添加一个新的厕率
This commit is contained in:
jackyu66git
+5
-6
@@ -26,7 +26,7 @@ class ChanMACDHistSet():
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def set_middle_klu(self, middle_klu):
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self.middle_klu = middle_klu
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#self.middle_area = abs(middle_klu.macdhist)
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self.middle_klu = None
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#self.middle_klu = None
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def set_unittf_div(self, unittf_div):
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self.unittf_div = unittf_div
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def add_klu(self, klu):
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@@ -92,12 +92,11 @@ class ChanMACDHistSet():
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self.peak_klu = self.start_klu
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else:
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self.peak_klu = end_klu
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if self.start_klu.index + 2 == end_klu.index:
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peak = self.klu_list[0]
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if len(self.klu_list) >= 3 and self.peak_klu == None:
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self.peak_klu = self.klu_list[0]
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for klu in self.klu_list:
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if abs(klu.macdhist) > abs(peak.macdhist):
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peak = klu
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self.peak_klu = peak
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if abs(klu.macdhist) > abs(self.peak_klu.macdhist):
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self.peak_klu = klu
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peak_str = ""
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state_str = ""
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for peak_div in self.peak_div_list:
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@@ -48,6 +48,15 @@ class ChanSBI():
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#print(self.start_bi.start_time, self.end_bi.end_time, self.pre.start_bi.start_time, self.next.start_bi.start_time, self.dir, self.has_fx_gap, self.fx)
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return Chan_FX_TYPE.BOTTOM
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return Chan_FX_TYPE.UNKNOWN
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def check_seg_bi_broken(self):
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broken = False
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if self.fx == Chan_FX_TYPE.TOP:
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if self.next.low < self.pre.high:
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broken = True
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elif self.fx == Chan_FX_TYPE.BOTTOM:
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if self.next.high > self.pre.low:
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broken = True
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return broken
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def check_bi_included(self, bi):
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included = False
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if self.high > bi.high:
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@@ -118,7 +118,7 @@ class TF_DF():
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df['volume_ratio'] = self.cal_volume_ratio(df)
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return df
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def get_klu_state(self, dataframe):
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klc_list = self.get_klc_list(dataframe)
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klc_list = self.get_klc_list(self.get_klu_list(dataframe))
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bi_list = self.cal_bi_list(klc_list)
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klu_state_list = []
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klc_index = 0
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@@ -127,24 +127,41 @@ class TF_DF():
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klc_index = len(klc_list) - 1
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klc = klc_list[klc_index]
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if klc.end_klu and klc.end_klu.idx == index:
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if klc.klc_fx_type == Chan_KLC_FX.TOP4:
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if klc.klc_fx_type == Chan_KLC_FX.TOP1 or klc.klc_fx_type == Chan_KLC_FX.TOP2:
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klu_state_list.append("10")
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elif klc.klc_fx_type == Chan_KLC_FX.BOTTOM4:
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#print(klc.end_time, klc.klc_fx_type)
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elif klc.klc_fx_type == Chan_KLC_FX.BOTTOM1 or klc.klc_fx_type == Chan_KLC_FX.BOTTOM2:
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klu_state_list.append("-10")
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#print(klc.end_time, klc.klc_fx_type)
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else:
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klu_state_list.append("00")
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if klc.continue_div:
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if klc.macdhist > 0:
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klu_state_list.append("20")
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#print(klc.end_time, "CD", 20)
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else:
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klu_state_list.append("-20")
