142 lines
4.9 KiB
Python
142 lines
4.9 KiB
Python
"""TF_DF builder mixin — 由 split_tfdf_builders 自动生成，逻辑与原 TF_DF 一致。"""
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from __future__ import annotations
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from datetime import timedelta
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from decimal import Decimal
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import numpy as np
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import pandas as pd
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from chanlun.indicators import ta
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from pandas import DataFrame
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from chanlun.core.ChanBI import ChanBI
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from chanlun.core.ChanBIZS import ChanBIZS
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from chanlun.core.ChanBSP import ChanBSP
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from chanlun.core.ChanEnum import (
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Chan_BI_DIR,
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Chan_BSP_DIR,
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Chan_BSP_TYPE,
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Chan_FX_TYPE,
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Chan_K_DIR,
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Chan_KLC_FX,
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Chan_KLC_STATE,
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Chan_KLINE_DIR,
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Chan_KLU_PATTERN,
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Chan_PRICE_TREND,
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Chan_SEG_DIR,
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Chan_ZS_DIR,
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)
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from chanlun.core.ChanKLC import ChanKLC
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from chanlun.core.ChanKLU import ChanKLU
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from chanlun.core.ChanSBI import ChanSBI
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from chanlun.core.ChanSEG import ChanSEG
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from chanlun.core.ChanZS import ChanZS, ChanZS_Big
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from chanlun.indicators.ChanMACD import ChanMACD
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class IndicatorsBuilderMixin:
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def get_ema52(self, index=-1):
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if self.klu_list:
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ema52_value = self.klu_list[index].ema52
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# 处理NaN值
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if pd.isna(ema52_value) or ema52_value is None:
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return None
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return float(ema52_value)
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return None
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def get_ema24(self, index=-1):
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if self.klu_list:
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ema24_value = self.klu_list[index].ema24
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# 处理NaN值
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if pd.isna(ema24_value) or ema24_value is None:
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return None
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return float(ema24_value)
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return None
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def add_indicators(self, df):
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"""算指标并一次性挂到 df 上。
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这里不逐列 `df['x'] = ...`：那样每一列都触发一次 BlockManager 插入，
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30 多列的开销比全部 TA 计算本身还大（2001 行实测 TA 合计 2.5ms，
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逐列赋值 3.6ms）。增量路径每根都要走一遍，这笔开销是白付的。
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"""
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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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bb2633 = ta.BBANDS(df, timeperiod=26, nbdevup=3.0, nbdevdn=3.0, 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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bbp2633 = (df['close'] - bb2633['lowerband']) / (bb2633['upperband'] - bb2633['lowerband'])
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cols = {
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'bb2633upper': bb2633['upperband'],
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'bb2633lower': bb2633['lowerband'],
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'bbp2633': bbp2633,
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'bb2633middle': bb2633['middleband'],
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'atr': ta.ATR(df, timeperiod=14),
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'bbup365': bb365['upperband'],
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'bblow365': bb365['lowerband'],
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'bbp365': bbp365,
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'bbup120': bb120['upperband'],
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'bblow120': bb120['lowerband'],
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'bbp120': bbp120,
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'bbup30': bb30['upperband'],
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'bblow30': bb30['lowerband'],
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'bbmiddle30': bb30_middle,
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'bbp30': bbp30,
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'bbup302': bb302['upperband'],
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'bblow302': bb302['lowerband'],
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'bbp302': bbp302,
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'macd': macd['macd'],
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'macdsignal': macd['macdsignal'],
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'macdhist': macd['macdhist'],
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}
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for _p, _n in ((5, 'ema5'), (10, 'ema10'), (24, 'ema24'), (52, 'ema52'),
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(104, 'ema104'), (156, 'ema156'), (208, 'ema208'),
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(26, 'ema26'), (13, 'ema13'), (7, 'ema7')):
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cols[_n] = ta.EMA(df, timeperiod=_p)
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cols['rsi'] = ta.RSI(df, timeperiod=14)
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cols['volume_ratio'] = self.cal_volume_ratio(df)
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# 重复调用（增量路径每根都会）时先摘掉旧列，否则 concat 出重名列。
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# 摘掉再接回末尾，列序与逐列覆盖的结果一致。
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new = pd.DataFrame(cols, index=df.index)
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dup = [c for c in new.columns if c in df.columns]
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if dup:
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df = df.drop(columns=dup)
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return pd.concat([df, new], axis=1)
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def get_ema_state(self, dataframe):
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klu_list = self.get_klu_list(dataframe)
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klc_list = self.get_klc_list(klu_list)
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bi_list = self.cal_bi_list(klc_list)
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klu_state_list = []
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for klu in klu_list:
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if klu.near0_return == 1:
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klu_state_list.append("1")
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elif klu.near0_return == 9:
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klu_state_list.append("-1")
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elif klu.candle_dir == Chan_K_DIR.BULL:
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klu_state_list.append("2")
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elif klu.candle_dir == Chan_K_DIR.BEAR:
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klu_state_list.append("-2")
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else:
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klu_state_list.append("0")
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return klu_state_list
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def get_decimal(self, value):
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return Decimal("{:.2f}".format(value))
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