Merge pull request #5566 from freqtrade/remove_hyperopt
Remove legacy hyperopt
This commit is contained in:
@@ -22,6 +22,7 @@ from pandas import DataFrame
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from freqtrade.constants import DATETIME_PRINT_FORMAT, FTHYPT_FILEVERSION, LAST_BT_RESULT_FN
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from freqtrade.data.converter import trim_dataframes
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from freqtrade.data.history import get_timerange
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from freqtrade.exceptions import OperationalException
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from freqtrade.misc import deep_merge_dicts, file_dump_json, plural
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from freqtrade.optimize.backtesting import Backtesting
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# Import IHyperOpt and IHyperOptLoss to allow unpickling classes from these modules
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@@ -30,7 +31,7 @@ from freqtrade.optimize.hyperopt_interface import IHyperOpt # noqa: F401
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from freqtrade.optimize.hyperopt_loss_interface import IHyperOptLoss # noqa: F401
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from freqtrade.optimize.hyperopt_tools import HyperoptTools, hyperopt_serializer
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from freqtrade.optimize.optimize_reports import generate_strategy_stats
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from freqtrade.resolvers.hyperopt_resolver import HyperOptLossResolver, HyperOptResolver
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from freqtrade.resolvers.hyperopt_resolver import HyperOptLossResolver
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# Suppress scikit-learn FutureWarnings from skopt
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@@ -78,10 +79,10 @@ class Hyperopt:
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if not self.config.get('hyperopt'):
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self.custom_hyperopt = HyperOptAuto(self.config)
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self.auto_hyperopt = True
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else:
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self.custom_hyperopt = HyperOptResolver.load_hyperopt(self.config)
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self.auto_hyperopt = False
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raise OperationalException(
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"Using separate Hyperopt files has been removed in 2021.9. Please convert "
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"your existing Hyperopt file to the new Hyperoptable strategy interface")
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self.backtesting._set_strategy(self.backtesting.strategylist[0])
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self.custom_hyperopt.strategy = self.backtesting.strategy
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@@ -103,31 +104,6 @@ class Hyperopt:
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self.num_epochs_saved = 0
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self.current_best_epoch: Optional[Dict[str, Any]] = None
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if not self.auto_hyperopt:
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# Populate "fallback" functions here
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# (hasattr is slow so should not be run during "regular" operations)
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if hasattr(self.custom_hyperopt, 'populate_indicators'):
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logger.warning(
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"DEPRECATED: Using `populate_indicators()` in the hyperopt file is deprecated. "
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"Please move these methods to your strategy."
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)
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self.backtesting.strategy.populate_indicators = ( # type: ignore
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self.custom_hyperopt.populate_indicators) # type: ignore
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if hasattr(self.custom_hyperopt, 'populate_buy_trend'):
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logger.warning(
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"DEPRECATED: Using `populate_buy_trend()` in the hyperopt file is deprecated. "
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"Please move these methods to your strategy."
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)
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self.backtesting.strategy.populate_buy_trend = ( # type: ignore
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self.custom_hyperopt.populate_buy_trend) # type: ignore
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if hasattr(self.custom_hyperopt, 'populate_sell_trend'):
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logger.warning(
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"DEPRECATED: Using `populate_sell_trend()` in the hyperopt file is deprecated. "
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"Please move these methods to your strategy."
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)
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self.backtesting.strategy.populate_sell_trend = ( # type: ignore
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self.custom_hyperopt.populate_sell_trend) # type: ignore
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# Use max_open_trades for hyperopt as well, except --disable-max-market-positions is set
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if self.config.get('use_max_market_positions', True):
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self.max_open_trades = self.config['max_open_trades']
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@@ -256,7 +232,7 @@ class Hyperopt:
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"""
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Assign the dimensions in the hyperoptimization space.
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"""
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if self.auto_hyperopt and HyperoptTools.has_space(self.config, 'protection'):
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if HyperoptTools.has_space(self.config, 'protection'):
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# Protections can only be optimized when using the Parameter interface
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logger.debug("Hyperopt has 'protection' space")
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# Enable Protections if protection space is selected.
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@@ -285,6 +261,15 @@ class Hyperopt:
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self.dimensions = (self.buy_space + self.sell_space + self.protection_space
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+ self.roi_space + self.stoploss_space + self.trailing_space)
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def assign_params(self, params_dict: Dict, category: str) -> None:
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"""
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Assign hyperoptable parameters
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"""
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for attr_name, attr in self.backtesting.strategy.enumerate_parameters(category):
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if attr.optimize:
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# noinspection PyProtectedMember
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attr.value = params_dict[attr_name]
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def generate_optimizer(self, raw_params: List[Any], iteration=None) -> Dict:
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"""
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Used Optimize function.
