106 lines
3.9 KiB
Python
106 lines
3.9 KiB
Python
# -*- encoding:utf-8 -*-
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"""
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技术指标工具基础模块
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"""
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from __future__ import absolute_import
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from __future__ import print_function
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from __future__ import division
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import logging
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import pandas as pd
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from enum import Enum
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from ..UtilBu import ABuDateUtil
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__author__ = '阿布'
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__weixin__ = 'abu_quant'
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class ECalcType(Enum):
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"""
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技术指标技术方式类
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"""
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"""使用talib透传技术指标计算"""
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E_FROM_TA = 0
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"""使用pandas等库实现技术指标计算"""
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E_FROM_PD = 1
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# try:
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# # 不强制要求talib，全部局部引用
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# # noinspection PyUnresolvedReferences
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# import talib
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# g_calc_type = ECalcType.E_FROM_TA
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# except ImportError:
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# # 没有安装talib，使用E_FROM_PD
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# g_calc_type = ECalcType.E_FROM_PD
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"""彻底不用talib，完全都使用自己计算的指标结果"""
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g_calc_type = ECalcType.E_FROM_PD
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def plot_from_order(plot_nd_func, order, date_ext, **kwargs):
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"""
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封装在技术指标上绘制交易order信号通用流程
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:param plot_nd_func: 绘制技术指标的具体实现函数，必须callable
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:param order: AbuOrder对象转换的pd.DataFrame对象or pd.Series对象
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:param date_ext: int对象 eg. 如交易在2015-06-01执行，如date_ext＝120，择start向前推120天，end向后推120天
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:param kwargs: plot_nd_func需要的其它关键字参数，直接透传给plot_nd_func
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"""
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if not callable(plot_nd_func):
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# plot_nd_func必须是callable
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raise TypeError('plot_nd_func must callable!!')
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if not isinstance(order, (pd.DataFrame, pd.Series)) and order.shape[0] > 0:
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# order必须是pd.DataFrame对象or pd.Series对象 且 单子数量要 > 0
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raise TypeError('order must DataFrame here!!')
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is_df = isinstance(order, pd.DataFrame)
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if is_df and order.shape[0] == 1:
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# 如果是只有1行pd.DataFrame对象则变成pd.Series
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is_df = False
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# 通过iloc即变成pd.Series对象
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# noinspection PyUnresolvedReferences
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order = order.iloc[0]
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def plot_from_series(p_order):
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"""
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根据交易的symbol信息买入，卖出时间，以及date_ext完成通过ABuSymbolPd.make_kl_df获取金融时间序列，
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在成功获取数据后使用plot_nd_func完成买入卖出信号绘制及对应的技术指标绘制
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:param p_order: AbuOrder对象转换的pd.Series对象
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"""
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# 确定交易对象
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target_symbol = p_order['symbol']
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# 单子都必须有买入时间
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buy_index = pd.to_datetime(str(p_order['buy_date']))
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sell_index = None
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start = ABuDateUtil.fmt_date(p_order['buy_date'])
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# 通过date_ext确定start，即买人单子向前推date_ext天
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start = ABuDateUtil.begin_date(date_ext, date_str=start, fix=False)
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if p_order['sell_type'] != 'keep':
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sell_index = pd.to_datetime(str(p_order['sell_date']))
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# 如果有卖出，继续通过sell_date，date_ext确定end时间
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end = ABuDateUtil.fmt_date(p_order['sell_date'])
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# -date_ext 向前
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end = ABuDateUtil.begin_date(-date_ext, date_str=end, fix=False)
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else:
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end = None
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from ..MarketBu import ABuSymbolPd
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# 组织好参数，确定了请求范围后开始获取金融时间序列数据
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kl_pd = ABuSymbolPd.make_kl_df(target_symbol, start=start, end=end)
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if kl_pd is None or kl_pd.shape[0] == 0:
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logging.debug(target_symbol + ': has net error in data')
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return
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# 使用plot_nd_func完成买入卖出信号绘制及对应的技术指标绘制
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return plot_nd_func(kl_pd, with_points=buy_index, with_points_ext=sell_index, **kwargs)
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if not is_df:
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return plot_from_series(order)
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else:
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# 多个order, apply迭代执行plot_from_series
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order = order[order['result'] != 0]
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return order.apply(plot_from_series, axis=1)
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