@vladisld: Thanks so much for your help! I spend few hours trying to find examples until you pointed me to that post.
So here is what seems to work but I have couple questions if you could confirm... See the questions in the code comments.
class PandasDataVW(PandasData):
"""Pandas feed with additional columns `vw` for volume weighted average."""
lines = ('vw',)
params = (('vw', -1),)
class _MyBar(bt.dataseries._Bar):
def bstart(self, maxdate=False):
super().bstart(maxdate)
self.vw = float('NaN')
self.vw_vol = 0
def bupdate(self, data, reopen=False):
return_value = super().bupdate(data, reopen)
self.vw_vol += data.vw[0] * data.volume[0]
self.vw = self.vw_vol / self.volume if self.volume else data.vw[0]
return return_value
class MyReplayer(bt.Replayer):
def __init__(self, data):
super().__init__(data)
self.bar = _MyBar(maxdate=True)
cerebro.addstrategy(TestStrat)
data0 = PandasDataVW(dataname=df, timeframe=bt.TimeFrame.Seconds, compression=5)
cerebro.adddata(data0, name='s5')
# For some reason cloning doesn't work here - DataClone doesn't have my `vw` line
# so I can recreate the feed. I assume I shouldn't add filter to the same feed directly
# because I'm already using it as is. Do I do something wrong with cloning?
# data1 = data0.clone()
data1 = PandasDataVW(dataname=df, timeframe=bt.TimeFrame.Seconds, compression=5)
data1.addfilter(MyReplayer,
timeframe=bt.TimeFrame.Minutes,
compression=1)
cerebro.adddata(data1, name='m1')
# `_doreply=True` I saw in cerebro.resampledata() along with cloning so I replicated it.
# Is this required?
cerebro._doreplay = True
cerebro.run(preload=False)
Hope this comes useful to others.
