Convert hyperoptloss resolver to static loader

This commit is contained in:
Matthias 2019-12-23 10:09:08 +01:00
parent 248ef5a0ea
commit 6d5aca4f32
3 changed files with 22 additions and 20 deletions

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@ -66,7 +66,7 @@ class Hyperopt:
self.custom_hyperopt = HyperOptResolver.load_hyperopt(self.config) self.custom_hyperopt = HyperOptResolver.load_hyperopt(self.config)
self.custom_hyperoptloss = HyperOptLossResolver(self.config).hyperoptloss self.custom_hyperoptloss = HyperOptLossResolver.load_hyperoptloss(self.config)
self.calculate_loss = self.custom_hyperoptloss.hyperopt_loss_function self.calculate_loss = self.custom_hyperoptloss.hyperopt_loss_function
self.trials_file = (self.config['user_data_dir'] / self.trials_file = (self.config['user_data_dir'] /

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@ -77,9 +77,9 @@ class HyperOptLossResolver(IResolver):
""" """
This class contains all the logic to load custom hyperopt loss class This class contains all the logic to load custom hyperopt loss class
""" """
__slots__ = ['hyperoptloss']
def __init__(self, config: Dict) -> None: @staticmethod
def load_hyperoptloss(config: Dict) -> IHyperOptLoss:
""" """
Load the custom class from config parameter Load the custom class from config parameter
:param config: configuration dictionary :param config: configuration dictionary
@ -89,20 +89,21 @@ class HyperOptLossResolver(IResolver):
# default hyperopt loss # default hyperopt loss
hyperoptloss_name = config.get('hyperopt_loss') or DEFAULT_HYPEROPT_LOSS hyperoptloss_name = config.get('hyperopt_loss') or DEFAULT_HYPEROPT_LOSS
self.hyperoptloss = self._load_hyperoptloss( hyperoptloss = HyperOptLossResolver._load_hyperoptloss(
hyperoptloss_name, config, extra_dir=config.get('hyperopt_path')) hyperoptloss_name, config, extra_dir=config.get('hyperopt_path'))
# Assign ticker_interval to be used in hyperopt # Assign ticker_interval to be used in hyperopt
self.hyperoptloss.__class__.ticker_interval = str(config['ticker_interval']) hyperoptloss.__class__.ticker_interval = str(config['ticker_interval'])
if not hasattr(self.hyperoptloss, 'hyperopt_loss_function'): if not hasattr(hyperoptloss, 'hyperopt_loss_function'):
raise OperationalException( raise OperationalException(
f"Found HyperoptLoss class {hyperoptloss_name} does not " f"Found HyperoptLoss class {hyperoptloss_name} does not "
"implement `hyperopt_loss_function`.") "implement `hyperopt_loss_function`.")
return hyperoptloss
def _load_hyperoptloss( @staticmethod
self, hyper_loss_name: str, config: Dict, def _load_hyperoptloss(hyper_loss_name: str, config: Dict,
extra_dir: Optional[str] = None) -> IHyperOptLoss: extra_dir: Optional[str] = None) -> IHyperOptLoss:
""" """
Search and loads the specified hyperopt loss class. Search and loads the specified hyperopt loss class.
:param hyper_loss_name: name of the module to import :param hyper_loss_name: name of the module to import
@ -112,11 +113,12 @@ class HyperOptLossResolver(IResolver):
""" """
current_path = Path(__file__).parent.parent.joinpath('optimize').resolve() current_path = Path(__file__).parent.parent.joinpath('optimize').resolve()
abs_paths = self.build_search_paths(config, current_path=current_path, abs_paths = IResolver.build_search_paths(config, current_path=current_path,
user_subdir=USERPATH_HYPEROPTS, extra_dir=extra_dir) user_subdir=USERPATH_HYPEROPTS,
extra_dir=extra_dir)
hyperoptloss = self._load_object(paths=abs_paths, object_type=IHyperOptLoss, hyperoptloss = IResolver._load_object(paths=abs_paths, object_type=IHyperOptLoss,
object_name=hyper_loss_name) object_name=hyper_loss_name)
if hyperoptloss: if hyperoptloss:
return hyperoptloss return hyperoptloss

