function exp_pausch2022(varargin)
%EXP_PAUSCH2022 - Reproduce the figures from Pausch et al. (2022)
%
% Usage: exp_pausch2022(fig)
%
% The fig flag may be one of:
%
% 'fig5' : Comparison of measurement-based mean ITDs between
% datasets in the horizontal plane, evaluated in a
% frequency range of 0.5-1.5 kHz and averaged across
% participants with standard deviations sigma (grey
% areas). Dashed and dotted lines show the mean ITD
% differences in front (F) and rear (R) HARTFs,
% respectively, compared to the mean ITDs in HRTFs.
% scenarios, represent differences to scenario A.
% 'fig9' : a) Measurement-based (light grey) and b), c) model-based
% broadband ITD estimations, colour-coded in grey, black
% and blue, respectively, evaluated for directions in
% the horizontal plane for HRTF and front (F) and
% rear (R) HARTF datasets. Deviations from measurement-
% based ITDs are shown as dashed-dotted (Models~1 and~3)
% or dotted lines (Model~2+), with standard deviations
% as shaded areas. d) Scatter plots comparing measurement-
% based and model-based ITD maxima, fitted by linear
% regression lines. Box plots show medians and IQRs of
% differences in e) ITD maxima and f) arguments of the
% ITD maxima, with whiskers covering 1.5 times the
% IQR, and outliers displayed as crosses. Horizontal
% black lines indicate non-significant (n.s.) mean
% differences at the 95% confidence level.
%
%
%
% Requirements:
% -------------
%
% 1) SOFA Toolbox v0.4.3 or higher from http://sourceforge.net/projects/sofacoustics
% for Matlab (in e.g. thirdparty/SOFA)
%
% 2) Data in auxdata/pausch2022 (downloaded on the fly)
%
%
% Examples:
% ---------
%
% To display results of Fig. 5:
%
% exp_pausch2022('fig5','plot');
%
% To display results of Fig. 9:
% exp_pausch2022('fig9');
%
%
% See also: pausch2022 data_pausch2022
%
% References:
% F. Pausch, S. Doma, and J. Fels. Hybrid multi-harmonic model for the
% prediction of interaural time differences in individual behind-the-ear
% hearing-aid-related transfer functions. Acta Acust., 6:34, 2022.
% [1]http ]
%
% References
%
% 1. https://doi.org/10.1051/aacus/2022020
%
%
% Url: http://amtoolbox.org/amt-1.5.0/doc/experiments/exp_pausch2022.php
% #Author: Florian Pausch (2022): integrated in the AMT
% #Author: Florian Pausch (2023): code improvements
% 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.
%% Parse flags and keyvals
definput.import={'pausch2022'};
definput.flags.fig = {'missingflag','fig5','fig9'};
%definput.flags.plot = {'plot', 'no_plot'}
[flags,kv] = ltfatarghelper({},definput,varargin);
if flags.do_missingflag
flagnames=[sprintf('%s, ',definput.flags.fig{2:end-2}),...
sprintf('%s or %s',definput.flags.fig{end-1},definput.flags.fig{end})];
error('%s: You must specify one of the following flags: %s.',upper(mfilename),flagnames);
end
%% Figure 3
% if flags.do_fig3
% amt_disp([mfilename,': Not yet implemented.'])
% fig_handle = [];
% end
%% Figure 5
if flags.do_fig5
% load directional datasets and estimate ITDs
[~,itd_hrtf] = data_pausch2022('hrtf');
[~,itd_hartf_front] = data_pausch2022('hartf_front');
[~,itd_hartf_rear] = data_pausch2022('hartf_rear');
% plot data
font_size = 18;
line_width = 3.5;
plot_size = [400,400,650,360];
phi_vec = 0:2.5:357.5;
phi_vec = phi_vec(:);
fig_handle = figure('Position',plot_size);
patch([phi_vec;flipud(phi_vec)],...
[(itd_hrtf(1).itd_hor_mean-itd_hrtf(1).itd_hor_std)*1e6;...
flipud(itd_hrtf(1).itd_hor_mean+itd_hrtf(1).itd_hor_std)*1e6],...
kv.col_shad_mod2plus,'EdgeColor','none');
hold on
alpha(kv.alpha)
ph = patch([phi_vec;flipud(phi_vec)],...
