view matlab/bmm/carfac/CARFAC_hacking.m @ 593:40934f897a56

Fixed certain minor documentation bugs.
Added the CAR::designFilters and CAR::stageG methods. These methods design the CAR.coeff coefficients. They have been compared to be the same as the matlab coefficients.
An Ear is now contructed with a specific FS or, it uses the default.
Added the PsychoAcoustics class to do ERB and Hz conversions.
Added the EarTest.C main which allows the construction of an Ear class for testing.

% Copyright 2012 Google Inc. All Rights Reserved.
% Author: Richard F. Lyon
%
% This Matlab file is part of an implementation of Lyon's cochlear model:
% "Cascade of Asymmetric Resonators with Fast-Acting Compression"
% to supplement Lyon's upcoming book "Human and Machine Hearing"
%
% Licensed under the Apache License, Version 2.0 (the "License");
% you may not use this file except in compliance with the License.
% You may obtain a copy of the License at
%
%     http://www.apache.org/licenses/LICENSE-2.0
%
% Unless required by applicable law or agreed to in writing, software
% distributed under the License is distributed on an "AS IS" BASIS,
% WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
% See the License for the specific language governing permissions and
% limitations under the License.

%% Test/demo hacking for CARFAC Matlab stuff:

clear variables

%%

use_plan_file = 1;
dB_list = -60:20:40

if use_plan_file
  
  file_signal = wavread('plan.wav');
  %   file_signal = file_signal(8100+(1:20000));  % trim for a faster test
  file_signal = file_signal(10000+(1:10000));  % trim for a faster test
  
else
  flist = 1400 + (1:4)*200;
  alist = [1, 1, 1, 1];
  sine_signal = 0;
  times = (0:9999)' / 22050;
  for fno = 1:length(flist)
    sine_signal = sine_signal + alist(fno)*sin(flist(fno)*2*pi*times);
  end
  growth_power = 0;  % use 0 for flat, 4 or more for near exponential
  file_signal = 1.0 * (sine_signal .* (times/max(times)).^growth_power);
end

% make a long test signal by repeating at different levels:
% dB = dB_list(1);
% test_signal =  10^(dB/20)* file_signal(1:4000) % lead-in [];
test_signal = [];
for dB =  dB_list
  test_signal = [test_signal; file_signal * 10^(dB/20)];
end


%% Run mono, then stereo test:

agc_plot_fig_num = 6;

for n_ears = 1:2
  
  CF_struct = CARFAC_Design(n_ears);  % default design
  
  if n_ears == 2
    % For the 2-channel pass, add a silent second channel:
    test_signal = [test_signal, zeros(size(test_signal))];
  end
  
  CF_struct = CARFAC_Init(CF_struct);
  
  [CF_struct, nap_decim, nap, BM, ohc, agc] = CARFAC_Run(CF_struct, test_signal, ...
    agc_plot_fig_num);
  
  %   nap = deskew(nap);  % deskew doesn't make much difference
  
  %   dB_BM = 10/log(10) * log(filter(1, [1, -0.995], BM(:, 20:50, :).^2));
  sm_BM = filter(1, [1, -0.995], BM(:, :, :).^2);
  
  % only ear 1:
  smoothed = sm_BM(100:100:end, :, 1);
  MultiScaleSmooth(10/log(10) * log(smoothed), 1);
  
 
  % Display results for 1 or 2 ears:
  for ear = 1:n_ears
    smooth_nap = nap_decim(:, :, ear);
    if n_ears == 1
      mono_max = max(smooth_nap(:));
    end
    figure(3 + ear + n_ears)  % Makes figures 5, ...
    image(63 * ((max(0, smooth_nap)/mono_max)' .^ 0.5))
    title('smooth nap from nap decim')
    colormap(1 - gray);
  end
  
  % Show resulting data, even though M-Lint complains:
  CF_struct
  CF_struct.ears(1).CAR_state
  CF_struct.ears(1).AGC_state
  min_max_decim = [min(nap_decim(:)), max(nap_decim(:))]
  
end

% Expected result:  Figure 3 looks like figure 2, a tiny bit darker.
% and figure 4 is empty (all zero)