Freqtrade 2021.7超选择空间定义问题
Freqtrade 2021.7超选择空间定义问题
提问于 2021-08-25 08:14:16
我是新来的。我想在我的策略中优化一些参数。据我所见，使用freqtrade 2021，我们可以优化参数，而无需定义单独的超级选择文件。我遵循了https://www.freqtrade.io/en/stable/hyperopt/上的例子，并编写了代码，这些代码附在我问题的末尾。但是，当我使用下面的命令运行hyperopt时
freqtrade --config config.json -- hyperopt -loss --策略MyFirstStrategy -e 500 --所有空格
它在下面输出错误消息：
2021-08-25 00:27:43,590 - freqtrade.configuration.config_validation - INFO - Validating configuration ...
2021-08-25 00:27:43,595 - freqtrade.resolvers.iresolver - INFO - Using resolved pairlist StaticPairList from '/media/Priamos/Projects/AutoTrade/freqtrade/freqtrade/plugins/pairlist/StaticPairList.py'...
2021-08-25 00:27:43,596 - freqtrade.resolvers.iresolver - INFO - Using resolved pairlist AgeFilter from '/media/Priamos/Projects/AutoTrade/freqtrade/freqtrade/plugins/pairlist/AgeFilter.py'...
2021-08-25 00:27:43,598 - freqtrade.resolvers.iresolver - INFO - Using resolved pairlist PrecisionFilter from '/media/Priamos/Projects/AutoTrade/freqtrade/freqtrade/plugins/pairlist/PrecisionFilter.py'...
2021-08-25 00:27:43,603 - freqtrade.resolvers.iresolver - INFO - Using resolved pairlist PriceFilter from '/media/Priamos/Projects/AutoTrade/freqtrade/freqtrade/plugins/pairlist/PriceFilter.py'...
2021-08-25 00:27:43,605 - freqtrade.resolvers.iresolver - INFO - Using resolved pairlist SpreadFilter from '/media/Priamos/Projects/AutoTrade/freqtrade/freqtrade/plugins/pairlist/SpreadFilter.py'...
2021-08-25 00:27:43,611 - freqtrade.resolvers.iresolver - INFO - Using resolved pairlist RangeStabilityFilter from '/media/Priamos/Projects/AutoTrade/freqtrade/freqtrade/plugins/pairlist/rangestabilityfilter.py'...
2021-08-25 00:27:53,516 - freqtrade.resolvers.iresolver - INFO - Using resolved hyperoptloss SharpeHyperOptLoss from '/media/Priamos/Projects/AutoTrade/freqtrade/freqtrade/optimize/hyperopt_loss_sharpe.py'...
2021-08-25 00:27:53,517 - freqtrade.optimize.hyperopt - INFO - Using optimizer random state: 56312
2021-08-25 00:27:53,517 - freqtrade - ERROR - The 'buy' space is included into the hyperoptimization but indicator_space() method is not found in your custom Hyperopt class. You should either implement this method or remove the 'buy' space from hyperoptimization.我增加了最后几行输出，以避免造成这里的拥堵。为什么它说我需要定义我不明白的indicator_space()方法。因为我试图使用默认的hyperopt来优化参数，这些参数是在我的示例策略中定义的。战略代码如下：
import numpy as np # noqa
import pandas as pd # noqa
from freqtrade.optimize.space import SKDecimal, Dimension, Integer
from pandas import DataFrame
from functools import reduce
from typing import Any, Callable, Dict, List
from freqtrade.strategy import (BooleanParameter, CategoricalParameter, DecimalParameter,
IStrategy, IntParameter)
import talib.abstract as ta
import freqtrade.vendor.qtpylib.indicators as qtpylib
class MyFirstStrategy(IStrategy):
