remove dependency on line codes

MissingNodes_SrcCode2014/DumpDataset.m

     LogMsg(sprintf('DumpDataset for %s%s iter %d/%d into %s%s.', dataFilePath, dataFileName, iter, i, outPath, outFile));
 end
     %fprintf('Completed DumpDataset.\n');
-
-

MissingNodes_SrcCode2014/MissingNodes_S8b.m

                                         % cases we are using the GED as the main measure
                                         fprintf('^%s', newPredictedGraph)
                                        
+                                        
                                         %remap the original data so that the known nodes match the
                                         %predicted data and the missing nodes match the predicted
                                         % nodes created from each cluster
                                         small_data4 = newPredictedGraph;
                                         small_data4(indices_to_remove,:) = [];
                                         small_data4(:,indices_to_remove) = [];
-                                        
-                                        %%% Sigal 27.1.13 - save reduce graphs for GED
+Sigal 27.1.13 - save reduce graphs for GED
                                         if dumpSmallFlag == 1
                                             saveSmallData(dumpSmallDataPath, dataFileName, iter, affinity_calculation_type, withAttrWeight, num_missing_nodes, small_data, 1);
                                             saveSmallData(dumpSmallDataPath, dataFileName, iter, affinity_calculation_type, withAttrWeight, num_missing_nodes, small_data2, 2);
                                         small_data2(:,indices_to_remove) = [];
                                         %fprintf('&%s', small_data2)
                                         %fprintf('&&%s', small_data)
- 
-                                        %%% Sigal 27.1.13 - save reduce graphs for GED
+Sigal 27.1.13 - save reduce graphs for GED
                                         withAttrWeight = origWithAttrWeight+1000*(1-percent_known_placeholders)*10;
                                         if dumpSmallFlag == 1
                                             saveSmallData(dumpSmallDataPath, dataFileName, iter, affinity_calculation_type, withAttrWeight, num_missing_nodes, small_data, 1);
 
 % sigal - 29.10.13
 % calc only PHs affinity
+
 function [affinity] = CalcPHsAffinity( data, affType, actual_graph_size, num_missing_nodes, num_attr_nodes, attWeight, addMissingAtt)
     global affinity_calculation_shortest_path;
     global affinity_calculation_euclid;
 
 
 function saveSmallData(dumpSmallDataPath, dataFileName, iter, affinity_type, withAttr, missNodes, small_data, i)
-    %%% Sigal 24.1.13 - TODO
+Sigal 24.1.13 - TODO
     outFile = sprintf('%s_%d_%d_%d_%d_small_data_%d', dataFileName, iter, missNodes, affinity_type, withAttr, i);
     if affinity_type == 9 % save instead a dummy size (1) and the best_alg
         SaveIntMatrixToFile(strcat(dumpSmallDataPath, outFile,'_edges.txt'), small_data, 1);
     end
     sumPurity = sum(crossPurity,2);
 end % function CalcSumPurity
- 

MissingNodes_SrcCode2014/PrepareAttributes5.m

-% Map attribute to categories
-% Use 0 for null/no value, 1 for unknown/private value (if exist) and then real values
-function [outAttributes, attUpperRange, selectedAttr, attStat] = PrepareAttributes5(dataFilePath, dataFileName, numNodes, expectedAttrCols, maxAttStat, inSelectedAttr, debug, debugPath)
+Map attribute to categories
+Use 0 for null/no value, 1 for unknown/private value (if exist) and then real values
+function [outAttributes, attUpperRange, selectedAttr, attStat] = PrepareAttributes5(dataFilePath, dataFileName, expectedAttrCols, maxAttStat, inSelectedAttr, debug, debugPath)
 
 
 outNoneValue = 0;
 m = size(attributes,1); % num nodes/lines
 n = size(attributes,2); % num attributes/cols
     
