class EnumCurveModelTest(test_util.PWLFitTest, parameterized.TestCase):
def test_simple_properties(self):
model = model_util.EnumCurveModel('x', {1: 1.5, 2: 2.5})
self.assertEqual('x', model.feature_name)
self.assertEqual('f_x', model.name)
self.assertEqual('f_x', model.clean_name)
@parameterized.named_parameters((
'not too sensitive',
model_util.EnumCurveModel('x', {
1: 1,
2: 2
}),
model_util.EnumCurveModel('x', {
1: 1.0,
2: 2.0
}),
True,
), (
'not a EnumCurveModel',
model_util.EnumCurveModel('x', {
1: 1.0,
2: 2.0
}),
's',
False,
), (
'different mappings',
model_util.EnumCurveModel('x', {
1: 1.0,
2: 2.0
}),
model_util.EnumCurveModel('x', {
1: 1.5,
2: 2.5
}),
False,
))
def test_eq(self, m1, m2, expected):
self.assertEqual(expected, m1 == m2)
def test_eval(self):
model = model_util.EnumCurveModel('x', {1: 1.5, 2: 2.5})
self.assert_allclose(
np.array([1.5, 1.5, 2.5, 2.5]), model.eval([1, 1, 2, 2]))
self.assert_allclose(
np.array([1.5, 1.5, 2.5, 2.5]),
model.eval(pd.DataFrame({'x': [1, 1, 2, 2]})))
def test_expr(self):
model = model_util.EnumCurveModel('x', {1: 1.5, 2: 2.5})
self.assertEqual('EnumCurve("x", {1: 1.5, 2: 2.5})', model.expr())
@parameterized.named_parameters(
('simple', 'EnumCurve("x", {1: 1.5, 2: 2.5})'),
('extra spaces', 'EnumCurve( "x" , {1: 1.5, 2: 2.5})'))
def test_from_expr(self, s):
model = model_util.EnumCurveModel('x', {1: 1.5, 2: 2.5})
self.assertEqual(model, model_util.EnumCurveModel.from_expr(s))
def test_eval(self):
model = model_util.EnumCurveModel('x', {1: 1.5, 2: 2.5})
self.assert_allclose(
np.array([1.5, 1.5, 2.5, 2.5]), model.eval([1, 1, 2, 2]))
self.assert_allclose(
np.array([1.5, 1.5, 2.5, 2.5]),
model.eval(pd.DataFrame({'x': [1, 1, 2, 2]})))
def test_from_expr(self, expr):
model = model_util.AdditiveModel([
model_util.PWLCurveModel('x1', [(1, 1), (2, 2)]),
model_util.EnumCurveModel('x2', {
1: 1,
2: 2
}),
model_util.ColumnModel('x3')
], 'my_model')
self.assertEqual(model,
model_util.AdditiveModel.from_expr(expr, 'my_model'))
def test_eval(self):
model = model_util.AdditiveModel([
model_util.PWLCurveModel('x1', [(1, 1), (2, 2)]),
model_util.EnumCurveModel('x2', {
1: 10,
2: 20
}),
model_util.ColumnModel('x3')
], 'my_model')
df = pd.DataFrame({'x1': [1, 1, 2], 'x2': [1, 1, 2], 'x3': [3, 3, 3]})
self.assert_allclose(np.array([14, 14, 25]), model.eval(df))
def test_simple_properties(self):
model = model_util.AdditiveModel([
model_util.PWLCurveModel('x1', [(1, 1), (2, 2)]),
model_util.EnumCurveModel('x2', {
1: 1,
2: 2
}),
model_util.ColumnModel('x3')
], 'my_model')
self.assertEqual('my_model', model.name)
self.assertEqual(['x1', 'x2', 'x3'], model.feature_names)
def test_expr(self):
model = model_util.AdditiveModel([
model_util.PWLCurveModel('x1', [(1, 1), (2, 2)]),
model_util.EnumCurveModel('x2', {
1: 1,
2: 2
}),
model_util.ColumnModel('x3')
], 'my_model')
expr = """score = sum([
PWLCurve("x1", [(1, 1), (2, 2)]),
EnumCurve("x2", {1: 1, 2: 2}),
Column("x3"),
])"""
self.assertEqual(expr, model.expr())
def test_from_expr(self, s):
model = model_util.EnumCurveModel('x', {1: 1.5, 2: 2.5})
self.assertEqual(model, model_util.EnumCurveModel.from_expr(s))
def test_expr(self):
model = model_util.EnumCurveModel('x', {1: 1.5, 2: 2.5})
self.assertEqual('EnumCurve("x", {1: 1.5, 2: 2.5})', model.expr())
def test_simple_properties(self):
model = model_util.EnumCurveModel('x', {1: 1.5, 2: 2.5})
self.assertEqual('x', model.feature_name)
self.assertEqual('f_x', model.name)
self.assertEqual('f_x', model.clean_name)