120.Triangle:修订间差异
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=Description= | =Description= | ||
{{LeetCode|id=triangle}} | {{LeetCode|id=triangle no=120 title=Triangle}} | ||
Given a triangle array, return the minimum path sum from top to bottom. | Given a triangle array, return the minimum path sum from top to bottom. |
2023年9月23日 (六) 05:08的版本
Description
#{{{no}}} | no=120 title=Triangle {{{title}}} | {{{difficulty}}} | ||
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{{{category}}} | {{{collection}}} | |||
{{{summary}}} |
Given a triangle array, return the minimum path sum from top to bottom.
For each step, you may move to an adjacent number of the row below. More formally, if you are on index i on the current row, you may move to either index i or index i + 1 on the next row.
Example 1:
Input: triangle = [[2],[3,4],[6,5,7],[4,1,8,3]]
Output: 11
Explanation: The triangle looks like:
2
3 4
6 5 7
4 1 8 3
The minimum path sum from top to bottom is 2 + 3 + 5 + 1 = 11 (underlined above).
Example 2:
Input: triangle = [[-10]]
Output: -10
Solution
First attampt
It works, but not good, especially memory.
- Runtime 3 ms
- Beats 65.79%
- Memory 44.4 MB
- Beats 13.95%
class Solution {
public int minimumTotal(List<List<Integer>> triangle) {
int maxRowSize = triangle.get(triangle.size() -1).size();
// create an array nxn to store the minimal distance that starts from triangle[i][j]
int[][] dp = new int[maxRowSize][maxRowSize];
for(int i = triangle.size() -1; i >=0; i--) {
List<Integer> row = triangle.get(i);
for(int j = 0; j < row.size(); j++) {
if(i < dp.length -1) {
// calculate minimal distance and update
dp[i][j] = Math.min(dp[i+1][j], dp[i+1][j+1]) + row.get(j);
} else {
// for the bottom line, there's no subpaths
dp[i][j] = row.get(j);
}
}
}
return dp[0][0];
}
}
Memory Optimization
class Solution {
public int minimumTotal(List<List<Integer>> triangle) {
int maxRowSize = triangle.get(triangle.size() -1).size();
// 只需要记录上一次的最短路径
int[] dp = new int[maxRowSize];
for(int i = triangle.size() -1; i >=0; i--) {
List<Integer> row = triangle.get(i);
for(int j = 0; j < row.size(); j++) {
if(i < dp.length -1) {
// 从左到右更新,正好计算右边的元素时,当前的值已经不需要用到了。所以可以直接更新
dp[j] = Math.min(dp[j], dp[j+1]) + row.get(j);
} else {
dp[j] = row.get(j);
}
}
}
return dp[0];
}
}