def main():
args = sanitize_help(get_parser()).parse_args()
total_hll = khmer.HLLCounter(args.error_rate, args.ksize)
report_fp = args.report
input_filename = None
for _, input_filename in enumerate(args.input_filenames):
hllcpp = khmer.HLLCounter(args.error_rate, args.ksize)
hllcpp.consume_fasta(input_filename,
stream_records=args.stream_records)
cardinality = hllcpp.estimate_cardinality()
print('Estimated number of unique {0}-mers in {1}: {2}'.format(
args.ksize, input_filename, cardinality),
file=sys.stderr)
if report_fp:
print(cardinality, args.ksize, '(total)', file=report_fp)
report_fp.flush()
total_hll.merge(hllcpp)
cardinality = total_hll.estimate_cardinality()
print('Total estimated number of unique {0}-mers: {1}'.format(
args.ksize, cardinality),
file=sys.stderr)
to_print = graphsize_args_report(cardinality, args.error_rate)
if args.diagnostics:
print(to_print, file=sys.stderr)
if report_fp:
print(cardinality, args.ksize, 'total', file=report_fp)
print(to_print, file=report_fp)
report_fp.flush()
def main():
args = sanitize_help(get_parser()).parse_args()
total_hll = khmer.HLLCounter(args.error_rate, args.ksize)
report_fp = args.report
input_filename = None
for _, input_filename in enumerate(args.input_filenames):
hllcpp = khmer.HLLCounter(args.error_rate, args.ksize)
hllcpp.consume_seqfile(input_filename,
stream_records=args.stream_records)
cardinality = hllcpp.estimate_cardinality()
print('Estimated number of unique {0}-mers in {1}: {2}'.format(
args.ksize, input_filename, cardinality), file=sys.stderr)
if report_fp:
print(cardinality, args.ksize, '(total)', file=report_fp)
report_fp.flush()
total_hll.merge(hllcpp)
cardinality = total_hll.estimate_cardinality()
print('Total estimated number of unique {0}-mers: {1}'.format(
args.ksize, cardinality), file=sys.stderr)
to_print = graphsize_args_report(cardinality, args.error_rate)
if args.diagnostics:
print(to_print, file=sys.stderr)
if report_fp:
print(cardinality, args.ksize, 'total', file=report_fp)
print(to_print, file=report_fp)
report_fp.flush()
def main():
info('optimal_args_nodegraph.py', ['graph', 'SeqAn'])
args = get_parser().parse_args()
report_on_config(args, graphtype='nodegraph')
filenames = args.input_filenames
base = filenames[0]
for _ in args.input_filenames:
check_input_files(_, False)
check_space(args.input_filenames, False)
print('Counting kmers from sequences in %s' % repr(filenames),
file=sys.stderr)
htable = khmer.new_nodegraph(args.ksize, args.max_tablesize, args.n_tables)
target_method = htable.consume_fasta_with_reads_parser
for _, filename in enumerate(filenames):
rparser = khmer.ReadParser(filename)
threads = []
print('consuming input', filename, file=sys.stderr)
for num in xrange(args.threads):
cur_thread = threading.Thread(target=target_method,
args=(rparser, ))
threads.append(cur_thread)
cur_thread.start()
for thread in threads:
thread.join()
unique_kmers = htable.n_unique_kmers()
print('Total number of unique k-mers: {0}'.format(unique_kmers),
file=sys.stderr)
info_optimal = open(base + '.optimal_args', 'w')
fp_rate = khmer.calc_expected_collisions(htable)
print('fp rate estimated to be %1.3f' % fp_rate, file=sys.stderr)
if fp_rate > 0.15: # 0.18 is ACTUAL MAX. Do not change.
print("**", file=sys.stderr)
print(
"** ERROR: the graph structure is too small for this data set."
"Increase table size/# tables.",
file=sys.stderr)
print("**", file=sys.stderr)
if not False:
sys.exit(1)
to_print = graphsize_args_report(unique_kmers, fp_rate)
print(to_print, file=info_optimal)
print('optimal arguments were written to',
base + '.optimal_args',
file=sys.stderr)
def main():
info('optimal_args_nodegraph.py', ['graph', 'SeqAn'])
args = get_parser().parse_args()
report_on_config(args, graphtype='nodegraph')
filenames = args.input_filenames
base = filenames[0]
for _ in args.input_filenames:
check_input_files(_, False)
check_space(args.input_filenames, False)
print('Counting kmers from sequences in %s' % repr(filenames),
file=sys.stderr)
htable = khmer.new_nodegraph(args.ksize, args.max_tablesize, args.n_tables)
target_method = htable.consume_fasta_with_reads_parser
for _, filename in enumerate(filenames):
rparser = khmer.ReadParser(filename)
threads = []
print('consuming input', filename, file=sys.stderr)
for num in xrange(args.threads):
cur_thread = threading.Thread(
target=target_method, args=(rparser,))
threads.append(cur_thread)
cur_thread.start()
for thread in threads:
thread.join()
unique_kmers = htable.n_unique_kmers()
print('Total number of unique k-mers: {0}'.format(unique_kmers),
file=sys.stderr)
info_optimal = open(base + '.optimal_args', 'w')
fp_rate = khmer.calc_expected_collisions(htable)
print('fp rate estimated to be %1.3f' % fp_rate, file=sys.stderr)
if fp_rate > 0.15: # 0.18 is ACTUAL MAX. Do not change.
print("**", file=sys.stderr)
print("** ERROR: the graph structure is too small for this data set."
"Increase table size/# tables.", file=sys.stderr)
print("**", file=sys.stderr)
if not False:
sys.exit(1)
to_print = graphsize_args_report(unique_kmers, fp_rate)
print(to_print, file=info_optimal)
print('optimal arguments were written to', base + '.optimal_args',
file=sys.stderr)
def main():
info('unique-kmers.py', ['SeqAn', 'hll'])
args = get_parser().parse_args()
total_hll = khmer.HLLCounter(args.error_rate, args.ksize)
report_fp = args.report
input_filename = None
for index, input_filename in enumerate(args.input_filenames):
hllcpp = khmer.HLLCounter(args.error_rate, args.ksize)
for record in screed.open(input_filename):
seq = record.sequence.upper().replace('N', 'A')
hllcpp.consume_string(seq)
if args.stream_out:
write_record(record, sys.stdout)
cardinality = hllcpp.estimate_cardinality()
print('Estimated number of unique {0}-mers in {1}: {2}'.format(
args.ksize, input_filename, cardinality),
file=sys.stderr)
if report_fp:
print(cardinality, args.ksize, '(total)', file=report_fp)
report_fp.flush()
total_hll.merge(hllcpp)
cardinality = total_hll.estimate_cardinality()
print('Total estimated number of unique {0}-mers: {1}'.format(
args.ksize, cardinality),
file=sys.stderr)
to_print = graphsize_args_report(cardinality, args.error_rate)
if args.diagnostics:
print(to_print, file=sys.stderr)
if report_fp:
print(cardinality, args.ksize, 'total', file=report_fp)
print(to_print, file=report_fp)
report_fp.flush()
def test_output_gen():
graphsize_args_report(99, 0.00701925498897)
