def test_runs():
dregion = (10,20)
i = [1 if dregion[0] <= x <= dregion[1] else 0 for x in range(100)]
assert runs(i, lambda x: x>0) == [dregion]
assert runs_gte(i, 1) == [dregion]
assert runs_gte(i, 1, 20) == []
assert runs_gte([], 1) == []
assert runs([], lambda x: True) == []
i = [0, 0, 0, 0, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 1, 1, 1]
ir = [(4,8), (14, 16)]
assert runs(i, lambda x: x > 0) == ir
assert runs_gte(i, 1) == ir
assert runs_gte_uint8(np.array(i, dtype=np.uint8), 1) == ir
i = [0] * 100
assert runs(i, lambda x: x > 0) == []
assert runs_gte(i, 1) == []
assert runs_gte_uint8(np.uint8(i),1) == []
i = [1] * 100
ir = [(0,99)]
assert runs(i, lambda x: x>0) == ir
assert runs_gte(i, 1) == ir
assert runs_gte_uint8(np.array(i, dtype=np.uint8), 1) == ir
def test_runs():
dregion = (10, 20)
i = [1 if dregion[0] <= x <= dregion[1] else 0 for x in range(100)]
assert runs(i, lambda x: x > 0) == [dregion]
assert runs_gte(i, 1) == [dregion]
assert runs_gte(i, 1, 20) == []
assert runs_gte([], 1) == []
assert runs([], lambda x: True) == []
i = [0, 0, 0, 0, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 1, 1, 1]
ir = [(4, 8), (14, 16)]
assert runs(i, lambda x: x > 0) == ir
assert runs_gte(i, 1) == ir
assert runs_gte_uint8(np.array(i, dtype=np.uint8), 1) == ir
i = [0] * 100
assert runs(i, lambda x: x > 0) == []
assert runs_gte(i, 1) == []
assert runs_gte_uint8(np.uint8(i), 1) == []
i = [1] * 100
ir = [(0, 99)]
assert runs(i, lambda x: x > 0) == ir
assert runs_gte(i, 1) == ir
assert runs_gte_uint8(np.array(i, dtype=np.uint8), 1) == ir
s = pyd.sgs.sgs_population(ped, seed_size=ms)
with smartopen('{}-{}.ibd.gz'.format(prefix, replicate)) as f:
trueibd = {}
for line in f:
fam, id1, id2, ibd_states = line.strip().split(None, 3)
trueibd[frozenset({id1,id2})] = np.array([int(x) for x in ibd_states.split()])
a = intervals_to_array(s[frozenset({ped['7'],ped['8']})][0], ped.chromosomes[0].nmark())
b = trueibd[frozenset({'7','8'})]
genos1 = zip(*ped['7'].genotypes[0])
genos2 = zip(*ped['8'].genotypes[0])
identical = [ibs(x,y) for x,y in zip(genos1, genos2)]
from pydigree.common import table, runs
for start, stop in runs(list(a), lambda x: x>0, ms):
print('Predicted segment: {}-{}'.format(start, stop))
print()
for start, stop in runs(list(b), lambda x: x>0, 2):
print('True IBD Segment: {}-{}'.format(start, stop))
correct_calls = a == b
print('Accuracy: {}'.format(correct_calls.sum() / float(correct_calls.shape[0])))
