# AudioMaskerExample.cc

This is an example of how to use the AudioMasker class See the example file to work out how to use these Audio masking classes

    /*
    *
    * This example shows how to use Dr M.R. Flax's (2000) hybrid
    * simultaneous audio masking class to find the masking threshold of a time domain signal.
    *
    * The compilation of this file is demonstrated in Makefile.
    * Run this file : ./AudioMaskerExample
    * View the results of this file using www.octave.org by running the script view.m
    * - simply type view once octave has started and you are in the suitable directory.
    *
    * The input audio should be stored in the file INPUTFILENAME in text format - each sample seperated by a * white space.
    *
    * ========================= HOWTO ===============================
    * \code
    *     // First find the masking threshold
    *     AudioMasker masker(sampleFreq, count); // Create the audio masker class using fs=sampleFreq and count filters
    *     masker.excite(input, sampleCount); // find the mask for the array of input data which has sampleCount time samples.
    *
    *     // Now do something with the masking threshold ...
    *
    *     // The frequency domain mask is now located here
    *     for (int j=0; j<count;j++)
    *         masker.mask[j]; // This is the mask at each of the count frequencies of interest
    *
    *     // A more sophisticated example - find the threshold for each Fourier bin
    *     double fact=(double)sampleFreq/((double)sampleCount-1.0); // convert from an index to the equivalent * Fourier bin frequency
    *     for (int j=0; j<halfSampleCount;j++){
    *         cout<<"finding for freq "<<j*fact<<'\t'; // The frequency we are inspecting
    *         double threshold=masker.findThreshold(j*fact); // The masking threshold
    *         20*log10(threshold); // The threshold in decibels (dB)
    *     }
    *
    * \endcode
    *   // The following example calculates the spectral power and the masking threshold for each Fourier bin of interest ...
    */

    #include <math.h>
    #include "AudioMasker.H"

    #define INPUTFILENAME "audio.44100.txt" // input file - text written samples seperated by white spaces
    #define POWFILENAME "fa.pow" // The power spectrum of the input signal
    #define THRESHFILENAME "thresh.dat" // The masking threshold at each frequency of the input signal
    #define TMASKFILENAME "fa.t.mask" // The masking threshold for each filter CF
    #define EXCITEFILENAME "fa.excite" // The excitation
    #include <fstream>

    int main(void){

        // Setup many variables
        // The number of time domain samples
      int sampleCount=1024, halfSampleCount=(int)rint((double)sampleCount/2.0);
      // The filter bank count and sample frequency
      int count=50, sampleFreq=44100;
      // The number of time domain samples to skip before the sample of interest.
      int skip=8192-sampleCount-1;
      // The input array to hold the input time data
      double input[sampleCount];

      // open the input file
      ifstream inputF(INPUTFILENAME);

      // Skip the first 2*'skip' samples.
      int temp;
      for (int i=0; i<skip;i++)
        inputF >> temp >> input[0];

        // load sampleCount samples as the input to the algorithm
      for (int i=0; i<sampleCount;i++)
        inputF >> input[i];
      inputF.close();

      ofstream outputCF("cf.dat"); // central freq. output file
      ofstream outputT(TMASKFILENAME);
      ofstream outputP(POWFILENAME); // Input data Fourier power file

      // Get our masking function (class) ...
      AudioMasker masker(sampleFreq, count);
      //AudioMasker masker; // Can also be called like so with default filter banks and sampleFrequency

      masker.excite(input, sampleCount); // find the mask

      for (int j=0; j<count;j++){ // Output the central freq to file
        outputCF <<masker.pfb->cf[j]*((double)sampleCount/(double)sampleFreq)<<'\t';
        outputT  << 20*log10(masker.mask[j])<<'\t'; // output the mask for each filter CF to file
      }
      outputCF<<endl;
      outputT<<endl;

      realFFTData fftData(sampleCount); // Find the fourier transform for the output of the power to file
      realFFT fft(&fftData); // init the Fourier transform
      for (int j=0; j<sampleCount;j++) // load the time domain input to the Fourier transform
        fftData.in[j]=input[j];
      fft.fwdTransform(); // Perform the transformation of the time domain to the frequency domain.
      fftData.compPowerSpec(); // Find the power spectrum
      for (int j=0; j<sampleCount/2;j++) // Output the power spectrum to file
        outputP<<20*log10(sqrt(fftData.power_spectrum[j]))<<'\t';
      outputP<<endl;

      outputCF.close();
      outputT.close();
      outputP.close();

      ofstream outputF(THRESHFILENAME); // Find and output the masking threshold for each Fourier bin in the power spectrum
      double fact=(double)sampleFreq/((double)sampleCount-1.0); // convert from an index to the equivalent Fourier bin frequency
      for (int j=0; j<halfSampleCount;j++){
        //    cout<<"finding for freq "<<j*fact<<'\t';
        outputF<<20*log10(masker.findThreshold(j*fact))<<'\t';
      }
      outputF<<endl;
      outputF.close();
    }

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