def test_pickle(track_abundance):
import pickle
from io import BytesIO
e1 = MinHash(n=5,
ksize=6,
is_protein=False,
track_abundance=track_abundance)
seq = 'ATGGCAGTGACGATGCCG'
e1.add_sequence(seq)
e1.add_sequence(seq)
fp = BytesIO()
pickle.dump(e1, fp)
fp2 = BytesIO(fp.getvalue())
e2 = pickle.load(fp2)
assert e1.get_mins(with_abundance=track_abundance) == \
e2.get_mins(with_abundance=track_abundance)
assert e1.num == e2.num
assert e1.ksize == e2.ksize
assert e1.is_protein == e2.is_protein
assert e1.max_hash == e2.max_hash
assert e1.seed == e2.seed
def build_query_mh_for_seed(self, seed, scaled):
mh = MinHash(0, self.ksize, scaled=scaled, seed=seed)
for record in screed.open(self.filename):
mh.add_sequence(record.sequence, True)
return sourmash_lib.SourmashSignature(mh, name=self.name,
filename=self.filename)
def build_query_mh_for_seed(self, seed, scaled):
mh = MinHash(0, self.ksize, scaled=scaled, seed=seed)
for record in screed.open(self.filename):
mh.add_sequence(record.sequence, True)
return sourmash_lib.SourmashSignature(mh,
name=self.name,
filename=self.filename)
def test_diff_seed(track_abundance):
E1 = MinHash(n=5, ksize=20, track_abundance=track_abundance, seed=1)
E2 = MinHash(n=5, ksize=20, track_abundance=track_abundance, seed=2)
for i in [1, 2, 3, 4, 5]:
E1.add_hash(i)
for i in [1, 2, 3, 4, 6]:
E2.add_hash(i)
with pytest.raises(ValueError):
E1.count_common(E2)
def test_common_1(track_abundance):
E1 = MinHash(n=5, ksize=20, track_abundance=track_abundance)
E2 = MinHash(n=5, ksize=20, track_abundance=track_abundance)
for i in [1, 2, 3, 4, 5]:
E1.add_hash(i)
for i in [1, 2, 3, 4, 6]:
E2.add_hash(i)
assert E1.count_common(E2) == 4
assert E2.count_common(E1) == 4
def build_query_mh_for_seed(seed, ksize, scaled, query_seq_file):
mh = MinHash(0, ksize, scaled=scaled, seed=seed)
name = None
for record in screed.open(query_seq_file):
if not name:
name = record.name
mh.add_sequence(record.sequence, True)
return sourmash_lib.SourmashSignature(mh,
name=name,
filename=query_seq_file)
def test_abund_similarity():
E1 = MinHash(n=5, ksize=20, track_abundance=True)
E2 = MinHash(n=5, ksize=20, track_abundance=True)
for i in [1]:
E1.add_hash(i)
for i in [1, 2]:
E2.add_hash(i)
assert round(E1.similarity(E1)) == 1.0
assert round(E1.similarity(E2), 2) == 0.5
assert round(E1.similarity(E1, ignore_abundance=True)) == 1.0
assert round(E1.similarity(E2, ignore_abundance=True), 2) == 0.5
def test_jaccard_1(track_abundance):
E1 = MinHash(n=5, ksize=20, track_abundance=track_abundance)
E2 = MinHash(n=5, ksize=20, track_abundance=track_abundance)
for i in [1, 2, 3, 4, 5]:
E1.add_hash(i)
for i in [1, 2, 3, 4, 6]:
E2.add_hash(i)
# here the union is [1, 2, 3, 4, 5]
# and the intesection is [1, 2, 3, 4] => 4/5.
assert round(E1.jaccard(E2), 2) == round(4 / 5.0, 2)
assert round(E2.jaccard(E1), 2) == round(4 / 5.0, 2)
def test_bad_construct_1(track_abundance):
try:
e1 = MinHash(ksize=6,
is_protein=False,
track_abundance=track_abundance)
assert 0, "require n in constructor"
except TypeError:
pass
def test_abund_similarity_zero():
E1 = MinHash(n=5, ksize=20, track_abundance=True)
E2 = MinHash(n=5, ksize=20, track_abundance=True)
for i in [1]:
E1.add_hash(i)
assert E1.similarity(E2) == 0.0
def test_protein_mh(track_abundance):
e1 = MinHash(n=5,
ksize=6,
is_protein=True,
track_abundance=track_abundance)
e2 = MinHash(n=5,
ksize=6,
is_protein=True,
track_abundance=track_abundance)
seq = 'ATGGCAGTGACGATGCCG'
e1.add_sequence(seq)
for i in range(len(seq) - 5):
kmer = seq[i:i + 6]
e2.add(kmer)
assert e1.get_mins() == e2.get_mins()
assert 901193879228338100 in e1.get_mins()
def test_dna_mh(track_abundance):
e1 = MinHash(n=5, ksize=4, track_abundance=track_abundance)
e2 = MinHash(n=5, ksize=4, track_abundance=track_abundance)
seq = 'ATGGCAGTGACGATGCCAG'
e1.add_sequence(seq)
for i in range(len(seq) - 3):
e2.add(seq[i:i + 4])
assert e1.get_mins() == e2.get_mins()
print(e1.get_mins())
assert 726311917625663847 in e1.get_mins()
assert 3697418565283905118 in e1.get_mins()
def test_jaccard_2_difflen(track_abundance):
E1 = MinHash(n=5, ksize=20, track_abundance=track_abundance)
E2 = MinHash(n=5, ksize=20, track_abundance=track_abundance)
for i in [1, 2, 3, 4, 5]:
E1.add_hash(i)
for i in [1, 2, 3, 4]:
E2.add_hash(i)
print(E1.jaccard(E2))
assert round(E1.jaccard(E2), 2) == 4 / 5.0
assert round(E2.jaccard(E1), 2) == 4 / 5.0