mirror of
https://github.com/freqtrade/freqtrade.git
synced 2024-11-10 18:23:55 +00:00
300 lines
12 KiB
Python
300 lines
12 KiB
Python
"""
|
|
IHyperStrategy interface, hyperoptable Parameter class.
|
|
This module defines a base class for auto-hyperoptable strategies.
|
|
"""
|
|
import logging
|
|
from abc import ABC, abstractmethod
|
|
from contextlib import suppress
|
|
from typing import Any, Optional, Sequence, Union
|
|
|
|
from freqtrade.enums import HyperoptState
|
|
from freqtrade.optimize.hyperopt_tools import HyperoptStateContainer
|
|
|
|
|
|
with suppress(ImportError):
|
|
from skopt.space import Integer, Real, Categorical
|
|
from freqtrade.optimize.space import SKDecimal
|
|
|
|
from freqtrade.exceptions import OperationalException
|
|
|
|
|
|
logger = logging.getLogger(__name__)
|
|
|
|
|
|
class BaseParameter(ABC):
|
|
"""
|
|
Defines a parameter that can be optimized by hyperopt.
|
|
"""
|
|
category: Optional[str]
|
|
default: Any
|
|
value: Any
|
|
in_space: bool = False
|
|
name: str
|
|
|
|
def __init__(self, *, default: Any, space: Optional[str] = None,
|
|
optimize: bool = True, load: bool = True, **kwargs):
|
|
"""
|
|
Initialize hyperopt-optimizable parameter.
|
|
:param space: A parameter category. Can be 'buy' or 'sell'. This parameter is optional if
|
|
parameter field
|
|
name is prefixed with 'buy_' or 'sell_'.
|
|
:param optimize: Include parameter in hyperopt optimizations.
|
|
:param load: Load parameter value from {space}_params.
|
|
:param kwargs: Extra parameters to skopt.space.(Integer|Real|Categorical).
|
|
"""
|
|
if 'name' in kwargs:
|
|
raise OperationalException(
|
|
'Name is determined by parameter field name and can not be specified manually.')
|
|
self.category = space
|
|
self._space_params = kwargs
|
|
self.value = default
|
|
self.optimize = optimize
|
|
self.load = load
|
|
|
|
def __repr__(self):
|
|
return f'{self.__class__.__name__}({self.value})'
|
|
|
|
@abstractmethod
|
|
def get_space(self, name: str) -> Union['Integer', 'Real', 'SKDecimal', 'Categorical']:
|
|
"""
|
|
Get-space - will be used by Hyperopt to get the hyperopt Space
|
|
"""
|
|
|
|
def can_optimize(self):
|
|
return (
|
|
self.in_space
|
|
and self.optimize
|
|
and HyperoptStateContainer.state != HyperoptState.OPTIMIZE
|
|
)
|
|
|
|
|
|
class NumericParameter(BaseParameter):
|
|
""" Internal parameter used for Numeric purposes """
|
|
float_or_int = Union[int, float]
|
|
default: float_or_int
|
|
value: float_or_int
|
|
|
|
def __init__(self, low: Union[float_or_int, Sequence[float_or_int]],
|
|
high: Optional[float_or_int] = None, *, default: float_or_int,
|
|
space: Optional[str] = None, optimize: bool = True, load: bool = True, **kwargs):
|
|
"""
|
|
Initialize hyperopt-optimizable numeric parameter.
|
|
Cannot be instantiated, but provides the validation for other numeric parameters
|
|
:param low: Lower end (inclusive) of optimization space or [low, high].
|
|
:param high: Upper end (inclusive) of optimization space.
|
|
Must be none of entire range is passed first parameter.
|
|
:param default: A default value.
|
|
:param space: A parameter category. Can be 'buy' or 'sell'. This parameter is optional if
|
|
parameter fieldname is prefixed with 'buy_' or 'sell_'.
|
|
:param optimize: Include parameter in hyperopt optimizations.
|
|
:param load: Load parameter value from {space}_params.
|
|
:param kwargs: Extra parameters to skopt.space.*.
|
|
"""
|
|
if high is not None and isinstance(low, Sequence):
|
|
raise OperationalException(f'{self.__class__.__name__} space invalid.')
