MAP

function UTIL_showMAP (options)

% options

% options.printModelParameters=1;

% options.showModelOutput=1;

% options.printFiringRates=1;

% options.showACF=1;

% options.showEfferent=1;

% options.surfProbability=0;

% options.fileName=[];

% options.surfProbability=0;

dbstop if warning

global dt ANdt saveAN_spikesOrProbability savedBFlist saveMAPparamsName...

    savedInputSignal TMoutput OMEoutput ARattenuation ...

    DRNLoutput IHC_cilia_output IHCrestingCiliaCond IHCrestingV...

    IHCoutput ANprobRateOutput ANoutput savePavailable tauCas  ...

    CNoutput  ICoutput ICmembraneOutput ICfiberTypeRates MOCattenuation

global OMEParams DRNLParams IHC_cilia_RPParams IHCpreSynapseParams

global AN_IHCsynapseParams MacGregorParams MacGregorMultiParams

restorePath=path;

addpath ( ['..' filesep 'utilities'], ['..' filesep 'parameterStore'])

if nargin<1

    options=[];

end

% defaults (plot staged outputs and print rates only)

if ~isfield(options,'printModelParameters'),options.printModelParameters=0;end

if ~isfield(options,'showModelOutput'),options.showModelOutput=1;end

if ~isfield(options,'printFiringRates'),options.printFiringRates=1;end

if ~isfield(options,'showACF'),options.showACF=0;end

if ~isfield(options,'showEfferent'),options.showEfferent=0;end

if ~isfield(options,'surfProbability'),options.surfProbability=0;end

if ~isfield(options,'fileName'),options.fileName=[];end

if options.printModelParameters

    % Read parameters from MAPparams<***> file in 'parameterStore' folder

    %  and print out all parameters

    cmd=['MAPparams' saveMAPparamsName ...

        '(-1, 1/dt, 1);'];

    eval(cmd);

end

if options.printFiringRates

    %% print summary firing rates

    fprintf('\n\n')

    disp('summary')

    disp(['AR: ' num2str(min(ARattenuation))])

    disp(['MOC: ' num2str(min(min(MOCattenuation)))])

    nANfiberTypes=length(tauCas);

    if strcmp(saveAN_spikesOrProbability, 'spikes')

        nANfibers=size(ANoutput,1);

        nHSRfibers=nANfibers/nANfiberTypes;

        duration=size(TMoutput,2)*dt;

        disp(['AN: ' num2str(sum(sum(ANoutput(end-nHSRfibers+1:end,:)))/...

            (nHSRfibers*duration))])

        nCNneurons=size(CNoutput,1);

        nHSRCNneuronss=nCNneurons/nANfiberTypes;

        disp(['CN: ' num2str(sum(sum(CNoutput(end-nHSRCNneuronss+1:end,:)))...

            /(nHSRCNneuronss*duration))])

        disp(['IC: ' num2str(sum(sum(ICoutput))/duration)])

        %         disp(['IC by type: ' num2str(mean(ICfiberTypeRates,2)')])

    else

        disp(['AN: ' num2str(mean(mean(ANprobRateOutput)))])

        [PSTH pointsPerBin]= UTIL_makePSTH(ANprobRateOutput, dt, 0.001);

        disp(['max max AN: ' num2str(max(max(...

            PSTH/pointsPerBin )))])

    end

end

%% figure (99) summarises main model output

if options.showModelOutput

    plotInstructions.figureNo=99;

    signalRMS=mean(savedInputSignal.^2)^0.5;

    signalRMSdb=20*log10(signalRMS/20e-6);

    % plot signal (1)

    plotInstructions.displaydt=dt;

    plotInstructions.numPlots=6;

    plotInstructions.subPlotNo=1;

    plotInstructions.title=...

        ['stimulus: ' num2str(signalRMSdb, '%4.0f') ' dB SPL'];

    r=size(savedInputSignal,1);

    if r==1, savedInputSignal=savedInputSignal'; end

    UTIL_plotMatrix(savedInputSignal', plotInstructions);

    % stapes (2)

    plotInstructions.subPlotNo=2;

    plotInstructions.title= ['stapes displacement'];

    UTIL_plotMatrix(OMEoutput, plotInstructions);

    % DRNL (3)

    plotInstructions.subPlotNo=3;

    plotInstructions.title= ['BM displacement'];

    plotInstructions.yValues= savedBFlist;

    UTIL_plotMatrix(DRNLoutput, plotInstructions);

    switch saveAN_spikesOrProbability

        case 'spikes'

            % AN (4)

            plotInstructions.displaydt=ANdt;

            plotInstructions.title='AN';

            plotInstructions.subPlotNo=4;

            plotInstructions.yLabel='BF';

            plotInstructions.yValues= savedBFlist;

            plotInstructions.rasterDotSize=1;

            if length(tauCas)==2

                plotInstructions.plotDivider=1;

            else

                plotInstructions.plotDivider=0;

            end

            if sum(sum(ANoutput))<100

                plotInstructions.rasterDotSize=3;

            end

            UTIL_plotMatrix(ANoutput, plotInstructions);

            % CN (5)

            plotInstructions.displaydt=ANdt;

            plotInstructions.subPlotNo=5;

            plotInstructions.title='CN spikes';

            if sum(sum(CNoutput))<100

                plotInstructions.rasterDotSize=3;

            end

            UTIL_plotMatrix(CNoutput, plotInstructions);

            % IC (6)

            plotInstructions.displaydt=ANdt;

            plotInstructions.subPlotNo=6;

            plotInstructions.title='IC';

            if size(ICoutput,1)>3

                if sum(sum(ICoutput))<100

                    plotInstructions.rasterDotSize=3;

                end

                UTIL_plotMatrix(ICoutput, plotInstructions);

            else

                plotInstructions.title='IC (HSR) membrane potential';

                plotInstructions.displaydt=dt;

                plotInstructions.yLabel='V';

                plotInstructions.zValuesRange= [-.1 0];

