gsdmm-print-topics.py

# print number of documents per topic
doc_count = np.array(gsdmm.cluster_doc_count)
print('Number of documents per topic :', doc_count)

# Topics sorted by the number of document they are allocated to
top_index = doc_count.argsort()[-15:][::-1]
print('Most important clusters (by number of docs inside):', top_index)

# define function to get top words per topic
def top_words(cluster_word_distribution, top_cluster, values):
    for cluster in top_cluster:
        sort_dicts = sorted(cluster_word_distribution[cluster].items(), key=lambda k: k[1], reverse=True)[:values]
        print("\nCluster %s : %s"%(cluster, sort_dicts))

# get top words in topics
top_words(gsdmm.cluster_word_distribution, top_index, 20)