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#print(klc.end_time, "CD", -20)
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elif klc.separate_div:
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if klc.macdhist > 0:
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klu_state_list.append("30")
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#print(klc.end_time, "SD", 30)
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else:
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klu_state_list.append("-30")
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#print(klc.end_time, "SD", -30)
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else:
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klu_state_list.append("00")
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klc_index += 1
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else:
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klu_state_list.append("00")
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return klu_state_list
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def check_fx(self, klc):
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if klc.pre and klc.next:
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if klc.high > klc.pre.high and klc.high > klc.next.high and klc.low > klc.pre.low and klc.low > klc.next.low:
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if klc.high > klc.pre.high and klc.high > klc.next.high and klc.low > klc.pre.low and klc.low > klc.next.low and klc.macd> 0:
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#if (klc.close > klc.ema52 or klc.next.close > klc.next.ema52) and klc.macd > 0:
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klc.set_fx(Chan_FX_TYPE.TOP)
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#print(klc.start_time, klc.end_time,klc.next.start_time, klc.next.end_time, klc.macd, klc.state, klc.fx, "TOP")
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return Chan_FX_TYPE.TOP
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elif klc.low < klc.pre.low and klc.low < klc.next.low and klc.high < klc.pre.high and klc.high < klc.next.high:
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elif klc.low < klc.pre.low and klc.low < klc.next.low and klc.high < klc.pre.high and klc.high < klc.next.high and klc.macd < 0:
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#if (klc.close < klc.ema52 or klc.next.close < klc.next.ema52) and klc.macd < 0:
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klc.set_fx(Chan_FX_TYPE.BOTTOM)
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#print(klc.start_time, klc.end_time,klc.next.start_time, klc.next.end_time, klc.macd, klc.state, klc.fx, "BOTTOM")
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@@ -862,6 +879,7 @@ class TF_DF():
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if fx == Chan_FX_TYPE.BOTTOM:
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if last_top:
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if self.check_bottom_fx(last_top, klc) == False:
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#print(klc.end_time, last_top.end_time, "---")
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fx = Chan_FX_TYPE.UNKNOWN
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# Do nothing
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if fx == Chan_FX_TYPE.UNKNOWN:
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@@ -1171,12 +1189,12 @@ class TF_DF():
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#print(bi_list[index].start_time, bi_list[index].start_klc.start_time, bi_list[index].dir)
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return bi_list
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def check_top_fx(self, last_bottom, klc):
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if last_bottom.high > klc.pre.low or last_bottom.high > klc.next.low:
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if (last_bottom.high > klc.pre.low or last_bottom.high > klc.next.low) and (klc.index - last_bottom.index < 10):
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return False
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return True
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def check_bottom_fx(self, last_top, klc):
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if last_top.low < klc.pre.high or last_top.low < klc.next.high:
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if (last_top.low < klc.pre.high or last_top.low < klc.next.high) and (klc.index - last_top.index < 10):
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return False
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return True
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@@ -20,7 +20,7 @@ logger = logging.getLogger(__name__)
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# freqtrade plot-dataframe --strategy ChanLun_BTC_30 --datadir user_data/data/binance -c ./user_data/ChanLun_SOL_30.json --timerange=20250309-
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# freqtrade trade -c ./user_data/Chan/config/ChanLun_BTC_30.json --strategy ChanLun_BTC_30 --strategy-path ./user_data/Chan/strategies
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# freqtrade backtesting -c ./user_data/Chan/config/ChanLun_BTC_30.json --strategy ChanLun_BTC_30 --strategy-path ./user_data/Chan/strategies --timerange=20250901-
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# freqtrade backtesting -c ./user_data/Chan/config/ChanLun_BTC_30.json --strategy ChanLun_BTC_30 --strategy-path ./user_data/Chan/strategies --timerange=20260101-
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# freqtrade download-data -c ./user_data/Chan/config/ChanLun_BTC_30.json -t 1m --pairs BTC/USDT:USDT --timerange=20250405-
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# freqtrade hyperopt --hyperopt-loss SharpeHyperOptLossDaily --spaces roi --strategy ChanLun_BTC_30 --strategy-path ./user_data/Chan/strategies -c ./user_data/Chan/config/ChanLun_BTC_30.json -e 200 --timerange=20250201-20250901
