import os import re import random import itertools random.seed(19181028) def preprocess(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+1): 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): """take k most common use frequencies x order use letter, digrams, trigrams use absolute x square""" ordered_own_trigrams = sorted(self.frequencies[2].items(), key=lambda kv: -kv[1])[:400] ordered_other_trigrams = sorted(other.frequencies[2].items(), key=lambda kv: -kv[1])[:400] ranked_own_trigrams = dict(zip([key for (key, freq) in ordered_own_trigrams], itertools.count(0))) ranked_other_trigrams = dict(zip([key for (key, freq) in ordered_other_trigrams], itertools.count(0))) res = sum(abs(v-ranked_other_trigrams.get(k, 400)) for (k, v) in ranked_own_trigrams.items()) + \ sum(abs(v-ranked_own_trigrams.get(k, 400)) for (k, v) in ranked_other_trigrams.items()) print(">", self.language, res) return res 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: 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() samples.append(Sample(lang, text)) samples[-1].print_overview() models[lang] = Sample.merge(samples) models[lang].print_overview()