IoC for patterns
This commit is contained in:
@@ -6,6 +6,7 @@ from InterruptIndices import InterruptIndices
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from Probability import Probability
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from RuneText import RuneTextFile
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from LPath import FILES_ALL, FILES_UNSOLVED, LPath
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from KeySearch import GuessPattern
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#########################################
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@@ -18,40 +19,21 @@ class InterruptDB(object):
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self.iguess = InterruptSearch(data, irp=interrupt, irp_stops=irp_stops)
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self.irp_count = len(self.iguess.stops)
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def make(self, dbname, name, keylen, fn_score):
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def find_best_solution(self, fn_score, keylen):
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if keylen == 0: # without interrupts
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score, skips = fn_score(self.iguess.join(), 1), [[]]
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else:
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score, skips = self.iguess.all(keylen, fn_score)
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for i, interrupts in enumerate(skips):
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skips[i] = self.iguess.to_occurrence_index(interrupts)
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for nums in skips:
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self.write(
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name, score, self.irp, self.irp_count, keylen, nums, dbname)
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return score, skips
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def make_secondary(self, dbname, name, keylen, fn_score, threshold):
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scores = []
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def fn(x, kl):
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score = fn_score(x, kl)
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if score >= threshold:
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scores.append(score)
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return 1
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return -1
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_, skips = self.iguess.all(keylen, fn)
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for i, interrupts in enumerate(skips):
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skips[i] = self.iguess.to_occurrence_index(interrupts)
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ret = list(zip(scores, skips))
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bestscore = max(ret)[0]
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# exclude best results, as they are already present in the main db
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filtered = [x for x in ret if x[0] < bestscore]
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for score, nums in filtered:
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self.write(
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name, score, self.irp, self.irp_count, keylen, nums, dbname)
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return len(filtered)
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def write(self, dbname, desc, score, keylen, nums):
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with open(LPath.db(dbname), 'a') as f:
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for solution in nums:
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solution = ','.join(map(str, solution))
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f.write('{}|{}|{:.5f}|{}|{}|{}\n'.format(
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desc, self.irp_count, score, self.irp, keylen, solution))
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@staticmethod
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def load(dbname):
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@@ -75,11 +57,11 @@ class InterruptDB(object):
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@staticmethod
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def load_scores(dbname):
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scores = {} # {fname: [irp0_[kl0, kl1, ...], irp1_[...]]}
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for k, v in InterruptDB.load(dbname).items():
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for irpc, score, irp, kl, nums in v:
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if k not in scores:
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scores[k] = [[] for _ in range(29)]
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part = scores[k][irp]
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for name, entries in InterruptDB.load(dbname).items():
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for irpc, score, irp, kl, nums in entries:
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if name not in scores:
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scores[name] = [[] for _ in range(29)]
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part = scores[name][irp]
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while kl >= len(part):
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part.append((0, 0)) # (score, irp_count)
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oldc = part[kl][1]
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@@ -87,101 +69,131 @@ class InterruptDB(object):
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part[kl] = (score, irpc)
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return scores
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@staticmethod
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def write(name, score, irp, irpmax, keylen, nums, dbname='db_main'):
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with open(LPath.db(dbname), 'a') as f:
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nums = ','.join(map(str, nums))
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f.write(f'{name}|{irpmax}|{score:.5f}|{irp}|{keylen}|{nums}\n')
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#########################################
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# helper functions
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#########################################
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def get_db(fname, irp, max_irp):
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stops, Z = InterruptIndices().consider(fname, irp, max_irp)
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data = RuneTextFile(LPath.page(fname)).index_no_white[:Z]
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return InterruptDB(data, irp, irp_stops=stops)
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def create_primary(dbname, fn_score, klset=range(1, 33),
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max_irp=20, irpset=range(29), files=FILES_ALL):
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oldDB = InterruptDB.load(dbname)
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def enum_db_irps(dbname, fn_score, max_irp=20, irpset=[0, 28],
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klset=range(1, 33), files=FILES_UNSOLVED, fn_load_db=get_db):
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oldValues = {k: set((a, b, c) for a, _, b, c, _ in v)
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for k, v in oldDB.items()}
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for k, v in InterruptDB.load(dbname).items()}
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for irp in irpset: # interrupt rune index
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for name in files:
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db = get_db(name, irp, max_irp)
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print('load:', name, 'interrupt:', irp, 'count:', db.irp_count)
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for fname in files:
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db = fn_load_db(fname, irp, max_irp)
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print('load:', fname, 'interrupt:', irp, 'count:', db.irp_count)
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for keylen in klset: # key length
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if (db.irp_count, irp, keylen) in oldValues.get(name, []):
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if (db.irp_count, irp, keylen) in oldValues.get(fname, []):
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print(f'{keylen}: skipped.')