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# freqtrade edge -c ./user_data/Chan/config/ChanLun_BTC_30.json --strategy ChanLun_BTC_30 --strategy-path ./user_data/Chan/strategies --timerange 20250721-20250901
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@@ -64,9 +64,9 @@ class ChanLun_BTC_30(IStrategy):
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}
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can_short = True
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lev = 2.0
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lev = 1.0
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stoploss = -0.3 # 设置为很大的负值，让custom_stoploss来控制
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use_custom_stoploss = True # 启用自定义止损
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use_custom_stoploss = False # 启用自定义止损
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trailing_stop = False
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trailing_stop_positive = 0.03
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@@ -75,7 +75,7 @@ class ChanLun_BTC_30(IStrategy):
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# 关闭分批止盈/仓位调整
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position_adjustment_enable = False
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startup_candle_count = 2880
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startup_candle_count = 1440
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time3 = 3
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time5 = 5
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time15 = 15
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@@ -92,61 +92,60 @@ class ChanLun_BTC_30(IStrategy):
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def populate_indicators(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
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# resample our dataframes
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dataframe_3 = resample_to_interval(dataframe, self.get_ticker_indicator() * 3)
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#dataframe_3 = resample_to_interval(dataframe, self.get_ticker_indicator() * 3)
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dataframe_5 = resample_to_interval(dataframe, self.get_ticker_indicator() * 5)
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dataframe_15 = resample_to_interval(dataframe, self.get_ticker_indicator() * 15)
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#dataframe_15 = resample_to_interval(dataframe, self.get_ticker_indicator() * 15)
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dataframe_30 = resample_to_interval(dataframe, self.get_ticker_indicator() * 30)
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dataframe_60 = resample_to_interval(dataframe, self.get_ticker_indicator() * 60)
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dataframe_2h = resample_to_interval(dataframe, self.get_ticker_indicator() * 120)
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dataframe_4h = resample_to_interval(dataframe, self.get_ticker_indicator() * 240)
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#dataframe_60 = resample_to_interval(dataframe, self.get_ticker_indicator() * 60)
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#dataframe_2h = resample_to_interval(dataframe, self.get_ticker_indicator() * 120)
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#dataframe_4h = resample_to_interval(dataframe, self.get_ticker_indicator() * 240)
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#dataframe_1d = self.dp.get_pair_dataframe(pair=metadata['pair'], timeframe='1d')
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#dataframe_1w = resample_to_interval(dataframe_1d, self.get_ticker_indicator() * 10080)
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#dataframe_1m = resample_to_interval(dataframe_1d, self.get_ticker_indicator() * 43200)
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dataframe_1d = resample_to_interval(dataframe, self.get_ticker_indicator() * 1440)
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#dataframe_1d = resample_to_interval(dataframe, self.get_ticker_indicator() * 1440)
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#dataframe_1w = resample_to_interval(dataframe, self.get_ticker_indicator() * 10080)
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#dataframe_1m = resample_to_interval(dataframe, self.get_ticker_indicator() * 43200)
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dataframe = self.add_indicators(dataframe)
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dataframe_3 = self.add_indicators(dataframe_3)
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#dataframe_3 = self.add_indicators(dataframe_3)
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dataframe_5 = self.add_indicators(dataframe_5)
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dataframe_15 = self.add_indicators(dataframe_15)
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#dataframe_15 = self.add_indicators(dataframe_15)
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dataframe_30 = self.add_indicators(dataframe_30)
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dataframe_60 = self.add_indicators(dataframe_60)
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dataframe_2h = self.add_indicators(dataframe_2h)
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dataframe_4h = self.add_indicators(dataframe_4h)
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dataframe_1d = self.add_indicators(dataframe_1d)
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#dataframe_60 = self.add_indicators(dataframe_60)
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#dataframe_2h = self.add_indicators(dataframe_2h)
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#dataframe_4h = self.add_indicators(dataframe_4h)
