Make CLI option and docs clearer that we're handling signals not trades

docs/advanced-backtesting.md

@@ -116,12 +116,12 @@ For example, if your backtest timerange was `20220101-20221231` but you only wan
 freqtrade backtesting-analysis -c <config.json> --timerange 20220101-20220201
 ```
 
-### Printing out rejected trades
+### Printing out rejected signals
 
-Use the `--rejected` option to print out rejected trades.
+Use the `--rejected-signals` option to print out rejected signals.
 
 ```bash
-freqtrade backtesting-analysis -c <config.json> --rejected
+freqtrade backtesting-analysis -c <config.json> --rejected-signals
 ```
 
 ### Writing tables to CSV
@@ -136,11 +136,11 @@ freqtrade backtesting-analysis -c <config.json> --analysis-to-csv
 By default this will write one file per output table you specified in the `backtesting-analysis` command, e.g.
 
 ```bash
-freqtrade backtesting-analysis -c <config.json> --analysis-to-csv --rejected --analysis-groups 0 1
+freqtrade backtesting-analysis -c <config.json> --analysis-to-csv --rejected-signals --analysis-groups 0 1
 ```
 
 This will write to `user_data/backtest_results`:
-* rejected.csv
+* rejected_signals.csv
 * group_0.csv
 * group_1.csv
 

freqtrade/commands/cli_options.py

@@ -659,8 +659,8 @@ AVAILABLE_CLI_OPTIONS = {
         default=[],
     ),
     "analysis_rejected": Arg(
-        '--rejected',
+        '--rejected-signals',
-        help='Analyse rejected trades',
+        help='Analyse rejected signals',
         action='store_true',
     ),
     "analysis_to_csv": Arg(

freqtrade/configuration/configuration.py

@@ -466,7 +466,7 @@ class Configuration:
                              logstring='Filter trades by timerange: {}')
 
         self._args_to_config(config, argname='analysis_rejected',
-                             logstring='Analyse rejected trades: {}')
+                             logstring='Analyse rejected signals: {}')
 
         self._args_to_config(config, argname='analysis_to_csv',
                              logstring='Store analysis tables to CSV: {}')

freqtrade/data/entryexitanalysis.py

@@ -25,15 +25,15 @@ def _load_backtest_analysis_data(backtest_dir: Path, name: str):
 
     try:
         scp = open(scpf, "rb")
-        rejected_trades = joblib.load(scp)
+        loaded_data = joblib.load(scp)
         logger.info(f"Loaded {name} data: {str(scpf)}")
     except Exception as e:
         logger.error(f"Cannot load {name} data from pickled results: ", e)
 
-    return rejected_trades
+    return loaded_data
 
 
-def _load_rejected_trades(backtest_dir: Path):
+def _load_rejected_signals(backtest_dir: Path):
     return _load_backtest_analysis_data(backtest_dir, "rejected")
 
 
@@ -163,13 +163,13 @@ def _do_group_table_output(bigdf, glist, to_csv=False, csv_path=None):
                 logger.warning("Invalid group mask specified.")
 
 
-def _do_rejected_trades_output(rejected_trades_df, to_csv=False, csv_path=None):
+def _do_rejected_signals_output(rejected_signals_df, to_csv=False, csv_path=None):
     cols = ['pair', 'date', 'enter_tag']
     sortcols = ['date', 'pair', 'enter_tag']
-    _print_table(rejected_trades_df[cols],
+    _print_table(rejected_signals_df[cols],
                  sortcols,
                  show_index=False,
-                 name="Rejected Trades:",
+                 name="Rejected Signals:",
                  to_csv=to_csv,
                  csv_path=csv_path)
 
@@ -208,13 +208,13 @@ def prepare_results(analysed_trades, stratname,
 
 
 def print_results(res_df, analysis_groups, indicator_list,
-                  rejected_trades=None, to_csv=False, csv_path=None):
+                  rejected_signals=None, to_csv=False, csv_path=None):
     if res_df.shape[0] > 0:
         if analysis_groups:
             _do_group_table_output(res_df, analysis_groups, to_csv=to_csv, csv_path=csv_path)
 
-        if rejected_trades is not None and not rejected_trades.empty:
+        if rejected_signals is not None and not rejected_signals.empty:
-            _do_rejected_trades_output(rejected_trades, to_csv=to_csv, csv_path=csv_path)
+            _do_rejected_signals_output(rejected_signals, to_csv=to_csv, csv_path=csv_path)
 
         # NB this can be large for big dataframes!
         if "all" in indicator_list:
@@ -291,8 +291,8 @@ def process_entry_exit_reasons(config: Config):
 
                 rej_df = None
                 if do_rejected:
-                    rejected_trades_dict = _load_rejected_trades(config['exportfilename'])
+                    rejected_signals_dict = _load_rejected_signals(config['exportfilename'])
-                    rej_df = prepare_results(rejected_trades_dict, strategy_name,
+                    rej_df = prepare_results(rejected_signals_dict, strategy_name,
                                              enter_reason_list, exit_reason_list,
