#!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created in February 2023
@author: Thomas Bonald <thomas.bonald&telecom-paris.fr>
"""
import numpy as np
from scipy import sparse
from sknetwork.linalg import normalize
from sknetwork.utils import get_degrees
[docs]def get_tfidf(count_matrix: sparse.csr_matrix):
"""Get the tf-idf from a count matrix in sparse format.
Parameters
----------
count_matrix : sparse.csr_matrix
Count matrix, shape (n_documents, n_words).
Returns
-------
tf_idf : sparse.csr_matrix
tf-idf matrix, shape (n_documents, n_words).
References
----------
https://en.wikipedia.org/wiki/Tfidf
"""
n_documents, n_words = count_matrix.shape
tf = normalize(count_matrix)
freq = get_degrees(count_matrix > 0, transpose=True)
idf = np.zeros(n_words)
idf[freq > 0] = np.log(n_documents / freq[freq > 0])
tf_idf = tf.dot(sparse.diags(idf))
return tf_idf