动态规划——303. Range Sum Query - Immutable[easy]

xiaoxiao2021-02-28  98

题目描述

Given an integer array nums, find the sum of the elements between indices i and j (i ≤ j), inclusive.

Example:

Given nums = [-2, 0, 3, -5, 2, -1] sumRange(0, 2) -> 1 sumRange(2, 5) -> -1 sumRange(0, 5) -> -3

Note:

You may assume that the array does not change.There are many calls to sumRange function.

给定一个数组,调用sumRange函数求某个子区间的和。

解题思路

大体思想  sumRange(i,j) = sumRange(0,j)- sumRange(0, i-1)

解法一(超时)

构造一个sum数组,存放(0,x)的和,x是全部的下标,在构造函数中计算整个sum

代码:

class NumArray { public: vector<int> sum; NumArray(vector<int> nums) { sum.resize(nums.size(), 0); for (int i = 0; i < nums.size(); i++) { for (int j = 0; j <= i; j++) sum[i] += nums[j]; } } int sumRange(int i, int j) { if (i == 0) return sum[j]; return sum[j] - sum[i - 1]; } }; /** * Your NumArray object will be instantiated and called as such: * NumArray obj = new NumArray(nums); * int param_1 = obj.sumRange(i,j); */

当数组十分巨大时,构造函数O(n^2)会很慢。

解法二:

并不先 全部计算出sum数组,有需要时才计算,也就是,当需要sum(0,x)且sum(0,x)==0时计算出sum(0,x)。因此还需要额外的数组tmp记录nums。而且随着调用sumRange次数越来越多,整个sum数组几乎被填满,此时会很快。

代码

class NumArray { public: vector<int> sum; vector<int> tmp; NumArray(vector<int> nums) { sum.resize(nums.size(), 0); tmp = nums; } int sumRange(int i, int j) { if (i == 0) { if (sum[j] == 0) { for (int p = 0; p <= j; p++) sum[j] += tmp[p]; } return sum[j]; } else { if (sum[i - 1] == 0) { for (int p = 0; p <= i - 1; p++) sum[i-1] += tmp[p]; } if (sum[j] == 0) { for (int p = 0; p <= j; p++) sum[j] += tmp[p]; } return sum[j] - sum[i - 1]; } } }; /** * Your NumArray object will be instantiated and called as such: * NumArray obj = new NumArray(nums); * int param_1 = obj.sumRange(i,j); */

(虽然ac了,可是时间是1192ms,大神们的时间是200ms左右,丢人了,丢人了,但是这道easy的通过率是28%,挺奇怪)
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