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The Sweep Line algorithm involves moving a vertical line from left to right over the x-coordinates and maintaining a list of currently active buildings using a max-heap. The priority queue helps keep track of the tallest building at each point. As the line reaches the start of a new building, add it to the heap, and as it reaches the end of a building, remove it. The key points are detected based on changes in the maximum height at points where buildings start or end.
Time Complexity: O(N log N), where N is the number of events (two for each building).
Space Complexity: O(N), as we store up to N building heights in the heap.
1import heapq
2
3def getSkyline(buildings):
4 events = [(L, -H, R) for L, R, H in buildings] + [(R, 0, 0) for _, R, _ in buildings]
5 events.sort()
6
7 res, hp = [[0, 0]], [(0, float('inf'))]
8 for L, negH, R in events:
9 while L >= hp[0][1]:
10 heapq.heappop(hp)
11 if negH:
12 heapq.heappush(hp, (negH, R))
13 if res[-1][1] != -hp[0][0]:
14 res.append([L, -hp[0][0]])
15
16 return res[1:]This code uses a priority queue (min-heap) where we push the negative of the height to simulate a max-heap, to manage the building heights efficiently. We handle start and end events separately, ensuring the heap accurately reflects the current tallest building. While processing each event, code also manages to merge the same consecutive heights, ensuring result compliance with the rules.
This approach involves breaking down the problem using the divide and conquer strategy. The buildings array is split into two halves recursively. The base case is a single building, where the skyline can directly be calculated. The results are then merged, taking care of overlapping heights and ensuring continuity and distinct key points.
Time Complexity: O(N log N), due to division of buildings and merging.
Space Complexity: O(N), needing space for recursive stack and individual skyline lists.
1import
The Java approach similarly applies divide and conquer logic, processing through recursive splitting and merging of skyline components. It ensures that the merged result retains only distinct key height changes without unnecessary redundancies.