|
| 1 | +class FloydWarshall: |
| 2 | + """ |
| 3 | + Implements : Floyd Warshall Algorithm |
| 4 | + Inputs : Adjaceny Matrix (list of lists) |
| 5 | + Outputs : Shortest distance between all pairs |
| 6 | + """ |
| 7 | + |
| 8 | + def __init__(self, adj_matrix): |
| 9 | + """ |
| 10 | + Initialises distance matrix (list of lists) |
| 11 | + """ |
| 12 | + |
| 13 | + self.adj_matrix = adj_matrix |
| 14 | + self.distance = adj_matrix |
| 15 | + self.num_vertices = len(adj_matrix) |
| 16 | + |
| 17 | + def run(self): |
| 18 | + """" |
| 19 | + Implements Floyd Warshall Algorithm |
| 20 | + """ |
| 21 | + |
| 22 | + for k in xrange(0, self.num_vertices): |
| 23 | + for i in xrange(0, self.num_vertices): |
| 24 | + for j in xrange(0, self.num_vertices): |
| 25 | + if self.distance[i][k] + self.distance[k][j] < self.distance[i][j]: |
| 26 | + self.distance[i][j] = self.distance[i][k] + self.distance[k][j] |
| 27 | + |
| 28 | + def get_distance(self): |
| 29 | + """ |
| 30 | + Returns the distance list |
| 31 | + """ |
| 32 | + |
| 33 | + return self.distance |
| 34 | + |
| 35 | + def print_distance(self): |
| 36 | + for node in self.distance: |
| 37 | + for each in node: |
| 38 | + print each, |
| 39 | + print |
| 40 | + |
| 41 | +def main(): |
| 42 | + graph = [[0, 5, float('inf'), 10], |
| 43 | + [float('inf'), 0, 3, float('inf')], |
| 44 | + [float('inf'), float('inf'), 0, 1], |
| 45 | + [float('inf'), float('inf'), float('inf'), 0]] |
| 46 | + |
| 47 | + |
| 48 | + floyd = FloydWarshall(graph) |
| 49 | + floyd.run() |
| 50 | + floyd.print_distance() |
| 51 | + |
| 52 | +if __name__ == '__main__': |
| 53 | + main() |
| 54 | + |
| 55 | +#OUTPUT |
| 56 | +#0 5 8 9 |
| 57 | +#inf 0 3 4 |
| 58 | +#inf inf 0 1 |
| 59 | +#inf inf inf 0 |
0 commit comments