def test_discard_incomplete(self): model_def = ModelDefinition(features=[F("a"), Map("b", np.abs)], target="y", discard_incomplete=False) x, y, ff, ft = generate_train(model_def, self.data) self.assertEqual(len(x), len(self.data)) # create incomplete cases self.data["a"][10] = None self.data["b"][11] = None self.data["b"][12] = None model_def = ModelDefinition(features=[F("a"), Map("b", np.abs)], target="y", discard_incomplete=True) x, y, ff, ft = generate_train(model_def, self.data) self.assertEqual(len(x), len(self.data) - 3)
def test_discard_incomplete(self): model_def = ModelDefinition(features=[F('a'), Map('b', np.abs)], target='y', discard_incomplete=False) x, y, ff, ft = generate_train(model_def, self.data) self.assertEqual(len(x), len(self.data)) # create incomplete cases self.data['a'][10] = None self.data['b'][11] = None self.data['b'][12] = None model_def = ModelDefinition(features=[F('a'), Map('b', np.abs)], target='y', discard_incomplete=True) x, y, ff, ft = generate_train(model_def, self.data) self.assertEqual(len(x), len(self.data) - 3)
def test_discard_incomplete(self): model_def = ModelDefinition(features=[F('a'), Map('b', np.abs)], target='y', discard_incomplete=False) self.assertEqual(model_def.filters, []) x, y, ff, ft = generate_train(model_def, self.data) self.assertEqual(len(x), len(self.data)) # create incomplete cases self.data['a'][10] = None self.data['b'][11] = None self.data['b'][12] = None model_def = ModelDefinition(features=[F('a'), Map('b', np.abs)], target='y', discard_incomplete=True) self.assertEqual(len(model_def.filters), 1) x, y, ff, ft = generate_train(model_def, self.data) self.assertEqual(len(x), len(self.data) - 3)
def test_generate_train(self): model_def = self.make_model_def_basic() train_index = self.data.index[:5] x_train, y_train, ff, x = generate_train(model_def, self.data, train_index=train_index) assert_almost_equal(x_train.index, train_index)