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EXP_BAUMGARTNER2015BINWEIGHT - Results from various publications of Baumgartner et al. (2015)
Program code:
function varargout = exp_baumgartner2015binweight(varargin)
%EXP_BAUMGARTNER2015BINWEIGHT Results from various publications of Baumgartner et al. (2015)
% Usage: data = exp_baumgartner2015(flag)
%
% exp_baumgartner2015(flag) reproduces figures of the studies from
% Baumgartner et al. (2015).
%
%
% The following flags can be specified
%
%
% 'fig5' Reproduce Fig.5 of Baumgartner et al. (2015):
% Effect of background noise on reliability of contralateral
% cues for various lateral eccentricities. Top row:
% Across-listener averages of performance measures for
% contralateral ear. Bottom row: Contralateral re ipsilateral
% averages of performance measures.
% Further, cache flags (see amt_cache) and plot flags can be specified:
%
% 'plot' Plot the output of the experiment. This is the default.
%
% 'no_plot' Don't plot, only return data.
%
% Requirements:
% -------------
%
% 1) SOFA API v0.4.3 or higher from http://sourceforge.net/projects/sofacoustics for Matlab (in e.g. thirdparty/SOFA)
%
% 2) Data in hrtf/baumgartner2014
%
% 3) Statistics Toolbox for Matlab (for some of the figures)
%
% Examples:
% ---------
%
% To display Fig.5 of Baumgartner et al. (2015) use :
%
% exp_baumgartner2015('fig5');
%
% See also: baumgartner2014 data_baumgartner2014
%
% References:
% R. Baumgartner, P. Majdak, and B. Laback. The reliability of
% contralateral spectral cues for sound localization in sagittal planes.
% In Midwinter Meeting of the Association for Research in Otolaryngology,
% Baltimore, MD, Feb 2015.
%
% 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.
%
% R. Baumgartner and P. Majdak. Modeling Localization of Amplitude-Panned
% Virtual Sources in Sagittal Planes. J. Audio Eng. Soc.,
% 63(7/8):562--569, Aug. 2015. [1]http ]
%
% References
%
% 1. http://www.aes.org/e-lib/browse.cfm?elib=17842
%
% bremen2010pinna goupell2010numchan macpherson2007 macpherson2003ripples
% majdak2013spatstrat middlebrooks1999nonindividualized morimoto2001
% pulkki2001localization
%
% Url: http://amtoolbox.sourceforge.net/amt-0.10.0/doc/experiments/exp_baumgartner2015binweight.php
% Copyright (C) 2009-2020 Piotr Majdak and the AMT team.
% This file is part of Auditory Modeling Toolbox (AMT) version 1.0.0
%
% 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
%% ------ Check input options --------------------------------------------
definput.import={'amt_cache'};
definput.keyvals.FontSize = 12;
definput.keyvals.MarkerSize = 6;
definput.flags.type = {'missingflag', 'fig5'};
definput.flags.plot = {'plot','no_plot'};
[flags,kv] = ltfatarghelper({'FontSize','MarkerSize'},definput,varargin);
if flags.do_missingflag
flagnames=[sprintf('%s, ',definput.flags.type{2:end-2}),...
sprintf('%s or %s',definput.flags.type{end-1},definput.flags.type{end})];
error('%s: You must specify one of the following flags: %s.',upper(mfilename),flagnames);
end;
%% General Plot Settings
TickLength = [0.02,0.04];
ltfatsetdefaults('dbspl','dboffset',100);
%% ------ FIG 5 of baumgartner2015aro -------------------------------------
if flags.do_fig5
[perr,qerr,snrFront,bwcoef,lat] = amt_cache('get','fig5_baumgartner2015aro',flags.cachemode);
if isempty(perr)
snrFront = -20:2:40; % in dB
latecc = [10,30,50];% lateral eccentricities
mrs = 17; % no sensorimotor mapping
s = data_baumgartner2014('pool',flags.cachemode);
bwcoef = [13,+eps,-eps]; % configuration of binaural weighting stage (binaural, ipsilateral, contralateral
lat = [-fliplr(latecc),latecc];
maskerNoise = noise(0.05*s(1).Obj.Data.SamplingRate,1,'white');
targetNoise = noise(0.05*s(1).Obj.Data.SamplingRate-255,1,'white');
perr = nan(length(snrFront),length(bwcoef),length(lat),length(s));
qerr = nan(length(snrFront),length(bwcoef),length(lat),length(s));
for isub=1:length(s)
idfrontal = find(s(isub).Obj.SourcePosition(:,1)==0 & s(isub).Obj.SourcePosition(:,2)==0);
frontalDtfs = shiftdim(s(isub).Obj.Data.IR(idfrontal,:,:),2);
frontalTarget = convolve(targetNoise,frontalDtfs);
lvl = mean(dbspl(frontalTarget)); % level of frontal target stimulus in dB
for ilat = 1:length(lat)
[spdtfs,tang] = extractsp(lat(ilat),s(isub).Obj);
targets = convolve(targetNoise,spdtfs);
targets = reshape(targets,[length(targets),size(targets,2)/2,2]);
for isnr = 1:length(snrFront)
targetsPlusMasker = targets + ...
