def test_random_20_a_succ_IV_save(self):
ht = khmer.Hashbits(20, 4 ** 7 + 1, 2)
filename = utils.get_test_data('random-20-a.fa')
savefile_ht = utils.get_temp_filename('ht')
savefile_tags = utils.get_temp_filename('tags')
outfile = filename + utils.get_temp_filename('out')
total_reads, _ = ht.consume_fasta_and_tag(filename)
ht.save(savefile_ht)
ht.save_tagset(savefile_tags)
del ht
ht = khmer.Hashbits(20, 4 ** 7 + 1, 2)
ht.load(savefile_ht)
ht.load_tagset(savefile_tags)
divvy = ht.divide_tags_into_subsets(1)
divvy.append(0)
subsets = []
for i in range(len(divvy) - 1):
x = ht.do_subset_partition(divvy[i], divvy[i + 1])
subsets.append(x)
for x in reversed(subsets):
ht.merge_subset(x)
n_partitions = ht.output_partitions(filename, outfile)
assert n_partitions == 1, n_partitions
def test_update_from():
htableable = khmer.Hashbits(5, 1000, 4)
other_htableable = khmer.Hashbits(5, 1000, 4)
assert htableable.get('AAAAA') == 0
assert htableable.get('GCGCG') == 0
assert other_htableable.get('AAAAA') == 0
assert other_htableable.get('GCGCG') == 0
other_htableable.count('AAAAA')
assert htableable.get('AAAAA') == 0
assert htableable.get('GCGCG') == 0
assert other_htableable.get('AAAAA') == 1
assert other_htableable.get('GCGCG') == 0
htableable.count('GCGCG')
assert htableable.get('AAAAA') == 0
assert htableable.get('GCGCG') == 1
assert other_htableable.get('AAAAA') == 1
assert other_htableable.get('GCGCG') == 0
htableable.update(other_htableable)
assert htableable.get('AAAAA') == 1
assert htableable.get('GCGCG') == 1
assert other_htableable.get('AAAAA') == 1
assert other_htableable.get('GCGCG') == 0
def test_update_from():
ht = khmer.Hashbits(5, 1000, 4)
ht2 = khmer.Hashbits(5, 1000, 4)
assert ht.get('AAAAA') == 0
assert ht.get('GCGCG') == 0
assert ht2.get('AAAAA') == 0
assert ht2.get('GCGCG') == 0
ht2.count('AAAAA')
assert ht.get('AAAAA') == 0
assert ht.get('GCGCG') == 0
assert ht2.get('AAAAA') == 1
assert ht2.get('GCGCG') == 0
ht.count('GCGCG')
assert ht.get('AAAAA') == 0
assert ht.get('GCGCG') == 1
assert ht2.get('AAAAA') == 1
assert ht2.get('GCGCG') == 0
ht.update(ht2)
assert ht.get('AAAAA') == 1
assert ht.get('GCGCG') == 1
assert ht2.get('AAAAA') == 1
assert ht2.get('GCGCG') == 0
def test_bloom_c_2(): # simple one
K = 4
HT_SIZE = 10 # use 11
N_HT1 = 1 # hashtable size = 11
N_HT2 = 2 # hashtable size = 11,13
# use only 1 hashtable, no bloom filter
ht1 = khmer.Hashbits(K, HT_SIZE, N_HT1)
ht1.count('AAAA') # 00 00 00 00 = 0
ht1.count('ACTG') # 00 10 01 11 =
assert ht1.n_unique_kmers() == 2
ht1.count('AACG') # 00 00 10 11 = 11 # collision with 1st kmer
assert ht1.n_unique_kmers() == 2
ht1.count('AGAC') # 00 11 00 10 # collision with 2nd kmer
assert ht1.n_unique_kmers() == 2
# use two hashtables with 11,13
ht2 = khmer.Hashbits(K, HT_SIZE, N_HT2)
ht2.count('AAAA') # 00 00 00 00 = 0
ht2.count('ACTG') # 00 10 01 11 = 2*16 +4 +3 = 39
assert ht2.n_unique_kmers() == 2
ht2.count('AACG') # 00 00 10 11 = 11 # collision with only 1st kmer
assert ht2.n_unique_kmers() == 3
ht2.count('AGAC') # 00 11 00 10 3*16 +2 = 50
# collision with both 2nd and 3rd kmers
assert ht2.n_unique_kmers() == 3
def test_update_from_diff_tablesize():
ht = khmer.Hashbits(5, 100, 4)
ht2 = khmer.Hashbits(5, 1000, 4)
try:
ht.update(ht2)
assert 0, "should not be reached"
