self._optuna_label_candles[pair] = 0
self.regressor: Regressor = self.freqai_info.get("regressor", REGRESSORS[0])
- if self.regressor not in REGRESSORS:
+ if self.regressor not in set(REGRESSORS):
self.regressor = REGRESSORS[0]
self.freqai_info["regressor"] = self.regressor
logger.info(
pivots_values.append(value)
pivots_directions.append(direction)
if len(pivots_values) > 1:
- prev_value = pivots_values[-2]
- if np.isclose(prev_value, 0.0):
+ prev_pivot_value = pivots_values[-2]
+ if np.isclose(prev_pivot_value, 0.0):
amplitude = np.nan
else:
- amplitude = abs(value - prev_value) / abs(prev_value)
+ amplitude = abs(value - prev_pivot_value) / abs(prev_pivot_value)
current_threshold = thresholds[pos]
if (
np.isfinite(current_threshold)