def lSigmoidSampler(sum_g_diffential, samplePairs):

    candPool = []
    mean_g_differential = sum_g_diffential / len(samplePairs)

    for hypPairItem in samplePairs:
        samp_prob = 1.0 / (1 + math.exp( mean_g_differential - hypPairItem[0] ))
        if getBinomial(1, samp_prob) == 1:
            candPool.append( hypPairItem[:] )

    return candPool
Implements the logistic sigmoid sampler
dataset/ETHPy150Open sfu-natlang/Kriya/src/Kriya-Decoder/mert-scripts/PRO.py/lSigmoidSampler