MAP

function testBM (BMlocations, paramsName,...

    relativeFrequencies, AN_spikesOrProbability, paramChanges)

% testBM generates input output functions for DRNL model for any number

% of locations.

% Computations are bast on a single channel model (channelBFs=BF)

% peak displacement (peakAmp) is measured.

%  if DRNLParams.useMOC is chosen, the full model is run (slow)

%  otherwise only DRNL is computed.

% Tuning curves are generated based on a range of frequencies reletove to

% the BF of the location.

%

global    DRNLParams

if nargin<5

    paramChanges=[];

end

if nargin<4

    AN_spikesOrProbability='probability';

end

savePath=path;

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

levels=-10:10:90;   nLevels=length(levels);

% levels= 50;   nLevels=length(levels);

% refBMdisplacement is the displacement of the BM at threshold

% 1 nm disp at  threshold (9 kHz, Ruggero)

% ? adjust for frequency

refBMdisplacement= 1e-8; % adjusted for 10 nm at 1 kHz

toneDuration=.200;

rampDuration=0.01;

silenceDuration=0.01;

sampleRate=30000;

dbstop if error

figure(3), clf

set(gcf,'position',[280   350   327   326])

set(gcf,'name','DRNL - BM')

pause(0.1)

finalSummary=[];

nBFs=length(BMlocations);

BFno=0; plotCount=0;

for BF=BMlocations

    BFno=BFno+1;

    plotCount=plotCount+nBFs;

    stimulusFrequencies=BF* relativeFrequencies;

    nFrequencies=length(stimulusFrequencies);

    peakAmpBM=zeros(nLevels,nFrequencies);

    peakAmpBMdB=NaN(nLevels,nFrequencies);

    peakEfferent=NaN(nLevels,nFrequencies);

    peakAREfferent=NaN(nLevels,nFrequencies);

    levelNo=0;

    for leveldB=levels

        disp(['level= ' num2str(leveldB)])

        levelNo=levelNo+1;

        freqNo=0;

        for frequency=stimulusFrequencies

            freqNo=freqNo+1;

            % Generate stimuli

            globalStimParams.FS=sampleRate;

            globalStimParams.overallDuration=...

                toneDuration+silenceDuration;  % s

            stim.phases='sin';

            stim.type='tone';

            stim.toneDuration=toneDuration;

            stim.frequencies=frequency;

            stim.amplitudesdB=leveldB;

            stim.beginSilence=silenceDuration;

            stim.rampOnDur=rampDuration;

            % no offset ramp

            stim.rampOffDur=rampDuration;

            doPlot=0;

            inputSignal=stimulusCreate(globalStimParams, stim, doPlot);

            inputSignal=inputSignal(:,1)';

            %% run the model

            MAPparamsName=paramsName;

            global DRNLoutput MOCattenuation ARattenuation

            MAP1_14(inputSignal, sampleRate, BF, ...

                MAPparamsName, AN_spikesOrProbability, paramChanges);

            DRNLresponse=DRNLoutput;

            peakAmp=max(max(...

                DRNLresponse(:, end-round(length(DRNLresponse)/2):end)));

            peakAmpBM(levelNo,freqNo)=peakAmp;

            peakAmpBMdB(levelNo,freqNo)=...

                20*log10(peakAmp/refBMdisplacement);

            peakEfferent(levelNo,freqNo)=min(min(MOCattenuation));

            peakAREfferent(levelNo,freqNo)=min(min(ARattenuation));

        end  % tone frequency

    end  % level

    %% analyses results and plot

    % BM I/O plot (top panel)

    figure(3)

    subplot(3,nBFs,BFno), cla

    plot(levels,peakAmpBMdB, 'linewidth',2)

    hold on, plot(levels, repmat(refBMdisplacement,1,length(levels)))

    hold off

    title(['BF=' num2str(BF,'%5.0f') ' - ' paramsName])

    xlabel('level')

    %     set(gca,'xtick',levels),  grid on

    if length(levels)>1,xlim([min(levels) max(levels)]), end

    ylabel(['dB re:' num2str(refBMdisplacement,'%6.1e') 'm'])

    ylim([-20 50])

    set(gca,'ytick',[-10 0 10 20 40])

    grid on

    %     legend({num2str(stimulusFrequencies')}, 'location', 'EastOutside')

    UTIL_printTabTable([levels' peakAmpBMdB], ...

        num2str([0 stimulusFrequencies]','%5.0f'), '%5.0f')

    finalSummary=[finalSummary peakAmpBMdB];

    % Tuning curve

    if length(relativeFrequencies)>2

        figure(3), subplot(3,nBFs, 2*nBFs+BFno)

        %         contour(stimulusFrequencies,levels,peakAmpBM,...

        %             [refBMdisplacement refBMdisplacement],'r')

        contour(stimulusFrequencies,levels,peakAmpBM,...

            refBMdisplacement.*[1 5 10 50 100])

        title(['tuning curve at ' num2str(refBMdisplacement) 'm']);

        ylabel('level (dB) at reference')

        xlim([100 10000])

        grid on

        hold on

        set(gca,'xscale','log')

    end

    % MOC contribution

    figure(3)

    subplot(3,nBFs,nBFs+BFno), cla

    plot(levels,20*log10(peakEfferent), 'linewidth',2)

    ylabel('MOC (dB attenuation)'), xlabel('level')

    title(['peak MOC: model= ' AN_spikesOrProbability])

    grid on

    if length(levels)>1, xlim([min(levels) max(levels)]), end

    % AR contribution

    hold on

    plot(levels,20*log10(peakAREfferent), 'r')

    hold off

end % best frequency

UTIL_showStructureSummary(DRNLParams, 'DRNLParams', 10)

    UTIL_printTabTable([levels' finalSummary], ...

        num2str([0 stimulusFrequencies]','%5.0f'), '%5.0f')

path(savePath);