[(itd_hartf_front(1).itd_hor_mean-itd_hartf_front(1).itd_hor_std)*1e6;...
flipud(itd_hartf_front(1).itd_hor_mean+itd_hartf_front(1).itd_hor_std)*1e6],...
kv.col_shad_mod1,'EdgeColor','none');
alpha(kv.alpha)
patch([phi_vec;flipud(phi_vec)],...
[(itd_hartf_rear(1).itd_hor_mean-itd_hartf_rear(1).itd_hor_std)*1e6;...
flipud(itd_hartf_rear(1).itd_hor_mean+itd_hartf_rear(1).itd_hor_std)*1e6],...
kv.col_shad_meas,'EdgeColor','none');
alpha(kv.alpha)
l1 = plot(phi_vec, itd_hrtf(1).itd_hor_mean*1e6,'Color',kv.col_mod2plus,'LineWidth',line_width);
hold on
l2 = plot(phi_vec, itd_hartf_front(1).itd_hor_mean*1e6,'Color',kv.col_shad_mod2plus,'LineWidth',line_width);
l3 = plot(phi_vec, (itd_hrtf(1).itd_hor_mean-itd_hartf_front(1).itd_hor_mean)*1e6,'Color',kv.col_mod1,'LineWidth',line_width,'LineStyle','-.');
l4 = plot(phi_vec, itd_hartf_rear(1).itd_hor_mean*1e6,'Color',kv.col_meas,'LineWidth',line_width);
l5 = plot(phi_vec, (itd_hrtf(1).itd_hor_mean-itd_hartf_rear(1).itd_hor_mean)*1e6,'Color',kv.col_shad_mod1,'LineWidth',line_width,'LineStyle',':');
leg = legend([l1,l2,l4,l3,l5,ph],{'HRTF','HARTF (F)','HARTF (R)','Deviation (F)','Deviation (R)','$\sigma$'},'fontsize',font_size-2);
%set(leg,'NumColumns', 2,'ItemTokenSize',[14,18],'Location','southwest','interpreter','latex')
set(leg,'ItemTokenSize',[14,18],'Location','southwest','interpreter','latex')
xlim([0,357.5])
grid on
box on
set(gca,...
'xlim',[phi_vec(1),phi_vec(end)],...
'ylim',[-800,800],...
'xTick', 0:30:360,...
'yTick', -800:200:800,...
'ticklabelinterpreter','latex',...
'fontsize',font_size)
xlabel('Azimuth (deg)','fontsize',font_size+1,'interpreter','latex')
ylabel('ITD ($\mu$s)','fontsize',font_size,'interpreter','latex')
xtickangle(0)
end
%% Figure 8a
% if flags.do_fig8a
% amt_disp([mfilename,': Not yet implemented.'])
% fig_handle = [];
% end
%% Figure 8b
% if flags.do_fig8b
% amt_disp([mfilename,': Not yet implemented.'])
% fig_handle = [];
% end
%% Figure 9
if flags.do_fig9
models = {'kuhn1977','aaronson2014','pausch2022'};
stf = {'hrtf','hartf_front','hartf_rear'};
title_stf = {'HRTF', 'HARTF (F)', 'HARTF (R)'};
num_stf = numel(stf);
num_mod = numel(models);
% load directional datasets and estimate ITDs
data_itd = cell(numel(stf),1);
for idx_stf = 1:numel(stf)
[~,data_itd{idx_stf}] = data_pausch2022(stf{idx_stf});
end
% load individual features
features = data_pausch2022('features');
% extract feature subsets as required per type_stf and type_mod
feature_stf = cell2mat(features(2:end,4:8));
feature_stf(:,:,2) = cell2mat(features(2:end,[4:6,33,34]));
feature_stf(:,:,3) = feature_stf(:,:,2);
feature_mod2_aux = cell2mat( features(2:end,[8,29,30,37]) ); % x5, d9, d10, Theta3
% evaluated azimuth directions
phi_vec = 0:2.5:180;
phi_vec = phi_vec(:);
num_dir = numel(phi_vec);
num_part = size(data_itd{1},2);
% extract modelled broadband ITDs (and max{ITD} and arg max_phi{ITD})
itd_mod = zeros(num_dir,num_part,num_stf,num_mod);
itd_mod_max = zeros(num_part,num_stf,num_mod);
itd_mod_arg_max_phi = itd_mod_max;
for idx_stf=1:num_stf
for idx_part=1:num_part
for idx_mod=1:num_mod
switch idx_mod
case 1 % kuhn
[itd_mod(:,idx_part,idx_stf,idx_mod),...
