MAP

function printReport(fileName, printTracks)

% End of run report (no args)

% *or*

% reprint previous report from file

global experiment stimulusParameters betweenRuns withinRuns statsModel   audio

global LevittControl expGUIhandles

global paramChanges

global inputStimulusParams OMEParams DRNLParams

global IHC_VResp_VivoParams IHCpreSynapseParams  AN_IHCsynapseParams

global MacGregorParams MacGregorMultiParams  filteredSACFParams

global experiment % used by calls from multiThreshold only

global IHC_cilia_RPParams

printReportGuide.structures=1;

printReportGuide.showPsychometric=0;

printReportGuide.HorizontalTracks=1;

if nargin==0

    % print new report

    printReportGuide.showTracks=experiment.printTracks;

    printReportGuide.fileName=[];

    if experiment.saveData

        saveFileName=...

            ['savedData/' experiment.name '_' ...

            experiment.date '_' experiment.paradigm];

    else

        % save this data (just in case)

        saveFileName=['savedData/mostRecentResults'];

    end

    experiment.minElapsed=etime(clock, betweenRuns.timeNow)/60;

    save(saveFileName, 'experiment', 'stimulusParameters',...

        'betweenRuns', 'withinRuns', 'statsModel', 'expGUIhandles')

    disp(['data saved as: ' saveFileName]);

else

    % reprint request (i.e print out old data)

    printReportGuide.fileName=fileName;

    load(printReportGuide.fileName)

    saveFileName=printReportGuide.fileName;

    if nargin>1

        printReportGuide.showTracks=printTracks;

    else

        printReportGuide.showTracks=experiment.printTracks;

    end

end

fprintf('******** multithreshold ')

x=pwd; disp(['version ' x(end-3:end)])

fprintf('\nName:\t%s ', experiment.name)

fprintf('\nparadigm:\t%s ', experiment.paradigm)

fprintf('\nEar:\t%s ', experiment.ear)

method=experiment.threshEstMethod;

if stimulusParameters.includeCue && ~strcmp(method(1:6),'2I2AFC')

    method=[method '/ withCue'];

end

fprintf('\nmethod:\t%s ', method)

fprintf('\ndate:\t%s ', experiment.date)

fprintf('\n\n')

if isempty(betweenRuns.thresholds)

    disp('no thresholds found')

end

% prepare results as matrices ready to print

%  first sort the actual sequence into a more readable sequence

[idx1, idx2, var1values, var2values]=...

    sortVariables(betweenRuns.variableList1, betweenRuns.variableList2,...

    betweenRuns.var1Sequence, betweenRuns.var2Sequence);

header1=betweenRuns.variableName1;

header2=betweenRuns.variableName2;

header1 = strrep(header1, 'none', ' '); % none is not a useful header

header2 = strrep(header2, 'none', ' '); % none is not a useful header

headers=strvcat([header1 '/'], header2);

disp('thresholds')

global resultsTable

resultsTable= sortTablesForPrinting(idx1,idx2,...

    var1values,var2values, betweenRuns.thresholds);

msg=printTabTable(resultsTable,  headers);

addToMsg(msg,0)

fprintf('\n')

disp(paramChanges)

% sort tracks into the same order

betweenRuns.levelTracks=betweenRuns.levelTracks(idx1);

betweenRuns.responseTracks=betweenRuns.responseTracks(idx1);

betweenRuns.bestThresholdTracks=betweenRuns.bestThresholdTracks(idx1);

betweenRuns.levelTracks=betweenRuns.levelTracks(idx2);

betweenRuns.responseTracks=betweenRuns.responseTracks(idx2);

betweenRuns.bestThresholdTracks=betweenRuns.bestThresholdTracks(idx2);

if printReportGuide.structures

    maxNoArrayValues=30;

    showStructureSummary(stimulusParameters, 'stimulusParameters', maxNoArrayValues)

    showStructureSummary(experiment, 'experiment',maxNoArrayValues)

    showStructureSummary(betweenRuns, 'betweenRuns',maxNoArrayValues)

    showStructureSummary(withinRuns, 'withinRuns')

    switch experiment.threshEstMethod

        case {'2I2AFC++', '2I2AFC+++'}

            showStructureSummary(LevittControl, 'LevittControl', maxNoArrayValues)

    end

    switch experiment.ear

        case {'statsModelLogistic','statsModelRareEvent'}

            showStructureSummary(statsModel, 'statsModel', maxNoArrayValues)

    end

end

if printReportGuide.showTracks

    % NB this procedure can only be used if all the tracks are present and

    % of equal length

    bigTable=[]; header=[];

    disp(' '); disp('Leveltracks starting from 1 response before the first reversal')

    for i=1:length(betweenRuns.levelTracks)

        if printReportGuide.HorizontalTracks

            printTabTable(betweenRuns.levelTracks{i});

        end

        header=strvcat(header, 'level');

    end

    disp(' '); disp('Response tracks starting from 1 response before the first reversal')

    for i=1:length(betweenRuns.responseTracks)

        if printReportGuide.HorizontalTracks

            printTabTable(betweenRuns.responseTracks{i});

        end

        header=strvcat(header, 'resp');

    end

    disp(' '); disp('threshold tracks starting from the first reversal')

    for i=1:length(betweenRuns.bestThresholdTracks)

        if printReportGuide.HorizontalTracks

        end

        printTabTable(betweenRuns.bestThresholdTracks{i});

        header=strvcat(header, 'mean');