-if n ~= expectedAttrCols || m ~= numNodes
-    fprintf('PrepareAttributes - Invalid size: expecting (%dx%d), got (%dx%d)\n',numNodes,expectedAttrCols,m,n);
+if n ~= expectedAttrCols 
+    fprintf('PrepareAttributes - Invalid size: expecting (%d), got (%dx%d)\n',expectedAttrCols,m,n);
     return;
 end
 
     for i=1:maxCountry
         indices = (new_values==i);
         count = sum(indices);
-        if count/numNodes > maxAttStat
+        if count/m > maxAttStat
            new_values(indices) = 0;
         end
     end
 % calculate statistics and filter according to zero & maxAttStat
 attStat = zeros(1,n);
 for a = 1:n
-    attStat(a) = nnz(outAttributes(:,a))/numNodes;
+    attStat(a) = nnz(outAttributes(:,a))/m;
     if attStat(a) == 0
         selectedAttr(a)=0;
     elseif selectedAttr(a)>0 && attStat(a) > maxAttStat && a>1 % don't filter country

MissingNodes_SrcCode2014/RemoveRandomNodesWithImages.m

         for i = missing_nodes_all_neighbors
             neighbors = find(data(i,:));
             missing_neighbors = intersect(neighbors, missing_nodes_list);
+            
             missing_neighbors = sort(missing_neighbors, 'descend');
             for curr_missing_neighbor = missing_neighbors
                 if data(i,curr_missing_neighbor) == 1
 end %function RemoveRandomNodes3
 
