function data = data_baumgartner2014(varargin)
%DATA_BAUMGARTNER2014 Data from Baumgartner et al. (2014)
% Usage: data = data_baumgartner2014(flag)
%
% `data_baumgartner2014(flag)` returns data from Baumgartner et al. (2014)
% describing a model for sound localization in sagittal planes (SPs)
% on the basis of listener-specific directional transfer functions (DTFs).
%
% The flag may be one of:
%
% 'pool' DTFs and calibration data of the pool. The output contains
% the following fields: *id*, *u*, *goupell10*, *walder10*,
% *fs* and *Obj*.
%
% 'baseline' Same as 'pool', but also with experimental data for
% baseline condition.
%
% The fields in the output contains the following information
%
% .id listener ID
%
% .u listener-specific uncertainty
%
% .goupell10 boolean flag indicating whether listener
% participated in Goupell et al. (2010)
%
% .walder10 boolean flag indicating whether listener
% participated in Walder (2010)
%
% .dtfs matrix containing DTFs.
% Dimensions: time, position, channel
% (more details see doc: HRTF format)
%
% .fs sampling rate of impulse responses
%
% .pos source-position matrix referring to
% 2nd dimension of hM and formated acc.
% to meta.pos (ARI format).
% 6th col: lateral angle
% 7th col: polar angle
%
% .Obj DTF data in SOFA Format
%
% .pe_exp experimental local polar RMS error
%
% .qe_exp experimental quadrant error rate
%
% .target experimental target angles
%
% .response experimental response angles
%
% Examples:
% ---------
%
% To get all listener-specific data of the pool, use::
%
% data_baumgartner2014('pool');
%
% To get all listener-specific data of the pool including experimental
% baseline data, use::
%
% data_baumgartner2014('baseline');
%
% See also: baumgartner2014, exp_baumgartner2014
% AUTHOR : Robert Baumgartner
%% ------ Check input options --------------------------------------------
% Define input flags
% definput.flags.plot = {'noplot','plot'};
definput.flags.type = {'pool','baseline'};
definput.flags.recalib = {'norecalib','recalib'};
definput.flags.HRTFformat = {'sofa','ari'};
definput.keyvals.mrsmsp=20; % motoric response scatter in elevation (degrees)
definput.keyvals.gamma=6; % degree of selectivity
definput.keyvals.do=1; % spectral gradient
% Parse input options
[flags,kv] = ltfatarghelper({'mrsmsp','gamma'},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;
%% Listener pool (listener-specific SP-DTFs)
if flags.do_pool || flags.do_baseline
listeners = {'NH12';'NH15';'NH21';'NH22';'NH33';'NH39';'NH41';'NH42';'NH43';...
'NH46';'NH53';'NH55';'NH58';'NH62';'NH64';'NH68';'NH71';'NH72'};
data=cell2struct(listeners,'id',2);
for ii = 1:length(data)
data(ii).S = 0.5; % default sensitivity
filename = fullfile(SOFAdbPath,'baumgartner2013',...
['ARI_' data(ii).id '_hrtf_M_dtf 256.sofa']);
if exist(filename,'file') ~= 2
fprintf([' Sorry! Before you can run this script, you have to download the HRTF Database from \n http://www.kfs.oeaw.ac.at/hrtf/database/amt/baumgartner2013.zip , \n unzip it, and move the folder into your HRTF repository \n ' SOFAdbPath ' .\n' ' Then, press any key to quit pausing. \n'])
pause
end
data(ii).Obj = SOFAload(filename);
data(ii).fs = data(ii).Obj.Data.SamplingRate;
end
%% Calibration of S
if not(exist('baumgartner2014calibration.mat','file')) || flags.do_recalib
data = loadBaselineData(data);
fprintf('Calibration procedure started. Please wait!\n')
data = baumgartner2014calibration(data,kv);
data_all = data;
data = rmfield(data,{'Obj','mm1','fs','target','response'}); % reduce filesize
save(fullfile(amtbasepath,'modelstages','baumgartner2014calibration.mat'),'data')
data = data_all;
else
if flags.do_baseline
data = loadBaselineData(data);
end
c = load('baumgartner2014calibration.mat');
for ss = 1:length(data)
for ii = 1:length(c.data)
if strcmp(data(ss).id,c.data(ii).id)
data(ss).S = c.data(ii).S;
end
end
end
end
end
end
function s = loadBaselineData(s)
latseg = 0;
dlat = 10;
% Experimental baseline data
numchan = data_goupell2010('BB');
methods = data_majdak2010('HMD_M');
spatstrat = data_majdak2013('BB');
ctcA = data_majdak2013ctc('A');
ctcB = data_majdak2013ctc('B');
for ll = 1:length(s)
s(ll).mm1 = [];
s(ll).mm1 = [s(ll).mm1 ; numchan(ismember({numchan.id},s(ll).id)).mtx];
s(ll).mm1 = [s(ll).mm1 ; methods(ismember({methods.id},s(ll).id)).mtx];
s(ll).mm1 = [s(ll).mm1 ; spatstrat(ismember({spatstrat.id},s(ll).id)).mtx];
s(ll).mm1 = [s(ll).mm1 ; ctcA(ismember({ctcA.id},s(ll).id)).mtx];
s(ll).mm1 = [s(ll).mm1 ; ctcB(ismember({ctcB.id},s(ll).id)).mtx];
s(ll).pe_exp = localizationerror(s(ll).mm1,'rmsPmedianlocal');
s(ll).qe_exp = localizationerror(s(ll).mm1,'querrMiddlebrooks');
for ii = 1:length(latseg)
latresp = s(ll).mm1(:,7);
idlat = latresp <= latseg+dlat & latresp > latseg-dlat;
mm2 = s(ll).mm1(idlat,:);
s(ll).target{ii} = mm2(:,6); % polar angle of target
s(ll).response{ii} = mm2(:,8); % polar angle of response
s(ll).Ntargets{ii} = length(s(ll).target{ii});
end
end
end