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@@ -296,18 +281,13 @@ class Hyperopt:
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# Apply parameters
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if HyperoptTools.has_space(self.config, 'buy'):
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self.backtesting.strategy.advise_buy = ( # type: ignore
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self.custom_hyperopt.buy_strategy_generator(params_dict))
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self.assign_params(params_dict, 'buy')
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if HyperoptTools.has_space(self.config, 'sell'):
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self.backtesting.strategy.advise_sell = ( # type: ignore
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self.custom_hyperopt.sell_strategy_generator(params_dict))
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self.assign_params(params_dict, 'sell')
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if HyperoptTools.has_space(self.config, 'protection'):
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for attr_name, attr in self.backtesting.strategy.enumerate_parameters('protection'):
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if attr.optimize:
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# noinspection PyProtectedMember
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attr.value = params_dict[attr_name]
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self.assign_params(params_dict, 'protection')
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if HyperoptTools.has_space(self.config, 'roi'):
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self.backtesting.strategy.minimal_roi = ( # type: ignore
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@@ -517,11 +497,10 @@ class Hyperopt:
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f"saved to '{self.results_file}'.")
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if self.current_best_epoch:
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if self.auto_hyperopt:
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HyperoptTools.try_export_params(
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self.config,
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self.backtesting.strategy.get_strategy_name(),
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self.current_best_epoch)
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HyperoptTools.try_export_params(
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self.config,
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self.backtesting.strategy.get_strategy_name(),
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self.current_best_epoch)
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HyperoptTools.show_epoch_details(self.current_best_epoch, self.total_epochs,
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self.print_json)
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@@ -4,9 +4,9 @@ This module implements a convenience auto-hyperopt class, which can be used toge
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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 typing import Callable, Dict, List
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from pandas import DataFrame
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from freqtrade.exceptions import OperationalException
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with suppress(ImportError):
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@@ -15,6 +15,14 @@ with suppress(ImportError):
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from freqtrade.optimize.hyperopt_interface import IHyperOpt
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def _format_exception_message(space: str) -> str:
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raise OperationalException(
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f"The '{space}' space is included into the hyperoptimization "
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f"but no parameter for this space was not found in your Strategy. "
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f"Please make sure to have parameters for this space enabled for optimization "
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f"or remove the '{space}' space from hyperoptimization.")
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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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@@ -22,26 +30,6 @@ class HyperOptAuto(IHyperOpt):
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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.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.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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@@ -60,21 +48,22 @@ class HyperOptAuto(IHyperOpt):
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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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def _get_indicator_space(self, category):
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# TODO: is this necessary, or can we call "generate_space" directly?
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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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_format_exception_message(category)
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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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return self._get_indicator_space('buy')
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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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return self._get_indicator_space('sell')
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def protection_space(self) -> List['Dimension']:
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return self._get_indicator_space('protection', 'protection_space')
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return self._get_indicator_space('protection')
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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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@@ -5,11 +5,10 @@ This module defines the interface to apply for hyperopt
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import logging
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import math
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from abc import ABC
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from typing import Any, Callable, Dict, List
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from typing import Dict, List
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from skopt.space import Categorical, Dimension, Integer
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from freqtrade.exceptions import OperationalException
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from freqtrade.exchange import timeframe_to_minutes
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from freqtrade.misc import round_dict
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from freqtrade.optimize.space import SKDecimal
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@@ -19,13 +18,6 @@ from freqtrade.strategy import IStrategy
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logger = logging.getLogger(__name__)
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def _format_exception_message(method: str, space: str) -> str:
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return (f"The '{space}' space is included into the hyperoptimization "
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f"but {method}() method is not found in your "
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f"custom Hyperopt class. You should either implement this "
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f"method or remove the '{space}' space from hyperoptimization.")
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class IHyperOpt(ABC):
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"""
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Interface for freqtrade hyperopt
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@@ -45,37 +37,6 @@ class IHyperOpt(ABC):
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IHyperOpt.ticker_interval = str(config['timeframe']) # DEPRECATED
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IHyperOpt.timeframe = str(config['timeframe'])
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def buy_strategy_generator(self, params: Dict[str, Any]) -> Callable:
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"""
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Create a buy strategy generator.
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"""
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raise OperationalException(_format_exception_message('buy_strategy_generator', 'buy'))
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def sell_strategy_generator(self, params: Dict[str, Any]) -> Callable:
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"""
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Create a sell strategy generator.
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"""
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raise OperationalException(_format_exception_message('sell_strategy_generator', 'sell'))
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def protection_space(self) -> List[Dimension]:
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"""
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Create a protection space.
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Only supported by the Parameter interface.
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"""
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raise OperationalException(_format_exception_message('indicator_space', 'protection'))
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def indicator_space(self) -> List[Dimension]:
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"""
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Create an indicator space.
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"""
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raise OperationalException(_format_exception_message('indicator_space', 'buy'))
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def sell_indicator_space(self) -> List[Dimension]:
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"""
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Create a sell indicator space.
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"""
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raise OperationalException(_format_exception_message('sell_indicator_space', 'sell'))
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def generate_roi_table(self, params: Dict) -> Dict[int, float]:
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"""
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Create a ROI table.
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