def test_wordnet(self):
self.assertIsInstance(wordnet.langs(), list)
self.assertIn("tha", wordnet.langs())
self.assertEqual(
wordnet.synset("spy.n.01").lemma_names("tha"), ["สปาย", "สายลับ"])
self.assertIsNotNone(wordnet.synsets("นก"))
self.assertIsNotNone(wordnet.all_synsets(pos=wn.ADJ))
self.assertIsNotNone(wordnet.lemmas("นก"))
self.assertIsNotNone(wordnet.all_lemma_names(pos=wn.ADV))
self.assertIsNotNone(wordnet.lemma("cat.n.01.cat"))
self.assertEqual(wordnet.morphy("dogs"), "dog")
bird = wordnet.synset("bird.n.01")
mouse = wordnet.synset("mouse.n.01")
self.assertEqual(wordnet.path_similarity(bird, mouse),
bird.path_similarity(mouse))
self.assertEqual(wordnet.wup_similarity(bird, mouse),
bird.wup_similarity(mouse))
self.assertEqual(wordnet.lch_similarity(bird, mouse),
bird.lch_similarity(mouse))
cat_key = wordnet.synsets("แมว")[0].lemmas()[0].key()
self.assertIsNotNone(wordnet.lemma_from_key(cat_key))
def test_wordnet(self):
self.assertIsNotNone(wordnet.langs())
self.assertEqual(
wordnet.synset("spy.n.01").lemma_names("tha"), ["สปาย", "สายลับ"]
)
self.assertIsNotNone(wordnet.synsets("นก"))
self.assertIsNotNone(wordnet.all_synsets(pos=wn.ADJ))
self.assertIsNotNone(wordnet.lemmas("นก"))
self.assertIsNotNone(wordnet.all_lemma_names(pos=wn.ADV))
self.assertIsNotNone(wordnet.lemma("cat.n.01.cat"))
self.assertEqual(wordnet.morphy("dogs"), "dog")
bird = wordnet.synset("bird.n.01")
mouse = wordnet.synset("mouse.n.01")
self.assertEqual(
wordnet.path_similarity(bird, mouse), bird.path_similarity(mouse)
)
self.assertEqual(
wordnet.wup_similarity(bird, mouse), bird.wup_similarity(mouse)
)
cat_key = wordnet.synsets("แมว")[0].lemmas()[0].key()
self.assertIsNotNone(wordnet.lemma_from_key(cat_key))
def find_synonyms(path_folder, namefile):
word = rw.get_data(f'./{path_folder}/{namefile}.csv')
max = len(word)
bar = IncrementalBar(f'Progress',
max=max,
suffix='%(percent)d%% %(elapsed_td)s')
for row in word:
trans_word = transform(row["word"])
try:
find_synonyms = lemmas(trans_word)
row.update({"synonyms": find_synonyms})
except:
pass
bar.next()
bar.finish()
fieldnames = [
'word', 'synonyms', 'tf-idf-pos', 'tf-idf-neg', 'tf-idf-val',
'node-label'
]
rw.write_data_by_columns(f"./synonyms/pythai/{path_folder}/{namefile}.csv",
fieldnames, word)