diff --git a/matlab/tfgm/scripts/combmul_norm.m b/matlab/tfgm/scripts/combmul_norm.m
deleted file mode 100644
index ae352b7a3acd91bc4d0965c3e321c0a128f600b7..0000000000000000000000000000000000000000
--- a/matlab/tfgm/scripts/combmul_norm.m
+++ /dev/null
@@ -1,145 +0,0 @@
-function mul1mul2_norms = combmul_norm(areas_lim, t_shifts, f_shifts, win_type)
-%This fonction computes the operator norm of the combination
-%of two Gabor multipliers
-% Inputs:
-% - areas_lim: real number array
-% - t_shifts, f_shifts: real number array
-% - win_type: analysis windox type
-% Outputs:
-% - mul1mul2_norms:operators norms of two Gabor multiplier
-%
-% Author: Marina KREME
-%%
-
-
-pwd;
-fig_dir ='combinaisonMult';
-if ~exist('combinaisonMult','dir')
- mkdir('combinaisonMult');
-end
-addpath('combinaisonMult')
-%%
-
-sig_len = 1024;
-fs = 1;
-win_len = 64;
-hop = 1 ;
-nbins = win_len * 2;
-
-
-dgt_params = generate_dgt_parameters(win_type, win_len, hop, nbins, sig_len);
-signal_params = generate_signal_parameters(fs, sig_len);
-
-
-%% plot window
-figure;
-plot_win(dgt_params.win, signal_params.fs, signal_params.sig_len, dgt_params.win_type);
-title([num2str(win_type),'\_window.png'])
-saveas(gcf,fullfile(fig_dir,[num2str(win_type),'_window_L' num2str(sig_len), '.png']));
-
-
-%% Generate rectangular mask
-
-mask1 = generate_rectangular_mask(dgt_params.('nbins'), dgt_params.('hop'),....,
- signal_params.('sig_len'), areas_lim.('t_lim'), areas_lim.('f_lim'));
-
-[dgt, idgt]= get_stft_operators(dgt_params, signal_params);
-
-mul1 = gen_gabmul_operator(dgt, idgt, mask1);
-
-mul1mul2_norms = zeros(length(f_shifts),length(t_shifts));
-
-%%
-for i_t = 1:length(t_shifts)
- dt = t_shifts(i_t);
- for i_f = 1: length(f_shifts)
- df = f_shifts(i_f);
- mask2= generate_rectangular_mask(dgt_params.nbins, dgt_params.hop,....,
- signal_params.sig_len, areas_lim.('t_lim')+dt, areas_lim.('f_lim')+df);
-
- full_mask = or(mask1, mask2);
-
- mul2 = gen_gabmul_operator(dgt, idgt, mask2);
-
- ev = eigs(@(x)mul1(mul2(x)), signal_params.sig_len, 1);
-
- mul1mul2_norms(i_f, i_t) = real(ev);
-
-
- figure;
-
-
- subplot(121)
-
- plot_mask(full_mask, dgt_params.hop, dgt_params.nbins, signal_params.fs);
- title({['Mask ' num2str(win_type) ],['dt = ' num2str(dt)],['df =',num2str(df)],['norm = ' num2str(mul1mul2_norms(i_f, i_t),'%.2e')]});
-
- subplot(122)
- mask_proj = dgt(idgt(double(full_mask)));
- plot_spectrogram(mask_proj, dgt_params, signal_params, dgt);
-
- title('dgt(idgt(mask))')
- saveas(gcf,fullfile(fig_dir,['mask_' num2str(win_type) 'dt_' num2str(dt) 'df_',num2str(df),'.png']));
-
- end
-end
-
-
-
-
-%%
-figure;
-step_t = t_shifts(2) - t_shifts(1);
-step_f = f_shifts(2) - f_shifts(1);
-extent = [t_shifts(1)-step_t/2, t_shifts(end)+step_t/2, f_shifts(1)-step_f/2, f_shifts(end)+step_f/2];
-imagesc(real(log10(mul1mul2_norms)),'XData', extent(1:2), 'YData', extent(3:4),'CDataMapping','scaled');
-colorbar()
-xlabel('t shift')
-ylabel('f shift')
-title(win_type)
-saveas(gcf,fullfile(fig_dir,['mul1mul2_norms_' num2str(win_type), '.png']));
-
-
-%%
-figure;
-
-for i=1: length(t_shifts)
-
- txt = ['dt =' num2str(t_shifts(i))];
- semilogy(f_shifts, mul1mul2_norms(:, i), 'LineWidth',2.5,'DisplayName',txt);
- hold on
