diff --git a/matlab/tfgm/experiments/compute_error_operator_norm.m b/matlab/tfgm/experiments/compute_error_operator_norm.m
deleted file mode 100644
index 38fa51266f2102b46a0cc0295d5efd2e829591f9..0000000000000000000000000000000000000000
--- a/matlab/tfgm/experiments/compute_error_operator_norm.m
+++ /dev/null
@@ -1,25 +0,0 @@
-function [eigs_norm, arrfevdn_norm, rrfevdn_norm]= compute_error_operator_norm(file_name, n_exp)
-
-eigs_norm = zeros(length(file_name), n_exp);
-arrfevdn_norm = zeros(length(file_name), n_exp);
-rrfevdn_norm = zeros(length(file_name), n_exp);
-
-for k=1:n_exp
-
- rep_dir = ['exp',num2str(k)];
-
- for l =1: 3%length(file_name)
- data_folder = dir(fullfile(rep_dir,'*.mat'));
- file = [data_folder(l).folder,filesep, file_name{l}];
-
- upload_file = load(file);
- eigs_norm(l,k) = error_operator_norm(upload_file.mul, upload_file.svd_result_eigs);
- arrfevdn_norm(l,k) = error_operator_norm(upload_file.mul, upload_file.svd_result_nystrom_Qadaptative);
- rrfevdn_norm(l,k) = error_operator_norm(upload_file.mul, upload_file.svd_result_nystrom);
-
- end
-end
-
-
-
-end
\ No newline at end of file
diff --git a/matlab/tfgm/experiments/estimated_rank.m b/matlab/tfgm/experiments/estimated_rank.m
deleted file mode 100644
index c383ae00b2321ff06089ab402ed8e24734f56258..0000000000000000000000000000000000000000
--- a/matlab/tfgm/experiments/estimated_rank.m
+++ /dev/null
@@ -1,20 +0,0 @@
-function q_with = estimated_rank(file_name, n_exp)
-
-
-q_with = zeros(length(file_name), n_exp);
-
-
-for k=1:n_exp
- rep_dir = ['exp',num2str(k)];
-
- for l =1:length(file_name)
- data_folder = dir(fullfile(rep_dir,'*.mat'));
- file = [data_folder(l).folder,filesep, file_name{l}];
- upload_file = load(file);
- q_with(l,k) = size(upload_file.svd_result_eigs.D,1);
-
-
- end
-end
-
-end
\ No newline at end of file
diff --git a/matlab/tfgm/experiments/exp_gabmul_eig_running_times.m b/matlab/tfgm/experiments/exp_gabmul_eig_running_times.m
deleted file mode 100644
index 2d6ae083f7b82380e7ce69390b2304077ab23d9d..0000000000000000000000000000000000000000
--- a/matlab/tfgm/experiments/exp_gabmul_eig_running_times.m
+++ /dev/null
@@ -1,72 +0,0 @@
-clc; clear; close all;
-
-
-%%
-setting='full';
-exp = get_experiment(setting);
-
-%%
-param = exp.data_params;
-t_lim = [exp.problem_params.t_val{1}, exp.problem_params.t_val{2}];
-f_lim = [exp.problem_params.f_val{1}, exp.problem_params.f_val{2}];
-win_type = exp.problem_params.win_type;
-
-t_arrf = zeros(length(param) ,1);
-t_rrf = zeros(length(param) ,1);
-t_arrfevdn = zeros(length(param) ,1);
-t_rrfevdn = zeros(length(param) ,1);
-t_eigs = zeros(length(param) ,1);
-%%
-
-n_runs = 1;%0;
-
-fprintf('je ferai au total %.1f runs\n\n',n_runs);
-%%
-for l=1:n_runs
-
-fprintf("C'est partie pour le %.1f run\n\n",l);
-
-%%
-tic;
-for k = 1:1%length(param)
- k=5;
-
- fprintf('je suis a la %.1f ieme iteration patiente\n',k);
- param_pow = param{k};