# Strategy interface version - allow new iterations of the strategy interface.
# Check the documentation or the Sample strategy to get the latest version.
INTERFACE_VERSION = 2
# Minimal ROI designed for the strategy.
# This attribute will be overridden if the config file contains "minimal_roi".
minimal_roi = {
"0": 0.06337,
"27": 0.03385,
"86": 0.01406,
"120": 0
}
# Optimal stoploss designed for the strategy.
# This attribute will be overridden if the config file contains "stoploss".
stoploss = -0.49122
# Trailing stoploss
trailing_stop = False
# trailing_only_offset_is_reached = False
# trailing_stop_positive = 0.01
# trailing_stop_positive_offset = 0.0 # Disabled / not configured
# Optimal timeframe for the strategy.
timeframe = '1h'
# Run "populate_indicators()" only for new candle.
process_only_new_candles = False
# These values can be overridden in the "ask_strategy" section in the config.
use_sell_signal = True
sell_profit_only = False
ignore_roi_if_buy_signal = False
# Number of candles the strategy requires before producing valid signals
startup_candle_count: int = 30
# Optional order type mapping.
order_types = {
'buy': 'limit',
'sell': 'limit',
'stoploss': 'limit',
'stoploss_on_exchange': False
}
# Optional order time in force.
order_time_in_force = {
'buy': 'gtc',
'sell': 'gtc'
}
plot_config = {
# Main plot indicators (Moving averages, ...)
'main_plot': {
'tema': {},
'sar': {'color': 'white'},
},
'subplots': {
# Subplots - each dict defines one additional plot
"MACD": {
'macd': {'color': 'blue'},
'macdsignal': {'color': 'orange'},
},
"RSI": {
'rsi': {'color': 'red'},
}
}
}
# BUY PARAMS
buy_rsi = IntParameter(10, 50, default=30, space='buy')
buy_rsi_enabled = CategoricalParameter([True, False], default=True, space='buy')
buy_trigger = CategoricalParameter(['buy_bb_lowerband1', 'buy_bb_lowerband2', 'buy_bb_lowerband3', 'buy_bb_lowerband4'],
default='buy_bb_lowerband2', space='buy')
# SELL PARAMS
sell_rsi = IntParameter(60, 90, default=30, space='sell')
sell_rsi_enabled = CategoricalParameter([True, False], default=True, space='sell')
sell_trigger = CategoricalParameter(['sell_bb_middle1', 'sell_bb_upper1',
'sell_bb_middle2', 'sell_bb_upper2',
'sell_bb_middle3', 'sell_bb_upper3',
'sell_bb_middle4', 'sell_bb_upper4'], default='sell-bb_middle2', space='sell')
def populate_indicators(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
"""
Adds several different TA indicators to the given DataFrame
Performance Note: For the best performance be frugal on the number of indicators
you are using. Let uncomment only the indicator you are using in your strategies
or your hyperopt configuration, otherwise you will waste your memory and CPU usage.
:param dataframe: Dataframe with data from the exchange
:param metadata: Additional information, like the currently traded pair
:return: a Dataframe with all mandatory indicators for the strategies
"""
dataframe['buy_rsi'] = ta.RSI(dataframe)
dataframe['sell_rsi'] = ta.RSI(dataframe)
# Overlap Studies
# ------------------------------------
# Bollinger Bands
bollinger1 = qtpylib.bollinger_bands(qtpylib.typical_price(dataframe), window=20, stds=1)
dataframe['buy_bb_lowerband1'] = bollinger1['lower']
dataframe['buy_bb_middleband1'] = bollinger1['mid']
dataframe['buy_bb_upperband1'] = bollinger1['upper']
bollinger2 = qtpylib.bollinger_bands(qtpylib.typical_price(dataframe), window=20, stds=2)
dataframe['buy_bb_lowerband2'] = bollinger2['lower']
dataframe['buy_bb_middleband2'] = bollinger2['mid']
dataframe['buy_bb_upperband2'] = bollinger2['upper']
bollinger3 = qtpylib.bollinger_bands(qtpylib.typical_price(dataframe), window=20, stds=3)
dataframe['buy_bb_lowerband3'] = bollinger3['lower']
dataframe['buy_bb_middleband3'] = bollinger3['mid']
dataframe['buy_bb_upperband3'] = bollinger3['upper']
bollinger4 = qtpylib.bollinger_bands(qtpylib.typical_price(dataframe), window=20, stds=4)
dataframe['buy_bb_lowerband4'] = bollinger4['lower']
dataframe['buy_bb_middleband4'] = bollinger4['mid']
dataframe['buy_bb_upperband4'] = bollinger4['upper']
return dataframe
def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
"""
Buy strategy Hyperopt will build and use.
