def test_hyperoptlossresolver_noname(default_conf):
with pytest.raises(
OperationalException,
match=
"No Hyperopt loss set. Please use `--hyperopt-loss` to specify "
"the Hyperopt-Loss class to use."):
HyperOptLossResolver.load_hyperoptloss(default_conf)
def test_loss_calculation_prefer_correct_trade_count(default_conf, hyperopt_results) -> None:
hl = HyperOptLossResolver(default_conf).hyperoptloss
correct = hl.hyperopt_loss_function(hyperopt_results, 600)
over = hl.hyperopt_loss_function(hyperopt_results, 600 + 100)
under = hl.hyperopt_loss_function(hyperopt_results, 600 - 100)
assert over > correct
assert under > correct
def test_loss_calculation_prefer_shorter_trades(default_conf, hyperopt_results) -> None:
resultsb = hyperopt_results.copy()
resultsb.loc[1, 'trade_duration'] = 20
hl = HyperOptLossResolver(default_conf).hyperoptloss
longer = hl.hyperopt_loss_function(hyperopt_results, 100)
shorter = hl.hyperopt_loss_function(resultsb, 100)
assert shorter < longer
def test_loss_calculation_has_limited_profit(default_conf, hyperopt_results) -> None:
results_over = hyperopt_results.copy()
results_over['profit_percent'] = hyperopt_results['profit_percent'] * 2
results_under = hyperopt_results.copy()
results_under['profit_percent'] = hyperopt_results['profit_percent'] / 2
hl = HyperOptLossResolver(default_conf).hyperoptloss
correct = hl.hyperopt_loss_function(hyperopt_results, 600)
over = hl.hyperopt_loss_function(results_over, 600)
under = hl.hyperopt_loss_function(results_under, 600)
assert over < correct
assert under > correct
def test_onlyprofit_loss_prefers_higher_profits(default_conf, hyperopt_results) -> None:
results_over = hyperopt_results.copy()
results_over['profit_percent'] = hyperopt_results['profit_percent'] * 2
results_under = hyperopt_results.copy()
results_under['profit_percent'] = hyperopt_results['profit_percent'] / 2
default_conf.update({'hyperopt_loss': 'OnlyProfitHyperOptLoss'})
hl = HyperOptLossResolver(default_conf).hyperoptloss
correct = hl.hyperopt_loss_function(hyperopt_results, len(hyperopt_results),
datetime(2019, 1, 1), datetime(2019, 5, 1))
over = hl.hyperopt_loss_function(results_over, len(hyperopt_results),
datetime(2019, 1, 1), datetime(2019, 5, 1))
under = hl.hyperopt_loss_function(results_under, len(hyperopt_results),
datetime(2019, 1, 1), datetime(2019, 5, 1))
assert over < correct
assert under > correct
def __init__(self, config: Dict[str, Any]) -> None:
self.config = config
self.backtesting = Backtesting(self.config)
if not self.config.get('hyperopt'):
self.custom_hyperopt = HyperOptAuto(self.config)
else:
self.custom_hyperopt = HyperOptResolver.load_hyperopt(self.config)
self.custom_hyperopt.strategy = self.backtesting.strategy
self.custom_hyperoptloss = HyperOptLossResolver.load_hyperoptloss(self.config)
self.calculate_loss = self.custom_hyperoptloss.hyperopt_loss_function
time_now = datetime.now().strftime("%Y-%m-%d_%H-%M-%S")
strategy = str(self.config['strategy'])
self.results_file = (self.config['user_data_dir'] /
'hyperopt_results' /
f'strategy_{strategy}_hyperopt_results_{time_now}.pickle')
self.data_pickle_file = (self.config['user_data_dir'] /
'hyperopt_results' / 'hyperopt_tickerdata.pkl')
self.total_epochs = config.get('epochs', 0)
self.current_best_loss = 100
self.clean_hyperopt()
self.num_epochs_saved = 0
# Previous evaluations
self.epochs: List = []
# Populate functions here (hasattr is slow so should not be run during "regular" operations)
if hasattr(self.custom_hyperopt, 'populate_indicators'):
self.backtesting.strategy.advise_indicators = ( # type: ignore
self.custom_hyperopt.populate_indicators) # type: ignore
if hasattr(self.custom_hyperopt, 'populate_buy_trend'):
self.backtesting.strategy.advise_buy = ( # type: ignore
self.custom_hyperopt.populate_buy_trend) # type: ignore
if hasattr(self.custom_hyperopt, 'populate_sell_trend'):
self.backtesting.strategy.advise_sell = ( # type: ignore
self.custom_hyperopt.populate_sell_trend) # type: ignore
# Use max_open_trades for hyperopt as well, except --disable-max-market-positions is set
if self.config.get('use_max_market_positions', True):
self.max_open_trades = self.config['max_open_trades']
else:
logger.debug('Ignoring max_open_trades (--disable-max-market-positions was used) ...')
