def test_transform_registered(self): algo = TestRegisterTransformAlgorithm(sids=[133]) algo.run(self.source) assert "mavg" in algo.registered_transforms assert algo.registered_transforms["mavg"]["args"] == (["price"],) assert algo.registered_transforms["mavg"]["kwargs"] == {"window_length": 2, "market_aware": True} assert algo.registered_transforms["mavg"]["class"] is MovingAverage
def test_df_as_input(self): algo = TestRegisterTransformAlgorithm( self.sim_params, sids=[0, 1] ) algo.run(self.df) assert isinstance(algo.sources[0], DataFrameSource)
def test_multi_source_as_input_no_start_end(self): algo = TestRegisterTransformAlgorithm( sids=[133] ) with self.assertRaises(AssertionError): algo.run([self.source, self.df_source])
def test_run_twice(self): algo = TestRegisterTransformAlgorithm(sim_params=self.sim_params, sids=[0, 1]) res1 = algo.run(self.df) res2 = algo.run(self.df) np.testing.assert_array_equal(res1, res2)
def test_transform_registered(self): algo = TestRegisterTransformAlgorithm(sids=[133]) algo.run(self.source) assert 'mavg' in algo.registered_transforms assert algo.registered_transforms['mavg']['args'] == (['price'], ) assert algo.registered_transforms['mavg']['kwargs'] == \ {'window_length': 2, 'market_aware': True} assert algo.registered_transforms['mavg']['class'] is MovingAverage
def test_source_as_input(self): algo = TestRegisterTransformAlgorithm( self.sim_params, sids=[133] ) algo.run(self.source) self.assertEqual(len(algo.sources), 1) assert isinstance(algo.sources[0], SpecificEquityTrades)
def test_transform_registered(self): algo = TestRegisterTransformAlgorithm(sids=[133]) algo.run(self.source) assert 'mavg' in algo.registered_transforms assert algo.registered_transforms['mavg']['args'] == (['price'],) assert algo.registered_transforms['mavg']['kwargs'] == \ {'window_length': 2, 'market_aware': True} assert algo.registered_transforms['mavg']['class'] is MovingAverage
def test_source_as_input(self): algo = TestRegisterTransformAlgorithm( sim_params=self.sim_params, sids=[133] ) algo.run(self.source) self.assertEqual(len(algo.sources), 1) assert isinstance(algo.sources[0], SpecificEquityTrades)
def test_data_frequency_setting(self): self.sim_params.data_frequency = 'daily' algo = TestRegisterTransformAlgorithm(sim_params=self.sim_params, ) self.assertEqual(algo.sim_params.data_frequency, 'daily') self.sim_params.data_frequency = 'minute' algo = TestRegisterTransformAlgorithm(sim_params=self.sim_params, ) self.assertEqual(algo.sim_params.data_frequency, 'minute')
def test_multi_source_as_input(self): sim_params = SimulationParameters( self.df.index[0], self.df.index[-1] ) algo = TestRegisterTransformAlgorithm( sim_params=sim_params, sids=[0, 1, 133] ) algo.run([self.source, self.df_source]) self.assertEqual(len(algo.sources), 2)
def test_data_frequency_setting(self): algo = TestRegisterTransformAlgorithm(self.sim_params, data_frequency='daily') self.assertEqual(algo.data_frequency, 'daily') self.assertEqual(algo.annualizer, 250) algo = TestRegisterTransformAlgorithm(self.sim_params, data_frequency='minute') self.assertEqual(algo.data_frequency, 'minute') self.assertEqual(algo.annualizer, 250 * 6 * 60) algo = TestRegisterTransformAlgorithm(self.sim_params, data_frequency='minute', annualizer=10) self.assertEqual(algo.data_frequency, 'minute') self.assertEqual(algo.annualizer, 10)
def test_multi_source_as_input(self): algo = TestRegisterTransformAlgorithm(sids=[0, 1, 133]) algo.run([self.source, self.df_source], start=self.df.index[0], end=self.df.index[-1]) self.assertEqual(len(algo.sources), 2)
def test_panel_as_input(self): algo = TestRegisterTransformAlgorithm(sim_params=self.sim_params, sids=[0, 1]) algo.run(self.panel) assert isinstance(algo.sources[0], DataPanelSource)
def test_panel_as_input(self): algo = TestRegisterTransformAlgorithm( sim_params=self.sim_params, sids=[0, 1]) algo.run(self.panel) assert isinstance(algo.sources[0], DataPanelSource)
def test_df_as_input(self): algo = TestRegisterTransformAlgorithm(self.sim_params, sids=[0, 1]) algo.run(self.df) assert isinstance(algo.sources[0], DataFrameSource)
def test_multi_source_as_input_no_start_end(self): algo = TestRegisterTransformAlgorithm(self.sim_params, sids=[133]) with self.assertRaises(AssertionError): algo.run([self.source, self.df_source])