|
|
if high is None or isinstance(low, Sequence):
|
|
if not isinstance(low, Sequence) or len(low) != 2:
|
|
raise OperationalException(f'{self.__class__.__name__} space must be [low, high]')
|
|
self.low, self.high = low
|
|
else:
|
|
self.low = low
|
|
self.high = high
|
|
|
|
super().__init__(default=default, space=space, optimize=optimize,
|
|
load=load, **kwargs)
|
|
|
|
|
|
class IntParameter(NumericParameter):
|
|
default: int
|
|
value: int
|
|
low: int
|
|
high: int
|
|
|
|
def __init__(self, low: Union[int, Sequence[int]], high: Optional[int] = None, *, default: int,
|
|
space: Optional[str] = None, optimize: bool = True, load: bool = True, **kwargs):
|
|
"""
|
|
Initialize hyperopt-optimizable integer parameter.
|
|
:param low: Lower end (inclusive) of optimization space or [low, high].
|
|
:param high: Upper end (inclusive) of optimization space.
|
|
Must be none of entire range is passed first parameter.
|
|
:param default: A default value.
|
|
:param space: A parameter category. Can be 'buy' or 'sell'. This parameter is optional if
|
|
parameter fieldname is prefixed with 'buy_' or 'sell_'.
|
|
:param optimize: Include parameter in hyperopt optimizations.
|
|
:param load: Load parameter value from {space}_params.
|
|
:param kwargs: Extra parameters to skopt.space.Integer.
|
|
"""
|
|
|
|
super().__init__(low=low, high=high, default=default, space=space, optimize=optimize,
|
|
load=load, **kwargs)
|
|
|
|
def get_space(self, name: str) -> 'Integer':
|
|
"""
|
|
Create skopt optimization space.
|
|
:param name: A name of parameter field.
|
|
"""
|
|
return Integer(low=self.low, high=self.high, name=name, **self._space_params)
|
|
|
|
@property
|
|
def range(self):
|
|
"""
|
|
Get each value in this space as list.
|
|
Returns a List from low to high (inclusive) in Hyperopt mode.
|
|
Returns a List with 1 item (`value`) in "non-hyperopt" mode, to avoid
|
|
calculating 100ds of indicators.
|
|
"""
|
|
if self.can_optimize():
|
|
# Scikit-optimize ranges are "inclusive", while python's "range" is exclusive
|
|
return range(self.low, self.high + 1)
|
|
else:
|
|
return range(self.value, self.value + 1)
|
|
|
|
|
|
class RealParameter(NumericParameter):
|
|
default: float
|
|
value: float
|
|
|
|
def __init__(self, low: Union[float, Sequence[float]], high: Optional[float] = None, *,
|
|
default: float, space: Optional[str] = None, optimize: bool = True,
|
|
load: bool = True, **kwargs):
|
|
"""
|
|
Initialize hyperopt-optimizable floating point parameter with unlimited precision.
|
|
:param low: Lower end (inclusive) of optimization space or [low, high].
|
|
:param high: Upper end (inclusive) of optimization space.
|
|
Must be none if entire range is passed first parameter.
|
|
:param default: A default value.
|
|
:param space: A parameter category. Can be 'buy' or 'sell'. This parameter is optional if
|
|
parameter fieldname is prefixed with 'buy_' or 'sell_'.
|
|
:param optimize: Include parameter in hyperopt optimizations.
|
|
:param load: Load parameter value from {space}_params.
|
|
:param kwargs: Extra parameters to skopt.space.Real.
|
|
"""
|
|
super().__init__(low=low, high=high, default=default, space=space, optimize=optimize,
|
|
load=load, **kwargs)
|
|
|
|
def get_space(self, name: str) -> 'Real':
|
|
"""
|
|
Create skopt optimization space.
|
|
:param name: A name of parameter field.
|
|
"""
|
|
return Real(low=self.low, high=self.high, name=name, **self._space_params)
|
|
|
|
|
|
class DecimalParameter(NumericParameter):
|
|
default: float
|
|
value: float
|
|
|
|
def __init__(self, low: Union[float, Sequence[float]], high: Optional[float] = None, *,
|
|
default: float, decimals: int = 3, space: Optional[str] = None,
|
|
optimize: bool = True, load: bool = True, **kwargs):
|
|
"""
|
|
Initialize hyperopt-optimizable decimal parameter with a limited precision.
|
|
:param low: Lower end (inclusive) of optimization space or [low, high].
|
|
:param high: Upper end (inclusive) of optimization space.
|
|
Must be none if entire range is passed first parameter.
|
|
:param default: A default value.
|
|
:param decimals: A number of decimals after floating point to be included in testing.
|
|
:param space: A parameter category. Can be 'buy' or 'sell'. This parameter is optional if
|
|
parameter fieldname is prefixed with 'buy_' or 'sell_'.
