Wave Sort
Detailed guide and Python implementation for the 'Wave Sort' problem.
1. Concept Overview
The 'Wave Sort' problem is a key challenge in the Searching & Sorting section.
This implementation focuses on easy-level logic in Python.
We prioritize technical accuracy and code readability in our provided solutions.
2. Real-World Applications
3. Visual Intuition
Visualizing the logic flow for Wave Sort.
4. Prerequisites
5. Step-by-Step Thinking
1. Understand the problem
Read the problem statement for Wave Sort carefully.
2. Formulate brute force
Draft a simple iterative solution.
3. Identify inefficiency
Look for redundant calculations.
4. Optimize search path
Use hashing or sorting to speed up the process.
5. Final Implementation
Clean up the code for production standards.
Problem Statement
Write a function wave_sort(arr) that takes an array of integers arr, sorts it in ascending order, and then swaps every adjacent pair of elements starting from index 0 (i.e., swap arr[0] and arr[1], then arr[2] and arr[3], and so on) to produce a wave-sorted array satisfying the property arr[0] >= arr[1] <= arr[2] >= arr[3] <= arr[4].... Return the resulting array.
- •1 <= len(arr) <= 10^5
- •-10^9 <= arr[i] <= 10^9
Examples
wave_sort([3, 6, 5, 10, 7, 20])
[5, 3, 7, 6, 20, 10]
First, sort the array to get [3, 5, 6, 7, 10, 20]. Swapping adjacent pairs: swap 3 and 5 -> [5, 3...], swap 6 and 7 -> [..., 7, 6...], swap 10 and 20 -> [..., 20, 10]. Result is [5, 3, 7, 6, 20, 10].
wave_sort([10, 90, 49, 2, 1, 5, 23])
[2, 1, 10, 5, 49, 23, 90]
Sort array to [1, 2, 5, 10, 23, 49, 90]. Swapping adjacent pairs gives [2, 1, 10, 5, 49, 23, 90].
Need a Hint?
Edge Cases to Watch
- Empty input structures
- Single element inputs
- Large numerical bounds
Ready to Solve?
Open the problem in PyRun's browser-based Python editor. Your code runs fully offline — no server required.
Interview Insights & Variations
Complexity Analysis Breakdown
Why Time: Directly evaluates all possibilities.
Why Space: Uses standard local memory.
Why Time: Optimized paths reduce total operations.
Why Space: May trade memory for speed.
Optimized Solution Python Code
Optimized Solution Python Code
def wave_sort_opt(arr):
for i in range(0, len(arr), 2):
if i > 0 and arr[i-1] > arr[i]: arr[i], arr[i-1] = arr[i-1], arr[i]
if i < len(arr)-1 and arr[i+1] > arr[i]: arr[i], arr[i+1] = arr[i+1], arr[i]
return arrBrute Force Code (Spoiler Guarded)
Brute Force Code (Spoiler Guarded)
def wave_sort_brute(arr):
arr.sort()
for i in range(0, len(arr) - 1, 2):
arr[i], arr[i+1] = arr[i+1], arr[i]
return arrAlgorithm Pattern Checklist
When dealing with Searching & Sorting data patterns.
Core Prerequisites
Revision Key Notes
Common Mistakes & Pitfalls
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