Computes all shortest paths from source node SourceNode to sink node SinkNode. The result is returned in the form of a sub-graph of the input graph, which contains all relevant edges. If there is no path, the predicate fails.
DistanceArg refers to the graph's EdgeData information that was specified when the graph was constructed. If EdgeData is a simple number, then DistanceArg should be 0 and EdgeData will be taken as the length of the edge. If EdgeData is a compound data structure, DistanceArg should be a number between 1 and the arity of that structure and determines which argument of the EdgeData structure will be interpreted as the edge's length. Important: the distance information in EdgeData must be a non-negative number.
If DistanceArg is given as -1, then any EdgeData is ignored and the length of every edge is assumed to be equal to 1.
Tolerance should be zero in order to find only the shortest paths. If Tolerance is greater than zero, then all paths that are within this tolerance of the shortest path length will be found.
The result is returned in the form of SubGraph, which is a sub-graph of the input Graph, containing the same nodes, but only those edges that are needed to construct the shortest paths for the given parameters. SubGraph does not inherit the nodename information from Graph, this can be set explicitly if required.
In addition, the Length of the shortest path from source to sink is returned.
To generate an actual path from the resulting SubGraph, start from the sink node J, select one of its incoming edges (graph_get_incoming_edges/3) to find a predecessor node, and continue this process until the SourceNode is reached. Depending on the parameters, the following 3 cases can occur:
?- sample_graph(G), single_pair_all_short_paths_as_graph(G, 0, 1, 5, 0, L, E). G = graph(13, ([e(1, 6, 1), e(1, 2, 1), e(1, 7, 1)], , ...) L = 2 SG = graph(13, ([e(1, 6, 1), e(1, 7, 1)], , ...)