except ValueError as err:
print(str(err))
def test_update_from_diff_num_tables():
htableable = khmer.Hashbits(5, 1000, 3)
other_htableable = khmer.Hashbits(5, 1000, 4)
try:
htableable.update(other_htableable)
assert 0, "should not be reached"
except ValueError as err:
print(str(err))
def test_count_within_radius_big():
inpfile = utils.get_test_data('random-20-a.fa')
ht = khmer.Hashbits(20, 1e6, 4)
ht.consume_fasta(inpfile)
n = ht.count_kmers_within_radius('CGCAGGCTGGATTCTAGAGG', int(1e6))
assert n == 3960
ht = khmer.Hashbits(21, 1e6, 4)
ht.consume_fasta(inpfile)
n = ht.count_kmers_within_radius('CGCAGGCTGGATTCTAGAGGC', int(1e6))
assert n == 39
def test_save_merge_from_disk(self):
ht = khmer.Hashbits(20, 4 ** 4 + 1, 2)
filename = utils.get_test_data('test-graph2.fa')
(total_reads, total_kmers) = ht.consume_fasta_and_tag(filename)
assert total_reads == 3, total_reads
divvy = ht.divide_tags_into_subsets(1)
print(divvy)
(a, b, c) = divvy
outfile1 = utils.get_temp_filename('x.pmap')
outfile2 = utils.get_temp_filename('y.pmap')
x = ht.do_subset_partition(a, b)
ht.save_subset_partitionmap(x, outfile1)
del x
y = ht.do_subset_partition(b, 0)
ht.save_subset_partitionmap(y, outfile2)
del y
ht.merge_subset_from_disk(outfile1)
ht.merge_subset_from_disk(outfile2)
outfile = utils.get_temp_filename('out.part')
n_partitions = ht.output_partitions(filename, outfile)
assert n_partitions == 1, n_partitions # combined.
def main():
info('merge-partitions.py', ['graph'])
args = get_parser().parse_args()
output_file = args.graphbase + '.pmap.merged'
pmap_files = glob.glob(args.graphbase + '.subset.*.pmap')
print('loading %d pmap files (first one: %s)' %
(len(pmap_files), pmap_files[0]),
file=sys.stderr)
ksize = args.ksize
htable = khmer.Hashbits(ksize, 1, 1)
for _ in pmap_files:
check_input_files(_, args.force)
check_space(pmap_files, args.force)
for pmap_file in pmap_files:
print('merging', pmap_file, file=sys.stderr)
htable.merge_subset_from_disk(pmap_file)
print('saving merged to', output_file, file=sys.stderr)
htable.save_partitionmap(output_file)
if args.remove_subsets:
print('removing pmap files', file=sys.stderr)
for pmap_file in pmap_files:
os.unlink(pmap_file)
def test_bloom_python_1():
# test python code to count unique kmers using bloom filter
filename = utils.get_test_data('random-20-a.fa')
ksize = 20 # size of kmer
htable_size = 100000 # size of hashtableable
num_htableables = 3 # number of hashtableables
htableable = khmer.Hashbits(ksize, htable_size, num_htableables)
n_unique = 0
for _, record in enumerate(fasta_iter(open(filename))):
sequence = record['sequence']
seq_len = len(sequence)
for n in range(0, seq_len + 1 - ksize):
kmer = sequence[n:n + ksize]
if not htableable.get(kmer):
n_unique += 1
htableable.count(kmer)
assert n_unique == 3960
assert htableable.n_occupied() == 3885, htableable.n_occupied()
# this number equals n_unique
assert htableable.n_unique_kmers() == 3960, htableable.n_unique_kmers()
def main():
info('annotate-partitions.py', ['graph'])
args = get_parser().parse_args()
ksize = args.ksize
filenames = args.input_filenames
htable = khmer.Hashbits(ksize, 1, 1)
partitionmap_file = args.graphbase + '.pmap.merged'
check_input_files(partitionmap_file, args.force)
for _ in filenames:
check_input_files(_, args.force)
