修改了很多，明天继续
This commit is contained in:
jackyu66git
@@ -1,6 +1,6 @@
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from datetime import timedelta
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from pandas import DataFrame
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from ChanEnum import Chan_FX_TYPE, Chan_KLINE_DIR, Chan_BI_DIR, Chan_SEG_DIR, Chan_ZS_DIR, Chan_BSP_DIR, Chan_BSP_TYPE, Chan_KLC_FX
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from ChanEnum import Chan_FX_TYPE, Chan_KLINE_DIR, Chan_BI_DIR, Chan_SEG_DIR, Chan_ZS_DIR, Chan_BSP_DIR, Chan_BSP_TYPE, Chan_KLC_FX, Chan_PRICE_TREND
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from ChanKLU import ChanKLU
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from ChanKLC import ChanKLC
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from ChanBI import ChanBI
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@@ -20,40 +20,213 @@ import numpy as np
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from ChanMACD import ChanMACD
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class TF_DF():
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def __init__(self, timeframe, df, ticker_indicator):
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self.timeframe = timeframe
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self.dataframe = resample_to_interval(df, ticker_indicator*timeframe)
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self.ticker_indicator = ticker_indicator
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self.klu_list = []
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self.klc_list = []
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self.bi_list = []
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self.zs_list = []
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self.bsp_list = []
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self.seg_list = []
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self.init_TF_DF()
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def init_TF_DF(self):
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self.klu_list = self.cal_kl_data(self.dataframe)
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self.klc_list = self.cal_klc_list(self.klu_list)
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self.bi_list = self.cal_bi_list(self.klc_list)
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self.seg_list = self.cal_seg_list(self.bi_list)
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self.zs_list = self.cal_zs_list(self.bi_list, self.seg_list)
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self.chanmacd = ChanMACD(self.klu_list)
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self.klu_list = self.chanmacd.cal_macd_state()
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def check_fx(self, klc):
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def __init__(self, timeframe, df, ticker_indicator):
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self.timeframe = timeframe
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self.dataframe = resample_to_interval(df, ticker_indicator*timeframe)
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self.dataframe = self.add_indicators(self.dataframe)
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self.ticker_indicator = ticker_indicator
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self.klu_list = []
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self.klc_list = []
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self.bi_list = []
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self.zs_list = []
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self.bsp_list = []
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self.seg_list = []
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self.init_TF_DF()
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def init_TF_DF(self):
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self.klu_list = self.cal_kl_data(self.dataframe)
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self.klc_list = self.cal_klc_list(self.klu_list)
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self.bi_list = self.cal_bi_list(self.klc_list)
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self.seg_list = self.cal_seg_list(self.bi_list)
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self.zs_list = self.cal_zs_list(self.bi_list, self.seg_list)
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self.chanmacd = ChanMACD(self.klu_list)
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self.klu_list = self.chanmacd.cal_macd_state()
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def add_indicators(self, df):
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fast = 12
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slow = 26
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period = 9
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macd = ta.MACD(df, fastperiod=fast, slowperiod=slow, signalperiod=period)
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bb365 = ta.BBANDS(df, timeperiod=365, nbdevup=3.0, nbdevdn=3.0, matype=0)
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bb120 = ta.BBANDS(df, timeperiod=120, nbdevup=3.0, nbdevdn=3.0, matype=0)
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bb30 = ta.BBANDS(df, timeperiod=41, nbdevup=2.3, nbdevdn=2.3, matype=0)
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bb302 = ta.BBANDS(df, timeperiod=41, nbdevup=2.0, nbdevdn=2.0, matype=0)
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bb30 = ta.BBANDS(df, timeperiod=20, nbdevup=2.0, nbdevdn=2.0, matype=0)
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bb302 = ta.BBANDS(df, timeperiod=20, nbdevup=2.0, nbdevdn=2.0, matype=0)
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# 计算布林带中轨（移动平均线）
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bb30_middle = ta.SMA(df, timeperiod=90)
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# 手动计算布林带 %B 指标 (BBP)
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# %B = (Price - Lower Band) / (Upper Band - Lower Band)
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bbp365 = (df['close'] - bb365['lowerband']) / (bb365['upperband'] - bb365['lowerband'])
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bbp120 = (df['close'] - bb120['lowerband']) / (bb120['upperband'] - bb120['lowerband'])
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bbp30 = (df['close'] - bb30['lowerband']) / (bb30['upperband'] - bb30['lowerband'])
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bbp302 = (df['close'] - bb302['lowerband']) / (bb302['upperband'] - bb302['lowerband'])
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df['atr'] = ta.ATR(df, timeperiod=14)
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df['bbup365'] = bb365['upperband']
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df['bblow365'] = bb365['lowerband']
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df['bbp365'] = bbp365
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df['bbup120'] = bb120['upperband']
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df['bblow120'] = bb120['lowerband']
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df['bbp120'] = bbp120
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df['bbup30'] = bb30['upperband']
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df['bblow30'] = bb30['lowerband']
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df['bbmiddle30'] = bb30_middle # 添加bb30中轨
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df['bbp30'] = bbp30
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df['bbup302'] = bb302['upperband']
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df['bblow302'] = bb302['lowerband']
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df['bbp302'] = bbp302
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df['macd'] = macd['macd']
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df['macdsignal'] = macd['macdsignal']
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df['macdhist'] = macd['macdhist']
