# [Solved] On a 2D plane, there are n points with integer coordinates points[i] = [xi, yi]. Return the minimum time in seconds to visit all the points in the order given by points.

## Question

On a 2D plane, there are `n` points with integer coordinates `points[i] = [xi, yi]`. Return the minimum time in seconds to visit all the points in the order given by `points`.

You can move according to these rules:

• In `1` second, you can either:
• move vertically by one unit,
• move horizontally by one unit, or
• move diagonally `sqrt(2)` units (in other words, move one unit vertically then one unit horizontally in `1` second).
• You have to visit the points in the same order as they appear in the array.
• You are allowed to pass through points that appear later in the order, but these do not count as visits.

Example 1:

```Input: points = [[1,1],[3,4],[-1,0]]
Output: 7
Explanation: One optimal path is [1,1] -> [2,2] -> [3,3] -> [3,4] -> [2,3] -> [1,2] -> [0,1] -> [-1,0]
Time from [1,1] to [3,4] = 3 seconds
Time from [3,4] to [-1,0] = 4 seconds
Total time = 7 seconds```

Example 2:

```Input: points = [[3,2],[-2,2]]
Output: 5
```

Constraints:

• `points.length == n`
• `1 <= n <= 100`
• `points[i].length == 2`
• `-1000 <= points[i], points[i] <= 1000`

## Python Solution

```class Solution:
def minTimeToVisitAllPoints(self, points: List[List[int]]) -> int:
ans = 0
for i in range(1, len(points)):
prev, cur = points[i - 1 : i + 1]
ans += max(map(abs, (prev - cur, prev - cur)))
return ans   ``` ##### Abhishek Sharma

Started my Data Science journey in my 2nd year of college and since then continuously into it because of the magical powers of ML and continuously doing projects in almost every domain of AI like ML, DL, CV, NLP.

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