check_space(filenames, args.force)
print('loading partition map from:', partitionmap_file, file=sys.stderr)
htable.load_partitionmap(partitionmap_file)
for infile in filenames:
print('outputting partitions for', infile, file=sys.stderr)
outfile = os.path.basename(infile) + '.part'
part_count = htable.output_partitions(infile, outfile)
print('output %d partitions for %s' % (part_count, infile),
file=sys.stderr)
print('partitions are in', outfile, file=sys.stderr)
def test_save_merge_from_disk_2(self):
ht = khmer.Hashbits(20, 4 ** 7 + 1, 2)
filename = utils.get_test_data('random-20-a.fa')
(total_reads, total_kmers) = ht.consume_fasta_and_tag(filename)
subset_size = total_reads // 2 + total_reads % 2
divvy = ht.divide_tags_into_subsets(subset_size)
outfile1 = utils.get_temp_filename('x.pmap')
outfile2 = utils.get_temp_filename('y.pmap')
x = ht.do_subset_partition(divvy[0], divvy[1])
ht.save_subset_partitionmap(x, outfile1)
del x
y = ht.do_subset_partition(divvy[1], 0)
ht.save_subset_partitionmap(y, outfile2)
del y
assert os.path.exists(outfile1)
assert os.path.exists(outfile2)
ht.merge_subset_from_disk(outfile1)
ht.merge_subset_from_disk(outfile2)
outfile = utils.get_temp_filename('out.part')
n_partitions = ht.output_partitions(filename, outfile)
assert n_partitions == 1, n_partitions # combined.
def test_save_load_merge_on_graph():
ht = khmer.Hashbits(20, 4 ** 4 + 1, 2)
filename = utils.get_test_data('test-graph2.fa')
(total_reads, total_kmers) = ht.consume_fasta_and_tag(filename)
assert total_reads == 3, total_reads
divvy = ht.divide_tags_into_subsets(1)
print(divvy)
assert len(divvy) is 3
(a, b, c) = divvy
outfile1 = utils.get_temp_filename('x.pmap')
outfile2 = utils.get_temp_filename('y.pmap')
x = ht.do_subset_partition(a, b)
ht.save_subset_partitionmap(x, outfile1)
del x
y = ht.do_subset_partition(b, 0)
ht.save_subset_partitionmap(y, outfile2)
del y
a = ht.load_partitionmap(outfile1) # <-- this is different
b = ht.load_subset_partitionmap(outfile2)
ht.merge_subset(b)
outfile = utils.get_temp_filename('out.part')
n_partitions = ht.output_partitions(filename, outfile)
assert n_partitions == 1, n_partitions # combined.
def main():
ht = khmer.Hashbits(K, 1, 1)
x = [0] * 255
y = [0] * 255
ht.load_stop_tags(sys.argv[1])
for n, record in enumerate(screed.open(sys.argv[2])):
if n % 10000 == 0:
sys.stderr.write('... %d\n' % n)
s, p = ht.trim_on_stoptags(record.sequence)
if len(s) == len(record.sequence):
continue
if p == 0:
p = 31
else:
p += 1
x[p] += 1
y[len(record.sequence)] += 1
for i, (n, m) in enumerate(zip(x, y)):
if m:
print('%d,%d,%d' % (i, n, m))
def test_tag_across_stoptraverse():
filename = utils.get_test_data('random-20-a.fa')
K = 20 # size of kmer
HT_SIZE = 100000 # size of hashtable
N_HT = 3 # number of hashtables
ht = khmer.Hashbits(K, HT_SIZE, N_HT)
# without tagging/joining across consume, this breaks into two partition;
# with, it is one partition.
ht.add_stop_tag('CCGAATATATAACAGCGACG')
ht.consume_fasta_and_tag_with_stoptags(filename) # DO join reads across
subset = ht.do_subset_partition(0, 0)
n, _ = ht.count_partitions()
assert n == 99 # reads only connected by traversal...
n, _ = ht.subset_count_partitions(subset)
assert n == 2 # but need main to cross stoptags.
ht.merge_subset(subset)
n, _ = ht.count_partitions() # ta-da!