    end

end

switch experiment.ear

    case  {'MAPmodelMultiCh', 'MAPmodelSingleCh'}

        % show all parameters but do not compute the model

        nm=UTIL_paramsList(whos);

        for i=1:length(nm)

            try

                eval(['UTIL_showStruct(' nm{i} ', ''' nm{i} ''')'])

            catch

            end

        end

end

if experiment.saveData

    fprintf('\n')

    disp('To reprint this report with tracks use:')

    disp([ 'printReport(''' saveFileName ''',1)'])

end

% print final summary (repeat of above)

fprintf('\n')

fprintf('\n')

disp('thresholds')

msg=printTabTable(sortTablesForPrinting(idx1,idx2,var1values,var2values, betweenRuns.thresholds),  headers);

addToMsg(msg,0)

fprintf('\n')

if length(var1values)==1 && length(var2values)==1 && experiment.maxTrials>49

    [psy, levelsBinVector, binFrequencies, nNo, nYes]= ...

        psychometricFunction(withinRuns.levelsPhaseTwo,withinRuns.responsesPhaseTwo, experiment.psyBinWidth);

    disp('Psychometric function')

    fprintf(' level  \tfreq\tprob\n')

    fprintf('%6.0f\t%6.2f\t%6.0f\n', [levelsBinVector; binFrequencies; psy])

    fprintf('\n')

    fprintf('k \t %6.2f\n',logistic.bestK)

    fprintf('g  \t%7.5f\n',rareEvent.bestGain)

    fprintf('\n')

end

fprintf('\nparadigm:\t%s\n ', experiment.paradigm)

disp(paramChanges)

% ------------------------------------------------------- sortTablesForPrinting

function table= sortTablesForPrinting(idx1,idx2, var1values,var2values, x)

% table converts a vector to a table

% after sorting according to idx1 and idx2

% the table is completed by adding row and column values

x=x(idx1);

x=x(idx2);

xMatrix=reshape(x,length(var1values),length(var2values));

table=[[-1000 var2values]; [var1values' xMatrix]];

% ------------------------------------------------------- showStructureSummary

function showStructureSummary(structure, name, maxNoArrayValues)

% showStructureSummary prints out the values of a single structure

% The header is the structure name and each row is a field

% e.g. showStructureSummary(params,'params')

% This not the same as 'UTIL_showstruct'

if nargin<3

    maxNoArrayValues=20;

end

fprintf('\n%s:', name)

fields=fieldnames(eval('structure'));

% for each field in the structure

for i=1:length(fields)

    y=eval([ 'structure.' fields{i}]);

    if isstr(y),

        % strings

        fprintf('\n%s=\t''%s''',  fields{i},y)

    elseif isnumeric(y)

        % arrays

        if length(y)>1

            % vectors

            [r c]=size(y);

            if r>c, y=y'; end

            [r c]=size(y);

            if r>1

                %                 fprintf('\n%s.%s=\t%g x %g matrix',name, fields{i}, r, c)

                fprintf('\n%s=\t%g x %g matrix',fields{i}, r, c)

            elseif c<maxNoArrayValues

                %                     fprintf('\n%s=\t[%s]',  fields{i},num2str(y))

                fprintf('\n%s=',  fields{i})

                fprintf('\t%g',y)

            else

                fprintf('\n%s=\t %g...   [%g element array]', fields{i}, y(1),c)

            end

        else

            % single valued arrays

            %             fprintf('\n%s.%s=\t%s;', name, fields{i},num2str(y))

            fprintf('\n%s=\t%s', fields{i},num2str(y))

        end

    elseif iscell(y)

        fprintf('\n%s=\t cell array', fields{i})

    elseif isstruct(y)

        fprintf('\n%s=\t structure', fields{i})

    end,

end,

fprintf('\n')

% ------------------------------------------------------- printTabTable

function strings= printTabTable(M, headers)

% printTabTable prints a matrix as a table with tabs

%headers are optional

%headers=strvcat('firstname', 'secondname')

%  printTabTable([1 2; 3 4],strvcat('a1','a2'));

stringCount=1; strings{stringCount}=[];

if nargin>1

    [r c]=size(headers);

    for no=1:r

        % print all headers in a row

        fprintf('%s\t',headers(no,:))

        strings{stringCount}=sprintf('%s\t',headers(no,:)); stringCount=stringCount+1;

    end

    fprintf('\n')

end

[r c]=size(M);

for row=1:r

    string=[];

    for col=1:c

        if row==1 & col==1 & M(1,1)==-1000

            %   Print nothing (tab follows below)

        else

            fprintf('%s',num2str(M(row,col)))

            string=[string ' ' sprintf('%s',num2str(M(row,col)))];

        end

        if col<c

            fprintf('\t')

            % 			strings{stringCount}=sprintf('\t'); stringCount=stringCount+1;

        end

    end % col

    strings{stringCount}=string; stringCount=stringCount+1;

    fprintf('\n')

end % row

% ------------------------------------------------------- sortVariables

function [idx1, idx2, var1values, var2values]= ...

    sortVariables(var1values, var2values, var1Sequence, var2Sequence)

[x idx1]= sort(var1Sequence);

var1Sequence= x;

var2Sequence= var2Sequence(idx1);

depVarName= 'th';

[x idx2]=sort(var2Sequence);

var2Sequence=x;

var1Sequence=var1Sequence(idx2);

var1values=sort(var1values);

var2values=sort(var2values);