- problem_data = get_problem_data(param_pow,t_lim, f_lim, win_type);
-
-
-
-tolerance = exp.solver_params.tolerance;
-r = exp.solver_params.r;
-mask = problem_data.mask;
-dgt_params = problem_data.dgt_params;
-signal_params = problem_data.signal_params;
-
-[gab_mul, direct_stft, adjoint_stft, q_mat_arrf, arrf_time,....,
- q_mat_rrf, rrf_time, svd_res_arrf,arrfevdn_time, svd_res_rrf,....,
- rrfevdn_time, svd_res_eigs, eigs_time, eigs_norm, arrfevdn_norm, ...,
- rrfevdn_norm,q_with] =solver(tolerance, r, mask, dgt_params, signal_params);
-
-
-t_arrf(k) = arrf_time;
-t_rrf(k) = rrf_time;
-t_arrfevdn(k) = arrfevdn_time;
-t_rrfevdn(k) = rrfevdn_time;
-t_eigs(k) = eigs_time;
-
-filename = ['gabmul_eig_dgtvar_', num2str(signal_params.sig_len),'.mat'];
-
-mkdir(['exp_gabmul_eig_running_times_',num2str(l)]);
-warning('off', 'MATLAB:MKDIR:DirectoryExists');
-path_name = ['exp_gabmul_eig_running_times_',num2str(l)];
-
-save(fullfile(path_name,filename),'setting','exp','problem_data', 'q_mat_arrf',....,
- 'arrf_time', 'q_mat_rrf', 'rrf_time', 'svd_res_arrf','arrfevdn_time',...,
- 'svd_res_rrf', 'rrfevdn_time', 'svd_res_eigs', 'eigs_time',...,
- 'eigs_norm','arrfevdn_norm','rrfevdn_norm','q_with','t_arrf','t_rrf','t_arrfevdn',...,
- 't_rrfevdn','t_eigs');
-end
-toc;
-end
-%%
\ No newline at end of file
diff --git a/matlab/tfgm/experiments/get_experiment.m b/matlab/tfgm/experiments/get_experiment.m
deleted file mode 100644
index dbee5307abd08de5d962be005efd7860697b9b13..0000000000000000000000000000000000000000
--- a/matlab/tfgm/experiments/get_experiment.m
+++ /dev/null
@@ -1,42 +0,0 @@
-function exp = get_experiment(setting)
-%create experiment parameter
-
-
-switch setting
- case 'full'
-
- param_pow = {0, 1, 2, 3, 4};
- data_params = param_pow;
-
- case 'light'
-
- param_pow = {0,1,2};
- data_params = param_pow;
- otherwise
-
- error('Unknown setting: ')
-
-end
-
-t_min = 0.3; t_max = 0.5; f_min = 0.1; f_max =0.2;
-t_val = {t_min, t_max};
-f_val={f_min, f_max};
-
-problem_params.win_type = 'hann';
-
-problem_params.t_val = t_val;
-problem_params.f_val = f_val;
-
-tolerance = 1e-6;
-r = 15;
-
-solver_params.tolerance = tolerance;
-solver_params.r = r;
-
-
-exp.data_params=data_params;
-exp.problem_params=problem_params;
-exp.solver_params=solver_params;
-end
-
-
diff --git a/matlab/tfgm/experiments/get_mask_area.m b/matlab/tfgm/experiments/get_mask_area.m
deleted file mode 100644
index f3701b9c08aafee0eb2eb566a6a43c144cd97d7e..0000000000000000000000000000000000000000
--- a/matlab/tfgm/experiments/get_mask_area.m
+++ /dev/null
@@ -1,10 +0,0 @@
-function [mask_area, varargout] = get_mask_area(mask)
-%compute mask area
-
-mask_area = sum(mask(:));
-mask_area_ratio = mask_area/ (size(mask,1)*size(mask,2));
- varargout{1} = mask_area_ratio;
-
-end
-
-
diff --git a/matlab/tfgm/experiments/get_problem_data.m b/matlab/tfgm/experiments/get_problem_data.m
deleted file mode 100644
