class TestHierarchicalSampleSpace(unittest.TestCase):
_sample_space1 = core.OrdinalSampleSpace('C', 'B', 'A')
_sample_space2 = core.NominalSampleSpace('Ba', 'Bb', 'Bc')
_sample_space3 = core.NominalSampleSpace('Bca', 'Bcb')
@classmethod
def setUpClass(cls):
"""Test hierarchical sample space construction"""
cls._space = core.HierarchicalSampleSpace(cls._sample_space1)
def test_partition(self):
"""Test hierarchical sample space partition"""
self.assertEqual(
self._space.values,
['A', 'B', 'C']) # list of (lexicographically ordered) values
self._space.partition('B', self._sample_space2)
self.assertEqual(
self._space.values,
['A', 'Ba', 'Bb', 'Bc', 'C'
]) # list of (lexicographically ordered) values after partition
self._space.partition('Bc', self._sample_space3)
self.assertEqual(
self._space.values,
['A', 'Ba', 'Bb', 'Bca', 'Bcb', 'C'
]) # list of (lexicographically ordered) values after partition
@classmethod
def tearDownClass(cls):
"""Test hierarchical sample space deletion"""
del cls._space
def setUpClass(cls):
"""Test multivariate data construction"""
cls._data_ordinal = data.load('retinopathy')
cls._data_hierarchical = data.load('retinopathy')
sample_spaces = []
ss1 = core.NominalSampleSpace(['0', '12'])
ss2 = core.NominalSampleSpace(['1', '2'])
hss = core.HierarchicalSampleSpace(ss1)
hss.partition('12', ss2)
sample_spaces.append(hss)
sample_spaces.append(core.controls.ZZ)
for i in [0, 1, 2]:
sample_spaces.append(core.controls.RR)
cls._data_hierarchical.RET.sample_space = hss
class TestHierarchical(unittest.TestCase, AbstractTestUnivariateDistribution):
_ordinal_space = core.OrdinalSampleSpace('C', 'B', 'A')
_nominal_space = core.NominalSampleSpace('Ba', 'Bb', 'Bc')
_hierarchical_space = core.HierarchicalSampleSpace(_ordinal_space)
_hierarchical_space.partition('B', _nominal_space)
_places = 10
@classmethod
def setUpClass(cls):
"""Test hierarchical distribution construction"""
cls._dist = core.HierarchicalDistribution(cls._hierarchical_space)
def test_internal_ldf(self):
"""Test internal log pdf of hierarchical distribution"""
self.assertAlmostEqual(self._dist.pdf('C'),
float(1 / 3),
places=self._places)
self.assertAlmostEqual(self._dist.pdf('Ba'),
float(1 / 9),
places=self._places)
self.assertAlmostEqual(self._dist.internal_pdf('B'),
float(1 / 3),
places=self._places)
@classmethod
def tearDownClass(cls):
"""Test hierarchical distribution deletion"""
del cls._dist
def setUpClass(cls):
"""Test reference regression construction"""
cls.predictor_init()
nss = core.NominalSampleSpace(*cls._categories)
cls._model = glm.NominalRegression(nss, cls._pred, cls._canonical_link)
def hierarchical_sample_space_init(cls):
ordinal_space = core.OrdinalSampleSpace(*cls._categories_root)
nominal_space = core.NominalSampleSpace(*cls._categories_B)
cls._hss = core.HierarchicalSampleSpace(ordinal_space)
cls._hss.partition('B', nominal_space)
def setUpClass(cls):
"""Test nominal sample space construction"""
cls._space = core.NominalSampleSpace('C', 'B', 'A')