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continue
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score, interrupts = db.make(dbname, name, keylen, fn_score)
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print(f'{keylen}: {score:.4f}, solutions: {len(interrupts)}')
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score, skips = db.find_best_solution(fn_score, keylen)
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yield db, fname, score, keylen, skips
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def create_primary(dbname, fn_score):
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for db, fname, score, kl, skips in enum_db_irps(dbname, fn_score,
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irpset=range(29),
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files=FILES_ALL):
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db.write(dbname, fname, score, kl, skips)
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print(f'{kl}: {score:.4f}, solutions: {len(skips)}')
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def create_secondary(db_in, db_out, fn_score, threshold=0.75, max_irp=20):
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oldDB = InterruptDB.load(db_in)
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search_set = set()
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for name, arr in oldDB.items():
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if name not in FILES_UNSOLVED:
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continue
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for irpc, score, irp, kl, nums in arr:
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if score <= threshold or kl > 26 or kl < 3:
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continue
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search_set.add((name, irp, kl))
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print('searching through', len(search_set), 'files.')
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for name, irp, kl in search_set:
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print('load:', name, 'interrupt:', irp, 'keylen:', kl)
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db = get_db(name, irp, max_irp)
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c = db.make_secondary(db_out, name, kl, fn_score, threshold)
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print('found', c, 'additional solutions')
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for fname, arr in InterruptDB.load(db_in).items():
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if fname in FILES_UNSOLVED:
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for irpc, score, irp, kl, nums in arr:
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if score > threshold and kl > 3 and kl < 26:
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search_set.add((fname, irp, kl))
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print('searching through', len(search_set), 'candidates.')
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for fname, irp, kl in search_set:
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print('load:', fname, 'interrupt:', irp, 'keylen:', kl)
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scores = []
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def fn_keep_scores(x, kl):
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score = fn_score(x, kl)
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if score >= threshold:
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scores.append(score) # hacky but gets the job done
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return 1
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return -1
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db = get_db(fname, irp, max_irp)
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_, skips = db.find_best_solution(fn_keep_scores, kl)
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ret = list(zip(scores, skips))
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bestscore = max(ret)[0]
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# exclude best results, as they are already present in the main db
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filtered = [x for x in ret if x[0] < bestscore]
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for score, nums in filtered:
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db.write(db_out, fname, score, kl, [nums])
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print('found', len(filtered), 'additional solutions')
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def create_mod_a_db(dbprefix, fn_score, klpairs, max_irp=20, irpset=[0, 28]):
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for mod, upto in klpairs:
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def create_mod_a_db(dbprefix, fn_score):
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for mod, upto in [(2, 13), (3, 8)]:
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for mo in range(mod):
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# if needed add combined check for all modulo parts
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def xor_split(data, keylen):
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return fn_score(data[mo::mod], keylen)
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create_primary(f'db_{dbprefix}_mod_a_{mod}.{mo}', xor_split,
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range(1, upto + 1), max_irp, irpset, FILES_UNSOLVED)
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dbname = f'db_{dbprefix}_mod_a_{mod}.{mo}'
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for db, fname, score, kl, skips in enum_db_irps(
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dbname, xor_split, klset=range(1, upto + 1)):
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db.write(dbname, fname, score, kl, skips)
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print(f'mod a {mod}.{mo}, kl: {kl}, score: {score:.4f}')
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def create_mod_b_db(dbprefix, fn_score, klpairs, max_irp=20, irpset=[0, 28]):
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def create_mod_b_db(dbprefix, fn_score):
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db_i = InterruptIndices()
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for mod, upto in klpairs:
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for mod, upto in [(2, 18), (3, 18)]:
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for mo in range(mod):
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dbname = f'db_{dbprefix}_mod_b_{mod}.{mo}'
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oldDB = {k: set((a, b, c) for a, _, b, c, _ in v)
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for k, v in InterruptDB.load(dbname).items()}
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# custom modulo data load function
