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3213. 最小代价构造字符串

news 2025/8/5 20:11:48

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3213. 最小代价构造字符串
- 题意
- 思路
- 代码

3213. 最小代价构造字符串

题意

给你一个字符串 target、一个字符串数组 words 以及一个整数数组 costs，这两个数组长度相同。

设想一个空字符串 s。

你可以执行以下操作任意次数（包括零次）：

选择一个在范围 [0, words.length - 1] 的索引 i。
将 words[i] 追加到 s。
该操作的成本是 costs[i]。
返回使 s 等于 target 的最小成本。如果不可能，返回 -1。

思路

字典树/字符串哈希 + dp

使用 Trie 树存储单词和成本：
我们将所有的单词和对应的成本插入到一个 Trie 树中。Trie 树是一种多叉树，可以快速查找以某个前缀开头的所有单词。
这样我们就能在 Trie 树中快速查找到以 target 中某个位置开始的所有前缀单词及其成本。
动态规划（Dynamic Programming）：
使用一个动态规划数组 dp，其中 dp[i] 表示构造 target 的前 i 个字符的最小成本。
初始化 dp[0] = 0，表示构造空字符串的成本为 0，其他位置初始化为无穷大，表示尚未计算到该位置。
遍历目标字符串：
对于目标字符串 target 的每一个位置 i，如果 dp[i] 是无穷大，表示不能从当前位置开始构造，则跳过。
否则，使用 Trie 树的 search 方法，从当前位置 i 开始查找所有可能的前缀及其成本。
对于每一个找到的前缀，更新 dp 数组：dp[i + length] = min(dp[i + length], dp[i] + cost)，表示从当前位置 i 开始构造到 i + length 的最小成本。

