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_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_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_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])
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)
