def main(): # pylint: disable=too-many-locals,too-many-branches
args = sanitize_help(get_parser()).parse_args()
graph_type = 'smallcountgraph' if args.small_count else 'countgraph'
configure_logging(args.quiet)
report_on_config(args, graph_type)
check_input_files(args.input_sequence_filename, args.force)
if args.savegraph is not None:
graphsize = calculate_graphsize(args, graph_type)
check_space_for_graph(args.savegraph, graphsize, args.force)
if (not args.squash_output
and os.path.exists(args.output_histogram_filename)):
log_error('ERROR: {output} exists; not squashing.',
output=args.output_histogram_filename)
sys.exit(1)
else:
hist_fp = open(args.output_histogram_filename, 'w')
hist_fp_csv = csv.writer(hist_fp)
# write headers:
hist_fp_csv.writerow(
['abundance', 'count', 'cumulative', 'cumulative_fraction'])
log_info('making countgraph')
# In case the user specified a maximum memory usage, use 8/(9+eps) of that
# for the countgraph and 1/(9+eps) for the tracking nodegraph
# `eps` is used to account for the memory used by the python interpreter
countgraph = khmer_args.create_countgraph(args, multiplier=8 / (9. + 0.3))
countgraph.set_use_bigcount(args.bigcount)
log_info('building k-mer tracking graph')
tracking = khmer_args.create_matching_nodegraph(countgraph)
log_info('kmer_size: {ksize}', ksize=countgraph.ksize())
log_info('k-mer countgraph sizes: {sizes}', sizes=countgraph.hashsizes())
log_info('outputting to {output}', output=args.output_histogram_filename)
# start loading
rparser = khmer.ReadParser(args.input_sequence_filename)
threads = []
log_info('consuming input, round 1 -- {input}',
input=args.input_sequence_filename)
for _ in range(args.threads):
thread = \
threading.Thread(
target=countgraph.consume_seqfile_with_reads_parser,
args=(rparser, )
)
threads.append(thread)
thread.start()
for thread in threads:
thread.join()
log_info('Total number of unique k-mers: {nk}',
nk=countgraph.n_unique_kmers())
abundance_lists = []
def __do_abundance_dist__(read_parser):
abundances = countgraph.abundance_distribution_with_reads_parser(
read_parser, tracking)
abundance_lists.append(abundances)
log_info('preparing hist from {seqfile}...',
seqfile=args.input_sequence_filename)
rparser = khmer.ReadParser(args.input_sequence_filename)
threads = []
log_info('consuming input, round 2 -- {filename}',
filename=args.input_sequence_filename)
for _ in range(args.threads):
thread = \
threading.Thread(
target=__do_abundance_dist__,
args=(rparser, )
)
threads.append(thread)
thread.start()
for thread in threads:
thread.join()
assert len(abundance_lists) == args.threads, len(abundance_lists)
abundance = {}
for abundance_list in abundance_lists:
for i, count in enumerate(abundance_list):
abundance[i] = abundance.get(i, 0) + count
total = sum(abundance.values())
if 0 == total:
log_error("ERROR: abundance distribution is uniformly zero; "
"nothing to report.")
log_error("\tPlease verify that the input files are valid.")
sys.exit(1)
sofar = 0
for _, i in sorted(abundance.items()):
if i == 0 and not args.output_zero:
continue
sofar += i
frac = sofar / float(total)
hist_fp_csv.writerow([_, i, sofar, round(frac, 3)])
if sofar == total:
break
if args.savegraph is not None:
log_info('Saving k-mer countgraph to {savegraph}',
savegraph=args.savegraph)
countgraph.save(args.savegraph)
log_info('wrote to: {output}', output=args.output_histogram_filename)
def test_create_matching_nodegraph(ntables, targetsize):
cg = khmer.Countgraph(31, targetsize, ntables)
ng = create_matching_nodegraph(cg)
assert cg.hashsizes() == ng.hashsizes()
def main(): # pylint: disable=too-many-locals,too-many-branches
args = sanitize_help(get_parser()).parse_args()
graph_type = 'smallcountgraph' if args.small_count else 'countgraph'
configure_logging(args.quiet)
report_on_config(args, graph_type)
check_input_files(args.input_sequence_filename, args.force)
if args.savegraph is not None:
graphsize = calculate_graphsize(args, graph_type)
check_space_for_graph(args.savegraph, graphsize, args.force)
if (not args.squash_output and
os.path.exists(args.output_histogram_filename)):
log_error('ERROR: {output} exists; not squashing.',
output=args.output_histogram_filename)
sys.exit(1)
else:
hist_fp = open(args.output_histogram_filename, 'w')
hist_fp_csv = csv.writer(hist_fp)
# write headers:
hist_fp_csv.writerow(['abundance', 'count', 'cumulative',
'cumulative_fraction'])
log_info('making countgraph')
# In case the user specified a maximum memory usage, use 8/(9+eps) of that
# for the countgraph and 1/(9+eps) for the tracking nodegraph
# `eps` is used to account for the memory used by the python interpreter
countgraph = khmer_args.create_countgraph(args, multiplier=8 / (9. + 0.3))
