor = 'none';
-h(2).EdgeColor = 'none';
+% stdAlpha = 0.4;
+% hold on
+% h = area(ppmScale,[(meanSpectrum - stdSpectrum) + offset (stdSpectrum * 2)]);
+% h(1).FaceColor = 'none';
+% h(2).FaceColor = colorSpectrum;
+% h(2).FaceAlpha = stdAlpha;
+% h(1).EdgeColor = 'none';
+% h(2).EdgeColor = 'none';
hold on
pSpectrum = plot(ppmScale,meanSpectrum + offset, 'LineWidth',2, 'Color', colorSpectrum);
@@ -114,7 +115,8 @@ xlim([5.5 9.5]);
set(gca,'xDir','reverse')
set(gca,'LineWidth',1);
set(gca,'ytick',[])
-xlabel('[ppm]');
+xlabel('\delta (ppm)');
+ylabel('Signal (arb.u.)');
title('Spectra mean and standard deviation')
% title(['Spectra TE ' num2str(TE) ' ms'])
end
\ No newline at end of file
diff --git a/DF_processing/plot_pH_sweep.m b/DF_processing/plot_pH_sweep.m
index 1c3202b07e42022d087512e731fc2d73bfa1a6b4..e1c967e4d6ed70ebd4238e792904f926593cb5ea 100644
--- a/DF_processing/plot_pH_sweep.m
+++ b/DF_processing/plot_pH_sweep.m
@@ -9,14 +9,18 @@ data_path = pathToDataFolder(pathName, sampleCriteria);
filepath = [data_path outputFolder];
if use_hCs
+ figure;
+ subplot(1,2,1)
metaboliteName = 'Homocarnosine';
metaboliteAbbr = 'hCs';
else
+ hold on
+ subplot(1,2,2)
metaboliteName = 'Histidine';
metaboliteAbbr ='hist';
end
pH_values =6.91:0.04:7.15;
-figure;
+
hold on
for pH_value = pH_values
filename = [metaboliteAbbr '_imidazole_pH_' sprintf('%.2f', pH_value) '.RAW'];
@@ -29,13 +33,13 @@ end
% deltaChar = char(948);
% it doesn't take the ASCII character
-xlabel('[ppm]');
+xlabel('\delta (ppm)');
xlim([6.9 8.2])
set(gca,'xDir','reverse');
title([metaboliteName ' pH Dependence']);
set(gca,'LineWidth',1);
yticks([])
-ylabel('[arb. unit]')
+ylabel('(arb. unit)')
% set(gca,'ytick',[]);
set(gca,'fontsize',14);
set(gca,'FontWeight','bold');
diff --git a/DF_processing/ureaExchangeRateCalculation.m b/DF_processing/ureaExchangeRateCalculation.m
new file mode 100644
index 0000000000000000000000000000000000000000..dcc8226f6fd34ac227c8e72fad5229626aa7d0af
--- /dev/null
+++ b/DF_processing/ureaExchangeRateCalculation.m
@@ -0,0 +1,25 @@
+k_0 = 0;
+pKw = 13.617;
+k_a = 9.95*1e6; %l/mol*s
+k_b = 6.21*1e6; %l/mol*s
+R_1s = 1.9; %s-1
+E_Ab= 43.52; %kJ/mol
+HR = 55.84; %kJ/mol
+R = 8.314; %J/(mol K)
+pHs = [6.0:0.01:8.0];
+k_sw = zeros(length(pHs),1);
+for index=1:length(pHs)
+ pH =pHs(index);
+ k_sw(index) = k_b * 10^(pH-pKw)+k_a *10^(-pH) + k_0;
+end
+figure
+plot(pHs, k_sw)
+
+T = 310.15;
+temp1 = HR / (R*log(10)) * (1/298.15 - 1/T);
+temp2 = E_Ab / (R*log(10)) * (1/310.15-1/T);
+k_sw = k_b * 10^(pH-14+temp1 + temp2)
+
+1/R_1s
+
+pi^2*2.5*1e-3*63.5^2
\ No newline at end of file
diff --git a/MM_T1processing/plot_mean_std_of_spectra_MMT1.m b/MM_T1processing/plot_mean_std_of_spectra_MMT1.m
index 14fbe603c6d433b6e22e9b1584066c42a23c7f99..26d7983bffc3013bf3a9dbb2688e94104142e394 100644
--- a/MM_T1processing/plot_mean_std_of_spectra_MMT1.m
+++ b/MM_T1processing/plot_mean_std_of_spectra_MMT1.m
@@ -3,9 +3,11 @@ function plot_mean_std_of_spectra_MM
pathName = 'MM data path';
[path] = pathToDataFolder(pathName);
-fileNameBase = [path, 'Summed_spectra_TE'];
+fileNameBase = [path, 'Summed_spectra_'];
TEs = [24; 32; 40; 52; 60];
+TI1 = [];
+TI2 = [];
colors = {[0 0.7 0]; [1 0 0]; [0 0 1]; [0 0 0]; [0 0.5 0.5];};
numberOfTEs = length(TEs);
diff --git a/MM_T1processing/plot_mean_std_of_spectra_T1.m b/MM_T1processing/plot_mean_std_of_spectra_T1.m
new file mode 100644
index 0000000000000000000000000000000000000000..f0ad46b3608b789e19fd73309db157b347166e1c
--- /dev/null
+++ b/MM_T1processing/plot_mean_std_of_spectra_T1.m
@@ -0,0 +1,172 @@
+function plot_mean_std_of_spectra_MM
+
+downField_MM_Met = 'MM';
+switch downField_MM_Met
+ case 'DF'
+ pathName = 'DF data path';
+ TEs = [24; 24; 32; 40; 52; 60; ];
+ colors = {[0 0.7 0]; [0 0.7 0]; [0 0 0]; [0 0 1]; [1 0 0]; [0 0.5 0.5];};
+ offsetStep = 2.2e-5;
+ case 'MM'
+ pathName = 'MM T1 data path';
+ TEs = [1; 2; 3; 4; 5; 6; 7; 8; 9; 10; 11; ];
+ colors = {[76 187 23]/255; [76 187 23]/255; [76 187 23]/255; [76 187 23]/255; [76 187 23]/255; [1 121 111]/255; [75 0 130]/255; [75 0 130]/255; [75 0 130]/255; [75 0 130]/255; [75 0 130]/255;};
+ offsetStep = 7.0e-5;
+ case 'MM WM'
+ pathName = 'MM WM T1 data path';
+ TEs = [1; 2; 3; 4; 5; 6; 7; 8; 9; 10; 11; ];
+ colors = {[76 187 23]/255; [76 187 23]/255; [76 187 23]/255; [76 187 23]/255; [76 187 23]/255; [1 121 111]/255; [75 0 130]/255; [75 0 130]/255; [75 0 130]/255; [75 0 130]/255; [75 0 130]/255;};
+ offsetStep = 7.0e-5;
+ case 'Met'
+ pathName = 'DF data path';
+ TEs = [24; 32; 40; 52; 60; ];
+ colors = {[0 0.7 0]; [0 0 0]; [0 0 1]; [1 0 0]; [0 0.5 0.5];};
+ offsetStep = 2.3e-4;
+end
+
+[path] = pathToDataFolder(pathName);
+
+fileNameBase = [path, 'Summed_Averaged_TI1_'];
+
+
+numberOfTEs = length(TEs);
+
+offSetBase = offsetStep * (numberOfTEs + 7); %+7 for WM
+
+for indexTE = 1:numberOfTEs
+ fileName = [fileNameBase num2str(TEs(indexTE))];
+ offset = offSetBase - indexTE * offsetStep;
+ if (indexTE == 1) && (strcmp(downField_MM_Met,'DF'))
+ plotOneTE(fileName, TEs(indexTE), colors{indexTE}, offset+offsetStep/2, 'DF_up');
+ else
+ plotOneTE(fileName, TEs(indexTE), colors{indexTE}, offset, downField_MM_Met);
+ end
+end
+
+end
+
+function plotOneTE(fileName, TE, colorSpectrum, offset, downField_MM_Met)
+load([fileName '.mat'], 'summedSpectraTI')
+
+zeroPPM = 4.67;
+nTimepoints = size(summedSpectraTI.Data{1},summedSpectraTI.kx_dim);
+nAverages = size(summedSpectraTI.Data{1},summedSpectraTI.meas_dim);
+waterFreq = summedSpectraTI.Parameter.Headers.ScanFrequency * 1E-6;
+bandwidth = summedSpectraTI.Parameter.Headers.Bandwidth_Hz;
+frequencyRange = linspace(-bandwidth/2,bandwidth/2,nTimepoints);
+
+if strcmp(downField_MM_Met,'DF_up')
+ fidSpectra = summedSpectraTI.Data{1}(:,1,1,1,1,1,1,1,1,1,1,:) * 5;
+else
+ fidSpectra = summedSpectraTI.Data{1}(:,1,1,1,1,1,1,1,1,1,1,:) * 1;
+end
+
+fidWater = summedSpectraTI.Data{1}(:,1,1,1,1,1,1,1,2,1,1,:);
+spectra = squeeze(fftshift(fft(fidSpectra)));
+water = squeeze(fftshift(fft(fidWater)));
+meanSpectrum = mean(spectra,2);
+stdSpectrum = std(spectra,[],2);
+relativeStd = stdSpectrum ./ max(meanSpectrum) * 100;
+
+ppmVector = (frequencyRange)/waterFreq+zeroPPM;
+
+% figure(101)
+% plot(ppmVector,relativeStd)
+% xlim([0.5 4.2]);
+% set(gca,'xDir','reverse')
+
+
+%%
+scalingRange = (ppmVector < 1.8) & (ppmVector > 0);
+for indexAverage = 1:nAverages
+ [maxWater,indexMaxWater] = max(abs(real(water(:, indexAverage))));
+
+ [~, indexMaxWaterInRange] = max(abs(real((water(scalingRange, indexAverage)-mean(water(scalingRange, indexAverage))))));
+
+ [maxWaterInRange, ~] = max(real(water(scalingRange, indexAverage)));
+ minWaterInRange = min(real(water(scalingRange, indexAverage)));
+
+ maxSpectraInRange = max(real(spectra(scalingRange, indexAverage)));
+ minSpectraInRange = min(real(spectra(scalingRange, indexAverage)));
+
+ indexStart = find(scalingRange);
+ indexMaxWaterInRange = indexMaxWaterInRange + indexStart(1);
+ referenceLines = zeros(nTimepoints,1);
+ referenceLines(:) = -maxWaterInRange*2;
+ referenceLines(indexMaxWaterInRange:indexMaxWater + (indexMaxWater - indexMaxWaterInRange)) = maxWaterInRange*2;
+
+ plotOffset = maxSpectraInRange;
+% figWaterSpectra = figure(2);
+% hold on
+% plot(ppmScale, real(water(:,indexAverage)) - minWaterInRange + plotOffset,'b')
+% plotScale = (maxWaterInRange-minWaterInRange);
+% ylim([minSpectraInRange-(plotOffset*0.3) plotScale*1.2+plotOffset]);
+% hold on
+% pSpectra = plot(ppmScale, real(spectra(:,indexAverage)),'r');
+% hold on
+% % figure
+% plot(ppmScale, referenceLines, 'k--')
+% xlim([0 8.5]);
+% set(gca,'xDir','reverse')
+% set(gca,'LineWidth',1);
+% % set(gca,'ytick',[])
+% xlabel('[ppm]');
+% makedatatip(pSpectra,[indexMaxWaterInRange])
+%
+% print(['WaterSpectraComparisonPlots\' num2str(indexAverage) '_' fileName],'-dpng')
+% close(figWaterSpectra)
+end
+%%
+% figure
+% plot(ppmScale, real(spectra))
+
+% xlim([0.5 4.2]);
+% set(gca,'xDir','reverse')
+% set(gca,'LineWidth',1);
+% % set(gca,'ytick',[])
+% xlabel('[ppm]');
+% title(['Individual Spectra TE ' num2str(TE) ' ms'])
+
+%%
+figure(1)
+stdAlpha = 0.4;
+hold on
+if strcmp(downField_MM_Met,'DF_up')
+ indexDFCut = find(ppmVector > 8.6, 1, 'first');
+ ppmVector = ppmVector(indexDFCut:end);
+ meanSpectrum = meanSpectrum(indexDFCut:end);
+ stdSpectrum = stdSpectrum(indexDFCut:end);
+end
+
+h = area(ppmVector,[(meanSpectrum - stdSpectrum) + offset (stdSpectrum * 2)]);
+
+h(1).FaceColor = 'none';
+h(2).FaceColor = colorSpectrum;
+h(2).FaceAlpha = stdAlpha;
+h(1).EdgeColor = 'none';
+h(2).EdgeColor = 'none';
+hold on
+pSpectrum = plot(ppmVector,meanSpectrum + offset, 'LineWidth',2, 'Color', colorSpectrum);
+
+switch downField_MM_Met
+ case 'DF'
+ xlim([5.5 9.4]);
+ case 'DF_up'
+ xlim([5.5 9.4]);
+ case 'MM'
+ xlim([0.5 4.2]);
+% ylim([4.5e-6 4.7e-5]);
+ case 'MM WM'
+ xlim([0.5 4.2]);
+ %ylim([2e-6 1.3e-4]); %TODO: check why scaling is different, then MM
+ case 'Met'
+ xlim([0.5 4.2]);
+ ylim([7e-5 1.65e-3]);
+end
+set(gca,'xDir','reverse')
+set(gca,'LineWidth',1);
+set(gca,'ytick',[])
+xlabel('[ppm]');
+title('Spectra mean and standard deviation')
+% title(['Spectra TE ' num2str(TE) ' ms'])
+end
\ No newline at end of file
diff --git a/MM_T1processing/reconstruct_all_MMT1.m b/MM_T1processing/reconstruct_all_MMT1.m
index 3c679cc14b7e25594c4552e89ea11dbb27206525..969d64f796a833cc1b1a89739c5dec4f14c85162 100644
--- a/MM_T1processing/reconstruct_all_MMT1.m
+++ b/MM_T1processing/reconstruct_all_MMT1.m
@@ -1,19 +1,18 @@
function reconstruct_all_MM()
-pathName = 'MM T1 data path';
+pathName = 'MM WM T1 data path';
subjects = { ...
-% '1717' ...
-% '2016' ...
-% '9810' ...
-% '3490' ...
-% '2017' ...
- '7338'...
-% '1658'...
-% '2349'...
-% '7782'...
-% '3373'...
-% '2020'...
- };
+ '1717' ...
+ '2016' ...
+ '9810' ...
+ '3490' ...
+ '2017' ...
+ '7338'...
+ '1658'...
+ '2349'...
+ '2020'...
+ }; % '7782'...
+ % '3373'...
pathBase = pathToDataFolder(pathName, subjects);
diff --git a/MM_processing/plot_mean_std_of_spectra_MM.m b/MM_processing/plot_mean_std_of_spectra_MM.m
index f06457ca18d6b6413ad64b2b3b2002ac0b58f73f..bfbec1a23982461390aeb6dbe2f5c6ddf8061932 100644
--- a/MM_processing/plot_mean_std_of_spectra_MM.m
+++ b/MM_processing/plot_mean_std_of_spectra_MM.m
@@ -1,6 +1,6 @@
function plot_mean_std_of_spectra_MM
-downField_MM_Met = 'MM WM';
+downField_MM_Met = 'MM';
switch downField_MM_Met
case 'DF'
pathName = 'DF data path';
diff --git a/MM_processing/reconstruct_MM.m b/MM_processing/reconstruct_MM.m
index 2f7fd4d7dbc5c75d197079fbe175a20d9b880dd0..581135c80518b902a3735273e3c912eb1aea6d63 100644
--- a/MM_processing/reconstruct_MM.m
+++ b/MM_processing/reconstruct_MM.m
@@ -5,9 +5,9 @@ end
%%
a = MR_spectroS(fid_id,1);
%%
-trunc_ms = 250;
-truncPoint = floor( trunc_ms/(a.Parameter.Headers.DwellTimeSig_ns*1e-6));
-a = a.Truncate(truncPoint);
+% trunc_ms = 250;
+% truncPoint = floor( trunc_ms/(a.Parameter.Headers.DwellTimeSig_ns*1e-6));
+% a = a.Truncate(truncPoint);
a = a.FrequencyAlign;
a = a.DeleteMovedAverages;
@@ -22,10 +22,10 @@ a.Parameter.FreqAlignFreqDomainSettings.selectedMix = 1;
%indices of Interest: given in ppm
% water peak
-a.Parameter.FreqAlignFreqDomainSettings.peaksInPpm = [3.925];
+% a.Parameter.FreqAlignFreqDomainSettings.peaksInPpm = [3.925];
%set zeroFillingParameter to get smooth approximations
-a.Parameter.FreqAlignFreqDomainSettings.zeroFillFactor = 50;
+% a.Parameter.FreqAlignFreqDomainSettings.zeroFillFactor = 50;
%search area (+-) in ppm
a.Parameter.FreqAlignFreqDomainSettings.searchArea = 0.1;
@@ -37,20 +37,20 @@ a.Parameter.FreqAlignFreqDomainSettings.splineSmoothingCoeff = 0.01;
% do the actual Frequency Alignment
a = a.FrequencyAlignFreqDomain;
%%
-a.Parameter.HsvdSettings.bound = [-160 250];
-a.Parameter.HsvdSettings.n = size(a.Data{1},1);
-a.Parameter.HsvdSettings.p = 25;
-[~, a] = a.Hsvd;
+% a.Parameter.HsvdSettings.bound = [-160 160];
+% a.Parameter.HsvdSettings.n = 4096; %size(a.Data{1},1);
+% a.Parameter.HsvdSettings.p = 25;
+% [~, a] = a.Hsvd;
+% %%
+% if(doReverse)
+% a = a.ReverseMC;
+% a.Parameter.HsvdSettings.bound = [-160 160];
+% [~, a] = a.Hsvd;
+% end
%%
-if(doReverse)
- a = a.ReverseMC;
- a.Parameter.HsvdSettings.bound = [-160 160];
- [~, a] = a.Hsvd;
-end
-%%
-trunc_ms = 150;
-truncPoint = floor( trunc_ms/(a.Parameter.Headers.DwellTimeSig_ns*1e-6));
-a = a.Truncate(truncPoint);
+% trunc_ms = 150;
+% truncPoint = floor( trunc_ms/(a.Parameter.Headers.DwellTimeSig_ns*1e-6));
+% a = a.Truncate(truncPoint);
%% Phase correction
if ~exist('phase0','var')
phase0 = 0;
diff --git a/Met_T1processing/plot_mean_std_of_spectra_metT1.m b/Met_T1processing/plot_mean_std_of_spectra_metT1.m
new file mode 100644
index 0000000000000000000000000000000000000000..18b35c7933b685c5e26cd378cd6969a01d2c3280
--- /dev/null
+++ b/Met_T1processing/plot_mean_std_of_spectra_metT1.m
@@ -0,0 +1,172 @@
+function plot_mean_std_of_spectra_metT1
+
+downField_MM_Met = 'Met';
+switch downField_MM_Met
+ case 'DF'
+ pathName = 'DF data path';
+ TEs = [24; 24; 32; 40; 52; 60; ];
+ colors = {[0 0.7 0]; [0 0.7 0]; [0 0 0]; [0 0 1]; [1 0 0]; [0 0.5 0.5];};
+ offsetStep = 2.2e-5;
+ case 'MM'
+ pathName = 'MM T1 data path';
+ TEs = [1; 2; 3; 4; 5; 6; 7; 8; 9; 10; 11; ];
+ colors = {[76 187 23]/255; [76 187 23]/255; [1 121 111]/255; [75 0 130]/255; [75 0 130]/255; [75 0 130]/255; [75 0 130]/255;};
+ offsetStep = 7.0e-5;
+ case 'MM WM'
+ pathName = 'MM WM T1 data path';
+ TEs = [1; 2; 3; 4; 5; 6; 7; 8; 9; 10; 11; ];
+ colors = {[76 187 23]/255; [76 187 23]/255; [76 187 23]/255; [76 187 23]/255; [76 187 23]/255; [1 121 111]/255; [75 0 130]/255; [75 0 130]/255; [75 0 130]/255; [75 0 130]/255; [75 0 130]/255;};
+ offsetStep = 7.0e-5;
+ case 'Met'
+ pathName = 'Met T1 WM data path';
+ TEs = [2500; 1400; 1000; 700; 400; 100; 20; ];
+ colors = {[76 187 23]/255; [76 187 23]/255; [1 121 111]/255; [75 0 130]/255; [75 0 130]/255; [75 0 130]/255; [75 0 130]/255;};%{[0 0.7 0]; [0 0 0]; [0 0 1]; [1 0 0]; [0 0.5 0.5];};
+ offsetStep = 40e-4;
+end
+
+[path] = pathToDataFolder(pathName);
+
+fileNameBase = [path, 'Summed_Averaged_TE'];
+
+
+numberOfTEs = length(TEs);
+
+offSetBase = offsetStep * (numberOfTEs); %+7 for WM
+
+for indexTE = 1:numberOfTEs
+ fileName = [fileNameBase num2str(TEs(indexTE))];
+ offset = offSetBase - indexTE * offsetStep;
+ if (indexTE == 1) && (strcmp(downField_MM_Met,'DF'))
+ plotOneTE(fileName, TEs(indexTE), colors{indexTE}, offset+offsetStep/2, 'DF_up');
+ else
+ plotOneTE(fileName, TEs(indexTE), colors{indexTE}, offset, downField_MM_Met);
+ end
+end
+
+end
+
+function plotOneTE(fileName, TE, colorSpectrum, offset, downField_MM_Met)
+load([fileName '.mat'], 'summedSpectraTE')
+
+zeroPPM = 4.67;
+nTimepoints = size(summedSpectraTE.Data{1},summedSpectraTE.kx_dim);
+nAverages = size(summedSpectraTE.Data{1},summedSpectraTE.meas_dim);
+waterFreq = summedSpectraTE.Parameter.Headers.ScanFrequency * 1E-6;
+bandwidth = summedSpectraTE.Parameter.Headers.Bandwidth_Hz;
+frequencyRange = linspace(-bandwidth/2,bandwidth/2,nTimepoints);
+
+if strcmp(downField_MM_Met,'DF_up')
+ fidSpectra = summedSpectraTE.Data{1}(:,1,1,1,1,1,1,1,1,1,1,:) * 5;
+else
+ fidSpectra = summedSpectraTE.Data{1}(:,1,1,1,1,1,1,1,1,1,1,:) * 1;
+end
+
+fidWater = summedSpectraTE.Data{1}(:,1,1,1,1,1,1,1,2,1,1,:);
+spectra = squeeze(fftshift(fft(fidSpectra)));
+water = squeeze(fftshift(fft(fidWater)));
+meanSpectrum = mean(spectra,2);
+stdSpectrum = std(spectra,[],2);
+relativeStd = stdSpectrum ./ max(meanSpectrum) * 100;
+
+ppmVector = (frequencyRange)/waterFreq+zeroPPM;
+
+% figure(101)
+% plot(ppmVector,relativeStd)
+% xlim([0.5 4.2]);
+% set(gca,'xDir','reverse')
+
+
+%%
+scalingRange = (ppmVector < 1.8) & (ppmVector > 0);
+for indexAverage = 1:nAverages
+ [maxWater,indexMaxWater] = max(abs(real(water(:, indexAverage))));
+
+ [~, indexMaxWaterInRange] = max(abs(real((water(scalingRange, indexAverage)-mean(water(scalingRange, indexAverage))))));
+
+ [maxWaterInRange, ~] = max(real(water(scalingRange, indexAverage)));
+ minWaterInRange = min(real(water(scalingRange, indexAverage)));
+
+ maxSpectraInRange = max(real(spectra(scalingRange, indexAverage)));
+ minSpectraInRange = min(real(spectra(scalingRange, indexAverage)));
+
+ indexStart = find(scalingRange);
+ indexMaxWaterInRange = indexMaxWaterInRange + indexStart(1);
+ referenceLines = zeros(nTimepoints,1);
+ referenceLines(:) = -maxWaterInRange*2;
+ referenceLines(indexMaxWaterInRange:indexMaxWater + (indexMaxWater - indexMaxWaterInRange)) = maxWaterInRange*2;
+
+ plotOffset = maxSpectraInRange;
+% figWaterSpectra = figure(2);
+% hold on
+% plot(ppmScale, real(water(:,indexAverage)) - minWaterInRange + plotOffset,'b')
+% plotScale = (maxWaterInRange-minWaterInRange);
+% ylim([minSpectraInRange-(plotOffset*0.3) plotScale*1.2+plotOffset]);
+% hold on
+% pSpectra = plot(ppmScale, real(spectra(:,indexAverage)),'r');
+% hold on
+% % figure
+% plot(ppmScale, referenceLines, 'k--')
+% xlim([0 8.5]);
+% set(gca,'xDir','reverse')
+% set(gca,'LineWidth',1);
+% % set(gca,'ytick',[])
+% xlabel('[ppm]');
+% makedatatip(pSpectra,[indexMaxWaterInRange])
+%
+% print(['WaterSpectraComparisonPlots\' num2str(indexAverage) '_' fileName],'-dpng')
+% close(figWaterSpectra)
+end
+%%
+% figure
+% plot(ppmScale, real(spectra))
+
+% xlim([0.5 4.2]);
+% set(gca,'xDir','reverse')
+% set(gca,'LineWidth',1);
+% % set(gca,'ytick',[])
+% xlabel('[ppm]');
+% title(['Individual Spectra TE ' num2str(TE) ' ms'])
+
+%%
+figure(1)
+stdAlpha = 0.4;
+hold on
+if strcmp(downField_MM_Met,'DF_up')
+ indexDFCut = find(ppmVector > 8.6, 1, 'first');
+ ppmVector = ppmVector(indexDFCut:end);
+ meanSpectrum = meanSpectrum(indexDFCut:end);
+% stdSpectrum = stdSpectrum(indexDFCut:end);
+end
+
+% h = area(ppmVector,[(meanSpectrum - stdSpectrum) + offset (stdSpectrum * 2)]);
+
+h(1).FaceColor = 'none';
+h(2).FaceColor = colorSpectrum;
+h(2).FaceAlpha = stdAlpha;
+h(1).EdgeColor = 'none';
+h(2).EdgeColor = 'none';
+hold on
+pSpectrum = plot(ppmVector,meanSpectrum + offset, 'LineWidth',2, 'Color', colorSpectrum);
+
+switch downField_MM_Met
+ case 'DF'
+ xlim([5.5 9.4]);
+ case 'DF_up'
+ xlim([5.5 9.4]);
+ case 'MM'
+ xlim([0.5 4.2]);
+% ylim([4.5e-6 4.7e-5]);
+ case 'MM WM'
+ xlim([0.5 4.2]);
+ %ylim([2e-6 1.3e-4]); %TODO: check why scaling is different, then MM
+ case 'Met'
+ xlim([0.5 4.2]);
+% ylim([5000 5000]);
+end
+set(gca,'xDir','reverse')
+set(gca,'LineWidth',1);
+set(gca,'ytick',[])
+xlabel('[ppm]');
+title('Spectra mean and standard deviation')
+% title(['Spectra TE ' num2str(TE) ' ms'])
+end
\ No newline at end of file
diff --git a/Met_T1processing/reconstruct_all_MetT1.m b/Met_T1processing/reconstruct_all_MetT1.m
index bb75c2afe9a798584e86231be05dd5496465c9d5..9d271c4b9b6bdaf4236f857bfb516a1a7775fb8e 100644
--- a/Met_T1processing/reconstruct_all_MetT1.m
+++ b/Met_T1processing/reconstruct_all_MetT1.m
@@ -1,6 +1,6 @@
function reconstruct_all_MetT1()
-pathName = 'MET_T1 data path';
+pathName = 'Met T1 WM data path';
subjects = { ...
'1405' ...
'1706' ...
@@ -18,7 +18,7 @@ subjects = { ...
pathBase = pathToDataFolder(pathName, subjects);
TIs = [20; 100; 400; 700; 1000; 1400; 2500];
-
+%TIs = [1000];
numberOfSubjects = length(subjects);
paths = cell(1,numberOfSubjects);
for indexSubj = 1:numberOfSubjects
@@ -48,7 +48,7 @@ addSinglet0ppm = 'Yes';
numberOfTIs = length(TIs);
filesPath = cell(numberOfTIs,numberOfSubjects);
-waterFilesPath = cell(1,numberOfSubjects);
+% waterFilesPath = cell(1,numberOfSubjects);
files = [files_TI20; files_TI100; files_TI400; files_TI700; files_TI1000; files_TI1400; files_TI2500];
for indexSubj = 1:numberOfSubjects
for indexTI = 1:numberOfTIs
diff --git a/algorithms/@MR_spectroS/Anonimize_MR_spectroS.m b/algorithms/@MR_spectroS/Anonimize_MR_spectroS.m
new file mode 100644
index 0000000000000000000000000000000000000000..c99c6820f04fdf0a57158e0411a4454d69a4ea18
--- /dev/null
+++ b/algorithms/@MR_spectroS/Anonimize_MR_spectroS.m
@@ -0,0 +1,37 @@
+function this = Anonimize_MR_spectroS(this, subjectNumber)
+% subjectNumber should be random, not pseudo-random.
+
+% if the subjectNumber is not given, use the timestamp of the execution as
+% a subjectID. Using the timestamp makes the data anominized, but also
+% unique. No other data set will have the same execution timestamp.
+if ~exist('subjectNumber','var')
+ subjectNumber = round(now*1e8);
+end
+% make subjectNumber a string and give at least 4 digit precision
+subjectNumberStr = ['Subj_', num2str(subjectNumber,'%.4d')];
+
+%% Header info
+patientID = this.Parameter.Headers.PatientID;
+this.Parameter.Headers.PatientID = subjectNumber;
+this.Parameter.Headers.PatientName = subjectNumber;
+
+% keep birthday only as year of birth, set rest to 1st of January
+birthday = this.Parameter.Headers.BirthDay;
+this.Parameter.Headers.BirthDay = round(birthday / 1e4)*1e4+0101;
+
+%% Filename
+% remove MID and FID numbers from filename and add the subjectNumberStr
+[~, fileName, extension] = fileparts(this.Parameter.Filename);
+fileNameChunks = strsplit(fileName,'_');
+idx = contains(fileNameChunks,'MID');
+fileNameChunks(idx) = [];
+idx = contains(fileNameChunks,'FID');
+fileNameChunks(idx) = [];
+fileNameAnonimized = [strjoin(fileNameChunks,'_'), '_', subjectNumberStr, extension];
+this.Parameter.Filename = fileNameAnonimized;
+
+%% Filepath
+%filepath may contain patientID. If true, this will replace it
+filepath = this.Parameter.Filepath;
+this.Parameter.Filepath = strrep(filepath,num2str(patientID),subjectNumberStr);
+end
\ No newline at end of file
diff --git a/algorithms/@MR_spectroS/EddyCurrentCorrection.m b/algorithms/@MR_spectroS/EddyCurrentCorrection.m
index 8a7952288d9154c2f8533eec805c67c0711b442e..9b0cc36a2eb9cdba3319508dae390e5bd45a5fb9 100644
--- a/algorithms/@MR_spectroS/EddyCurrentCorrection.m
+++ b/algorithms/@MR_spectroS/EddyCurrentCorrection.m
@@ -85,9 +85,9 @@ end
nBlocks = this.Parameter.AverageSettings.nBlocks;
% average the data based on the number of blocks
nAverages = size(waterReferenceData, this.meas_dim);
- if mod(nAverages, nBlocks)~=0
- error('The number of measurements of the water reference should be multiple of the number of blocks')
- end
+% if mod(nAverages, nBlocks)~=0
+% error('The number of measurements of the water reference should be multiple of the number of blocks')
+% end
averagesPerBlock = nAverages/nBlocks;
for indexOfBlocks=1:nBlocks
@@ -98,7 +98,7 @@ end
%% TODO: add combine coils with the weights - one has to add the weights as a parameter
%% Apply the actual Eddy Current Correction using the phase of the water reference (Klose correction)
- data = data.*exp(-1j*angle(averagedWaterReferenceData));
+ data = data.*exp(-1*j*angle(averagedWaterReferenceData)); %
end
this.Data{1} = data;
this.Parameter.ReconFlags.isEddyCurrentCorrected= true;
diff --git a/algorithms/@MR_spectroS/ExportLcmRaw.m b/algorithms/@MR_spectroS/ExportLcmRaw.m
index 441e92699ae62489d87d04b8ccb6c244c94ad061..46991c0858be9f131f404d840eddac8e6f8ef70a 100644
--- a/algorithms/@MR_spectroS/ExportLcmRaw.m
+++ b/algorithms/@MR_spectroS/ExportLcmRaw.m
@@ -1,4 +1,4 @@
-function ExportLcmRaw(this, path, name, addSinglet, makeBasisExport, referencePeakPpm, scalingFactorRefPeak)
+function ExportLcmRaw(this, path, name, addSinglet, makeBasisExport, referencePeakPpm, scalingFactorRefPeak, MC_mix)
% Define the fileptath where the .RAW files will be saved
if exist('path','var')
@@ -26,6 +26,10 @@ if ~exist('scalingFactorRefPeak','var')
scalingFactorRefPeak = 0.05;
end
+if ~exist('MC_mix','var')
+ MC_mix = 1; %1 = normal case, export spectra. 2 = export MC water
+end
+
if exist('addSinglet','var')
choice = addSinglet;
if choice == true
@@ -51,7 +55,7 @@ data = this.Data{1};
NMeas = size( data, this.meas_dim); % # Averages
%NCha = size( data, this.coil_dim); % # Channels
%NRep = size( data, this.dyn_dim); % # Repetitions
-%NMix = size( data, this.mix_dim); % # Mixes
+NMix = size( data, this.mix_dim); % # Mixes
isAveraged = this.Parameter.ReconFlags.isAveraged;
isMovingAveraged = this.Parameter.ReconFlags.isfMRSMovingAveraged;
isISISAveraged = this.Parameter.ReconFlags.isISISAveraged;
@@ -104,7 +108,7 @@ switch makeBasis
metaboliteName = 'Leu';
end
-dataExport = data(:,1,1,1,1,1,1,1,1,1,1,1);
+dataExport = data(:,1,1,1,1,1,1,1,MC_mix,1,1,1);
brukerFormat = true;
ExportLCModelBasis(dataExport, dwellTime, scanFrequency, filepath, filename, metaboliteName, choice, ...
brukerFormat, referencePeakPpm, scalingFactorRefPeak, makeBasis, TE, sequenceName)
diff --git a/algorithms/@MR_spectroS/MR_spectroS.m b/algorithms/@MR_spectroS/MR_spectroS.m
index ad3a13eef4908b1023dd91ed89287285ac88edc1..baeff2e699388978d2e13b08580f900ec6bff310 100644
--- a/algorithms/@MR_spectroS/MR_spectroS.m
+++ b/algorithms/@MR_spectroS/MR_spectroS.m
@@ -80,7 +80,7 @@ classdef MR_spectroS
this = Filtering( this );
this = Truncate( this, truncPoint)
this = RemoveFiltering( this );
- this = ExportLcmRaw( this, path, name, advoigdSinglet, makeBasisExport, referencePeakPpm, scalingFactorRefPeak);
+ this = ExportLcmRaw( this, path, name, advoigdSinglet, makeBasisExport, referencePeakPpm, scalingFactorRefPeak, MC_mix);
this = ExportMruiText(this, path, name, nucleus);
this = AverageData( this );
this = DeleteCoilChannels( this, coilChannels2Delete );
@@ -118,6 +118,7 @@ classdef MR_spectroS
[this, this2, weights] = ISIS_main_processing(this,verbose);
this = ISIS_prep_freqAlign(this, this2, weights);
this = FrequencyAlignISIS(this,freqShiftsISISBlock,freqShiftsISISSteps);
+ this = Anonimize_MR_spectroS(this, subjectNumber);
%//////////////////////////////////////////////////////////////////////////
diff --git a/algorithms/@MR_spectroS/Sorting.m b/algorithms/@MR_spectroS/Sorting.m
index fe41cb7c8d546008ba16a8baffd481e537a2d42d..b1c5f4ad7fb243867819f7252d6e4c96640882a2 100644
--- a/algorithms/@MR_spectroS/Sorting.m
+++ b/algorithms/@MR_spectroS/Sorting.m
@@ -9,6 +9,7 @@ else
nAverages = size(this.Data{1},this.meas_dim);
newDataSize = size(this.Data{1});
newDataSize(this.dyn_dim) = 1;
+ newDataSize(this.extr2_dim) = 1;
newDataSize(this.meas_dim) = NDyns*nAverages;
newData = zeros(newDataSize);
oldData = this.Data{1};
diff --git a/createTestData/compareFitInput_Output.m b/createTestData/compareFitInput_Output.m
new file mode 100644
index 0000000000000000000000000000000000000000..c32d238006be761a8fc0ff11798500153c120d63
--- /dev/null
+++ b/createTestData/compareFitInput_Output.m
@@ -0,0 +1,76 @@
+function [diff_conc, diff_em, diff_gm, diff_pc0, diff_df2, diff_pc12, diff_T2] = compareFitInput_Output(dataExportPath, filenameData, iteration)
+
+saveFigures = false;
+
+fileNameOff = strrep(filenameData,'On', 'Off');
+xx = ls([dataExportPath, fileNameOff '*']);
+
+load([dataExportPath, fileNameOff, '.mat'], 'summedFidWithNoise', 'current_em', 'currentConcentrationRm', ...
+ 'current_pc0', 'current_pc1', 'current_df2', 'current_gm', 'current_em_std_factor', 'conc_std_factor');
+
+fileNameProFit = [filenameData '_profit'];
+% close all;
+load(strcat(dataExportPath,fileNameProFit, '.mat'),'fitresult');
+
+currentFitresult = fitresult{1,iteration};
+
+% metabolites and results have to be first sorted
+metabolites = {'Asp', 'tCr(CH2)', 'tCr(CH3)', 'GABA', 'Gln', 'Glu', 'Glyc', 'GSH', 'Lac', 'mI', 'NAA(CH3)', 'NAA(CH2)', 'NAAG', 'tCho+', 'Scy', 'Tau', 'MMB'};
+metabolitesName = {'Asp', 'Cr_CH2', 'Cr', 'GABA', 'Gln', 'Glu', 'Glyc', 'GSH', 'Lac', 'mI', 'NAA_ac', 'NAA_as', 'NAAG', 'tCho_P', 'Scyllo', 'Tau', 'Leu'};
+
+active_met_names = currentFitresult.met(currentFitresult.active_mets);
+sortedIndeces = zeros(length(metabolitesName),1);
+for indexMet = 1: length(metabolitesName)
+ indexX = find(strcmp(metabolitesName{indexMet}, active_met_names));
+ sortedIndeces(indexX) = indexMet;
+end
+
+currentConcentrationRm(end) = currentConcentrationRm(end)*1e-8;
+diff_conc = currentFitresult.fitted_values.conc * currentFitresult.sub_mask.conc.full - currentConcentrationRm(sortedIndeces);
+diff_conc(currentFitresult.fitted_values.conc==0)=NaN;
+diff_em = currentFitresult.fitted_values.em * currentFitresult.sub_mask.em.full - current_em(sortedIndeces);
+diff_gm = currentFitresult.fitted_values.gm * currentFitresult.sub_mask.gm.full- current_gm;
+diff_pc0 = currentFitresult.fitted_values.pc0 * currentFitresult.sub_mask.pc0.full - current_pc0;
+diff_df2 = currentFitresult.fitted_values.df2 * currentFitresult.sub_mask.df2.full - current_df2(sortedIndeces);
+diff_pc12 = currentFitresult.fitted_values.pc12 * currentFitresult.sub_mask.pc12.full - current_pc1;
+diff_T2 = 1./(pi*currentFitresult.fitted_values.em * currentFitresult.sub_mask.em.full) *1e3 - ...
+ 1./(pi*current_em(sortedIndeces)) * 1e3;
+
+figId2=figure;
+set(figId2,...
+ 'Position',[350 400 890 600],'Color',[1 1 1]);
+crlb_print =currentFitresult.crlb;
+crlb_print(abs(crlb_print)>=1000) = 999.9999;
+dataOfTable={};
+columnname = {'met','conc', '<html>crlb<br />[%]</html>', ...
+ '<html>T2<br />[ms]</html>','<html>em<br />[Hz]</html>',...
+ '<html>gm<br />[Hz]</html>', '<html>em_g<br />[Hz]</html>', ...
+ '<html>pc0<br />[deg]</html>', '<html>df2<br />[Hz]</html>', ...
+ '<html>pc12<br />[deg/ppm]</html>'};
+columnformat={'char',[],[],[],[],[],[],[],[],[]};
+concentrations = zeros(1,currentFitresult.nr_act_mets);
+
+for met_cnt=1:currentFitresult.nr_act_mets
+ dataOfTable=[dataOfTable;{...
+ active_met_names{met_cnt},...
+ num2str(diff_conc(met_cnt),'%6.4f'),...
+ num2str(crlb_print(currentFitresult.sub_mask.conc.full(:,met_cnt)'),'%6.4f'),...
+ num2str(diff_T2(met_cnt),'%6.4f'),...
+ num2str(diff_em(met_cnt),'%6.4f'),...
+ num2str(diff_gm(met_cnt),'%6.4f'),...
+ num2str(diff_pc0(met_cnt),'%6.4f'),...
+ num2str(diff_df2(met_cnt),'%6.4f'),...
+ num2str(diff_pc12(met_cnt),'%6.4f')...
+ }];
+ concentrations(met_cnt) = currentFitresult.fitted_values.conc(currentFitresult.sub_mask.conc.full(:,met_cnt)');
+end
+tableProfit = uitable(...%'Units','normalized',...%
+ 'Position',[20 20 850 580],'Data', dataOfTable,...
+ 'ColumnName', columnname,'ColumnFormat',columnformat,...
+ 'RowName',[],'ColumnWidth',{65});
+
+if saveFigures
+ saveas(figId2, [dataExportPath,fileNameProFit, '_compare_iter', num2str(iteration), '_table.tif']);
+ savefig(figId2, [dataExportPath,fileNameProFit, '_compare_iter', num2str(iteration), '_table.fig'],'compact');
+end
+end
diff --git a/createTestData/createSimulatedSpectra.m b/createTestData/createSimulatedSpectra.m
index 97634c1e62caaf9870f76d903830ba6f1a5f9d50..a287c53efcb9c4dbab17c43db62c213c2652453a 100644
--- a/createTestData/createSimulatedSpectra.m
+++ b/createTestData/createSimulatedSpectra.m
@@ -14,7 +14,8 @@ T2_std = [ 12, 10, 16, 35, 20, 25, 10,
TE = 24 * 1e-3;
numMetabolites = length(metabolites);
-saveData = true;
+saveData = false;
+saveFigures = true;
saveRandNumbers = false; %should generally be kept false to have the same random numbers consistently
%% path to the export of the spectra
@@ -25,11 +26,21 @@ dataExportPathBase = strcat(pathBaseExportFiles, exportFolder{1}, '\');
% think whether to change tCho+ from original (1.0+-0.2) to max(2.5+-0.5) current(1.5+-0.4) to accomodate PE
-gaussianValues = [6:2:30]; %Hz
-pc0 = [-20:5:20]; %grad
-pc1 = [-7.5:2.5:7.5]; %grad/ppm
-df2_global = [-15:2.5:15]; % Hz : Global and local shifts
-df2_local_std = 5;%7; %Hz coresponds to ~0.02 ppm. This is the maximal shift, which can occur by temperature between moieties (Wermter, MRMP 2017)
+gaussianValues = [4:2:32]; %Hz
+pc0 = [-35:5:35]; %grad
+% The first order phase does not fully mimick in vivo conditions. While we
+%could mimick a truncation of the first points, a maximum echo sampling is
+%not possible with the normal echo sampling basis set
+pc1 = [-17.5:2.5:17.5]; %grad/ppm
+% pc1 = [-30:5:30]; %grad/ppm
+df2_global = [-17.5:2.5:17.5]; % Hz : Global and local shifts
+df2_local_scale = [0.25 0.25 0.5 0.5 0.75 0.75 1 1 1.5 1.5 2 2 3 3 5];
+df2_local_std = 3;% 3 Hz coresponds to ~0.0075 ppm.
