def test_tick_rule_encoding(self):
"""
Test tick rule encoding function
"""
with self.assertRaises(ValueError):
encode_tick_rule_array([-1, 1, 0, 20000000])
encoded_tick_rule = encode_tick_rule_array([-1, 1, 0, 0])
self.assertEqual('bacc', encoded_tick_rule)
def _get_bar_features(self, date_time: pd.Timestamp,
list_bars: list) -> list:
"""
Calculate inter-bar features: lambdas, entropies, avg_tick_size, vwap
:param date_time: (pd.Timestamp) when bar was formed
:param list_bars: (list) of previously formed bars
:return: (list) of inter-bar features
"""
features = [date_time]
# Tick rule sum, avg tick size, VWAP
features.append(get_avg_tick_size(self.trade_size))
features.append(sum(self.tick_rule))
features.append(vwap(self.dollar_size, self.trade_size))
# Lambdas
features.extend(
get_trades_based_kyle_lambda(self.price_diff, self.trade_size,
self.tick_rule)) # Kyle lambda
features.extend(
get_trades_based_amihud_lambda(self.log_ret,
self.dollar_size)) # Amihud lambda
features.extend(
get_trades_based_hasbrouck_lambda(
self.log_ret, self.dollar_size,
self.tick_rule)) # Hasbrouck lambda
# Entropy features
encoded_tick_rule_message = encode_tick_rule_array(self.tick_rule)
features.append(get_shannon_entropy(encoded_tick_rule_message))
features.append(get_plug_in_entropy(encoded_tick_rule_message))
features.append(get_lempel_ziv_entropy(encoded_tick_rule_message))
features.append(get_konto_entropy(encoded_tick_rule_message))
if self.volume_encoding is not None:
message = encode_array(self.trade_size, self.volume_encoding)
features.append(get_shannon_entropy(message))
features.append(get_plug_in_entropy(message))
features.append(get_lempel_ziv_entropy(message))
features.append(get_konto_entropy(message))
if self.pct_encoding is not None:
message = encode_array(self.log_ret, self.pct_encoding)
features.append(get_shannon_entropy(message))
features.append(get_plug_in_entropy(message))
features.append(get_lempel_ziv_entropy(message))
features.append(get_konto_entropy(message))
list_bars.append(features)