from matplotlib import pyplot as plt
from sklearn.manifold import TSNE

def tsne_plot():
    "Creates and TSNE model and plots it"
    labels = []
    tokens = []

    for word in selected_words:
        if word in word2index.keys():
            tokens.append(word2vec(word))
            labels.append(word)

    tsne_model = TSNE(perplexity=40, n_components=2, init='pca', n_iter=2500, random_state=23)
    new_values = tsne_model.fit_transform(tokens)

    x = []
    y = []
    for value in new_values:
        x.append(value[0])
        y.append(value[1])

    plt.figure(figsize=(16, 16))
    for i in range(len(x)):
        plt.scatter(x[i],y[i])
        plt.annotate(labels[i],
                     xy=(x[i], y[i]),
                     xytext=(5, 2),
                     textcoords='offset points',
                     ha='right',
                     va='bottom')
    plt.show()