assert n == 1, n
def test_extract_unique_paths_2():
kh = khmer.Hashbits(10, 1e5, 4)
kh.consume('ATGGAGAGAC')
x = kh.extract_unique_paths('ATGGAGAGACACAGATAGACAGGAGTGGCGATG', 10, 1)
print x
assert x == ['TGGAGAGACACAGATAGACAGGAGTGGCGATG'] # all but the 1st k-mer
def test_bloom_python_1():
# test python code to count unique kmers using bloom filter
filename = utils.get_test_data('random-20-a.fa')
K = 20 # size of kmer
HT_SIZE = 100000 # size of hashtable
N_HT = 3 # number of hashtables
ht2 = khmer.Hashbits(K, HT_SIZE, N_HT)
n_unique = 0
for n, record in enumerate(fasta_iter(open(filename))):
sequence = record['sequence']
seq_len = len(sequence)
for n in range(0, seq_len + 1 - K):
kmer = sequence[n:n + K]
if (not ht2.get(kmer)):
n_unique += 1
ht2.count(kmer)
assert n_unique == 3960
assert ht2.n_occupied() == 3885, ht2.n_occupied()
# this number equals n_unique
assert ht2.n_unique_kmers() == 3960, ht2.n_unique_kmers()
def test__get_set_tag_density():
ht = khmer.Hashbits(32, 1, 1)
orig = ht._get_tag_density()
assert orig != 2
ht._set_tag_density(2)
assert ht._get_tag_density() == 2
def test_tiny_real_partitions():
filename = utils.get_test_data('real-partition-tiny.fa')
ht = khmer.Hashbits(32, 8e2, 4)
ht.consume_fasta_and_tag(filename)
subset = ht.do_subset_partition(0, 0)
ht.merge_subset(subset)
outfile = utils.get_temp_filename('part')
ht.output_partitions(filename, outfile)
data = open(outfile).read()
assert len(data)
records = [r for r in screed.open(outfile)]
names = [r.name for r in records]
parts = [n.rsplit('\t', 1)[1] for n in names]
assert len(parts) == 2, len(parts)
assert len(set(parts)) == 1
assert set(parts) != set(['0'])
test_tiny_real_partitions.runme = True
def test_consume_fasta_and_tag_with_badreads_parser():
presencetable = khmer.Hashbits(6, 1e6, 2)
readsparser = khmer.ReadParser(utils.get_test_data("test-empty.fa"))
try:
presencetable.consume_fasta_and_tag_with_reads_parser(readsparser)
assert 0, "this should fail"
except IOError, e:
print str(e)
def test_find_stoptags():
ht = khmer.Hashbits(5, 1, 1)
ht.add_stop_tag("AAAAA")
assert ht.identify_stoptags_by_position("AAAAA") == [0]
assert ht.identify_stoptags_by_position("AAAAAA") == [0, 1]
assert ht.identify_stoptags_by_position("TTTTT") == [0]
assert ht.identify_stoptags_by_position("TTTTTT") == [0, 1]
def test_find_radius_for_volume():
inpfile = utils.get_test_data('all-A.fa')
ht = khmer.Hashbits(4, 1e6, 2)
ht.consume_fasta(inpfile)
assert ht.find_radius_for_volume('AAAA', 0, 100) == 0
assert ht.find_radius_for_volume('AAAA', 1, 100) == 0
assert ht.find_radius_for_volume('AAAA', 2, 100) == 100
def main():
filename1 = sys.argv[1]
filename2 = sys.argv[2]
uniq1 = open(os.path.basename(sys.argv[1]) + '.uniq', 'w')
uniq2 = open(os.path.basename(sys.argv[2]) + '.uniq', 'w')
paths = sys.argv[3]
kh1 = khmer.Hashbits(K, HASHTABLE_SIZE, N_HT)
kh1.consume_fasta(filename1)
kh2 = khmer.Hashbits(K, HASHTABLE_SIZE, N_HT)
kh2.consume_fasta(filename2)
for record in screed.open(paths):
n = 0
n_present = 0
path = record.sequence
n = len(path) - K + 1
for i in range(n):
if kh1.get(path[i:i + K]):
n_present += 1
if n_present / float(n) >= THRESHOLD:
present1 = True
else:
present1 = False
n = 0
n_present = 0
path = record.sequence
n = len(path) - K + 1
for i in range(n):
if kh2.get(path[i:i + K]):
n_present += 1
if n_present / float(n) >= THRESHOLD:
