[SQUASH] Address PR comments.
* Split Parameter into IntParameter/FloatParameter/CategoricalParameter. * Rename IHyperStrategy to HyperStrategyMixin and use it as mixin. * --hyperopt parameter is now optional if strategy uses HyperStrategyMixin. * Use OperationalException() instead of asserts.
This commit is contained in:
Rokas Kupstys
@@ -2,5 +2,6 @@
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from freqtrade.exchange import (timeframe_to_minutes, timeframe_to_msecs, timeframe_to_next_date,
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timeframe_to_prev_date, timeframe_to_seconds)
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from freqtrade.strategy.interface import IStrategy
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from freqtrade.strategy.hyper import IHyperStrategy, Parameter
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from freqtrade.strategy.hyper import HyperStrategyMixin, IntParameter, FloatParameter,\
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CategoricalParameter
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from freqtrade.strategy.strategy_helper import merge_informative_pair, stoploss_from_open
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@@ -2,83 +2,158 @@
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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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from abc import ABC
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from typing import Union, List, Iterator, Tuple
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from typing import Iterator, Tuple, Any, Optional, Sequence
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from skopt.space import Integer, Real, Categorical
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from freqtrade.strategy.interface import IStrategy
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from freqtrade.exceptions import OperationalException
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class Parameter(object):
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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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"""
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default: Union[int, float, str, bool]
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space: List[Union[int, float, str, bool]]
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category: str
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category: Optional[str]
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default: Any
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value: Any
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space: Sequence[Any]
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def __init__(self, *, space: List[Union[int, float, str, bool]], default: Union[int, float, str, bool] = None,
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category: str = None, **kwargs):
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def __init__(self, *, space: Sequence[Any], default: Any, category: Optional[str] = None,
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**kwargs):
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"""
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Initialize hyperopt-optimizable parameter.
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:param space: Optimization space. [min, max] for ints and floats or a list of strings for categorial parameters.
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:param default: A default value. Required for ints and floats, optional for categorial parameters (first item
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from the space will be used). Type of default value determines skopt space used for optimization.
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:param category: A parameter category. Can be 'buy' or 'sell'. This parameter is optional if parameter field
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name is prefixed with 'buy_' or 'sell_'.
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:param kwargs: Extra parameters to skopt.space.(Integer|Real|Categorical).
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"""
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assert 'name' not in kwargs, 'Name is determined by parameter field name and can not be specified manually.'
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self.value = default
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self.space = space
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if 'name' in kwargs:
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raise OperationalException(
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'Name is determined by parameter field name and can not be specified manually.')
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self.category = category
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self._space_params = kwargs
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if default is None:
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assert len(space) > 0
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self.value = space[0]
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self.value = default
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self.space = space
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def get_space(self, name: str) -> Union[Integer, Real, Categorical, None]:
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def __repr__(self):
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return f'{self.__class__.__name__}({self.value})'
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class IntParameter(BaseParameter):
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default: int
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value: int
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space: Sequence[int]
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def __init__(self, *, space: Sequence[int], default: int, category: Optional[str] = None,
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**kwargs):
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"""
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Initialize hyperopt-optimizable parameter.
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:param space: Optimization space, [min, max].
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:param default: A default value.
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:param category: A parameter category. Can be 'buy' or 'sell'. This parameter is optional if parameter field
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name is prefixed with 'buy_' or 'sell_'.
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:param kwargs: Extra parameters to skopt.space.Integer.
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"""
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if len(space) != 2:
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raise OperationalException('IntParameter space must be [min, max]')
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super().__init__(space=space, default=default, category=category, **kwargs)
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def get_space(self, name: str) -> Integer:
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"""
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Create skopt optimization space.
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:param name: A name of parameter field.
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:return: skopt space of this parameter, or None if parameter is not optimizable (i.e. space is set to None)
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"""
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if not self.space:
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return None
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if isinstance(self.value, int):
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assert len(self.space) == 2
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return Integer(*self.space, name=name, **self._space_params)
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if isinstance(self.value, float):
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assert len(self.space) == 2
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return Real(*self.space, name=name, **self._space_params)
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return Integer(*self.space, name=name, **self._space_params)
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assert len(self.space) > 0
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class FloatParameter(BaseParameter):
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default: float
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value: float
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space: Sequence[float]
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def __init__(self, *, space: Sequence[float], default: float, category: Optional[str] = None,
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**kwargs):
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"""
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Initialize hyperopt-optimizable parameter.
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:param space: Optimization space, [min, max].
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:param default: A default value.
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:param category: A parameter category. Can be 'buy' or 'sell'. This parameter is optional if parameter field
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name is prefixed with 'buy_' or 'sell_'.
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:param kwargs: Extra parameters to skopt.space.Real.
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"""
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if len(space) != 2:
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raise OperationalException('IntParameter space must be [min, max]')
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super().__init__(space=space, default=default, category=category, **kwargs)
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def get_space(self, name: str) -> Real:
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"""
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Create skopt optimization space.
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:param name: A name of parameter field.
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"""
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return Real(*self.space, name=name, **self._space_params)
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class CategoricalParameter(BaseParameter):
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default: Any
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value: Any
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space: Sequence[Any]
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def __init__(self, *, space: Sequence[Any], default: Optional[Any] = None,
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category: Optional[str] = None,
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**kwargs):
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"""
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Initialize hyperopt-optimizable parameter.
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:param space: Optimization space, [a, b, ...].
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:param default: A default value. If not specified, first item from specified space will be
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used.
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:param category: A parameter category. Can be 'buy' or 'sell'. This parameter is optional if
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parameter field
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name is prefixed with 'buy_' or 'sell_'.
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:param kwargs: Extra parameters to skopt.space.Categorical.
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"""
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if len(space) < 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__(space=space, default=default, category=category, **kwargs)
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def get_space(self, name: str) -> Categorical:
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"""
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Create skopt optimization space.
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:param name: A name of parameter field.
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"""
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return Categorical(self.space, name=name, **self._space_params)
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class IHyperStrategy(IStrategy, ABC):
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class HyperStrategyMixin(object):
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"""
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A helper base class which allows HyperOptAuto class to reuse implementations of of buy/sell strategy logic.
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A helper base class which allows HyperOptAuto class to reuse implementations of of buy/sell
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strategy logic.
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"""
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def __init__(self, config):
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super().__init__(config)
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# Hint that class can be used with HyperOptAuto.
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HYPER_STRATEGY = 1
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def __init__(self):
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"""
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Initialize hyperoptable strategy mixin.
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:param config:
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"""
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self._load_params(getattr(self, 'buy_params', None))
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self._load_params(getattr(self, 'sell_params', None))
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def enumerate_parameters(self, category: str = None) -> Iterator[Tuple[str, Parameter]]:
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def enumerate_parameters(self, category: str = None) -> Iterator[Tuple[str, BaseParameter]]:
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"""
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Find all optimizeable parameters and return (name, attr) iterator.
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:param category:
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:return:
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"""
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assert category in ('buy', 'sell', None)
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if category not in ('buy', 'sell', None):
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raise OperationalException('Category must be one of: "buy", "sell", None.')
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for attr_name in dir(self):
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if not attr_name.startswith('__'): # Ignore internals, not strictly necessary.
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attr = getattr(self, attr_name)
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if isinstance(attr, Parameter):
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if category is None or category == attr.category or attr_name.startswith(category + '_'):
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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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def _load_params(self, params: dict) -> None:
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