def action(args):
seqs = fastalite(args.fasta)
pairs = list(all_pairwise(seqs))
if args.distance:
pairs = [(q, t, 1 - i) for q, t, i in pairs]
if args.split_info and args.matrix_out:
primary, secondary = args.primary_group, args.secondary_group
split_info = list(csv.DictReader(args.split_info))
info = {r['seqname']: r for r in split_info if r['seqname']}
tax = {r['tax_id']:r for r in split_info}
pairs += map(itemgetter(1,0,2), pairs)
def group(seqname):
i = info[seqname]
return i[primary] or i[secondary] if secondary else i[primary]
pairs = ((group(left), group(right), score) for left,right,score in pairs)
# sort and group rows
pairs = list(groupbyl(pairs, key = itemgetter(0)))
matrix_out = csv.writer(args.matrix_out)
# this is the tax_id order we will be using for columns
tax_ids = map(itemgetter(0), pairs)
# get the species names to output as first row
matrix_out.writerow([''] + [tax[t]['tax_name'] for t in tax_ids])
# iterator through the sorted rows (pairs)
for row_id, columns in pairs:
# sort and group columns
columns = dict(groupbyl(columns, key = itemgetter(1)))
# get the species name
row = [tax[row_id]['tax_name']]
for t in tax_ids:
# if t not in columns that means there is only
# sequence representing the group
# therefore the median destance is 0
if t not in columns:
med = 0
else:
col = columns[t]
med = median(map(itemgetter(2), col))
# percent and round
med = math.ceil(med * 100) / 100
row.append(med)
matrix_out.writerow(row)
else:
writer = csv.writer(args.out)
writer.writerow(['query', 'target', 'identity'])
writer.writerows(pairs)
def test02(self):
with open(self.data('two.fasta')) as f:
seqs = list(sequtils.fastalite(f))
pairs = list(sequtils.all_pairwise(seqs))
self.assertEqual(len(pairs), (len(seqs) * (len(seqs) - 1)) / 2)
self.assertEqual(
[s.id for s in seqs], list(sequtils.names_from_pairs(pairs)))