 %sigal - move old implementation to function
+
+function [missing_nodes] = ChooseMissingNodes(num_nodes_to_remove, data, attData, totalAttNum, numAttPerPH, missing_nodes_mapping, numImagesProfiles)
+    missing_nodes_all_neighbors = zeros(1, size(data,2));
+    
+    %randomize a list of nodes to remove and sort it
+    if size(missing_nodes_mapping,1)> 0
+        %Sigal 23.1.14 - second row is the profile mapping
+        missing_nodes = missing_nodes_mapping(1:2,:); %%sort(missing_nodes_mapping(1,:) , 2, 'descend');
+        %find all missing node neighbors
+        for curr_missing_node = missing_nodes(1,:) % first row is the removed nodes
+            missing_nodes_all_neighbors = missing_nodes_all_neighbors | data(curr_missing_node,:);
+            missing_nodes_all_neighbors(1,curr_missing_node)=1;
+        end
+    else
+        missing_nodes = [];
+    end
+
+    % outlier1 - nodes with only one edge
+    numEdges = sum(data,1);
+    invalidNodes1a = (numEdges==1); %%numEdges<3); %%(numEdges==1);
+    missing_nodes_all_neighbors(1,invalidNodes1a) = 1;
+    %invalidNodes1b = (numEdges>7); %% 6.13 (mem issues) use 7
+    %invalidNodes1b = (numEdges>15); %%25); %%(numEdges==1); %% sigal - 6.2.13 max=15 (sarit)
+    %invalidNodes1b = (numEdges>8); %%15); %% sigal/sarit - 9.12.13 max=8
+    %missing_nodes_all_neighbors(1,invalidNodes1b) = 1;
+    % outlier2 - nodes with less than numAttPerPH attributes
+    % sigal 31.1.14 - support remove without attributes
+    if totalAttNum > 0 && numAttPerPH > 0
+        numAttr = sum(attData,2)';
+        invalidNodes2 = (numAttr<numAttPerPH);
+        missing_nodes_all_neighbors(1,invalidNodes2) = 1;
+    else
+        invalidNodes2 = zeros(1,size(invalidNodes1a,2));
+    end
+    % outlier statistics
+    count = nnz(invalidNodes1a|invalidNodes2);
+    if count*1.5 > size(data,2)
+        fprintf('RemoveRandomNodes2: too many outliers nodes %d.\n',count);
+    end
+    
+    %sigal - 23.1.14 - choose image profile
+    imagesProfiles = 1:1:numImagesProfiles;
+    if size(missing_nodes,1)> 0
+        usedProfiles = missing_nodes(2,:);  
+        imagesProfiles(usedProfiles)=[];
+    end
+    
+   for i=1:num_nodes_to_remove
+        valid_nodes = find(missing_nodes_all_neighbors~=1);
+        if(size(valid_nodes,2) < 1)
+            fprintf('Full Graph')
+        end
+        
+        inx = ceil(rand(1)*size(valid_nodes,2));
+
+        node = valid_nodes(inx);
+        %sigal - 23.1.14 - choose image profile
+        profile = ceil(rand(1)*size(imagesProfiles,2));
+        newNode = [node;imagesProfiles(profile)];
+        imagesProfiles(profile) = [];
+        % add selected node to missing_nodes list and update the all neighbors list
+        missing_nodes = [missing_nodes newNode];
+        missing_nodes_all_neighbors(1,node)=1;
+        missing_nodes_all_neighbors = missing_nodes_all_neighbors | data(node,:);
+   end
+    
+end %ChooseMissingNodes
+
+
+% sigal - append col & row for the placeholder
+function [data] = ExpandDataByOne(data, friend, non_neighbors_distance)
+    new_col = ones(size(data, 1), 1) * non_neighbors_distance;
+    new_col(friend) = 1;
+    data = [data new_col];
+    new_row =  ones(1,size(data, 2)) * non_neighbors_distance;
+    new_row(friend) = 1;
+    data = [data; new_row];
+    data(size(data, 1), size(data,2)) = 0;
+end %ExpandDataByOne
+
+% sigal - append row for the placeholder
+function [attData] = ExpandAttByOne(attData, orgNode, non_neighbors_distance, totalAttNum, numAttPerPH)
+    if totalAttNum>0 && numAttPerPH>0
+        attIndices = find(attData(orgNode, :)==1);
+        while size(attIndices,2) > numAttPerPH
+            inx = ceil(rand(1)*size(attIndices,2));
+            attIndices(:,inx) = [];
+        end
+    else
+        attIndices=[];
+    end
+    new_row =  ones(1,size(attData, 2)) * non_neighbors_distance;
+    for i=1:size(attIndices,2)
+        new_row(i)=1;
+    end
+    attData = [attData; new_row];
+end %ExpandAttByOne
+
+
+
+function [ data, attData, missing_nodes_mapping ] = RemoveRandomNodesWithImages( data, attData, totalAttNum, num_missing_nodes, missing_nodes_mapping, numImagesProfiles, non_neighbors_distance, missingNodesInput )
+    %RemoveRandomNodes Remove num_missing_nodes from data. If some nodes are
+    %removed already, provide missing_nodes_mapping
+    %   Detailed explanation goes here
+
+    if nargin < 7
+        non_neighbors_distance = 0;
+    end
+    if nargin >= 8 % i.e. getting  missingNodesInput
+        missing_nodes = missingNodesInput;
+    else
+        %%data_orig = data;
+        numAttPerPH = 0;
+
+        % if the mapping is larger than the number of nodes we want to remove, empty
+        % it and start a new mapping. This can happen if we finished looping over
+        % the number of missing nodes and started a new iteration of an outer loop.
+        if size(missing_nodes_mapping,2) > num_missing_nodes
+            missing_nodes_mapping = [];
+            num_nodes_to_remove = num_missing_nodes;
