diff --git a/freqtrade/optimize/hyperopt.py b/freqtrade/optimize/hyperopt.py index ee5599e20..fe590f0d2 100644 --- a/freqtrade/optimize/hyperopt.py +++ b/freqtrade/optimize/hyperopt.py @@ -379,7 +379,8 @@ class Hyperopt: strat_stats = generate_strategy_stats( self.pairlist, self.backtesting.strategy.get_strategy_name(), - backtesting_results, min_date, max_date, market_change=self.market_change + backtesting_results, min_date, max_date, market_change=self.market_change, + is_hyperopt=True, ) results_explanation = HyperoptTools.format_results_explanation_string( strat_stats, self.config['stake_currency']) diff --git a/freqtrade/optimize/optimize_reports.py b/freqtrade/optimize/optimize_reports.py index cbae6aede..1c5088cc1 100644 --- a/freqtrade/optimize/optimize_reports.py +++ b/freqtrade/optimize/optimize_reports.py @@ -7,8 +7,8 @@ from typing import Any, Dict, List, Union from pandas import DataFrame, to_datetime from tabulate import tabulate -from freqtrade.constants import (DATETIME_PRINT_FORMAT, LAST_BT_RESULT_FN, UNLIMITED_STAKE_AMOUNT, - Config, IntOrInf) +from freqtrade.constants import (BACKTEST_BREAKDOWNS, DATETIME_PRINT_FORMAT, LAST_BT_RESULT_FN, + UNLIMITED_STAKE_AMOUNT, Config, IntOrInf) from freqtrade.data.metrics import (calculate_cagr, calculate_calmar, calculate_csum, calculate_expectancy, calculate_market_change, calculate_max_drawdown, calculate_sharpe, calculate_sortino) @@ -296,6 +296,7 @@ def generate_periodic_breakdown_stats(trade_list: List, period: str) -> List[Dic stats.append( { 'date': name.strftime('%d/%m/%Y'), + 'date_ts': int(name.to_pydatetime().timestamp() * 1000), 'profit_abs': profit_abs, 'wins': wins, 'draws': draws, @@ -305,6 +306,13 @@ def generate_periodic_breakdown_stats(trade_list: List, period: str) -> List[Dic return stats +def generate_all_periodic_breakdown_stats(trade_list: List) -> Dict[str, List]: + result = {} + for period in BACKTEST_BREAKDOWNS: + result[period] = generate_periodic_breakdown_stats(trade_list, period) + return result + + def generate_trading_stats(results: DataFrame) -> Dict[str, Any]: """ Generate overall trade statistics """ if len(results) == 0: @@ -381,7 +389,8 @@ def generate_strategy_stats(pairlist: List[str], strategy: str, content: Dict[str, Any], min_date: datetime, max_date: datetime, - market_change: float + market_change: float, + is_hyperopt: bool = False, ) -> Dict[str, Any]: """ :param pairlist: List of pairs to backtest @@ -416,6 +425,11 @@ def generate_strategy_stats(pairlist: List[str], daily_stats = generate_daily_stats(results) trade_stats = generate_trading_stats(results) + + periodic_breakdown = {} + if not is_hyperopt: + periodic_breakdown = {'periodic_breakdown': generate_all_periodic_breakdown_stats(results)} + best_pair = max([pair for pair in pair_results if pair['key'] != 'TOTAL'], key=lambda x: x['profit_sum']) if len(pair_results) > 1 else None worst_pair = min([pair for pair in pair_results if pair['key'] != 'TOTAL'], @@ -434,7 +448,6 @@ def generate_strategy_stats(pairlist: List[str], 'results_per_enter_tag': enter_tag_results, 'exit_reason_summary': exit_reason_stats, 'left_open_trades': left_open_results, - # 'days_breakdown_stats': days_breakdown_stats, 'total_trades': len(results), 'trade_count_long': len(results.loc[~results['is_short']]), @@ -499,6 +512,7 @@ def generate_strategy_stats(pairlist: List[str], 'exit_profit_only': config['exit_profit_only'], 'exit_profit_offset': config['exit_profit_offset'], 'ignore_roi_if_entry_signal': config['ignore_roi_if_entry_signal'], + **periodic_breakdown, **daily_stats, **trade_stats } @@ -891,8 +905,11 @@ def show_backtest_result(strategy: str, results: Dict[str, Any], stake_currency: print(table) for period in backtest_breakdown: - days_breakdown_stats = generate_periodic_breakdown_stats( - trade_list=results['trades'], period=period) + if period in results.get('periodic_breakdown', {}): + days_breakdown_stats = results['periodic_breakdown'][period] + else: + days_breakdown_stats = generate_periodic_breakdown_stats( + trade_list=results['trades'], period=period) table = text_table_periodic_breakdown(days_breakdown_stats=days_breakdown_stats, stake_currency=stake_currency, period=period) if isinstance(table, str) and len(table) > 0: