phyer/myTestFreqAI
1
0
Fork 0
Code Issues Pull Requests Actions Packages Projects Releases Wiki Activity

加入了在a117548d02中拥有的ai辅助指标

Browse Source
This commit is contained in:
zhangkun9038@dingtalk.com 2025-05-23 00:38:03 +00:00
parent 406a412f8c
commit cb032be176
1 changed files with 18 additions and 1 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

19
freqtrade/templates/freqaiprimer.py
View File

@ -51,6 +51,7 @@ class FreqaiPrimer(IStrategy):
}
def feature_engineering_expand_all(self, dataframe: DataFrame, period: int, metadata: dict, **kwargs) -> DataFrame:
# 保留原有指标
dataframe["%-rsi-period"] = ta.RSI(dataframe, timeperiod=period)
dataframe["%-sma-period"] = ta.SMA(dataframe, timeperiod=period)
dataframe["%-ema-period"] = ta.EMA(dataframe, timeperiod=period)
@ -61,8 +62,24 @@ class FreqaiPrimer(IStrategy):
dataframe["bb_upperband-period"] = upperband
dataframe["bb_middleband-period"] = middleband
dataframe["%-bb_width-period"] = (dataframe["bb_upperband-period"] - dataframe["bb_lowerband-period"]) / dataframe["bb_middleband-period"]
dataframe["%-roc-period"] = ta.ROC(dataframe, timeperiod=period)
# 添加策略 B 的指标
dataframe["%-mfi-period"] = ta.MFI(dataframe, timeperiod=period) # 资金流指标
dataframe["%-adx-period"] = ta.ADX(dataframe, timeperiod=period) # 趋势强度
dataframe["%-tema-period"] = ta.TEMA(dataframe, timeperiod=period) # TEMA 指标
dataframe["%-relative_volume-period"] = dataframe["volume"] / dataframe["volume"].rolling(period).mean() # 相对成交量
dataframe["%-close-bb_lower-period"] = dataframe["close"] / dataframe["bb_lowerband-period"] # 收盘价/布林带下轨
# 数据清理
columns_to_clean = [
"%-rsi-period", "%-mfi-period", "%-sma-period", "%-ema-period", "%-adx-period",
"bb_lowerband-period", "bb_middleband-period", "bb_upperband-period",
"%-bb_width-period", "%-roc-period", "%-relative_volume-period", "%-close-bb_lower-period", "%-tema-period"
]
for col in columns_to_clean:
dataframe[col] = dataframe[col].replace([np.inf, -np.inf], 0).ffill().fillna(0)
return dataframe
def set_freqai_targets(self, dataframe: DataFrame, metadata: dict, **kwargs) -> DataFrame: