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heracles in New API, Bugs fixed

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This commit is contained in:
Masoud Azizi
2021-06-27 03:12:18 +00:00
parent 6158f1e714
commit 9880524f05
2 changed files with 115 additions and 187 deletions
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user_data/hyperopts/HeraclesHo.py
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# Heracles Strategy Hyperopt
# Author: @Mablue (Masoud Azizi)
# github: https://github.com/mablue/
# IMPORTANT: INSTALL TA BEFOUR RUN:
# :~$ pip install ta
# freqtrade hyperopt --hyperopt GodStraHo --hyperopt-loss SharpeHyperOptLossDaily --gene all --strategy GodStra --config config.json -e 100
# --- Do not remove these libs ---
from functools import reduce
from typing import Any, Callable, Dict, List
import numpy as np # noqa
import pandas as pd # noqa
from pandas import DataFrame
from skopt.space import Categorical, Dimension, Integer, Real # noqa
from freqtrade.optimize.hyperopt_interface import IHyperOpt
# --------------------------------
# Add your lib to import here
# import talib.abstract as ta # noqa
from ta import add_all_ta_features
from ta.utils import dropna
import freqtrade.vendor.qtpylib.indicators as qtpylib
# this is your trading strategy DNA Size
# you can change it and see the results...
class HeraclesHo(IHyperOpt):
@staticmethod
def indicator_space() -> List[Dimension]:
"""
Define your Hyperopt space for searching buy strategy parameters.
"""
return [
Real(-0.1, 1.1, name='buy-div'),
Integer(0, 5, name='DFINDShift'),
Integer(0, 5, name='DFCRSShift'),
]
@staticmethod
def buy_strategy_generator(params: Dict[str, Any]) -> Callable:
"""
Define the buy strategy parameters to be used by Hyperopt.
"""
def populate_buy_trend(dataframe: DataFrame, metadata: dict) -> DataFrame:
"""
Buy strategy Hyperopt will build and use.
"""
conditions = []
IND = 'volatility_dcp'
CRS = 'volatility_kcw'
DFIND = dataframe[IND]
DFCRS = dataframe[CRS]
conditions.append(
DFIND.shift(params['DFINDShift']).div(
DFCRS.shift(params['DFCRSShift'])
) <= params['buy-div']
)
if conditions:
dataframe.loc[
reduce(lambda x, y: x & y, conditions),
'buy'] = 1
return dataframe
return populate_buy_trend
@ staticmethod
def sell_indicator_space() -> List[Dimension]:
"""
Define your Hyperopt space for searching sell strategy parameters.
"""
return [
Real(1.e-10, 1.e-0, name='sell-rtol'),
Real(1.e-16, 1.e-0, name='sell-atol'),
Integer(0, 5, name='DFINDShift'),
Integer(0, 5, name='DFCRSShift'),
]
@ staticmethod
def sell_strategy_generator(params: Dict[str, Any]) -> Callable:
"""
Define the sell strategy parameters to be used by Hyperopt.
"""
def populate_sell_trend(dataframe: DataFrame, metadata: dict) -> DataFrame:
"""
Sell strategy Hyperopt will build and use.
"""
conditions = []
IND = 'trend_ema_fast'
CRS = 'trend_macd_signal'
DFIND = dataframe[IND]
DFCRS = dataframe[CRS]
conditions.append(
np.isclose(
DFIND.shift(params['DFINDShift']),
DFCRS.shift(params['DFCRSShift']),
rtol=params['sell-rtol'],
atol=params['sell-atol']
)
)
if conditions:
dataframe.loc[
reduce(lambda x, y: x & y, conditions),
'sell']=1
return dataframe
return populate_sell_trend