|
|
:param optimize: Include parameter in hyperopt optimizations.
|
|
:param load: Load parameter value from {space}_params.
|
|
:param kwargs: Extra parameters to skopt.space.Integer.
|
|
"""
|
|
self._decimals = decimals
|
|
default = round(default, self._decimals)
|
|
|
|
super().__init__(low=low, high=high, default=default, space=space, optimize=optimize,
|
|
load=load, **kwargs)
|
|
|
|
def get_space(self, name: str) -> 'SKDecimal':
|
|
"""
|
|
Create skopt optimization space.
|
|
:param name: A name of parameter field.
|
|
"""
|
|
return SKDecimal(low=self.low, high=self.high, decimals=self._decimals, name=name,
|
|
**self._space_params)
|
|
|
|
@property
|
|
def range(self):
|
|
"""
|
|
Get each value in this space as list.
|
|
Returns a List from low to high (inclusive) in Hyperopt mode.
|
|
Returns a List with 1 item (`value`) in "non-hyperopt" mode, to avoid
|
|
calculating 100ds of indicators.
|
|
"""
|
|
if self.can_optimize():
|
|
low = int(self.low * pow(10, self._decimals))
|
|
high = int(self.high * pow(10, self._decimals)) + 1
|
|
return [round(n * pow(0.1, self._decimals), self._decimals) for n in range(low, high)]
|
|
else:
|
|
return [self.value]
|
|
|
|
|
|
class CategoricalParameter(BaseParameter):
|
|
default: Any
|
|
value: Any
|
|
opt_range: Sequence[Any]
|
|
|
|
def __init__(self, categories: Sequence[Any], *, default: Optional[Any] = None,
|
|
space: Optional[str] = None, optimize: bool = True, load: bool = True, **kwargs):
|
|
"""
|
|
Initialize hyperopt-optimizable parameter.
|
|
:param categories: Optimization space, [a, b, ...].
|
|
:param default: A default value. If not specified, first item from specified space will be
|
|
used.
|
|
:param space: A parameter category. Can be 'buy' or 'sell'. This parameter is optional if
|
|
parameter field
|
|
name is prefixed with 'buy_' or 'sell_'.
|
|
:param optimize: Include parameter in hyperopt optimizations.
|
|
:param load: Load parameter value from {space}_params.
|
|
:param kwargs: Extra parameters to skopt.space.Categorical.
|
|
"""
|
|
if len(categories) < 2:
|
|
raise OperationalException(
|
|
'CategoricalParameter space must be [a, b, ...] (at least two parameters)')
|
|
self.opt_range = categories
|
|
super().__init__(default=default, space=space, optimize=optimize,
|
|
load=load, **kwargs)
|
|
|
|
def get_space(self, name: str) -> 'Categorical':
|
|
"""
|
|
Create skopt optimization space.
|
|
:param name: A name of parameter field.
|
|
"""
|
|
return Categorical(self.opt_range, name=name, **self._space_params)
|
|
|
|
@property
|
|
def range(self):
|
|
"""
|
|
Get each value in this space as list.
|
|
Returns a List of categories in Hyperopt mode.
|
|
Returns a List with 1 item (`value`) in "non-hyperopt" mode, to avoid
|
|
calculating 100ds of indicators.
|
|
"""
|
|
if self.can_optimize():
|
|
return self.opt_range
|
|
else:
|
|
return [self.value]
|
|
|
|
|
|
class BooleanParameter(CategoricalParameter):
|
|
|
|
def __init__(self, *, default: Optional[Any] = None,
|
|
space: Optional[str] = None, optimize: bool = True, load: bool = True, **kwargs):
|
|
"""
|
|
Initialize hyperopt-optimizable Boolean Parameter.
|
|
It's a shortcut to `CategoricalParameter([True, False])`.
|
|
:param default: A default value. If not specified, first item from specified space will be
|
|
used.
|
|
:param space: A parameter category. Can be 'buy' or 'sell'. This parameter is optional if
|
|
parameter field
|
|
name is prefixed with 'buy_' or 'sell_'.
|
|
:param optimize: Include parameter in hyperopt optimizations.
|
|
:param load: Load parameter value from {space}_params.
|
|
:param kwargs: Extra parameters to skopt.space.Categorical.
|
|
"""
|
|
|
|
categories = [True, False]
|
|
super().__init__(categories=categories, default=default, space=space, optimize=optimize,
|
|
load=load, **kwargs)
|