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| 1 | +function demo_gui(set,user_path,varargin) |
| 2 | +%DEMO_GUI executes the processes: segmentation, labelling, classification |
| 3 | +%and produces the results |
| 4 | + |
| 5 | + %%Global Options |
| 6 | + seg_overlap = [0.7,0.9]; |
| 7 | + seg_length = 250; |
| 8 | + if ~isempty(varargin) |
| 9 | + if varargin{1} == -1 |
| 10 | + seg_overlap = 0.7; |
| 11 | + end |
| 12 | + end |
| 13 | + |
| 14 | + |
| 15 | + user_path = char_project_path(user_path); |
| 16 | + h = waitbar(0,'Initializing...'); |
| 17 | + |
| 18 | + %% Create project folder tree (set_folder.m) |
| 19 | + if set == 1 |
| 20 | + error = build_folder_tree(user_path, 'demo_original_set_1'); |
| 21 | + elseif set == 2 |
| 22 | + error = build_folder_tree(user_path, 'demo_original_set_2'); |
| 23 | + end |
| 24 | + if error |
| 25 | + return |
| 26 | + end |
| 27 | + project_path = fullfile(user_path,'demo_original_set_1'); |
| 28 | + waitbar(1/2); |
| 29 | + |
| 30 | + %% Copy the settings mat files (skip gui_project.m) |
| 31 | + if isdeployed |
| 32 | + if set == 1 |
| 33 | + datapath = fullfile(ctfroot,'import','original_data_1_settings'); |
| 34 | + elseif set == 2 |
| 35 | + datapath = fullfile(ctfroot,'import','original_data_2_settings'); |
| 36 | + end |
| 37 | + else |
| 38 | + if set == 1 |
| 39 | + datapath = fullfile(pwd,'import','original_data_1_settings'); |
| 40 | + elseif set == 2 |
| 41 | + datapath = fullfile(pwd,'import','original_data_2_settings'); |
| 42 | + end |
| 43 | + end |
| 44 | + files = dir(fullfile(datapath,'*.mat')); |
| 45 | + for i = 1:length(files) |
| 46 | + copyfile(fullfile(datapath,files(i).name),fullfile(project_path,'settings')); |
| 47 | + end |
| 48 | + ptags = fullfile(datapath,'tags.txt'); |
| 49 | + copyfile(ptags,fullfile(project_path,'settings')); |
| 50 | + waitbar(2/2); |
| 51 | + delete(h); |
| 52 | + |
| 53 | + %% Segmentation |
| 54 | + try |
| 55 | + load(fullfile(project_path,'settings','new_properties.mat')); |
| 56 | + load(fullfile(project_path,'settings','animal_groups.mat')); |
| 57 | + load(fullfile(project_path,'settings','my_trajectories.mat')); |
| 58 | + catch |
| 59 | + errordlg('Cannot load project settings','Error'); |
| 60 | + return |
| 61 | + end |
| 62 | + |
| 63 | + for i = 1:length(seg_overlap) |
| 64 | + seg_properties = [seg_length,seg_overlap(i)]; |
| 65 | + segmentation_configs = config_segments(new_properties, seg_properties, trajectory_groups, my_trajectories); |
| 66 | + save_segmentation(segmentation_configs, project_path); |
| 67 | + end |
| 68 | + |
| 69 | + %% Labelling |
| 70 | + files = {'labels_1301_250_07-tiago.csv','labels_1657_250_09-tiago.csv'}; |
| 71 | + seg_name = {'segmentation_configs_10388_250_07.mat','segmentation_configs_29476_250_09.mat'}; |
| 72 | + for i = 1:length(seg_overlap) |
| 73 | + %check if everything is ok |
| 74 | + if ~exist(fullfile(datapath,files{i}),'file') || ~exist(fullfile(project_path,'segmentation',seg_name{i}),'file') |
| 75 | + errordlg('Cannot create labels files','Error'); |
| 76 | + return |
| 77 | + end |
| 78 | + %copy the csv files from the datapath |
| 79 | + labels_path = fullfile(datapath,files{i}); |
| 80 | + copyfile(labels_path,fullfile(project_path,'labels')); |
| 81 | + %the labels are now inside the project path |
| 82 | + labels_path = fullfile(project_path,'labels',files{i}); |
| 83 | + %load the segmentation and generate the labels mat file |
| 84 | + load(fullfile(project_path,'segmentation',seg_name{i})); |
| 85 | + generate_mat_from_labels(labels_path,segmentation_configs); |
| 86 | + clear segmentation_configs |
| 87 | + end |
| 88 | + |
| 89 | + %% Classification |
| 90 | + lab_name = {'labels_1301_250_07-tiago.mat','labels_1657_250_09-tiago.mat'}; |
| 91 | + for i = 1:length(seg_overlap) |
| 92 | + %check if everything is ok |
| 93 | + if ~exist(fullfile(project_path,'labels',lab_name{i}),'file') |