itd_mod_max(idx_part,idx_stf,idx_mod),...
itd_mod_arg_max_phi(idx_part,idx_stf,idx_mod)] = ...
pausch2022(feature_stf(idx_part,:,idx_stf), ...
models{idx_mod}, ...
stf{idx_stf});
case 2 % woodworth_ext
[itd_mod(:,idx_part,idx_stf,idx_mod),...
itd_mod_max(idx_part,idx_stf,idx_mod),...
itd_mod_arg_max_phi(idx_part,idx_stf,idx_mod)] = ...
pausch2022(feature_stf(idx_part,:,idx_stf), ...
models{idx_mod},...
stf{idx_stf},...
'x5',feature_mod2_aux(idx_part,1),...
'd9',feature_mod2_aux(idx_part,2),...
'd10',feature_mod2_aux(idx_part,3),...
'Theta3',feature_mod2_aux(idx_part,4));
otherwise % pausch
[itd_mod(:,idx_part,idx_stf,idx_mod),...
itd_mod_max(idx_part,idx_stf,idx_mod),...
itd_mod_arg_max_phi(idx_part,idx_stf,idx_mod)] = ...
pausch2022(feature_stf(idx_part,:,idx_stf), ...
models{idx_mod},...
stf{idx_stf});
end
itd_mod(:,idx_part,idx_stf,idx_mod) = itd_mod(:,idx_part,idx_stf,idx_mod)*1e6;
itd_mod_max(idx_part,idx_stf,idx_mod) = itd_mod_max(idx_part,idx_stf,idx_mod)*1e6;
itd_mod_arg_max_phi(idx_part,idx_stf,idx_mod) = phi_vec(itd_mod_arg_max_phi(idx_part,idx_stf,idx_mod));
end
end
end
% extract measured broadband ITDs (and max{ITD} and arg max_phi{ITD})
itd_meas = zeros(num_dir,num_part,num_stf);
itd_meas_max = zeros(num_part,num_stf);
itd_meas_arg_max_phi = itd_meas_max;
for idx_stf=1:num_stf
for idx_part=1:num_part
itd_meas(:,idx_part,idx_stf) = data_itd{idx_stf}(idx_part).itd_hor(1:numel(phi_vec))*1e6;
[itd_meas_max(idx_part,idx_stf), itd_meas_arg_max_phi(idx_part,idx_stf)] = ...
max(itd_meas(:,idx_part,idx_stf));
itd_meas_arg_max_phi(idx_part,idx_stf) = phi_vec(itd_meas_arg_max_phi(idx_part,idx_stf));
end
end
% calculate direction-dependent mean +- std of ITD deviations across participants
delta_itd_mean = squeeze( mean(itd_mod-itd_meas,2) );
delta_itd_std = squeeze( std(itd_mod-itd_meas,0,2) );
% calculate coefficients of the linear regression line fitting modelled to measured ITD maxima
reg_coef = zeros(num_stf,2,num_mod);
for idx_mod = 1:num_mod
for idx_stf = 1:num_stf
temp = fitlm(itd_meas_max(:,idx_stf),itd_mod_max(:,idx_stf,idx_mod),'linear');
reg_coef(idx_stf,:,idx_mod) = temp.Coefficients.Estimate;
end
end
% plot settings
ylabel_meas = 'ITD$_{\textnormal{meas}}$ ($\mu s$)';
xlabel_mod = 'Azimuth (deg)';
ylabel_mod = {'ITD$_{\textnormal{Model\,1}}$ ($\mu s$)',...
'ITD$_{\textnormal{Model\,2+}}$ ($\mu s$)',...
