function initializeFunction(askModel, h, m)

global mainFolder segmentationFolder trackAnalysisFolder trackingFolder modelFolder ...
    globalFolder moviesFile parameters segmentationIndexes nbMovies trackingIndexes evaluationIndexes...
    trackAssemblyIndexes trainingIndexes predictionIndexes modelName manualLabelingFolder sharedManLab...
    mainFunctionFolder resultFolder predictionFolder gp33 noPept noP14 BMDCRatio_OVA BMDCRatio_GP33 agSpeRatio_OVA avg_grouping...
    figureFolder facs_data apl human mlr ova_clean ova gp33_clean BMDCNumber w_eff w_fdr

%% Folders


if nargin == 0
    askModel = false;
    human = false;
    mlr = false;
else 
    human = h;
    mlr = m;
end
%%

mainFolder = 'pathToFolder';
addpath(genpath(mainFolder));
mainFunctionFolder = fullfile(mainFolder, 'mainFunction');
segmentationFolder= fullfile(mainFolder, 'segmentation');
trackingFolder = fullfile(mainFolder, 'Tracking'); 
trackAnalysisFolder = fullfile(mainFolder, 'TrackAssembly'); 
predictionFolder = fullfile(mainFolder, 'prediction'); 
modelFolder = fullfile(mainFolder, 'models'); 
globalFolder = fullfile(mainFolder, 'globalFunctions'); 
resultFolder = 'pathToFolder';
figureFolder = fullfile(mainFolder, 'figures'); 
manualLabelingFolder  = fullfile(mainFolder, 'manualLabeling'); 
if mlr
    resultFolder = pathToFolder;
end

addpath(genpath(mainFolder));

%% Important Txt files
moviesFile = fullfile(mainFolder, 'moviesFile_DMEM.txt');
parameters = fullfile(mainFolder, 'parameters.txt');
if mlr
    moviesFile = fullfile(mainFolder, 'moviesFile_mouseMLR.txt');
    %moviesFile = fullfile(mainFolder, 'moviesFile_human_Allo.txt');
end
% Import relevant movie Indexes
[segmentationIndexes, nbMovies, trackingIndexes, trackAssemblyIndexes,trainingIndexes, evaluationIndexes, predictionIndexes] = importGeneralInfos;

% Ask the user which SVM model he would like to use
if askModel
    if isempty(modelName)
        modelName = askWhichModelToUse;
    end
end

%% 

gp33 = [42:47, 54:59, 168:179, 264:323];
noPept = [72:77, 84:89];
noP14 = 96:131;
BMDCRatio_OVA = [13:35, 96:119];
BMDCRatio_GP33 = 168:179;
BMDCNumber = 216:227;
agSpeRatio_OVA = [180:191, 336:371];
gp33_clean = setdiff(gp33,BMDCRatio_GP33(4:end));

avg_grouping = [1,4,7,10,13,16,19,22,24,27,30,33,36,39,42,48,51,54,60,63,72,75,78,81,84,...
    87,90,93,96,99,102,105,108,111,114,117,120,123,126,129,132,138,144,147,...
    150,153,156,159,162,165,168,171,174,177,180,183,186,189,192,195,198,201,...
    204,207,210,213,216,219,222,225];
facs_data = [72:80,84:89,93:95,120:131];
apl = [120:131,324:335, 372:383]; % [120:131,324:335, 372:407];
ova = setdiff(predictionIndexes, gp33);
ova_clean = setdiff(predictionIndexes, noPept);
ova_clean = setdiff(ova_clean, noP14);
ova_clean = setdiff(ova_clean, gp33);
ova_clean = setdiff(ova_clean, BMDCRatio_OVA);
ova_clean = setdiff(ova_clean, agSpeRatio_OVA);
ova_clean = setdiff(ova_clean, BMDCNumber(4:end));

w_eff = 1;
w_fdr = 5;


%facs_data = setdiff(72:191, [96:98, 108:110]);