标签:leetcode
Given an array of n integers where n > 1, nums, return an array output such that output[i] is equal to the product of all the elements of nums except nums[i].
Solve it without division and in O(n).
For example, given [1,2,3,4], return [24,12,8,6].
Follow up:
Could you solve it with constant space complexity? (Note: The output array does not count as extra space for the purpose of space complexity analysis.)
题目比较好理解,但是有几个关键点这里需要明确一下:
我们以一个4个元素的数组为例,nums=[a1, a2, a3, a4]。
想在O(n)时间复杂度完成最终的数组输出,res=[a2*a3*a4, a1*a3*a4, a1*a2*a4, a2*a3*a4]。
比较好的解决方法是构造两个数组相乘:
这样思路是不是清楚了很多,而且这两个数组我们是比较好构造的。
AC代码如下:
public int[] productExceptSelf(int[] nums) {
int len = nums.length;
int[] pSeq = new int[nums.length];
int[] nSeq = new int[nums.length];
pSeq[0] = 1;
for (int i = 1; i < len; i ++) {
pSeq[i] = pSeq[i - 1] * nums[i - 1];
}
nSeq[len - 1] = 1;
for (int i = len - 2; i >= 0; i --) {
nSeq[i] = nSeq[i + 1] * nums[i + 1];
}
for (int i = 0; i < len; i ++) {
pSeq[i] *= nSeq[i];
}
return pSeq;
}
但是,上面的空间复杂度为O(N),不满足常数时间复杂度。我们可以对上面的代码进行空间优化,用一个常数p来保存每次计算的结果值。
优化AC代码:
int len = nums.length, p;
int[] arr = new int[nums.length];
arr[0] = p = 1;
for (int i = 1; i < len; i ++) {
p = p * nums[i - 1];
arr[i] = p;
}
p = 1;
for (int i = len - 2; i >= 0; i --) {
p = p * nums[i + 1];
arr[i] *= p;
}
return arr;
本以为这样就已经很不错了,但是在discuss讨论区发现了一个特别牛逼的递归解法,非常精妙,这里分享给大家。
public int[] productExceptSelfRev(int[] nums) {
multiply(nums, 1, 0, nums.length);
return nums;
}
private int multiply(int[] a, int fwdProduct, int indx, int N) {
int revProduct = 1;
if (indx < N) {
revProduct = multiply(a, fwdProduct * a[indx], indx + 1, N);
int cur = a[indx];
a[indx] = fwdProduct * revProduct;
revProduct *= cur;
}
return revProduct;
}
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[LeetCode]Product of Array Except Self,解题报告
标签:leetcode
原文地址:http://blog.csdn.net/wzy_1988/article/details/46916179