values = ["F", "M"]
var = data.DiscreteVariable(name="Feature 0", values=values)
self.assertEqual(var.to_val(0), 0)
self.assertEqual(var.to_val("F"), 0)
self.assertEqual(var.to_val(0.), 0)
self.assertTrue(math.isnan(var.to_val("?")))
# TODO: with self.assertRaises(ValueError): var.to_val(2)
with self.assertRaises(ValueError):
var.to_val("G")
PickleContinuousVariable = create_pickling_tests(
"PickleContinuousVariable",
("variable", lambda: data.ContinuousVariable()),
("with_name", lambda: data.ContinuousVariable(name="Feature 0")),
)
PickleDiscreteVariable = create_pickling_tests(
"PickleDiscreteVariable",
("variable", lambda: data.DiscreteVariable()),
("with_name", lambda: data.DiscreteVariable(name="Feature 0")),
("with_int_values",
lambda: data.DiscreteVariable(name="Feature 0", values=[1, 2, 3])),
("with_str_value",
lambda: data.DiscreteVariable(name="Feature 0", values=["F", "M"])),
("ordered", lambda: data.DiscreteVariable(
name="Feature 0", values=["F", "M"], ordered=True)),
("with_base_value", lambda: data.DiscreteVariable(
name="Feature 0", values=["F", "M"], base_value=0)),
race=DiscreteVariable(name="race",
values=["White", "Hypsanic", "African", "Other"]))
def map_vars(s):
return [vars[x] for x in s]
return Domain(*[map_vars(s) for s in ss])
PickleDomain = create_pickling_tests(
"PickleDomain",
("empty_domain", lambda: create_domain([])),
("with_continuous_variable", lambda: create_domain(["age"])),
("with_discrete_variable", lambda: create_domain(["gender"])),
("with_mixed_variables", lambda: create_domain(["age", "gender"])),
("with_continuous_class", lambda: create_domain(["age", "gender"], ["incomeA"])),
("with_discrete_class", lambda: create_domain(["age", "gender"], ["education"])),
("with_multiple_classes", lambda: create_domain(["age", "gender"],
["incomeA", "education"])),
("with_metas", lambda: create_domain(["age", "gender"], [], ["ssn"])),
("with_class_and_metas", lambda: create_domain(["age", "gender"],
["incomeA", "education"],
["ssn"])),
)
age, gender, incomeA, income, education, ssn, race = \
create_domain([], [],
["age", "gender", "incomeA", "income", "education", "ssn",
"race"]).metas
values = ["F", "M"]
var = data.DiscreteVariable(name="Feature 0", values=values)
self.assertEqual(var.to_val(0), 0)
self.assertEqual(var.to_val("F"), 0)
self.assertEqual(var.to_val(0.), 0)
self.assertTrue(math.isnan(var.to_val("?")))
# TODO: with self.assertRaises(ValueError): var.to_val(2)
with self.assertRaises(ValueError):
var.to_val("G")
PickleContinuousVariable = create_pickling_tests(
"PickleContinuousVariable",
("variable", lambda: data.ContinuousVariable()),
("with_name", lambda: data.ContinuousVariable(name="Feature 0")),
)
PickleDiscreteVariable = create_pickling_tests(
"PickleDiscreteVariable",
("variable", lambda: data.DiscreteVariable()),
("with_name", lambda: data.DiscreteVariable(name="Feature 0")),
("with_int_values", lambda: data.DiscreteVariable(name="Feature 0",
values=[1, 2, 3])),
("with_str_value", lambda: data.DiscreteVariable(name="Feature 0",
values=["F", "M"])),
("ordered", lambda: data.DiscreteVariable(name="Feature 0",
values=["F", "M"],
ordered=True)),
("with_base_value", lambda: data.DiscreteVariable(name="Feature 0",
values=["White", "Hypsanic", "African", "Other"]))
def map_vars(s):
return [vars[x] for x in s]
return Domain(*[map_vars(s) for s in ss])
PickleDomain = create_pickling_tests(
"PickleDomain",
("empty_domain", lambda: create_domain([])),
("with_continuous_variable", lambda: create_domain(["age"])),
("with_discrete_variable", lambda: create_domain(["gender"])),
("with_mixed_variables", lambda: create_domain(["age", "gender"])),
("with_continuous_class",
lambda: create_domain(["age", "gender"], ["incomeA"])),
("with_discrete_class",
lambda: create_domain(["age", "gender"], ["education"])),
("with_multiple_classes",
lambda: create_domain(["age", "gender"], ["incomeA", "education"])),
("with_metas", lambda: create_domain(["age", "gender"], [], ["ssn"])),
("with_class_and_metas", lambda: create_domain(
["age", "gender"], ["incomeA", "education"], ["ssn"])),
)
age, gender, incomeA, income, education, ssn, race = \
create_domain([], [],
["age", "gender", "incomeA", "income", "education", "ssn",
"race"]).metas
income = data.ContinuousVariable(name="income")
education = data.DiscreteVariable(name="education",
values=["GS", "HS", "C"])
ssn = data.StringVariable(name="SSN")
race = data.DiscreteVariable(name="race",
values=["White", "Hypsanic", "African", "Other"])
PickleDomain = create_pickling_tests(
"PickleDomain",
("empty_domain", lambda: data.Domain([])),
("with_continuous_variable", lambda: data.Domain([age])),
("with_discrete_variable", lambda: data.Domain([gender])),
("with_mixed_variables", lambda: data.Domain([age, gender])),
("with_continuous_class", lambda: data.Domain([age, gender],
[incomeA])),
("with_discrete_class", lambda: data.Domain([age, gender],
[education])),
("with_multiple_classes", lambda: data.Domain([age, gender],
[incomeA, education])),
("with_metas", lambda: data.Domain([age, gender], metas=[ssn])),
("with_class_and_metas", lambda: data.Domain([age, gender],
[incomeA, education],
[ssn])),
)
class TestDomainInit(unittest.TestCase):
def test_init_class(self):
attributes = (age, gender, income)
d = data.Domain(attributes, race)
self.assertEqual(d.variables, attributes + (race,))