present2 = True
else:
present2 = False
if present1 and not present2:
print('>%s\n%s' % (record.name, record.sequence), file=uniq1)
elif present2 and not present1:
print('>%s\n%s' % (record.name, record.sequence), file=uniq2)
def test_extract_unique_paths_0():
kh = khmer.Hashbits(10, 1e5, 4)
x = kh.extract_unique_paths('ATGGAGAGACACAGATAGACAGGAGTGGCGATG', 10, 1)
assert x == ['ATGGAGAGACACAGATAGACAGGAGTGGCGATG']
kh.consume('ATGGAGAGACACAGATAGACAGGAGTGGCGATG')
x = kh.extract_unique_paths('ATGGAGAGACACAGATAGACAGGAGTGGCGATG', 10, 1)
assert not x
def test_count_kmer_degree():
inpfile = utils.get_test_data('all-A.fa')
ht = khmer.Hashbits(4, 1e6, 2)
ht.consume_fasta(inpfile)
assert ht.kmer_degree('AAAA') == 2
assert ht.kmer_degree('AAAT') == 1
assert ht.kmer_degree('AATA') == 0
assert ht.kmer_degree('TAAA') == 1
def test_connected_20_b(self):
filename = utils.get_test_data('random-20-b.fa')
ht = khmer.Hashbits(20, 1e4, 4)
ht.consume_fasta_and_tag(filename)
subset = ht.do_subset_partition(0, 0)
x = ht.subset_count_partitions(subset)
assert x == (1, 0) # connected @ 20
def test_connected_31_c(self):
filename = utils.get_test_data('random-31-c.fa')
ht = khmer.Hashbits(31, 1e5, 4)
ht.consume_fasta_and_tag(filename)
subset = ht.do_subset_partition(0, 0)
x = ht.subset_count_partitions(subset)
assert x == (1, 0) # connected @ K = 31
def main():
parser = build_construct_args()
parser.add_argument('input_filename')
parser.add_argument('read_filename')
args = parser.parse_args()
if not args.quiet:
if args.min_hashsize == DEFAULT_MAX_TABLESIZE:
print("** WARNING: hashsize is default! " \
"You absodefly want to increase this!\n** " \
"Please read the docs!", file=sys.stderr)
print('\nPARAMETERS:', file=sys.stderr)
print(' - kmer size = %d \t\t(-k)' % args.ksize, file=sys.stderr)
print(' - n hashes = %d \t\t(-N)' % args.n_hashes, file=sys.stderr)
print(' - min hashsize = %-5.2g \t(-x)' % \
args.min_hashsize, file=sys.stderr)
print('', file=sys.stderr)
print('Estimated memory usage is %.2g bytes ' \
'(n_hashes x min_hashsize / 8)' % (
args.n_hashes * args.min_hashsize / 8.), file=sys.stderr)
print('-' * 8, file=sys.stderr)
K = args.ksize
HT_SIZE = args.min_hashsize
N_HT = args.n_hashes
inp = args.input_filename
readsfile = args.read_filename
outfile = os.path.basename(readsfile) + '.sweep2'
outfp = open(outfile, 'w')
# create a hashbits data structure
ht = khmer.Hashbits(K, HT_SIZE, N_HT)
# load contigs, connect into N partitions
print('loading input reads from', inp)
ht.consume_fasta(inp)
print('starting sweep.')
n = 0
m = 0
for record in screed.open(readsfile):
if len(record.sequence) < K:
continue
if n % 10000 == 0:
print('...', n, m)
count = ht.get_median_count(record.sequence)[0]
if count:
m += 1
outfp.write('>%s\n%s\n' % (record.name, record.sequence))
n += 1
def create_nodegraph(args, ksize=None, multiplier=1.0):
if ksize is None:
ksize = args.ksize
if ksize > 32:
print_error("\n** ERROR: khmer only supports k-mer sizes <= 32.\n")
sys.exit(1)
tablesize = _calculate_tablesize(args, 'nodegraph', multiplier=multiplier)
return khmer.Hashbits(ksize, tablesize, args.n_tables)
def test_merge_from_disk_file_version(self):
ht = khmer.Hashbits(20, 4 ** 4 + 1, 2)
infile = utils.get_test_data('badversion-k12.ht')
try:
ht.merge_subset_from_disk(infile)
assert 0, "this should fail"
except OSError as e:
print(str(e))