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EXP_BAUMGARTNER2013 - Figures from Baumgartner et al. (2013)
Program code:
function varargout=exp_baumgartner2013(varargin)
%EXP_BAUMGARTNER2013 Figures from Baumgartner et al. (2013)
% Usage: data = exp_baumgartner2013(flag)
%
% EXP_BAUMGARTNER2013(flags) reproduces figures of the book
% chapter from Baumgartner et al. (2013).
%
% Optional fields of output data structure:
%
% data.id
% listener ID
%
% data.u
% listener-specific uncertainty
%
% data.dtfs
% matrix containing DTFs. Dimensions: time, position, channel
% (more details see doc: HRTF format)
%
% data.fs
% sampling rate of impulse responses
%
% data.pos
% source-position matrix referring to 2nd dimension of
% hM and formated acc. to meta.pos (ARI format).
% 6th col is the lateral angle. 7th col is the polar angle.
%
% data.spdtfs
% DTFs of specific SPs
%
% data.polangs
% polar angles corresponding to data.spdtfs*
%
% data.pmv
% predicted polar angular response PMVs
%
% data.respangs
% polar response angules corresponding to data.p*
%
% data.pe
% predicted local polar RMS error in degrees
%
% data.qe
% predicted quadrant error
%
% The following flags can be specified:
%
% 'plot' Plot the output of the experiment. This is the default.
%
% 'noplot' Don't plot, only return data.
%
% 'fig12' Reproduce Fig. 12:
% DTFs of median SP (left ear).
% Left: NH12. Center: NH58. Right: NH33.
% Brightness: Spectral magnitude.
%
% 'fig13' Reproduce Fig. 13:
% Listener's localization performance for non-individualized
% versus individualized DTFs.
% Bars: Individualized DTFs.
% Circles: Non-individualized DTFs averaged over 16 DTF sets.
% Error bars: ±1 standard deviation of the average.
% Horizontal line: Chance performance corresponding to
% guessing the direction of the sound.
%
% 'fig14' Reproduce Fig. 14:
% Bars: Increase in localization errors when listening to a
% binaural recording created with the DTFs from NH58.
% Asterisk: Difference between actual (experiment) and
% predicted performance when listening to individualized DTFs.
% Horizontal lines: chance performance corresponding to
% guessing the direction of the sound.
%
% 'fig15' Reproduce Fig. 15:
% Bars: Localization performance of the pool listening to
% selected DTFs.
% Circles: DTFs from NH12.
% Squares: DTFs from NH58.
% Triangles: DTFs from NH33.
%
% 'fig18' Reproduce Fig. 18:
% Predicted response probabilities (PMVs) as a function of
% the amplitude panning ratio between a rear and a front
% loudspeaker in the same SP (lateral angle: 30 deg.).
% Left: Results for NH12.
% Center: Results for NH15.
% Right: Results for our pool of listeners.
% Circle: Maximum of a PMV.
% Panning ratio of 0: Only front loudspeaker active.
% Panning ratio of 1: Only rear loudspeaker active.
%
% 'fig19' Reproduce Fig. 19:
% Prediction matrices (PMVs) for different loudspeaker spans
% and NH12.
% Left: Span of 0 deg. (single-loudspeaker reproduction, baseline).
% Center: Span of 30 deg.
% Right: Span of 60 deg.
% P: Predicted performance.
%
% 'fig20' Reproduce Fig. 20:
% Increase in localization errors as a function of the
% loudspeaker span.
% Circles: Averages over all listeners from the pool.
% Error bars: +/- 1 standard deviation of the averages.
%
% 'fig22' Reproduce Fig. 22:
% Predictions for the surround setups in the VBAP configuration.
% Left: 5.1 setup, panning between the loudspeakers L and LS.
% Center: 10.2 setup (DSX), panning from L (polar angle of 0 deg.)
% via LH2 (55 deg.) to LS (180 deg.)