+% This is the maximal shift, which can occur by temperature between
+% moieties (Wermter, MRMP 2017), assuming up to 10°C temperature change.
+% pH changes should have a similar order of magnitude.
+
+em_local_scale = [0.2 0.2 0.4 0.4 0.6 0.6 0.8 0.8 1 1 1.2 1.2 1.5 1.5 2];
% when truncating at 200 ms like used in real spectra, the NAA SNR of the defaultSummedFid corresponds to
% Chosen NoiseLevel -> SNR(NAA)
% 1 -> SNR = 207; 3 -> SNR = 158; 7 -> SNR = 110; 15 -> SNR = 44; 25 -> SNR = 13
@@ -42,6 +53,7 @@ if saveRandNumbers
save([dataExportPathBase, 'df2_local_RandNumbers.mat'], 'df2_local_RandNumbers');
end
load([dataExportPathBase, 'df2_local_RandNumbers.mat'], 'df2_local_RandNumbers');
+em_local_RandNumbers = df2_local_RandNumbers; %use the same random numbers for simplicity
%%
metaboliteFileNames = metabolites;
@@ -86,17 +98,19 @@ for indexMetabolite = 1:numMetabolites
end
end
+water_ppm = 4.66; % ppm
+referencePeakPpm = -water_ppm;
nTimepoints = length(fids{1});
dwellTime = 1/bandwidth;
timePointsSampling =(0:nTimepoints - 1) * dwellTime;
-referencePeakPpm = -4.7;
scalingFactorRefPeak = 0.05;
-phase_1_f2_mx = linspace(-1, 1, nTimepoints);
-refFreqPpm = -2.3; % the reference Frequency for the excitation pulse, given in ppm compared to the water (minus is upfield, + downfield)
-phase_1_f2_mx = phase_1_f2_mx .* bandwidth ./ scanFrequency / 2 + (-referencePeakPpm + refFreqPpm);
+refFreqPpm = -0; % the reference Frequency for the excitation pulse, given in ppm compared to the water (minus is upfield, + downfield)
+phasePivot_ppm = water_ppm + refFreqPpm;%in ppm
ppmVector = ppmVectorFunction(scanFrequency*1e6, bandwidth, nTimepoints, '1H');
+phase_1_f2_mx = ppmVector-phasePivot_ppm;
+
ppmMask = (ppmVector>0.6) & (ppmVector<4.1);
@@ -104,7 +118,8 @@ ppmMask = (ppmVector>0.6) & (ppmVector<4.1);
default_pc0 = 0;
default_pc1 = 0;
default_df2 = zeros(1,numMetabolites);
-default_gm = gaussianValues(4);
+default_gm = 12;
+default_em_std_factor = zeros(1,numMetabolites);
default_noiseLevel = 3;
noiseVector = wgn(1,nTimepoints, default_noiseLevel);
trunc_ms = 200;
@@ -115,7 +130,7 @@ current_pc0 = default_pc0;
current_pc1 = default_pc1;
current_df2 = default_df2;
current_gm = default_gm;
-current_em_std_factor = 0; %TODO
+current_em_std_factor = default_em_std_factor;
conc_std_factor = zeros(1,numMetabolites);
% generate the default spectrum
@@ -123,9 +138,12 @@ conc_std_factor = zeros(1,numMetabolites);
createSummedSpectrum(...
fids, concentrations, conc_std, T2s, T2_std, TE, metabolites, metaboliteFileNames, timePointsSampling, phase_1_f2_mx, ppmMask, ...
current_pc0, current_pc1, current_df2, current_gm, current_em_std_factor, conc_std_factor, noiseVector, ...
- truncPoint, saveData, 'meanConc', [], dwellTime * 1e3, scanFrequency, dataExportPathBase, referencePeakPpm, scalingFactorRefPeak);
+ truncPoint, saveData, 'meanConc', [], dwellTime * 1e3, scanFrequency, dataExportPathBase, water_ppm, scalingFactorRefPeak);
-figure;
+figure(1);
+subplot(5,4,8+7:8+8)
+% figure(2);
+% subplot(3,4,7:8)
plot(ppmVector,real(fftshift(fft(defaultSummedFid))));
%% generate the series of different concentrations
@@ -169,7 +187,11 @@ for indexParam = 1:numberConcPermutations
% ImportLCModelBasis(dataExportPath, fileName, true, '1H');
end
-save([dataExportPathBase, 'concentrations_simulated_', paramKeyword, '.mat'], 'concentrationsRm', 'metabolites', 'metaboliteFileNames');
+titleStr = '{\boldmath$c$}';
+plotSimulationSetup(titleStr, paramKeyword, saveFigures, dataExportPathBase);
+if saveData
+ save([dataExportPathBase, 'concentrations_simulated_', paramKeyword, '.mat'], 'concentrationsRm', 'metabolites', 'metaboliteFileNames');
+end
for indexMetabolite = 1:numMetabolites
figure;
@@ -177,160 +199,219 @@ for indexMetabolite = 1:numMetabolites
title(metabolites(indexMetabolite))
end
-% %% #############################################################################################
-% % generate the series of different parameters, same concentrations
-% % #############################################################################################
-% conc_std_factor = zeros(1,numMetabolites); % reset value
-%
-% %% gauss
-% paramKeyword = 'gauss';
-% dataExportPath = [dataExportPathBase, paramKeyword, '\'];
-% concentrationsRm = zeros(length(gaussianValues), numMetabolites);
-%
-% figure;
-% for indexParam = 1:length(gaussianValues)
-%
-% current_gm = gaussianValues(indexParam);
-% [summedFid, summedFidWithNoise, current_em, currentConcentrationRm] = createSummedSpectrum(...
-% fids, concentrations, conc_std, T2s, T2_std, TE, metabolites, metaboliteFileNames, timePointsSampling, phase_1_f2_mx, ppmMask, ...
-% current_pc0, current_pc1, current_df2, current_gm, current_em_std_factor, conc_std_factor, noiseVector, ...
-% truncPoint, saveData, paramKeyword, indexParam, dwellTime * 1e3, scanFrequency, dataExportPath, referencePeakPpm, scalingFactorRefPeak);
-%
-% concentrationsRm(indexParam,:) = currentConcentrationRm;
-% hold on;
-% plot(ppmVector,real(fftshift(fft(summedFid))));
-% end
-% % reset parameter
-% current_gm = default_gm;
-%
-% save([dataExportPathBase, 'concentrations_simulated_', paramKeyword, '.mat'], 'concentrationsRm', 'metabolites', 'metaboliteFileNames');
-%
-% %% pc0 - zero order phase
-% paramKeyword = 'pc0';
-% dataExportPath = [dataExportPathBase, paramKeyword, '\'];
-% concentrationsRm = zeros(length(pc0), numMetabolites);
-%
-% figure;
-% for indexParam = 1:length(pc0)
-%
-% current_pc0 = pc0(indexParam);
-% [summedFid, summedFidWithNoise, current_em, currentConcentrationRm] = createSummedSpectrum(...
-% fids, concentrations, conc_std, T2s, T2_std, TE, metabolites, metaboliteFileNames, timePointsSampling, phase_1_f2_mx, ppmMask, ...
-% current_pc0, current_pc1, current_df2, current_gm, current_em_std_factor, conc_std_factor, noiseVector, ...
-% truncPoint, saveData, paramKeyword, indexParam, dwellTime * 1e3, scanFrequency, dataExportPath, referencePeakPpm, scalingFactorRefPeak);
-%
-% concentrationsRm(indexParam,:) = currentConcentrationRm;
-% hold on;
-% plot(ppmVector,real(fftshift(fft(summedFid))));
-% end
-% % reset parameter
-% current_pc0 = default_pc0;
-%
-% save([dataExportPathBase, 'concentrations_simulated_', paramKeyword, '.mat'], 'concentrationsRm', 'metabolites', 'metaboliteFileNames');
-%
-% %% pc1 - first order phase
-% paramKeyword = 'pc1';
-% dataExportPath = [dataExportPathBase, paramKeyword, '\'];
-% concentrationsRm = zeros(length(pc1), numMetabolites);
-%
-% figure;
-% for indexParam = 1:length(pc1)
-%
-% current_pc1 = pc1(indexParam);
-% [summedFid, summedFidWithNoise, current_em, currentConcentrationRm] = createSummedSpectrum(...
-% fids, concentrations, conc_std, T2s, T2_std, TE, metabolites, metaboliteFileNames, timePointsSampling, phase_1_f2_mx, ppmMask, ...
-% current_pc0, current_pc1, current_df2, current_gm, current_em_std_factor, conc_std_factor, noiseVector, ...
-% truncPoint, saveData, paramKeyword, indexParam, dwellTime * 1e3, scanFrequency, dataExportPath, referencePeakPpm, scalingFactorRefPeak);
-%
-% concentrationsRm(indexParam,:) = currentConcentrationRm;
-% hold on;
-% plot(ppmVector,real(fftshift(fft(summedFid))));
-% end
-% % reset parameter
-% current_pc1 = default_pc1;
-%
-% save([dataExportPathBase, 'concentrations_simulated_', paramKeyword, '.mat'], 'concentrationsRm', 'metabolites', 'metaboliteFileNames');
-
-% %% df2 - frequency shifts
-% paramKeyword = 'df2';
-% dataExportPath = [dataExportPathBase, paramKeyword, '\'];
-% concentrationsRm = zeros(length(df2_global), numMetabolites);
-%
-% figure;
-% for indexParam = 1:length(df2_global)
-%
-%
-% for indexMetabolite = 1:numMetabolites
-% % generate a random number between [-stdLim; stdLim]
-% stdRand = 2 * df2_local_std * df2_local_RandNumbers(indexParam,indexMetabolite) - df2_local_std;
-% switch metabolites{indexMetabolite}
-% case 'tCr(CH2)'
-% creatineStdRand = stdRand;
-% case 'tCr(CH3)'
-% stdRand = creatineStdRand;
-% case 'NAA(CH3)'
-% NaaStdRand = stdRand;
-% case 'NAA(CH2)'
-% stdRand = NaaStdRand;
-% otherwise
-% % nothing to do
-% end
-% current_df2(indexMetabolite) = df2_global(indexParam) + stdRand;
-% end
-% [summedFid, summedFidWithNoise, current_em, currentConcentrationRm] = createSummedSpectrum(...
-% fids, concentrations, conc_std, T2s, T2_std, TE, metabolites, metaboliteFileNames, timePointsSampling, phase_1_f2_mx, ppmMask, ...
-% current_pc0, current_pc1, current_df2, current_gm, current_em_std_factor, conc_std_factor, noiseVector, ...
-% truncPoint, saveData, paramKeyword, indexParam, dwellTime * 1e3, scanFrequency, dataExportPath, referencePeakPpm, scalingFactorRefPeak);
-%
-% concentrationsRm(indexParam,:) = currentConcentrationRm;
-% hold on;
-% plot(ppmVector,real(fftshift(fft(summedFid))));
-% end
-% % reset parameter
-% current_df2 = default_df2;
-%
-% save([dataExportPathBase, 'concentrations_simulated_', paramKeyword, '.mat'], 'concentrationsRm', 'metabolites', 'metaboliteFileNames');
-
-% %% em - lorentzian components of T2
-% paramKeyword = 'em';
-% dataExportPath = [dataExportPathBase, paramKeyword, '\'];
-% concentrationsRm = zeros(length(df2_global), numMetabolites);
-%
-% figure;
-% for indexParam = 1:length(df2_global)
-%
-%
-% for indexMetabolite = 1:numMetabolites
-% % generate a random number between [-stdLim; stdLim]
-% stdRand = 2 * df2_local_std * df2_local_RandNumbers(indexParam,indexMetabolite) - df2_local_std;
-% switch metabolites{indexMetabolite}
-% case 'tCr(CH2)'
-% creatineStdRand = stdRand;
-% case 'tCr(CH3)'
-% stdRand = creatineStdRand;
-% case 'NAA(CH3)'
-% NaaStdRand = stdRand;
-% case 'NAA(CH2)'
-% stdRand = NaaStdRand;
-% otherwise
-% % nothing to do
-% end
-% current_df2(indexMetabolite) = df2_global(indexParam) + stdRand;
-% end
-% [summedFid, summedFidWithNoise, current_em, currentConcentrationRm] = createSummedSpectrum(...
-% fids, concentrations, conc_std, T2s, T2_std, TE, metabolites, metaboliteFileNames, timePointsSampling, phase_1_f2_mx, ppmMask, ...
-% current_pc0, current_pc1, current_df2, current_gm, current_em_std_factor, conc_std_factor, noiseVector, ...
-% truncPoint, saveData, paramKeyword, indexParam, dwellTime * 1e3, scanFrequency, dataExportPath, referencePeakPpm, scalingFactorRefPeak);
-%
-% concentrationsRm(indexParam,:) = currentConcentrationRm;
-% hold on;
-% plot(ppmVector,real(fftshift(fft(summedFid))));
-% end
-% % reset parameter
-% current_df2 = default_df2;
-%
-% save([dataExportPathBase, 'concentrations_simulated_', paramKeyword, '.mat'], 'concentrationsRm', 'metabolites', 'metaboliteFileNames');
-%
+%% #############################################################################################
+% generate the series of different parameters, same concentrations
+% #############################################################################################
+conc_std_factor = zeros(1,numMetabolites); % reset value
+
+%% gauss
+paramKeyword = 'gauss';
+dataExportPath = [dataExportPathBase, paramKeyword, '\'];
+concentrationsRm = zeros(length(gaussianValues), numMetabolites);
+
+figure(1);
+subplot(5,4,5:6)
+% subplot(2,4,5:6)
+for indexParam = 1:length(gaussianValues)
+
+ current_gm = gaussianValues(indexParam);
+ [summedFid, summedFidWithNoise, current_em, currentConcentrationRm] = createSummedSpectrum(...
+ fids, concentrations, conc_std, T2s, T2_std, TE, metabolites, metaboliteFileNames, timePointsSampling, phase_1_f2_mx, ppmMask, ...
+ current_pc0, current_pc1, current_df2, current_gm, current_em_std_factor, conc_std_factor, noiseVector, ...
+ truncPoint, saveData, paramKeyword, indexParam, dwellTime * 1e3, scanFrequency, dataExportPath, referencePeakPpm, scalingFactorRefPeak);
+
+ concentrationsRm(indexParam,:) = currentConcentrationRm;
+ hold on;
+ plot(ppmVector,real(fftshift(fft(summedFid))));
+end
+% reset parameter
+current_gm = default_gm;
+
+
+titleStr = '$$\nu_{g}$$';
+plotSimulationSetup(titleStr, paramKeyword, saveFigures, dataExportPathBase);
+if saveData
+ save([dataExportPathBase, 'concentrations_simulated_', paramKeyword, '.mat'], 'concentrationsRm', 'metabolites', 'metaboliteFileNames');
+end
+
+%% pc0 - zero order phase
+paramKeyword = 'pc0';
+dataExportPath = [dataExportPathBase, paramKeyword, '\'];
+concentrationsRm = zeros(length(pc0), numMetabolites);
+
+figure(1);
+subplot(5,4,1:2)
+% subplot(2,4,1:2)
+for indexParam = 1:length(pc0)
+
+ current_pc0 = pc0(indexParam);
+ [summedFid, summedFidWithNoise, current_em, currentConcentrationRm] = createSummedSpectrum(...
+ fids, concentrations, conc_std, T2s, T2_std, TE, metabolites, metaboliteFileNames, timePointsSampling, phase_1_f2_mx, ppmMask, ...
+ current_pc0, current_pc1, current_df2, current_gm, current_em_std_factor, conc_std_factor, noiseVector, ...
+ truncPoint, saveData, paramKeyword, indexParam, dwellTime * 1e3, scanFrequency, dataExportPath, referencePeakPpm, scalingFactorRefPeak);
+
+ concentrationsRm(indexParam,:) = currentConcentrationRm;
+ hold on;
+ plot(ppmVector,real(fftshift(fft(summedFid))));
+end
+% reset parameter
+current_pc0 = default_pc0;
+
+titleStr = '$$\varphi_{0}$$';
+plotSimulationSetup(titleStr, paramKeyword, saveFigures, dataExportPathBase);
+if saveData
+ save([dataExportPathBase, 'concentrations_simulated_', paramKeyword, '.mat'], 'concentrationsRm', 'metabolites', 'metaboliteFileNames');
+end
+
+%% pc1 - first order phase
+paramKeyword = 'pc1';
+dataExportPath = [dataExportPathBase, paramKeyword, '\'];
+concentrationsRm = zeros(length(pc1), numMetabolites);
+
+figure(1);
+subplot(5,4,3:4)
+% subplot(2,4,3:4)
+for indexParam = 1:length(pc1)
+
+ current_pc1 = pc1(indexParam);
+ [summedFid, summedFidWithNoise, current_em, currentConcentrationRm] = createSummedSpectrum(...
+ fids, concentrations, conc_std, T2s, T2_std, TE, metabolites, metaboliteFileNames, timePointsSampling, phase_1_f2_mx, ppmMask, ...
+ current_pc0, current_pc1, current_df2, current_gm, current_em_std_factor, conc_std_factor, noiseVector, ...
+ truncPoint, saveData, paramKeyword, indexParam, dwellTime * 1e3, scanFrequency, dataExportPath, referencePeakPpm, scalingFactorRefPeak);
+
+ concentrationsRm(indexParam,:) = currentConcentrationRm;
+ hold on;
+ plot(ppmVector,real(fftshift(fft(summedFid))));
+end
+% reset parameter
+current_pc1 = default_pc1;
+
+titleStr = '$$\varphi_{1}$$';
+plotSimulationSetup(titleStr, paramKeyword, saveFigures, dataExportPathBase);
+if saveData
+ save([dataExportPathBase, 'concentrations_simulated_', paramKeyword, '.mat'], 'concentrationsRm', 'metabolites', 'metaboliteFileNames');
+end
+
+%% df2 local - frequency shifts
+paramKeyword = 'df2_local';
+dataExportPath = [dataExportPathBase, paramKeyword, '\'];
+concentrationsRm = zeros(length(df2_local_scale), numMetabolites);
+
+figure(1);
+subplot(5,4,8+1:8+2)
+% figure(2);
+% subplot(3,4,1:2)
+for indexParam = 1:length(df2_local_scale)
+
+ for indexMetabolite = 1:numMetabolites
+ % generate a random number between [-stdLim; stdLim]
+ stdRand = 2 * df2_local_std * df2_local_RandNumbers(indexParam,indexMetabolite) - df2_local_std;
+ switch metabolites{indexMetabolite}
+ case 'tCr(CH2)'
+ creatineStdRand = stdRand;
+ case 'tCr(CH3)'
+ stdRand = creatineStdRand;
+ case 'NAA(CH3)'
+ NaaStdRand = stdRand;
+ case 'NAA(CH2)'
+ stdRand = NaaStdRand;
+ otherwise
+ % nothing to do
+ end
+ current_df2(indexMetabolite) = df2_local_scale(indexParam) * stdRand;
+ end
+ [summedFid, summedFidWithNoise, current_em, currentConcentrationRm] = createSummedSpectrum(...
+ fids, concentrations, conc_std, T2s, T2_std, TE, metabolites, metaboliteFileNames, timePointsSampling, phase_1_f2_mx, ppmMask, ...
+ current_pc0, current_pc1, current_df2, current_gm, current_em_std_factor, conc_std_factor, noiseVector, ...
+ truncPoint, saveData, paramKeyword, indexParam, dwellTime * 1e3, scanFrequency, dataExportPath, water_ppm, scalingFactorRefPeak);
+
+ concentrationsRm(indexParam,:) = currentConcentrationRm;
+ hold on;
+ plot(ppmVector,real(fftshift(fft(summedFid))));
+end
+% reset parameter
+current_df2 = default_df2;
+
+titleStr = '{\boldmath$\omega_{local}$}';
+plotSimulationSetup(titleStr, paramKeyword, saveFigures, dataExportPathBase);
+if saveData
+ save([dataExportPathBase, 'concentrations_simulated_', paramKeyword, '.mat'], 'concentrationsRm', 'metabolites', 'metaboliteFileNames');
+end
+
+%% df2 global - frequency shifts
+paramKeyword = 'df2_global';
+dataExportPath = [dataExportPathBase, paramKeyword, '\'];
+concentrationsRm = zeros(length(df2_global), numMetabolites);
+
+figure(1);
+subplot(5,4,7:8)
+% subplot(2,4,7:8)
+for indexParam = 1:length(df2_global)
+ for indexMetabolite = 1:numMetabolites
+ current_df2(indexMetabolite) = df2_global(indexParam);
+ end
+ [summedFid, summedFidWithNoise, current_em, currentConcentrationRm] = createSummedSpectrum(...
+ fids, concentrations, conc_std, T2s, T2_std, TE, metabolites, metaboliteFileNames, timePointsSampling, phase_1_f2_mx, ppmMask, ...
+ current_pc0, current_pc1, current_df2, current_gm, current_em_std_factor, conc_std_factor, noiseVector, ...
+ truncPoint, saveData, paramKeyword, indexParam, dwellTime * 1e3, scanFrequency, dataExportPath, water_ppm, scalingFactorRefPeak);
+
+ concentrationsRm(indexParam,:) = currentConcentrationRm;
+ hold on;
+ plot(ppmVector,real(fftshift(fft(summedFid))));
+end
+% reset parameter
+current_df2 = default_df2;
+
+titleStr = '$$\omega_{global}$$';
+plotSimulationSetup(titleStr, paramKeyword, saveFigures, dataExportPathBase);
+if saveData
+ save([dataExportPathBase, 'concentrations_simulated_', paramKeyword, '.mat'], 'concentrationsRm', 'metabolites', 'metaboliteFileNames');
+end
+
+%% em - lorentzian components of T2
+paramKeyword = 'em';
+dataExportPath = [dataExportPathBase, paramKeyword, '\'];
+concentrationsRm = zeros(length(df2_global), numMetabolites);
+
+figure(1);
+subplot(5,4,8+3:8+4)
+% figure(2);
+% subplot(3,4,3:4)
+for indexParam = 1:length(df2_global)
+ for indexMetabolite = 1:numMetabolites
+ % generate a random number between [-stdLim; stdLim]
+ stdRand = 2 * em_local_RandNumbers(indexParam,indexMetabolite) - 1;
+ switch metabolites{indexMetabolite}
+ case 'tCr(CH2)'
+ creatineStdRand = stdRand;
+ case 'tCr(CH3)'
+ stdRand = creatineStdRand;
+ case 'NAA(CH3)'
+ NaaStdRand = stdRand;
+ case 'NAA(CH2)'
+ stdRand = NaaStdRand;
+ otherwise
+ % nothing to do
+ end
+ current_em_std_factor(indexMetabolite) = em_local_scale(indexParam) * stdRand;
+ end
+ [summedFid, summedFidWithNoise, current_em, currentConcentrationRm] = createSummedSpectrum(...
+ fids, concentrations, conc_std, T2s, T2_std, TE, metabolites, metaboliteFileNames, timePointsSampling, phase_1_f2_mx, ppmMask, ...
+ current_pc0, current_pc1, current_df2, current_gm, current_em_std_factor, conc_std_factor, noiseVector, ...
+ truncPoint, saveData, paramKeyword, indexParam, dwellTime * 1e3, scanFrequency, dataExportPath, referencePeakPpm, scalingFactorRefPeak);
+
+ concentrationsRm(indexParam,:) = currentConcentrationRm;
+ hold on;
+ plot(ppmVector,real(fftshift(fft(summedFid))));
+end
+% reset parameter
+current_em_std_factor = default_em_std_factor;
+
+titleStr = '{\boldmath$\nu_{e}$}';
+plotSimulationSetup(titleStr, paramKeyword, saveFigures, dataExportPathBase);
+if saveData
+ save([dataExportPathBase, 'concentrations_simulated_', paramKeyword, '.mat'], 'concentrationsRm', 'metabolites', 'metaboliteFileNames');
+end
%% noise - add different noise levels
@@ -338,7 +419,10 @@ paramKeyword = 'noise';
dataExportPath = [dataExportPathBase, paramKeyword, '\'];
concentrationsRm = zeros(length(noiseLevel), numMetabolites);
-figure;
+figure(1);
+subplot(5,4,8+5:8+6)
+% figure(2);
+% subplot(3,4,5:6)
for indexParam = 1:length(noiseLevel)
noiseVector = wgn(1,nTimepoints, noiseLevel(indexParam));
[summedFid, summedFidWithNoise, current_em, currentConcentrationRm] = createSummedSpectrum(...
@@ -353,7 +437,64 @@ end
% reset parameter
noiseVector = wgn(1,nTimepoints, default_noiseLevel);
-save([dataExportPathBase, 'concentrations_simulated_', paramKeyword, '.mat'], 'concentrationsRm', 'metabolites', 'metaboliteFileNames');
+titleStr = '{\boldmath$noise$}';
+plotSimulationSetup(titleStr, paramKeyword, saveFigures, dataExportPathBase);
+if saveData
+ save([dataExportPathBase, 'concentrations_simulated_', paramKeyword, '.mat'], 'concentrationsRm', 'metabolites', 'metaboliteFileNames');
+end
+
+%% noise - add different noise levels
+paramKeyword = 'baseline';
+dataExportPath = [dataExportPathBase, paramKeyword, '\'];
+concentrationsRm = zeros(length(noiseLevel), numMetabolites);
+
+baselinesPath = [dataExportPathBase 'Baselines\'];
+prefixBaseline = 'Baseline_';
+baselines = {'1Flat_drop_H20'; '2Flat'; '3Flat'; '4Flat'; '5Wildish'; '6Wildish'; '7Very_wild';...
+ '8Very_wild'; '9Wild'; '10Wild'; '11Wildish'; '12Wildish'; '13Normal'; '14Lipid_1.3'; '15Lipid_1.3_phased'; '16Zero'};
+
+figure(1);
+subplot(5,4,8+10:8+11)
+% figure(2);
+% subplot(3,4,10:11)
+for indexParam = 1:length(baselines)
+ baselineFileName = strcat(prefixBaseline, baselines{indexParam});
+ [currentBaseline, ~, ~, ~, ~] = ImportLCModelBasis(baselinesPath, baselineFileName, plotBasis, '1H');
+ currentBaseline = currentBaseline(1:length(fids{1}));% will fail if the fids are longer than the baseline
+ [summedFid, summedFidWithNoise, current_em, currentConcentrationRm] = createSummedSpectrum(...
+ fids, concentrations, conc_std, T2s, T2_std, TE, metabolites, metaboliteFileNames, timePointsSampling, phase_1_f2_mx, ppmMask, ...
+ current_pc0, current_pc1, current_df2, current_gm, current_em_std_factor, conc_std_factor, noiseVector, ...
+ truncPoint, saveData, paramKeyword, indexParam, dwellTime * 1e3, scanFrequency, dataExportPath, referencePeakPpm, scalingFactorRefPeak, currentBaseline);
+ concentrationsRm(indexParam,:) = currentConcentrationRm;
+ hold on;
+ plot(ppmVector,real(fftshift(fft(summedFidWithNoise))));
+end
+titleStr = '{\boldmath$baseline$}';
+plotSimulationSetup(titleStr, paramKeyword, saveFigures, dataExportPathBase);
+if saveData
+ save([dataExportPathBase, 'concentrations_simulated_', paramKeyword, '.mat'], 'concentrationsRm', 'metabolites', 'metaboliteFileNames');
+end
end
+function plotSimulationSetup(titleStr, paramKeyword, saveFigures, dataExportPathBase)
+FontSize = 12;
+LineWidth = 1.5;
+xlim([0.6, 4.1])
+xlabel('\delta (ppm)')
+ylabel('Signal (arb. u.)')
+set(gca,'xDir','reverse')
+set(gca,'ytick',[]);
+title(['Spectra with ', titleStr, ' variations'], 'Interpreter','latex');
+set(gca,'fontsize',FontSize);
+set(gca,'FontWeight','bold');
+h = findobj(gca,'Type','line');
+for plots = h
+ set(plots,'LineWidth',LineWidth)
+end
+if saveFigures
+ fileNameFull = [dataExportPathBase, 'Plots\Simulations_', paramKeyword];
+ print([fileNameFull, '.tif'],'-dtiff','-r600');
+ savefig(gcf, [fileNameFull, '.fig'],'compact');
+end
+end
diff --git a/createTestData/createSummedSpectrum.m b/createTestData/createSummedSpectrum.m
index daad3df44487fc5165a1757074d7a816240d8266..58bda11a3c7f8be6dbb15e9fb53c3a071840c137 100644
--- a/createTestData/createSummedSpectrum.m
+++ b/createTestData/createSummedSpectrum.m
@@ -1,17 +1,30 @@
function [summedFid, summedFidWithNoise, current_em, currentConcentrationRm] = createSummedSpectrum( ...
fids, concentrations, conc_std, T2s, T2_std, TE, metabolites, metaboliteFileNames, shift_t2_mx, phase_1_f2_mx, ppmMask, ...
current_pc0, current_pc1, current_df2, current_gm, current_em_std_factor, conc_std_factor, noiseVector, ...
- truncPoint, saveData, paramKeyWord, indexParam, dwellTimeMs, scanFrequency, dataExportPath, referencePeakPpm, scalingFactorRefPeak)
+ truncPoint, saveData, paramKeyWord, indexParam, dwellTimeMs, scanFrequency, dataExportPath, referencePeakPpm, scalingFactorRefPeak, baseline)
+
+if ~exist('baseline','var')
+ baseline = zeros(size(fids{1}));
+end
summedFid = zeros(size(fids{1}));
current_em = size(1,length(metabolites));
currentConcentrationRm = size(1,length(metabolites));
for indexMetabolite = 1:length(metabolites)
- current_T2 = T2s(indexMetabolite) + current_em_std_factor * T2_std(indexMetabolite);%in ms
+ current_T2 = T2s(indexMetabolite) + current_em_std_factor(indexMetabolite) * T2_std(indexMetabolite);%in ms
if strcmp(metabolites(indexMetabolite),'MMB')
current_em(indexMetabolite) = 1;
+ %the Gaussian for the acquired MMB should be smaller than the one for
+ %metabolites, since it was already measured with the inherent
+ %micro- and macro-susceptibility. It should however not be negative!
+ if current_gm - 8 > 0
+ gm = current_gm - 8;
+ else
+ gm = 0;
+ end
else
current_em(indexMetabolite) = 1 / (pi * current_T2 * 1e-3);%from ms to s and then Hz
+ gm = current_gm;
end
%----- precalculate coefficients for the corrections and filters -----%
% zero order phase correction
@@ -32,7 +45,7 @@ for indexMetabolite = 1:length(metabolites)
% gauss filter
% calculate the gauss filter coefficients
- gauss_filter_coeff1 = current_gm*pi;
+ gauss_filter_coeff1 = gm*pi;
gauss_filter_coeff2 = -(4*log(2));
gauss_filter_coeff = gauss_filter_coeff1 ^2 /gauss_filter_coeff2;
%--------------- end of coefficient precalculations ------------------%
@@ -84,7 +97,14 @@ for indexMetabolite = 1:length(metabolites)
end
-summedFidWithNoise = summedFid + noiseVector;
+% the baselines were scaled down to the maximal peak being 1, hence we need
+% to rescale the baseline; Use the NAA peak (cheating hard coded points!)
+spectrum = fftshift(fft(summedFid));
+% We use abs because of already added phase
+maxValueSpectrum = max(abs(spectrum(1400:1600)));
+baselineScaled = baseline * maxValueSpectrum;
+summedFidWithNoise = summedFid + noiseVector + baselineScaled;
+% figure; plot(real(fftshift(fft(summedFid)))); hold on; plot(real(fftshift(fft(baseline*maxValueSpectrum))))
if saveData
% export the spectra but also the used concentrations and all parameters
@@ -93,13 +113,13 @@ if saveData
ExportLCModelBasis(summedFidWithNoise, dwellTimeMs, scanFrequency, dataExportPath, fileName, fileName, 'No', ...
true, referencePeakPpm, scalingFactorRefPeak, 'No', TE*1e3, 'sLASER');
save([dataExportPath, fileName, '.mat'], 'summedFidWithNoise', 'current_em', 'currentConcentrationRm', ...
- 'current_pc0', 'current_pc1', 'current_df2', 'current_gm', 'current_em_std_factor', 'conc_std_factor');
+ 'current_pc0', 'current_pc1', 'current_df2', 'current_gm', 'current_em_std_factor', 'conc_std_factor', 'baselineScaled');
% export truncated data
summedFidWithNoise(:, truncPoint:end)=0;
fileNameTrunc = ['Simulated_', paramKeyWord, '_', num2str(indexParam) '_truncOn'];
ExportLCModelBasis(summedFidWithNoise, dwellTimeMs, scanFrequency, dataExportPath, fileNameTrunc, fileNameTrunc, 'No', ...
true, referencePeakPpm, scalingFactorRefPeak, 'No', TE*1e3, 'sLASER');
save([dataExportPath, fileName, '.mat'], 'summedFidWithNoise', 'current_em', 'currentConcentrationRm', ...
- 'current_pc0', 'current_pc1', 'current_df2', 'current_gm', 'current_em_std_factor', 'conc_std_factor');
+ 'current_pc0', 'current_pc1', 'current_df2', 'current_gm', 'current_em_std_factor', 'conc_std_factor', 'baselineScaled');
end
end
\ No newline at end of file
diff --git a/createTestData/evaluateProFitFittingParameters.m b/createTestData/evaluateProFitFittingParameters.m
new file mode 100644
index 0000000000000000000000000000000000000000..df93d774d7475cf6d3e073d9bcece80449c8cb27
--- /dev/null
+++ b/createTestData/evaluateProFitFittingParameters.m
@@ -0,0 +1,89 @@
+function evaluateProFitFittingParameters()
+
+folderName = 'final_simulations';
+exportFolder = {'11 Simulations'};
+pathNameExport = 'ProFit test data';
+pathBaseExportFiles = pathToDataFolder(pathNameExport, exportFolder);
+% pathBaseExportFiles = pathBaseExportFiles(1:end-1);
+% pathBaseExportFiles = [pathBaseExportFiles ' - R3\'];
+dataExportPathBase = strcat(pathBaseExportFiles, exportFolder{1}, '\');
+truncSuffix = '_truncOn';
+folderFigures = [pathBaseExportFiles 'Output\' folderName, truncSuffix, '\'];
+mkdir(folderFigures)
+
+folders = {'conc', 'df2', 'pc1', 'pc0', 'gauss', 'conc2', 'conc3', 'noise'};
+folders = {'df2', 'pc1', 'pc0', 'gauss'};
+folders = {'df2_global', 'df2_local', 'pc1', 'pc0', 'gauss', 'em', 'noise', 'baseline'};
+folders = {'pc0', 'pc1', 'gauss', 'df2_global', 'df2_local', ...
+ 'em', 'noise', 'baseline'};
+xAxisLabels = {'$$\varphi_0$$', '$$\varphi_1$$', '$$\nu_g$$', '$$\omega_{global}$$', '{\boldmath$\omega_{local}$}', ...
+ '{\boldmath$\nu_{e}$}', '{\boldmath$noise$}', '{\boldmath$baseline$}'};
+legendLabels = {'\varphi_0 :\hspace{3em}', '\varphi_1 :\hspace{3.em}', '\nu_g :\hspace{3.em}', '\omega_{global} :\hspace{1.5em}', '${\boldmath$\omega_{local}$}$:\hspace{1.7em}', ...
+ '${\boldmath$\nu_{e}$}$:\hspace{3.5em}', '${\boldmath$noise$}$:\hspace{1.5em}', '${\boldmath$baseline$}$:'};
+
+parameters = {'pc0', 'pc12', 'gm', 'df2', ...
+ 'em', 'conc', 'T2'};
+titleLabels = {'\Delta\varphi_0', '\Delta\varphi_1', '\Delta\nu_g', '${\boldmath$\overline{\mid\Delta\omega\mid}$}$', ...
+ '${\boldmath$\overline{\mid\Delta\nu_{e}\mid}$}$', '${\boldmath$\overline{\mid\Delta c\mid}$}$', '${\boldmath$\overline{\mid\Delta T_{2}\mid}$}$'};
+units = { ' (degrees)', ' (degrees/ppm)', ' (Hz)', ' (Hz)',...
+ ' (Hz)', ' (mmol/kg)', ' (ms)'};
+% titleOffset = {'\quad variations:\quad\quad','\quad variations:\quad', '\quad variations:\quad\quad\quad', '\quad variations:\quad\quad',...
+% '\quad variations:\quad\quad', '\quad variations:\quad', '\quad variations:\quad\quad'};
+titleOffset = {'\quad variations:\quad','\quad variations:\,\,', '\quad variations:\quad\quad', '\quad variations:\quad',...
+ '\quad variations:\quad', '\quad variations:\,\,', '\quad variations:\quad'};
+% parameters = {'conc'};
+
+useSubPlots = true;
+if useSubPlots
+ numParam = length(parameters)-1;
+ figure;
+else
+ numParam = length(parameters);
+end
+for iParam = 1: numParam
+ legendLabels_ = {};
+ unitLabel = [titleLabels{iParam}, units{iParam}];
+ for iFolder = 1:length(folders)
+ load([dataExportPathBase, folders{iFolder}, '\Diff_Summaries', truncSuffix, '_no_BL_df3.mat'], 'diff_conc_mat', 'diff_em_mat', 'diff_gm_mat', ...
+ 'diff_pc0_mat', 'diff_df2_mat', 'diff_pc12_mat', 'diff_T2_mat');
+ size1 = size(diff_conc_mat, 1);
+ size2 = size(diff_conc_mat, 2);
+ % think about these more
+ diff_conc_mean = mean(mean(abs(diff_conc_mat)));
+ diff_conc_std = std(abs(diff_conc_mat));
+
+ eval(['diff_mat = diff_', parameters{iParam}, '_mat;']);
+
+ diff_mean = mean(mean(abs(diff_mat), 'omitnan'));
+ diff_std = std(mean(abs(diff_mat), 'omitnan'));
+% numberOfNaNs = sum(sum(isnan(diff_mat)))
+% numberOfNaNsV = sum((isnan(diff_mat)),2)'
+
+ if useSubPlots
+ subplot(3,2,iParam)
+ else
+ figure(iParam+10);
+ end
+ hold on
+ if strcmp(parameters{iParam},'em') || strcmp(parameters{iParam},'conc') || ...
+ strcmp(parameters{iParam},'df2') || strcmp(parameters{iParam},'T2')
+ scatter(zeros(1,size2)+iFolder, mean(abs(diff_mat)));
+ else
+ scatter(zeros(1,size2)+iFolder, mean(diff_mat));
+ end
+ title(['$$', titleLabels{iParam}, '$$'],'Interpreter','latex');
+ legendLabels_{iFolder}= ['$$' legendLabels{iFolder}, num2str(diff_mean,'%.2f'), ' \pm ', num2str(diff_std,'%.2f'), '$$'];
+ lgd = legend(legendLabels_,'Interpreter','latex','Location','northwest');
+
+ title(lgd,{'$$Spectra\,\,with\,\,induced$$',['$$', titleOffset{iParam}, unitLabel,'$$']},'FontSize',8);
+ end
+ xlim([0, length(folders)+1]);
+ xticks(1:length(folders));
+ xticklabels(xAxisLabels);
+ xlabel('Simulations')
+ set(gca,'YAxisLocation','right')
+ ylabel(['$$', unitLabel, '$$'],'Interpreter','latex');
+ set(gca,'TickLabelInterpreter','latex')
+ set(gca,'XTickLabelRotation',60)
+ savefig([folderFigures, parameters{iParam}])
+end
\ No newline at end of file
diff --git a/createTestData/fittingLCModelWithTransfer.m b/createTestData/fittingLCModelWithTransfer.m
index b3040c9eb6e4e326be6292dab472df4078819183..d9a3a4b030d57c3f4817dcb3a3f9fcd5a737a436 100644
--- a/createTestData/fittingLCModelWithTransfer.m
+++ b/createTestData/fittingLCModelWithTransfer.m
@@ -1,15 +1,23 @@
function fittingLCModelWithTransfer(LCModelCallerInstance, localFilePath, filenameData, dataPath, ...
- filenameWater, waterPath, currentTEString, copyFiles)
+ filenameWater, waterPath, currentTEString, copyFiles, fitWater)
+if ~exist('fitWater','var')
+ fitWater = false;
+end
+
extensionTable = '.table';
extensionCoord = '.coord';
defaultTE = 'TE24';
-defaultLCModelUser = 'tborbath@mpi.localnet';
+defaultLCModelUser = 'tborbath';
defaultSpectraName = 'XXXX';
defaultWaterRefName = 'YYYY';
controlFilesBase = 'fitsettings_';
-controlFilesBaseSuffix = '_Metabolite.control';
+if fitWater
+ controlFilesBaseSuffix = '_MC_Water.control';
+else %normal case
+ controlFilesBaseSuffix = '_Metabolite.control';
+end
%% file paths setup
controlFilesPathLocal = [localFilePath, 'LCModelConfig/'];
diff --git a/createTestData/fitting_all_test_data_profit.m b/createTestData/fitting_all_test_data_profit.m
index 95105f731fb7b1b3cc23262d677e80d0f7fc1d49..f6e58f48bab1f2ca8d3db32b9526663a04e0affd 100644
--- a/createTestData/fitting_all_test_data_profit.m
+++ b/createTestData/fitting_all_test_data_profit.m
@@ -6,7 +6,7 @@ use_water_references = true;
%TODO change
TR = 6000;%ms
-reconOption = 4;
+reconOption = 2;
truncOn = true;
exportFolders = {'0 Water References',...
@@ -47,20 +47,21 @@ else
end
subjects = { ...
- '1658' ...
- '1717' ...
- '2017' ...
- '3373' ...
- '3490' ...
- '5771' ...
- '6249' ...
- '6971' ...
- '7338' ...
- '7782' ...
- '9810' ...
+% 'Summed' ...
+ 'Subj_1' ...
+ 'Subj_2' ...
+ 'Subj_3' ...
+ 'Subj_4' ...
+ 'Subj_5' ...
+ 'Subj_6' ...
+ 'Subj_7' ...
+ 'Subj_8' ...
+ 'Subj_9' ...
+ 'Subj_10' ...
+ 'Subj_11' ...
