from collections import defaultdict
from heapq import heappop, heappush


class Graph(object):
    def __init__(self):
        self.graph = defaultdict(list)

    def __len__(self):
        return len(self.graph)

    def add_edge(self, src, dst, weight=1):
        self.graph[src].append((dst, weight))

    def get_nodes(self):
        return self.graph.keys()


class Dijkstra(object):
    def __init__(self, graph, start):
        self.g = graph.graph
        self.dist = defaultdict(lambda: float('inf'))
        self.dist[start] = 0
        self.prev = defaultdict(lambda: None)
        self.Q = []
        heappush(self.Q, (self.dist[start], start))
        while self.Q:
            dist_u, u = heappop(self.Q)
            if self.dist[u] < dist_u:
                continue
            for v, weight in self.g[u]:
                alt = dist_u + weight
                if self.dist[v] > alt:
                    self.dist[v] = alt
                    self.prev[v] = u
                    heappush(self.Q, (alt, v))

    def shortest_distance(self, goal):
        return self.dist[goal]


N, M = [int(i) for i in input().split()]
graphs = [Graph() for _ in range(M + 1)]
inputs = [(int(i) for i in input().split()) for _ in range(M)]

for i, (a, b, c) in enumerate(inputs):
    for j, graph in enumerate(graphs):
        if i == j:
            graph.add_edge(a, b, 0)
            graph.add_edge(b, a, 0)
        else:
            graph.add_edge(a, b, c)
            graph.add_edge(b, a, c)

for j in range(N):
    result = Dijkstra(graphs[0], 1).shortest_distance(
        j + 1) + min([Dijkstra(graph, 1).shortest_distance(j + 1) for graph in graphs[1:]])
    print(result)