Extract generation of report for one strategy to it's own method
This commit is contained in:
Matthias
parent
b125c975c7
commit
9994fce577
@ -235,6 +235,142 @@ def generate_daily_stats(results: DataFrame) -> Dict[str, Any]:
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}
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def generate_strategy_stats(btdata: Dict[str, DataFrame],
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strategy: str,
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content: Dict[str, Any],
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min_date: Arrow, max_date: Arrow,
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market_change: float
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) -> Dict[str, Any]:
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"""
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:param btdata: Backtest data
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:param strategy: Strategy name
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:param content: Backtest result data in the format:
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{'results: results, 'config: config}}.
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:param min_date: Backtest start date
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:param max_date: Backtest end date
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:param market_change: float indicating the market change
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:return: Dictionary containing results per strategy and a stratgy summary.
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"""
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results: Dict[str, DataFrame] = content['results']
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if not isinstance(results, DataFrame):
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return
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config = content['config']
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max_open_trades = min(config['max_open_trades'], len(btdata.keys()))
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starting_balance = config['dry_run_wallet']
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stake_currency = config['stake_currency']
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pair_results = generate_pair_metrics(btdata, stake_currency=stake_currency,
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starting_balance=starting_balance,
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results=results, skip_nan=False)
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sell_reason_stats = generate_sell_reason_stats(max_open_trades=max_open_trades,
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results=results)
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left_open_results = generate_pair_metrics(btdata, stake_currency=stake_currency,
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starting_balance=starting_balance,
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results=results.loc[results['is_open']],
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skip_nan=True)
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daily_stats = generate_daily_stats(results)
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best_pair = max([pair for pair in pair_results if pair['key'] != 'TOTAL'],
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key=lambda x: x['profit_sum']) if len(pair_results) > 1 else None
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worst_pair = min([pair for pair in pair_results if pair['key'] != 'TOTAL'],
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key=lambda x: x['profit_sum']) if len(pair_results) > 1 else None
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results['open_timestamp'] = results['open_date'].astype(int64) // 1e6
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results['close_timestamp'] = results['close_date'].astype(int64) // 1e6
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backtest_days = (max_date - min_date).days
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strat_stats = {
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'trades': results.to_dict(orient='records'),
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'locks': [lock.to_json() for lock in content['locks']],
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'best_pair': best_pair,
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'worst_pair': worst_pair,
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'results_per_pair': pair_results,
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'sell_reason_summary': sell_reason_stats,
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'left_open_trades': left_open_results,
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'total_trades': len(results),
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'total_volume': float(results['stake_amount'].sum()),
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'avg_stake_amount': results['stake_amount'].mean() if len(results) > 0 else 0,
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'profit_mean': results['profit_ratio'].mean() if len(results) > 0 else 0,
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'profit_total': results['profit_abs'].sum() / starting_balance,
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'profit_total_abs': results['profit_abs'].sum(),
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'backtest_start': min_date.datetime,
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'backtest_start_ts': min_date.int_timestamp * 1000,
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'backtest_end': max_date.datetime,
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'backtest_end_ts': max_date.int_timestamp * 1000,
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'backtest_days': backtest_days,
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'backtest_run_start_ts': content['backtest_start_time'],
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'backtest_run_end_ts': content['backtest_end_time'],
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'trades_per_day': round(len(results) / backtest_days, 2) if backtest_days > 0 else 0,
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'market_change': market_change,
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'pairlist': list(btdata.keys()),
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'stake_amount': config['stake_amount'],
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'stake_currency': config['stake_currency'],
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'stake_currency_decimals': decimals_per_coin(config['stake_currency']),
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'starting_balance': starting_balance,
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'dry_run_wallet': starting_balance,
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'final_balance': content['final_balance'],
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'max_open_trades': max_open_trades,
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'max_open_trades_setting': (config['max_open_trades']
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if config['max_open_trades'] != float('inf') else -1),
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'timeframe': config['timeframe'],
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'timerange': config.get('timerange', ''),
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'enable_protections': config.get('enable_protections', False),
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'strategy_name': strategy,
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# Parameters relevant for backtesting
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'stoploss': config['stoploss'],
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'trailing_stop': config.get('trailing_stop', False),
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'trailing_stop_positive': config.get('trailing_stop_positive'),
