数据过滤器 – backtrader中文教程

...
61,2006-01-02-volume-min-001,61,2006-01-02 10:30:00,3613.0,3614.0,3613.0,3614.0,112.0,0.0,Strategy,61
62,2006-01-02-volume-min-001,62,2006-01-02 10:31:00,3614.0,3614.0,3614.0,3614.0,183.0,0.0,Strategy,62
63,2006-01-02-volume-min-001,63,2006-01-02 10:34:00,3614.0,3614.0,3614.0,3614.0,841.0,0.0,Strategy,63
64,2006-01-02-volume-min-001,64,2006-01-02 10:35:00,3614.0,3614.0,3614.0,3614.0,17.0,0.0,Strategy,64
...

缺少 10:32 和 10:33 分钟的数据。作为今年的第一个交易日，可能根本没有谈判。或者数据馈送可能未能捕获该数据。

出于 Ticket #23 的目的，并能够将给定分钟的交易量与前一天的同一分钟进行比较，我们将填写缺失的数据。

已经backtrader有一个SessionFiller正如预期的那样填充缺失的数据。代码很长并且比过滤器更复杂（完整实现见最后），但让我们看看类/参数定义：

class SessionFiller(with_metaclass(metabase.MetaParams, object)):
    '''
    Bar Filler for a Data Source inside the declared session start/end times.

    The fill bars are constructed using the declared Data Source ``timeframe``
    and ``compression`` (used to calculate the intervening missing times)

    Params:

      - fill_price (def: None):

        If None is passed, the closing price of the previous bar will be
        used. To end up with a bar which for example takes time but it is not
        displayed in a plot ... use float('Nan')

      - fill_vol (def: float('NaN')):

        Value to use to fill the missing volume

      - fill_oi (def: float('NaN')):

        Value to use to fill the missing Open Interest

      - skip_first_fill (def: True):

        Upon seeing the 1st valid bar do not fill from the sessionstart up to
        that bar
    '''
    params = (('fill_price', None),
              ('fill_vol', float('NaN')),
              ('fill_oi', float('NaN')),
              ('skip_first_fill', True))

示例脚本现在可以过滤和填充数据：

./data-filler.py --writer --wrcsv --tstart 09:30 --tend 17:30 --filter --filler

...
62,2006-01-02-volume-min-001,62,2006-01-02 10:31:00,3614.0,3614.0,3614.0,3614.0,183.0,0.0,Strategy,62
63,2006-01-02-volume-min-001,63,2006-01-02 10:32:00,3614.0,3614.0,3614.0,3614.0,0.0,,Strategy,63
64,2006-01-02-volume-min-001,64,2006-01-02 10:33:00,3614.0,3614.0,3614.0,3614.0,0.0,,Strategy,64
65,2006-01-02-volume-min-001,65,2006-01-02 10:34:00,3614.0,3614.0,3614.0,3614.0,841.0,0.0,Strategy,65
...

分钟 10:32 和 10:33 在那里。该脚本使用最后一个已知的“收盘价”来填充价格值并将交易量和未平仓量字段设置为 0。该脚本接受一个--fvol参数以将交易量设置为任何值（包括“NaN”）

完成票 #23

有了SessionFilter和SessionFiller以下已经完成：

• 未交付前/后市场数据
• 没有数据（在给定的时间范围内）丢失

RelativeVolume现在不再需要在 Ticket 23 中讨论的“同步”来实现 指标，因为所有日子都有完全相同的柱数（在示例中，从 09:30 到 17:30 的所有分钟都包括在内）

