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)