+        else
+            num_nodes_to_remove = num_missing_nodes - size(missing_nodes_mapping,2);
+        end
+
+        % randomly choose missing nodes
+        %missing_nodes = ChooseMissingNodes_old(num_nodes_to_remove, data, missing_nodes_mapping, non_neighbors_distance);
+        missing_nodes = ChooseMissingNodes(num_nodes_to_remove, data, attData, totalAttNum, numAttPerPH, missing_nodes_mapping, numImagesProfiles);
+
+        %sort the list and create a list of the new nodes that each missing node is mapped to - each link 
+        %to a missing node is replaced by a link to a new, "UNK" node
+        
+        %Sigal 23.1.14 - missing_nodes is now matrix with two rows: 
+        % first the removed node and second the selected profile)
+        % no need to call unique as validation is already done in ChooseMissingNodes
+        %missing_nodes = sort( unique(missing_nodes), 'descend');
+        %missing_nodes = sort( missing_nodes , 2, 'descend');
+        missing_nodes_mapping = missing_nodes;
+        missing_nodes_list =  sort(missing_nodes(1,:),'descend');
+
+        %replace each link to a missing node with a link to a new node
+        %find all missing node neighbors
+        missing_nodes_all_neighbors = zeros(1, size(data,2));
+        for curr_nissing_node = missing_nodes_list
+            missing_nodes_all_neighbors = missing_nodes_all_neighbors | data(curr_nissing_node,:);
+        end
+        missing_nodes_all_neighbors = find(missing_nodes_all_neighbors);
+        %for each node in missing_nodes_all_neighbors add edges to placeholder
+        for i = missing_nodes_all_neighbors
+            neighbors = find(data(i,:));
+            missing_neighbors = intersect(neighbors, missing_nodes_list);
+            
+            missing_neighbors = sort(missing_neighbors, 'descend');
+            for curr_missing_neighbor = missing_neighbors
+                if data(i,curr_missing_neighbor) == 1
+                    % append col & row for the placeholder
+                    data = ExpandDataByOne(data, i, non_neighbors_distance);
+                    % sigal 31.1.14 - support remove without attributes
+                    if totalAttNum > 0
+                        attData = ExpandAttByOne(attData, curr_missing_neighbor, non_neighbors_distance, totalAttNum, numAttPerPH);
+                    end
+                    %add the new UNK node to the missing nodes mapping j is the index of the missing node
+                    %look for the first zero in column j of the missing nodes mapping and put the new node
+                    %index there
+                    added_node = 0;
+                    %add it in the first position which equals zero
+                    %sigal 23.1.14 - find index according to actual structure (not sorted)
+                    j = find( missing_nodes_mapping(1,:) == curr_missing_neighbor, 1);
+                    for k = 1 : size(missing_nodes_mapping,1)
+                        if missing_nodes_mapping(k, j) == 0
+                            %if we start with 1000 nodes, and we have 5 missing nodes, after
+                            %adding one node at this point, the size of the graph is 1001. 5 nodes
+                            %will be removed so the correct index of the new node will be 1001 - 5 = 996.
+                            %The next one is 997 and so on.
+                            missing_nodes_mapping(k, j) = size(data,1) - num_missing_nodes;
+                            added_node = 1;
+                            break;
+                        end
+                    end
+                    %if all the column is non-zero, add a new row and put it there
+                    if added_node == 0
+                        missing_nodes_mapping = [missing_nodes_mapping; zeros(1, size(missing_nodes_mapping,2))];
+                        missing_nodes_mapping(size(missing_nodes_mapping,1), j) = size(data,1) - num_missing_nodes;
+                    end
+                end %if friend
+            end %missing_neighbors
+        end %missing_nodes_all_neighbors
+    end % if getting  missingNodesInput
+    
+
+    %remove the missing nodes from the matrix (missing nodes MUST be sorted in descending order!!
+    %so that removing one does not affect the index of the others)
+    for j = 1:size(missing_nodes_list,2)
+        missing_node_idx = missing_nodes_list(j);
+        %remove column
+        data(:, missing_node_idx) = [];
+        %remove row
+        data(missing_node_idx, :) = [];
+        % sigal 31.1.14 - support remove without attributes
+        if totalAttNum > 0
+            attData(missing_node_idx, :) = [];
+        end
+    end
+
+end %function RemoveRandomNodes3
+
+%sigal - move old implementation to function
+
 function [missing_nodes] = ChooseMissingNodes(num_nodes_to_remove, data, attData, totalAttNum, numAttPerPH, missing_nodes_mapping, numImagesProfiles)
     missing_nodes_all_neighbors = zeros(1, size(data,2));
     
