Cleaning up and adding AU training - WIP

.gitignore

@@ -26,3 +26,4 @@ matlab_runners/Action Unit Experiments/out_SEMAINE/
 *.ipch
 exe/FeatureExtraction/out_bp4d/
 x64/Debug/
+matlab_runners/Action Unit Experiments/out_unbc/

exe/FeatureExtraction/FeatureExtraction.cpp

@@ -688,7 +688,7 @@ int main (int argc, char **argv)
 		{
 			
 			// If the video is long enough post-process it for AUs
-			if (output_AUs && frame_count > 100)
+			if (output_AUs && frame_count > 1000)
 			{
 				cout << "Postprocessing the Action Unit predictions" << endl;
 

lib/local/FaceAnalyser/include/FaceAnalyser.h

@@ -118,6 +118,11 @@ public:
 	std::vector<std::string> GetAUClassNames() const; // Presence
 	std::vector<std::string> GetAURegNames() const; // Intensity
 
+	// Identify if models are static or dynamic (useful for correction and shifting)
+	std::vector<bool> GetDynamicAUClass() const; // Presence
+	std::vector<bool> GetDynamicAUReg() const; // Intensity
+
+
 	void ExtractAllPredictionsOfflineReg(vector<std::pair<std::string, vector<double>>>& au_predictions, vector<double>& confidences, vector<bool>& successes, vector<double>& timestamps);
 	void ExtractAllPredictionsOfflineClass(vector<std::pair<std::string, vector<double>>>& au_predictions, vector<double>& confidences, vector<bool>& successes, vector<double>& timestamps);
 

lib/local/FaceAnalyser/src/FaceAnalyser.cpp

@@ -168,6 +168,42 @@ std::vector<std::string> FaceAnalyser::GetAURegNames() const
 	return au_reg_names_all;
 }
 
+std::vector<bool> FaceAnalyser::GetDynamicAUClass() const
+{
+	std::vector<bool> au_dynamic_class;
+	std::vector<std::string> au_class_names_stat = AU_SVM_static_appearance_lin.GetAUNames();
+	std::vector<std::string> au_class_names_dyn = AU_SVM_dynamic_appearance_lin.GetAUNames();
+
+	for (size_t i = 0; i < au_class_names_stat.size(); ++i)
+	{
+		au_dynamic_class.push_back(false);
+	}
+	for (size_t i = 0; i < au_class_names_dyn.size(); ++i)
+	{
+		au_dynamic_class.push_back(true);
+	}
+
+	return au_dynamic_class;
+}
+
+std::vector<bool> FaceAnalyser::GetDynamicAUReg() const
+{
+	std::vector<bool> au_dynamic_reg;
+	std::vector<std::string> au_reg_names_stat = AU_SVR_static_appearance_lin_regressors.GetAUNames();
+	std::vector<std::string> au_reg_names_dyn = AU_SVR_dynamic_appearance_lin_regressors.GetAUNames();
+
+	for (size_t i = 0; i < au_reg_names_stat.size(); ++i)
+	{
+		au_dynamic_reg.push_back(false);
+	}
+	for (size_t i = 0; i < au_reg_names_dyn.size(); ++i)
+	{
+		au_dynamic_reg.push_back(true);
+	}
+
+	return au_dynamic_reg;
+}
+
 cv::Mat_<int> FaceAnalyser::GetTriangulation()
 {
 	return triangulation.clone();
@@ -569,6 +605,7 @@ void FaceAnalyser::ExtractAllPredictionsOfflineReg(vector<std::pair<std::string,
 	confidences = this->confidences;
 	successes = this->valid_preds;
 
+	// TODO only if the video is long enough or there is enough range? Compare stdev of BP4D and this
 	for(auto au_iter = AU_predictions_reg_all_hist.begin(); au_iter != AU_predictions_reg_all_hist.end(); ++au_iter)
 	{
 		vector<double> au_good;
@@ -599,9 +636,10 @@ void FaceAnalyser::ExtractAllPredictionsOfflineReg(vector<std::pair<std::string,
 		aus_valid.push_back(au_good);
 	}
 
-	// sort each of the aus
+	// sort each of the aus and adjust the dynamic ones
 	for(size_t au = 0; au < au_predictions.size(); ++au)
 	{
+
 		for(size_t frame = 0; frame < au_predictions[au].second.size(); ++frame)
 		{
 

lib/local/FaceAnalyser/src/SVM_dynamic_lin.cpp

@@ -75,7 +75,7 @@ void SVM_dynamic_lin::Read(std::ifstream& stream, const std::vector<std::string>
 		LandmarkDetector::ReadMatBin(stream, m_tmp);
 		if(cv::norm(m_tmp - this->means > 0.00001))
 		{
-			cout << "Something went wrong with the SVR dynamic regressors" << endl;
+			cout << "Something went wrong with the SVM dynamic classifiers" << endl;
 		}
 	}
 

lib/local/FaceAnalyser/src/SVM_static_lin.cpp

@@ -75,7 +75,7 @@ void SVM_static_lin::Read(std::ifstream& stream, const std::vector<std::string>&
 		LandmarkDetector::ReadMatBin(stream, m_tmp);
 		if(cv::norm(m_tmp - this->means > 0.00001))
 		{
-			cout << "Something went wrong with the SVR dynamic regressors" << endl;
+			cout << "Something went wrong with the SVM static classifiers" << endl;
 		}
 	}
 

lib/local/FaceAnalyser/src/SVR_static_lin_regressors.cpp

@@ -75,7 +75,7 @@ void SVR_static_lin_regressors::Read(std::ifstream& stream, const std::vector<st
 		LandmarkDetector::ReadMatBin(stream, m_tmp);
 		if(cv::norm(m_tmp - this->means > 0.00001))
 		{
-			cout << "Something went wrong with the SVR dynamic regressors" << endl;
+			cout << "Something went wrong with the SVR static regressors" << endl;
 		}
 	}
 

matlab_runners/Action Unit Experiments/BP4D_valid_res_class.txt

@@ -1,6 +1,16 @@
-AU6 intensity, Precision - 0.182, Recall - 0.050, F1 - 0.079
+AU1 class, Precision - 0.296, Recall - 0.637, F1 - 0.404
-AU10 intensity, Precision - 0.200, Recall - 0.058, F1 - 0.090
+AU2 class, Precision - 0.189, Recall - 0.875, F1 - 0.311
-AU12 intensity, Precision - 0.361, Recall - 0.081, F1 - 0.132
+AU4 class, Precision - 0.372, Recall - 0.533, F1 - 0.438
-AU12 class, Precision - 0.494, Recall - 0.551, F1 - 0.521
+AU6 intensity, Precision - 0.843, Recall - 0.730, F1 - 0.782
-AU14 intensity, Precision - 0.098, Recall - 0.059, F1 - 0.074
+AU6 class, Precision - 0.812, Recall - 0.735, F1 - 0.772
-AU17 intensity, Precision - 0.358, Recall - 0.048, F1 - 0.085
+AU7 class, Precision - 0.767, Recall - 0.695, F1 - 0.730
+AU10 intensity, Precision - 0.864, Recall - 0.761, F1 - 0.809
+AU10 class, Precision - 0.867, Recall - 0.843, F1 - 0.855
+AU12 intensity, Precision - 0.920, Recall - 0.775, F1 - 0.841
+AU12 class, Precision - 0.878, Recall - 0.862, F1 - 0.870
+AU14 intensity, Precision - 0.620, Recall - 0.700, F1 - 0.658
+AU14 class, Precision - 0.635, Recall - 0.660, F1 - 0.647
+AU15 class, Precision - 0.369, Recall - 0.556, F1 - 0.444
+AU17 intensity, Precision - 0.554, Recall - 0.689, F1 - 0.614
+AU17 class, Precision - 0.515, Recall - 0.802, F1 - 0.627
+AU23 class, Precision - 0.445, Recall - 0.450, F1 - 0.447

matlab_runners/Action Unit Experiments/BP4D_valid_res_int.txt

@@ -1,5 +1,5 @@
-AU6 results - corr 0.548, ccc - 0.319
+AU6 results - corr 0.774, ccc - 0.744
-AU10 results - corr 0.415, ccc - 0.216
+AU10 results - corr 0.716, ccc - 0.681
-AU12 results - corr 0.495, ccc - 0.297
+AU12 results - corr 0.736, ccc - 0.686
-AU14 results - corr 0.241, ccc - 0.122
+AU14 results - corr 0.466, ccc - 0.451
-AU17 results - corr 0.456, ccc - 0.253
+AU17 results - corr 0.477, ccc - 0.448

matlab_runners/Action Unit Experiments/SEMAINE_valid_res.txt

@@ -1,7 +1,6 @@
-AU2 intensity, Precision - 0.454, Recall - 0.462, F1 - 0.458
+AU2 class, Precision - 0.489, Recall - 0.536, F1 - 0.511
-AU12 intensity, Precision - 0.510, Recall - 0.393, F1 - 0.444
+AU12 class, Precision - 0.521, Recall - 0.751, F1 - 0.615
-AU12 class, Precision - 0.406, Recall - 0.828, F1 - 0.545
+AU17 class, Precision - 0.408, Recall - 0.486, F1 - 0.444
-AU17 intensity, Precision - 0.394, Recall - 0.392, F1 - 0.393
+AU25 class, Precision - 0.410, Recall - 0.542, F1 - 0.467
-AU25 intensity, Precision - 0.342, Recall - 0.768, F1 - 0.473
+AU28 class, Precision - 0.493, Recall - 0.398, F1 - 0.441
-AU28 class, Precision - 0.613, Recall - 0.500, F1 - 0.551
+AU45 class, Precision - 0.223, Recall - 0.723, F1 - 0.341
-AU45 class, Precision - 0.300, Recall - 0.636, F1 - 0.408

matlab_runners/Action Unit Experiments/UNBC_valid_res_class.txt

@@ -0,0 +1,6 @@
+AU6 class, Precision - 0.277, Recall - 0.464, F1 - 0.347
+AU7 class, Precision - 0.189, Recall - 0.495, F1 - 0.274
+AU10 class, Precision - 0.143, Recall - 0.322, F1 - 0.198
+AU12 class, Precision - 0.306, Recall - 0.939, F1 - 0.462
+AU25 class, Precision - 0.073, Recall - 0.251, F1 - 0.112
+AU26 class, Precision - 0.052, Recall - 0.730, F1 - 0.096

matlab_runners/Action Unit Experiments/extract_UNBC_labels.m

@@ -0,0 +1,70 @@
+function [ labels, valid_ids, filenames  ] = extract_UNBC_labels( UNBC_dir, recs, aus )
+%EXTRACT_SEMAINE_LABELS Summary of this function goes here
+%   Detailed explanation goes here
+    
+    UNBC_dir = [UNBC_dir, '/Frame_Labels/FACS/'];
+
+    aus_UNBC = [4, 6, 7, 9, 10, 12, 20, 25, 26, 43];
+    
+    inds_to_use = [];
+    
+    for i=1:numel(aus)
+    
+        inds_to_use = cat(1, inds_to_use, find(aus_UNBC == aus(i)));
+        
+    end
+    aus_UNBC = aus_UNBC(inds_to_use);
+    labels_all = {};
+    valid_ids_all = {};
+    filenames_all = {};
+    
+    for i=1:numel(recs)
+
+        % get all the dirs, etc.
+        
+        sessions = dir([UNBC_dir, recs{i}]);
+        sessions = sessions(3:end);
+        
+        num_sessions = numel(sessions);
+        
+        labels = cell(num_sessions, 1);
+        valid_ids = cell(num_sessions, 1);
+        filenames = cell(num_sessions, 1);
+
+        for s=1:numel(sessions)
+
+            frames = dir([UNBC_dir, '/', recs{i}, '/', sessions(s).name, '/*.txt']);
+
+            labels_c = zeros(numel(frames), numel(aus));
+            
+            for f=1:numel(frames)
+
+                file = [UNBC_dir, '/', recs{i}, '/', sessions(s).name, '/', frames(f).name];
+
+                fileID = fopen(file);                
+                C = textscan(fileID,'%d %d %d %d\n');
+                fclose(fileID); 
+                
+%                 OCC = csvread(file); %import annotations for one video file
+                for au = 1:numel(C{1})                    
+                    labels_c(f, aus_UNBC == C{1}(au)) = C{2}(au);
+                end
+                
+            end 
+            labels{s} = labels_c;
+            filenames(s) = {sessions(s).name};
+            valid_ids{s} = true(size(labels_c,1),1);
+        end
+        
+        
+        labels_all = cat(1, labels_all, labels);
+        valid_ids_all = cat(1, valid_ids_all, valid_ids);
+        filenames_all = cat(1, filenames_all, filenames);
+
+    end
+    
+    labels = labels_all;
+    valid_ids = valid_ids_all;
+    filenames = filenames_all;
+end
+

matlab_runners/Action Unit Experiments/helpers/extract_UNBC_labels.m

@@ -0,0 +1,70 @@
+function [ labels, valid_ids, filenames  ] = extract_UNBC_labels( UNBC_dir, recs, aus )
+%EXTRACT_SEMAINE_LABELS Summary of this function goes here
+%   Detailed explanation goes here
+    
+    UNBC_dir = [UNBC_dir, '/Frame_Labels/FACS/'];
+
+    aus_UNBC = [4, 6, 7, 9, 10, 12, 20, 25, 26, 43];
+    
+    inds_to_use = [];
+    
+    for i=1:numel(aus)
+    
+        inds_to_use = cat(1, inds_to_use, find(aus_UNBC == aus(i)));
+        
+    end
+    aus_UNBC = aus_UNBC(inds_to_use);
+    labels_all = {};
+    valid_ids_all = {};
+    filenames_all = {};
+    
+    for i=1:numel(recs)
+
+        % get all the dirs, etc.
+        
+        sessions = dir([UNBC_dir, recs{i}]);
+        sessions = sessions(3:end);
+        
+        num_sessions = numel(sessions);
+        
+        labels = cell(num_sessions, 1);
+        valid_ids = cell(num_sessions, 1);
+        filenames = cell(num_sessions, 1);
+
+        for s=1:numel(sessions)
+
+            frames = dir([UNBC_dir, '/', recs{i}, '/', sessions(s).name, '/*.txt']);
+
+            labels_c = zeros(numel(frames), numel(aus));
+            
+            for f=1:numel(frames)
+
+                file = [UNBC_dir, '/', recs{i}, '/', sessions(s).name, '/', frames(f).name];
+
+                fileID = fopen(file);                
+                C = textscan(fileID,'%d %d %d %d\n');
+                fclose(fileID); 
+                
+%                 OCC = csvread(file); %import annotations for one video file
+                for au = 1:numel(C{1})                    
+                    labels_c(f, aus_UNBC == C{1}(au)) = C{2}(au);
+                end
+                
+            end 
+            labels{s} = labels_c;
+            filenames(s) = {sessions(s).name};
+            valid_ids{s} = true(size(labels_c,1),1);
+        end
+        
+        
+        labels_all = cat(1, labels_all, labels);
+        valid_ids_all = cat(1, valid_ids_all, valid_ids);
+        filenames_all = cat(1, filenames_all, filenames);
+
+    end
+    
+    labels = labels_all;
+    valid_ids = valid_ids_all;
+    filenames = filenames_all;
+end
+

matlab_runners/Action Unit Experiments/helpers/find_UNBC.m

@@ -0,0 +1,17 @@
+if(exist('D:\Datasets\UNBC/', 'file'))
+    UNBC_dir = 'D:\Datasets\UNBC/';   
+    hog_data_dir = 'D:\Datasets\face_datasets\hog_aligned_rigid';
+else
+    fprintf('UNBC location not found (or not defined)\n'); 
+end
+
+all_recs = {'042-ll042', '043-jh043', '047-jl047', '048-aa048', '049-bm049',...
+            '052-dr052', '059-fn059', '064-ak064', '066-mg066', '080-bn080',...
+            '092-ch092', '095-tv095', '096-bg096', '097-gf097', '101-mg101',...
+            '103-jk103', '106-nm106', '107-hs107', '108-th108', '109-ib109',...
+            '115-jy115', '120-kz120', '121-vw121', '123-jh123', '124-dn124'};
+        
+devel_recs = all_recs(1:5:25);
+train_recs = setdiff(all_recs, devel_recs);
+
+all_aus = [4, 6, 7, 9, 10, 12, 20, 25, 26, 43];

matlab_runners/Action Unit Experiments/run_AU_prediction_BP4D.asv

@@ -1,226 +0,0 @@
-clear
-
-bp4d_loc = 'D:/Datasets/FERA_2015/BP4D/BP4D-training/';
-
-out_loc = './out_bp4d/';
-
-if(~exist(out_loc, 'dir'))
-    mkdir(out_loc);
-end
-
-%%
-executable = '"../../x64/Release/FeatureExtraction.exe"';
-
-bp4d_dirs = {'F002', 'F004', 'F006', 'F008', 'F010', 'F012', 'F014', 'F016', 'F018', 'F020', 'F022', 'M002', 'M004', 'M006', 'M008', 'M010', 'M012', 'M014', 'M016', 'M018'};
-
-parfor f1=1:numel(bp4d_dirs)
-
-    if(isdir([bp4d_loc, bp4d_dirs{f1}]))
-        
-        bp4d_2_dirs = dir([bp4d_loc, bp4d_dirs{f1}]);
-        bp4d_2_dirs = bp4d_2_dirs(3:end);
-        
-        f1_dir = bp4d_dirs{f1};
-
-        command = [executable ' -asvid -q -no2Dfp -no3Dfp -noMparams -noPose -noGaze '];
-
-        for f2=1:numel(bp4d_2_dirs)
-            f2_dir = bp4d_2_dirs(f2).name;
-            if(isdir([bp4d_loc, bp4d_dirs{f1}]))
-                
-                curr_vid = [bp4d_loc, f1_dir, '/', f2_dir, '/'];
-
-                name = [f1_dir '_' f2_dir];
-                output_file = [out_loc name '.au.txt'];
-                
-                command = cat(2, command, [' -fdir "' curr_vid '" -of "' output_file '"']);
-            end
-        end
-        
-        dos(command);
-    end
-end
-
-%%
-addpath('./helpers/');
-
-find_BP4D;
-
-aus_BP4D = [1, 2, 4, 6, 7, 10, 12, 14, 15, 17, 23];
-
-[ labels_gt, valid_ids, vid_ids, filenames] = extract_BP4D_labels(BP4D_dir, bp4d_dirs, aus_BP4D);
-labels_gt = cat(1, labels_gt{:});
-
-%% Identifying which column IDs correspond to which AU
-tab = readtable([out_loc, bp4d_dirs{1}, '_T1.au.txt']);
-column_names = tab.Properties.VariableNames;
-
-% As there are both classes and intensities list and evaluate both of them
-aus_pred_int = [];
-aus_pred_class = [];
-
-inds_int_in_file = [];
-inds_class_in_file = [];
-
-for c=1:numel(column_names)
-    if(strfind(column_names{c}, '_r') > 0)
-        aus_pred_int = cat(1, aus_pred_int, int32(str2num(column_names{c}(3:end-2))));
-        inds_int_in_file = cat(1, inds_int_in_file, c);
-    end
-    if(strfind(column_names{c}, '_c') > 0)
-        aus_pred_class = cat(1, aus_pred_class, int32(str2num(column_names{c}(3:end-2))));
-        inds_class_in_file = cat(1, inds_class_in_file, c);
-    end
-end
-
-%%
-inds_au_int = zeros(size(aus_BP4D));
-inds_au_class = zeros(size(aus_BP4D));
-
-for ind=1:numel(aus_BP4D)  
-    if(~isempty(find(aus_pred_int==aus_BP4D(ind), 1)))
-        inds_au_int(ind) = find(aus_pred_int==aus_BP4D(ind));
-    end
-end
-
-for ind=1:numel(aus_BP4D)  
-    if(~isempty(find(aus_pred_class==aus_BP4D(ind), 1)))
-        inds_au_class(ind) = find(aus_pred_class==aus_BP4D(ind));
-    end
-end
-
-preds_all_class = [];
-preds_all_int = [];
-
-for i=1:numel(filenames)
-   
-    fname = [out_loc, filenames{i}, '.au.txt'];
-    preds = dlmread(fname, ',', 1, 0);
-    
-    % Read all of the intensity AUs
-    preds_int = preds(:, inds_int_in_file);
-    
-    % Read all of the classification AUs
-    preds_class = preds(:, inds_class_in_file);
-    
-    preds_all_class = cat(1, preds_all_class, preds_class);
-    preds_all_int = cat(1, preds_all_int, preds_int);
-end
-
-%%
-f = fopen('BP4D_valid_res_class.txt', 'w');
-for au = 1:numel(aus_BP4D)
-
-    if(inds_au_int(au) ~= 0)
-        tp = sum(labels_gt(:,au) == 1 & preds_all_int(:, inds_au_int(au)) >= 1);
-        fp = sum(labels_gt(:,au) == 0 & preds_all_int(:, inds_au_int(au)) >= 1);
-        fn = sum(labels_gt(:,au) == 1 & preds_all_int(:, inds_au_int(au)) < 1);
-        tn = sum(labels_gt(:,au) == 0 & preds_all_int(:, inds_au_int(au)) < 1);
-
-        precision = tp./(tp+fp);
-        recall = tp./(tp+fn);
-
-        f1 = 2 * precision .* recall ./ (precision + recall);
-
-        fprintf(f, 'AU%d intensity, Precision - %.3f, Recall - %.3f, F1 - %.3f\n', aus_BP4D(au), precision, recall, f1);
-    end
-    
-    if(inds_au_class(au) ~= 0)
-        tp = sum(labels_gt(:,au) == 1 & preds_all_class(:, inds_au_class(au)) == 1);
-        fp = sum(labels_gt(:,au) == 0 & preds_all_class(:, inds_au_class(au)) == 1);
-        fn = sum(labels_gt(:,au) == 1 & preds_all_class(:, inds_au_class(au)) == 0);
-        tn = sum(labels_gt(:,au) == 0 & preds_all_class(:, inds_au_class(au)) == 0);
-
-        precision = tp./(tp+fp);
-        recall = tp./(tp+fn);
-
-        f1 = 2 * precision .* recall ./ (precision + recall);
-
-        fprintf(f, 'AU%d class, Precision - %.3f, Recall - %.3f, F1 - %.3f\n', aus_BP4D(au), precision, recall, f1);
-    end    
-    
-end
-fclose(f);
-
-%%
-addpath('./helpers/');
-
-find_BP4D;
-
-aus_BP4D = [6, 10, 12, 14, 17];
-[ labels_gt, valid_ids, vid_ids, filenames] = extract_BP4D_labels_intensity(BP4D_dir_int, devel_recs, aus_BP4D);
-labels_gt = cat(1, labels_gt{:});
-
-%% Identifying which column IDs correspond to which AU
-tab = readtable([out_loc, bp4d_dirs{1}, '_T1.au.txt']);
-column_names = tab.Properties.VariableNames;
-
-% As there are both classes and intensities list and evaluate both of them
-aus_pred_int = [];
-inds_int_in_file = [];
-
-for c=1:numel(column_names)
-    if(strfind(column_names{c}, '_r') > 0)
-        aus_pred_int = cat(1, aus_pred_int, int32(str2num(column_names{c}(3:end-2))));
-        inds_int_in_file = cat(1, inds_int_in_file, c);
-    end
-end
-
-%%
-inds_au_int = zeros(size(aus_BP4D));
-
-for ind=1:numel(aus_BP4D)  
-    if(~isempty(find(aus_pred_int==aus_BP4D(ind), 1)))
-        inds_au_int(ind) = find(aus_pred_int==aus_BP4D(ind));
-    end
-end
-
-preds_all_class = [];
-
-for i=1:numel(filenames)
-   
-    fname = [out_loc, filenames{i}, '.au.txt'];
-    preds = dlmread(fname, ',', 1, 0);
-    
-    % Read all of the intensity AUs
-    preds_int = preds(:, inds_int_in_file);
-    
-    
-    preds_all_class = cat(1, preds_all_class, preds_class);
-    preds_all_int = cat(1, preds_all_int, preds_int);
-end
-
-%%
-f = fopen('BP4D_valid_res_class.txt', 'w');
-for au = 1:numel(aus_BP4D)
-
-    if(inds_au_int(au) ~= 0)
-        tp = sum(labels_gt(:,au) == 1 & preds_all_int(:, inds_au_int(au)) >= 1);
-        fp = sum(labels_gt(:,au) == 0 & preds_all_int(:, inds_au_int(au)) >= 1);
-        fn = sum(labels_gt(:,au) == 1 & preds_all_int(:, inds_au_int(au)) < 1);
-        tn = sum(labels_gt(:,au) == 0 & preds_all_int(:, inds_au_int(au)) < 1);
-
-        precision = tp./(tp+fp);
-        recall = tp./(tp+fn);
-
-        f1 = 2 * precision .* recall ./ (precision + recall);
-
-        fprintf(f, 'AU%d intensity, Precision - %.3f, Recall - %.3f, F1 - %.3f\n', aus_BP4D(au), precision, recall, f1);
-    end
-    
-    if(inds_au_class(au) ~= 0)
-        tp = sum(labels_gt(:,au) == 1 & preds_all_class(:, inds_au_class(au)) == 1);
-        fp = sum(labels_gt(:,au) == 0 & preds_all_class(:, inds_au_class(au)) == 1);
-        fn = sum(labels_gt(:,au) == 1 & preds_all_class(:, inds_au_class(au)) == 0);
-        tn = sum(labels_gt(:,au) == 0 & preds_all_class(:, inds_au_class(au)) == 0);
-
-        precision = tp./(tp+fp);
-        recall = tp./(tp+fn);
-
-        f1 = 2 * precision .* recall ./ (precision + recall);
-
-        fprintf(f, 'AU%d class, Precision - %.3f, Recall - %.3f, F1 - %.3f\n', aus_BP4D(au), precision, recall, f1);
-    end    
-    
-end
-fclose(f);

matlab_runners/Action Unit Experiments/run_AU_prediction_UNBC.m

@@ -0,0 +1,188 @@
+clear
+
+unbc_loc = 'D:/Datasets/UNBC/Images/';
+
+out_loc = './out_unbc/';
+
+if(~exist(out_loc, 'dir'))
+    mkdir(out_loc);
+end
+
+%%
+executable = '"../../x64/Release/FeatureExtraction.exe"';
+
+unbc_dirs = {'042-ll042', '043-jh043', '047-jl047', '048-aa048', '049-bm049',...
+            '052-dr052', '059-fn059', '064-ak064', '066-mg066', '080-bn080',...
+            '092-ch092', '095-tv095', '096-bg096', '097-gf097', '101-mg101',...
+            '103-jk103', '106-nm106', '107-hs107', '108-th108', '109-ib109',...
+            '115-jy115', '120-kz120', '121-vw121', '123-jh123', '124-dn124'};
+        
+parfor f1=1:numel(unbc_dirs)
+
+    if(isdir([unbc_loc, unbc_dirs{f1}]))
+        
+        unbc_2_dirs = dir([unbc_loc, unbc_dirs{f1}]);
+        unbc_2_dirs = unbc_2_dirs(3:end);
+        
+        f1_dir = unbc_dirs{f1};
+
+        command = [executable ' -asvid -q -no2Dfp -no3Dfp -noMparams -noPose -noGaze '];
+
+        for f2=1:numel(unbc_2_dirs)
+            f2_dir = unbc_2_dirs(f2).name;
+            if(isdir([unbc_loc, unbc_dirs{f1}]))
+                
+                curr_vid = [unbc_loc, f1_dir, '/', f2_dir, '/'];
+
+                name = [f1_dir '_' f2_dir];
+                output_file = [out_loc name '.au.txt'];
+                
+                command = cat(2, command, [' -fdir "' curr_vid '" -of "' output_file '"']);
+            end
+        end
+        
+        dos(command);
+    end
+end
+
+%%
+addpath('./helpers/');
+
+find_UNBC;
+
+aus_UNBC = [6, 7, 10, 12, 25, 26];
+
+[ labels_gt, valid_ids, filenames] = extract_UNBC_labels(UNBC_dir, unbc_dirs, aus_UNBC);
+labels_gt = cat(1, labels_gt{:});
+
+%% Identifying which column IDs correspond to which AU
+tab = readtable([out_loc, '042-ll042_ll042t1aaaff.au.txt']);
+column_names = tab.Properties.VariableNames;
+
+% As there are both classes and intensities list and evaluate both of them
+aus_pred_int = [];
+aus_pred_class = [];
+
+inds_int_in_file = [];
+inds_class_in_file = [];
+
+for c=1:numel(column_names)
+    if(strfind(column_names{c}, '_r') > 0)
+        aus_pred_int = cat(1, aus_pred_int, int32(str2num(column_names{c}(3:end-2))));
+        inds_int_in_file = cat(1, inds_int_in_file, c);
+    end
+    if(strfind(column_names{c}, '_c') > 0)
+        aus_pred_class = cat(1, aus_pred_class, int32(str2num(column_names{c}(3:end-2))));
+        inds_class_in_file = cat(1, inds_class_in_file, c);
+    end
+end
+
+%%
+inds_au_int = zeros(size(aus_UNBC));
+inds_au_class = zeros(size(aus_UNBC));
+
+for ind=1:numel(aus_UNBC)  
+    if(~isempty(find(aus_pred_int==aus_UNBC(ind), 1)))
+        inds_au_int(ind) = find(aus_pred_int==aus_UNBC(ind));
+    end
+end
+
+for ind=1:numel(aus_UNBC)  
+    if(~isempty(find(aus_pred_class==aus_UNBC(ind), 1)))
+        inds_au_class(ind) = find(aus_pred_class==aus_UNBC(ind));
+    end
+end
+
+preds_all_class = [];
+preds_all_int = [];
+
+for i=1:numel(filenames)
+   
+    fname = dir([out_loc, '/*', filenames{i}, '.au.txt']);
+    fname = fname(1).name;
+    
+    preds = dlmread([out_loc '/' fname], ',', 1, 0);
+    
+    % Read all of the intensity AUs
+    preds_int = preds(:, inds_int_in_file);
+    
+    % Read all of the classification AUs
+    preds_class = preds(:, inds_class_in_file);
+    
+    preds_all_class = cat(1, preds_all_class, preds_class);
+    preds_all_int = cat(1, preds_all_int, preds_int);
+end
+
+%%
+f = fopen('UNBC_valid_res_class.txt', 'w');
+for au = 1:numel(aus_UNBC)
+    
+    if(inds_au_class(au) ~= 0)
+        tp = sum(labels_gt(:,au) == 1 & preds_all_class(:, inds_au_class(au)) == 1);
+        fp = sum(labels_gt(:,au) == 0 & preds_all_class(:, inds_au_class(au)) == 1);
+        fn = sum(labels_gt(:,au) == 1 & preds_all_class(:, inds_au_class(au)) == 0);
+        tn = sum(labels_gt(:,au) == 0 & preds_all_class(:, inds_au_class(au)) == 0);
+
+        precision = tp./(tp+fp);
+        recall = tp./(tp+fn);
+
+        f1 = 2 * precision .* recall ./ (precision + recall);
+
+        fprintf(f, 'AU%d class, Precision - %.3f, Recall - %.3f, F1 - %.3f\n', aus_UNBC(au), precision, recall, f1);
+    end    
+    
+end
+fclose(f);
+
+%%
+addpath('./helpers/');
+
+find_BP4D;
+
+aus_UNBC = [6, 10, 12, 14, 17];
+[ labels_gt, valid_ids, vid_ids, filenames] = extract_BP4D_labels_intensity(BP4D_dir_int, devel_recs, aus_UNBC);
+labels_gt = cat(1, labels_gt{:});
+
+%% Identifying which column IDs correspond to which AU
+tab = readtable([out_loc, bp4d_dirs{1}, '_T1.au.txt']);
+column_names = tab.Properties.VariableNames;
+
+% As there are both classes and intensities list and evaluate both of them
+aus_pred_int = [];
+inds_int_in_file = [];
+
+for c=1:numel(column_names)
+    if(strfind(column_names{c}, '_r') > 0)
+        aus_pred_int = cat(1, aus_pred_int, int32(str2num(column_names{c}(3:end-2))));
+        inds_int_in_file = cat(1, inds_int_in_file, c);
+    end
+end
+
+%%
+inds_au_int = zeros(size(aus_UNBC));
+
+for ind=1:numel(aus_UNBC)  
+    if(~isempty(find(aus_pred_int==aus_UNBC(ind), 1)))
+        inds_au_int(ind) = find(aus_pred_int==aus_UNBC(ind));
+    end
+end
+
+preds_all_int = [];
+
+for i=1:numel(filenames)
+   
+    fname = [out_loc, filenames{i}, '.au.txt'];
+    preds = dlmread(fname, ',', 1, 0);
+    
+    % Read all of the intensity AUs
+    preds_int = preds(:, inds_int_in_file);    
+    preds_all_int = cat(1, preds_all_int, preds_int);
+end
+
+%%
+f = fopen('BP4D_valid_res_int.txt', 'w');
+for au = 1:numel(aus_UNBC)
+    [ accuracies, F1s, corrs, ccc, rms, classes ] = evaluate_au_prediction_results( preds_all_int(:, inds_au_int(au)), labels_gt(:,au));
+    fprintf(f, 'AU%d results - corr %.3f, ccc - %.3f\n', aus_UNBC(au), corrs, ccc);    
+end
+fclose(f);

