Hello Tiago,
Thanks for the quick reply .
I don't have time for opening the issues right now, but I'll try to do so later
today or tomorrow. Regardless, below you'll find a minimal example for the
first issue I mentioned, for if you want to try it in the meantime.
Best regards,
JA
_
from graph_tool import Graph
from graph_tool.topology import shortest_distance
if __name__ == '__main__':
"""In this example we have a 4 vertices/ 3 edges graph with the following
topology:
(2) <----- (1) ----> (3) ----> (4)
where each edge has weight=5.
Shortest distance is calculated from vertex (1).
"""
# Create graphs
g = Graph(directed=True)
# Add vertices
g.add_vertex()
g.add_vertex()
g.add_vertex()
g.add_vertex()
# Edge weight property
w = g.new_edge_property("float")
# Add edges
e1 = g.add_edge(1, 2)
w[e1] = 5
e2 = g.add_edge(1, 3)
w[e2] = 5
e3 = g.add_edge(3, 4)
w[e3] = 5
# Tests:
# Case 1: max_dist = 1, so only the source should be reached.
dist, reached = shortest_distance(g, source=g.vertex(1), weights=w,
max_dist=1, return_reached=True)
print(f"\nCase 1 (source=1, max_dist=1): \n\t- Reached: {reached}\n\t-
Dist.: {dist.a}")
# Result: reached has vertex 1 (the only reached), but also the neighbours
2 and 3 which have dist == inf
# Case 2: max_dist = 6, so 1,2,3 should be reached but not 4
dist, reached = shortest_distance(g, source=g.vertex(1), weights=w,
max_dist=6, return_reached=True)
print(f"\nCase 2 (source=1, max_dist=6): \n\t- Reached: {reached}\n\t-
Dist.: {dist.a}")
# Result: reached has all vertices, despite 1 -> 4 having total distance of
10 (path 1 -> 3 -> 4, two edges with w=5)
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