【LeetCode-233】Number of Digit One

一看到这道题就想到了动态规划,但是tle了,先看看我的python代码吧!

class Solution(object):
    # 最容易想到的方法了(动态规划),但是tle了
    def countDigitOne(self, n):
        """
        :type n: int
        :rtype: int
        """
        if n < 1:
            return 0

        assist = [0 for i in range(n + 1)]

        assist[1] = 1

        for i in range(10,n + 1):
            assist[i] = assist[i // 10] + assist[i % 10]

        return sum(assist)

后来实在不会了,发现了别人的优秀代码

public class Solution {
    /**
     * 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).  
     * 例子: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);
     * 
     */
    public int countDigitOne(int n) {  
        int ones = 0;  
        for (long m = 1; m <= n; m *= 10) {  
            long a = n / m, b = n % m;  
            ones += (a + 8) / 10 * m;  
            if(a % 10 == 1) 
                ones += b + 1;  
        }  
        return ones;  
    }  
}


### 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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