def test_calculate_ani_valid(test_fragment_matches):
# check ANI for *valid* test fragment matches
test_fragment_matches = test_fragment_matches[0:2]
ani = ra.calculate_ani(test_fragment_matches)
expected_ani = sum(
map(
lambda k: (k['alignment_length'] - k['no_non_identities']) / k[
'alignment_length'],
test_fragment_matches)) / len(test_fragment_matches)
assert ani == expected_ani
def test_calculate_ani_all(test_fragment_matches):
# check ANI over all test fragment matches
ani = ra.calculate_ani(test_fragment_matches)
valid_dna_fragment_matches = test_fragment_matches[0:2]
expected_ani = sum(
map(
lambda k: (k['alignment_length'] - k['no_non_identities']) / k[
'alignment_length'],
valid_dna_fragment_matches)) / len(valid_dna_fragment_matches)
assert ani == expected_ani
def test_calculate_ani_empty():
# check ANI for empty test fragment matches
ani = ra.calculate_ani([])
expected_ani = 0.0
assert ani == expected_ani
def test_calculate_ani_unvalid(test_fragment_matches):
# check ANI for *unvalid* test fragment matches
test_fragment_matches = test_fragment_matches[2:]
ani = ra.calculate_ani(test_fragment_matches)
expected_ani = 0.0
assert ani == expected_ani