};
-TEs = [24; 32; 40; 52; 60];
+TEs = [24; ];%32; 40; 52; 60];
numberOfSubjects = length(subjects);
waterExportPath = cell(1,numberOfSubjects);
@@ -95,6 +96,12 @@ for indexSubj = 1:numberOfSubjects
% load([filenameWater '.mat'], 'aWater', 'maxWaterPeak');
concentrations = cell(numberOfTEs,length(namingSuffixesAve));
+ concentrations_H2O = cell(numberOfTEs,length(namingSuffixesAve));
+ concentrations_MC_H2O = cell(numberOfTEs,length(namingSuffixesAve));
+ if ~fitLCModel
+ FQNs = cell(numberOfTEs,length(namingSuffixesAve));
+ FQNs2 = cell(numberOfTEs,length(namingSuffixesAve));
+ end
%% reconstruct data
for indexTE = 1:1%numberOfTEs
for indexAverageDelete = 1: length(namingSuffixesAve)
@@ -106,6 +113,10 @@ for indexSubj = 1:numberOfSubjects
filenameData = [ subjects{indexSubj}, '_', TE_string namingSuffixAve namingSuffixCoil truncSuffix];
dataExportPathTE = [dataExportPath{indexSubj}, '\\', TE_string, '\\'];
+ load([dataExportPathTE, filenameData, '.mat'],'a')
+ MC_mix =2;
+ filenameData_MC_water = [filenameData, '_MC_water'];
+ a.ExportLcmRaw(dataExportPathTE, filenameData_MC_water, false, 'No', -4.7, 0.05, MC_mix);
if fitLCModel
if use_water_references
try
@@ -114,6 +125,12 @@ for indexSubj = 1:numberOfSubjects
movefile([outputFilesPathLocal filenameData '.*'], dataExportPathTE);
concentrations{indexTE,indexAverageDelete, indexCoilDelete} = ...
importConcentrationLCModelTable([filenameData '.table'],dataExportPathTE, TE_string, 'Met moiety');
+ %MC_water
+% fittingLCModelWithTransfer(LCModelCallerInstance, pathBaseExportFiles, ...
+% filenameData_MC_water, dataExportPathTE, filenameWater, waterPath, TE_string, copyFiles, true);
+% movefile([outputFilesPathLocal filenameData_MC_water '.*'], dataExportPathTE);
+% concentrations_MC_H2O{indexTE,indexAverageDelete, indexCoilDelete} = ...
+% importConcentrationLCModelTable([filenameData_MC_water '.table'],dataExportPathTE, TE_string, 'Met moiety');
catch
concentrations{indexTE,indexAverageDelete, indexCoilDelete} = {};
continue;
@@ -122,14 +139,20 @@ for indexSubj = 1:numberOfSubjects
fittingLCModelWithTransfer(LCModelCallerInstance, pathBaseExportFiles, ...
filenameData, dataExportPathTE, [], [], TE_string, copyFiles);
end
- plot_All_Fit_Metabolites([filenameData, '.coord'],dataExportPathTE, 'Met moiety', true);
+ plot_All_Fit_Metabolites([filenameData, '.coord'],dataExportPathTE, 'Met moiety', true, true);
else %TODO
if use_water_references
fittingProFit(filenameData, dataExportPathTE, filenameWater, waterPath, TEs(indexTE), TR, dataExportPathTE);
+ fitting_MC_water(filenameData_MC_water, dataExportPathTE, TEs(indexTE), TR, dataExportPathTE)
else
fittingProFit(filenameData, dataExportPathTE, [], [], TEs(indexTE), TR, dataExportPathTE);
end
- [concentrations{indexTE,indexAverageDelete, indexCoilDelete}, activeMetabolites] = plot_ProFit_Metabolites_Fit([filenameData, '_profit.mat'],dataExportPathTE, 'Met', true);
+ [concentrations{indexTE,indexAverageDelete, indexCoilDelete}, activeMetabolites, FQNs{indexTE,indexAverageDelete, indexCoilDelete}, FQNs2{indexTE,indexAverageDelete, indexCoilDelete}] = ...
+ plot_ProFit_Metabolites_Fit([filenameData, '_profit.mat'],dataExportPathTE, 'Met', true);
+ load([dataExportPathTE, filenameData, '_profit_H2O.mat'],'concH2O');
+ concentrations_H2O{indexTE,indexAverageDelete, indexCoilDelete}=concH2O;
+ load([dataExportPathTE, filenameData_MC_water, '_profit.mat'],'concH2O');
+ concentrations_MC_H2O{indexTE,indexAverageDelete, indexCoilDelete}=concH2O;
end
close all
end
@@ -137,8 +160,11 @@ for indexSubj = 1:numberOfSubjects
end
if fitLCModel
save([dataExportPath{indexSubj}, 'concentrations' truncSuffix '.mat'], 'concentrations');
+ save([dataExportPath{indexSubj}, 'concentrations', truncSuffix '_MC_H2O.mat'], 'concentrations_MC_H2O');
else
- save([dataExportPath{indexSubj}, 'concentrations', truncSuffix '_profit.mat'], 'concentrations', 'activeMetabolites');
+ save([dataExportPath{indexSubj}, 'concentrations', truncSuffix '_profit.mat'], 'concentrations', 'activeMetabolites', 'FQNs', 'FQNs2');
+ save([dataExportPath{indexSubj}, 'concentrations', truncSuffix '_H2O_profit.mat'], 'concentrations_H2O');
+ save([dataExportPath{indexSubj}, 'concentrations', truncSuffix '_MC_H2O_profit.mat'], 'concentrations_MC_H2O');
end
end
diff --git a/createTestData/fitting_simulated_test_data_profit.m b/createTestData/fitting_simulated_test_data_profit.m
index 0fce67f59e065c81d9973e7c5de7d577214fcc9b..f02bd6ebe7da14ede2b2823edbe8455e93623838 100644
--- a/createTestData/fitting_simulated_test_data_profit.m
+++ b/createTestData/fitting_simulated_test_data_profit.m
@@ -1,6 +1,7 @@
-function fitting_simulated_test_data_profit()
-
-fitLCModel = false; %false fits profit
+function fitting_simulated_test_data_profit(fitLCModel)
+if ~exist('fitLCModel','var')
+ fitLCModel = false; %false fits profit
+end
%TODO change
TR = 6000;%ms
@@ -12,12 +13,6 @@ pathNameExport = 'ProFit test data';
pathBaseExportFiles = pathToDataFolder(pathNameExport, exportFolder);
dataExportPathBase = strcat(pathBaseExportFiles, exportFolder{1}, '\');
-if truncOn == false
- truncSuffix = '_truncOff';
-else
- truncSuffix = '_truncOn';
-end
-
TE = 24;
if fitLCModel
@@ -36,120 +31,149 @@ else
end
%% do the actual fitting
-numberConcPermutations = 100;
-paramKeyword = 'conc';
-truncSuffix = '_truncOn';
-fileNameBase = ['Simulated_', paramKeyword, '_'];
-actualFitting(numberConcPermutations, paramKeyword, dataExportPathBase, TE, TR, fileNameBase, ...
- truncSuffix, fitLCModel, LCModelCallerInstance, pathBaseExportFiles, copyFiles, outputFilesPathLocal);
-%
-numberConcPermutations = 100;
-paramKeyword = 'conc';
-truncSuffix = '_truncOff';
-fileNameBase = ['Simulated_', paramKeyword, '_'];
-actualFitting(numberConcPermutations, paramKeyword, dataExportPathBase, TE, TR, fileNameBase, ...
- truncSuffix, fitLCModel, LCModelCallerInstance, pathBaseExportFiles, copyFiles, outputFilesPathLocal);
-
-numberConcPermutations = 13;
-paramKeyword = 'df2';
-truncSuffix = '_truncOn';
-fileNameBase = ['Simulated_', paramKeyword, '_'];
-actualFitting(numberConcPermutations, paramKeyword, dataExportPathBase, TE, TR, fileNameBase, ...
- truncSuffix, fitLCModel, LCModelCallerInstance, pathBaseExportFiles, copyFiles, outputFilesPathLocal);
-%
-numberConcPermutations = 13;
-paramKeyword = 'df2';
-truncSuffix = '_truncOff';
-fileNameBase = ['Simulated_', paramKeyword, '_'];
-actualFitting(numberConcPermutations, paramKeyword, dataExportPathBase, TE, TR, fileNameBase, ...
- truncSuffix, fitLCModel, LCModelCallerInstance, pathBaseExportFiles, copyFiles, outputFilesPathLocal);
-
-numberConcPermutations = 7;
-paramKeyword = 'pc1';
-truncSuffix = '_truncOn';
-fileNameBase = ['Simulated_', paramKeyword, '_'];
-actualFitting(numberConcPermutations, paramKeyword, dataExportPathBase, TE, TR, fileNameBase, ...
- truncSuffix, fitLCModel, LCModelCallerInstance, pathBaseExportFiles, copyFiles, outputFilesPathLocal);
-%
-numberConcPermutations = 7;
-paramKeyword = 'pc1';
-truncSuffix = '_truncOff';
-fileNameBase = ['Simulated_', paramKeyword, '_'];
-actualFitting(numberConcPermutations, paramKeyword, dataExportPathBase, TE, TR, fileNameBase, ...
- truncSuffix, fitLCModel, LCModelCallerInstance, pathBaseExportFiles, copyFiles, outputFilesPathLocal);
-
-numberConcPermutations = 9;
-paramKeyword = 'pc0';
-truncSuffix = '_truncOn';
-fileNameBase = ['Simulated_', paramKeyword, '_'];
-actualFitting(numberConcPermutations, paramKeyword, dataExportPathBase, TE, TR, fileNameBase, ...
- truncSuffix, fitLCModel, LCModelCallerInstance, pathBaseExportFiles, copyFiles, outputFilesPathLocal);
-%
-numberConcPermutations = 9;
-paramKeyword = 'pc0';
-truncSuffix = '_truncOff';
-fileNameBase = ['Simulated_', paramKeyword, '_'];
-actualFitting(numberConcPermutations, paramKeyword, dataExportPathBase, TE, TR, fileNameBase, ...
- truncSuffix, fitLCModel, LCModelCallerInstance, pathBaseExportFiles, copyFiles, outputFilesPathLocal);
-
-numberConcPermutations = 13;
-paramKeyword = 'gauss';
-truncSuffix = '_truncOn';
-fileNameBase = ['Simulated_', paramKeyword, '_'];
-actualFitting(numberConcPermutations, paramKeyword, dataExportPathBase, TE, TR, fileNameBase, ...
- truncSuffix, fitLCModel, LCModelCallerInstance, pathBaseExportFiles, copyFiles, outputFilesPathLocal);
-%
-numberConcPermutations = 13;
-paramKeyword = 'gauss';
-truncSuffix = '_truncOff';
-fileNameBase = ['Simulated_', paramKeyword, '_'];
-actualFitting(numberConcPermutations, paramKeyword, dataExportPathBase, TE, TR, fileNameBase, ...
- truncSuffix, fitLCModel, LCModelCallerInstance, pathBaseExportFiles, copyFiles, outputFilesPathLocal);
-
-% do the actual fitting
-numberConcPermutations = 50;
-paramKeyword = 'conc2';
-truncSuffix = '_truncOn';
-fileNameBase = ['Simulated_', paramKeyword, '_'];
-actualFitting(numberConcPermutations, paramKeyword, dataExportPathBase, TE, TR, fileNameBase, ...
- truncSuffix, fitLCModel, LCModelCallerInstance, pathBaseExportFiles, copyFiles, outputFilesPathLocal);
-
-numberConcPermutations = 50;
-paramKeyword = 'conc2';
-truncSuffix = '_truncOff';
-fileNameBase = ['Simulated_', paramKeyword, '_'];
-actualFitting(numberConcPermutations, paramKeyword, dataExportPathBase, TE, TR, fileNameBase, ...
- truncSuffix, fitLCModel, LCModelCallerInstance, pathBaseExportFiles, copyFiles, outputFilesPathLocal);
-
-numberConcPermutations = 50;
-paramKeyword = 'conc3';
-truncSuffix = '_truncOn';
-fileNameBase = ['Simulated_', paramKeyword, '_'];
-actualFitting(numberConcPermutations, paramKeyword, dataExportPathBase, TE, TR, fileNameBase, ...
- truncSuffix, fitLCModel, LCModelCallerInstance, pathBaseExportFiles, copyFiles, outputFilesPathLocal);
-%
-numberConcPermutations = 50;
-paramKeyword = 'conc3';
-truncSuffix = '_truncOff';
-fileNameBase = ['Simulated_', paramKeyword, '_'];
-actualFitting(numberConcPermutations, paramKeyword, dataExportPathBase, TE, TR, fileNameBase, ...
- truncSuffix, fitLCModel, LCModelCallerInstance, pathBaseExportFiles, copyFiles, outputFilesPathLocal);
-
-%
-numberConcPermutations = 25;
-paramKeyword = 'noise';
-truncSuffix = '_truncOn';
-fileNameBase = ['Simulated_', paramKeyword, '_'];
-actualFitting(numberConcPermutations, paramKeyword, dataExportPathBase, TE, TR, fileNameBase, ...
- truncSuffix, fitLCModel, LCModelCallerInstance, pathBaseExportFiles, copyFiles, outputFilesPathLocal);
-
-numberConcPermutations = 25;
-paramKeyword = 'noise';
-truncSuffix = '_truncOff';
-fileNameBase = ['Simulated_', paramKeyword, '_'];
-actualFitting(numberConcPermutations, paramKeyword, dataExportPathBase, TE, TR, fileNameBase, ...
- truncSuffix, fitLCModel, LCModelCallerInstance, pathBaseExportFiles, copyFiles, outputFilesPathLocal);
+if truncOn
+ numberConcPermutations = 100;
+ paramKeyword = 'conc';
+ truncSuffix = '_truncOn';
+ fileNameBase = ['Simulated_', paramKeyword, '_'];
+ actualFitting(numberConcPermutations, paramKeyword, dataExportPathBase, TE, TR, fileNameBase, ...
+ truncSuffix, fitLCModel, LCModelCallerInstance, pathBaseExportFiles, copyFiles, outputFilesPathLocal);
+else
+ numberConcPermutations = 100;
+ paramKeyword = 'conc';
+ truncSuffix = '_truncOff';
+ fileNameBase = ['Simulated_', paramKeyword, '_'];
+ actualFitting(numberConcPermutations, paramKeyword, dataExportPathBase, TE, TR, fileNameBase, ...
+ truncSuffix, fitLCModel, LCModelCallerInstance, pathBaseExportFiles, copyFiles, outputFilesPathLocal);
+end
+
+if truncOn
+ numberConcPermutations = 15;
+ paramKeyword = 'df2_local';
+ truncSuffix = '_truncOn';
+ fileNameBase = ['Simulated_', paramKeyword, '_'];
+ actualFitting(numberConcPermutations, paramKeyword, dataExportPathBase, TE, TR, fileNameBase, ...
+ truncSuffix, fitLCModel, LCModelCallerInstance, pathBaseExportFiles, copyFiles, outputFilesPathLocal);
+else
+ numberConcPermutations = 15;
+ paramKeyword = 'df2_local';
+ truncSuffix = '_truncOff';
+ fileNameBase = ['Simulated_', paramKeyword, '_'];
+ actualFitting(numberConcPermutations, paramKeyword, dataExportPathBase, TE, TR, fileNameBase, ...
+ truncSuffix, fitLCModel, LCModelCallerInstance, pathBaseExportFiles, copyFiles, outputFilesPathLocal);
+end
+
+if truncOn
+ numberConcPermutations = 15;
+ paramKeyword = 'df2_global';
+ truncSuffix = '_truncOn';
+ fileNameBase = ['Simulated_', paramKeyword, '_'];
+ actualFitting(numberConcPermutations, paramKeyword, dataExportPathBase, TE, TR, fileNameBase, ...
+ truncSuffix, fitLCModel, LCModelCallerInstance, pathBaseExportFiles, copyFiles, outputFilesPathLocal);
+else
+ numberConcPermutations = 15;
+ paramKeyword = 'df2_global';
+ truncSuffix = '_truncOff';
+ fileNameBase = ['Simulated_', paramKeyword, '_'];
+ actualFitting(numberConcPermutations, paramKeyword, dataExportPathBase, TE, TR, fileNameBase, ...
+ truncSuffix, fitLCModel, LCModelCallerInstance, pathBaseExportFiles, copyFiles, outputFilesPathLocal);
+end
+
+if truncOn
+ numberConcPermutations = 15;
+ paramKeyword = 'pc1';
+ truncSuffix = '_truncOn';
+ fileNameBase = ['Simulated_', paramKeyword, '_'];
+ actualFitting(numberConcPermutations, paramKeyword, dataExportPathBase, TE, TR, fileNameBase, ...
+ truncSuffix, fitLCModel, LCModelCallerInstance, pathBaseExportFiles, copyFiles, outputFilesPathLocal);
+else
+ numberConcPermutations = 15;
+ paramKeyword = 'pc1';
+ truncSuffix = '_truncOff';
+ fileNameBase = ['Simulated_', paramKeyword, '_'];
+ actualFitting(numberConcPermutations, paramKeyword, dataExportPathBase, TE, TR, fileNameBase, ...
+ truncSuffix, fitLCModel, LCModelCallerInstance, pathBaseExportFiles, copyFiles, outputFilesPathLocal);
+end
+if truncOn
+ numberConcPermutations = 15;
+ paramKeyword = 'pc0';
+ truncSuffix = '_truncOn';
+ fileNameBase = ['Simulated_', paramKeyword, '_'];
+ actualFitting(numberConcPermutations, paramKeyword, dataExportPathBase, TE, TR, fileNameBase, ...
+ truncSuffix, fitLCModel, LCModelCallerInstance, pathBaseExportFiles, copyFiles, outputFilesPathLocal);
+else
+ numberConcPermutations = 15;
+ paramKeyword = 'pc0';
+ truncSuffix = '_truncOff';
+ fileNameBase = ['Simulated_', paramKeyword, '_'];
+ actualFitting(numberConcPermutations, paramKeyword, dataExportPathBase, TE, TR, fileNameBase, ...
+ truncSuffix, fitLCModel, LCModelCallerInstance, pathBaseExportFiles, copyFiles, outputFilesPathLocal);
+end
+
+if truncOn
+ numberConcPermutations = 15;
+ paramKeyword = 'gauss';
+ truncSuffix = '_truncOn';
+ fileNameBase = ['Simulated_', paramKeyword, '_'];
+ actualFitting(numberConcPermutations, paramKeyword, dataExportPathBase, TE, TR, fileNameBase, ...
+ truncSuffix, fitLCModel, LCModelCallerInstance, pathBaseExportFiles, copyFiles, outputFilesPathLocal);
+else
+ numberConcPermutations = 15;
+ paramKeyword = 'gauss';
+ truncSuffix = '_truncOff';
+ fileNameBase = ['Simulated_', paramKeyword, '_'];
+ actualFitting(numberConcPermutations, paramKeyword, dataExportPathBase, TE, TR, fileNameBase, ...
+ truncSuffix, fitLCModel, LCModelCallerInstance, pathBaseExportFiles, copyFiles, outputFilesPathLocal);
+end
+
+if truncOn
+ numberConcPermutations = 15;
+ paramKeyword = 'em';
+ truncSuffix = '_truncOn';
+ fileNameBase = ['Simulated_', paramKeyword, '_'];
+ actualFitting(numberConcPermutations, paramKeyword, dataExportPathBase, TE, TR, fileNameBase, ...
+ truncSuffix, fitLCModel, LCModelCallerInstance, pathBaseExportFiles, copyFiles, outputFilesPathLocal);
+else
+ numberConcPermutations = 15;
+ paramKeyword = 'em';
+ truncSuffix = '_truncOff';
+ fileNameBase = ['Simulated_', paramKeyword, '_'];
+ actualFitting(numberConcPermutations, paramKeyword, dataExportPathBase, TE, TR, fileNameBase, ...
+ truncSuffix, fitLCModel, LCModelCallerInstance, pathBaseExportFiles, copyFiles, outputFilesPathLocal);
+end
+
+if truncOn
+ numberConcPermutations = 25;
+ paramKeyword = 'noise';
+ truncSuffix = '_truncOn';
+ fileNameBase = ['Simulated_', paramKeyword, '_'];
+ actualFitting(numberConcPermutations, paramKeyword, dataExportPathBase, TE, TR, fileNameBase, ...
+ truncSuffix, fitLCModel, LCModelCallerInstance, pathBaseExportFiles, copyFiles, outputFilesPathLocal);
+else
+ numberConcPermutations = 25;
+ paramKeyword = 'noise';
+ truncSuffix = '_truncOff';
+ fileNameBase = ['Simulated_', paramKeyword, '_'];
+ actualFitting(numberConcPermutations, paramKeyword, dataExportPathBase, TE, TR, fileNameBase, ...
+ truncSuffix, fitLCModel, LCModelCallerInstance, pathBaseExportFiles, copyFiles, outputFilesPathLocal);
+end
+
+if truncOn
+ numberConcPermutations = 16;
+ paramKeyword = 'baseline';
+ truncSuffix = '_truncOn';
+ fileNameBase = ['Simulated_', paramKeyword, '_'];
+ actualFitting(numberConcPermutations, paramKeyword, dataExportPathBase, TE, TR, fileNameBase, ...
+ truncSuffix, fitLCModel, LCModelCallerInstance, pathBaseExportFiles, copyFiles, outputFilesPathLocal);
+else
+ numberConcPermutations = 16;
+ paramKeyword = 'baseline';
+ truncSuffix = '_truncOff';
+ fileNameBase = ['Simulated_', paramKeyword, '_'];
+ actualFitting(numberConcPermutations, paramKeyword, dataExportPathBase, TE, TR, fileNameBase, ...
+ truncSuffix, fitLCModel, LCModelCallerInstance, pathBaseExportFiles, copyFiles, outputFilesPathLocal);
+end
end
function actualFitting(numberConcPermutations, paramKeyword, dataExportPathBase, TE, TR, fileNameBase, ...
@@ -157,33 +181,55 @@ function actualFitting(numberConcPermutations, paramKeyword, dataExportPathBase,
%% do the actual fitting
dataExportPath = [dataExportPathBase, paramKeyword, '/'];
concentrations = cell(1,numberConcPermutations);
-for indexConc = 1:numberConcPermutations
+if ~fitLCModel
+ diff_conc = cell(1,numberConcPermutations);
+ diff_em = cell(1,numberConcPermutations);
+ diff_gm = cell(1,numberConcPermutations);
+ diff_pc0 = cell(1,numberConcPermutations);
+ diff_df2 = cell(1,numberConcPermutations);
+ diff_pc12 = cell(1,numberConcPermutations);
+ diff_T2 = cell(1,numberConcPermutations);
+end
+for index = 1:numberConcPermutations
%% reconstruct data
TE_string = ['TE', num2str(TE)];
- filenameData = [fileNameBase, num2str(indexConc), truncSuffix];
+ filenameData = [fileNameBase, num2str(index), truncSuffix];
if fitLCModel
fittingLCModelWithTransfer(LCModelCallerInstance, pathBaseExportFiles, ...
filenameData, dataExportPath, '', '', TE_string, copyFiles);
movefile([outputFilesPathLocal filenameData '.*'], dataExportPath);
- concentrations{indexConc} = ...
+ concentrations{index} = ...
importConcentrationLCModelTable([filenameData '.table'],dataExportPath, TE_string, 'Met moiety');
close all;
- plot_All_Fit_Metabolites([filenameData, '.coord'],dataExportPath, 'Met moiety', true);
+ plot_All_Fit_Metabolites([filenameData, '.coord'],dataExportPath, 'Met moiety', true, false);
else
- fittingProFit(filenameData, dataExportPath, '', '', TE, TR, dataExportPath);
-% plot_ProFit_Metabolites_Fit([filenameData, '_profit.mat'],dataExportPath, 'Met moiety', true);
- [concentrations{indexConc}, activeMetabolites] = plot_ProFit_Metabolites_Fit([filenameData, '_profit.mat'],dataExportPath, 'Met', true);
+ refFreqPpm = 0;
+ fittingProFit(filenameData, dataExportPath, '', '', TE, TR, dataExportPath,refFreqPpm);
+ [concentrations{index}, activeMetabolites] = plot_ProFit_Metabolites_Fit([filenameData, '_profit.mat'],dataExportPath, 'Met', true, false);
+ [diff_conc{index}, diff_em{index}, diff_gm{index}, diff_pc0{index}, diff_df2{index}, diff_pc12{index}, diff_T2{index}] = ...
+ compareFitInput_Output(dataExportPath, filenameData, 3);
+% close all;
end
end
+
if fitLCModel
save([dataExportPathBase, 'concentrations_', paramKeyword, truncSuffix '.mat'], 'concentrations');
else
save([dataExportPathBase, 'concentrations_', paramKeyword, truncSuffix '_profit.mat'], 'concentrations', 'activeMetabolites');
+ diff_conc_mat = reshape(cell2mat(diff_conc), length(diff_conc{1}), numberConcPermutations);
+ diff_em_mat = reshape(cell2mat(diff_em), length(diff_em{1}), numberConcPermutations);
+ diff_gm_mat = reshape(cell2mat(diff_gm), length(diff_gm{1}), numberConcPermutations);
+ diff_pc0_mat = reshape(cell2mat(diff_pc0), length(diff_pc0{1}), numberConcPermutations);
+ diff_df2_mat = reshape(cell2mat(diff_df2), length(diff_df2{1}), numberConcPermutations);
+ diff_pc12_mat = reshape(cell2mat(diff_pc12), length(diff_pc12{1}), numberConcPermutations);
+ diff_T2_mat = reshape(cell2mat(diff_T2), length(diff_T2{1}), numberConcPermutations);
+ save([dataExportPathBase, paramKeyword, '\Diff_Summaries', truncSuffix, '_no_BL_df3.mat'], 'diff_conc_mat', 'diff_em_mat', 'diff_gm_mat', ...
+ 'diff_pc0_mat', 'diff_df2_mat', 'diff_pc12_mat', 'diff_T2_mat');
end
close all
diff --git a/createTestData/getLCModelBaseline.m b/createTestData/getLCModelBaseline.m
new file mode 100644
index 0000000000000000000000000000000000000000..a9fd17ad83bce3a338dff0a7ff6d7723e75aeede
--- /dev/null
+++ b/createTestData/getLCModelBaseline.m
@@ -0,0 +1,135 @@
+function [baselineFid] = getLCModelBaseline()
+
+exportFolders = {'1 Normal recon', '5 Water Supp Off', '8 Rescale Water Supp Off'};
+
+subjects = {{1658; 2017; 5771; 6971;};...
+ {3373; 7338;}; ...
+ {3490; 6249; 1717; 3373; 7338; 9810; 7782};};
+Labels = {{'Flat_drop_H20'; 'Flat'; 'Flat'; 'Flat';};...
+ {'Wildish'; 'Wildish'}; ...
+ {'Very_wild';'Very_wild';'Wild'; 'Wild';'Wildish'; 'Wildish'; 'Normal'};};
+pathNameExport = 'ProFit test data';
+pathBaseExportFiles = pathToDataFolder(pathNameExport, exportFolders);
+pathBaselineExport = strcat(pathBaseExportFiles, '11 Simulations\Baselines\');
+pathBaseExportFiles(end:end+1) = '_\';
+dataPathMatFiles = strcat(pathBaseExportFiles, exportFolders{1}, '\');
+
+extensionCoord = '.coord';
+extensionMat = '.mat';
+phase90 = -90 * pi/180;
+zeroFillFactor = 2;
+
+runningIndex = 0;
+for indexFolder = 1:3
+ LCModelOutputPathBase = strcat(pathBaseExportFiles, exportFolders{indexFolder}, '\');
+ for indexSubj = 1 : length(subjects{indexFolder})
+ runningIndex = runningIndex + 1;
+ currentSubject = num2str(subjects{indexFolder}{indexSubj});
+ LCModelOutputPath = strcat(LCModelOutputPathBase, currentSubject, '\TE24\');
+
+ fileName = [currentSubject '_TE24'];
+
+ LCModelTableFitsCoord = strcat(fileName, extensionCoord);
+ reconstructedSpectra = strcat(dataPathMatFiles, currentSubject, '\TE24\', fileName, extensionMat);
+
+
+ load(reconstructedSpectra, 'a');
+ currentLCModelCoordFit = LCModelTableFitsCoord;
+ [nOfPoints, ppmVector_lcm, phasedData_lcm, fitData, baselineData_lcm, residualData, ...
+ metaboliteNames, metaboliteData, tableConcentrations, ppmStart_lcm, ppmEnd_lcm, ...
+ scanFrequency, frequencyShift, ppmGap, phase0_deg_lcm, phase1_deg_ppm_lcm] = ...
+ extractFits(LCModelOutputPath,currentLCModelCoordFit);
+
+ water_ppm = 4.7;
+
+ % align the two spectra
+ fid = a.Data{1}(:,1,1,1,1,1,1,1,1,1,1,1)';
+
+ samples = length(fid);
+ scanFreq = a.Parameter.Headers.ScanFrequency*1e-6;
+ bandWidth = a.Parameter.Headers.Bandwidth_Hz;
+ frequencyRange_zf = linspace(-bandWidth/2,bandWidth/2, samples * zeroFillFactor);
+ ppm_zf = frequencyRange_zf/scanFreq + water_ppm;
+
+ % max of the LCModel fit
+ maxSpectrum_lcm = max(phasedData_lcm+baselineData_lcm);
+ baselineData_lcm = baselineData_lcm ./ maxSpectrum_lcm;
+
+ c = polyfit([ppmVector_lcm(end-300:end); ppm_zf(ppm_zf<0)'], [baselineData_lcm(end-300:end); 0*(ppm_zf(ppm_zf<0))'],30);
+ baselineData_Low = polyval(c,ppm_zf(ppm_zf<ppmEnd_lcm));
+
+ c = polyfit([ppmVector_lcm(1:300); ppm_zf(ppm_zf>4.7)'], [baselineData_lcm(1:300); 0*(ppm_zf(ppm_zf>4.7))'],30);
+ baselineData_High = polyval(c,ppm_zf(ppm_zf>ppmStart_lcm));
+
+ figure; plot(ppmVector_lcm,baselineData_lcm);
+ hold on; plot(ppm_zf(ppm_zf<ppmEnd_lcm),baselineData_Low)
+ hold on; plot(ppm_zf(ppm_zf>ppmStart_lcm),baselineData_High)
+
+ baselineFullReal = [baselineData_Low(2:end)'; flipud(baselineData_lcm); baselineData_High(1:end-1)'];
+
+ figure; plot(ppm_zf,baselineFullReal);
+
+ baselineFid = ifft(ifftshift(complex(baselineFullReal)));
+ baselineFid(length(baselineFid)/2:end)=0;
+ baselineSpectrumPhased90 = fftshift(fft(baselineFid .* exp(1i*phase90))).*2; %multiply by 2 to account for nulling the half of the FID
+ baselineFullImag = real(baselineSpectrumPhased90);
+ baselineFid = ifft(ifftshift(complex(baselineFullReal, baselineFullImag)));
+
+ aBaseline = a;
+ aBaseline.Data{1} = baselineFid;
+ aBaseline.ExportLcmRaw(pathBaselineExport,['Baseline_', num2str(runningIndex), Labels{indexFolder}{indexSubj}],false);
+ end
+end
+
+%% extract a sample dataset with the new data naming.
+% currentSubject = 'Subj_1';
+% fileName = [currentSubject '_TE24'];
+% reconstructedSpectra = strcat(dataPathMatFiles, currentSubject, '\TE24\', fileName, extensionMat);
+% load(reconstructedSpectra, 'a');
+%% single lipid peak 1.3ppm
+runningIndex = runningIndex + 1; %would be 14
+
+fid = a.Data{1}(:,1,1,1,1,1,1,1,1,1);
+ppmVector = a.getPpmVector();
+time = (0:length(fid) - 1)' * (1/a.Parameter.Headers.Bandwidth_Hz);
+%create peak to fit gradient modulation downfield
+scanFrequency = a.Parameter.Headers.ScanFrequency;
+f = (1.3-4.66) *scanFrequency*1E-6; %Hz
+T2 = 0.2; %s
+singlet = exp(1i*2*pi*f*time).*exp(-time/T2);
+Fgau = 400; %parameter that sets the decay rate
+W = exp(- time.^2*(Fgau)^2);
+singletW = singlet.*W;
+
+maxValue = max(real(fftshift(fft(singletW))));
+singletW = singletW ./ maxValue .* 0.3; %scale to 0.3 of NAA peak later
+
+figure;
+plot(ppmVector, real(fftshift(fft(singletW))));
+xlim([0.6 4.2])
+
+aBaseline = a;
+aBaseline.Data{1} = singletW;
+aBaseline.ExportLcmRaw(pathBaselineExport,['Baseline_', num2str(runningIndex), 'Lipid_1.3'],false);
+
+%% phased single lipid peak 1.3ppm
+runningIndex = runningIndex + 1;
+phasedSingletW = singletW * exp(-pi*1i*90/180);
+
+figure;
+plot(ppmVector, real(fftshift(fft(phasedSingletW))));
+xlim([0.6 4.2])
+
+aBaseline = a;
+aBaseline.Data{1} = phasedSingletW;
+aBaseline.ExportLcmRaw(pathBaselineExport,['Baseline_', num2str(runningIndex), 'Lipid_1.3_phased'],false);
+
+%% zero baseline
+runningIndex = runningIndex + 1;
+zeroBaseline = zeros(size(singletW));
+
+aBaseline = a;
+aBaseline.Data{1} = zeroBaseline;
+aBaseline.ExportLcmRaw(pathBaselineExport,['Baseline_', num2str(runningIndex), 'Zero'],false);
+
+end
\ No newline at end of file
diff --git a/createTestData/plotBaselines_and_fitted_spectra.m b/createTestData/plotBaselines_and_fitted_spectra.m
new file mode 100644
index 0000000000000000000000000000000000000000..3d519c0652607eca535698b46254f40c1b20a026
--- /dev/null
+++ b/createTestData/plotBaselines_and_fitted_spectra.m
@@ -0,0 +1,258 @@
+function plotBaselines_and_fitted_spectra()
+
+%% path to the export of the spectra
+exportFolder = {'11 Simulations'};
+pathNameExport = 'ProFit test data';
+pathBaseExportFiles = pathToDataFolder(pathNameExport, exportFolder);
+pathBaseExportFiles = pathBaseExportFiles(1:end-1);
+pathBaseExportFiles = [pathBaseExportFiles ' - R3\'];
+dataExportPathBase = strcat(pathBaseExportFiles, exportFolder{1}, '\');
+plotPath = [dataExportPathBase, 'Plots\BaselinePlots\'];
+
+plot_dkntmn = false;
+%%
+paramKeyword = 'baseline';
+if plot_dkntmn
+ dataExportPath_05 = [dataExportPathBase, paramKeyword, ' - dkntmn0.5\'];
+ dataExportPath_015 = [dataExportPathBase, paramKeyword, ' - dkntmn0.15\'];
+ dataExportPath = [dataExportPathBase, paramKeyword, ' - dkntmn0.25\'];
+else
+ dataExportPath = [dataExportPathBase, paramKeyword, '\'];
+end
+
+baselines = {'1Flat_drop_H20'; '2Flat'; '3Flat'; '4Flat'; '5Wildish'; '6Wildish'; '7Very_wild';...
+ '8Very_wild'; '9Wild'; '10Wild'; '11Wildish'; '12Wildish'; '13Normal'; '14Lipid_1.3'; '15Lipid_1.3_phased'; '16Zero'};
+
+
+bandwidth = 8000;
+
+trunc = true;
+if trunc
+ truncSuffix = '_truncOn';
+else
+ truncSuffix = '_truncOff';
+end
+
+iteration = 4 ;
+
+colorSpectrum = [0 0.45 0.74];
+colorOriginal = [0 0 0];
+colorProFit = [0.49 0.18 0.56];
+colorLCModel = [0.85 0.33 0.1];
+if plot_dkntmn
+ colorLCModel_05 = [0.45 0.05 0.];
+ colorLCModel_015 = [1 0.53 0.1];
+end
+arrowsColor = [0.4 0.4 0.4];
+backgroundInlayColor = [0.8 0.8 0.8];
+LineWidth = 1.5;
+
+offsetBaseline = 7; % percent of max peak
+offsetResidual = 20; % percent of max peak
+offsetPlots = 4; % percent of max peak
+subplotGridX = 2;
+subplotGridY = 2;
+nGrid = subplotGridX * subplotGridY;
+
+sortedFigure = [16, 15, 14, 12, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 13];
+
+subplotNames = {'A', 'B', 'C', 'D'};
+
+for indexParam = 1:length(baselines)
+ if mod(indexParam-1,nGrid)==0
+% figure;
+ figure('units','normalized','outerposition',[0.13,-0.014,0.85,0.99]); %Works on the Dell screen
+ end
+ indexParamSorted = sortedFigure(indexParam);
+ %% load data: Input data, LCModel fit, ProFit Fit
+ % import the spectra but also the used concentrations and all parameters
+ fileName = ['Simulated_', paramKeyword, '_', num2str(indexParamSorted) '_truncOff'];
+ load([dataExportPath, fileName, '.mat'], 'summedFidWithNoise', 'current_em', 'currentConcentrationRm', ...
+ 'current_pc0', 'current_pc1', 'current_df2', 'current_gm', 'current_em_std_factor', 'conc_std_factor', 'baselineScaled');
+ if plot_dkntmn
+ fileName = ['Simulated_', paramKeyword, '_', num2str(indexParamSorted) truncSuffix];
+ [~, ~, phasedData_lcm_05, fitData_05, baselineData_lcm_05, residualData_05, ...
+ ~, ~, ~, ~, ~, ~, ~, ~, ~, ~] = ...
+ extractFits(dataExportPath_05,[fileName, '.coord']);
+ [~, ~, phasedData_lcm_015, fitData_015, baselineData_lcm_015, residualData_015, ...
+ ~, ~, ~, ~, ~, ~, ~, ~, ~, ~] = ...
+ extractFits(dataExportPath_015,[fileName, '.coord']);
+ end
+ [nOfPoints, ppmVector_lcm, phasedData_lcm, fitData, baselineData_lcm, residualData, ...
+ metaboliteNames, metaboliteData, tableConcentrations, ppmStart_lcm, ppmEnd_lcm, ...
+ scanFrequency, frequencyShift, ppmGap, phase0_deg_lcm, phase1_deg_ppm_lcm] = ...
+ extractFits(dataExportPath,[fileName, '.coord']);
+
+ load(strcat(dataExportPath,fileName, '_profit.mat'),'fitresult', 'data');
+
+ %% process input data
+ nTimepoints = length(summedFidWithNoise);
+ ppmVector = ppmVectorFunction(scanFrequency*1e6, bandwidth, nTimepoints, '1H');
+
+ spectrum = fftshift(fft(summedFidWithNoise));
+ baselineSpectrum = fftshift(fft(baselineScaled));
+
+ indexEnd = find(ppmVector > ppmEnd_lcm, 1);
+ spectrumInputOffset = real(spectrum(indexEnd));
+ baselineInputOffset = real(baselineSpectrum(indexEnd));
+
+ %% process ProFit data
+ currentFitresult = fitresult{1,iteration};
+ ppm_profit = currentFitresult.common_data.data.fitroi.ppm2;
+ %phasedData
+ pData_profit = currentFitresult.processed_spec;
+ %residual
+ rData_profit = currentFitresult.residual_spec;
+ %spline baseline
+ if ~isempty(currentFitresult.splines_baseline)
+ spBB = currentFitresult.splines_baseline.basis_matrix;
+ concSpline = currentFitresult.splines_baseline.coeff;
+ bData_profit = (spBB * concSpline(1:size(spBB,2)))';
+ splines_lambda = currentFitresult.splines_lambda;
+ splines_ed_vec = currentFitresult.splines_ed_vec;
+ splines_optim_model_vec = currentFitresult.splines_optim_model_vec;
+ splines_optim_idx = currentFitresult.splines_optim_idx;
+ else
+ bData_profit = zeros(size(currentFitresult.residual_spec));
+ splines_lambda = 0;
+ splines_ed_vec = [];
+ splines_optim_model_vec = [];
+ splines_optim_idx = 0;
+ end
+
+ %% Scale for plotting
+ % calculate scaling. Maximum has to be from the same fitted range as in LCModel/ProFit
+ ppmMask = (ppmVector < ppmStart_lcm) & (ppmVector > ppmEnd_lcm);
+ maxSpectrum = max(real(spectrum(ppmMask)));
+ maxSpectrum_lcm = max(phasedData_lcm);
+ maxSpectrum_profit = max(real(pData_profit));
+ scalingFactor_lcm = maxSpectrum ./ maxSpectrum_lcm;
+ scalingFactor_profit = maxSpectrum ./ maxSpectrum_profit;
+
+ minBaseline = min(real(baselineSpectrum(ppmMask)));
+
+ %scale the offsets
+ offsetBaselineScaled = offsetBaseline * maxSpectrum / 100;
+ offsetResidualScaled = offsetResidual * maxSpectrum / 100 - minBaseline;
+ offsetPlotsScaled = offsetPlots * maxSpectrum / 100;
+
+ %% create the figure
+ indexSubplot = mod(indexParam-1, nGrid)+1;
+ hs = subplot(subplotGridX,subplotGridY,indexSubplot);
+ coordinates = hs.Position;
+
+ hold on; %if not alligned, mind that the ppmVector has to be defined with the water resonance at 4.7 ppm
+ plot(ppmVector,real(spectrum),'LineWidth', LineWidth, 'Color', colorSpectrum);
+% plot(ppmVector_lcm,real(phasedData_lcm)*scalingFactor_lcm,'LineWidth', LineWidth, 'Color', colorLCModel);
+% plot(ppm_profit,real(pData_profit)*scalingFactor_profit,'LineWidth', LineWidth, 'Color', colorProFit);
+
+ if plot_dkntmn
+ offsetBaselineScaled = offsetBaselineScaled + offsetPlotsScaled;
+ plot(ppmVector_lcm,real(baselineData_lcm_05)*scalingFactor_lcm-offsetBaselineScaled+2.4*offsetPlotsScaled,':','LineWidth', LineWidth, 'Color', colorLCModel_05);
+ plot(ppmVector_lcm,real(baselineData_lcm)*scalingFactor_lcm-offsetBaselineScaled+1.6*offsetPlotsScaled,'-.','LineWidth', LineWidth, 'Color', colorLCModel);
+ plot(ppmVector_lcm,real(baselineData_lcm_015)*scalingFactor_lcm-offsetBaselineScaled+0.8*offsetPlotsScaled,':','LineWidth', LineWidth, 'Color', colorLCModel_015);
+ else
+ plot(ppmVector_lcm,real(baselineData_lcm)*scalingFactor_lcm-offsetBaselineScaled+offsetPlotsScaled,'-.','LineWidth', LineWidth, 'Color', colorLCModel);
+ end
+ plot(ppmVector,real(baselineSpectrum)-offsetBaselineScaled,'-.','LineWidth', LineWidth, 'Color', colorOriginal);
+ plot(ppm_profit,real(bData_profit)*scalingFactor_profit-offsetBaselineScaled-offsetPlotsScaled,'-.','LineWidth', LineWidth, 'Color', colorProFit);
+
+ plot(ppmVector_lcm,real(residualData)*scalingFactor_lcm-offsetResidualScaled,'LineWidth', LineWidth, 'Color', colorLCModel);
+ plot(ppm_profit,real(rData_profit)*scalingFactor_profit-offsetResidualScaled-offsetPlotsScaled,'LineWidth', LineWidth, 'Color', colorProFit);
+ set(gca,'xdir','reverse');
+ xlim([ppmEnd_lcm, ppmStart_lcm]);
+ ylim([-offsetResidualScaled-3*offsetPlotsScaled maxSpectrum+5*offsetPlotsScaled])
+ xlabel('\delta (ppm)');
+ ylabel('Signal (arb. u.)');
+ set(gca,'ytick',[]);
+
+
+ if plot_dkntmn
+ legend('Spectrum',sprintf('LCModel baseline\ndkntmn=0.5'),sprintf('LCModel baseline\ndkntmn=0.25'),sprintf('LCModel baseline\ndkntmn=0.15'),'Input baseline','ProFit baseline','LCModel residual','ProFit residual')
+ else
+ legend('Spectrum','LCModel baseline','Input baseline','ProFit baseline','LCModel residual','ProFit residual')
+ end
+
+ %arrows residual
+ yUpper = -offsetResidualScaled;
+ yLower = -offsetResidualScaled-offsetPlotsScaled;
+ xa = [ppmEnd_lcm ppmEnd_lcm]-0.05;
+ doublePointedArrowInside(xa,yUpper,yLower, arrowsColor);
+
+ %arrows LCModel - Input baseline
+ yUpper = baselineInputOffset-offsetBaselineScaled;
+ yLower = baselineInputOffset-offsetBaselineScaled-offsetPlotsScaled;
+ xa = [ppmEnd_lcm ppmEnd_lcm]-0.05;
+ doublePointedArrowInside(xa,yUpper,yLower, arrowsColor);
+
+ %arrows Input baseline - ProFit
+ yUpper = baselineInputOffset-offsetBaselineScaled+offsetPlotsScaled;
+ yLower = baselineInputOffset-offsetBaselineScaled;
+ xa = [ppmEnd_lcm ppmEnd_lcm]-0.1;
+ doublePointedArrowInside(xa,yUpper,yLower, arrowsColor);
+
+ % text box with label "Plot offsets"
+ xa = [ppmEnd_lcm 0]+0.1;
+ ya = [spectrumInputOffset-offsetPlotsScaled*2 0];
+ [xaf,yaf] = axescoord2figurecoord(xa,ya);
+ str = {'Plot','offsets'};
+ annotation('textbox',[xaf(1) yaf(1)-0.02 0.1 0.1],'String',str,'FitBoxToText','On', ...