matlab_runners/Head Pose Experiments/find_paired_matches.m

@@ -0,0 +1,51 @@
+% Working out corrections for head pose and model correlations
+clear
+%%
+% first need to run run_clm_head_pose_tests_clnf
+if(exist([getenv('USERPROFILE') '/Dropbox/AAM/test data/'], 'file'))
+    database_root = [getenv('USERPROFILE') '/Dropbox/AAM/test data/'];    
+else
+    database_root = 'F:/Dropbox/Dropbox/AAM/test data/';
+end
+buDir = [database_root, '/bu/uniform-light/'];
+resFolderBUclnf_general = [database_root, '/bu/uniform-light/CLMr3/'];
+[~, pred_hp_bu, gt_hp_bu, ~, rels_bu] = calcBUerror(resFolderBUclnf_general, buDir);
+
+biwi_dir = '/biwi pose/';
+biwi_results_root = '/biwi pose results/';
+res_folder_clnf_general = '/biwi pose results//CLMr4/';
+[~, pred_hp_biwi, gt_hp_biwi, ~, ~, rels_biwi] = calcBiwiError([database_root res_folder_clnf_general], [database_root biwi_dir]);
+
+ict_dir = ['ict/'];
+ict_results_root = ['ict results/'];
+res_folder_ict_clnf_general = 'ict results//CLMr4/';
+[~, pred_hp_ict, gt_hp_ict, ~, ~, rel_ict] = calcIctError([database_root res_folder_ict_clnf_general], [database_root ict_dir]);
+
+% Finding matching pairs to make sure they are independently distributed?
+
+% 
+%%
+all_hps = cat(1, pred_hp_bu, pred_hp_biwi, pred_hp_ict);
+all_gts = cat(1, gt_hp_bu, gt_hp_biwi, gt_hp_ict);
+all_rels = cat(1, rels_bu, rels_biwi, rel_ict);
+
+rel_frames = all_rels > 0.8;
+
+all_err = mean(abs(all_gts - all_hps), 2);
+
+all_hps = all_hps(rel_frames, :);
+all_gts = all_gts(rel_frames, :);
+
+% Variation along pitch when others are close to 0
+pitch_bins = [-40:5:40];
+for p = pitch_bins
+    rel_frames = find(abs(all_gts(:,2))<3 & abs(all_gts(:,3))<3 & abs(all_gts(:,1) - p)<3);
+    if ~isempty(rel_frames)
+        corr_coeff = corr(all_hps(rel_frames,1), all_gts(rel_frames,1));
+        fprintf('%d, %.3f\n', numel(rel_frames), corr_coeff);
+    end
+end
+
+plot(find(abs(all_gts(:,1))<1 & abs(all_gts(:,3))<1));
+
+plot(find(abs(all_gts(:,1))<1 & abs(all_gts(:,2))<1));

matlab_runners/Head Pose Experiments/run_f2f_videos.m

@@ -0,0 +1,75 @@
+executable = '"../../x64/Release/FeatureExtraction.exe"';
+
+outputDir = 'D:\Datasets\face2face\2007_processed/';
+
+% First collect the filenames of the data to be used
+input_label_dir = 'D:\Datasets\face2face\f2f-2007-all-transcriptions/';
+
+folds = dir([input_label_dir, '*Rapport*']);
+
+listener_file_labels = {};
+speaker_file_labels = {};
+
+listener_vid_files = {};
+speaker_vid_files = {};
+
+speaker_vid_dir = 'D:\Datasets\face2face\f2f-2007-all-movie-speaker/';
+listener_vid_dir = 'D:\Datasets\face2face\f2f-2007-all-movie-listener/';
+verbose = true;
+for i=1:numel(folds)
+    
+    listener_file = dir([input_label_dir, folds(i).name, '/*.L.nod.eaf']);
+    speaker_file = dir([input_label_dir, folds(i).name, '/*.S.nod.eaf']);
+            
+    if(~isempty(listener_file))
+        % Need to find the appropriate video file if it exists
+        num = listener_file.name(end-15:end-10);
+        vid_file_dir = dir([listener_vid_dir, '/*', num, '*']);
+        vid_file = dir([listener_vid_dir, '/', vid_file_dir.name, '/*.mp4']);
+        if(~isempty(vid_file))
+            listener_vid_files = cat(1, listener_vid_files, [listener_vid_dir, '/', vid_file_dir.name, '/', vid_file.name]);
+            listener_file_labels = cat(1, listener_file_labels, [input_label_dir, '/' folds(i).name, '/' listener_file.name]);
+        end
+    end
+    
+    if(~isempty(speaker_file))
+        num = speaker_file.name(end-15:end-10);
+        vid_file_dir = dir([speaker_vid_dir, '/*', num, '*']);
+        vid_file = dir([speaker_vid_dir, '/', vid_file_dir.name, '/*.mp4']);
+        if(~isempty(vid_file))
+            speaker_vid_files = cat(1, speaker_vid_files, [speaker_vid_dir, '/', vid_file_dir.name, '/', vid_file.name]);
+            speaker_file_labels = cat(1, speaker_file_labels, [input_label_dir, '/' folds(i).name, '/' speaker_file.name]);
+        end
+    end
+    
+end
+
+file_labels = cat(1, listener_file_labels, speaker_file_labels);
+video_files = cat(1, listener_vid_files, speaker_vid_files);
+
+parfor i=1:numel(file_labels)
+    
+    [~,short_name,vid_ext] = fileparts(video_files{i});
+    
+    command = executable;
+           
+    inputFile = video_files{i};
+    outputFile = [outputDir short_name '.txt'];
+
+    outputEaf = [outputDir short_name '.eaf'];
+    
+    command = cat(2, command, [' -f "' inputFile '" -of "' outputFile  '"']);
+
+    if(verbose)
+        outputVideo = [outputDir short_name '.track.avi'];
+        command = cat(2, command, [' -ov "' outputVideo '"']);    
+    end
+
+    command = cat(2, command, [' -no2Dfp -no3Dfp -noMparams -noAUs -noGaze']);
+            
+    dos(command);
+    
+    copyfile(file_labels{i}, outputEaf);
+    copyfile(video_files{i}, [outputDir '/' short_name, '.mp4']);
+    
+end

matlab_runners/Head Pose Experiments/run_f2f_videos_2006.m

@@ -0,0 +1,78 @@
+executable = '"../../x64/Release/FeatureExtraction.exe"';
+
+outputDir = 'D:\Datasets\face2face\2006_processed/';
+
+% First collect the filenames of the data to be used
+input_label_dir = 'D:\Datasets\face2face\rapport-oct-2006-all-transcriptions/';
+
+folds = dir([input_label_dir, '*SES*']);
+
+listener_file_labels = {};
+speaker_file_labels = {};
+
+listener_vid_files = {};
+speaker_vid_files = {};
+
+speaker_vid_dir = 'D:\Datasets\face2face\rapport-oct-2006-all-movie-speaker/';
+listener_vid_dir = 'D:\Datasets\face2face\rapport-oct-2006-all-movie-listener/';
+verbose = true;
+for i=1:numel(folds)
+    
+    listener_file = dir([input_label_dir, folds(i).name, '/*.L.nod.eaf']);
+    speaker_file = dir([input_label_dir, folds(i).name, '/*.S.nod.eaf']);
+            
+    if(~isempty(listener_file))
+        % Need to find the appropriate video file if it exists
+        num = listener_file.name(end-13:end-10);
+        vid_file_dir = dir([listener_vid_dir, '/*', num, '*']);
+        vid_file = dir([listener_vid_dir, '/', vid_file_dir.name, '/*.mp4']);
+        if(~isempty(vid_file))
+            listener_vid_files = cat(1, listener_vid_files, [listener_vid_dir, '/', vid_file_dir.name, '/', vid_file.name]);
+            listener_file_labels = cat(1, listener_file_labels, [input_label_dir, '/' folds(i).name, '/' listener_file.name]);
+        end
+    end
+    
+    if(~isempty(speaker_file))
+        num = speaker_file.name(end-13:end-10);
+        vid_file_dir = dir([speaker_vid_dir, '/*', num, '*']);
+        vid_file = dir([speaker_vid_dir, '/', vid_file_dir.name, '/*.mp4']);
+        if(~isempty(vid_file))
+            speaker_vid_files = cat(1, speaker_vid_files, [speaker_vid_dir, '/', vid_file_dir.name, '/', vid_file.name]);
+            speaker_file_labels = cat(1, speaker_file_labels, [input_label_dir, '/' folds(i).name, '/' speaker_file.name]);
+        end
+    end
+    
+end
+
+% file_labels = cat(1, listener_file_labels, speaker_file_labels);
+% video_files = cat(1, listener_vid_files, speaker_vid_files);
+
+file_labels = listener_file_labels;
+video_files = listener_vid_files;
+
+parfor i=1:numel(file_labels)
+    
+    [~,short_name,vid_ext] = fileparts(video_files{i});
+    
+    command = executable;
+           
+    inputFile = video_files{i};
+    outputFile = [outputDir short_name '.txt'];
+
+    outputEaf = [outputDir short_name '.eaf'];
+    
+    command = cat(2, command, [' -f "' inputFile '" -of "' outputFile  '"']);
+
+    if(verbose)
+        outputVideo = [outputDir short_name '.track.avi'];
+        command = cat(2, command, [' -ov "' outputVideo '"']);    
+    end
+
+    command = cat(2, command, [' -no2Dfp -no3Dfp -noMparams -noAUs -noGaze']);
+            
+    dos(command);
+    
+    copyfile(file_labels{i}, outputEaf);
+    copyfile(video_files{i}, [outputDir '/' short_name, '.mp4']);
+    
+end

matlab_version/AU_training/data extraction/ParseSEMAINEAnnotations.m

@@ -0,0 +1,181 @@
+
+% Function ParseSEMAINEAnnotations is intended to demonstrate example usage
+% of SEMAINE Action Unit annotations made with ELAN annotation toolbox.
+% This function loads the XML structure from an ELAN annotation file with
+% ".eaf" extension, parses it and returns a numerical matrix called
+% "activations" of size NUMBER OF FRAMES X NUMBER OF ACTION UNITS. The
+% matrix holds binary activation status for each frame / AU combination.
+% The matrix also has a row header showing which AU corresponds to which
+% row as well as a column header displaying original frame indexes.
+
+% The function takes 1 compulsory and 2 optional arguments: 
+
+% - "filepath" (compulsory) - complete path to an annotation file to parse.
+% For example, "/matlab/annotation.eaf" or "C:\matlab\annotation.eaf" on
+% Windows.
+
+% - "startFrame" (optional) - ignore all annotations before "startFrame".
+% Default is 1.
+
+% - "endFrame" (optional) - ignore all annotations after "endFrame".
+% Default is the last frame of a video.
+
+% The function requires XML IO Toolbox
+% (http://www.mathworks.com/matlabcentral/fileexchange/12907-xml-io-tools)
+% to run properly (supplied).
+
+function activations = ParseSEMAINEAnnotations (filepath, startFrame, endFrame)
+    activations = [];
+
+    % Framerate value used to convert ELAN millisecond time slots to more
+    % usual frames. 50 is a valid framerate for all SEMAINE videos.
+    framerate = 50;
+
+    % A fixed set of 6 Action Units selected for the challenge from the
+    % SEMAINE annotations
+    aus = [2 12 17 25 28 45];
+    
+    % Total number of AUs.
+	naus = length(aus);
+    
+    % Load XML structure from the file, return in case of a problem.
+    [success, XML] = OpenXML(filepath);
+    if ~success
+		return
+    end
+    
+    % Parse annotation time slots
+    tslots = ParseTimeSlots(XML);
+    
+    % Init start and end frames with default values
+    if nargin < 2
+        startFrame = 1;
+    end
+    
+    if nargin < 3
+        % Get total number of time slots
+        ntslots = length(tslots);
+        % Get last slot ID        
+        lastID = strcat('ts', num2str(ntslots));
+        % Get last time slot value in ms
+        lastValue = tslots(lastID);
+        % Convert last time slot value in ms to frames
+        endFrame = floor((lastValue / 1000) * framerate);
+    end
+    
+    % Get total number of tiers. There are 65 of them, 1 for speech, 32 for
+    % activations (1 per AU) and 32 for intensities. We are going to ignore
+    % intensity tiers.
+    ntiers = length(XML.TIER);
+    
+    % Compose vector of frame indexes to extract annotations from
+	frames = (startFrame:endFrame);
+    
+    % Preallocate activations matrix
+    activations = zeros(length(frames), naus);
+    
+    indx = 1;
+    % Go through all tiers skipping the first one (speech) as well as every
+    % intensity tier. A single activation tier is processed at every
+    % iteration.
+    for k = 2:2:ntiers
+		tier = XML.TIER(k);
+        % Only extract annotations of selected AUs, skip the rest
+        au = strcat('AU', num2str(aus(indx)));
+        if strcmp(au, tier.ATTRIBUTE.TIER_ID)
+            % Read all activation periods from the current tier
+            activationTier = ParseActivationTier(tier, tslots);
+            % Convert of all activation periods into frame level numerical
+            % representation
+            activations(:, indx) = ParseOccurrences(activationTier, frames, framerate);
+
+            indx = indx + 1;
+        end
+        
+        if indx > naus
+            break
+        end
+    end
+    
+    activations = [frames' activations];
+    activations = [[0 aus]; activations];
+end
+
+function occurrences = ParseOccurrences (activations, frames, framerate)
+    % Preallocate activations vector
+    occurrences = zeros(length(frames), 1);
+    % Go through all activation periods, convert ms into frames and init
+    % corresponding values of activations vector with 1 leaving the rest be 0
+	for i = 1:length(activations)
+        % Convert ms into frames 
+		sframe = floor((activations(i).start / 1000) * framerate);
+		eframe = floor((activations(i).end / 1000) * framerate);
+
+        % Determine indexes of frames vector corresponding to the above
+        % time frame
+		sindx = find(frames == sframe);
+		eindx = find(frames == eframe);
+
+        % Mark active set of frames with 1
+		occurrences(sindx:eindx) = 1;
+	end
+end
+
+function activationTier = ParseActivationTier (tier, tslots)
+    % Get total number of activation periods
+    nactivations = length(tier.ANNOTATION);
+    % Preallocate activation tier structure holding start and end time
+    % stamps of all activation periods for the given AU
+	activationTier = repmat(struct('start', 0, 'end', 0), nactivations, 1);
+    % Go through all activation periods and init activation tier
+    % structure array
+    for i = 1:nactivations
+        % Read start time slot ID of the current activation period
+		t = tier.ANNOTATION(i).ALIGNABLE_ANNOTATION.ATTRIBUTE.TIME_SLOT_REF1;
+        % Read time in ms corresponding to the time slot ID
+        activationTier(i).start = tslots(t);
+        
+        % Read end time slot ID of the current activation period
+		t = tier.ANNOTATION(i).ALIGNABLE_ANNOTATION.ATTRIBUTE.TIME_SLOT_REF2;
+        % Read time in ms corresponding to the time slot ID
+		activationTier(i).end = tslots(t);
+    end
+end
+
+function tslots = ParseTimeSlots (xmlObject)
+    % Get total number of time slots
+	nslots = length(xmlObject.TIME_ORDER.TIME_SLOT);
+    % Preallocate cell arrays of time slot IDs and values
+	tids = cell(nslots, 1);
+	tvalues = zeros(nslots, 1);
+    % Read all time slot IDs and numerical values (in ms)
+	for i = 1:nslots
+		tids{i} = xmlObject.TIME_ORDER.TIME_SLOT(i).ATTRIBUTE.TIME_SLOT_ID;
+		tvalues(i) = xmlObject.TIME_ORDER.TIME_SLOT(i).ATTRIBUTE.TIME_VALUE;
+    end
+    % Map time slot IDs and values together so that values are accessible
+    % by their IDs
+	tslots = containers.Map(tids, tvalues);
+end
+
+function [success, xmlObject] = OpenXML (xmlPath)
+	fprintf(' *** Attempting to load \"%s\" ... ', xmlPath);
+	xmlObject = [];
+    success = false;
+    % Check if the specified file exists and return error otherwise
+	if exist(xmlPath, 'file')
+        % Load XML structure
+		xmlObject = xml_read(xmlPath);
+        % Check if XML object loaded correctly, return error otherwise
+		if isempty(xmlObject)
+			fprintf(' ERROR - unable to read xml tree *** \n');
+			return
+		else
+			success = true;
+		end
+	else
+		fprintf(' ERROR - specified path does not exist *** \n');
+		return
+	end
+	fprintf(' Done *** \n');
+end

matlab_version/AU_training/data extraction/create_file_list_single_au_classification.m

@@ -0,0 +1,98 @@
+AU_dir = 'D:/Databases/DISFA/ActionUnit_Labels/';
+
+aus = [1,2,4,5,6,9,12,15,17,20,25,26];
+
+subjects = dir([AU_dir, 'SN*']);
+
+% Store all of the AU directories in a cell
+input_label_dirs = cell(numel(subjects), 1);
+for i=1:numel(subjects)
+    input_label_dirs{i} = [AU_dir, subjects(i).name, '/', subjects(i).name];
+end
+
+for user=1:numel(subjects)
+
+    testing_label_files = input_label_dirs(user);
+
+    training_label_files = setdiff(input_label_dirs, testing_label_files);  
+    
+    training_labels_all = [];
+    
+    testing_labels_all = [];
+    
+    % First extract AU information
+    for au=aus
+
+        % Extract all of the AUs from the current user
+        [training_labels, training_vid_inds_all, training_frame_inds_all] = extract_au_labels(training_label_files, au);        
+        [testing_labels, testing_vid_inds_all, testing_frame_inds_all] = extract_au_labels(testing_label_files, au);        
+
+        training_labels_all = cat(2, training_labels_all, training_labels);
+        testing_labels_all = cat(2, testing_labels_all, testing_labels);        
+        
+    end
+
+    % File lists for each of the AUs
+    for au_ind=1:numel(aus)
+                   
+        % extract the interesting frames for training, the interesting ones
+        % are the AU
+
+        positive_samples = training_labels_all(:,au_ind) > 0;
+        
+        active_samples = sum(training_labels_all,2) > 10;
+                
+        % Remove neighboring images as they are not very informative
+        negative_samples = sum(training_labels_all,2) == 0;
+        neg_inds = find(negative_samples);
+        neg_to_use = randperm(numel(neg_inds));
+        % taking a number of neutral samples that bring the positive and
+        % negative samples to a balanced level
+        neg_to_use = neg_inds(neg_to_use(1:(2*sum(positive_samples) - sum(active_samples | positive_samples))));
+        negative_samples(:) = false;
+        negative_samples(neg_to_use) = true;
+        
+        % Collect all the data for training now
+        training_samples = positive_samples | active_samples | negative_samples;
+        
+        % Create a training file list file        
+        f_train_file_list = fopen(sprintf('%s/%s_au%02d_filelist_train.txt', 'single_au_class', subjects(user).name, aus(au_ind)), 'w');
+        
+        sample_inds_train = find(training_samples);
+        
+        for sample_ind = sample_inds_train'
+            
+            img_file_l = sprintf('../../LeftVideo%s_comp/frame_det_%06d.png', training_vid_inds_all{sample_ind}, training_frame_inds_all(sample_ind));
+            img_file_r = sprintf('../../RightVideo%s_comp/frame_det_%06d.png', training_vid_inds_all{sample_ind}, training_frame_inds_all(sample_ind));
+            
+            au_class = training_labels_all(sample_ind, au_ind) > 1;
+            
+            fprintf(f_train_file_list, '%s %d\r\n', img_file_l, au_class);                        
+            fprintf(f_train_file_list, '%s %d\r\n', img_file_r, au_class);                        
+            
+        end                
+        fclose(f_train_file_list);
+        
+         % Create a testing file list file        
+        f_train_file_list = fopen(sprintf('%s/%s_au%02d_filelist_test.txt', 'single_au_class', subjects(user).name, aus(au_ind)), 'w');
+        
+        
+        testing_samples = true(size(testing_labels_all,1),1);        
+        sample_inds_test = find(testing_samples);
+        
+        for sample_ind = sample_inds_test'
+            
+            img_file_l = sprintf('../../LeftVideo%s_comp/frame_det_%06d.png', testing_vid_inds_all{sample_ind}, testing_frame_inds_all(sample_ind));
+            img_file_r = sprintf('../../RightVideo%s_comp/frame_det_%06d.png', testing_vid_inds_all{sample_ind}, testing_frame_inds_all(sample_ind));
+            
+            au_class = testing_labels_all(sample_ind, au_ind) > 1;
+            
+            fprintf(f_train_file_list, '%s %d\r\n', img_file_l, au_class);                        
+            fprintf(f_train_file_list, '%s %d\r\n', img_file_r, au_class);                        
+            
+        end                
+        fclose(f_train_file_list);       
+        
+    end
+    
+end

matlab_version/AU_training/data extraction/extract_BP4D_labels.m

@@ -0,0 +1,67 @@
+function [ labels, valid_ids, vid_ids, filenames  ] = extract_BP4D_labels( BP4D_dir, recs, aus )
+%EXTRACT_SEMAINE_LABELS Summary of this function goes here
+%   Detailed explanation goes here
+    
+    aus_BP4D = [1, 2, 4, 6, 7, 10, 12, 14, 15, 17, 23];
+    
+    inds_to_use = [];
+    
+    for i=1:numel(aus)
+    
+        inds_to_use = cat(1, inds_to_use, find(aus_BP4D == aus(i)));
+        
+    end
+    num_files = numel(dir([BP4D_dir, '/*.csv']));
+    
+    labels = cell(num_files, 1);
+    valid_ids = cell(num_files, 1);
+    vid_ids = zeros(num_files, 2);
+    filenames = cell(num_files, 1);
+    
+    file_id = 1;
+    
+    for i=1:numel(recs)
+
+        csvs = dir([BP4D_dir, '/', recs{i}, '*.csv']);
+    
+        for f=1:numel(csvs)
+            
+            file = [BP4D_dir, '/', csvs(f).name];
+            
+            [~, filename,~] = fileparts(file);
+            filenames{file_id} = filename;
+            
+            OCC = csvread(file); %import annotations for one video file
+            frame_nums = OCC(2:end,1); %get all frame numbers
+            codes = OCC(2:end,2:end); %get codes for all action units
+            occlusions = OCC(2:end,end);
+            
+            codes = codes(:, aus_BP4D);
+            
+            % Finding the invalid regions
+            valid = occlusions ~= 1;
+            
+            for s=1:size(codes,2)
+               
+                valid = valid & codes(:,s) ~= 9;
+                
+            end
+            
+            vid_ids(file_id,:) = [frame_nums(1), frame_nums(end)];
+
+            labels{file_id} = codes(:, inds_to_use);
+
+            % all indices in SEMAINE are valid
+            valid_ids{file_id} = valid;
+            
+            file_id = file_id + 1;
+        end 
+    end
+    
+    labels = labels(1:file_id-1);
+    valid_ids = valid_ids(1:file_id-1);
+    vid_ids = vid_ids(1:file_id-1, :);
+    filenames = filenames(1:file_id-1);
+    
+end
+

matlab_version/AU_training/data extraction/extract_BP4D_labels_intensity.m

@@ -0,0 +1,63 @@
+function [ labels, valid_ids, vid_ids, filenames  ] = extract_BP4D_labels_intensity( BP4D_dir, recs, aus )
+%EXTRACT_SEMAINE_LABELS Summary of this function goes here
+%   Detailed explanation goes here
+    
+    files_all = dir(sprintf('%s/AU%02d/%s', BP4D_dir, aus(1), '/*.csv'));
+    num_files = numel(files_all);
+            
+    labels = cell(num_files, 1);
+    valid_ids = cell(num_files, 1);
+    vid_ids = zeros(num_files, 2);
+    filenames = cell(num_files, 1);
+    
+    file_id = 1;
+    
+    for r=1:numel(recs)
+        
+        files_root = sprintf('%s/AU%02d/', BP4D_dir, aus(1));
+        files_all = dir([files_root, recs{r}, '*.csv']);
+
+        for f=1:numel(files_all)
+            for au=aus
+                
+                % Need to find relevant files for the relevant user and for the
+                % relevant AU
+                files_root = sprintf('%s/AU%02d/', BP4D_dir, au);
+                files_all = dir([files_root, recs{r}, '*.csv']);
+        
+                file = [files_root, '/', files_all(f).name];
+
+                [~, filename,~] = fileparts(file);
+                filenames{file_id} = filename(1:7);
+
+                intensities = csvread(file); % import annotations for one session
+
+                frame_nums = intensities(:,1); % get all frame numbers
+
+                codes = intensities(:,2);
+
+                % Finding the invalid regions
+                valid = codes ~= 9;
+
+                vid_ids(file_id,:) = [frame_nums(1), frame_nums(end)];
+
+                if(au == aus(1))
+                    valid_ids{file_id} = valid;
+                    labels{file_id} = codes;
+                else
+                    valid_ids{file_id} = valid_ids{file_id} & valid;
+                    labels{file_id} = cat(2, labels{file_id}, codes);
+                end
+
+            end 
+            file_id = file_id + 1;
+        end
+    end
+    
+    labels = labels(1:file_id-1);
+    valid_ids = valid_ids(1:file_id-1);
+    vid_ids = vid_ids(1:file_id-1, :);
+    filenames = filenames(1:file_id-1);
+    
+end
+

matlab_version/AU_training/data extraction/extract_FERA2011_labels.m

@@ -0,0 +1,45 @@
+function [ labels, valid_ids, filenames  ] = extract_FERA2011_labels( FERA2011_dir, recs, aus )
+%EXTRACT_SEMAINE_LABELS Summary of this function goes here
+%   Detailed explanation goes here
+    
+    num_files = numel(recs);
+
+    % speech invalidates lower face AUs    
+    labels = cell(num_files, 1);
+    valid_ids = cell(num_files, 1);
+    filenames = cell(num_files, 1);
+    
+    file_id = 1;
+    
+    for i=1:numel(recs)
+
+        file = [FERA2011_dir, '/', recs{i}, '/', recs{i}, '-au.dat'];
+    
+        [~, filename,~] = fileparts(file);
+        filenames{file_id} = filename;
+
+        data = csvread(file); %import annotations for one video file
+       
+        speech = data(:,end);
+
+        labels{file_id} = data(:, aus);
+
+        % Finding the invalid regions
+        if(aus(1) >= 10)
+            valid = speech == 0;
+        else
+            valid = true(size(speech,1), 1);
+        end
+        
+        % all indices in SEMAINE are valid
+        valid_ids{file_id} = valid;
+
+        file_id = file_id + 1;
+    end
+    
+    labels = labels(1:file_id-1);
+    valid_ids = valid_ids(1:file_id-1);
+    filenames = filenames(1:file_id-1);
+    
+end
+

