utils.py 文件源码

def normalize(timeSeries,nfFactor) :

    if isinstance(timeSeries[0],(int,float)) == True :
        nFeatures = 1
    else :
        nFeatures = len(timeSeries[0])

    assert len(nfFactor) == nFeatures
    nSamples = len(timeSeries)
    normalizedTimeSeries = []

    for i in xrange(0,nFeatures) :
        if nfFactor[i] == 0.0 :
            nfFactor[i] = 1.0

    for i in xrange(0,nSamples):
        if isinstance(timeSeries[0],(int,float)) == True :
            normalizedTimeSeries.append(float(timeSeries[i])/float(nfFactor[0]))
        else :
            normalizedTimeSeries.append(map(truediv,timeSeries[i],nfFactor))


    return np.array(normalizedTimeSeries)