%'monocularDeprivation_diffProbs_local_s'
function parTest(folders, nWorkers, runParallel)

%     folders = {'GammaVsMetCosts_0,5mio'}; % cluster run tier
%     folders = {'CritLRVsMetCosts_1mio'};

    nStim = 40;
    testpaths = {};
    iter = 1;

    for k = 1 : length(folders) % single run tier
        folder = folders{k};
        % parent = strcat('/home/aecgroup/aecdata/Results/SAB2018/', folder);
        parent = strcat('/home/aecgroup/aecdata/Results/eLifePaper/', folder);
        % subfolders = dir(sprintf('%s/*fixVergAngleAt6m_filtB_29_strabAngle_5*', parent));
        % subfolders = dir(sprintf('%s/*strabAngle_10*', parent));
        % subfolders = dir(sprintf('%s/*lapSigma_200.00*', parent));
        % subfolders = dir(sprintf('%s/*rotatePlane*', parent));
        % subfolders = dir(sprintf('%s/*filtBoth_46*', parent)); %45, 46
        % subfolders = dir(sprintf('%s/*yaw+tilt*', parent));
        % subfolders = dir(sprintf('%s/*twoScales*', parent));
        % parent = strcat('/home/aecgroup/aecdata/Results/', folder);
        % subfolders = dir(sprintf('%s/*prelearnedBF*', parent));
        % subfolders = dir(sprintf('%s/*aniseikonia+*', parent));
        % subfolders = dir(sprintf('%s/*MGRandomTextures2*', parent));
        subfolders = dir(sprintf('%s/*_randomMcGillImages_*', parent));
        % subfolders = dir(sprintf('%s/*aniseikonia+_aniLR_[0-+0.10]*', parent));
        
        % subfolders = dir(sprintf('%s/*iter*', parent));


        for s = 1 : length(subfolders) % test folder tier
            subfolder = subfolders(s);

            subsubfolders = dir(sprintf('%s/%s/modelAt*', subfolder.folder,subfolder.name));
%             if subfolder.isdir
%                 testpaths{iter} = sprintf('%s/%s/model.mat', parent, subfolder.name);
%                 iter = iter + 1;
%             end
            for ss = 1:length(subsubfolders)
                subsubfolder = subsubfolders(ss);

                    % if ~isfile(sprintf('%s/%s/vergenceAngleApproach.png', parent, subfolder.name))
                    if ~isfile(sprintf('%s/%s/scModel2eyes3_freq.mat', parent, subfolder.name))
%                     if ~isfile(sprintf('%s/%s/scModel2eyes3.mat', subsubfolder.folder, subsubfolder.name))
                        fpath = sprintf('%s/%s/model.mat', subsubfolder.folder, subsubfolder.name)
                        testpaths{iter} = fpath;
                        iter = iter + 1;
                    end

        %             testfolders = dir(sprintf('%s/%s/*modelAt*0',parent, subfolder.name));
        %             % testfolders = dir(sprintf('%s/%s/*modelAt*',parent, subfolder.name));
        %
        %             for t = 1 : length(testfolders)
        %                 testfolder = testfolders(t);
        %                 testpaths{iter} = sprintf('%s/%s/%s/model.mat', parent, subfolder.name, testfolder.name);
        %                 iter = iter + 1;
        %             end
            end
        end
    end

%     testpaths = testpaths(3:end); % remove '.' and '..
%     testpaths = fliplr(testpaths); % change order to run on different nodes

    % testpaths = testpaths(randperm(length(testpaths)));

    % % only for BF fitting
    % myCluster = parcluster('local');
    % myCluster.NumWorkers = nWorkers;
    % % saveProfile(myCluster);