     missing_nodes_all_neighbors(1,invalidNodes1a) = 1;
     %invalidNodes1b = (numEdges>7); %% 6.13 (mem issues) use 7
     %invalidNodes1b = (numEdges>15); %%25); %%(numEdges==1); %% sigal - 6.2.13 max=15 (sarit)
-    invalidNodes1b = (numEdges>8); %%15); %% sigal/sarit - 9.12.13 max=8
-    missing_nodes_all_neighbors(1,invalidNodes1b) = 1;
+    %invalidNodes1b = (numEdges>8); %%15); %% sigal/sarit - 9.12.13 max=8
+    %missing_nodes_all_neighbors(1,invalidNodes1b) = 1;
     % outlier2 - nodes with less than numAttPerPH attributes
     % sigal 31.1.14 - support remove without attributes
     if totalAttNum > 0 && numAttPerPH > 0
         invalidNodes2 = zeros(1,size(invalidNodes1a,2));
     end
     % outlier statistics
-    count = nnz(invalidNodes1a|invalidNodes1b|invalidNodes2);
+    count = nnz(invalidNodes1a|invalidNodes2);
     if count*1.5 > size(data,2)
         fprintf('RemoveRandomNodes2: too many outliers nodes %d.\n',count);
     end
     
    for i=1:num_nodes_to_remove
         valid_nodes = find(missing_nodes_all_neighbors~=1);
-		inx = ceil(rand(1)*size(valid_nodes,2));
+        if(size(valid_nodes,2) < 1)
+            fprintf('Full Graph')
+        end
+        
+        inx = ceil(rand(1)*size(valid_nodes,2));
+
         node = valid_nodes(inx);
         %sigal - 23.1.14 - choose image profile
         profile = ceil(rand(1)*size(imagesProfiles,2));
 end %ExpandAttByOne
 
 
+

MissingNodes_SrcCode2014/RunExpSrv8s.m

-function [] = RunExpSrv8s(iterStartStr, iterEndStr, netSizeStr, addAttPercStr)
-%function [] = RunExpSrv8s(iterStartStr, iterEndStr, netSizeStr, normF1, normF2, normF3, addAttPercStr)
+function [] = RunExpSrv8s(iterStartStr, iterEndStr, netSizeStr, normF1, normF2, normF3, addAttPercStr)
+function [] = RunExpSrv8s(iterStartStr, iterEndStr, addAttPercStr)
 
 %affinity calculation types
 % affinity_calculation_shortest_path = 0;
 % ds_100k = [20000 25000 50000 75000 100000];
 % ds_100km = [100001];
 % ds_Train = [2001 2049];
-ds_GridTrain = [12];
+ds_GridTrain = [45];
 
 % input netSize
-netSize = str2num(netSizeStr);
 % if find(ds_10k==netSize)
 %     ds_str = 'Datasets_10K/';
 %     num_missing_nodes_arr = [10 20 30 50 70 100];%[10 100 150];
 %     fprintf('RunExpSrv8s:Invalid netSize %d.\n',netSize);
 %     return;
 % end
-ds_str = 'graph_production/produced_graphs/';
-num_missing_nodes_arr = [1 2 3];
+ds_str = 'in/';
+num_missing_nodes_arr = [2];
 
-fprintf('RunExpSrv8s: netSize %d, dataset %s\n',netSize,ds_str);
 
 rootDir = '../';
 %rootDir = '/Users/armin/Desktop/DML/projects/graphgenproj/'; %Facebook/';
 %rootDir = 'D:/__SN_Jan14_FF75/'; %Facebook/';
 filePrefix = 'testgraph_*'; % 'facebook_sparse_'; %
-netSizes = netSize; %%[2048 4096 5000 8192 10000 16384 32768];
 
