Languedoc Changeset - 8e4769dd4ca6

Changeset - 8e4769dd4ca6

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Laman - 2 years ago 2022-10-20 23:16:46

tests for ngram extraction

2 files changed with 49 insertions and 6 deletions:

src/languedoc/predict.py

tests/test_predict.py

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src/languedoc/predict.py

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@@ @@ -14,7 +14,12 @@ def preprocess(text: str) -> str: @@
 	return text.lower()
 def extract_kgram_counts(text, k):
 def extract_kgram_counts(text: str, k: int) -> dict[str, int]:
 	"""Extract k-gram counts from the text for a provided k.
 	:param text: the source text
 	:param k: length of the kgrams to extract. 1 for letters, 2 for bigrams, ...
 	:return: a dict mapping kgrams to their counts in the text"""
 	n = len(text)
 	counts = dict()
@@ @@ -28,7 +33,11 @@ def extract_kgram_counts(text, k): @@
 	return counts
 def extract_ngram_counts(text):
 def extract_ngram_counts(text: str) -> dict[str, int]:
 	"""Extract counts of 1- to 3-grams from the text.
 	:param text: the source text
 	:return: a dict mapping ngrams to their counts in the text"""
 	counts = dict()
 	for k in range(1, 4):
@@ @@ -37,12 +46,20 @@ def extract_ngram_counts(text): @@
 	return counts
 def rank_ngram_counts(counts):
 def rank_ngram_counts(counts: dict[str, int]) -> dict[str, int]:
 	"""Order supplied ngrams by their counts (then length, then alphabetically) and return their ranking.
 	:param counts: a dict mapping ngrams to their counts
 	:return: a dict mapping ngrams to their rank (the most frequent: 0, the second: 1, ...)"""
 	ordered_ngrams = sorted(counts.items(), key=lambda kv: (-kv[1], len(kv[0]), kv[0]))[:TOP_NGRAM_COUNT]
-	return dict(zip([key for (key, freq) in ordered_ngrams], itertools.count(0)))
+	return dict(zip([key for (key, count) in ordered_ngrams], itertools.count(0)))
 def extract_ranked_ngrams(text):
 def extract_ranked_ngrams(text: str) -> dict[str, int]:
 	"""Extract ngrams from the text and rank them from the most common.
 	:param text: the source text
 	:return: a dict mapping ngrams to their ranks {most_common_ngram: 0, second: 1, ...}"""
 	counts = extract_ngram_counts(text)
 	return rank_ngram_counts(counts)

tests/test_predict.py

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 from unittest import TestCase
 from languedoc.predict import preprocess, rank_ngram_counts, Sample, identify
 from languedoc.predict import preprocess, extract_kgram_counts, extract_ngram_counts, rank_ngram_counts, \
 	extract_ranked_ngrams, Sample, identify
 class TestPredict(TestCase):
@@ @@ -10,11 +11,36 @@ class TestPredict(TestCase): @@
 		self.assertEqual(preprocess("1% "), " ")
 		self.assertEqual(preprocess("Глава ĚŠČŘŽ"), " глава ěščřž ")
 	def test_extract_kgram_counts(self):
 		text = "abbbabb"
 		self.assertEqual(extract_kgram_counts(text, 1), {"a": 2, "b": 5})
 		self.assertEqual(extract_kgram_counts(text, 2), {"ab": 2, "bb": 3, "ba": 1})
 	def test_extract_ngram_counts(self):
 		text = "aab"
 		self.assertEqual(extract_ngram_counts(text), {"a": 2, "b": 1, "aa": 1, "ab": 1, "aab": 1})
 		text = "abbbabb"
 		self.assertEqual(
 			extract_ngram_counts(text),
 			{"a": 2, "b": 5, "ab": 2, "bb": 3, "ba": 1, "abb": 2, "bbb": 1, "bba": 1, "bab": 1}
+		)
 	def test_rank_ngram_counts(self):
 		freqs = {"a": 3, "aa": 1, "b": 4, "bb": 1, "c": 1}
 		expected = {"b": 0, "a": 1, "c": 2, "aa": 3, "bb": 4}
 		self.assertEqual(rank_ngram_counts(freqs), expected)
 	def test_extract_ranked_ngrams(self):
 		text = "aab"
 		self.assertEqual(extract_ranked_ngrams(text), {"a": 0, "b": 1, "aa": 2, "ab": 3, "aab": 4})
 		text = "abbbabb"
 		self.assertEqual(
 			extract_ranked_ngrams(text),
 			{"b": 0, "bb": 1, "a": 2, "ab": 3, "abb": 4, "ba": 5, "bab": 6, "bba": 7, "bbb": 8}
+		)
 class TestSample(TestCase):
 	def test_extract(self):

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