请记住，默认设置是将缺失的交易量设置为0一个简单的 RelativeVolume指标，可以开发：

class RelativeVolume(bt.Indicator):
    csv = True  # show up in csv output (default for indicators is False)

    lines = ('relvol',)
    params = (
        ('period', 20),
        ('volisnan', True),
    )

    def __init__(self):
        if self.p.volisnan:
            # if missing volume will be NaN, do a simple division
            # the end result for missing volumes will also be NaN
            relvol = self.data.volume(-self.p.period) / self.data.volume
        else:
            # Else do a controlled Div with a built-in function
            relvol = bt.DivByZero(
                self.data.volume(-self.p.period),
                self.data.volume,
                zero=0.0)

        self.lines.relvol = relvol

这很聪明，可以通过使用内置辅助来避免被零除 backtrader。

在脚本的下一次调用中将所有部分放在一起：

./data-filler.py --writer --wrcsv --tstart 09:30 --tend 17:30 --filter --filler --relvol

===============================================================================
Id,2006-01-02-volume-min-001,len,datetime,open,high,low,close,volume,openinterest,Strategy,len,RelativeVolume,len,relvol
1,2006-01-02-volume-min-001,1,2006-01-02 09:30:00,3604.0,3605.0,3603.0,3604.0,546.0,0.0,Strategy,1,RelativeVolume,1,
2,2006-01-02-volume-min-001,2,2006-01-02 09:31:00,3604.0,3606.0,3604.0,3606.0,438.0,0.0,Strategy,2,RelativeVolume,2,
...

RelativeVolume正如预期的那样，该指标在第 1^根柱线期间没有产生任何输出 。周期在脚本中计算为：(17:30 – 09:30 * 60) + 1。让我们直接看一下第二天 10:32 和 10:33 的相对交易量如何，假设 1 ^st天，体积值被填充0：

...
543,2006-01-02-volume-min-001,543,2006-01-03 10:31:00,3648.0,3648.0,3647.0,3648.0,56.0,0.0,Strategy,543,RelativeVolume,543,3.26785714286
544,2006-01-02-volume-min-001,544,2006-01-03 10:32:00,3647.0,3648.0,3647.0,3647.0,313.0,0.0,Strategy,544,RelativeVolume,544,0.0
545,2006-01-02-volume-min-001,545,2006-01-03 10:33:00,3647.0,3647.0,3647.0,3647.0,135.0,0.0,Strategy,545,RelativeVolume,545,0.0
546,2006-01-02-volume-min-001,546,2006-01-03 10:34:00,3648.0,3648.0,3647.0,3648.0,171.0,0.0,Strategy,546,RelativeVolume,546,4.91812865497
...

两者都按预期设置0。

结论

数据源中的filter机制开启了完全操纵数据流的可能性。谨慎使用。

脚本代码和用法

可作为以下来源的样本backtrader：

usage: data-filler.py [-h] [--data DATA] [--filter] [--filler] [--fvol FVOL]
                      [--tstart TSTART] [--tend TEND] [--relvol]
                      [--fromdate FROMDATE] [--todate TODATE] [--writer]
                      [--wrcsv] [--plot] [--numfigs NUMFIGS]

DataFilter/DataFiller Sample

optional arguments:
  -h, --help            show this help message and exit
  --data DATA, -d DATA  data to add to the system
  --filter, -ft         Filter using session start/end times
  --filler, -fl         Fill missing bars inside start/end times
  --fvol FVOL           Use as fill volume for missing bar (def: 0.0)
  --tstart TSTART, -ts TSTART
                        Start time for the Session Filter (HH:MM)
  --tend TEND, -te TEND
                        End time for the Session Filter (HH:MM)
  --relvol, -rv         Add relative volume indicator
  --fromdate FROMDATE, -f FROMDATE
                        Starting date in YYYY-MM-DD format
  --todate TODATE, -t TODATE
                        Starting date in YYYY-MM-DD format
  --writer, -w          Add a writer to cerebro
  --wrcsv, -wc          Enable CSV Output in the writer
  --plot, -p            Plot the read data
  --numfigs NUMFIGS, -n NUMFIGS
                        Plot using numfigs figures

