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Refactor methods in backtesting

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This commit is contained in:
Matthias 2023-04-28 16:09:09 +02:00
parent 0753f427b1
commit 6e395ad7c9
2 changed files with 15 additions and 13 deletions
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2
freqtrade/data/entryexitanalysis.py
View File

@ -1,6 +1,6 @@
import logging
from pathlib import Path
from typing import List, Optional
from typing import List
import joblib
import pandas as pd

26
freqtrade/optimize/backtesting.py
View File

@ -1252,8 +1252,8 @@ class Backtesting:
def backtest_one_strategy(self, strat: IStrategy, data: Dict[str, DataFrame],
timerange: TimeRange):
self.progress.init_step(BacktestState.ANALYZE, 0)
logger.info(f"Running backtesting for Strategy {strat.get_strategy_name()}")
strategy_name = strat.get_strategy_name()
logger.info(f"Running backtesting for Strategy {strategy_name}")
backtest_start_time = datetime.now(timezone.utc)
self._set_strategy(strat)
@ -1288,20 +1288,23 @@ class Backtesting:
)
backtest_end_time = datetime.now(timezone.utc)
results.update({
'run_id': self.run_ids.get(strat.get_strategy_name(), ''),
'run_id': self.run_ids.get(strategy_name, ''),
'backtest_start_time': int(backtest_start_time.timestamp()),
'backtest_end_time': int(backtest_end_time.timestamp()),
})
self.all_results[self.strategy.get_strategy_name()] = results
self.all_results[strategy_name] = results
if (self.config.get('export', 'none') == 'signals' and
self.dataprovider.runmode == RunMode.BACKTEST):
self._generate_trade_signal_candles(preprocessed_tmp, results)
self._generate_rejected_signals(preprocessed_tmp, self.rejected_dict)
self.processed_dfs[strategy_name] = self._generate_trade_signal_candles(
preprocessed_tmp, results)
self.rejected_df[strategy_name] = self._generate_rejected_signals(
preprocessed_tmp, self.rejected_dict)
return min_date, max_date
def _generate_trade_signal_candles(self, preprocessed_df, bt_results):
def _generate_trade_signal_candles(self, preprocessed_df: Dict[str, pd.DataFrame],
bt_results: Dict[str, Any]) -> pd.DataFrame:
signal_candles_only = {}
for pair in preprocessed_df.keys():
signal_candles_only_df = DataFrame()
@ -1319,10 +1322,10 @@ class Backtesting:
signal_inds.infer_objects()])
signal_candles_only[pair] = signal_candles_only_df
return signal_candles_only
self.processed_dfs[self.strategy.get_strategy_name()] = signal_candles_only
def _generate_rejected_signals(self, preprocessed_df, rejected_dict):
def _generate_rejected_signals(self, preprocessed_df: Dict[str, DataFrame],
rejected_dict: Dict[str, DataFrame]) -> Dict[str, DataFrame]:
rejected_candles_only = {}
for pair, signals in rejected_dict.items():
rejected_signals_only_df = DataFrame()
@ -1338,8 +1341,7 @@ class Backtesting:
data_df_row.infer_objects()])
rejected_candles_only[pair] = rejected_signals_only_df
self.rejected_df[self.strategy.get_strategy_name()] = rejected_candles_only
return rejected_candles_only
def _get_min_cached_backtest_date(self):
min_backtest_date = None