> For the complete documentation index, see [llms.txt](https://heihei12305.gitbook.io/my-underscore/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://heihei12305.gitbook.io/my-underscore/memoized-han-shu.md).

# memoized 函数

知道算法里的动态规划不?

**动态规划**\
 **动态规划的基本思想是将待求解问题分解成若干个子问题，先求解子问题，然后从这些子问题的解得到原问题的解，其经过分解的子问题往往不是相互独立的**

* 其解依赖于子问题
* 子问题的求解是重复的
* 采用重递归出现的大量重复运算

如 Fib 数列\
&#x20;采用动态规划方法<br>

* 构造所有子问题的一个表格
* 采用自底向上的方法依次求解子问题
* 也可以采用自上而下，为避免重复运算，采用 备忘录 或称为 记忆递归 <br>

`memoized`函数使得函数能够记住其计算结果,避免大量重复计算.

```
_.memoized = (fn,hasher) => {
      //这里依旧利用闭包可以记录上下文的特性
        const lookupTable = {};

        return (key)=>{
                //为了应对多个参数的情况,可接受传入hasher自定义对象的key
                var address = hasher ? hasher.apply(this,arguments) : key;

                return lookupTable[address] || (lookupTable[address] = fn(address));
        }
}
```

示例:

```
let fc = _.memoized((n)=>{
    if(n===0){
        return 1;
    }
    return n*fc(n-1);
})

console.time(1)
console.log(fc(10));//3628800
console.timeEnd(1);//3.876ms

console.time(2);
console.log(fc(11));//39916800
console.timeEnd(2);//0.896ms
```


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