| 94 | + errordlg('Cannot create classifiers','Error'); |
| 95 | + return |
| 96 | + end |
| 97 | + default_classification(project_path,seg_name{i},lab_name{i}); |
| 98 | + end |
| 99 | + |
| 100 | + %% Results |
| 101 | + groups = [1,2]; |
| 102 | + load(fullfile(project_path,'segmentation',seg_name{1})); |
| 103 | + [exit, animals_trajectories_map] = trajectories_map(segmentation_configs,groups,'Friedman',set); |
| 104 | + |
| 105 | + % METRICS |
| 106 | + str = num2str(groups); |
| 107 | + str = regexprep(str,'[^\w'']',''); %remove gaps |
| 108 | + str = strcat('group',str); |
| 109 | + output_dir = fullfile(project_path,'results','metrics',str); |
| 110 | + if ~exist(output_dir,'dir') |
| 111 | + mkdir(output_dir); |
| 112 | + end |
| 113 | + try |
| 114 | + results_latency_speed_length(segmentation_configs,animals_trajectories_map,1,output_dir); |
| 115 | + catch |
| 116 | + errordlg('Error: metrics generation','Error'); |
| 117 | + end |
| 118 | + |
| 119 | + % STRATEGIES - TRANSITIONS - PROBABILITIES - STATISTICS |
| 120 | + b_pressed = {'Strategies','Transitions','Probabilities'}; |
| 121 | + class = {'class_1301_10388_250_07_10_10_mr0-tiago','class_1657_29476_250_09_10_10_mr0-tiago'}; |
| 122 | + |
| 123 | + for j = 1:length(seg_overlap) |
| 124 | + |
| 125 | + % Check if everything is ok |
| 126 | + if ~exist(fullfile(project_path,'Mclassification',class{j}),'file') |
| 127 | + errordlg('Check fail for results: strategies, transitions and probabilities','Error'); |
| 128 | + return |
| 129 | + end |
| 130 | + |
| 131 | + % Statistics |
| 132 | + [error,~,~] = class_statistics(project_path, class{j}); |
| 133 | + if error |
| 134 | + errordlg('Error: statistics generation','Error'); |
| 135 | + end |
| 136 | + |
| 137 | + % Check the classification |
| 138 | + [error,name,classifications] = check_classification(project_path,segmentation_configs,class{j}); |
| 139 | + if error |
| 140 | + errordlg('Classification check failed','Error'); |
| 141 | + return |
| 142 | + end |
| 143 | + |
| 144 | + % Generate the results |
| 145 | + for i = 1:length(b_pressed) |
| 146 | + error = generate_results(project_path, name, segmentation_configs, classifications, animals_trajectories_map, b_pressed{i}, groups); |
| 147 | + if error |
| 148 | + errordlg('Cannot create results for strategies, transitions and probabilities','Error'); |
| 149 | + return |
| 150 | + end |
| 151 | + end |
| 152 | + end |
| 153 | + |
| 154 | + %% Labelling Quality |
| 155 | + files = {'labels_1301_250_07-tiago.mat','labels_1657_250_09-tiago.mat'}; |
| 156 | + for i = 1:length(seg_name) |
| 157 | + load(fullfile(project_path,'segmentation',seg_name{i})); |
| 158 | + load(fullfile(project_path,'labels',files{i})); |
| 159 | + |
| 160 | + p = strsplit(files{i},'.mat'); |
| 161 | + p = p{1}; |
| 162 | + output_path = char(fullfile(project_path,'labels',strcat(p,'_check'))); |
| 163 | + if ~exist(output_path,'dir') |
| 164 | + mkdir(output_path); |
| 165 | + end |
| 166 | + [nc,res1bare,res2bare,res1,res2,res3,covering] = results_clustering_parameters(segmentation_configs,labels,0,output_path,10,100,1); |
| 167 | + output_path = char(fullfile(project_path,'results',strcat(p,'_cross_validation'))); |
| 168 | + if exist(output_path,'dir'); |
| 169 | + rmdir(output_path,'s'); |
| 170 | + end |
| 171 | + mkdir(output_path); |
| 172 | + [nc,per_errors1,per_undefined1,coverage] = algorithm_statistics(1,1,nc,res1bare,res2bare,res1,res2,res3,covering); |
| 173 | + data = [nc', per_errors1', per_undefined1', coverage']; |
| 174 | + % export results to CSV file |
| 175 | + export_num_of_clusters(output_path,data); |
| 176 | + % generate graphs |
| 177 | + results_clustering_parameters_graphs(output_path,nc,res1bare,res2bare,res1,res2,res3,covering); |
| 178 | + end |
| 179 | +end |
| 180 | + |
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