Hi,

when I am using SharpeRatio or PeriodStats analyzers with optimization, I get the following error

TypeError: __init__() missing 9 required positional arguments: 'status', 'dt', 'barlen', 'size', 'price', 'value', 'pnl', 'pnlcomm', and 'tz'

Both analyzers are based on TimeReturn which does not give any error if added as analyzer.

Any feedback would be really helpful.

Thanks

Hi,

I wonder why when runonce is False, then the data are not preloaded in optimization. I also wonder what happens when someone is using _nextforce = True instead. It seems to me that preloading will take place as the indicators that will call _disable_runonce are added afterwards.

Thanks

        iterstrats = itertools.product(*self.strats)
        if not self._dooptimize or self.p.maxcpus == 1:
            # If no optimmization is wished ... or 1 core is to be used
            # let's skip process "spawning"
            for iterstrat in iterstrats:
                runstrat = self.runstrategies(iterstrat)
                self.runstrats.append(runstrat)
                if self._dooptimize:
                    for cb in self.optcbs:
                        cb(runstrat)  # callback receives finished strategy
        else:
            if self.p.optdatas and self._dopreload and self._dorunonce:
                for data in self.datas:
                    data.reset()
                    if self._exactbars < 1:  # datas can be full length
                        data.extend(size=self.params.lookahead)
                    data._start()
                    if self._dopreload:
                        data.preload()

            pool = multiprocessing.Pool(self.p.maxcpus or None)
            for r in pool.imap(self, iterstrats):
                self.runstrats.append(r)
                for cb in self.optcbs:
                    cb(r)  # callback receives finished strategy

            pool.close()

You don't pass to the SimpleMovingAverage the ha_close line (self.hk.close) but rather a specific value of it (self.hk.close[0]).

If you look at the implementation of class HeikinAshi, it has line alias

    lines = ('ha_open', 'ha_high', 'ha_low', 'ha_close',)

    linealias = (
        ('ha_open', 'open',),
        ('ha_high', 'high',),
        ('ha_low', 'low',),
        ('ha_close', 'close',),
    )

The error has to do with division with zero, so I would suspect it has to do with the indicator. There is a parameter for RSI the safediv that you can set to True.

If you think that problem is with reading data, then I would suggest you check that bar(s) in next has the correct data

Hope this helps

Hi,

I am trying to change the rollover class to use it with input data feeds added in cerebro. I guess in this case next for the data feeds is also called by cerebro and thus no need to be called within rollover. I wonder how I can check for the end of the data feed without using the check for _next being False.

Many thanks

cerebro.setbroker(<instance of your broker class>)

Haven't tested it, but I think your csv file looks more like the following.

params = (
# ('nullvalue', float('NaN')),
('dtformat', '%Y-%m-%d %H:%M:%S'),
('datetime', 5),
('Open', 0),
('High', 1),
('Low', 2),
('Close', 3),
('Volume', 4),
)

Without having tested it, perhaps you can use in next of strategy B self.cerebro.runningstrats[self._id ^ 1] to get access to strategy A

I guess by filters you mean indicators and not data filters. This is an example having a list of indicators (in this case SimpleMovingAverage applied on close), one per data feed.

class TestStrategy(bt.Strategy):

    params = (
        ('maperiod', 15),
    )

    def __init__(self):
        self.smas = []
        for d in self.datas:
            self.smas.append(bt.indicators.SimpleMovingAverage(d.lines.close, period=self.params.maperiod))

I even like better the _nextforce = True pointed out to me by @backtrader some time ago.

class CustomIndicator(bt.Indicator):
    _nextforce = True
...