MAP

function test_toneInNoise

% test_MAP1_14 is a general purpose test routine that can be adjusted to

% test a number of different applications of MAP1_14

%

% A range of options are supplied in the early part of the program

%

% One use of the function is to create demonstrations; filenames <demoxx>

%  to illustrate particular features

%

% #1

% Identify the file (in 'MAPparamsName') containing the model parameters

%

% #2

% Identify the kind of model required (in 'AN_spikesOrProbability').

%  A full brainstem model (spikes) can be computed or a shorter model

%  (probability) that computes only so far as the auditory nerve

%

% #3

% Choose between a tone signal or file input (in 'signalType')

%

% #4

% Set the signal rms level (in leveldBSPL)

%

% #5

% Identify the channels in terms of their best frequencies in the vector

%  BFlist.

%

% Last minute changes to the parameters fetched earlier can be made using

%  the cell array of strings 'paramChanges'.

%  Each string must have the same format as the corresponding line in the

%  file identified in 'MAPparamsName'

%

% When the demonstration is satisfactory, freeze it by renaming it <demoxx>

global dt dtSpikes  savedBFlist saveAN_spikesOrProbability saveMAPparamsName...

    savedInputSignal OMEextEarPressure TMoutput OMEoutput ARattenuation ...

    DRNLoutput IHC_cilia_output IHCrestingCiliaCond IHCrestingV...

    IHCoutput ANprobRateOutput ANoutput savePavailable ANtauCas  ...

    CNtauGk CNoutput  ICoutput ICmembraneOutput ICfiberTypeRates ...

    MOCattenuation

global OMEParams DRNLParams IHC_cilia_RPParams IHCpreSynapseParams

global AN_IHCsynapseParams MacGregorParams MacGregorMultiParams

global ICrate

dbstop if error

restorePath=path;

addpath (['..' filesep 'MAP'],    ['..' filesep 'wavFileStore'], ...

    ['..' filesep 'utilities'])

%%  #1 parameter file name

MAPparamsName='Normal';

%% #2 probability (fast) or spikes (slow) representation

AN_spikesOrProbability='spikes';

%   or

AN_spikesOrProbability='probability';

%% #3 pure tone, harmonic sequence or speech file input

signalType= 'tones';

sampleRate= 44100;          % must agree with noise

duration=0.010;                 % seconds

rampDuration=.001;              % raised cosine ramp (seconds)

beginSilence=0.010;

endSilence=0.010;

toneFrequency= 2000;            % or a pure tone (Hz)

%   or

% harmonic sequence (Hz)

% F0=210;

% toneFrequency= F0:F0:8000;

%   or

% signalType= 'file';

% fileName='twister_44kHz';

%% #4 rms level

% signal details

leveldBSPL= 70;                  % dB SPL (80 for Lieberman)

leveldBSPLNoise=30;

%% #5 number of channels in the model

%   21-channel model (log spacing)

numChannels=21;

lowestBF=250; 	highestBF= 8000;

BFlist=round(logspace(log10(lowestBF), log10(highestBF), numChannels));

% %   or specify your own channel BFs

% numChannels=1;

% BFlist=toneFrequency;

%% #6 change model parameters

paramChanges={};

% Parameter changes can be used to change one or more model parameters

%  *after* the MAPparams file has been read

% This example declares only one fiber type with a calcium clearance time

% constant of 80e-6 s (HSR fiber) when the probability option is selected.

% paramChanges={'AN_IHCsynapseParams.ANspeedUpFactor=5;', ...

%     'IHCpreSynapseParams.tauCa=86e-6; '};

paramChanges={'DRNLParams.MOCtauProb =.25;', ...

    'DRNLParams.rateToAttenuationFactorProb = 0.02; '};

% paramChanges={'DRNLParams.MOCtauProb =.15;', ...