+ 'EdgeColor','none', 'FontWeight','bold','Color',arrowsColor);
+
+ set(gcf,'Color','w')
+
+ annotation('rectangle',[coordinates(1)+coordinates(3)*0.02 coordinates(2)+coordinates(4)*0.62 ...
+ .35./subplotGridX .4./subplotGridY],'FaceColor', 'w', 'FaceAlpha',0, 'Color',[0 0.4 0.1])
+
+ axes('Position',[coordinates(1)+coordinates(3)*0.15 coordinates(2)+coordinates(4)*0.81 ...
+ .2./subplotGridX .2./subplotGridY])
+ box on;
+ plot(splines_ed_vec, splines_optim_model_vec,'Color',[0. 0.5 0.2]);
+ hold on
+ if ~isempty(splines_ed_vec(splines_optim_idx))
+ xl = xline(splines_ed_vec(splines_optim_idx),'-.', {['ED: ' sprintf('%.f',splines_ed_vec(splines_optim_idx))],...
+ ['mAIC: ', sprintf('%.1f',splines_optim_model_vec(splines_optim_idx))]}, ...
+ 'HandleVisibility','off', 'LineWidth', 2);
+ xl.LabelVerticalAlignment = 'top';
+ xl.LabelHorizontalAlignment = 'center';
+ xl.FontSize = 9;
+ end
+ set(gca,'FontSize',10)
+ set(gca,'Xscale','log');
+% set(gca,'Color',backgroundInlayColor)
+ xlabel('Baseline ED / ppm');
+ ylabel('mAIC');
+ ylim([min(splines_optim_model_vec)*0.99 max(splines_optim_model_vec)*1.01])
+ title('ProFit Baseline Smoothness');
+
+ annotation('textbox',[coordinates(1)+coordinates(3)*0.02-0.03 coordinates(2)+coordinates(4)*0.62 ...
+ .35./subplotGridX .4./subplotGridY],'String',subplotNames{indexSubplot},'FontSize', 16, 'FontWeight', 'bold','LineStyle','none')
+ if mod(indexParam,nGrid)==0
+ print('-dtiff','-r600',[plotPath, 'Baseline_Fit_',num2str(indexParam),'.tif'])
+ savefig(gcf,[plotPath, 'Baseline_Fit_',num2str(indexParam),'.fig'], 'compact');
+ end
+end
+end
+
+function doublePointedArrowInside(xa,yUpper,yLower, arrowsColor)
+ set(gcf,'Units','normalized');
+ yaDown = [yUpper+1e-8 yUpper];
+ yaLine = [yLower yUpper];
+ yaUp = [yLower-1e-8 yLower];
+ [xaf,yafLine] = axescoord2figurecoord(xa,yaLine);
+ line = annotation('line',xaf,yafLine);
+ [xaf,yafDown] = axescoord2figurecoord(xa,yaDown);
+ arDown = annotation('arrow',xaf,yafDown);
+ [xaf,yafUp] = axescoord2figurecoord(xa,yaUp);
+ arUp = annotation('arrow',xaf,yafUp);
+ %styling
+ line.Color = arrowsColor;
+ arDown.HeadStyle = 'vback2';
+ arDown.HeadLength = 5;
+ arDown.HeadWidth = 7;
+ arDown.Color = arrowsColor;
+ arUp.HeadStyle = 'vback2';
+ arUp.HeadLength = 5;
+ arUp.HeadWidth = 7;
+ arUp.Color = arrowsColor;
+end
diff --git a/createTestData/plotSimulationResults.m b/createTestData/plotSimulationResults.m
index a577fe094c2eb22929ecafcaa155fd07502e4689..fde9ce3f5f8760969a910c63fd4c1f484c6c8de5 100644
--- a/createTestData/plotSimulationResults.m
+++ b/createTestData/plotSimulationResults.m
@@ -1,51 +1,73 @@
function plotSimulationResults()
-
%% path to the export of the spectra
exportFolder = {'11 Simulations'};
pathNameExport = 'ProFit test data';
pathBaseExportFiles = pathToDataFolder(pathNameExport, exportFolder);
+pathBaseExportFiles = pathBaseExportFiles(1:end-1);
+pathBaseExportFiles = [pathBaseExportFiles ' - R3\'];
dataExportPathBase = strcat(pathBaseExportFiles, exportFolder{1}, '\');
-
-paramKeyword = 'conc';
truncSuffix = '_truncOn';
-if contains(paramKeyword,'conc')
- scalingOn = true;
-else
- scalingOn = false;
-end
+scalingOn = true;
+
% name of metabolites in LCModel
metabolitesLCModel = {'Asp', 'Cr_CH2', 'Cr', 'GABA', 'Gln', 'Glu', 'Glyc', 'GSH', 'Lac', 'mI', 'NAA_as', 'NAA_ac', 'NAAG', 'tCho_P', 'Scyllo', 'Tau', 'Leu'};
% name of metabolites in ProFit
metabolitesProFit = {'Asp', 'Cr_CH2', 'Cr', 'GABA', 'Gln', 'Glu', 'Glyc', 'GSH', 'Lac', 'mI', 'NAA_as', 'NAA_ac', 'NAAG', 'tCho_P', 'Scyllo', 'Tau', 'Leu'};
-%% load simulated data
-load([dataExportPathBase, 'concentrations_simulated_', paramKeyword, '.mat'], 'concentrationsRm', 'metabolites', 'metaboliteNames');
+% name of metabolites to display
+metabolitesToDisplay = {'Asp', 'tCr(CH_2)', 'tCr(CH_3)', 'GABA', 'Gln', 'Glu', 'Gly', 'GSH', 'Lac', 'mI', 'NAA(CH_2)', 'NAA(CH_3)', 'NAAG', 'tCho+', 'sI', 'Tau', 'MM spectrum'};
+metabolitesLabels = {'Asp', 'tCr(CH2)', 'tCr(CH3)', 'GABA', 'Gln', 'Glu', 'Gly', 'GSH', 'Lac', 'mI', 'NAA(CH2)', 'NAA(CH3)', 'NAAG', 'tCho+', 'sI', 'Tau', 'MM spectrum'};
+
+numberOfMet = length(metabolitesLabels);
+indexesMainMet = zeros(1,numberOfMet);
+mainMetabolites = { 'tCr(CH3)', 'tCr(CH2)', 'Glu', 'mI', 'NAA(CH2)', 'NAA(CH3)', 'tCho+'};
+for indexMet = 1:numberOfMet
+ indexesMainMet(indexMet) = ~isempty(find(strcmp(mainMetabolites,metabolitesLabels{indexMet}), 1));
+end
+indexesMainMet = logical(indexesMainMet);
+
+numOfParameters = 4;
+[metaboliteTable, indexTable] = setupTable(numberOfMet, numOfParameters, metabolitesLabels);
+
+sumAllMeanProFit = 0;
+sumAllStdProFit = 0;
+sumAllMeanProFitMain = 0;
+sumAllStdProFitMain = 0;
+
+plotColors = {[0 0 1], [1 0 0], [0 0 0], [1 0.5 0.3], [0.49 0.18 0.56], [0.0 0.4 0.0]};
+
+plotCorrelations = false;
+plotPrecision = true;
-%% load fitted data LCModel
+figIds = [];
+secondaryFigures =0;
+%%
+paramKeyword = 'pc0';
+% load simulated data
+load([dataExportPathBase, 'concentrations_simulated_', paramKeyword, '.mat'], 'concentrationsRm', 'metabolites', 'metaboliteNames');
+% load fitted data LCModel
load([dataExportPathBase, 'concentrations_', paramKeyword, truncSuffix, '.mat'], 'concentrations');
concentrationsLCModel = concentrations;
-
-%% load fitted data ProFit
+% load fitted data ProFit
load([dataExportPathBase, 'concentrations_', paramKeyword, truncSuffix, '_profit.mat'], 'concentrations', 'activeMetabolites');
concentrationsProFit = concentrations;
-
-plotCorrelations = true;
-plotColors = {[0 0 1], [1 0 0]};
-% plotColors2 = {[0.0 0.4 0.0], [1 0.5 0.3]};
-plotColors2 = {[0.0 0.4 0.0], [0 0 0], [1 0.5 0.3]};
-offsetPlot = 0.2;
-plotPrecision = false;
-[allSimulMetConc, allLCModelMetConc, allProFitMetConc, allLCModelMetConcDev, allProFitMetConcDev, ~, figIdsCorr] = getConcentrations(...
- metabolites, metabolitesLCModel, metabolitesProFit, ...
+offsetPlot = -0.45;
+indexTable = indexTable +2;
+metaboliteTable{1,indexTable} = paramKeyword;
+[allSimulMetConc, allLCModelMetConc, allProFitMetConc, allLCModelMetConcDev, allProFitMetConcDev, metaboliteTable, figIds, ~, ...
+ allMeanProFit, allStdProFit,allMeanProFitMain, allStdProFitMain] = getConcentrations(...
+ metabolites, metabolitesLCModel, metabolitesProFit, metabolitesToDisplay, metabolitesLabels, ...
concentrationsRm, concentrationsLCModel, concentrationsProFit, activeMetabolites, ...
scalingOn, plotCorrelations, dataExportPathBase, paramKeyword, truncSuffix, ...
- plotPrecision, plotColors{1}, -offsetPlot, [], []);
-
-plotPrecision = false;
+ plotPrecision, plotColors{1}, offsetPlot, figIds, [], metaboliteTable, indexTable, indexesMainMet, secondaryFigures);
+sumAllMeanProFit = sumAllMeanProFit + allMeanProFit;
+sumAllStdProFit = sumAllStdProFit + allStdProFit;
+sumAllMeanProFitMain = sumAllMeanProFitMain + allMeanProFitMain;
+sumAllStdProFitMain = sumAllStdProFitMain + allStdProFitMain;
%%
-paramKeyword = 'conc3';
+paramKeyword = 'pc1';
% load simulated data
load([dataExportPathBase, 'concentrations_simulated_', paramKeyword, '.mat'], 'concentrationsRm', 'metabolites', 'metaboliteNames');
% load fitted data LCModel
@@ -54,17 +76,21 @@ concentrationsLCModel = concentrations;
% load fitted data ProFit
load([dataExportPathBase, 'concentrations_', paramKeyword, truncSuffix, '_profit.mat'], 'concentrations', 'activeMetabolites');
concentrationsProFit = concentrations;
-[allSimulMetConc, allLCModelMetConc, allProFitMetConc, allLCModelMetConcDev, allProFitMetConcDev, ~, figIdsCorr] = getConcentrations(...
- metabolites, metabolitesLCModel, metabolitesProFit, ...
+offsetPlot = -0.15;
+indexTable = indexTable +2;
+metaboliteTable{1,indexTable} = paramKeyword;
+[allSimulMetConc, allLCModelMetConc, allProFitMetConc, allLCModelMetConcDev, allProFitMetConcDev, metaboliteTable, figIds, ~,...
+ allMeanProFit, allStdProFit,allMeanProFitMain, allStdProFitMain] = getConcentrations(...
+ metabolites, metabolitesLCModel, metabolitesProFit, metabolitesToDisplay, metabolitesLabels, ...
concentrationsRm, concentrationsLCModel, concentrationsProFit, activeMetabolites, ...
scalingOn, plotCorrelations, dataExportPathBase, paramKeyword, truncSuffix, ...
- plotPrecision, plotColors{1}, -offsetPlot, [], figIdsCorr);
-
-
-plotCorrelations = false;
-plotPrecision = true;
+ plotPrecision, plotColors{2}, offsetPlot, figIds, [], metaboliteTable, indexTable, indexesMainMet, secondaryFigures);
+sumAllMeanProFit = sumAllMeanProFit + allMeanProFit;
+sumAllStdProFit = sumAllStdProFit + allStdProFit;
+sumAllMeanProFitMain = sumAllMeanProFitMain + allMeanProFitMain;
+sumAllStdProFitMain = sumAllStdProFitMain + allStdProFitMain;
%%
-paramKeyword = 'pc0';
+paramKeyword = 'df2_global';
% load simulated data
load([dataExportPathBase, 'concentrations_simulated_', paramKeyword, '.mat'], 'concentrationsRm', 'metabolites', 'metaboliteNames');
% load fitted data LCModel
@@ -73,14 +99,21 @@ concentrationsLCModel = concentrations;
% load fitted data ProFit
load([dataExportPathBase, 'concentrations_', paramKeyword, truncSuffix, '_profit.mat'], 'concentrations', 'activeMetabolites');
concentrationsProFit = concentrations;
-offsetPlot = -0.2;
-[allSimulMetConc, allLCModelMetConc, allProFitMetConc, allLCModelMetConcDev, allProFitMetConcDev, figIds] = getConcentrations(...
- metabolites, metabolitesLCModel, metabolitesProFit, ...
+offsetPlot = 0.15;
+indexTable = indexTable +2;
+metaboliteTable{1,indexTable} = paramKeyword;
+[allSimulMetConc, allLCModelMetConc, allProFitMetConc, allLCModelMetConcDev, allProFitMetConcDev, metaboliteTable, figIds, ~,...
+ allMeanProFit, allStdProFit,allMeanProFitMain, allStdProFitMain] = getConcentrations(...
+ metabolites, metabolitesLCModel, metabolitesProFit, metabolitesToDisplay, metabolitesLabels, ...
concentrationsRm, concentrationsLCModel, concentrationsProFit, activeMetabolites, ...
scalingOn, plotCorrelations, dataExportPathBase, paramKeyword, truncSuffix, ...
- plotPrecision, plotColors{1}, offsetPlot, [], []);
+ plotPrecision, plotColors{3}, offsetPlot, figIds, [], metaboliteTable, indexTable, indexesMainMet, secondaryFigures);
+sumAllMeanProFit = sumAllMeanProFit + allMeanProFit;
+sumAllStdProFit = sumAllStdProFit + allStdProFit;
+sumAllMeanProFitMain = sumAllMeanProFitMain + allMeanProFitMain;
+sumAllStdProFitMain = sumAllStdProFitMain + allStdProFitMain;
%%
-paramKeyword = 'pc1';
+paramKeyword = 'df2_local';
% load simulated data
load([dataExportPathBase, 'concentrations_simulated_', paramKeyword, '.mat'], 'concentrationsRm', 'metabolites', 'metaboliteNames');
% load fitted data LCModel
@@ -89,12 +122,44 @@ concentrationsLCModel = concentrations;
% load fitted data ProFit
load([dataExportPathBase, 'concentrations_', paramKeyword, truncSuffix, '_profit.mat'], 'concentrations', 'activeMetabolites');
concentrationsProFit = concentrations;
-offsetPlot = 0;
-[allSimulMetConc, allLCModelMetConc, allProFitMetConc, allLCModelMetConcDev, allProFitMetConcDev, figIds] = getConcentrations(...
- metabolites, metabolitesLCModel, metabolitesProFit, ...
+offsetPlot = 0.45;
+indexTable = indexTable +2;
+metaboliteTable{1,indexTable} = paramKeyword;
+[allSimulMetConc, allLCModelMetConc, allProFitMetConc, allLCModelMetConcDev, allProFitMetConcDev, metaboliteTable, figIds, ~,...
+ allMeanProFit, allStdProFit,allMeanProFitMain, allStdProFitMain] = getConcentrations(...
+ metabolites, metabolitesLCModel, metabolitesProFit, metabolitesToDisplay, metabolitesLabels, ...
concentrationsRm, concentrationsLCModel, concentrationsProFit, activeMetabolites, ...
scalingOn, plotCorrelations, dataExportPathBase, paramKeyword, truncSuffix, ...
- plotPrecision, plotColors{2}, offsetPlot, figIds, []);
+ plotPrecision, plotColors{4}, offsetPlot, figIds, [], metaboliteTable, indexTable, indexesMainMet, secondaryFigures);
+sumAllMeanProFit = sumAllMeanProFit + allMeanProFit;
+sumAllStdProFit = sumAllStdProFit + allStdProFit;
+sumAllMeanProFitMain = sumAllMeanProFitMain + allMeanProFitMain;
+sumAllStdProFitMain = sumAllStdProFitMain + allStdProFitMain;
+%% -----------------------------------------------------------------------------------------------------------
+axes(figIds{1})
+str = {'$$\varphi_0$$', '$$\varphi_1$$', '$$\omega_{global}$$', '{\boldmath$\omega_{local}$}'};
+xOffset = 0.65;
+yOffsetRect = 0.085; %0.075; -for two subfigures
+for indexSim = 1:4
+ yOffset = 0.84;% 4 subfigs%0.80; - Two figs placed lower%0.86 -Two figs
+ annotation('textbox',[xOffset yOffset 0.1 0.1],'String',str{indexSim},'FitBoxToText','On', ...
+ 'EdgeColor','none', 'FontSize', 12, 'Interpreter','latex','Color',plotColors{indexSim})
+ annotation('rectangle',[xOffset-0.012 yOffset+yOffsetRect 0.01 0.01],'EdgeColor','none', 'FaceColor',plotColors{indexSim})
+ yOffset = 0.612;% 4 subfigs%0.37; - Two figs placed lower%0.37 -Two figs
+ annotation('textbox',[xOffset yOffset 0.1 0.1],'String',str{indexSim},'FitBoxToText','On', ...
+ 'EdgeColor','none', 'FontSize', 12, 'FontWeight','bold', 'Interpreter','latex','Color',plotColors{indexSim})
+ annotation('rectangle',[xOffset-0.012 yOffset+yOffsetRect 0.01 0.01],'EdgeColor','none', 'FaceColor',plotColors{indexSim})
+ xOffset = xOffset + 0.004*length(str{indexSim});
+end
+
+% save Table
+xlswrite([dataExportPathBase, 'SimulationsTable1.xlsx'],metaboliteTable);
+numOfParameters2 = 5;
+[metaboliteTable, indexTable] = setupTable(numberOfMet, numOfParameters2, metabolitesLabels);
+
+% figIds = [];
+secondaryFigures = 2;
+%% -----------------------------------------------------------------------------------------------------------
%%
paramKeyword = 'gauss';
% load simulated data
@@ -105,14 +170,17 @@ concentrationsLCModel = concentrations;
% load fitted data ProFit
load([dataExportPathBase, 'concentrations_', paramKeyword, truncSuffix, '_profit.mat'], 'concentrations', 'activeMetabolites');
concentrationsProFit = concentrations;
-offsetPlot = 0.2;
-[allSimulMetConc, allLCModelMetConc, allProFitMetConc, allLCModelMetConcDev, allProFitMetConcDev, figIds] = getConcentrations(...
- metabolites, metabolitesLCModel, metabolitesProFit, ...
+offsetPlot = -0.45;
+indexTable = indexTable +2;
+metaboliteTable{1,indexTable} = paramKeyword;
+[allSimulMetConc, allLCModelMetConc, allProFitMetConc, allLCModelMetConcDev, allProFitMetConcDev, metaboliteTable, figIds, ~,...
+ allMeanProFit, allStdProFit,allMeanProFitMain, allStdProFitMain] = getConcentrations(...
+ metabolites, metabolitesLCModel, metabolitesProFit, metabolitesToDisplay, metabolitesLabels, ...
concentrationsRm, concentrationsLCModel, concentrationsProFit, activeMetabolites, ...
scalingOn, plotCorrelations, dataExportPathBase, paramKeyword, truncSuffix, ...
- plotPrecision, plotColors2{1}, offsetPlot, figIds, []);
+ plotPrecision, plotColors{1}, offsetPlot, figIds, [], metaboliteTable, indexTable, indexesMainMet, secondaryFigures);
%%
-paramKeyword = 'df2';
+paramKeyword = 'em';
% load simulated data
load([dataExportPathBase, 'concentrations_simulated_', paramKeyword, '.mat'], 'concentrationsRm', 'metabolites', 'metaboliteNames');
% load fitted data LCModel
@@ -121,12 +189,19 @@ concentrationsLCModel = concentrations;
% load fitted data ProFit
load([dataExportPathBase, 'concentrations_', paramKeyword, truncSuffix, '_profit.mat'], 'concentrations', 'activeMetabolites');
concentrationsProFit = concentrations;
-offsetPlot = 0.4;
-[allSimulMetConc, allLCModelMetConc, allProFitMetConc, allLCModelMetConcDev, allProFitMetConcDev, figIds] = getConcentrations(...
- metabolites, metabolitesLCModel, metabolitesProFit, ...
+offsetPlot = -0.15;
+indexTable = indexTable +2;
+metaboliteTable{1,indexTable} = paramKeyword;
+[allSimulMetConc, allLCModelMetConc, allProFitMetConc, allLCModelMetConcDev, allProFitMetConcDev, metaboliteTable, figIds, ~,...
+ allMeanProFit, allStdProFit,allMeanProFitMain, allStdProFitMain] = getConcentrations(...
+ metabolites, metabolitesLCModel, metabolitesProFit, metabolitesToDisplay, metabolitesLabels, ...
concentrationsRm, concentrationsLCModel, concentrationsProFit, activeMetabolites, ...
scalingOn, plotCorrelations, dataExportPathBase, paramKeyword, truncSuffix, ...
- plotPrecision, plotColors2{2}, offsetPlot, figIds, []);
+ plotPrecision, plotColors{2}, offsetPlot, figIds, [], metaboliteTable, indexTable, indexesMainMet, secondaryFigures);
+sumAllMeanProFit = sumAllMeanProFit + allMeanProFit;
+sumAllStdProFit = sumAllStdProFit + allStdProFit;
+sumAllMeanProFitMain = sumAllMeanProFitMain + allMeanProFitMain;
+sumAllStdProFitMain = sumAllStdProFitMain + allStdProFitMain;
%%
paramKeyword = 'noise';
% load simulated data
@@ -137,139 +212,367 @@ concentrationsLCModel = concentrations;
% load fitted data ProFit
load([dataExportPathBase, 'concentrations_', paramKeyword, truncSuffix, '_profit.mat'], 'concentrations', 'activeMetabolites');
concentrationsProFit = concentrations;
-offsetPlot = 0.6;
-[allSimulMetConc, allLCModelMetConc, allProFitMetConc, allLCModelMetConcDev, allProFitMetConcDev, figIds] = getConcentrations(...
- metabolites, metabolitesLCModel, metabolitesProFit, ...
+offsetPlot = 0.15;
+indexTable = indexTable +2;
+metaboliteTable{1,indexTable} = paramKeyword;
+[allSimulMetConc, allLCModelMetConc, allProFitMetConc, allLCModelMetConcDev, allProFitMetConcDev, metaboliteTable, figIds, ~,...
+ allMeanProFit, allStdProFit,allMeanProFitMain, allStdProFitMain] = getConcentrations(...
+ metabolites, metabolitesLCModel, metabolitesProFit, metabolitesToDisplay, metabolitesLabels, ...
+ concentrationsRm, concentrationsLCModel, concentrationsProFit, activeMetabolites, ...
+ scalingOn, plotCorrelations, dataExportPathBase, paramKeyword, truncSuffix, ...
+ plotPrecision, plotColors{3}, offsetPlot, figIds, [], metaboliteTable, indexTable, indexesMainMet, secondaryFigures);
+sumAllMeanProFit = sumAllMeanProFit + allMeanProFit;
+sumAllStdProFit = sumAllStdProFit + allStdProFit;
+sumAllMeanProFitMain = sumAllMeanProFitMain + allMeanProFitMain;
+sumAllStdProFitMain = sumAllStdProFitMain + allStdProFitMain;
+%%
+paramKeyword = 'baseline';
+% load simulated data
+load([dataExportPathBase, 'concentrations_simulated_', paramKeyword, '.mat'], 'concentrationsRm', 'metabolites', 'metaboliteNames');
+% load fitted data LCModel
+load([dataExportPathBase, 'concentrations_', paramKeyword, truncSuffix, '.mat'], 'concentrations');
+concentrationsLCModel = concentrations;
+% load fitted data ProFit
+load([dataExportPathBase, 'concentrations_', paramKeyword, truncSuffix, '_profit.mat'], 'concentrations', 'activeMetabolites');
+concentrationsProFit = concentrations;
+offsetPlot = 0.45;
+indexTable = indexTable +2;
+metaboliteTable{1,indexTable} = paramKeyword;
+[allSimulMetConc, allLCModelMetConc, allProFitMetConc, allLCModelMetConcDev, allProFitMetConcDev, metaboliteTable, figIds, ~,...
+ allMeanProFit, allStdProFit,allMeanProFitMain, allStdProFitMain] = getConcentrations(...
+ metabolites, metabolitesLCModel, metabolitesProFit, metabolitesToDisplay, metabolitesLabels, ...
+ concentrationsRm, concentrationsLCModel, concentrationsProFit, activeMetabolites, ...
+ scalingOn, plotCorrelations, dataExportPathBase, paramKeyword, truncSuffix, ...
+ plotPrecision, plotColors{4}, offsetPlot, figIds, [], metaboliteTable, indexTable, indexesMainMet, secondaryFigures);
+sumAllMeanProFit = sumAllMeanProFit + allMeanProFit;
+sumAllStdProFit = sumAllStdProFit + allStdProFit;
+sumAllMeanProFitMain = sumAllMeanProFitMain + allMeanProFitMain;
+sumAllStdProFitMain = sumAllStdProFitMain + allStdProFitMain;
+
+%%
+paramKeyword = 'conc';
+% load simulated data
+load([dataExportPathBase, 'concentrations_simulated_', paramKeyword, '.mat'], 'concentrationsRm', 'metabolites', 'metaboliteNames');
+% load fitted data LCModel
+load([dataExportPathBase, 'concentrations_', paramKeyword, truncSuffix, '.mat'], 'concentrations');
+concentrationsLCModel = concentrations;
+% load fitted data ProFit
+load([dataExportPathBase, 'concentrations_', paramKeyword, truncSuffix, '_profit.mat'], 'concentrations', 'activeMetabolites');
+concentrationsProFit = concentrations;
+
+plotCorrelations = true;
+offsetPlot = 0.;
+plotPrecision = false;
+indexTable = indexTable +2;
+metaboliteTable{1,indexTable} = paramKeyword;
+[allSimulMetConc, allLCModelMetConc, allProFitMetConc, allLCModelMetConcDev, allProFitMetConcDev, metaboliteTable, ~, figIdsCorr, ...
+ allMeanProFit, allStdProFit,allMeanProFitMain, allStdProFitMain] = getConcentrations(...
+ metabolites, metabolitesLCModel, metabolitesProFit, metabolitesToDisplay, metabolitesLabels, ...
concentrationsRm, concentrationsLCModel, concentrationsProFit, activeMetabolites, ...
scalingOn, plotCorrelations, dataExportPathBase, paramKeyword, truncSuffix, ...
- plotPrecision, plotColors2{3}, offsetPlot, figIds, []);
+ plotPrecision, plotColors{1}, -offsetPlot, [], [], metaboliteTable, indexTable, indexesMainMet, secondaryFigures);
+sumAllMeanProFit = sumAllMeanProFit + allMeanProFit;
+sumAllStdProFit = sumAllStdProFit + allStdProFit;
+sumAllMeanProFitMain = sumAllMeanProFitMain + allMeanProFitMain;
+sumAllStdProFitMain = sumAllStdProFitMain + allStdProFitMain;
-txt = 'ProFit: blue: $$\varphi_0$$, red:$$\varphi_1$$, green:$$\nu_g$$, black:$$\omega_k$$';
-title(txt, 'Interpreter','latex','FontSize', 20)
+%%
+sumAllMeanProFit = sumAllMeanProFit / (numOfParameters + numOfParameters2)
+sumAllStdProFit = sumAllStdProFit / (numOfParameters + numOfParameters2)
+sumAllMeanProFitMain = sumAllMeanProFitMain / (numOfParameters + numOfParameters2)
+sumAllStdProFitMain = sumAllStdProFitMain / (numOfParameters + numOfParameters2)
+%%
+%% -----------------------------------------------------------------------------------------------------------
+axes(figIds{1})
+str = {'$$\nu_g$$', '{\boldmath$\nu_{e}$}', '{\boldmath$noise$}', '{\boldmath$baseline$}'};
+stringLenghts = {13, 13, 19, 27};
+xOffset = 0.63;
+yOffsetRect = 0.085; %0.075; -for two subfigures
+for indexSim = 1:4
+ yOffset = 0.392;% 4 subfigs%0.80; - Two figs placed lower%0.86 -Two figs
+ annotation('textbox',[xOffset yOffset 0.1 0.1],'String',str{indexSim},'FitBoxToText','On', ...
+ 'EdgeColor','none', 'FontSize', 12, 'Interpreter','latex','Color',plotColors{indexSim})
+ annotation('rectangle',[xOffset-0.012 yOffset+yOffsetRect 0.01 0.01],'EdgeColor','none', 'FaceColor',plotColors{indexSim})
+ yOffset = 0.172;% 4 subfigs%0.37; - Two figs placed lower%0.37 -Two figs
+ annotation('textbox',[xOffset yOffset 0.1 0.1],'String',str{indexSim},'FitBoxToText','On', ...
+ 'EdgeColor','none', 'FontSize', 12, 'FontWeight','bold', 'Interpreter','latex','Color',plotColors{indexSim})
+ annotation('rectangle',[xOffset-0.012 yOffset+yOffsetRect 0.01 0.01],'EdgeColor','none', 'FaceColor',plotColors{indexSim})
+ xOffset = xOffset + 0.004*stringLenghts{indexSim};
end
-function [allSimulMetConc, allLCModelMetConc, allProFitMetConc, allLCModelMetConcDev, allProFitMetConcDev, figIds, figIdsCorr] = ...
- getConcentrations(metabolites, metabolitesLCModel, metabolitesProFit, ...
- concentrationsRm, concentrationsLCModel, concentrationsProFit, activeMetabolites, ...
- scalingOn, plotCorrelations, dataExportPathBase, paramKeyword, truncSuffix, ...
- plotPrecision, plotColors, offsetPlot, figIds, figIdsCorr)
-
-
- if isempty(figIdsCorr)
- emptyFigureIdsCorr = true;
- figIdsCorr = cell(1,length(metabolites));
- else
- emptyFigureIdsCorr = false;
+xlswrite([dataExportPathBase, 'SimulationsTable2.xlsx'],metaboliteTable);
+end
+
+%% get metabolite concentrations for a given paramKeyword and create the requested plots
+function [allSimulMetConc, allLCModelMetConc, allProFitMetConc, allLCModelMetConcDev, allProFitMetConcDev, metaboliteTable, figIds, figIdsCorr,...
+ allMeanProFit, allStdProFit,allMeanProFitMain, allStdProFitMain] = ...
+ getConcentrations(metabolites, metabolitesLCModel, metabolitesProFit, metabolitesToDisplay, metabolitesLabels, ...
+ concentrationsRm, concentrationsLCModel, concentrationsProFit, activeMetabolites, ...
+ scalingOn, plotCorrelations, dataExportPathBase, paramKeyword, truncSuffix, ...
+ plotPrecision, plotColors, offsetPlot, figIds, figIdsCorr, metaboliteTable, indexTable, indexesMainMet, secondaryFigures)
+numberOfMet = length(metabolites);
+
+[allSimulMetConc, allLCModelMetConc, allProFitMetConc, allLCModelMetConcDev, allProFitMetConcDev] = ...
+ reorganizeMetConcentrationsToMatrices(metabolites, metabolitesLCModel, metabolitesProFit, ...
+ concentrationsRm, concentrationsLCModel, concentrationsProFit, activeMetabolites, scalingOn);
+if plotCorrelations
+ figIdsCorr = plotCorrelationFigs(concentrationsRm, allLCModelMetConc, allProFitMetConc, metabolitesToDisplay, numberOfMet, ...
+ dataExportPathBase, paramKeyword, truncSuffix, figIdsCorr);
+end
+if plotPrecision
+ figIds = plotPrecisionFigs(figIds, numberOfMet, offsetPlot, secondaryFigures, plotColors, ...
+ allLCModelMetConcDev, allProFitMetConcDev, metabolitesLabels);
+end
+
+display([paramKeyword, ' NANs:', num2str(sum(isnan(allLCModelMetConcDev)))]);
+meanConcDevLCModel = mean(allLCModelMetConcDev,'omitnan');
+stdConcDevLCModel = std(allLCModelMetConcDev,'omitnan');
+display([paramKeyword, ' NANs ProFit:', num2str(sum(isnan(allProFitMetConcDev)))]);
+meanConcDevProFit = mean(allProFitMetConcDev,'omitnan');
+stdConcDevProFit = std(allProFitMetConcDev,'omitnan');
+
+allMeanLCModel = mean(abs(meanConcDevLCModel));
+allStdLCModel = mean(abs(stdConcDevLCModel));
+allMeanProFit = mean(abs(meanConcDevProFit));
+allStdProFit = mean(abs(stdConcDevProFit));
+
+allMeanLCModelMain = mean(abs(meanConcDevLCModel(indexesMainMet)));
+allStdLCModelMain = mean(abs(stdConcDevLCModel(indexesMainMet)));
+allMeanProFitMain = mean(abs(meanConcDevProFit(indexesMainMet)));
+allStdProFitMain = mean(abs(stdConcDevProFit(indexesMainMet)));
+
+plusMinusSign = char(177);
+metaboliteTable{2,indexTable} = 'ProFit';
+metaboliteTable{2,indexTable+1} = 'LCModel';
+for indexMet = 1:numberOfMet
+ metaboliteTable{indexMet+2,indexTable} = [num2str(meanConcDevProFit(indexMet),'%.1f'), plusMinusSign, num2str(stdConcDevProFit(indexMet),'%.1f')];
+ metaboliteTable{indexMet+2,indexTable+1} = [num2str(meanConcDevLCModel(indexMet),'%.1f'), plusMinusSign, num2str(stdConcDevLCModel(indexMet),'%.1f')];
+end
+
+metaboliteTable{numberOfMet+3,indexTable} = [num2str(allMeanProFit,'%.1f'), plusMinusSign, num2str(allStdProFit,'%.1f')];
+metaboliteTable{numberOfMet+3,indexTable+1} = [num2str(allMeanLCModel,'%.1f'), plusMinusSign, num2str(allStdLCModel,'%.1f')];
+
+metaboliteTable{numberOfMet+4,indexTable} = [num2str(allMeanProFitMain,'%.1f'), plusMinusSign, num2str(allStdProFitMain,'%.1f')];
+metaboliteTable{numberOfMet+4,indexTable+1} = [num2str(allMeanLCModelMain,'%.1f'), plusMinusSign, num2str(allStdLCModelMain,'%.1f')];
+end
+
+%% reorganize the fitted concentrations to 2D tables
+function [allSimulMetConc, allLCModelMetConc, allProFitMetConc, allLCModelMetConcDev, allProFitMetConcDev] = ...
+ reorganizeMetConcentrationsToMatrices(metabolites, metabolitesLCModel, metabolitesProFit, ...
+ concentrationsRm, concentrationsLCModel, concentrationsProFit, activeMetabolites, scalingOn)
+
+iterationProFit = 4;
+numberOfMet = length(metabolites);
+allSimulMetConc = concentrationsRm;
+allLCModelMetConc = zeros(size(allSimulMetConc));
+allProFitMetConc = zeros(size(allSimulMetConc));
+allLCModelMetConcDev = zeros(size(allSimulMetConc));
+allProFitMetConcDev = zeros(size(allSimulMetConc));
+for indexMetabolite = 1:numberOfMet
+ simulatedMetConc = concentrationsRm(:, indexMetabolite);
+ indexMetSim = find(strcmp(metabolites,'tCr(CH3)')); %'MMB'
+ fittedMetConcLCModel = zeros(size(simulatedMetConc));
+ for indexFit = 1:length(concentrationsLCModel)
+ currentConcentrationsLCModel = concentrationsLCModel{indexFit};
+ indexMetLCModel = find(strcmp(currentConcentrationsLCModel(1,:),'Cr')); %'Leu'
+ RefConc = currentConcentrationsLCModel{2,indexMetLCModel};
+ RefConcSim = concentrationsRm(indexFit,indexMetSim);
+ if scalingOn
+ scaling = RefConcSim/RefConc;
+ else
+ scaling = 1;
+ end
+ indexMetLCModel = find(strcmp(currentConcentrationsLCModel(1,:),metabolitesLCModel(indexMetabolite)));
+ fittedMetConcLCModel(indexFit) = currentConcentrationsLCModel{2,indexMetLCModel}*scaling;
+ end
+ fittedMetConcProFit = zeros(size(simulatedMetConc));
+ for indexFit = 1:length(concentrationsProFit)
+ currentConcentrationsProFit = concentrationsProFit{indexFit}{iterationProFit};
+ indexMetProFit = find(strcmp(activeMetabolites{iterationProFit},'Cr')); %'Leu'
+ RefConc = currentConcentrationsProFit(indexMetProFit);
+ RefConcSim = concentrationsRm(indexFit,indexMetSim);
+ if scalingOn
+ scaling = RefConcSim/RefConc;
+ else
+ scaling = 1;
+ end
+ indexMetProFit = find(strcmp(activeMetabolites{iterationProFit},metabolitesProFit(indexMetabolite)));
+ fittedMetConcProFit(indexFit) = currentConcentrationsProFit(indexMetProFit)*scaling;
+ end
+ if strcmp(metabolitesProFit(indexMetabolite),'Leu')
+ fittedMetConcProFit = fittedMetConcProFit *1e8;
end
- allSimulMetConc = concentrationsRm;
- allLCModelMetConc = zeros(size(allSimulMetConc));
- allProFitMetConc = zeros(size(allSimulMetConc));
- allLCModelMetConcDev = zeros(size(allSimulMetConc));
- allProFitMetConcDev = zeros(size(allSimulMetConc));
- for indexMetabolite = 1:length(metabolites)
- simulatedMetConc = concentrationsRm(:, indexMetabolite);
- indexMetSim = find(strcmp(metabolites,'tCr(CH3)')); %'MMB'
- fittedMetConcLCModel = zeros(size(simulatedMetConc));
- for indexFit = 1:length(concentrationsLCModel)
- currentConcentrationsLCModel = concentrationsLCModel{indexFit};
- indexMetLCModel = find(strcmp(currentConcentrationsLCModel(1,:),'Cr')); %'Leu'
- MMBConc = currentConcentrationsLCModel{2,indexMetLCModel};
- MMBConcSim = concentrationsRm(indexFit,indexMetSim);
- if scalingOn
- scaling = MMBConcSim/MMBConc;
- else
- scaling = 1;
- end
- indexMetLCModel = find(strcmp(currentConcentrationsLCModel(1,:),metabolitesLCModel(indexMetabolite)));
- fittedMetConcLCModel(indexFit) = currentConcentrationsLCModel{2,indexMetLCModel}*scaling;
+ allLCModelMetConc(:, indexMetabolite) = fittedMetConcLCModel;
+ allProFitMetConc(:, indexMetabolite) = fittedMetConcProFit;
+ allLCModelMetConcDev(:, indexMetabolite) = (simulatedMetConc-fittedMetConcLCModel)./simulatedMetConc.*100;
+ allProFitMetConcDev(:, indexMetabolite) = (simulatedMetConc-fittedMetConcProFit)./simulatedMetConc.*100;
+end
+end
+
+%% plot Correlation plots between the fitted ProFit, LCModel concentrations and the true simulated concentrations
+function figIdsCorr = plotCorrelationFigs(concentrationsRm, allLCModelMetConc, allProFitMetConc,...
+ metabolitesToDisplay, numberOfMet, dataExportPathBase, paramKeyword, truncSuffix, figIdsCorr)
+
+if isempty(figIdsCorr)
+ emptyFigureIdsCorr = true;
+ figIdsCorr = cell(1,numberOfMet);
+else
+ emptyFigureIdsCorr = false;
+end
+
+% Main Figure = 12 subplots
+figureMainRows = 4;
+figureMainCols = 3;
+metabolitesFigureMain = {'NAA(CH_2)', 'tCr(CH_2)', 'tCho+','Gly','Glu','Gln',...
