Leetcode #1243: Array Transformation
In this guide, we solve Leetcode #1243 Array Transformation in Python and focus on the core idea that makes the solution efficient.
You will see the intuition, the step-by-step method, and a clean Python implementation you can use in interviews.
Problem Statement
Given an initial array arr, every day you produce a new array using the array of the previous day. On the i-th day, you do the following operations on the array of day i-1 to produce the array of day i: If an element is smaller than both its left neighbor and its right neighbor, then this element is incremented.
Quick Facts
- Difficulty: Easy
- Premium: Yes
- Tags: Array, Simulation
Intuition
The rules are explicit, so simulating the process step by step is safest.
Careful state updates prevent subtle bugs.
Approach
Translate the rules into state updates and apply them in order.
Track the final state or aggregate as required.
Steps:
- Translate rules into state updates.
- Iterate for each step.
- Return the final state.
Example
Input: arr = [6,2,3,4]
Output: [6,3,3,4]
Explanation:
On the first day, the array is changed from [6,2,3,4] to [6,3,3,4].
No more operations can be done to this array.
Python Solution
class Solution:
def transformArray(self, arr: List[int]) -> List[int]:
f = True
while f:
f = False
t = arr[:]
for i in range(1, len(t) - 1):
if t[i] > t[i - 1] and t[i] > t[i + 1]:
arr[i] -= 1
f = True
if t[i] < t[i - 1] and t[i] < t[i + 1]:
arr[i] += 1
f = True
return arr
Complexity
The time complexity is , and the space complexity is . The space complexity is .
Edge Cases and Pitfalls
Watch for boundary values, empty inputs, and duplicate values where applicable. If the problem involves ordering or constraints, confirm the invariant is preserved at every step.
Summary
This Python solution focuses on the essential structure of the problem and keeps the implementation interview-friendly while meeting the constraints.