源码：

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

import argparse
import datetime
import math

# The above could be sent to an independent module
import backtrader as bt
import backtrader.feeds as btfeeds
import backtrader.utils.flushfile
import backtrader.filters as btfilters

from relativevolume import RelativeVolume


def runstrategy():
    args = parse_args()

    # Create a cerebro
    cerebro = bt.Cerebro()

    # Get the dates from the args
    fromdate = datetime.datetime.strptime(args.fromdate, '%Y-%m-%d')
    todate = datetime.datetime.strptime(args.todate, '%Y-%m-%d')

    # Get the session times to pass them to the indicator
    # datetime.time has no strptime ...
    dtstart = datetime.datetime.strptime(args.tstart, '%H:%M')
    dtend = datetime.datetime.strptime(args.tend, '%H:%M')

    # Create the 1st data
    data = btfeeds.BacktraderCSVData(
        dataname=args.data,
        fromdate=fromdate,
        todate=todate,
        timeframe=bt.TimeFrame.Minutes,
        compression=1,
        sessionstart=dtstart,  # internally just the "time" part will be used
        sessionend=dtend,  # internally just the "time" part will be used
    )

    if args.filter:
        data.addfilter(btfilters.SessionFilter)

    if args.filler:
        data.addfilter(btfilters.SessionFiller, fill_vol=args.fvol)

    # Add the data to cerebro
    cerebro.adddata(data)

    if args.relvol:
        # Calculate backward period - tend tstart are in same day
        # + 1 to include last moment of the interval dstart <-> dtend
        td = ((dtend - dtstart).seconds // 60) + 1
        cerebro.addindicator(RelativeVolume,
                             period=td,
                             volisnan=math.isnan(args.fvol))

    # Add an empty strategy
    cerebro.addstrategy(bt.Strategy)

    # Add a writer with CSV
    if args.writer:
        cerebro.addwriter(bt.WriterFile, csv=args.wrcsv)

    # And run it - no trading - disable stdstats
    cerebro.run(stdstats=False)

    # Plot if requested
    if args.plot:
        cerebro.plot(numfigs=args.numfigs, volume=True)


def parse_args():
    parser = argparse.ArgumentParser(
        description='DataFilter/DataFiller Sample')

    parser.add_argument('--data', '-d',
                        default='../../datas/2006-01-02-volume-min-001.txt',
                        help='data to add to the system')

    parser.add_argument('--filter', '-ft', action='store_true',
                        help='Filter using session start/end times')

    parser.add_argument('--filler', '-fl', action='store_true',
                        help='Fill missing bars inside start/end times')

    parser.add_argument('--fvol', required=False, default=0.0,
                        type=float,
                        help='Use as fill volume for missing bar (def: 0.0)')

    parser.add_argument('--tstart', '-ts',
                        # default='09:14:59',
                        # help='Start time for the Session Filter (%H:%M:%S)')
                        default='09:15',
                        help='Start time for the Session Filter (HH:MM)')

    parser.add_argument('--tend', '-te',
                        # default='17:15:59',
                        # help='End time for the Session Filter (%H:%M:%S)')
                        default='17:15',
                        help='End time for the Session Filter (HH:MM)')

    parser.add_argument('--relvol', '-rv', action='store_true',
                        help='Add relative volume indicator')

    parser.add_argument('--fromdate', '-f',
                        default='2006-01-01',
                        help='Starting date in YYYY-MM-DD format')

    parser.add_argument('--todate', '-t',
                        default='2006-12-31',
                        help='Starting date in YYYY-MM-DD format')

    parser.add_argument('--writer', '-w', action='store_true',
                        help='Add a writer to cerebro')

    parser.add_argument('--wrcsv', '-wc', action='store_true',
                        help='Enable CSV Output in the writer')

    parser.add_argument('--plot', '-p', action='store_true',
                        help='Plot the read data')

    parser.add_argument('--numfigs', '-n', default=1,
                        help='Plot using numfigs figures')

    return parser.parse_args()


if __name__ == '__main__':
    runstrategy()