Changeset - 1cae4ecc8978
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Laman - 3 years ago 2022-09-18 16:05:43

created a Sample object
1 file changed with 49 insertions and 7 deletions:
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languedoc.py
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import os
 
import re
 
import random
 

	
 
random.seed(19181028)
 

	
 

	
 
def preprocess(text):
 
	text = re.sub(r"[\W\d]+", " ", text)
 
	text = re.sub(r"[\W\d_]+", " ", " "+text+" ")
 
	return text.lower()
 

	
 

	
 
def extract_ngram_freqs(text, k):
 
	n = len(text)
 
	d = dict()
 

	
 
	for i in range(0, n-k):
 
		key = text[i:i+k]
 
		if key.isspace():
 
			continue
 

	
 
		d[key] = d.get(key, 0) + 1
 

	
 
	count = sum(d.values())
 

	
 
	return {key: val/count for (key, val) in d.items()}
 

	
 

	
 
def merge_ngram_freqs(freqs):
 
	n = len(freqs)
 
	res = dict()
 

	
 
	for d in freqs:
 
		for (key, val) in d.items():
 
			res.setdefault(key, 0)
 
			res[key] += val/n
 

	
 
	return res
 

	
 

	
 
class Sample:
 
	def __init__(self, language="??", text=""):
 
		self.language = language
 
		self.frequencies = [dict(), dict(), dict()]
 

	
 
		if text:
 
			self._extract(text)
 

	
 
	def _extract(self, text):
 
		for k in range(1, 4):
 
			self.frequencies[k-1] = extract_ngram_freqs(text, k)
 

	
 
	@staticmethod
 
	def merge(samples):
 
		assert len({x.language for x in samples}) == 1
 

	
 
		res = Sample(samples[0].language)
 
		res.frequencies = []
 

	
 
		for freqs in zip(*(x.frequencies for x in samples)):
 
			res.frequencies.append(merge_ngram_freqs(freqs))
 

	
 
		return res
 

	
 
	def compare(self, other):
 
		pass
 

	
 
	def print_overview(self):
 
		print(f"Sample({self.language}):")
 

	
 
		for freqs in self.frequencies:
 
			x = [
 
				(k, round(v, 3))
 
				for (k, v) in sorted(freqs.items(), key=lambda kv: -kv[1])
 
			]
 
			print("  ", x[:8], "...", x[-8:])
 

	
 
		print()
 

	
 

	
 
DATA_DIR = os.path.join(os.path.dirname(__file__), "data")
 
LANG_DIRS = [x.path for x in os.scandir(DATA_DIR)]
 

	
 
models = dict()
 

	
 
for d in LANG_DIRS:
 
	models = [[], [], []]
 
	lang = os.path.basename(d)
 
	samples = []
 

	
 
	for file in os.scandir(d):
 
		with open(file) as f:
 
			text = f.read()
 
			text = preprocess(text)
 
			print(f"{file.name} ({len(text)})")
 
			print(text[:256])
 
			print()
 

	
 
			for k in range(1, 4):
 
				models[k-1].append(extract_ngram_freqs(text, k))
 
			samples.append(Sample(lang, text))
 
			samples[-1].print_overview()
 

	
 
	models = [merge_ngram_freqs(sources) for sources in models]
 
	print(sorted(((key, round(val, 3)) for (key, val) in models[0].items()), key=lambda kv: -kv[1]))
 
	print(sorted(((key, round(val, 3)) for (key, val) in models[1].items()), key=lambda kv: -kv[1]))
 
	models[lang] = Sample.merge(samples)
 
	models[lang].print_overview()
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