题目:
Given n non-negative integers representing an elevation map where the width of each bar is 1, compute how much water it is able to trap after raining.
For example,
Given [0,1,0,2,1,0,1,3,2,1,2,1], return 6.
The above elevation map is represented by array [0,1,0,2,1,0,1,3,2,1,2,1]. In this case, 6 units of rain water (blue section) are being trapped. Thanks Marcos for contributing this image!
解法一:
这道收集雨水的题跟之前的那道 Largest Rectangle in Histogram 直方图中最大的矩形 有些类似,但是又不太一样,我们先来看一种方法,这种方法是基于动态规划Dynamic Programming的,我们维护一个一维的dp数组,这个DP算法需要遍历两遍数组,第一遍遍历dp[i]中存入i位置左边的最大值,然后开始第二遍遍历数组,第二次遍历时找右边最大值,然后和左边最大值比较取其中的较小值,然后跟当前值A[i]相比,如果大于当前值,则将差值存入结果。
class Solution {
public:
int trap(vector& height) {
int res = 0, mx = 0, n = height.size();
vector dp(n, 0);
for (int i = 0; i < n; ++i) {
dp[i] = mx;
mx = max(mx, height[i]);
}
mx = 0;
for (int i = n - 1; i >= 0; --i) {
dp[i] = min(dp[i], mx);
mx = max(mx, height[i]);
if (dp[i] > height[i]) res += dp[i] - height[i];
}
return res;
}
};
最后我们来看一种只需要遍历一次即可的解法,这个算法需要left和right两个指针分别指向数组的首尾位置,从两边向中间扫描,在当前两指针确定的范围内,先比较两头找出较小值,如果较小值是left指向的值,则从左向右扫描,如果较小值是right指向的值,则从右向左扫描,若遇到的值比当较小值小,则将差值存入结果,如遇到的值大,则重新确定新的窗口范围,以此类推直至left和right指针重合。
解法二:
class Solution {
public:
int trap(vector& height) {
int res = 0, l = 0, r = height.size() - 1;
while (l < r) {
int mn = min(height[l], height[r]);
if (mn == height[l]) {
++l;
while (l < r && height[l] < mn) {
res += mn - height[l++];
}
} else {
--r;
while (l < r && height[r] < mn) {
res += mn - height[r--];
}
}
}
return res;
}
};