repmat(scaletodbspl(maskerNoise,lvl-snrFront(isnr)),[1,size(targets,2),2]);
for ibwc = 1:length(bwcoef)
[p,rang] = baumgartner2014(targetsPlusMasker,s(isub).Obj,...
'S',s(isub).S,'mrsmsp',mrs,...
'lat',lat(ilat),'bwcoef',bwcoef(ibwc));
[ qerr(isnr,ibwc,ilat,isub) , perr(isnr,ibwc,ilat,isub) ] = ...
baumgartner2014_pmv2ppp(p,tang,rang);
end
end
end
amt_disp([num2str(isub) ' of ' num2str(length(s)) ' completed']);
end
amt_cache('set','fig5_baumgartner2015aro',perr,qerr,snrFront,bwcoef,lat)
end
r = struct('perr',perr,'qerr',qerr,'snrFront',snrFront,'bwcoef',bwcoef,'lat',lat);
varargout{1} = r;
if flags.do_plot
% pool left/right
perr = (r.perr(:,:,length(r.lat)/2:-1:1,:) + r.perr(:,:,1+length(r.lat)/2:length(r.lat),:))/2;
qerr = (r.qerr(:,:,length(r.lat)/2:-1:1,:) + r.qerr(:,:,1+length(r.lat)/2:length(r.lat),:))/2;
latecc = r.lat(1+length(r.lat)/2:length(r.lat)); % lateral eccentricity
perr_ipsipro = squeeze(perr(:,3,:,:) - perr(:,2,:,:)); % contra minus ipsi
qerr_ipsipro = squeeze(qerr(:,3,:,:) - qerr(:,2,:,:));
snr_int = r.snrFront(1):r.snrFront(end);
figure
% display 0-error line
for ii = 1:2
subplot(2,2,2+ii)
plot(snr_int,zeros(length(snr_int),1),'k:')
hold on
end
color = [ 0.2081 0.1663 0.8292;...
0.8292 0.1663 0.2081;...
0.8081 0.6081 0.2081];
for ii=1:length(latecc)
subplot(2,2,1)
abspecontra_int = interp1(r.snrFront,mean(perr(:,ii,3,:),4),snr_int,'spline');
h(ii) = plot(snr_int,abspecontra_int,'Color',color(ii,:)); hold on
xlabel('SNR (dB)','FontSize',kv.FontSize)
ylabel('PE_{contra} (deg)','FontSize',kv.FontSize)
axis([-20,40,31,54])
set(gca,'FontSize',kv.FontSize)
subplot(2,2,2)
absqecontra_int = interp1(r.snrFront,mean(qerr(:,ii,3,:),4),snr_int,'spline');
h(ii) = plot(snr_int,absqecontra_int,'Color',color(ii,:)); hold on
xlabel('SNR (dB)','FontSize',kv.FontSize)
ylabel('QE_{contra} (deg)','FontSize',kv.FontSize)
axis([-20,40,6,49])
set(gca,'FontSize',kv.FontSize)
subplot(2,2,3)
pe_int = interp1(r.snrFront,mean(perr_ipsipro(:,ii,:),3),snr_int,'spline');
h(ii) = plot(snr_int,pe_int,'Color',color(ii,:));
xlabel('SNR (dB)','FontSize',kv.FontSize)
ylabel('PE_{contra} - PE_{ipsi} (deg)','FontSize',kv.FontSize)
axis([-20,40,-4,29])
set(gca,'FontSize',kv.FontSize)
subplot(2,2,4)
qe_int = interp1(r.snrFront,mean(qerr_ipsipro(:,ii,:),3),snr_int,'spline');
plot(snr_int,qe_int,'Color',color(ii,:))
xlabel('SNR (dB)','FontSize',kv.FontSize)
ylabel('QE_{contra} - QE_{ipsi} (deg)','FontSize',kv.FontSize)
axis([-20,40,-4,29])
set(gca,'FontSize',kv.FontSize)
end
subplot(2,2,3)
legendentries = [repmat('\phi = \pm',length(latecc),1) num2str(latecc(:)) repmat('\circ',length(latecc),1)];
leg = legend(h,legendentries,'Location','north');
set(leg,'FontSize',kv.FontSize)
end
ltfatsetdefaults('dbspl','dboffset',93.98);
end
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