view matlab/bmm/carfac/CARFAC_Run_Open_Loop.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.
% 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.

function [CF, decim_naps, naps] = CARFAC_Run_Open_Loop ...
  (CF, input_waves, AGC_plot_fig_num)
% function [CF, decim_naps, naps] = CARFAC_Run_Open_Loop ...
%   (CF, input_waves, AGC_plot_fig_num)
%
% Freeze the damping by disabling AGC feedback, and run so we can
% see what the filters and AGC do in that frozen state.  And zap the
% stage gain in the AGC so we can see the state filters without combining
% them.

[n_samp, n_ears] = size(input_waves);
n_ch = CF.n_ch;

if nargin < 3
  AGC_plot_fig_num = 0;
end

if n_ears ~= CF.n_ears
  error('bad number of input_waves channels passed to CARFAC_Run')
end


naps = zeros(n_samp, n_ch, n_ears);

seglen = 16;
n_segs = ceil(n_samp / seglen);

if nargout > 1
  % make decimated detect output:
  decim_naps = zeros(n_segs, CF.n_ch, CF.n_ears);
else
  decim_naps = [];
end

if nargout > 2
  % make decimated detect output:
  naps = zeros(n_samp, CF.n_ch, CF.n_ears);
else
  naps = [];
end

% zero the deltas:
for ear = 1:CF.n_ears
  CF.CAR_state(ear).dzB_memory = 0;
  CF.CAR_state(ear).dg_memory = 0;
end
open_loop = 1;
CF.AGC_coeffs.AGC_stage_gain = 0;  % HACK to see the stages separately

smoothed_state = 0;

for seg_num = 1:n_segs
  if seg_num == n_segs
    % The last segement may be short of seglen, but do it anyway:
    k_range = (seglen*(seg_num - 1) + 1):n_samp;
  else
    k_range = seglen*(seg_num - 1) + (1:seglen);
  end
  % Process a segment to get a slice of decim_naps, and plot AGC state:
  [seg_naps, CF] = CARFAC_Run_Segment(CF, input_waves(k_range, :), ...
    open_loop);
  
  if ~isempty(naps)
    for ear = 1:n_ears
      % Accumulate segment naps to make full naps
      naps(k_range, :, ear) = seg_naps(:, :, ear);
    end
  end
  
  if ~isempty(decim_naps)
    for ear = 1:n_ears
      decim_naps(seg_num, :, ear) = CF.IHC_state(ear).ihc_accum / seglen;
      CF.IHC_state(ear).ihc_accum = zeros(n_ch,1);
    end
  end
  
  if AGC_plot_fig_num
    figure(AGC_plot_fig_num); hold off; clf
    set(gca, 'Position', [.25, .25, .5, .5])
    smoothed_state = (3*smoothed_state + CF.AGC_state(1).AGC_memory) / 4;
    for ear = 1
      total_state = 0;
      for stage = 1:4;
        weighted_state = smoothed_state(:, stage) * 2^(stage-1);
        plot(weighted_state, 'k-', 'LineWidth', 0.4);
        hold on
        total_state = total_state + weighted_state;
      end
      maxes(ear) = max(total_state);
      plot(total_state, 'k-', 'LineWidth', 1.1)
    end
    
    axis([0, CF.n_ch+1, 0.0, max(maxes) * 1.01 + 0.002]);
    drawnow
  end
  
end