代码

# 3.8.19 import
import random
from collections import Counter, defaultdict, deque
from datetime import datetime, timedelta
from functools import lru_cache
from heapq import heapify, heappop, heappush, nlargest, nsmallest
from itertools import combinations, compress, permutations, starmap, tee
from math import ceil, fabs, floor, gcd, log, sqrt
from string import ascii_lowercase, ascii_uppercase
from sys import exit, setrecursionlimit, stdin
from typing import Any, Dict, List, Tuple, TypeVar, Union# Constants
TYPE = TypeVar('TYPE')
N = int(2e5 + 10)  # If using AR, modify accordingly
M = int(20)  # If using AR, modify accordingly
INF = int(2e9)
OFFSET = int(100)# Set recursion limit
setrecursionlimit(INF)class Arr:array = staticmethod(lambda x=0, size=N: [x] * size)array2d = staticmethod(lambda x=0, rows=N, cols=M: [Arr.array(x, cols) for _ in range(rows)])graph = staticmethod(lambda size=N: [[] for _ in range(size)])@staticmethoddef to_1_indexed(data: Union[List, str, List[List]]):"""Adds a zero prefix to the data and returns the modified data and its length."""if isinstance(data, list):if all(isinstance(item, list) for item in data):  # Check if it's a 2D arraynew_data = [[0] * (len(data[0]) + 1)] + [[0] + row for row in data]return new_data, len(new_data) - 1, len(new_data[0]) - 1else:new_data = [0] + datareturn new_data, len(new_data) - 1elif isinstance(data, str):new_data = '0' + datareturn new_data, len(new_data) - 1else:raise TypeError("Input must be a list, a 2D list, or a string")class Str:letter_to_num = staticmethod(lambda x: ord(x.upper()) - 65)  # A -> 0num_to_letter = staticmethod(lambda x: ascii_uppercase[x])  # 0 -> Aremoveprefix = staticmethod(lambda s, prefix: s[len(prefix):] if s.startswith(prefix) else s)removesuffix = staticmethod(lambda s, suffix: s[:-len(suffix)] if s.endswith(suffix) else s)class Math:max = staticmethod(lambda a, b: a if a > b else b)min = staticmethod(lambda a, b: a if a < b else b)class IO:input = staticmethod(lambda: stdin.readline().rstrip("\r\n"))read = staticmethod(lambda: map(int, IO.input().split()))read_list = staticmethod(lambda: list(IO.read()))class Std:@staticmethoddef find(container: Union[List[TYPE], str], value: TYPE):"""Returns the index of value in container or -1 if value is not found."""if isinstance(container, list):try:return container.index(value)except ValueError:return -1elif isinstance(container, str):return container.find(value)@staticmethoddef pairwise(iterable):"""Return successive overlapping pairs taken from the input iterable."""a, b = tee(iterable)next(b, None)return zip(a, b)@staticmethoddef bisect_left(a, x, key=lambda y: y):"""The insertion point is the first position where the element is not less than x."""left, right = 0, len(a)while left < right:mid = (left + right) >> 1if key(a[mid]) < x:left = mid + 1else:right = midreturn left@staticmethoddef bisect_right(a, x, key=lambda y: y):"""The insertion point is the first position where the element is greater than x."""left, right = 0, len(a)while left < right:mid = (left + right) >> 1if key(a[mid]) <= x:left = mid + 1else:right = midreturn leftclass SparseTable:def __init__(self, data: list, func=lambda x, y: x | y):"""Initialize the Sparse Table with the given data and function."""self.func = funcself.st = [list(data)]i, n = 1, len(self.st[0])while 2 * i <= n:pre = self.st[-1]self.st.append([func(pre[j], pre[j + i]) for j in range(n - 2 * i + 1)])i <<= 1def query(self, begin: int, end: int):"""Query the combined result over the interval [begin, end]."""lg = (end - begin + 1).bit_length() - 1return self.func(self.st[lg][begin], self.st[lg][end - (1 << lg) + 1])class TrieNode:def __init__(self):"""Initialize children dictionary and cost. The trie tree is a 26-ary tree."""self.children = {}self.cost = INFdef add(self, word, cost):"""Add a word to the trie with the associated cost."""node = selffor c in word:if c not in node.children:node.children[c] = Std.TrieNode()node = node.children[c]node.cost = min(node.cost, cost)def search(self, word):"""Search for prefixes of 'word' in the trie and return their lengths and costs."""node = selfans = []for i, c in enumerate(word):if c not in node.children:breaknode = node.children[c]if node.cost != INF:ans.append([i + 1, node.cost])  # i + 1 to denote length from startreturn ansclass StringHash:def __init__(self, s: str, mod: int = 1_070_777_777):"""Initialize the StringHash object with the string, base, and mod."""self.s = sself.mod = modself.base = random.randint(8 * 10 ** 8, 9 * 10 ** 8)self.n = len(s)self.pow_base = [1] + Arr.array(0, self.n)  # pow_base[i] = BASE^iself.pre_hash = Arr.array(0, self.n + 1)  # pre_hash[i] = hash(s[:i])self._compute_hash()def _compute_hash(self):"""Compute the prefix hash values and power of base values for the string."""for i, b in enumerate(self.s):self.pow_base[i + 1] = self.pow_base[i] * self.base % self.modself.pre_hash[i + 1] = (self.pre_hash[i] * self.base + ord(b)) % self.moddef get_sub_hash(self, l: int, r: int) -> int:"""Get the hash value of the substring s[l:r+1] """return (self.pre_hash[r + 1] - self.pre_hash[l] * self.pow_base[r - l + 1] % self.mod + self.mod) % self.moddef get_full_hash(self) -> int:"""Get the hash value of the full string"""return self.pre_hash[self.n]def compute_hash(self, word: str) -> int:"""Compute the hash value of a given word using the object's base and mod."""h = 0for b in word:h = (h * self.base + ord(b)) % self.modreturn h# ————————————————————— Division line ——————————————————————class Solution:def minimumCost(self, target: str, words: List[str], costs: List[int]) -> int:# Build the Trietrie = Std.TrieNode()for word, cost in zip(words, costs):trie.add(word, cost)n = len(target)dp = Arr.array(INF, n + 1)dp[0] = 0# Dynamic programming to calculate the minimum costfor i in range(n):if dp[i] == INF:continuefor length, cost in trie.search(target[i:]):dp[i + length] = min(dp[i + length], dp[i] + cost)return dp[n] if dp[n] != INF else -1class Solution:def minimumCost(self, target: str, words: List[str], costs: List[int]) -> int:n = len(target)target_hash = Std.StringHash(target)# 每个 words[i] 的哈希值 -> 最小成本min_cost = defaultdict(lambda: INF)for w, c in zip(words, costs):h = target_hash.compute_hash(w)min_cost[h] = min(min_cost[h], c)# 获取所有唯一的单词长度sorted_lens = sorted(set(map(len, words)))dp = Arr.array(INF, n + 1)dp[0] = 0for i in range(n):if dp[i] == INF:continuefor sz in sorted_lens:if i + sz > n:break# 计算子串 target[i:i+sz] 的哈希值sub_hash = target_hash.get_sub_hash(i, i + sz - 1)dp[i + sz] = min(dp[i + sz], dp[i] + min_cost[sub_hash])return -1 if dp[n] == INF else dp[n]