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fix(csharp): Modify method name to PascalCase, simplify new expression (#840)

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* Modify method name to PascalCase(array and linked list)

* Modify method name to PascalCase(backtracking)

* Modify method name to PascalCase(computational complexity)

* Modify method name to PascalCase(divide and conquer)

* Modify method name to PascalCase(dynamic programming)

* Modify method name to PascalCase(graph)

* Modify method name to PascalCase(greedy)

* Modify method name to PascalCase(hashing)

* Modify method name to PascalCase(heap)

* Modify method name to PascalCase(searching)

* Modify method name to PascalCase(sorting)

* Modify method name to PascalCase(stack and queue)

* Modify method name to PascalCase(tree)

* local check
This commit is contained in:
hpstory
2023-10-08 01:33:46 +08:00
committed by GitHub
parent 6f7e768cb7
commit f62256bee1
129 changed files with 1186 additions and 1192 deletions
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28
codes/csharp/chapter_dynamic_programming/knapsack.cs
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@ -8,24 +8,24 @@ namespace hello_algo.chapter_dynamic_programming;
public class knapsack {
/* 0-1 背包：暴力搜索 */
public int knapsackDFS(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 knapsackDFS(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 = knapsackDFS(weight, val, i - 1, c);
int yes = knapsackDFS(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 knapsackDFSMem(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 knapsackDFSMem(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 = knapsackDFSMem(weight, val, mem, i - 1, c);
int yes = knapsackDFSMem(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 knapsackDP(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：空间优化后的动态规划 */
public int knapsackDPComp(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
int res = knapsackDFS(weight, val, n, cap);
int res = KnapsackDFS(weight, val, n, cap);
Console.WriteLine("不超过背包容量的最大物品价值为 " + res);
// 记忆化搜索
@ -104,15 +104,15 @@ public class knapsack {
mem[i] = new int[cap + 1];
Array.Fill(mem[i], -1);
}
res = knapsackDFSMem(weight, val, mem, n, cap);
res = KnapsackDFSMem(weight, val, mem, n, cap);
Console.WriteLine("不超过背包容量的最大物品价值为 " + res);
// 动态规划
res = knapsackDP(weight, val, cap);
res = KnapsackDP(weight, val, cap);
Console.WriteLine("不超过背包容量的最大物品价值为 " + res);
// 空间优化后的动态规划
res = knapsackDPComp(weight, val, cap);
res = KnapsackDPComp(weight, val, cap);
Console.WriteLine("不超过背包容量的最大物品价值为 " + res);
}
}