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.num_schemas = 2
schema_ga = Schema.GeneticAlgorithmFinder()
schema_ga.min_generations = 1
self.finder = Schema.SchemaFinder(num_schemas=self.num_schemas,
schema_finder=schema_ga)
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')
records.extend(
SeqIO.parse(handle, "fasta", alphabet=IUPAC.unambiguous_dna))
handle.close()
self.num_schemas = 2
schema_ga = Schema.GeneticAlgorithmFinder()
schema_ga.min_generations = 1
self.finder = Schema.SchemaFinder(num_schemas=self.num_schemas,
schema_finder=schema_ga)
