Rename DefahltHyperoptLoss function to ShortTradeDurHyperOptLoss

docs/bot-usage.md

@@ -353,7 +353,7 @@ optional arguments:
                         class (IHyperOptLoss). Different functions can
                         generate completely different results, since the
                         target for optimization is different. Built-in
-                        Hyperopt-loss-functions are: DefaultHyperOptLoss,
+                        Hyperopt-loss-functions are: ShortTradeDurHyperOptLoss,
                         OnlyProfitHyperOptLoss, SharpeHyperOptLoss,
                         SharpeHyperOptLossDaily, SortinoHyperOptLoss,
                         SortinoHyperOptLossDaily.

docs/hyperopt.md

@@ -221,7 +221,7 @@ This class should be in its own file within the `user_data/hyperopts/` directory
 
 Currently, the following loss functions are builtin:
 
-* `DefaultHyperOptLoss` (default legacy Freqtrade hyperoptimization loss function) - Mostly for short trade duration and avoiding losses.
+* `ShortTradeHyperOptLoss` (default legacy Freqtrade hyperoptimization loss function) - Mostly for short trade duration and avoiding losses.
 * `OnlyProfitHyperOptLoss` (which takes only amount of profit into consideration)
 * `SharpeHyperOptLoss` (optimizes Sharpe Ratio calculated on trade returns relative to standard deviation)
 * `SharpeHyperOptLossDaily` (optimizes Sharpe Ratio calculated on **daily** trade returns relative to standard deviation)

freqtrade/commands/cli_options.py

@@ -257,8 +257,8 @@ AVAILABLE_CLI_OPTIONS = {
         help='Specify the class name of the hyperopt loss function class (IHyperOptLoss). '
         'Different functions can generate completely different results, '
         'since the target for optimization is different. Built-in Hyperopt-loss-functions are: '
-        'DefaultHyperOptLoss, OnlyProfitHyperOptLoss, SharpeHyperOptLoss, SharpeHyperOptLossDaily, '
+        'ShortTradeDurHyperOptLoss, OnlyProfitHyperOptLoss, SharpeHyperOptLoss, '
-        'SortinoHyperOptLoss, SortinoHyperOptLossDaily.',
+        'SharpeHyperOptLossDaily, SortinoHyperOptLoss, SortinoHyperOptLossDaily.',
         metavar='NAME',
     ),
     "hyperoptexportfilename": Arg(

freqtrade/optimize/default_hyperopt_loss.py

@@ -1,5 +1,5 @@
 """
-DefaultHyperOptLoss
+ShortTradeDurHyperOptLoss
 This module defines the default HyperoptLoss class which is being used for
 Hyperoptimization.
 """
@@ -26,7 +26,7 @@ EXPECTED_MAX_PROFIT = 3.0
 MAX_ACCEPTED_TRADE_DURATION = 300
 
 
-class DefaultHyperOptLoss(IHyperOptLoss):
+class ShortTradeDurHyperOptLoss(IHyperOptLoss):
     """
     Defines the default loss function for hyperopt
     """
@@ -50,3 +50,7 @@ class DefaultHyperOptLoss(IHyperOptLoss):
         duration_loss = 0.4 * min(trade_duration / MAX_ACCEPTED_TRADE_DURATION, 1)
         result = trade_loss + profit_loss + duration_loss
         return result
+
+
+# Create an alias for This to allow the legacy Method to work as well.
+DefaultHyperOptLoss = ShortTradeDurHyperOptLoss

tests/optimize/test_hyperopt.py

@@ -17,7 +17,7 @@ from freqtrade import constants
 from freqtrade.commands.optimize_commands import setup_optimize_configuration, start_hyperopt
 from freqtrade.data.history import load_data
 from freqtrade.exceptions import DependencyException, OperationalException
-from freqtrade.optimize.default_hyperopt_loss import DefaultHyperOptLoss
+from freqtrade.optimize.default_hyperopt_loss import ShortTradeDurHyperOptLoss
 from freqtrade.optimize.hyperopt import Hyperopt
 from freqtrade.resolvers.hyperopt_resolver import HyperOptLossResolver, HyperOptResolver
 from freqtrade.state import RunMode
@@ -33,7 +33,7 @@ def hyperopt_conf(default_conf):
     hyperconf = deepcopy(default_conf)
     hyperconf.update({
                          'hyperopt': 'DefaultHyperOpt',
-                         'hyperopt_loss': 'DefaultHyperOptLoss',
+                         'hyperopt_loss': 'ShortTradeDurHyperOptLoss',
                          'hyperopt_path': str(Path(__file__).parent / 'hyperopts'),
                          'epochs': 1,
                          'timerange': None,
@@ -239,12 +239,12 @@ def test_hyperoptlossresolver_noname(default_conf):
 
 def test_hyperoptlossresolver(mocker, default_conf) -> None:
 
-    hl = DefaultHyperOptLoss
+    hl = ShortTradeDurHyperOptLoss
     mocker.patch(
         'freqtrade.resolvers.hyperopt_resolver.HyperOptLossResolver.load_object',
         MagicMock(return_value=hl)
     )
-    default_conf.update({'hyperopt_loss': 'DefaultHyperoptLoss'})
+    default_conf.update({'hyperopt_loss': 'SharpeHyperOptLossDaily'})
     x = HyperOptLossResolver.load_hyperoptloss(default_conf)
     assert hasattr(x, "hyperopt_loss_function")
 
@@ -287,7 +287,7 @@ def test_start(mocker, hyperopt_conf, caplog) -> None:
         'hyperopt',
         '--config', 'config.json',
         '--hyperopt', 'DefaultHyperOpt',
-        '--hyperopt-loss', 'DefaultHyperOptLoss',
+        '--hyperopt-loss', 'SharpeHyperOptLossDaily',
         '--epochs', '5'
     ]
     pargs = get_args(args)
@@ -311,7 +311,7 @@ def test_start_no_data(mocker, hyperopt_conf) -> None:
         'hyperopt',
         '--config', 'config.json',
         '--hyperopt', 'DefaultHyperOpt',
-        '--hyperopt-loss', 'DefaultHyperOptLoss',
+        '--hyperopt-loss', 'SharpeHyperOptLossDaily',
         '--epochs', '5'
     ]
     pargs = get_args(args)
@@ -329,7 +329,7 @@ def test_start_filelock(mocker, hyperopt_conf, caplog) -> None:
         'hyperopt',
         '--config', 'config.json',
         '--hyperopt', 'DefaultHyperOpt',
-        '--hyperopt-loss', 'DefaultHyperOptLoss',
+        '--hyperopt-loss', 'SharpeHyperOptLossDaily',
         '--epochs', '5'
     ]
     pargs = get_args(args)
@@ -384,7 +384,7 @@ def test_sharpe_loss_prefers_higher_profits(default_conf, hyperopt_results) -> N
     results_under = hyperopt_results.copy()
     results_under['profit_percent'] = hyperopt_results['profit_percent'] / 2
 
-    default_conf.update({'hyperopt_loss': 'SharpeHyperOptLoss'})
+    default_conf.update({'hyperopt_loss': 'SharpeHyperOptLossDaily'})
     hl = HyperOptLossResolver.load_hyperoptloss(default_conf)
     correct = hl.hyperopt_loss_function(hyperopt_results, len(hyperopt_results),
                                         datetime(2019, 1, 1), datetime(2019, 5, 1))