"""
conditions = []
# GUARDS AND TRENDS
if self.buy_rsi_enabled.value:
conditions.append(dataframe['buy_rsi'] < self.buy_rsi.value)
# TRIGGERS
if self.buy_trigger.value:
if self.buy_trigger.value == 'buy_bb_lowerband1':
conditions.append(dataframe['close'] < dataframe['buy_bb_lowerband1'])
if self.buy_trigger.value == 'buy_bb_lowerband2':
conditions.append(dataframe['close'] < dataframe['buy_bb_lowerband2'])
if self.buy_trigger.value == 'buy_bb_lowerband3':
conditions.append(dataframe['close'] < dataframe['buy_bb_lowerband3'])
if self.buy_trigger.value == 'buy_bb_lowerband4':
conditions.append(dataframe['close'] < dataframe['buy_bb_lowerband4'])
# Check that the candle had volume
conditions.append(dataframe['volume'] > 0)
if conditions:
dataframe.loc[
reduce(lambda x, y: x & y, conditions),
'buy'] = 1
return dataframe
def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
"""
Based on TA indicators, populates the sell signal for the given dataframe
:param dataframe: DataFrame populated with indicators
:param metadata: Additional information, like the currently traded pair
:return: DataFrame with buy column
"""
conditions = []
# GUARDS AND TRENDS
if self.sell_rsi_enabled.value:
conditions.append(dataframe['rsi'] > self.sell_rsi.value)
# TRIGGERS
if self.sell_trigger.value:
if self.sell_trigger.value == 'sell_bb_middle1':
conditions.append(dataframe['close'] < dataframe['sell_bb_middle1'])
if self.sell_trigger.value == 'sell_bb_middle2':
conditions.append(dataframe['close'] < dataframe['sell_bb_middle2'])
if self.sell_trigger.value == 'sell_bb_middle3':
conditions.append(dataframe['close'] < dataframe['sell_bb_middle3'])
if self.sell_trigger.value == 'sell_bb_middle4':
conditions.append(dataframe['close'] < dataframe['sell_bb_middle4'])
if self.sell_trigger.value == 'sell_bb_upper1':
conditions.append(dataframe['close'] < dataframe['sell_bb_upper1'])
if self.sell_trigger.value == 'sell_bb_upper2':
conditions.append(dataframe['close'] < dataframe['sell_bb_upper2'])
if self.sell_trigger.value == 'sell_bb_upper3':
conditions.append(dataframe['close'] < dataframe['sell_bb_upper3'])
if self.sell_trigger.value == 'sell_bb_upper4':
conditions.append(dataframe['close'] < dataframe['sell_bb_upper4'])
# Check that the candle had volume
conditions.append(dataframe['volume'] > 0)
if conditions:
dataframe.loc[
reduce(lambda x, y: x & y, conditions),
'buy'] = 1
return dataframe我的目标是什么？
我试图在我的策略中优化参数。尝试在不定义显式hyperopt文件的情况下使用默认hyperopt。在策略中实现了优化代码。
定义问题：
我在上面包含了错误消息，其中最后写着"freqtrade - error -- 'buy‘空间包含在超级优化中，但是在您的自定义Hyperopt类中找不到indicator_space()方法。您应该实现这个方法，或者从超级优化中删除’购买‘空间。“
如何复制这个问题：
使用命令: freqtrade hyperopt --config config.json --hyperopt-loss --策略MyFirstStrategy -e 500 --空格全部
系统：
Ubuntu21.04(带有VMware虚拟机)Python3.9PyCharm 2021.2社区版
感谢您提供的任何帮助或澄清。
回答 1
Stack Overflow用户
发布于 2021-08-28 20:58:06
Freqtrade期待一个名为indicator_space()的方法，如下所示：
@staticmethod
def indicator_space() -> List[Dimension]:
"""
Define your Hyperopt space for searching buy strategy parameters.
"""
return [
Integer(10, 50, name='buy_rsi'),
Integer(60, 90, name='sell_rsi'),
Categorical([True, False], name='buy_rsi_enabled'),
Categorical([True, False], name='sell_rsi_enabled'),
Categorical(['buy_bb_lowerband1', 'buy_bb_lowerband2',
'buy_bb_lowerband3', 'buy_bb_lowerband4'], name='buy_trigger'),
Categorical(['sell_bb_middle1', 'sell_bb_upper1',
'sell_bb_middle2', 'sell_bb_upper2',
'sell_bb_middle3', 'sell_bb_upper3',
'sell_bb_middle4', 'sell_bb_upper4'], name='sell_trigger')
]页面原文内容由Stack Overflow提供。腾讯云小微IT领域专用引擎提供翻译支持
原文链接：
https://stackoverflow.com/questions/68919211
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