%     'DRNLParams.rateToAttenuationFactorProb = 0.00; '};

%% delare 'showMap' options to control graphical output

showMapOptions.printModelParameters=1;   % prints all parameters

showMapOptions.showModelOutput=1;       % plot of all stages

showMapOptions.printFiringRates=1;      % prints stage activity levels

showMapOptions.showACF=0;               % shows SACF (probability only)

showMapOptions.showEfferent=1;          % tracks of AR and MOC

showMapOptions.surfProbability=1;       % 2D plot of HSR response

showMapOptions.surfSpikes=1;            % 2D plot of spikes histogram

showMapOptions.ICrates=0;               % IC rates by CNtauGk

% disable certain silly options

if strcmp(AN_spikesOrProbability, 'spikes')

    % avoid nonsensical options

    showMapOptions.surfProbability=0;

    showMapOptions.showACF=0;

end

if strcmp(signalType, 'file')

    % needed for labeling plot

    showMapOptions.fileName=fileName;

else

    showMapOptions.fileName=[];

end

%% Generate stimuli

switch signalType

    case 'tones'

        % Create pure tone stimulus

        dt=1/sampleRate; % seconds

        time=dt: dt: duration;

        inputSignal=sum(sin(2*pi*toneFrequency'*time), 1);

        amp=10^(leveldBSPL/20)*28e-6;   % converts to Pascals (peak)

        inputSignal=amp*inputSignal;

        % apply ramps

        % catch rampTime error

        if rampDuration>0.5*duration, rampDuration=duration/2; end

        rampTime=dt:dt:rampDuration;

        ramp=[0.5*(1+cos(2*pi*rampTime/(2*rampDuration)+pi)) ...

            ones(1,length(time)-length(rampTime))];

        inputSignal=inputSignal.*ramp;

        ramp=fliplr(ramp);

        inputSignal=inputSignal.*ramp;

        % add silence

        intialSilence= zeros(1,round(beginSilence/dt));

        finalSilence= zeros(1,round(endSilence/dt));

        inputSignal= [intialSilence inputSignal finalSilence];

%         [inputNoise sampleRateN]=wavread('babble');

        [inputNoise sampleRateN]=wavread('white noise');

        inputNoise=inputNoise(1:length(inputSignal));

        inputNoise=inputNoise(:,1);

        targetRMS=20e-6*10^(leveldBSPLNoise/20);

        rms=(mean(inputNoise.^2))^0.5;

        amp=targetRMS/rms;

        inputNoise=inputNoise*amp;

        inputSignal=inputSignal+inputNoise';

        figure(2), subplot(2,1,1)

        time=dt:dt:dt*length(inputSignal);

        plot(time,inputSignal,'k')

    case 'file'

        %% file input simple or mixed

        [inputSignal sampleRate]=wavread(fileName);

        dt=1/sampleRate;

        inputSignal=inputSignal(:,1);

        targetRMS=20e-6*10^(leveldBSPL/20);

        rms=(mean(inputSignal.^2))^0.5;

        amp=targetRMS/rms;

        inputSignal=inputSignal*amp;

        intialSilence= zeros(1,round(0.1/dt));

        finalSilence= zeros(1,round(0.2/dt));

        inputSignal= [intialSilence inputSignal' finalSilence];

end

%% run the model

tic

fprintf('\n')

disp(['Signal duration= ' num2str(length(inputSignal)/sampleRate)])

disp([num2str(numChannels) ' channel model: ' AN_spikesOrProbability])

disp('Computing ...')

MAP1_14(inputSignal, sampleRate, BFlist, ...

    MAPparamsName, AN_spikesOrProbability, paramChanges);

%% the model run is now complete. Now display the results

UTIL_showMAP(showMapOptions, paramChanges)

if strcmp(signalType,'tones')

    disp(['duration=' num2str(duration)])

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

    disp(['toneFrequency=' num2str(toneFrequency)])

    global DRNLParams

    disp(['attenuation factor =' ...

        num2str(DRNLParams.rateToAttenuationFactor, '%5.3f') ])

    disp(['attenuation factor (probability)=' ...

        num2str(DRNLParams.rateToAttenuationFactorProb, '%5.3f') ])

    disp(AN_spikesOrProbability)

end

figure(2), subplot(2,1,2), plot(ANprobRateOutput(13+21,:))

disp([ 'peak channel 13: ' num2str(max(ANprobRateOutput(13+21,:)))])

for i=1:length(paramChanges)

    disp(paramChanges{i})

end

path(restorePath)