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Add required_startup to backtesting

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This commit is contained in:
Matthias 2019-10-20 13:56:01 +02:00
parent 9e7e051eb4
commit 9c7696a8ce
1 changed files with 28 additions and 5 deletions
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33
freqtrade/optimize/backtesting.py
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@ -15,7 +15,7 @@ from freqtrade import OperationalException
from freqtrade.configuration import TimeRange
from freqtrade.data import history
from freqtrade.data.dataprovider import DataProvider
from freqtrade.exchange import timeframe_to_minutes
from freqtrade.exchange import timeframe_to_minutes, timeframe_to_seconds
from freqtrade.misc import file_dump_json
from freqtrade.persistence import Trade
from freqtrade.resolvers import ExchangeResolver, StrategyResolver
@ -90,6 +90,9 @@ class Backtesting:
self.ticker_interval = str(self.config.get('ticker_interval'))
self.ticker_interval_mins = timeframe_to_minutes(self.ticker_interval)
# Get maximum required startup period
self.required_startup = max([strat.startup_candle_count for strat in self.strategylist])
self.required_startup_s = self.required_startup * timeframe_to_seconds(self.ticker_interval)
# Load one (first) strategy
self._set_strategy(self.strategylist[0])
@ -418,11 +421,19 @@ class Backtesting:
timerange = TimeRange.parse_timerange(None if self.config.get(
'timerange') is None else str(self.config.get('timerange')))
logger.info('Using indicator startup period: %s ...', self.required_startup)
# Timerange_startup is timerange - startup-candles
timerange_startup = deepcopy(timerange)
timerange_startup.subtract_start(self.required_startup_s)
data = history.load_data(
datadir=Path(self.config['datadir']),
pairs=pairs,
ticker_interval=self.ticker_interval,
timerange=timerange,
startup_candles=self.required_startup
)
if not data:
@ -439,11 +450,14 @@ class Backtesting:
min_date, max_date = history.get_timeframe(data)
logger.info(
'Backtesting with data from %s up to %s (%s days)..',
min_date.isoformat(),
max_date.isoformat(),
(max_date - min_date).days
'Loading backtest data from %s up to %s (%s days)..',
min_date.isoformat(), max_date.isoformat(), (max_date - min_date).days
)
if not timerange_startup.starttype:
# If no startts was defined, we need to move the backtesting start
logger.info("Moving start-date by %s candles.", self.required_startup)
timerange.startts = min_date.timestamp + self.required_startup_s
timerange.starttype = 'date'
for strat in self.strategylist:
logger.info("Running backtesting for Strategy %s", strat.get_strategy_name())
@ -452,6 +466,15 @@ class Backtesting:
# need to reprocess data every time to populate signals
preprocessed = self.strategy.tickerdata_to_dataframe(data)
# Trim startup period from analyzed dataframe
for pair, df in preprocessed.items():
preprocessed[pair] = history.trim_dataframe(df, timerange)
min_date, max_date = history.get_timeframe(preprocessed)
logger.info(
'Backtesting with data from %s up to %s (%s days)..',
min_date.isoformat(), max_date.isoformat(), (max_date - min_date).days
)
# Execute backtest and print results
all_results[self.strategy.get_strategy_name()] = self.backtest(
{