Add to strategy
This commit is contained in:
jackyu66git
@@ -8,6 +8,7 @@ sys.path.append(os.path.dirname(os.path.dirname(os.path.abspath(__file__))))
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from ChanLun import ChanLun
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from ChanLun_Classifier import ChanLunClassifier
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from ChanEnum import Chan_FX_TYPE, Chan_KLC_FX, Chan_BI_DIR, Chan_KLC_FX
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from ChanPY import ChanPY
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# --------------------------------
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from technical.util import resample_to_interval, resampled_merge
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import talib.abstract as ta
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@@ -61,7 +62,7 @@ class ChanLun_BTC_30(IStrategy):
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"3600": 0
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}
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can_short = True
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lev = 50.0
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lev = 1.0
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stoploss = -0.3
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trailing_stop = False
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trailing_stop_positive = 0.025
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@@ -76,9 +77,9 @@ class ChanLun_BTC_30(IStrategy):
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time30 = 30
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time60 = 60
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time4h = 240
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time5 = 30
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last_time = datetime.now()
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chan = ChanLun()
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chanpy = ChanPY()
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classifier = ChanLunClassifier(None)
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def populate_indicators(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
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@@ -104,7 +105,7 @@ class ChanLun_BTC_30(IStrategy):
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dataframe_1d = self.add_indicators(dataframe_1d)
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#self.chan.plot_dual(dataframe_5, dataframe_30)
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dataframe['rsi'] = ta.RSI(dataframe, timeperiod=14)
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dataframe_5['chanpy_state'] = self.chanpy.get_bsp_state(dataframe_5)
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state_list, fx_list = self.chan.get_klc_strength_list(dataframe_30)
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dataframe_30['state'] = state_list
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dataframe_30['fx'] = fx_list
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@@ -116,7 +117,7 @@ class ChanLun_BTC_30(IStrategy):
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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)
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print("-------------------------------------------------------------------------------")
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self.last_time = datetime.now()
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#dataframe = resampled_merge(dataframe, dataframe_5)
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dataframe = resampled_merge(dataframe, dataframe_5)
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dataframe = resampled_merge(dataframe, dataframe_30)
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#dataframe = resampled_merge(dataframe, dataframe_30)
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#dataframe = resampled_merge(dataframe, dataframe_60)
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@@ -169,13 +170,16 @@ class ChanLun_BTC_30(IStrategy):
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return new_exitprice
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def populate_entry_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
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state_str = 'resample_{}_state'.format(self.get_ticker_indicator()*self.time5)
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fx_str = 'resample_{}_fx'.format(self.get_ticker_indicator()*self.time5)
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state_str = 'resample_{}_state'.format(self.get_ticker_indicator()*self.time30)
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fx_str = 'resample_{}_fx'.format(self.get_ticker_indicator()*self.time30)
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chanpy_state_str = 'resample_{}_chanpy_state'.format(self.get_ticker_indicator()*self.time5)
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shift_time = self.time30
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dataframe.loc[
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(
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#(dataframe['state'] == "-30")
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(dataframe[state_str].shift(self.time5) > 1.0) &
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(dataframe[fx_str].shift(self.time5) == -1)
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(dataframe[state_str].shift(shift_time) > 1.0) &
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(dataframe[fx_str].shift(shift_time) == -1) &
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(dataframe[chanpy_state_str].shift(shift_time) == 1)
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#(dataframe['resample_{}_state'.format(self.get_ticker_indicator()*self.time5)].shift(self.time5) == "-10") &
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#(dataframe['resample_{}_state'.format(self.get_ticker_indicator()*self.time30)] == "-10") &
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#(dataframe['resample_{}_state'.format(self.get_ticker_indicator()*self.time5)].shift(self.time5) == "-10")
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@@ -185,8 +189,9 @@ class ChanLun_BTC_30(IStrategy):
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dataframe.loc[
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(
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#(dataframe['state'] == "-30")
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(dataframe[state_str].shift(self.time5) > 1.0) &
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(dataframe[fx_str].shift(self.time5) == 1)
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(dataframe[state_str].shift(shift_time) > 1.0) &
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(dataframe[fx_str].shift(shift_time) == 1) &
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(dataframe[chanpy_state_str].shift(shift_time) == -1)
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#(dataframe['resample_{}_state'.format(self.get_ticker_indicator()*self.time5)].shift(self.time5) == "-10") &
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#(dataframe['resample_{}_state'.format(self.get_ticker_indicator()*self.time30)] == "-10") &
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#(dataframe['resample_{}_state'.format(self.get_ticker_indicator()*self.time5)].shift(self.time5) == "-10")
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@@ -195,13 +200,16 @@ class ChanLun_BTC_30(IStrategy):
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['enter_short', 'enter_tag']] = (1, 'short_signal_chan')
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return dataframe
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def populate_exit_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
