sid = random.randint(0,1080) dg = -2 gene = folder.getSequenceForStructure(sid, dg) (new_sid, new_dg) = folder.fold(translate.Translate(gene)) assert(sid == new_sid and new_dg <= dg) if False: print "\n****\nTesting misfold module with compact lattice folder" side_length = 5 struct_id = 599 target_fraction_accurate = 0.85 ca_cost = 5 max_free_energy = -5 prot_length = side_length*side_length misfold.init(folder, prot_length, struct_id, max_free_energy, ca_cost, target_fraction_accurate, 111) err_rate = misfold.getErrorRate() gene = "ATTATTGTCTCGAAGGGTGCTATCTCCGCCGTCAGTTCCTTCGCAAAGTACATCTTCTTGCTTCTAACTAAAGAC" (facc, frob, ftrunc, ffold) = misfold.calcOutcomes(gene); print "%s\t%1.4f\t%1.4f\t%1.4f\t%1.4f" % ("calcOutcomes ", facc, frob, ftrunc, ffold) (facc, frob, ftrunc, ffold) = misfold.countOutcomes(gene, 10000); print "%s\t%d\t%d\t%d\t%d" % ("countOutcomes ", facc, frob, ftrunc, ffold) (facc, frob, ftrunc, ffold) = misfold.countOutcomeFractions(gene, 10000); print "%s\t%1.4f\t%1.4f\t%1.4f\t%1.4f" % ("countOutcomeFractions", facc, frob, ftrunc, ffold) if False: print "\n****\nTesting decoyfolder module" sid = 1 prot_length = 300 log_nconf = 10*math.log(10) map_file = os.path.abspath("test/data/williams_contact_maps/maps.txt")
map_dir = os.path.abspath("test/data/rand_contact_maps/")+"/" decoyfolder.init(prot_length, log_nconf, map_file, map_dir) print "sid dg" p = "PRPEEEKKKREREEKRRKEDKLERIRDLPRKILKMIVEPKRRKKGETEDDDEKESKRREEMEKFKREFFTICIKLLECEEEMARRREKRREEEDIDSLRELMKDCRRFIDDPRRVEQQSQRLDFRSRRKLEDEKDDEDKRKPDFLFEFEMCEEDMRRRPLDRVKDICRVCCEMDEEEEIREEEEFFRPEEEDMKLKSFRESFKDVRRCILRKFEKSRREKSAEFLRHEIPMFSSEDEEDRKKKDRRRQRPMMRHFMKRIKEKEEERKKREFKEQEEPKPKSFKWKTEEEMEELGEQEKRV" (sid, dg) = decoyfolder.fold(p) print sid, dg if True: side_length = 5 struct_id = 599 target_fraction_accurate = 0.1 ca_cost = 4 max_free_energy = -5 misfold.init(side_length, struct_id, max_free_energy, ca_cost, target_fraction_accurate) #print misfold.getErrorRate() gene = "CCCCTGTACCGTACGACGAAATCTAACACTGGATCATGGCCTTCTGATTGGAAACCCCTACCTTATGAGTCAAAG" #(facc, frob, ftrunc, ffold) = misfold.calcOutcomes(gene); #print "%s\t%1.4f\t%1.4f\t%1.4f\t%1.4f" % ("mis", facc, frob, ftrunc, ffold) if True: f = file(os.path.expanduser('~/research/trsim/data/trs599ca4nmut-genes.txt'),'r') for line in f.readlines()[2:]: flds = line.strip().split('\t') gene = flds[-1] # print gene #(facc, frob, ftrunc, ffold) = misfold.calcOutcomes(gene); #print "%s\t%1.4f\t%1.4f\t%1.4f\t%1.4f" % (flds[0], facc, frob, ftrunc, ffold) (facc, frob, ftrunc, ffold) = misfold.countOutcomes(gene, 1000); print "%s\t%d\t%d\t%d\t%d" % (flds[0], facc, frob, ftrunc, ffold) #print line,
sid = random.randint(0, 1080) dg = -2 gene = folder.getSequenceForStructure(sid, dg) (new_sid, new_dg) = folder.fold(translate.Translate(gene)) assert (sid == new_sid and new_dg <= dg) if False: print "\n****\nTesting misfold module with compact lattice folder" side_length = 5 struct_id = 599 target_fraction_accurate = 0.85 ca_cost = 5 max_free_energy = -5 prot_length = side_length * side_length misfold.init(folder, prot_length, struct_id, max_free_energy, ca_cost, target_fraction_accurate, 111) err_rate = misfold.getErrorRate() gene = "ATTATTGTCTCGAAGGGTGCTATCTCCGCCGTCAGTTCCTTCGCAAAGTACATCTTCTTGCTTCTAACTAAAGAC" (facc, frob, ftrunc, ffold) = misfold.calcOutcomes(gene) print "%s\t%1.4f\t%1.4f\t%1.4f\t%1.4f" % ("calcOutcomes ", facc, frob, ftrunc, ffold) (facc, frob, ftrunc, ffold) = misfold.countOutcomes(gene, 10000) print "%s\t%d\t%d\t%d\t%d" % ("countOutcomes ", facc, frob, ftrunc, ffold) (facc, frob, ftrunc, ffold) = misfold.countOutcomeFractions(gene, 10000) print "%s\t%1.4f\t%1.4f\t%1.4f\t%1.4f" % ("countOutcomeFractions", facc, frob, ftrunc, ffold) if False: print "\n****\nTesting decoyfolder module" sid = 1
map_dir = os.path.abspath("test/data/rand_contact_maps/") + "/" decoyfolder.init(prot_length, log_nconf, map_file, map_dir) print "sid dg" p = "PRPEEEKKKREREEKRRKEDKLERIRDLPRKILKMIVEPKRRKKGETEDDDEKESKRREEMEKFKREFFTICIKLLECEEEMARRREKRREEEDIDSLRELMKDCRRFIDDPRRVEQQSQRLDFRSRRKLEDEKDDEDKRKPDFLFEFEMCEEDMRRRPLDRVKDICRVCCEMDEEEEIREEEEFFRPEEEDMKLKSFRESFKDVRRCILRKFEKSRREKSAEFLRHEIPMFSSEDEEDRKKKDRRRQRPMMRHFMKRIKEKEEERKKREFKEQEEPKPKSFKWKTEEEMEELGEQEKRV" (sid, dg) = decoyfolder.fold(p) print sid, dg if True: side_length = 5 struct_id = 599 target_fraction_accurate = 0.1 ca_cost = 4 max_free_energy = -5 misfold.init(side_length, struct_id, max_free_energy, ca_cost, target_fraction_accurate) #print misfold.getErrorRate() gene = "CCCCTGTACCGTACGACGAAATCTAACACTGGATCATGGCCTTCTGATTGGAAACCCCTACCTTATGAGTCAAAG" #(facc, frob, ftrunc, ffold) = misfold.calcOutcomes(gene); #print "%s\t%1.4f\t%1.4f\t%1.4f\t%1.4f" % ("mis", facc, frob, ftrunc, ffold) if True: f = file( os.path.expanduser( '~/research/trsim/data/trs599ca4nmut-genes.txt'), 'r') for line in f.readlines()[2:]: flds = line.strip().split('\t') gene = flds[-1] # print gene #(facc, frob, ftrunc, ffold) = misfold.calcOutcomes(gene); #print "%s\t%1.4f\t%1.4f\t%1.4f\t%1.4f" % (flds[0], facc, frob, ftrunc, ffold) (facc, frob, ftrunc, ffold) = misfold.countOutcomes(gene, 1000)