utils.py 文件源码

def build_data_auto_encoder(data, step, win_size):
    count = data.shape[1] / float(step)
    docX = np.zeros((count, 3, win_size))

    for i in range(0, data.shape[1] - win_size, step):
        c = i / step
        docX[c][0] = np.abs(data[0, i:i + win_size] - data[1, i:i + win_size])
        docX[c][1] = np.power(data[0, i:i + win_size] - data[1, i:i + win_size], 2)
        docX[c][2] = np.pad(
            (data[0, i:i + win_size - 1] - data[0, i + 1:i + win_size]) * (data[1, i:i + win_size - 1] - data[1, i + 1:i + win_size]),
            (0, 1), 'constant', constant_values=0)
    data = np.dstack((docX[:, 0], docX[:, 1], docX[:, 2])).reshape(docX.shape[0], docX.shape[1]*docX.shape[2])

    return data