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state_str = 'resample_{}_state'.format(self.get_ticker_indicator()*self.time5)
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fx_str = 'resample_{}_fx'.format(self.get_ticker_indicator()*self.time5)
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state_str = 'resample_{}_state'.format(self.get_ticker_indicator()*self.time30)
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fx_str = 'resample_{}_fx'.format(self.get_ticker_indicator()*self.time30)
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chanpy_state_str = 'resample_{}_chanpy_state'.format(self.get_ticker_indicator()*self.time5)
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shift_time = self.time30
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dataframe.loc[
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(
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#(dataframe['state']== "30")
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(dataframe[state_str].shift(self.time5) > 1.0) &
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(dataframe[fx_str].shift(self.time5) == 1)
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(dataframe[state_str].shift(shift_time) > 1.0) &
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(dataframe[fx_str].shift(shift_time) == 1) &
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(dataframe[chanpy_state_str].shift(shift_time) == -1)
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#(dataframe['resample_{}_state'.format(self.get_ticker_indicator()*self.time30)] == "10") &
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#(dataframe['resample_{}_state'.format(self.get_ticker_indicator()*self.time60)] == "10")
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),
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@@ -209,8 +217,9 @@ class ChanLun_BTC_30(IStrategy):
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dataframe.loc[
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(
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#(dataframe['state']== "30")
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(dataframe[state_str].shift(self.time5) > 1.0) &
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(dataframe[fx_str].shift(self.time5) == -1)
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(dataframe[state_str].shift(shift_time) > 1.0) &
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(dataframe[fx_str].shift(shift_time) == -1) &
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(dataframe[chanpy_state_str].shift(shift_time) == 1)
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#(dataframe['resample_{}_state'.format(self.get_ticker_indicator()*self.time30)] == "10") &
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#(dataframe['resample_{}_state'.format(self.get_ticker_indicator()*self.time60)] == "10")
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),
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@@ -1,274 +0,0 @@
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import sys
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import os
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#sys.path.append(os.path.abspath("/Users/jack/Documents/GitHub/chan.py"))
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sys.path.append(os.path.abspath("/Users/jack/Project/chan.py"))
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from Chan import CChan
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from BuySellPoint.BS_Point import CBS_Point
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from ChanConfig import CChanConfig
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from Common.CEnum import AUTYPE, DATA_SRC, KL_TYPE, DATA_FIELD, BSP_TYPE, FX_TYPE, BI_DIR, KLINE_DIR, SEG_DIR
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from KLine.KLine_Unit import CKLine_Unit
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from Common.CTime import CTime
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from Common.func_util import kltype_lt_day, str2float
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from Bi.Bi import CBi
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from typing import Dict, List
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from functools import reduce
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from pandas import DataFrame
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from datetime import datetime, timedelta, timezone
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def GetColumnNameFromFieldList(fileds: str):
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_dict = {
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"time": DATA_FIELD.FIELD_TIME,
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"open": DATA_FIELD.FIELD_OPEN,
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"high": DATA_FIELD.FIELD_HIGH,
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"low": DATA_FIELD.FIELD_LOW,
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"close": DATA_FIELD.FIELD_CLOSE,
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"volume": DATA_FIELD.FIELD_VOLUME
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}
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return [_dict[x] for x in fileds.split(",")]
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class ChanPY():
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k_type = KL_TYPE.K_5M
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config = CChanConfig({
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"bi_strict": True,
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"bi_algo": "fx",
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"trigger_step": True,
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"skip_step": 0,
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"divergence_rate": 0.9,
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"bsp2_follow_1": False,
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"bsp3_follow_1": False,
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"min_zs_cnt": 1,
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"bs1_peak": False,
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"macd_algo": "peak",
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"bs_type": '1,2,3a,1p,2s,3b',
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"print_warning": True,
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"zs_algo": "normal",
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})
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chan = CChan(
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code="BTC/USDT:USDT",
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data_src=DATA_SRC.CCXT,
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lv_list=[k_type],
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config=config,
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autype=AUTYPE.QFQ,
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)
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klu_list = []
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chanIn = True
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#def __init__(self, dataframe):
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#self.klu_list = self.get_kl_data(dataframe)
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#for klu in self.klu_list:
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#self.chan.trigger_load({self.k_type: [klu]})
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def add_klu(self, klu):
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if klu:
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self.chan.trigger_load({self.k_type: [klu]})
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self.klu_list.append(klu)
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def add_klu_from_dataframe(self, dataframe):
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if len(dataframe) > len(self.klu_list):
