def test_normalize_categorical():
categories = ["cat", "dog", "rat"]
a = Categorical(categories, transform="normalize")
for i in range(len(categories)):
assert a.rvs(random_state=i)[0] in categories
assert a.inverse_transform([0.0]) == [categories[0]]
assert a.inverse_transform([0.5]) == [categories[1]]
assert a.inverse_transform([1.0]) == [categories[2]]
assert_array_equal(categories, a.inverse_transform([0.0, 0.5, 1]))
categories = [1, 2, 3]
a = Categorical(categories, transform="normalize")
assert_array_equal(categories,
np.sort(np.unique(a.rvs(100, random_state=1))))
assert_array_equal(categories, a.inverse_transform([0.0, 0.5, 1.0]))
categories = [1.0, 2.0, 3.0]
a = Categorical(categories, transform="normalize")
assert_array_equal(categories,
np.sort(np.unique(a.rvs(100, random_state=1))))
assert_array_equal(categories, a.inverse_transform([0.0, 0.5, 1.0]))
categories = [1, 2, 3]
a = Categorical(categories, transform="string")
a.set_transformer("normalize")
assert_array_equal(categories,
np.sort(np.unique(a.rvs(100, random_state=1))))
assert_array_equal(categories, a.inverse_transform([0.0, 0.5, 1.0]))
def test_categorical_identity():
categories = ["cat", "dog", "rat"]
cat = Categorical(categories, transform="identity")
samples = cat.rvs(100)
assert all([t in categories for t in cat.rvs(100)])
transformed = cat.transform(samples)
assert_array_equal(transformed, samples)
assert_array_equal(samples, cat.inverse_transform(transformed))
def test_categorical_string():
categories = [1, 2, 3]
categories_transformed = ["1", "2", "3"]
cat = Categorical(categories, transform="string")
samples = cat.rvs(100)
assert all([t in categories for t in cat.rvs(100)])
transformed = cat.transform(samples)
assert all([t in categories_transformed for t in transformed])
assert_array_equal(samples, cat.inverse_transform(transformed))
def check_categorical(vals, random_val):
x = Categorical(vals)
assert_equal(x, Categorical(vals))
assert x != Categorical(vals[:-1] + ("zzz", ))
assert_equal(x.rvs(random_state=1), random_val)