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@ -198,7 +198,7 @@ def test_hyperoptlossresolver(mocker, default_conf, caplog) -> None:
'freqtrade.resolvers.hyperopt_resolver.HyperOptLossResolver._load_hyperoptloss', 'freqtrade.resolvers.hyperopt_resolver.HyperOptLossResolver._load_hyperoptloss',
MagicMock(return_value=hl) MagicMock(return_value=hl)
) )
x = HyperOptLossResolver(default_conf).hyperoptloss x = HyperOptLossResolver.load_hyperoptloss(default_conf)
assert hasattr(x, "hyperopt_loss_function") assert hasattr(x, "hyperopt_loss_function")
@ -206,7 +206,7 @@ def test_hyperoptlossresolver_wrongname(mocker, default_conf, caplog) -> None:
default_conf.update({'hyperopt_loss': "NonExistingLossClass"}) default_conf.update({'hyperopt_loss': "NonExistingLossClass"})
with pytest.raises(OperationalException, match=r'Impossible to load HyperoptLoss.*'): with pytest.raises(OperationalException, match=r'Impossible to load HyperoptLoss.*'):
HyperOptLossResolver(default_conf).hyperopt HyperOptLossResolver.load_hyperoptloss(default_conf)
def test_start_not_installed(mocker, default_conf, caplog, import_fails) -> None: def test_start_not_installed(mocker, default_conf, caplog, import_fails) -> None:
@ -286,7 +286,7 @@ def test_start_filelock(mocker, default_conf, caplog) -> None:
def test_loss_calculation_prefer_correct_trade_count(default_conf, hyperopt_results) -> None: def test_loss_calculation_prefer_correct_trade_count(default_conf, hyperopt_results) -> None:
hl = HyperOptLossResolver(default_conf).hyperoptloss hl = HyperOptLossResolver.load_hyperoptloss(default_conf)
correct = hl.hyperopt_loss_function(hyperopt_results, 600) correct = hl.hyperopt_loss_function(hyperopt_results, 600)
over = hl.hyperopt_loss_function(hyperopt_results, 600 + 100) over = hl.hyperopt_loss_function(hyperopt_results, 600 + 100)
under = hl.hyperopt_loss_function(hyperopt_results, 600 - 100) under = hl.hyperopt_loss_function(hyperopt_results, 600 - 100)
@ -298,7 +298,7 @@ def test_loss_calculation_prefer_shorter_trades(default_conf, hyperopt_results)
resultsb = hyperopt_results.copy() resultsb = hyperopt_results.copy()
resultsb.loc[1, 'trade_duration'] = 20 resultsb.loc[1, 'trade_duration'] = 20
hl = HyperOptLossResolver(default_conf).hyperoptloss hl = HyperOptLossResolver.load_hyperoptloss(default_conf)
longer = hl.hyperopt_loss_function(hyperopt_results, 100) longer = hl.hyperopt_loss_function(hyperopt_results, 100)
shorter = hl.hyperopt_loss_function(resultsb, 100) shorter = hl.hyperopt_loss_function(resultsb, 100)
assert shorter < longer assert shorter < longer
@ -310,7 +310,7 @@ def test_loss_calculation_has_limited_profit(default_conf, hyperopt_results) ->
results_under = hyperopt_results.copy() results_under = hyperopt_results.copy()
results_under['profit_percent'] = hyperopt_results['profit_percent'] / 2 results_under['profit_percent'] = hyperopt_results['profit_percent'] / 2
hl = HyperOptLossResolver(default_conf).hyperoptloss hl = HyperOptLossResolver.load_hyperoptloss(default_conf)
correct = hl.hyperopt_loss_function(hyperopt_results, 600) correct = hl.hyperopt_loss_function(hyperopt_results, 600)
over = hl.hyperopt_loss_function(results_over, 600) over = hl.hyperopt_loss_function(results_over, 600)
under = hl.hyperopt_loss_function(results_under, 600) under = hl.hyperopt_loss_function(results_under, 600)
@ -325,7 +325,7 @@ def test_sharpe_loss_prefers_higher_profits(default_conf, hyperopt_results) -> N
results_under['profit_percent'] = hyperopt_results['profit_percent'] / 2 results_under['profit_percent'] = hyperopt_results['profit_percent'] / 2
default_conf.update({'hyperopt_loss': 'SharpeHyperOptLoss'}) default_conf.update({'hyperopt_loss': 'SharpeHyperOptLoss'})
hl = HyperOptLossResolver(default_conf).hyperoptloss hl = HyperOptLossResolver.load_hyperoptloss(default_conf)
correct = hl.hyperopt_loss_function(hyperopt_results, len(hyperopt_results), correct = hl.hyperopt_loss_function(hyperopt_results, len(hyperopt_results),
datetime(2019, 1, 1), datetime(2019, 5, 1)) datetime(2019, 1, 1), datetime(2019, 5, 1))
over = hl.hyperopt_loss_function(results_over, len(hyperopt_results), over = hl.hyperopt_loss_function(results_over, len(hyperopt_results),
@ -343,7 +343,7 @@ def test_onlyprofit_loss_prefers_higher_profits(default_conf, hyperopt_results)
results_under['profit_percent'] = hyperopt_results['profit_percent'] / 2 results_under['profit_percent'] = hyperopt_results['profit_percent'] / 2
default_conf.update({'hyperopt_loss': 'OnlyProfitHyperOptLoss'}) default_conf.update({'hyperopt_loss': 'OnlyProfitHyperOptLoss'})
hl = HyperOptLossResolver(default_conf).hyperoptloss hl = HyperOptLossResolver.load_hyperoptloss(default_conf)
correct = hl.hyperopt_loss_function(hyperopt_results, len(hyperopt_results), correct = hl.hyperopt_loss_function(hyperopt_results, len(hyperopt_results),
datetime(2019, 1, 1), datetime(2019, 5, 1)) datetime(2019, 1, 1), datetime(2019, 5, 1))
over = hl.hyperopt_loss_function(results_over, len(hyperopt_results), over = hl.hyperopt_loss_function(results_over, len(hyperopt_results),