Make CLI option and docs clearer that we're handling signals not trades
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froggleston
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854f056eaf
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@ -116,12 +116,12 @@ For example, if your backtest timerange was `20220101-20221231` but you only wan
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freqtrade backtesting-analysis -c <config.json> --timerange 20220101-20220201
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```
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### Printing out rejected trades
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### Printing out rejected signals
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Use the `--rejected` option to print out rejected trades.
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Use the `--rejected-signals` option to print out rejected signals.
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```bash
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freqtrade backtesting-analysis -c <config.json> --rejected
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freqtrade backtesting-analysis -c <config.json> --rejected-signals
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```
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### Writing tables to CSV
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@ -136,11 +136,11 @@ freqtrade backtesting-analysis -c <config.json> --analysis-to-csv
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By default this will write one file per output table you specified in the `backtesting-analysis` command, e.g.
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```bash
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freqtrade backtesting-analysis -c <config.json> --analysis-to-csv --rejected --analysis-groups 0 1
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freqtrade backtesting-analysis -c <config.json> --analysis-to-csv --rejected-signals --analysis-groups 0 1
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```
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This will write to `user_data/backtest_results`:
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* rejected.csv
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* rejected_signals.csv
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* group_0.csv
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* group_1.csv
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@ -659,8 +659,8 @@ AVAILABLE_CLI_OPTIONS = {
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default=[],
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),
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"analysis_rejected": Arg(
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'--rejected',
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help='Analyse rejected trades',
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'--rejected-signals',
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help='Analyse rejected signals',
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action='store_true',
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),
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"analysis_to_csv": Arg(
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@ -466,7 +466,7 @@ class Configuration:
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logstring='Filter trades by timerange: {}')
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self._args_to_config(config, argname='analysis_rejected',
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logstring='Analyse rejected trades: {}')
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logstring='Analyse rejected signals: {}')
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self._args_to_config(config, argname='analysis_to_csv',
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logstring='Store analysis tables to CSV: {}')
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@ -25,15 +25,15 @@ def _load_backtest_analysis_data(backtest_dir: Path, name: str):
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try:
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scp = open(scpf, "rb")
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rejected_trades = joblib.load(scp)
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loaded_data = joblib.load(scp)
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logger.info(f"Loaded {name} data: {str(scpf)}")
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except Exception as e:
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logger.error(f"Cannot load {name} data from pickled results: ", e)
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return rejected_trades
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return loaded_data
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def _load_rejected_trades(backtest_dir: Path):
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def _load_rejected_signals(backtest_dir: Path):
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return _load_backtest_analysis_data(backtest_dir, "rejected")
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@ -163,13 +163,13 @@ def _do_group_table_output(bigdf, glist, to_csv=False, csv_path=None):
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logger.warning("Invalid group mask specified.")
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def _do_rejected_trades_output(rejected_trades_df, to_csv=False, csv_path=None):
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def _do_rejected_signals_output(rejected_signals_df, to_csv=False, csv_path=None):
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cols = ['pair', 'date', 'enter_tag']
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sortcols = ['date', 'pair', 'enter_tag']
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_print_table(rejected_trades_df[cols],
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_print_table(rejected_signals_df[cols],
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sortcols,
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show_index=False,
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name="Rejected Trades:",
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name="Rejected Signals:",
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to_csv=to_csv,
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csv_path=csv_path)
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@ -208,13 +208,13 @@ def prepare_results(analysed_trades, stratname,
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def print_results(res_df, analysis_groups, indicator_list,
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rejected_trades=None, to_csv=False, csv_path=None):
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rejected_signals=None, to_csv=False, csv_path=None):
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if res_df.shape[0] > 0:
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if analysis_groups:
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_do_group_table_output(res_df, analysis_groups, to_csv=to_csv, csv_path=csv_path)
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if rejected_trades is not None and not rejected_trades.empty:
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_do_rejected_trades_output(rejected_trades, to_csv=to_csv, csv_path=csv_path)
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if rejected_signals is not None and not rejected_signals.empty:
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_do_rejected_signals_output(rejected_signals, to_csv=to_csv, csv_path=csv_path)
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# NB this can be large for big dataframes!
