"""Тесты TF-IDF и LSA."""

from __future__ import annotations

import numpy as np

from stylometry.datasets import load_feature_frame
from stylometry.lsa import (
    make_char_ngram_vectorizer,
    make_lsa_vectorizer,
    make_pos_ngram_vectorizer,
    make_text_vectorizer,
)


def test_lsa_word_shape_and_variance() -> None:
    frame = load_feature_frame(verbose=False).head(100)
    vectorizer = make_lsa_vectorizer("word", n_components=10)
    matrix = vectorizer.fit_transform(frame)
    assert matrix.shape == (100, 10)
    assert np.isfinite(matrix).all()
    assert 0 <= vectorizer.cumulative_explained_variance_[-1] <= 1.0
    assert len(vectorizer.top_terms(5)) == 10


def test_lsa_pos_and_char() -> None:
    frame = load_feature_frame(verbose=False).head(100)
    for variant in ("pos", "char"):
        vectorizer = make_lsa_vectorizer(variant, n_components=5)
        matrix = vectorizer.fit_transform(frame)
        assert matrix.shape[0] == 100
        assert matrix.shape[1] == 5
        assert np.isfinite(matrix).all()


def test_text_vectorizers() -> None:
    frame = load_feature_frame(verbose=False).head(50)
    for vectorizer in (
        make_text_vectorizer("word"),
        make_pos_ngram_vectorizer(),
        make_char_ngram_vectorizer(),
    ):
        matrix = vectorizer.fit_transform(frame)
        assert matrix.shape[0] == 50
        assert matrix.shape[1] > 0