def test_encode_dataset(self):
data = pd.DataFrame(np.random.randn(3, 2), columns=["X1", "X2"])
data["Color"] = ["Red", "Blue", "Green"]
encoder = R.EffectEncoder("Color", ["Red", "Blue", "Green"])
enc = encoder.encode_dataset(data)
expected = np.array([[1.0, 0.0], [0.0, 1.0], [-1.0, -1.0]])
self.assertTrue(np.allclose(enc, expected))
def test_init(self):
encoder = R.EffectEncoder("Color", ["Red", "Blue", "Green"])
self.assertEqual(encoder._levels, ["Red", "Blue"])
self.assertEqual(encoder._baseline, "Green")
self.assertEqual(2, encoder.dim)
self.assertEqual(["Color.Red", "Color.Blue"],
encoder.encoded_variable_names)
encoder_rep = str(encoder)
self.assertEqual("EffectEncoder for Color", encoder_rep)
def test_encoding(self):
enc1 = R.EffectEncoder("Color", ["Red", "Blue"])
enc2 = R.IdentityEncoder("Height")
enc3 = R.InteractionEncoder(enc1, enc2)
encoder = R.DatasetEncoder([enc1, enc2, enc3])
sample_size = 1000
data = pd.DataFrame({
"Height":
np.random.randn(sample_size),
"Color":
np.random.choice(["Red", "Blue"], sample_size)
})
enc = encoder.encode_dataset(data)
self.assertEqual(sample_size, enc.shape[0])
self.assertEqual(4, enc.shape[1])
self.assertTrue(np.allclose(enc[:, 2], data.iloc[:, 0]))
def test_init(self):
enc1 = R.EffectEncoder("Color", ["Red", "Blue"])
enc2 = R.IdentityEncoder("Height")
enc3 = R.InteractionEncoder(enc1, enc2)
d = R.DatasetEncoder([enc1, enc2, enc3])
self.assertIsInstance(d, R.DatasetEncoder)
def test_new_level(self):
encoder = R.EffectEncoder("Color", ["Red", "Blue", "Green"])
enc = encoder.encode(["Red", "Blue", "Orange", np.NaN, 17, "Green"])
expected = np.array([[1.0, 0.0], [0.0, 1.0], [0.0, 0.0], [0.0, 0.0],
[0.0, 0.0], [-1.0, -1.0]])
self.assertTrue(np.allclose(enc, expected))
def test_encoding(self):
encoder = R.EffectEncoder("Color", ["Red", "Blue", "Green"])
x = ["Red", "Blue", "Green"]
enc = encoder.encode(x)
expected = np.array([[1.0, 0.0], [0.0, 1.0], [-1.0, -1.0]])
self.assertTrue(np.allclose(enc, expected))