 %Sigal - 13.2.14 - images data
 imagesDir = strcat(rootDir,'Images/'); 
 datasetDir = strcat(rootDir,ds_str); %'Datasets_10K/'); %'Facebook/Datasets_10K/'); %'Traing_16K/');    %% TODO sigal - change rootDir path before EXE build
 factor_str = sprintf('F%d%d%d_',normFactorVec);
 images_str = sprintf('I%dP%dM%d_',imgSimType,imgSimProbDiff*10,imgMissProb*10);
-results_dir = strcat(datasetDir,'testImg_noTh_',netSizeStr,'/',factor_str,images_str,'Iter_',iterStartStr,iterEndStr,'/');
+results_dir = strcat(datasetDir,'testImg_noTh_','/',factor_str,images_str,'Iter_',iterStartStr,iterEndStr,'/');
 fprintf('RunExpSrv8b: results_dir %s\n',results_dir);
 
 runAlgFlag = 1;
 % end
 % LogMsg(sprintf('Select %d attributes out of %d ...', sum(attSelected), size(attSelected,2)));
 
-for nodes = netSizes
-    fprintf('----------!!!!%d---------', nodes);
-    if size(strfind(filePrefix, 'facebook'),1)>0
-        prefix = sprintf('%s%s%d_%s',datasetDir,filePrefix,nodes,'*.mat'); % '0*.txt.mat');
-    else
-        prefix = sprintf('%s%s%d_%s',datasetDir,filePrefix,nodes,'*.txt.mat'); % '0*.txt.mat');
-    end
+    prefix = sprintf('%s%s_%s',datasetDir,filePrefix,'*.txt.mat'); % '0*.txt.mat');
     files = dir(prefix);
     firstIter = 1;
 
         end
 
         for i = 1:size(files,1)     % loop over the list of networks
+            try
+                file = files(i).name;
+    
 
-            file = files(i).name;
-
-            if size(strfind(filePrefix, 'facebook'),1)>0
-                LogMsg(sprintf('facebook netwrok, skipping attributes ...'));
-                attributes = [];
-                attUpperRange = [];
-            else 
                 % sigal 12/6/13 - use binary attribute mat file 
                 attFile = strrep(file, '.txt.mat', '.usr.mat');
-                [attributes, attUpperRange, attSelected, attStat] = PrepareAttributes5(datasetDir, attFile, nodes, numAttrCols, maxAttStat, attSelected);
+                [attributes, attUpperRange, attSelected, ~] = PrepareAttributes5(datasetDir, attFile, numAttrCols, maxAttStat, attSelected);
                 LogMsg(sprintf('Select %d attributes out of %d ...', sum(attSelected), size(attSelected,2)));
-            end
             
