Merge branch 'develop' into backtest_live_models
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@@ -68,6 +68,9 @@ class IFreqaiModel(ABC):
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if self.save_backtest_models:
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logger.info('Backtesting module configured to save all models.')
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self.dd = FreqaiDataDrawer(Path(self.full_path), self.config, self.follow_mode)
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# set current candle to arbitrary historical date
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self.current_candle: datetime = datetime.fromtimestamp(637887600, tz=timezone.utc)
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self.dd.current_candle = self.current_candle
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self.scanning = False
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self.ft_params = self.freqai_info["feature_parameters"]
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self.corr_pairlist: List[str] = self.ft_params.get("include_corr_pairlist", [])
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@@ -75,7 +78,7 @@ class IFreqaiModel(ABC):
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if self.keras and self.ft_params.get("DI_threshold", 0):
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self.ft_params["DI_threshold"] = 0
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logger.warning("DI threshold is not configured for Keras models yet. Deactivating.")
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self.CONV_WIDTH = self.freqai_info.get("conv_width", 2)
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self.CONV_WIDTH = self.freqai_info.get('conv_width', 1)
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if self.ft_params.get("inlier_metric_window", 0):
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self.CONV_WIDTH = self.ft_params.get("inlier_metric_window", 0) * 2
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self.pair_it = 0
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@@ -93,7 +96,6 @@ class IFreqaiModel(ABC):
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# get_corr_dataframes is controlling the caching of corr_dataframes
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# for improved performance. Careful with this boolean.
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self.get_corr_dataframes: bool = True
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self._threads: List[threading.Thread] = []
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self._stop_event = threading.Event()
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@@ -338,6 +340,7 @@ class IFreqaiModel(ABC):
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if self.dd.historic_data:
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self.dd.update_historic_data(strategy, dk)
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logger.debug(f'Updating historic data on pair {metadata["pair"]}')
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self.track_current_candle()
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if not self.follow_mode:
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@@ -682,8 +685,6 @@ class IFreqaiModel(ABC):
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" avoid blinding open trades and degrading performance.")
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self.pair_it = 0
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self.inference_time = 0
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if self.corr_pairlist:
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self.get_corr_dataframes = True
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return
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def train_timer(self, do: Literal['start', 'stop'] = 'start', pair: str = ''):
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@@ -759,12 +760,24 @@ class IFreqaiModel(ABC):
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"is included in the column names when you are creating features "
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"in `populate_any_indicators()`.")
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self.get_corr_dataframes = not bool(self.corr_dataframes)
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else:
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elif self.corr_dataframes:
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dataframe = dk.attach_corr_pair_columns(
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dataframe, self.corr_dataframes, dk.pair)
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return dataframe
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def track_current_candle(self):
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"""
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Checks if the latest candle appended by the datadrawer is
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equivalent to the latest candle seen by FreqAI. If not, it
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asks to refresh the cached corr_dfs, and resets the pair
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counter.
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"""
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if self.dd.current_candle > self.current_candle:
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self.get_corr_dataframes = True
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self.pair_it = 1
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self.current_candle = self.dd.current_candle
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def ensure_data_exists(self, dataframe_backtest: DataFrame,
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tr_backtest: TimeRange, pair: str) -> bool:
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"""
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