
方法一:动态规划
java
class Solution {
public int trap(int[] height) {
int n = height.length;
if (n == 0) {
return 0;
}
int[] leftMax = new int[n];
leftMax[0] = height[0];
for (int i = 1; i < n; ++i) {
leftMax[i] = Math.max(leftMax[i - 1], height[i]);
}//索引i左边的最大高度
int[] rightMax = new int[n];
rightMax[n - 1] = height[n - 1];
for (int i = n - 2; i >= 0; --i) {
rightMax[i] = Math.max(rightMax[i + 1], height[i]);
}索引i右边的最大高度
int ans = 0;
for (int i = 0; i < n; ++i) {
ans += Math.min(leftMax[i], rightMax[i]) - height[i];
}//每次计算i索引处的雨水量
return ans;
}
}
方法二:单调栈
java
class Solution {
public int trap(int[] height) {
int ans = 0;
Deque<Integer> stack = new LinkedList<Integer>();
int n = height.length;
for (int i = 0; i < n; ++i) {
while (!stack.isEmpty() && height[i] > height[stack.peek()]) {//i为"凹"的右边
int top = stack.pop();//这是"凹"的底部
if (stack.isEmpty()) {
break;
}
int left = stack.peek();//这是"凹"的左边
int currWidth = i - left - 1;
int currHeight = Math.min(height[left], height[i]) - height[top];
ans += currWidth * currHeight;
}
stack.push(i);
}
return ans;
}
}
方法三:双指针
java
class Solution {
public int trap(int[] height) {
int ans = 0;
int left = 0, right = height.length - 1;
int leftMax = 0, rightMax = 0;
while (left < right) {
leftMax = Math.max(leftMax, height[left]);
rightMax = Math.max(rightMax, height[right]);
if (height[left] < height[right]) {
ans += leftMax - height[left];
++left;
} else {
ans += rightMax - height[right];
--right;
}
}//left和right两边向内叠加
return ans;
}
}

方法:滑动窗口
java
class Solution {
public int lengthOfLongestSubstring(String s) {
// 哈希集合,记录每个字符是否出现过
Set<Character> occ = new HashSet<Character>();
int n = s.length();
// 右指针,初始值为 -1,相当于我们在字符串的左边界的左侧,还没有开始移动
int rk = -1, ans = 0;
for (int i = 0; i < n; ++i) {
if (i != 0) {
// 左指针向右移动一格,移除一个字符
occ.remove(s.charAt(i - 1));
}
while (rk + 1 < n && !occ.contains(s.charAt(rk + 1))) {
// 不断地移动右指针
occ.add(s.charAt(rk + 1));
++rk;
}
// 第 i 到 rk 个字符是一个极长的无重复字符子串
ans = Math.max(ans, rk - i + 1);
}
return ans;
}
}