from sklearn.cluster import KMeans
import numpy as np
from sklearn.feature_extraction.text import TfidfVectorizer
import matplotlib.pyplot as plt




with open("test-A/in.tsv") as file:
    corpus = file.readlines()
    vectorizer = TfidfVectorizer(ngram_range=(1,2), use_idf = True)
    vectors = vectorizer.fit_transform(corpus)

    kmeans = KMeans(n_clusters=255, random_state = 0).fit(vectors)
    prediction = kmeans.fit_predict(vectors)
    labels = kmeans.labels_
    labels = np.array2string(labels, precision=2, separator='\n', suppress_small=True)

    file = open("test-A/out.tsv", "w")
    file.write(labels[1:-1])