ref: 03bf63f40e0fdd56e86dfe5a7c5ce1937ab9127a
dir: /other/make_text_dict.py/
import array memos = {} memoslist = [] def memo(s): m = memos.get(s) if m == None: m = len(memoslist) memos[s] = m memoslist.append(s) return m def tos(s): return "".join(memoslist[c] for c in s) lines = [] for line in open('dialogue.txt', 'r').read().splitlines(): line = line.split(': ')[1] r = array.array('H') i = 0 while i < len(line): if line[i] == '[': j = line.index(']', i + 1) r.append(memo(line[i:j+1])) i = j + 1 else: r.append(memo(line[i])) i += 1 #print(repr(line)) #print(r) lines.append(list(r)) import collections def find_all_ngrams(lines, N, cost): ctr = collections.Counter() for line in lines: for i in range(len(line) - N + 1): if line[i] != line[i+1]: ctr[tuple(line[i:i+N])] += 1 r = list((b, a) for a, b in ctr.items() if b >= 2) if len(r) == 0: return None, 0 b, a = max(r) return a, (N - cost) * b - N - 2 # 2 is the overhead of the dict def find_best_ngram(cost): best_score=0 for i in range(2, 32): text, score = find_all_ngrams(lines, i, cost) if score > best_score: best_score = score best_text = text return best_score, best_text def update_ngrams(lines, replace_from, replace_to): for line in lines: for i in range(len(line) - len(replace_from) + 1): if tuple(line[i:i+len(replace_from)]) == replace_from: line[i:i+len(replace_from)] = replace_to total_gain = 0 original_tokens = sum(len(line) for line in lines) kTextDictionary_US = [ ' ', ' ', ' ', "'s ", 'and ', 'are ', 'all ', 'ain', 'and', 'at ', 'ast', 'an', 'at', 'ble', 'ba', 'be', 'bo', 'can ', 'che', 'com', 'ck', 'des', 'di', 'do', 'en ', 'er ', 'ear', 'ent', 'ed ', 'en', 'er', 'ev', 'for', 'fro', 'give ', 'get', 'go', 'have', 'has', 'her', 'hi', 'ha', 'ight ', 'ing ', 'in', 'is', 'it', 'just', 'know', 'ly ', 'la', 'lo', 'man', 'ma', 'me', 'mu', "n't ", 'non', 'not', 'open', 'ound', 'out ', 'of', 'on', 'or', 'per', 'ple', 'pow', 'pro', 're ', 're', 'some', 'se', 'sh', 'so', 'st', 'ter ', 'thin', 'ter', 'tha', 'the', 'thi', 'to', 'tr', 'up', 'ver', 'with', 'wa', 'we', 'wh', 'wi', 'you', 'Her', 'Tha', 'The', 'Thi', 'You', ] dictionary = [] for i in range(111+256): best_score, best_text = find_best_ngram(1 if i < 111 else 2) if best_score == 0: break total_gain += best_score print(f'Removed best bigram "{tos(best_text)}" with gain {best_score}, total gain {total_gain} / {original_tokens}') dictionary.append(best_text) update_ngrams(lines, best_text, [memo('{%s}' % tos(best_text))]) #print('kTextDictionary_NEW = [') #for i, d in enumerate(dictionary): # repl = tos(d).replace('{', '').replace('}', '') # print(f'{repr(repl)},') #print(']') for i, a in enumerate(lines): print(i, tos(a))