def __init__(self, barDataSeries, period, dSMAPeriod=3, useAdjustedValues=False, maxLen=None):
assert dSMAPeriod > 1, "dSMAPeriod must be > 1"
assert isinstance(barDataSeries, bards.BarDataSeries), \
"barDataSeries must be a dataseries.bards.BarDataSeries instance"
super(StochasticOscillator, self).__init__(barDataSeries, SOEventWindow(period, useAdjustedValues), maxLen)
self.__d = ma.SMA(self, dSMAPeriod, maxLen)
def __init__(self, dataSeries, period, numStdDev, maxLen=None):
self.__sma = ma.SMA(dataSeries, period, maxLen=maxLen)
self.__stdDev = stats.StdDev(dataSeries, period, maxLen=maxLen)
self.__upperBand = dataseries.SequenceDataSeries(maxLen)
self.__lowerBand = dataseries.SequenceDataSeries(maxLen)
self.__numStdDev = numStdDev
# It is important to subscribe after sma and stddev since we'll use those values.
dataSeries.getNewValueEvent().subscribe(self.__onNewValue)
from dmwTrader import dataseries
close = numpy.random.random(100)
print(close)
print()
# talib
start1 = time.time()
output1 = talib.SMA(close, 30)
end1 = time.time()
# print(output1)
# dmwTrader
start2 = time.time()
seqDS = dataseries.SequenceDataSeries()
output2 = ma.SMA(seqDS, 30)
for ele in close:
seqDS.append(ele)
# print(output2[-1])
end2 = time.time()
# 检查是否一致
# for i in range(100):
# if numpy.isnan(output1[i]) and output2[i] is None:
# print('neither')
# elif not numpy.isnan(output1[i]) and output2[i] is not None:
# print(round(output1[i] - output2[i], 10))
# else:
# print("error")
print("talib time: " + str(end1 - start1))
def __init__(self, feed, instrument, smaPeriod):
super(MyStrategy, self).__init__(feed)
self.__position = None
self.__instrument = instrument
# 将sma与bar的收盘价绑定，拿收盘价作sma
self.__sma = ma.SMA(feed[instrument].getPriceDataSeries(), smaPeriod)
def __init__(self, feed, instrument):
super(myStrategy, self).__init__(feed, 100000)
self.__position = None
self.__instrument = instrument
self.__sma5 = ma.SMA(feed[instrument].getPriceDataSeries(), 5)
self.__sma30 = ma.SMA(feed[instrument].getPriceDataSeries(), 30)