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if "all" in indicator_list:
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@ -291,8 +291,8 @@ def process_entry_exit_reasons(config: Config):
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rej_df = None
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if do_rejected:
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rejected_trades_dict = _load_rejected_trades(config['exportfilename'])
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rej_df = prepare_results(rejected_trades_dict, strategy_name,
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rejected_signals_dict = _load_rejected_signals(config['exportfilename'])
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rej_df = prepare_results(rejected_signals_dict, strategy_name,
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enter_reason_list, exit_reason_list,
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timerange=timerange)
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@ -307,7 +307,7 @@ def process_entry_exit_reasons(config: Config):
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print_results(res_df,
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analysis_groups,
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indicator_list,
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rejected_trades=rej_df,
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rejected_signals=rej_df,
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to_csv=to_csv,
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csv_path=csv_path)
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@ -29,7 +29,7 @@ from freqtrade.mixins import LoggingMixin
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from freqtrade.optimize.backtest_caching import get_strategy_run_id
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from freqtrade.optimize.bt_progress import BTProgress
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from freqtrade.optimize.optimize_reports import (generate_backtest_stats, show_backtest_results,
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store_backtest_rejected_trades,
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store_backtest_rejected_signals,
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store_backtest_signal_candles,
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store_backtest_stats)
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from freqtrade.persistence import LocalTrade, Order, PairLocks, Trade
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@ -1053,7 +1053,7 @@ class Backtesting:
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def _collate_rejected(self, pair, row):
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"""
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Temporarily store rejected trade information for downstream use in backtesting_analysis
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Temporarily store rejected signal information for downstream use in backtesting_analysis
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"""
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# It could be fun to enable hyperopt mode to write
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# a loss function to reduce rejected signals
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@ -1283,7 +1283,7 @@ class Backtesting:
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if (self.config.get('export', 'none') == 'signals' and
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self.dataprovider.runmode == RunMode.BACKTEST):
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self._generate_trade_signal_candles(preprocessed_tmp, results)
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self._generate_rejected_trades(preprocessed_tmp, self.rejected_dict)
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self._generate_rejected_signals(preprocessed_tmp, self.rejected_dict)
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return min_date, max_date
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@ -1308,22 +1308,22 @@ class Backtesting:
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self.processed_dfs[self.strategy.get_strategy_name()] = signal_candles_only
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def _generate_rejected_trades(self, preprocessed_df, rejected_dict):
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def _generate_rejected_signals(self, preprocessed_df, rejected_dict):
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rejected_candles_only = {}
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for pair, trades in rejected_dict.items():
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rejected_trades_only_df = DataFrame()
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for pair, signals in rejected_dict.items():
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rejected_signals_only_df = DataFrame()
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pairdf = preprocessed_df[pair]
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for t in trades:
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for t in signals:
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data_df_row = pairdf.loc[(pairdf['date'] == t[0])].copy()
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data_df_row['pair'] = pair
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data_df_row['enter_tag'] = t[1]
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rejected_trades_only_df = pd.concat([
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rejected_trades_only_df.infer_objects(),
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rejected_signals_only_df = pd.concat([
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rejected_signals_only_df.infer_objects(),
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data_df_row.infer_objects()])
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rejected_candles_only[pair] = rejected_trades_only_df
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rejected_candles_only[pair] = rejected_signals_only_df
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self.rejected_df[self.strategy.get_strategy_name()] = rejected_candles_only
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@ -1392,7 +1392,7 @@ class Backtesting:
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store_backtest_signal_candles(
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self.config['exportfilename'], self.processed_dfs, dt_appendix)
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store_backtest_rejected_trades(
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store_backtest_rejected_signals(
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self.config['exportfilename'], self.rejected_df, dt_appendix)
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# Results may be mixed up now. Sort them so they follow --strategy-list order.
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@ -75,7 +75,7 @@ def store_backtest_signal_candles(
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return _store_backtest_analysis_data(Path(recordfilename), candles, dtappendix, "signals")
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def store_backtest_rejected_trades(
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def store_backtest_rejected_signals(
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recordfilename: Path, trades: Dict[str, Dict], dtappendix: str) -> Path:
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return _store_backtest_analysis_data(Path(recordfilename), trades, dtappendix, "rejected")
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@ -201,8 +201,8 @@ def test_backtest_analysis_nomock(default_conf, mocker, caplog, testdatadir, tmp
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assert 'enter_tag_long_b' not in captured.out
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# test rejected - how to mock this?
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# args = get_args(base_args + ['--rejected'])
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# args = get_args(base_args + ['--rejected-signals'])
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# start_analysis_entries_exits(args)
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# captured = capsys.readouterr()
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# assert 'Rejected Trades:' in captured.out
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# assert 'Rejected Signals:' in captured.out
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# assert False
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