% Right: 9.1 setup (Auro-3D), panning from L (0 deg.) via
% LH1 (34 deg.) and LSH (121 deg.) to LS (180 deg.).
% Desired polar angle: Continuous scale representing the VBAP
% across pair-wise contributing loudspeakers.
% All other conventions as in Fig. 18.
%
% 'fig23' Reproduce Fig. 23:
% Predictions for two modifications to the 9.1 setup (Auro 3D).
% Left: Original setup, loudspeakers LS and LSH
% at the azimuth of 110 deg.
% Center: LSH at the azimuth of 130 deg.
% Right: LS and LSH at the azimuth of 130 deg.
% All other conventions as in Fig. 22.
%
% 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/baumgartner2013
%
% See also: baumgartner2013, data_baumgartner2013
%
% Examples:
% ---------
%
% To display Fig. 12 use :
%
% exp_baumgartner2013('fig12');
%
% To display Fig. 13 use :
%
% exp_baumgartner2013('fig13');
%
% To display Fig. 14 use :
%
% exp_baumgartner2013('fig14');
%
% To display Fig. 15 use :
%
% exp_baumgartner2013('fig15');
%
% To display Fig. 18 use :
%
% exp_baumgartner2013('fig18');
%
% To display Fig. 19 use :
%
% exp_baumgartner2013('fig19');
%
% To display Fig. 20 use :
%
% exp_baumgartner2013('fig20');
%
% To display Fig. 22 use :
%
% exp_baumgartner2013('fig22');
%
% To display Fig. 23 use :
%
% exp_baumgartner2013('fig23');
%
% References:
% R. Baumgartner. Modeling sagittal-plane sound localization with the
% application to subband-encoded head related transfer functions.
% Master's thesis, University of Music and Performing Arts, Graz, June
% 2012.
%
% R. Baumgartner, P. Majdak, and B. Laback. Assessment of Sagittal-Plane
% Sound Localization Performance in Spatial-Audio Applications,
% chapter 4, pages 93-119. Springer-Verlag GmbH, 2013.
%
%
% Url: http://amtoolbox.sourceforge.net/amt-0.9.9/doc/experiments/exp_baumgartner2013.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/>.
% AUTHOR: Robert Baumgartner
%% ------ Check input options --------------------------------------------
definput.flags.type = {'missingflag',...
'fig12','fig13','fig14','fig15',... % Ch. 4.1 (binaural rec.)
'fig18','fig19','fig20','fig22','fig23'}; % Ch. 4
definput.flags.plot = {'plot','noplot'};
definput.import={'amt_cache'};
% Parse input options
[flags,kv] = ltfatarghelper({},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;
%% Figure 12
if flags.do_fig12
s = data_baumgartner2013('pool', flags.cachemode);
s = s([2 1 14]); % NH12, NH58, NH33
nfft = 2^12;
range = 50; % dB
lat = 0; % median sagittal plane
fhigh = 18e3; % Hz
da = 3; % white frame for ticks (angles)
df = 0.1; % white frame for ticks (freq)
figure
for ll = 1:length(s)
f = 0:s(1).fs/nfft:s(ll).fs/2;
f = f/1e3; % in kHz
s(ll).spdtfs = [];
s(ll).polangs = [];
[s(ll).spdtfs,s(ll).polangs] = extractsp(lat,s(ll).Obj);
mag = 20*log10(abs(fft(s(ll).spdtfs,nfft)));
mag = mag(1:nfft/2+1,:,:);
maxmag = max(max(max(mag)));
mag = mag - maxmag; % normalize to 0dB
maxmag = 0;
mag(mag < maxmag-range) = maxmag-range; % limit dynamic range
crange = [floor(maxmag-range), ceil(maxmag)];% range of color code
idf = f<fhigh/1e3;
magl = mag(idf,:,1);
fp = f(idf);
polp = s(ll).polangs;
subplot(1,3,ll)
h = pcolor(fp,polp,magl');
caxis(crange)
shading interp
colormap('bone')
xlabel('Frequency (kHz)')
ylabel('Polar Angle (\circ)')
set(gca,...
