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Fix backtesting - refactor remove training from dataframe

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This commit is contained in:
Wagner Costa Santos
2022-09-19 14:31:05 -03:00
parent 8b1e5daf22
commit 1facde2f8b
2 changed files with 16 additions and 6 deletions
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12
freqtrade/data/dataprovider.py
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@@ -90,8 +90,12 @@ class DataProvider:
if saved_pair not in self.__cached_pairs_backtesting:
timerange = TimeRange.parse_timerange(None if self._config.get(
'timerange') is None else str(self._config.get('timerange')))
# In backtesting, the training data was already add
add_train_candles = self.runmode in (RunMode.DRY_RUN, RunMode.LIVE)
startup_candles = self.get_required_startup(str(timeframe), add_train_candles)
# Move informative start time respecting startup_candle_count
startup_candles = self.get_required_startup(str(timeframe))
tf_seconds = timeframe_to_seconds(str(timeframe))
timerange.subtract_start(tf_seconds * startup_candles)
self.__cached_pairs_backtesting[saved_pair] = load_pair_history(
@@ -105,7 +109,7 @@ class DataProvider:
)
return self.__cached_pairs_backtesting[saved_pair].copy()
def get_required_startup(self, timeframe: str) -> int:
def get_required_startup(self, timeframe: str, add_train_candles: bool = True) -> int:
freqai_config = self._config.get('freqai', {})
if not freqai_config.get('enabled', False):
return self._config.get('startup_candle_count', 0)
@@ -115,7 +119,9 @@ class DataProvider:
# make sure the startupcandles is at least the set maximum indicator periods
self._config['startup_candle_count'] = max(startup_candles, max(indicator_periods))
tf_seconds = timeframe_to_seconds(timeframe)
train_candles = freqai_config['train_period_days'] * 86400 / tf_seconds
train_candles = 0
if add_train_candles:
train_candles = freqai_config['train_period_days'] * 86400 / tf_seconds
total_candles = int(self._config['startup_candle_count'] + train_candles)
logger.info(f'Increasing startup_candle_count for freqai to {total_candles}')
return total_candles