log_info('building k-mer tracking graph')
tracking = khmer_args.create_matching_nodegraph(countgraph)
log_info('kmer_size: {ksize}', ksize=countgraph.ksize())
log_info('k-mer countgraph sizes: {sizes}', sizes=countgraph.hashsizes())
log_info('outputting to {output}', output=args.output_histogram_filename)
# start loading
rparser = khmer.ReadParser(args.input_sequence_filename)
threads = []
log_info('consuming input, round 1 -- {input}',
input=args.input_sequence_filename)
for _ in range(args.threads):
thread = \
threading.Thread(
target=countgraph.consume_seqfile,
args=(rparser, )
)
threads.append(thread)
thread.start()
for thread in threads:
thread.join()
log_info('Total number of unique k-mers: {nk}',
nk=countgraph.n_unique_kmers())
abundance_lists = []
def __do_abundance_dist__(read_parser):
abundances = countgraph.abundance_distribution(
read_parser, tracking)
abundance_lists.append(abundances)
log_info('preparing hist from {seqfile}...',
seqfile=args.input_sequence_filename)
rparser = khmer.ReadParser(args.input_sequence_filename)
threads = []
log_info('consuming input, round 2 -- {filename}',
filename=args.input_sequence_filename)
for _ in range(args.threads):
thread = \
threading.Thread(
target=__do_abundance_dist__,
args=(rparser, )
)
threads.append(thread)
thread.start()
for thread in threads:
thread.join()
assert len(abundance_lists) == args.threads, len(abundance_lists)
abundance = {}
for abundance_list in abundance_lists:
for i, count in enumerate(abundance_list):
abundance[i] = abundance.get(i, 0) + count
total = sum(abundance.values())
if 0 == total:
log_error("ERROR: abundance distribution is uniformly zero; "
"nothing to report.")
log_error("\tPlease verify that the input files are valid.")
sys.exit(1)
sofar = 0
for _, i in sorted(abundance.items()):
if i == 0 and not args.output_zero:
continue
sofar += i
frac = sofar / float(total)
hist_fp_csv.writerow([_, i, sofar, round(frac, 3)])
if sofar == total:
break
if args.savegraph is not None:
log_info('Saving k-mer countgraph to {savegraph}',
savegraph=args.savegraph)
countgraph.save(args.savegraph)
log_info('wrote to: {output}', output=args.output_histogram_filename)
def sequenceToHistograma(nome, sequence):
ksize = 3
nkmers = 4**ksize
tablesize = nkmers + 10
# Initialize countgraph
cg = khmer.Countgraph(ksize, tablesize, 1)
# print('Created a countgraph with', cg.hashsizes(), 'buckets')
# start loading
auxNome = "sequenciaAuxliar.fa"
aux = open(auxNome, 'w')
aux.write(nome)
aux.write(sequence + "\n")
aux.close()
rparser = khmer.ReadParser(auxNome)
# rparser2 = rparser
# aux.closes
# os.remove(auxNome)
# rparser = khmer.ReadParser(sequence)
threads = []
for _ in range(1):
thread = \
threading.Thread(
target=cg.consume_seqfile_with_reads_parser,
args=(rparser, )
)
threads.append(thread)
thread.start()
for thread in threads:
thread.join()
# print('unique', cg.n_unique_kmers())
h = Histograma(nome, cg.n_unique_kmers(), nkmers, tablesize, len(sequence))
abundance_lists = []
tracking = khmer_args.create_matching_nodegraph(cg)
def __do_abundance_dist__(read_parser):
abundances = cg.abundance_distribution_with_reads_parser(
read_parser, tracking)
abundance_lists.append(abundances)
# aux = open(auxNome, 'r')
rparser2 = khmer.ReadParser(auxNome) # TESTE AQUI
os.remove(auxNome)
threads = []
for _ in range(1):
thread = \
threading.Thread(
target=__do_abundance_dist__,
args=(rparser2, )
)
threads.append(thread)
thread.start()
for thread in threads:
thread.join()
assert len(abundance_lists) == 1, len(abundance_lists)
abundance = {}
for abundance_list in abundance_lists:
for i, count in enumerate(abundance_list):
abundance[i] = abundance.get(i, 0) + count
total = sum(abundance.values())
if 0 == total:
print("ERROR: abundance distribution is uniformly zero; "
"nothing to report.")
print("\tPlease verify that the input files are valid.")
return 0
sofar = 0
line = 0
for _, i in sorted(abundance.items()):
if i == 0 and line < h.tablesize:
continue
sofar += i
frac = sofar / float(total)
#hist_fp_csv.writerow([_, i, sofar, round(frac, 3)])
# print(line, tablesize, [_, i, sofar, round(frac, 3)])
h.histo[line][0] = _
h.histo[line][1] = i
h.histo[line][2] = sofar
h.histo[line][3] = round(frac, 3)
line = line + 1
if sofar == total:
break
return h
def test_create_matching_nodegraph(ntables, targetsize):
cg = khmer.Countgraph(31, targetsize, ntables)
ng = create_matching_nodegraph(cg)
assert cg.hashsizes() == ng.hashsizes()