PythonProgrammingPuzzles/generators/IMO.py

417 строки
15 KiB
Python

"""Problems inspired by the
[International Mathematical Olympiad](https://en.wikipedia.org/wiki/International_Mathematical_Olympiad)
[problems](https://www.imo-official.org/problems.aspx)"""
from puzzle_generator import PuzzleGenerator, Tags
from typing import List
# See https://github.com/microsoft/PythonProgrammingPuzzles/wiki/How-to-add-a-puzzle to learn about adding puzzles
class ExponentialCoinMoves(PuzzleGenerator):
"""
This problem has *long* answers, not that the code to solve it is long but that what the solution outputs is long.
The version below uses only 5 boxes (unlike the IMO problem with 6 boxes since 2010^2010^2010 is too big
for computers) but the solution is quite similar to the solution to the IMO problem. Because the solution
requires exponential many moves, our representation allows combining multiple Type-1 (advance) operations
into a single step.
Inspired by [IMO 2010 Problem 5](https://www.imo-official.org/problems.aspx)"""
skip_example = True # so that we can add a multiplier in gen method below
@staticmethod
def sat(states: List[List[int]], n=16385):
"""
There are five boxes each having one coin initially. Two types of moves are allowed:
* (advance) remove `k > 0` coins from box `i` and add `2k` coins to box `i + 1`
* (swap) remove a coin from box `i` and swap the contents of boxes `i+1` and `i+2`
Given `0 <= n <= 16385`, find a sequence of states that result in 2^n coins in the last box.
Note that `n` can be as large as 16385 yielding 2^16385 coins (a number with 4,933 digits) in the last
box. Encode each state as a list of the numbers of coins in the five boxes.
Sample Input:
`n = 2`
Sample Output:
`[[1, 1, 1, 1, 1], [0, 3, 1, 1, 1], [0, 1, 5, 1, 1], [0, 1, 4, 1, 1], [0, 0, 1, 4, 1], [0, 0, 0, 1, 4]]`
The last box now has 2^2 coins. This is a sequence of two advances followed by three swaps.
states is encoded by lists of 5 coin counts
"""
assert states[0] == [1] * 5 and all(len(li) == 5 for li in states) and all(i >= 0 for li in states for i in li)
for prev, cur in zip(states, states[1:]):
for i in range(5):
if cur[i] != prev[i]:
break
assert cur[i] < prev[i]
assert (
cur[i + 1] - prev[i + 1] == 2 * (prev[i] - cur[i]) and cur[i + 2:] == prev[i + 2:] # k decrements
or
cur[i:i + 3] == [prev[i] - 1, prev[i + 2], prev[i + 1]] and cur[i + 3:] == prev[i + 3:] # swap
)
return states[-1][-1] == 2 ** n
@staticmethod
def sol(n):
assert n >= 1
ans = [[1] * 5, [0, 3, 1, 1, 1], [0, 2, 3, 1, 1], [0, 2, 2, 3, 1], [0, 2, 2, 0, 7], [0, 2, 1, 7, 0],
[0, 2, 1, 0, 14], [0, 2, 0, 14, 0], [0, 1, 14, 0, 0]]
def exp_move(): # shifts last 3 [..., a, 0, 0] to [..., 0, 2^a, 0] for a>0
state = ans[-1][:]
state[2] -= 1
state[3] += 2
ans.append(state[:])
while state[2]:
state[3], state[4] = 0, 2 * state[3]
ans.append(state[:])
state[2:] = [state[2] - 1, state[4], 0]
ans.append(state[:])
exp_move()
assert ans[-1] == [0, 1, 0, 2 ** 14, 0]
ans.append([0, 0, 2 ** 14, 0, 0])
if n <= 16:
ans.append([0, 0, 0, 2 ** 15, 0])
else:
exp_move()
assert ans[-1] == [0, 0, 0, 2 ** (2 ** 14), 0]
state = ans[-1][:]
state[-2] -= 2 ** (n - 1)
state[-1] = 2 ** n
ans.append(state)
return ans
def gen(self, target_num_instances):
self.add(dict(n=2**14 + 1), multiplier=10) # n=16385 will be first instance because of skip_example
for i in range(10):
n = 2 ** i
self.add(dict(n=n), multiplier=1 if n <= 4 else n)
class NoRelativePrimes(PuzzleGenerator):
"""
Inspired by [IMO 2016 Problem 4](https://www.imo-official.org/problems.aspx)
Question: Is there a more efficient solution than the brute-force one we give, perhaps using the Chinese remainder
theorem?
"""
@staticmethod
def sat(nums: List[int], b=7, m=6):
"""
Let P(n) = n^2 + n + 1.
Given b>=6 and m>=1, find m non-negative integers for which the set {P(a+1), P(a+2), ..., P(a+b)} has
the property that there is no element that is relatively prime to every other element.