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def db_load_mod(fname, irp, max_irp):
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stops, Z = db_i.consider_mod_b(fname, irp, max_irp, mod)
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stops = stops[mo]
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Z = Z[mo]
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data = RuneTextFile(LPath.page(fname)).index_no_white
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data = data[mo::mod][:Z]
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return InterruptDB(data, irp, irp_stops=stops)
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for irp in irpset: # interrupt rune index
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for name in FILES_UNSOLVED:
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stops, Z = db_i.consider_mod_b(name, irp, max_irp, mod)
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stops = stops[mo]
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Z = Z[mo]
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data = RuneTextFile(LPath.page(name)).index_no_white
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data = data[mo::mod][:Z]
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db = InterruptDB(data, irp, irp_stops=stops)
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print(f'load: {name} interrupt: {irp} count: {len(stops)}')
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for keylen in range(2, upto + 1): # key length
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if (db.irp_count, irp, keylen) in oldDB.get(name, []):
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print(f'{keylen}: skipped.')
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continue
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score, irps = db.make(dbname, name, keylen, fn_score)
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print(f'{keylen}: {score:.4f}, solutions: {len(irps)}')
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dbname = f'db_{dbprefix}_mod_b_{mod}.{mo}'
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for db, fname, score, kl, skips in enum_db_irps(
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dbname, fn_score, klset=range(2, upto + 1),
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fn_load_db=db_load_mod):
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db.write(dbname, fname, score, kl, skips)
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print(f'mod b {mod}.{mo}, kl: {kl}, score: {score:.4f}')
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def create_pattern_shift_db(offset=0):
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# we misuse the db's keylen column as pattern shift multiply
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for kpl in range(4, 19): # key pattern length, equiv. to x^2 vigenere
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def fn_score(x, kpl_shift):
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parts = GuessPattern.groups(x, kpl, kpl_shift, offset)
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return sum(Probability(x).IC() for x in parts) / kpl
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# return 1 - (sum(Probability(x).IC_norm() for x in parts) / kl)
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dbname = f'db_high_pattern_shift_{kpl}.{offset}'
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for db, fname, score, kl, skips in enum_db_irps(dbname, fn_score,
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irpset=[0],
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klset=range(1, kpl)):
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db.write(dbname, fname, score, kl, skips)
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print(f'shift_pattern {kpl}.{offset}, shift: {kl}, score: {score:.4f}')
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if __name__ == '__main__':
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create_primary('db_high', Probability.IC_w_keylen, max_irp=20)
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create_primary('db_norm', Probability.target_diff, max_irp=20)
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create_mod_a_db('high', Probability.IC_w_keylen, [(2, 13), (3, 8)])
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create_mod_a_db('norm', Probability.target_diff, [(2, 13), (3, 8)])
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create_mod_b_db('high', Probability.IC_w_keylen, [(2, 18), (3, 18)])
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create_mod_b_db('norm', Probability.target_diff, [(2, 18), (3, 18)])
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# create_primary('db_high', Probability.IC_w_keylen)
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# create_primary('db_norm', Probability.target_diff)
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# create_mod_a_db('high', Probability.IC_w_keylen)
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# create_mod_a_db('norm', Probability.target_diff)
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# create_mod_b_db('high', Probability.IC_w_keylen)
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# create_mod_b_db('norm', Probability.target_diff)
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create_pattern_shift_db(offset=0)
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# create_secondary('db_high', 'db_high_secondary',
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# Probability.IC_w_keylen, threshold=1.4)
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# create_secondary('db_norm', 'db_norm_secondary',
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@@ -60,27 +60,38 @@ class GuessAffine(object):
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#########################################
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class GuessPattern(object):
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def __init__(self, nums):
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self.nums = nums
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@staticmethod
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def groups(nums, keylen, shift=1, offset=0):
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gen = GuessPattern.shift_pattern(keylen, shift)
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for _ in range(offset):
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next(gen)
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ret = [[] for _ in range(keylen)]
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for idx, value in zip(gen, nums):
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ret[idx].append(value)
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return ret
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def shift_pattern(kl, shift=1): # shift by (more than) one, 012201120