matlab_version/AU_training/data extraction/extract_SEMAINE_labels.m

@@ -0,0 +1,52 @@
+function [ labels, valid_ids, vid_ids  ] = extract_SEMAINE_labels( SEMAINE_dir, recs, aus )
+%EXTRACT_SEMAINE_LABELS Summary of this function goes here
+%   Detailed explanation goes here
+
+    % Get the right eaf file
+
+    aus_SEMAINE = [2 12 17 25 28 45];
+
+    inds_to_use = [];
+    
+    for i=1:numel(aus)
+    
+        inds_to_use = cat(1, inds_to_use, find(aus_SEMAINE == aus(i)));
+        
+    end
+    
+    labels = cell(numel(recs), 1);
+    valid_ids = cell(numel(recs), 1);
+    vid_ids = zeros(numel(recs), 2);
+    
+    for i=1:numel(recs)
+       
+        file = dir([SEMAINE_dir, '/', recs{i}, '/*.eaf']);
+        
+        vid_ids(i,:) = dlmread([SEMAINE_dir, '/', recs{i}, '.txt'], ' ');
+        
+        xml_file = [SEMAINE_dir, recs{i}, '\' file.name];
+        [root_xml, name_xml, ~] = fileparts(xml_file);
+        m_file = [root_xml, name_xml, '.mat'];
+            
+        if(~exist(m_file, 'file'))            
+            activations = ParseSEMAINEAnnotations([SEMAINE_dir, recs{i}, '\' file.name]);
+            save(m_file, 'activations');
+        else
+            load(m_file);
+        end
+        if(size(activations,1) < vid_ids(i,2))
+            vid_ids(i,2) = size(activations,1);
+            if(vid_ids(i,2) > 2999)
+                vid_ids(i,1) = vid_ids(i,2) - 2999;
+            end
+        end
+        
+        labels{i} = activations(vid_ids(i,1)+1:vid_ids(i,2), 1 + inds_to_use);
+        
+        % all indices in SEMAINE are valid
+        valid_ids{i} = ones(size(labels{i},1),1);
+        
+    end
+    
+end
+

matlab_version/AU_training/data extraction/extract_UNBC_labels.m

@@ -0,0 +1,70 @@
+function [ labels, valid_ids, filenames  ] = extract_UNBC_labels( UNBC_dir, recs, aus )
+%EXTRACT_SEMAINE_LABELS Summary of this function goes here
+%   Detailed explanation goes here
+    
+    UNBC_dir = [UNBC_dir, '/Frame_Labels/FACS/'];
+
+    aus_UNBC = [4, 6, 7, 9, 10, 12, 20, 25, 26, 43];
+    
+    inds_to_use = [];
+    
+    for i=1:numel(aus)
+    
+        inds_to_use = cat(1, inds_to_use, find(aus_UNBC == aus(i)));
+        
+    end
+    aus_UNBC = aus_UNBC(inds_to_use);
+    labels_all = {};
+    valid_ids_all = {};
+    filenames_all = {};
+    
+    for i=1:numel(recs)
+
+        % get all the dirs, etc.
+        
+        sessions = dir([UNBC_dir, recs{i}]);
+        sessions = sessions(3:end);
+        
+        num_sessions = numel(sessions);
+        
+        labels = cell(num_sessions, 1);
+        valid_ids = cell(num_sessions, 1);
+        filenames = cell(num_sessions, 1);
+
+        for s=1:numel(sessions)
+
+            frames = dir([UNBC_dir, '/', recs{i}, '/', sessions(s).name, '/*.txt']);
+
+            labels_c = zeros(numel(frames), numel(aus));
+            
+            for f=1:numel(frames)
+
+                file = [UNBC_dir, '/', recs{i}, '/', sessions(s).name, '/', frames(f).name];
+
+                fileID = fopen(file);                
+                C = textscan(fileID,'%d %d %d %d\n');
+                fclose(fileID); 
+                
+%                 OCC = csvread(file); %import annotations for one video file
+                for au = 1:numel(C{1})                    
+                    labels_c(f, aus_UNBC == C{1}(au)) = C{2}(au);
+                end
+                
+            end 
+            labels{s} = labels_c;
+            filenames(s) = {sessions(s).name};
+            valid_ids{s} = true(size(labels_c,1),1);
+        end
+        
+        
+        labels_all = cat(1, labels_all, labels);
+        valid_ids_all = cat(1, valid_ids_all, valid_ids);
+        filenames_all = cat(1, filenames_all, filenames);
+
+    end
+    
+    labels = labels_all;
+    valid_ids = valid_ids_all;
+    filenames = filenames_all;
+end
+

matlab_version/AU_training/data extraction/extract_au_labels.m

@@ -0,0 +1,29 @@
+function [ labels, vid_inds, frame_inds ] = extract_au_labels( input_folders, au_id)
+%EXTRACT_AU_LABELS Summary of this function goes here
+%   Detailed explanation goes here
+
+    labels = [];    
+    vid_inds = [];
+    frame_inds = [];
+    for i=1:numel(input_folders)
+        
+        in_file = sprintf('%s_au%d.txt', input_folders{i}, au_id);
+        
+        A = dlmread(in_file, ',');
+                
+        vid_inds_curr = cell(numel(A(:,2)), 1);
+        
+        labels = cat(1, labels, A(:,2));
+        
+        [~,curr_name,~] = fileparts(input_folders{i});
+        
+        frame_inds_curr = 0:numel(A(:,2))-1;
+        frame_inds = cat(1, frame_inds, frame_inds_curr');
+        
+        vid_inds_curr(:) = {curr_name};
+        vid_inds = cat(1, vid_inds, vid_inds_curr);
+        
+    end
+
+end
+

matlab_version/AU_training/data extraction/extract_features_BP4D.m

@@ -0,0 +1,73 @@
+clear
+
+features_exe = '"..\..\..\x64\Release\FeatureExtraction.exe"';
+
+find_BP4D;
+BP4D_dir = [BP4D_dir '\..\BP4D-training\'];
+
+bp4d_dirs = train_recs;
+out_loc = [BP4D_dir '\..\processed_data\train\'];
+
+parfor f1=1:numel(bp4d_dirs)
+
+    if(isdir([BP4D_dir, bp4d_dirs{f1}]))
+        
+        bp4d_2_dirs = dir([BP4D_dir, bp4d_dirs{f1}]);
+        bp4d_2_dirs = bp4d_2_dirs(3:end);
+        
+        f1_dir = bp4d_dirs{f1};
+        
+        for f2=1:numel(bp4d_2_dirs)
+            f2_dir = bp4d_2_dirs(f2).name;
+            if(isdir([BP4D_dir, bp4d_dirs{f1}]))
+                command = features_exe;
+
+                curr_vid = [BP4D_dir, f1_dir, '/', f2_dir, '/'];
+
+                name = [f1_dir '_' f2_dir];
+                output_file = [out_loc name '/'];
+
+                output_hog = [out_loc name '.hog'];
+                output_params = [out_loc name '.params.txt'];
+                
+                command = cat(2, command, [' -fx 2000 -fy 2000 -rigid -q -asvid -fdir "' curr_vid '" -simalign "' output_file  '" -simscale 0.7 -simsize 112']);
+                command = cat(2, command, [' -hogalign "' output_hog '"']);
+                command = cat(2, command, [' -of "' output_params '" -no2Dfp -no3Dfp -noAUs -noPose -noGaze']);
+                dos(command);
+            end
+        end
+    end
+end
+
+bp4d_dirs = devel_recs;
+out_loc = [BP4D_dir '\..\processed_data\devel\'];
+parfor f1=1:numel(bp4d_dirs)
+
+    if(isdir([BP4D_dir, bp4d_dirs{f1}]))
+        
+        bp4d_2_dirs = dir([BP4D_dir, bp4d_dirs{f1}]);
+        bp4d_2_dirs = bp4d_2_dirs(3:end);
+        
+        f1_dir = bp4d_dirs{f1};
+        
+        for f2=1:numel(bp4d_2_dirs)
+            f2_dir = bp4d_2_dirs(f2).name;
+            if(isdir([BP4D_dir, bp4d_dirs{f1}]))
+                command = features_exe;
+
+                curr_vid = [BP4D_dir, f1_dir, '/', f2_dir, '/'];
+
+                name = [f1_dir '_' f2_dir];
+                output_file = [out_loc name '/'];
+
+                output_hog = [out_loc name '.hog'];
+                output_params = [out_loc name '.params.txt'];
+
+                command = cat(2, command, [' -fx 2000 -fy 2000 -rigid -q -asvid -fdir "' curr_vid '" -simalign "' output_file  '" -simscale 0.7 -simsize 112']);
+                command = cat(2, command, [' -hogalign "' output_hog '"']);
+                command = cat(2, command, [' -of "' output_params '" -no2Dfp -no3Dfp -noAUs -noPose -noGaze']);
+                dos(command);
+            end
+        end
+    end
+end

matlab_version/AU_training/data extraction/extract_features_CK.m

@@ -0,0 +1,42 @@
+clear
+features_exe = '"..\..\..\x64\Release\FeatureExtraction.exe"';
+
+ck_loc = 'D:\Datasets\ck+\cohn-kanade-images\';
+
+out_loc = 'D:\datasets\face_datasets/hog_aligned_rigid\';
+out_loc_params = 'D:\datasets\face_datasets/clm_params\';
+
+% Go two levels deep
+ck_dirs = dir(ck_loc);
+ck_dirs = ck_dirs(3:end);
+
+parfor f1=1:numel(ck_dirs)
+
+    ck_dirs_level_2 = dir([ck_loc, ck_dirs(f1).name]);
+    ck_dirs_level_2 = ck_dirs_level_2(3:end);
+   
+    for f2=1:numel(ck_dirs_level_2)
+
+        if(~isdir([ck_loc, ck_dirs(f1).name, '/', ck_dirs_level_2(f2).name]))
+           continue; 
+        end       
+        
+        command = features_exe;
+
+        curr_vid = [ck_loc, ck_dirs(f1).name, '/', ck_dirs_level_2(f2).name];
+        
+        name = [ck_dirs(f1).name, '_',  ck_dirs_level_2(f2).name];
+
+        output_file = [out_loc name '/'];
+
+        output_hog = [out_loc name '.hog'];
+        output_params = [out_loc_params name '.txt'];
+            
+        command = cat(2, command, [' -rigid -asvid -fdir "' curr_vid '" -simalign "' output_file  '" -simscale 0.7 -simsize 112 -g -q ']);
+        command = cat(2, command, [' -hogalign "' output_hog, '"' ]);
+        
+        dos(command);
+            
+    end    
+    
+end

matlab_version/AU_training/data extraction/extract_features_DISFA.m

@@ -0,0 +1,84 @@
+% Biwi dataset experiment
+
+features_exe = '"..\..\..\x64\Release\FeatureExtraction.exe"';
+
+if(exist('D:/Databases/DISFA/', 'dir'))
+    DISFA_loc = 'D:/Databases/DISFA/';    
+elseif(exist('D:/Datasets/DISFA/', 'dir'))
+    DISFA_loc = 'D:/Datasets/DISFA/';   
+elseif(exist('E:/datasets/DISFA/', 'dir'))
+    DISFA_loc = 'E:/datasets/DISFA/';       
+elseif(exist('C:/tadas/DISFA', 'dir'))
+    DISFA_loc = 'C:/tadas/DISFA/';
+elseif(exist('D:\datasets\face_datasets\DISFA/', 'dir'))
+    DISFA_loc = 'D:\datasets\face_datasets\DISFA/';    
+else
+   fprintf('DISFA not found\n'); 
+end
+
+output = [DISFA_loc, '/aligned_rigid/'];
+output_hog_root = [DISFA_loc '/hog_aligned_rigid/'];
+output_params_root = [DISFA_loc '/model_params/'];
+
+DISFA_loc_1 = [DISFA_loc, 'Videos_LeftCamera/'];
+DISFA_loc_2 = [DISFA_loc, 'Video_RightCamera/'];
+
+if(~exist(output, 'dir'))
+    mkdir(output);
+end
+
+if(~exist(output_hog_root, 'dir'))
+    mkdir(output_hog_root);
+end
+
+if(~exist(output_params_root, 'dir'))
+    mkdir(output_params_root);
+end
+
+disfa_loc_1_files = dir([DISFA_loc_1, '/*.avi']);
+disfa_loc_2_files = dir([DISFA_loc_2, '/*.avi']);
+
+%%
+tic;
+
+parfor i=1:numel(disfa_loc_1_files)
+           
+    command = features_exe;
+               
+    input_file = [DISFA_loc_1 disfa_loc_1_files(i).name];
+        
+    [~,name,~] = fileparts(disfa_loc_1_files(i).name);
+    output_file = [output name '/'];
+
+    output_hog = [output_hog_root name '.hog'];
+    output_params = [output_params_root '/' name '.txt'];
+        
+    command = cat(2, command, [' -rigid -f "' input_file '" -simalign "' output_file  '" -simscale 0.7 -simsize 112']);
+    command = cat(2, command, [' -hogalign "' output_hog '"' ]);
+    command = cat(2, command, [' -of "' output_params '" -no2Dfp -no3Dfp -noAUs -noPose -noGaze -q']);
+
+    dos(command);
+end
+
+%%
+parfor i=1:numel(disfa_loc_2_files)
+           
+    command = features_exe;
+               
+    input_file = [DISFA_loc_2 disfa_loc_2_files(i).name];
+        
+    [~,name,~] = fileparts(disfa_loc_2_files(i).name);
+    output_file = [output name '/'];
+    
+    output_hog = [output_hog_root name '.hog'];
+        
+    output_params = [output_params_root '/' name '.txt'];
+        
+    command = cat(2, command, [' -rigid -f "' input_file '" -simalign "' output_file  '" -simscale 0.7 -simsize 112']);  
+    command = cat(2, command, [' -hogalign "' output_hog '"']);
+    command = cat(2, command, [' -of "' output_params '" -no2Dfp -no3Dfp -noAUs -noPose -noGaze -q']);
+    
+    dos(command);
+end
+
+timeTaken = toc;

matlab_version/AU_training/data extraction/extract_features_FERA_2011.m

@@ -0,0 +1,46 @@
+clear
+features_exe = '"..\..\..\x64\Release\FeatureExtraction.exe"';
+
+fera_loc = 'D:\Datasets\fera\';
+
+out_loc = 'D:\Datasets\face_datasets\hog_aligned_rigid\';
+out_loc_params = 'D:\Datasets\face_datasets\model_params\';
+
+% Go two levels deep
+fera_dirs = dir(fera_loc);
+fera_dirs = fera_dirs(3:end);
+
+for f1=1:numel(fera_dirs)
+
+    fera_dirs_level_2 = dir([fera_loc, fera_dirs(f1).name]);
+    fera_dirs_level_2 = fera_dirs_level_2(3:end);
+   
+    for f2=1:numel(fera_dirs_level_2)
+
+        vid_files = dir([fera_loc, fera_dirs(f1).name, '/', fera_dirs_level_2(f2).name, '/*.avi']);
+        
+        parfor v=1:numel(vid_files)
+            
+            command = features_exe;
+            
+            curr_vid = [fera_loc, fera_dirs(f1).name, '/', fera_dirs_level_2(f2).name, '/', vid_files(v).name];
+            
+            [~,name,~] = fileparts(curr_vid);
+            output_file = [out_loc fera_dirs(f1).name '_' name '/'];
+
+            output_hog = [out_loc fera_dirs(f1).name '_' name '.hog'];
+                
+            output_params = [out_loc_params fera_dirs(f1).name '_' name '.txt'];
+            
+            command = cat(2, command, [' -rigid -f "' curr_vid '" -simalign "' output_file  '" -simscale 0.7 -simsize 112']);
+            command = cat(2, command, [' -hogalign "' output_hog '"']);
+    
+            command = cat(2, command, [' -of "' output_params '" -no2Dfp -no3Dfp -noAUs -noPose -noGaze -q']);
+    
+            dos(command);
+            
+        end
+
+    end    
+    
+end

matlab_version/AU_training/data extraction/extract_features_SEMAINE.m

@@ -0,0 +1,71 @@
+
+features_exe = '"..\..\..\x64\Release\FeatureExtraction.exe"';
+
+find_SEMAINE;
+
+
+% Go two levels deep
+semaine_dirs = train_recs;
+out_loc = [SEMAINE_dir, '../processed_data/train/'];
+
+parfor f1=1:numel(semaine_dirs)
+
+    if(isdir([SEMAINE_dir, semaine_dirs{f1}]))
+        
+        vid_files = dir([SEMAINE_dir, semaine_dirs{f1}, '/*.avi']);
+
+        f1_dir = semaine_dirs{f1};
+        
+        for v=1:numel(vid_files)
+
+            command = features_exe;
+
+            curr_vid = [SEMAINE_dir, f1_dir, '/', vid_files(v).name];
+
+            name = f1_dir;
+            output_file = [out_loc name '/'];
+
+            output_hog = [out_loc name '.hog'];
+            output_params = [out_loc name '.params.txt'];
+
+            command = cat(2, command, [' -rigid -f "' curr_vid '" -simalign "' output_file  '" -simscale 0.7 -simsize 112']);
+            command = cat(2, command, [' -hogalign "' output_hog '"']);
+            command = cat(2, command, [' -of "' output_params '" -no2Dfp -no3Dfp -noAUs -noPose -noGaze -q']);
+            dos(command);
+
+        end
+    end
+end
+
+%%
+semaine_dirs = devel_recs;
+out_loc = [SEMAINE_dir, '../processed_data/devel/'];
+
+parfor f1=1:numel(semaine_dirs)
+
+    if(isdir([SEMAINE_dir, semaine_dirs{f1}]))
+        
+        vid_files = dir([SEMAINE_dir, semaine_dirs{f1}, '/*.avi']);
+
+        f1_dir = semaine_dirs{f1};
+        
+        for v=1:numel(vid_files)
+
+            command = features_exe;
+
+            curr_vid = [SEMAINE_dir, f1_dir, '/', vid_files(v).name];
+
+            name = f1_dir;
+            output_file = [out_loc name '/'];
+
+            output_hog = [out_loc name '.hog'];
+            output_params = [out_loc name '.params.txt'];
+
+            command = cat(2, command, [' -rigid -f "' curr_vid '" -simalign "' output_file  '" -simscale 0.7 -simsize 112']);
+            command = cat(2, command, [' -hogalign "' output_hog '"']);
+            command = cat(2, command, [' -of "' output_params '" -no2Dfp -no3Dfp -noAUs -noPose -noGaze -q']);
+            dos(command);
+
+        end
+    end
+end

matlab_version/AU_training/data extraction/extract_features_UNBC.m

@@ -0,0 +1,47 @@
+clear
+features_exe = '"..\..\..\x64\Release\FeatureExtraction.exe"';
+
+unbc_loc = 'D:\Datasets\UNBC\Images/';
+
+out_loc = 'D:\Datasets\face_datasets/';
+
+% Go two levels deep
+unbc_dirs = dir(unbc_loc);
+unbc_dirs = unbc_dirs(3:end);
+
+if(~exist([out_loc, '/clm_params/'], 'file'))
+    mkdir([out_loc, '/clm_params/']);   
+end
+
+parfor f1=1:numel(unbc_dirs)
+
+    unbc_dirs_level_2 = dir([unbc_loc, unbc_dirs(f1).name]);
+    unbc_dirs_level_2 = unbc_dirs_level_2(3:end);
+   
+    for f2=1:numel(unbc_dirs_level_2)
+
+        if(~isdir([unbc_loc, unbc_dirs(f1).name, '/', unbc_dirs_level_2(f2).name]))
+           continue; 
+        end       
+        
+        command = features_exe;
+
+        curr_vid = [unbc_loc, unbc_dirs(f1).name, '/', unbc_dirs_level_2(f2).name];
+        
+        name = [unbc_dirs(f1).name, '_',  unbc_dirs_level_2(f2).name];
+
+        output_file = [out_loc, '/hog_aligned_rigid/', name '/'];
+
+        output_hog = [out_loc, '/hog_aligned_rigid/', name '.hog'];
+        output_params = [out_loc, '/model_params/', name '.txt'];
+        
+        command = cat(2, command, [' -rigid -asvid -fdir "' curr_vid '" -simalign "' output_file  '" -simscale 0.7 -simsize 112 -g']);
+        command = cat(2, command, [' -hogalign "' output_hog '"']);
+            
+        command = cat(2, command, [' -of "' output_params '" -no2Dfp -no3Dfp -noAUs -noPose -noGaze -q']);
+    
+        dos(command);
+            
+    end    
+    
+end

matlab_version/AU_training/data extraction/find_BP4D.m

@@ -0,0 +1,28 @@
+if(exist('C:\tadas\face_datasets\fera_2015\bp4d\AUCoding/', 'file'))
+    BP4D_dir = 'C:\tadas\face_datasets\fera_2015\bp4d\AUCoding/';   
+    BP4D_dir_int = 'C:\tadas\face_datasets\fera_2015\bp4d\AU Intensity Codes3.0/';
+elseif(exist('E:\datasets\FERA_2015\BP4D\AUCoding/', 'file'))
+    BP4D_dir = 'E:\datasets\FERA_2015\BP4D\AUCoding/';       
+    BP4D_dir_int = 'E:\datasets\FERA_2015\BP4D\AU Intensity Codes3.0/';       
+elseif(exist('D:\datasets\face_datasets\fera_2015\bp4d\AUCoding/','file'))
+    BP4D_dir = 'D:\datasets\face_datasets\fera_2015\bp4d\AUCoding/';
+    BP4D_dir_int = 'D:\datasets\face_datasets\fera_2015\bp4d\AU Intensity Codes3.0/';
+elseif(exist('D:\Datasets\FERA_2015\BP4D\AUCoding/','file'))
+    BP4D_dir = 'D:\Datasets\FERA_2015\BP4D\AUCoding/';
+    BP4D_dir_int = 'D:\Datasets\FERA_2015\BP4D\AU Intensity Codes3.0/';
+elseif(exist('I:\datasets\FERA_2015\BP4D\AUCoding/', 'file'))
+    BP4D_dir = 'I:\datasets\FERA_2015\BP4D\AUCoding/';
+    BP4D_dir_int = 'I:\datasets\FERA_2015\BP4D\AU Intensity Codes3.0/';
+elseif(exist('D:/fera_2015/bp4d/AUCoding/', 'file'))
+    BP4D_dir = 'D:/fera_2015/bp4d/AUCoding/';
+    BP4D_dir_int = 'D:/fera_2015/bp4d/AU Intensity Codes3.0/';
+else    
+    fprintf('BP4D location not found (or not defined)\n'); 
+end
+
+
+hog_data_dir = [BP4D_dir, '../processed_data'];
+
+train_recs = {'F001', 'F003', 'F005', 'F007', 'F009', 'F011', 'F013', 'F015', 'F017', 'F019', 'F021', 'F023', 'M001', 'M003', 'M005', 'M007', 'M009', 'M011', 'M013', 'M015' 'M017'};
+devel_recs = {'F002', 'F004', 'F006', 'F008', 'F010', 'F012', 'F014', 'F016', 'F018', 'F020', 'F022', 'M002', 'M004', 'M006', 'M008', 'M010', 'M012', 'M014', 'M016', 'M018'};
+

matlab_version/AU_training/data extraction/find_DISFA.m

@@ -0,0 +1,49 @@
+% load all of the data together (for efficiency)
+% it will be split up accordingly at later stages
+if(exist('F:/datasets/DISFA/', 'file'))
+    DISFA_dir = 'F:/datasets/DISFA/';
+elseif(exist('D:/Databases/DISFA/', 'file'))        
+    DISFA_dir = 'D:/Databases/DISFA/';
+elseif(exist('D:\datasets\face_datasets\DISFA/', 'file'))        
+    DISFA_dir = 'D:\datasets\face_datasets\DISFA/';    
+elseif(exist('D:\Datasets\DISFA/', 'file'))        
+    DISFA_dir = 'D:\Datasets\DISFA/';  
+elseif(exist('Z:/datasets/DISFA/', 'file'))        
+    DISFA_dir = 'Z:/Databases/DISFA/';
+elseif(exist('E:/datasets/DISFA/', 'file'))        
+    DISFA_dir = 'E:/datasets/DISFA/';
+elseif(exist('C:/tadas/DISFA/', 'file'))        
+    DISFA_dir = 'C:/tadas/DISFA/';
+else
+    fprintf('DISFA location not found (or not defined)\n'); 
+end
+
+hog_data_dir = [DISFA_dir, '/hog_aligned_rigid/'];
+
+users = {'SN001';
+         'SN002';
+         'SN003';
+         'SN004';
+         'SN005';
+         'SN006';
+         'SN007';
+         'SN008';
+         'SN009';
+         'SN010';
+         'SN011';
+         'SN012';
+         'SN016';
+         'SN017';
+         'SN018';
+         'SN021';
+         'SN023';
+         'SN024';
+         'SN025';
+         'SN026';
+         'SN027';
+         'SN028';
+         'SN029';
+         'SN030';
+         'SN031';
+         'SN032';
+         'SN013'};

matlab_version/AU_training/data extraction/find_FERA2011.m

@@ -0,0 +1,31 @@
+if(exist('D:\Datasets\fera/au_training', 'file'))
+    FERA2011_dir = 'D:\Datasets\fera/au_training/';   
+    hog_data_dir = 'D:\Datasets\face_datasets\hog_aligned_rigid/';
+else
+    fprintf('FERA2011 location not found (or not defined)\n'); 
+end
+
+all_recs = {'train_001', 'train_002', 'train_003', 'train_004', 'train_005',...
+            'train_006', 'train_007', 'train_008', 'train_009', 'train_010',...
+            'train_011', 'train_012', 'train_013', 'train_014', 'train_015',...
+            'train_016', 'train_017', 'train_018', 'train_019', 'train_020',...
+            'train_021', 'train_022', 'train_023', 'train_024', 'train_025',...
+            'train_026', 'train_027', 'train_028', 'train_029', 'train_030',...
+            'train_031', 'train_032', 'train_033', 'train_034', 'train_035',...
+            'train_036', 'train_037', 'train_038', 'train_039', 'train_040',...
+            'train_041', 'train_042', 'train_043', 'train_044', 'train_045',...
+            'train_046', 'train_047', 'train_048', 'train_049', 'train_050',...
+            'train_051', 'train_052', 'train_053', 'train_054', 'train_055',...
+            'train_056', 'train_057', 'train_058', 'train_059', 'train_060',...
+            'train_061', 'train_062', 'train_063', 'train_064', 'train_065',...
+            'train_066', 'train_067', 'train_068', 'train_069', 'train_070',...
+            'train_071', 'train_072', 'train_073', 'train_074', 'train_075',...
+            'train_076', 'train_077', 'train_078', 'train_079', 'train_080',...
+            'train_081', 'train_082', 'train_083', 'train_084', 'train_085',...
+            'train_086', 'train_087'};
+        
+% Making them person independent        
+train_recs = all_recs(1:56);
+devel_recs = setdiff(all_recs, train_recs);
+
+all_aus = [1, 2, 4, 6, 7, 10, 12, 15, 17, 18, 25, 26];

matlab_version/AU_training/data extraction/find_SEMAINE.m

@@ -0,0 +1,22 @@
+if(exist('E:\datasets\FERA_2015\semaine/SEMAINE-Sessions/', 'file'))
+    SEMAINE_dir = 'E:\datasets\FERA_2015\semaine/SEMAINE-Sessions/';   
+elseif(exist('I:\datasets\FERA_2015\Semaine\SEMAINE-Sessions/', 'file'))
+    SEMAINE_dir = 'I:\datasets\FERA_2015\Semaine\SEMAINE-Sessions/';   
+elseif(exist('C:\tadas\face_datasets\fera_2015\semaine/SEMAINE-Sessions/', 'file'))
+    SEMAINE_dir = 'C:\tadas\face_datasets\fera_2015\semaine/SEMAINE-Sessions/';   
+elseif(exist('D:\datasets\face_datasets\fera_2015\semaine\SEMAINE-Sessions/', 'file'))
+    SEMAINE_dir = 'D:\datasets\face_datasets\fera_2015\semaine\SEMAINE-Sessions/';
+elseif(exist('D:\Datasets\FERA_2015\semaine\SEMAINE-Sessions/', 'file'))
+    SEMAINE_dir = 'D:\Datasets\FERA_2015\semaine\SEMAINE-Sessions/';    
+elseif(exist('D:/fera_2015/semaine/SEMAINE-Sessions/', 'file'))
+    SEMAINE_dir = 'D:/fera_2015/semaine/SEMAINE-Sessions/';
+else
+    fprintf('DISFA location not found (or not defined)\n'); 
+end
+
+if(exist('SEMAINE_dir', 'var'))
+    hog_data_dir = [SEMAINE_dir, '../processed_data/'];
+end
+
+train_recs = {'rec1', 'rec12', 'rec14', 'rec19', 'rec23', 'rec25', 'rec37', 'rec39', 'rec43', 'rec45', 'rec48', 'rec50', 'rec52', 'rec54', 'rec56', 'rec60'};
+devel_recs = {'rec9', 'rec13', 'rec15', 'rec20', 'rec24', 'rec26', 'rec38', 'rec42', 'rec44', 'rec46', 'rec49', 'rec51', 'rec53', 'rec55', 'rec58'};

matlab_version/AU_training/data extraction/find_UNBC.m

@@ -0,0 +1,17 @@
+if(exist('D:\Datasets\UNBC/', 'file'))
+    UNBC_dir = 'D:\Datasets\UNBC/';   
+    hog_data_dir = 'D:\Datasets\face_datasets\hog_aligned_rigid';
+else
+    fprintf('UNBC location not found (or not defined)\n'); 
+end
+
+all_recs = {'042-ll042', '043-jh043', '047-jl047', '048-aa048', '049-bm049',...
+            '052-dr052', '059-fn059', '064-ak064', '066-mg066', '080-bn080',...
+            '092-ch092', '095-tv095', '096-bg096', '097-gf097', '101-mg101',...
+            '103-jk103', '106-nm106', '107-hs107', '108-th108', '109-ib109',...
+            '115-jy115', '120-kz120', '121-vw121', '123-jh123', '124-dn124'};
+        
+devel_recs = all_recs(1:5:25);
+train_recs = setdiff(all_recs, devel_recs);
+
+all_aus = [4, 6, 7, 9, 10, 12, 20, 25, 26, 43];

matlab_version/AU_training/data extraction/xml_io_tools_2010_11_05/base64decode.m