index a3619c341f8c7b38f889a6c2b51e48e79fd8917d..0000000000000000000000000000000000000000
--- a/matlab/tfgm/experiments/get_problem_data.m
+++ /dev/null
@@ -1,23 +0,0 @@
-function problem_data = get_problem_data(param_pow,t_lim, f_lim, win_type)
-
-% generate problem data for tf filtering
-
-
-sig_len = 256*4^param_pow;
-win_len = 8*2^param_pow;
-hop = 2*2^param_pow;
-nbins = 32*2^param_pow;
-fs=1;
-
-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);
-mask = generate_rectangular_mask(nbins, hop, sig_len, t_lim, f_lim);
-
-problem_data.dgt_params= dgt_params;
-problem_data.signal_params = signal_params;
-problem_data.hop = hop;
-problem_data.mask = mask;
-
-end
\ No newline at end of file
diff --git a/matlab/tfgm/experiments/get_ratio_of_eigs_running_times.m b/matlab/tfgm/experiments/get_ratio_of_eigs_running_times.m
deleted file mode 100644
index 083dd632565c4cb4caec91dc88b0fc5eccc51c34..0000000000000000000000000000000000000000
--- a/matlab/tfgm/experiments/get_ratio_of_eigs_running_times.m
+++ /dev/null
@@ -1,16 +0,0 @@
-function [ratio_arrf_time_over_eigs,ratio_rrf_time_over_eigs,...,
- ratio_evdnarrf_over_eigs,ratio_evdnrrf_over_eigs]= get_ratio_of_eigs_running_times(arrf_time, rrf_time, evdnarrf_time, evdnrrf_time,eigs_time)
-
-
-
-
-
-ratio_arrf_time_over_eigs = arrf_time./eigs_time;
-ratio_rrf_time_over_eigs = rrf_time./eigs_time;
-ratio_evdnarrf_over_eigs = evdnarrf_time./eigs_time;
-ratio_evdnrrf_over_eigs = evdnrrf_time./eigs_time ;
-
-
-
-
-end
\ No newline at end of file
diff --git a/matlab/tfgm/experiments/perf_measures.m b/matlab/tfgm/experiments/perf_measures.m
deleted file mode 100644
index eddb65ba7f3a70fec4beb1d4780542a517a69020..0000000000000000000000000000000000000000
--- a/matlab/tfgm/experiments/perf_measures.m
+++ /dev/null
@@ -1,65 +0,0 @@
-function [arrf_time, rrf_time, eigs_time, evdnrrf_time, evdnarrf_time,...,
- arrf_time_mean, rrf_time_mean, evdnrrf_time_mean, evdnarrf_time_mean,...,
- evdarrrf_mean, evdrrf_mean,eigs_mean, arrf_time_std, rrf_time_std,...,
- evdnrrf_time_std, evdnarrf_time_std, evdarrrf_std, ....,
- evdrrf_std, eigs_std] = perf_measures(file_name, n_exp)
-
-
-
-arrf_time=[];
-rrf_time = [];
-eigs_time = [];
-evdnrrf_time = [];
-evdnarrf_time = [];
-
-
-for k=1:n_exp
-
-upload_file = load(fullfile((['exp',num2str(k)]),file_name{5}));
-
-arrf_time = [arrf_time, upload_file.time_adaptative_Q];
-arrf_time = squeeze(arrf_time);
-
-
-rrf_time = [rrf_time, upload_file.time_randomized_Q];
-rrf_time = squeeze(rrf_time);
-
-eigs_time = [eigs_time, upload_file.time_EVD_eigs];
-eigs_time = squeeze(eigs_time);
-
-evdnrrf_time = [evdnrrf_time, upload_file.time_EVD_nystrom];
-evdnrrf_time = squeeze(evdnrrf_time);
-
-evdnarrf_time = [evdnarrf_time, upload_file.time_EVD_nystrom_Qadapt];
-evdnarrf_time = squeeze(evdnarrf_time);
-
-
-end
-
-% mean
-
-arrf_time_mean = mean(arrf_time,2); % temps moyen adaptative randomized range finder