-
- xlabel('f shift')
- title(win_type)
- grid('on');
- set(gca, 'FontSize', 15, 'fontName','Times');
- axis tight;
- saveas(gcf,fullfile(fig_dir,['mul1mul2_norms_' num2str(win_type), '_f.png']));
-end
-legend show;
-
-
-%%
-figure;
-for i=1: length(f_shifts)
-
- txt = ['df =' num2str(f_shifts(i))];
- plot(t_shifts, mul1mul2_norms(i, :),'LineWidth',2.5 ,'DisplayName',txt);
-
- hold on;
-
- xlabel('t shift')
- title(win_type)
- grid('on');
- set(gca, 'FontSize', 15, 'fontName','Times');
-
- set(gca, 'YScale','log');
- axis tight;
- saveas(gcf,fullfile(fig_dir,['mul1mul2_norms_' num2str(win_type), '_t.png']));
-
-end
-hold off
-legend show;
-
-
-end
diff --git a/matlab/tfgm/scripts/compare_win.m b/matlab/tfgm/scripts/compare_win.m
deleted file mode 100644
index 471a6db26f43837b23dfa4e49b024831449cf789..0000000000000000000000000000000000000000
--- a/matlab/tfgm/scripts/compare_win.m
+++ /dev/null
@@ -1,93 +0,0 @@
- clc; clear; close all;
-%%
-%Comparison of hann vs gauss window size
-
-%%
-
-pwd;
-fig_dir ='fig_compare_win';
-if ~exist('fig_compare_win','dir')
- mkdir('fig_compare_win');
-end
-addpath('fig_compare_win')
-
-%%
-
-win_list = {{'gauss',128}, {'hann',128}, {'hann',256}};
-
-sig_len = 16384;
-fs = 8000;
-
-
-dgt_params= struct();
-
-for k=1:length(win_list)
- win_type = win_list{k}{1};
- win_len = win_list{k}{2};
- hop = win_len/4;
- nbins = win_len * 4;
- dgt_params.([win_type, num2str(win_len)]) = generate_dgt_parameters(win_type, win_len, hop, nbins, sig_len);
-
-end
-%%
-signal_params = generate_signal_parameters(fs, sig_len);
-
-% %%
-%
-figure;
-%set(gcf,'position',[1, 1 1100 400]);
-subplot(221)
-h = cell(3,1);
-for k=1:length(win_list)
-
- win_type = win_list{k}{1};
- win_len = win_list{k}{2};
- win = dgt_params.([win_type, num2str(win_len)]).win;
-
- plot_win(win, signal_params.fs, sig_len, win_type);
- h{k} = [num2str(win_type), ' - ',num2str(win_len)];
- hold on;
-end
-xlim([-win_len / fs, win_len / fs]);
-legend (h)
-hold off
-
-
-%%
-
-dynrange=10;
-for k=1:length(win_list)
-
- subplot(2,2,k+1)
- win_type = win_list{k}{1};
- win_len = win_list{k}{2};
-
-
- [dgt, idgt] = get_stft_operators( dgt_params.([win_type, num2str(win_len)]), signal_params);
-
- M = dgt_params.([win_type, num2str(win_len)]).nbins/2+1;
- N = sig_len/dgt_params.([win_type, num2str(win_len)]).hop;
-
-
- mask = zeros(M,N);
- gab_mul = gen_gabmul_operator(dgt, idgt, mask);
-
- plot_ambiguity_function(dgt_params.([win_type, num2str(win_len)]).win,...,
- dgt ,dgt_params.([win_type, num2str(win_len)]), signal_params,dynrange);
- hold on;
-
-
- title([num2str(win_type),' - ' num2str(win_len)])
- ylim([0, 90])
-
-end
-
-subplot(2, 2, 2)
-xlim([1.005, 1.045])
-subplot(2, 2, 3)
-xlim([0.015, 0.055])
-subplot(2, 2, 4)
-xlim([0.045, 0.085])
-saveas(gcf,fullfile(fig_dir, 'compare_win_ambig_functions.pdf'));
-
-
diff --git a/matlab/tfgm/scripts/gabmul_eig_dgtvar.m b/matlab/tfgm/scripts/gabmul_eig_dgtvar.m
deleted file mode 100644
index e37c5bccd3a10be686ff7b309e831454f50ff994..0000000000000000000000000000000000000000
--- a/matlab/tfgm/scripts/gabmul_eig_dgtvar.m
+++ /dev/null
@@ -1,151 +0,0 @@
-
-clc; clear; close all
-
-%%
-%Study and comparison of EVD computation times obtained by random vs.
