merge develop into RL
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@@ -14,7 +14,7 @@ from numpy.typing import NDArray
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from pandas import DataFrame
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from freqtrade.configuration import TimeRange
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from freqtrade.constants import DATETIME_PRINT_FORMAT, Config
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from freqtrade.constants import Config
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from freqtrade.data.dataprovider import DataProvider
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from freqtrade.enums import RunMode
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from freqtrade.exceptions import OperationalException
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@@ -803,14 +803,8 @@ class IFreqaiModel(ABC):
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:return: if the data exists or not
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"""
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if self.config.get("freqai_backtest_live_models", False) and len(dataframe_backtest) == 0:
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tr_backtest_startts_str = datetime.fromtimestamp(
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tr_backtest.startts,
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tz=timezone.utc).strftime(DATETIME_PRINT_FORMAT)
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tr_backtest_stopts_str = datetime.fromtimestamp(
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tr_backtest.stopts,
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tz=timezone.utc).strftime(DATETIME_PRINT_FORMAT)
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logger.info(f"No data found for pair {pair} from {tr_backtest_startts_str} "
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f" from {tr_backtest_startts_str} to {tr_backtest_stopts_str}. "
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logger.info(f"No data found for pair {pair} from "
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f"from { tr_backtest.start_fmt} to {tr_backtest.stop_fmt}. "
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"Probably more than one training within the same candle period.")
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return False
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return True
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@@ -825,18 +819,11 @@ class IFreqaiModel(ABC):
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:param pair: the current pair
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:param total_trains: total trains (total number of slides for the sliding window)
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"""
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tr_train_startts_str = datetime.fromtimestamp(
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tr_train.startts,
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tz=timezone.utc).strftime(DATETIME_PRINT_FORMAT)
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tr_train_stopts_str = datetime.fromtimestamp(
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tr_train.stopts,
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tz=timezone.utc).strftime(DATETIME_PRINT_FORMAT)
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if not self.config.get("freqai_backtest_live_models", False):
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logger.info(
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f"Training {pair}, {self.pair_it}/{self.total_pairs} pairs"
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f" from {tr_train_startts_str} "
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f"to {tr_train_stopts_str}, {train_it}/{total_trains} "
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f" from {tr_train.start_fmt} "
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f"to {tr_train.stop_fmt}, {train_it}/{total_trains} "
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"trains"
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)
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# Following methods which are overridden by user made prediction models.
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