Description
https://leetcode.com/problems/triangle/
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
Constraints:
1 <= triangle.length <= 200
triangle[0].length == 1
triangle[i].length == triangle[i - 1].length + 1
-104 <= triangle[i][j] <= 104
Follow up: Could you do this using only O(n)
extra space, where n
is the total number of rows in the triangle?
Explanation
Track the minimum path sum at each element. At each row, the j th element’s minimum path sum could either get from the previous row j – 1 element or j – 1 element.
Python Solution
class Solution:
def minimumTotal(self, triangle: List[List[int]]) -> int:
if not triangle or not triangle[0]:
return -1
n = len(triangle)
dp = [[0] * (i + 1) for i in range(n)]
dp[0][0] = triangle[0][0]
for i in range(1, n):
dp[i][0] = dp[i - 1][0] + triangle[i][0]
dp[i][i] = dp[i - 1][i - 1] + triangle[i][i]
for j in range(1, i):
dp[i][j] = min(dp[i - 1][j - 1], dp[i - 1][j]) + triangle[i][j]
return min(dp[n - 1])
- Time Complexity: O(N^2).
- Space Complexity: O(N^2).