Added defragmentation-related stuff
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import random, math
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def mk_initial_balances(accts, coins):
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o = []
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for i in range(accts):
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o.extend([i] * random.randrange((coins - len(o)) * 2 // (accts - i)))
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o.extend([accts-1] * (coins - len(o)))
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return o
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def fragments(coins):
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o = 0
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for i in range(1, len(coins)):
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if coins[i] != coins[i-1]:
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o += 1
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return o
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def xfer(coins, frm, to, value):
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coins = coins[::]
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pos = 0
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while pos < len(coins) and value > 0:
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if coins[pos] == frm:
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coins[pos] = to
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value -= 1
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pos += 1
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return coins
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def unscramble(coins, c1, c2):
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coins = coins[::]
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k1 = coins.count(c1)
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pos = 0
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while pos < len(coins):
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if coins[pos] in (c1, c2):
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coins[pos] = c1 if k1 > 0 else c2
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if coins[pos] == c1:
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k1 -= 1
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pos += 1
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return coins
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def multi_unscramble(coins, addrs):
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coins = coins[::]
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ks = [coins.count(c) for c in addrs]
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pos = 0
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at = 0
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while pos < len(coins):
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if coins[pos] in addrs:
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coins[pos] = addrs[at]
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ks[at] -= 1
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if ks[at] == 0:
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at += 1
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pos += 1
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return coins
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def unscramble_swap_strategy(coins, rounds):
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for i in range(rounds):
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c1, c2 = sorted([random.randrange(max(coins)+1) for _ in range(2)])
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coins = unscramble(coins, c1, c2)
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return coins
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def run_with_unscrambling(coins, rounds):
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M = max(coins) + 1
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for i in range(rounds):
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c1, c2 = [random.randrange(M) for _ in range(2)]
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value = int(coins.count(c1) ** random.random())
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coins = xfer(coins, c1, c2, value)
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coins = unscramble(coins, min(c1, c2), max(c1, c2))
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return coins
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def run_with_unscramble_online(coins, rounds):
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M = max(coins) + 1
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for i in range(rounds):
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c1, c2 = [random.randrange(M) for _ in range(2)]
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value = int(coins.count(c1) ** random.random())
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coins = xfer(coins, c1, c2, value)
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if random.random() < 1:
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cx = sorted([random.randrange(M) for _ in range(5)])
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coins = multi_unscramble(coins, cx)
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return coins
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c = mk_initial_balances(200, 10000)
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# random.shuffle(c)
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# c = unscramble_swap_strategy(c, 20000)
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c = run_with_unscramble_online(c, 10000)
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print(fragments(c))
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@ -0,0 +1,49 @@
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import random
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def mk_shuffle(n):
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L = list(range(n))
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random.shuffle(L)
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return L
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def mk_fragmented_shuffle(n, shuffs):
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L = list(range(n))
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for i in range(shuffs):
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x1 = random.randrange(n)
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x2 = random.randrange(n)
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value = int(min(n - x1, n - x2, abs(x2 - x1)) ** random.random())
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L[x1:x1+value], L[x2:x2+value] = L[x2:x2+value], L[x1:x1+value]
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return L
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def fragments(vals):
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tot = 1
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for i in range(1, len(vals)):
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if vals[i] != vals[i-1] + 1:
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tot += 1
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return tot
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def apply_perm(vals, perm):
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o = [0 for x in vals]
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for i in range(len(perm)):
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o[i] = vals[perm[i]]
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return o
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def attempt_fix(vals):
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perm = list(range(len(vals)))
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indices = {}
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for i, x in enumerate(vals):
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indices[x] = i
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for i in range(len(vals)):
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if perm[i] == i and vals[i] != i:
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poz = indices[i]
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if perm[poz] == poz:
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perm[i], perm[poz] = perm[poz], perm[i]
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assert apply_perm(perm, perm) == list(range(len(vals)))
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return perm
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def fix(vals):
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goal = list(range(len(vals)))
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path = []
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while vals != goal:
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vals = apply_perm(vals, attempt_fix(vals))
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path.append(vals)
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return path
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@ -0,0 +1,65 @@
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import heapq, random
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def distance_score(state):
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state = [int(x) for x in state.split(',')]
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tot = 0
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for i, s in enumerate(state):
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xorval = (i+1) ^ s
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indexmask = 1
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while indexmask < len(state):
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if xorval & indexmask:
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tot += 1
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indexmask <<= 1
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return tot
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def generate_legal_moves_for_bit(state, bit):
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o = set()
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xormask = 2**bit
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state = [int(x) for x in state.split(',')]
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for i in range(2**(len(state)-1)):
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new_state = state[::]
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indexmask = 1
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for j in range(len(state)):
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if j > (j ^ xormask):
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if i & indexmask:
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new_state[j], new_state[j ^ xormask] = new_state[j ^ xormask], new_state[j]
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indexmask <<= 1
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o.add(','.join([str(x) for x in new_state]))
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return o
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def generate_legal_moves(state):
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o = set()
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b = 0
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while 2**b < len(state):
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o = o.union(generate_legal_moves_for_bit(state, b))
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b += 1
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return o
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def mk_shuffle(n):
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L = list(range(1, n+1))
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random.shuffle(L)
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return ','.join([str(x) for x in L])
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def find_path(start):
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parents = {}
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scores = {start: 0}
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queue = [(distance_score(start), start)]
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goal = ','.join([str(x) for x in sorted([int(x) for x in start.split(',')])])
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totvs = 0
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while len(queue):
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qval = heapq.heappop(queue)[1]
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newvals = [x for x in generate_legal_moves(qval) if x not in scores]
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for v in newvals:
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if scores.get(v, 99999) > scores[qval] + 1:
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scores[v] = scores[qval] + 1
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parents[v] = qval
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totvs += 1
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if v == goal:
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path = [v]
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while path[-1] != start:
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parent = parents[path[-1]]
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path.append(parent)
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return path
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for v in newvals:
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heapq.heappush(queue, (distance_score(v), v))
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raise Exception("huh")
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