self.max_open_trades = 0
self.position_stacking = self.config.get('position_stacking', False)
if self.has_space('sell'):
# Make sure use_sell_signal is enabled
if 'ask_strategy' not in self.config:
self.config['ask_strategy'] = {}
self.config['ask_strategy']['use_sell_signal'] = True
self.print_all = self.config.get('print_all', False)
self.hyperopt_table_header = 0
self.print_colorized = self.config.get('print_colorized', False)
self.print_json = self.config.get('print_json', False)
def __init__(self, config: Dict[str, Any]) -> None:
self.config = config
self.backtesting = Backtesting(self.config)
self.custom_hyperopt = HyperOptResolver(self.config).hyperopt
self.custom_hyperoptloss = HyperOptLossResolver(
self.config).hyperoptloss
self.calculate_loss = self.custom_hyperoptloss.hyperopt_loss_function
self.trials_file = (self.config['user_data_dir'] / 'hyperopt_results' /
'hyperopt_results.pickle')
self.tickerdata_pickle = (self.config['user_data_dir'] /
'hyperopt_results' /
'hyperopt_tickerdata.pkl')
self.total_epochs = config.get('epochs', 0)
self.current_best_loss = 100
if not self.config.get('hyperopt_continue'):
self.clean_hyperopt()
else:
logger.info("Continuing on previous hyperopt results.")
self.num_trials_saved = 0
# Previous evaluations
self.trials: List = []
# Populate functions here (hasattr is slow so should not be run during "regular" operations)
if hasattr(self.custom_hyperopt, 'populate_indicators'):
self.backtesting.strategy.advise_indicators = \
self.custom_hyperopt.populate_indicators # type: ignore
if hasattr(self.custom_hyperopt, 'populate_buy_trend'):
self.backtesting.strategy.advise_buy = \
self.custom_hyperopt.populate_buy_trend # type: ignore
if hasattr(self.custom_hyperopt, 'populate_sell_trend'):
self.backtesting.strategy.advise_sell = \
self.custom_hyperopt.populate_sell_trend # type: ignore
# Use max_open_trades for hyperopt as well, except --disable-max-market-positions is set
if self.config.get('use_max_market_positions', True):
self.max_open_trades = self.config['max_open_trades']
else:
logger.debug(
'Ignoring max_open_trades (--disable-max-market-positions was used) ...'