-rrf_time_mean = mean(rrf_time,2); % temps moyen randomized range finder
-evdnrrf_time_mean = mean(evdnrrf_time,2);
-evdnarrf_time_mean = mean(evdnarrf_time,2);
-
-evdarrrf_mean = mean(arrf_time+ evdnarrf_time,2); % arrf + evd/nystrom
-evdrrf_mean = mean(rrf_time+ evdnrrf_time,2); % rrf +evd/nystom
-eigs_mean = mean(eigs_time,2); % temps moyen eigs
-
-%std
-
-
-arrf_time_std = std(arrf_time, 0,2); % temps moyen adaptative randomized range finder
-rrf_time_std = std(rrf_time, 0, 2); % temps moyen randomized range finder
-evdnrrf_time_std = std(evdnrrf_time,0, 2);
-evdnarrf_time_std = std(evdnarrf_time, 0, 2);
-
-evdarrrf_std = std(arrf_time+ evdnarrf_time, 0,2); % arrf + evd/nystrom
-evdrrf_std = std(rrf_time+ evdnrrf_time, 0, 2); % rrf +evd/nystom
-eigs_std = std(eigs_time,0, 2); % temps moyen eigs
-
-
-
-
-end
\ No newline at end of file
diff --git a/matlab/tfgm/experiments/plot_results.m b/matlab/tfgm/experiments/plot_results.m
deleted file mode 100644
index d07c70299ae499fed939fc118fe2d8d21ee140e7..0000000000000000000000000000000000000000
--- a/matlab/tfgm/experiments/plot_results.m
+++ /dev/null
@@ -1,230 +0,0 @@
-function plot_results()
-
-%%
-
-pwd;
-pathname ='GabMulEigRunTimeExperiment';
-if ~exist('GabMulEigRunTimeExperiment','dir')
- mkdir('GabMulEigRunTimeExperiment');
-end
-addpath('GabMulEigRunTimeExperiment')
-
-%%
-% fichier .mat
-file_name = {'time_halko_vs_eigs256.mat', 'time_halko_vs_eigs1024.mat',...,
- 'time_halko_vs_eigs4096.mat', 'time_halko_vs_eigs16384.mat',....,
- 'time_halko_vs_eigs65536.mat'};
-%%
-mask_area_list = zeros(length(file_name),1);
-mask_area_ratio_list = zeros(length(file_name),1);
-sig_len_list = zeros(length(file_name),1);
-
-for k =1:1
- rep_dir = ['exp',num2str(k)];
-
- for l=1:length(file_name)
-
- figure(l)
- data_folder = dir(fullfile(rep_dir,'*.mat'));
- file = [data_folder(l).folder,filesep, file_name{l}];
-
- upload_file = load(file);
-
- sig_len_list(l) = upload_file.signal_params.sig_len;
-
- % figure mask
- plot_mask(upload_file.mask, upload_file.dgt_params.hop, upload_file.dgt_params.nbins, upload_file.fs);
- axis tight;
- saveas(gcf,fullfile(pathname,['mask_',num2str(upload_file.signal_params.sig_len),'.png']));
-
-
- % figure window
-
- plot_win(upload_file.dgt_params.win, upload_file.fs, upload_file.signal_params.sig_len, upload_file.dgt_params.win_type);
- axis tight;
- saveas(gcf,fullfile(pathname,['win_',num2str(upload_file.signal_params.sig_len),'.png']));
-
-
- % mask area
- mask = 1- upload_file.mask;
-
- [mask_area, mask_area_ratio] = get_mask_area(mask);
- mask_area_list(l) = mask_area;
- mask_area_ratio_list(l) = mask_area_ratio;
- end
-
-end
-%%
-% mask area
-figure;
-plot(sig_len_list, mask_area_list,'LineWidth',2.5);
-grid()
-set(gca,'YScale','log','XScale','log');
-xlabel('Signal length')
-ylabel('# time-frequency coefficients')
-title('Mask area')
-set(gca, 'FontSize', 15, 'fontName','Times');