+ 'Asp', 'GABA', 'Lac', 'GSH', 'NAAG', 'MM spectrum'};
+figID_Main = figure();
+mainFigureRunningIndex = 0;
+% Supporting Figure = 5 subplots
+figureSupportingRows = 3;
+figureSupportingCols = 4;
+metabolitesFigureSupporting = {'tCr(CH_3)', 'mI', 'sI', 'NAA(CH_3)','Tau'};
+figID_Supporting = figure();
+supportingFigureRunningIndex = 0;
+
+colorOriginal = [0 0 0];
+colorProFit = [0.49 0.18 0.56];
+colorLCModel = [0.85 0.33 0.1];
+
+for indexMetabolite = 1:numberOfMet
+ simulatedMetConc = concentrationsRm(:, indexMetabolite);
+ fittedMetConcLCModel = allLCModelMetConc(:, indexMetabolite);
+ fittedMetConcProFit = allProFitMetConc(:, indexMetabolite);
+% if emptyFigureIdsCorr
+% figIdsCorr{indexMetabolite} = figure;
+% end
+% figure(figIdsCorr{indexMetabolite});
+ if sum(contains(metabolitesFigureMain, metabolitesToDisplay{indexMetabolite}))
+ figure(figID_Main);
+ mainFigureRunningIndex = mainFigureRunningIndex + 1;
+ subplot(figureMainRows, figureMainCols, mainFigureRunningIndex);
+ if mod(mainFigureRunningIndex,figureMainCols)== 1
+ plotYLabel = true;
+ else
+ plotYLabel = false;
+ end
+ if round((mainFigureRunningIndex+1)/figureMainCols)== figureMainRows
+ plotXLabel = true;
+ else
+ plotXLabel = false;
end
- fittedMetConcProFit = zeros(size(simulatedMetConc));
- for indexFit = 1:length(concentrationsProFit)
- currentConcentrationsProFit = concentrationsProFit{indexFit}{3};
- indexMetProFit = find(strcmp(activeMetabolites{3},'Cr')); %'Leu'
- MMBConc = currentConcentrationsProFit(indexMetProFit);
- MMBConcSim = concentrationsRm(indexFit,indexMetSim);
-% if scalingOn
-% scaling = MMBConcSim/MMBConc;
-% else
- scaling = 1;
-% end
- indexMetProFit = find(strcmp(activeMetabolites{3},metabolitesProFit(indexMetabolite)));
- fittedMetConcProFit(indexFit) = currentConcentrationsProFit(indexMetProFit)*scaling;
+ elseif sum(contains(metabolitesFigureSupporting, metabolitesToDisplay{indexMetabolite}))
+ figure(figID_Supporting);
+ supportingFigureRunningIndex = supportingFigureRunningIndex + 2;
+ if round((supportingFigureRunningIndex+1)/figureSupportingCols)== figureSupportingRows % offset plot
+ supportingFigureRunningIndex = supportingFigureRunningIndex + 1;
end
- if strcmp(metabolitesProFit(indexMetabolite),'Leu')
- fittedMetConcProFit = fittedMetConcProFit *1e8;
+ subplot(figureSupportingRows, figureSupportingCols, supportingFigureRunningIndex-1:supportingFigureRunningIndex)
+ if mod(supportingFigureRunningIndex-1,figureSupportingCols)<= 2
+ plotYLabel = true;
+ else
+ plotYLabel = false;
end
- allLCModelMetConc(:, indexMetabolite) = fittedMetConcLCModel;
- allProFitMetConc(:, indexMetabolite) = fittedMetConcProFit;
- allLCModelMetConcDev(:, indexMetabolite) = (simulatedMetConc-fittedMetConcLCModel)./simulatedMetConc.*100;
- allProFitMetConcDev(:, indexMetabolite) = (simulatedMetConc-fittedMetConcProFit)./simulatedMetConc.*100;
- if plotCorrelations
- if emptyFigureIdsCorr
- figIdsCorr{indexMetabolite} = figure;
- end
- figure(figIdsCorr{indexMetabolite});
- hold on
- scatter(simulatedMetConc, fittedMetConcLCModel);
- scatter(simulatedMetConc, fittedMetConcProFit, 'x'); % ###
-
-% if ~emptyFigureIdsCorr % ### delete this if later
- plot(simulatedMetConc,simulatedMetConc);
-% end
- title(metabolites(indexMetabolite))
- xlabel('Simulated concentrations [mmol/kg]');
- ylabel('Fitted concentrations [mmol/kg]');
- legend('LCModel concentrations', 'ProFit concentrations', 'Identity Line', 'Location', 'Northwest') %##
- legend('LCModel concentrations', 'Identity Line', 'Location', 'Northwest')
-% legend('\nu_e = all identical T_2', '\nu_e = metabolite specific T_2', 'Identity Line', 'Location', 'Northwest')
- xl = xlim;
- if xl(2) > max(simulatedMetConc)
- xl(2) = max(simulatedMetConc);
- end
- xlim(xl);
-
- pathName = [dataExportPathBase, paramKeyword, '/correlations/'];
- if ~exist(pathName, 'dir')
- mkdir(pathName);
- end
- fileName = [metabolites{indexMetabolite}, '_', paramKeyword, truncSuffix];
- saveas(figIdsCorr{indexMetabolite}, [pathName, fileName, '.tif']);
- savefig(figIdsCorr{indexMetabolite}, [pathName,fileName, '.fig'],'compact');
-% BlandAltman(simulatedMetConc, fittedMetConcLCModel);
-% title(metabolites(indexMetabolite));
-% BlandAltman(simulatedMetConc, fittedMetConcProFit);
-% title(metabolites(indexMetabolite));
+ if round((supportingFigureRunningIndex+1)/figureSupportingCols)>= figureSupportingRows-1
+ plotXLabel = true;
+ else
+ plotXLabel = false;
end
+ else
+ warning('Metabolite not associated with either main or supporting figure: ', metabolitesToDisplay{indexMetabolite});
+ figure();
+ plotYLabel = true;
+ plotXLabel = true;
end
- allLCModelMetConcDev = allLCModelMetConcDev - median(allLCModelMetConcDev,1);
- allProFitMetConcDev = allProFitMetConcDev - median(allProFitMetConcDev,1);
- if plotPrecision
- yLimValue = 100;
- numberOfMet = length(metabolites);
- if isempty(figIds)
- figIds{1} = figure;
- figIds{2} = figure;
- end
- positionsTicks = [2.2:1.5:1.5*numberOfMet+1.5];
- positions = positionsTicks + offsetPlot;
- figure(figIds{1})
- hold on
- boxPlotLCModel = boxplot(allLCModelMetConcDev, metabolites,'colors',plotColors,'symbol','+', 'positions',positions,'width',0.18);
- xtickangle(45)
- title('LCModel')
- ylim([-yLimValue,yLimValue]);
- ylabel('Concentration change [%]')
- set(boxPlotLCModel(:,:),'linewidth',1);
-
- %%
- figure(figIds{2})
- hold on
- boxPlotLCModel = boxplot(allProFitMetConcDev, metabolites,'colors',plotColors,'symbol','+', 'positions',positions,'width',0.18);
- xtickangle(45)
- title('ProFit')
- ylim([-yLimValue,yLimValue]);
- ylabel('Concentration change [%]')
- set(boxPlotLCModel(:,:),'linewidth',1);
+ if strcmp(metabolitesToDisplay(indexMetabolite),'MM spectrum')
+ simulatedMetConc = simulatedMetConc *1e-7;
+ fittedMetConcLCModel = fittedMetConcLCModel *1e-7;
+ fittedMetConcProFit = fittedMetConcProFit *1e-7;
+ end
+ hold on
+ scatter(simulatedMetConc, fittedMetConcLCModel, 15, 'MarkerEdgeColor', colorLCModel);
+ scatter(simulatedMetConc, fittedMetConcProFit, 15, 'x', 'MarkerEdgeColor', colorProFit);
+ offSetEnds = max(simulatedMetConc)*0.05;
+ identityLine = min(simulatedMetConc)-offSetEnds:0.01:max(simulatedMetConc)+offSetEnds;
+ plot(identityLine,identityLine,'color',colorOriginal);
+ title(metabolitesToDisplay(indexMetabolite))
+
+ if plotXLabel
+ xlabel('$c_{k}^{simulated} \,\, (mmol/kg)$', 'Interpreter', 'latex','FontSize', 10)
+ end
+ if plotYLabel
+ ylabel('$c_k^{fitted} \,\, (mmol/kg)$', 'Interpreter', 'latex','FontSize', 10)
+ end
+ legend('$LCModel \,\, c_k^{fitted}$', '$ProFit \,\, c_k^{fitted}$', '$Identity \, Line$', 'Location', 'best', 'Interpreter', 'latex', 'FontSize', 8)
+
+
+ xlim([min(identityLine),max(identityLine)])
+ ylim([min(identityLine),max(identityLine)])
+
+% pathName = [dataExportPathBase, paramKeyword, '/correlations/'];
+% if ~exist(pathName, 'dir')
+% mkdir(pathName);
+% end
+% fileName = [metabolitesToDisplay{indexMetabolite}, '_', paramKeyword, truncSuffix];
+% saveas(figIdsCorr{indexMetabolite}, [pathName, fileName, '.tif']);
+% savefig(figIdsCorr{indexMetabolite}, [pathName,fileName, '.fig'],'compact');
+end
+end
+
+%% plot Precision plots with boxplots showing percentages
+function figIds = plotPrecisionFigs(figIds, numberOfMet, offsetPlot, secondaryFigures, plotColors, ...
+ allLCModelMetConcDev, allProFitMetConcDev, metabolitesLabels)
+
+ yLimValue = 100;
+ if isempty(figIds)
+ % figure('Position',[612,509,1132,469],'OuterPosition',[604,501,1148,562], 'Units','pixels')
+ % figure('Position',[100,275,890,680],'Units','pixels')
+ % figIds{1} = subplot(2,1,2);
+ % figIds{2} = subplot(2,1,1);%, 'Position', [0.58,0.16,0.35,0.76], 'Position', [0.13,0.16,0.35,0.76]
+ %
+ figure('Position',[-908,-589,890,1400],'Units','pixels')
+ figIds{1} = subplot(4,1,2);
+ figIds{2} = subplot(4,1,1);
+ figIds{3} = subplot(4,1,4);
+ figIds{4} = subplot(4,1,3);
end
+ positionsTicks = [2.2:1.5:1.5*numberOfMet+1.5];
+ positions = positionsTicks + offsetPlot;
+ axes(figIds{1 + secondaryFigures})
+ hold on
+ boxPlotLCModel = boxplot(allLCModelMetConcDev, metabolitesLabels,'colors',plotColors,'symbol','+', 'positions',positions,'width',0.18);
+ xticks(positionsTicks)
+ xticklabels(metabolitesLabels)
+ xtickangle(45)
+ xlim([1 27.5])
+ title('LCModel')
+ ylim([-yLimValue,yLimValue]);
+ xlim([positionsTicks(1)-1, positionsTicks(end)+1])
+ set(gca, 'FontSize', 11)
+ ylabel('$Concentration\,\,change\,\,c^\%_{k}\,(\%)$', 'FontSize', 13, 'Interpreter', 'latex')
+ set(boxPlotLCModel(:,:),'linewidth',1);
+ yline(0,':', 'Color',[0.5 0.5 0.5]);
+ %%
+ axes(figIds{2 + secondaryFigures})
+ hold on
+ boxPlotProFit = boxplot(allProFitMetConcDev, metabolitesLabels,'colors',plotColors,'symbol','+', 'positions',positions,'width',0.18);
+ xticks(positionsTicks)
+ xticklabels(metabolitesLabels)
+ xtickangle(45)
+ xlim([1 27.5])
+ title('ProFit')
+ ylim([-yLimValue,yLimValue]);
+ set(gca, 'FontSize', 11)
+ ylabel('$Concentration\,\,change\,\,c^\%_{k}\,(\%)$', 'FontSize', 13, 'Interpreter', 'latex')
+ set(boxPlotProFit(:,:),'linewidth',1);
+ yline(0,':', 'Color',[0.5 0.5 0.5]);
end
+
+%% setup the table to show metabolite concentration changes
+function [metaboliteTable, indexTable] = setupTable(numberOfMet, numOfParameters, metabolitesLabels)
+metaboliteTable = cell(numberOfMet+4,numOfParameters*2+1);
+metaboliteTable(3:numberOfMet+2,1) = metabolitesLabels;
+metaboliteTable{numberOfMet+3,1} = 'Mean';
+metaboliteTable{numberOfMet+4,1} = 'Mean Main Metabolites';
+indexTable = 0;
+end
\ No newline at end of file
diff --git a/createTestData/plotSimulationResults2.m b/createTestData/plotSimulationResults2.m
new file mode 100644
index 0000000000000000000000000000000000000000..a420c1679d3d30a3ef8a693393db19ab6eae0172
--- /dev/null
+++ b/createTestData/plotSimulationResults2.m
@@ -0,0 +1,216 @@
+function plotSimulationResults2()
+
+
+%% path to the export of the spectra
+exportFolder = {'11 Simulations'};
+pathNameExport = 'ProFit test data';
+pathBaseExportFiles = pathToDataFolder(pathNameExport, exportFolder);
+dataExportPathBase = strcat(pathBaseExportFiles, exportFolder{1}, '\');
+
+paramKeyword = 'conc';
+truncSuffix = '_truncOn';
+iterationProFit = 4;
+if contains(paramKeyword,'conc')
+ scalingOn = true;
+else
+ scalingOn = false;
+end
+% name of metabolites in LCModel
+metabolitesLCModel = {'Asp', 'Cr_CH2', 'Cr', 'GABA', 'Gln', 'Glu', 'Glyc', 'GSH', 'Lac', 'mI', 'NAA_as', 'NAA_ac', 'NAAG', 'tCho_P', 'Scyllo', 'Tau', 'Leu'};
+
+% name of metabolites in ProFit
+metabolitesProFit = {'Asp', 'Cr_CH2', 'Cr', 'GABA', 'Gln', 'Glu', 'Glyc', 'GSH', 'Lac', 'mI', 'NAA_as', 'NAA_ac', 'NAAG', 'tCho_P', 'Scyllo', 'Tau', 'Leu'};
+
+%% load simulated data
+load([dataExportPathBase, 'concentrations_simulated_', paramKeyword, '.mat'], 'concentrationsRm', 'metabolites', 'metaboliteNames');
+
+%% load fitted data LCModel
+load([dataExportPathBase, 'concentrations_', paramKeyword, truncSuffix, '.mat'], 'concentrations');
+concentrationsLCModel = concentrations;
+
+%% load fitted data ProFit
+load([dataExportPathBase, 'concentrations_', paramKeyword, truncSuffix, '_profit.mat'], 'concentrations', 'activeMetabolites');
+concentrationsProFit = concentrations;
+
+plotCorrelations = true;
+plotColors = {[0 0 1], [1 0 0]};
+% plotColors2 = {[0.0 0.4 0.0], [1 0.5 0.3]};
+plotColors2 = {[0.0 0.4 0.0], [0 0 0], [1 0.5 0.3], [0.49 0.18 0.56]};
+offsetPlot = 0.2;
+
+plotCorrelations = false;
+plotPrecision = true;
+
+%%
+paramKeyword = 'baseline';
+% load simulated data
+load([dataExportPathBase, 'concentrations_simulated_', paramKeyword, '.mat'], 'concentrationsRm', 'metabolites', 'metaboliteNames');
+% load fitted data LCModel
+load([dataExportPathBase, 'concentrations_', paramKeyword, '_dkntmn0.15', truncSuffix, '.mat'], 'concentrations');
+concentrationsLCModel = concentrations;
+% load fitted data ProFit
+load([dataExportPathBase, 'concentrations_', paramKeyword, truncSuffix, '_profit.mat'], 'concentrations', 'activeMetabolites');
+concentrationsProFit = concentrations;
+offsetPlot = -0.4;
+[allSimulMetConc, allLCModelMetConc, allProFitMetConc, allLCModelMetConcDev, allProFitMetConcDev, figIds, figIdsCorr, meanError_015] = getConcentrations(...
+ metabolites, metabolitesLCModel, metabolitesProFit, ...
+ concentrationsRm, concentrationsLCModel, concentrationsProFit, activeMetabolites, ...
+ scalingOn, plotCorrelations, dataExportPathBase, paramKeyword, truncSuffix, ...
+ plotPrecision, plotColors2{3}, offsetPlot, [], []);
+%%
+paramKeyword = 'baseline';
+% load simulated data
+load([dataExportPathBase, 'concentrations_simulated_', paramKeyword, '.mat'], 'concentrationsRm', 'metabolites', 'metaboliteNames');
+% load fitted data LCModel
+load([dataExportPathBase, 'concentrations_', paramKeyword, '_dkntmn0.25', truncSuffix, '.mat'], 'concentrations');
+concentrationsLCModel = concentrations;
+% load fitted data ProFit
+load([dataExportPathBase, 'concentrations_', paramKeyword, truncSuffix, '_profit.mat'], 'concentrations', 'activeMetabolites');
+concentrationsProFit = concentrations;
+offsetPlot = 0.;
+[allSimulMetConc, allLCModelMetConc, allProFitMetConc, allLCModelMetConcDev, allProFitMetConcDev, figIds, figIdsCorr, meanError_025] = getConcentrations(...
+ metabolites, metabolitesLCModel, metabolitesProFit, ...
+ concentrationsRm, concentrationsLCModel, concentrationsProFit, activeMetabolites, ...
+ scalingOn, plotCorrelations, dataExportPathBase, paramKeyword, truncSuffix, ...
+ plotPrecision, plotColors2{4}, offsetPlot, figIds, []);
+%%
+paramKeyword = 'baseline';
+% load simulated data
+load([dataExportPathBase, 'concentrations_simulated_', paramKeyword, '.mat'], 'concentrationsRm', 'metabolites', 'metaboliteNames');
+% load fitted data LCModel
+load([dataExportPathBase, 'concentrations_', paramKeyword, '_dkntmn0.5', truncSuffix, '.mat'], 'concentrations');
+concentrationsLCModel = concentrations;
+% load fitted data ProFit
+load([dataExportPathBase, 'concentrations_', paramKeyword, truncSuffix, '_profit.mat'], 'concentrations', 'activeMetabolites');
+concentrationsProFit = concentrations;
+offsetPlot = 0.4;
+[allSimulMetConc, allLCModelMetConc, allProFitMetConc, allLCModelMetConcDev, allProFitMetConcDev, figIds, figIdsCorr, meanError_05] = getConcentrations(...
+ metabolites, metabolitesLCModel, metabolitesProFit, ...
+ concentrationsRm, concentrationsLCModel, concentrationsProFit, activeMetabolites, ...
+ scalingOn, plotCorrelations, dataExportPathBase, paramKeyword, truncSuffix, ...
+ plotPrecision, plotColors2{2}, offsetPlot, figIds, []);
+
+txt = {'LCModel Setup/error', ['orange: dkntmn=0.15 / ', num2str(meanError_015,3)], ...
+ ['purple: dkntmn=0.25 / ', num2str(meanError_025,3)], [' black: dkntmn=0.5 / ', num2str(meanError_05,3)]};
+title(txt, 'Interpreter','latex','FontSize', 14)
+end
+
+function [allSimulMetConc, allLCModelMetConc, allProFitMetConc, allLCModelMetConcDev, allProFitMetConcDev, figIds, figIdsCorr, meanError] = ...
+ getConcentrations(metabolites, metabolitesLCModel, metabolitesProFit, ...
+ concentrationsRm, concentrationsLCModel, concentrationsProFit, activeMetabolites, ...
+ scalingOn, plotCorrelations, dataExportPathBase, paramKeyword, truncSuffix, ...
+ plotPrecision, plotColors, offsetPlot, figIds, figIdsCorr)
+
+ iterationProFit = 4;
+ if isempty(figIdsCorr)
+ emptyFigureIdsCorr = true;
+ figIdsCorr = cell(1,length(metabolites));
+ else
+ emptyFigureIdsCorr = false;
+ end
+ allSimulMetConc = concentrationsRm;
+ allLCModelMetConc = zeros(size(allSimulMetConc));
+ allProFitMetConc = zeros(size(allSimulMetConc));
+ allLCModelMetConcDev = zeros(size(allSimulMetConc));
+ allProFitMetConcDev = zeros(size(allSimulMetConc));
+ for indexMetabolite = 1:length(metabolites)
+ simulatedMetConc = concentrationsRm(:, indexMetabolite);
+ indexMetSim = find(strcmp(metabolites,'tCr(CH3)')); %'MMB'
+ fittedMetConcLCModel = zeros(size(simulatedMetConc));
+ for indexFit = 1:length(concentrationsLCModel)
+ currentConcentrationsLCModel = concentrationsLCModel{indexFit};
+ indexMetLCModel = find(strcmp(currentConcentrationsLCModel(1,:),'Cr')); %'Leu'
+ MMBConc = currentConcentrationsLCModel{2,indexMetLCModel};
+ MMBConcSim = concentrationsRm(indexFit,indexMetSim);
+ if scalingOn
+ scaling = MMBConcSim/MMBConc;
+ else
+ scaling = 1;
+ end
+ indexMetLCModel = find(strcmp(currentConcentrationsLCModel(1,:),metabolitesLCModel(indexMetabolite)));
+ fittedMetConcLCModel(indexFit) = currentConcentrationsLCModel{2,indexMetLCModel}*scaling;
+ end
+ fittedMetConcProFit = zeros(size(simulatedMetConc));
+% for indexFit = 1:length(concentrationsProFit)
+% currentConcentrationsProFit = concentrationsProFit{indexFit}{iterationProFit};
+% indexMetProFit = find(strcmp(activeMetabolites{iterationProFit},'Cr')); %'Leu'
+% MMBConc = currentConcentrationsProFit(indexMetProFit);
+% MMBConcSim = concentrationsRm(indexFit,indexMetSim);
+% % if scalingOn
+% % scaling = MMBConcSim/MMBConc;
+% % else
+% scaling = 1;
+% % end
+% indexMetProFit = find(strcmp(activeMetabolites{iterationProFit},metabolitesProFit(indexMetabolite)));
+% fittedMetConcProFit(indexFit) = currentConcentrationsProFit(indexMetProFit)*scaling;
+% end
+% if strcmp(metabolitesProFit(indexMetabolite),'Leu')
+% fittedMetConcProFit = fittedMetConcProFit *1e8;
+% end
+ allLCModelMetConc(:, indexMetabolite) = fittedMetConcLCModel;
+ allProFitMetConc(:, indexMetabolite) = fittedMetConcProFit;
+ allLCModelMetConcDev(:, indexMetabolite) = (simulatedMetConc-fittedMetConcLCModel)./simulatedMetConc.*100;
+ allProFitMetConcDev(:, indexMetabolite) = (simulatedMetConc-fittedMetConcProFit)./simulatedMetConc.*100;
+ if plotCorrelations
+ if emptyFigureIdsCorr
+ figIdsCorr{indexMetabolite} = figure;
+ end
+ figure(figIdsCorr{indexMetabolite});
+ hold on
+ scatter(simulatedMetConc, fittedMetConcLCModel);
+ scatter(simulatedMetConc, fittedMetConcProFit, 'x'); % ###
+
+% if ~emptyFigureIdsCorr % ### delete this if later
+ plot(simulatedMetConc,simulatedMetConc);
+% end
+ title(metabolites(indexMetabolite))
+ xlabel('Simulated concentrations [mmol/kg]');
+ ylabel('Fitted concentrations [mmol/kg]');
+ legend('LCModel concentrations', 'ProFit concentrations', 'Identity Line', 'Location', 'Northwest') %##
+% legend('LCModel concentrations', 'Identity Line', 'Location', 'Northwest')
+% legend('\nu_e = all identical T_2', '\nu_e = metabolite specific T_2', 'Identity Line', 'Location', 'Northwest')
+ xl = xlim;
+ if xl(2) > max(simulatedMetConc)
+ xl(2) = max(simulatedMetConc);
+ end
+ xlim(xl);
+
+ pathName = [dataExportPathBase, paramKeyword, '/correlations/'];
+ if ~exist(pathName, 'dir')
+ mkdir(pathName);
+ end
+ fileName = [metabolites{indexMetabolite}, '_', paramKeyword, truncSuffix];
+ saveas(figIdsCorr{indexMetabolite}, [pathName, fileName, '.tif']);
+ savefig(figIdsCorr{indexMetabolite}, [pathName,fileName, '.fig'],'compact');
+% BlandAltman(simulatedMetConc, fittedMetConcLCModel);
+% title(metabolites(indexMetabolite));
+% BlandAltman(simulatedMetConc, fittedMetConcProFit);
+% title(metabolites(indexMetabolite));
+ end
+ end
+
+ allLCModelMetConcDev = allLCModelMetConcDev - median(allLCModelMetConcDev,1, 'omitnan');
+ allProFitMetConcDev = allProFitMetConcDev - median(allProFitMetConcDev,1, 'omitnan');
+ meanError =0;
+ if plotPrecision
+ yLimValue = 50;
+ numberOfMet = length(metabolites);
+ if isempty(figIds)
+ figIds{1} = figure;
+ figIds{2} = figure;
+ end
+ positionsTicks = [3:1.5:1.5*numberOfMet+1.5];
+ positions = positionsTicks + offsetPlot;
+ figure(figIds{1})
+ hold on
+ boxPlotLCModel = boxplot(allLCModelMetConcDev, metabolites,'colors',plotColors,'symbol','+', 'positions',positions,'width',0.3);
+ xtickangle(45)
+ title('LCModel')
+ ylim([-yLimValue,yLimValue]);
+ xlim([positionsTicks(1)-1, positionsTicks(end)+1])
+ ylabel('Concentration change [%]')
+ set(boxPlotLCModel(:,:),'linewidth',1);
+ meanLCModelMetConcDev = mean(abs(allLCModelMetConcDev),1, 'omitnan');
+ meanError = mean(meanLCModelMetConcDev)
+ end
+end
diff --git a/createTestData/plot_ProFit_Metabolites_Fit.m b/createTestData/plot_ProFit_Metabolites_Fit.m
index a5feb5c70ba76f6f8b18f95317af96b8ce85512f..9d7a702829637c758284ba8f5cbbf38a6152edd2 100644
--- a/createTestData/plot_ProFit_Metabolites_Fit.m
+++ b/createTestData/plot_ProFit_Metabolites_Fit.m
@@ -1,4 +1,4 @@
-function [concentrations, activeMetabolites] = plot_ProFit_Metabolites_Fit(FileName, PathName, downField_MM_Met, saveFigures)
+function [concentrations, activeMetabolites, FQNs, FQNs2] = plot_ProFit_Metabolites_Fit(FileName, PathName, downField_MM_Met, saveFigures, displayBaseline)
if ~exist('FileName', 'var')
[FileName,PathName] = uigetfile('*.mat','Please select .mat files from ProFit output','Multiselect','on');
@@ -14,8 +14,11 @@ end
if ~exist('saveFigures','var')
saveFigures = false;
end
+if ~exist('displayBaseline','var')
+ displayBaseline = false;
+end
-iterations = 3;%:4;
+iterations = 4;
switch downField_MM_Met
case 'Met moiety'
@@ -35,7 +38,7 @@ switch downField_MM_Met
metaboliteLabels = {'Asp';'Cr';'PCr';'GABA';'Glu';'Gln';'GSH';'Glyc';'Lac';'mI';'NAA';'NAAG';'Scyllo';'Tau';'PCh';'GPC';'PE'};
metaboliteNames = {'Asp' 'Cr' 'Cr_CH2' 'GABA' 'Glu' 'Gln' 'GSH' 'Glyc' 'Lac' 'mI' 'NAA_as' 'NAA_ac' 'NAAG' 'Scyllo' 'Tau' 'tCho_P'};
- metaboliteLabels = {'Asp';'Cr(CH3)';'Cr(CH2)';'GABA';'Glu';'Gln';'GSH';'Glyc';'Lac';'mI';'NAA(CH2)';'NAA(CH3)'; 'NAAG';'Scyllo';'Tau';'tCho+';};
+ metaboliteLabels = {'Asp';'tCr(CH_3)';'tCr(CH_2)';'GABA';'Glu';'Gln';'GSH';'Gly';'Lac';'mI';'NAA(CH_2)';'NAA(CH_3)'; 'NAAG';'sI';'Tau';'tCho+';};
% %Braino
% metaboliteNames = {'Cr_CH3' 'Cr_CH2' 'Glu' 'Lac' 'mI' 'NAA_as' 'NAA_ac' 'Cho'};
@@ -82,6 +85,8 @@ rData = {};
% close all;
concentrations = cell(length(FileName),length(iterations));
activeMetabolites = cell(length(FileName),length(iterations));
+FQNs = cell(length(FileName),length(iterations));
+FQNs2 = cell(length(FileName),length(iterations));
for iteration = iterations
for index =1:length(FileName)
@@ -92,39 +97,30 @@ for iteration = iterations
% get mean values for pc0, pc1 and df1, df2
% values which should be applied on spectra and not the basis set
pc0 = zeros(1, currentFitresult.nr_act_mets);
- pc11 = zeros(1, currentFitresult.nr_act_mets);
pc12 = zeros(1, currentFitresult.nr_act_mets);
- df1 = zeros(1, currentFitresult.nr_act_mets);
df2 = zeros(1, currentFitresult.nr_act_mets);
for met_cnt=1:currentFitresult.nr_act_mets
pc0(met_cnt) = currentFitresult.fitted_values.pc0(currentFitresult.sub_mask.pc0.full(:,met_cnt));
- pc11(met_cnt) = currentFitresult.fitted_values.pc11(currentFitresult.sub_mask.pc11.full(:,met_cnt));
pc12(met_cnt) = currentFitresult.fitted_values.pc12(currentFitresult.sub_mask.pc12.full(:,met_cnt));
- df1(met_cnt) = currentFitresult.fitted_values.df1(currentFitresult.sub_mask.df1.full(:,met_cnt));
df2(met_cnt) = currentFitresult.fitted_values.df2(currentFitresult.sub_mask.df2.full(:,met_cnt));
end
- mean_pc0 = mean(pc0);
- mean_pc11 = mean(pc11);
- mean_pc12 = mean(pc12);
- mean_df1 = mean(df1);
- mean_df2 = mean(df2);
- total_pc0 = currentFitresult.preprocessedValues.pc0 + mean_pc0;
- total_df1 = currentFitresult.preprocessedValues.df1 + mean_df1;
- total_df2 = currentFitresult.preprocessedValues.df2 + mean_df2;
%ppm axis
ppm{index} = currentFitresult.common_data.data.fitroi.ppm2;
%phaseData
- pData{index} = currentFitresult.fitroi_spec;
+ pData{index} = currentFitresult.processed_spec;
%fit data
fData{index} = currentFitresult.fitted_spec;
%residual
rData{index} = currentFitresult.residual_spec;
%spline baseline
- spBB = currentFitresult.splines_baseline.basis_matrix;
- concSpline = currentFitresult.splines_baseline.coeff;
- bData{index} = (spBB * concSpline(1:size(spBB,2)))';
-
+ if ~isempty(currentFitresult.splines_baseline)
+ spBB = currentFitresult.splines_baseline.basis_matrix;
+ concSpline = currentFitresult.splines_baseline.coeff;
+ bData{index} = (spBB * concSpline(1:size(spBB,2)))';
+ else
+ bData{index} = zeros(size(currentFitresult.residual_spec));
+ end
%Macromolecular baseline
if strcmp(downField_MM_Met,'Met') || strcmp(downField_MM_Met,'Met moiety')
indexMMB = find(strcmp(currentFitresult.met(currentFitresult.active_mets), 'Leu'));
@@ -145,22 +141,38 @@ for iteration = iterations
end
%scaling calculation
- scale = max(pData{index});
+ scale = real(max(pData{index}));
%plotting
hold on
- if MMB_available
- p = plot(ppm{index}, (pData{index} - bData{index}) ./ scale, ...
- ppm{index},(fData{index} - bData{index}) ./ scale, ...
- ppm{index}, mmData{index} ./ scale - 0.03, ...
- ppm{index},bData{index} ./ scale - offsetBaseline, ...
- ppm{index},rData{index} ./ scale - offsetResidual);
- text(xLimitsText,-0.03,'MMB', 'FontSize', FontSize);
+ if displayBaseline
+ if MMB_available
+ p = plot(ppm{index}, pData{index} ./ scale, ...
+ ppm{index},fData{index} ./ scale, ...
+ ppm{index}, mmData{index} ./ scale - 0.03, ...
+ ppm{index},bData{index} ./ scale - offsetBaseline, ...
+ ppm{index},rData{index} ./ scale - offsetResidual);
+ text(xLimitsText,-0.03,'MM spectrum', 'FontSize', FontSize);
+ else
+ p = plot(ppm{index}, pData{index} ./ scale, ...
+ ppm{index},fData{index} ./ scale, ...
+ ppm{index},bData{index} ./ scale - offsetBaseline, ...
+ ppm{index},rData{index} ./ scale - offsetResidual);
+ end
else
- p = plot(ppm{index}, (pData{index} - bData{index}) ./ scale, ...
- ppm{index},(fData{index} - bData{index}) ./ scale, ...
- ppm{index},bData{index} ./ scale - offsetBaseline, ...
- ppm{index},rData{index} ./ scale - offsetResidual);
+ if MMB_available
+ p = plot(ppm{index}, (pData{index} - bData{index}) ./ scale, ...
+ ppm{index},(fData{index} - bData{index}) ./ scale, ...
+ ppm{index}, mmData{index} ./ scale - 0.03, ...
+ ppm{index},bData{index} ./ scale - offsetBaseline, ...
+ ppm{index},rData{index} ./ scale - offsetResidual);
+ text(xLimitsText,-0.03,'MM spectrum', 'FontSize', FontSize);
+ else
+ p = plot(ppm{index}, (pData{index} - bData{index}) ./ scale, ...
+ ppm{index},(fData{index} - bData{index}) ./ scale, ...
+ ppm{index},bData{index} ./ scale - offsetBaseline, ...
+ ppm{index},rData{index} ./ scale - offsetResidual);
+ end
end
text(xLimitsText,0.05,'Data + Fit', 'FontSize', FontSize);
@@ -199,11 +211,18 @@ for iteration = iterations
set(gca,'fontsize',FontSize);
if saveFigures
- set(figId, 'Units', 'Normalized', 'OuterPosition', [0, 0.04, 1, 0.96]);
+ set(figId, 'Units', 'Normalized', 'OuterPosition', [0, 0.04, 1, 0.96]);
+ set(gca, 'Position', [0.13,0.11,0.75,0.815])
+% set(gca, 'Position', [0.13,0.11,0.75,0.88])
saveas(figId, [PathName,FileName{index}(1:end-4), '_iter', num2str(iteration), '.tif']);
savefig(figId, [PathName,FileName{index}(1:end-4), '_iter', num2str(iteration), '.fig'],'compact');
end
[concentrations{index,iteration}, activeMetabolites{index,iteration}] = saveFitResultsTable(currentFitresult, saveFigures, PathName, FileName{index}, iteration);
+
+ FQN2 = calculate_fit_quality_number(currentFitresult.residual_spec, currentFitresult.common_data.data.fitroi.ppm2, ...
+ currentFitresult.common_data.spec, currentFitresult.common_data.data.ppm2, [1.95 4.0]);
+ FQNs{index,iteration} = currentFitresult.fit_quality_number;
+ FQNs2{index,iteration} = FQN2;
end
end
end
@@ -218,13 +237,14 @@ active_met_names = currentFitresult.met(currentFitresult.active_mets);
dataOfTable={};
columnname = {'met','conc', '/Cr', '<html>crlb<br />[%]</html>', ...
'<html>T2<br />[ms]</html>','<html>em<br />[Hz]</html>',...
- '<html>gm<br />[Hz]</html>', '<html>em_g<br />[Hz]</html>', ...
- '<html>pc0<br />[deg]</html>', '<html>df1<br />[Hz]</html>', ...
- '<html>df2<br />[Hz]</html>', '<html>pc11<br />[deg/ppm]</html>', ...
+ '<html>gm<br />[Hz]</html>', ...
+ '<html>pc0<br />[deg]</html>', '<html>df2<br />[Hz]</html>', ...
'<html>pc12<br />[deg/ppm]</html>'};
-columnformat={'char',[],[],[],[],[],[],[],[],[],[],[],[]};
+columnformat={'char',[],[],[],[],[],[],[],[],[],[]};
concentrations = zeros(1,currentFitresult.nr_act_mets);
creatineConc = currentFitresult.GetFittedValues({'Cr'},{'conc'});
+
+boundsTable = zeros(currentFitresult.nr_act_mets,10);
for met_cnt=1:currentFitresult.nr_act_mets
dataOfTable=[dataOfTable;{...
active_met_names{met_cnt},...
@@ -241,21 +261,46 @@ for met_cnt=1:currentFitresult.nr_act_mets
currentFitresult.sub_mask.em.full(:,met_cnt)'),'%6.4f'),...
num2str(currentFitresult.fitted_values.gm(...
currentFitresult.sub_mask.gm.full(:,met_cnt)'),'%6.4f'),...
- num2str(currentFitresult.fitted_values.em_g(...
- currentFitresult.sub_mask.em_g.full(:,met_cnt)'),'%6.4f'),...
num2str(currentFitresult.fitted_values.pc0(...
currentFitresult.sub_mask.pc0.full(:,met_cnt)'),'%6.4f'),...
- num2str(currentFitresult.fitted_values.df1(...
- currentFitresult.sub_mask.df1.full(:,met_cnt)'),'%6.4f'),...
num2str(currentFitresult.fitted_values.df2(...
currentFitresult.sub_mask.df2.full(:,met_cnt)'),'%6.4f'),...
- num2str(currentFitresult.fitted_values.pc11(...
- currentFitresult.sub_mask.pc11.full(:,met_cnt)'),'%6.4f'),...
num2str(currentFitresult.fitted_values.pc12(...
currentFitresult.sub_mask.pc12.full(:,met_cnt)'),'%6.4f')...
}];
concentrations(met_cnt) = currentFitresult.fitted_values.conc(currentFitresult.sub_mask.conc.full(:,met_cnt)');
+ boundsTable(met_cnt,:) = [...
+ 0,...
+ checkBounds(currentFitresult,'conc', met_cnt),...
+ 0,... %conc/Cr
+ 0,... %crlb
+ 0,... % T2
+ checkBounds(currentFitresult,'em', met_cnt),...
+ checkBounds(currentFitresult,'gm', met_cnt),...
+ checkBounds(currentFitresult,'pc0', met_cnt),...
+ checkBounds(currentFitresult,'df2', met_cnt),...
+ checkBounds(currentFitresult,'pc12', met_cnt),...
+ ];
end
+%reached upper bounds- blue
+idx = boundsTable == 1;
+dataOfTable(idx) = strcat(...
+ '<html><span style="color: #0000FF; font-weight: bold;">', ...
+ dataOfTable(idx), ...
+ '</span></html>');
+%reached lower bounds - red
+idx = boundsTable == -1;
+dataOfTable(idx) = strcat(...
+ '<html><span style="color: #FF0000; font-weight: bold;">', ...
+ dataOfTable(idx), ...
+ '</span></html>');
+%reached both bounds - green
+idx = isnan(boundsTable);
+dataOfTable(idx) = strcat(...
+ '<html><span style="color: #00FF00; font-weight: bold;">', ...
+ dataOfTable(idx), ...
+ '</span></html>');
+
tableProfit = uitable(...%'Units','normalized',...%
'Position',[20 20 850 580],'Data', dataOfTable,...
'ColumnName', columnname,'ColumnFormat',columnformat,...
@@ -267,21 +312,31 @@ if saveFigures
end
end
-function spec = applyGlobalFactors(spec, pc0, pc12, df1, df2, data)
-
- spec_roi = [data.fitroi.bounds(1,1) data.fitroi.bounds(1,2); data.fitroi.bounds(2,1) data.fitroi.bounds(2,2)];
- coeff_F2_degree_ppm = 1i*pc12*pi/180;
- spec = spec .* exp( ...
- ... applying the F2 corrections ...
- coeff_F2_degree_ppm * data.phase_1_f2_mx(spec_roi(1,1):spec_roi(2,1), spec_roi(1,2):spec_roi(2,2)));
- fid = ifft(ifftshift(spec)); %TODO check, do we need the ifftshift
- % zero order phase correction
- fid = fid .* exp(1i*-pc0*pi/180*data.phase_0_mx);
-
- % frequency shift in the F1
- fid = fid .* exp(1i*-df1*2*pi*data.shift_t1_mx);
-
- % frequency shift in the F2
- fid = fid .* exp(1i*-df2*2*pi*data.shift_t2_mx);
- spec = fftshift(fft(fid));
-end
\ No newline at end of file
+function bounds = checkBounds(currentFitresult,param, met_cnt)
+ % bounds = 0 : no bounds reached
+ % bounds = 1 : upper bounds reached
+ % bounds = -1 : lower bounds reached
+ % bounds = NaN : both bounds reached
+ bounds = 0;
+ factorBounds = 1.1; %within 10% from bound
+ sub_mask = eval(['currentFitresult.sub_mask.', param, '.full(:,met_cnt)'])';
+ preprocessed_value = 0;
+ try %should work for pc0, pc12, df2 (df2_global is not a parameter of interest)
+ preprocessed_value = eval(['currentFitresult.preprocessedValues.' param]);
+ catch
+ %nothing
+ end
+ fitted_value = eval(['currentFitresult.fitted_values.', param])-preprocessed_value;
+ if (eval(['currentFitresult.full_upper_bounds.', param,'(sub_mask)']) < ...
+ (fitted_value(sub_mask) * factorBounds))
+ bounds = 1;
+ end
+ if (eval(['currentFitresult.full_lower_bounds.', param,'(sub_mask)']) > ...
+ (fitted_value(sub_mask) / factorBounds))
+ if bounds == 0
+ bounds = -1; %reached only lower bounds
+ else
+ bounds = NaN; %reached both bounds
+ end
+ end
+end
diff --git a/createTestData/plot_all_test_data_profit.m b/createTestData/plot_all_test_data_profit.m
index e1c45fe62c7aca3cc6be233e073a6bc47030a2c0..bba246e127d4e0b6b907406286a063495378d13c 100644
--- a/createTestData/plot_all_test_data_profit.m
+++ b/createTestData/plot_all_test_data_profit.m
@@ -1,26 +1,24 @@
function plot_all_test_data_profit()
-fitLCModel = true; %false fits profit
+
reconOption = 5;
truncOn = false;
offsetScatter = 0.3;
markerScatter = 'o';
markerColor = [1 0 0];
-fitLCModel = true; %false fits profit
reconOption = 6;
truncOn = false;
offsetScatter = 0;
markerScatter = 'd';
markerColor = [0 1 0];
-%
+%
reconOption = 2;
-truncOn = false;
-offsetScatter = -0.3;
+truncOn = true;
+offsetScatter = 0.15;
markerScatter = 'x';
markerColor = [1 0 0];
-plotInSameFigureAllSubjects = true;
exportFolders = {'0 Water References',...
'1 Normal recon', '2 Removed averages ','3 Removed coils',...
@@ -28,6 +26,10 @@ exportFolders = {'0 Water References',...
'7 Rescale off', '8 Rescale Water Supp Off'};
pathNameExport = 'ProFit test data';
pathBaseExportFiles = pathToDataFolder(pathNameExport, exportFolders);
+
+pathBaseExportFiles = pathBaseExportFiles(1:end-1);
+pathBaseExportFiles = [pathBaseExportFiles ' - R3\'];
+
dataExportPathBaseRef = strcat(pathBaseExportFiles, exportFolders{2}, '\');
dataExportPathBase = strcat(pathBaseExportFiles, exportFolders{reconOption+1}, '\');
@@ -60,21 +62,327 @@ else
end
subjects = { ...
- '1658' ...
- '1717' ...
- '2017' ...
- '3373' ...
- '3490' ...
- '5771' ...
- '6249' ...
- '6971' ...
- '7338' ...
- '7782' ...
- '9810' ...
+ 'Subj_1' ...
+ 'Subj_2' ...
+ 'Subj_3' ...
+ 'Subj_4' ...
+ 'Subj_5' ...
+ 'Subj_6' ...
+ 'Subj_7' ...
+ 'Subj_8' ...
+ 'Subj_9' ...
+ 'Subj_10' ...
+ 'Subj_11' ...
