mirror of
https://gitee.com/fasiondog/hikyuu.git
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136 lines
4.4 KiB
Python
136 lines
4.4 KiB
Python
#!/usr/bin/python
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# -*- coding: utf8 -*-
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# cp936
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#
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# The MIT License (MIT)
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#
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# Copyright (c) 2017 fasiondog
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#
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# Permission is hereby granted, free of charge, to any person obtaining a copy
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# of this software and associated documentation files (the "Software"), to deal
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# in the Software without restriction, including without limitation the rights
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# to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
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# copies of the Software, and to permit persons to whom the Software is
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# furnished to do so, subject to the following conditions:
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#
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# The above copyright notice and this permission notice shall be included in all
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# copies or substantial portions of the Software.
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#
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# THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
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# IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
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# FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
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# AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
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# LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
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# OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
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# SOFTWARE.
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from hikyuu.core import *
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from hikyuu import Datetime
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import pandas as pd
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def indicator_iter(indicator):
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for i in range(len(indicator)):
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yield indicator[i]
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def indicator_getitem(data, i):
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"""
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:param i: int | Datetime | slice | str 类型
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"""
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if isinstance(i, int):
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length = len(data)
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index = length + i if i < 0 else i
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if index < 0 or index >= length:
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raise IndexError("index out of range: %d" % i)
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return data.get(index)
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elif isinstance(i, slice):
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return [data.get(x) for x in range(*i.indices(len(data)))]
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elif isinstance(i, Datetime):
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return data.get_by_datetime(i)
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elif isinstance(i, str):
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return data.get_by_datetime(Datetime(i))
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else:
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raise IndexError("Error index type")
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Indicator.__getitem__ = indicator_getitem
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Indicator.__iter__ = indicator_iter
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def indicator_to_df(indicator):
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"""转化为pandas.DataFrame"""
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if indicator.get_result_num() == 1:
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return pd.DataFrame(indicator.to_np(), columns=[indicator.name])
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data = {}
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name = indicator.name
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columns = []
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for i in range(indicator.get_result_num()):
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data[name + str(i)] = indicator.get_result(i)
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columns.append(name + str(i + 1))
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return pd.DataFrame(data, columns=columns)
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Indicator.to_df = indicator_to_df
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def concat_to_df(dates, ind_list, head_stock_code=True, head_ind_name=False):
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"""将列表中的指标至合并在一张 pandas DataFrame 中
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:param DatetimeList dates: 指定的日期列表
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:param sequence ind_list: 已计算的指标列表
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:param bool head_ind_name: 表标题是否使用指标名称
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:param bool head_stock_code: 表标题是否使用证券代码
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:return: 合并后的 DataFrame, 以 dates 为 index（注: dates列 为 Datetime 类型）
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示例:
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query = Query(-200)
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k_list = [stk.get_kdata(query) for stk in [sm['sz000001'], sm['sz000002']]]
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ma_list = [MA(k) for k in k_list]
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concat_to_df(sm.get_trading_calendar(query), ma_list, head_stock_code=True, head_ind_name=False)
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输出：
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date SZ000001 SZ000002
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0 2023-05-12 00:00:00 12.620000 15.060000
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1 2023-05-15 00:00:00 12.725000 15.060000
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2 2023-05-16 00:00:00 12.690000 15.010000
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3 2023-05-17 00:00:00 12.640000 14.952500
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4 2023-05-18 00:00:00 12.610000 14.886000
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... ... ... ...
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195 2024-03-01 00:00:00 9.950455 9.837273
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196 2024-03-04 00:00:00 9.995909 9.838182
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197 2024-03-05 00:00:00 10.038182 9.816364
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198 2024-03-06 00:00:00 10.070455 9.776818
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199 2024-03-07 00:00:00 10.101364 9.738182
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"""
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df = pd.DataFrame(dates, columns=['date'])
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for ind in ind_list:
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x = ALIGN(ind, dates)
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if head_ind_name and head_stock_code:
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x.name = f"{ind.name}/{ind.get_context().get_stock().market_code}"
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elif head_ind_name:
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x.name = ind.name
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else:
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x.name = ind.get_context().get_stock().market_code
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df = pd.concat([df, x.to_df()], axis=1)
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df.set_index('date')
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return df
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# 避免 python 中公式原型必须加括号
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KDATA = C_KDATA()
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CLOSE = C_CLOSE()
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OPEN = C_OPEN()
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HIGH = C_HIGH()
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LOW = C_LOW()
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AMO = C_AMO()
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VOL = C_VOL()
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# 同名指标
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VALUE = PRICELIST
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CAPITAL = LIUTONGPAN
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