-%eigs projection methods
-%%
-param_list = cell(4,1);
-for i =0:4
- sig_len = 256*4^i;
- win_len = 8*2^i;
- hop = 2*2^i;
- nbins = 32*2^i;
-
- param_list{i+1}= struct('sig_len',sig_len,'win_len',win_len,'hop',hop,'nbins',nbins);
-
-end
-fprintf("Parameters: \n");
-disp(param_list{1});
-fprintf("**************\n");
-disp(param_list{2});
-fprintf("**************\n");
-disp(param_list{3});
-fprintf("**************\n");
-disp(param_list{4});
-
-
-%%
-areas_lim = struct('t_lim', [0.3, 0.7], 'f_lim', [0.1, 0.3]);
-win_type = 'hann';
-fs=1;
-
-
-%% random eigs
-tolerance = 1e-2;
-proba = 1-1e-4;
-
-%%
-% figure directory
-
-pwd;
-fig_dir ='gabmul_eig_dgtvar';
-if ~exist('gabmul_eig_dgtvar','dir')
- mkdir('gabmul_eig_dgtvar');
-end
-addpath('gabmul_eig_dgtvar')
-
-% initialisations
-
-t_arrf = zeros(length(param_list),1);
-t_rrf = zeros(length(param_list),1);
-t_evdn = zeros(length(param_list),1);
-t_eigs = zeros(length(param_list),1);
-ranks = zeros(length(param_list),1);
-
-%%
-for i = 1: length(param_list)-1
- %%
-
- sig_len = param_list{i}.('sig_len');
- fs=1;
-
- win_len = param_list{i}.('win_len');
- hop = param_list{i}.('hop');
- nbins = param_list{i}.('nbins');
- fprintf("****************************************\n");
- fprintf("Signal length: %.f\n", sig_len);
-
- %% dgt params, signals prams,plot window
-
- dgt_params = generate_dgt_parameters(win_type, win_len, hop, nbins, sig_len);
- signal_params = generate_signal_parameters(fs, sig_len);
-
- % figures
- % window
- figure;
- plot_win(dgt_params.win, signal_params.fs, dgt_params.win_type);
- title([num2str(win_type),'_window.png'])
- saveas(gcf,fullfile(fig_dir,[num2str(win_type),'_window_L' num2str(sig_len), '.png']));
-
-
-
- %% mask, gabor multiplier
- % mask
-
- mask = generate_rectangular_mask(dgt_params.('nbins'), dgt_params.('hop'),....,
- signal_params.('sig_len'),areas_lim.('t_lim'), areas_lim.('f_lim'));
-
-
-
-
- %%
- [dgt, idgt] = get_stft_operators(dgt_params, signal_params);
- gab_mul = gen_gabmul_operator(dgt, idgt, mask);
-
- % figure mask
- figure;
- plot_mask(mask, dgt_params.hop, dgt_params.nbins, signal_params.fs);
- title('Mask')
- saveas(gcf,fullfile(fig_dir,['mask_L_' num2str(sig_len), '.png']));
-
- %% ambiguity function
-
- figure;
- dynrange=90;
- plot_ambiguity_function(dgt_params.win, dgt, dgt_params, signal_params, dynrange)
- title(['Ambiguity function - ', num2str(win_type)]);
- saveas(gcf,fullfile(fig_dir,[ num2str(win_type) '_ambiguity_L_' num2str(sig_len), '.png']));
-
-
-
- %% evd parameters
- r = compute_r(sig_len, sig_len, proba);
- %% compute evd
- tic;
- Q = adaptative_randomized_range_finder(gab_mul, sig_len, tolerance, r);
- t_arrf(i) =toc;
-
- tic;
- Q_ = randomized_range_finder(gab_mul, sig_len, size(Q,2));
- t_rrf(i) = toc;
-
- tic;
- res_evdn = EVD_nystrom(gab_mul, Q);
- t_evdn(i) = toc;
-
- tic;
- res_eigs = EVD_eigs(gab_mul, sig_len, size(Q,2));
- t_eigs(i) = toc;
-
- %% set ranks
- ranks(i) = size(Q,2);