};
TEs = [24;];% 32; 40; 52; 60];
+% name of metabolites in LCModel
+metabolitesLCModel = {'Asp', 'Cr_CH2', 'Cr', 'GABA', 'Gln', 'Glu', 'Glyc', 'GSH', 'Lac', 'mI', 'NAA_as', 'NAA_ac', 'NAAG', 'tCho_P', 'Scyllo', 'Tau', 'Leu'};
+
+% name of metabolites in ProFit
+metabolitesProFit = {'Asp', 'Cr_CH2', 'Cr', 'GABA', 'Gln', 'Glu', 'Glyc', 'GSH', 'Lac', 'mI', 'NAA_as', 'NAA_ac', 'NAAG', 'tCho_P', 'Scyllo', 'Tau', 'Leu'};
+
+% name of metabolites to display
+metabolitesToDisplay = {'Asp', 'tCr(CH_2)', 'tCr(CH_3)', 'GABA', 'Gln', 'Glu', 'Gly', 'GSH', 'Lac', 'mI', 'NAA(CH_2)', 'NAA(CH_3)', 'NAAG', 'tCho+', 'sI', 'Tau', 'MM spectrum'};
+metabolitesLabels = {'Asp', 'tCr(CH2)', 'tCr(CH3)', 'GABA', 'Gln', 'Glu', 'Gly', 'GSH', 'Lac', 'mI', 'NAA(CH2)', 'NAA(CH3)', 'NAAG', 'tCho+', 'sI', 'Tau', 'MM spectrum'};
+
+numberOfMet = length(metabolitesLabels);
+indecesMainMet = zeros(1,numberOfMet);
+mainMetabolites = { 'tCr(CH3)', 'tCr(CH2)', 'Glu', 'mI', 'NAA(CH2)', 'NAA(CH3)', 'tCho+'};
+for indexMet = 1:numberOfMet
+ indecesMainMet(indexMet) = ~isempty(find(strcmp(mainMetabolites,metabolitesLabels{indexMet}), 1));
+end
+indecesMainMet = logical(indecesMainMet);
+
+fitLCModel = true; %false fits profit
+if fitLCModel
+ SoftwareName = 'LCModel';
+else
+ SoftwareName = 'ProFit';
+end
+[metConcAllSubjLCModel, metConcAllSubjRefLCModel, metConcAllSubjNormLCModel, MC_H2O_ConcAllSubjLCModel, MC_H2O_ConcAllSubjRefLCModel] = ...
+ 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, MC_H2O_ConcAllSubjProFit, MC_H2O_ConcAllSubjRefProFit] = ...
+ 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 = 'Repeatability '; % figure title
+subsets = {'32 ave.1','32 ave.2','32 ave.3', '64 ave.1', '64 ave.2', '64 ave.3'};
+subsets_refit = {'32 ave.', '64 ave.'};
+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_refit = {'c^{fits1}_{i,k}','c^{fits2}_{i,k}','arb.u.'}; % 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
+BAinfo_refit = {''}; % 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
+
+paramsBA.data1TreatmentMode = 'Compare';
+paramsBA.diffValueMode = 'percent';
+
+numOfSimulations = length(namingSuffixesAve)*length(namingSuffixesCoil);
+
+%there seems to be a fit error in the fitting of even the MC water data.
+% BlandAltman(MC_H2O_ConcAllSubjLCModel, MC_H2O_ConcAllSubjProFit*1e-6, label_SW_comp,[tit 'Water'],subsets,...
+% 'corrInfo',corrinfo,'baInfo',BAinfo,'axesLimits',limits,'showFitCI',' on',...
+% 'baStatsMode','Gaussian','forceZeroIntercept','on', 'diffValueMode', 'percent');
+%
+% BlandAltman(MC_H2O_ConcAllSubjRefLCModel, MC_H2O_ConcAllSubjRefProFit*1e-6, label_SW_comp,[tit 'Water'],subsets,...
+% 'corrInfo',corrinfo,'baInfo',BAinfo,'axesLimits',limits,'showFitCI',' on',...
+% 'baStatsMode','Gaussian','forceZeroIntercept','on', 'diffValueMode', 'percent');
+
+rpc_table = cell(numberOfMet+5,5);
+rpc_table{1,2} = softwareNames{1};
+rpc_table{1,4} = softwareNames{2};
+rpc_table{2,2} = subsets_refit{1};
+rpc_table{2,3} = subsets_refit{2};
+rpc_table{2,4} = subsets_refit{1};
+rpc_table{2,5} = subsets_refit{2};
+rpc_table(3:end-3,1) = metabolitesToDisplay;
+rpc_table{end-1,1} = 'Mean Main';
+rpc_table{end,1} = 'Mean';
+
+%title('Reproducibility');
+subplotsX = 4;
+subplotsY = 4;
+totalSubplots1 = subplotsX * subplotsY;
+rpcSum = zeros(1,numberOfMet);
+diffMedian = zeros(1,numberOfMet);
+for indexMet = 1: numberOfMet
+ if indexMet == metaboliteRef
+ continue;
+ end
+ if (indexMet == 1) || (indexMet == totalSubplots1/2+1)
+ figure;
+ if indexMet >= 8
+ subplotsX = 6;
+ subplotsY = 3;
+ totalSubplots = subplotsX * subplotsY;
+ end
+ end
+ if indexMet <= totalSubplots1/2
+ runningIndexPlot = (indexMet-1)+1+floor((indexMet-1)/subplotsY)*subplotsY-floor((indexMet-1)/totalSubplots1*2)*totalSubplots1;
+ else
+ indexMet2 = indexMet - totalSubplots1/2;
+ runningIndexPlot = (indexMet2-1)+1+floor((indexMet2-1)/subplotsY)*subplotsY-floor((indexMet2-1)/totalSubplots*2)*totalSubplots;
+ end
+
+ %ProFit Concentrations
+ metConcAllSubjProFitScaled_ = metConcAllSubjProFitScaled(:, :, indexMet);
+ metConcAllSubjProFitScaled_ = reshape(metConcAllSubjProFitScaled_,11*3,2);%group same SNR
+ metConcAllSubjRefProFitScaled_ = metConcAllSubjRefProFitScaled(:, indexMet);
+ metConcAllSubjRefProFitScaled_ = repmat(metConcAllSubjRefProFitScaled_,1,6);
+ metConcAllSubjRefProFitScaled_ = reshape(metConcAllSubjRefProFitScaled_,11*3,2);%group same SNR
+
+ %LCModel Concentrations
+ metConcAllSubjLCModelScaled_ = metConcAllSubjLCModelScaled(:, :, indexMet);
+ metConcAllSubjLCModelScaled_ = reshape(metConcAllSubjLCModelScaled_,11*3,2);%group same SNR
+ metConcAllSubjRefLCModelScaled_ = metConcAllSubjRefLCModelScaled(:, indexMet);
+ metConcAllSubjRefLCModelScaled_ = repmat(metConcAllSubjRefLCModelScaled_,1,6);
+ metConcAllSubjRefLCModelScaled_ = reshape(metConcAllSubjRefLCModelScaled_,11*3,2);%group same SNR
+
+ %ProFit&LCModel Concentrations
+ metConcAllSubjScaled_ = cat(3, metConcAllSubjProFitScaled_, metConcAllSubjLCModelScaled_);
+ metConcAllSubjRefScaled_ = cat(3, metConcAllSubjRefProFitScaled_, metConcAllSubjRefLCModelScaled_);
+%% ref Fits vs subfits: Code not used anymore in this style
+% BlandAltman(metConcAllSubjRefScaled_, metConcAllSubjScaled_, label,[tit metabolitesLCModel{indexMet}],gnames,...
+% 'corrInfo',corrinfo,'baInfo',BAinfo,'axesLimits',limits,'colors',colors, 'showFitCI',' on',...
+% 'baStatsMode','non-parametric','forceZeroIntercept','on');
+% % Reference fits vs all per Software
+% %ProFit ref Fits vs subfits
+% rpcProFit = BlandAltman(metConcAllSubjRefProFitScaled_, metConcAllSubjProFitScaled_, 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(metConcAllSubjRefLCModelScaled_, metConcAllSubjLCModelScaled_, 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;
+%% LCModel vs ProFit
+% BlandAltman(metConcAllSubjLCModelScaled_, metConcAllSubjProFitScaled_, label_SW_comp,[tit metabolitesLCModel{indexMet}],subsets,...
+% 'corrInfo',corrinfo,'baInfo',BAinfo,'axesLimits',limits,'colors',colors, 'showFitCI',' on',...
+% 'baStatsMode','non-parametric','forceZeroIntercept','on', 'diffValueMode', 'percent');
+% [rpc, ~, stat] = BlandAltman(metConcAllSubjRefLCModelScaled_, metConcAllSubjRefProFitScaled_, label_SW_comp,[tit metabolitesLCModel{indexMet}],subsets,...
+% 'corrInfo',corrinfo,'baInfo',BAinfo,'axesLimits',limits,'colors',colors, 'showFitCI',' on',...
+% 'baStatsMode','non-parametric','forceZeroIntercept','on', 'diffValueMode', 'percent');
+% rpcs(indexMet) = rpc;
+% diffMedian(indexMet) = stat.differenceMedian;
+%% Subfits vs subfits per Software
+ %ProFit ref Fits vs subfits
+ rpc_ProFit_32_ave = calculate_rpc_percent(metConcAllSubjProFitScaled_(1:11,1), metConcAllSubjProFitScaled_(12:22,1));
+ rpc_ProFit_64_ave = calculate_rpc_percent(metConcAllSubjProFitScaled_(1:11,2), metConcAllSubjProFitScaled_(12:22,2));
+ legendText = {['{\color{blue}\bf32-ave: RPC=' mynum2str(rpc_ProFit_32_ave,2) '%}'];['{\color{red}\bf64-ave: RPC=' mynum2str(rpc_ProFit_64_ave,2) '%}']};
+
+ sProFit = subplot(subplotsX,subplotsY,runningIndexPlot);
+ [rpcProFit, fig, stats] = BlandAltmanOnly(sProFit, metConcAllSubjProFitScaled_(1:11,:), metConcAllSubjProFitScaled_(12:22,:),...
+ label_refit,[metabolitesToDisplay{indexMet}],legendText,...
+ 'corrInfo',corrinfo,'baInfo',BAinfo_refit,'axesLimits',limits,'colors','br', 'showFitCI',' on',...
+ 'baStatsMode','Gaussian','forceZeroIntercept','on', 'diffValueMode', 'percent');
+
+ %LCModel ref Fits vs subfits
+ rpc_LCModel_32_ave = calculate_rpc_percent(metConcAllSubjLCModelScaled_(1:11,1), metConcAllSubjLCModelScaled_(12:22,1));
+ rpc_LCModel_64_ave = calculate_rpc_percent(metConcAllSubjLCModelScaled_(1:11,2), metConcAllSubjLCModelScaled_(12:22,2));
+ legendText = {['{\color{blue}\bf32-ave: RPC=' mynum2str(rpc_LCModel_32_ave,2) '%}'];['{\color{red}\bf64-ave: RPC=' mynum2str(rpc_LCModel_64_ave,2) '%}']};
+
+ sLCModel = subplot(subplotsX,subplotsY,runningIndexPlot+subplotsY);
+ [rpcLCModel, fig, stats] = BlandAltmanOnly(sLCModel, metConcAllSubjRefLCModelScaled_(1:11,:), metConcAllSubjLCModelScaled_(12:22,:), ...
+ label_refit,[metabolitesToDisplay{indexMet}], legendText,...
+ 'corrInfo',corrinfo,'baInfo',BAinfo_refit,'axesLimits',limits,'colors','br', 'showFitCI',' on',...
+ 'baStatsMode','Gaussian','forceZeroIntercept','on', 'diffValueMode', 'percent');
+
+ if mod(indexMet,subplotsY)==1
+ pos1 = sProFit.Position;
+ annotation('textarrow', [pos1(1), 0], [pos1(2)+pos1(4)/2, 0],'String',softwareNames{1}, ...
+ 'HeadStyle','none','LineStyle', 'none', 'TextRotation',90,'units','normalized', 'FontSize', 16, ...
+ 'FontWeight','bold','HorizontalAlignment','center', 'VerticalAlignment','middle');
+ pos2 = sLCModel.Position;
+ annotation('textarrow', [pos1(1), 0], [pos2(2)+pos2(4)/2, 0],'String',softwareNames{2}, ...
+ 'HeadStyle','none','LineStyle', 'none', 'TextRotation',90,'units','normalized', 'FontSize', 16, ...
+ 'FontWeight','bold','HorizontalAlignment','center', 'VerticalAlignment','middle');
+ end
+ rpc_table{indexMet+2,2} = rpc_ProFit_32_ave;
+ rpc_table{indexMet+2,3} = rpc_ProFit_64_ave;
+ rpc_table{indexMet+2,4} = rpc_LCModel_32_ave;
+ rpc_table{indexMet+2,5} = rpc_LCModel_64_ave;
+end
+
+rpc_values = cell2mat(rpc_table(3:end-3,2:5));
+rpc_meanProFit_32ave_main = mean(rpc_values(indecesMainMet,1));
+rpc_meanProFit_64ave_main = mean(rpc_values(indecesMainMet,2));
+rpc_meanLCModel_32ave_main = mean(rpc_values(indecesMainMet,3));
+rpc_meanLCModel_64ave_main = mean(rpc_values(indecesMainMet,4));
+rpc_table(3:end-3,2:5) = sprintfc('%.0f',rpc_values);
+rpc_table{end-1,2} = num2str(rpc_meanProFit_32ave_main, '%.0f');
+rpc_table{end-1,3} = num2str(rpc_meanProFit_64ave_main, '%.0f');
+rpc_table{end-1,4} = num2str(rpc_meanLCModel_32ave_main, '%.0f');
+rpc_table{end-1,5} = num2str(rpc_meanLCModel_64ave_main, '%.0f');
+rpc_meanProFit_32ave = mean(rpc_values(:,1));
+rpc_meanProFit_64ave = mean(rpc_values(:,2));
+rpc_meanLCModel_32ave = mean(rpc_values(:,3));
+rpc_meanLCModel_64ave = mean(rpc_values(:,4));
+rpc_table{end,2} = num2str(rpc_meanProFit_32ave, '%.0f');
+rpc_table{end,3} = num2str(rpc_meanProFit_64ave, '%.0f');
+rpc_table{end,4} = num2str(rpc_meanLCModel_32ave, '%.0f');
+rpc_table{end,5} = num2str(rpc_meanLCModel_64ave, '%.0f');
+xlswrite([pathBaseExportFiles, 'InVivoResults_RPC.xlsx'], rpc_table)
+
+%% code will break here. This used to be the old style plotting/results without Bland-Altman plots.
+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,...
+ MC_H2O_ConcentrationsAllSubj, MC_H2O_ConcentrationsAllSubjRef] = ...
+ 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);
@@ -82,29 +390,48 @@ 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);
-for indexSubj = 1:numberOfSubjects/2
+meanPercentualChange = 0;
+iterator = 0;
+nansIterator = 0;
+meanFQN = 0;
+meanFQN2 = 0;
+numOfSimulations = length(namingSuffixesAve)*length(namingSuffixesCoil);
+metaboliteConcentrationsAllSubjNorm = zeros(numberOfSubjects * numOfSimulations, numberOfMet);
+MC_H2O_ConcentrationsAllSubj = zeros(numberOfSubjects, numOfSimulations);
+metaboliteConcentrationsAllSubj = zeros(numberOfSubjects, numOfSimulations, numberOfMet);
+metaboliteConcentrationsAllSubjRef = zeros(numberOfSubjects, numberOfMet);
+MC_H2O_ConcentrationsAllSubjRef = zeros(numberOfSubjects, 1);
+%% do the actual plotting
+for indexSubj = 1:numberOfSubjects
if fitLCModel
load([dataExportPathRef{indexSubj}, 'concentrations' truncSuffix '.mat'], 'concentrations');
+ load([dataExportPathRef{indexSubj}, 'concentrations', truncSuffix '_MC_H2O.mat'], 'concentrations_MC_H2O');
concentrationsRef = concentrations;
+ concentrations_MC_H2ORef = concentrations_MC_H2O;
load([dataExportPath{indexSubj}, 'concentrations' truncSuffix '.mat'], 'concentrations');
+ load([dataExportPath{indexSubj}, 'concentrations', truncSuffix '_MC_H2O.mat'], 'concentrations_MC_H2O');
else
- load([dataExportPathRef{indexSubj}, 'concentrations' truncSuffix '_profit.mat'], 'concentrations', 'activeMetabolites');
- concentrationsRef = concentrations;
+ load([dataExportPathRef{indexSubj}, 'concentrations' truncSuffix '_profit.mat'], 'concentrations', 'activeMetabolites', 'FQNs', 'FQNs2');
+ load([dataExportPathRef{indexSubj}, 'concentrations', truncSuffix '_H2O_profit.mat'], 'concentrations_H2O');
+ load([dataExportPathRef{indexSubj}, 'concentrations', truncSuffix '_MC_H2O_profit.mat'], 'concentrations_MC_H2O');
+ concentrationsRef = concentrations;
+ concentrations_H2ORef = cell2mat(concentrations_H2O);
+ concentrations_MC_H2ORef = cell2mat(concentrations_MC_H2O);
activeMetabolitesRef = activeMetabolites;
- load([dataExportPath{indexSubj}, 'concentrations' truncSuffix '_profit.mat'], 'concentrations', 'activeMetabolites');
+ FQNsRef = FQNs;
+ FQNsRef2 = FQNs2;
+ load([dataExportPath{indexSubj}, 'concentrations' truncSuffix '_profit.mat'], 'concentrations', 'activeMetabolites', 'FQNs', 'FQNs2');
+ load([dataExportPath{indexSubj}, 'concentrations', truncSuffix '_H2O_profit.mat'], 'concentrations_H2O');
+ load([dataExportPath{indexSubj}, 'concentrations', truncSuffix '_MC_H2O_profit.mat'], 'concentrations_MC_H2O');
+ concentrations_H2O = cell2mat(concentrations_H2O);
+ concentrations_MC_H2O = cell2mat(concentrations_MC_H2O);
end
% load stats (SNR, FWHM, etc)
load([dataExportPathRef{indexSubj}, 'stats' truncSuffix '.mat'], 'stats');
@@ -113,9 +440,14 @@ for indexSubj = 1:numberOfSubjects/2
%%
for indexTE = 1:numberOfTEs
if plotInSameFigureAllSubjects
- indexFigure = TEs(indexTE);
+ indexFigure = TEs(indexTE)+indexFigSoftware;
else
- indexFigure = str2double(subjects{indexSubj})*100 + TEs(indexTE);
+ indexFigure = str2double(subjects{indexSubj})*100 + TEs(indexTE)+indexFigSoftware;
+ meanPercentualChange = 0;
+ iterator = 0;
+ nansIterator = 0;
+ meanFQN = 0;
+ meanFQN2 = 0;
end
%get Reference
figure(indexFigure);
@@ -126,30 +458,39 @@ for indexSubj = 1:numberOfSubjects/2
water_ref_amplitude = currentStatsRef{end,4};
currentColorRef = colormapVect(round(NAA_ref_SNR/NAA_ref_SNR/scalingFactorColor * numberOfColors),:);
currentConcentrationRef = concentrationsRef{indexTE,1, 1};
+
if fitLCModel
- metaboliteNamesRef = currentConcentrationRef(1,2:3:end-2);
- metaboliteConcentrationsRef = cell2mat(currentConcentrationRef(2,2:3:end-2));
- metaboliteConcentrationsRef(1) = metaboliteConcentrationsRef(1) / 1e6; % adjust the MMB to be within range
+% MC_H2O_ConcentrationsRef = concentrations_MC_H2ORef{indexTE,1, 1};
+% MC_H2O_ConcentrationsAllSubjRef(indexSubj) = MC_H2O_ConcentrationsRef{2,2};
+ metaboliteConcentrationsRef = matchFittedMetabolites(fitLCModel, currentConcentrationRef, metabolitesLCModel, [], []);
+ metaboliteConcentrationsRef(end) = metaboliteConcentrationsRef(end) .* 1e-8;
else
- metaboliteNamesRef = activeMetabolitesRef{3};
- metaboliteConcentrationsRef = currentConcentrationRef{3};
-% metaboliteConcentrationsRef(1) = metaboliteConcentrationsRef(1) / 1e6; % adjust the MMB to be within range
+ metaboliteConcentrationsRef_notScaled = matchFittedMetabolites(fitLCModel, currentConcentrationRef, metabolitesProFit, proFitIteration, activeMetabolitesRef);
+ %scale the concentations similarly as LCModel
+ metaboliteConcentrationsRef = metaboliteConcentrationsRef_notScaled * 40873 / concentrations_H2ORef * 2;
+% MC_H2O_ConcentrationsRef = concentrations_MC_H2ORef * 40873 / concentrations_H2ORef * 2;
+% MC_H2O_ConcentrationsAllSubjRef(indexSubj) = MC_H2O_ConcentrationsRef;
+ end
+ if ~fitLCModel
+ currentFQNRef = FQNsRef{indexTE,1, 1};
+ FQN_Ref = currentFQNRef{proFitIteration};
+ currentFQNRef2 = FQNsRef2{indexTE,1, 1};
+ FQN_Ref2 = currentFQNRef2{proFitIteration};
end
%scale with the MC water reference amplitude
- metaboliteConcentrationsRef = metaboliteConcentrationsRef ./ water_ref_amplitude;
metaboliteConcentrationsRefNormalized = (metaboliteConcentrationsRef-metaboliteConcentrationsRef) ./ metaboliteConcentrationsRef *100;
- numberMetabolitesRef = length(metaboliteConcentrationsRef);
- scatter(1:numberMetabolitesRef,metaboliteConcentrationsRefNormalized,[],'x', 'MarkerEdgeColor', currentColorRef);
-
-% cb = colorbar;
-% cb.Limits = [0 NAA_ref_SNR*scalingFactorColor];
-% cb.Color = colormapVect
-
- metaboliteConcentrationsAll = zeros(length(namingSuffixesAve)*length(namingSuffixesCoil), numberMetabolitesRef);
+ scatter([1:numberOfMet]-offsetScatter,metaboliteConcentrationsRefNormalized,[],'d', 'MarkerEdgeColor', currentColorRef);
+
+ 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)
for indexCoilDelete = 1: length(namingSuffixesCoil)
- runningIndex = indexAverageDelete * length(namingSuffixesCoil) + indexCoilDelete;
+ runningIndex = (indexAverageDelete-1) * length(namingSuffixesCoil) + indexCoilDelete;
currentStats = stats{indexTE,indexAverageDelete, indexCoilDelete};
currentConcentration = concentrations{indexTE,indexAverageDelete, indexCoilDelete};
if ~isempty(currentConcentration)
@@ -158,32 +499,50 @@ for indexSubj = 1:numberOfSubjects/2
figure(indexFigure);
hold on
if fitLCModel
- metaboliteNames = currentConcentration(1,2:3:end-2);
- metaboliteConcentrations = cell2mat(currentConcentration(2,2:3:end-2));
- metaboliteConcentrations(1) = metaboliteConcentrations(1) / 1e6; % adjust the MMB to be within range
+% MC_H2O_Concentrations = concentrations_MC_H2O{indexTE,indexAverageDelete, indexCoilDelete};
+% MC_H2O_ConcentrationsAllSubj(indexSubj, runningIndex) = MC_H2O_Concentrations{2,2};
+ metaboliteConcentrations = matchFittedMetabolites(fitLCModel, currentConcentration, metabolitesLCModel, [], []);
+ metaboliteConcentrations(end) = metaboliteConcentrations(end) .* 1e-8;
else
- metaboliteNames = activeMetabolites{3};
- metaboliteConcentrations = currentConcentration{3};
- % metaboliteConcentrationsRef(1) = metaboliteConcentrationsRef(1) / 1e6; % adjust the MMB to be within range
+ metaboliteConcentrations_notScaled = matchFittedMetabolites(fitLCModel, currentConcentration, metabolitesProFit, proFitIteration, activeMetabolites);
+ %scale the concentations similarly as LCModel
+ metaboliteConcentrations = metaboliteConcentrations_notScaled * 40873 / concentrations_H2O(runningIndex) * 2;
+% MC_H2O_Concentrations = concentrations_MC_H2O(runningIndex) * 40873 / concentrations_H2O(runningIndex) * 2;
+% MC_H2O_ConcentrationsAllSubj(indexSubj, runningIndex) = MC_H2O_Concentrations;
end
- %scale with the MC water reference amplitude
- metaboliteConcentrations = metaboliteConcentrations ./ water_amplitude;
- numberMetabolites = length(metaboliteConcentrations);
- if numberMetabolites ~= numberMetabolitesRef
- error('numberMetabolites not identical to numberMetabolitesRef');
+ if runningIndex <= 3 %scale with coresponding averages
+ metaboliteConcentrations = metaboliteConcentrations * 3;
+ MC_H2O_ConcentrationsAllSubj(indexSubj, runningIndex) = MC_H2O_ConcentrationsAllSubj(indexSubj, runningIndex) * 3;
+ else
+ metaboliteConcentrations = metaboliteConcentrations *3/2;
+ MC_H2O_ConcentrationsAllSubj(indexSubj, runningIndex) = MC_H2O_ConcentrationsAllSubj(indexSubj, runningIndex) *3/2;
end
+ if ~fitLCModel
+ currentFQN = FQNs{indexTE,indexAverageDelete, indexCoilDelete};
+ FQN = currentFQN{proFitIteration};
+ meanFQN = meanFQN + FQN;
+ currentFQN2 = FQNs2{indexTE,indexAverageDelete, indexCoilDelete};
+ FQN2 = currentFQN2{proFitIteration};
+ meanFQN2 = meanFQN2 + FQN2;
+ end
metaboliteConcentrationsNormalized = (metaboliteConcentrations-metaboliteConcentrationsRef) ...
./ metaboliteConcentrationsRef *100;
metaboliteConcentrationsAll(runningIndex, :) = metaboliteConcentrationsNormalized;
- metaboliteConcentrationsNormalized(abs(metaboliteConcentrationsNormalized) > yLimValue) = yLimValue;
+ metaboliteConcentrationsNormalized(abs(metaboliteConcentrationsNormalized) > yLimValue*2) = NaN; %TODO change! This is actually stupid
+ 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:numberMetabolites]+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:numberMetabolites]+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);
+ iterator = iterator + ~(currentNans);
end
end
end
@@ -191,25 +550,56 @@ for indexSubj = 1:numberOfSubjects/2
cb = colorbar('XTickLabel',num2str(round(xticksSNR)'), 'Direction','reverse');
ylabel(cb,'SNR_{NAA(CH3)}');
-% boxplot(metaboliteConcentrationsAll);
- xticks(1:numberMetabolitesRef);
- xticklabels(metaboliteNamesRef);
+ % boxplot(metaboliteConcentrationsAll);
+ xticks(1:numberOfMet);
+ xticklabels(metabolitesLabels);
xtickangle(45)
- title(['Subject: ', subjects{indexSubj}, ' TE ', num2str(TEs(indexTE)) ' ms']);
ylim([-yLimValue,yLimValue]);
xlim([0.5,17.5])
- ylabel('Concentration change [%]')
- end
+ 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
-%
-% 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 rpc = calculate_rpc_percent(dataS1, dataS2)
+ data.set1 = dataS1;
+ data.set2 = dataS2;
+ s = size(data.set1);
+ if ~isequal(s,size(data.set2))
+ error('data1 and data2 must have the same size');
+ end
+
+ data.set1 = reshape(data.set1, [numel(data.set1),1]);
+ data.set2 = reshape(data.set2, [numel(data.set2),1]);
+ data.mask = isfinite(data.set1) & isnumeric(data.set1) & isfinite(data.set2) & isnumeric(data.set2);
+ data.maskedSet1 = data.set1(data.mask);
+ data.maskedSet2 = data.set2(data.mask);
+
+ data.maskedBaRefData = mean([data.maskedSet1,data.maskedSet2],2);
+ data.maskedDifferences = (data.maskedSet2-data.maskedSet1) ./ data.maskedBaRefData*100;
+
+ differenceSTD = std(data.maskedDifferences, 'omitnan');
+ rpc = 1.96*differenceSTD;
+end
\ No newline at end of file
diff --git a/createTestData/reconstruct_all_test_data_profit.m b/createTestData/reconstruct_all_test_data_profit.m
index 2164c58662b36e3e993eb81229c2bd87da136fda..37725db861f441041cffb67e2fa55e12bfcc24b5 100644
--- a/createTestData/reconstruct_all_test_data_profit.m
+++ b/createTestData/reconstruct_all_test_data_profit.m
@@ -1,9 +1,30 @@
-function reconstruct_all_test_data_profit()
-
-reconstruct_water_references = false;
-
-reconOption = 4;
-truncOn = false;
+function rand_indeces = reconstruct_all_test_data_profit(subjects, reconstruct_water_references, reconOption, truncOn, rand_indeces)
+% reconstruct test data to
+%input arguments:
+% subjects - mandatory parameter. Should be a cell array of the subjectIDs
+% reconstruct_water_references = true or false: to reconstruct water reference data
+% reconOption:
+% 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
+% 7 = Rescale off
+% 8 = Rescale Water Supp Off
+% truncOn = true or false: to truncate or not the data: both as first and last step of the data reconstruction
+% rand_indeces = random indeces permutating the subjects. Should not be stored to assure correct anonimization
+
+if ~exist('reconstruct_water_references','var')
+ reconstruct_water_references = false;
+end
+if ~exist('reconOption','var')
+ reconOption = 1;
+end
+if ~exist('truncOn','var')
+ truncOn = false;
+end
exportFolders = {'0 Water References',...
'1 Normal recon', '2 Removed averages ','3 Removed coils',...
@@ -95,32 +116,27 @@ end
%% import file setup
pathName = 'DF data path';
-subjects = { ...
- '1658' ...
- '1717' ...
- '2017' ...
- '3373' ...
- '3490' ...
- '5771' ...
- '6249' ...
- '6971' ...
- '7338' ...
- '7782' ...
- '9810' ...
- };
+
+numberOfSubjects = length(subjects);
+if ~exist('rand_indeces','var')
+ [~,rand_indeces] = sort(rand(1,numberOfSubjects));
+end
+anonimizedSubjects = cell(1,numberOfSubjects);
+for indexSubj = 1 : numberOfSubjects
+ anonimizedSubjects{indexSubj} = strcat('Subj_', num2str(rand_indeces(indexSubj)));
+end
pathBaseRawFiles = pathToDataFolder(pathName, subjects);
TEs = [24; 32; 40; 52; 60];
-numberOfSubjects = length(subjects);
paths = cell(1,numberOfSubjects);
waterExportPath = cell(1,numberOfSubjects);
dataExportPath = cell(1,numberOfSubjects);
for indexSubj = 1:numberOfSubjects
paths{indexSubj} = [pathBaseRawFiles subjects{indexSubj} '\\'];
- waterExportPath{indexSubj} = [waterExportPathBase subjects{indexSubj} '\\'];
- dataExportPath{indexSubj} = [dataExportPathBase subjects{indexSubj} '\\'];
+ waterExportPath{indexSubj} = [waterExportPathBase anonimizedSubjects{indexSubj} '\\'];
+ dataExportPath{indexSubj} = [dataExportPathBase anonimizedSubjects{indexSubj} '\\'];
end
files_TE24 = cell(1, numberOfSubjects);
@@ -153,19 +169,21 @@ end
%% do the actual reconstruction
parfor indexSubj = 1:numberOfSubjects
- filenameWater = [waterExportPath{indexSubj} subjects{indexSubj} '_water.mat'];
+ filenameWater = [waterExportPath{indexSubj} anonimizedSubjects{indexSubj} '_water.mat'];
if reconstruct_water_references
%% water data
[aWater] = reconstructWater(waterFilesPath{indexSubj});
mkdir(waterExportPath{indexSubj});
- aWater.ExportLcmRaw(waterExportPath{indexSubj}, [subjects{indexSubj}, '_water'], addSinglet0ppm);
+ aWater = aWater.Anonimize_MR_spectroS(rand_indeces(indexSubj));
+ aWater.ExportLcmRaw(waterExportPath{indexSubj}, [anonimizedSubjects{indexSubj}, '_water'], addSinglet0ppm);
%calculate scaling factor the summedSpectra individually according to water peak
waterData = aWater.Data{1};
maxWaterPeak = max(real(fftshift(fft(waterData))));
- save(filenameWater, 'aWater', 'maxWaterPeak');
+ parsaveWater(filenameWater, aWater, maxWaterPeak);
else
if exist(filenameWater,'file')
% does not work in parfor load(filenameWater,'maxWaterPeak')
+ maxWaterPeak = parloadWater(filenameWater);
else
maxWaterPeak = 1;
end
@@ -184,8 +202,9 @@ parfor indexSubj = 1:numberOfSubjects
[a, stats{indexTE,indexAverageDelete, indexCoilDelete}] = ...
reconstruct_testData(filesPath{indexTE, indexSubj}, flagsReconstruct, ...
averages2Keep, coilChannels2Delete);
+ a = a.Anonimize_MR_spectroS(rand_indeces(indexSubj));
TE_string = ['TE', num2str(TEs(indexTE))];
- filenameData = [ subjects{indexSubj}, '_', TE_string namingSuffixAve namingSuffixCoil truncSuffix];
+ filenameData = [ anonimizedSubjects{indexSubj}, '_', TE_string namingSuffixAve namingSuffixCoil truncSuffix];
mkdir(dataExportPath{indexSubj});
dataExportPathTE = [dataExportPath{indexSubj}, '\\', TE_string, '\\'];
mkdir(dataExportPathTE);
@@ -208,6 +227,14 @@ close all
end
+function parsaveWater(fname, aWater, maxWaterPeak)
+save(fname, 'aWater', 'maxWaterPeak')
+end
+
+function maxWaterPeak = parloadWater(fname)
+load(fname, 'maxWaterPeak')
+end
+
function parsave(fname, a)
save(fname, 'a')
end
diff --git a/createTestData/reconstruct_all_test_data_profit_anonimizing_function.m b/createTestData/reconstruct_all_test_data_profit_anonimizing_function.m
new file mode 100644
index 0000000000000000000000000000000000000000..bfdc67340bb304af579b0f53949dad1788dac154
--- /dev/null
+++ b/createTestData/reconstruct_all_test_data_profit_anonimizing_function.m
@@ -0,0 +1,38 @@
+function reconstruct_all_test_data_profit_anonimizing_function()
+% this is not a fully anonimized function. Do not add to final repository
+subjects = { ...
+ '1658' ...
+ '1717' ...
+ '2017' ...
+ '3373' ...
+ '3490' ...
+ '5771' ...
+ '6249' ...
+ '6971' ...
+ '7338' ...
+ '7782' ...
+ '9810' ...
+ };
+
+[~,rand_indeces] = sort(rand(1,length(subjects)));
+save('randIndices.mat','rand_indeces'); %saved only for the case the for loop crashes
+for indexTrunc = 1:2
+ if indexTrunc == 1
+ truncOn = true;
+ else
+ truncOn = false;
+ end
+ for reconOption = 1:8
+ if reconOption == 1
+ reconstruct_water_references = true;
+ reconstruct_all_test_data_profit(subjects, ...
+ reconstruct_water_references, reconOption, truncOn, rand_indeces);
+ else
+ reconstruct_water_references = false;
+ reconstruct_all_test_data_profit(subjects,...
+ reconstruct_water_references, reconOption, truncOn, rand_indeces);
+ end
+ end
+end
+delete 'randIndices.mat'; % delete the random indices, and hence assure the additional level of anonimization
+end
\ No newline at end of file
diff --git a/fitting/makeBasis_pH_sweep.m b/fitting/makeBasis_pH_sweep.m
index 5959c5063d38c7f9bbba87c43289b3b3c71f0ad9..665fce8be4f37f4a4a0159395e78efc18cd3cb14 100644
--- a/fitting/makeBasis_pH_sweep.m
+++ b/fitting/makeBasis_pH_sweep.m
@@ -12,7 +12,7 @@ pH_values = [6.9:0.01:7.1]';
pH_values = [7.1:0.01:7.15]';
pH_values = [7.0:0.01:7.09]';
% pH_values = [7.0:0.01:7.15]';
-% pH_values = [6.9:0.01:7.15]';
+pH_values = [6.9:0.01:7.15]';
% pH_values = [7.09]';
pH_valuesSting = cellstr(num2str(pH_values, '%.2f'));
pH_default = '7.00';
@@ -24,6 +24,7 @@ if moietyFit
if imidazoleFit
%DF
makeBasisFilesBase = 'sLASER_7ppm_moiety_imidazole_';
+ makeBasisFilesBase = 'sLASER_7ppm_moiety_imidazole_newNAA_';
% makeBasisFilesBase = 'deGraaf_sLASER_7ppm_moiety_imidazole_';
else
%DF
@@ -47,8 +48,8 @@ makeBasisFilesPathRemote = '/Desktop/DATA_df/Basis_sets/pH_sweep/';
makeBasisFilesPathLocal = [localFilePathBase, 'Basis_sets/pH_sweep/'];
if imidazoleFit
-LCModelBasisOutputFilesPathRemote = '/Desktop/DATA_df/Basis_sets/pH_sweep/BasisImidazole/';
-LCModelBasisOutputPath = [localFilePathBase, 'Basis_sets/pH_sweep/BasisImidazole/'];
+LCModelBasisOutputFilesPathRemote = '/Desktop/DATA_df/Basis_sets/pH_sweep/NewBasisImidazole_deGraaf/';
+LCModelBasisOutputPath = [localFilePathBase, 'Basis_sets/pH_sweep/NewBasisImidazole_deGraaf/'];
else
LCModelBasisOutputFilesPathRemote = '/Desktop/DATA_df/Basis_sets/pH_sweep/BasisFull/';
LCModelBasisOutputPath = [localFilePathBase, 'Basis_sets/pH_sweep/BasisFull/'];
diff --git a/howIsFittingDone.m b/howIsFittingDone.m
new file mode 100644
index 0000000000000000000000000000000000000000..bb631182c83af1d9ee26fd035891547d80631665
--- /dev/null
+++ b/howIsFittingDone.m
@@ -0,0 +1,273 @@
+function howIsFittingDone()
+
+%% Concentrations and T2 values taken from the Murali Manohar MRM 2019 paper
+% Concentration values were down or upscaled a bit to match better the literature comparison, if they were needed (Table 3)
+% Values were rounded, standard deviations increased for values where possible mismatch with literature could be assumed. Both for concentrations and T2s
+% Default T2 value taken for the metabolites, where these were not determined in the paper: GABA, Lac, Scyllo, Tau were taken as 75+-35ms
+metabolites = {'Asp', 'tCr(CH2)', 'tCr(CH3)', 'GABA', 'Gln', 'Glu', 'Glyc', 'GSH', 'Lac', 'mI', 'NAA(CH3)', 'NAA(CH2)', 'NAAG', 'tCho+', 'Scy', 'Tau', 'MMB'};
+% filenames = {'Asp', 'Cr_CH2', 'Cr', 'GABA', 'Gln', 'Glu', 'Glyc', 'GSH', 'Lac', 'mI', 'NAA_ac', 'NAA_as', 'NAAG', 'tCho_P', 'Scyllo', 'Tau', 'Leu'};
+concentrations = [ 3, 8.5, 8.5, 1.8, 3, 9, 1.2, 1.4, 0.7, 5.5, 12, 12, 1.4, 1.5, 0.4, 1.5, 1.5e7]; %mmol/kg
+conc_std = [0.8, 0.7, 0.7, 0.5, 0.8, 1, 0.3, 0.2, 0.2, 0.5, 1, 1, 0.3, 0.4, 0.1, 0.3, 0.2e7]; %mmol/kg
+T2s = [ 54, 82, 100, 75, 50, 85, 60, 75, 75, 90, 110, 100, 45, 90, 75, 75, 25]; %ms
+T2_std = [ 12, 10, 16, 35, 20, 25, 10, 35, 35, 20, 30, 25, 20, 25, 35, 35, 10]; %ms
+
+TE = 24 * 1e-3;
+numMetabolites = length(metabolites);
+
+saveData = false;
+
+%% path to the export of the spectra
+exportFolder = {'11 Simulations'};
+pathNameExport = 'ProFit test data';
+pathBaseExportFiles = pathToDataFolder(pathNameExport, exportFolder);
+dataExportPathBase = strcat(pathBaseExportFiles, exportFolder{1}, '\');
+
+%%
+metaboliteFileNames = metabolites;
+% replace the weirdos
+metaboliteFileNames = strrep(metaboliteFileNames, 'tCr(CH2)', 'Cr_singlet_tot_3.925');
+metaboliteFileNames = strrep(metaboliteFileNames, 'tCr(CH3)', 'Cr_singlet_tot_3.028');
+metaboliteFileNames = strrep(metaboliteFileNames, 'NAA(CH3)', 'NAA_2');
+metaboliteFileNames = strrep(metaboliteFileNames, 'NAA(CH2)', 'NAA_1');
+metaboliteFileNames = strrep(metaboliteFileNames, 'tCho+', 'tCho_PE');
+metaboliteFileNames = strrep(metaboliteFileNames, 'Scy', 'Scyllo');
+metaboliteFileNames = strrep(metaboliteFileNames, 'MMB', 'MMB_without_metabolite_TE24');
+
+%% paths to the basis set files
+pathName = 'DF data path';
+sampleCriteria = {'Basis_sets'};
+[filePath] = pathToDataFolder(pathName, sampleCriteria);
+
+
+filePathBasis = strcat(filePath, 'Basis_sets/final_T2_met_MM_paper/');
+pathMM = 'sLASER_MM/';
+pathMetabolites = 'sLASER_new_UF_7ppm/TE24/';
+
+fids = cell(1, numMetabolites);
+plotBasis = false;
+
+for indexMetabolite = 1:numMetabolites
+ fileName = metaboliteFileNames{indexMetabolite};
+ if strcmp(metabolites{indexMetabolite},'MMB')
+ filePathMetabolite = strcat(filePathBasis, pathMM);
+ else
+ filePathMetabolite = strcat(filePathBasis, pathMetabolites);
+ end
+ [fid, bandwidth, scanFrequency, metaboliteName, singletPresent] = ...
+ ImportLCModelBasis(filePathMetabolite, fileName, plotBasis, '1H');
+ if strcmp(metabolites{indexMetabolite},'NAA_ac')
+% fid = fid * 3;
+ end
+ if strcmp(metabolites{indexMetabolite},'MMB')
+ fids{indexMetabolite}(1,:)= fid(1:4096); % stupid change to make all metabolites 4096 long!
+ else
+ fids{indexMetabolite}(1,:)= fid;
+ end
+end
+
+water_ppm = 4.66; % ppm
+nTimepoints = length(fids{1});
+dwellTime = 1/bandwidth;
+timePointsSampling =(0:nTimepoints - 1) * dwellTime;
+scalingFactorRefPeak = 0.05;
+
+refFreqPpm = -0; % the reference Frequency for the excitation pulse, given in ppm compared to the water (minus is upfield, + downfield)
+
+phasePivot_ppm = water_ppm + refFreqPpm;%in ppm
+ppmVector = ppmVectorFunction(scanFrequency*1e6, bandwidth, nTimepoints, '1H');
+phase_1_f2_mx = ppmVector-phasePivot_ppm;
+
+ppmMask = (ppmVector>0.6) & (ppmVector<4.1);
+
+%I didn't like the DSS amplitude, some stupid code for adjusting it.
