def test_dump(self):
s = 'ACGTACGTAGCAT'
bwt = BWT(s)
t = TemporaryFile()
bwt.dump(t)
t.seek(0)
bwt2 = BWT('', t)
t.close()
assert_array_equal(bwt.seq, bwt2.seq)
assert_array_equal(bwt.sa, bwt2.sa)
self.assertEqual(bwt.alphabet, bwt2.alphabet)
#Parse some arguments
parser = argparse.ArgumentParser()
parser.add_argument('command', help="Command [index, search]")
parser.add_argument('files', metavar='file', nargs='+', help='files to index/search (FASTA)')
parser.add_argument('--fastq', help='fastq file containing reads to map')
parser.add_argument('--fasta', help='fasta file containing reads to map')
parser.add_argument('--ed', type=int, help='maximum edit distance to search for')
args = parser.parse_args()
print args
#Index goes through all the input files and creats a FM-index and dumps it to a JSON file
if args.command == 'index':
for fasta in args.files:
bwt = BWT(SeqIO.read(fasta, 'fasta').seq.tostring())
with open(fasta + '.index', 'w') as out:
bwt.dump(out)
del bwt
#For the meat:
elif args.command == 'search':
#Pull all of our genomes into memory
indices = {}
#Try to grab existing indices, otherwise create them
for fasta in args.files:
try:
with open(fasta + '.index') as f:
indices[fasta] = BWT('', f)
except IOError:
indices[fasta] = BWT(SeqIO.read(fasta, 'fasta').seq.tostring())
#Check if reads are in fastq or fasta format, and in a file or from stdin
#Parse using BioPython
