[SQUASH] Add a way to temporarily disable a parameter (excludes from parameter loading/hyperopt) and print parameter values when executed.
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@ -51,7 +51,8 @@ class HyperOptAuto(IHyperOpt):
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def _generate_indicator_space(self, category):
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for attr_name, attr in self.strategy.enumerate_parameters(category):
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yield attr.get_space(attr_name)
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if attr.enabled:
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yield attr.get_space(attr_name)
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def _get_indicator_space(self, category, fallback_method_name):
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indicator_space = list(self._generate_indicator_space(category))
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@ -2,6 +2,7 @@
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IHyperStrategy interface, hyperoptable Parameter class.
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This module defines a base class for auto-hyperoptable strategies.
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"""
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import logging
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from contextlib import suppress
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from typing import Iterator, Tuple, Any, Optional, Sequence, Union
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@ -11,6 +12,9 @@ with suppress(ImportError):
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from freqtrade.exceptions import OperationalException
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logger = logging.getLogger(__name__)
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class BaseParameter(object):
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"""
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Defines a parameter that can be optimized by hyperopt.
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@ -21,7 +25,7 @@ class BaseParameter(object):
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opt_range: Sequence[Any]
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def __init__(self, *, opt_range: Sequence[Any], default: Any, space: Optional[str] = None,
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**kwargs):
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enabled: bool = True, **kwargs):
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"""
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Initialize hyperopt-optimizable parameter.
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:param space: A parameter category. Can be 'buy' or 'sell'. This parameter is optional if
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@ -36,6 +40,7 @@ class BaseParameter(object):
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self._space_params = kwargs
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self.value = default
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self.opt_range = opt_range
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self.enabled = enabled
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def __repr__(self):
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return f'{self.__class__.__name__}({self.value})'
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@ -50,7 +55,7 @@ class IntParameter(BaseParameter):
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opt_range: Sequence[int]
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def __init__(self, low: Union[int, Sequence[int]], high: Optional[int] = None, *, default: int,
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space: Optional[str] = None, **kwargs):
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space: Optional[str] = None, enabled: bool = True, **kwargs):
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"""
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Initialize hyperopt-optimizable parameter.
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:param low: lower end of optimization space or [low, high].
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@ -67,7 +72,8 @@ class IntParameter(BaseParameter):
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opt_range = low
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else:
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opt_range = [low, high]
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super().__init__(opt_range=opt_range, default=default, space=space, **kwargs)
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super().__init__(opt_range=opt_range, default=default, space=space, enabled=enabled,
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**kwargs)
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def get_space(self, name: str) -> 'Integer':
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"""
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@ -83,7 +89,7 @@ class FloatParameter(BaseParameter):
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opt_range: Sequence[float]
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def __init__(self, low: Union[float, Sequence[float]], high: Optional[int] = None, *,
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default: float, space: Optional[str] = None, **kwargs):
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default: float, space: Optional[str] = None, enabled: bool = True, **kwargs):
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"""
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Initialize hyperopt-optimizable parameter.
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:param low: lower end of optimization space or [low, high].
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@ -100,7 +106,8 @@ class FloatParameter(BaseParameter):
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opt_range = low
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else:
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opt_range = [low, high]
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super().__init__(opt_range=opt_range, default=default, space=space, **kwargs)
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super().__init__(opt_range=opt_range, default=default, space=space, enabled=enabled,
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**kwargs)
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def get_space(self, name: str) -> 'Real':
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"""
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@ -116,7 +123,7 @@ class CategoricalParameter(BaseParameter):
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opt_range: Sequence[Any]
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def __init__(self, categories: Sequence[Any], *, default: Optional[Any] = None,
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space: Optional[str] = None, **kwargs):
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space: Optional[str] = None, enabled: bool = True, **kwargs):
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"""
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Initialize hyperopt-optimizable parameter.
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:param categories: Optimization space, [a, b, ...].
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@ -130,7 +137,8 @@ class CategoricalParameter(BaseParameter):
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if len(categories) < 2:
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raise OperationalException(
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'IntParameter space must be [a, b, ...] (at least two parameters)')
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super().__init__(opt_range=categories, default=default, space=space, **kwargs)
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super().__init__(opt_range=categories, default=default, space=space, enabled=enabled,
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**kwargs)
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def get_space(self, name: str) -> 'Categorical':
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"""
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@ -167,7 +175,8 @@ class HyperStrategyMixin(object):
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if issubclass(attr.__class__, BaseParameter):
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if category is None or category == attr.category or \
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attr_name.startswith(category + '_'):
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yield attr_name, attr
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if attr.enabled:
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yield attr_name, attr
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def _load_params(self, params: dict) -> None:
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"""
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@ -178,4 +187,9 @@ class HyperStrategyMixin(object):
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return
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for attr_name, attr in self.enumerate_parameters():
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if attr_name in params:
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attr.value = params[attr_name]
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if attr.enabled:
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attr.value = params[attr_name]
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logger.info(f'attr_name = {attr.value}')
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else:
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logger.warning(f'Parameter "{attr_name}" exists, but is disabled. '
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f'Default value "{attr.value}" used.')
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