'ITD$_{\textnormal{Model\,3}}$ ($\mu s)$'};
xlabel_itd_max = 'max\{ITD$_{\textnormal{meas}}$\} ($\mu s$)';
ylabel_itd_max = 'max\{ITD$_{\textnormal{mod}}$\} ($\mu s$)';
ylabel_delta_itd_max = '$\Delta$max\{ITD\} ($\mu s$)';
xlabel_delta_arg_max_phi = 'Model';
ylabel_delta_arg_max_phi = '$\Delta$arg\,max\{ITD\} (deg)';
shade_mod = {kv.col_shad_mod1, kv.col_shad_mod2plus, kv.col_shad_mod3};
marker_mod = {'o','x','.'};
marker_size = 10;
fsize = 7.5;
lwidth = 2;
ymin_data = -200;
ymax_data = 850;
ystep_data = 200;
xminax = 500;
xmaxax = 850;
yminax = xminax;
ymaxax = xmaxax;
xstep = 100;
ystep = xstep;
yminbox_ITDmax = -230;
ymaxbox_ITDmax = 136;
yminbox_ITDmaxphi = -20;
ymaxbox_ITDmaxphi = 30;
% horizontal lines denoting significant differences
lineoff = 4.75;
line_HRTF_ITDmaxphi_Delta12.xrange = [1 2];
line_HRTF_ITDmaxphi_Delta12.y = 21.5;
line_HRTF_ITDmaxphi_Delta23.xrange = [2 3];
line_HRTF_ITDmaxphi_Delta23.y = line_HRTF_ITDmaxphi_Delta12.y+0.7*lineoff;
line_rHARTF_ITDmaxphi_Delta23.xrange = [2 3];
line_rHARTF_ITDmaxphi_Delta23.y = line_HRTF_ITDmaxphi_Delta12.y;
% labels a)...d)
xpos_anno1 = -0.45;
ypos_anno1 = 1.05;
% create figure
fig_handle = figure;
set(gcf,'Position',[281,208,427,788])
for idx_tile = 1:18
subplot(6,3,idx_tile)
% itd_meas
if ismember(idx_tile,1:3)
plot(phi_vec,itd_meas(:,:,idx_tile),'color',kv.col_meas)
if idx_tile==1
text(xpos_anno1,ypos_anno1,'$\textbf{a)}$',...
'interpreter','latex','fontsize',fsize,'units','normalized')
ylabel(ylabel_meas,'fontsize',fsize,'interpreter','latex')
end
grid on
hold on
title(title_stf{idx_tile},'interpreter','latex')
set(gca,...
'xlim',[phi_vec(1) phi_vec(end)],...
'ylim',[ymin_data-50,ymax_data],...
'xtick',0:30:180,...
'ytick',ymin_data:ystep_data:ymax_data,...
'ticklabelinterpreter','latex',...
'fontsize',fsize)
axis square
box on
% itd_mod1, itd_mod2plus, ITD deviations
elseif ismember(idx_tile,4:6)
fillarea1 = [delta_itd_mean(:,idx_tile-3,1)+delta_itd_std(:,idx_tile-3,1); ...
flipud(delta_itd_mean(:,idx_tile-3,1)-delta_itd_std(:,idx_tile-3,1))];
fill([phi_vec; flipud(phi_vec)], fillarea1, kv.col_mod1+0.4, 'edgecolor','none');
hold on
fillarea2 = [delta_itd_mean(:,idx_tile-3,2)+delta_itd_std(:,idx_tile-3,2); ...
flipud(delta_itd_mean(:,idx_tile-3,2)-delta_itd_std(:,idx_tile-3,2))];
fill([phi_vec; flipud(phi_vec)], fillarea2, kv.col_mod2plus+0.5, 'edgecolor','none');
plot(phi_vec,delta_itd_mean(:,idx_tile-3,1),'color',kv.col_mod1,'linestyle','-.','linewidth',lwidth/2)
plot(phi_vec,delta_itd_mean(:,idx_tile-3,2),'color',kv.col_mod2plus,'linestyle',':','linewidth',lwidth/2)
plot(phi_vec,itd_mod(:,:,idx_tile-3,1),'color',kv.col_mod1)
plot(phi_vec,itd_mod(:,:,idx_tile-3,2),'color',kv.col_mod2plus)
if idx_tile==4
text(xpos_anno1,ypos_anno1,'$\textbf{b)}$',...
'interpreter','latex','fontsize',fsize,'units','normalized')
ylabel(ylabel_mod{idx_tile-2},'fontsize',fsize,'interpreter','latex')
text(-.49,0.5,ylabel_mod{1},'fontsize',fsize,'interpreter','latex',...
'Rotation',90,'horizontalalignment','center',...
'color',kv.col_mod1,'units','normalized')
end
grid on
set(gca,...
'xlim',[phi_vec(1) phi_vec(end)],...
'ylim',[ymin_data-50,ymax_data],...
'xtick',0:30:180,...
'ytick',ymin_data:ystep_data:ymax_data,...
'ticklabelinterpreter','latex',...
