main_test.py 文件源码

def getAccRel(sim,dst):
    # for how many is the most similar one also the one with the smallest dst
    #  relaxed formulation: of the most similar ones (if more than one is equally similar) one is among those with smallest dst (if more than one is equally far away)
    maxSim = numpy.max(sim, axis=1)
    minDst = numpy.min(dst, axis=1)
    nSamp = sim.shape[0]
    nCorrect = 0.
    nCorrectClass = 0.
    for i in xrange(nSamp):
        maxSimIdx, = (sim[i,:] == maxSim[i]).nonzero()
        minDstIdx, = (dst[i,:] == minDst[i]).nonzero()
        if len(numpy.intersect1d(maxSimIdx,minDstIdx, assume_unique=True)) > 0:
            nCorrect += 1.

        if numpy.min(sim[i,minDstIdx]) > -2.:
            nCorrectClass += 1.

    acc = nCorrect / nSamp

    # classification accuracy. for how many percent is the closest from the correct class
    classAcc = nCorrectClass / nSamp

    return (acc,classAcc)