hello-algo/codes/go/chapter_dynamic_programming/knapsack_test.go
Reanon c1adeb2399
feat(go/dp): support dynamic programming (#622)
* feat(go/dp): support climbing stairs

* feat(go/dp): support knapsack

* feat(go/dp): coin_change & edit_distance
2023-07-24 03:08:35 +08:00

54 lines
1.3 KiB
Go

// File: knapsack_test.go
// Created Time: 2023-07-23
// Author: Reanon (793584285@qq.com)
package chapter_dynamic_programming
import (
"fmt"
"testing"
)
func TestKnapsack(t *testing.T) {
wgt := []int{10, 20, 30, 40, 50}
val := []int{50, 120, 150, 210, 240}
c := 50
n := len(wgt)
// 暴力搜索
res := knapsackDFS(wgt, val, n, c)
fmt.Printf("不超过背包容量的最大物品价值为 %d\n", res)
// 记忆化搜索
mem := make([][]int, n+1)
for i := 0; i <= n; i++ {
mem[i] = make([]int, c+1)
for j := 0; j <= c; j++ {
mem[i][j] = -1
}
}
res = knapsackDFSMem(wgt, val, mem, n, c)
fmt.Printf("不超过背包容量的最大物品价值为 %d\n", res)
// 动态规划
res = knapsackDP(wgt, val, c)
fmt.Printf("不超过背包容量的最大物品价值为 %d\n", res)
// 状态压缩后的动态规划
res = knapsackDPComp(wgt, val, c)
fmt.Printf("不超过背包容量的最大物品价值为 %d\n", res)
}
func TestUnboundedKnapsack(t *testing.T) {
wgt := []int{1, 2, 3}
val := []int{5, 11, 15}
c := 4
// 动态规划
res := unboundedKnapsackDP(wgt, val, c)
fmt.Printf("不超过背包容量的最大物品价值为 %d\n", res)
// 状态压缩后的动态规划
res = unboundedKnapsackDPComp(wgt, val, c)
fmt.Printf("不超过背包容量的最大物品价值为 %d\n", res)
}