def test_get_aln_results_6():
"""
Align two completely different sequences.
"""
ref_seq = ''.join([random.choice('AC') for i in xrange(3000)])
query_seq = ''.join([random.choice('GT') for i in xrange(3000)])
min_seq_len = 2000
result = mod.get_aln_results(ref_seq, query_seq, min_seq_len)
result = (result[0], round(result[1], 2), round(result[2], 2))
expected = (0, 0.00, 0.00) # delta_len, idt, cov
assert(result == expected)
def test_get_aln_results_5():
"""
The DW alignment has a 100bp minimum distance threshold for (e1 - s1) and (e2 - s2).
"""
ref_seq = ''.join([random.choice('ACTG') for i in xrange(90)])
query_seq = ref_seq
min_seq_len = 50
result = mod.get_aln_results(ref_seq, query_seq, min_seq_len)
result = (result[0], round(result[1], 2), round(result[2], 2))
expected = (0, 0.00, 0.00) # delta_len, idt, cov
assert(result == expected)
def test_get_aln_results_1():
"""
Test aligning identical sequences.
"""
ref_seq = ''.join([random.choice('ACTG') for i in xrange(45000)])
query_seq = ref_seq
min_seq_len = 2000
result = mod.get_aln_results(ref_seq, query_seq, min_seq_len)
result = (result[0], round(result[1], 2), round(result[2], 2))
expected = (0, 1.00, 1.00) # delta_len, idt, cov
assert(result == expected)
def test_get_aln_results_6():
"""
Align two completely different sequences.
"""
ref_seq = ''.join([random.choice('AC') for i in range(3000)])
query_seq = ''.join([random.choice('GT') for i in range(3000)])
min_seq_len = 2000
result = mod.get_aln_results(ref_seq, query_seq, min_seq_len)
result = (result[0], round(result[1], 2), round(result[2], 2))
expected = (0, 0.00, 0.00) # delta_len, idt, cov
assert(result == expected)
def test_get_aln_results_1():
"""
Test aligning identical sequences.
"""
ref_seq = ''.join([random.choice('ACTG') for i in range(45000)])
query_seq = ref_seq
min_seq_len = 2000
result = mod.get_aln_results(ref_seq, query_seq, min_seq_len)
result = (result[0], round(result[1], 2), round(result[2], 2))
expected = (0, 1.00, 1.00) # delta_len, idt, cov
assert(result == expected)
def test_get_aln_results_5():
"""
The DW alignment has a 100bp minimum distance threshold for (e1 - s1) and (e2 - s2).
"""
ref_seq = ''.join([random.choice('ACTG') for i in range(90)])
query_seq = ref_seq
min_seq_len = 50
result = mod.get_aln_results(ref_seq, query_seq, min_seq_len)
result = (result[0], round(result[1], 2), round(result[2], 2))
expected = (0, 0.00, 0.00) # delta_len, idt, cov
assert(result == expected)
def test_get_aln_results_4():
"""
The legacy deduplication code has a threshold on minimum sequence
length for alignment. If any of the sequences was shorter than this,
the alignment wouldn't be performed, and the sequence would not be deduplicated
even if it was a duplicate.
"""
ref_seq = ''.join([random.choice('ACTG') for i in xrange(300)])
query_seq = ref_seq
min_seq_len = 2000
result = mod.get_aln_results(ref_seq, query_seq, min_seq_len)
result = (result[0], round(result[1], 2), round(result[2], 2))
expected = (0, 0.00, 0.00) # delta_len, idt, cov
assert(result == expected)
def test_get_aln_results_4():
"""
The legacy deduplication code has a threshold on minimum sequence
length for alignment. If any of the sequences was shorter than this,
the alignment wouldn't be performed, and the sequence would not be deduplicated
even if it was a duplicate.
"""
ref_seq = ''.join([random.choice('ACTG') for i in range(300)])
query_seq = ref_seq
min_seq_len = 2000
result = mod.get_aln_results(ref_seq, query_seq, min_seq_len)
result = (result[0], round(result[1], 2), round(result[2], 2))
expected = (0, 0.00, 0.00) # delta_len, idt, cov
assert(result == expected)
def test_get_aln_results_3():
"""
This tests alignment of very long sequences.
Ideally, this would return (0, 1.00, 1.00), but the DW alignment
implementation has a quadratic memory complexity, so there is a
hardcoded threshold than either ref or query cannot be longer than
250000 bp. In this case, (0, -1.0, -1.0) is returned.
This test case would fail with a normal linear-memory aligner,
which is actually what would be expected.
"""
ref_seq = ''.join([random.choice('ACTG') for i in xrange(300000)])
query_seq = ref_seq
min_seq_len = 2000
result = mod.get_aln_results(ref_seq, query_seq, min_seq_len)
result = (result[0], round(result[1], 2), round(result[2], 2))
expected = (0, -1.00, -1.00) # delta_len, idt, cov
assert(result == expected)
def test_get_aln_results_3():
"""
This tests alignment of very long sequences.
Ideally, this would return (0, 1.00, 1.00), but the DW alignment
implementation has a quadratic memory complexity, so there is a
hardcoded threshold than either ref or query cannot be longer than
250000 bp. In this case, (0, -1.0, -1.0) is returned.
This test case would fail with a normal linear-memory aligner,
which is actually what would be expected.
"""
ref_seq = ''.join([random.choice('ACTG') for i in range(300000)])
query_seq = ref_seq
min_seq_len = 2000
result = mod.get_aln_results(ref_seq, query_seq, min_seq_len)
result = (result[0], round(result[1], 2), round(result[2], 2))
expected = (0, -1.00, -1.00) # delta_len, idt, cov
assert(result == expected)