-saveas(gcf,fullfile(pathname, 'mask_area.pdf'));
-
-% mask area ratio
-
-figure;
-plot(sig_len_list, mask_area_ratio_list,'LineWidth',2.5)
-grid()
-set(gca,'XScale','log');
-
-xlabel('Signal length')
-ylabel('%')
-title('Mask area ratio')
-set(gca, 'FontSize', 15, 'fontName','Times');
-saveas(gcf,fullfile(pathname, 'mask_area_ratio.pdf'));
-
-
-
-
-%% Computation time, mean and std
-n_exp = 10;
-[arrf_time, rrf_time, eigs_time, evdnrrf_time, evdnarrf_time,...,
- arrf_time_mean, rrf_time_mean, evdnrrf_time_mean, evdnarrf_time_mean,...,
- evdarrrf_mean, evdrrf_mean,eigs_mean, arrf_time_std, rrf_time_std,...,
- evdnrrf_time_std, evdnarrf_time_std, evdarrrf_std, ....,
- evdrrf_std, eigs_std] = perf_measures(file_name,n_exp);
-
-
-%% figure;
-% comparaisons temps de calcul des 3 algos
-
-figure;
-errorbar(sig_len_list, evdarrrf_mean, evdarrrf_std,'b-*','LineWidth',2.5); hold on;
-errorbar(sig_len_list, eigs_mean, eigs_std, 'r-*','LineWidth',2.5);
-errorbar(sig_len_list, evdrrf_mean, evdrrf_std,'m-*','LineWidth',2.5 );
-xlabel('signal length');
-ylabel('Computation time (s)')
-legend('Adaptative Range Finder + EVD/Nystr�m', 'eigs','Fixed Range Finder + EVD/Nystr�m',...,
- 'Location','northwest')
-set(gca, 'FontSize', 15, 'fontName','Times');
-set(gca,'YScale','log','XScale','log');
-grid('on');
-axis tight;
-saveas(gcf,fullfile(pathname,['running_times','.png']));
-%%
-% comparaisons temps de calcul de tous les algos
-figure;
-
-errorbar(sig_len_list, arrf_time_mean, arrf_time_std,'LineWidth',2.5); hold on;
-errorbar(sig_len_list, rrf_time_mean, rrf_time_std,'LineWidth',2.5);
-errorbar(sig_len_list, eigs_mean, eigs_std, 'LineWidth',2.5);
-errorbar(sig_len_list, evdnarrf_time_mean, evdnarrf_time_std, 'LineWidth',2.5);
-errorbar(sig_len_list, evdnrrf_time_mean, evdnrrf_time_std, 'LineWidth',2.5);
-
-legend('Adaptative Range Finder','Fixed Range Finder','eigs',...,
- 'EVD/Nystr�m(ARRF)','EVD/Nystr�m(RRF)','Location','northwest')
-set(gca, 'FontSize', 15, 'fontName','Times');
-set(gca,'YScale','log','XScale','log');
-grid('on');
-axis tight;
-xlabel('Signal length')
-ylabel('Running time (s)')
-saveas(gcf,fullfile(pathname,['running_times_by_step','.png']));
-
-%% Step by step: ratio of eigs running times (pas juste a revoir)
-% ratio
-
-
-[ratio_arrf_time_over_eigs,ratio_rrf_time_over_eigs,...,
- ratio_evdnarrf_over_eigs,ratio_evdnrrf_over_eigs]= get_ratio_of_eigs_running_times(arrf_time, rrf_time, evdnarrf_time, evdnrrf_time,eigs_time);
-
-
-
-%mean ratio
-ratio_arrf_time_over_eigs_mean = mean(ratio_arrf_time_over_eigs,2)*100;
-ratio_rrf_time_over_eigs_mean = mean(ratio_rrf_time_over_eigs,2)*100;
-ratio_evdnarrf_over_eigs_mean = mean(ratio_evdnarrf_over_eigs, 2)*100;
-ratio_evdnrrf_over_eigs_mean = mean(ratio_evdnrrf_over_eigs, 2)*100;
-
-
-% std
-
-ratio_arrf_time_over_eigs_std = std(ratio_arrf_time_over_eigs,0,2)*100;