'fontsize',fsize)
axis square
box on
% itd_mod3, ITD deviations
elseif ismember(idx_tile,7:9)
fillarea3 = [delta_itd_mean(:,idx_tile-6,3)+delta_itd_std(:,idx_tile-6,3); ...
flipud(delta_itd_mean(:,idx_tile-6,3)-delta_itd_std(:,idx_tile-6,3))];
fill([phi_vec; flipud(phi_vec)], fillarea3, kv.col_shad_mod3, 'edgecolor','none');
hold on
plot(phi_vec,delta_itd_mean(:,idx_tile-6,3),'color',kv.col_mod3,'linestyle','-.','linewidth',lwidth/2)
plot(phi_vec,itd_mod(:,:,idx_tile-6,3),'color',kv.col_mod3)
if idx_tile==7
text(xpos_anno1,ypos_anno1,'$\textbf{c)}$',...
'interpreter','latex','fontsize',fsize,'units','normalized')
ylabel(ylabel_mod{idx_tile-4},'fontsize',fsize,'interpreter','latex')
end
grid on
set(gca,...
'xlim',[phi_vec(1) phi_vec(end)],...
'ylim',[ymin_data-50,ymax_data],...
'xtick',0:30:180,...
'ytick',ymin_data:ystep_data:ymax_data,...
'ticklabelinterpreter','latex',...
'fontsize',fsize)
xlabel(xlabel_mod,'fontsize',fsize,'interpreter','latex')
axis square
box on
% max{ITD}, scatter plots / regression lines
elseif ismember(idx_tile,10:12)
warning('off','MATLAB:handle_graphics:Layout:NoPositionSetInTiledChartLayout')
plot(linspace(500,xmaxax,num_part),linspace(500,xmaxax,num_part),'linewidth',0.5,'linestyle',':','color','k');
hold on
scatter(itd_meas_max(:,idx_tile-9),itd_mod_max(:,idx_tile-9,1),marker_size,shade_mod{1},marker_mod{1})
scatter(itd_meas_max(:,idx_tile-9),itd_mod_max(:,idx_tile-9,2),marker_size,shade_mod{2},marker_mod{2})
scatter(itd_meas_max(:,idx_tile-9),itd_mod_max(:,idx_tile-9,3),marker_size,shade_mod{3},marker_mod{3})
grid minor
plot(itd_meas_max(:,idx_tile-9),reg_coef(idx_tile-9,2,1)*itd_meas_max(:,idx_tile-9) + ...
reg_coef(idx_tile-9,1,1),'linewidth',lwidth,'color',kv.col_mod1);
plot(itd_meas_max(:,idx_tile-9),reg_coef(idx_tile-9,2,2)*itd_meas_max(:,idx_tile-9) + ...
reg_coef(idx_tile-9,1,2),'linewidth',lwidth,'color',kv.col_mod2plus);
plot(itd_meas_max(:,idx_tile-9),reg_coef(idx_tile-9,2,3)*itd_meas_max(:,idx_tile-9) + ...
reg_coef(idx_tile-9,1,3),'linewidth',lwidth,'color',kv.col_mod3);
if idx_tile==10
text(xpos_anno1,ypos_anno1,'$\textbf{d)}$',...
'interpreter','latex','fontsize',fsize,'units','normalized')
ylabel(ylabel_itd_max,'fontsize',fsize,'interpreter','latex')
end
set(gca,'ticklabelinterpreter','latex','fontsize',fsize,...
'xlim',[xminax xmaxax],'ylim',[yminax ymaxax],...
'xtick',xminax:xstep:xmaxax,'ytick',yminax:ystep:ymaxax)
xtickangle(0)
box on
axis square
xlabel(xlabel_itd_max,'fontsize',fsize,'interpreter','latex')
hA=get(gca);
hA.XAxis.MinorTickValues = xminax:(xstep/2):xmaxax;
hA.XAxis.MinorTick = 'on';
hA.YAxis.MinorTickValues = yminax:(ystep/2):ymaxax;
hA.YAxis.MinorTick = 'on';
hA.MinorGrid = 'on';
% Delta max{ITD}
elseif ismember(idx_tile,13:15)
boxplot([itd_mod_max(:,idx_tile-12,1)-itd_meas_max(:,idx_tile-12), ...
itd_mod_max(:,idx_tile-12,2)-itd_meas_max(:,idx_tile-12), ...
itd_mod_max(:,idx_tile-12,3)-itd_meas_max(:,idx_tile-12)],...
'Notch','on','Labels',{'1','2+','3'},...
