Backtrader量化平台教程（八) TimeFrame

有时候我们原有的数据和我们想要的数据不是同一个时间框架下的。譬如，我们手上只有分钟级别的数据，而我们想要的是日线级别的数据，或者说手上是日线级别的数据，希望变成周线级别的数据。在backtrader中，有很好的的方法解决这样的问题。总而言之，就是timeframe转换的问题

1.resampling

这个方法，字面意思看起来是“采样”，准确的来说，是上采样，从小的时间点变成大的时间点。

方法很简单，就是在添加数据的时候，不在使用 cerebro.adddata(data)，而是使用cerebro.resampledata(data, **kwargs)。

后面的参数主要有两个，一个是timeframe，也就是你希望变成的timeframe是多少，day还是week；另外一个是compression，就是对bar进行压缩。

2.代码

所有的代码是这样的:

from __future__ import (absolute_import, division, print_function,
unicode_literals)

import datetime  # For datetime objects
import backtrader as bt
import backtrader.feeds as btfeeds
import backtrader.indicators as btind
import pandas as pd
import numpy as np

class MyStrategy(bt.Strategy):
params = (
('ssa_window', 15),
('maperiod', 15),
)

def log(self, txt, dt=None):
''' Logging function fot this strategy'''
dt = dt or self.datas[0].datetime.date(0)
print('%s, %s' % (dt.isoformat(), txt))

def __init__(self):
# Keep a reference to the "close" line in the data[0] dataseries
self.dataclose = self.datas[0].close

# To keep track of pending orders and buy price/commission
self.order = None
self.buyprice = None
self.buycomm = None

self.sma = bt.indicators.SimpleMovingAverage(
self.datas[0], period=self.params.maperiod)

def start(self):
print("the world call me!")

def prenext(self):
print("not mature")

def notify_order(self, order):
if order.status in [order.Submitted, order.Accepted]:
# Buy/Sell order submitted/accepted to/by broker - Nothing to do
return

# Check if an order has been completed
# Attention: broker could reject order if not enougth cash
if order.status in [order.Completed]:
if order.isbuy():
self.log(
'BUY EXECUTED, Price: %.2f, Cost: %.2f, Comm %.2f' %
(order.executed.price,
order.executed.value,
order.executed.comm))

self.buyprice = order.executed.price
self.buycomm = order.executed.comm
else:  # Sell
self.log('SELL EXECUTED, Price: %.2f, Cost: %.2f, Comm %.2f' %
(order.executed.price,
order.executed.value,
order.executed.comm))

self.bar_executed = len(self)

elif order.status in [order.Canceled, order.Margin, order.Rejected]:
self.log('Order Canceled/Margin/Rejected')

self.order = None

def notify_trade(self, trade):
if not trade.isclosed:
return

self.log('OPERATION PROFIT, GROSS %.2f, NET %.2f' %
(trade.pnl, trade.pnlcomm))

def next(self):
# Simply log the closing price of the series from the reference
self.log('Close, %.2f' % self.dataclose[0])

# Check if an order is pending ... if yes, we cannot send a 2nd one
if self.order:
return

# Check if we are in the market
if not self.position:

# Not yet ... we MIGHT BUY if ...
if self.dataclose[0] > self.sma[0]:

# BUY, BUY, BUY!!! (with all possible default parameters)
self.log('BUY CREATE, %.2f' % self.dataclose[0])

# Keep track of the created order to avoid a 2nd order
self.order = self.buy()

else:

if self.dataclose[0] < self.sma[0]:
# SELL, SELL, SELL!!! (with all possible default parameters)
self.log('SELL CREATE, %.2f' % self.dataclose[0])

# Keep track of the created order to avoid a 2nd order
self.order = self.sell()
def stop(self):
print("death")

if __name__ == '__main__':

# Create a cerebro entity
cerebro = bt.Cerebro(stdstats=False)

# Add a strategy
cerebro.addstrategy(MyStrategy)

dataframe = pd.read_csv('RB.SHF.csv', index_col=0, parse_dates=True)
data0 = bt.feeds.PandasData(dataname=dataframe,
fromdate=datetime.datetime(2014, 5, 13),
todate=datetime.datetime(2014, 6, 20),
timeframe=bt.TimeFrame.Minutes
)
# Add the Data Feed to Cerebro
cerebro.adddata(data0)

data2 = cerebro.resampledata(data0, timeframe=bt.TimeFrame.Days)
cerebro.run()
cerebro.plot(style='bar')

老样子，我们来看一下比较核心的代码。

读取数据，数据为分钟级别的数据，如下：

2014-05-13 08:59:00.005004,3198.0,3198.0,3198.0,3198.0,2148.0,0
2014-05-13 09:00:00.005000,3198.0,3202.0,3195.0,3195.0,37426.0,0
2014-05-13 09:01:00.004997,3195.0,3199.0,3194.0,3198.0,19704.0,0
2014-05-13 09:02:00.005003,3198.0,3199.0,3193.0,3193.0,22682.0,0
2014-05-13 09:03:00.005000,3193.0,3195.0,3192.0,3193.0,23064.0,0
2014-05-13 09:04:00.004996,3193.0,3194.0,3190.0,3190.0,29058.0,0
2014-05-13 09:05:00.005002,3191.0,3191.0,3186.0,3188.0,25044.0,0
2014-05-13 09:06:00.004999,3188.0,3189.0,3186.0,3189.0,16020.0,0
2014-05-13 09:07:00.004995,3189.0,3189.0,3187.0,3188.0,12336.0,0
2014-05-13 09:08:00.005002,3188.0,3188.0,3185.0,3186.0,20484.0,0
2014-05-13 09:09:00.004998,3186.0,3187.0,3184.0,3186.0,19234.0,0



dataframe = pd.read_csv('RB.SHF.csv', index_col=0, parse_dates=True)
data0 = bt.feeds.PandasData(dataname=dataframe,
fromdate=datetime.datetime(2014, 5, 13),
todate=datetime.datetime(2014, 6, 20),
timeframe=bt.TimeFrame.Minutes
)
#timeframe=bt.TimeFrame.Minutes用来指明datafeed的timeframe，默认是days

# Add the Data Feed to Cerebro，就像平常一样
cerebro.adddata(data0)

data2 = cerebro.resampledata(data0, timeframe=bt.TimeFrame.Days)#加入另外一个新的timeframe的datafeed的时候，就不能是adddata了，而是之前说的resampling
cerebro.run()
cerebro.plot(style='bar')
最后，画出来的plot是这样的：