def testBasicWithCovar(self):
PhenoCovar.sex_as_covariate = False
pc = PhenoCovar()
load_pedigree(pc, self.ped)
pc.individual_mask = [0, 0, 0, 0, 0, 0, 1, 1]
pc.load_covarfile(self.header, names=["BMI", "MSA"])
pc.freeze_subjects()
pheno = [0.1, 0.4, 1.0, 0.5, 0.9, 1.0]
sex = [1, 1, 2, 1, 1, 1]
# First, test without sex as covariate
count = 0
for test in pc:
test_pheno, covars, nonmissing = test.get_variables()
self.assertEqual(6, numpy.sum(nonmissing))
self.assertEqual(2, len(covars))
for phenotype in self.phenotypes[0:2]:
self.assertEqual(self.phenotypes[0], list(covars[0]))
self.assertEqual(self.phenotypes[2], list(covars[1]))
self.assertEqual("BMI", test.get_covariate_name(0))
self.assertEqual("MSA", test.get_covariate_name(1))
self.assertEqual(6, len(pheno))
self.assertEqual("Pheno-1", test.get_phenotype_name())
for i in range(0, len(pheno)):
self.assertAlmostEqual(pheno[i], test_pheno[i])
count += 1
self.assertEqual(1, count)
PhenoCovar.sex_as_covariate = True
def testPhenoWithAllMissing(self):
pc = PhenoCovar()
count = 0
invalid = 0
missingness = 0
pc.add_subject("1:1", phenotype=1)
pc.add_subject("2:2", phenotype=1)
pc.add_subject("3:3", phenotype=1)
pc.add_subject("4:4", phenotype=1)
pc.freeze_subjects()
try:
for test in pc:
(pheno, covars, nonmissing) = test.get_variables(
numpy.array([True, True, True, True]))
count += 1
except InvariantVar as e:
invalid += 1
except TooMuchMissingpPhenoCovar as e:
missingness += 1
self.assertEqual(0, invalid)
self.assertEqual(1, missingness)
self.assertEqual(0, count)