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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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#chanpy_state = self.chanpy.get_bsp_state(dataframe_5)
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#dataframe_5['chanpy_state'] = chanpy_state
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state_list = self.chan.get_klu_state_list(dataframe_3)
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dataframe_3['state'] = state_list
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state_list = self.chan.get_klu_state_list(dataframe_5)
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#state_list = self.chan.get_klu_state(dataframe_3)
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#dataframe_3['state'] = state_list
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state_list = self.chan.get_klu_state(dataframe_5)
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dataframe_5['state'] = state_list
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state_list = self.chan.get_klu_state_list(dataframe_15)
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dataframe_15['state'] = state_list
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state_list = self.chan.get_klu_state_list(dataframe_30)
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#state_list = self.chan.get_klu_state(dataframe_15)
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#dataframe_15['state'] = state_list
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state_list = self.chan.get_klu_state(dataframe_30)
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dataframe_30['state'] = state_list
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state_list = self.chan.get_klu_state_list(dataframe_60)
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dataframe_60['state'] = state_list
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state_list = self.chan.get_klu_state_list(dataframe_2h)
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dataframe_2h['state'] = state_list
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state_list = self.chan.get_klu_state_list(dataframe_4h)
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dataframe_4h['state'] = state_list
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state_list = self.chan.get_klu_state_list(dataframe_1d)
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dataframe_1d['state'] = state_list
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#state_list = self.chan.get_klu_state(dataframe_60)
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#dataframe_60['state'] = state_list
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#state_list = self.chan.get_klu_state(dataframe_2h)
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#dataframe_2h['state'] = state_list
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#state_list = self.chan.get_klu_state(dataframe_4h)
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#dataframe_4h['state'] = state_list
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#state_list = self.chan.get_klu_state(dataframe_1d)
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#dataframe_1d['state'] = state_list
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if self.last_time + timedelta(minutes=1) < datetime.now():
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print("-------------------------------------------------------------------------------")
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self.last_time = datetime.now()
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dataframe = resampled_merge(dataframe, dataframe_3)
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#dataframe = resampled_merge(dataframe, dataframe_3)
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dataframe = resampled_merge(dataframe, dataframe_5)
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dataframe = resampled_merge(dataframe, dataframe_15)
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#dataframe = resampled_merge(dataframe, dataframe_15)
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dataframe = resampled_merge(dataframe, dataframe_30)
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dataframe = resampled_merge(dataframe, dataframe_60)
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dataframe = resampled_merge(dataframe, dataframe_2h)
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dataframe = resampled_merge(dataframe, dataframe_4h)
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dataframe = resampled_merge(dataframe, dataframe_1d)
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#dataframe = resampled_merge(dataframe, dataframe_60)
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#dataframe = resampled_merge(dataframe, dataframe_2h)
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#dataframe = resampled_merge(dataframe, dataframe_4h)
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#dataframe = resampled_merge(dataframe, dataframe_1d)
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return dataframe
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def print_seg(self, dataframe):
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klc_list = self.chan.get_klc_list(dataframe)
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@@ -267,9 +266,9 @@ class ChanLun_BTC_30(IStrategy):
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return -0.05
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dataframe, _ = self.dp.get_analyzed_dataframe(trade.pair, self.timeframe)
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last_candle = dataframe.iloc[-1].squeeze()
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ema52_str = 'resample_{}_ema52'.format(self.get_ticker_indicator()*self.time60)
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ema52_str = 'resample_{}_ema52'.format(self.get_ticker_indicator()*self.time30)
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ema52_val = float(last_candle.get(ema52_str, 0) or 0)
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close_str = 'resample_{}_close'.format(self.get_ticker_indicator()*self.time60)
