Leetcode 233. Number of Digit One

本文详细解析了LeetCode233题“Number of Digit One”的算法思路,通过观察规律,提出了一种O(log n)的时间复杂度解法。文章以百位为例,讲解了如何计算指定位置上数字1出现的次数,并给出了Python实现代码。

题目描述:给定n,找出小于n的数字中含1的个数。

题目链接:Leetcode 233. Number of Digit One

reference: https://leetcode.com/discuss/44281/4-lines-o-log-n-c-java-python

intuitive: 每10个数, 有一个个位是1, 每100个数, 有10个十位是1, 每1000个数, 有100个百位是1. 做一个循环, 每次计算单个位上1得总个数(个位,十位, 百位).

以算百位上1为例子: 假设百位上是0, 1, 和 >=2 三种情况:

  • case 1: n=3141092, a= 31410, b=92. 计算百位上1的个数应该为 3141 *100 次.
  • case 2: n=3141192, a= 31411, b=92. 计算百位上1的个数应该为 3141 *100 + (92+1) 次.
  • case 3: n=3141592, a= 31415, b=92. 计算百位上1的个数应该为 (3141+1) *100 次.

以上三种情况可以用 一个公式概括:

(a + 8) / 10 * m + (a % 10 == 1) * (b + 1);

代码如下

class Solution:
    def countDigitOne(self, n):
        """
        :type n: int
        :rtype: int
        """
        ans = 0
        m = 1
        while(m<=n):
            a = n//m
            b = n%m
            ans += (a+8)//10 * m
            if(a%10 == 1): ans += (b+1)
            m *= 10
        return ans

参考链接

### LeetCode Problem 37: Sudoku Solver #### Problem Description The task involves solving a partially filled Sudoku puzzle. The input is represented as a two-dimensional integer array `board` where each element can be either a digit from '1' to '9' or '.' indicating empty cells. #### Solution Approach To solve this problem, one approach uses backtracking combined with depth-first search (DFS). This method tries placing numbers between 1 and 9 into every cell that contains '.', checking whether it leads to a valid solution by ensuring no conflicts arise within rows, columns, and subgrids[^6]. ```cpp void solveSudoku(vector<vector<char>>& board) { backtrack(board); } bool backtrack(vector<vector<char>> &board){ for(int row = 0; row < 9; ++row){ for(int col = 0; col < 9; ++col){ if(board[row][col] != '.') continue; for(char num='1';num<='9';++num){ if(isValidPlacement(board,row,col,num)){ placeNumber(num,board,row,col); if(backtrack(board)) return true; removeNumber(num,board,row,col); } } return false; } } return true; } ``` In the provided code snippet: - A function named `solveSudoku()` initiates the process. - Within `backtrack()`, nested loops iterate over all positions in the grid looking for unassigned spots denoted by '.' - For any such spot found, attempts are made to insert digits ranging from '1' through '9'. - Before insertion, validation checks (`isValidPlacement`) ensure compliance with Sudoku rules regarding uniqueness per row/column/subgrid constraints. - If inserting a number results in reaching a dead end without finding a complete solution, removal occurs before trying another possibility. This algorithm continues until filling out the entire board correctly or exhausting possibilities when returning failure status upward along recursive calls stack frames. --related questions-- 1. How does constraint propagation improve efficiency while solving puzzles like Sudoku? 2. Can genetic algorithms provide alternative methods for tackling similar combinatorial problems effectively? 3. What optimizations could enhance performance further beyond basic DFS/backtracking techniques used here?
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