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'trailing_stop_positive_offset': config.get('trailing_stop_positive_offset', 0.0),
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'trailing_only_offset_is_reached': config.get('trailing_only_offset_is_reached', False),
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'use_custom_stoploss': config.get('use_custom_stoploss', False),
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'minimal_roi': config['minimal_roi'],
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'use_sell_signal': config['ask_strategy']['use_sell_signal'],
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'sell_profit_only': config['ask_strategy']['sell_profit_only'],
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'sell_profit_offset': config['ask_strategy']['sell_profit_offset'],
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'ignore_roi_if_buy_signal': config['ask_strategy']['ignore_roi_if_buy_signal'],
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**daily_stats,
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}
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try:
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max_drawdown, _, _, _, _ = calculate_max_drawdown(
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results, value_col='profit_ratio')
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drawdown_abs, drawdown_start, drawdown_end, high_val, low_val = calculate_max_drawdown(
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results, value_col='profit_abs')
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strat_stats.update({
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'max_drawdown': max_drawdown,
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'max_drawdown_abs': drawdown_abs,
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'drawdown_start': drawdown_start,
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'drawdown_start_ts': drawdown_start.timestamp() * 1000,
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'drawdown_end': drawdown_end,
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'drawdown_end_ts': drawdown_end.timestamp() * 1000,
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'max_drawdown_low': low_val,
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'max_drawdown_high': high_val,
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})
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csum_min, csum_max = calculate_csum(results, starting_balance)
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strat_stats.update({
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'csum_min': csum_min,
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'csum_max': csum_max
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})
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except ValueError:
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strat_stats.update({
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'max_drawdown': 0.0,
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'max_drawdown_abs': 0.0,
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'max_drawdown_low': 0.0,
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'max_drawdown_high': 0.0,
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'drawdown_start': datetime(1970, 1, 1, tzinfo=timezone.utc),
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'drawdown_start_ts': 0,
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'drawdown_end': datetime(1970, 1, 1, tzinfo=timezone.utc),
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'drawdown_end_ts': 0,
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'csum_min': 0,
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'csum_max': 0
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})
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return strat_stats
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def generate_backtest_stats(btdata: Dict[str, DataFrame],
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all_results: Dict[str, Dict[str, Union[DataFrame, Dict]]],
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min_date: Arrow, max_date: Arrow
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@ -245,131 +381,16 @@ def generate_backtest_stats(btdata: Dict[str, DataFrame],
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{ Strategy: {'results: results, 'config: config}}.
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:param min_date: Backtest start date
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:param max_date: Backtest end date
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:return:
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Dictionary containing results per strategy and a stratgy summary.
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:return: Dictionary containing results per strategy and a stratgy summary.
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"""
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result: Dict[str, Any] = {'strategy': {}}
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market_change = calculate_market_change(btdata, 'close')
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for strategy, content in all_results.items():
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results: Dict[str, DataFrame] = content['results']
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if not isinstance(results, DataFrame):
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continue
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config = content['config']
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max_open_trades = min(config['max_open_trades'], len(btdata.keys()))
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starting_balance = config['dry_run_wallet']
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stake_currency = config['stake_currency']
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pair_results = generate_pair_metrics(btdata, stake_currency=stake_currency,
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starting_balance=starting_balance,
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results=results, skip_nan=False)
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sell_reason_stats = generate_sell_reason_stats(max_open_trades=max_open_trades,
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results=results)
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left_open_results = generate_pair_metrics(btdata, stake_currency=stake_currency,
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starting_balance=starting_balance,
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results=results.loc[results['is_open']],
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skip_nan=True)
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daily_stats = generate_daily_stats(results)
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best_pair = max([pair for pair in pair_results if pair['key'] != 'TOTAL'],
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key=lambda x: x['profit_sum']) if len(pair_results) > 1 else None
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worst_pair = min([pair for pair in pair_results if pair['key'] != 'TOTAL'],
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key=lambda x: x['profit_sum']) if len(pair_results) > 1 else None
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results['open_timestamp'] = results['open_date'].astype(int64) // 1e6
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results['close_timestamp'] = results['close_date'].astype(int64) // 1e6
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backtest_days = (max_date - min_date).days
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strat_stats = {
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'trades': results.to_dict(orient='records'),
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'locks': [lock.to_json() for lock in content['locks']],
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'best_pair': best_pair,