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close_str = 'resample_{}_close'.format(self.get_ticker_indicator()*self.time30)
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close_val = float(last_candle.get(close_str, 0) or 0)
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if close_val < ema52_val:
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return -0.01
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@@ -282,6 +281,8 @@ class ChanLun_BTC_30(IStrategy):
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def custom_exit(self, pair: str, trade: Trade, current_time: datetime, current_rate: float,
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current_profit: float, **kwargs):
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# 不做分批止盈/最终止盈处理，退出由策略信号/ROI/止损决定
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if current_profit > 0.008:
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return "Take profit"
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return None
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def confirm_trade_entry(self, pair: str, order_type: str, amount: float, rate: float,
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@@ -295,7 +296,7 @@ class ChanLun_BTC_30(IStrategy):
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if dataframe is None or len(dataframe) == 0:
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return False
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last = dataframe.iloc[-1]
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atr_str = 'resample_{}_atr'.format(self.get_ticker_indicator()*self.time60)
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atr_str = 'resample_{}_atr'.format(self.get_ticker_indicator()*self.time30)
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atr_val = float(last.get(atr_str, 0) or 0)
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if atr_val < 0.001:
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#logger.info(f"ATR过滤：atr={atr_val:.2f} < 100, 拒绝进场 {pair}")
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@@ -318,7 +319,7 @@ class ChanLun_BTC_30(IStrategy):
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# Obtain pair dataframe (just to show how to access it)
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dataframe, _ = self.dp.get_analyzed_dataframe(trade.pair, self.timeframe)
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last_candle = dataframe.iloc[-1].squeeze()
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atr_str = 'resample_{}_atr'.format(self.get_ticker_indicator()*self.time60)
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atr_str = 'resample_{}_atr'.format(self.get_ticker_indicator()*self.time30)
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# 保存开仓时的ATR值用于止损计算
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if (trade.nr_of_successful_entries == 1) and (order.ft_order_side == trade.entry_side):
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entry_atr = last_candle[atr_str] * 4
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@@ -326,36 +327,34 @@ class ChanLun_BTC_30(IStrategy):
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#logger.info(f"保存开仓时ATR值: {entry_atr}")
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return None
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def populate_entry_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
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shift60 = self.time60
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state60 = 'resample_{}_state'.format(self.get_ticker_indicator()*shift60)
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shift30 = self.time30
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state30 = 'resample_{}_state'.format(self.get_ticker_indicator()*shift30)
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dataframe.loc[
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(
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(dataframe[state60].shift(shift60) == "-20")
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(dataframe[state30].shift(shift30) == "-10") |
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(dataframe[state30].shift(shift30) == "-20") |
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(dataframe[state30].shift(shift30) == "-30")
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),
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['enter_long', 'enter_tag']] = (1, 'long_30')
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['enter_long', 'enter_tag']] = (1, 'long_10')
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dataframe.loc[
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(
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(dataframe[state30].shift(shift30) == "40")
|
||||
(dataframe[state30].shift(shift30) == "10") |
|
||||
(dataframe[state30].shift(shift30) == "20") |
|
||||
(dataframe[state30].shift(shift30) == "30")
|
||||
),
|
||||
['enter_short', 'enter_tag']] = (1, 'short_30')
|
||||
['enter_short', 'enter_tag']] = (1, 'short_10')
|
||||
return dataframe
|
||||
def populate_exit_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
|
||||
shift60 = self.time60
|
||||
state60 = 'resample_{}_state'.format(self.get_ticker_indicator()*shift60)
|
||||
shift30 = self.time30
|
||||
state30 = 'resample_{}_state'.format(self.get_ticker_indicator()*shift30)
|
||||
dataframe.loc[
|
||||
(
|
||||
(dataframe[state60].shift(shift60) == "20") |
|
||||
(dataframe[state60].shift(shift60) == "30")
|
||||
(dataframe[state30].shift(shift30) == "10")
|
||||
),
|
||||
['exit_long', 'exit_tag']] = (1, 'long_close_30')
|
||||
dataframe.loc[
|
||||
(
|
||||
(dataframe[state30].shift(shift30) == "-20") |
|
||||
(dataframe[state30].shift(shift30) == "-30")
|
||||
(dataframe[state30].shift(shift30) == "-10")
|
||||
),
|
||||
['exit_short', 'exit_tag']] = (1, 'short_close_30')
|
||||
return dataframe
|
||||
|
||||
Reference in New Issue
Block a user