Sample input:
b = 6
m = 2
Sample output:
[195, 196]
"""
assert len(nums) == len(set(nums)) == m and min(nums) >= 0
def gcd(i, j):
r, s = max(i, j), min(i, j)
while s >= 1:
r, s = s, (r % s)
return r
for a in nums:
nums = [(a + i + 1) ** 2 + (a + i + 1) + 1 for i in range(b)]
assert all(any(i != j and gcd(i, j) > 1 for j in nums) for i in nums)
return True
@staticmethod
def sol(b, m):
ans = []
seen = set()
deltas = set()
def go(a):
if a < 0 or a in seen or len(ans) == m:
return
seen.add(a)
nums = [(a + i + 1) ** 2 + (a + i + 1) + 1 for i in range(b)]
if all(any(i != j and gcd(i, j) > 1 for j in nums) for i in nums):
new_deltas = [abs(a - a2) for a2 in ans if a != a2 and abs(a - a2) not in deltas]
ans.append(a)
for delta in new_deltas:
for a2 in ans:
go(a2 + delta)
go(a2 - delta)
deltas.update(new_deltas)
for delta in sorted(deltas):
go(a + delta)
def gcd(i, j):
r, s = max(i, j), min(i, j)
while s >= 1:
r, s = s, (r % s)
return r
a = 0
while len(ans) < m:
go(a)
a += 1
return ans
def gen_random(self):
b = self.random.randrange(6, 20)
m = self.random.randrange(1, 100)
# print(self.__class__, b, m, tick())
self.add(dict(b=b, m=m), test=(b < 10))
class FindRepeats(PuzzleGenerator):
"""
Note: This problem is much easier than the IMO problem which also required a proof that it is impossible
for a_0 not divisible by 3.
Inspired by [IMO 2017 Problem 1](https://www.imo-official.org/problems.aspx)
"""
@staticmethod
def sat(indices: List[int], a0=123):
"""
Find a repeating integer in an infinite sequence of integers, specifically the indices for which the same value
occurs 1000 times. The sequence is defined by a starting value a_0 and each subsequent term is:
a_{n+1} = the square root of a_n if the a_n is a perfect square, and a_n + 3 otherwise.
For a given a_0 (that is a multiple of 3), the goal is to find 1000 indices where the a_i's are all equal.
Sample input:
9
Sample output:
[0, 3, 6, ..., 2997]
The sequence starting with a0=9 is [9, 3, 6, 9, 3, 6, 9, ...] thus a_n at where n is a multiple of 3 are
all equal in this case.
"""
assert a0 >= 0 and a0 % 3 == 0, "Hint: a_0 is a multiple of 3."
s = [a0]
for i in range(max(indices)):
s.append(int(s[-1] ** 0.5) if int(s[-1] ** 0.5) ** 2 == s[-1] else s[-1] + 3)
return len(indices) == len(set(indices)) == 1000 and min(indices) >= 0 and len({s[i] for i in indices}) == 1
@staticmethod
def sol(a0):
n = a0
ans = []
i = 0
while len(ans) < 1000:
if n == 3: # use the fact that 3 will repeat infinitely often
ans.append(i)
n = int(n ** 0.5) if int(n ** 0.5) ** 2 == n else n + 3
i += 1
return ans
def gen_random(self):
a0 = 3 * self.random.randrange(1, 10 ** 6)
# print(self.__class__, a0, tick())
self.add(dict(a0=a0))
class PickNearNeighbors(PuzzleGenerator):
"""Inspired by [IMO 2017 Problem 5](https://www.imo-official.org/problems.aspx)
The puzzle solution follows the judge's proof closely."""
@staticmethod
def sat(keep: List[bool], heights=[10, 2, 14, 1, 8, 19, 16, 6, 12, 3, 17, 0, 9, 18, 5, 7, 11, 13, 15, 4]):
"""
Given a permutation of the integers up to n(n+1) as a list, choose 2n numbers to keep (in the same order)
so that the remaining list of numbers satisfies:
* its largest number is next to its second largest number
* its third largest number is next to its fourth largest number
...
* its second smallest number is next to its smallest number
Sample input:
[4, 0, 5, 3, 1, 2]
n = 2
Sample output:
[True, False, True, False, True, True]
Keeping these indices results in the sublist [4, 5, 1, 2] where 4 and 5 are adjacent as are 1 and 2.
"""
n = int(len(heights) ** 0.5)
assert sorted(heights) == list(range(n * n + n)), "hint: heights is a permutation of range(n * n + n)"
kept = [i for i, k in zip(heights, keep) if k]
assert len(kept) == 2 * n, "must keep 2n items"
pi = sorted(range(2 * n), key=lambda i: kept[i]) # the sort indices
return all(abs(pi[2 * i] - pi[2 * i + 1]) == 1 for i in range(n))
@staticmethod
def sol(heights):
# Based on the judge's solution.
n = int(len(heights) ** 0.5)
assert sorted(heights) == list(range(n * (n + 1)))
groups = [h // (n + 1) for h in heights]
ans = [False] * len(heights)
a = 0
used_groups = set()
while sum(ans) < 2 * n:
group_tracker = {}
b = a
while groups[b] not in group_tracker or groups[b] in used_groups:
group_tracker[groups[b]] = b
b += 1
ans[group_tracker[groups[b]]] = True
ans[b] = True
used_groups.add(groups[b])
a = b + 1
return ans
def gen_random(self):
n = self.random.randrange(1, 10)
heights = list(range(n * (n + 1)))
# print(self.__class__, n, tick())
self.random.shuffle(heights)
self.add(dict(heights=heights))
class FindProductiveList(PuzzleGenerator):
"""
Note: This problem is easier than the IMO problem because the hard part is proving that sequences do not
exists for non-multiples of 3.
