1178. Number of Valid Words for Each Puzzle

With respect to a given puzzle string, a word is valid if both the following conditions are satisfied:

  • word contains the first letter of puzzle.
  • For each letter in word, that letter is in puzzle.
    For example, if the puzzle is "abcdefg", then valid words are "faced", "cabbage", and "baggage"; while invalid words are "beefed" (doesn't include "a") and "based" (includes "s" which isn't in the puzzle).

Return an array answer, where answer[i] is the number of words in the given word list words that are valid with respect to the puzzle puzzles[i].

 

Example :

Input: 
words = ["aaaa","asas","able","ability","actt","actor","access"], 
puzzles = ["aboveyz","abrodyz","abslute","absoryz","actresz","gaswxyz"]
Output: [1,1,3,2,4,0]
Explanation:
1 valid word for "aboveyz" : "aaaa" 
1 valid word for "abrodyz" : "aaaa"
3 valid words for "abslute" : "aaaa", "asas", "able"
2 valid words for "absoryz" : "aaaa", "asas"
4 valid words for "actresz" : "aaaa", "asas", "actt", "access"
There're no valid words for "gaswxyz" cause none of the words in the list contains letter 'g'.

 

Constraints:

  • 1 <= words.length <= 10^5
  • 4 <= words[i].length <= 50
  • 1 <= puzzles.length <= 10^4
  • puzzles[i].length == 7
  • words[i][j]puzzles[i][j] are English lowercase letters.
  • Each puzzles[i] doesn't contain repeated characters.

思路:关键是抓住puzzle的长度是7,直接枚举即可,去掉第一位,6位组合最多2**6=64

import itertools
from collections import Counter
class Solution(object):
    def findNumOfValidWords(self, words, puzzles):
        """
        :type words: List[str]
        :type puzzles: List[str]
        :rtype: List[int]
        """
        cnt = Counter(''.join(sorted(set(w))) for w in words)
        res = [0]*len(puzzles)
        for idx,p in enumerate(puzzles):
            first = p[0]
            t = set(p[1:])
            for i in range(len(t)+1):
                for cs in itertools.combinations(t, i):
                    cs = set(list(cs)+[first])
                    res[idx] += cnt.get(''.join(sorted(list(cs))), 0)
        return res

Trie也是可以的,参考https://leetcode.com/problems/number-of-valid-words-for-each-puzzle/discuss/371944/Python-Trie-O(km%2Bn)

基于python实现的粒子群的VRP(车辆配送路径规划)问题建模求解+源码+项目文档+算法解析,适合毕业设计、课程设计、项目开发。项目源码已经过严格测试,可以放心参考并在此基础上延申使用,详情见md文档 算法设计的关键在于如何向表现较好的个体学习,标准粒子群算法引入惯性因子w、自我认知因子c1、社会认知因子c2分别作为自身、当代最优解和历史最优解的权重,指导粒子速度和位置的更新,这在求解函数极值问题时比较容易实现,而在VRP问题上,速度位置的更新则难以直接采用加权的方式进行,一个常见的方法是采用基于遗传算法交叉算子的混合型粒子群算法进行求解,这里采用顺序交叉算子,对惯性因子w、自我认知因子c1、社会认知因子c2则以w/(w+c1+c2),c1/(w+c1+c2),c2/(w+c1+c2)的概率接受粒子本身、当前最优解、全局最优解交叉的父代之一(即按概率选择其中一个作为父代,不加权)。 算法设计的关键在于如何向表现较好的个体学习,标准粒子群算法引入惯性因子w、自我认知因子c1、社会认知因子c2分别作为自身、当代最优解和历史最优解的权重,指导粒子速度和位置的更新,这在求解函数极值问题时比较容易实现,而在VRP问题上,速度位置的更新则难以直接采用加权的方式进行,一个常见的方法是采用基于遗传算法交叉算子的混合型粒子群算法进行求解,这里采用顺序交叉算子,对惯性因子w、自我认知因子c1、社会认知因子c2则以w/(w+c1+c2),c1/(w+c1+c2),c2/(w+c1+c2)的概率接受粒子本身、当前最优解、全局最优解交叉的父代之一(即按概率选择其中一个作为父代,不加权)。
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