-ratio_rrf_time_over_eigs_std = std(ratio_rrf_time_over_eigs,0,2)*100;
-ratio_evdnarrf_over_eigs_std = std(ratio_evdnarrf_over_eigs, 0,2)*100;
-ratio_evdnrrf_over_eigs_std = std(ratio_evdnrrf_over_eigs, 0,2)*100;
-
-
-figure;
-errorbar(sig_len_list, ratio_arrf_time_over_eigs_mean, ratio_arrf_time_over_eigs_std,'LineWidth',2.5); hold on;
-errorbar(sig_len_list, ratio_rrf_time_over_eigs_mean, ratio_rrf_time_over_eigs_std,'LineWidth',2.5);
-errorbar(sig_len_list, ratio_evdnarrf_over_eigs_mean, ratio_evdnarrf_over_eigs_std, 'LineWidth',2.5);
-errorbar(sig_len_list, ratio_evdnrrf_over_eigs_mean, ratio_evdnrrf_over_eigs_std, 'LineWidth',2.5);
-
-legend('Adaptative Range Finder','Fixed Range Finder',...,
- 'EVD/Nystr�m(ARRF)','EVD/Nystr�m(RRF)','Location','northwest')
-set(gca, 'FontSize', 15, 'fontName','Times');
-set(gca,'XScale','log');
-grid('on');
-axis tight;
-xlabel('Signal length')
-ylabel('Ratio of eigs running time (%)')
-saveas(gcf,fullfile(pathname,['running_times_ratio_by_step','.png']));
-
-%% error operator norm (erreur a revoir)
-
-[eigs_norm, arrfevdn_norm, rrfevdn_norm]= compute_error_operator_norm(file_name, n_exp);
-eigs_norm_mean = mean(eigs_norm,2);
-arrfevdn_norm_mean = mean(arrfevdn_norm,2);
-rrfevdn_norm_mean = mean(rrfevdn_norm, 2);
-
-
-eigs_norm_std = std(eigs_norm,0,2);
-arrfevdn_norm_std = std(arrfevdn_norm, 0, 2);
-rrfevdn_norm_std = std(rrfevdn_norm, 0, 2);
-
-figure;
-errorbar(sig_len_list, eigs_norm_mean , eigs_norm_std,'LineWidth',2.5); hold on;
-errorbar(sig_len_list, arrfevdn_norm_mean, arrfevdn_norm_std,'LineWidth',2.5);
-errorbar(sig_len_list, rrfevdn_norm_mean, rrfevdn_norm_std, 'LineWidth',2.5);
-
-legend('eigs','Adaptative Range Finder + EVD/Nystr�m(ARRF)',...,
- 'Fixed Range Finder + EVD/Nystr�m(RRF)','Location','northwest')
-set(gca, 'FontSize', 15, 'fontName','Times');
-set(gca,'YScale','log','XScale','log');
-grid('on');
-axis tight;
-xlabel('Signal length')
-ylabel('Operator estimation error')
-saveas(gcf,fullfile(pathname, 'operator_error.pdf'));
-
-%% Estimated rank
-
-q_with = estimated_rank(file_name, n_exp);
-q_with_mean = mean(q_with, 2);
-q_with_std = std(q_with, 0, 2);
-
-figure;
-errorbar(sig_len_list, q_with_mean, q_with_std,'LineWidth',2)
-set(gca, 'FontSize', 15, 'fontName','Times');
-set(gca, 'YScale','log','XScale','log')
-xlabel('Signal length')
-ylabel('Estimated rank')
-grid('on');
-legend('Estimated rank','Location','northwest');
-saveas(gcf,fullfile(pathname,'rank_estimation.pdf'));
-
-
-%% Estimated rank / sig length
-rank_ratio = q_with./sig_len_list;
-rank_ratio_mean = mean(rank_ratio,2)*100;
-rank_ratio_std = std(rank_ratio_mean,0,2)*100;
-
-figure;
-errorbar(sig_len_list, rank_ratio_mean, rank_ratio_std,'LineWidth',2)
-set(gca, 'FontSize', 15, 'fontName','Times');
-set(gca,'XScale','log')
-xlabel('Signal length')
-ylabel('Estimated rank / signal length')
-grid('on');
-legend('Estimated rank');