- %% print
-
- fprintf('adaptive_randomized_range_finder: %.2f secondes\n',t_arrf(i));
- fprintf('randomized_range_finder: %.2f secondes\n', t_rrf(i));
-
- fprintf('evd_nystrom: %.2f secondes\n',t_evdn(i));
- fprintf('adaptive_randomized_range_finder+evd_nystrom: %.2f secondes\n ',....,
- t_arrf(i)+t_evdn(i));
- fprintf('randomized_range_finder+evd_nystrom: %.2f secondes\n', t_rrf(i)+t_evdn(i));
- fprintf('eigs: %.2f\n',t_eigs(i));
- fprintf('rank: %.2f\n',ranks(i));
-
-
-
-end
-
-save('gabmul_eig_dgtvar.mat', 't_arrf','t_rrf','t_evdn','t_eigs','ranks','param_list');
-
-
diff --git a/matlab/tfgm/scripts/poc_gabmul_randsvd.m b/matlab/tfgm/scripts/poc_gabmul_randsvd.m
deleted file mode 100644
index 79cd0792cc21758005904f8f05a1c9a3b4253be8..0000000000000000000000000000000000000000
--- a/matlab/tfgm/scripts/poc_gabmul_randsvd.m
+++ /dev/null
@@ -1,96 +0,0 @@
-
-clc; clear; close all;
-%%
-
-pwd;
-fig_dir ='fig_poc_gabmul_randsvd';
-if ~exist('fig_poc_gabmul_randsvd','dir')
- mkdir('fig_poc_gabmul_randsvd');
-end
-addpath('fig_poc_gabmul_randsvd')
-
-%%
-
-areas_lim = struct('t_lim',[0.1, 0.15], 'f_lim',[0.2, 0.25]);
-win_type = 'hann';
-
-sig_len = 8192;
-fs = 1;
-win_len = 512;
-hop = 32 ;
-nbins = win_len * 4;
-
-dgt_params = generate_dgt_parameters(win_type, win_len, hop, nbins, sig_len);
-%%
-
-signal_params = generate_signal_parameters(fs, sig_len);
-[dgt, idgt] = get_stft_operators(dgt_params, signal_params);
-
-%% window
-figure;
-plot_win(dgt_params.win, signal_params.fs, signal_params.sig_len, dgt_params.win_type);
-title([num2str(win_type),'\_window.png'])
-
-%% mask -gabmul
-
-
-mask = generate_rectangular_mask(dgt_params.nbins, dgt_params.hop,....,
- signal_params.sig_len,areas_lim.t_lim, areas_lim.f_lim);
-
-gab_mul = gen_gabmul_operator(dgt, idgt, mask);
-fprintf('Gabor multiplier with shape (%.f %.f) \n', signal_params.sig_len,signal_params.sig_len );
-%% figure mask
-figure;
-plot_mask(mask, dgt_params.hop, dgt_params.nbins, signal_params.fs);
-title('Mask')
-saveas(gcf,fullfile(fig_dir,['mask' num2str(sig_len), '.png']));
-
-%% ambiguity function
-figure;
-dynrange=90;
-
-
-plot_ambiguity_function(dgt_params.win, dgt, dgt_params,signal_params, dynrange);
-title(['Ambiguity function - ', num2str(win_type)]);
-saveas(gcf,fullfile(fig_dir,[ num2str(win_type) '_ambiguity_L_' num2str(sig_len), '.png']));
-
-
-%% evd parameters
-proba = 0.99;
-tolerance =1e-3;
-r = compute_r(sig_len, sig_len, proba);
-%% compute evd
-tic;
-Q = adaptative_randomized_range_finder(gab_mul, sig_len, tolerance, r);
-t_arrf =toc;
-
-tic;
-Q_ = randomized_range_finder(gab_mul, sig_len, size(Q,2));
-t_rrf = toc;
-
-tic;
-res_evdn = EVD_nystrom(gab_mul, Q);
-t_evdn = toc;
-
-tic;
-res_eigs = EVD_eigs(gab_mul, sig_len, size(Q,2));
-t_eigs = toc;
-
-
-%%
-fprintf('adaptive_randomized_range_finder: %.2f secondes\n',t_arrf);
-fprintf('randomized_range_finder: %.2f secondes\n', t_rrf);
-
-fprintf('evd_nystrom: %.2f secondes\n',t_evdn);