                                              timerange=timerange)
 
@@ -307,7 +307,7 @@ def process_entry_exit_reasons(config: Config):
                 print_results(res_df,
                               analysis_groups,
                               indicator_list,
-                              rejected_trades=rej_df,
+                              rejected_signals=rej_df,
                               to_csv=to_csv,
                               csv_path=csv_path)
 

freqtrade/optimize/backtesting.py

@@ -29,7 +29,7 @@ from freqtrade.mixins import LoggingMixin
 from freqtrade.optimize.backtest_caching import get_strategy_run_id
 from freqtrade.optimize.bt_progress import BTProgress
 from freqtrade.optimize.optimize_reports import (generate_backtest_stats, show_backtest_results,
-                                                 store_backtest_rejected_trades,
+                                                 store_backtest_rejected_signals,
                                                  store_backtest_signal_candles,
                                                  store_backtest_stats)
 from freqtrade.persistence import LocalTrade, Order, PairLocks, Trade
@@ -1053,7 +1053,7 @@ class Backtesting:
 
     def _collate_rejected(self, pair, row):
         """
-        Temporarily store rejected trade information for downstream use in backtesting_analysis
+        Temporarily store rejected signal information for downstream use in backtesting_analysis
         """
         # It could be fun to enable hyperopt mode to write
         # a loss function to reduce rejected signals
@@ -1283,7 +1283,7 @@ class Backtesting:
         if (self.config.get('export', 'none') == 'signals' and
                 self.dataprovider.runmode == RunMode.BACKTEST):
             self._generate_trade_signal_candles(preprocessed_tmp, results)
-            self._generate_rejected_trades(preprocessed_tmp, self.rejected_dict)
+            self._generate_rejected_signals(preprocessed_tmp, self.rejected_dict)
 
         return min_date, max_date
 
@@ -1308,22 +1308,22 @@ class Backtesting:
 
         self.processed_dfs[self.strategy.get_strategy_name()] = signal_candles_only
 
-    def _generate_rejected_trades(self, preprocessed_df, rejected_dict):
+    def _generate_rejected_signals(self, preprocessed_df, rejected_dict):
         rejected_candles_only = {}
-        for pair, trades in rejected_dict.items():
+        for pair, signals in rejected_dict.items():
-            rejected_trades_only_df = DataFrame()
+            rejected_signals_only_df = DataFrame()
             pairdf = preprocessed_df[pair]
 
-            for t in trades:
+            for t in signals:
                 data_df_row = pairdf.loc[(pairdf['date'] == t[0])].copy()
                 data_df_row['pair'] = pair
                 data_df_row['enter_tag'] = t[1]
 
-                rejected_trades_only_df = pd.concat([
+                rejected_signals_only_df = pd.concat([
-                    rejected_trades_only_df.infer_objects(),
+                    rejected_signals_only_df.infer_objects(),
                     data_df_row.infer_objects()])
 
-            rejected_candles_only[pair] = rejected_trades_only_df
+            rejected_candles_only[pair] = rejected_signals_only_df
 
         self.rejected_df[self.strategy.get_strategy_name()] = rejected_candles_only
 
@@ -1392,7 +1392,7 @@ class Backtesting:
                 store_backtest_signal_candles(
                     self.config['exportfilename'], self.processed_dfs, dt_appendix)
 
-                store_backtest_rejected_trades(
+                store_backtest_rejected_signals(
                     self.config['exportfilename'], self.rejected_df, dt_appendix)
 
         # Results may be mixed up now. Sort them so they follow --strategy-list order.

freqtrade/optimize/optimize_reports.py

@@ -75,7 +75,7 @@ def store_backtest_signal_candles(
     return _store_backtest_analysis_data(Path(recordfilename), candles, dtappendix, "signals")
 
 
-def store_backtest_rejected_trades(
+def store_backtest_rejected_signals(
         recordfilename: Path, trades: Dict[str, Dict], dtappendix: str) -> Path:
     return _store_backtest_analysis_data(Path(recordfilename), trades, dtappendix, "rejected")
 

tests/data/test_entryexitanalysis.py

@@ -201,8 +201,8 @@ def test_backtest_analysis_nomock(default_conf, mocker, caplog, testdatadir, tmp
     assert 'enter_tag_long_b' not in captured.out
 
     # test rejected - how to mock this?
-    # args = get_args(base_args + ['--rejected'])
+    # args = get_args(base_args + ['--rejected-signals'])
     # start_analysis_entries_exits(args)
     # captured = capsys.readouterr()
-    # assert 'Rejected Trades:' in captured.out
+    # assert 'Rejected Signals:' in captured.out
     # assert False