STConvolution.py 文件源码

def seqCNN_CPT(c_conf=(4, 3, 32, 32), p_conf=(4, 3, 32, 32), t_conf=(4, 3, 32, 32)):
    '''
    C - Temporal Closeness
    P - Period
    T - Trend
    conf = (nb_flow, seq_len, map_height, map_width)
    '''
    model = Sequential()
    components = []

    for conf in [c_conf, p_conf, t_conf]:
        if conf is not None:
            components.append(seqCNNBaseLayer1(conf))
            nb_flow = conf[0]
    model.add(Merge(components, mode='concat', concat_axis=1))  # concat
    model.add(Convolution2D(64, 3, 3, border_mode='same'))
    model.add(Activation('relu'))

    model.add(Convolution2D(64, 3, 3, border_mode='same'))
    model.add(Activation('relu'))

    model.add(Convolution2D(nb_flow, 3, 3, border_mode='same'))
    model.add(Activation('tanh'))
    return model