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cosmetics in sample_hyperopt and default_hyperopt

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hroff-1902 2019-08-12 02:19:50 +03:00
parent 85094a59e6
commit e5dcd520ba
2 changed files with 55 additions and 30 deletions
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41
freqtrade/optimize/default_hyperopt.py
View File

@ -14,36 +14,48 @@ from freqtrade.optimize.hyperopt_interface import IHyperOpt
class DefaultHyperOpts(IHyperOpt): class DefaultHyperOpts(IHyperOpt):
""" """
Default hyperopt provided by the Freqtrade bot. Default hyperopt provided by the Freqtrade bot.
You can override it with your own hyperopt You can override it with your own Hyperopt
""" """
@staticmethod @staticmethod
def populate_indicators(dataframe: DataFrame, metadata: dict) -> DataFrame: def populate_indicators(dataframe: DataFrame, metadata: dict) -> DataFrame:
"""
Add several indicators needed for buy and sell strategies defined below.
"""
# ADX
dataframe['adx'] = ta.ADX(dataframe) dataframe['adx'] = ta.ADX(dataframe)
# MACD
macd = ta.MACD(dataframe) macd = ta.MACD(dataframe)
dataframe['macd'] = macd['macd'] dataframe['macd'] = macd['macd']
dataframe['macdsignal'] = macd['macdsignal'] dataframe['macdsignal'] = macd['macdsignal']
# MFI
dataframe['mfi'] = ta.MFI(dataframe) dataframe['mfi'] = ta.MFI(dataframe)
# RSI
dataframe['rsi'] = ta.RSI(dataframe) dataframe['rsi'] = ta.RSI(dataframe)
# Stochastic Fast
stoch_fast = ta.STOCHF(dataframe) stoch_fast = ta.STOCHF(dataframe)
dataframe['fastd'] = stoch_fast['fastd'] dataframe['fastd'] = stoch_fast['fastd']
# Minus-DI
dataframe['minus_di'] = ta.MINUS_DI(dataframe) dataframe['minus_di'] = ta.MINUS_DI(dataframe)
# Bollinger bands # Bollinger bands
bollinger = qtpylib.bollinger_bands(qtpylib.typical_price(dataframe), window=20, stds=2) bollinger = qtpylib.bollinger_bands(qtpylib.typical_price(dataframe), window=20, stds=2)
dataframe['bb_lowerband'] = bollinger['lower'] dataframe['bb_lowerband'] = bollinger['lower']
dataframe['bb_upperband'] = bollinger['upper'] dataframe['bb_upperband'] = bollinger['upper']
# SAR
dataframe['sar'] = ta.SAR(dataframe) dataframe['sar'] = ta.SAR(dataframe)
return dataframe return dataframe
@staticmethod @staticmethod
def buy_strategy_generator(params: Dict[str, Any]) -> Callable: def buy_strategy_generator(params: Dict[str, Any]) -> Callable:
""" """
Define the buy strategy parameters to be used by hyperopt Define the buy strategy parameters to be used by Hyperopt.
""" """
def populate_buy_trend(dataframe: DataFrame, metadata: dict) -> DataFrame: def populate_buy_trend(dataframe: DataFrame, metadata: dict) -> DataFrame:
""" """
Buy strategy Hyperopt will build and use Buy strategy Hyperopt will build and use.
""" """
conditions = [] conditions = []
# GUARDS AND TRENDS # GUARDS AND TRENDS
if 'mfi-enabled' in params and params['mfi-enabled']: if 'mfi-enabled' in params and params['mfi-enabled']:
conditions.append(dataframe['mfi'] < params['mfi-value']) conditions.append(dataframe['mfi'] < params['mfi-value'])
@ -79,7 +91,7 @@ class DefaultHyperOpts(IHyperOpt):
@staticmethod @staticmethod
def indicator_space() -> List[Dimension]: def indicator_space() -> List[Dimension]:
""" """
Define your Hyperopt space for searching strategy parameters Define your Hyperopt space for searching buy strategy parameters.
""" """
return [ return [
Integer(10, 25, name='mfi-value'), Integer(10, 25, name='mfi-value'),
@ -96,14 +108,14 @@ class DefaultHyperOpts(IHyperOpt):
@staticmethod @staticmethod
def sell_strategy_generator(params: Dict[str, Any]) -> Callable: def sell_strategy_generator(params: Dict[str, Any]) -> Callable:
""" """
Define the sell strategy parameters to be used by hyperopt Define the sell strategy parameters to be used by Hyperopt.
""" """
def populate_sell_trend(dataframe: DataFrame, metadata: dict) -> DataFrame: def populate_sell_trend(dataframe: DataFrame, metadata: dict) -> DataFrame:
""" """
Sell strategy Hyperopt will build and use Sell strategy Hyperopt will build and use.