+ FWHM = 1.75; %Hz
+ T2 = 1/(pi*FWHM)*1e+3; %ms
+ f = -4.7076 *scanFrequency; %Hz
+ singlet = scalingFactorRefPeak*0.042*exp(1i*2*pi*f*timePointsSampling).*exp(-timePointsSampling*1e3/T2);
+ FWHM = 3; %Hz
+ T2 = 1/(pi*FWHM)*1e+3; %ms
+ f = -4.7077 *scanFrequency; %Hz
+ singlet2 = scalingFactorRefPeak*0.0278*exp(1i*2*pi*f*timePointsSampling).*exp(-timePointsSampling*1e3/T2);
+
+
+%% set default values for the parameters
+default_noiseLevel = 3;
+noiseVector = wgn(1,nTimepoints, default_noiseLevel);
+trunc_ms = 200;
+truncPoint = floor( trunc_ms/(dwellTime*1e+3));
+
+%% create the actual spectra
+current_pc0 = 0;
+current_pc1 = 0;
+current_df2 = zeros(1,numMetabolites);
+current_gm = 12;
+current_em_std_factor = zeros(1,numMetabolites);
+conc_std_factor = zeros(1,numMetabolites);
+
+indexNAA_ac = find(strcmp('NAA(CH3)',metabolites));
+indexNAA_as = find(strcmp('NAA(CH2)',metabolites));
+fid_NAA_ac = fids{indexNAA_ac};
+fid_NAA_as = fids{indexNAA_as};
+fids_NAA = {fid_NAA_ac, fid_NAA_as};
+concentrations_NAA = [concentrations(indexNAA_ac), concentrations(indexNAA_as)];
+conc_std_NAA = [0 0];
+current_df2_NAA = [0 0];
+conc_std_factor_NAA = [0 0];
+T2s_NAA = [T2s(indexNAA_ac), T2s(indexNAA_as)];
+T2_std_NAA = [0 0];
+current_em_std_factor_NAA = [0 0];
+metabolites_NAA = {'NAA(CH3)', 'NAA(CH2)'};
+metaboliteFileNames_NAA = {metaboliteFileNames{indexNAA_ac}, metaboliteFileNames{indexNAA_as}};
+%%
+[simulatedNAA, defaultSummedFidWithNoise, defaultCurrent_em, defaultCurrentConcentrationRm] = ...
+ createSummedSpectrum(...
+ fids_NAA, concentrations_NAA, conc_std_NAA, [1000 1000], T2_std_NAA, TE, metabolites_NAA, metaboliteFileNames_NAA, timePointsSampling, phase_1_f2_mx, ppmMask, ...
+ current_pc0, current_pc1, current_df2_NAA, current_gm*0, current_em_std_factor_NAA, conc_std_factor_NAA, noiseVector, ...
+ truncPoint, saveData, 'meanConc', [], dwellTime * 1e3, scanFrequency, dataExportPathBase, water_ppm, scalingFactorRefPeak);
+scalingFactor = 3 * (1 / max(real(fftshift(fft(simulatedNAA)))));
+concentrations_NAA = concentrations_NAA * scalingFactor;
+[simulatedNAA, defaultSummedFidWithNoise, defaultCurrent_em, defaultCurrentConcentrationRm] = ...
+ createSummedSpectrum(...
+ fids_NAA, concentrations_NAA, conc_std_NAA, [1000 1000], T2_std_NAA, TE, metabolites_NAA, metaboliteFileNames_NAA, timePointsSampling, phase_1_f2_mx, ppmMask, ...
+ current_pc0, current_pc1, current_df2_NAA, current_gm*0, current_em_std_factor_NAA, conc_std_factor_NAA, noiseVector, ...
+ truncPoint, saveData, 'meanConc', [], dwellTime * 1e3, scanFrequency, dataExportPathBase, water_ppm, scalingFactorRefPeak);
+figure;
+hold on
+plot(ppmVector, real(fftshift(fft(simulatedNAA-singlet+singlet2))));%I didn't like the DSS amplitude
+% plot(ppmVector, real(fftshift(fft(simulatedNAA))));
+plotSetup();
+ylim([-0.11; 3.1])
+title('Simulated NAA')
+legend('$$NAA$$', 'Interpreter','latex','Location','NorthWest')
+xlim([-0.2 8.2])
+
+[simulatedNAA_T2, defaultSummedFidWithNoise, defaultCurrent_em, defaultCurrentConcentrationRm] = ...
+ createSummedSpectrum(...
+ fids_NAA, concentrations_NAA, conc_std_NAA, T2s_NAA, T2_std_NAA, TE, metabolites_NAA, metaboliteFileNames_NAA, timePointsSampling, phase_1_f2_mx, ppmMask, ...
+ current_pc0, current_pc1, current_df2_NAA, current_gm*0, current_em_std_factor_NAA, conc_std_factor_NAA, noiseVector, ...
+ truncPoint, saveData, 'meanConc', [], dwellTime * 1e3, scanFrequency, dataExportPathBase, water_ppm, scalingFactorRefPeak);
+figure;
+plot(ppmVector, real(fftshift(fft(simulatedNAA))));
+hold on;
+plot(ppmVector, real(fftshift(fft(simulatedNAA_T2))),'r');
+plotSetup();
+ylim([-0.11; 3.1])
+title('Simulated NAA')
+legend('$$NAA$$', [10, '$$NAA*exp(-\nu_{e,k}\pi(TE+\overrightarrow{t}))$$'],...
+ 'Interpreter','latex','Location','NorthWest')
+figure;
+plot(ppmVector, real(fftshift(fft(simulatedNAA))));
+hold on;
+plot(ppmVector, real(fftshift(fft(simulatedNAA_T2))),'r');
+plotSetup();
+ylim([-0.11; 1.2])
+title('Simulated NAA')
+legend('$$NAA$$', [10, '$$NAA*exp(-\nu_{e,k}\pi(TE+\overrightarrow{t}))$$'],...
+ 'Interpreter','latex','Location','NorthWest')
+
+[simulatedNAA_T2_gm, defaultSummedFidWithNoise, defaultCurrent_em, defaultCurrentConcentrationRm] = ...
+ createSummedSpectrum(...
+ fids_NAA, concentrations_NAA, conc_std_NAA, T2s_NAA, T2_std_NAA, TE, metabolites_NAA, metaboliteFileNames_NAA, timePointsSampling, phase_1_f2_mx, ppmMask, ...
+ current_pc0, current_pc1, current_df2_NAA, current_gm, current_em_std_factor_NAA, conc_std_factor_NAA, noiseVector, ...
+ truncPoint, saveData, 'meanConc', [], dwellTime * 1e3, scanFrequency, dataExportPathBase, water_ppm, scalingFactorRefPeak);
+
+figure;
+plot(ppmVector, real(fftshift(fft(simulatedNAA))));
+hold on;
+plot(ppmVector, real(fftshift(fft(simulatedNAA_T2))),'r');
+plot(ppmVector, real(fftshift(fft(simulatedNAA_T2_gm))),'k');
+plotSetup();
+ylim([-0.11; 1.2])
+
+legend('$$NAA$$', [10, '$$NAA \cdot exp(-\nu_{e,k}\pi(TE+\overrightarrow{t}))$$'],...
+ [10,10, '$$NAA \cdot exp(-\nu_{e,k}\pi(TE+\overrightarrow{t}))\cdot$$',10, '$$\exp\left(\frac{\left(\nu_g\pi\,\vec{t}\right)^2}{4ln\left(2\right)}\right)$$'], ...
+ 'Interpreter','latex','Location','NorthWest')
+title('Simulated NAA')
+
+figure;
+plot(ppmVector, real(fftshift(fft(simulatedNAA))));
+hold on;
+plot(ppmVector, real(fftshift(fft(simulatedNAA_T2))),'r');
+plot(ppmVector, real(fftshift(fft(simulatedNAA_T2_gm))),'k');
+plotSetup();
+ylim([-0.11; 0.48])
+
+legend('$$NAA$$', [10, '$$NAA \cdot exp(-\nu_{e,k}\pi(TE+\overrightarrow{t}))$$'],...
+ [10,10, '$$NAA \cdot exp(-\nu_{e,k}\pi(TE+\overrightarrow{t}))\cdot$$',10, '$$\exp\left(\frac{\left(\nu_g\pi\,\vec{t}\right)^2}{4ln\left(2\right)}\right)$$'], ...
+ 'Interpreter','latex','Location','NorthWest')
+title('Simulated NAA')
+
+
+% generate the default spectrum
+[simulatedSpectrum, defaultSummedFidWithNoise, defaultCurrent_em, defaultCurrentConcentrationRm] = ...
+ createSummedSpectrum(...
+ fids(1:end-1), concentrations(1:end-1), conc_std(1:end-1), T2s(1:end-1), T2_std(1:end-1), TE, metabolites(1:end-1), metaboliteFileNames(1:end-1), timePointsSampling, phase_1_f2_mx, ppmMask, ...
+ current_pc0, current_pc1, current_df2(1:end-1), current_gm, current_em_std_factor(1:end-1), conc_std_factor(1:end-1), noiseVector, ...
+ truncPoint, saveData, 'meanConc', [], dwellTime * 1e3, scanFrequency, dataExportPathBase, water_ppm, scalingFactorRefPeak);
+
+figure;
+plot(ppmVector,real(fftshift(fft(simulatedSpectrum))));
+plotSetup();
+xlim([0.6 4.1])
+ylim([-130; 7000])
+set(gca,'ytick',[]);
+legend('Metabolites','Interpreter','latex','Location','NorthWest')
+title('Simulated Metabolite Spectra')
+
+% generate the default spectrum
+[simulatedSpectrum, defaultSummedFidWithNoise, defaultCurrent_em, defaultCurrentConcentrationRm] = ...
+ createSummedSpectrum(...
+ fids, concentrations, conc_std, T2s, T2_std, TE, metabolites, metaboliteFileNames, timePointsSampling, phase_1_f2_mx, ppmMask, ...
+ current_pc0, current_pc1, current_df2, current_gm, current_em_std_factor, conc_std_factor, noiseVector, ...
+ truncPoint, saveData, 'meanConc', [], dwellTime * 1e3, scanFrequency, dataExportPathBase, water_ppm, scalingFactorRefPeak);
+
+figure;
+plot(ppmVector,real(fftshift(fft(simulatedSpectrum))));
+hold on
+plot(ppmVector,real(fftshift(fft(fids{end}.*exp(-pi* abs(TE + timePointsSampling)).*concentrations(end)))))
+plotSetup();
+xlim([0.6 4.1])
+ylim([-130; 7000])
+set(gca,'ytick',[]);
+
+legend('Metabolites and MMs', [10, 'MM spectrum'],'Interpreter','latex','Location','NorthWest')
+title('Simulated Metabolite and MM Spectra')
+
+% generate the realistic spectrum
+current_pc0 = -15;
+current_pc1 = 8;
+current_df2_ = current_df2 + -20;
+[simulatedSpectrumWithAll, summedFidWithNoiseAndAll, defaultCurrent_em, defaultCurrentConcentrationRm] = ...
+ createSummedSpectrum(...
+ fids, concentrations, conc_std, T2s, T2_std, TE, metabolites, metaboliteFileNames, timePointsSampling, phase_1_f2_mx, ppmMask, ...
+ current_pc0, current_pc1, current_df2_, current_gm, current_em_std_factor, conc_std_factor, noiseVector, ...
+ truncPoint, saveData, 'meanConc', [], dwellTime * 1e3, scanFrequency, dataExportPathBase, water_ppm, scalingFactorRefPeak);
+
+figure;
+plot(ppmVector,real(fftshift(fft(simulatedSpectrum))));
+hold on
+plot(ppmVector,real(fftshift(fft(summedFidWithNoiseAndAll))),'Color',[0 114/255 104/255]);
+plotSetup();
+xlim([0.6 4.1])
+ylim([-130; 7000])
+set(gca,'ytick',[]);
+
+legend('Metabolites and MMs', [10, 'Actual in vivo quality', 10, '$$with \; \varphi_{0}, \varphi_{1}, \omega_{global}, \: noise$$'],'Interpreter','latex','Location','NorthWest')
+title('Simulated in vivo quality spectra')
+end
+
+function plotSetup()
+FontSize = 12;
+LineWidth = 1.5;
+xlim([1.5, 3.0])
+xlabel('\delta (ppm)')
+ylabel('Signal (arb. u.)')
+set(gca,'xDir','reverse')
+% set(gca,'ytick',[]);
+set(gca,'fontsize',FontSize);
+set(gca,'FontWeight','bold');
+h = findobj(gca,'Type','line');
+for plots = h
+ set(plots,'LineWidth',LineWidth)
+end
+end
diff --git a/plot_spect/Functions/snr.m b/plot_spect/Functions/snr.m
index e093c8db9dded32e454eb5acdab336feed66045a..09bdbdce726d18d4d9759e9c1d1ad391a6df4c63 100644
--- a/plot_spect/Functions/snr.m
+++ b/plot_spect/Functions/snr.m
@@ -21,7 +21,7 @@ else
noise = noise - y;% now the noise does not have linear component
noise = std(noise);
- snrValue = amplitude;%noise;
+ snrValue = amplitude/noise;
%snrValue = 20*log(amplitude/noise); %in dB
diff --git a/postprocessing/calculateMolal_MolarConcentrations.m b/postprocessing/calculateMolal_MolarConcentrations.m
index 2ec51e28a721d5fe3e13f452f12b95705e226e25..0c0fdc5958465aa8862af672d153082e87a20c98 100644
--- a/postprocessing/calculateMolal_MolarConcentrations.m
+++ b/postprocessing/calculateMolal_MolarConcentrations.m
@@ -64,6 +64,13 @@ a_WM = 0.65;
a_GM = 0.78;
a_CSF = 0.97;
+% tissue densities (g/mL)
+% (Brooks R. - 1980 - Explanation of cerebral white - gray contrast in computer tomography
+% additional reference in Kreis R. & Ernst T. - 1993 - Absolute Quantitation of Water and Metabolites in the Human Brain. I. Compartments and Water)
+d_WM = 1.04;
+d_GM = 1.04;
+d_CSF = 1;
+
%T1 relaxation times of water in the given tissue type [ms] at 9.4T : From
%Gisela Hagberg 2017 Neuroimage
T1_GM = 2120;
@@ -117,10 +124,12 @@ if strcmpi(doMolal_Molar, 'Molal') %MOLAL calculations
%Calculate water fraction from volume fractions obtained from segmentation
%and relative water fraction in each segmentation
f_sum = fv_GM .* a_GM + fv_WM .* a_WM + fv_CSF .* a_CSF;
+ %corrected version considering also the water densities
+ f_sum = fv_GM .* a_GM .* d_GM + fv_WM .* a_WM .* d_WM + fv_CSF .* a_CSF .* d_CSF;
- f_GM = fv_GM .* a_GM ./ f_sum;
- f_WM = fv_WM .* a_WM ./ f_sum;
- f_CSF = fv_CSF .* a_CSF ./f_sum;
+ f_GM = fv_GM .* a_GM .* d_GM ./ f_sum;
+ f_WM = fv_WM .* a_WM .* d_WM ./ f_sum;
+ f_CSF = fv_CSF .* a_CSF .* d_CSF ./f_sum;
%% calculate true water concentration for each subject : density terms do not come in molality
water_conc_relaxation_corrected = conc_pure_water * ...
@@ -136,9 +145,9 @@ else %MOLAR calculations
%% calculate true water concentration for each subject
water_conc_relaxation_corrected = conc_pure_water * ...
- ( fv_GM * a_GM * R_GM + ... correction for gray matter concentration
- fv_WM * a_WM * R_WM + ... correction for white matter concentration
- fv_CSF * a_CSF * R_CSF ) / ... correction for cerebrospinal fluid concentration
+ ( fv_GM * a_GM * d_GM * R_GM + ... correction for gray matter concentration
+ fv_WM * a_WM * d_WM * R_WM + ... correction for white matter concentration
+ fv_CSF * a_CSF * d_CSF * R_CSF ) / ... correction for cerebrospinal fluid concentration
(1 - fv_CSF);
end
diff --git a/postprocessing/calculate_FWHM.m b/postprocessing/calculate_FWHM.m
index ae425726127a24bf23bf6b90d9d4b64bfdaf91dd..d0d3633a039b1e5bc0cad0e0371c97492db4d2b6 100644
--- a/postprocessing/calculate_FWHM.m
+++ b/postprocessing/calculate_FWHM.m
@@ -12,7 +12,7 @@ end
if ~exist('downField_MM_Met', 'var')
- downField_MM_Met = 'DF';
+ downField_MM_Met = 'MM';
end
switch downField_MM_Met
@@ -20,10 +20,21 @@ switch downField_MM_Met
keyMM_ppmNaming = {'DF58' 'DF60' 'DF61' 'DF68' 'DF70' 'DF73' 'DF75' 'DF82' 'DF83' 'DF835' 'DF85' 'NAAB' 'hCs' 'NAA_DF' 'NAD' 'Cr'};%'hist'
orderMet = {'DF58';'DF60';'DF61';'DF68';'DF70';'DF73';'DF75';'DF82';'DF83';'DF835';'DF85';'NAA Broad';'hCs';'NAA'; 'NAD'; 'Cr'};%;'hist'
case 'MM'
+% keyMM_ppmNaming = {'MM09' 'MM12' 'MM14' 'MM17' 'MM20' 'MM22' 'MM26' 'MM27' ...
+% 'MM30' 'MM32' 'MM36' 'MM37' 'MM38' 'Cr39' 'Cr30' 'NAA'};
+% orderMet = { 'M_{0.92}';'M_{1.21}';'M_{1.39}';'M_{1.67}';'M_{2.04}';'M_{2.26}';'M_{2.56}';'M_{2.70}';...
+% 'M_{2.99}';'M_{3.21}';'M_{3.62}';'M_{3.75}';'M_{3.86}'; 'tCr(CH_2)'; 'tCr(CH_3)'; 'NAA'};
+
+% keyMM_ppmNaming = {'MM09' 'MM12' 'MM14' 'MM17' 'MM20' 'MM22' 'MM26' 'MM27' ...
+% 'MM30' 'MM32' 'MM36' 'MM37' 'MM38' 'NAA' 'Creat' 'Cho' 'Glu' 'Tau' 'Glycin' 'PCr'};
+% orderMet = { 'M_{0.92}';'M_{1.21}';'M_{1.39}';'M_{1.67}';'M_{2.04}';'M_{2.26}';'M_{2.56}';'M_{2.70}';...
+% 'M_{2.99}';'M_{3.21}';'M_{3.62}';'M_{3.75}';'M_{3.86}'; 'NAA'; 'tCr(CH_3)'; 'tCho'; 'Glu'; 'Tau'; 'Glyc'; 'tCr(CH_2)'};
+
keyMM_ppmNaming = {'MM09' 'MM12' 'MM14' 'MM17' 'MM20' 'MM22' 'MM26' 'MM27' ...
- 'MM30' 'MM32' 'MM36' 'MM37' 'MM38' 'MM40' 'Cre'};
+ 'MM30' 'MM32' 'MM36' 'MM37' 'MM38' 'MM39' 'Cr39' 'NAA' 'NAA_as' 'Cho' 'mI'};
orderMet = { 'M_{0.92}';'M_{1.21}';'M_{1.39}';'M_{1.67}';'M_{2.04}';'M_{2.26}';'M_{2.56}';'M_{2.70}';...
- 'M_{2.99}';'M_{3.21}';'M_{3.62}';'M_{3.75}';'M_{3.86}';'M_{4.03}'; 'tCr(CH_2)'};
+ 'M_{2.99}';'M_{3.21}';'M_{3.62}';'M_{3.75}';'M_{3.86}'; 'M_{4.03}'; 'tCr(CH_2)'; 'NAA'; 'NAA_{asp}';'tCho'; 'mI'}
+
case 'MM WM'
keyMM_ppmNaming = {'MM09' 'MM12' 'MM14' 'MM17' 'MM20' 'MM22' 'MM26' 'MM27' ...
'MM30' 'MM32' 'MM36' 'MM37' 'MM38' 'MM40' 'Cre'};
@@ -43,15 +54,15 @@ numberOfMet = length(orderMet);
%threshold for crlbs
threshold_CRLB = 900;
FontSize = 14;
-LineWidth = 1.5;
+LineWidth = 2.5;
ppmEnd = 4.2;
ppmStart = 0.2;
interpolationFactor = 20;
%plotting offsets
-offsetMetabolite = 0.1;
+offsetMetabolite = 0.085;
offsetResidual = offsetMetabolite * (numberOfMet+1);
-offsetBaseline = offsetResidual + 0.05;
+offsetBaseline = offsetResidual + 0.042;
%% do the absolute quantification on all files
if ~iscell(FileNames)
@@ -93,7 +104,7 @@ for index =1:length(FileNames)
if strcmp(downField_MM_Met,'DF')
xlim([5.5 9.4]);
else
- xlim([0.5 4.097]);
+ xlim([0.5 4.02]);
end
for plots = 1:length(p)
set(p(plots),'LineWidth',LineWidth);
@@ -112,7 +123,7 @@ for index =1:length(FileNames)
pMetabolite = plot(ppmVector{index}, metaboliteSpectrum ./ scale - indexMetabolite * offsetMetabolite);
text(0.47, -indexMetabolite * offsetMetabolite,orderMet{indexMetabolite}, 'FontSize', FontSize);
set(pMetabolite,'LineWidth',LineWidth);
-
+
if strcmp(downField_MM_Met,'DF')
switch keyMM_ppmNaming{indexMetabolite}
case 'Cr'
@@ -152,11 +163,10 @@ for index =1:length(FileNames)
end
else % assuming no downfield peaks
if ~isempty(ppmGap)
- ppmEnd = ppmGap;
+ % make the downfield 0, if there was a ppmGap
+ indexDF = find((ppmVector{index} < ppmGap), 1, 'first');
+ metaboliteSpectrum(1:indexDF) = 0;
end
- % ppmEnd is where upfield ends in fit config
- indexDF = find((ppmVector{index} < ppmEnd), 1, 'first');
-% metaboliteSpectrum(1:indexDF) = 0; TODO
end
dataPoints = length(metaboliteSpectrum);
diff --git a/postprocessing/doAbsoluteConcentrationProcessing.m b/postprocessing/doAbsoluteConcentrationProcessing.m
index 44cc509ce20e4c779d7efabbf4509185e502f141..c5de48cddf8163d9b616b5b610cfa9eedc4ea447 100644
--- a/postprocessing/doAbsoluteConcentrationProcessing.m
+++ b/postprocessing/doAbsoluteConcentrationProcessing.m
@@ -3,7 +3,7 @@ function [absoluteConcentrations, metaboliteNames, subjectsAbs, data_path] = doA
switch compare
case 'DF'
- outputFolder = 'Output\';
+ outputFolder = 'Output\FWHMBA Results 7.5e-3\';
pathName = 'DF data path';
case 'MM'
outputFolder = 'OutputMM\';
@@ -114,9 +114,9 @@ end
eliminateMetabolites = {'Lac', 'Leu','Cho+GPC+PCh', 'mI+Glyc', 'Glu+Gln', 'Lip13a', 'Lip13b', 'Lip13c', 'Lip13d','Lip20', 'Lip13a+Lip13b'};
if strcmp(compare,'DF')
- eliminateMetabolites = {'Asp', 'Cr-CH3', 'Cr-CH2', 'GABA', 'Gln', 'Glu', 'Glyc', 'GSH', 'mI', 'NAA-asp', 'NAA-ace', 'NAAG', 'tCho_PE', 'Scyllo', 'Tau', 'Glx', 'Lac', 'Leu','Cho+GPC+PCh', 'mI+Glyc', 'Glu+Gln', 'Lip13a', 'Lip13b', 'Lip13c', 'Lip13d','Lip20', 'Lip13a+Lip13b'};
- metaboliteNameOrder = {'DF58';'DF60';'DF61';'DF68';'DF70';'DF73';'DF75';'DF82';'DF83';'DF835';'DF85';'NAD';'hCs';'NAA Broad';'NAA';'total NAA';};
- metaboliteNamesDisplay = {'DF5.75';'DF5.97';'DF6.12';'DF6.83';'DF7.04';'DF7.30';'DF7.48';'DF8.18';'DF8.24';'DF8.37';'DF8.49';'NAD+';'hCs';'NAA Broad';'NAA';'total NAA'};
+ eliminateMetabolites = {'NAD', 'Asp', 'Cr-CH3', 'Cr-CH2', 'GABA', 'Gln', 'Glu', 'Glyc', 'GSH', 'mI', 'NAA-asp', 'NAA-ace', 'NAAG', 'tCho_PE', 'Scyllo', 'Tau', 'Glx', 'Lac', 'Leu','Cho+GPC+PCh', 'mI+Glyc', 'Glu+Gln', 'Lip13a', 'Lip13b', 'Lip13c', 'Lip13d','Lip20', 'Lip13a+Lip13b'};
+ metaboliteNameOrder = {'DF58';'DF60';'DF61';'DF68';'DF70';'DF73';'DF75';'DF82';'DF83';'DF835';'DF85';'hCs';'NAA Broad';'NAA';'total NAA';};
+ metaboliteNamesDisplay = {'DF5.75';'DF5.97';'DF6.12';'DF6.83';'DF7.04';'DF7.30';'DF7.48';'DF8.18';'DF8.24';'DF8.37';'DF8.49';'hCs';'NAA Broad';'NAA';'total NAA'};
numberOfMet = length(metaboliteNameOrder);
absoluteConcentrationsOrdered = zeros(size(absoluteConcentrations,1), numberOfMet);
absoluteConcentrationsOrdered2 = zeros(size(absoluteConcentrations,1), numberOfMet);
diff --git a/postprocessing/evaluateT2FitsNew.m b/postprocessing/evaluateT2FitsNew.m
index de0d12b1dbdae43ccfa98cee059a7eb29bd229e4..00397f218daf0e1daf122f9ad5cea64e36f20abc 100644
--- a/postprocessing/evaluateT2FitsNew.m
+++ b/postprocessing/evaluateT2FitsNew.m
@@ -25,8 +25,8 @@ else
plotColors2 = {[0.1 0.9 0.1], [0.5 0.5 0.5]};
end
-sortT2sDescending = true;
-usePpm = true;
+sortT2sDescending = false;
+usePpm = false;
if isempty(figureIds)
emptyFigureIds = true;
@@ -37,7 +37,7 @@ end
switch downField_MM_Met
case 'DF'
pathNameMM = 'DF data path';
- outputFolder = 'Output\';
+ outputFolder = 'Output\FWHMBA Results 7.5e-3\';
case 'Met'
pathNameMM = 'DF data path';
outputFolder = 'Output_UF\';
@@ -66,22 +66,22 @@ end
switch downField_MM_Met
case 'DF'
if useTotalNAA
- metaboliteNameOrder = {'Cr-CH3';'DF58';'DF60';'DF61';'DF68';'DF70';'DF73';'DF75';'DF82';'DF83';'DF835';'DF85';'NAD';'hCs';'NAA Broad';'NAA';'total NAA'};'ATP';'hist';
- metaboliteNameOrderConc = {'Cr';'DF58';'DF60';'DF61';'DF68';'DF70';'DF73';'DF75';'DF82';'DF83';'DF835';'DF85';'NAD';'hCs';'NAAB';'NAA_DF';'NAAB+NAA_DF'};
- metaboliteNamesDisplay = {'tCr-CH3';'DF5.75';'DF5.97';'DF6.12';'DF6.83';'DF7.04';'DF7.30';'DF7.48';'DF8.18';'DF8.24';'DF8.37';'DF8.49';'NAD+';'hCs';'NAA Broad';'NAA';'total NAA'};'ATP';'hist';
- metaboliteNamesDisplay2 = {'tCr-CH3';'DF_{5.75}';'DF_{5.97}';'DF_{6.12}';'DF_{6.83}';'DF_{7.04}';'DF_{7.30}';'DF_{7.48}';'DF_{8.18}';'DF_{8.24}';'DF_{8.37}';'DF_{8.49}';'NAD^+';'hCs';'NAA Broad';'NAA';'total NAA'};'ATP';'hist';
+ metaboliteNameOrder = {'Cr-CH3';'DF58';'DF60';'DF61';'DF68';'DF70';'DF73';'DF75';'DF82';'DF83';'DF835';'DF85';'hCs';'NAA Broad';'NAA';'total NAA'};'ATP';'hist';'NAD';
+ metaboliteNameOrderConc = {'Cr';'DF58';'DF60';'DF61';'DF68';'DF70';'DF73';'DF75';'DF82';'DF83';'DF835';'DF85';'hCs';'NAAB';'NAA_DF';'NAAB+NAA_DF'};'NAD';
+ metaboliteNamesDisplay = {'tCr-CH3';'DF5.75';'DF5.97';'DF6.12';'DF6.83';'DF7.04';'DF7.30';'DF7.48';'DF8.18';'DF8.24';'DF8.37';'DF8.49';'hCs';'NAA Broad';'NAA';'total NAA'};'ATP';'hist';'NAD+';
+ metaboliteNamesDisplay2 = {'tCr-CH3';'DF_{5.75}';'DF_{5.97}';'DF_{6.12}';'DF_{6.83}';'DF_{7.04}';'DF_{7.30}';'DF_{7.48}';'DF_{8.18}';'DF_{8.24}';'DF_{8.37}';'DF_{8.49}';'hCs';'NAA Broad';'NAA';'total NAA'};'ATP';'hist';'NAD^+';
else
- metaboliteNameOrder = {'Cr-CH3';'DF58';'DF60';'DF61';'DF68';'DF70';'DF73';'DF75';'DF82';'DF83';'DF835';'DF85';'NAD';'hCs';'NAA Broad';'NAA'};'ATP';'hist';
- metaboliteNameOrderConc = {'Cr';'DF58';'DF60';'DF61';'DF68';'DF70';'DF73';'DF75';'DF82';'DF83';'DF835';'DF85';'NAD';'hCs';'NAAB';'NAA_DF'};'NAAB+NAA_DF'
- metaboliteNamesDisplay = {'tCr-CH3';'DF5.75';'DF5.97';'DF6.12';'DF6.83';'DF7.04';'DF7.30';'DF7.48';'DF8.18';'DF8.24';'DF8.37';'DF8.49';'NAD+';'hCs';'NAA Broad';'NAA'};'ATP';'hist';
- metaboliteNamesDisplay2 = {'tCr-CH3';'DF_{5.75}';'DF_{5.97}';'DF_{6.12}';'DF_{6.83}';'DF_{7.04}';'DF_{7.30}';'DF_{7.48}';'DF_{8.18}';'DF_{8.24}';'DF_{8.37}';'DF_{8.49}';'NAD^+';'hCs';'NAA Broad';'NAA';};'ATP';'hist';
+ metaboliteNameOrder = {'Cr-CH3';'DF58';'DF60';'DF61';'DF68';'DF70';'DF73';'DF75';'DF82';'DF83';'DF835';'DF85';'hCs';'NAA Broad';'NAA'};'ATP';'hist';'NAD';
+ metaboliteNameOrderConc = {'Cr';'DF58';'DF60';'DF61';'DF68';'DF70';'DF73';'DF75';'DF82';'DF83';'DF835';'DF85';'hCs';'NAAB';'NAA_DF'};'ATP';'hist';'NAD';
+ metaboliteNamesDisplay = {'tCr-CH3';'DF5.75';'DF5.97';'DF6.12';'DF6.83';'DF7.04';'DF7.30';'DF7.48';'DF8.18';'DF8.24';'DF8.37';'DF8.49';'hCs';'NAA Broad';'NAA'};'ATP';'hist';'NAD+';
+ metaboliteNamesDisplay2 = {'tCr-CH3';'DF_{5.75}';'DF_{5.97}';'DF_{6.12}';'DF_{6.83}';'DF_{7.04}';'DF_{7.30}';'DF_{7.48}';'DF_{8.18}';'DF_{8.24}';'DF_{8.37}';'DF_{8.49}';'hCs';'NAA Broad';'NAA';};'ATP';'hist'; 'NAD^+';
end
metaboliteNameOrderFWHM = metaboliteNameOrder;
metaboliteNameOrderFWHM{1} = 'Cr';
subjects = {'1658';'1717';'2017';'3373';'3490';'5771';'6249';'6971';'7338';'7782';'9810'};
yAxisLim = 65;
-% yAxisLim = 90;
+ yAxisLim = 90;
case 'Met'
metaboliteNameOrder = {'Leu';'Asp';'Cr-CH3';'Cr-CH2';'GABA';'Glu';'Gln';'GSH_no';'Glyc';'GPC';'mI';'NAA-asp';'NAA-ace';'NAAG';'PCh';'PE';'Scyllo';'Tau';'tCho';'tNAA';'mI+Glyc';'Glx'};
metaboliteNameOrder = {'Leu';'Asp';'Cr-CH3';'Cr-CH2';'GABA';'Glu';'Gln';'GSH_no';'Glyc';'mI';'NAA-asp';'NAA-ace';'NAAG';'Scyllo';'Tau';'tCho_PE';'tNAA';'mI+Glyc';'Glx'; 'Lac'; 'NAA+NAAG'};
@@ -126,6 +126,7 @@ numOfSubjects = length(tableT2sSubjects);
T2s = cell(numOfSubjects,numberOfMet);
R2s = cell(numOfSubjects,numberOfMet);
concentrations = cell(numOfSubjects, numberOfMet, numberOfTEs);
+CRLBs = cell(numOfSubjects, numberOfMet, numberOfTEs);
for indexSubject = 1:numOfSubjects
T2times = tableT2sSubjects{indexSubject}(2,2:end);
R2times = tableT2sSubjects{indexSubject}(3,2:end);
@@ -136,9 +137,12 @@ for indexSubject = 1:numOfSubjects
R2s(indexSubject,indexMetabolite) = R2times(index);
indexConc = find(strcmp(metaboliteNameOrderConc(indexMetabolite),concentrationsSubject(1,:)));
concentrations(indexSubject, indexMetabolite,:) = concentrationsSubject(2:6,indexConc);
+ CRLBs(indexSubject, indexMetabolite,:) = concentrationsSubject(2:6,indexConc+1);
end
end
+saveCRLBs(CRLBs, TEs, metaboliteNamesDisplay, data_path, outputFolder)
+
concentrations = cell2mat(concentrations);
T2sNumeric = str2double(T2s);
R2sNumeric = str2double(R2s);
@@ -152,8 +156,8 @@ acceptableT2s = nonNegT2s;
acceptableR2s = R2sNumeric;
switch downField_MM_Met
case 'DF'
- acceptableT2s(R2sNumeric<=0.51) = NaN;
- acceptableR2s(R2sNumeric<=0.51) = NaN;
+ acceptableT2s(R2sNumeric<=0.53) = NaN;
+ acceptableR2s(R2sNumeric<=0.53) = NaN;
for indexSubject = 1:numOfSubjects
for indexMetabolite = 1:numberOfMet
if R2sNumeric(indexSubject, indexMetabolite) <= 0.5
@@ -212,14 +216,24 @@ for index = 2:numberOfMet
% currentLabel = string([metaboliteNamesDisplay2{indexMetabolite}, ' : T_2=' num2str(acceptableMeanT2s(indexMetabolite),2), ' ms']);
currentLabel = string([metaboliteNamesDisplay2{indexMetabolite}]);
if mod(index,plotGroups) == 2
- figure;
+ myVal = mod(ceil(index/plotGroups)+1,2)+1;
+ if myVal == 1
+ figure;
+ sgtitle('Estimated T_2^{app} Decay by Fitting: Signal \propto exp( - TE / T_2^{app} )','FontWeight', 'bold')
+ end
+ subplot(1,2, myVal);
+ if myVal == 1
+ text(-0.15,0.98,'A','Units', 'Normalized', 'VerticalAlignment', 'Top', 'FontSize', 12,'FontWeight', 'bold');
+ else
+ text(-0.15,0.98,'B','Units', 'Normalized', 'VerticalAlignment', 'Top', 'FontSize', 12,'FontWeight', 'bold');
+ end
hold on
offsetRec = plotOffset * (plotGroups/2+1.5);
for indexTE = 1: numberOfTEs
rectangle('position',[TEs(indexTE)-offsetRec -0.92 offsetRec*2 100], 'FaceColor',[0.85 .85 .85], 'LineStyle', 'none')
end
ylim([-1,0]);
- title('T_2 decay curves and measured T_2 times')
+% title('T_2 decay curves and measured T_2 times')
xlim([20 65])
xlabel('TE (ms)')
ylabel('Signal (arb. u.)')
@@ -293,6 +307,7 @@ if sortT2sDescending
metaboliteNameOrderFWHM = metaboliteNameOrderFWHM(sortedIndeces);
acceptableStdT2s = acceptableStdT2s(sortedIndeces);
acceptableT2s = acceptableT2s(:, sortedIndeces);
+ acceptableR2s = acceptableR2s(:, sortedIndeces);
R2sNumeric = R2sNumeric(:, sortedIndeces);
nonNegT2s = nonNegT2s(:, sortedIndeces);
metaboliteNamesDisplay = metaboliteNamesDisplay(sortedIndeces);
@@ -309,7 +324,7 @@ end
positionsTicks = [2.2:1.5:1.5*numberOfMet+1.5];
positions1 = positionsTicks + offsetPlot;
boxPlotT2 = boxplot(acceptableT2s, metaboliteNamesDisplay,'colors',plotColors{1},'symbol','+','positions',positions1,'width',0.18);
-ylabel('T_2 (ms)')
+ylabel('T_2^{app} (ms)')
axT2 = get(figureIds{1},'CurrentAxes');
axT2.XAxis.TickLength = [0,0];
axT2.YColor = 'k';
@@ -317,8 +332,8 @@ axT2.YColor = 'k';
set(boxPlotT2(:,:),'linewidth',1);
switch downField_MM_Met
case 'DF'
- set(gca, 'YLim', [-5,90]);
- set(gca, 'XLim', [positionsTicks(1)-abs(offsetPlot)-0.8 positionsTicks(end)+abs(offsetPlot)+0.8]);
+ set(gca, 'YLim', [-5,70]);
+ set(gca, 'XLim', [positionsTicks(1)-abs(offsetPlot)-0.8+1.5 positionsTicks(end)+abs(offsetPlot)+0.8]);
case 'MM'
set(gca, 'YLim', [-5,95]);
set(gca, 'XLim', [positionsTicks(2)-abs(offsetPlot)-0.8 positionsTicks(end)+abs(offsetPlot)+0.8]);
@@ -335,8 +350,7 @@ set(gca, 'XTickMode', 'manual');
set(gca, 'XTick', positionsTicks);
set(gca, 'XTickLabelRotation', 90.0);
set(gca, 'FontSize', 16);
-% title('T_2^\rho Relaxation Times');
-title('T_2 Relaxation Times');
+title('T_2^{app} Relaxation Times');
%% FWHM
if doFWHMevalutation
@@ -376,22 +390,28 @@ if doFWHMevalutation
%% plotting of FWHM
if emptyFigureIds
- figureIds{2} = plotFWHMs(fwhmReshaped, [], metaboliteNamesDisplay, numberOfMet, scanFrequency, plotColors, 'Full Width Half Maxima', usePpm, yAxisLim, offsetPlot);
- figureIds{3} = plotFWHMs(fwhmReshaped3, [], metaboliteNamesDisplay, numberOfMet, scanFrequency, plotColors2, 'Full-Width-Half-Maxima T_2 and B_0 corrected', usePpm, yAxisLim, offsetPlot);
+ figureIds{2} = plotFWHMs(fwhmReshaped, [], metaboliteNamesDisplay, numberOfMet, scanFrequency, plotColors, '\Delta\nu_{1/2}', usePpm, yAxisLim, offsetPlot);
+ figureIds{3} = plotFWHMs(fwhmReshaped3, [], metaboliteNamesDisplay, numberOfMet, scanFrequency, plotColors2, '\Delta\nu_{residual}', usePpm, yAxisLim, offsetPlot);
else
- figureIds{2} = plotFWHMs(fwhmReshaped, [], metaboliteNamesDisplay, numberOfMet, scanFrequency, plotColors, 'Full Width Half Maxima', usePpm, yAxisLim, offsetPlot, figureIds{2});
- figureIds{3} = plotFWHMs(fwhmReshaped3, [], metaboliteNamesDisplay, numberOfMet, scanFrequency, plotColors2, 'Full-Width-Half-Maxima T_2 and B_0 corrected', usePpm, yAxisLim, offsetPlot, figureIds{3});
+ figureIds{2} = plotFWHMs(fwhmReshaped, [], metaboliteNamesDisplay, numberOfMet, scanFrequency, plotColors, '\Delta\nu_{1/2}', usePpm, yAxisLim, offsetPlot, figureIds{2});
+ figureIds{3} = plotFWHMs(fwhmReshaped3, [], metaboliteNamesDisplay, numberOfMet, scanFrequency, plotColors2, '\Delta\nu_{residual}', usePpm, yAxisLim, offsetPlot, figureIds{3});
end
%%
if emptyFigureIds
- figureIds{4} = plotFWHMs(T2RelaxationLinewidth, [], metaboliteNamesDisplay, numberOfMet, scanFrequency, plotColors2, 'Full-Width-Half-Maxima vs. Linewidth Component from T_2', usePpm, yAxisLim, offsetPlot);
+ figureIds{4} = plotFWHMs(T2RelaxationLinewidth, [], metaboliteNamesDisplay, numberOfMet, scanFrequency, plotColors2, '\Delta\nu_{1/2} vs. (\pi T_2^{app})^{-1}', usePpm, yAxisLim, offsetPlot);
else
- figureIds{4} = plotFWHMs(T2RelaxationLinewidth, [], metaboliteNamesDisplay, numberOfMet, scanFrequency, plotColors2, 'Full-Width-Half-Maxima vs. Linewidth Component from T_2', usePpm, yAxisLim, offsetPlot, figureIds{4});
+ figureIds{4} = plotFWHMs(T2RelaxationLinewidth, [], metaboliteNamesDisplay, numberOfMet, scanFrequency, plotColors2, '\Delta\nu_{1/2} vs. (\pi T_2^{app})^{-1}', usePpm, yAxisLim, offsetPlot, figureIds{4});
+ end
+ figureIds{4} = plotFWHMs(fwhmReshaped, [], metaboliteNamesDisplay, numberOfMet, scanFrequency, plotColors, '\Delta\nu_{1/2} vs. (\pi T_2^{app})^{-1}', usePpm, yAxisLim, offsetPlot, figureIds{4});
+ if usePpm
+ text(0.06,1.0,'\Delta\nu_{1/2}','Units', 'Normalized', 'VerticalAlignment', 'Top', ...
+ 'FontSize', 13,'FontWeight', 'bold', 'Color',[0 0 1]);
+ text(0.06,0.90,'(\pi T_2^{app})^{-1}','Units', 'Normalized', 'VerticalAlignment', 'Top', ...
