visualize.py 文件源码

def word_cloud(word_embedding_matrix, vocab, s, save_file='scatter.png'):
    words = [(i, vocab[i]) for i in s]
    model = TSNE(n_components=2, random_state=0)
    #Note that the following line might use a good chunk of RAM
    tsne_embedding = model.fit_transform(word_embedding_matrix)
    words_vectors = tsne_embedding[np.array([item[1] for item in words])]

    plt.subplots_adjust(bottom = 0.1)
    plt.scatter(
        words_vectors[:, 0], words_vectors[:, 1], marker='o', cmap=plt.get_cmap('Spectral'))

    for label, x, y in zip(s, words_vectors[:, 0], words_vectors[:, 1]):
        plt.annotate(
            label,
            xy=(x, y), xytext=(-20, 20),
            textcoords='offset points', ha='right', va='bottom',
            fontsize=20,
            # bbox=dict(boxstyle='round,pad=1.', fc='yellow', alpha=0.5),
            arrowprops=dict(arrowstyle = '<-', connectionstyle='arc3,rad=0')
            )
    plt.show()
    # plt.savefig(save_file)