)
self.max_open_trades = 0
self.position_stacking = self.config.get('position_stacking', False)
if self.has_space('sell'):
# Make sure use_sell_signal is enabled
if 'ask_strategy' not in self.config:
self.config['ask_strategy'] = {}
self.config['ask_strategy']['use_sell_signal'] = True
self.print_all = self.config.get('print_all', False)
self.print_colorized = self.config.get('print_colorized', False)
self.print_json = self.config.get('print_json', False)
def __init__(self, config: Dict[str, Any]) -> None:
self.buy_space: List[Dimension] = []
self.sell_space: List[Dimension] = []
self.protection_space: List[Dimension] = []
self.roi_space: List[Dimension] = []
self.stoploss_space: List[Dimension] = []
self.trailing_space: List[Dimension] = []
self.dimensions: List[Dimension] = []
self.config = config
self.backtesting = Backtesting(self.config)
self.pairlist = self.backtesting.pairlists.whitelist
if not self.config.get('hyperopt'):
self.custom_hyperopt = HyperOptAuto(self.config)
else:
raise OperationalException(
"Using separate Hyperopt files has been removed in 2021.9. Please convert "
"your existing Hyperopt file to the new Hyperoptable strategy interface")
self.backtesting._set_strategy(self.backtesting.strategylist[0])
self.custom_hyperopt.strategy = self.backtesting.strategy
self.custom_hyperoptloss = HyperOptLossResolver.load_hyperoptloss(self.config)
self.calculate_loss = self.custom_hyperoptloss.hyperopt_loss_function
time_now = datetime.now().strftime("%Y-%m-%d_%H-%M-%S")
strategy = str(self.config['strategy'])
self.results_file: Path = (self.config['user_data_dir'] / 'hyperopt_results' /
f'strategy_{strategy}_{time_now}.fthypt')
self.data_pickle_file = (self.config['user_data_dir'] /
'hyperopt_results' / 'hyperopt_tickerdata.pkl')
self.total_epochs = config.get('epochs', 0)
self.current_best_loss = 100
self.clean_hyperopt()
self.num_epochs_saved = 0
self.current_best_epoch: Optional[Dict[str, Any]] = None
# Use max_open_trades for hyperopt as well, except --disable-max-market-positions is set
if self.config.get('use_max_market_positions', True):
self.max_open_trades = self.config['max_open_trades']
else:
logger.debug('Ignoring max_open_trades (--disable-max-market-positions was used) ...')
self.max_open_trades = 0
self.position_stacking = self.config.get('position_stacking', False)
if HyperoptTools.has_space(self.config, 'sell'):
# Make sure use_sell_signal is enabled
if 'ask_strategy' not in self.config:
self.config['ask_strategy'] = {}
self.config['ask_strategy']['use_sell_signal'] = True
self.print_all = self.config.get('print_all', False)
self.hyperopt_table_header = 0
self.print_colorized = self.config.get('print_colorized', False)
self.print_json = self.config.get('print_json', False)
def test_hyperoptlossresolver(mocker, default_conf, caplog) -> None:
hl = DefaultHyperOptLoss
mocker.patch(
'freqtrade.resolvers.hyperopt_resolver.HyperOptLossResolver._load_hyperoptloss',
MagicMock(return_value=hl))
x = HyperOptLossResolver(default_conf, ).hyperoptloss
assert hasattr(x, "hyperopt_loss_function")
def test_hyperoptlossresolver(mocker, default_conf) -> None:
hl = ShortTradeDurHyperOptLoss
mocker.patch(
'freqtrade.resolvers.hyperopt_resolver.HyperOptLossResolver.load_object',
MagicMock(return_value=hl()))
default_conf.update({'hyperopt_loss': 'SharpeHyperOptLossDaily'})
x = HyperOptLossResolver.load_hyperoptloss(default_conf)
assert hasattr(x, "hyperopt_loss_function")
def test_loss_calculation_prefer_shorter_trades(default_conf, hyperopt_results) -> None:
