def test_autotune_reads_per_batch_more_jobs_than_reads(self):
self.assertEqual(
_autotune_reads_per_batch(self.seq_path, n_jobs=1105), 1)
def extract_reads(sequences: DNASequencesDirectoryFormat, f_primer: str,
r_primer: str, trunc_len: int = 0, trim_left: int = 0,
identity: float = 0.8, min_length: int = 50,
max_length: int = 0, n_jobs: int = 1,
batch_size: int = 'auto') -> DNAFASTAFormat:
"""Extract the read selected by a primer or primer pair. Only sequences
which match the primers at greater than the specified identity are returned
Parameters
----------
sequences : DNASequencesDirectoryFormat
An aligned list of skbio.sequence.DNA query sequences
f_primer : skbio.sequence.DNA
Forward primer sequence
r_primer : skbio.sequence.DNA
Reverse primer sequence
trunc_len : int, optional
Read is cut to trunc_len if trunc_len is positive. Applied before
trim_left.
trim_left : int, optional
`trim_left` nucleotides are removed from the 5' end if trim_left is
positive. Applied after trunc_len.
identity : float, optional
Minimum combined primer match identity threshold. Default: 0.8
min_length: int, optional
Minimum amplicon length. Shorter amplicons are discarded. Default: 50
max_length: int, optional
Maximum amplicon length. Longer amplicons are discarded.
n_jobs: int, optional
Number of seperate processes to break the task into.
batch_size: int, optional
Number of samples to be processed in one batch.
Returns
-------
q2_types.DNAFASTAFormat
containing the reads
"""
if min_length > trunc_len - trim_left and trunc_len > 0:
raise ValueError('The minimum length setting is greater than the '
'length of the truncated sequences. This will cause '
'all sequences to be removed from the dataset. To '
'proceed, set a min_length ≤ trunc_len - trim_left.')
n_jobs = effective_n_jobs(n_jobs)
if batch_size == 'auto':
batch_size = _autotune_reads_per_batch(
sequences.file.view(DNAFASTAFormat), n_jobs)
sequences = sequences.file.view(DNAIterator)
ff = DNAFASTAFormat()
with open(str(ff), 'a') as fh:
with Parallel(n_jobs) as parallel:
for chunk in _chunks(sequences, batch_size):
amplicons = parallel(delayed(_gen_reads)(sequence, f_primer,
r_primer, trunc_len,
trim_left, identity,
min_length,
max_length)
for sequence in chunk)
for amplicon in amplicons:
if amplicon is not None:
skbio.write(amplicon, format='fasta', into=fh)
if os.stat(str(ff)).st_size == 0:
raise RuntimeError("No matches found")
return ff
def test_autotune_reads_per_batch_zero_jobs(self):
with self.assertRaisesRegex(
ValueError, "Value other than zero must be specified"):
_autotune_reads_per_batch(self.seq_path, n_jobs=0)
def test_autotune_reads_per_batch_ceil(self):
self.assertEqual(
_autotune_reads_per_batch(self.seq_path, n_jobs=5), 221)
def test_autotune_reads_per_batch(self):
self.assertEqual(
_autotune_reads_per_batch(self.seq_path, n_jobs=4), 276)
def test_autotune_reads_per_batch_disable_if_single_job(self):
self.assertEqual(
_autotune_reads_per_batch(self.seq_path, n_jobs=1), 500000)
def test_autotune_reads_per_batch_more_jobs_than_reads(self):
self.assertEqual(
_autotune_reads_per_batch(self.seq_path, n_jobs=1105), 1)
def test_autotune_reads_per_batch_ceil(self):
self.assertEqual(
_autotune_reads_per_batch(self.seq_path, n_jobs=5), 221)
def test_autotune_reads_per_batch_zero_jobs(self):
with self.assertRaisesRegex(
ValueError, "Value other than zero must be specified"):
_autotune_reads_per_batch(self.seq_path, n_jobs=0)
def test_autotune_reads_per_batch_disable_if_single_job(self):
self.assertEqual(
_autotune_reads_per_batch(self.seq_path, n_jobs=1), 20000)
def test_autotune_reads_per_batch(self):
self.assertEqual(
_autotune_reads_per_batch(self.seq_path, n_jobs=4), 276)