-saveas(gcf,fullfile(pathname,'rank_estimation_over_siglen.pdf'));
-
-
-end
\ No newline at end of file
diff --git a/matlab/tfgm/experiments/solver.m b/matlab/tfgm/experiments/solver.m
deleted file mode 100644
index 98e0894c91037af90ff06f1060408f43284232fd..0000000000000000000000000000000000000000
--- a/matlab/tfgm/experiments/solver.m
+++ /dev/null
@@ -1,43 +0,0 @@
-function [gab_mul, direct_stft, adjoint_stft, q_mat_arrf, arrf_time,....,
- q_mat_rrf, rrf_time, svd_res_arrf,arrfevdn_time, svd_res_rrf,....,
- rrfevdn_time, svd_res_eigs, eigs_time, eigs_norm, arrfevdn_norm, ...,
- rrfevdn_norm,q_with] =solver(tolerance, r, mask, dgt_params, signal_params)
-
-[direct_stft, adjoint_stft] = get_stft_operators(dgt_params, signal_params);
-gab_mul = gen_gabmul_operator(direct_stft, adjoint_stft, mask);
-
-
-tic;
-q_mat_arrf = adaptative_randomized_range_finder(gab_mul ,signal_params.sig_len, tolerance, r);
-arrf_time = toc;
-
-
-tic;
-q_mat_rrf = randomized_range_finder(gab_mul, signal_params.sig_len, size(q_mat_arrf,2));
-rrf_time = toc;
-
-
-tic;
-svd_res_arrf = EVD_nystrom(gab_mul, q_mat_arrf);
-arrfevdn_time= toc;
-
-tic;
-svd_res_rrf = EVD_nystrom(gab_mul, q_mat_rrf);
-rrfevdn_time= toc;
-
-
-tic;
-svd_res_eigs = EVD_eigs(gab_mul, signal_params.sig_len, size(q_mat_arrf,2) );
-eigs_time = toc;
-
-
-
-eigs_norm = error_operator_norm(gab_mul, svd_res_eigs);
-arrfevdn_norm = error_operator_norm(gab_mul, svd_res_arrf);
-rrfevdn_norm = error_operator_norm(gab_mul, svd_res_rrf);
-
-
-q_with = size(q_mat_arrf,2);
-
-
-end
\ No newline at end of file
diff --git a/matlab/tfgm/experiments/step_mask.m b/matlab/tfgm/experiments/step_mask.m
deleted file mode 100644
index df1cd14b19370a935bc097e29c92d6a229a2ac7d..0000000000000000000000000000000000000000
--- a/matlab/tfgm/experiments/step_mask.m
+++ /dev/null
@@ -1,84 +0,0 @@
-clc ; clear; close all;
-%%
-
-pwd;
-pathname ='figures_JSTSP';
-if ~exist('figures_JSTSP','dir')
- mkdir('figures_JSTSP');
-end
-addpath('figures_JSTSP')
-
-%%
-ind_loc = 5;
-ind_wd = 3;
-deb_ind_loc = 0;
-deb_ind_wd=0;
-resampling_fs = 8000;
-sig_len = 16384;
-%%
-
-
-param_gauss = get_win_gauss_param();
-
-
-win_len = param_gauss.win_len;
-win_type = param_gauss.win_type;
-alpha = param_gauss.alpha;
-seuil = param_gauss.seuil;
-radius = param_gauss.radius;
-
-%%
-sig_loc = load_localized_signal(ind_loc, resampling_fs, sig_len, deb_ind_loc);
-sig_wd = load_wideband_signal(ind_wd, resampling_fs, sig_len, deb_ind_wd);
-
-signals = generate_mix_signal(sig_wd, sig_loc);
-
-fs = resampling_fs;
-sig_len = length(sig_loc);
-signal_params = generate_signal_parameters(fs, sig_len);
-
-%% dgt
-dgt_params = generate_dgt_parameters(win_type, win_len);
-dgt_params.hop = 32; %
-dgt_params.nbins = 512;%
-[dgt, idgt] = get_stft_operators(dgt_params, signal_params);
-
-
- tf_mat_wb = compute_dgt(signals.target, dgt );
- tf_mat_loc = compute_dgt(signals.noise, dgt );
-
-
-%% Etape 1
-figure;