@@ -0,0 +1,117 @@
+function y = base64decode(x, outfname, alg)
+%BASE64DECODE Perform base64 decoding on a string.
+%
+% INPUT:
+%   x    - block of data to be decoded.  Can be a string or a numeric  
+%          vector containing integers in the range 0-255. Any character
+%          not part of the 65-character base64 subset set is silently
+%          ignored.  Characters occuring after a '=' padding character are 
+%          never decoded. If the length of the string to decode (after 
+%          ignoring non-base64 chars) is not a multiple of 4, then a 
+%          warning is generated.
+%
+%   outfname - if provided the binary date from decoded string will be
+%          saved into a file. Since Base64 coding is often used to embbed
+%          binary data in xml files, this option can be used to extract and
+%          save them.
+%
+%   alg  - Algorithm to use: can take values 'java' or 'matlab'. Optional
+%          variable defaulting to 'java' which is a little faster. If 
+%          'java' is chosen than core of the code is performed by a call to
+%          a java library. Optionally all operations can be performed using
+%          matleb code. 
+%
+% OUTPUT:
+%   y    - array of binary data returned as uint8 
+%
+%   This function is used to decode strings from the Base64 encoding specified
+%   in RFC 2045 - MIME (Multipurpose Internet Mail Extensions).  The Base64
+%   encoding is designed to represent arbitrary sequences of octets in a form
+%   that need not be humanly readable.  A 65-character subset ([A-Za-z0-9+/=])
+%   of US-ASCII is used, enabling 6 bits to be represented per printable
+%   character.
+%
+%   See also BASE64ENCODE.
+%
+%   Written by Jarek Tuszynski, SAIC, jaroslaw.w.tuszynski_at_saic.com
+%
+%   Matlab version based on 2004 code by Peter J. Acklam
+%   E-mail:      pjacklam@online.no
+%   URL:         http://home.online.no/~pjacklam
+%   http://home.online.no/~pjacklam/matlab/software/util/datautil/base64encode.m
+
+if nargin<3, alg='java';  end
+if nargin<2, outfname=''; end
+
+%% if x happen to be a filename than read the file
+if (numel(x)<256)
+  if (exist(x, 'file')==2)
+    fid = fopen(x,'rb');
+    x = fread(fid, 'uint8');   
+    fclose(fid);
+  end
+end
+x = uint8(x(:)); % unify format
+
+%% Perform conversion
+switch (alg)
+  case 'java' 
+    base64 = org.apache.commons.codec.binary.Base64;
+    y = base64.decode(x);
+    y = mod(int16(y),256); % convert from int8 to uint8
+  case 'matlab'
+    %%  Perform the mapping
+    %   A-Z  ->  0  - 25
+    %   a-z  ->  26 - 51
+    %   0-9  ->  52 - 61
+    %   + -  ->  62       '-' is URL_SAFE alternative
+    %   / _  ->  63       '_' is URL_SAFE alternative
+    map = uint8(zeros(1,256)+65);
+    map(uint8(['A':'Z', 'a':'z', '0':'9', '+/=']))= 0:64;
+    map(uint8('-_'))= 62:63;  % URL_SAFE alternatives
+    x = map(x);  % mapping
+    
+    x(x>64)=[]; % remove non-base64 chars
+    if rem(numel(x), 4)
+      warning('Length of base64 data not a multiple of 4; padding input.');
+    end
+    x(x==64)=[]; % remove padding characters
+    
+    %% add padding and reshape
+    nebytes = length(x);         % number of encoded bytes
+    nchunks = ceil(nebytes/4);   % number of chunks/groups
+    if rem(nebytes, 4)>0
+      x(end+1 : 4*nchunks) = 0;  % add padding
+    end
+    x = reshape(uint8(x), 4, nchunks);
+    y = repmat(uint8(0), 3, nchunks);            % for the decoded data
+    
+    %% Rearrange every 4 bytes into 3 bytes
+    %    00aaaaaa 00bbbbbb 00cccccc 00dddddd
+    % to form
+    %    aaaaaabb bbbbcccc ccdddddd
+    y(1,:) = bitshift(x(1,:), 2);                 % 6 highest bits of y(1,:)
+    y(1,:) = bitor(y(1,:), bitshift(x(2,:), -4)); % 2 lowest  bits of y(1,:)
+    y(2,:) = bitshift(x(2,:), 4);                 % 4 highest bits of y(2,:)
+    y(2,:) = bitor(y(2,:), bitshift(x(3,:), -2)); % 4 lowest  bits of y(2,:)
+    y(3,:) = bitshift(x(3,:), 6);                 % 2 highest bits of y(3,:)
+    y(3,:) = bitor(y(3,:), x(4,:));               % 6 lowest  bits of y(3,:)
+    
+    %% remove extra padding
+    switch rem(nebytes, 4)
+      case 2
+        y = y(1:end-2);
+      case 3
+        y = y(1:end-1);
+    end
+end
+
+%% reshape to a row vector and make it a character array
+y = uint8(reshape(y, 1, numel(y)));
+
+%% save to file if needed
+if ~isempty(outfname)
+  fid = fopen(outfname,'wb');
+  fwrite(fid, y, 'uint8');  
+  fclose(fid);
+end

matlab_version/AU_training/data extraction/xml_io_tools_2010_11_05/base64encode.m

@@ -0,0 +1,138 @@
+function y = base64encode(x, alg, isChunked, url_safe)
+%BASE64ENCODE Perform base64 encoding on a string.
+% INPUT:
+%   x    - block of data to be encoded.  Can be a string or a numeric
+%          vector containing integers in the range 0-255.
+%   alg  - Algorithm to use: can take values 'java' or 'matlab'. Optional
+%          variable defaulting to 'java' which is a little faster. If
+%          'java' is chosen than core of the code is performed by a call to
+%          a java library. Optionally all operations can be performed using
+%          matleb code.
+%   isChunked - encode output into 76 character blocks. The returned 
+%          encoded string is broken into lines of no more than
+%          76 characters each, and each line will end with EOL. Notice that
+%          if resulting string is saved as part of an xml file, those EOL's
+%          are often stripped by xmlwrite funtrion prior to saving.      
+%   url_safe - use Modified Base64 for URL applications ('base64url'
+%   encoding) "Base64 alphabet" ([A-Za-z0-9-_=]). 
+%
+%
+% OUTPUT:
+%   y    - character array using only "Base64 alphabet" characters 
+%
+%   This function may be used to encode strings into the Base64 encoding
+%   specified in RFC 2045 - MIME (Multipurpose Internet Mail Extensions).  
+%   The Base64 encoding is designed to represent arbitrary sequences of 
+%   octets in a form that need not be humanly readable.  A 65-character 
+%   subset ([A-Za-z0-9+/=]) of US-ASCII is used, enabling 6 bits to be 
+%   represented per printable character.
+%
+%   See also BASE64DECODE.
+%
+%   Written by Jarek Tuszynski, SAIC, jaroslaw.w.tuszynski_at_saic.com
+%
+%   Matlab version based on 2004 code by Peter J. Acklam
+%   E-mail:      pjacklam@online.no
+%   URL:         http://home.online.no/~pjacklam
+%   http://home.online.no/~pjacklam/matlab/software/util/datautil/base64encode.m
+
+if nargin<2, alg='java';      end
+if nargin<3, isChunked=false; end
+if ~islogical(isChunked) 
+  if isnumeric(isChunked)
+    isChunked=(isChunked>0);
+  else
+    isChunked=false;
+  end 
+end
+if nargin<4, url_safe=false; end
+if ~islogical(url_safe) 
+  if isnumeric(url_safe)
+    url_safe=(url_safe>0);
+  else
+    url_safe=false;
+  end 
+end
+
+
+%% if x happen to be a filename than read the file
+if (numel(x)<256)
+  if (exist(x, 'file')==2)
+    fid = fopen(x,'rb');
+    x = fread(fid, 'uint8');             % read image file as a raw binary
+    fclose(fid);
+  end
+end
+
+%% Perform conversion
+switch (alg)
+  case 'java'
+    base64 = org.apache.commons.codec.binary.Base64;
+    y = base64.encodeBase64(x, isChunked); 
+    if url_safe
+      y = strrep(y,'=','-');
+      y = strrep(y,'/','_');
+    end
+    
+  case 'matlab'
+    
+    %% add padding if necessary, to make the length of x a multiple of 3
+    x   = uint8(x(:));
+    ndbytes = length(x);                 % number of decoded bytes
+    nchunks = ceil(ndbytes / 3);         % number of chunks/groups
+    if rem(ndbytes, 3)>0
+      x(end+1 : 3*nchunks) = 0;          % add padding
+    end
+    x = reshape(x, [3, nchunks]);        % reshape the data
+    y = repmat(uint8(0), 4, nchunks);    % for the encoded data
+    
+    %% Split up every 3 bytes into 4 pieces
+    %    aaaaaabb bbbbcccc ccdddddd
+    % to form
+    %    00aaaaaa 00bbbbbb 00cccccc 00dddddd
+    y(1,:) = bitshift(x(1,:), -2);                  % 6 highest bits of x(1,:)
+    y(2,:) = bitshift(bitand(x(1,:), 3), 4);        % 2 lowest  bits of x(1,:)
+    y(2,:) = bitor(y(2,:), bitshift(x(2,:), -4));   % 4 highest bits of x(2,:)
+    y(3,:) = bitshift(bitand(x(2,:), 15), 2);       % 4 lowest  bits of x(2,:)
+    y(3,:) = bitor(y(3,:), bitshift(x(3,:), -6));   % 2 highest bits of x(3,:)
+    y(4,:) = bitand(x(3,:), 63);                    % 6 lowest  bits of x(3,:)
+    
+    %% Perform the mapping
+    %   0  - 25  ->  A-Z
+    %   26 - 51  ->  a-z
+    %   52 - 61  ->  0-9
+    %   62       ->  +
+    %   63       ->  /
+    map = ['A':'Z', 'a':'z', '0':'9', '+/'];
+    if (url_safe), map(63:64)='-_'; end
+    y = map(y(:)+1);
+    
+    %% Add padding if necessary.
+    npbytes = 3 * nchunks - ndbytes;    % number of padding bytes
+    if npbytes>0
+      y(end-npbytes+1 : end) = '=';     % '=' is used for padding
+    end
+    
+    %% break into lines with length LineLength
+    if (isChunked)
+      eol = sprintf('\n');
+      nebytes = numel(y);
+      nlines  = ceil(nebytes / 76);     % number of lines
+      neolbytes = length(eol);          % number of bytes in eol string
+      
+      % pad data so it becomes a multiple of 76 elements
+      y(nebytes + 1 : 76 * nlines) = 0;
+      y = reshape(y, 76, nlines);
+      
+      % insert eol strings
+      y(end + 1 : end + neolbytes, :) = eol(:, ones(1, nlines));
+      
+      % remove padding, but keep the last eol string
+      m = nebytes + neolbytes * (nlines - 1);
+      n = (76+neolbytes)*nlines - neolbytes;
+      y(m+1 : n) = [];
+    end
+end
+
+%% reshape to a row vector and make it a character array
+y = char(reshape(y, 1, numel(y)));

matlab_version/AU_training/data extraction/xml_io_tools_2010_11_05/gen_object_display.m

@@ -0,0 +1,143 @@
+function gen_object_display( obj_struct,indent )
+%
+% gen_object_display - general function to display an object's content
+%
+% format:   gen_object_display( obj_struct,indent )
+%
+% input:    obj_struct  - a copy of the object stored inside a structure
+%           indent      - amount of "indent" when printing to the screen
+%
+% output:   to the screen
+%
+% example:  gen_object_display( struct( my_object_handle) );
+%           gen_object_display( ny_structure );
+%
+% Correction History:
+%  2006-11-01 - Jarek Tuszynski - added support for struct arrays
+
+%% handle insufficient input
+if ( nargin == 0 )
+  help gen_object_display;
+  return;
+elseif (nargin == 1)
+  indent = 1;
+end
+
+%% check input for errors
+% if ~isstruct( obj_struct )
+%     fprintf( '\n\n\tMake sure that ''obj_struct'' is a struct type\n' );
+%     return
+% end
+
+% if (iscell( obj_struct ))
+%   for i =1:length(obj_struct)
+%     gen_object_display( obj_struct{i},indent + 2 );
+%   end
+%   return
+% end
+if ~isstruct( obj_struct )
+  space = sprintf( sprintf( '%%%ds',indent ),' ' );
+  fprintf( '   %s', space);
+  disp(obj_struct);
+  return
+end
+
+% find the longest name
+field_list      = fieldnames( obj_struct );
+max_strlen      = 0;
+for idx = 1:length( field_list )
+  max_strlen  = max( max_strlen,length(field_list{idx}) );
+end
+
+%% setup the display format (spacing)
+space       = sprintf( sprintf( '%%%ds',indent ),' ' );
+name_format = sprintf( '   %s%%%ds: ', space, max_strlen );
+name_format2= sprintf( '     %s%%%ds', space, max_strlen );
+max_displen = 110 - max_strlen - indent;
+
+%% display each field, if it is not too long
+for iItem = 1:length( obj_struct ) % loop added  by JT
+  for idx = 1:length( field_list )
+    
+    % prepare field name to be displayed
+    name = sprintf( name_format,field_list{idx} );
+    %temp = getfield( obj_struct,field_list{idx} ); % original by OG
+    temp = obj_struct(iItem).(field_list{idx});    % modification by JT
+    
+    % proceed according the variable's type
+    switch (1)
+      case islogical( temp ), % case added by JT
+        if isscalar(temp)
+          if (temp)
+            fprintf( '%strue\n',name );
+          else
+            fprintf( '%sfalse\n',name );
+          end
+        else
+          fprintf( '%s[%dx%d logical]\n',name,size(temp,1),size(temp,2) );
+        end
+      case ischar( temp ),
+        if (length(temp)<max_displen )
+          fprintf( '%s''%s''\n',name,temp' );
+        else
+          fprintf( '%s[%dx%d char]\n',name,size(temp,1),size(temp,2) );
+        end
+      case isnumeric( temp ),
+        if (size( temp,1 )==1 )
+          temp_b = num2str( temp );
+          if (length(temp_b)<max_displen )
+            fprintf( '%s[%s]\n',name,temp_b );
+          else
+            fprintf( '%s[%dx%d double]\n',name,size(temp,1),size(temp,2) );
+          end
+        else
+          fprintf( '%s[%dx%d double]\n',name,size(temp,1),size(temp,2) );
+        end
+      case iscell( temp ),
+        if (numel(temp)<10 && (isvector(temp) || isscalar(temp)))
+          fprintf( '%s[%dx%d cell] = \n',name,size(temp,1),size(temp,2) );
+          %disp(temp)
+          for r =1:numel(temp)
+            gen_object_display( temp{r},indent + max_strlen + 2 );
+            fprintf('\n');
+          end
+        elseif (numel(temp)<10)
+          fprintf( '%s[%dx%d cell] = \n',name,size(temp,1),size(temp,2) );
+          for r =1:size(temp,1)
+            gen_object_display( temp(r,:),indent + max_strlen + 2 );
+          end
+        else
+          fprintf( '%s[%dx%d cell]\n',name,size(temp,1),size(temp,2) );
+        end
+      case isstruct( temp ),  
+        fprintf( '%s[%dx%d struct]\n',name,size(temp,1),size(temp,2) );
+        if (indent<80)
+          if (numel(temp)<10 && (isvector(temp) || isscalar(temp))) 
+            gen_object_display( temp,indent + max_strlen + 2 );
+          elseif (numel(temp)<10)
+            name2 = sprintf( name_format2,field_list{idx} );
+            for r =1:size(temp,1)
+              for c =1:size(temp,2)
+                fprintf( '%s(%d,%d) =\n',name2,r,c );
+                gen_object_display( temp(r,c),indent + max_strlen + 3 );
+              end
+            end
+          end
+        end
+      case isobject( temp ),  fprintf( '%s[inherent object]\n',name );
+        if (indent<80)
+          cmd = sprintf( 'display( obj_struct.%s,%d );',field_list{idx},indent + max_strlen + 2 );
+          eval( cmd );
+        end
+      otherwise,
+        fprintf( '%s',name );
+        try
+          fprintf( temp );
+        catch %#ok<CTCH>
+          fprintf( '[No method to display type]' );
+        end
+        fprintf( '\n' );
+    end
+  end
+  if (length(obj_struct)>1), fprintf('\n'); end % added by JT
+end                                             % added by JT

matlab_version/AU_training/data extraction/xml_io_tools_2010_11_05/html/test.html

@@ -0,0 +1,21 @@
+<?xml version="1.0" encoding="utf-8"?>
+<MyTree>
+   <table border="1">
+      <tr>
+         <td>Apples</td>
+         <td>44%</td>
+      </tr>
+      <tr>
+         <td>Bannanas</td>
+         <td>23%</td>
+      </tr>
+      <tr>
+         <td>Oranges</td>
+         <td>13%</td>
+      </tr>
+      <tr>
+         <td>Other</td>
+         <td>10%</td>
+      </tr>
+   </table>
+</MyTree>

matlab_version/AU_training/data extraction/xml_io_tools_2010_11_05/license.txt

@@ -0,0 +1,24 @@
+Copyright (c) 2007, Jaroslaw Tuszynski
+All rights reserved.
+
+Redistribution and use in source and binary forms, with or without
+modification, are permitted provided that the following conditions are
+met:
+
+    * Redistributions of source code must retain the above copyright
+      notice, this list of conditions and the following disclaimer.
+    * Redistributions in binary form must reproduce the above copyright
+      notice, this list of conditions and the following disclaimer in
+      the documentation and/or other materials provided with the distribution
+
+THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
+AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
+IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE
+ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE
+LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR
+CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF
+SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS
+INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN
+CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE)
+ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE
+POSSIBILITY OF SUCH DAMAGE.

matlab_version/AU_training/data extraction/xml_io_tools_2010_11_05/test_file.xml

@@ -0,0 +1,22 @@
+<?xml version="1.0" encoding="utf-8" ?> 
+<?xml-stylesheet type="text/css" href="foo.css"?>
+<!-- This is a Global Comment -->
+<aaa xmlns:xsi="http://www.foo.org">
+  <?ProcInst type="local processing instruction"?>
+  <!-- local comment 1 -->
+  bbb
+  <!-- local comment 2 -->
+  ccc
+  <matrix bad-name='fff'>
+    5e3+2*i, Inf
+    NaN,     pi
+  </matrix>
+  <ee_e> ee_e </ee_e>
+  <ff-f> ff-f </ff-f>
+  <ggög> ggög </ggög>
+  <![CDATA[
+    Here <ddd>xml</ddd> tags are treated as ...
+    ... text
+	]]>
+</aaa>
+