'XLim',[fp(1)-df,fp(end)+df],...
'YLim',[polp(1)-da,polp(end)+da],...
'XTick',1:2:17,...
'YTick',-30:30:polp(end),...
'XMinorTick','on',...
'YMinorTick','on'...
)
end
if nargout == 1
varargout{1} = s;
end
end
%% Figures 13-15 (non-individual binaural recordings)
if flags.do_fig13 || flags.do_fig14 || flags.do_fig15
latdivision = [-20,0,20]; % lateral center angles of SPs
[s,qe,pe]=amt_cache('get','fig13to15',flags.cachemode);
if isempty(s)
s = data_baumgartner2013('pool', flags.cachemode);
ns = length(s);
% DTFs of the SPs
for ll = 1:ns
for ii = 1:length(latdivision)
s(ll).latang{ii} = latdivision(ii);
s(ll).polangs{ii} = [];
s(ll).spdtfs{ii} = [];
[s(ll).spdtfs{ii},s(ll).polangs{ii}] = extractsp(...
s(ll).latang{ii},s(ll).Obj);
end
end
%fprintf('\n Please wait a little! \n');
qe = zeros(ns,ns,length(latdivision)); % init QEs
pe = qe; % init PEs
for ll = 1:ns % listener
for jj = 1:ns % ears
for ii = 1:length(latdivision) % SPs
s(ll).pmv{jj,ii} = [];
s(ll).respangs{ii} = [];
[s(ll).pmv{jj,ii},s(ll).respangs{ii}] = baumgartner2013(...
s(jj).spdtfs{ii},s(ll).spdtfs{ii},s(ll).fs,...
'u',s(ll).u,'lat',s(ll).latang{ii},...
'polsamp',s(ll).polangs{ii});
[ qe(ll,jj,ii),pe(ll,jj,ii) ] = baumgartner2013_pmv2ppp( ...
s(ll).pmv{jj,ii} , s(jj).polangs{ii} , s(ll).respangs{ii});
end
end
amt_disp([num2str(ll,'%2u') ' of ' num2str(ns,'%2u') ' completed'],'progress');
end
qe = mean(qe,3);
pe = mean(pe,3);
for ll = 1:length(s)
s(ll).pe = pe(ll,:);
s(ll).qe = qe(ll,:);
end
amt_cache('set','fig13to15',s,qe,pe);
end
ns = length(s);
if nargout == 1
varargout{1} = s; % SAME for Fig. 13-15!!!!
end
if flags.do_fig13 % -----------------------------------------------------
if flags.do_plot
markersize = 4;
[qechance,pechance] = baumgartner2013_pmv2ppp(ones(49,44));
% IDs for XTick of plots
for ll = 1:ns
nhs(ll,:) = s(ll).id;
end
% Polar error
figure
subplot(121)
peinc = zeros(ns,ns-1);
for l = 1:ns
peinc(l,:) = pe(l,[1:l-1,l+1:ns]);
end
mpeinc = mean(peinc,2);
speinc = std(peinc,0,2);
h = bar(diag(pe));
set(h,'FaceColor','white')
hold on
errorbar(mpeinc,speinc,'ko',...
'MarkerSize',markersize,'MarkerFaceColor','w');
plot(0:ns+1,pechance*ones(ns+2,1),'k--')
ylabel('Local Polar RMS Error (\circ)')
xlabel({'NH'})
set(gca,'YLim',[20.1 48],'XLim',[0 ns+1],...
'XTick',1:ns,'XTickLabel',nhs(:,3:4),...
'YMinorTick','on')
% Quadrant error
subplot(122)
qeinc = zeros(ns,ns-1);
for l = 1:ns
qeinc(l,:) = qe(l,[1:l-1,l+1:ns]);
end
mqeinc = mean(qeinc,2);
sqeinc = std(qeinc,0,2);
h = bar(diag(qe));
set(h,'FaceColor','white')
hold on
errorbar(mqeinc,sqeinc,'ko',...
