analogy_glove.py

# function to compute and display analogies between a group of word-pairs.
def plot_analogy(word_groups, model, func, colors, title, ax=None):
    if ax==None:
        fig, ax = plt.subplots(1,1,figsize=(5,5))
    for i, words in enumerate(word_groups):
        analogical_word = model.most_similar(positive=[words[0], words[1]], 
                                             negative=[words[2]], 
                                             topn=1)[0][0]
        words.append(analogical_word)
        word_vectors = np.array([model[w] for w in words])
        twodim = func.fit_transform(word_vectors)[:,:2]
        ax.scatter(twodim[:,0], twodim[:,1], edgecolors='k', c=colors[i])
        for word, (x,y) in zip(words, twodim):
            ax.text(x+0.05, y+0.05, word);
    ax.set_title(title)


word_groups = [['russia', 'paris', 'france'],
               ['woman', 'king', 'man'],
               ['dog', 'kitten', 'cat'],
               ['chef', 'stone', 'sculptor'],
               ['bees', 'den', 'bears']
               ]

colors = ['r', 'b', 'y', 'm', 'c']

plot_analogy(word_groups, model, PCA(), colors, 'PCA - 100d embeddings')