-           if runAlgFlag == 1
-                date_now = clock;
-                date_now = strcat(num2str(date_now(1)),'_',num2str(date_now(2)),'_', num2str(date_now(3)),'_', num2str(date_now(4)), num2str(date_now(5)),'_', num2str(date_now(6)));
-
-                % make sure dump & results directories exist
-                if (firstIter == 1 && i == 1)
-                    firstIter = 0;
-                    if isdir(results_dir) == 0
-                        mkdir(results_dir);
+               if runAlgFlag == 1
+                    date_now = clock;
+                    date_now = strcat(num2str(date_now(1)),'_',num2str(date_now(2)),'_', num2str(date_now(3)),'_', num2str(date_now(4)), num2str(date_now(5)),'_', num2str(date_now(6)));
+    
+                    % make sure dump & results directories exist
+                    if (firstIter == 1 && i == 1)
+                        firstIter = 0;
+                        if isdir(results_dir) == 0
+                            mkdir(results_dir);
+                        end
+                        dumpFilePath = sprintf('%sdumpKronEM_%s/', results_dir, date_now);
+                        if (dumpKronEM == 1)
+                            mkdir(dumpFilePath);
+                        end
+                        dump_data_dir = sprintf('%sdumpData_%s/', results_dir, date_now);
+                        if dumpGED == 1 && isdir(dump_data_dir) == 0
+                            mkdir(dump_data_dir)
+                        end
                     end
-                    dumpFilePath = sprintf('%sdumpKronEM_%s/', results_dir, date_now);
-                    if (dumpKronEM == 1)
-                        mkdir(dumpFilePath);
+    
+                     % run algorithm (file load is done internaly)
+                    [rand_score,purity,p_triads,missing_nodes_mapping,removed_nodes] = MissingNodes_S8b(datasetDir, file, ...
+                        attributes, attUpperRange, attWeight, addMissingAtt, normFactorVec, affinities, num_missing_nodes_arr, attAffinityThreshold, ...
+                        imagesData, numImagesProfiles, imgMissProb, imgSimType, imgSimProbDiff, percentKnownPHsVec, dumpGED, dump_data_dir, iter); 
+                    %[rand_score,purity,p_triads,missing_nodes_mapping,removed_nodes] = MissingNodes_Sparse(datasetDir, file, affinities, 1); 
+    
+                   % dump graph data for KronEM runs
+                    if dumpKronEM == 1
+                        DumpDataset(datasetDir, file, iter, removed_nodes, dumpFilePath);
                     end
-                    dump_data_dir = sprintf('%sdumpData_%s/', results_dir, date_now);
-                    if dumpGED == 1 && isdir(dump_data_dir) == 0
-                        mkdir(dump_data_dir)
+    
+                    % save results
+                    out_file = sprintf('%sres_%s_%s.mat', results_dir, file, date_now);
+                    save(out_file);
+                    file_name = sprintf('%s_%s','../output/mine/',file);
+                    if(iter == 0)
+                        copyfile('../output/graphed_0.mat',file_name);
                     end
-                end
-
-                 % run algorithm (file load is done internaly)
-                [rand_score,purity,p_triads,missing_nodes_mapping,removed_nodes] = MissingNodes_S8b(datasetDir, file, ...
-                    attributes, attUpperRange, attWeight, addMissingAtt, normFactorVec, affinities, num_missing_nodes_arr, attAffinityThreshold, ...
-                    imagesData, numImagesProfiles, imgMissProb, imgSimType, imgSimProbDiff, percentKnownPHsVec, dumpGED, dump_data_dir, iter); 
-                %[rand_score,purity,p_triads,missing_nodes_mapping,removed_nodes] = MissingNodes_Sparse(datasetDir, file, affinities, 1); 
-
-               % dump graph data for KronEM runs
-                if dumpKronEM == 1
-                    DumpDataset(datasetDir, file, iter, removed_nodes, dumpFilePath);
-                end
-
-                % save results
-                out_file = sprintf('%sres_%s_%s.mat', results_dir, file, date_now);
-                save(out_file);
-
-                LogMsg(sprintf('Results for file %s,iter %d at %s',file,iter,out_file));
-                %fprintf('Completed RunExperiment cycle - results at %s.\n',out_file);
+                    
+                    LogMsg(sprintf('Results for file %s,iter %d at %s',file,iter,out_file));
+                    %fprintf('Completed RunExperiment cycle - results at %s.\n',out_file);
+               end
+            catch
+                fprintf('An Error Occured!!!!!')
             end
 
           %  beep;
         end
-    end
 end
 
 date_now = clock;
 date_now = strcat(num2str(date_now(1)),'_',num2str(date_now(2)),'_', num2str(date_now(3)),'_', num2str(date_now(4)), num2str(date_now(5)),'_', num2str(date_now(6)));
 LogMsg(sprintf('%s Completed RunExpSrv8s RunExperiment (random %d).',date_now,randSeed));
 
-end
+end

MissingNodes_SrcCode2014/RunGraphEditDist.m

 %       calc GED vice the orignal graph
 % end
 %graphDist = [];
-rootDir = '/Users/armin/Desktop/DML/projects/graphgenproj/graph_production/' ;
+rootDir = 'C:\Users\Iraj\Desktop\DML\' ;
 datasetDir = strcat(rootDir,'produced_graphs/'); %' '; % sigal 28.8.12 
 resultsDir = strcat(rootDir,'results_ged/');
 file1Iter = []; % networks options [1:1:10] - selection iter