if args.pseudocounts: sys.stderr.write("This run is using pseudocounts.\n\n\n") sys.stderr.write("Starting the training and testing separation...\n\n") m.training_testing_sets_separation(args.infile,3,training_filename,testing_filename) ######## 2 +/- ########### ######## 3 kmer dict ##### if (args.pseudocounts): sys.stderr.write("Starting the training background and foreground separation...\n\n") back_dict=m.build_hash_pseudocount([x for x in m.background_separation(training_filename)],k) sys.stderr.write("The MM for the bg is generated...\n\n") sign_dict=m.build_hash_pseudocount([x for x in m.signal_separation(training_filename)],k) sys.stderr.write("The MM for the bg is generated...\n\n") else: back_dict=m.build_hash([x for x in m.background_separation(training_filename)],k) sign_dict=m.build_hash([x for x in m.signal_separation(training_filename)],k) ######### 4 print ######## output_filename=args.outfile+"_k_"+str(k)+"_l_"+str(l)+'.MM' sys.stderr.write("Printing the model in {}...\n\n".format(output_filename)) m.print_hash(sign_dict,back_dict,output_filename) ######## 5 windows ####### sys.stderr.write("Starting the testing background and foreground separation...\n\n") output_filename= args.outfile+"_k_"+str(k)+"_l_"+str(l)+'.data'
if args.pseudocounts: sys.stderr.write("This run is using pseudocounts.\n\n\n") sys.stderr.write("Starting the training and testing separation...\n\n") m.training_testing_sets_separation(args.infile,3,training_filename,testing_filename) ######## 2 +/- ########### ######## 3 kmer dict ##### if (args.pseudocounts): sys.stderr.write("Starting the training background and foreground separation...\n\n") back_dict=m.build_hash_pseudocount([x for x in m.background_separation(training_filename)],args.order) sys.stderr.write("The MM for the bg is generated...\n\n") sign_dict=m.build_hash_pseudocount([x for x in m.signal_separation(training_filename)],args.order) sys.stderr.write("The MM for the bg is generated...\n\n") else: back_dict=m.build_hash([x for x in m.background_separation(training_filename)],args.order) sign_dict=m.build_hash([x for x in m.signal_separation(training_filename)],args.order) ######### 4 print ######## output_filename=args.outfile+'.MM' sys.stderr.write("Printing the model in {}...\n\n".format(output_filename)) m.print_hash(sign_dict,back_dict,output_filename) ######## 5 windows ####### sys.stderr.write("Starting the testing background and foreground separation...\n\n") sys.stderr.write("Starting the computation of the Scores...\n\n") output_filename_fg=args.outfile+'_fg.th'
if args.pseudocounts: sys.stderr.write("This run is using pseudocounts.\n\n\n") sys.stderr.write("Starting the training and testing separation...\n\n") m.training_testing_sets_separation(args.infile,3,training_filename,testing_filename) ######## 2 +/- ########### ######## 3 kmer dict ##### if (args.pseudocounts): sys.stderr.write("Starting the training background and foreground separation...\n\n") back_dict=m.build_hash_pseudocount([x for x in m.background_separation(training_filename)],k) sys.stderr.write("The MM for the bg is generated...\n\n") sign_dict=m.build_hash_pseudocount([x for x in m.signal_separation(training_filename)],k) sys.stderr.write("The MM for the bg is generated...\n\n") else: back_dict=m.build_hash([x for x in m.background_separation(training_filename)],k) sign_dict=m.build_hash([x for x in m.signal_separation(training_filename)],k) ######### 4 print ######## output_filename=args.outfile+"_k_"+str(k)+"_l_"+str(l)+'.MM' sys.stderr.write("Printing the model in {}...\n\n".format(output_filename)) m.print_hash(sign_dict,back_dict,output_filename) ######## 5 windows ####### sys.stderr.write("Starting the testing background and foreground separation...\n\n") sys.stderr.write("Starting the computation of the Scores...\n\n") output_filename_fg=args.outfile+"_k_"+str(k)+"_l_"+str(l)+'_fg.th'