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df['ema5'] = ta.EMA(df, timeperiod=5)
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df['ema10'] = ta.EMA(df, timeperiod=10)
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df['ema24'] = ta.EMA(df, timeperiod=24)
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df['ema26'] = ta.EMA(df, timeperiod=26)
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df['ema52'] = ta.EMA(df, timeperiod=52)
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df['rsi'] = ta.RSI(df, timeperiod=14)
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df['volume_ratio'] = self.cal_volume_ratio(df)
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return df
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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:
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if klc.macd > 0 and klc.macd > klc.signal and klc.signal > klc.macdhist:
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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.fx, "TOP")
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# print(klc.start_time, klc.end_time,klc.next.start_time, klc.next.end_time,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:
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if klc.macd < 0 and klc.macd < klc.signal and klc.signal < klc.macdhist:
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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.fx, "BOTTOM")
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# print(klc.start_time, klc.end_time,klc.next.start_time, klc.next.end_time,klc.fx, "BOTTOM")
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return Chan_FX_TYPE.BOTTOM
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return Chan_FX_TYPE.UNKNOWN
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def cal_kl_data(self, dataframe:DataFrame):
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def cal_volume_ratio(self, dataframe, window=10):
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df = dataframe.copy()
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# 计算过去N根K线的平均成交量
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df['avg_volume'] = df['volume'].rolling(window=window).mean()
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# 计算量比
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df['volume_ratio'] = df['volume'] / df['avg_volume']
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# 填充缺失值（前N根K线）
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df['volume_ratio'] = df['volume_ratio'].fillna(1.0)
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return df['volume_ratio']
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def cal_trend(self, klc_list):
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"""
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基于价格与EMA24/EMA52的位置关系、以及MACD/Signal/Hist的方向，
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为每个KLC打上趋势标签：'UP' / 'DOWN' / 'FLAT'。
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仅设置 klc.trend，不影响其它字段。
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"""
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if not klc_list:
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return klc_list
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last_trend = Chan_PRICE_TREND.UNKNOWN
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for klc in klc_list:
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price = getattr(klc, 'close', None)
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ema24 = getattr(klc, 'ema24', None)
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ema52 = getattr(klc, 'ema52', None)
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macd = getattr(klc, 'macd', 0) if getattr(klc, 'macd', None) is not None else 0
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signal = getattr(klc, 'signal', 0) if getattr(klc, 'signal', None) is not None else 0
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hist = getattr(klc, 'macdhist', 0) if getattr(klc, 'macdhist', None) is not None else 0
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rsi = getattr(klc, 'rsi', None)
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trend = Chan_PRICE_TREND.UNKNOWN
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try:
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# 有效性
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price_valid = price is not None and price != 0
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ema24_valid = ema24 is not None and ema24 != 0
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ema52_valid = ema52 is not None and ema52 != 0
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# 多因子投票
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score = 0
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# 1) 均线结构 + 价位
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if ema24_valid and ema52_valid:
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score += 1 if ema24 > ema52 else -1
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if price_valid and ema24_valid:
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score += 1 if price > ema24 else -1
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if price_valid and ema52_valid:
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score += 1 if price > ema52 else -1
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# 2) MACD结构
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score += 1 if macd >= signal else -1
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if hist != 0:
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score += 1 if hist > 0 else -1
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# 3) 动量与均线差分斜率
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pre = getattr(klc, 'pre', None)
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if pre:
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pre_close = getattr(pre, 'close', None)
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if price_valid and pre_close is not None:
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score += 1 if price >= pre_close else -1
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pre_ema24 = getattr(pre, 'ema24', None)
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pre_ema52 = getattr(pre, 'ema52', None)
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if ema24_valid and ema52_valid and pre_ema24 not in (None, 0) and pre_ema52 not in (None, 0):
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spread_now = ema24 - ema52
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spread_pre = pre_ema24 - pre_ema52
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score += 1 if spread_now >= spread_pre else -1
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# 4) RSI 辅助
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if rsi is not None:
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if rsi >= 55:
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score += 1
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elif rsi <= 45:
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score -= 1
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# 5) 指标未就绪回退（EMA/MACD缺失时，用动量与RSI辅助，延续趋势）
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has_full_ind = ema24_valid and ema52_valid and not (macd == 0 and signal == 0 and hist == 0)
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if not has_full_ind:
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# 仅根据价动量/RSI做轻量判断，默认延续 last_trend，除非出现强反向
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strong_up = False
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strong_down = False
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pre = getattr(klc, 'pre', None)
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if pre:
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pre_close = getattr(pre, 'close', None)
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if price_valid and pre_close is not None:
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strong_up = (price >= pre_close)