-fprintf('adaptive_randomized_range_finder + evd_nystrom: %.2f secondes\n ',....,
- t_arrf+t_evdn);
-fprintf('randomized_range_finder + evd_nystrom: %.2f secondes\n', t_rrf+t_evdn);
-fprintf('eigs: %.2f secondes\n',t_eigs);
-%%
-figure;
-semilogy(diag(res_evdn.D));
-grid('on');
-title('Rand SVD: eigenvalues');
-saveas(gcf,fullfile(fig_dir,['eigenvalues_' num2str(win_type), '.png']));
-
-
diff --git a/matlab/tfgm/scripts/run_combmul.m b/matlab/tfgm/scripts/run_combmul.m
deleted file mode 100644
index b3eb8f7f6bc397892f0705950641f013b034d85a..0000000000000000000000000000000000000000
--- a/matlab/tfgm/scripts/run_combmul.m
+++ /dev/null
@@ -1,20 +0,0 @@
-clc; clear; close all;
-
-%% test of spectral norm of the combination of two multipliers.
-
-t_shifts = 0:0.1:0.7;
-f_shifts = 0: 0.1:0.6;
-
-
-areas_lim = struct('t_lim', [0.1, 0.2], 'f_lim', [0.2, 0.3]);
-win_type = {'hann','gauss'};
-
-%%
-for i = 1:length(win_type)
- %%
-
-res = combmul_norm(areas_lim, t_shifts, f_shifts, win_type{i});
-
-
-end
-
diff --git a/matlab/tfgm/scripts/run_show_rect_masks.m b/matlab/tfgm/scripts/run_show_rect_masks.m
deleted file mode 100644
index 7817e3e1e3c0121e82f338f59d0b0a8d520e4c4f..0000000000000000000000000000000000000000
--- a/matlab/tfgm/scripts/run_show_rect_masks.m
+++ /dev/null
@@ -1,21 +0,0 @@
-clc; clear; close all;
-
-%%
-areas_lim1 = {struct('t_lim', [0.1, 0.5], 'f_lim', [0.2, 0.3])};
-areas_lim2 = {struct('t_lim', [0.1, 0.5], 'f_lim', [0.2, 0.3]),...,
- struct('t_lim', [0.4, 0.8], 'f_lim', [0.5, 0.7])};
-
-
-%%
-
-win_type = {'hann','gauss'};
-
-for i =1 : length(win_type)
- %%
- masks1 = show_rect_masks(areas_lim1, win_type{i});
- masks2 = show_rect_masks(areas_lim2, win_type{i});
- %%
-end
-
-
-
diff --git a/matlab/tfgm/scripts/script_wins.m b/matlab/tfgm/scripts/script_wins.m
deleted file mode 100644
index 57d4c3035b75e20d0aa8579f6439ec0d53bd666c..0000000000000000000000000000000000000000
--- a/matlab/tfgm/scripts/script_wins.m
+++ /dev/null
@@ -1,49 +0,0 @@
-clc; clear; close all;
-
-%%
-
-sig_len = 16384;
-fs = 8000;
-signal_params = generate_signal_parameters(fs, sig_len);
-
-settings = {struct('win_type','gauss','approx_win_len',128,'nbins',128*4,'hop',...,
- 128/4,'sig_len',sig_len), struct('win_type','gauss','approx_win_len',256,'nbins',256*4,'hop',...,
- 256/4,'sig_len',sig_len), struct('win_type','gauss','approx_win_len',512,'nbins',512*4,'hop',...,
- 512/4,'sig_len',sig_len),struct('win_type','hann','approx_win_len',256,'nbins',128*2,'hop',...,
- 128/8,'sig_len',sig_len), struct('win_type','hann','approx_win_len',512,'nbins',256*2,'hop',...,
- 256/8,'sig_len',sig_len), struct('win_type','hann','approx_win_len',1024,'nbins',512*2,'hop',...,
- 512/8,'sig_len',sig_len)};
-%
-%%
-
-for k =1:length(settings)
-
- params = settings{k};
-
- dgt_params = generate_dgt_parameters(params.win_type, params.approx_win_len,...,
- params.hop, params.nbins, sig_len);
-
