yetao
/
hello-algo
mirror of https://github.com/krahets/hello-algo.git
1
0
Fork 0
Code Issues Packages Projects Releases Wiki Activity

fix(csharp): fix csharp method name in knapsack (#592)

Browse Source 
* fix(csharp): fix csharp method name in knapsack

* feat(csharp): add csharp code for min path sum

* move INF define into method

* change INF to int max value
pull/594/head
hpstory 1 year ago committed by GitHub
parent 459449d41a
commit 5ea016816a
No known key found for this signature in database
GPG Key ID: 4AEE18F83AFDEB23
2 changed files with 138 additions and 14 deletions
Show Stats Download Patch File Download Diff File

28
codes/csharp/chapter_dynamic_programming/knapsack.cs
Unescape View File

@ -8,24 +8,24 @@ namespace hello_algo.chapter_dynamic_programming;
public class knapsack {
/* 0-1 背包：暴力搜索 */
public int knapsack_dfs(int[] weight, int[] val, int i, int c) {
public int knapsackDFS(int[] weight, int[] val, int i, int c) {
// 若已选完所有物品或背包无容量，则返回价值 0
if (i == 0 || c == 0) {
return 0;
}
// 若超过背包容量，则只能不放入背包
if (weight[i - 1] > c) {
return knapsack_dfs(weight, val, i - 1, c);
return knapsackDFS(weight, val, i - 1, c);
}
// 计算不放入和放入物品 i 的最大价值
int no = knapsack_dfs(weight, val, i - 1, c);
int yes = knapsack_dfs(weight, val, i - 1, c - weight[i - 1]) + val[i - 1];
int no = knapsackDFS(weight, val, i - 1, c);
int yes = knapsackDFS(weight, val, i - 1, c - weight[i - 1]) + val[i - 1];
// 返回两种方案中价值更大的那一个
return Math.Max(no, yes);
}
/* 0-1 背包：记忆化搜索 */
public int knapsack_dfs_mem(int[] weight, int[] val, int[][] mem, int i, int c) {
public int knapsackDFSMem(int[] weight, int[] val, int[][] mem, int i, int c) {
// 若已选完所有物品或背包无容量，则返回价值 0
if (i == 0 || c == 0) {
return 0;
@ -36,18 +36,18 @@ public class knapsack {
}
// 若超过背包容量，则只能不放入背包
if (weight[i - 1] > c) {
return knapsack_dfs_mem(weight, val, mem, i - 1, c);
return knapsackDFSMem(weight, val, mem, i - 1, c);
}
// 计算不放入和放入物品 i 的最大价值
int no = knapsack_dfs_mem(weight, val, mem, i - 1, c);
int yes = knapsack_dfs_mem(weight, val, mem, i - 1, c - weight[i - 1]) + val[i - 1];
int no = knapsackDFSMem(weight, val, mem, i - 1, c);
int yes = knapsackDFSMem(weight, val, mem, i - 1, c - weight[i - 1]) + val[i - 1];
// 记录并返回两种方案中价值更大的那一个
mem[i][c] = Math.Max(no, yes);
return mem[i][c];
}
/* 0-1 背包：动态规划 */
public int knapsack_dp(int[] weight, int[] val, int cap) {
public int knapsackDP(int[] weight, int[] val, int cap) {
int n = weight.Length;
// 初始化 dp 表
int[,] dp = new int[n + 1, cap + 1];
@ -67,7 +67,7 @@ public class knapsack {
}
/* 0-1 背包：状态压缩后的动态规划 */
public int knapsack_dp_comp(int[] weight, int[] val, int cap) {
public int knapsackDPComp(int[] weight, int[] val, int cap) {
int n = weight.Length;
// 初始化 dp 表
int[] dp = new int[cap + 1];
@ -95,7 +95,7 @@ public class knapsack {
int n = weight.Length;
// 暴力搜索
Console.WriteLine(knapsack_dfs(weight, val, n, cap));
Console.WriteLine(knapsackDFS(weight, val, n, cap));
// 记忆化搜索
int[][] mem = new int[n + 1][];
@ -104,12 +104,12 @@ public class knapsack {
Array.Fill(mem[i], -1);
}
Console.WriteLine(knapsack_dfs_mem(weight, val, mem, n, cap));
Console.WriteLine(knapsackDFSMem(weight, val, mem, n, cap));
// 动态规划
Console.WriteLine(knapsack_dp(weight, val, cap));
Console.WriteLine(knapsackDP(weight, val, cap));
// 状态压缩后的动态规划
Console.WriteLine(knapsack_dp_comp(weight, val, cap));
Console.WriteLine(knapsackDPComp(weight, val, cap));
}
}

