Merge pull request #518 from gcarq/cleaning_up_backtesting

Cleaning up backtesting/hyperopt

freqtrade/misc.py

@@ -207,13 +207,7 @@ def scripts_options(parser: argparse.ArgumentParser) -> None:
     )
 
 
-def backtesting_options(parser: argparse.ArgumentParser) -> None:
-    parser.add_argument(
-        '-l', '--live',
-        action='store_true',
-        dest='live',
-        help='using live data',
-    )
+def optimizer_shared_options(parser: argparse.ArgumentParser) -> None:
     parser.add_argument(
         '-i', '--ticker-interval',
         help='specify ticker interval in minutes (1, 5, 30, 60, 1440)',
@@ -227,6 +221,22 @@ def backtesting_options(parser: argparse.ArgumentParser) -> None:
         action='store_true',
         dest='realistic_simulation',
     )
+    parser.add_argument(
+        '--timerange',
+        help='Specify what timerange of data to use.',
+        default=None,
+        type=str,
+        dest='timerange',
+    )
+
+
+def backtesting_options(parser: argparse.ArgumentParser) -> None:
+    parser.add_argument(
+        '-l', '--live',
+        action='store_true',
+        dest='live',
+        help='using live data',
+    )
     parser.add_argument(
         '-r', '--refresh-pairs-cached',
         help='refresh the pairs files in tests/testdata with the latest data from Bittrex. \
@@ -242,13 +252,6 @@ def backtesting_options(parser: argparse.ArgumentParser) -> None:
         default=None,
         dest='export',
     )
-    parser.add_argument(
-        '--timerange',
-        help='Specify what timerange of data to use.',
-        default=None,
-        type=str,
-        dest='timerange',
-    )
 
 
 def hyperopt_options(parser: argparse.ArgumentParser) -> None:
@@ -266,20 +269,6 @@ def hyperopt_options(parser: argparse.ArgumentParser) -> None:
         dest='mongodb',
         action='store_true',
     )
-    parser.add_argument(
-        '-i', '--ticker-interval',
-        help='specify ticker interval in minutes (1, 5, 30, 60, 1440)',
-        dest='ticker_interval',
-        type=int,
-        metavar='INT',
-    )
-    parser.add_argument(
-        '--timerange',
-        help='Specify what timerange of data to use.',
-        default=None,
-        type=str,
-        dest='timerange',
-    )
     parser.add_argument(
         '-s', '--spaces',
         help='Specify which parameters to hyperopt. Space separate list. \
@@ -330,11 +319,13 @@ def build_subcommands(parser: argparse.ArgumentParser) -> None:
     # Add backtesting subcommand
     backtesting_cmd = subparsers.add_parser('backtesting', help='backtesting module')
     backtesting_cmd.set_defaults(func=backtesting.start)
+    optimizer_shared_options(backtesting_cmd)
     backtesting_options(backtesting_cmd)
 
     # Add hyperopt subcommand
     hyperopt_cmd = subparsers.add_parser('hyperopt', help='hyperopt module')
     hyperopt_cmd.set_defaults(func=hyperopt.start)
+    optimizer_shared_options(hyperopt_cmd)
     hyperopt_options(hyperopt_cmd)
 
 

freqtrade/optimize/backtesting.py

@@ -103,13 +103,12 @@ def backtest(args) -> DataFrame:
         realistic: do we try to simulate realistic trades? (default: True)
         sell_profit_only: sell if profit only
         use_sell_signal: act on sell-signal
-        stoploss: use stoploss
     :return: DataFrame
     """
     headers = ['date', 'buy', 'open', 'close', 'sell']
     processed = args['processed']
     max_open_trades = args.get('max_open_trades', 0)
-    realistic = args.get('realistic', True)
+    realistic = args.get('realistic', False)
     record = args.get('record', None)
     records = []
     trades = []
@@ -224,7 +223,6 @@ def start(args):
                         'realistic': args.realistic_simulation,
                         'sell_profit_only': sell_profit_only,
                         'use_sell_signal': use_sell_signal,
-                        'stoploss': strategy.stoploss,
                         'record': args.export
                         })
     logger.info(

freqtrade/optimize/hyperopt.py

@@ -403,24 +403,24 @@ def buy_strategy_generator(params: Dict[str, Any]) -> Callable:
     return populate_buy_trend
 
 
-def optimizer(params):
+def generate_optimizer(args):
+    def optimizer(params):
         global _CURRENT_TRIES
 
         strategy = Strategy()
-    if 'roi_t1' in params:
+        if has_space(args.spaces, 'roi'):
             strategy.minimal_roi = generate_roi_table(params)
 
-    if 'trigger' in params:
+        if has_space(args.spaces, 'buy'):
             backtesting.populate_buy_trend = buy_strategy_generator(params)
 
-    if 'stoploss' in params:
-        stoploss = params['stoploss']
-    else:
-        stoploss = strategy.stoploss
+        if has_space(args.spaces, 'stoploss'):
+            strategy.stoploss = params['stoploss']
 
         results = backtest({'stake_amount': OPTIMIZE_CONFIG['stake_amount'],
                             'processed': PROCESSED,
-                        'stoploss': stoploss})
+                            'realistic': args.realistic_simulation,
+                            })
         result_explanation = format_results(results)
 
         total_profit = results.profit_percent.sum()
@@ -451,6 +451,8 @@ def optimizer(params):
             'result': result_explanation,
         }
 
+    return optimizer
+
 
 def format_results(results: DataFrame):
     return ('{:6d} trades. Avg profit {: 5.2f}%. '
@@ -519,7 +521,7 @@ def start(args):
 
     try:
         best_parameters = fmin(
-            fn=optimizer,
+            fn=generate_optimizer(args),
             space=hyperopt_space(args.spaces),
             algo=tpe.suggest,
             max_evals=TOTAL_TRIES,