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Merge pull request #4979 from kamontat/patch-1

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Fix hyperopt trim to empty dataframe
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Matthias 2021-05-21 08:17:35 +02:00 committed by GitHub
commit d19b37c777
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2 changed files with 14 additions and 7 deletions
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5
freqtrade/optimize/backtesting.py
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@ -191,8 +191,9 @@ class Backtesting:
data: Dict = {} data: Dict = {}
# Create dict with data # Create dict with data
for pair, pair_data in processed.items(): for pair, pair_data in processed.items():
pair_data.loc[:, 'buy'] = 0 # cleanup from previous run if not pair_data.empty:
pair_data.loc[:, 'sell'] = 0 # cleanup from previous run pair_data.loc[:, 'buy'] = 0 # cleanup if buy_signal is exist
pair_data.loc[:, 'sell'] = 0 # cleanup if sell_signal is exist
df_analyzed = self.strategy.advise_sell( df_analyzed = self.strategy.advise_sell(
self.strategy.advise_buy(pair_data, {'pair': pair}), {'pair': pair})[headers].copy() self.strategy.advise_buy(pair_data, {'pair': pair}), {'pair': pair})[headers].copy()

16
freqtrade/optimize/hyperopt.py
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@ -349,19 +349,25 @@ class Hyperopt:
def prepare_hyperopt_data(self) -> None: def prepare_hyperopt_data(self) -> None:
data, timerange = self.backtesting.load_bt_data() data, timerange = self.backtesting.load_bt_data()
logger.info("Dataload complete. Calculating indicators") logger.info("Dataload complete. Calculating indicators")
preprocessed = self.backtesting.strategy.ohlcvdata_to_dataframe(data)
processed: Dict[str, DataFrame] = {}
preprocessed = self.backtesting.strategy.ohlcvdata_to_dataframe(data)
# Trim startup period from analyzed dataframe # Trim startup period from analyzed dataframe
for pair, df in preprocessed.items(): for pair, df in preprocessed.items():
preprocessed[pair] = trim_dataframe(df, timerange, trimed_df = trim_dataframe(df, timerange,
startup_candles=self.backtesting.required_startup) startup_candles=self.backtesting.required_startup)
self.min_date, self.max_date = get_timerange(preprocessed) if not trimed_df.empty:
processed[pair] = trimed_df
else:
logger.warn(f'Pair {pair} got removed because triming dataframe left nothing')
self.min_date, self.max_date = get_timerange(processed)
logger.info(f'Hyperopting with data from {self.min_date.strftime(DATETIME_PRINT_FORMAT)} ' logger.info(f'Hyperopting with data from {self.min_date.strftime(DATETIME_PRINT_FORMAT)} '
f'up to {self.max_date.strftime(DATETIME_PRINT_FORMAT)} ' f'up to {self.max_date.strftime(DATETIME_PRINT_FORMAT)} '
f'({(self.max_date - self.min_date).days} days)..') f'({(self.max_date - self.min_date).days} days)..')
dump(preprocessed, self.data_pickle_file) dump(processed, self.data_pickle_file)
def start(self) -> None: def start(self) -> None:
self.random_state = self._set_random_state(self.config.get('hyperopt_random_state', None)) self.random_state = self._set_random_state(self.config.get('hyperopt_random_state', None))