def test_lossless_reads():
A = Alphabet('ACGT')
S = rand_seq(A, 100)
with pytest.raises(AssertionError):
next(rand_read(S, len_mean=200, num=1)) # len_mean must be < len(S)
with pytest.raises(AssertionError):
# at most one of num or expected_coverage given
next(rand_read(S, len_mean=50, num=1, expected_coverage=1))
assert sum(1 for _ in rand_read(S, len_mean=50, num=10)) == 10, \
'The number of sampled reads should be controllable'
assert sum(1 for _ in rand_read(S, len_mean=50)) == 1, \
'If neither num or expected coverage is given only one sample is read'
# there should be no noise added
read, pos = next(rand_read(S, len_mean=40, num=1))
assert S[pos:pos+len(read)] == read
S = A.parse('ACT' * 100)
reads = [x for x in rand_read(S, len_mean=100, len_sd=0.01, num=100)]
assert set(len(read) for read, _ in reads) > 1, \
'Read lengths should be randomly chosen'
len_mean = sum(len(read) for read, _ in reads) / 100.
assert len_mean > 50 and len_mean < 150, \
'Normal distribution of read lengths works'
# index edge cases
A = Alphabet(['00', '01'])
S = A.parse('01' * 10)
_bak = np.random.normal
np.random.normal = mock.Mock(return_value=[1])
assert next(rand_read(S, len_mean=1, num=1))[0] == A.parse('01'), \
'sequences in alphabets with > 1 long letters can be sampled too'
np.random.normal = _bak
def test_expected_coverage():
A = Alphabet('ACGT')
S = rand_seq(A, 100)
cov = 10
reads = [r for r in rand_read(S, len_mean=len(S)/2, expected_coverage=cov)]
assert len(reads) == 2 * cov
