1. Question
Givennnon-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]
, return6
.
2. Implementation
(1) Two Pointers
class Solution {
public int trap(int[] height) {
if (height == null || height.length <= 1) {
return 0;
}
int left = 0, right = height.length - 1;
int leftMaxHeight = height[left], rightMaxHeight = height[right];
int res = 0;
while (left < right) {
if (height[left] < height[right]) {
++left;
leftMaxHeight = Math.max(leftMaxHeight, height[left]);
res += leftMaxHeight - height[left];
}
else {
--right;
rightMaxHeight = Math.max(rightMaxHeight, height[right]);
res += rightMaxHeight - height[right];
}
}
return res;
}
}
(2) Monotone Stack
思路:(1) 凹陷处可以积水。所以寻找先递减后递增的位置就可以了
(2) 维护一个单调递减的Stack,当heights[stack.peek()] <= heights[i], 找到凹陷处,出栈,计算可蓄水的体积
(3) 计算体积时,以bottomIndex作为中点,向两边找出比它高的bar(corner case: 如果此时stack为空,则无法找到左边的bar)
class Solution {
public int trap(int[] height) {
Stack<Integer> stack = new Stack<>();
int res = 0, water = 0;
for (int i = 0; i < height.length; i++) {
while (!stack.isEmpty() && height[stack.peek()] <= height[i]) {
int bottomIndex = stack.pop();
if (stack.isEmpty()) {
water = 0;
}
else {
int width = i - stack.peek() - 1;
int h = Math.min(height[stack.peek()], height[i]) - height[bottomIndex];
water = width * h;
}
res += water;
}
stack.push(i);
}
return res;
}
}
3. Time & Space Complexity
Two Pointers: 时间复杂度O(n), 空间复杂度O(1)
Monotone Stack: 时间复杂度O(n), 空间复杂度O(n)