結果
| 問題 | No.2179 Planet Traveler | 
| コンテスト | |
| ユーザー |  lam6er | 
| 提出日時 | 2025-04-15 23:28:29 | 
| 言語 | PyPy3 (7.3.15) | 
| 結果 | 
                                WA
                                 
                             | 
| 実行時間 | - | 
| コード長 | 1,488 bytes | 
| コンパイル時間 | 300 ms | 
| コンパイル使用メモリ | 81,556 KB | 
| 実行使用メモリ | 91,904 KB | 
| 最終ジャッジ日時 | 2025-04-15 23:30:01 | 
| 合計ジャッジ時間 | 3,784 ms | 
| ジャッジサーバーID (参考情報) | judge4 / judge3 | 
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| ファイルパターン | 結果 | 
|---|---|
| sample | AC * 4 | 
| other | AC * 25 WA * 1 | 
ソースコード
import math
import heapq
def main():
    n = int(input())
    planets = []
    for _ in range(n):
        x, y, t = map(int, input().split())
        r = math.hypot(x, y)
        planets.append((x, y, t, r))
    
    # Precompute all pairs' minimal distance squared
    edges = [[0.0] * n for _ in range(n)]
    for i in range(n):
        xi, yi, ti, ri = planets[i]
        for j in range(n):
            if i == j:
                continue
            xj, yj, tj, rj = planets[j]
            if ti != tj:
                d_sq = (ri - rj) ** 2
            else:
                dx = xi - xj
                dy = yi - yj
                d_sq = dx * dx + dy * dy
            edges[i][j] = d_sq
    
    # Dijkstra's algorithm to find the minimal maximum edge weight
    INF = float('inf')
    dist = [INF] * n
    dist[0] = 0.0  # Starting at planet 1 (index 0)
    heap = []
    heapq.heappush(heap, (0.0, 0))
    
    while heap:
        current_max, u = heapq.heappop(heap)
        if u == n - 1:
            print(math.ceil(current_max))
            return
        if current_max > dist[u]:
            continue
        for v in range(n):
            if v == u:
                continue
            new_max = max(current_max, edges[u][v])
            if new_max < dist[v]:
                dist[v] = new_max
                heapq.heappush(heap, (new_max, v))
    
    # If no path found (shouldn't happen as per problem constraints)
    print(-1)
if __name__ == "__main__":
    main()
            
            
            
        