def setUp(self):
test_file = os.path.join('NeuralNetwork', 'enolase.fasta')
diff_file = os.path.join('NeuralNetwork', 'repeat.fasta')
self.test_records = []
self.diff_records = []
# load the records
for file, records in ((test_file, self.test_records),
(diff_file, self.diff_records)):
handle = open(file, 'r')
iterator = SeqIO.parse(handle,
"fasta",
alphabet=IUPAC.unambiguous_dna)
while 1:
try:
seq_record = next(iterator)
except StopIteration:
break
if seq_record is None:
break
records.append(seq_record)
handle.close()
self.motif_finder = Motif.MotifFinder()
def _load_schema_repository(self):
"""Helper function to load a schema repository from a file.
This also caches a schema bank, to prevent having to do this
time consuming operation multiple times.
"""
# if we already have a cached repository, return it
if self.schema_bank is not None:
return self.schema_bank
# otherwise, we'll read in a new schema bank
# read in the all of the motif records
motif_handle = open(self.test_file, 'r')
seq_records = list(
SeqIO.parse(motif_handle, "fasta", alphabet=IUPAC.unambiguous_dna))
motif_handle.close()
# find motifs from the file
motif_finder = Motif.MotifFinder()
motif_size = 9
motif_bank = motif_finder.find(seq_records, motif_size)
schema_bank = self.factory.from_motifs(motif_bank, .1, 2)
# cache the repository
self.schema_bank = schema_bank
return schema_bank
def setUp(self):
test_file = os.path.join('NeuralNetwork', 'enolase.fasta')
diff_file = os.path.join('NeuralNetwork', 'repeat.fasta')
self.test_records = []
self.diff_records = []
# load the records
for file, records in ((test_file, self.test_records),
(diff_file, self.diff_records)):
handle = open(file, 'r')
seq_parser = Fasta.SequenceParser(alphabet=IUPAC.unambiguous_dna)
iterator = Fasta.Iterator(handle, seq_parser)
while 1:
seq_record = iterator.next()
if seq_record is None:
break
records.append(seq_record)
handle.close()
self.motif_finder = Motif.MotifFinder()