ProductQuant.py 文件源码

def PQEval(data,lenSubVec,numSubCenter,centersPQ):
    (dataSize, dataDim)=data.shape
    if 0!=dataDim%lenSubVec:
        print "Cannot partition the feature space with the given segment number"
        return
    numSubVec=dataDim/lenSubVec
    codePQ=-npy.ones((dataSize, numSubVec),dtype=npy.int32)
    objKmeans=KMeans(numSubCenter)
    if (centersPQ.shape[0]!=numSubVec*numSubCenter 
        or centersPQ.shape[1]!=lenSubVec):
        print "PQ model dimension is not compatible with input data"
        return
    for ii in range(numSubVec):
        objKmeans.cluster_centers_=centersPQ[ii*numSubCenter:(ii+1)*numSubCenter,:]
        codePQ[:,ii]=objKmeans.predict(data[:,ii*lenSubVec:(ii+1)*lenSubVec])
    return codePQ