94 lines
3.8 KiB
Python
94 lines
3.8 KiB
Python
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"""
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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 skopt.space import Integer, Real, Categorical
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from freqtrade.strategy.interface import IStrategy
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class Parameter(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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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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"""
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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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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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def get_space(self, name: str) -> Union[Integer, Real, Categorical, None]:
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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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assert len(self.space) > 0
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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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"""
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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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"""
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def __init__(self, config):
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super().__init__(config)
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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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"""
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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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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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yield attr_name, attr
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def _load_params(self, params: dict) -> None:
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"""
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Set optimizeable parameter values.
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:param params: Dictionary with new parameter values.
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"""
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if not params:
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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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