添加新股票
This commit is contained in:
jackyu66git
@@ -5,8 +5,6 @@ import sys
|
||||
import os
|
||||
# 添加父目录到系统路径
|
||||
sys.path.append(os.path.dirname(os.path.dirname(os.path.abspath(__file__))))
|
||||
from ChanLun import ChanLun
|
||||
from ChanLun_Classifier import ChanLunClassifier
|
||||
from ChanEnum import Chan_FX_TYPE, Chan_KLC_FX, Chan_BI_DIR, Chan_KLC_FX
|
||||
# --------------------------------
|
||||
from technical.util import resample_to_interval, resampled_merge
|
||||
@@ -17,6 +15,7 @@ from freqtrade.persistence import Trade
|
||||
from typing import Optional
|
||||
import logging
|
||||
logger = logging.getLogger(__name__)
|
||||
from TF_DF import TF_DF
|
||||
### Now you can use logger.info('asfd') to log
|
||||
# freqtrade plot-dataframe --strategy ChanLun_BTC_15 --datadir user_data/data/binance -c ./user_data/ChanLun_SOL_15.json --timerange=20250309-
|
||||
|
||||
@@ -88,76 +87,23 @@ class ChanLun_BTC_15(IStrategy):
|
||||
time1d = 1440
|
||||
time5 = 1440
|
||||
last_time = datetime.now()
|
||||
chan = ChanLun()
|
||||
classifier = ChanLunClassifier(None)
|
||||
def populate_indicators(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
|
||||
tf_df_5 = TF_DF(dataframe, self.time5, '5m')
|
||||
tf_df_15 = TF_DF(dataframe, self.time15, '15m')
|
||||
tf_df_30 = TF_DF(dataframe, self.time30, '30m')
|
||||
tf_df_60 = TF_DF(dataframe, self.time60, '60m')
|
||||
tf_df_4h = TF_DF(dataframe, self.time4h, '4h')
|
||||
tf_df_1d = TF_DF(dataframe, self.time1d, '1d')
|
||||
|
||||
# resample our dataframes
|
||||
dataframe_5 = resample_to_interval(dataframe, self.get_ticker_indicator() * 5)
|
||||
dataframe_15 = resample_to_interval(dataframe, self.get_ticker_indicator() * 15)
|
||||
dataframe_30 = resample_to_interval(dataframe, self.get_ticker_indicator() * 30)
|
||||
dataframe_60 = resample_to_interval(dataframe, self.get_ticker_indicator() * 60)
|
||||
dataframe_4h = resample_to_interval(dataframe, self.get_ticker_indicator() * 240)
|
||||
|
||||
#dataframe_1d = self.dp.get_pair_dataframe(pair=metadata['pair'], timeframe='1d')
|
||||
#dataframe_1w = resample_to_interval(dataframe_1d, self.get_ticker_indicator() * 10080)
|
||||
#dataframe_1m = resample_to_interval(dataframe_1d, self.get_ticker_indicator() * 43200)
|
||||
|
||||
dataframe_1d = resample_to_interval(dataframe, self.get_ticker_indicator() * 1440)
|
||||
#dataframe_1w = resample_to_interval(dataframe, self.get_ticker_indicator() * 10080)
|
||||
#dataframe_1m = resample_to_interval(dataframe, self.get_ticker_indicator() * 43200)
|
||||
dataframe = self.add_indicators(dataframe)
|
||||
dataframe_5 = self.add_indicators(dataframe_5)
|
||||
dataframe_30 = self.add_indicators(dataframe_30)
|
||||
dataframe_60 = self.add_indicators(dataframe_60)
|
||||
dataframe_4h = self.add_indicators(dataframe_4h)
|
||||
dataframe_1d = self.add_indicators(dataframe_1d)
|
||||
#self.chan.plot_dual(dataframe_5, dataframe_30)
|
||||
dataframe['rsi'] = ta.RSI(dataframe, timeperiod=14)
|
||||
|
||||
state_list, fx_list = self.chan.get_klc_strength_list(dataframe_15)
|
||||
dataframe_15['state'] = state_list
|
||||
dataframe_15['fx'] = fx_list
|
||||
dataframe_15['bsp'] = self.chan.get_klc_bsp_list(dataframe_15)
|
||||
klc_list = self.chan.get_klc_list(dataframe_15)
|
||||
bi_list = self.chan.cal_bi_list(klc_list)
|
||||
if self.last_time + timedelta(minutes=1) < datetime.now():
|
||||
print(state_list[-1], state_list[-2], state_list[-3], state_list[-4], state_list[-5])
|
||||
print(fx_list[-1], fx_list[-2], fx_list[-3], fx_list[-4], fx_list[-5])
|
||||
print(klc_list[-1].klc_fx_type, klc_list[-2].klc_fx_type, klc_list[-3].klc_fx_type, klc_list[-4].klc_fx_type, klc_list[-5].klc_fx_type)
|
||||
print("-------------------------------------------------------------------------------")
|
||||
self.last_time = datetime.now()
|
||||
#dataframe = resampled_merge(dataframe, dataframe_5)
|
||||
dataframe = resampled_merge(dataframe, dataframe_15)
|
||||
#dataframe = resampled_merge(dataframe, dataframe_30)
|
||||
#dataframe = resampled_merge(dataframe, dataframe_60)
|
||||
#dataframe = resampled_merge(dataframe, dataframe_4h)
|
||||
|
||||
dataframe = resampled_merge(dataframe, tf_df_5.dataframe)
|
||||
dataframe = resampled_merge(dataframe, tf_df_15.dataframe)
|
||||
dataframe = resampled_merge(dataframe, tf_df_30.dataframe)
|
||||
dataframe = resampled_merge(dataframe, tf_df_60.dataframe)
|
||||
dataframe = resampled_merge(dataframe, tf_df_4h.dataframe)
|
||||
dataframe = resampled_merge(dataframe, tf_df_1d.dataframe)
|
||||
return dataframe
|
||||
|
||||
def add_indicators(self, df):
|
||||
fast = 8
|
||||
slow = 16
|
||||
period = 6
|
||||
macd = ta.MACD(df, fastperiod=fast, slowperiod=slow, signalperiod=period)
|
||||
df['macd'] = macd['macd']
|
||||
df['macdsignal'] = macd['macdsignal']
|
||||
df['macdhist'] = macd['macdhist']
|
||||
df['ma5'] = ta.MA(df, timeperiod=5)
|
||||
df['ma10'] = ta.MA(df, timeperiod=10)
|
||||
df['ma30'] = ta.EMA(df, timeperiod=30)
|
||||
df['ma250'] = ta.MA(df, timeperiod=250)
|
||||
df['rsi'] = ta.RSI(df, timeperiod=14)
|
||||
df['volume_ratio'] = self.cal_volume_ratio(df)
|
||||
return df
|
||||
def cal_volume_ratio(self, dataframe, window=10):
|
||||
df = dataframe.copy()
|
||||
# 计算过去N根K线的平均成交量
|
||||
df['avg_volume'] = df['volume'].rolling(window=window).mean()
|
||||
# 计算量比
|
||||
df['volume_ratio'] = df['volume'] / df['avg_volume']
|
||||
# 填充缺失值（前N根K线）
|
||||
df['volume_ratio'] = df['volume_ratio'].fillna(1.0)
|
||||
return df['volume_ratio']
|
||||
|
||||
def custom_entry_price(self, pair: str, trade: Trade | None, current_time: datetime, proposed_rate: float,
|
||||
entry_tag: str | None, side: str, **kwargs) -> float:
|
||||
|
||||
Reference in New Issue
Block a user