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
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
def setUpClass(cls):
"""Test multivariate data construction"""
cls._data = data.load('cars')
oss = cls._data.AirConditioning.sample_space.as_ordinal()
oss.ordered = ['little_important', 'important', 'very_important']
cls._data.AirConditioning.sample_space = oss
cls._data.Sex.sample_space.reference = 'women'
cls._data.Age.sample_space.reference = '18_23'
def setUpClass(cls):
"""Test multivariate data construction"""
cls._data = data.load('cars')
oss = cls._data.AirConditioning.sample_space.as_ordinal()
oss.ordered = ['little_important', 'important', 'very_important']
cls._data.AirConditioning.sample_space = oss
cls._data.Sex.sample_space.reference = 'women'
cls._data.Age.sample_space.reference = '18_23'
def setUpClass(cls):
"""Test Binomial regression construction"""
# cls.predictor_init()
# cls._canonical_model = glm.BinomialRegression(cls._kappa, cls._pred, cls._canonical_link)
cls._data = data.load('crabs')
for index, event in enumerate(cls._data.Satellites.events):
if event.value > 0:
cls._data.Satellites.events[index] = core.DiscreteElementaryEvent(1)
def setUpClass(cls):
"""Test Binomial regression construction"""
# cls.predictor_init()
# cls._canonical_model = glm.BinomialRegression(cls._kappa, cls._pred, cls._canonical_link)
cls._data = data.load('crabs')
for index, event in enumerate(cls._data.Satellites.events):
if event.value > 0:
cls._data.Satellites.events[
index] = core.DiscreteElementaryEvent(1)
def setUpClass(cls):
"""Test Poisson regression construction"""
#cls.predictor_init()
#cls._canonical_model = glm.PoissonRegression(cls._pred, cls._canonical_link)
cls._data = data.load('crabs')
def setUpClass(cls):
"""Test multivariate data construction"""
cls._data = data.load('retinopathy')
def setUpClass(cls):
"""Test multivariate data construction"""
cls._data = data.load('retinopathy')
def setUpClass(cls):
"""Test multivariate data construction"""
cls._data = data.load('travel')
cls._data.TravelMode.sample_space.reference = "car"
def setUpClass(cls):
"""Test Multinomial splitting regression construction"""
cls._data = data.load('KN03')
def setUpClass(cls):
"""Test multivariate data construction"""
cls._data = data.load('cars')
cls._data.AirConditioning.sample_space.reference = 'little_important'
cls._data.Sex.sample_space.reference = 'women'
cls._data.Age.sample_space.reference = '18_23'
def setUpClass(cls):
"""Test multivariate data construction"""
cls._data = data.load('beetles')
cls._data.data.State.sample_space.reference = 'alive'
def setUpClass(cls):
"""Test multivariate data construction"""
cls._data = data.load('travel')
cls._data.TravelMode.sample_space.reference = "car"
def setUpClass(cls):
"""Test multivariate data construction"""
cls._data = data.load('cars')
cls._data.AirConditioning.sample_space.reference = 'little_important'
cls._data.Sex.sample_space.reference = 'women'
cls._data.Age.sample_space.reference = '18_23'
def setUpClass(cls):
"""Test multivariate data construction"""
cls._data = data.load('beetles')
cls._data.data.State.sample_space.reference = 'alive'
def setUpClass(cls):
"""Test Poisson regression construction"""
#cls.predictor_init()
#cls._canonical_model = glm.PoissonRegression(cls._pred, cls._canonical_link)
cls._data = data.load('crabs')
def setUpClass(cls):
"""Test Multinomial splitting regression construction"""
cls._data = data.load('KN03')