Еще примеры для профилировщика событий в pyalgotrade

Я пытаюсь научиться внедрять собственные стратегии в профилировщик событий для pyalgotrade. Это пример по умолчанию, который они дают.

from pyalgotrade           import eventprofiler
from pyalgotrade.technical import stats
from pyalgotrade.technical import roc
from pyalgotrade.technical import ma
from pyalgotrade.tools     import yahoofinance

#     Event inspired on an example from Ernie Chan's book:
#    'Algorithmic Trading: Winning Strategies and Their Rationale'

class BuyOnGap(eventprofiler.Predicate):
    def __init__(self, feed):
        stdDevPeriod = 90
        smaPeriod = 20
        self.__returns = {}
        self.__stdDev = {}
        self.__ma = {}
        for instrument in feed.getRegisteredInstruments():
            priceDS = feed[instrument].getAdjCloseDataSeries()
            #      Returns over the adjusted close values.
            self.__returns[instrument] = roc.RateOfChange(priceDS, 1)
            #      StdDev over those returns.
            self.__stdDev[instrument] = stats.StdDev(self.__returns[instrument], stdDevPeriod)
            #      MA over the adjusted close values.
            self.__ma[instrument] = ma.SMA(priceDS, smaPeriod)

    def __gappedDown(self, instrument, bards):
        ret = False
        if self.__stdDev[instrument][-1] != None:
            prevBar = bards[-2]
            currBar = bards[-1]
            low2OpenRet = (currBar.getAdjOpen() - prevBar.getAdjLow()) / float(prevBar.getAdjLow())
            if low2OpenRet < (self.__returns[instrument][-1] - self.__stdDev[instrument][-1]):
                ret = True
        return ret

    def __aboveSMA(self, instrument, bards):
        ret = False
        if self.__ma[instrument][-1] != None and bards[-1].getAdjOpen() > self.__ma[instrument][-1]:
            ret = True
        return ret

    def eventOccurred(self, instrument, bards):
        ret = False
        if self.__gappedDown(instrument, bards) and self.__aboveSMA(instrument, bards):
            ret = True
        return ret

def main(plot):
    instruments = ["AA", "AES", "AIG"]
    feed = yahoofinance.build_feed(instruments, 2008, 2009, ".")

    predicate = BuyOnGap(feed)
    eventProfiler = eventprofiler.Profiler(predicate, 5, 5)
    eventProfiler.run(feed, True)

    results = eventProfiler.getResults()
    print "%d events found" % (results.getEventCount())
    if plot:
        eventprofiler.plot(results)

if __name__ == "__main__":
    main(True)

Есть ли у кого-нибудь источник еще нескольких примеров?

Я пытаюсь выяснить, как eventprofiler получает и использует данные, хотя вызывается довольно много методов класса, и мне кажется, что это немного сложно анализировать.

Я хочу начать с простого и просто использовать price и volume. Одной из стратегий будет
if volume > 1000 and close < 50: event == True

Любая помощь будет оценена по достоинству.

P.s.: дополнительный вопрос: есть ли аналогичный профилировщик событий для zipline?

РЕДАКТИРОВАТЬ: благодаря user3666197 я смог внести изменения, которые хотел, однако я получаю эту ошибку:

Traceback (most recent call last):
  File "C:\Users\David\Desktop\Python\Coursera\Computational Finance\Week2\PyAlgoTrade\Bitfinex\FCT\FCT_single_event_test.py", line 43, in <module>
    main(True)
  File "C:\Users\David\Desktop\Python\Coursera\Computational Finance\Week2\PyAlgoTrade\Bitfinex\FCT\FCT_single_event_test.py", line 35, in main
    eventProfiler.run(feed, True)
  File "C:\Python27\lib\site-packages\pyalgotrade\eventprofiler.py", line 215, in run
    disp.run()
  File "C:\Python27\lib\site-packages\pyalgotrade\dispatcher.py", line 102, in run
    eof, eventsDispatched = self.__dispatch()
  File "C:\Python27\lib\site-packages\pyalgotrade\dispatcher.py", line 90, in __dispatch
    if self.__dispatchSubject(subject, smallestDateTime):
  File "C:\Python27\lib\site-packages\pyalgotrade\dispatcher.py", line 68, in __dispatchSubject
    ret = subject.dispatch() is True
  File "C:\Python27\lib\site-packages\pyalgotrade\feed\__init__.py", line 105, in dispatch
    self.__event.emit(dateTime, values)
  File "C:\Python27\lib\site-packages\pyalgotrade\observer.py", line 59, in emit
    handler(*args, **kwargs)
  File "C:\Python27\lib\site-packages\pyalgotrade\eventprofiler.py", line 172, in __onBars
    eventOccurred = self.__predicate.eventOccurred(instrument, self.__feed[instrument])
  File "C:\Python27\lib\site-packages\pyalgotrade\eventprofiler.py", line 89, in eventOccurred
    raise NotImplementedError()
NotImplementedError
[Finished in 1.9s]

Я просмотрел исходный файл «eventprofiler.py» и не могу понять, что это такое. Вот код

from pyalgotrade import eventprofiler
from pyalgotrade.technical import stats
from pyalgotrade.technical import roc
from pyalgotrade.technical import ma
from pyalgotrade.barfeed import csvfeed

# Event inspired on an example from Ernie Chan's book:
# 'Algorithmic Trading: Winning Strategies and Their Rationale'

class single_event_strat( eventprofiler.Predicate ):
    def __init__(self,feed):
        self.__returns = {} # CLASS ATTR
        for inst in feed.getRegisteredInstruments():

            priceDS = feed[inst].getAdjCloseDataSeries() # STORE: priceDS ( a temporary representation )

            self.__returns[inst] = roc.RateOfChange( priceDS, 1 )
            # CALC:  ATTR <- Returns over the adjusted close values, consumed priceDS 
            #( could be expressed as self.__returns[inst] = roc.RateOfChange( ( feed[inst].getAdjCloseDataSeries() ), 1 ), 
            #but would be less readable

    def eventOccoured( self, instrument, aBarDS):
        if (aBarDS[-1].getVolume() > 1000 and aBarDS[-1].getClose() > 50 ):
            return True
        else: 
            return False

def main(plot):
    feed = csvfeed.GenericBarFeed(0)

    feed.addBarsFromCSV('FCT', "FCT_daily_converted.csv")

    predicate = single_event_strat(feed)
    eventProfiler = eventprofiler.Profiler(predicate, 5, 5)
    eventProfiler.run(feed, True)

    results = eventProfiler.getResults()
    print "%d events found" % (results.getEventCount())
    if plot:
        eventprofiler.plot(results)

if __name__ == "__main__":
    main(True)