resultsb = hyperopt_results.copy()
resultsb.loc[1, 'trade_duration'] = 20
hl = HyperOptLossResolver.load_hyperoptloss(default_conf)
longer = hl.hyperopt_loss_function(hyperopt_results, 100,
datetime(2019, 1, 1), datetime(2019, 5, 1))
shorter = hl.hyperopt_loss_function(resultsb, 100,
datetime(2019, 1, 1), datetime(2019, 5, 1))
assert shorter < longer
def test_loss_calculation_prefer_correct_trade_count(default_conf, hyperopt_results) -> None:
hl = HyperOptLossResolver.load_hyperoptloss(default_conf)
correct = hl.hyperopt_loss_function(hyperopt_results, 600,
datetime(2019, 1, 1), datetime(2019, 5, 1))
over = hl.hyperopt_loss_function(hyperopt_results, 600 + 100,
datetime(2019, 1, 1), datetime(2019, 5, 1))
under = hl.hyperopt_loss_function(hyperopt_results, 600 - 100,
datetime(2019, 1, 1), datetime(2019, 5, 1))
assert over > correct
assert under > correct
def test_loss_calculation_has_limited_profit(default_conf, hyperopt_results) -> None:
results_over = hyperopt_results.copy()
results_over['profit_percent'] = hyperopt_results['profit_percent'] * 2
results_under = hyperopt_results.copy()
results_under['profit_percent'] = hyperopt_results['profit_percent'] / 2
hl = HyperOptLossResolver.load_hyperoptloss(default_conf)
correct = hl.hyperopt_loss_function(hyperopt_results, 600,
datetime(2019, 1, 1), datetime(2019, 5, 1))
over = hl.hyperopt_loss_function(results_over, 600,
datetime(2019, 1, 1), datetime(2019, 5, 1))
under = hl.hyperopt_loss_function(results_under, 600,
datetime(2019, 1, 1), datetime(2019, 5, 1))
assert over < correct
assert under > correct
def test_sortino_loss_daily_prefers_higher_profits(default_conf, hyperopt_results) -> None:
results_over = hyperopt_results.copy()
results_over['profit_percent'] = hyperopt_results['profit_percent'] * 2
results_under = hyperopt_results.copy()
results_under['profit_percent'] = hyperopt_results['profit_percent'] / 2
default_conf.update({'hyperopt_loss': 'SortinoHyperOptLossDaily'})
hl = HyperOptLossResolver.load_hyperoptloss(default_conf)
correct = hl.hyperopt_loss_function(hyperopt_results, len(hyperopt_results),
datetime(2019, 1, 1), datetime(2019, 5, 1))
over = hl.hyperopt_loss_function(results_over, len(hyperopt_results),
datetime(2019, 1, 1), datetime(2019, 5, 1))
under = hl.hyperopt_loss_function(results_under, len(hyperopt_results),
datetime(2019, 1, 1), datetime(2019, 5, 1))
assert over < correct
assert under > correct
def test_loss_calculation_has_limited_profit(hyperopt_conf,
hyperopt_results) -> None:
results_over = hyperopt_results.copy()
results_over['profit_ratio'] = hyperopt_results['profit_ratio'] * 2
results_under = hyperopt_results.copy()
results_under['profit_ratio'] = hyperopt_results['profit_ratio'] / 2
hyperopt_conf.update({'hyperopt_loss': "ShortTradeDurHyperOptLoss"})
hl = HyperOptLossResolver.load_hyperoptloss(hyperopt_conf)
correct = hl.hyperopt_loss_function(hyperopt_results, 600,
datetime(2019, 1, 1),
datetime(2019, 5, 1))
over = hl.hyperopt_loss_function(results_over, 600, datetime(2019, 1, 1),
datetime(2019, 5, 1))
under = hl.hyperopt_loss_function(results_under, 600, datetime(2019, 1, 1),
datetime(2019, 5, 1))
assert over < correct
assert under > correct
def test_loss_functions_better_profits(default_conf, hyperopt_results,
lossfunction) -> None:
results_over = hyperopt_results.copy()
results_over['profit_abs'] = hyperopt_results['profit_abs'] * 2 + 0.2
results_over['profit_ratio'] = hyperopt_results['profit_ratio'] * 2
results_under = hyperopt_results.copy()
results_under['profit_abs'] = hyperopt_results['profit_abs'] / 2 - 0.2