-subplot(131)
-set(gcf,'position',[1, 1, 1000 400]);
-mask = and(abs(tf_mat_wb)<alpha*abs(tf_mat_loc), abs(tf_mat_loc)>seuil);
-%figure('name','mask');
-plot_spectrogram(mask, dgt_params,signal_params, dgt );
-axis square;
-set(gca, 'FontSize', 20, 'fontName','Times');
-%saveas(gcf,fullfile(pathname, 'mask_cuicui_gauss_1.png'));
-
-
-%Etape 2
-
-se = strel('disk',radius);
-
-mask = imclose(mask,se);
-%figure('name','mask');
-subplot(132)
-plot_spectrogram(mask, dgt_params,signal_params, dgt );
-set(gca, 'FontSize', 20, 'fontName','Times');
-axis square;
-%saveas(gcf,fullfile(pathname, 'mask_cuicui_gauss_2.png'));
-
-
-subplot(133)
-mask = imopen(mask,se);
-%figure('name','mask');
-plot_spectrogram(mask, dgt_params,signal_params, dgt );
-set(gca, 'FontSize', 20, 'fontName','Times');
-axis square;
-%saveas(gcf,fullfile(pathname, 'mask_cuicui_gauss_3.png'));
-saveas(gcf,fullfile(pathname, 'mask_step.png'));
-
diff --git a/matlab/tfgm/experiments/test_gen_gabmul_operator.m b/matlab/tfgm/experiments/test_gen_gabmul_operator.m
deleted file mode 100644
index b3db5fa33e76f7d581ad5c34dd59b63d89ca954d..0000000000000000000000000000000000000000
--- a/matlab/tfgm/experiments/test_gen_gabmul_operator.m
+++ /dev/null
@@ -1,27 +0,0 @@
-clc; clear; close all;
-%%
-setting='full';
-exp = get_experiment(setting);
-param = exp.data_params;
-t_lim = [exp.problem_params.t_val{1}, exp.problem_params.t_val{2}];
-f_lim = [exp.problem_params.f_val{1}, exp.problem_params.f_val{2}];
-win_type = exp.problem_params.win_type;
-
-%%
-param_pow = param{4};
- problem_data = get_problem_data(param_pow,t_lim, f_lim, win_type);
-
- %%
- dgt_params = problem_data.dgt_params;
-signal_params = problem_data.signal_params;
-mask = problem_data.mask;
-[direct_stft, adjoint_stft] = get_stft_operators(dgt_params, signal_params);
-gab_mul = gen_gabmul_operator(direct_stft, adjoint_stft, mask);
-
-%%
-figure; imagesc(mask)
-x = randn(signal_params.sig_len,1);
-A = gab_mul(x);
-figure; plot(x);
-figure; plot(A);
-figure; sgram(A,'dynrange',90)
diff --git a/matlab/tfgm/experiments/test_get_problem_data.m b/matlab/tfgm/experiments/test_get_problem_data.m
deleted file mode 100644
index eb97a828cd04200b11ee15c0326f53cd37e0ca2a..0000000000000000000000000000000000000000
--- a/matlab/tfgm/experiments/test_get_problem_data.m
+++ /dev/null
@@ -1,22 +0,0 @@
-clc; close all;
-
-%%
-setting='full';
-exp = get_experiment(setting);
-
-%%
-param = exp.data_params;
-t_lim = [exp.problem_params.t_val{1}, exp.problem_params.t_val{2}];
-f_lim = [exp.problem_params.f_val{1}, exp.problem_params.f_val{2}];
-win_type = exp.problem_params.win_type;
-
-%%
-figure;
-for k = 1:length(param)
- param_pow = param{k};
- problem_data = get_problem_data(param_pow,t_lim, f_lim, win_type);
-
- figure(k);
- plot_mask(problem_data.mask, problem_data.hop, problem_data.dgt_params.nbins, problem_data.signal_params.fs)
-
-end
\ No newline at end of file