params_virilis.m

function segParams = params_virilis(fs)
%Creates parameters data structure
%Input:
%   fs -> Data sampling frequency (default = 10000)
%
%Output:
%   segParams -> struct containing parameters used in model building and fitting
%
% (C) Gordon J. Berman, Jan Clemens, Kelly M. LaRue, and Mala Murthy, 2015
%     Princeton University


    if nargin < 1  || isempty(fs)
        fs = 10000;
    end
    
    %%%%%%%%%%%%%%ALL USER DEFINED PARAMETERS ARE SET HERE%%%%%%%%%%%%%%%%%%%%%
    
    
    %frequencies to use (don't change unless you want to re-run the likelihood
    %models)
    fc = 100:20:900;
    
    %factor for computing window around pulse peak
    %(this determines how much of the signal before and after the peak
    %is included in the pulse, and sets the parameters w0 and w1.)
    pulseWindow = round(fs/25);
    
    %factor times the mean of xempty - only pulses larger than
    %this amplitude are counted as true pulses
    noiseFactor = 1;
    
    %male pulse carrier frequency
    mpf = 350;
    
    %100Hz lowpass filter for male pulse detection
    male = 100;
    
    %40Hz lowpass filter for female pulse detection
    female = 40;
    
    %20Hz lowpass filter for male song bout detection
    bout = 20;
    
    %male bout detection based on IPI, in samples
    male_IPI = 250;
    
    %Smoothing parameter for data
    filterWindow = 5;
    
    
    %%%%%%%%%%%%%%%%%%%%%%%
    
    %Threshold for P(both singing | data)
    probThreshold = 1;
    
    %Male probability threshold
    maleThreshold = .2;
    
    %minimum size of a female pulse in the midst of a male pulse (in data
    %points)
    minFemalePulseSize = 150;
    
    %number of PCA modes to use in analysis (3 -> 41)
    probModes = 20; 
    
    %Pnoise < noiseThreshold to count as signal
    noiseThreshold = .5;
    
    %minimum percentage of time where p(male) > p(female) in order for the bout
    %to be counted as male (***)
    minMaleBoutFraction = 1/5;
    
    %Number of time points over which to test male activity (i is called male if
    %the number of initially called male frames is greater than
    %minMaleBoutFraction*maleTestDuration points over
    %(i-maleTestDuration):(i+maleTestDuration)
    maleTestDuration = 500;
    
    %minimum duration for a bout to be called a male bout (in time points) (***)
    minMaleDuration = 1000;
    
    %Smoothing parameter for male and combination song likelihoods (***)
    smoothParameter_male = 25;
    
    %Smoothing parameter for female and nosie song likelihoods (***)
    smoothParameter_female = 50;
    
    %Smoothing parameter for female and nosie song likelihoods
    smoothParameter_amplitudes = 25;
    
    %Threshold for amplitude
    amplitudeThreshold = .1;
    
    %Threshold for for noise likelihood  (***)
    %(smaller = more stringent, do not make lower than -5490, must be changed if probModes is changed)
    noiseLikelihoodThreshold = 0;
    
    %Threshold for calling the posterior value noise (between 0 and 1).
    %Closer to 1 implies a more stringent cut-off
    ampPostThreshold = .95;
    
    %Maximum noise data set from which to create noise models
    maxNumNoise = 500000;
    
    %Maximum number of peaks to create GMM noise distribution PDF
    maxNumPeaks = 4;
    
    %Maximum number of peaks to create GMM noise distribution PDF for the first
    %mode
    maxNumPeaks_firstMode = 6;
    
    %Number of PDF modes used to find female bouts within male bouts
    num_male_both_modes = 5;
    
    %Definition of closeness for female peak elimination (in ms)
    female_IPI_limit = 26;
    
    %Num of consecutive close female peaks needed for elimination (should be
    %odd)
    num_female_IPI_limit = 3;
    
    %Length of time (in seconds)
    stop_recording_time = 140;
    
    %Whether or not to refine probabilities using the PDF projection theorem
    usePDFProjections = false;
    
    %Maximum number of data to use in GMM fitting of projection distributions
    maxNumGMM = 10000;
    
    %Number of replicates to use in GMM fits
    gmm_replicates = 3;
    
    
    %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
    %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
    
    
    
    
    segParams.maxNumGMM = maxNumGMM;
    segParams.gmm_replicates = gmm_replicates;
    segParams.fc = fc;
    segParams.fs = fs;
    segParams.dt = 1/fs;
    segParams.pulsewindow = pulseWindow;
    segParams.noiseFactor = noiseFactor;
    segParams.mpf = mpf;
    segParams.male = male;
    segParams.female = female;
    segParams.bout = bout;
    segParams.male_IPI = male_IPI;
    segParams.probThreshold = probThreshold;
    segParams.minFemalePulseSize = minFemalePulseSize;
    segParams.filterWindow = filterWindow;
    segParams.probModes = probModes;
    segParams.noiseThreshold = noiseThreshold;
    segParams.minMaleBoutFraction = minMaleBoutFraction;
    segParams.minMaleDuration = minMaleDuration;
    segParams.smoothParameter_male = smoothParameter_male;
    segParams.smoothParameter_female = smoothParameter_female;
    segParams.smoothParameter_amplitudes = smoothParameter_amplitudes;
    segParams.amplitudeThreshold = amplitudeThreshold;
    segParams.noiseLikelihoodThreshold = noiseLikelihoodThreshold;
    segParams.maleThreshold = maleThreshold;
    segParams.ampPostThreshold = ampPostThreshold;
    segParams.maxNumNoise = maxNumNoise;
    segParams.maxNumPeaks = maxNumPeaks;
    segParams.maxNumPeaks_firstMode = maxNumPeaks_firstMode;
    segParams.num_male_both_modes = num_male_both_modes;
    segParams.female_IPI_limit = female_IPI_limit;
    segParams.num_female_IPI_limit = num_female_IPI_limit;
    segParams.stop_recording_time = stop_recording_time;
    segParams.usePDFProjections = usePDFProjections;
    segParams.maleTestDuration = maleTestDuration;