function [V,Y,E,CF]=verhulst2012(sign,fs,fc,spl,normalizeRMS,subject,irregularities)
%VERHULST2012 Process a signal with the cochlear model by Verhulst et. al. 2012
% Usage: output = verhulst2012(insig,fs,fc,spl,normalizeRMS,subject,irregularities,sheraPo)
%
% Input parameters:
% sign : the input signal to be processed. Each column is processed
% in parallel, so it is possible to run several
% simulation in parallel
% fs : sampling rate
% fc : list of frequencies specifying the probe positions on
% the basilar membrane, or 'all' to probe all 1000
% cochlear sections
% spl : array of the sound pressure levels that correspond to
% value 1 of the correspondent input signal
% normalizeRms : arry to control the normalization of each
% signal. With value 1 normalize the energy of the signal, so the
% relative spl value correspond to the rms of the signal (default 0)
% subject : the subject number controls the cochlear irregulatiries (default 1)
% irregularities : array that enable (1) or disable (0)
% irregularities and nonlinearities for each simulation (default 1)
%
% Output parameters:
% V : velocity of the basilar membrane sections V(time,section,channel)
% Y : displacement of the basilar membrane sections Y(time,section,channel)
% E : sound pressure at the middle ear
% CF : center frequencies of the probed basiliar membrane sections
%
% This function computes the basilar membrane displacement and the
% velocity of the movement at different positions employing a faster
% implementation of the nonlinear time-domain model of cochlea by
% Verhulsts, Dau, Shera 2012, through the method described in Alto? et
% al. 2014
%
% The processing is implemented as follows:
%
% 1) the input signal is resampled to the 96 kHz sampling rate
% employed in the cochlea model
%
% 2) the list of frequencies in fc are converted in to probe
% positions in a manner that the frequencies are divided evenly into
% low and high frequency categories.
%
% 3) the signals are processed in parallel
%
% 4) the values obtained are resampled back to the original sampling
% rate
%
% Requirements and installation:
% ------------------------------
%
% 1) Python >2.6 is required with numpy and scipi packages. On Linux, use sudo apt-get install python-scipy python-numpy
%
% 2) Compiled files with a C-compiler, e.g. gcc. In amtbase/src/verhulst start make (Linux) or make.bat (Windows)
%
% 3) On linux, when problems with GFORTRAN lib appear, try sudo ln -sf /usr/lib64/libgfortran.so.3.0.0 /mymatlabroot/sys/os/glnxa64/libgfortran.so.3 (mymatlabroot is usually /usr/local/MATLAB/version
%
% See also: verhulst2012,
%
% References:
% S. Verhulst, T. Dau, and C. A. Shera. Nonlinear time-domain cochlear
% model for transient stimulation and human otoacoustic emission. J.
% Acoust. Soc. Am., 132(6):3842 - 3848, 2012.
%
% A. Altoè, S. Verhulst, and V. Pulkki. Transmission line cochlear
% models: improved accuracy and efficiency. J. Acoust. Soc. Am.,
% 136(EL302), 2014.
%
%
% AUTHOR: Alessandro Altoe'
%
% Url: http://amtoolbox.sourceforge.net/amt-0.9.9/doc/models/verhulst2012.php
% Copyright (C) 2009-2015 Piotr Majdak and the AMT team.
% This file is part of Auditory Modeling Toolbox (AMT) version 0.9.9
%
% This program is free software: you can redistribute it and/or modify
% it under the terms of the GNU General Public License as published by
% the Free Software Foundation, either version 3 of the License, or
% (at your option) any later version.
%
% This program is distributed in the hope that it will be useful,
% but WITHOUT ANY WARRANTY; without even the implied warranty of
% MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
% GNU General Public License for more details.
%
% You should have received a copy of the GNU General Public License
% along with this program. If not, see <http://www.gnu.org/licenses/>.
if nargin<5
[channels,idx]=min(size(sign));
normalizeRMS=zeros(channels,1);
end
if nargin < 6
subject = 1;
end
if nargin<7
[channels,idx]=min(size(sign));
irregularities=ones(1,channels);
end
% sign=double(sign); %force to write signal as double array
Fs=96000;
sectionsNo=1000;
[channels,idx]=min(size(sign));
if(idx==2) %transpose it (python C-style row major order)
sign=sign';
end
stim=zeros(channels,length(resample(sign(1,:),Fs,fs)));
for i=1:channels
stim(i,:)=resample(sign(i,:),Fs,fs);
% figure; plot(stim(i,:));
if normalizeRMS(i)
s_rms=rms(stim(i,:));
stim(i,:)=stim(i,:)./s_rms;
end
end
sheraPo=0.061;
if(isstr(fc) && strcmp(fc,'all')) %if probing all sections 1001 output (1000 sections plus the middle ear)
p=sectionsNo;
else %else pass it as a column vector
[p,idx]=max(size(fc));
if(idx==2)
fc=fc';
end
fc=round(fc);
end
probes=fc;
[path,name,ext]=fileparts(which('verhulst2012'));
[path,name,ext]=fileparts(path);
act_path=pwd;
cd(strcat(path,'/bin/verhulst2012/'));
if ~exist('tridiag.so','file')
error('tridiag.so library is missing. Goto to AMT/bin/verhulst2012 and compile by executing the makefile');
end
save('input.mat','stim','Fs','channels','spl','subject','sheraPo','irregularities','probes','-v7');
system('python run_cochlear_model.py');
l=length(stim(1,:));
rl=length(resample(stim(1,:),fs,Fs));
V=zeros(rl,p,channels);
Y=zeros(rl,p,channels);
E=zeros(rl,channels);
CF=zeros(p,1);
for i=1:channels
fname=strcat('out/v',int2str(i),'.np');
f=fopen(fname,'r');
V(:,:,i)=resample(fread(f,[p,l],'double','n')',fs,Fs);
fclose(f);
fname=strcat('out/y',int2str(i),'.np');
f=fopen(fname,'r');
Y(:,:,i)=resample(fread(f,[p,l],'double','n')',fs,Fs);
fclose(f);
fname=strcat('out/E',int2str(i),'.np');
f=fopen(fname,'r');
E(:,i)=resample(fread(f,[l,1],'double','n'),fs,Fs);
fclose(f);
if(i==1)
fname=strcat('out/F',int2str(i),'.np');
f=fopen(fname,'r');
CF=fread(f,[p,1],'double','n');
fclose(f);
end
end
cd(act_path);