function si = baumgartner2014_similarityestimation(sigma,varargin)
%BAUMGARTNER2014_SIMILARITYESTIMATION Similarity estimation with listener-specific sensitivity
% Usage: si = baumgartner2014_similarityestimation(sigma)
%
% Input parameters:
% sigma : internal distance metrics
%
% Output parameters:
% si : similarity indices
%
% BAUMGARTNER2014_SIMILARITYESTIMATION(...) maps internal distance
% metrics to similarity indices according to listener-specific
% sensitivity
%
% BAUMGARTNER2014_SIMILARITYESTIMATION accepts the following optional parameters:
%
% 'S',S Set the listener-specific sensitivity threshold
% (threshold of the sigmoid link function representing
% the psychometric link between transformation from the
% distance metric and similarity index) to S.
% Default value is 1.
%
% 'gamma',G Set the degree of selectivity
% (slope of the sigmoid link function representing
% the psychometric link between transformation from the
% distance metric and similarity index) to G.
% Default value is 6.
%
% References:
% R. Baumgartner, P. Majdak, and B. Laback. Modeling sound-source
% localization in sagittal planes for human listeners. The Journal of the
% Acoustical Society of America, 136(2):791--802, 2014.
%
%
% Url: http://amtoolbox.org/amt-1.4.0/doc/modelstages/baumgartner2014_similarityestimation.php
% #StatusDoc: Perfect
% #StatusCode: Perfect
% #Verification: Verified
% #Requirements: SOFA CircStat M-SIGNAL M-Stats O-Statistics
% #Author: Robert Baumgartner (2014), Acoustics Research Institute, Vienna, Austria
% This file is licensed unter the GNU General Public License (GPL) either
% version 3 of the license, or any later version as published by the Free Software
% Foundation. Details of the GPLv3 can be found in the AMT directory "licences" and
% at <https://www.gnu.org/licenses/gpl-3.0.html>.
% You can redistribute this file and/or modify it under the terms of the GPLv3.
% This file is distributed without any warranty; without even the implied warranty
% of merchantability or fitness for a particular purpose.
definput.import={'baumgartner2014'};
[flags,kv]=ltfatarghelper({},definput,varargin);
%% Similarity estimation, Eq.(5)
si=zeros(size(sigma)); % init
for ch = 1:size(sigma,3)
for it = 1:size(sigma,2)
si(:,it,ch) = 1+eps - (1+exp(-kv.gamma*(sigma(:,it,ch)-kv.S))).^-1;
end
end
end