""" """
# print(params)
conditions = [] conditions = []
# GUARDS AND TRENDS # GUARDS AND TRENDS
if 'sell-mfi-enabled' in params and params['sell-mfi-enabled']: if 'sell-mfi-enabled' in params and params['sell-mfi-enabled']:
conditions.append(dataframe['mfi'] > params['sell-mfi-value']) conditions.append(dataframe['mfi'] > params['sell-mfi-value'])
@ -139,7 +151,7 @@ class DefaultHyperOpts(IHyperOpt):
@staticmethod @staticmethod
def sell_indicator_space() -> List[Dimension]: def sell_indicator_space() -> List[Dimension]:
""" """
Define your Hyperopt space for searching sell strategy parameters Define your Hyperopt space for searching sell strategy parameters.
""" """
return [ return [
Integer(75, 100, name='sell-mfi-value'), Integer(75, 100, name='sell-mfi-value'),
@ -157,9 +169,9 @@ class DefaultHyperOpts(IHyperOpt):
def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame: def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
""" """
Based on TA indicators. Should be a copy of from strategy Based on TA indicators. Should be a copy of same method from strategy.
must align to populate_indicators in this file Must align to populate_indicators in this file.
Only used when --spaces does not include buy Only used when --spaces does not include buy space.
""" """
dataframe.loc[ dataframe.loc[
( (
@ -174,9 +186,9 @@ class DefaultHyperOpts(IHyperOpt):
def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame: def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
""" """
Based on TA indicators. Should be a copy of from strategy Based on TA indicators. Should be a copy of same method from strategy.
must align to populate_indicators in this file Must align to populate_indicators in this file.
Only used when --spaces does not include sell Only used when --spaces does not include sell space.
""" """
dataframe.loc[ dataframe.loc[
( (
@ -186,4 +198,5 @@ class DefaultHyperOpts(IHyperOpt):
(dataframe['fastd'] > 54) (dataframe['fastd'] > 54)
), ),
'sell'] = 1 'sell'] = 1
return dataframe return dataframe

44
user_data/hyperopts/sample_hyperopt.py
View File

@ -1,11 +1,10 @@
# pragma pylint: disable=missing-docstring, invalid-name, pointless-string-statement # pragma pylint: disable=missing-docstring, invalid-name, pointless-string-statement
from functools import reduce from functools import reduce
from math import exp
from typing import Any, Callable, Dict, List from typing import Any, Callable, Dict, List
from datetime import datetime from datetime import datetime
import numpy as np# noqa F401 import numpy as np
import talib.abstract as ta import talib.abstract as ta
from pandas import DataFrame from pandas import DataFrame
from skopt.space import Categorical, Dimension, Integer, Real from skopt.space import Categorical, Dimension, Integer, Real
@ -16,7 +15,7 @@ from freqtrade.optimize.hyperopt_interface import IHyperOpt
class SampleHyperOpts(IHyperOpt): class SampleHyperOpts(IHyperOpt):
""" """
This is a sample hyperopt to inspire you. This is a sample Hyperopt to inspire you.
Feel free to customize it. Feel free to customize it.
More information in https://github.com/freqtrade/freqtrade/blob/develop/docs/hyperopt.md More information in https://github.com/freqtrade/freqtrade/blob/develop/docs/hyperopt.md
@ -37,32 +36,44 @@ class SampleHyperOpts(IHyperOpt):
""" """
@staticmethod @staticmethod
def populate_indicators(dataframe: DataFrame, metadata: dict) -> DataFrame: def populate_indicators(dataframe: DataFrame, metadata: dict) -> DataFrame:
"""
Add several indicators needed for buy and sell strategies defined below.
"""
# ADX
dataframe['adx'] = ta.ADX(dataframe) dataframe['adx'] = ta.ADX(dataframe)
# MACD
macd = ta.MACD(dataframe) macd = ta.MACD(dataframe)
dataframe['macd'] = macd['macd'] dataframe['macd'] = macd['macd']
dataframe['macdsignal'] = macd['macdsignal'] dataframe['macdsignal'] = macd['macdsignal']
# MFI
dataframe['mfi'] = ta.MFI(dataframe) dataframe['mfi'] = ta.MFI(dataframe)
# RSI
dataframe['rsi'] = ta.RSI(dataframe) dataframe['rsi'] = ta.RSI(dataframe)
# Stochastic Fast
stoch_fast = ta.STOCHF(dataframe) stoch_fast = ta.STOCHF(dataframe)
dataframe['fastd'] = stoch_fast['fastd'] dataframe['fastd'] = stoch_fast['fastd']
# Minus-DI
dataframe['minus_di'] = ta.MINUS_DI(dataframe) dataframe['minus_di'] = ta.MINUS_DI(dataframe)
# Bollinger bands # Bollinger bands
bollinger = qtpylib.bollinger_bands(qtpylib.typical_price(dataframe), window=20, stds=2) bollinger = qtpylib.bollinger_bands(qtpylib.typical_price(dataframe), window=20, stds=2)
dataframe['bb_lowerband'] = bollinger['lower'] dataframe['bb_lowerband'] = bollinger['lower']
dataframe['bb_upperband'] = bollinger['upper'] dataframe['bb_upperband'] = bollinger['upper']
# SAR
dataframe['sar'] = ta.SAR(dataframe) dataframe['sar'] = ta.SAR(dataframe)
return dataframe return dataframe
@staticmethod @staticmethod
def buy_strategy_generator(params: Dict[str, Any]) -> Callable: def buy_strategy_generator(params: Dict[str, Any]) -> Callable:
""" """
Define the buy strategy parameters to be used by hyperopt Define the buy strategy parameters to be used by Hyperopt.