matlab_version/AU_training/data extraction/xml_io_tools_2010_11_05/xml_read.m

@@ -0,0 +1,550 @@
+function [tree, RootName, DOMnode] = xml_read(xmlfile, Pref)
+%XML_READ reads xml files and converts them into Matlab's struct tree.
+%
+% DESCRIPTION
+% tree = xml_read(xmlfile) reads 'xmlfile' into data structure 'tree'
+%
+% tree = xml_read(xmlfile, Pref) reads 'xmlfile' into data structure 'tree'
+% according to your preferences
+%
+% [tree, RootName, DOMnode] = xml_read(xmlfile) get additional information
+% about XML file
+%
+% INPUT:
+%  xmlfile	URL or filename of xml file to read
+%  Pref     Preferences:
+%    Pref.ItemName - default 'item' - name of a special tag used to itemize
+%                    cell arrays
+%    Pref.ReadAttr - default true - allow reading attributes
+%    Pref.ReadSpec - default true - allow reading special nodes
+%    Pref.Str2Num  - default 'smart' - convert strings that look like numbers
+%                   to numbers. Options: "always", "never", and "smart"
+%    Pref.KeepNS   - default true - keep or strip namespace info
+%    Pref.NoCells  - default true - force output to have no cell arrays
+%    Pref.Debug    - default false - show mode specific error messages
+%    Pref.NumLevels- default infinity - how many recursive levels are
+%      allowed. Can be used to speed up the function by prunning the tree.
+%    Pref.RootOnly - default true - output variable 'tree' corresponds to
+%      xml file root element, otherwise it correspond to the whole file.
+%    Pref.CellItem - default 'true' - leave 'item' nodes in cell notation.
+% OUTPUT:
+%  tree         tree of structs and/or cell arrays corresponding to xml file
+%  RootName     XML tag name used for root (top level) node.
+%               Optionally it can be a string cell array storing: Name of
+%               root node, document "Processing Instructions" data and
+%               document "comment" string
+%  DOMnode      output of xmlread
+%
+% DETAILS:
+% Function xml_read first calls MATLAB's xmlread function and than
+% converts its output ('Document Object Model' tree of Java objects)
+% to tree of MATLAB struct's. The output is in format of nested structs
+% and cells. In the output data structure field names are based on
+% XML tags, except in cases when tags produce illegal variable names.
+%
+% Several special xml node types result in special tags for fields of
+% 'tree' nodes:
+%  - node.CONTENT - stores data section of the node if other fields are
+%    present. Usually data section is stored directly in 'node'.
+%  - node.ATTRIBUTE.name - stores node's attribute called 'name'.
+%  - node.COMMENT - stores node's comment section (string). For global
+%    comments see "RootName" output variable.
+%  - node.CDATA_SECTION - stores node's CDATA section (string).
+%  - node.PROCESSING_INSTRUCTIONS - stores "processing instruction" child
+%    node. For global "processing instructions" see "RootName" output variable.
+%  - other special node types like: document fragment nodes, document type
+%   nodes, entity nodes, notation nodes and processing instruction nodes
+%   will be treated like regular nodes
+%
+% EXAMPLES:
+%   MyTree=[];
+%   MyTree.MyNumber = 13;
+%   MyTree.MyString = 'Hello World';
+%   xml_write('test.xml', MyTree);
+%   [tree treeName] = xml_read ('test.xml');
+%   disp(treeName)
+%   gen_object_display()
+%   % See also xml_examples.m
+%
+% See also:
+%   xml_write, xmlread, xmlwrite
+%
+% Written by Jarek Tuszynski, SAIC, jaroslaw.w.tuszynski_at_saic.com
+% References:
+%  - Function inspired by Example 3 found in xmlread function.
+%  - Output data structures inspired by xml_toolbox structures.
+
+%% default preferences
+DPref.TableName  = {'tr','td'}; % name of a special tags used to itemize 2D cell arrays
+DPref.ItemName  = 'item'; % name of a special tag used to itemize 1D cell arrays
+DPref.CellItem  = false;  % leave 'item' nodes in cell notation
+DPref.ReadAttr  = true;   % allow reading attributes
+DPref.ReadSpec  = true;   % allow reading special nodes: comments, CData, etc.
+DPref.KeepNS    = true;   % Keep or strip namespace info
+DPref.Str2Num   = 'smart';% convert strings that look like numbers to numbers
+DPref.NoCells   = true;   % force output to have no cell arrays
+DPref.NumLevels = 1e10;   % number of recurence levels
+DPref.PreserveSpace = false; % Preserve or delete spaces at the beggining and the end of stings?
+RootOnly        = true;   % return root node  with no top level special nodes
+Debug           = false;  % show specific errors (true) or general (false)?
+tree            = [];
+RootName        = [];
+
+%% Check Matlab Version
+v = ver('MATLAB');
+version = str2double(regexp(v.Version, '\d.\d','match','once'));
+if (version<7.1)
+  error('Your MATLAB version is too old. You need version 7.1 or newer.');
+end
+
+%% read user preferences
+if (nargin>1)
+  if (isfield(Pref, 'TableName')), DPref.TableName = Pref.TableName; end
+  if (isfield(Pref, 'ItemName' )), DPref.ItemName  = Pref.ItemName;  end
+  if (isfield(Pref, 'CellItem' )), DPref.CellItem  = Pref.CellItem;  end
+  if (isfield(Pref, 'Str2Num'  )), DPref.Str2Num   = Pref.Str2Num ;  end
+  if (isfield(Pref, 'NoCells'  )), DPref.NoCells   = Pref.NoCells ;  end
+  if (isfield(Pref, 'NumLevels')), DPref.NumLevels = Pref.NumLevels; end
+  if (isfield(Pref, 'ReadAttr' )), DPref.ReadAttr  = Pref.ReadAttr;  end
+  if (isfield(Pref, 'ReadSpec' )), DPref.ReadSpec  = Pref.ReadSpec;  end
+  if (isfield(Pref, 'KeepNS'   )), DPref.KeepNS    = Pref.KeepNS;    end
+  if (isfield(Pref, 'RootOnly' )), RootOnly        = Pref.RootOnly;  end
+  if (isfield(Pref, 'Debug'    )), Debug           = Pref.Debug   ;  end
+  if (isfield(Pref, 'PreserveSpace')), DPref.PreserveSpace = Pref.PreserveSpace; end
+end
+if ischar(DPref.Str2Num), % convert from character description to numbers
+  DPref.Str2Num = find(strcmpi(DPref.Str2Num, {'never', 'smart', 'always'}))-1;
+  if isempty(DPref.Str2Num), DPref.Str2Num=1; end % 1-smart by default
+end
+
+%% read xml file using Matlab function
+if isa(xmlfile, 'org.apache.xerces.dom.DeferredDocumentImpl');
+  % if xmlfile is a DOMnode than skip the call to xmlread
+  try
+    try
+      DOMnode = xmlfile;
+    catch ME
+      error('Invalid DOM node: \n%s.', getReport(ME));
+    end
+  catch %#ok<CTCH> catch for mablab versions prior to 7.5
+    error('Invalid DOM node. \n');
+  end
+else         % we assume xmlfile is a filename
+  if (Debug) % in debuging mode crashes are allowed
+    DOMnode = xmlread(xmlfile);
+  else       % in normal mode crashes are not allowed
+    try
+      try
+        DOMnode = xmlread(xmlfile);
+      catch ME
+        error('Failed to read XML file %s: \n%s',xmlfile, getReport(ME));
+      end
+    catch %#ok<CTCH> catch for mablab versions prior to 7.5
+      error('Failed to read XML file %s\n',xmlfile);
+    end
+  end
+end
+Node = DOMnode.getFirstChild;
+
+%% Find the Root node. Also store data from Global Comment and Processing
+%  Instruction nodes, if any.
+GlobalTextNodes = cell(1,3);
+GlobalProcInst  = [];
+GlobalComment   = [];
+GlobalDocType   = [];
+while (~isempty(Node))
+  if (Node.getNodeType==Node.ELEMENT_NODE)
+    RootNode=Node;
+  elseif (Node.getNodeType==Node.PROCESSING_INSTRUCTION_NODE)
+    data   = strtrim(char(Node.getData));
+    target = strtrim(char(Node.getTarget));
+    GlobalProcInst = [target, ' ', data];
+    GlobalTextNodes{2} = GlobalProcInst;
+  elseif (Node.getNodeType==Node.COMMENT_NODE)
+    GlobalComment = strtrim(char(Node.getData));
+    GlobalTextNodes{3} = GlobalComment;
+    %   elseif (Node.getNodeType==Node.DOCUMENT_TYPE_NODE)
+    %     GlobalTextNodes{4} = GlobalDocType;
+  end
+  Node = Node.getNextSibling;
+end
+
+%% parse xml file through calls to recursive DOMnode2struct function
+if (Debug)   % in debuging mode crashes are allowed
+  [tree RootName] = DOMnode2struct(RootNode, DPref, 1);
+else         % in normal mode crashes are not allowed
+  try
+    try
+      [tree RootName] = DOMnode2struct(RootNode, DPref, 1);
+    catch ME
+      error('Unable to parse XML file %s: \n %s.',xmlfile, getReport(ME));
+    end
+  catch %#ok<CTCH> catch for mablab versions prior to 7.5
+    error('Unable to parse XML file %s.',xmlfile);
+  end
+end
+
+%% If there were any Global Text nodes than return them
+if (~RootOnly)
+  if (~isempty(GlobalProcInst) && DPref.ReadSpec)
+    t.PROCESSING_INSTRUCTION = GlobalProcInst;
+  end
+  if (~isempty(GlobalComment) && DPref.ReadSpec)
+    t.COMMENT = GlobalComment;
+  end
+  if (~isempty(GlobalDocType) && DPref.ReadSpec)
+    t.DOCUMENT_TYPE = GlobalDocType;
+  end
+  t.(RootName) = tree;
+  tree=t;
+end
+if (~isempty(GlobalTextNodes))
+  GlobalTextNodes{1} = RootName;
+  RootName = GlobalTextNodes;
+end
+
+
+%% =======================================================================
+%  === DOMnode2struct Function ===========================================
+%  =======================================================================
+function [s TagName LeafNode] = DOMnode2struct(node, Pref, level)
+
+%% === Step 1: Get node name and check if it is a leaf node ==============
+[TagName LeafNode] = NodeName(node, Pref.KeepNS);
+s = []; % initialize output structure
+
+%% === Step 2: Process Leaf Nodes (nodes with no children) ===============
+if (LeafNode)
+  if (LeafNode>1 && ~Pref.ReadSpec), LeafNode=-1; end % tags only so ignore special nodes
+  if (LeafNode>0) % supported leaf node types
+    try
+      try         % use try-catch: errors here are often due to VERY large fields (like images) that overflow java memory
+        s = char(node.getData);
+        if (isempty(s)), s = ' '; end                              % make it a string
+        % for some reason current xmlread 'creates' a lot of empty text
+        % fields with first chatacter=10 - those will be deleted.
+        if (~Pref.PreserveSpace || s(1)==10) 
+          if (isspace(s(1)) || isspace(s(end))), s = strtrim(s); end % trim speces is any
+        end
+        if (LeafNode==1), s=str2var(s, Pref.Str2Num, 0); end       % convert to number(s) if needed
+      catch ME    % catch for mablab versions 7.5 and higher
+        warning('xml_io_tools:read:LeafRead', ...
+          'This leaf node could not be read and was ignored. ');
+        getReport(ME)
+      end
+    catch         %#ok<CTCH> catch for mablab versions prior to 7.5
+      warning('xml_io_tools:read:LeafRead', ...
+        'This leaf node could not be read and was ignored. ');
+    end
+  end
+  if (LeafNode==3) % ProcessingInstructions need special treatment
+    target = strtrim(char(node.getTarget));
+    s = [target, ' ', s];
+  end
+  return % We are done the rest of the function deals with nodes with children
+end
+if (level>Pref.NumLevels+1), return; end % if Pref.NumLevels is reached than we are done
+
+%% === Step 3: Process nodes with children ===============================
+if (node.hasChildNodes)        % children present
+  Child  = node.getChildNodes; % create array of children nodes
+  nChild = Child.getLength;    % number of children
+  
+  % --- pass 1: how many children with each name -----------------------
+  f = [];
+  for iChild = 1:nChild        % read in each child
+    [cname cLeaf] = NodeName(Child.item(iChild-1), Pref.KeepNS);
+    if (cLeaf<0), continue; end % unsupported leaf node types
+    if (~isfield(f,cname)),
+      f.(cname)=0;           % initialize first time I see this name
+    end
+    f.(cname) = f.(cname)+1; % add to the counter
+  end                        % end for iChild
+  % text_nodes become CONTENT & for some reason current xmlread 'creates' a
+  % lot of empty text fields so f.CONTENT value should not be trusted
+  if (isfield(f,'CONTENT') && f.CONTENT>2), f.CONTENT=2; end
+  
+  % --- pass 2: store all the children as struct of cell arrays ----------
+  for iChild = 1:nChild        % read in each child
+    [c cname cLeaf] = DOMnode2struct(Child.item(iChild-1), Pref, level+1);
+    if (cLeaf && isempty(c))   % if empty leaf node than skip
+      continue;                % usually empty text node or one of unhandled node types
+    elseif (nChild==1 && cLeaf==1)
+      s=c;                     % shortcut for a common case
+    else                       % if normal node
+      if (level>Pref.NumLevels), continue; end
+      n = f.(cname);           % how many of them in the array so far?
+      if (~isfield(s,cname))   % encountered this name for the first time
+        if (n==1)              % if there will be only one of them ...
+          s.(cname) = c;       % than save it in format it came in
+        else                   % if there will be many of them ...
+          s.(cname) = cell(1,n);
+          s.(cname){1} = c;    % than save as cell array
+        end
+        f.(cname) = 1;         % initialize the counter
+      else                     % already have seen this name
+        s.(cname){n+1} = c;    % add to the array
+        f.(cname) = n+1;       % add to the array counter
+      end
+    end
+  end   % for iChild
+end % end if (node.hasChildNodes)
+
+%% === Step 4: Post-process struct's created for nodes with children =====
+if (isstruct(s))
+  fields = fieldnames(s);
+  nField = length(fields);
+  
+  % Detect structure that looks like Html table and store it in cell Matrix
+  if (nField==1 && strcmpi(fields{1},Pref.TableName{1}))
+    tr = s.(Pref.TableName{1});
+    fields2 = fieldnames(tr{1});
+    if (length(fields2)==1 && strcmpi(fields2{1},Pref.TableName{2}))
+      % This seems to be a special structure such that for 
+      % Pref.TableName = {'tr','td'} 's' corresponds to 
+      %    <tr> <td>M11</td> <td>M12</td> </tr>
+      %    <tr> <td>M12</td> <td>M22</td> </tr>
+      % Recognize it as encoding for 2D struct
+      nr = length(tr);
+      for r = 1:nr
+        row = tr{r}.(Pref.TableName{2});
+        Table(r,1:length(row)) = row; %#ok<AGROW>
+      end
+      s = Table;
+    end
+  end
+
+  % --- Post-processing: convert 'struct of cell-arrays' to 'array of structs'
+  % Example: let say s has 3 fields s.a, s.b & s.c  and each field is an
+  % cell-array with more than one cell-element and all 3 have the same length.
+  % Then change it to array of structs, each with single cell.
+  % This way element s.a{1} will be now accessed through s(1).a
+  vec = zeros(size(fields));
+  for i=1:nField, vec(i) = f.(fields{i}); end
+  if (numel(vec)>1 && vec(1)>1 && var(vec)==0)  % convert from struct of
+    s = cell2struct(struct2cell(s), fields, 1); % arrays to array of struct
+  end % if anyone knows better way to do above conversion please let me know.
+
+end
+
+%% === Step 5: Process nodes with attributes =============================
+if (node.hasAttributes && Pref.ReadAttr)
+  if (~isstruct(s)),              % make into struct if is not already
+    ss.CONTENT=s;
+    s=ss;
+  end
+  Attr  = node.getAttributes;     % list of all attributes
+  for iAttr = 1:Attr.getLength    % for each attribute
+    name  = char(Attr.item(iAttr-1).getName);  % attribute name
+    name  = str2varName(name, Pref.KeepNS);    % fix name if needed
+    value = char(Attr.item(iAttr-1).getValue); % attribute value
+    value = str2var(value, Pref.Str2Num, 1);   % convert to number if possible
+    s.ATTRIBUTE.(name) = value;   % save again
+  end                             % end iAttr loop
+end % done with attributes
+if (~isstruct(s)), return; end %The rest of the code deals with struct's
+
+%% === Post-processing: fields of "s"
+% convert  'cell-array of structs' to 'arrays of structs'
+fields = fieldnames(s);     % get field names
+nField = length(fields);
+for iItem=1:length(s)       % for each struct in the array - usually one
+  for iField=1:length(fields)
+    field = fields{iField}; % get field name
+    % if this is an 'item' field and user want to leave those as cells
+    % than skip this one
+    if (strcmpi(field, Pref.ItemName) && Pref.CellItem), continue; end
+    x = s(iItem).(field);
+    if (iscell(x) && all(cellfun(@isstruct,x(:))) && numel(x)>1) % it's cell-array of structs
+      % numel(x)>1 check is to keep 1 cell-arrays created when Pref.CellItem=1
+      try                           % this operation fails sometimes
+        % example: change s(1).a{1}.b='jack'; s(1).a{2}.b='john'; to
+        % more convinient s(1).a(1).b='jack'; s(1).a(2).b='john';
+        s(iItem).(field) = [x{:}]';  %#ok<AGROW> % converted to arrays of structs
+      catch %#ok<CTCH>
+        % above operation will fail if s(1).a{1} and s(1).a{2} have
+        % different fields. If desired, function forceCell2Struct can force
+        % them to the same field structure by adding empty fields.
+        if (Pref.NoCells)
+          s(iItem).(field) = forceCell2Struct(x); %#ok<AGROW>
+        end
+      end % end catch
+    end
+  end
+end
+
+%% === Step 4: Post-process struct's created for nodes with children =====
+
+% --- Post-processing: remove special 'item' tags ---------------------
+% many xml writes (including xml_write) use a special keyword to mark
+% arrays of nodes (see xml_write for examples). The code below converts
+% s.item to s.CONTENT
+ItemContent = false;
+if (isfield(s,Pref.ItemName))
+  s.CONTENT = s.(Pref.ItemName);
+  s = rmfield(s,Pref.ItemName);
+  ItemContent = Pref.CellItem; % if CellItem than keep s.CONTENT as cells
+end
+
+% --- Post-processing: clean up CONTENT tags ---------------------
+% if s.CONTENT is a cell-array with empty elements at the end than trim
+% the length of this cell-array. Also if s.CONTENT is the only field than
+% remove .CONTENT part and store it as s.
+if (isfield(s,'CONTENT'))
+  if (iscell(s.CONTENT) && isvector(s.CONTENT))
+    x = s.CONTENT;
+    for i=numel(x):-1:1, if ~isempty(x{i}), break; end; end
+    if (i==1 && ~ItemContent)
+      s.CONTENT = x{1};   % delete cell structure
+    else
+      s.CONTENT = x(1:i); % delete empty cells
+    end
+  end
+  if (nField==1)
+    if (ItemContent)
+      ss = s.CONTENT;       % only child: remove a level but ensure output is a cell-array
+      s=[]; s{1}=ss;
+    else
+      s = s.CONTENT;        % only child: remove a level
+    end
+  end
+end
+
+
+
+%% =======================================================================
+%  === forceCell2Struct Function =========================================
+%  =======================================================================
+function s = forceCell2Struct(x)
+% Convert cell-array of structs, where not all of structs have the same
+% fields, to a single array of structs
+
+%% Convert 1D cell array of structs to 2D cell array, where each row
+% represents item in original array and each column corresponds to a unique
+% field name. Array "AllFields" store fieldnames for each column
+AllFields = fieldnames(x{1});     % get field names of the first struct
+CellMat = cell(length(x), length(AllFields));
+for iItem=1:length(x)
+  fields = fieldnames(x{iItem});  % get field names of the next struct
+  for iField=1:length(fields)     % inspect all fieldnames and find those
+    field = fields{iField};       % get field name
+    col = find(strcmp(field,AllFields),1);
+    if isempty(col)               % no column for such fieldname yet
+      AllFields = [AllFields; field]; %#ok<AGROW>
+      col = length(AllFields);    % create a new column for it
+    end
+    CellMat{iItem,col} = x{iItem}.(field); % store rearanged data
+  end
+end
+%% Convert 2D cell array to array of structs
+s = cell2struct(CellMat, AllFields, 2);
+
+%% =======================================================================
+%  === str2var Function ==================================================
+%  =======================================================================
+function val=str2var(str, option, attribute)
+% Can this string 'str' be converted to a number? if so than do it.
+val = str;
+len = numel(str);
+if (len==0    || option==0), return; end % Str2Num="never" of empty string -> do not do enything
+if (len>10000 && option==1), return; end % Str2Num="smart" and string is very long -> probably base64 encoded binary
+digits = '(Inf)|(NaN)|(pi)|[\t\n\d\+\-\*\.ei EI\[\]\;\,]';
+s = regexprep(str, digits, ''); % remove all the digits and other allowed characters
+if (~all(~isempty(s)))          % if nothing left than this is probably a number
+  if (~isempty(strfind(str, ' '))), option=2; end %if str has white-spaces assume by default that it is not a date string
+  if (~isempty(strfind(str, '['))), option=2; end % same with brackets
+  str(strfind(str, '\n')) = ';';% parse data tables into 2D arrays, if any
+  if (option==1)                % the 'smart' option
+    try                         % try to convert to a date, like 2007-12-05
+      datenum(str);             % if successful than leave it as string
+    catch                       %#ok<CTCH> % if this is not a date than ...
+      option=2;                 % ... try converting to a number
+    end
+  end
+  if (option==2)
+    if (attribute)
+      num = str2double(str);      % try converting to a single number using sscanf function
+      if isnan(num), return; end  % So, it wasn't really a number after all    
+    else
+      num = str2num(str);         %#ok<ST2NM> % try converting to a single number or array using eval function
+    end
+    if(isnumeric(num) && numel(num)>0), val=num; end % if convertion to a single was succesful than save
+  end
+elseif ((str(1)=='[' && str(end)==']') || (str(1)=='{' && str(end)=='}')) % this looks like a (cell) array encoded as a string
+  try 
+    val = eval(str); 
+  catch              %#ok<CTCH>
+    val = str; 
+  end                     
+elseif (~attribute)   % see if it is a boolean array with no [] brackets
+  str1 = lower(str);
+  str1 = strrep(str1, 'false', '0');
+  str1 = strrep(str1, 'true' , '1');
+  s = regexprep(str1, '[01 \;\,]', ''); % remove all 0/1, spaces, commas and semicolons 
+  if (~all(~isempty(s)))          % if nothing left than this is probably a boolean array
+    num  = str2num(str1); %#ok<ST2NM>
+    if(isnumeric(num) && numel(num)>0), val = (num>0);  end % if convertion was succesful than save as logical
+  end
+end
+
+
+%% =======================================================================
+%  === str2varName Function ==============================================
+%  =======================================================================
+function str = str2varName(str, KeepNS)
+% convert a sting to a valid matlab variable name
+if(KeepNS)
+  str = regexprep(str,':','_COLON_', 'once', 'ignorecase');
+else
+  k = strfind(str,':');
+  if (~isempty(k))
+    str = str(k+1:end);
+  end
+end
+str = regexprep(str,'-','_DASH_'  ,'once', 'ignorecase');
+if (~isvarname(str)) && (~iskeyword(str))
+  str = genvarname(str);
+end
+
+%% =======================================================================
+%  === NodeName Function =================================================
+%  =======================================================================
+function [Name LeafNode] = NodeName(node, KeepNS)
+% get node name and make sure it is a valid variable name in Matlab.
+% also get node type:
+%   LeafNode=0 - normal element node,
+%   LeafNode=1 - text node
+%   LeafNode=2 - supported non-text leaf node,
+%   LeafNode=3 - supported processing instructions leaf node,
+%   LeafNode=-1 - unsupported non-text leaf node
+switch (node.getNodeType)
+  case node.ELEMENT_NODE
+    Name = char(node.getNodeName);% capture name of the node
+    Name = str2varName(Name, KeepNS);     % if Name is not a good variable name - fix it
+    LeafNode = 0;
+  case node.TEXT_NODE
+    Name = 'CONTENT';
+    LeafNode = 1;
+  case node.COMMENT_NODE
+    Name = 'COMMENT';
+    LeafNode = 2;
+  case node.CDATA_SECTION_NODE
+    Name = 'CDATA_SECTION';
+    LeafNode = 2;
+  case node.DOCUMENT_TYPE_NODE
+    Name = 'DOCUMENT_TYPE';
+    LeafNode = 2;
+  case node.PROCESSING_INSTRUCTION_NODE
+    Name = 'PROCESSING_INSTRUCTION';
+    LeafNode = 3;
+  otherwise
+    NodeType = {'ELEMENT','ATTRIBUTE','TEXT','CDATA_SECTION', ...
+      'ENTITY_REFERENCE', 'ENTITY', 'PROCESSING_INSTRUCTION', 'COMMENT',...
+      'DOCUMENT', 'DOCUMENT_TYPE', 'DOCUMENT_FRAGMENT', 'NOTATION'};
+    Name = char(node.getNodeName);% capture name of the node
+    warning('xml_io_tools:read:unkNode', ...
+      'Unknown node type encountered: %s_NODE (%s)', NodeType{node.getNodeType}, Name);
+    LeafNode = -1;
+end
+
+

matlab_version/AU_training/data extraction/xml_io_tools_2010_11_05/xml_tutorial_script.m