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klu = self.get_last_klu(dataframe)
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self.chan.trigger_load({self.k_type: [klu]})
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self.klu_list.append(klu)
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def parse_time_column(self, inp):
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if len(inp) == 10:
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year = int(inp[:4])
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month = int(inp[5:7])
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day = int(inp[8:10])
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hour = minute = 0
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elif len(inp) == 17:
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year = int(inp[:4])
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month = int(inp[4:6])
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day = int(inp[6:8])
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hour = int(inp[8:10])
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minute = int(inp[10:12])
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elif len(inp) == 19:
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year = int(inp[:4])
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month = int(inp[5:7])
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day = int(inp[8:10])
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hour = int(inp[11:13])
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minute = int(inp[14:16])
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else:
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raise Exception(f"unknown time column from TradingView:{inp}")
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return CTime(year, month, day, hour, minute, auto=not kltype_lt_day(self.k_type))
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def create_item_dict(self, data, column_name):
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for i in range(len(data)):
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data[i] = self.parse_time_column(data[i]) if i == 0 else str2float(data[i])
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return dict(zip(column_name, data))
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def get_last_klu(self, dataframe:DataFrame):
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fields = "time,open,high,low,close,volume"
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item = dataframe.iloc[-1]
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date = item['date']
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o = item['open']
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h = item['high']
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l = item['low']
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c = item['close']
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v = item['volume']
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#time_obj = date.fromtimestamp(date)
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time_str = date.strftime('%Y-%m-%d %H:%M:%S')
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item_data = [
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time_str,
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o,
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h,
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l,
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c,
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v
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]
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klu = CKLine_Unit(self.create_item_dict(item_data, GetColumnNameFromFieldList(fields)), autofix=True)
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klu.set_idx(len(dataframe)-1)
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return klu
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def get_kl_data(self, dataframe:DataFrame):
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fields = "time,open,high,low,close,volume"
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klu_list = []
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for i in range(0, len(dataframe)):
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item = dataframe.iloc[i]
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date = item['date']
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o = item['open']
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h = item['high']
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l = item['low']
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c = item['close']
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v = item['volume']
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#time_obj = date.fromtimestamp(date)
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time_str = date.strftime('%Y-%m-%d %H:%M:%S')
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item_data = [
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time_str,
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o,
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h,
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l,
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c,
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v
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]
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klu = CKLine_Unit(self.create_item_dict(item_data, GetColumnNameFromFieldList(fields)), autofix=True)
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klu.set_idx(i)
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klu_list.append(klu)
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return klu_list
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def get_bsp_type(self, bsp_type, is_buy):
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if is_buy:
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if bsp_type == BSP_TYPE.T1:
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return 1
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if bsp_type == BSP_TYPE.T1P:
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return 2
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if bsp_type == BSP_TYPE.T2:
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return 3
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if bsp_type == BSP_TYPE.T2S:
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return 4
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if bsp_type == BSP_TYPE.T3A:
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return 5
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if bsp_type == BSP_TYPE.T3B:
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return 6
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else:
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if bsp_type == BSP_TYPE.T1:
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return -1
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if bsp_type == BSP_TYPE.T1P:
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return -2
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if bsp_type == BSP_TYPE.T2:
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return -3
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if bsp_type == BSP_TYPE.T2S:
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return -4
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if bsp_type == BSP_TYPE.T3A:
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return -5
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if bsp_type == BSP_TYPE.T3B:
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return -6
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def get_bsps(self, dataframe:DataFrame):
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bsps = []
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updown = []