""" """
def populate_buy_trend(dataframe: DataFrame, metadata: dict) -> DataFrame: def populate_buy_trend(dataframe: DataFrame, metadata: dict) -> DataFrame:
""" """
Buy strategy Hyperopt will build and use Buy strategy Hyperopt will build and use.
""" """
conditions = [] conditions = []
# GUARDS AND TRENDS # GUARDS AND TRENDS
if 'mfi-enabled' in params and params['mfi-enabled']: if 'mfi-enabled' in params and params['mfi-enabled']:
conditions.append(dataframe['mfi'] < params['mfi-value']) conditions.append(dataframe['mfi'] < params['mfi-value'])
@ -98,7 +109,7 @@ class SampleHyperOpts(IHyperOpt):
@staticmethod @staticmethod
def indicator_space() -> List[Dimension]: def indicator_space() -> List[Dimension]:
""" """
Define your Hyperopt space for searching strategy parameters Define your Hyperopt space for searching buy strategy parameters.
""" """
return [ return [
Integer(10, 25, name='mfi-value'), Integer(10, 25, name='mfi-value'),
@ -115,14 +126,14 @@ class SampleHyperOpts(IHyperOpt):
@staticmethod @staticmethod
def sell_strategy_generator(params: Dict[str, Any]) -> Callable: def sell_strategy_generator(params: Dict[str, Any]) -> Callable:
""" """
Define the sell strategy parameters to be used by hyperopt Define the sell strategy parameters to be used by Hyperopt.
""" """
def populate_sell_trend(dataframe: DataFrame, metadata: dict) -> DataFrame: def populate_sell_trend(dataframe: DataFrame, metadata: dict) -> DataFrame:
""" """
Sell strategy Hyperopt will build and use Sell strategy Hyperopt will build and use.
""" """
# print(params)
conditions = [] conditions = []
# GUARDS AND TRENDS # GUARDS AND TRENDS
if 'sell-mfi-enabled' in params and params['sell-mfi-enabled']: if 'sell-mfi-enabled' in params and params['sell-mfi-enabled']:
conditions.append(dataframe['mfi'] > params['sell-mfi-value']) conditions.append(dataframe['mfi'] > params['sell-mfi-value'])
@ -158,7 +169,7 @@ class SampleHyperOpts(IHyperOpt):
@staticmethod @staticmethod
def sell_indicator_space() -> List[Dimension]: def sell_indicator_space() -> List[Dimension]:
""" """
Define your Hyperopt space for searching sell strategy parameters Define your Hyperopt space for searching sell strategy parameters.
""" """
return [ return [
Integer(75, 100, name='sell-mfi-value'), Integer(75, 100, name='sell-mfi-value'),
@ -176,9 +187,9 @@ class SampleHyperOpts(IHyperOpt):
def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame: def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
""" """
Based on TA indicators. Should be a copy of from strategy Based on TA indicators. Should be a copy of same method from strategy.
must align to populate_indicators in this file Must align to populate_indicators in this file.
Only used when --spaces does not include buy Only used when --spaces does not include buy space.
""" """
dataframe.loc[ dataframe.loc[
( (
@ -193,9 +204,9 @@ class SampleHyperOpts(IHyperOpt):
def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame: def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
""" """
Based on TA indicators. Should be a copy of from strategy Based on TA indicators. Should be a copy of same method from strategy.
must align to populate_indicators in this file Must align to populate_indicators in this file.
Only used when --spaces does not include sell Only used when --spaces does not include sell space.
""" """
dataframe.loc[ dataframe.loc[
( (
@ -205,4 +216,5 @@ class SampleHyperOpts(IHyperOpt):
(dataframe['fastd'] > 54) (dataframe['fastd'] > 54)
), ),
'sell'] = 1 'sell'] = 1
return dataframe return dataframe