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@ -4,14 +4,18 @@
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package chapter_dynamic_programming
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import "math"
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/* 爬楼梯最小代价:动态规划 */
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func minCostClimbingStairsDP(cost []int) int {
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n := len(cost) - 1
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if n == 1 || n == 2 {
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return cost[n]
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}
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min := func(a, b int) int {
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if a < b {
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return a
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}
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return b
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}
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// 初始化 dp 表,用于存储子问题的解
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dp := make([]int, n+1)
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// 初始状态:预设最小子问题的解
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@ -19,7 +23,7 @@ func minCostClimbingStairsDP(cost []int) int {
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dp[2] = cost[2]
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// 状态转移:从较小子问题逐步求解较大子问题
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for i := 3; i <= n; i++ {
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dp[i] = int(math.Min(float64(dp[i-1]), float64(dp[i-2]+cost[i])))
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dp[i] = min(dp[i-1], dp[i-2]) + cost[i]
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}
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return dp[n]
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}
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@ -30,12 +34,18 @@ func minCostClimbingStairsDPComp(cost []int) int {
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if n == 1 || n == 2 {
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return cost[n]
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}
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min := func(a, b int) int {
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if a < b {
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return a
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}
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return b
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}
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// 初始状态:预设最小子问题的解
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a, b := cost[1], cost[2]
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// 状态转移:从较小子问题逐步求解较大子问题
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for i := 3; i <= n; i++ {
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tmp := b
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b = int(math.Min(float64(a), float64(tmp+cost[i])))
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b = min(a, tmp) + cost[i]
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a = tmp
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}
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return b
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