124
codes/csharp/chapter_dynamic_programming/min_path_sum.cs
Unescape View File

@ -0,0 +1,124 @@
/**
* File: min_path_sum.cs
* Created Time: 2023-07-10
* Author: hpstory (hpstory1024@163.com)
*/
namespace hello_algo.chapter_dynamic_programming;
public class min_path_sum {
/* 最小路径和：暴力搜索 */
public int minPathSumDFS(int[][] grid, int i, int j) {
// 若为左上角单元格，则终止搜索
if (i == 0 && j == 0){
return grid[0][0];
}
// 若行列索引越界，则返回 +∞ 代价
if (i < 0 || j < 0) {
return int.MaxValue;
}
// 计算从左上角到 (i-1, j) 和 (i, j-1) 的最小路径代价
int left = minPathSumDFS(grid, i - 1, j);
int up = minPathSumDFS(grid, i, j - 1);
// 返回从左上角到 (i, j) 的最小路径代价
return Math.Min(left, up) + grid[i][j];
}
/* 最小路径和：记忆化搜索 */
public int minPathSumDFSMem(int[][] grid, int[][] mem, int i, int j) {
// 若为左上角单元格，则终止搜索
if (i == 0 && j == 0) {
return grid[0][0];
}
// 若行列索引越界，则返回 +∞ 代价
if (i < 0 || j < 0) {
return int.MaxValue;
}
// 若已有记录，则直接返回
if (mem[i][j] != -1) {
return mem[i][j];
}
// 左边和上边单元格的最小路径代价
int left = minPathSumDFSMem(grid, mem, i - 1, j);
int up = minPathSumDFSMem(grid, mem, i, j - 1);
// 记录并返回左上角到 (i, j) 的最小路径代价
mem[i][j] = Math.Min(left, up) + grid[i][j];
return mem[i][j];
}
/* 最小路径和：动态规划 */
public int minPathSumDP(int[][] grid) {
int n = grid.Length, m = grid[0].Length;
// 初始化 dp 表
int[,] dp = new int[n, m];
dp[0, 0] = grid[0][0];
// 状态转移：首行
for (int j = 1; j < m; j++) {
dp[0, j] = dp[0, j - 1] + grid[0][j];
}
// 状态转移：首列
for (int i = 1; i < n; i++) {
dp[i, 0] = dp[i - 1, 0] + grid[i][0];
}
// 状态转移：其余行列
for (int i = 1; i < n; i++) {
for (int j = 1; j < m; j++) {
dp[i, j] = Math.Min(dp[i, j - 1], dp[i - 1, j]) + grid[i][j];
}
}
return dp[n - 1, m - 1];
}
/* 最小路径和：状态压缩后的动态规划 */
public int minPathSumDPComp(int[][] grid) {
int n = grid.Length, m = grid[0].Length;
// 初始化 dp 表
int[] dp = new int[m];
dp[0] = grid[0][0];
// 状态转移：首行
for (int j = 1; j < m; j++) {
dp[j] = dp[j - 1] + grid[0][j];
}
// 状态转移：其余行
for (int i = 1; i < n; i++) {
// 状态转移：首列
dp[0] = dp[0] + grid[i][0];
// 状态转移：其余列
for (int j = 1; j < m; j++) {
dp[j] = Math.Min(dp[j - 1], dp[j]) + grid[i][j];
}
}
return dp[m - 1];
}
[Test]
public void Test() {
int[][] grid =
{
new int[4] { 1, 3, 1, 5 },
new int[4] { 2, 2, 4, 2 },
new int[4] { 5, 3, 2, 1 },
new int[4] { 4, 3, 5, 2 }
};
int n = grid.Length, m = grid[0].Length;
// 暴力搜索
Console.WriteLine(minPathSumDFS(grid, n - 1, m - 1));
// 记忆化搜索
int[][] mem = new int[n][];
for (int i = 0; i < n; i++) {
mem[i] = new int[m];
Array.Fill(mem[i], -1);
}
Console.WriteLine(minPathSumDFSMem(grid, mem, n - 1, m - 1));
// 动态规划
Console.WriteLine(minPathSumDP(grid));
// 状态压缩后的动态规划
Console.WriteLine(minPathSumDPComp(grid));
}
}
Write Preview
Loading…
Cancel
Save