function scalib = baumgartner2016_calibration(s,varargin)
%baumgartner2016_calibration Calibration of listener-specific sensitivity thresholds to experimental performance
% Usage: scalib = baumgartner2016_calibration(s)
%
% Input parameter:
% s : strucure containing subject's data. It must include the
% fields Obj, baseline.pe_exp, and baseline.qe_exp, representing
% the listener's HRTF as SOFA object, the baseline local
% polar RMS error, and the baseline quadrant error rate,
% respectively.
%
% Output parameter:
% scalib : strucure containing subject's data with calibrated u
%
% BAUMGARTNER2016_CALIBRATION returns listener data with
% listener-specific sensitivity thresholds calibrated by joint
% optimization of PE and QE to minimize mismatch between experimental
% and predicted results.
%
% BAUMGARTNER2016_CALIBRATION accepts the following optional parameters:
%
% 'Srange',Sr Define the sensitivity range. Default is [eps,10].
%
% 'prange',pr Define the prior range. Default is [0,1].
%
% 'latseg',ls Define lateral segment(s) of data used for
% calibration. Default value is 0 deg.
%
% 'c',c Structure for optional definition of listener-specific
% settings like playback level or stimulus.
%
% 'TolX',tx Minimum tolerance of optimization argument (see help
% optimset for details).
%
% 'MaxIter',mi Maximum number of optimization iterations (see help
% optimset for details).
%
% BAUMGARTNER2016_CALIBRATION accepts the following flags:
%
% 'calibprior' Calibrate also expectation prior.
%
% 'fminbnd' Use fminbnd routine for calibration. This is the
% default.
%
% 'fminsearch' Use fminsearch routine for calibration.
%
% 'search' Try all possibilities.
%
% Url: http://amtoolbox.org/amt-1.1.0/doc/modelstages/baumgartner2016_calibration.php
% Copyright (C) 2009-2021 Piotr Majdak, Clara Hollomey, and the AMT team.
% This file is part of Auditory Modeling Toolbox (AMT) version 1.1.0
%
% 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/>.
% AUTHOR : Robert Baumgartner
definput.import={'baumgartner2016'};
definput.keyvals.c = {};
% Parse input options
[flags,kv] = ltfatarghelper({},definput,varargin);
c = kv.c;
if isempty(c)
c.SPL = kv.SPL*ones(length(s),1);
c.stim = cell(length(s),1);
end
if flags.do_gammatone && kv.tiwin > .5
kv.Srange = [-1,5];
elseif flags.do_gammatone && kv.tiwin < .5
kv.Srange = [-5,10];
end
scalib = s;
for ss = 1:length(s)
if flags.do_calibprior
xopt = fminsearch(@(x) local_evaldist(s(ss),x,kv,flags,c.SPL(ss),c.stim{ss}),...
[mean(kv.Srange) mean(kv.prange)],...
optimset('MaxIter',kv.MaxIter,'TolX',kv.TolX,'Display','iter','TolFun',1e-10)...
);
scalib(ss).S = real(xopt(1));
scalib(ss).prior = real(xopt(2))*100; % to equalize sensitivity between S and prior
else
switch flags.optimization
case 'fminsearch'
xopt = fminsearch(@(x) local_evaldist(s(ss),x,kv,flags,c.SPL(ss),c.stim{ss}),mean(kv.Srange),...
optimset('MaxIter',kv.MaxIter,'TolX',kv.TolX,'Display','iter','TolFun',1e-10)...
);
scalib(ss).S = real(xopt);
case 'fminbnd'
xopt = fminbnd(@(x) local_evaldist(s(ss),x,kv,flags,c.SPL(ss),c.stim{ss}),kv.Srange(1),kv.Srange(2),...
optimset('MaxIter',kv.MaxIter,'TolX',kv.TolX,'Display','iter','TolFun',1e-10)...
);
scalib(ss).S = real(xopt);
case 'search'
iS = kv.Srange(1):(kv.Srange(2)-kv.Srange(1))/100:kv.Srange(2);
distmetric = zeros(length(iS),1);
for ii = 1:length(iS)
distmetric(ii) = local_evaldist(s(ss),iS(ii),kv,flags,c.SPL(ss),c.stim{ss});
end
[~,Imin] = min(distmetric);
scalib(ss).S = iS(Imin);
figure; plot(iS,distmetric); title(s(ss).id)
pause(0.5)
end
end
disp([num2str(ss,'%2.0u') ' of ' num2str(length(s),'%2.0u') ' calibrated.'])
end
end
function [distmetric,qeM,peM] = local_evaldist(s,x,kv,flags,SPL,stim)
% if x(1) < 0 || x(2) <= 0
% distmetric = Inf;
% return
% end
% if x < 0
% distmetric = Inf;
% return
% end
% SimDL = x(1);
S = real(x(1));
if length(x) == 2
prior = x(2);
else
prior = 0;
end
if prior < 0
distmetric = Inf;
return
end
%% LocaMo
qeM = zeros(length(s),1);
peM = zeros(length(s),1);
for ll = 1:length(s)
if not(isfield(s,'fsstim'))
s(ll).fsstim = s(ll).fs;
end
for ii = 1:length(kv.latseg)
s(ll).p{ii} = 0; % init
[s(ll).p{ii},respangs,polang] = baumgartner2016(...
s(ll).Obj,s(ll).Obj,'argimport',flags,kv,...
'ID',s(ll).id,'fs',s(ll).fs,'mrsmsp',s(ll).mrs,'S',S,'SPL',SPL,...
'stim',stim,'fsstim',s(ll).fsstim,'priordist',s(ll).priordist);
[ qe(ii),pe(ii) ] = baumgartner2014_pmv2ppp( ...
s(ll).p{ii} , polang , respangs , s(ll).target{ii});
latweight = length(s(ll).target{ii})/length(cat(1,s(ll).target{:}));
qeM(ll) = qeM(ll) + qe(ii)*latweight;
peM(ll) = peM(ll) + pe(ii)*latweight;
end
dQE(ll) = s(ll).qe_exp - qeM(ll); % s(ll).baseline.qe_exp
dPE(ll) = s(ll).pe_exp - peM(ll); % s(ll).baseline.pe_exp
end
% [qe_chance,pe_chance] = baumgartner2014_pmv2ppp('chance');
% distmetric = (dQE/qe_chance).^2 + (dPE/pe_chance).^2; % Joint distance metric of QE and PE (standardized scatter)
QEmax = 100;
PEmax = 90;
distmetric = sqrt((dQE/QEmax).^2 + (dPE/PEmax).^2);
end