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110
leetcode/0509.Fibonacci-Number/509. Fibonacci Number.go
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110
leetcode/0509.Fibonacci-Number/509. Fibonacci Number.go
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package leetcode
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import "math"
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// 解法一 递归法 时间复杂度 O(2^n),空间复杂度 O(n)
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func fib(N int) int {
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if N <= 1 {
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return N
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}
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return fib(N-1) + fib(N-2)
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}
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// 解法二 自底向上的记忆化搜索 时间复杂度 O(n),空间复杂度 O(n)
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func fib1(N int) int {
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if N <= 1 {
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return N
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}
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cache := map[int]int{0: 0, 1: 1}
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for i := 2; i <= N; i++ {
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cache[i] = cache[i-1] + cache[i-2]
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}
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return cache[N]
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}
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// 解法三 自顶向下的记忆化搜索 时间复杂度 O(n),空间复杂度 O(n)
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func fib2(N int) int {
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if N <= 1 {
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return N
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}
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return memoize(N, map[int]int{0: 0, 1: 1})
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}
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func memoize(N int, cache map[int]int) int {
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if _, ok := cache[N]; ok {
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return cache[N]
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}
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cache[N] = memoize(N-1, cache) + memoize(N-2, cache)
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return memoize(N, cache)
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}
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// 解法四 优化版的 dp,节约内存空间 时间复杂度 O(n),空间复杂度 O(1)
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func fib3(N int) int {
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if N <= 1 {
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return N
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}
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if N == 2 {
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return 1
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}
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current, prev1, prev2 := 0, 1, 1
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for i := 3; i <= N; i++ {
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current = prev1 + prev2
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prev2 = prev1
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prev1 = current
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}
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return current
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}
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// 解法五 矩阵快速幂 时间复杂度 O(log n),空间复杂度 O(log n)
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// | 1 1 | ^ n = | F(n+1) F(n) |
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// | 1 0 | | F(n) F(n-1) |
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func fib4(N int) int {
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if N <= 1 {
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return N
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}
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var A = [2][2]int{
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{1, 1},
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{1, 0},
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}
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A = matrixPower(A, N-1)
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return A[0][0]
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}
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func matrixPower(A [2][2]int, N int) [2][2]int {
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if N <= 1 {
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return A
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}
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A = matrixPower(A, N/2)
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A = multiply(A, A)
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var B = [2][2]int{
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{1, 1},
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{1, 0},
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}
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if N%2 != 0 {
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A = multiply(A, B)
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}
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return A
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}
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func multiply(A [2][2]int, B [2][2]int) [2][2]int {
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x := A[0][0]*B[0][0] + A[0][1]*B[1][0]
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y := A[0][0]*B[0][1] + A[0][1]*B[1][1]
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z := A[1][0]*B[0][0] + A[1][1]*B[1][0]
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w := A[1][0]*B[0][1] + A[1][1]*B[1][1]
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A[0][0] = x
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A[0][1] = y
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A[1][0] = z
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A[1][1] = w
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return A
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}
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// 解法六 公式法 f(n)=(1/√5)*{[(1+√5)/2]^n -[(1-√5)/2]^n},用 时间复杂度在 O(log n) 和 O(n) 之间,空间复杂度 O(1)
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// 经过实际测试,会发现 pow() 系统函数比快速幂慢,说明 pow() 比 O(log n) 慢
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// 斐波那契数列是一个自然数的数列,通项公式却是用无理数来表达的。而且当 n 趋向于无穷大时,前一项与后一项的比值越来越逼近黄金分割 0.618(或者说后一项与前一项的比值小数部分越来越逼近 0.618)。
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// 斐波那契数列用计算机计算的时候可以直接用四舍五入函数 Round 来计算。
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func fib5(N int) int {
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var goldenRatio float64 = float64((1 + math.Sqrt(5)) / 2)
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return int(math.Round(math.Pow(goldenRatio, float64(N)) / math.Sqrt(5)))
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}
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53
leetcode/0509.Fibonacci-Number/509. Fibonacci Number_test.go
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53
leetcode/0509.Fibonacci-Number/509. Fibonacci Number_test.go
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package leetcode
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import (
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"fmt"
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"testing"
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)
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type question509 struct {
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para509
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ans509
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}
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// para 是参数
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// one 代表第一个参数
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type para509 struct {
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one int
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}
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// ans 是答案
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// one 代表第一个答案
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type ans509 struct {
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one int
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}
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func Test_Problem509(t *testing.T) {
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qs := []question509{
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question509{
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para509{1},
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ans509{1},
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},
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question509{
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para509{2},
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ans509{1},
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},
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question509{
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para509{3},
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ans509{2},
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},
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// 如需多个测试,可以复制上方元素。
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}
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fmt.Printf("------------------------Leetcode Problem 509------------------------\n")
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for _, q := range qs {
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_, p := q.ans509, q.para509
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fmt.Printf("【input】:%v 【output】:%v\n", p, fib(p.one))
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}
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fmt.Printf("\n\n\n")
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}
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53
leetcode/0509.Fibonacci-Number/README.md
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53
leetcode/0509.Fibonacci-Number/README.md
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# [509. Fibonacci Number](https://leetcode.com/problems/fibonacci-number/)
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## 题目:
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The **Fibonacci numbers**, commonly denoted `F(n)` form a sequence, called the **Fibonacci sequence**, such that each number is the sum of the two preceding ones, starting from `0` and `1`. That is,
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F(0) = 0, F(1) = 1
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F(N) = F(N - 1) + F(N - 2), for N > 1.
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Given `N`, calculate `F(N)`.
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**Example 1:**
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Input: 2
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Output: 1
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Explanation: F(2) = F(1) + F(0) = 1 + 0 = 1.
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**Example 2:**
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Input: 3
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Output: 2
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Explanation: F(3) = F(2) + F(1) = 1 + 1 = 2.
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**Example 3:**
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Input: 4
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Output: 3
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Explanation: F(4) = F(3) + F(2) = 2 + 1 = 3.
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**Note:**
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0 ≤ `N` ≤ 30.
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## 题目大意
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斐波那契数,通常用 F(n) 表示,形成的序列称为斐波那契数列。该数列由 0 和 1 开始,后面的每一项数字都是前面两项数字的和。也就是:
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```
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F(0) = 0, F(1) = 1
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F(N) = F(N - 1) + F(N - 2), 其中 N > 1.
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```
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给定 N,计算 F(N)。
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提示:0 ≤ N ≤ 30
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## 解题思路
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- 求斐波那契数列
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- 这一题解法很多,大的分类是四种,递归,记忆化搜索(dp),矩阵快速幂,通项公式。其中记忆化搜索可以写 3 种方法,自底向上的,自顶向下的,优化空间复杂度版的。通项公式方法实质是求 a^b 这个还可以用快速幂优化时间复杂度到 O(log n) 。
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