doctorAI.py 文件源码

def padMatrixWithTime(seqs, labels, times, options):
    lengths = np.array([len(seq) for seq in seqs]) - 1
    n_samples = len(seqs)
    maxlen = np.max(lengths)
    inputDimSize = options['inputDimSize']
    numClass = options['numClass']

    x = np.zeros((maxlen, n_samples, inputDimSize)).astype(config.floatX)
    y = np.zeros((maxlen, n_samples, numClass)).astype(config.floatX)
    t = np.zeros((maxlen, n_samples)).astype(config.floatX)
    mask = np.zeros((maxlen, n_samples)).astype(config.floatX)
    for idx, (seq,time,label) in enumerate(zip(seqs,times,labels)):
        for xvec, subseq in zip(x[:,idx,:], seq[:-1]):
            xvec[subseq] = 1.
        for yvec, subseq in zip(y[:,idx,:], label[1:]):
            yvec[subseq] = 1.
        mask[:lengths[idx], idx] = 1.
        t[:lengths[idx], idx] = time[:-1]

    lengths = np.array(lengths, dtype=config.floatX)
    if options['useLogTime']:
        t = np.log(t + options['logEps'])

    return x, y, t, mask, lengths