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test_jaccard.py
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test_jaccard.py
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"""
Legacy tests from when there were Estimator objects and not just MinHash
objects.
"""
import pytest
from sourmash import MinHash
import sourmash_tst_utils as utils
# below, 'track_abundance' is toggled to both True and False by py.test --
# see conftest.py.
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 intersection 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_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
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 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_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_kmer(seq[i:i + 4])
assert e1.hashes.keys() == e2.hashes.keys()
print(e1.hashes.keys())
assert 726311917625663847 in e1.hashes.keys()
assert 3697418565283905118 in e1.hashes.keys()
def test_protein_mh(track_abundance):
e1 = MinHash(n=5, ksize=2, is_protein=True,
track_abundance=track_abundance)
e2 = MinHash(n=5, ksize=2, is_protein=True,
track_abundance=track_abundance)
# ok, so this is confusing, but: we are adding _DNA_ kmers here,
# and translating. so, add_sequence and add_kmer actually both add
# 6-mers.
seq = 'ATGGCAGTGACGATGCCG'
e1.add_sequence(seq)
for i in range(len(seq) - 5):
kmer = seq[i:i + 6]
e2.add_kmer(kmer)
assert e1.hashes.keys() == e2.hashes.keys()
assert 901193879228338100 in e1.hashes.keys()
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.hashes == e2.hashes
assert e1.num == e2.num
assert e1.ksize == e2.ksize
assert e1.is_protein == e2.is_protein
assert e1.scaled == e2.scaled
assert e1.scaled == 0
assert e1.seed == e2.seed
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_bad_construct_2(track_abundance):
try:
e1 = MinHash(n=100, is_protein=False,
track_abundance=track_abundance)
assert 0, "require ksize in constructor"
except TypeError:
pass
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_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_jaccard_on_real_data():
from sourmash.signature import load_signatures
afile = 'n10000/GCF_000005845.2_ASM584v2_genomic.fna.gz.sig.gz'
a = utils.get_test_data(afile)
sig1 = list(load_signatures(a))[0]
mh1 = sig1.minhash
bfile = 'n10000/GCF_000006945.1_ASM694v1_genomic.fna.gz.sig.gz'
b = utils.get_test_data(bfile)
sig2 = list(load_signatures(b))[0]
mh2 = sig2.minhash
assert mh1.similarity(mh2) == 0.0183
assert mh2.similarity(mh1) == 0.0183
mh1 = mh1.downsample(num=1000)
mh2 = mh2.downsample(num=1000)
assert mh1.similarity(mh2) == 0.011
assert mh2.similarity(mh1) == 0.011
mh1 = mh1.downsample(num=100)
mh2 = mh2.downsample(num=100)
assert mh1.similarity(mh2) == 0.01
assert mh2.similarity(mh1) == 0.01
mh1 = mh1.downsample(num=10)
mh2 = mh2.downsample(num=10)
assert mh1.similarity(mh2) == 0.0
assert mh2.similarity(mh1) == 0.0
def test_scaled_on_real_data():
from sourmash.signature import load_signatures
afile = 'scaled100/GCF_000005845.2_ASM584v2_genomic.fna.gz.sig.gz'
a = utils.get_test_data(afile)
sig1 = list(load_signatures(a))[0]
mh1 = sig1.minhash
bfile = 'scaled100/GCF_000006945.1_ASM694v1_genomic.fna.gz.sig.gz'
b = utils.get_test_data(bfile)
sig2 = list(load_signatures(b))[0]
mh2 = sig2.minhash
assert round(mh1.similarity(mh2), 5) == 0.01644
assert round(mh2.similarity(mh1), 5) == 0.01644
mh1 = mh1.downsample(scaled=100)
mh2 = mh2.downsample(scaled=100)
assert round(mh1.similarity(mh2), 5) == 0.01644
assert round(mh2.similarity(mh1), 5) == 0.01644
mh1 = mh1.downsample(scaled=1000)
mh2 = mh2.downsample(scaled=1000)
assert round(mh1.similarity(mh2), 5) == 0.01874
assert round(mh2.similarity(mh1), 5) == 0.01874
mh1 = mh1.downsample(scaled=10000)
mh2 = mh2.downsample(scaled=10000)
assert mh1.similarity(mh2) == 0.01
assert mh2.similarity(mh1) == 0.01
def test_scaled_on_real_data_2():
from sourmash.signature import load_signatures
afile = 'scaled100/GCF_000005845.2_ASM584v2_genomic.fna.gz.sig.gz'
a = utils.get_test_data(afile)
sig1 = list(load_signatures(a))[0]
mh1 = sig1.minhash
bfile = 'scaled100/GCF_000006945.1_ASM694v1_genomic.fna.gz.sig.gz'
b = utils.get_test_data(bfile)
sig2 = list(load_signatures(b))[0]
mh2 = sig2.minhash
assert round(mh1.similarity(mh2), 5) == 0.01644
assert round(mh2.similarity(mh1), 5) == 0.01644
mh1 = mh1.downsample(scaled=1000)
mh2 = mh2.downsample(scaled=1000)
assert round(mh1.similarity(mh2), 4) == 0.0187
assert round(mh2.similarity(mh1), 4) == 0.0187
mh1 = mh1.downsample(scaled=10000)
mh2 = mh2.downsample(scaled=10000)
assert round(mh1.similarity(mh2), 3) == 0.01
assert round(mh2.similarity(mh1), 3) == 0.01
mh1 = mh1.downsample(scaled=100000)
mh2 = mh2.downsample(scaled=100000)
assert round(mh1.similarity(mh2), 2) == 0.01
assert round(mh2.similarity(mh1), 2) == 0.01
def test_downsample_scaled_with_num():
from sourmash.signature import load_signatures
afile = 'scaled100/GCF_000005845.2_ASM584v2_genomic.fna.gz.sig.gz'
a = utils.get_test_data(afile)
sig1 = list(load_signatures(a))[0]
mh1 = sig1.minhash
with pytest.raises(ValueError) as exc:
mh = mh1.downsample(num=500)
assert 'cannot downsample a scaled MinHash using num' in str(exc.value)