LibLocalStep.py 文件源码

def calcDocTopicCount_numpy(
        activeDocs, docIndices, word_count,
        Prior, Lik,
        sumR=None, DocTopicCount=None):
    if sumR is None:
        sumR = np.zeros(N)
    if DocTopicCount is None:
        DocTopicCount = np.zeros((D, K), order='C')
    if np.isfortran(DocTopicCount):
        print 'here!!!!'
        DocTopicCount = np.ascontiguousarray(DocTopicCount)

    for d in activeDocs:
        start = docIndices[d]
        stop = docIndices[d + 1]
        Lik_d = Lik[start:stop]

        np.dot(Lik_d, Prior[d], out=sumR[start:stop])

        np.dot(word_count[start:stop] / sumR[start:stop],
               Lik_d,
               out=DocTopicCount[d, :]
               )

    DocTopicCount[activeDocs] *= Prior[activeDocs]
    return sumR, DocTopicCount