results_under['profit_ratio'] = hyperopt_results['profit_ratio'] / 2
default_conf.update({'hyperopt_loss': lossfunction})
hl = HyperOptLossResolver.load_hyperoptloss(default_conf)
correct = hl.hyperopt_loss_function(hyperopt_results,
len(hyperopt_results),
datetime(2019, 1, 1),
datetime(2019, 5, 1))
over = hl.hyperopt_loss_function(results_over, len(results_over),
datetime(2019, 1, 1),
datetime(2019, 5, 1))
under = hl.hyperopt_loss_function(results_under, len(results_under),
datetime(2019, 1, 1),
datetime(2019, 5, 1))
assert over < correct
assert under > correct
def test_loss_functions_better_profits(default_conf, hyperopt_results,
lossfunction) -> None:
results_over = hyperopt_results.copy()
results_over['profit_abs'] = hyperopt_results['profit_abs'] * 2 + 0.2
results_over['profit_ratio'] = hyperopt_results['profit_ratio'] * 2
results_under = hyperopt_results.copy()
results_under['profit_abs'] = hyperopt_results['profit_abs'] / 2 - 0.2
results_under['profit_ratio'] = hyperopt_results['profit_ratio'] / 2
default_conf.update({'hyperopt_loss': lossfunction})
hl = HyperOptLossResolver.load_hyperoptloss(default_conf)
correct = hl.hyperopt_loss_function(
hyperopt_results,
trade_count=len(hyperopt_results),
min_date=datetime(2019, 1, 1),
max_date=datetime(2019, 5, 1),
config=default_conf,
processed=None,
backtest_stats={'profit_total': hyperopt_results['profit_abs'].sum()})
over = hl.hyperopt_loss_function(
results_over,
trade_count=len(results_over),
min_date=datetime(2019, 1, 1),
max_date=datetime(2019, 5, 1),
config=default_conf,
processed=None,
backtest_stats={'profit_total': results_over['profit_abs'].sum()})
under = hl.hyperopt_loss_function(
results_under,
trade_count=len(results_under),
min_date=datetime(2019, 1, 1),
max_date=datetime(2019, 5, 1),
config=default_conf,
processed=None,
backtest_stats={'profit_total': results_under['profit_abs'].sum()})
assert over < correct
assert under > correct
def __init__(self, config: Dict[str, Any]) -> None:
super().__init__(config)
self.custom_hyperopt = HyperOptResolver(self.config).hyperopt
self.custom_hyperoptloss = HyperOptLossResolver(
self.config).hyperoptloss
self.calculate_loss = self.custom_hyperoptloss.hyperopt_loss_function
self.total_tries = config.get('epochs', 0)
self.current_best_loss = 100
if not self.config.get('hyperopt_continue'):
self.clean_hyperopt()
else:
logger.info("Continuing on previous hyperopt results.")
# Previous evaluations
self.trials_file = TRIALSDATA_PICKLE
self.trials: List = []
# Populate functions here (hasattr is slow so should not be run during "regular" operations)
if hasattr(self.custom_hyperopt, 'populate_buy_trend'):
self.advise_buy = self.custom_hyperopt.populate_buy_trend # type: ignore
if hasattr(self.custom_hyperopt, 'populate_sell_trend'):
self.advise_sell = self.custom_hyperopt.populate_sell_trend # type: ignore
# Use max_open_trades for hyperopt as well, except --disable-max-market-positions is set
if self.config.get('use_max_market_positions', True):
self.max_open_trades = self.config['max_open_trades']
else:
logger.debug(
'Ignoring max_open_trades (--disable-max-market-positions was used) ...'
)
self.max_open_trades = 0
self.position_stacking = self.config.get('position_stacking', False),
def test_hyperoptlossresolver_wrongname(mocker, default_conf, caplog) -> None:
default_conf.update({'hyperopt_loss': "NonExistingLossClass"})
with pytest.raises(OperationalException,
match=r'Impossible to load HyperoptLoss.*'):
HyperOptLossResolver(default_conf, ).hyperopt
