Python/graphs/graphs_floyd_warshall.py

124 lines
3.5 KiB
Python
Raw Normal View History

# floyd_warshall.py
"""
The problem is to find the shortest distance between all pairs of vertices in a
weighted directed graph that can have negative edge weights.
"""
def _print_dist(dist, v):
print("The shortest path matrix using Floyd Warshall algorithm\n")
2019-10-05 05:14:13 +00:00
for i in range(v):
for j in range(v):
if dist[i][j] != float("inf"):
2024-10-17 09:15:32 +00:00
print(int(dist[i][j]), end="\t")
2019-10-05 05:14:13 +00:00
else:
2024-10-17 09:15:32 +00:00
print("INF", end="\t")
2019-10-05 05:14:13 +00:00
print()
2018-10-19 12:48:28 +00:00
def floyd_warshall(graph, v):
2019-10-05 05:14:13 +00:00
"""
:param graph: 2D array calculated from weight[edge[i, j]]
:type graph: List[List[float]]
:param v: number of vertices
:type v: int
:return: shortest distance between all vertex pairs
distance[u][v] will contain the shortest distance from vertex u to v.
1. For all edges from v to n, distance[i][j] = weight(edge(i, j)).
3. The algorithm then performs distance[i][j] = min(distance[i][j], distance[i][k] +
distance[k][j]) for each possible pair i, j of vertices.
4. The above is repeated for each vertex k in the graph.
5. Whenever distance[i][j] is given a new minimum value, next vertex[i][j] is
updated to the next vertex[i][k].
2024-10-17 07:59:27 +00:00
>>> graph = [
2024-10-17 09:26:52 +00:00
... [0, 3, float('inf')],
... [2, 0, float('inf')],
... [float('inf'), 7, 0]
2024-10-17 07:59:27 +00:00
... ]
2024-10-17 08:51:54 +00:00
2024-10-17 07:59:27 +00:00
>>> expected = [
2024-10-17 09:26:52 +00:00
... [0, 3, float('inf')],
... [2, 0, float('inf')],
... [9, 7, 0]
2024-10-17 07:59:27 +00:00
... ]
2024-10-17 09:31:28 +00:00
>>> dist, _ = floyd_warshall(graph, 3)
The shortest path matrix using Floyd Warshall algorithm
0 3 INF
2 0 INF
9 7 0
2024-10-17 08:42:14 +00:00
>>> dist == expected
2024-10-17 07:59:27 +00:00
True
"""
2019-10-05 05:14:13 +00:00
dist = [[float("inf") for _ in range(v)] for _ in range(v)]
for i in range(v):
for j in range(v):
dist[i][j] = graph[i][j]
# check vertex k against all other vertices (i, j)
for k in range(v):
# looping through rows of graph array
for i in range(v):
# looping through columns of graph array
for j in range(v):
if (
dist[i][k] != float("inf")
and dist[k][j] != float("inf")
and dist[i][k] + dist[k][j] < dist[i][j]
):
dist[i][j] = dist[i][k] + dist[k][j]
_print_dist(dist, v)
2019-10-05 05:14:13 +00:00
return dist, v
if __name__ == "__main__":
v = int(input("Enter number of vertices: "))
e = int(input("Enter number of edges: "))
graph = [[float("inf") for i in range(v)] for j in range(v)]
for i in range(v):
graph[i][i] = 0.0
# src and dst are indices that must be within the array size graph[e][v]
# failure to follow this will result in an error
for i in range(e):
print("\nEdge ", i + 1)
src = int(input("Enter source:"))
dst = int(input("Enter destination:"))
weight = float(input("Enter weight:"))
graph[src][dst] = weight
floyd_warshall(graph, v)
# Example Input
# Enter number of vertices: 3
# Enter number of edges: 2
# # generated graph from vertex and edge inputs
# [[inf, inf, inf], [inf, inf, inf], [inf, inf, inf]]
# [[0.0, inf, inf], [inf, 0.0, inf], [inf, inf, 0.0]]
# specify source, destination and weight for edge #1
# Edge 1
# Enter source:1
# Enter destination:2
# Enter weight:2
# specify source, destination and weight for edge #2
# Edge 2
# Enter source:2
# Enter destination:1
# Enter weight:1
# # Expected Output from the vertice, edge and src, dst, weight inputs!!
# 0 INF INF
# INF 0 2
# INF 1 0