def test_regression():
"""Check regression"""
simulated_market_data = simulated_market_data_4_years_gen()
simulated_market_data["signal"] = simulated_market_data["close"].shift(-1)
price_prediction_from_signal = PricePredictionFromSignalRegression()
out = price_prediction_from_signal.fit_transform(simulated_market_data)
assert isinstance(out, pd.DataFrame)
def test_pipeline_signal_to_position():
"""Checks we can use a signal in conjunction with a rule to calculate a position."""
signal_to_positions = make_pipeline(
scikit_signal_factory(normalised_close,), PricePredictionFromSignalRegression(), PositionsFromPricePrediction()
)
df = signal_to_positions.fit_transform(simulated_market_data_4_years_gen())
assert isinstance(df, pd.DataFrame)
def test_readme_example_four():
"""Get price prediction and positions from an external signal transformer"""
adapted_aroon = ta_adaptor(AroonIndicator, "aroon_down", window=1)
pipeline = make_pipeline(
scikit_signal_factory(adapted_aroon), PricePredictionFromSignalRegression(), PositionsFromPricePrediction()
)
pipeline.fit_transform(simulated_market_data_4_years_gen())
def test_readme_example_three():
"""Get price prediction and positions from a signal transformer"""
pipeline = make_pipeline(
scikit_signal_factory(normalised_close), PricePredictionFromSignalRegression(), PositionsFromPricePrediction()
)
pipeline.fit_transform(simulated_market_data_4_years_gen())