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@hauleth
Created December 12, 2022 13:47
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Bellman-Ford implementation using ETS
defmodule BellmanFord2 do
@moduledoc """
The Bellman–Ford algorithm is an algorithm that computes shortest paths from a single
source vertex to all of the other vertices in a weighted digraph.
It is capable of handling graphs in which some of the edge weights are negative numbers
Time complexity: O(VLogV)
"""
@type distance :: %{Graph.vertex_id() => integer}
@doc """
Returns nil when graph has negative cycle.
"""
@spec call(Graph.t(), Graph.vertex()) :: [Graph.vertex()] | nil
def call(%Graph{vertices: vs, edges: meta} = g, a) do
distances = a |> Graph.Utils.vertex_id() |> init_distances(vs)
weights = Enum.map(meta, &edge_weight/1)
for _ <- 1..map_size(vs),
edge <- weights do
update_distance(edge, distances)
end
if has_negative_cycle?(distances, weights) do
nil
else
distances
|> :ets.tab2list()
|> Map.new(fn {k, v} -> {Map.fetch!(g.vertices, k), v} end)
end
end
@spec init_distances(Graph.vertex(), Graph.vertices()) :: distance
defp init_distances(vertex_id, vertices) do
tab = :ets.new(:distances, [:set, :private, :compressed])
init =
Enum.map(vertices, fn
{id, _vertex} when id == vertex_id -> {id, 0}
{id, _} -> {id, :infinity}
end)
:ets.insert_new(tab, init)
tab
end
@spec update_distance(term, distance) :: distance
defp update_distance({{u, v}, weight}, distances) do
[{_, du}] = :ets.lookup(distances, u)
[{_, dv}] = :ets.lookup(distances, v)
if du != :infinity and du + weight < dv do
:ets.update_element(distances, v, {2, du + weight})
else
distances
end
end
@spec edge_weight(term) :: float
defp edge_weight({e, edge_value}), do: {e, edge_value |> Map.values() |> List.first()}
defp has_negative_cycle?(distances, meta) do
Enum.any?(meta, fn {{u, v}, weight} ->
[{_, du}] = :ets.lookup(distances, u)
[{_, dv}] = :ets.lookup(distances, v)
du != :infinity and du + weight < dv
end)
end
end
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