@@ -0,0 +1,914 @@
+%% Tutorial for xml_io_tools Package
+% *By Jarek Tuszynski*
+%
+% Package xml_io_tools can read XML files into MATLAB struct and writes 
+% MATLAB data types to XML files with help of simple interface to 
+% MATLAB's xmlwrite and xmlread functions.
+% 
+% Two function to simplify reading and writing XML files from MATLAB:
+%
+% * Function xml_read first calls MATLAB's xmlread function and than 
+% converts its output ('Document Object Model' tree of Java objects) 
+% to tree of MATLAB struct's. The output is in the format of nested 
+% structs and cells. In the output data structure field names are based on
+% XML tags.
+%
+% * Function xml_write first convert input tree of MATLAB structs and cells 
+% and other types to tree of 'Document Object Model' nodes, and then writes 
+% resulting object to XML file using MATLAB's xmlwrite function. .
+%
+%% This package can:
+% * Read most XML files, created inside and outside of MATLAB environment, 
+%   and convert them to MATLAB data structures.
+% * Write any MATLAB's struct tree to XML file
+% * Handle XML attributes and special XML nodes like comments, processing  
+%   instructions and CDATA sections
+% * Supports base64 encoding and decoding to allow handling embeded binary
+%   data
+% * Be studied, modified, customized, rewritten and used in other packages 
+%   without any limitations. All code is included and documented. Software
+%   is distributed under BSD Licence (included).   
+%
+%% This package does not:
+% * Guarantee to recover the same Matlab objects that were saved. If you 
+% need to be able to recover carbon copy of the structure that was saved 
+% than you will have to use one of the packages that uses special set of 
+% tags saved as xml attributes that help to guide the parsing of XML code. 
+% This package does not use those tags.
+% * Guarantee to work with older versions of MATLAB. Functions do not work
+% with versions of MATLAB prior to 7.1 (26-Jul-2005). 
+%
+%% Change History
+% * 2006-11-06 - original version
+% * 2006-11-26 - corrected xml_write to handle writing Matlab's column
+%   arrays to xml files. Bug discovered and diagnosed by Kalyan Dutta.
+% * 2006-11-28 - made changes to handle special node types like: 
+%   COMMENTS and CDATA sections 
+% * 2007-03-12 - Writing CDATA sections still did not worked. The problem 
+%   was diagnosed and fixed by Alberto Amaro. The fix involved rewriting
+%   xmlwrite to use Apache Xerces java files directly instead of MATLAB's 
+%   XMLUtils java class.
+% * 2007-06-21 - Fixed problem reported by Anna Kelbert in Reviews about 
+%   not writing attributes of ROOT node. Also: added support for Processing
+%   Instructions, added support for global text nodes: Processing
+%   Instructions and comments, allowed writing tag names with special
+%   characters
+% * 2007-07-20 - Added tutorial script file. Extended support for global
+%   text nodes. Added more Preference fields.
+% * 2008-01-23 - Fixed problem reported by Anna Krewet of converting dates 
+%   in format '2007-01-01' to numbers. Improved and added warning messages.
+%   Added detection of old Matlab versions incompatible with the library.
+%   Expanded documentation.
+% * 2008-06-23 - Fixed problem with writing 1D array reported by Mark Neil. 
+%   Extended xml_read's Pref.Num2Str to 3 settings (never, smart and always) 
+%   for better control. Added parameter Pref.KeepNS for keeping or ignoring 
+%   namespace data when reading. Fixed a bug related to writing 2D cell
+%   arrays brought up by Andrej's Mosat review. 
+% * 2008-09-11 - Resubmitting last upload - zip file is still old
+% * 2009-02-26 - Small changes. More error handling. More robust in case of
+%   large binary objects. Added support for Base64 encoding/decoding of
+%   binary objects (using functions by Peter J. Acklam).
+% * 2009-06-26 - changes to xml_read: added CellItem parameter to allow
+%   better control of reading files with 'item' notation (see comment by
+%   Shlomi); changed try-catch statements so xml_read would work for mablab
+%   versions prior to 7.5 (see Thomas Pilutti comment)
+% * 2009-12-03 - added PreserveSpace parameter for contolling empty string
+%   handling as suggested by Sebastiaan. Fix suggested by Michael Murphy.
+%   Fixed number recognition code as suggested by Yuan Ren.  
+% * 2010-05-04 - implemented fixes suggested by Dylan Reynolds from Airbus.  
+% * 2010-07-28 - implemented support for 2D arrays of cells and structs 
+%   suggested by Rodney Behn from MIT Lincoln Laboratory. Also attempted
+%   large scale cleanup of xml_write function
+% * 2010-08-18 - minor extension to allow better handling of logical
+%   scalars and arrays and function handles suggested by Andreas Richter 
+%   and others
+% * 2010-09-20 - allow reading and writing of sparse matrices. Improve
+%   reading of 1D boolean arrays.
+% * 2010-11-05 - Fix problem with empty cells reported by Richard Cotton;
+%   fixed issues with reading boolean arrays reported by Zohar Bar-Yehuda;
+%   Improved speed of base64 coding and decoding by switching to java based 
+%   code.
+%% Licence
+% The package is distributed under BSD License
+format compact; % viewing preference
+clear variables;
+type('license.txt')
+
+%% Write XML file based on a Struct using "xml_write"
+% Any MATLAB data struct can be saved to XML file.
+MyTree=[];
+MyTree.MyNumber = 13;
+MyTree.MyString = 'Hello World';
+xml_write('test.xml', MyTree);
+type('test.xml')
+
+%% Read XML file producing a Struct using "xml_read"
+[tree treeName] = xml_read ('test.xml');
+disp([treeName{1} ' ='])
+gen_object_display(tree)
+
+%% "Pref.XmlEngine" flag in "xml_write"
+% Occasionaly some operations are performed better by Apache Xerces XML 
+% engine than default xmlread function. That is why xml_write provide an 
+% option for choosing the underlaying xml engine. Code below performs the 
+% same operation as the previous section but using Apache Xerces XML engine.
+% Notice that in this case name of root element 
+% was passed as variable and not extracted from the variable name.
+Pref=[]; Pref.XmlEngine = 'Xerces';  % use Xerces xml generator directly
+xml_write('test.xml', MyTree, 'TreeOfMine', Pref);
+type('test.xml')
+
+%% Writing Struct with different type MATLAB arrays
+MyTree=[];
+MyTree.Empty   = [];                   % Empty variable
+MyTree.Num_1x1 = 13;                   % simple scalar
+MyTree.Vec_1x3 = [1 2 3];              % horizontal vector
+MyTree.Vec_4x1 = [1; 2; 3; 4];         % vertical vector
+MyTree.Mat_2x2 = [1, 2; 3, 4];         % 2D matrix
+MyTree.Cube_3D = reshape(1:8,[2 2 2]); % 3D array
+MyTree.String1 = '[2003 10 30]';       % number string with    [] brackets
+MyTree.String2 = ' 2003 10 30 ';       % number string without [] brackets
+MyTree.Logical_1x1 = false;            % single logical
+MyTree.Logical_2x2 = [false, true; true, false]; % 2D matrix of logicals
+MyTree.Logical_Str = 'False False	True True';
+MyTree.Int_2x2 = uint8([1 2;3 4]);     % 2D matrix of uint8 integers
+MyTree.Complex_1x1 = complex(1, 7);    % complex scalar
+MyTree.Complex_2x2 = complex([1 2;3 4],[2 2;7 7]); % 2D matrix of complex numbers
+MyTree.Sparse_9x9 = sparse(1:9,1:9,1); % sparse 9x9 matrix
+MyTree.Function = @sum;                % function handle
+xml_write('test.xml', MyTree);
+type('test.xml')
+
+%% Read Struct with MATLAB arrays
+% Notice that 'Cube_3D' did not preserve original dimentions 
+[tree treeName] = xml_read ('test.xml');
+disp([treeName{1} ' ='])
+gen_object_display(tree)
+
+%% "Pref.StructItem" flag in "xml_write" (controls 1D arrays of structs)
+% *Create a simple structure with 1D array of struct's*
+MyTree = [];
+MyTree.a(1).b = 'jack';
+MyTree.a(2).b = 'john';
+gen_object_display(MyTree)
+%%
+% *Write XML with "StructItem = true" (default).  Notice single 'a' 
+% section and multiple 'item' sub-sections. Those subsections are used 
+% to store array elements*
+wPref.StructItem = true;
+xml_write('test.xml', MyTree, 'MyTree',wPref);
+type('test.xml')
+fprintf('\nxml_read output:\n')
+gen_object_display(xml_read ('test.xml'))
+%%
+% *Write XML with "StructItem = false". Notice multiple 'a' sections*
+wPref.StructItem = false;
+xml_write('test.xml', MyTree, 'MyTree',wPref);
+type('test.xml')
+fprintf('\nxml_read output:\n')
+gen_object_display(xml_read ('test.xml'))
+%%
+% *Notice that xml_read function produced the same struct when reading both files*
+%%
+% *Potential problems with "StructItem = true":*
+wPref.StructItem = true;
+MyTree1 = []; MyTree1.a.b    = 'jack';
+MyTree2 = []; MyTree2.a(1).b = 'jack';
+MyTree3 = []; MyTree3.a(2).b = 'jack';
+xml_write('test.xml', MyTree1, [], wPref); type('test.xml');
+xml_write('test.xml', MyTree2, [], wPref); type('test.xml');
+xml_write('test.xml', MyTree3, [], wPref); type('test.xml');
+%%
+% *Notice that MyTree1 and MyTree2 produce identical files with no 'items',
+% while MyTree2 and MyTree3 produce very different file structures. It was
+% pointed out to me that files produced from MyTree2 and MyTree3 can not 
+% belong to the same schema, which can be a problem. The solution is to use 
+% cells.* 
+wPref.CellItem = true;
+wPref.NoCells  = true;
+MyTree2 = []; MyTree2.a{1}.b = 'jack';
+MyTree3 = []; MyTree3.a{2}.b = 'jack';
+xml_write('test.xml', MyTree2, [], wPref); type('test.xml');
+xml_write('test.xml', MyTree3, [], wPref); type('test.xml');
+
+
+%% "Pref.CellItem" flag in "xml_write" (controls 1D arrays of cells)
+% *Create a simple structure with cell arrays*
+MyTree = [];
+MyTree.a = {'jack', 'john'};
+disp(MyTree)
+%%
+% *Write XML with "CellItem = true" (default).  Notice single 'a' 
+% section and multiple 'item' sections*
+Pref=[]; Pref.CellItem = true;
+xml_write('test.xml', MyTree, 'MyTree',Pref);
+type('test.xml')
+fprintf('\nxml_read output:\n');
+disp(xml_read ('test.xml'))
+%%
+% *Write XML with "CellItem = false". Notice multiple 'a' sections*
+Pref=[]; Pref.CellItem = false;
+xml_write('test.xml', MyTree, 'MyTree',Pref);
+type('test.xml')
+fprintf('\nxml_read output:\n');
+disp(xml_read ('test.xml'))
+%%
+% *Notice that xml_read function produced the same struct when reading both files*
+
+%% "Pref.NoCells" flag in "xml_read"
+% *Create a cell/struct mixture object*
+MyTree = [];
+MyTree.a{1}.b = 'jack';
+MyTree.a{2}.b = [];
+MyTree.a{2}.c = 'john';
+gen_object_display(MyTree);
+%%
+% *Save it to xml file*
+Pref=[]; Pref.CellItem = false;
+xml_write('test.xml', MyTree, 'MyTree',Pref);
+type('test.xml')
+%%
+% *Read above file with "Pref.NoCells=true" (default) - output is quite different then input*
+% By default program is trying to convert everything to struct's and arrays
+% of structs. In case arrays of structs all the structs in array need to have the
+% same fields, and if they are not than MATLAB creates empty fields.
+Pref=[]; Pref.NoCells=true;
+gen_object_display(xml_read('test.xml', Pref))
+%%
+% *Read above file with "Pref.NoCells=false" - now input and output are the same*
+% Cell arrays of structs allow structs in array to have different fields.
+Pref=[]; Pref.NoCells=false;
+gen_object_display(xml_read('test.xml', Pref))
+
+%% "Pref.ItemName" flag in "xml_write" (customize 1D arrays of structs and cells)
+% *Create a cell/struct mixture object*
+MyTree = [];
+MyTree.a{1}.b = 'jack';
+MyTree.a{2}.c = 'john';
+gen_object_display(MyTree);
+%%
+% *Save it to xml file, using 'item' notation but with different name*
+Pref=[]; 
+Pref.CellItem = true;
+Pref.ItemName = 'MyItem';
+xml_write('test.xml', MyTree, 'MyTree',Pref);
+type('test.xml')
+
+%% "Pref.ItemName" flag in "xml_read"
+% *Read above file with default settings ("Pref.ItemName = 'item'")*
+% The results do not match the original structure
+Pref=[]; Pref.NoCells  = false;
+gen_object_display(xml_read('test.xml', Pref))
+%%
+% *Read above file with "Pref.ItemName = 'MyItem'" - now saved and read 
+% MATLAB structures are the same*
+Pref=[]; 
+Pref.ItemName = 'MyItem';
+Pref.NoCells  = false;
+gen_object_display(xml_read('test.xml', Pref))
+
+%% "Pref.CellItem" flag in "xml_read"
+% "Pref.ItemName" is used to create xml files with clearly marked arrays
+% "Pref.CellItem" flag in "xml_read" ensures that they are always read as
+% arrays by forcing output to stay in cell format. In cell format s{1} is
+% different than s, while s(1) is indistinguishable from s.
+%%
+% *Create a test file*
+MyTree = [];
+MyTree.a1{1}.b = 'jack'; % a1 - single struct
+MyTree.a2{1}.b = 'jack'; % a2 - cell array of structs with the same fields
+MyTree.a2{2}.b = 'john';
+MyTree.a3{1}.b = 'jack'; % a3 - cell array of structs with the different fields
+MyTree.a3{2}.c = 'john';
+Pref=[]; 
+Pref.CellItem = true;
+Pref.Debug = true;
+xml_write('test.xml', MyTree, 'MyTree',Pref);
+type('test.xml')
+%%
+% *Read above file with "Pref.CellItem = true" (default)*
+% All outputs are in cell format
+Pref=[]; 
+Pref.NoCells  = false;  % allow cell output
+Pref.CellItem = true;   % keep 'item' arrays as cells 
+gen_object_display(xml_read('test.xml', Pref))
+%%
+% *Read above file with "Pref.CellItem = false"*
+% Outputs format is determined by content
+Pref=[]; 
+Pref.NoCells  = false; % allow cell output
+Pref.CellItem = false; % allow 'item' arrays to beheave like other fields 
+gen_object_display(xml_read('test.xml', Pref))
+%%
+% *Read above file with "Pref.CellItem = false" and "Pref.NoCells  = true"*
+% All outputs are in struct format
+Pref=[]; 
+Pref.NoCells  = true;  % don't allow cell output 
+Pref.CellItem = false; % allow 'item' arrays to beheave like other fields
+gen_object_display(xml_read('test.xml', Pref))
+
+%% "Pref.CellTable" flag in "xml_write" (controls 2D arrays of cells)
+% *Create a structure with 2D arrays of cells*
+MyTree = [];
+MyTree.M = {[1,2;3,4], 'M12'; struct('a','jack'), {11, 'N12'; 21, 'N22'}};
+gen_object_display(MyTree)
+%%
+% *Write XML with "CellTable = 'Html" (default). This option mimics use of  
+%  HTML "tr" and "td" tags to encode 2D tables. Tag names can  
+%  be changed using TableName parameter (see below)*
+wPref = [];
+wPref.CellTable = 'Html';
+xml_write('test.xml', MyTree, 'MyTree',wPref);
+type('test.xml')
+fprintf('\nxml_read output:\n')
+rPref=[]; rPref.NoCells=false;
+gen_object_display(xml_read('test.xml', rPref))
+%%
+% *Write XML with "CellTable = 'Vector'".*
+%  Converts 2D arrays to 1D array and item or regular notation. This option 
+%  is mostly provided for backward compatibility since this was the 
+%  behavior in prior verions of the code
+wPref = [];
+wPref.CellTable = 'Vector';
+xml_write('test.xml', MyTree, 'MyTree',wPref);
+type('test.xml')
+fprintf('\nxml_read output:\n')
+rPref=[]; rPref.NoCells=false;
+gen_object_display(xml_read('test.xml', rPref))
+%%
+% *Create a simpler structure without struct's*
+MyTree = [];
+MyTree.M = {[1,2;3,4], 'M12'; 'M21', {11, 'N12'; 21, 'N22'}};
+gen_object_display(MyTree)
+%%
+% *Write XML with "CellTable = 'Matlab". This option encodes tables
+% consisting of numbers, strings and other cell arrays as MATLAB command
+% string. Unlike 'Html' option it does not work if one of the cells is 
+% a struct*
+wPref = [];
+wPref.CellTable = 'Matlab';
+xml_write('test.xml', MyTree, 'MyTree',wPref);
+type('test.xml')
+fprintf('\nxml_read output:\n')
+rPref=[]; rPref.NoCells=false;
+gen_object_display(xml_read('test.xml', rPref))
+
+%% Write 2D cell array in HTML format
+MyTree = [];
+MyTree.table.ATTRIBUTE.border=1;
+MyTree.table.CONTENT = {'Apples', '44%'; 'Bannanas', '23%'; 'Oranges', '13%'; 'Other', '10%'};
+xml_write('html/test.html', MyTree);
+type('html/test.html')
+%%
+% Click on <test.html> to opened this file with a web brouwser
+
+%% "Pref.StructTable" flag in "xml_write" (controls 2D arrays of structs)
+% *Create a simple structure with arrays of struct's*
+MyTree = [];
+MyTree.a(1,1).b = 'jack';
+MyTree.a(1,2).b = 'john';
+MyTree.a(2,1).b = 'jim';
+MyTree.a(2,2).b = 'jill';
+gen_object_display(MyTree)
+%%
+% *Write XML with "StructTable = 'Html" (default). This option mimics use of  
+%  HTML "tr" and "td"  tags to encode 2D tables. Tag names can  
+%  be changed using TableName parameter (see below)*
+wPref = [];
+wPref.StructTable = 'Html';
+xml_write('test.xml', MyTree, 'MyTree',wPref);
+type('test.xml')
+fprintf('\nxml_read output:\n')
+gen_object_display(xml_read ('test.xml'))
+%%
+% *Write XML with "CellTable = 'Vector'".*
+%  Converts 2D arrays to 1D array and item or regular notation. This option 
+%  is mostly provided for backward compatibility since this was the 
+%  behavior in prior verions of the code
+wPref = [];
+wPref.StructTable = 'Vector';
+xml_write('test.xml', MyTree, 'MyTree',wPref);
+type('test.xml')
+fprintf('\nxml_read output:\n')
+gen_object_display(xml_read ('test.xml'))
+
+%% "Pref.TableName" flag in "xml_write" (controls encoding tags used for 2D arrays)
+% *Create a cell object*
+MyTree = [];
+MyTree.M = {[1,2;3,4], 'M12'; 21, {11, 'N12'; 21, 'N22'}};
+gen_object_display(MyTree);
+%%
+% *Save it to xml file, using 'Html' notation but with different names for 
+%  rows and cells*
+Pref=[]; Pref.TableName = {'row','cell'};
+xml_write('test.xml', MyTree, 'MyTree',Pref);
+type('test.xml')
+
+%% "Pref.TableName" flag in "xml_read"
+% *Read above file with default settings ("Pref.TableName = {'tr','td'}")*
+% The results do not match the original structure
+Pref=[]; Pref.NoCells  = false;
+gen_object_display(xml_read('test.xml', Pref))
+%%
+% *Read above file with "Pref.TableName = {'row','cell'}" - now saved and read 
+% MATLAB structures are the same*
+Pref=[]; 
+Pref.TableName = {'row','cell'};
+Pref.NoCells  = false;
+gen_object_display(xml_read('test.xml', Pref))
+
+%% "Pref.Str2Num" flag in xml_read (control conversion to numbers while reading)
+% *Create a cell/struct mixture object*
+MyTree = [];
+MyTree.str     = 'sphere';
+MyTree.num1    =  123;
+MyTree.num2    = '123';
+MyTree.num3    = '[Inf,NaN]';
+MyTree.calc    = '1+2+3+4';
+MyTree.func    = 'sin(pi)/2';
+MyTree.String1 = '[2003 10 30]'; 
+MyTree.String2 = '2003 10 30';   % array resembling date
+MyTree.ISO8601 = '2003-10-30';   % date in ISO 8601 format
+MyTree.US_date = '2003/10/30';   % US style date format
+MyTree.complex = '2003i-10e-30'; % complex number resembling a date
+gen_object_display(MyTree);
+%%
+% *Save it to xml file*
+xml_write('test.xml', MyTree);
+type('test.xml')
+%%
+% *Read above file with default settings*
+% ("Pref.Str2Num = true" or "Pref.Str2Num = 'smart'"). Under this setting all
+% strings that look like numbers are converted to numbers, except for 
+% strings that are recognized by MATLAB 'datenum' function as dates
+gen_object_display(xml_read('test.xml'))
+%%
+% *Note that all the fields of 'MyTree' can be converted to numbers (even 
+% 'sphere') but by default the function is trying to 'judge' if a string  
+% should be converted to a number or not*
+MyCell = {'sphere','1+2+3+4','sin(pi)/2','2003 10 30','2003-10-30','2003/10/30','2003i-10e-30'};
+cellfun(@str2num, MyCell, 'UniformOutput', false)
+%%
+% *Read above file with "Pref.Str2Num = false" or "Pref.Str2Num = 'never'" 
+% to keep all the fields in string format*
+Pref=[]; Pref.Str2Num = false;
+gen_object_display(xml_read('test.xml', Pref))
+%%
+% *Read above file with "Pref.Str2Num = always"  
+% to convert all strings that look like numbers to numbers* note the likelly 
+% unintendet conversion of 'ISO8601'
+Pref=[]; Pref.Str2Num   = 'always';
+gen_object_display(xml_read('test.xml', Pref))
+%%
+% *Notice that all three settings will produce the same output for "num1" and
+% "num2" and there is no way to reproduce the original "MyTree" structure.*
+
+%% "Pref.PreserveSpace" flag in xml_write (control handling of strings with leading/trailing spaces)
+% *Create a struct with strings*
+MyTree=[];
+MyTree.Empty     = '';
+MyTree.OneSpace  = ' ';
+MyTree.TwoSpaces = '  '; 
+MyTree.String1   = ' Hello      World ';
+%%
+% *Write XML with "PreserveSpace = false" (default).*
+Pref=[]; Pref.PreserveSpace = false; % (default setting)
+xml_write('test.xml', MyTree, [], Pref);
+type('test.xml')
+%%
+% *Write XML with "PreserveSpace = true".*
+Pref=[]; Pref.PreserveSpace = true; 
+xml_write('test.xml', MyTree, [], Pref);
+type('test.xml')
+
+%% "Pref.PreserveSpace" flag in xml_read
+% *Read file while using "PreserveSpace = false" (default).*
+Pref=[]; Pref.PreserveSpace = false; % (default setting)
+gen_object_display(xml_read('test.xml',Pref))
+%%
+% *Read file while using "PreserveSpace = true".*
+Pref=[]; Pref.PreserveSpace = true; 
+gen_object_display(xml_read('test.xml',Pref))
+
+
+%% Write XML files with ATTRIBUTEs 
+% In order to add node attributes a special ATTRIBUTE field is used. 
+% ATTRIBUTEs have to be of simple types like numbers or strings (not
+% struct or cells). Attributes are easy to attach to structs nodes like 
+% MyTree below. 
+MyTree=[];
+MyTree.MyNumber = 13;
+MyTree.MyString = 'Hello World'; % simple case
+MyTree.ATTRIBUTE.Num = 2;
+xml_write('test.xml', MyTree);
+type('test.xml')
+
+%%  
+% In case when one needs to attach attributes to nodes which are not
+% structs (for example strings, numbers or calls) then special CONTENT 
+% field needs to be used to make the node a struct node.
+MyTree=[];
+MyTree.MyNumber = 13;
+MyTree.MyString.CONTENT = 'Hello World'; % simple case
+MyTree.MyString.ATTRIBUTE.Num = 2;
+xml_write('test.xml', MyTree);
+type('test.xml')
+
+%% "Pref.Str2Num" flag in file with ATTRIBUTEs
+% *Create a cell/struct mixture object*
+MyTree = [];
+MyTree.X.ATTRIBUTE.str     = 'sphere';
+MyTree.X.ATTRIBUTE.num1    =  123;
+MyTree.X.ATTRIBUTE.num2    = '123';
+MyTree.X.ATTRIBUTE.num3    = '[Inf,NaN]';
+MyTree.X.ATTRIBUTE.calc    = '1+2+3+4';
+MyTree.X.ATTRIBUTE.func    = 'sin(pi)/2';
+MyTree.X.ATTRIBUTE.String1 = '[2003 10 30]'; 
+MyTree.X.ATTRIBUTE.String2 = '2003 10 30';   % array resembling date
+MyTree.X.ATTRIBUTE.ISO8601 = '2003-10-30';   % date in ISO 8601 format
+MyTree.X.ATTRIBUTE.US_date = '2003/10/30';   % US style date format
+MyTree.X.ATTRIBUTE.complex = '2003i-10e-30'; % complex number resembling a date
+gen_object_display(MyTree);
+%%
+% *Save it to xml file*
+xml_write('test.xml', MyTree);
+type('test.xml')
+%%
+% *Read above file with default settings*
+% ("Pref.Str2Num = true" or "Pref.Str2Num = 'smart'"). Under this setting all
+% strings that look like numbers are converted to numbers, except for 
+% strings that are recognized by MATLAB 'datenum' function as dates
+gen_object_display(xml_read('test.xml'))
+
+%%
+% *Read above file with "Pref.Str2Num = false" or "Pref.Str2Num = 'never'" 
+% to keep all the fields in string format*
+Pref=[]; Pref.Str2Num = false;
+gen_object_display(xml_read('test.xml', Pref))
+%%
+% *Read above file with "Pref.Str2Num = always"  
+% to convert all strings that look like numbers to numbers* 
+Pref=[]; Pref.Str2Num   = 'always';
+gen_object_display(xml_read('test.xml', Pref))
+%%
+% *Notice that all three settings will produce the same output for "num1" and
+% "num2" and there is no way to reproduce the original "MyTree" structure.*
+
+
+%% Write XML files with COMMENTs
+% Insertion of Comments is done with help of special COMMENT field.
+% Note that MATLAB's xmlwrite is less readable due to lack of end-of-line 
+% characters around comment section. 
+MyTree=[];
+MyTree.COMMENT = 'This is a comment';
+MyTree.MyNumber = 13;
+MyTree.MyString.CONTENT = 'Hello World';
+xml_write('test.xml', MyTree);
+type('test.xml')
+
+%%
+% *Same operation using Apache Xerces XML engine*
+% gives the same result
+Pref=[]; Pref.XmlEngine = 'Xerces';  % use Xerces xml generator directly
+xml_write('test.xml', MyTree, 'MyTree', Pref);
+type('test.xml')
+
+%%
+% *Comments in XML top level (method #1)*
+% This method uses cell array 
+MyTree=[];
+MyTree.MyNumber = 13;
+MyTree.MyString = 'Hello World';
+xml_write('test.xml', MyTree, {'MyTree', [], 'This is a global comment'});
+type('test.xml')
+%%
+% *Same operation using Apache Xerces XML engine* 
+% gives even nicer results.
+Pref=[]; Pref.XmlEngine = 'Xerces';  % use Xerces xml generator directly
+xml_write('test.xml', MyTree, {'MyTree', [], 'This is a global comment'}, Pref);
+type('test.xml')
+
+%%
+% *Comments in XML top level (method #2)*
+% This method adds an extra top layer to the struct 'tree' and sets
+% "Pref.RootOnly = false", which informs the function about the extra 
+% layer. Notice that RootName is also saved as a part of
+% the 'tree', and does not have to be passed in separately.
+MyTree=[];
+MyTree.COMMENT = 'This is a global comment';
+MyTree.MyTest.MyNumber = 13;
+MyTree.MyTest.MyString = 'Hello World';
+Pref=[]; Pref.RootOnly = false;
+xml_write('test.xml', MyTree, [], Pref);
+type('test.xml')
+%%
+% *Same operation using Apache Xerces XML engine*
+Pref=[]; Pref.XmlEngine = 'Xerces';  % use Xerces xml generator directly
+Pref.RootOnly  = false;
+xml_write('test.xml', MyTree, [], Pref);
+type('test.xml')
+
+%% Write XML files with PROCESSING_INSTRUCTIONs 
+% Insertion of Processing Instructions is done through use of special 
+% PROCESSING_INSTRUCTION field, which stores the instruction string. The
+% string has to be in 'target data' format separated by space.
+MyTree=[];
+MyTree.PROCESSING_INSTRUCTION = 'xml-stylesheet type="a" href="foo"';
+MyTree.MyNumber = 13;
+MyTree.MyString = 'Hello World';
+xml_write('test.xml', MyTree);
+type('test.xml')
+
+%%
+% *Same operation using Apache Xerces XML engine*
+Pref=[]; Pref.XmlEngine = 'Xerces';  % use Xerces xml generator directly
+xml_write('test.xml', MyTree, 'MyTree', Pref);
+type('test.xml')
+
+%%
+% *PROCESSING_INSTRUCTIONs in XML top level (method #1)*
+% This method uses cell array 
+MyTree=[];
+MyTree.MyNumber = 13;
+MyTree.MyString = 'Hello World';
+xml_write('test.xml', MyTree, {'MyTree', 'xml-stylesheet type="a" href="foo"'});
+type('test.xml')
+%%
+% *Same operation using Apache Xerces XML engine*
+Pref=[]; Pref.XmlEngine = 'Xerces';  % use Xerces xml generator directly
+xml_write('test.xml', MyTree, {'MyTree', 'xml-stylesheet type="a" href="foo"'}, Pref);
+type('test.xml')
+
+%%
+% *PROCESSING_INSTRUCTIONs in XML top level (method #2)*
+% This method adds an extra top layer to the struct 'tree' and sets
+% pref.RootOnly=false, which informs the function about the extra 
+% layer. Notice that RootName is also saved as a part of
+% the 'tree', and does not have to be passed in separately.
+MyTree=[];
+MyTree.PROCESSING_INSTRUCTION =  'xml-stylesheet type="a" href="foo"';
+MyTree.MyTest.MyNumber = 13;
+MyTree.MyTest.MyString = 'Hello World';
+Pref=[]; Pref.RootOnly = false;
+xml_write('test.xml', MyTree, [], Pref);
+type('test.xml')
+%%
+% *Same operation using Apache Xerces XML engine*
+Pref=[]; Pref.XmlEngine = 'Xerces';  % use Xerces xml generator directly
+Pref.RootOnly  = false;
+xml_write('test.xml', MyTree, 'MyTree', Pref);
+type('test.xml')
+
+%% Write XML files with CDATA Sections 
+% "In an XML document a CDATA (Character DATA) section is a section of 
+%  element content that is marked for the parser to interpret as only 
+%  character data, not markup." (from Wikipedia) 
+% To insert CDATA Sections one use special CDATA_SECTION field,
+%  which stores the instruction string. Note that MATLAB's xmlwrite created
+%  wrong xml code for CDATA section
+MyTree=[];
+MyTree.CDATA_SECTION = '<A>txt</A>';
+MyTree.MyNumber = 13;
+MyTree.MyString = 'Hello World';
+xml_write('test.xml', MyTree);
+type('test.xml')
+%%
+% *Same operation using Apache Xerces XML engine produces correct results*
+Pref=[]; Pref.XmlEngine = 'Xerces';  % use Xerces xml generator directly
+xml_write('test.xml', MyTree, 'MyTree', Pref);
+type('test.xml')
+
+%% Write XML files with special characters in TAG names
+% The input to xml_write requires that all tags one wants in XML document 
+% have to be encoded as field names of MATLAB's struct's. Matlab has a lot
+% of restrictions on variable names. This section is about XML tags with
+% names not allowed as MATLAB variables, or more specifically with
+% characters allowed as xml tag names but not allowed as MATLAB variable
+% names. Characters like that can be replaced by their hexadecimal
+% representation just as it is done by genvarname function. Alternative way
+% of writing the first example is:
+MyTree=[];
+MyTree.('MyNumber') = 13;               % same as MyTree.MyNumber = 13;
+MyTree.MyString.CONTENT = 'Hello World';
+MyTree.MyString.ATTRIBUTE.('Num') = 2;  % same as MyTree.MyString.ATTRIBUTE.Num = 2;
+xml_write('test.xml', MyTree);
+type('test.xml')
+
+%%
+% *This approach fails for some characters like dash '-', colon ':', and
+% international characters.*
+MyTree=[];
+try
+  MyTree.('My-Number') = 13;
+  MyTree.MyString.CONTENT = 'Hello World';
+  MyTree.MyString.ATTRIBUTE.('Num_ö') = 2;
+catch  %#ok<CTCH>
+  err = lasterror; %#ok<LERR>
+  disp(err.message);
+end
+
+%%
+% It can be overcome by replacing offending characters with their 
+% hexadecimal representation. That can be done manually or with use of 
+% genvarname function. Note that MATLAB 'type' function does not show
+% correctly 'ö' letter in xml file, but opening the file in editor shows 
+% that it is correct.
+MyTree=[];
+MyTree.(genvarname('My-Number')) = 13;
+MyTree.MyString.CONTENT = 'Hello World';
+MyTree.MyString.ATTRIBUTE.Num_0xF6 = 2;
+gen_object_display(MyTree);
+xml_write('test.xml', MyTree);
+type('test.xml')
+
+%%
+% *Also two of the characters '-' and ':' can be encoded by a special strings:
+% '_DASH_' and '_COLON_' respectively*
+MyTree=[];
+MyTree.My_DASH_Number = 13;
+MyTree.MyString.CONTENT = 'Hello World';
+MyTree.MyString.ATTRIBUTE.Num0xF6 = 2;
+xml_write('test.xml', MyTree);
+type('test.xml')
+
+%% Write XML files with Namespaces
+% No extra special fields are needed to define XML namespaces, only colon 
+% character written using '0x3A' or '_COLON_'. Below is an
+% example of a namespace definition
+MyTree=[];
+MyTree.f_COLON_child.ATTRIBUTE.xmlns_COLON_f = 'http://www.foo.com';
+MyTree.f_COLON_child.f_COLON_MyNumber = 13;
+MyTree.f_COLON_child.f_COLON_MyString = 'Hello World';
+xml_write('test.xml', MyTree, 'MyTree');
+type('test.xml')
+%%
+% *Same operation using Apache Xerces XML engine*
+Pref=[]; Pref.XmlEngine = 'Xerces';  % use Xerces xml generator directly
+xml_write('test.xml', MyTree, 'f_COLON_MyTree', Pref);
+type('test.xml')
+
+%% "Pref.KeepNS" flag in "xml_read"
+% Thise option allow keeping  or exclusion of namespaces in tag names. 
+% By default the namespace data is kept but it produces much longer field
+% names in the output structure. Ignoring namespace will produce more
+% readible output.
+% Perform default read of file with namespace
+tree = xml_read('test.xml');
+gen_object_display(tree);
+
+%%
+% Now the same operation with KeepNS = false. 
+Pref=[]; Pref.KeepNS = false; % do not read attributes
+tree = xml_read('test.xml', Pref);
+gen_object_display(tree);
+
+%% Read XML files with special node types
+% Display and read the file, then show the data structure. Note that 
+% MATLAB 'type' function shows 'ö' letter incorrectly as 'A¶' in xml file, 
+% but opening the file in editor shows that it is correct.
+fprintf('Test xml file:\n');
+type('test_file.xml')
+%%
+% Read only the Root Element (default) 
+[tree GlobalTextNodes] = xml_read('test_file.xml');
+fprintf('Global Data (Root name, Global Processing Instructions and Global Comments):\n');
+disp(GlobalTextNodes')
+fprintf('\nStructure read from the file (uncludes COMMENT and CDATA sections):\n');
+gen_object_display(tree);
+%%
+% Read the whole tree including global Comments and Processing Instructions
+Pref=[]; Pref.RootOnly = false;
+[tree GlobalTextNodes] = xml_read('test_file.xml', Pref);
+fprintf('Global Data (Root name, Global Processing Instructions and Global Comments):\n');
+disp(GlobalTextNodes')
+fprintf('\nStructure read from the file (uncludes COMMENT and CDATA sections):\n');
+gen_object_display(tree);
+
+%% "Pref.ReadAttr" flag in "xml_read" (control handling of nodes with attributes)
+% Those option allow exclusion of attributes 
+Pref=[]; Pref.ReadAttr = false; % do not read attributes
+tree = xml_read('test_file.xml', Pref);
+gen_object_display(tree);
+
+%% "Pref.ReadSpec" flag in "xml_read"
+% Those option allow exclusion of special nodes, like
+% comments, processing instructions, CData sections, etc.
+Pref=[]; Pref.ReadSpec = false; % do not read special node types
+tree = xml_read('test_file.xml', Pref);
+gen_object_display(tree);
+
+%% "Pref.RootOnly" flag in "xml_read"
+% As it was shown in previous examples RootOnly parameter can be used to
+% capture global (top level) special nodes (like COMMENTs and
+% PROCESSING_INSTRUCTIONs) which are ignored by default
+Pref=[]; Pref.RootOnly = false; % do not read special node types
+tree = xml_read('test_file.xml', Pref);
+gen_object_display(tree);
+
+%% "Pref.RootOnly" flag in "xml_write"
+% Writing previously read tree with default "Pref.RootOnly = true" gives
+% wrong output file
+Pref=[]; Pref.RootOnly = true; % do not read special node types
+xml_write('test.xml', tree, [], Pref);
+fprintf('Test xml file:\n');
+type('test.xml')
+%%
+% Writing the same tree with "Pref.RootOnly = false" gives correct output
+Pref=[]; Pref.RootOnly = false; % do not read special node types
+xml_write('test.xml', tree, [], Pref);
+fprintf('Test xml file:\n');
+type('test.xml')
+
+%% "Pref.NumLevels" flag in "xml_read"
+% This parameter allows user to skip parts of the tree in order to save
+% time and memory. Usefull only in a rare case when a small portion of
+% large XML file is needed.
+%
+% Create test tile
+MyTree = [];
+MyTree.Level1 = 1;
+MyTree.Level1_.Level2 = 2;
+MyTree.Level1_.Level2_.Level3 = 3;
+MyTree.Level1_.Level2_.Level3_.Level4 = 4;
+xml_write('test.xml', MyTree);
+fprintf('Test xml file:\n');
+type('test.xml')
+%%
+% *Use Default ("Pref.NumLevels = infinity") setting*
+tree = xml_read('test.xml');
+gen_object_display(tree);
+%%
+% *Limit the read to only 2 levels*
+Pref=[]; Pref.NumLevels = 2; 
+tree = xml_read('test.xml', Pref);
+gen_object_display(tree);
+
+
+
+
+%% Create DOM object based on a Struct using "xml_write"
+% *Create Struct tree*
+MyTree=[];
+MyTree.MyNumber = 13;
+MyTree.MyString = 'Hello World';
+%%
+% *Convert Struct to DOM object using xml_write*
+DOM = xml_write([], MyTree); 
+xmlwrite('test.xml', DOM);   % Save DOM object using MATLAB function 
+type('test.xml')
+
+%% Convert DOM object to Struct using "xml_read"
+DOM = xmlread('test.xml');       % Read DOM object using MATLAB function
+[tree treeName] = xml_read(DOM); % Convert DOM object to Struct
+disp([treeName{1} ' ='])
+gen_object_display(tree)
+
+%% Write XML file based on a DOM using "xml_write_xerces"
+xmlwrite_xerces('test.xml', DOM); % Save DOM object using Xerces library 
+type('test.xml')
+
+%% Write XML to string instead of a file
+DOM = xml_write([], MyTree);
+str = xmlwrite(DOM);
+disp(str)
+
+%% Write XML file with embedded binary data encoded as Base64 (using java version)
+fid = fopen('football.jpg', 'rb');       
+raw1 = uint8(fread(fid, 'uint8'));                % read image file as a raw binary
+fclose(fid);
+
+MyTree=[];
+MyTree.Size = 13;
+MyTree.MyString = 'Hello World'; % simple case
+MyTree.MyImage.ATTRIBUTE.EncodingMIMEType = 'base64';
+MyTree.MyImage.CONTENT = base64encode(raw1,'java');% perform base64 encoding of the binary data
+xml_write('test.xml', MyTree);             % write xml file
+
+%% Read XML file with embedded binary data encoded as Base64 (using java version)
+tree = xml_read('test.xml', Pref);         % read xml file
+raw  = base64decode(tree.MyImage.CONTENT, '', 'java');   % convert xml image to raw binary
+fid = fopen('MyFootball.jpg', 'wb');  
+fwrite(fid, raw, 'uint8');                 % dumb the raw binary to the hard disk 
+fclose(fid);
+I = imread('MyFootball.jpg');              % read it as an image
+imshow(I);
+
+%% Write XML file with embedded binary data encoded as Base64 (simpler version using only matlab code
+% Notice that process of writing to xml stripped all end-of-lie characters
+% from base64 code.
+isChunked = true; % break into chunks 76 characters long
+url_safe  = true; % 'base64url' encoding
+code = base64encode('license.txt', 'matlab', isChunked, url_safe);
+disp(code)
+MyTree=[];
+MyTree.Size = 13;
+MyTree.MyString = 'Hello World'; 
+MyTree.MyImage.ATTRIBUTE.EncodingMIMEType = 'base64';
+MyTree.MyImage.CONTENT = code;   % perform base64 encoding of the binary data
+xml_write('test.xml', MyTree);   % write xml file
+type('test.xml')
+
+%% Read XML file with embedded binary data encoded as Base64 (simpler version using only matlab code
+tree = xml_read('test.xml', Pref);         % read xml file
+base64decode(tree.MyImage.CONTENT, 'license2.txt', 'matlab'); % save xml image as raw binary
+type('license2.txt')

