93 lines
2.9 KiB
Python
93 lines
2.9 KiB
Python
"""TF-IDF 特征 + DBSCAN 聚类测试。"""
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import _bootstrap # noqa: F401
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import unittest
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from fault_log_analyzer.cluster import (
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Clusterer,
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cosine_distance,
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cosine_similarity,
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dbscan,
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tfidf_vectors,
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)
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class TestTfidf(unittest.TestCase):
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def test_empty(self):
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self.assertEqual(tfidf_vectors([]), [])
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def test_vectors_shape(self):
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vecs = tfidf_vectors(["no space left on device", "out of memory error"])
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self.assertEqual(len(vecs), 2)
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def test_identical_docs_similar(self):
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vecs = tfidf_vectors(["disk full", "disk full"])
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self.assertAlmostEqual(cosine_similarity(vecs[0], vecs[1]), 1.0)
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def test_distinct_docs_less_similar(self):
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vecs = tfidf_vectors(["disk full error", "memory exhausted"])
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self.assertLess(cosine_similarity(vecs[0], vecs[1]), 1.0)
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class TestCosine(unittest.TestCase):
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def test_similarity_zero_for_empty(self):
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self.assertEqual(cosine_similarity({}, {}), 0.0)
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def test_distance_identical_is_zero(self):
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self.assertAlmostEqual(cosine_distance({"a": 1.0}, {"a": 1.0}), 0.0)
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def test_distance_is_one_for_orthogonal(self):
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self.assertAlmostEqual(cosine_distance({"a": 1.0}, {"b": 1.0}), 1.0)
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class TestDbscan(unittest.TestCase):
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def test_empty(self):
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self.assertEqual(dbscan([], 0.75, 5), [])
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def test_single_sample_is_noise(self):
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self.assertEqual(dbscan([{"a": 1.0}], 0.75, 5), [-1])
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def test_two_identical_with_min2(self):
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labels = dbscan([{"a": 1.0}, {"a": 1.0}], 0.75, 2)
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self.assertEqual(labels, [0, 0])
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def test_two_distinct_with_min2_are_noise(self):
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labels = dbscan([{"a": 1.0}, {"b": 1.0}], 0.75, 2)
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self.assertEqual(labels, [-1, -1])
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class TestClusterer(unittest.TestCase):
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def test_fit_predict_small_returns_noise(self):
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c = Clusterer(eps=0.75, min_samples=5)
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self.assertEqual(c.fit_predict(["only one message"]), [-1])
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def test_assign_empty_centroids(self):
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self.assertEqual(Clusterer().assign("anything"), -1)
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def test_fit_predict_group(self):
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messages = [
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"no space left on device",
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"no space left on device /var",
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"no space left on device /tmp",
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"out of memory error",
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"out of memory killed process",
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]
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c = Clusterer(eps=0.75, min_samples=2)
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labels = c.fit_predict(messages)
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self.assertEqual(len(labels), 5)
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self.assertGreaterEqual(c.n_clusters, 1)
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def test_assign_to_nearest_cluster(self):
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messages = [
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"no space left on device",
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"no space left on device /var",
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"no space left on device /tmp",
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]
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c = Clusterer(eps=0.75, min_samples=2)
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c.fit_predict(messages)
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self.assertGreaterEqual(c.n_clusters, 1)
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self.assertGreaterEqual(c.assign("no space left on device /opt"), 0)
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if __name__ == "__main__":
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unittest.main()
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