Merge pull request #5285 from freqtrade/backtest_startup_afte_populates
Remove startup-candles after populating buy/sell signals
This commit is contained in:
Matthias
GitHub
commit
71838dc51a
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@ -15,7 +15,7 @@ from freqtrade.configuration import TimeRange, remove_credentials, validate_conf
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from freqtrade.constants import DATETIME_PRINT_FORMAT
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from freqtrade.data import history
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from freqtrade.data.btanalysis import trade_list_to_dataframe
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from freqtrade.data.converter import trim_dataframes
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from freqtrade.data.converter import trim_dataframe, trim_dataframes
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from freqtrade.data.dataprovider import DataProvider
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from freqtrade.enums import BacktestState, SellType
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from freqtrade.exceptions import DependencyException, OperationalException
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@ -116,6 +116,9 @@ class Backtesting:
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self.wallets = Wallets(self.config, self.exchange, log=False)
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self.timerange = TimeRange.parse_timerange(
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None if self.config.get('timerange') is None else str(self.config.get('timerange')))
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# Get maximum required startup period
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self.required_startup = max([strat.startup_candle_count for strat in self.strategylist])
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self.exchange.validate_required_startup_candles(self.required_startup, self.timeframe)
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@ -154,14 +157,11 @@ class Backtesting:
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"""
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self.progress.init_step(BacktestState.DATALOAD, 1)
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timerange = TimeRange.parse_timerange(None if self.config.get(
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'timerange') is None else str(self.config.get('timerange')))
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data = history.load_data(
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datadir=self.config['datadir'],
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pairs=self.pairlists.whitelist,
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timeframe=self.timeframe,
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timerange=timerange,
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timerange=self.timerange,
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startup_candles=self.required_startup,
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fail_without_data=True,
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data_format=self.config.get('dataformat_ohlcv', 'json'),
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@ -174,11 +174,11 @@ class Backtesting:
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f'({(max_date - min_date).days} days).')
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# Adjust startts forward if not enough data is available
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timerange.adjust_start_if_necessary(timeframe_to_seconds(self.timeframe),
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self.required_startup, min_date)
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self.timerange.adjust_start_if_necessary(timeframe_to_seconds(self.timeframe),
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self.required_startup, min_date)
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self.progress.set_new_value(1)
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return data, timerange
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return data, self.timerange
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def prepare_backtest(self, enable_protections):
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"""
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@ -223,7 +223,9 @@ class Backtesting:
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df_analyzed = self.strategy.advise_sell(
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self.strategy.advise_buy(pair_data, {'pair': pair}), {'pair': pair})[headers].copy()
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# Trim startup period from analyzed dataframe
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df_analyzed = trim_dataframe(df_analyzed, self.timerange,
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startup_candles=self.required_startup)
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# To avoid using data from future, we use buy/sell signals shifted
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# from the previous candle
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df_analyzed.loc[:, 'buy'] = df_analyzed.loc[:, 'buy'].shift(1)
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@ -537,14 +539,15 @@ class Backtesting:
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preprocessed = self.strategy.ohlcvdata_to_dataframe(data)
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# Trim startup period from analyzed dataframe
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preprocessed = trim_dataframes(preprocessed, timerange, self.required_startup)
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preprocessed_tmp = trim_dataframes(preprocessed, timerange, self.required_startup)
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if not preprocessed:
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if not preprocessed_tmp:
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raise OperationalException(
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"No data left after adjusting for startup candles.")
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min_date, max_date = history.get_timerange(preprocessed)
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# Use preprocessed_tmp for date generation (the trimmed dataframe).
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# Backtesting will re-trim the dataframes after buy/sell signal generation.
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min_date, max_date = history.get_timerange(preprocessed_tmp)
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logger.info(f'Backtesting with data from {min_date.strftime(DATETIME_PRINT_FORMAT)} '
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f'up to {max_date.strftime(DATETIME_PRINT_FORMAT)} '
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f'({(max_date - min_date).days} days).')
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@ -378,16 +378,15 @@ class Hyperopt:
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preprocessed = self.backtesting.strategy.ohlcvdata_to_dataframe(data)
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# Trim startup period from analyzed dataframe
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# Trim startup period from analyzed dataframe to get correct dates for output.
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processed = trim_dataframes(preprocessed, timerange, self.backtesting.required_startup)
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self.min_date, self.max_date = get_timerange(processed)
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logger.info(f'Hyperopting with data from {self.min_date.strftime(DATETIME_PRINT_FORMAT)} '
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f'up to {self.max_date.strftime(DATETIME_PRINT_FORMAT)} '
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f'({(self.max_date - self.min_date).days} days)..')
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dump(processed, self.data_pickle_file)
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# Store non-trimmed data - will be trimmed after signal generation.
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dump(preprocessed, self.data_pickle_file)
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def start(self) -> None:
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self.random_state = self._set_random_state(self.config.get('hyperopt_random_state', None))
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@ -575,6 +575,7 @@ def test_backtest_results(default_conf, fee, mocker, caplog, data) -> None:
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frame = _build_backtest_dataframe(data.data)
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backtesting = Backtesting(default_conf)
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backtesting._set_strategy(backtesting.strategylist[0])
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backtesting.required_startup = 0
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backtesting.strategy.advise_buy = lambda a, m: frame
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backtesting.strategy.advise_sell = lambda a, m: frame
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backtesting.strategy.use_custom_stoploss = data.use_custom_stoploss
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@ -727,6 +727,7 @@ def test_backtest_alternate_buy_sell(default_conf, fee, mocker, testdatadir):
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pair='UNITTEST/BTC', datadir=testdatadir)
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default_conf['timeframe'] = '1m'
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backtesting = Backtesting(default_conf)
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backtesting.required_startup = 0
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backtesting._set_strategy(backtesting.strategylist[0])
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backtesting.strategy.advise_buy = _trend_alternate # Override
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backtesting.strategy.advise_sell = _trend_alternate # Override
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