def test_incremental_difference(self, data_frame, exchange):
transformer = FractionalDifference(difference_order=0.5, inplace=True)
transformed_frame = transformer.transform(data_frame,
exchange.generated_space)
expected_data_frame = pd.DataFrame([{
'open': -26.20469322,
'low': -46.15180724,
'high': 33.63664884,
'close': 13.68953482,
}, {
'open': 134.53651465,
'low': 118.24976426,
'high': 183.39676584,
'close': 167.11001545,
}])
assert np.allclose(expected_data_frame.values,
transformed_frame.values)
next_frame = pd.DataFrame([{
'open': 200,
'low': 150,
'high': 350,
'close': 300,
}, {
'open': 300,
'low': 250,
'high': 450,
'close': 400,
}])
transformed_frame = transformer.transform(next_frame,
exchange.generated_space)
expected_data_frame = pd.DataFrame([{
'open': 127.785105,
'low': 87.031409,
'high': 250.046192,
'close': 209.292496,
}, {
'open': 185.484853,
'low': 166.817514,
'high': 241.486873,
'close': 222.819533,
}])
assert np.allclose(expected_data_frame.values,
transformed_frame.values)
def test_difference_not_inplace(self, data_frame, exchange):
transformer = FractionalDifference(difference_order=0.5, inplace=False)
transformed_frame = transformer.transform(data_frame,
exchange.generated_space)
expected_data_frame = pd.DataFrame([{
'open': 100,
'low': 50,
'high': 250,
'close': 200,
'open_diff_0.5': -26.20469322,
'low_diff_0.5': -46.15180724,
'high_diff_0.5': 33.63664884,
'close_diff_0.5': 13.68953482,
}, {
'open': 200,
'low': 150,
'high': 350,
'close': 300,
'open_diff_0.5': 134.53651465,
'low_diff_0.5': 118.24976426,
'high_diff_0.5': 183.39676584,
'close_diff_0.5': 167.11001545,
}])
assert np.allclose(expected_data_frame.values,
transformed_frame.values)
def test_incremental_difference_inplace_false(self, data_frame,
reference_frame):
frame_tail = data_frame.tail(200)
transformer = FractionalDifference(difference_order=0.5, inplace=False)
transformed_frame = transformer.transform(frame_tail)
assert transformed_frame is not None
assert isinstance(frame_tail, pd.DataFrame)
def test_incremental_difference(self, data_frame, reference_frame):
frame_tail = data_frame.tail(200)
transformer = FractionalDifference(difference_order=0.5, inplace=True)
significant = 3
transformed_frame = transformer.transform(frame_tail)
reference_frame = reference_frame.round(significant)
transformed_frame = transformed_frame.round(significant)
close_1 = transformed_frame.Close.values
close_2 = reference_frame.Close.values
is_valid = (close_1 == close_2).all()
assert transformed_frame is not None
assert is_valid
def test_select_correct_columns(self, data_frame, exchange):
transformer = FractionalDifference(
columns=['open', 'close'], difference_order=0.5, inplace=True)
transformed_frame = transformer.transform(data_frame, exchange.generated_space)
expected_data_frame = pd.DataFrame([{
'open': -26.20469322,
'low': 50,
'high': 250,
'close': 13.68953482,
},
{
'open': 134.53651465,
'low': 150,
'high': 350,
'close': 167.11001545,
}])
assert np.allclose(expected_data_frame.values, transformed_frame.values)
def test_difference_inplace(self, data_frame):
transformer = FractionalDifference(
difference_order=0.5, inplace=True, all_column_names=data_frame.columns)
transformed_frame = transformer.transform(data_frame)
expected_data_frame = pd.DataFrame([{
'open': -26.20469322,
'low': -46.15180724,
'high': 33.63664884,
'close': 13.68953482,
},
{
'open': 134.53651465,
'low': 118.24976426,
'high': 183.39676584,
'close': 167.11001545,
}])
assert np.allclose(expected_data_frame.values, transformed_frame.values)
