def test_imbalance_dollar_bars_add_features(self):
"""
Tests the additional features functionality with dollar imbalance bars.
"""
# Arrange
exp_num_ticks_init = 1000
num_prev_bars = 3
high_over_low = BarFeature(
name='high_over_low',
function=lambda df: df['Price'].max() / df['Price'].min())
low_over_high = BarFeature(
name='low_over_high',
function=lambda df: df['Price'].min() / df['Price'].max())
# Act
bars = ds.get_dollar_imbalance_bars(
self.path,
exp_num_ticks_init=exp_num_ticks_init,
num_prev_bars=num_prev_bars,
batch_size=1000,
verbose=False,
additional_features=[high_over_low, low_over_high])
# Assert
self.assertTrue(
np.all(bars['high_over_low'] == bars['high'] / bars['low']))
self.assertTrue(
np.all(bars['low_over_high'] == bars['low'] / bars['high']))
def test_dollar_bars_add_features(self):
"""
Tests the additional features functionality with dollar bars.
"""
# Arrange
threshold = 100000
high_over_low = BarFeature(
name='high_over_low',
function=lambda df: df['Price'].max() / df['Price'].min()
)
low_over_high = BarFeature(
name='low_over_high',
function=lambda df: df['Price'].min() / df['Price'].max()
)
# Act
bars = ds.get_dollar_bars(self.path, threshold=threshold, batch_size=1000, verbose=False,
additional_features=[high_over_low, low_over_high])
# Assert
self.assertTrue(np.all(bars['high_over_low'] == bars['high'] / bars['low']))
self.assertTrue(np.all(bars['low_over_high'] == bars['low'] / bars['high']))