clear; clc; dataDir = 'D:/SocialNets/Steam/Exp_Test/Weights/Iter15/'; files = dir(strcat(dataDir, 'res_Steam*.mat')); dateNow = clock; dateNow = strcat(num2str(dateNow(1)),'_',num2str(dateNow(2)),'_', num2str(dateNow(3)),'_', num2str(dateNow(4)), num2str(dateNow(5)),'_', num2str(dateNow(6))); outFile = sprintf('%sDumpResults_%s.txt',dataDir, dateNow); fileID = fopen(outFile,'w'); ged = 0; first = 1; numAlg = 0; for f = files' data = load(strcat(dataDir,f.name)); numResults = size(data.purity,2); numMissing = size(data.removed_nodes,2); line = numResults/numMissing; % print header if first == 1 fprintf(fileID,'\tfile\tinx\titer\tnodes\tedges\tattEdges\tattNodes\tmissInx\tmissNum\tnumPHs\tavgPHs'); for i=1:line r=data.purity(1,i); if r.withAttr == 0 fprintf(fileID,'\t%d_Best\t%d_Orig',r.affinity_calculation_type,r.affinity_calculation_type); numAlg = numAlg+1; else fprintf(fileID,'\t%d_Att%d',r.affinity_calculation_type,r.withAttr); end end fprintf(fileID,'\n'); first = 0; end numAlgVars = line/numAlg; %print data for i=1:numResults r = data.purity(1,i); if mod(i,line)==1 || numResults==1 fprintf(fileID,'\t%s',data.file); fprintf(fileID,'\t%d',data.i); fprintf(fileID,'\t%d',data.iter); fprintf(fileID,'\t%d',r.graph_size); fprintf(fileID,'\t%d',r.graph_edges); %12.12.12 fprintf(fileID,'\t%d',r.graph_attr_edges); % 12.12.12 fprintf(fileID,'\t%d', data.purity(1,i).num_attr_nodes); fprintf(fileID,'\t%d',r.num_missing_nodes_idx); fprintf(fileID,'\t%d',r.num_missing_nodes); fprintf(fileID,'\t%d',r.num_placeholders); fprintf(fileID,'\t%d',r.num_placeholders/r.num_missing_nodes); end if mod(i,numAlgVars)==1 fprintf(fileID,'\t'); % place for min calculation end if ged == 1 fprintf(fileID,'\t%d',r.edit_distance); else fprintf(fileID,'\t%d',r.score); end if mod(i,line)==0 fprintf(fileID,'\n'); end end end fclose(fileID); LogMsg(sprintf('Completed DumpResults at%s',outFile));