matlab_version/AU_training/data extraction/xml_io_tools_2010_11_05/xml_write.m

@@ -0,0 +1,447 @@
+function DOMnode = xml_write(filename, tree, RootName, Pref)
+%XML_WRITE  Writes Matlab data structures to XML file
+%
+% DESCRIPTION
+% xml_write( filename, tree) Converts Matlab data structure 'tree' containing
+% cells, structs, numbers and strings to Document Object Model (DOM) node
+% tree, then saves it to XML file 'filename' using Matlab's xmlwrite
+% function. Optionally one can also use alternative version of xmlwrite
+% function which directly calls JAVA functions for XML writing without
+% MATLAB middleware. This function is provided as a patch to existing
+% bugs in xmlwrite (in R2006b).
+%
+% xml_write(filename, tree, RootName, Pref) allows you to specify
+% additional preferences about file format
+%
+% DOMnode = xml_write([], tree) same as above except that DOM node is
+% not saved to the file but returned.
+%
+% INPUT
+%   filename     file name
+%   tree         Matlab structure tree to store in xml file.
+%   RootName     String with XML tag name used for root (top level) node
+%                Optionally it can be a string cell array storing: Name of
+%                root node, document "Processing Instructions" data and
+%                document "comment" string
+%   Pref         Other preferences:
+%     Pref.ItemName - default 'item' -  name of a special tag used to
+%                     itemize cell or struct arrays
+%     Pref.XmlEngine - let you choose the XML engine. Currently default is
+%       'Xerces', which is using directly the apache xerces java file.
+%       Other option is 'Matlab' which uses MATLAB's xmlwrite and its
+%       XMLUtils java file. Both options create identical results except in
+%       case of CDATA sections where xmlwrite fails.
+%     Pref.CellItem - default 'true' - allow cell arrays to use 'item'
+%       notation. See below.
+%    Pref.RootOnly - default true - output variable 'tree' corresponds to
+%       xml file root element, otherwise it correspond to the whole file.
+%     Pref.StructItem - default 'true' - allow arrays of structs to use
+%       'item' notation. For example "Pref.StructItem = true" gives:
+%         <a>
+%           <b>
+%             <item> ... <\item>
+%             <item> ... <\item>
+%           <\b>
+%         <\a>
+%       while "Pref.StructItem = false" gives:
+%         <a>
+%           <b> ... <\b>
+%           <b> ... <\b>
+%         <\a>
+%
+%
+% Several special xml node types can be created if special tags are used
+% for field names of 'tree' nodes:
+%  - node.CONTENT - stores data section of the node if other fields
+%    (usually ATTRIBUTE are present. Usually data section is stored
+%    directly in 'node'.
+%  - node.ATTRIBUTE.name - stores node's attribute called 'name'.
+%  - node.COMMENT - create comment child node from the string. For global
+%    comments see "RootName" input variable.
+%  - node.PROCESSING_INSTRUCTIONS - create "processing instruction" child
+%    node from the string. For global "processing instructions" see
+%    "RootName" input variable.
+%  - node.CDATA_SECTION - stores node's CDATA section (string). Only works
+%    if Pref.XmlEngine='Xerces'. For more info, see comments of F_xmlwrite.
+%  - other special node types like: document fragment nodes, document type
+%    nodes, entity nodes and notation nodes are not being handled by
+%    'xml_write' at the moment.
+%
+% OUTPUT
+%   DOMnode      Document Object Model (DOM) node tree in the format
+%                required as input to xmlwrite. (optional)
+%
+% EXAMPLES:
+%   MyTree=[];
+%   MyTree.MyNumber = 13;
+%   MyTree.MyString = 'Hello World';
+%   xml_write('test.xml', MyTree);
+%   type('test.xml')
+%   %See also xml_tutorial.m
+%
+% See also
+%   xml_read, xmlread, xmlwrite
+%
+% Written by Jarek Tuszynski, SAIC, jaroslaw.w.tuszynski_at_saic.com
+
+%% Check Matlab Version
+v = ver('MATLAB');
+v = str2double(regexp(v.Version, '\d.\d','match','once'));
+if (v<7)
+  error('Your MATLAB version is too old. You need version 7.0 or newer.');
+end
+
+%% default preferences
+DPref.TableName  = {'tr','td'}; % name of a special tags used to itemize 2D cell arrays
+DPref.ItemName   = 'item'; % name of a special tag used to itemize 1D cell arrays
+DPref.StructItem = true;  % allow arrays of structs to use 'item' notation
+DPref.CellItem   = true;  % allow cell arrays to use 'item' notation
+DPref.StructTable= 'Html';
+DPref.CellTable  = 'Html';
+DPref.XmlEngine  = 'Matlab';  % use matlab provided XMLUtils
+%DPref.XmlEngine  = 'Xerces';  % use Xerces xml generator directly
+DPref.PreserveSpace = false; % Preserve or delete spaces at the beggining and the end of stings?
+RootOnly         = true;  % Input is root node only
+GlobalProcInst = [];
+GlobalComment  = [];
+GlobalDocType  = [];
+
+%% read user preferences
+if (nargin>3)
+  if (isfield(Pref, 'TableName' )),  DPref.TableName  = Pref.TableName; end
+  if (isfield(Pref, 'ItemName'  )), DPref.ItemName   = Pref.ItemName;   end
+  if (isfield(Pref, 'StructItem')), DPref.StructItem = Pref.StructItem; end
+  if (isfield(Pref, 'CellItem'  )), DPref.CellItem   = Pref.CellItem;   end
+  if (isfield(Pref, 'CellTable')),   DPref.CellTable  = Pref.CellTable; end
+  if (isfield(Pref, 'StructTable')), DPref.StructTable= Pref.StructTable; end
+  if (isfield(Pref, 'XmlEngine' )), DPref.XmlEngine  = Pref.XmlEngine;  end
+  if (isfield(Pref, 'RootOnly'  )), RootOnly         = Pref.RootOnly;   end
+  if (isfield(Pref, 'PreserveSpace')), DPref.PreserveSpace = Pref.PreserveSpace; end
+end
+if (nargin<3 || isempty(RootName)), RootName=inputname(2); end
+if (isempty(RootName)), RootName='ROOT'; end
+if (iscell(RootName)) % RootName also stores global text node data
+  rName = RootName;
+  RootName = char(rName{1});
+  if (length(rName)>1), GlobalProcInst = char(rName{2}); end
+  if (length(rName)>2), GlobalComment  = char(rName{3}); end
+  if (length(rName)>3), GlobalDocType  = char(rName{4}); end
+end
+if(~RootOnly && isstruct(tree))  % if struct than deal with each field separatly
+  fields = fieldnames(tree);
+  for i=1:length(fields)
+    field = fields{i};
+    x = tree(1).(field);
+    if (strcmp(field, 'COMMENT'))
+      GlobalComment = x;
+    elseif (strcmp(field, 'PROCESSING_INSTRUCTION'))
+      GlobalProcInst = x;
+    elseif (strcmp(field, 'DOCUMENT_TYPE'))
+      GlobalDocType = x;
+    else
+      RootName = field;
+      t = x;
+    end
+  end
+  tree = t;
+end
+
+%% Initialize jave object that will store xml data structure
+RootName = varName2str(RootName);
+if (~isempty(GlobalDocType))
+  %   n = strfind(GlobalDocType, ' ');
+  %   if (~isempty(n))
+  %     dtype = com.mathworks.xml.XMLUtils.createDocumentType(GlobalDocType);
+  %   end
+  %   DOMnode = com.mathworks.xml.XMLUtils.createDocument(RootName, dtype);
+  warning('xml_io_tools:write:docType', ...
+    'DOCUMENT_TYPE node was encountered which is not supported yet. Ignoring.');
+end
+DOMnode = com.mathworks.xml.XMLUtils.createDocument(RootName);
+
+
+%% Use recursive function to convert matlab data structure to XML
+root = DOMnode.getDocumentElement;
+struct2DOMnode(DOMnode, root, tree, DPref.ItemName, DPref);
+
+%% Remove the only child of the root node
+root   = DOMnode.getDocumentElement;
+Child  = root.getChildNodes; % create array of children nodes
+nChild = Child.getLength;    % number of children
+if (nChild==1)
+  node = root.removeChild(root.getFirstChild);
+  while(node.hasChildNodes)
+    root.appendChild(node.removeChild(node.getFirstChild));
+  end
+  while(node.hasAttributes)            % copy all attributes
+    root.setAttributeNode(node.removeAttributeNode(node.getAttributes.item(0)));
+  end
+end
+
+%% Save exotic Global nodes
+if (~isempty(GlobalComment))
+  DOMnode.insertBefore(DOMnode.createComment(GlobalComment), DOMnode.getFirstChild());
+end
+if (~isempty(GlobalProcInst))
+  n = strfind(GlobalProcInst, ' ');
+  if (~isempty(n))
+    proc = DOMnode.createProcessingInstruction(GlobalProcInst(1:(n(1)-1)),...
+      GlobalProcInst((n(1)+1):end));
+    DOMnode.insertBefore(proc, DOMnode.getFirstChild());
+  end
+end
+% Not supported yet as the code below does not work
+% if (~isempty(GlobalDocType))
+%   n = strfind(GlobalDocType, ' ');
+%   if (~isempty(n))
+%     dtype = DOMnode.createDocumentType(GlobalDocType);
+%     DOMnode.insertBefore(dtype, DOMnode.getFirstChild());
+%   end
+% end
+
+%% save java DOM tree to XML file
+if (~isempty(filename))
+  if (strcmpi(DPref.XmlEngine, 'Xerces'))
+    xmlwrite_xerces(filename, DOMnode);
+  else
+    xmlwrite(filename, DOMnode);
+  end
+end
+
+
+%% =======================================================================
+%  === struct2DOMnode Function ===========================================
+%  =======================================================================
+function [] = struct2DOMnode(xml, parent, s, TagName, Pref)
+% struct2DOMnode is a recursive function that converts matlab's structs to
+% DOM nodes.
+% INPUTS:
+%  xml - jave object that will store xml data structure
+%  parent - parent DOM Element
+%  s - Matlab data structure to save
+%  TagName - name to be used in xml tags describing 's'
+%  Pref - preferenced
+% OUTPUT:
+%  parent - modified 'parent'
+
+% perform some conversions
+if (ischar(s) && min(size(s))>1) % if 2D array of characters
+  s=cellstr(s);                  % than convert to cell array
+end
+% if (strcmp(TagName, 'CONTENT'))
+%   while (iscell(s) && length(s)==1), s = s{1}; end % unwrap cell arrays of length 1
+% end
+TagName  = varName2str(TagName);
+
+%% == node is a 2D cell array ==
+% convert to some other format prior to further processing
+nDim = nnz(size(s)>1);  % is it a scalar, vector, 2D array, 3D cube, etc?
+if (iscell(s) && nDim==2 && strcmpi(Pref.CellTable, 'Matlab'))
+  s = var2str(s, Pref.PreserveSpace);
+end
+if (nDim==2 && (iscell  (s) && strcmpi(Pref.CellTable,   'Vector')) || ...
+               (isstruct(s) && strcmpi(Pref.StructTable, 'Vector')))
+  s = s(:);
+end
+if (nDim>2), s = s(:); end % can not handle this case well
+nItem = numel(s);
+nDim  = nnz(size(s)>1);  % is it a scalar, vector, 2D array, 3D cube, etc?
+
+%% == node is a cell ==
+if (iscell(s)) % if this is a cell or cell array
+  if ((nDim==2 && strcmpi(Pref.CellTable,'Html')) || (nDim< 2 && Pref.CellItem))
+    % if 2D array of cells than can use HTML-like notation or if 1D array
+    % than can use item notation
+    if (strcmp(TagName, 'CONTENT')) % CONTENT nodes already have <TagName> ... </TagName>
+      array2DOMnode(xml, parent, s, Pref.ItemName, Pref ); % recursive call
+    else
+      node = xml.createElement(TagName);   % <TagName> ... </TagName>
+      array2DOMnode(xml, node, s, Pref.ItemName, Pref ); % recursive call
+      parent.appendChild(node);
+    end
+  else % use  <TagName>...<\TagName> <TagName>...<\TagName> notation
+    array2DOMnode(xml, parent, s, TagName, Pref ); % recursive call
+  end
+%% == node is a struct ==
+elseif (isstruct(s))  % if struct than deal with each field separatly
+  if ((nDim==2 && strcmpi(Pref.StructTable,'Html')) || (nItem>1 && Pref.StructItem))
+    % if 2D array of structs than can use HTML-like notation or
+    % if 1D array of structs than can use 'items' notation
+    node = xml.createElement(TagName);
+    array2DOMnode(xml, node, s, Pref.ItemName, Pref ); % recursive call
+    parent.appendChild(node);
+  elseif (nItem>1) % use  <TagName>...<\TagName> <TagName>...<\TagName> notation
+    array2DOMnode(xml, parent, s, TagName, Pref ); % recursive call
+  else % otherwise save each struct separatelly
+    fields = fieldnames(s);
+    node = xml.createElement(TagName);
+    for i=1:length(fields) % add field by field to the node
+      field = fields{i};
+      x = s.(field);
+      switch field
+        case {'COMMENT', 'CDATA_SECTION', 'PROCESSING_INSTRUCTION'}
+          if iscellstr(x)  % cell array of strings -> add them one by one
+            array2DOMnode(xml, node, x(:), field, Pref ); % recursive call will modify 'node'
+          elseif ischar(x) % single string -> add it
+            struct2DOMnode(xml, node, x, field, Pref ); % recursive call will modify 'node'
+          else % not a string - Ignore
+            warning('xml_io_tools:write:badSpecialNode', ...
+             ['Struct field named ',field,' encountered which was not a string. Ignoring.']);
+          end
+        case 'ATTRIBUTE' % set attributes of the node
+          if (isempty(x)), continue; end
+          if (isstruct(x))
+            attName = fieldnames(x);       % get names of all the attributes
+            for k=1:length(attName)        % attach them to the node
+              att = xml.createAttribute(varName2str(attName(k)));
+              att.setValue(var2str(x.(attName{k}),Pref.PreserveSpace));
+              node.setAttributeNode(att);
+            end
+          else
+            warning('xml_io_tools:write:badAttribute', ...
+              'Struct field named ATTRIBUTE encountered which was not a struct. Ignoring.');
+          end
+        otherwise                            % set children of the node
+          struct2DOMnode(xml, node, x, field, Pref ); % recursive call will modify 'node'
+      end
+    end  % end for i=1:nFields
+    parent.appendChild(node);
+  end
+%% == node is a leaf node ==
+else  % if not a struct and not a cell than it is a leaf node
+  switch TagName % different processing depending on desired type of the node
+    case 'COMMENT'   % create comment node
+      com = xml.createComment(s);
+      parent.appendChild(com);
+    case 'CDATA_SECTION' % create CDATA Section
+      cdt = xml.createCDATASection(s);
+      parent.appendChild(cdt);
+    case 'PROCESSING_INSTRUCTION' % set attributes of the node
+      OK = false;
+      if (ischar(s))
+        n = strfind(s, ' ');
+        if (~isempty(n))
+          proc = xml.createProcessingInstruction(s(1:(n(1)-1)),s((n(1)+1):end));
+          parent.insertBefore(proc, parent.getFirstChild());
+          OK = true;
+        end
+      end
+      if (~OK)
+        warning('xml_io_tools:write:badProcInst', ...
+          ['Struct field named PROCESSING_INSTRUCTION need to be',...
+          ' a string, for example: xml-stylesheet type="text/css" ', ...
+          'href="myStyleSheet.css". Ignoring.']);
+      end
+    case 'CONTENT' % this is text part of already existing node
+      txt  = xml.createTextNode(var2str(s, Pref.PreserveSpace)); % convert to text
+      parent.appendChild(txt);
+    otherwise      % I guess it is a regular text leaf node
+      txt  = xml.createTextNode(var2str(s, Pref.PreserveSpace));
+      node = xml.createElement(TagName);
+      node.appendChild(txt);
+      parent.appendChild(node);
+  end
+end % of struct2DOMnode function
+
+%% =======================================================================
+%  === array2DOMnode Function ============================================
+%  =======================================================================
+function [] = array2DOMnode(xml, parent, s, TagName, Pref)
+% Deal with 1D and 2D arrays of cell or struct. Will modify 'parent'.
+nDim = nnz(size(s)>1);  % is it a scalar, vector, 2D array, 3D cube, etc?
+switch nDim
+  case 2 % 2D array
+    for r=1:size(s,1)
+      subnode = xml.createElement(Pref.TableName{1});
+      for c=1:size(s,2)
+        v = s(r,c);
+        if iscell(v), v = v{1}; end
+        struct2DOMnode(xml, subnode, v, Pref.TableName{2}, Pref ); % recursive call
+      end
+      parent.appendChild(subnode);
+    end
+  case 1 %1D array
+    for iItem=1:numel(s)
+      v = s(iItem);
+      if iscell(v), v = v{1}; end
+      struct2DOMnode(xml, parent, v, TagName, Pref ); % recursive call
+    end
+  case 0 % scalar -> this case should never be called
+    if ~isempty(s) 
+      if iscell(s), s = s{1}; end
+      struct2DOMnode(xml, parent, s, TagName, Pref );
+    end
+end
+
+%% =======================================================================
+%  === var2str Function ==================================================
+%  =======================================================================
+function str = var2str(object, PreserveSpace)
+% convert matlab variables to a string
+switch (1)
+  case isempty(object)
+    str = '';
+  case (isnumeric(object) || islogical(object))
+    if ndims(object)>2, object=object(:); end  % can't handle arrays with dimention > 2
+    str=mat2str(object);           % convert matrix to a string
+    % mark logical scalars with [] (logical arrays already have them) so the xml_read
+    % recognizes them as MATLAB objects instead of strings. Same with sparse
+    % matrices
+    if ((islogical(object) && isscalar(object)) || issparse(object)),
+      str = ['[' str ']'];
+    end
+    if (isinteger(object)),
+      str = ['[', class(object), '(', str ')]'];
+    end
+  case iscell(object)
+    if ndims(object)>2, object=object(:); end  % can't handle cell arrays with dimention > 2
+    [nr nc] = size(object);
+    obj2 = object;
+    for i=1:length(object(:))
+      str = var2str(object{i}, PreserveSpace);
+      if (ischar(object{i})), object{i} = ['''' object{i} '''']; else object{i}=str; end
+      obj2{i} = [object{i} ','];
+    end
+    for r = 1:nr, obj2{r,nc} = [object{r,nc} ';']; end
+    obj2 = obj2.';
+    str = ['{' obj2{:} '}'];
+  case isstruct(object)
+    str='';
+    warning('xml_io_tools:write:var2str', ...
+      'Struct was encountered where string was expected. Ignoring.');
+  case isa(object, 'function_handle')
+    str = ['[@' char(object) ']'];
+  case ischar(object)
+    str = object;
+  otherwise
+    str = char(object);
+end
+
+%% string clean-up
+str=str(:); str=str.';            % make sure this is a row vector of char's
+if (~isempty(str))
+  str(str<32|str==127)=' ';       % convert no-printable characters to spaces
+  if (~PreserveSpace)
+    str = strtrim(str);             % remove spaces from begining and the end
+    str = regexprep(str,'\s+',' '); % remove multiple spaces
+  end
+end
+
+%% =======================================================================
+%  === var2Namestr Function ==============================================
+%  =======================================================================
+function str = varName2str(str)
+% convert matlab variable names to a sting
+str = char(str);
+p   = strfind(str,'0x');
+if (~isempty(p))
+  for i=1:length(p)
+    before = str( p(i)+(0:3) );          % string to replace
+    after  = char(hex2dec(before(3:4))); % string to replace with
+    str = regexprep(str,before,after, 'once', 'ignorecase');
+    p=p-3; % since 4 characters were replaced with one - compensate
+  end
+end
+str = regexprep(str,'_COLON_',':', 'once', 'ignorecase');
+str = regexprep(str,'_DASH_' ,'-', 'once', 'ignorecase');
+

matlab_version/AU_training/data extraction/xml_io_tools_2010_11_05/xmlwrite_xerces.m

@@ -0,0 +1,109 @@
+function varargout=xmlwrite_xerces(varargin)
+%XMLWRITE_XERCES Serialize an XML Document Object Model node using Xerces parser. 
+%  xmlwrite_xerces(FILENAME,DOMNODE) serializes the DOMNODE to file FILENAME.
+%
+% The function xmlwrite_xerces is very similar the Matlab function xmlwrite 
+% but works directly with the XERCES java classes (written by Apache XML 
+% Project) instead of the XMLUtils class created by Mathworks. Xerces files
+% are provided in standard MATLAB instalation and live in root\java\jarext
+% directory. 
+%
+% Written by A.Amaro (02-22-2007) and generously donated to xml_io_tools. 
+% This function is needed as a work-around for a bug in XMLUtils library
+% which can not write CDATA SECTION nodes correctly. Also Xerces and 
+% XMLUtils libraries handle namespaces differently.  
+%
+% Examples:
+%   % See xmlwrite examples this function have almost identical behavior.
+%  
+% Advanced use:
+%  FILENAME can also be a URN, java.io.OutputStream or java.io.Writer object
+%  SOURCE can also be a SAX InputSource, JAXP Source, InputStream, or 
+%    Reader object
+
+returnString = false;
+if length(varargin)==1
+    returnString = true;
+    result = java.io.StringWriter;
+    source = varargin{1};
+else
+    result = varargin{1};
+    if ischar(result)
+      % Using the XERCES classes directly, is not needed to modify the
+      % filename string. So I have commented this next line
+      %  result = F_xmlstringinput(result,false);
+    end
+    
+    source = varargin{2};
+    if ischar(source)
+        source = F_xmlstringinput(source,true);
+    end
+end
+
+% SERIALIZATION OF THE DOM DOCUMENT USING XERCES CLASSES DIRECTLY
+
+% 1) create the output format according to the document definitions
+% and type
+objOutputFormat = org.apache.xml.serialize.OutputFormat(source);
+set(objOutputFormat,'Indenting','on');
+
+% 2) create the output stream. In this case: an XML file
+objFile = java.io.File(result);
+objOutputStream = java.io.FileOutputStream(objFile);
+
+% 3) Create the Xerces Serializer object
+objSerializer= org.apache.xml.serialize.XMLSerializer(objOutputStream,objOutputFormat);
+
+% 4) Serialize to the XML files
+javaMethod('serialize',objSerializer,source);
+
+% 5) IMPORTANT! Delete the objects to liberate the XML file created
+objOutputStream.close;
+
+if returnString
+    varargout{1}=char(result.toString);
+end
+
+%% ========================================================================
+ function out = F_xmlstringinput(xString,isFullSearch,varargin)
+% The function F_xmlstringinput is a copy of the private function:
+% 'xmlstringinput' that the original xmlwrite function uses.
+
+if isempty(xString)
+    error('Filename is empty');
+elseif ~isempty(findstr(xString,'://'))
+    %xString is already a URL, most likely prefaced by file:// or http://
+    out = xString;
+    return;
+end
+
+xPath=fileparts(xString);
+if isempty(xPath)
+    if nargin<2 || isFullSearch
+        out = which(xString);
+        if isempty(out)
+            error('xml:FileNotFound','File %s not found',xString);
+        end
+    else
+        out = fullfile(pwd,xString);
+    end
+else
+    out = xString;
+    if (nargin<2 || isFullSearch) && ~exist(xString,'file')
+        %search to see if xString exists when isFullSearch
+        error('xml:FileNotFound','File %s not found',xString);
+    end
+end
+
+%Return as a URN
+if strncmp(out,'\\',2)
+    % SAXON UNC filepaths need to look like file:///\\\server-name\
+    out = ['file:///\',out];
+elseif strncmp(out,'/',1)
+    % SAXON UNIX filepaths need to look like file:///root/dir/dir
+    out = ['file://',out];
+else
+    % DOS filepaths need to look like file:///d:/foo/bar
+    out = ['file:///',strrep(out,'\','/')];
+end
+

matlab_version/AU_training/experiments/BP4D/Prepare_HOG_AU_data_generic.m

@@ -0,0 +1,98 @@
+function [data_train, labels_train, data_devel, labels_devel, raw_devel, PC, means_norm, stds_norm, valid_ids_test] = ...
+    Prepare_HOG_AU_data_generic(train_users, devel_users, au_train, bp4d_dir, hog_data_dir, pca_file)
+
+%%
+addpath(genpath('../../data extraction/'));
+
+au_other = setdiff([1, 2, 4, 6, 7, 10, 12, 14, 15, 17, 23], au_train);
+[ labels_other, ~, ~ ] = extract_BP4D_labels(bp4d_dir, train_users, au_other);
+labels_other = cat(1, labels_other{:});
+
+% First extracting the labels
+[ labels_train, valid_ids_train, vid_ids_train ] = extract_BP4D_labels(bp4d_dir, train_users, au_train);
+
+train_geom_data = Read_geom_files(train_users, hog_data_dir);
+% Reading in the HOG data (of only relevant frames)
+[train_appearance_data, valid_ids_train_hog, vid_ids_train_string] = Read_HOG_files(train_users, hog_data_dir);
+train_appearance_data = cat(2, train_appearance_data, train_geom_data);
+
+% Subsample the data to make training quicker
+labels_train = cat(1, labels_train{:});
+valid_ids_train = logical(cat(1, valid_ids_train{:}));
+reduced_inds = false(size(labels_train,1),1);
+
+if(numel(au_train) == 1)
+    reduced_inds(labels_train == 1) = true;
+else
+    reduced_inds(:) = true; 
+end
+
+% make sure the same number of positive and negative samples is taken
+pos_count = sum(labels_train == 1);
+neg_count = sum(labels_train == 0);
+
+num_other = floor(pos_count / (size(labels_other, 2)));
+
+inds_all = 1:size(labels_train,1);
+
+if(numel(au_train) == 1)
+    for i=1:size(labels_other, 2)+1
+
+        if(i > size(labels_other, 2))
+            % fill the rest with a proportion of neutral
+            inds_other = inds_all(sum(labels_other,2)==0 & ~labels_train );   
+            num_other_i = min(numel(inds_other), pos_count - sum(labels_train(reduced_inds,:)==0));     
+        else
+            % take a proportion of each other AU
+            inds_other = inds_all(labels_other(:, i) & ~labels_train );      
+            num_other_i = min(numel(inds_other), num_other);        
+        end
+        inds_other_to_keep = inds_other(round(linspace(1, numel(inds_other), num_other_i)));
+        reduced_inds(inds_other_to_keep) = true;
+
+    end
+end
+% Remove invalid ids based on CLM failing or AU not being labelled
+reduced_inds(~valid_ids_train) = false;
+reduced_inds(~valid_ids_train_hog) = false;
+
+% labels_other = labels_other(reduced_inds, :);
+labels_train = labels_train(reduced_inds,:);
+train_appearance_data = train_appearance_data(reduced_inds,:);
+vid_ids_train_string = vid_ids_train_string(reduced_inds,:);
+
+%% Extract devel data
+
+% First extracting the labels
+[ labels_devel, valid_ids_devel, vid_ids_devel ] = extract_BP4D_labels(bp4d_dir, devel_users, au_train);
+
+% Reading in the HOG data (of only relevant frames)
+devel_geom_data = Read_geom_files(devel_users, hog_data_dir);
+[devel_appearance_data, valid_ids_devel_hog, vid_ids_devel_string] = Read_HOG_files(devel_users, hog_data_dir);
+devel_appearance_data = cat(2, devel_appearance_data, devel_geom_data);
+
+labels_devel = cat(1, labels_devel{:});
+
+valid_ids_test = valid_ids_devel_hog;
+
+% normalise the data
+load(pca_file);
+     
+PC_n = zeros(size(PC)+size(train_geom_data, 2));
+PC_n(1:size(PC,1), 1:size(PC,2)) = PC;
+PC_n(size(PC,1)+1:end, size(PC,2)+1:end) = eye(size(train_geom_data, 2));
+PC = PC_n;
+
+means_norm = cat(2, means_norm, zeros(1, size(train_geom_data,2)));
+stds_norm = cat(2, stds_norm, ones(1, size(train_geom_data,2)));
+
+% Grab all data for validation as want good params for all the data
+raw_devel = devel_appearance_data;
+
+devel_appearance_data = bsxfun(@times, bsxfun(@plus, devel_appearance_data, -means_norm), 1./stds_norm);
+train_appearance_data = bsxfun(@times, bsxfun(@plus, train_appearance_data, -means_norm), 1./stds_norm);
+
+data_train = train_appearance_data * PC;
+data_devel = devel_appearance_data * PC;
+
+end

matlab_version/AU_training/experiments/BP4D/Prepare_HOG_AU_data_generic_dynamic.m

@@ -0,0 +1,94 @@
+function [data_train, labels_train, data_devel, labels_devel, raw_devel, PC, means_norm, stds_norm, valid_ids_devel] = ...
+    Prepare_HOG_AU_data_generic_dynamic(train_users, devel_users, au_train, bp4d_dir, hog_data_dir, pca_file)
+
+%%
+addpath(genpath('../../data extraction/'));
+
+au_other = setdiff([1, 2, 4, 6, 7, 10, 12, 14, 15, 17, 23], au_train);
+[ labels_other, ~, ~ ] = extract_BP4D_labels(bp4d_dir, train_users, au_other);
+labels_other = cat(1, labels_other{:});
+
+% First extracting the labels
+[ labels_train, valid_ids_train, vid_ids_train ] = extract_BP4D_labels(bp4d_dir, train_users, au_train);
+
+train_geom_data = Read_geom_files_dynamic(train_users, hog_data_dir);
+
+% Reading in the HOG data (of only relevant frames)
+[train_appearance_data, valid_ids_train_hog, vid_ids_train_string] = Read_HOG_files_dynamic_pp(train_users, hog_data_dir);
+
+train_appearance_data = cat(2, train_appearance_data, train_geom_data);
+
+% Subsample the data to make training quicker
+labels_train = cat(1, labels_train{:});
+valid_ids_train = logical(cat(1, valid_ids_train{:}));
+
+reduced_inds = false(size(labels_train,1),1);
+reduced_inds(labels_train == 1) = true;
+
+% make sure the same number of positive and negative samples is taken
+pos_count = sum(labels_train == 1);
+neg_count = sum(labels_train == 0);
+
+num_other = floor(pos_count / (size(labels_other, 2)));
+
+inds_all = 1:size(labels_train,1);
+
+for i=1:size(labels_other, 2)+1
+   
+    if(i > size(labels_other, 2))
+        % fill the rest with a proportion of neutral
+        inds_other = inds_all(sum(labels_other,2)==0 & ~labels_train );   
+        num_other_i = min(numel(inds_other), pos_count - sum(labels_train(reduced_inds,:)==0));     
+    else
+        % take a proportion of each other AU
+        inds_other = inds_all(labels_other(:, i) & ~labels_train );      
+        num_other_i = min(numel(inds_other), num_other);        
+    end
+    inds_other_to_keep = inds_other(round(linspace(1, numel(inds_other), num_other_i)));
+    reduced_inds(inds_other_to_keep) = true;
+    
+end
+
+% Remove invalid ids based on CLM failing or AU not being labelled
+reduced_inds(~valid_ids_train) = false;
+reduced_inds(~valid_ids_train_hog) = false;
+
+labels_other = labels_other(reduced_inds, :);
+labels_train = labels_train(reduced_inds,:);
+train_appearance_data = train_appearance_data(reduced_inds,:);
+vid_ids_train_string = vid_ids_train_string(reduced_inds,:);
+
+%% Extract devel data
+
+% First extracting the labels
+[ labels_devel, valid_ids_devel, vid_ids_devel ] = extract_BP4D_labels(bp4d_dir, devel_users, au_train);
+labels_devel = cat(1, labels_devel{:});
+
+% Reading in the HOG data (of only relevant frames)
+devel_geom_data = Read_geom_files_dynamic(devel_users, hog_data_dir);
+[devel_appearance_data, valid_ids_devel_hog, vid_ids_devel_string] = Read_HOG_files_dynamic_pp(devel_users, hog_data_dir);
+devel_appearance_data = cat(2, devel_appearance_data, devel_geom_data);
+
+valid_ids_devel = valid_ids_devel_hog;
+
+% normalise the data
+load(pca_file);
+     
+PC_n = zeros(size(PC)+size(train_geom_data, 2));
+PC_n(1:size(PC,1), 1:size(PC,2)) = PC;
+PC_n(size(PC,1)+1:end, size(PC,2)+1:end) = eye(size(train_geom_data, 2));
+PC = PC_n;
+
+means_norm = cat(2, means_norm, zeros(1, size(train_geom_data,2)));
+stds_norm = cat(2, stds_norm, ones(1, size(train_geom_data,2)));
+
+% Grab all data for validation as want good params for all the data
+raw_devel = devel_appearance_data;
+
+devel_appearance_data = bsxfun(@times, bsxfun(@plus, devel_appearance_data, -means_norm), 1./stds_norm);
+train_appearance_data = bsxfun(@times, bsxfun(@plus, train_appearance_data, -means_norm), 1./stds_norm);
+
+data_train = train_appearance_data * PC;
+data_devel = devel_appearance_data * PC;
+
+end

matlab_version/AU_training/experiments/BP4D/Prepare_HOG_AU_data_generic_intensity.m