- [dgt, idgt] = get_stft_operators(dgt_params, signal_params);
-
- m = zeros(params.nbins/2+1, sig_len/params.hop);
- g = gen_gabmul_operator(dgt, idgt, m);
-
- figure;
- dynrange=30;
- plot_ambiguity_function(dgt_params.win, dgt , dgt_params, signal_params, dynrange)
-
- dx = 0.1;
- switch params.win_type
- case 'gauss'
-
- xlim([1 - dx, 1 + dx])
- case 'hann'
- xlim([0.1 - dx, 0.1 + dx])
- end
- ylim([0, 100])
- title([params.win_type, params.approx_win_len, num2str(std(dgt_params.win)) {} {}'])
-
-end
-
-
-
diff --git a/matlab/tfgm/scripts/show_rect_masks.m b/matlab/tfgm/scripts/show_rect_masks.m
deleted file mode 100644
index aae4518945847940f874033a792a0c1e10d977dc..0000000000000000000000000000000000000000
--- a/matlab/tfgm/scripts/show_rect_masks.m
+++ /dev/null
@@ -1,93 +0,0 @@
-function masks = show_rect_masks(areas_lim, win_type)
-%%
-% masks = show_rect_masks(areas_lim, win_type)
-% Generate rectangular mask and compute its ambiguity function
-%
-%Inputs:
-% - areas_lim: array- allow to select the rectangle
-% - win_type: analysis window type (hann/gauss)
-%Output:
-% - masks: mask
-%
-%Author : Marina KREME
-%%
-
-pwd;
-fig_dir ='fig_rect_masks';
-if ~exist('fig_rect_masks','dir')
- mkdir('fig_rect_masks');
-end
-addpath('fig_rect_masks')
-
-%%
-sig_len = 1024;
-fs = 1;
-win_len = 32;
-hop = 1 ;
-nbins = win_len * 2;
-
-
-approx_win_len = win_len;
-dgt_params = generate_dgt_parameters(win_type, approx_win_len, hop, nbins, sig_len);
-signal_params = generate_signal_parameters(fs, sig_len);
-
-
-[dgt, idgt] = get_stft_operators(dgt_params, signal_params);
-
-
-% window
-figure;
-plot_win(dgt_params.win, signal_params.fs, dgt_params.win_type);
-title([num2str(win_type),'\_window.png']);
-
-%
-n_areas = length(areas_lim);
-
-if n_areas == 1
- name = '1area';
-else
- name = [num2str(n_areas), '_areas'];
-
-end
-masks = [];
-for i =1: n_areas
-
-
- mask = generate_rectangular_mask(dgt_params.nbins, dgt_params.hop,....,
- signal_params.sig_len,areas_lim{i}.t_lim, areas_lim{i}.f_lim);
-
- masks =[masks, mask];
-
-end
-%%
-full_mask = masks;
-for i =1:n_areas
- full_mask = or(full_mask,masks(i));
-end
-
-gab_mul = gen_gabmul_operator(dgt, idgt, full_mask);
-
-% figure mask
-figure;
-plot_mask(masks, dgt_params.hop, dgt_params.nbins, signal_params.fs);
-title('Mask')
-saveas(gcf,fullfile(fig_dir,['mask' num2str(sig_len), '.png']));
-
-% ambiguity function
-figure;
-dynrange=90;
-
-plot_ambiguity_function(dgt_params.win,dgt, dgt_params, signal_params, dynrange)
-title(['Ambiguity function - ', num2str(win_type)]);
-saveas(gcf,fullfile(fig_dir,[ num2str(win_type) '_ambiguity_L_' num2str(sig_len), '.png']));
-
-%
-figure;
-mask_proj = dgt(idgt(double(full_mask)));
-plotdgtreal(mask_proj, dgt_params.hop, dgt_params.nbins, fs, dynrange);
-title(['dgt(idgt(mask)) - ' num2str(win_type)]);
-saveas(gcf,fullfile(fig_dir,[num2str(name) '_' num2str(win_type) '_' 'projected_mask.png.png']));
-
-
-
-end
\ No newline at end of file