'MarkerSize',markersize,'MarkerFaceColor','w');
plot(0:ns+1,qechance*ones(ns+2,1),'k--')
set(gca,'YLim',[floor(min(diag(qe))-1) ceil(qechance+1)],...
'XLim',[0 ns+1],'XTick',1:ns,'XTickLabel',nhs(:,3:4),...
'YMinorTick','on')
ylabel('Quadrant Error (%)')
xlabel({'NH'})
end
elseif flags.do_fig14 % -------------------------------------------------
ears = 1; % NH58
s(ears).peexp = 23.5;
s(ears).qeexp = 0.775;
if flags.do_plot
[qechance,pechance] = baumgartner2013_pmv2ppp(ones(49,44));
% IDs for XTick of plots
for ll = 1:ns
nhs(ll,:) = s(ll).id;
end
figure
% Polar error
subplot(121)
h = bar(pe(:,ears)-diag(pe));
hold on
plot(ears,s(ears).peexp-pe(ears,ears),'k*')
dx = 0.42;
peincchance = pechance-diag(pe);
for ll = 1:length(s)
plot(ll+[-dx,+dx],ones(2,1)*peincchance(ll),'k--')
end
ylabel('Increase in Local Polar RMS Error (\circ)')
xlabel('NH')
set(h,'FaceColor','white')
set(gca,'XLim',[0 length(s)+1],...
'XTick',1:length(s),'XTickLabel',nhs(:,3:4),...
'YLim',[-1 21.9],'YMinorTick','on')
% Quadrant error
subplot(122)
h = bar(qe(:,ears)-diag(qe));
hold on
plot(ears,s(ears).qeexp-qe(ears,ears),'k*')
dx = 0.4;
qeincchance = qechance-diag(qe);
for ll = 1:length(s)
plot(ll+[-dx,+dx],ones(2,1)*qeincchance(ll),'k--')
end
set(h,'FaceColor','white')
set(gca,'XLim',[0 length(s)+1],...
'XTick',1:length(s),'XTickLabel',nhs(:,3:4),...
'YLim',[-5 18],'YMinorTick','on')
xlabel('NH')
ylabel('Increase in Quadrant Error (%)')
end
elseif flags.do_fig15
pepoor = pe(:,14); % NH33 (14)
pemed = pe(:,1); % NH58 (1)
pegood = pe(:,2); % NH12 (2)
qepoor = qe(:,14);
qemed = qe(:,1);
qegood = qe(:,2);
if flags.do_plot
markersize = 4;
[qechance,pechance] = baumgartner2013_pmv2ppp(ones(49,44));
% IDs for XTick of plots
for ll = 1:ns
nhs(ll,:) = s(ll).id;
end
figure
% Polar error
subplot(121)
h = bar(diag(pe));
hold on
plot(pegood,'ko','MarkerSize',markersize,'MarkerFaceColor','k')
plot(pemed, 'ks','MarkerSize',markersize,'MarkerFaceColor',0.5*ones(3,1))
plot(pepoor,'kv','MarkerSize',markersize,'MarkerFaceColor','w')
plot(0:length(s)+1,pechance*ones(length(s)+2,1),'k--')
set(gca,'XLim',[0 length(s)+1],'XTick',1:length(s),'XTickLabel',nhs(:,3:4),...
'YLim',[20.1 48],'YMinorTick','on')
set(h,'FaceColor','white')%,'BarWidth',0.5)
ylabel('Local Polar RMS Error (\circ)')
xlabel('NH')
% Quadrant error
subplot(122)
h = bar(diag(qe));
hold on
plot(qegood,'ko','MarkerSize',markersize,'MarkerFaceColor','k')
plot(qemed,'ks','MarkerSize',markersize,'MarkerFaceColor',0.5*ones(3,1))
plot(qepoor,'kv','MarkerSize',markersize,'MarkerFaceColor','w')
plot(0:length(s)+1,qechance*ones(length(s)+2,1),'k--')
set(gca,'XLim',[0 length(s)+1],'XTick',1:length(s),'XTickLabel',nhs(:,3:4),...