Inspired by [IMO 2010 Problem 5](https://www.imo-official.org/problems.aspx)
"""
@staticmethod
def sat(li: List[int], n=18):
"""
Given n, find n integers such that li[i] * li[i+1] + 1 == li[i+2], for i = 0, 1, ..., n-1
where indices >= n "wrap around". Note: only n multiples of 3 are given since this is only possible for n
that are multiples of 3 (as proven in the IMO problem).
Sample input:
6
Sample output:
[_, _, _, _, _, _]
(Sample output hidden because showing sample output would give away too much information.)
"""
assert n % 3 == 0, "Hint: n is a multiple of 3"
return len(li) == n and all(li[(i + 2) % n] == 1 + li[(i + 1) % n] * li[i] for i in range(n))
@staticmethod
def sol(n):
return [-1, -1, 2] * (n // 3)
def gen(self, target_num_instances):
for n in range(3, 3 * target_num_instances + 3, 3):
# print(self.__class__, n, tick())
self.add(dict(n=n))
class HalfTag(PuzzleGenerator):
"""Inspired by [IMO 2020 Problem 3](https://www.imo-official.org/problems.aspx)"""
@staticmethod
def sat(li: List[int], tags=[3, 0, 3, 2, 0, 1, 0, 3, 1, 1, 2, 2, 0, 2, 1, 3]):
"""
The input tags is a list of 4n integer tags each in range(n) with each tag occurring 4 times.
The goal is to find a subset (list) li of half the indices such that:
* The sum of the indices equals the sum of the sum of the missing indices.
* The tags of the chosen indices contains exactly each number in range(n) twice.
Sample input:
n = 3
tags = [0, 1, 2, 0, 0, 1, 1, 1, 2, 2, 0, 2]
Sample output:
[0, 3, 5, 6, 8, 11]
Note the sum of the output is 33 = (0+1+2+...+11)/2 and the selected tags are [0, 0, 1, 1, 2, 2]
"""
n = max(tags) + 1
assert sorted(tags) == sorted(list(range(n)) * 4), "hint: each tag occurs exactly four times"
assert len(li) == len(set(li)) and min(li) >= 0
return sum(li) * 2 == sum(range(4 * n)) and sorted([tags[i] for i in li]) == [i // 2 for i in range(2 * n)]
@staticmethod
def sol(tags):
n = max(tags) + 1
pairs = {(i, 4 * n - i - 1) for i in range(2 * n)}
by_tag = {tag: [] for tag in range(n)}
for p in pairs:
a, b = [tags[i] for i in p]
by_tag[a].append(p)
by_tag[b].append(p)
cycles = []
cycle = []
while pairs:
if not cycle: # start new cycle
p = pairs.pop()
pairs.add(p) # just to pick a tag
tag = tags[p[0]]
# print("Starting cycle with tag", tag)
p = by_tag[tag].pop()
a, b = [tags[i] for i in p]
# print(p, a, b)
tag = a if a != tag else b
by_tag[tag].remove(p)
cycle.append(p if tag == b else p[::-1])
pairs.remove(p)
if not by_tag[tag]:
cycles.append(cycle)
cycle = []
while any(len(c) % 2 for c in cycles):
cycle_tags = [{tags[k] for p in c for k in p} for c in cycles]
merged = False
for i in range(len(cycles)):
for j in range(i):
intersection = cycle_tags[i].intersection(cycle_tags[j])
if intersection:
c = intersection.pop()
# print(f"Merging cycle {i} and cycle {j} at tag {c}", cycles)
cycle_i = cycles.pop(i)
for i1, p in enumerate(cycle_i):
if tags[p[0]] == c:
break
for j1, p in enumerate(cycles[j]):
if tags[p[0]] == c:
break
cycles[j][j1:j1] = cycle_i[i1:] + cycle_i[:i1]
merged = True
break
if merged:
break
ans = []
for c in cycles:
for i, p in enumerate(c):
if i % 2:
ans += p
return ans
def gen_random(self):
n = self.random.randrange(1, 10)
tags = [i // 4 for i in range(4 * n)]
self.random.shuffle(tags)
# print(self.__class__, n, tick())
self.add(dict(tags=tags))
if __name__ == "__main__":
PuzzleGenerator.debug_problems()