'colors',[kv.col_mod1; kv.col_mod2plus; kv.col_mod3])
set(findobj(gca,'type','line'),'linew',1.25)
h=findobj(gca,'tag','Outliers');
set(h(3),'MarkerEdgeColor',kv.col_mod1);
set(h(2),'MarkerEdgeColor',kv.col_mod2plus);
set(h(1),'MarkerEdgeColor',kv.col_mod3);
if idx_tile==13
text(xpos_anno1,ypos_anno1,'$\textbf{e)}$',...
'interpreter','latex','fontsize',fsize,'units','normalized')
ylabel(ylabel_delta_itd_max,'fontsize',fsize,'interpreter','latex')
end
grid on
box on
set(gca,'ticklabelinterpreter','latex',...
'fontsize',fsize,...
'yminorgrid','on',...
'ylim',[yminbox_ITDmax ymaxbox_ITDmax],...
'ytick',-200:50:250)
axis square
% Delta arg_max_phi{ITD}
else
boxplot([itd_mod_arg_max_phi(:,idx_tile-15,1)-itd_meas_arg_max_phi(:,idx_tile-15), ...
itd_mod_arg_max_phi(:,idx_tile-15,2)-itd_meas_arg_max_phi(:,idx_tile-15), ...
itd_mod_arg_max_phi(:,idx_tile-15,3)-itd_meas_arg_max_phi(:,idx_tile-15)],...
'Notch','on','Labels',{'1','2+','3'},...
'colors',[kv.col_mod1; kv.col_mod2plus; kv.col_mod3])
set(findobj(gca,'type','line'),'linew',1.25)
h=findobj(gca,'tag','Outliers');
set(h(3),'MarkerEdgeColor',kv.col_mod1);
set(h(2),'MarkerEdgeColor',kv.col_mod2plus);
set(h(1),'MarkerEdgeColor',kv.col_mod3);
if idx_tile==16
text(xpos_anno1,ypos_anno1,'$\textbf{f)}$',...
'interpreter','latex','fontsize',fsize,'units','normalized')
ylabel(ylabel_delta_arg_max_phi,'fontsize',fsize,'interpreter','latex')
line(line_HRTF_ITDmaxphi_Delta12.xrange,...
[line_HRTF_ITDmaxphi_Delta12.y line_HRTF_ITDmaxphi_Delta12.y],...
'color','k','linewidth',lwidth/2)
text(mean(line_HRTF_ITDmaxphi_Delta12.xrange),...
line_HRTF_ITDmaxphi_Delta12.y+2.5,'n.s.',...
'interpreter','latex',...
'fontsize',fsize,...
'horizontalalignment','center')
line(line_HRTF_ITDmaxphi_Delta23.xrange,...
[line_HRTF_ITDmaxphi_Delta23.y line_HRTF_ITDmaxphi_Delta23.y],...
'color','k','linewidth',lwidth/2)
text(mean(line_HRTF_ITDmaxphi_Delta23.xrange),...
line_HRTF_ITDmaxphi_Delta23.y+2.5,'n.s.',...
'interpreter','latex',...
'fontsize',fsize,...
'horizontalalignment','center')
elseif idx_tile==18
line(line_rHARTF_ITDmaxphi_Delta23.xrange,...
[line_rHARTF_ITDmaxphi_Delta23.y line_rHARTF_ITDmaxphi_Delta23.y],...
'color','k','linewidth',lwidth/2)
text(mean(line_rHARTF_ITDmaxphi_Delta23.xrange),...
line_rHARTF_ITDmaxphi_Delta23.y+2.5,'n.s.',...
'interpreter','latex',...
'fontsize',fsize,...
'horizontalalignment','center')
end
xlabel(xlabel_delta_arg_max_phi,'fontsize',fsize,'interpreter','latex')
grid on
box on
set(gca,'ticklabelinterpreter','latex',...
'fontsize',fsize,...
'ylim',[yminbox_ITDmaxphi ymaxbox_ITDmaxphi],...
'ytick',-40:10:40,...
'yminorgrid','on')
axis square
end
end
end
%% Figure 10
% if flags.do_fig10
% amt_disp([mfilename,': Not yet implemented.'])
% fig_handle = [];
% end
%% Figure 11
% if flags.do_fig11
% amt_disp([mfilename,': Not yet implemented.'])
% fig_handle = [];
% end
%% no_fig
% if flags.do_no_fig
% amt_disp([mfilename,': No figure selected for plotting.'])
% fig_handle = [];
% end