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for i in range(10000):
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p = (i * shift) % kl
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yield from range(p, kl)
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yield from range(p)
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def mirror_pattern_a(kl): # mirrored, 012210012210
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for i in range(10000):
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yield from range(kl)
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yield from range(kl - 1, -1, -1)
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def mirror_pattern_b(kl): # mirrored, 012101210
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for i in range(10000):
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yield from range(kl)
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yield from range(kl - 2, 0, -1)
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@staticmethod
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def pattern(keylen, fn_pattern):
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mask = '0123456789ABCDEFGHIJKLMNOPQRSTUVWXYZ'[:keylen]
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return fn_pattern(mask, keylen)
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def split(self, keylen, mask, offset=0):
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ret = {}
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def zip(nums, key, keylen, shift=1, offset=0):
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gen = GuessPattern.shift_pattern(keylen, shift)
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for _ in range(offset):
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next(mask)
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ret = {k: [] for k in '0123456789ABCDEFGHIJKLMNOPQRSTUVWXYZ'[:keylen]}
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for n, k in zip(self.nums, mask):
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ret[k].append(n)
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return ret.values()
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def zip(self, key_mask, offset=0):
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for _ in range(offset):
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next(key_mask)
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return [(n - k) % 29 for n, k in zip(self.nums, key_mask)]
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next(gen)
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return [(n - key[k]) % 29 for n, k in zip(nums, gen)]
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@staticmethod
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def guess(parts, score_fn): # minimize score_fn
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@@ -97,3 +108,7 @@ class GuessPattern(object):
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avg_score += best
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found.append(candidate)
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return avg_score / len(parts), found
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if __name__ == '__main__':
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print(list(GuessPattern.shift_pattern(4, 3))[:20])
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@@ -84,27 +84,15 @@ def pattern_solver(fname, irp=0):
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def fn_similarity(x):
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return LP.Probability(x).similarity()
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def fn_pattern_mirror(x, kl):
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for i in range(10000): # mirrored, 012210012210 or 012101210
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yield from x
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# yield from x[::-1]
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yield from x[::-1][1:-1]
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prnt_fmt = 'kl: {}, pattern-n: {}, IoC: {:.3f}, dist: {:.4f}, offset: {}, key: {}'
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print(fname)
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gr = LP.GuessPattern(data)
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# gr = LP.GuessPattern(data)
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for kl in range(3, 19):
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for pattern_shift in range(1, kl):
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def fn_pattern_shift(x, kl): # shift by (more than) one, 012201120
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for i in range(10000):
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yield from x[(i * pattern_shift) % kl:]
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yield from x[:(i * pattern_shift) % kl]
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for kl_shift in range(1, kl):
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# Find proper pattern
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res = []
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for offset in range(kl): # up to keylen offset
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mask = LP.GuessPattern.pattern(kl, fn_pattern_shift)
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parts = gr.split(kl, mask, offset)
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parts = LP.GuessPattern.groups(data, kl, kl_shift, offset)
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score = sum(LP.Probability(x).IC() for x in parts) / kl
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if score > 1.6 and score < 2.1:
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res.append((score, parts, offset))
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@@ -113,9 +101,9 @@ def pattern_solver(fname, irp=0):
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for score, parts, off in res:
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sc, key = LP.GuessPattern.guess(parts, fn_similarity)
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if sc < 0.1:
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print(prnt_fmt.format(kl, pattern_shift, score, sc, off,
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print(prnt_fmt.format(kl, kl_shift, score, sc, off,
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LP.RuneText(key).text))
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solved = gr.zip(fn_pattern_shift(key, kl), off)
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solved = LP.GuessPattern.zip(data, key, kl, kl_shift, off)
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for i in whitespace_i:
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solved.insert(i, 29)
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print(' ', LP.RuneText(solved).text)
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