'YLim',[1 44],'YMinorTick','on')
set(h,'FaceColor','white')%,'BarWidth',0.5)
ylabel('Quadrant Error (%)')
xlabel('NH')
end
end
end
%% Figures 18, 22, 23 (Amplitude panning between loudspeakers)
if flags.do_fig18 || flags.do_fig22 || flags.do_fig23
% Coordinates (azi,ele) of loudspeakers
if flags.do_fig18
LSPsetup{1} = [ 30,0 ; 150,0 ]; % lat: 30 deg.
package='fig18';
elseif flags.do_fig22
LSPsetup{1} = [ 30,0 ; 110,0 ]; % 5.1
LSPsetup{2} = [ 30,0 ; 45,45 ; 110,0 ]; % 10.2
LSPsetup{3} = [ 30,0 ; 30,30 ; 110,30 ; 110,0 ]; % 9.1
package='fig22';
elseif flags.do_fig23
LSPsetup{1} = [ 30,0 ; 30,30 ; 110,30 ; 110,0 ]; % 9.1
LSPsetup{2} = [ 30,0 ; 30,30 ; 140,30 ; 110,0 ]; % 9.1 (prop. LSH)
LSPsetup{3} = [ 30,0 ; 30,30 ; 140,30 ; 140,0 ]; % 9.1 (prop. LSH&LS)
package='fig23';
end
dpol = 5; % step size in deg
[s, D]=amt_cache('get',package,flags.cachemode);
if isempty(s),
s = data_baumgartner2013('pool', flags.cachemode);
ns = length(s);
for ss = 1:length(LSPsetup)
LSPsph = LSPsetup{ss};
nLSP = size(LSPsph,1);
LSPhp = zeros(nLSP,2);
[LSPhp(:,1),LSPhp(:,2)] = sph2horpolar(LSPsph(:,1),LSPsph(:,2));
LSPcart = zeros(nLSP,3);
[LSPcart(:,1),LSPcart(:,2),LSPcart(:,3)] = ...
sph2cart(LSPsph(:,1),LSPsph(:,2),ones(nLSP,1));
D = LSPhp(1,2):dpol:LSPhp(nLSP,2); % Desired polar angle
%fprintf('\n Please wait a little! \n');
for ll = 1:ns
s(ll).pos(:,1)=bsxfun(@times,s(ll).Obj.SourcePosition(:,1),ones(s(ll).Obj.API.M,1));
s(ll).pos(:,2)=bsxfun(@times,s(ll).Obj.SourcePosition(:,2),ones(s(ll).Obj.API.M,1));
[poscart(:,1),poscart(:,2),poscart(:,3)] = ...
sph2cart(s(ll).pos(:,1),s(ll).pos(:,2),ones(size(s(ll).pos,1),1));
% DTF indices of LSPs
idLSP = zeros(nLSP,1);
for ii = 1:nLSP
e = poscart-repmat(LSPcart(ii,:),size(poscart,1),1);
[tmp,idLSP(ii)] = min( sqrt(sum(e.^2,2)) ); % minimum euclidean distance
end
clear poscart
Lp = 1; % LSP pair index
for d = 1:length(D)
if D(d) > LSPhp(Lp+1,2) % Switch to next LSP pair?