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strong_down = (price < pre_close)
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if rsi is not None:
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if rsi >= 60:
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strong_up = True
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elif rsi <= 40:
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strong_down = True
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if last_trend == Chan_PRICE_TREND.UP and not strong_down:
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trend = Chan_PRICE_TREND.UP
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elif last_trend == Chan_PRICE_TREND.DOWN and not strong_up:
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trend = Chan_PRICE_TREND.DOWN
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else:
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trend = Chan_PRICE_TREND.UP if strong_up and not strong_down else (Chan_PRICE_TREND.DOWN if strong_down and not strong_up else Chan_PRICE_TREND.FLAT)
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else:
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# 6) 震荡过滤（仅当极近EMA52且MACD贴合时判作震荡）
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near_flat = False
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if price_valid and ema52_valid:
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near_ema52 = abs(price - ema52) / abs(ema52) <= 0.0005 # 0.05%
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near_macd = abs(macd - signal) <= (abs(price) * 0.00005 if price_valid else 0)
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near_flat = near_ema52 and near_macd
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# 7) 动态阈值 + 趋势记忆（更强粘滞：趋势中容忍小幅反分）
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if near_flat:
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trend = Chan_PRICE_TREND.FLAT
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else:
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if last_trend == Chan_PRICE_TREND.UP:
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# 仅当出现明显反向才翻转，否则维持UP
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if score <= -2:
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trend = Chan_PRICE_TREND.DOWN
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else:
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trend = Chan_PRICE_TREND.UP
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elif last_trend == Chan_PRICE_TREND.DOWN:
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if score >= 2:
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trend = Chan_PRICE_TREND.UP
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else:
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trend = Chan_PRICE_TREND.DOWN
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else:
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# 初始无记忆时，降低进入门槛
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if score >= 1:
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trend = Chan_PRICE_TREND.UP
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elif score <= -1:
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trend = Chan_PRICE_TREND.DOWN
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else:
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trend = Chan_PRICE_TREND.FLAT
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except Exception:
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trend = Chan_PRICE_TREND.UNKNOWN
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# 写回趋势
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if hasattr(klc, 'set_trend'):
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klc.set_trend(trend)
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else:
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setattr(klc, 'trend', trend)
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last_trend = trend
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price_diff = klc.close - klc.pre.close if klc.pre else 0
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print(klc.start_time, klc.end_time, klc.close, klc.ema24, klc.ema52, klc.macd, klc.signal, klc.macdhist, klc.trend, price_diff)
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#print(klc.start_time, klc.end_time, klc.trend, price_diff)
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return klc_list
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def cal_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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last_klu = None
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@@ -65,8 +238,8 @@ class TF_DF():
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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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#date = date + timedelta(hours=8)
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# time_obj = date.fromtimestamp(date)
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# date = date + timedelta(hours=8)
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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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@@ -76,9 +249,9 @@ class TF_DF():
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c,
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v
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]
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#klu = KLU(self.create_item_dict(item_data, GetColumnNameFromFieldList(fields)))
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# klu = KLU(self.create_item_dict(item_data, GetColumnNameFromFieldList(fields)))
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klu = ChanKLU(time_str, o, h, l, c, v)
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#print(klu.time, klu.open, klu.high, klu.low, klu.close, klu.volume)
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# print(klu.time, klu.open, klu.high, klu.low, klu.close, klu.volume)
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klu.set_idx(i)
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klu_list.append(klu)
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if last_klu:
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@@ -89,7 +262,7 @@ class TF_DF():
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klu.set_indicators(item)
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return klu_list
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def cal_klc_list(self, klu_list):
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def cal_klc_list(self, klu_list):
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klc_list = []
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last_klu = None
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macd = ChanMACD(klu_list)
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@@ -117,9 +290,10 @@ class TF_DF():
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klc = ChanKLC(klu, 0, ddir)
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klc_list.append(klc)
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last_klu = klu
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klc_list = self.cal_trend(klc_list)
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return klc_list
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def cal_seg_list(self, bi_list):
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def cal_seg_list(self, bi_list):
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seg_list = []
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up_bi_list = []
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down_bi_list = []
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@@ -707,7 +881,7 @@ 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 get_decimal(self, value):
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def get_decimal(self, value):
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return Decimal("{:.2f}".format(value))
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def cal_zs_list(self, bi_list, seg_list):
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