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series.py
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245 lines (194 loc) · 6.15 KB
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# -*- coding: utf-8 -*-
import numpy as np
from quantdigger.errors import SeriesIndexError
import datetime
class SeriesBase(object):
def __init__(self, data=[], name='series', indic=None, default=None):
""" 序列变量的基类。
name用来跟踪
"""
self.curbar = 0
self._window_size = len(data)
self._indic = indic
self._default = default
self._realtime = False
self.name = name
if len(data) == 0:
self.data = np.array([self._default] * self._window_size)
else:
self.data = data
def reset_data(self, data, wsize):
""" 初始化值和窗口大小
Args:
data (list|ndarray|pd.Series): 数据，类型为支持索引的数据结构
wwsize (int): 窗口大小
"""
self._window_size = wsize
if len(data) == 0:
self.data = np.array([self._default] * self._window_size)
else:
# 序列系统变量
self.data = data
def update_curbar(self, curbar):
""" 更新当前Bar索引 """
self.curbar = curbar
def update(self, v):
""" 更新最后一个值 """
if isinstance(v, SeriesBase):
self.data[self.curbar] = v[0]
else:
self.data[self.curbar] = v
def __len__(self):
return len(self.data)
def duplicate_last_element(self):
"""
非指标序列变量才会运行
"""
try:
pre_elem = self.data[(self.curbar-1) % self._window_size]
except KeyError:
return
else:
self.data[self.curbar] = pre_elem
def __str__(self):
return str(self[0])
def __getitem__(self, index):
raise NotImplementedError
#def __call__(self, *args):
#length = len(args)
#if length == 0:
#return float(self)
#elif length == 1:
#return self.data[self.curbar - args[0]]
class NumberSeries(SeriesBase):
""" 数字序列变量"""
DEFAULT_VALUE = 0.0
value_type = float
def __init__(self, data=[], name='NumberSeries', indic=None, default=0.0):
super(NumberSeries, self).__init__(data, name, indic, default)
return
def __float__(self):
return self[0]
#
def __eq__(self, r):
return self[0] == float(r)
def __lt__(self, r):
return self[0] < float(r)
def __le__(self, r):
return self[0] <= float(r)
def __ne__(self, r):
return self[0] != float(r)
def __gt__(self, r):
return self[0] > float(r)
def __ge__(self, r):
return self[0] >= float(r)
#
def __iadd__(self, r):
self[0] += float(r)
return self
def __isub__(self, r):
self[0] -= float(r)
return self
def __imul__(self, r):
self[0] *= float(r)
return self
def __idiv__(self, r):
self[0] /= float(r)
return self
def __ifloordiv__(self, r):
self[0] %= float(r)
return self
#
def __add__(self, r):
return self[0] + float(r)
def __sub__(self, r):
return self[0] - float(r)
def __mul__(self, r):
return self[0] * float(r)
def __div__(self, r):
return self[0] / float(r)
def __mod__(self, r):
return self[0] % float(r)
def __pow__(self, r):
return self[0] ** float(r)
#
def __radd__(self, r):
return float(r) + self[0]
def __rsub__(self, r):
return float(r) - self[0]
def __rmul__(self, r):
return float(r) * self[0]
def __rdiv__(self, r):
return float(r) / self[0]
def __rmod__(self, r):
return float(r) % self[0]
def __rpow__(self, r):
return float(r) ** self[0]
def __getitem__(self, index):
try:
if self._realtime:
#if index<0:
#return self._default
#if self._shift:
## 输入
#return self.data[self._index-index]
## 输出
#i = self.curbar - index
#if self._indic:
## 延迟计算
#self._indic.compute_element(i%self._window_size, index)
#return self.data[i%self._window_size]
assert(False)
else:
i = self.curbar - index
if i < 0 or index < 0:
return self._default
else:
return float(self.data[i])
except SeriesIndexError:
raise SeriesIndexError
def __call__(self, index):
return self[index]
class DateTimeSeries(SeriesBase):
""" 时间序列变量 """
DEFAULT_VALUE = datetime.datetime(1980, 1, 1)
value_type = datetime.datetime
def __init__(self, data=[], name='DateTimeSeries'):
super(DateTimeSeries, self).__init__(data, name,
default=self.DEFAULT_VALUE)
return
def __getitem__(self, index):
try:
i = self.curbar - index
if i < 0 or index < 0:
return self._default
#return datetime.fromtimestamp(self.data[i%self._window_size]/1000)
return self.data[i]
except SeriesIndexError:
raise SeriesIndexError
def __str__(self):
return str(self.data[self.curbar])
def __eq__(self, r):
if isinstance(r, DateTimeSeries):
return self[0] == r[0]
return self[0] == r
def __lt__(self, r):
if isinstance(r, DateTimeSeries):
return self[0] < r[0]
return self[0] < r
def __le__(self, r):
if isinstance(r, DateTimeSeries):
return self[0] <= r[0]
return self[0] <= r
def __ne__(self, r):
if isinstance(r, DateTimeSeries):
return self[0] != r[0]
return self[0] != r
def __gt__(self, r):
if isinstance(r, DateTimeSeries):
return self[0] > r[0]
return self[0] > r
def __ge__(self, r):
if isinstance(r, DateTimeSeries):
return self[0] >= r[0]
return self[0] >= r