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'worst_pair': worst_pair,
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'results_per_pair': pair_results,
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'sell_reason_summary': sell_reason_stats,
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'left_open_trades': left_open_results,
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'total_trades': len(results),
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'total_volume': float(results['stake_amount'].sum()),
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'avg_stake_amount': results['stake_amount'].mean() if len(results) > 0 else 0,
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'profit_mean': results['profit_ratio'].mean() if len(results) > 0 else 0,
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'profit_total': results['profit_abs'].sum() / starting_balance,
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'profit_total_abs': results['profit_abs'].sum(),
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'backtest_start': min_date.datetime,
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'backtest_start_ts': min_date.int_timestamp * 1000,
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'backtest_end': max_date.datetime,
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'backtest_end_ts': max_date.int_timestamp * 1000,
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'backtest_days': backtest_days,
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'backtest_run_start_ts': content['backtest_start_time'],
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'backtest_run_end_ts': content['backtest_end_time'],
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'trades_per_day': round(len(results) / backtest_days, 2) if backtest_days > 0 else 0,
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'market_change': market_change,
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'pairlist': list(btdata.keys()),
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'stake_amount': config['stake_amount'],
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'stake_currency': config['stake_currency'],
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'stake_currency_decimals': decimals_per_coin(config['stake_currency']),
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'starting_balance': starting_balance,
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'dry_run_wallet': starting_balance,
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'final_balance': content['final_balance'],
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'max_open_trades': max_open_trades,
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'max_open_trades_setting': (config['max_open_trades']
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if config['max_open_trades'] != float('inf') else -1),
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'timeframe': config['timeframe'],
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'timerange': config.get('timerange', ''),
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'enable_protections': config.get('enable_protections', False),
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'strategy_name': strategy,
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# Parameters relevant for backtesting
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'stoploss': config['stoploss'],
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'trailing_stop': config.get('trailing_stop', False),
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'trailing_stop_positive': config.get('trailing_stop_positive'),
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'trailing_stop_positive_offset': config.get('trailing_stop_positive_offset', 0.0),
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'trailing_only_offset_is_reached': config.get('trailing_only_offset_is_reached', False),
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'use_custom_stoploss': config.get('use_custom_stoploss', False),
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'minimal_roi': config['minimal_roi'],
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'use_sell_signal': config['ask_strategy']['use_sell_signal'],
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'sell_profit_only': config['ask_strategy']['sell_profit_only'],
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'sell_profit_offset': config['ask_strategy']['sell_profit_offset'],
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'ignore_roi_if_buy_signal': config['ask_strategy']['ignore_roi_if_buy_signal'],
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**daily_stats,
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}
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strat_stats = generate_strategy_stats(btdata, strategy, content,
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min_date, max_date, market_change=market_change)
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result['strategy'][strategy] = strat_stats
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try:
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max_drawdown, _, _, _, _ = calculate_max_drawdown(
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results, value_col='profit_ratio')
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drawdown_abs, drawdown_start, drawdown_end, high_val, low_val = calculate_max_drawdown(
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results, value_col='profit_abs')
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strat_stats.update({
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'max_drawdown': max_drawdown,
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'max_drawdown_abs': drawdown_abs,
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'drawdown_start': drawdown_start,
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'drawdown_start_ts': drawdown_start.timestamp() * 1000,
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'drawdown_end': drawdown_end,
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'drawdown_end_ts': drawdown_end.timestamp() * 1000,
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'max_drawdown_low': low_val,
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'max_drawdown_high': high_val,
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})
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csum_min, csum_max = calculate_csum(results, starting_balance)
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strat_stats.update({
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'csum_min': csum_min,
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'csum_max': csum_max
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})
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except ValueError:
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strat_stats.update({
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'max_drawdown': 0.0,
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'max_drawdown_abs': 0.0,
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'max_drawdown_low': 0.0,
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'max_drawdown_high': 0.0,
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'drawdown_start': datetime(1970, 1, 1, tzinfo=timezone.utc),
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'drawdown_start_ts': 0,
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'drawdown_end': datetime(1970, 1, 1, tzinfo=timezone.utc),
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'drawdown_end_ts': 0,
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'csum_min': 0,
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'csum_max': 0
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})
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strategy_results = generate_strategy_comparison(all_results=all_results)
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result['strategy_comparison'] = strategy_results
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