freqtrade_origin/freqtrade/optimize/hyperopt_auto.py

"""
HyperOptAuto class.
This module implements a convenience auto-hyperopt class, which can be used together with strategies
 that implement IHyperStrategy interface.
"""

import logging
from contextlib import suppress
from typing import Callable, Dict, List

from freqtrade.exceptions import OperationalException


with suppress(ImportError):
    from skopt.space import Dimension

from freqtrade.optimize.hyperopt_interface import EstimatorType, IHyperOpt


logger = logging.getLogger(__name__)


def _format_exception_message(space: str, ignore_missing_space: bool) -> None:
    msg = (
        f"The '{space}' space is included into the hyperoptimization "
        f"but no parameter for this space was found in your Strategy. "
    )
    if ignore_missing_space:
        logger.warning(msg + "This space will be ignored.")
    else:
        raise OperationalException(
            msg + f"Please make sure to have parameters for this space enabled for optimization "
            f"or remove the '{space}' space from hyperoptimization."
        )


class HyperOptAuto(IHyperOpt):
    """
    This class delegates functionality to Strategy(IHyperStrategy) and Strategy.HyperOpt classes.
     Most of the time Strategy.HyperOpt class would only implement indicator_space and
     sell_indicator_space methods, but other hyperopt methods can be overridden as well.
    """

    def _get_func(self, name) -> Callable:
        """
        Return a function defined in Strategy.HyperOpt class, or one defined in super() class.
        :param name: function name.
        :return: a requested function.
        """
        hyperopt_cls = getattr(self.strategy, "HyperOpt", None)
        default_func = getattr(super(), name)
        if hyperopt_cls:
            return getattr(hyperopt_cls, name, default_func)
        else:
            return default_func

    def _generate_indicator_space(self, category):
        for attr_name, attr in self.strategy.enumerate_parameters(category):
            if attr.optimize:
                yield attr.get_space(attr_name)

    def _get_indicator_space(self, category) -> List:
        # TODO: is this necessary, or can we call "generate_space" directly?
        indicator_space = list(self._generate_indicator_space(category))
        if len(indicator_space) > 0:
            return indicator_space
        else:
            _format_exception_message(
                category, self.config.get("hyperopt_ignore_missing_space", False)
            )
            return []

    def buy_indicator_space(self) -> List["Dimension"]:
        return self._get_indicator_space("buy")

    def sell_indicator_space(self) -> List["Dimension"]:
        return self._get_indicator_space("sell")

    def protection_space(self) -> List["Dimension"]:
        return self._get_indicator_space("protection")

    def generate_roi_table(self, params: Dict) -> Dict[int, float]:
        return self._get_func("generate_roi_table")(params)

    def roi_space(self) -> List["Dimension"]:
        return self._get_func("roi_space")()

    def stoploss_space(self) -> List["Dimension"]:
        return self._get_func("stoploss_space")()

    def generate_trailing_params(self, params: Dict) -> Dict:
        return self._get_func("generate_trailing_params")(params)

    def trailing_space(self) -> List["Dimension"]:
        return self._get_func("trailing_space")()

    def max_open_trades_space(self) -> List["Dimension"]:
        return self._get_func("max_open_trades_space")()

    def generate_estimator(self, dimensions: List["Dimension"], **kwargs) -> EstimatorType:
        return self._get_func("generate_estimator")(dimensions=dimensions, **kwargs)