90 lines
3.4 KiB
Python
90 lines
3.4 KiB
Python
"""
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HyperOptAuto class.
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This module implements a convenience auto-hyperopt class, which can be used together with strategies
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that implement IHyperStrategy interface.
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"""
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from contextlib import suppress
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from typing import Any, Callable, Dict, List
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from pandas import DataFrame
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with suppress(ImportError):
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from skopt.space import Dimension
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from freqtrade.optimize.hyperopt_interface import IHyperOpt
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class HyperOptAuto(IHyperOpt):
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"""
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This class delegates functionality to Strategy(IHyperStrategy) and Strategy.HyperOpt classes.
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Most of the time Strategy.HyperOpt class would only implement indicator_space and
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sell_indicator_space methods, but other hyperopt methods can be overridden as well.
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"""
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def buy_strategy_generator(self, params: Dict[str, Any]) -> Callable:
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def populate_buy_trend(dataframe: DataFrame, metadata: dict):
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for attr_name, attr in self.strategy.enumerate_parameters('buy'):
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if attr.optimize:
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# noinspection PyProtectedMember
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attr._set_value(params[attr_name])
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return self.strategy.populate_buy_trend(dataframe, metadata)
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return populate_buy_trend
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def sell_strategy_generator(self, params: Dict[str, Any]) -> Callable:
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def populate_sell_trend(dataframe: DataFrame, metadata: dict):
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for attr_name, attr in self.strategy.enumerate_parameters('sell'):
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if attr.optimize:
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# noinspection PyProtectedMember
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attr._set_value(params[attr_name])
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return self.strategy.populate_sell_trend(dataframe, metadata)
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return populate_sell_trend
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def _get_func(self, name) -> Callable:
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"""
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Return a function defined in Strategy.HyperOpt class, or one defined in super() class.
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:param name: function name.
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:return: a requested function.
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"""
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hyperopt_cls = getattr(self.strategy, 'HyperOpt', None)
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default_func = getattr(super(), name)
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if hyperopt_cls:
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return getattr(hyperopt_cls, name, default_func)
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else:
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return default_func
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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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if attr.optimize:
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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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if len(indicator_space) > 0:
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return indicator_space
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else:
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return self._get_func(fallback_method_name)()
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def indicator_space(self) -> List['Dimension']:
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return self._get_indicator_space('buy', 'indicator_space')
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def sell_indicator_space(self) -> List['Dimension']:
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return self._get_indicator_space('sell', 'sell_indicator_space')
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def generate_roi_table(self, params: Dict) -> Dict[int, float]:
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return self._get_func('generate_roi_table')(params)
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def roi_space(self) -> List['Dimension']:
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return self._get_func('roi_space')()
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def stoploss_space(self) -> List['Dimension']:
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return self._get_func('stoploss_space')()
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def generate_trailing_params(self, params: Dict) -> Dict:
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return self._get_func('generate_trailing_params')(params)
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def trailing_space(self) -> List['Dimension']:
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return self._get_func('trailing_space')()
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