+ 'FontSize', 13,'FontWeight', 'bold', 'Color',[0 0.5 0]);
+ scatter(2.2,0.217,'filled','s','MarkerEdgeColor',[0,0,1], 'MarkerFaceColor',[0,0,1], 'LineWidth',2)
+ scatter(2.2,0.187,'filled','s','MarkerEdgeColor',[0,0.5,0], 'MarkerFaceColor',[0,0.5,0], 'LineWidth',2)
end
- figureIds{4} = plotFWHMs(fwhmReshaped, [], metaboliteNamesDisplay, numberOfMet, scanFrequency, plotColors, 'Full-Width-Half-Maxima vs. Linewidth Component from T_2', usePpm, yAxisLim, offsetPlot, figureIds{4});
-
-
tableFWHMSummarized = cell(numberOfMet+1,4);
tableFWHMSummarized(2:end,1) = metaboliteNamesDisplay;
tableFWHMSummarized(1,2) = {['FWHM' plusMinusSign 'Std']};
@@ -408,7 +428,7 @@ if doFWHMevalutation
for index=1:numberOfMet
tableFWHMSummarized{index+1,2} = [num2str(meanFwhmReshaped(index), writePrecision) plusMinusSign num2str(stdFwhmReshaped(index), writePrecision)];
end
- exportFileXlsx = [data_path ,'Output\FWHM_Results_Mean_std.xlsx'];
+ exportFileXlsx = [data_path , outputFolder, 'FWHM_Results_Mean_std.xlsx'];
xlswrite(exportFileXlsx, tableFWHMSummarized, 1, 'A1');
end
@@ -450,10 +470,10 @@ end
% set(gca, 'YLim', [0,fwhm_plot_limit_ppm]);
% end
-ylabel('FWHM (Hz)')
+ylabel('\Delta\nu (Hz)')
if usePpm
yyaxis right
- ylabel('FWHM (ppm)', 'Color', 'k')
+ ylabel('\Delta\nu (ppm)', 'Color', 'k')
yyaxis left
end
@@ -481,3 +501,52 @@ else
set(gca, 'YLim', [0,yAxisLim]);
end
end
+
+function saveCRLBs(CRLBs, TEs, metaboliteNamesDisplay, data_path, outputFolder)
+CRLBs = cell2mat(CRLBs(:,2:end,:));
+metaboliteNamesDisplay = metaboliteNamesDisplay(2:end);
+CRLBs_mean = squeeze(mean(CRLBs,1, 'omitnan'));
+CRLBs_std = squeeze(std(CRLBs,1, 'omitnan'));
+numberOfMet = size(CRLBs_mean,1);
+plusMinusSign = [' ' char(177) ' '];
+tableCRLBSummarized = cell(numberOfMet+1,6);
+tableCRLBSummarized(2:end,1) = metaboliteNamesDisplay;
+for indexTE = 1:length(TEs)
+ tableCRLBSummarized{1,indexTE+1} = ['TE = ', num2str(TEs(indexTE)), ' ms'];
+ for indexMet=1:numberOfMet
+ tableCRLBSummarized{indexMet+1,indexTE+1} = [sprintf('%.1f', CRLBs_mean(indexMet, indexTE))...
+ plusMinusSign sprintf('%.1f', CRLBs_std(indexMet, indexTE))];
+ end
+end
+
+exportFileXlsx = [data_path , outputFolder, 'CRLB_Results_Mean_std.xlsx'];
+xlswrite(exportFileXlsx, tableCRLBSummarized, 1, 'A1');
+
+colors = {[0 0 1]; [0 0 0]; [0 0.5 0]; [0 0 0]; [0.7 0.2 0.2]};
+offsetPlot = 0.25;
+positionsTicks = 2.2:1.5:1.5*numberOfMet+1.5;
+figId = figure;
+hold on
+for indexTE = 1:2:length(TEs)
+
+ positions = positionsTicks + offsetPlot * (indexTE-3);
+ boxplot(CRLBs(:,:,indexTE), metaboliteNamesDisplay,'colors',colors{indexTE},'symbol','+',...
+ 'positions',positions, 'Widths',0.3);
+ text(0.3,0.95 - (indexTE-1) * 0.03,['TE = ' num2str(TEs(indexTE)), ' ms'],'Units', 'Normalized', ...
+ 'VerticalAlignment', 'Top', 'FontSize', 12,'FontWeight', 'bold', 'Color',colors{indexTE});
+ scatter(7.5,580 - (indexTE-1) * 20,'filled','s','MarkerEdgeColor',colors{indexTE}, 'MarkerFaceColor',colors{indexTE}, 'LineWidth',1.5);
+end
+
+ylabel('CRLBs (%)')
+ylim([0 620])
+
+ax = get(figId,'CurrentAxes');
+ax.XAxis.TickLength = [0,0];
+ax.YColor = 'k';
+
+set(gca, 'YGrid', 'on');
+set(gca, 'XTickMode', 'manual');
+set(gca, 'XTick', positionsTicks);
+set(gca, 'XLim', [positionsTicks(1)-0.8 positionsTicks(end)+0.8]);
+set(gca, 'XTickLabelRotation', 90.0);
+end
\ No newline at end of file
diff --git a/postprocessing/extractFits.m b/postprocessing/extractFits.m
index 163bb44cdb28ebd5c1521341362f060de9c16c54..72b3ddf32c6436d068f057f75dbf5f59d15ec814 100644
--- a/postprocessing/extractFits.m
+++ b/postprocessing/extractFits.m
@@ -1,5 +1,6 @@
function [nOfPoints, ppmVector, phasedData, fitData, baselineData, residualData, ...
- metaboliteNames, metaboliteData, tableConcentrations, ppmStart, ppmEnd, scanFrequency, frequencyShift, ppmGap] = ...
+ metaboliteNames, metaboliteData, tableConcentrations, ppmStart, ppmEnd, ...
+ scanFrequency, frequencyShift, ppmGap, phase0, phase1] = ...
extractFits(PathName, FileName)
c = textread(strcat(PathName,FileName),'%s');
@@ -87,17 +88,31 @@ for indexMetabolite = 1:numberOfMetabolites
end
%other information
-indexOfValue = find(strcmp(c,'ppmst='))+1;
+indexOfValue = find(strcmpi(c,'ppmst='))+1;
+if isempty(indexOfValue)
+ indexOfValue = find(strcmpi(c,'ppmst'))+2;
+end
ppmStart = str2double( c(indexOfValue,1));
-indexOfValue = find(strcmp(c,'ppmend='))+1;
+indexOfValue = find(strcmpi(c,'ppmend='))+1;
+if isempty(indexOfValue)
+ indexOfValue = find(strcmpi(c,'ppmend'))+2;
+end
ppmEnd = str2double( c(indexOfValue,1));
-indexOfValue = find(strcmp(c,'hzpppm='))+1;
+indexOfValue = find(strcmpi(c,'hzpppm='))+1;
+if isempty(indexOfValue)
+ indexOfValue = find(strcmp(c,'hzpppm'))+2;
+end
scanFrequency = str2double( c(indexOfValue,1));
-indexOfValue = find(strcmp(c,'shift'))+2; % 'Data shift = x.xx ppm'
+indexOfValue = find(strcmpi(c,'shift'))+2; % 'Data shift = x.xx ppm'
frequencyShift = str2double( c(indexOfValue,1));
+indexOfValue = find(strcmpi(c,'Ph:'))+1; % 'Ph: xx deg xx.x deg/ppm'
+phase0 = str2double( c(indexOfValue,1));
+phase1 = str2double( c(indexOfValue+2,1));
+
tempX = strfind(c,'ppmgap(2,1)=');
indexOfValue = find(~cellfun(@isempty,tempX));
+
if isempty(indexOfValue)
ppmGap = [];
else
diff --git a/postprocessing/getRelaxationTimes.m b/postprocessing/getRelaxationTimes.m
index 29eebeeccfc8958bc03de6ddc9d68d83e5f3c257..3edf2c3bfbc73671ef6c27980ec6f5d18dc9cd52 100644
--- a/postprocessing/getRelaxationTimes.m
+++ b/postprocessing/getRelaxationTimes.m
@@ -2,7 +2,7 @@ function [T1_met, T2_met, metaboliteNames] = getRelaxationTimes(compare, metabol
%% setting up data paths
switch compare
case 'DF'
- outputFolder = 'Output\';
+ outputFolder = 'Output\FWHMBA Results 7.5e-3\';
pathName = 'DF data path';
case 'MM'
outputFolder = 'OutputMM\';
@@ -102,9 +102,20 @@ switch compare
%values taken from A.Wright ISMRM 2019 abstract
metaboliteNamesT1 = {'NAA-asp'; 'NAA-ace'; 'tCho'; 'mI'; 'Gln'; 'Glu'; 'Cr-CH2'; 'Cr-CH3'; 'Tau'; 'GSH'; 'Glx'; 'tNAA'}; %'GABA'
T1_met_known = [1158 ; 1602 ; 1111; 1309 ; 1831; 1405 ; 1162 ; 1565 ; 1961 ; 1310 ; 1618 ; 1380 ]; %'966' (Gaba)
+ %values taken from A.Wright MRM 2021 paper (revision 2)
+ metaboliteNamesT1 = {'NAA-asp'; 'NAA-ace'; 'tCho'; 'mI'; 'Gln'; 'Glu'; 'Cr-CH2'; 'Cr-CH3'; 'Tau'; 'GSH'; 'Asp'; 'GABA'; 'Glyc'; 'NAAG'; 'PE'; 'Scyllo'; 'Glx'; 'tNAA'; 'tCr'; 'tCho+'; 'mI+Glyc'};
+ T1_met_known = [1137 ; 1701 ; 1161; 1499; 1214; 1343 ; 1118 ; 1678 ; 2063; 1505; 1300; 1240; 739; 1185; 1305; 1632; 1366; 1385; 1528; 1241; 1540];
defaultT1 = round(mean(T1_met_known(1:end-1)),2); %average of the MM T1 times
- [T1_met, metaboliteNames] = matchRelaxationTimes(T1_met_known, metaboliteNamesT1, defaultT1, metaboliteNames, true, mapMet_Names);
+ [T1_met, metaboliteNames] = matchRelaxationTimes(T1_met_known, metaboliteNamesT1, defaultT1, metaboliteNames, true, mapMet_Names);%CHECK ME
+
+ Cr_names = {'Cr+PCr'};
+ Cr_to_replace = {'Cr', 'PCr', 'Cr+PCr'};
+ [T1_met] = replaceRelaxationTimes(T1_met_known, metaboliteNamesT1, defaultT1, Cr_names, true, mapMetNamesDisplay, metaboliteNames, T1_met, Cr_to_replace);
+
+ NAA_names = {'NAA+NAAG'};%trick to use tNAA - for T1 the name was used as NAA(CH2)+NAA(CH3), while normally it means NAA+NAAG
+ NAA_to_replace = {'NAA','NAA+NAAG'};
+ [T1_met] = replaceRelaxationTimes(T1_met_known, metaboliteNamesT1, defaultT1, NAA_names, true, mapMetNamesDisplay, metaboliteNames, T1_met, NAA_to_replace);
%get T2 values
% load(['D:\Software\Spectro Data\DATA_df\Output_UF\meanT2s.mat'], 'acceptableMeanT2s', 'metaboliteNamesDisplay');
@@ -138,7 +149,7 @@ numberOfDesiredMetabolites = length(desiredMetaboliteNames);
desiredRelaxationTimes = zeros(1,numberOfDesiredMetabolites);
for index = 1:numberOfDesiredMetabolites
if exist('mapMet_Names','var')
- desiredMetaboliteName = mapMet_Names(desiredMetaboliteNames{index})
+ desiredMetaboliteName = mapMet_Names(desiredMetaboliteNames{index});
else
desiredMetaboliteName = desiredMetaboliteNames{index};
end
diff --git a/postprocessing/plot_All_Fit_Metabolites.m b/postprocessing/plot_All_Fit_Metabolites.m
index 4f0dc25186a13874a1dbf95932a01a09b39b8c18..937fef874c9a47b9c51a07cba4230dc19eaf9980 100644
--- a/postprocessing/plot_All_Fit_Metabolites.m
+++ b/postprocessing/plot_All_Fit_Metabolites.m
@@ -1,4 +1,4 @@
-function plot_All_Fit_Metabolites(FileName, PathName, downField_MM_Met, saveFigures)
+function plot_All_Fit_Metabolites(FileName, PathName, downField_MM_Met, saveFigures, displayBaseline)
if ~exist('FileName', 'var')
[FileName,PathName] = uigetfile('*.coord','Please select .coord files from LCModel','Multiselect','on');
@@ -8,11 +8,14 @@ if ~iscell(FileName)
FileName= {FileName};
end
+
+
if ~exist('downField_MM_Met','var')
% downField_MM_Met = 'Met moiety';
downField_MM_Met = 'Met moiety fMRS';
% downField_MM_Met = 'DF';
% downField_MM_Met = 'MM';
+ downField_MM_Met = 'fit';
end
overviewPlots = false;
@@ -21,6 +24,10 @@ if ~exist('saveFigures','var')
saveFigures = true;
end
+if ~exist('displayBaseline','var')
+ displayBaseline = false;
+end
+
switch downField_MM_Met
case 'Met moiety'
metaboliteNames = {'Asp' 'Cr' 'Cr_CH2' 'GABA' 'Glu' 'Gln' 'GSH' 'Glyc' 'Lac' 'mI' 'NAA_as' 'NAA_ac' 'NAAG' 'Scyllo' 'Tau' 'tCho_P'};
@@ -40,16 +47,16 @@ switch downField_MM_Met
metaboliteLabels = {'NAA' 'NAAG' 'Asp' 'Glu' 'Gln' 'GABA' 'Lac' ...
'tCr' 'tCho' 'mI' 'sI' 'Gly' 'Glc' 'GSH' 'PE' 'Tau'};
-
+
metaboliteNames = {'Asp' 'Cr' 'PCr' 'GABA' 'Glu' 'Gln' 'GSH' 'Glyc' 'Lac' 'mI' 'NAA_as' 'NAA_ac' 'NAAG' 'Scyllo' 'Tau' 'tCho' 'PE'};
metaboliteLabels = {'Asp';'Cr';'PCr';'GABA';'Glu';'Gln';'GSH';'Glyc';'Lac';'mI';'NAA(CH_2)';'NAA(CH_3)';'NAAG';'Scyllo';'Tau';'tCho';'PE'};
metaboliteNames = {'Asp' 'Cr' 'PCr' 'GABA' 'Glu' 'Gln' 'GSH' 'Glyc' 'Lac' 'mI' 'NAA' 'NAAG' 'Scyllo' 'Tau' 'PCh' 'GPC' 'PE'};
metaboliteLabels = {'Asp';'Cr';'PCr';'GABA';'Glu';'Gln';'GSH';'Glyc';'Lac';'mI';'NAA';'NAAG';'Scyllo';'Tau';'PCh';'GPC';'PE'};
-
-% %Braino
-% metaboliteNames = {'Cr_CH3' 'Cr_CH2' 'Glu' 'Lac' 'mI' 'NAA_as' 'NAA_ac' 'Cho'};
-% metaboliteLabels = {'Cr_CH3';'Cr_CH2';'Glu';'Lac';'mI';'NAA(CH_2)';'NAA(CH_3)';'Cho'};
-
+
+ % %Braino
+ % metaboliteNames = {'Cr_CH3' 'Cr_CH2' 'Glu' 'Lac' 'mI' 'NAA_as' 'NAA_ac' 'Cho'};
+ % metaboliteLabels = {'Cr_CH3';'Cr_CH2';'Glu';'Lac';'mI';'NAA(CH_2)';'NAA(CH_3)';'Cho'};
+
xLimits = [0.5 4.097];
offsetMetabolite = 0.1;
@@ -61,7 +68,7 @@ switch downField_MM_Met
xLimits = [0.5 9];
metaboliteNames = {'hCs';'DF70';'ATP';'NAA_DF';'NAD';'DF58';'DF60';'DF68';'DF73';'DF75';'DF82';'DF83';'DF835';'NAAB';'DF61';'DF85'};
metaboliteLabels = {'hCs';'DF70';'ATP';'NAA_DF';'NAD';'DF58';'DF60';'DF68';'DF73';'DF75';'DF82';'DF83';'DF835';'NAAB';'DF61';'DF85'};
-
+
metaboliteNames = {'hCs';'NAA_DF';'NAD'; 'DF58'; 'DF60'; 'DF61'; 'DF68'; 'DF70'; 'DF73'; 'DF75'; 'NAAB'; 'DF82'; 'DF83'; 'DF835'; 'DF85'};
metaboliteLabels = {'hCs';'NAA'; 'NAD^+';'DF_{5.75}';'DF_{5.97}';'DF_{6.12}';'DF_{6.83}';'DF_{7.04}';'DF_{7.30}';'DF_{7.48}';'NAA Broad';'DF_{8.18}';'DF_{8.24}';'DF_{8.37}';'DF_{8.49}'};
xLimits = [5.5 9.4];
@@ -74,15 +81,25 @@ switch downField_MM_Met
end
case '31P'
- metaboliteNames = {'PCr' 'ATP-g' 'ATP-a' 'ATP-b' 'GPC' 'GPE' 'Pi_in' 'Pi_ext' 'PC' 'PE' 'NADH' 'NAD+' 'UDPG'};
- metaboliteLabels = {'PCr' 'ATP-gamma' 'ATP-alpha' 'ATP-beta' 'GPC' 'GPE' 'Pi intra' 'Pi extra' 'PC' 'PE' 'NADH' 'NAD+' 'UDPG'};
- xLimits = [-20 10];
- offsetMetabolite = 0.1;
- case 'MM'
- metaboliteNames = {'MM09' 'MM12' 'MM14' 'MM17' 'MM20' 'MM22' 'MM26' 'MM27' 'MM30' 'MM32' 'MM36' 'MM37' 'MM38' 'MM40' 'Cre'};
- metaboliteLabels = {'MM09' 'MM12' 'MM14' 'MM17' 'MM20' 'MM22' 'MM26' 'MM27' 'MM30' 'MM32' 'MM36' 'MM37' 'MM38' 'MM40' 'Cre'};
- xLimits = [0.5 4.097];
- offsetMetabolite = 0.1;
+
+ metaboliteNames = {'Cr' 'ATP-g' 'ATP-a' 'GPC' 'GPE' 'Pi_in' 'Pi_ext' 'PC' 'PE' 'NADH' 'NAD' 'UDPG'};
+ metaboliteLabels = {'PCr' 'ATP-gamma' 'ATP-alpha' 'GPC' 'GPE' 'Pi intra' 'Pi extra' 'PC' 'PE' 'NADH' 'NAD+' 'UDPG'};
+ xLimits = [-10 10];
+ case 'fit'
+
+ metaboliteNames = {}; %, 'NAA', 'Cr39', 'MMB_si', 'NAA', 'Cr39', 'Cr30', 'mI' 'combin'
+ metaboliteLabels = {}; %, 'NAA', 'Cr', 'MM' , 'NAA', 'Cr-CH_2', 'Cr-CH_3', 'mI' 'MM'
+ xLimits = [0.5 4.05]
+ offsetMetabolite = 0.15; %0.25
+
+ case 'MM'
+
+ metaboliteNames = {'MM09', 'MM12', 'MM14', 'MM17', 'MM20', 'MM22', 'MM26', 'MM27', 'MM30', 'MM32', 'MM36', 'MM37', 'MM38', 'Cr39', 'NAA', 'mI' ,'GPC', 'Glu', 'NAA_as'};% %, 'Cho', 'Glu', 'Gln', 'Tau', 'Glycin' 'PCr' %, 'NAA_si', 'Creat', 'PCreat', 'GPC','Glu', 'Gln', 'GABA','NAA_as','Asp','Tau', 'mI', 'Glycin'
+ metaboliteLabels = {'M_{0.92}', 'M_{1.21}', 'M_{1.39}', 'M_{1.67}', 'M_{2.04}', 'M_{2.26}', 'M_{2.56}', 'M_{2.70}', 'M_{2.99}', 'M_{3.21}', 'M_{3.62}', 'M_{3.75}', 'M_{3.86}' , 'tCr(CH_2)', 'NAA(CH_3)', 'mI', 'GPC', 'Glu', 'NAA_(asp)'}; %%'NAA', 'tCr(CH_{3})', 'tCho', 'Glu', 'Gln', 'Tau', 'Glyc', %, , 'NAA(CH_3)','tCr(CH_3)', 'tCr(CH_2)','GPC','Glu','Gln','GABA','NAA_{asp}', 'Asp', 'Tau', 'mI', 'Glycin'
+ xLimits = [0.5 4.097]
+ offsetMetabolite = 0.60; %0.25
+
+
otherwise
error('Not known downField_MM_Met');
end
@@ -95,13 +112,15 @@ end
numberOfMet = length(metaboliteNames);
%plotting offsets
+
offsetResidual = offsetMetabolite * (numberOfMet+1);
offsetBaseline = offsetResidual + offsetMetabolite;
-FontSize = 14;
+FontSize = 18;
% LineWidth = 1.5;
-% FontSize = 12;
+FontSize = 12;
LineWidth = 2;
+
%
ppm = {};
pData = {};
@@ -112,7 +131,7 @@ rData = {};
% close all;
for index =1:length(FileName)
- figId = figure(index+10);
+ figId = figure;%(index+10); %I am not sure if we need this indexing anymore. It is useful to have it like this for ProFit comparison
%[c1 c2 c3 c4] = textread(strcat(PathName,FileName{i}),'%s %s %s %s');
c = textread(strcat(PathName,FileName{index}),'%s');
nOfPoints = find(strcmp(c ,'points'),1);
@@ -156,38 +175,54 @@ for index =1:length(FileName)
%residual
rData{index} = pData{index} - fData{index};
- %scaling calculation
+ %scaling calculation
scale = max(pData{index});
%plotting
hold on
- if MMB_available
- p = plot(ppm{index}, (pData{index} - bData{index}) ./ scale , ...
- ppm{index},(fData{index} - bData{index}) ./ scale , ...
- ppm{index},(mmData{index}- bData{index} ) ./ scale - 0.03 , ...
- ppm{index},bData{index} ./ scale - offsetBaseline, ...
- ppm{index},rData{index} ./ scale - offsetResidual);
- text(xLimitsText,-0.03,'MMB', 'FontSize', FontSize, 'FontWeight', 'bold');
+ if displayBaseline
+ if MMB_available
+ p = plot(ppm{index}, pData{index} ./ scale , ...
+ ppm{index},fData{index} ./ scale , ...
+ ppm{index},(mmData{index}- bData{index}) ./ scale - 0.03 , ...
+ ppm{index},bData{index} ./ scale - offsetBaseline, ...
+ ppm{index},rData{index} ./ scale - offsetResidual);
+ text(xLimitsText,-0.03,'MM Spec.', 'FontSize', FontSize, 'FontWeight', 'bold');
+ else
+ p = plot(ppm{index}, pData{index} ./ scale, ...
+ ppm{index},fData{index} ./ scale, ...
+ ppm{index},bData{index} ./ scale - offsetBaseline, ...
+ ppm{index},rData{index} ./ scale - offsetResidual);
+ end
else
- p = plot(ppm{index}, (pData{index}- bData{index}) ./ scale, ...
- ppm{index},(fData{index}- bData{index}) ./ scale, ...
- ppm{index},bData{index} ./ scale - offsetBaseline, ...
- ppm{index},rData{index} ./ scale - offsetResidual);
+ if MMB_available
+ p = plot(ppm{index}, (pData{index} - bData{index}) ./ scale , ...
+ ppm{index},(fData{index} - bData{index}) ./ scale , ...
+ ppm{index},(mmData{index}- bData{index} ) ./ scale - 0.03 , ...
+ ppm{index},bData{index} ./ scale - offsetBaseline, ...
+ ppm{index},rData{index} ./ scale - offsetResidual);
+ text(xLimitsText,-0.03,'MM Spec.', 'FontSize', FontSize, 'FontWeight', 'bold');
+ else
+ p = plot(ppm{index}, (pData{index}- bData{index}) ./ scale, ...
+ ppm{index},(fData{index}- bData{index}) ./ scale, ...
+ ppm{index},bData{index} ./ scale - offsetBaseline, ...
+ ppm{index},rData{index} ./ scale - offsetResidual);
+ end
end
-
+
if overviewPlots && strcmp(downField_MM_Met, 'DF')
-% text(xLimitsText,0.05,'Data + Fit', 'FontSize', FontSize, 'FontWeight', 'bold');
+ % text(xLimitsText,0.05,'Data + Fit', 'FontSize', FontSize, 'FontWeight', 'bold');
text(xLimitsText,0.07,'Data + Fit', 'FontSize', FontSize, 'FontWeight', 'bold');
else
- text(xLimitsText,0.015,'Data + Fit', 'FontSize', FontSize, 'FontWeight', 'bold');
+ text(xLimitsText,0.03,'Data + Fit', 'FontSize', FontSize, 'FontWeight', 'bold');
end
text(xLimitsText,-offsetResidual,'Residual', 'FontSize', FontSize, 'FontWeight', 'bold');
-% text(xLimitsText,-offsetBaseline,'Baseline', 'FontSize', FontSize, 'FontWeight', 'bold');
+ % text(xLimitsText,-offsetBaseline,'Baseline', 'FontSize', FontSize, 'FontWeight', 'bold');
text(xLimitsText,-offsetBaseline-0.01,'Baseline', 'FontSize', FontSize, 'FontWeight', 'bold');
for plots = 1:length(p)
set(p(plots),'LineWidth',LineWidth);
end
-
+
for indexMetabolite = 1:length(metaboliteNames)
%evaluate each metabolite
if strcmp(metaboliteNames{indexMetabolite},'NAD+')
@@ -204,6 +239,7 @@ for index =1:length(FileName)
metaboliteSpectrum = metaboliteSpectrum + str2double(c(indexOfMet:endOfMet,1)) - bData{index};
end
end
+
if MMB_available
pMetabolite = plot(ppm{index}, metaboliteSpectrum ./ scale - indexMetabolite * offsetMetabolite);
text(xLimitsText, indexMetabolite * -offsetMetabolite,metaboliteLabels{indexMetabolite}, 'FontSize', FontSize, 'FontWeight', 'bold');
@@ -211,14 +247,14 @@ for index =1:length(FileName)
pMetabolite = plot(ppm{index}, metaboliteSpectrum ./ scale - (indexMetabolite-1) * offsetMetabolite);
text(xLimitsText, (indexMetabolite-1) * -offsetMetabolite,metaboliteLabels{indexMetabolite}, 'FontSize', FontSize, 'FontWeight', 'bold');
end
+
set(pMetabolite,'LineWidth',LineWidth);
end
- deltaChar = char(948);
-
xlim(xLimits);
- xlabel([deltaChar ' (ppm)']);
- ylim([-offsetBaseline-offsetMetabolite*2 1.1]);
+ xlabel('\delta (ppm)');
+ % ylim([-offsetBaseline-offsetMetabolite*2 0.07]);
+ ylim([-offsetBaseline-offsetMetabolite*2 1.1]);% for ProFit
if strcmp(downField_MM_Met, 'Met moiety')
else
% ylim([-0.08 0.1]);
@@ -228,14 +264,18 @@ for index =1:length(FileName)
ylim([-0.21 0.1]);
% ylim([-0.16 0.115]);
ylim([-2 1.1]);
+
end
+
set(gca,'xDir','reverse')
set(gca,'ytick',[]);
-
-% title(['Summed Metabolite Spectrum with Fitted Metabolites TE = 24 ms'])
-% title(FileName{index}, 'Interpreter', 'none')
+
+ % title(['Summed Metabolite Spectrum with Fitted Metabolites TE = 24 ms'])
+ % title(FileName{index}, 'Interpreter', 'none')
+
set(gca,'fontsize',FontSize);
set(gca,'FontWeight','bold');
+
clear nOfPoints indexOfMet i
if saveFigures
diff --git a/postprocessing/subtractMetabolitesFromMMB.m b/postprocessing/subtractMetabolitesFromMMB.m
index 9f3a0e6b31266049a98afd760e49db286c80aa74..50a3bffb658bea89c79b44286b5b219b11ceca63 100644
--- a/postprocessing/subtractMetabolitesFromMMB.m
+++ b/postprocessing/subtractMetabolitesFromMMB.m
@@ -1,16 +1,16 @@
function subtractMetabolitesFromMMB()
-pathName = 'MM data path';
-sampleCriteria = {'Output'};
+pathName = 'MM T1 data path';
+sampleCriteria = {'Output_GM_FinalCorrected'};
[localFilePathBase] = pathToDataFolder(pathName, sampleCriteria);
-LCModelOutputPath = [localFilePathBase, 'Output/'];
+LCModelOutputPath = [localFilePathBase, 'Output_GM_FinalCorrected/'];
-outputFileNameBase = 'Summed_Averaged_TE';
-fileNameBaseWithoutMetabolite = 'MMB_without_metabolite_TE';
-orderTEs = {'24' '32' '40' '52' '60'};
+outputFileNameBase = 'Summed_Averaged_TI1_';
+fileNameBaseWithoutMetabolite = 'MMB_without_metabolite_TI1_';
+orderTEs = {'1900'}; %'2360' '2000' '1900' '1800'
extensionCoord = '.coord';
extensionMat = '.mat';
-metabolitesToSubtract = {'Cre'};
+metabolitesToSubtract = {'Cr39', 'Cr30', 'NAA', 'Glx'};
doNullingOfDownField = true;
LCModelTableFitsCoord = strcat(outputFileNameBase, orderTEs, extensionCoord);
reconstructedSpectra = strcat(localFilePathBase, outputFileNameBase, orderTEs, extensionMat);
@@ -28,25 +28,25 @@ LineWidth = 1.5;
for indexTE = 1:numberOfTEs
currentReconstructedSpectra = reconstructedSpectra{indexTE};
- load(currentReconstructedSpectra, 'summedSpectraTE');
+ load(currentReconstructedSpectra, 'summedSpectraTI');
currentLCModelCoordFit = LCModelTableFitsCoord{indexTE};
[nOfPoints, ppmVector, phasedData, fitData, baselineData, residualData, ...
metaboliteNames, metaboliteData, tableConcentrations, ppmStart, ppmEnd, ...
scanFrequency, frequencyShift, ppmGap] = ...
extractFits(LCModelOutputPath,currentLCModelCoordFit);
-
+ ppmGap = 4.1
% align the two spectra
- fid = summedSpectraTE.Data{1};
+ fid = summedSpectraTI.Data{1};
spectrum = fftshift(fft(fid(:,1,1,1,1,1,1,1,1,1,1,1),size(fid,1)*zeroFillFactor));
- ppmSpectrum = summedSpectraTE.getPpmVector(zeroFillFactor);
+ ppmSpectrum = summedSpectraTI.getPpmVector(zeroFillFactor);
[~, maxPpmValueSpectrum] = getMaxPeak(ppmSpectrum', real(spectrum), 3.925, 0.1);
[~, maxPpmValueLCModel] = getMaxPeak(ppmVector, phasedData, 3.925, 0.1);
frequencyShiftDiff = maxPpmValueSpectrum - maxPpmValueLCModel;
- summedSpectraTE = summedSpectraTE.ApplyFrequencyShift(frequencyShiftDiff);
+ summedSpectraTI = summedSpectraTI.ApplyFrequencyShift(frequencyShiftDiff);
%get the aligned reconstructed spectra
- fid = summedSpectraTE.Data{1};
+ fid = summedSpectraTI.Data{1};
spectrum = fftshift(fft(fid(:,1,1,1,1,1,1,1,1,1,1,1),size(fid,1)*zeroFillFactor));
% max of the reconstructed spectrum
if isempty(ppmGap)
@@ -122,7 +122,7 @@ for indexTE = 1:numberOfTEs
% xlim([0 4.2])
% title(sprintf('Imag MMB TE %s', orderTEs{indexTE}))
- MMB_without_metabolite = summedSpectraTE;
+ MMB_without_metabolite = summedSpectraTI;
newFid = ifft(ifftshift(newSpectrum));
MMB_without_metabolite.Data{1} = newFid;
diff --git a/reconstruct_all_Met.m b/reconstruct_all_Met.m
new file mode 100644
index 0000000000000000000000000000000000000000..11fb0de70cd4fee488a9baa0376a0ee850b1feb1
--- /dev/null
+++ b/reconstruct_all_Met.m
@@ -0,0 +1,161 @@
+function reconstruct_all_Met()
+
+pathName = 'Met T1 GM data path';
+subjects = { ...
+ '1405' ...
+ '1706' ...
+ '1717' ...
+ '2016' ...
+ '2017' ...
+ '3373' ...
+ '3490' ...
+ '6971' ...
+ '7338' ...
+ '7782' ...
+ '9810' ...
+ };
+
+pathBase = pathToDataFolder(pathName, subjects);
+
+TI = [20; 100; 400; 700; 1000; 1400; 2500];
+
+numberOfSubjects = length(subjects);
+paths = cell(1,numberOfSubjects);
+for indexSubj = 1:numberOfSubjects
+ paths{indexSubj} = [pathBase subjects{indexSubj} '\\'];
+end
+
+files_TI_20 = cell(1, numberOfSubjects);
+files_TI_100 = cell(1, numberOfSubjects);
+files_TI_400 = cell(1, numberOfSubjects);
+files_TI_700 = cell(1, numberOfSubjects);
+files_TI_1000 = cell(1, numberOfSubjects);
+files_TI_1400 = cell(1, numberOfSubjects);
+files_TI_2500 = cell(1, numberOfSubjects);
+
+% water_files = cell(1, numberOfSubjects);
+for indexSubject = 1:numberOfSubjects
+ files_TI_20{indexSubject} = ls([paths{indexSubject}, '*_semiLASER_2360_625_*.dat']);
+ files_TI_100{indexSubject} = ls([paths{indexSubject}, '*_semiLASER_1800_525_*.dat']);
+ files_TI_400{indexSubject} = ls([paths{indexSubject}, '*_semiLASER_1900_550_*.dat']);
+ files_TI_700{indexSubject} = ls([paths{indexSubject}, '*_semiLASER_2000_575_*.dat']);
+ files_TI_1000{indexSubject} = ls([paths{indexSubject}, '*_semiLASER_2150_600_*.dat']);
+ files_TI_1400{indexSubject} = ls([paths{indexSubject}, '*_semiLASER_1200_20_*.dat']);
+ files_TI_2500{indexSubject} = ls([paths{indexSubject}, '*_semiLASER_1250_20_*.dat']);
+% files_TI_1300_80{indexSubject} = ls([paths{indexSubject}, '*_semiLASER_1300_80_*.dat']);
+% files_TI_1300_60{indexSubject} = ls([paths{indexSubject}, '*_semiLASER_1300_60_*.dat']);
+% files_TI_1300_20{indexSubject} = ls([paths{indexSubject}, '*_semiLASER_1300_20_*.dat']);
+% files_TI_1050_238{indexSubject} = ls([paths{indexSubject}, '*_semiLASER_1050_238_*.dat']);
+% water_files{indexSubject} = ls([paths{indexSubject}, '*_scout_wref_*.dat']);
+end
+
+addSinglet0ppm = 'Yes';
+numberOfTIs = length(TI);
+
+filesPath = cell(numberOfTIs,numberOfSubjects);
+waterFilesPath = cell(1,numberOfSubjects);
+files = [files_TI_20; files_TI_100; files_TI_400;files_TI_700;...
+ files_TI_1000; files_TI_1400; files_TI_2500;];
+for indexSubj = 1:numberOfSubjects
+ for indexTI = 1:numberOfTIs
+ filesPath{indexTI, indexSubj} = [paths{indexSubj} files{indexTI, indexSubj}];
+ end
+% waterFilesPath{indexSubj} = [paths{indexSubj} water_files{indexSubj}];
+end
+
+summedSpectra = cell(numberOfTIs,1);
+indexSubjTIs = zeros(numberOfTIs,1);
+for indexSubj = 1:numberOfSubjects
+ %% water data
+% [a] = reconstructWater(waterFilesPath{indexSubj});
+% filename = [paths{indexSubj} subjects{indexSubj} '_water.mat'];
+% save(filename, 'a');
+% a.ExportLcmRaw(paths{indexSubj}, strcat(subjects{indexSubj}, '_water'), addSinglet0ppm);
+ %calculate scaling factor the summedSpectra individually according to water peak
+% waterData = a.Data{1};
+% maxWaterPeak = max(real(fftshift(fft(waterData))));
+% %scale the data for equalizing between subjects
+% a.Data{1} = a.Data{1}./ maxWaterPeak;
+ %create summed spectra
+% if(indexSubj == 1)
+% summedWater = a;
+% newDataWater= zeros(length(a.Data{1}),1,1,1,1,1,1,1,1,1,1,numberOfSubjects);
+% else
+% oldDataWater = summedWater.Data{1};
+% if (ndims(oldDataWater) ~= 12)
+% newDataWater(:,1,1,1,1,1,1,1,1,1,1,1) = oldDataWater;
+% else
+% newDataWater(:,1,1,1,1,1,1,1,1,1,1,:) = oldDataWater;
+% end
+% newDataWater(:,1,1,1,1,1,1,1,1,1,1,indexSubj) = a.Data{1};
+% summedWater.Data{1} = newDataWater;
+% end
+
+
+
+ %% reconstruct Macromolecule data
+ for indexTI = 1:numberOfTIs
+ if((TI(indexTI) == 1300)| (TI(indexTI) ==1250) | (TI(indexTI)==1200))
+ doReverse = false;
+ else
+ doReverse = false;
+ end
+ a = reconstruct(filesPath{indexTI, indexSubj}, 1, 1);
+ filename = [paths{indexSubj} subjects{indexSubj} '_TI_' num2str(TI(indexTI)) '.mat'];
+ save(filename, 'a');
+ a.ExportLcmRaw(paths{indexSubj}, strcat(subjects{indexSubj}, '_TI1_', num2str(TI(indexTI))) , addSinglet0ppm);
+ %scale the data for equalizing between subjects
+% a.Data{1} = a.Data{1}./ maxWaterPeak;
+
+ % eliminate data with too many deleted averages from the summedSpectra
+
+ deletedAverages = a.Parameter.DeleteMovedAveragesSettings.deletedAverages;
+ if ~isempty(deletedAverages)
+ numDeletedAverages = length(deletedAverages);
+ else
+ numDeletedAverages = 0;
+ end
+
+ if numDeletedAverages <= 2
+ indexSubjTIs(indexTI) = indexSubjTIs(indexTI) + 1;
+ %create summed spectra
+ if(indexSubjTIs(indexTI) == 1)
+ summedSpectra{indexTI} = a;
+ newData= zeros(length(a.Data{1}),1,1,1,1,1,1,1,2,1,1,numberOfSubjects);
+ else
+ oldData = summedSpectra{indexTI}.Data{1};
+ if (ndims(oldData) ~= 12)
+ newData(:,1,1,1,1,1,1,1,:,1,1,1) = oldData;
+ else
+ newData(:,1,1,1,1,1,1,1,:,1,1,:) = oldData;
+ end
+ newData(:,1,1,1,1,1,1,1,:,1,1,indexSubjTIs(indexTI)) = a.Data{1};
+ summedSpectra{indexTI}.Data{1} = newData;
+ end
+ end
+ end
+end
+
+%
+
+% filename = [pathBase, 'Summed_water.mat'];
+% save(filename, 'summedWater');
+% summedWater = summedWater.AverageData;
+% save([pathBase, 'Summed_Averaged_water.mat'], 'summedWater');
+% summedWater.ExportLcmRaw(pathBase, 'Summed_Averaged_water', addSinglet0ppm);
+for indexTI = 1:numberOfTIs
+ filename = [pathBase, 'Summed_spectra_TI' num2str(TI(indexTI)) '.mat'];
+ summedSpectraTI = summedSpectra{indexTI};
+ %store only the data, which was kept after eliminating the deleted ones
+ actualData = summedSpectraTI.Data{1}./indexSubjTIs(indexTI);
+ summedSpectraTI.Data{1} = actualData(:,1,1,1,1,1,1,1,:,1,1,1:indexSubjTIs(indexTI));
+ save(filename, 'summedSpectraTI');
+ %average across subjects
+ summedSpectraTI = summedSpectraTI.AverageData;
+ filename = [pathBase, 'Summed_Averaged_TI_' num2str(TI(indexTI)) '.mat'];
+ save(filename, 'summedSpectraTI');
+ summedSpectraTI.ExportLcmRaw(pathBase, strcat('Summed_Averaged_TI_', num2str(TI(indexTI))), addSinglet0ppm);
+end
+
+%summarize_Deleted_Averages(subjects, pathBase, TI1)
+close all
diff --git a/spant_metabolites_basis_sets_creation.m b/spant_metabolites_basis_sets_creation.m
new file mode 100644
index 0000000000000000000000000000000000000000..6810dcadb74eaa725b3cee7c96180a16477e59ad
--- /dev/null
+++ b/spant_metabolites_basis_sets_creation.m
@@ -0,0 +1,61 @@
+
+function spant_metabolites_basis_sets_creation()
+
+plotBasis = false;
+
+metabolites = {'Asp', 'Cr_singlet_tot_3.925', 'Cr_singlet_tot_3.028', 'GABA', 'Gln', 'Glu', 'Glyc', ...
+ 'GSH', 'Lac', 'mI', 'NAA_2', 'NAA_1', 'NAAG', 'tCho_PE', 'Scyllo', 'Tau'};
+
+numberOfMet = length(metabolites);
+abbreviations = metabolites;
+metaboliteNames = metabolites;
+scalingFactors = zeros(numberOfMet,1)+1;
+
+abbreviationsUnique = unique(abbreviations);
+
+pathName = 'DF data path';
+sampleCriteria = {};
+[localFilePathBase] = pathToDataFolder(pathName, sampleCriteria);
+
+filePathBase = strcat(localFilePathBase, 'Basis_sets/final_T2_met_MM_paper/sLASER_new_UF_7ppm/');
+filePathBaseOut = strcat(filePathBase, 'Out/');
+orderTEs = {'24' '32' '40' '52' '60'};
+filePaths = strcat(filePathBase, 'TE', orderTEs , '\');
+filePathsOut = strcat(filePathBaseOut, 'TE', orderTEs , '\');
+
+for indexTE = 1 : length(orderTEs)
+ filePath = filePaths{indexTE};
+ filePathOut = filePathsOut{indexTE};
+ for indexMetabolite = 1 : length(abbreviationsUnique)
+ combined_metabolite_name = abbreviationsUnique{indexMetabolite};
+ indeces = strcmp(abbreviations,combined_metabolite_name);
+ numOfMetToCombine = sum(indeces);
+ metabolitesToMix = metaboliteNames(indeces);
+ factorsToMix = scalingFactors(indeces);
+ %
+ dataMix = cell(1,numOfMetToCombine);
+ metaboliteNameMix = cell(1,numOfMetToCombine);
+ singletPresentMix = cell(1,numOfMetToCombine);
+
+ for indexMetabolitesToMix = 1:numOfMetToCombine
+ [dataMix{indexMetabolitesToMix}, bandwidth, scanFrequency, metaboliteNameMix{indexMetabolitesToMix}, ...
+ singletPresentMix{indexMetabolitesToMix}] = ...
+ ImportLCModelBasis(filePath, metabolitesToMix{indexMetabolitesToMix}, ...
+ plotBasis);
+ end
+ %combine
+ combinedData = dataMix{1} * factorsToMix(1);
+ for indexMetabolitesToMix = 2:numOfMetToCombine
+ % average the contributions. Don't worry about the
+ % ref. singlet, it does not influence the fitting
+ combinedData = combinedData + factorsToMix{indexMetabolitesToMix} * ...
+ dataMix{indexMetabolitesToMix};
+ end
+
+ dwellTimeMs = 1/bandwidth * 1e3;
+ addSinglet = false;
+
+ ExportLCModelBasis(combinedData', dwellTimeMs, scanFrequency, filePathOut, ...
+ combined_metabolite_name, combined_metabolite_name, addSinglet);
+ end
+end