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bi_sure = []
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if self.chanIn:
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kl_data = self.get_kl_data(dataframe)
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bsp_list = []
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bsp_list_pre_len = 0
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last_bsp_value = 0
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last_updown = -1
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bi_list_pre_len = 0
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pre_bi = None
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zs_list_pre_len = 0
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pre_zs = None
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for klu in kl_data: # 获取单根K线
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self.chan.trigger_load({self.k_type: [klu]}) # 喂给CChan新增k线
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self.last_kline = klu
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bsp_list = self.chan.get_bsp()
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kl_datas = self.chan.kl_datas[self.k_type]
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bi_list = kl_datas.bi_list
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lst = kl_datas.lst
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if len(bsp_list) > 0:
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last_bsp = bsp_list[-1]
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#print(klu.time, klu.idx, last_bsp.klu.time, last_bsp.klu.idx, last_bsp_value, lst[-2].fx, bi_list[-1].dir, bi_list[-1].is_sure,klu.close)
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if bsp_list_pre_len > len(bsp_list):
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bsps.append(99)
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#print(klu.time, klu.idx, last_bsp.klu.time, last_bsp.klu.idx, last_bsp_value, 99)
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else:
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if bsp_list_pre_len == len(bsp_list):
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if klu.idx == last_bsp.klu.idx:
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last_bsp_value = self.get_bsp_type(last_bsp.type[0], last_bsp.is_buy)
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bsps.append(last_bsp_value)
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#print(klu.time, klu.idx, last_bsp.klu.time, last_bsp.klu.idx, last_bsp_value)
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else:
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bsps.append(0)
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else:
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last_bsp_value = self.get_bsp_type(last_bsp.type[0], last_bsp.is_buy)
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bsps.append(last_bsp_value)
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#print(klu.time, klu.idx, last_bsp.klu.time, last_bsp.klu.idx, last_bsp_value)
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else:
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bsps.append(0)
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bsp_list_pre_len = len(bsp_list)
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#Check zs -----------------------------------
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zs_list = kl_datas.zs_list
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if len(zs_list) > 0:
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zs = zs_list[-1]
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#if zs_list_pre_len > len(zs_list):
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#print("No zs", zs.begin.time)
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#if len(zs_list) > zs_list_pre_len:
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#print(zs.begin.time, zs.end.time, zs.end.idx, zs.high, zs.low, zs.peak_high, zs.peak_low)
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zs_list_pre_len = len(zs_list)
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pre_zs = zs
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#Check Bi -----------------------------------
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if len(bi_list) > 0:
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last_bi = bi_list[-1]
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if len(bi_list) == 1:
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if last_bi.dir == BI_DIR.UP:
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updown.append(1)
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last_updown = 1
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else:
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updown.append(-1)
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last_updown = -1
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else:
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if last_updown == 1:
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if last_bi.dir == BI_DIR.UP:
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updown.append(0)
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else:
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updown.append(-1)
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last_updown = -1
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else:
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if last_bi.dir == BI_DIR.DOWN:
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updown.append(0)
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else:
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updown.append(1)
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last_updown = 1
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else:
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updown.append(0)
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bi_list = kl_datas.bi_list
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if len(bi_list) > 0:
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last_bi = bi_list[-1]
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#if bi_list_pre_len > len(bi_list):
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#print("Bi ", klu.time, pre_bi.idx, pre_bi.is_sure, bi_list[-1].idx, bi_list[-1].is_sure)
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if last_bi.is_sure:
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bi_sure.append(1)
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#print(klu.time, last_bi.is_sure)
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else:
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bi_sure.append(0)
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pre_bi = bi_list[-1]
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bi_list_pre_len = len(bi_list)
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else:
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bi_sure.append(0)
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#if bsps[-1] != 0 or updown[-1] != 0:
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#print(klu.time, bsps[-1], updown[-1], bi_list[-1].is_sure)
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self.chanIn = False
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else:
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klu = CKLine_Unit(self.create_item_dict(self.get_last_item_data(dataframe), GetColumnNameFromFieldList(fields)), autofix=True)
|
||||
if self.last_kline.time < klu.time:
|
||||
self.chan.trigger_load({self.k_type: [klu]}) # 喂给CChan新增k线
|
||||
self.last_kline = klu
|
||||
#print(bsps)
|
||||
#print(updown)
|
||||
kl_datas = self.chan.kl_datas[self.k_type]
|
||||
#for zs in kl_datas.zs_list:
|
||||
#print(zs.begin.time, zs.end.time)
|
||||
return bsps, updown, bi_sure
|
||||
Reference in New Issue
Block a user