clear; clc; %affinity calculation types % affinity_calculation_shortest_path = 0; % affinity_calculation_euclid = 1; % affinity_calculation_common_friends = 2; % affinity_calculation_random_clustering = 3; % affinity_calculation_adamic_adar = 4; % affinity_calculation_katz_beta_0_5 = 5; % affinity_calculation_katz_beta_0_05 = 6; % affinity_calculation_katz_beta_0_005 = 7; affinities = 3; %%[2,3,4,6]; %3,4]; %,6]; num_missing_nodes_arr = 11; %%[11 21 31 41 50]; %%5:5:30; %10:10:50; %%[11 21 31 41 50]; %10:10:50; percentKnownPHsVec = 1; datasetDir = 'D:/SocialNets/Steam/Exp_March13/Train/' ; results_dir = strcat(datasetDir,'Stat/'); filePrefix = 'Steam_*'; netSizes = 10000; %10000; %2048; runAlgFlag = 1; debugFlag = 0; dumpFlag = 0; numThreshold = 0; %%maxAttStat = 0.25; % use this attribute only if it appears less than this percentage numAttrCols = 60; %%21; %40; %50 %attSelected = ones(1,numAttrCols); %attSelected(1) = 0; %skip country attWeight = 0.3; addMissingAtt = 0; 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 Strating CheckProperties ...',date_now)); outFile = sprintf('%sPropertiesStat_%s.txt', results_dir, date_now); fileID = 0; for nodes = netSizes prefix = sprintf('%s%s%d_%s',datasetDir,filePrefix,nodes,'*.mat'); files = dir(prefix); firstIter = 1; for iter = 1 %1:2 %100 % loop over same network with different missing nodes for i = 1:size(files,1) % loop over the list of networks file = files(i).name; fprintf('reading network information from file %s%s ...\n', datasetDir, file); load(strcat(datasetDir, file), 'data'); data = sparse(data); for maxAttStat = 1 %%[0.25 0.3 0.4 0.5 0.75 1] attSelected = ones(1,numAttrCols); %skip all games % for g=2:1:11 % attSelected(g) = 0; % end %skip all groups % for g=12:1:50 % attSelected(g) = 0; % end attSelectedNum = nnz(attSelected); attFile = strrep(file, '.txt.mat', '.usr.txt'); [attributes, attUpperRange, attSelected, attStat] = PrepareAttributes2(datasetDir, attFile, nodes, numAttrCols, maxAttStat, attSelected); 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 fileID = fopen(outFile,'w'); fprintf(fileID,'\tfile\ti\titer\tnodes\tedges\tnonedges\tmaxAttStat\tattSelectedNum\tnumAtt\tAttId\tp\tp^2\t(1-p)^2\t2p(1-p)'); fprintf(fileID,'\tedgesAttOne\tpercAttOne\tedgesAttZero\tpercAttZero\tedgesAttTwo\tpercAttTwo'); %fprintf(fileID,'\tnonedgesAttOne\tpercAttOne\tnonedgesAttZero\tpercAttZero\tnonedgesAttTwo\tpercAttTwo'); fprintf(fileID,'\n'); end numAtt = nnz(attSelected); %%size(attributes,2); edges = nnz(data); nonedges = nodes*nodes-nodes-edges; for attId = 1:numAttrCols % Calc Attributes Affinity - similarity score fprintf('calculating attribtes similarity matrix for attId=%d ...\n',attId); [attSimilarity] = CalcOneAttributeSimilarity(data, attributes, attId, 1); % save iteration data fprintf(fileID,'\t%s',file); fprintf(fileID,'\t%d',i); fprintf(fileID,'\t%d',iter); fprintf(fileID,'\t%d',nodes); fprintf(fileID,'\t%d',edges); fprintf(fileID,'\t%d',nonedges); fprintf(fileID,'\t%d',maxAttStat); fprintf(fileID,'\t%d',attSelectedNum); fprintf(fileID,'\t%d',numAtt); fprintf(fileID,'\t%d',attId); p=attStat(attId); fprintf(fileID,'\t%d',p); fprintf(fileID,'\t%d',p*p); fprintf(fileID,'\t%d',(1-p)*(1-p)); fprintf(fileID,'\t%d',2*p*(1-p)); %Note - Sigal, replace 0 and 2 so we can have sparse matrix % edges properties edgesInd = find(data); edgesAttOne = size(find(attSimilarity(edgesInd)==1),1); edgesAttTwo = size(find(attSimilarity(edgesInd)==0),1); edgesAttZero = size(find(attSimilarity(edgesInd)==2),1); fprintf(fileID,'\t%d\t%d',edgesAttOne,edgesAttOne/edges); fprintf(fileID,'\t%d\t%d',edgesAttZero,edgesAttZero/edges); fprintf(fileID,'\t%d\t%d',edgesAttTwo,edgesAttTwo/edges); % nonedges properties % nonedges = nodes*nodes-nodes-edges; % nonedgesInd = find(data==0); % nonedgesAttOne = size(find(attSimilarity(nonedgesInd)==1),1)-nodes; % nonedgesAttTwo = size(find(attSimilarity(nonedgesInd)==0),1); % nonedgesAttZero = size(find(attSimilarity(nonedgesInd)==2),1); % % fprintf(fileID,'\t%d\t%d',nonedgesAttOne,nonedgesAttOne/nonedges); % fprintf(fileID,'\t%d\t%d',nonedgesAttZero,nonedgesAttZero/nonedges); % fprintf(fileID,'\t%d\t%d',nonedgesAttTwo,nonedgesAttTwo/nonedges); fprintf(fileID,'\n'); %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 end end % beep; end end end if fileID ~= 0 fclose(fileID); end LogMsg(sprintf('%s Completed RunExperiment.',date_now));