def test_joint_probability(self):
# One gene
people = hrd.load_data("data/family0.csv")
one_gene = {"Harry"}
two_genes = {"James"}
have_trait = {"James"}
self.assertAlmostEqual(
hrd.joint_probability(people, one_gene, two_genes, have_trait),
0.00266,
5,
)
# No genes
one_gene = {}
two_genes = {"James"}
have_trait = {"James"}
self.assertAlmostEqual(
hrd.joint_probability(people, one_gene, two_genes, have_trait),
0.000060546,
5,
)
# Two genes
one_gene = {}
two_genes = {"James", "Harry"}
have_trait = {"James"}
self.assertAlmostEqual(
hrd.joint_probability(people, one_gene, two_genes, have_trait),
0.000021405,
5,
)
def testJointProbability(self):
joint_prob_0 = hr.joint_probability(self.people_0, {"Harry"},
{"James"}, {"James"})
# Verified
self.assertEqual(joint_prob_0, 0.0026643247488)
joint_prob_1 = hr.joint_probability(self.people_1, {}, {}, {"Fred"})
self.assertEqual(joint_prob_1, 0.008764324299878399)
joint_prob_2 = hr.joint_probability(self.people_2, {}, {'Arthur'},
{'Arthur'})
self.assertEqual(joint_prob_2, 0.00022787243179683852)
def test_joint_probability(self):
people = {
'Lily': {
'name': 'Lily',
'mother': None,
'father': None,
'trait': False
},
'James': {
'name': 'James',
'mother': None,
'father': None,
'trait': True
},
'Harry': {
'name': 'Harry',
'mother': 'Lily',
'father': 'James',
'trait': None
}
}
one_gene = {"Harry"}
two_genes = {"James"}
have_trait = {"James"}
result = joint_probability(people, one_gene, two_genes, have_trait)
self.assertEqual(result, 0.0026643247488)
def test_joint_probability(self):
people = {
'Harry': {'name': 'Harry', 'mother': 'Lily', 'father': 'James', 'trait': None},
'James': {'name': 'James', 'mother': None, 'father': None, 'trait': True},
'Lily': {'name': 'Lily', 'mother': None, 'father': None, 'trait': False}
}
self.assertAlmostEqual(
joint_probability(people, {"Harry"}, {"James"}, {"James"}),
0.0026643247488,
places=5
)
def test_joint_probability():
assert heredity.joint_probability(people, {"Harry"}, {"James"},
{"James"}) == 0.0026643247488
Return a list of all possible subsets of set s.
"""
s = list(s)
return [
set(s) for s in itertools.chain.from_iterable(
itertools.combinations(s, r) for r in range(len(s) + 1))
]
people = load_data(sys.argv[1])
names = set(people)
print(people)
print(names)
print(powerset(names))
print(joint_probability(people, {"Harry"}, {"James"}, {"James"}))
# for have_trait in powerset(names):
# # Check if current set of people violates known information
# fails_evidence = any(
# (people[person]["trait"] is not None and
# people[person]["trait"] != (person in have_trait))
# for person in names
# )
# if fails_evidence:
# print('\n fails_evidence is True')
# print(have_trait)
# continue