@@ -0,0 +1,103 @@
+function [data_train, labels_train, vid_ids_train_string, data_devel, labels_devel, vid_ids_devel_string, raw_devel, PC, means_norm, stds_norm, success_devel] = ...
+    Prepare_HOG_AU_data_generic_intensity(train_users, devel_users, au_train, bp4d_dir, hog_data_dir, pca_file)
+
+%%
+addpath(genpath('../data extraction/'));
+
+% First extracting the labels
+[ labels_train, valid_ids_train, vid_ids_train ] = extract_BP4D_labels_intensity(bp4d_dir, train_users, au_train);
+au_other = setdiff([6, 10, 12, 14, 17], au_train);
+[ labels_other, ~, ~ ] = extract_BP4D_labels_intensity(bp4d_dir, train_users, au_other);
+labels_other = cat(1, labels_other{:});
+
+train_geom_data = Read_geom_files(train_users, hog_data_dir);
+
+% Reading in the HOG data (of only relevant frames)
+[train_appearance_data, valid_ids_train_hog, vid_ids_train_string] = Read_HOG_files(train_users, hog_data_dir);
+train_appearance_data = cat(2, train_appearance_data, train_geom_data);
+
+% Subsample the data to make training quicker
+labels_train = cat(1, labels_train{:});
+valid_ids_train = logical(cat(1, valid_ids_train{:}));
+
+reduced_inds = false(size(labels_train,1),1);
+reduced_inds(labels_train > 0) = true;
+
+% make sure the same number of positive and negative samples is taken
+pos_count = sum(labels_train > 0);
+neg_count = sum(labels_train == 0);
+
+num_other = floor(pos_count / (size(labels_other, 2)));
+
+inds_all = 1:size(labels_train,1);
+
+if(numel(train_users) > 0)
+    if(numel(au_train) == 1)
+        for i=1:size(labels_other, 2)+1
+
+            if(i > size(labels_other, 2))
+                % fill the rest with a proportion of neutral
+                inds_other = inds_all(sum(labels_other,2)==0 & ~labels_train );   
+                num_other_i = min(numel(inds_other), pos_count - sum(labels_train(reduced_inds,:)==0));     
+            else
+                % take a proportion of each other AU
+                inds_other = inds_all(labels_other(:, i) & ~labels_train );      
+                num_other_i = min(numel(inds_other), num_other);        
+            end
+            inds_other_to_keep = inds_other(round(linspace(1, numel(inds_other), num_other_i)));
+            reduced_inds(inds_other_to_keep) = true;
+
+        end
+    end
+    % Remove invalid ids based on CLM failing or AU not being labelled
+    reduced_inds(~valid_ids_train) = false;
+    reduced_inds(~valid_ids_train_hog) = false;
+
+    labels_other = labels_other(reduced_inds, :);
+    labels_train = labels_train(reduced_inds,:);
+    train_appearance_data = train_appearance_data(reduced_inds,:);
+    vid_ids_train_string = vid_ids_train_string(reduced_inds,:);
+
+end
+
+%% Extract devel data
+
+% First extracting the labels
+[ labels_devel, valid_ids_devel, vid_ids_devel ] = extract_BP4D_labels_intensity(bp4d_dir, devel_users, au_train);
+
+devel_geom_data = Read_geom_files(devel_users, hog_data_dir);
+% Reading in the HOG data (of only relevant frames)
+[devel_appearance_data, valid_ids_devel_hog, vid_ids_devel_string] = Read_HOG_files(devel_users, hog_data_dir);
+devel_appearance_data = cat(2, devel_appearance_data, devel_geom_data);
+
+valid_ids_devel = logical(cat(1, valid_ids_devel{:}));
+
+labels_devel = cat(1, labels_devel{:});
+
+success_devel = valid_ids_devel;
+
+% normalise the data
+load(pca_file);
+
+PC_n = zeros(size(PC)+size(devel_geom_data, 2));
+PC_n(1:size(PC,1), 1:size(PC,2)) = PC;
+PC_n(size(PC,1)+1:end, size(PC,2)+1:end) = eye(size(devel_geom_data, 2));
+PC = PC_n;
+
+means_norm = cat(2, means_norm, zeros(1, size(devel_geom_data,2)));
+stds_norm = cat(2, stds_norm, ones(1, size(devel_geom_data,2)));
+
+% Grab all data for validation as want good params for all the data
+raw_devel = devel_appearance_data;
+
+devel_appearance_data = bsxfun(@times, bsxfun(@plus, devel_appearance_data, -means_norm), 1./stds_norm);
+data_devel = devel_appearance_data * PC;
+
+if(numel(train_users) > 0)
+    train_appearance_data = bsxfun(@times, bsxfun(@plus, train_appearance_data, -means_norm), 1./stds_norm);
+    data_train = train_appearance_data * PC;
+else
+    data_train = [];
+end
+
+end

matlab_version/AU_training/experiments/BP4D/Read_HOG_files.m

@@ -0,0 +1,93 @@
+function [hog_data, valid_inds, vid_id] = Read_HOG_files(users, hog_data_dir)
+
+    hog_data = [];
+    vid_id = {};
+    valid_inds = [];
+    
+    feats_filled = 0;
+
+    for i=1:numel(users)
+        
+        hog_files = dir([hog_data_dir, '/train/' users{i} '*.hog']);
+        hog_dir = [hog_data_dir, '/train/'];
+        if(isempty(hog_files))
+            hog_files = dir([hog_data_dir, '/devel/' users{i} '*.hog']);
+            hog_dir = [hog_data_dir, '/devel/'];
+        end
+        
+        for h=1:numel(hog_files)
+            hog_file = [hog_dir, hog_files(h).name];
+            f = fopen(hog_file, 'r');
+
+            curr_data = [];
+            curr_ind = 0;
+
+            while(~feof(f))
+
+                if(curr_ind == 0)
+                    num_cols = fread(f, 1, 'int32');
+                    if(isempty(num_cols))
+                        break;
+                    end
+
+                    num_rows = fread(f, 1, 'int32');
+                    num_chan = fread(f, 1, 'int32');
+
+                    curr_ind = curr_ind + 1;            
+
+                    % preallocate some space
+                    if(curr_ind == 1)
+                        curr_data = zeros(1000, 1 + num_rows * num_cols * num_chan);
+                        num_feats =  1 + num_rows * num_cols * num_chan;
+                    end
+
+                    if(curr_ind > size(curr_data,1))
+                        curr_data = cat(1, curr_data, zeros(1000, 1 + num_rows * num_cols * num_chan));
+                    end
+                    feature_vec = fread(f, [1, 1 + num_rows * num_cols * num_chan], 'float32');
+                    curr_data(curr_ind, :) = feature_vec;
+                else
+
+                    % Reading in batches of 5000
+
+                    feature_vec = fread(f, [4 + num_rows * num_cols * num_chan, 5000], 'float32');
+                    feature_vec = feature_vec(4:end,:)';
+
+                    num_rows_read = size(feature_vec,1);
+
+                    curr_data(curr_ind+1:curr_ind+num_rows_read,:) = feature_vec;
+
+                    curr_ind = curr_ind + size(feature_vec,1);
+
+                end
+
+            end
+
+            fclose(f);
+
+            curr_data = curr_data(1:curr_ind,:);
+            vid_id_curr = cell(curr_ind,1);
+            vid_id_curr(:) = users(i);
+
+            vid_id = cat(1, vid_id, vid_id_curr);
+
+            % Assume same number of frames per video
+            if(i==1 && h == 1)
+                hog_data = zeros(curr_ind * numel(users) * 8, num_feats);
+            end
+
+            if(size(hog_data,1) < feats_filled+curr_ind)
+               hog_data = cat(1, hog_data, zeros(size(hog_data,1), num_feats));
+            end
+
+            hog_data(feats_filled+1:feats_filled+curr_ind,:) = curr_data;
+
+            feats_filled = feats_filled + curr_ind;
+        end
+    end
+    
+    if(~isempty(hog_data))        
+        valid_inds = hog_data(1:feats_filled,1);
+        hog_data = hog_data(1:feats_filled,2:end);
+    end
+end

matlab_version/AU_training/experiments/BP4D/Read_HOG_files_dynamic_pp.m

@@ -0,0 +1,101 @@
+function [hog_data, valid_inds, vid_id] = Read_HOG_files_dynamic_pp(users, hog_data_dir)
+
+    hog_data = [];
+    vid_id = {};
+    valid_inds = [];
+    
+    feats_filled = 0;
+
+    for i=1:numel(users)
+        
+        start_person_ind = feats_filled + 1;
+        
+        hog_files = dir([hog_data_dir, '/train/' users{i} '*.hog']);
+        hog_dir = [hog_data_dir, '/train/'];
+        if(isempty(hog_files))
+            hog_files = dir([hog_data_dir, '/devel/' users{i} '*.hog']);
+            hog_dir = [hog_data_dir, '/devel/'];
+        end
+        
+        for h=1:numel(hog_files)
+            hog_file = [hog_dir, hog_files(h).name];
+            f = fopen(hog_file, 'r');
+
+            curr_data = [];
+            curr_ind = 0;
+
+            while(~feof(f))
+
+                if(curr_ind == 0)
+                    num_cols = fread(f, 1, 'int32');
+                    if(isempty(num_cols))
+                        break;
+                    end
+
+                    num_rows = fread(f, 1, 'int32');
+                    num_chan = fread(f, 1, 'int32');
+
+                    curr_ind = curr_ind + 1;            
+
+                    % preallocate some space
+                    if(curr_ind == 1)
+                        curr_data = zeros(1000, 1 + num_rows * num_cols * num_chan);
+                        num_feats =  1 + num_rows * num_cols * num_chan;
+                    end
+
+                    if(curr_ind > size(curr_data,1))
+                        curr_data = cat(1, curr_data, zeros(1000, 1 + num_rows * num_cols * num_chan));
+                    end
+                    feature_vec = fread(f, [1, 1 + num_rows * num_cols * num_chan], 'float32');
+                    curr_data(curr_ind, :) = feature_vec;
+                else
+
+                    % Reading in batches of 5000
+
+                    feature_vec = fread(f, [4 + num_rows * num_cols * num_chan, 5000], 'float32');
+                    feature_vec = feature_vec(4:end,:)';
+
+                    num_rows_read = size(feature_vec,1);
+
+                    curr_data(curr_ind+1:curr_ind+num_rows_read,:) = feature_vec;
+
+                    curr_ind = curr_ind + size(feature_vec,1);
+
+                end
+
+            end
+
+            fclose(f);
+
+            curr_data = curr_data(1:curr_ind,:);
+            vid_id_curr = cell(curr_ind,1);
+            vid_id_curr(:) = users(i);
+
+            vid_id = cat(1, vid_id, vid_id_curr);
+
+            % Assume same number of frames per video
+            if(i==1 && h == 1)
+                hog_data = zeros(curr_ind * numel(users) * 8, num_feats);
+            end
+
+            if(size(hog_data,1) < feats_filled+curr_ind)
+               hog_data = cat(1, hog_data, zeros(size(hog_data,1), num_feats));
+            end
+
+
+            hog_data(feats_filled+1:feats_filled+curr_ind,:) = curr_data;
+
+            feats_filled = feats_filled + curr_ind;
+        end
+        
+        person_ids = start_person_ind:feats_filled;
+        % Do the median normalisation per person here
+        hog_data(person_ids,2:end) = bsxfun(@plus, hog_data(person_ids,2:end), -median(hog_data(person_ids,2:end)));
+
+    end
+    
+    if(~isempty(hog_data))        
+        valid_inds = hog_data(1:feats_filled,1);
+        hog_data = hog_data(1:feats_filled,2:end);
+    end
+end

matlab_version/AU_training/experiments/BP4D/Read_geom_files.m

@@ -0,0 +1,41 @@
+function [geom_data, valid_ids] = Read_geom_files(users, hog_data_dir)
+
+    geom_data = [];
+    valid_ids = [];
+
+    load('../../pca_generation/pdm_68_aligned_wild.mat');
+    
+    for i=1:numel(users)
+        
+        geom_files = dir([hog_data_dir, '/train/', users{i} '*.params.txt']);
+        geom_dir = [hog_data_dir, '/train/'];
+        if(isempty(geom_files))
+            geom_files = dir([hog_data_dir, '/devel/', users{i} '*.params.txt']);
+            geom_dir = [hog_data_dir, '/devel/'];
+        end
+        
+        for h=1:numel(geom_files)
+            geom_file = [geom_dir, geom_files(h).name];
+            [~, nm, ~] = fileparts(geom_file);
+            m_file = [geom_dir, '/' nm '.params.mat'];
+              
+            if(~exist(m_file, 'file'))
+                res = dlmread(geom_file, ',', 1, 0);
+                save(m_file, 'res');
+            else
+                load(m_file);
+            end
+
+            valid = res(:, 4);
+            res = res(:, 11:end);
+                    
+            actual_locs = res * V';
+            res = cat(2, actual_locs, res);
+            
+            valid_ids = cat(1, valid_ids, valid);
+            
+            geom_data = cat(1, geom_data, res);
+                
+        end
+    end
+end

matlab_version/AU_training/experiments/BP4D/Read_geom_files_dynamic.m

@@ -0,0 +1,46 @@
+function [geom_data, valid_ids] = Read_geom_files_dynamic(users, hog_data_dir)
+
+    geom_data = [];
+    valid_ids = [];
+    
+    load('../../pca_generation/pdm_68_aligned_wild.mat');
+    
+    for i=1:numel(users)
+        
+        geom_files = dir([hog_data_dir, '/train/', users{i} '*.params.txt']);
+        geom_dir = [hog_data_dir, '/train/'];
+        if(isempty(geom_files))
+            geom_files = dir([hog_data_dir, '/devel/', users{i} '*.params.txt']);
+            geom_dir = [hog_data_dir, '/devel/'];
+        end
+        
+        geom_data_curr = [];
+        for h=1:numel(geom_files)
+            geom_file = [geom_dir, geom_files(h).name];
+                        
+            [~, nm, ~] = fileparts(geom_file);
+            m_file = [geom_dir, '/' nm '.params.mat'];
+              
+            if(~exist(m_file, 'file'))
+                res = dlmread(geom_file, ',', 1, 0);
+                save(m_file, 'res');
+            else
+                load(m_file);
+            end
+
+            valid = res(:, 4);
+            res = res(:, 11:end);
+                    
+            actual_locs = res * V';
+            res = cat(2, actual_locs, res);
+            
+            valid_ids = cat(1, valid_ids, valid);            
+            
+            geom_data_curr = cat(1, geom_data_curr, res);
+        end
+        geom_data_curr = bsxfun(@plus, geom_data_curr, -median(geom_data_curr));
+        
+        geom_data = cat(1, geom_data, geom_data_curr);
+                
+    end
+end

matlab_version/AU_training/experiments/BP4D/Script_HOG_SVM_dynamic.m

@@ -0,0 +1,64 @@
+% Change to your downloaded location
+clear
+addpath('C:\liblinear\matlab')
+addpath('../training_code/');
+addpath('../utilities/');
+addpath('../../data extraction/');
+%% load shared definitions and AU data
+shared_defs;
+
+% Set up the hyperparameters to be validated
+hyperparams.c = 10.^(-7:0.5:1);
+hyperparams.e = 10.^(-3);
+
+hyperparams.validate_params = {'c', 'e'};
+
+% Set the training function
+svm_train = @svm_train_linear;
+    
+% Set the test function (the first output will be used for validation)
+svm_test = @svm_test_linear;
+
+pca_loc = '../../pca_generation/generic_face_rigid.mat';
+
+hog_data_dir_BP4D = hog_data_dir;
+
+aus = [1, 2, 4, 6, 7, 10, 12, 14, 15, 17, 23];
+%%
+for a=1:numel(aus)
+        
+    au = aus(a);
+
+    rest_aus = setdiff(all_aus, au);        
+
+    % load the training and testing data for the current fold
+    [train_samples, train_labels, valid_samples, valid_labels, ~, PC, means, scaling] = Prepare_HOG_AU_data_generic_dynamic(train_recs, devel_recs, au, BP4D_dir, hog_data_dir_BP4D, pca_loc);
+
+    train_samples = sparse(train_samples);
+    valid_samples = sparse(valid_samples);
+
+    %% Cross-validate here                
+    [ best_params, ~ ] = validate_grid_search_no_par(svm_train, svm_test, false, train_samples, train_labels, valid_samples, valid_labels, hyperparams);
+    model = svm_train(train_labels, train_samples, best_params);        
+    
+    [~, predictions_all] = svm_test(valid_labels, valid_samples, model);
+    
+    name = sprintf('results_BP4D_devel/AU_%d_dynamic.mat', au);
+
+    [ accuracies, F1s, corrs, ccc, rms, classes ] = evaluate_regression_results( predictions_all, valid_labels );
+    
+    save(name, 'model', 'F1s', 'accuracies', 'predictions_all', 'valid_labels');
+       
+    % Write out the model
+    name = sprintf('models/AU_%d_dynamic.dat', au);
+
+    pos_lbl = model.Label(1);
+    neg_lbl = model.Label(2);
+    
+    w = model.w(1:end-1)';
+    b = model.w(end);
+
+    svs = bsxfun(@times, PC, 1./scaling') * w;
+    
+    write_lin_dyn_svm(name, means, svs, b, pos_lbl, neg_lbl);
+end

matlab_version/AU_training/experiments/BP4D/Script_HOG_SVM_static.m

@@ -0,0 +1,66 @@
+% Change to your downloaded location
+clear
+addpath('C:\liblinear\matlab')
+addpath('../training_code/');
+addpath('../utilities/');
+addpath('../../data extraction/');
+%% load shared definitions and AU data
+shared_defs;
+
+% Set up the hyperparameters to be validated
+hyperparams.c = 10.^(-7:0.5:1);
+hyperparams.e = 10.^(-3);
+
+hyperparams.validate_params = {'c', 'e'};
+
+% Set the training function
+svm_train = @svm_train_linear;
+    
+% Set the test function (the first output will be used for validation)
+svm_test = @svm_test_linear;
+
+pca_loc = '../../pca_generation/generic_face_rigid.mat';
+
+hog_data_dir_BP4D = hog_data_dir;
+
+aus = [1, 2, 4, 6, 7, 10, 12, 14, 15, 17, 23];
+%%
+for a=1:numel(aus)
+        
+    au = aus(a);
+
+    rest_aus = setdiff(all_aus, au);        
+
+    % load the training and testing data for the current fold
+    [train_samples, train_labels, valid_samples, valid_labels, ~, PC, means, scaling] = Prepare_HOG_AU_data_generic(train_recs, devel_recs, au, BP4D_dir, hog_data_dir_BP4D, pca_loc);
+
+    train_samples = sparse(train_samples);
+    valid_samples = sparse(valid_samples);
+
+    %% Cross-validate here                
+    [ best_params, ~ ] = validate_grid_search_no_par(svm_train, svm_test, false, train_samples, train_labels, valid_samples, valid_labels, hyperparams);
+    model = svm_train(train_labels, train_samples, best_params);        
+    
+    [~, predictions_all] = svm_test(valid_labels, valid_samples, model);
+    
+    name = sprintf('results_BP4D_devel/AU_%d_static.mat', au);
+
+    [ accuracies, F1s, corrs, ccc, rms, classes ] = evaluate_regression_results( predictions_all, valid_labels );
+    
+    save(name, 'model', 'F1s', 'accuracies', 'predictions_all', 'valid_labels');
+       
+    % Write out the model
+    name = sprintf('models/AU_%d_static.dat', au);
+
+    pos_lbl = model.Label(1);
+    neg_lbl = model.Label(2);
+    
+    w = model.w(1:end-1)';
+    b = model.w(end);
+
+    svs = bsxfun(@times, PC, 1./scaling') * w;
+    
+    write_lin_svm(name, means, svs, b, pos_lbl, neg_lbl);
+end
+
+

matlab_version/AU_training/experiments/BP4D/Script_HOG_SVR_dynamic_shift.m

@@ -0,0 +1,83 @@
+%% load shared definitions and AU data
+clear
+
+addpath('../../data extraction/');
+addpath('../utilities/');
+addpath('../training_code/');
+
+shared_defs;
+
+% Set up the hyperparameters to be validated
+hyperparams.c = 10.^(-7:1:4);
+hyperparams.p = 10.^(-2);
+
+hyperparams.validate_params = {'c', 'p'};
+
+% Set the training function
+svr_train = @svr_train_linear_shift_fancy;
+    
+% Set the test function (the first output will be used for validation)
+svr_test = @svr_test_linear_shift_fancy;
+
+pca_loc = '../../pca_generation/generic_face_rigid.mat';
+
+hog_data_dir_BP4D = hog_data_dir;
+
+aus = [6, 10, 12, 14, 17];
+%%
+for a=1:numel(aus)
+    
+    predictions_all = [];
+    test_labels_all = [];
+    
+    au = aus(a);
+
+    rest_aus = setdiff(all_aus, au);        
+    
+    % load the training and testing data for the current fold
+    [train_samples, train_labels, ~, valid_samples, valid_labels, vid_ids_devel, ~, PC, means, scaling, success_devel] = Prepare_HOG_AU_data_generic_intensity(train_recs, devel_recs, au, BP4D_dir_int, hog_data_dir_BP4D, pca_loc);
+    
+    ignore = valid_labels == 9;
+    
+    valid_samples = valid_samples(~ignore, :);
+    valid_labels = valid_labels(~ignore);
+    vid_ids_devel = vid_ids_devel(~ignore);
+    success_devel = success_devel(~ignore);    
+    
+    train_samples = sparse(train_samples);
+    valid_samples = sparse(valid_samples);
+
+    hyperparams.success = success_devel;
+    hyperparams.valid_samples = valid_samples;
+    hyperparams.valid_labels = valid_labels;
+    hyperparams.vid_ids = vid_ids_devel;
+    
+    %% Cross-validate here                
+    [ best_params, ~ ] = validate_grid_search_no_par(svr_train, svr_test, false, train_samples, train_labels, valid_samples, valid_labels, hyperparams);
+    model = svr_train(train_labels, train_samples, best_params);        
+    
+    clear 'train_samples'
+    
+    %% Now test the model
+    model.vid_ids = vid_ids_devel;
+    
+    [~, prediction] = svr_test(valid_labels, valid_samples, model);
+
+    name = sprintf('results_BP4D_devel/AU_%d_static_intensity_shift.mat', au);
+
+    [ accuracies, F1s, corrs, ccc, rms, classes ] = evaluate_regression_results( prediction, valid_labels );
+    
+    save(name, 'model', 'F1s', 'corrs', 'accuracies', 'ccc', 'rms', 'prediction', 'valid_labels');
+        
+        % Go from raw data to the prediction
+    w = model.w(1:end-1)';
+    b = model.w(end);
+
+    svs = bsxfun(@times, PC, 1./scaling') * w;
+
+    name = sprintf('models/AU_%d_static_intensity_shift.dat', au);
+
+    write_lin_svr(name, means, svs, b);
+    
+end
+

matlab_version/AU_training/experiments/BP4D/Script_HOG_SVR_static.m

@@ -0,0 +1,80 @@
+%% load shared definitions and AU data
+clear
+
+addpath('../../data extraction/');
+addpath('../utilities/');
+addpath('../training_code/');
+
+shared_defs;
+
+% Set up the hyperparameters to be validated
+hyperparams.c = 10.^(-7:1:4);
+hyperparams.p = 10.^(-2);
+
+hyperparams.validate_params = {'c', 'p'};
+
+% Set the training function
+svr_train = @svr_train_linear;
+    
+% Set the test function (the first output will be used for validation)
+svr_test = @svr_test_linear;
+
+pca_loc = '../../pca_generation/generic_face_rigid.mat';
+
+hog_data_dir_BP4D = hog_data_dir;
+
+aus = [6, 10, 12, 14, 17];
+%%
+for a=1:numel(aus)
+    
+    predictions_all = [];
+    test_labels_all = [];
+    
+    au = aus(a);
+
+    rest_aus = setdiff(all_aus, au);        
+    
+    % load the training and testing data for the current fold
+    [train_samples, train_labels, ~, valid_samples, valid_labels, vid_ids_devel, ~, PC, means, scaling, success_devel] = Prepare_HOG_AU_data_generic_intensity(train_recs, devel_recs, au, BP4D_dir_int, hog_data_dir_BP4D, pca_loc);
+    
+    ignore = valid_labels == 9;
+    
+    valid_samples = valid_samples(~ignore, :);
+    valid_labels = valid_labels(~ignore);
+    vid_ids_devel = vid_ids_devel(~ignore);
+    success_devel = success_devel(~ignore);
+    
+    train_samples = sparse(train_samples);
+    valid_samples = sparse(valid_samples);
+
+    hyperparams.success = success_devel;
+
+    %% Cross-validate here                
+    [ best_params, ~ ] = validate_grid_search_no_par(svr_train, svr_test, false, train_samples, train_labels, valid_samples, valid_labels, hyperparams);
+    model = svr_train(train_labels, train_samples, best_params);        
+    
+    clear 'train_samples'
+    
+    %% Now test the model
+    model.vid_ids = vid_ids_devel;
+    
+    [~, prediction] = svr_test(valid_labels, valid_samples, model);
+
+    name = sprintf('results_BP4D_devel/AU_%d_static_intensity.mat', au);
+
+    [ accuracies, F1s, corrs, ccc, rms, classes ] = evaluate_regression_results( prediction, valid_labels );
+    
+    save(name, 'model', 'F1s', 'corrs', 'accuracies', 'ccc', 'rms', 'prediction', 'valid_labels');
+        
+        % Go from raw data to the prediction
+    w = model.w(1:end-1)';
+    b = model.w(end);
+
+    svs = bsxfun(@times, PC, 1./scaling') * w;
+
+    name = sprintf('models/AU_%d_static_intensity.dat', au);
+
+    write_lin_svr(name, means, svs, b);
+    
+end
+

matlab_version/AU_training/experiments/BP4D/Script_HOG_SVR_static_shift.m

@@ -0,0 +1,83 @@
+%% load shared definitions and AU data
+clear
+
+addpath('../../data extraction/');
+addpath('../utilities/');
+addpath('../training_code/');
+
+shared_defs;
+
+% Set up the hyperparameters to be validated
+hyperparams.c = 10.^(-7:1:4);
+hyperparams.p = 10.^(-2);
+
+hyperparams.validate_params = {'c', 'p'};
+
+% Set the training function
+svr_train = @svr_train_linear_shift_fancy;
+    
+% Set the test function (the first output will be used for validation)
+svr_test = @svr_test_linear_shift_fancy;
+
+pca_loc = '../../pca_generation/generic_face_rigid.mat';
+
+hog_data_dir_BP4D = hog_data_dir;
+
+aus = [6, 10, 12, 14, 17];
+%%
+for a=1:numel(aus)
+    
+    predictions_all = [];
+    test_labels_all = [];
+    
+    au = aus(a);
+
+    rest_aus = setdiff(all_aus, au);        
+    
+    % load the training and testing data for the current fold
+    [train_samples, train_labels, ~, valid_samples, valid_labels, vid_ids_devel, ~, PC, means, scaling, success_devel] = Prepare_HOG_AU_data_generic_intensity(train_recs, devel_recs, au, BP4D_dir_int, hog_data_dir_BP4D, pca_loc);
+    
+    ignore = valid_labels == 9;
+    
+    valid_samples = valid_samples(~ignore, :);
+    valid_labels = valid_labels(~ignore);
+    vid_ids_devel = vid_ids_devel(~ignore);
+    success_devel = success_devel(~ignore);    
+    
+    train_samples = sparse(train_samples);
+    valid_samples = sparse(valid_samples);
+
+    hyperparams.success = success_devel;
+    hyperparams.valid_samples = valid_samples;
+    hyperparams.valid_labels = valid_labels;
+    hyperparams.vid_ids = vid_ids_devel;
+    
+    %% Cross-validate here                
+    [ best_params, ~ ] = validate_grid_search_no_par(svr_train, svr_test, false, train_samples, train_labels, valid_samples, valid_labels, hyperparams);
+    model = svr_train(train_labels, train_samples, best_params);        
+    
+    clear 'train_samples'
+    
+    %% Now test the model
+    model.vid_ids = vid_ids_devel;
+    
+    [~, prediction] = svr_test(valid_labels, valid_samples, model);
+
+    name = sprintf('results_BP4D_devel/AU_%d_static_intensity_shift.mat', au);
+
+    [ accuracies, F1s, corrs, ccc, rms, classes ] = evaluate_regression_results( prediction, valid_labels );
+    
+    save(name, 'model', 'F1s', 'corrs', 'accuracies', 'ccc', 'rms', 'prediction', 'valid_labels');
+        
+        % Go from raw data to the prediction
+    w = model.w(1:end-1)';
+    b = model.w(end);
+
+    svs = bsxfun(@times, PC, 1./scaling') * w;
+
+    name = sprintf('models/AU_%d_static_intensity_shift.dat', au);
+
+    write_lin_svr(name, means, svs, b);
+    
+end
+

matlab_version/AU_training/experiments/BP4D/get_balanced_fold.m

@@ -0,0 +1,21 @@
+function [train_users, dev_users] = get_balanced_fold(BP4D_dir, users, au, prop_test)
+
+    % Extracting the labels
+    [labels, valid_ids, vid_ids, filenames] = extract_BP4D_labels(BP4D_dir, users, au);
+    
+    % the grouping should be done per person
+    
+    for f=1:numel(filenames)
+        filenames{f} = filenames{f}(1:4);
+    end
+    
+    counts = zeros(numel(users),1);
+    for k=1:numel(users)
+        counts(k) = sum(cat(1, labels{strcmp(filenames, users{k})}));
+    end
+
+    [sorted, inds] = sort(counts);
+
+    dev_users = users(inds(1:round(1/prop_test):end));
+    train_users = setdiff(users, dev_users);
+end