Lp = Lp + 1;
end
pol1 = LSPhp(Lp,2);
pol2 = LSPhp(Lp+1,2);
if abs(pol1-pol2) < 180
pol0 = mean([pol1 pol2]); % polar angle of center
phi0 = abs(pol1-pol2)/2; % basis angle
M = (1-tan(deg2rad(pol0-D(d)))/tan(deg2rad(phi0)))/2;
else
M = (D(d)-pol1) / (pol2-pol1);
end
lat1 = LSPhp(Lp,1);
lat2 = LSPhp(Lp+1,1);
lat0 = mean([lat1 lat2]); % lateral angle of center
phi0 = abs(lat1-lat2)/2; % basis angle
phiM = rad2deg( atan( tan(deg2rad(phi0)) * (1-2*M) ) );
latM = lat0 - phiM;
s(ll).dtfs = permute(double(s(ll).Obj.Data.IR),[3 1 2]);
dtfLSP = (1-M)*s(ll).dtfs(:,idLSP(Lp),:) + M*s(ll).dtfs(:,idLSP(Lp+1),:);
[spdtfs,polangs] = extractsp(latM,s(ll).Obj);
[pmv,respangs] = baumgartner2013(dtfLSP,spdtfs,s(ll).fs,...
'lat',latM,'u',s(ll).u,...
'polsamp',polangs);
idP = respangs >= -30 & respangs <= 210;
s(ll).pmv{ss}(:,d) = pmv(idP)/sum(pmv(idP));
s(ll).respangs = respangs(idP);
end
amt_disp([num2str(ll,'%2u') ' of ' num2str(ns,'%2u') ' completed'],'progress')
end
% Pool
ppool = zeros(size(s(1).pmv{ss}));
for ll = 1:ns
ppool = ppool + s(ll).pmv{ss};
end
s(ns+1).pmv{ss} = ppool/length(s);
s(ns+1).respangs = s(1).respangs;
s(ns+1).id = 'Pool';
end
amt_cache('set',package,s,D);
end
% Output
if nargout == 1
varargout{1} = s;
end
% Plots
if flags.do_plot
if flags.do_fig18
subject = [9 5 18];
setup = [1 1 1];
elseif flags.do_fig22
subject = [18 18 18];
setup = 1:3;
elseif flags.do_fig23
subject = [18 18 18];
setup = 1:3;
end
figure
for ii = 1:3
ll = subject(ii);
ss = setup(ii);
subplot(1,3,ii)
h = pcolor(D,s(ll).respangs,s(ll).pmv{ss});
if not(isoctave) % does not work with x11 (mac osx)
axis equal
end
if flags.do_fig23 || (flags.do_fig22 && ss > 1)
set(gca,'XLim',[D(1)-3 D(end)+3],'XMinorTick','on',...
'XTick',0:30:180,'XTickLabel',{0:30:150,180})
xlabel('Desired Polar Angle (\circ)')
else
set(gca,'XLim',[D(1)-3 D(end)+3],'XMinorTick','on',...
'XTick',18:36:180,'XTickLabel',{0.1:0.2:0.9})
xlabel('Panning Ratio')
end
set(gca,'YLim',[s(ll).respangs(1)-3 s(ll).respangs(end)+3],...
'YMinorTick','on','YTick',(0:30:180)+2.5,'YTickLabel',0:30:180)
colormap bone
shading flat
caxis([0 0.1])
ylabel('Response Angle (\circ)')
[tmp,Imax] = max(s(ll).pmv{ss});
hold on
h1 = plot( D,s(ll).respangs(Imax)+2.5, 'wo'); % shadow
set(h1,'MarkerSize',4,'MarkerFaceColor','none')
h2 = plot( D,s(ll).respangs(Imax)+2.5, 'ko');
set(h2,'MarkerSize',3,'MarkerFaceColor','none')
end
end
end
%% Figures 19, 20 (Effect of loudspeaker span)
if flags.do_fig19 || flags.do_fig20
s = data_baumgartner2013('pool', flags.cachemode);
if flags.do_fig19
dPol = [0 30,60];
s = s(2); % NH12
elseif flags.do_fig20
dPol = 10:10:90;
end
lat = 0;
s(1).spdtfs = [];
[s(1).spdtfs,polang] = extractsp(lat,s(1).Obj);
qeI = zeros(length(s),length(dPol));
peI = qeI;
ii = 0;
while ii < length(dPol)
ii = ii + 1;
% find comparable angles
id0 = [];
id1 = [];
id2 = [];
for jj = 1: length(polang)
t0 = find( round(polang) == round(polang(jj)+dPol(ii)/2) );
t2 = find( round(polang) == round(polang(jj)+dPol(ii)) );
if ~isempty(t0) && ~isempty(t2)
id0 = [id0 t0];
id1 = [id1 jj];
id2 = [id2 t2];
end
end
pol2{ii} = (polang(id1)+polang(id2)) /2;
amt_disp([' Span: ' num2str(dPol(ii)) ' deg.'],'progress');
for ll = 1:length(s)
s(ll).spdtfs = extractsp(lat,s(ll).Obj);
% superposition
s(ll).dtfs2{ii} = s(ll).spdtfs(:,id1,:) + s(ll).spdtfs(:,id2,:);
[s(ll).pmv1{ii},respang] = baumgartner2013(...
