def test_subsample_paired_power_interval_error(self):
with self.assertRaises(ValueError):
subsample_paired_power(self.f,
self.meta,
cat='INT',
control_cats=['SEX', 'AGE'],
min_observations=2,
counts_interval=12,
min_counts=5,
max_counts=7)
def test_subsample_paired_power_multi_p(self):
def f(x):
return np.array([0.5, 0.5, 0.005])
cat = 'INT'
control_cats = ['SEX']
# Tests for the control cats
test_p, test_c = subsample_paired_power(f,
meta=self.meta,
cat=cat,
control_cats=control_cats,
counts_interval=1,
num_iter=10,
num_runs=2)
self.assertEqual(test_p.shape, (2, 4, 3))
def test_subsample_paired_power(self):
known_c = np.array([1, 2, 3, 4])
# Sets up the handling values
cat = 'INT'
control_cats = ['SEX']
# Tests for the control cats
test_p, test_c = subsample_paired_power(self.meta_f,
meta=self.meta,
cat=cat,
control_cats=control_cats,
counts_interval=1,
num_iter=10,
num_runs=2)
# Test the output shapes are sane
self.assertEqual(test_p.shape, (2, 4))
npt.assert_array_equal(known_c, test_c)
def test_subsample_paired_power_min_observations_error(self):
with self.assertRaises(ValueError):
subsample_paired_power(self.f,
self.meta,
cat=self.cat,
control_cats=self.control_cats)