    % if (isempty(gcp('nocreate')))
    %     mPool = parpool(nWorkers);
    % end

    if runParallel
        myCluster = parcluster('local');
        myCluster.NumWorkers = nWorkers;
        % saveProfile(myCluster);

        if (isempty(gcp('nocreate')))
            mPool = parpool(nWorkers);
        end

        % parfor tp = 1 : length(testpaths)
        for tp = 1 : length(testpaths)
            savePath = testpaths{tp}
            try
                model = load(strcat(savePath));
            catch
                sprintf('no valid file found')
                continue
            end
            model = model.model;
            simulator = [];  % lets see if it works with the parallel pool like this
            % if ~exist(sprintf('%s/modelAt%d/muscleActivityTrajectory.png', model.savePath, model.trainedUntil), 'file') % if the last image from the test procedure does not exists ...
            % if ~any(model.testHist(find(model.testAt == model.trainedUntil))) % test if according field in testHist is empty
%             if isempty(model.testResult7)
%                 sprintf('could not find test results in %s\n starting test procedure.', savePath)
%                 testModelContinuous(model, nStim, 1, 1, 1, simulator, 0, sprintf('modelAt%d', model.trainedUntil), [1, 3 : 6]);
%                 testModelContinuous(model, 0, 1, 1, 1, simulator, 0, sprintf('modelAt%d', model.trainedUntil), [1, 3 : 4, 6]);
                testModelContinuous(model, 0, 1, 1, 1, simulator, 0, sprintf('modelAt%d', model.trainedUntil), [1, 3, 4, 6]); % only save testHist
%             else
%                 sprintf('skip testing for\n%s', savePath)
%             end
        end

    else
        % textureFile = 'Textures_mcgillManMade40.mat';
        % simulator = OpenEyeSimV5('create'); % latest renderer

        % simulator.initRenderer();

        % texture = load(sprintf('config/%s', textureFile));
        % texture = texture.texture;
        % for i = 1 : nStim
        %     simulator.add_texture(i, texture{i});
        % end
        % sprintf('%d textures added to the testing simulator', nStim)

        for tp = 1 : length(testpaths)
            savePath = testpaths{tp}
            try
                model = load(strcat(savePath));
            catch
                sprintf('no valid file found')
                continue
            end
            model = model.model;

%             % if model.rlModel.CCritic.gamma == 0.01
% %             if model.trainedUntil ~= model.trainTime
% %                 continue
% %             end
%
% %             if model.trainedUntil == model.trainTime
% %                 model.allPlotSave(1:7);
% %                 close all;
% %                 sprintf('finisched plotting')
% %             else
% %                 sprintf('skip testing')
% %             end
%             testModelContinuous(model, 40, 1, 1, 1, simulator, 0, sprintf('modelAt%d_trainInpt', model.trainedUntil), [1, 3, 4, 6]);
%             % testModelContinuous_explore(model, 40, 1, 1, 1, simulator, 0, sprintf('modelAt%d+expl', model.trainedUntil), [1, 3, 4, 6]);

            % sprintf('trainedUntil: %d', model.trainedUntil
            % if ~exist(sprintf('%s/modelAt%d/muscleActivityTrajectory.png', model.savePath, model.trainedUntil), 'file') % if the last image from the test procedure does not exists ...
            if model.trainedUntil == 500000
%             if model.trainedUntil == 0%250000
                % if ~isfile(sprintf('%s/%s/scModel2eyes3.mat', parent, subfolder.name))
                    % model.allPlotSave([1 : 8]);
                    model.allPlotSave(9);   % fitting of basis functions
                    % testModelContinuous(model, nStim, 1, 1, 1, simulator, 0, sprintf('modelAt%d', model.trainedUntil), [1, 3 : 6]);

            end

                % if ~exist(sprintf('%s/modelAt%d/muscleActivityTrajectory.png', model.savePath, 500000), 'file')
                %     testModelContinuous(model, nStim, 1, 1, 2, simulator, 0, sprintf('modelAt%d', model.trainedUntil), [1, 3 : 5]);
                %     % store simulated time & testHist
                %     save(strcat(model.savePath, '/model'), 'model');
                % end
% %             if ~any(model.testHist(find(model.testAt == model.trainedUntil))) % test if according field in testHist is empty
% %             if isempty(model.testResult7)
% %                 sprintf('could not find test results in %s\n starting test procedure.', savePath)
%                 % testModelContinuous(model, nStim, 1, 1, 2, simulator, 0, sprintf('modelAt%d', model.trainedUntil), [1, 3 : 6]);
% %                 close all;
% %             else
% %                 sprintf('skip testing for\n%s', savePath)

                % if ~exist(sprintf('%s/binocularity.png', model.savePath, model.trainedUntil), 'file')
                %     model.allPlotSave([1, 2, 5, 8]);
                % end
            % end
            close all
        end
    end
end