s(ll).spdtfs(:,id0,:),s(ll).spdtfs,s(ll).fs,'u',s(ll).u,...
'polsamp',polang);
s(ll).pmv2{ii} = baumgartner2013(...
s(ll).dtfs2{ii},s(ll).spdtfs,s(ll).fs,'u',s(ll).u,...
'polsamp',polang);
[s(ll).qe1{ii},s(ll).pe1{ii}] = baumgartner2013_pmv2ppp(...
s(ll).pmv1{ii},polang(id0),respang);
[s(ll).qe2{ii},s(ll).pe2{ii}] = baumgartner2013_pmv2ppp(...
s(ll).pmv2{ii},pol2{ii},respang);
% Increse of error
qeI(ll,ii) = s(ll).qe2{ii} - s(ll).qe1{ii};
peI(ll,ii) = s(ll).pe2{ii} - s(ll).pe1{ii};
end
end
if nargout == 1
varargout{1} = s;
end
if flags.do_plot
if flags.do_fig19
figure;
subplot(1,3,1)
plot_baumgartner2013(s(1).pmv1{1},polang,respang,'cmax',0.1,'nocolorbar');
title(['P: PE = ' num2str(s(1).pe1{1},2) '\circ, QE = ' num2str(s(1).qe1{1},2) '%'])
subplot(1,3,2)
plot_baumgartner2013(s(1).pmv2{2},pol2{2},respang,'cmax',0.1,'nocolorbar');
title(['P: PE = ' num2str(s(1).pe2{2},2) '\circ, QE = ' num2str(s(1).qe2{2},2) '%'])
subplot(1,3,3)
plot_baumgartner2013(s(1).pmv2{3},pol2{3},respang,'cmax',0.1,'nocolorbar');
title(['P: PE = ' num2str(s(1).pe2{3},2) '\circ, QE = ' num2str(s(1).qe2{3},2) '%'])
elseif flags.do_fig20
qeIm = mean(qeI);
peIm = mean(peI);
qeIs = std(qeI);
peIs = std(peI);
MarkerSize = 5;
figure
subplot(121)
errorbar(dPol,peIm,peIs,'ko-',...
'MarkerSize',MarkerSize,...
'MarkerFaceColor','k');
ylabel('Increase in Local Polar RMS Error (\circ)')
xlabel('Loudspeaker Span (\circ)')
set(gca,...
'XLim',[dPol(1)-10 dPol(end)+10],...
'XTick',dPol,...
'YLim',[-1,12.9],...
'YMinorTick','on')
axis square
subplot(122)
errorbar(dPol,qeIm,qeIs,'ko-',...
'MarkerSize',MarkerSize,...
'MarkerFaceColor','k');
ylabel('Increase in Quadrant Error (%)')
xlabel('Loudspeaker Span (\circ)')
set(gca,...
'XLim',[dPol(1)-10 dPol(end)+10],...
'XTick',dPol,...
'YLim',[-1,12.9],...
'YMinorTick','on')
axis square
end
end
end
end
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