                UTIL_plotMatrix(ICmembraneOutput, plotInstructions);

            end

        otherwise % probability (4-6)

            plotInstructions.displaydt=dt;

            plotInstructions.numPlots=2;

            plotInstructions.subPlotNo=2;

            plotInstructions.yLabel='BF';

            if nANfiberTypes>1,

                plotInstructions.yLabel='LSR    HSR';

                plotInstructions.plotDivider=1;

            end

            plotInstructions.title='AN - spike probability';

            UTIL_plotMatrix(ANprobRateOutput, plotInstructions);

    end

end

if options.surfProbability

    %% surface plot of probability

    figure(97), clf

    % select only HSR fibers at the bottom of the matrix

    ANprobRateOutput= ANprobRateOutput(end-length(savedBFlist)+1:end,:);

    PSTHbinWidth=0.001;

    PSTH=UTIL_PSTHmakerb(ANprobRateOutput, ANdt, PSTHbinWidth);

    [nY nX]=size(PSTH);

    time=PSTHbinWidth*(1:nX);

    surf(time, savedBFlist, PSTH)

    shading interp

    set(gca, 'yScale','log')

    xlim([0 max(time)])

    ylim([0 max(savedBFlist)])

    zlim([0 1000])

    xlabel('time (s)')

    ylabel('best frequency (Hz)')

    zlabel('spike rate')

    view([-20 60])

    %     view([0 90])

    title ([options.fileName ':   ' num2str(signalRMSdb,'% 3.0f') ' dB'])

end

%% plot efferent control values as dB

if options.showEfferent

    plotInstructions=[];

    plotInstructions.figureNo=98;

    figure(98), clf

    plotInstructions.displaydt=dt;

    plotInstructions.numPlots=2;

    plotInstructions.subPlotNo=1;

    plotInstructions.zValuesRange=[ -25 0];

    plotInstructions.title= ['AR strength.  Signal level= ' ...

        num2str(signalRMSdb,'%4.0f') ' dB SPL'];

    UTIL_plotMatrix(20*log10(ARattenuation), plotInstructions);

    plotInstructions.subPlotNo=2;

    plotInstructions.yValues= savedBFlist;

    plotInstructions.yLabel= 'BF';

    plotInstructions.title= ['MOC strength'];

    plotInstructions.zValuesRange=[ -25 0];

    subplot(2,1,2)

    % imagesc(MOCattenuation)

    UTIL_plotMatrix(20*log10(MOCattenuation), plotInstructions);

    colorbar

end

%% ACF plot if required

if options.showACF

    tic

    method.dt=dt;

    method.segmentNo=1;

    method.nonlinCF=savedBFlist;

    minPitch=	80; maxPitch=	4000; numPitches=100;    % specify lags

    pitches=10.^ linspace(log10(minPitch), log10(maxPitch),numPitches);

    pitches=fliplr(pitches);

    filteredSACFParams.lags=1./pitches;     % autocorrelation lags vector

    filteredSACFParams.acfTau=	.003;       % time constant of running ACF

    filteredSACFParams.lambda=	0.12;       % slower filter to smooth ACF

    filteredSACFParams.lambda=	0.01;       % slower filter to smooth ACF

    filteredSACFParams.plotACFs=0;          % special plot (see code)

    filteredSACFParams.plotFilteredSACF=0;  % 0 plots unfiltered ACFs

    filteredSACFParams.plotMoviePauses=.3;          % special plot (see code)

    filteredSACFParams.usePressnitzer=0; % attenuates ACF at  long lags

    filteredSACFParams.lagsProcedure=  'useAllLags';

    % filteredSACFParams.lagsProcedure=  'useBernsteinLagWeights';

    % filteredSACFParams.lagsProcedure=  'omitShortLags';

    filteredSACFParams.criterionForOmittingLags=3;

    filteredSACFParams.plotACFsInterval=200;

    if filteredSACFParams.plotACFs

        % plot original waveform on ACF plot

        figure(13), clf

        subplot(4,1,1)

        t=dt*(1:length(savedInputSignal));

        plot(t,savedInputSignal)

        xlim([0 t(end)])

        title(['stimulus: ' num2str(signalRMSdb, '%4.0f') ' dB SPL']);

    end

    % plot original waveform on summary/smoothed ACF plot

    figure(96), clf

    subplot(2,1,1)

    t=dt*(1:length(savedInputSignal));

    plot(t,savedInputSignal)

    xlim([0 t(end)])

    title(['stimulus: ' num2str(signalRMSdb, '%4.0f') ' dB SPL']);

    % compute ACF

    switch saveAN_spikesOrProbability

        case 'probability'

            inputToACF=ANprobRateOutput.^0.5;

        otherwise

            inputToACF=ANoutput;

    end

    disp ('computing ACF...')

    [P, BFlist, sacf, boundaryValue] = ...

        filteredSACF(inputToACF, method, filteredSACFParams);

    disp(' ACF done.')

    % SACF

    subplot(2,1,2)

    imagesc(P)

    ylabel('periodicities (Hz)')

    xlabel('time (s)')

    title(['running smoothed (root) SACF. ' saveAN_spikesOrProbability ' input'])

    pt=[1 get(gca,'ytick')]; % force top xtick to show

    set(gca,'ytick',pt)

    set(gca,'ytickLabel', round(pitches(pt)))

    tt=get(gca,'xtick');

    set(gca,'xtickLabel', round(100*t(tt))/100)

end

path(restorePath)