The following Code highlights the breadth-first scan tree

g = GridGraph[{3, 5}, VertexSize -> {5 -> Medium}]


This produces the output (where <-> represents undirected edge).

{{2, 5, 2, 5, 5, 5, 4, 5, 6, 7, 8, 9, 10, 11, 12}, {{5 <-> 2, 5 <-> 4, 5 <-> 6, 5 <-> 8, 2 <-> 1, 2 <-> 3, 4 <-> 7, 6 <-> 9, 8 <-> 11, 7 <-> 10, 9 <-> 12, 11 <-> 14, 10 <-> 13, 12 <-> 15}}}

I have read up on reap and sow and understand the second list. The first list which is supposed to capture the final outcome of the compound expression however is not clear.

What do the vertices in this first list represent (in the context of reap and sow for this particular application)?

{2, 5, 2, 5, 5, 5, 4, 5, 6, 7, 8, 9, 10, 11, 12}

In a breadth first scan I would have expected the final outcomes to be more closely related to the order of visiting nodes in the scan.

Is this output consistent with what ought to be produced in a reap and sow context for this particular application? And if so, can you clarify how this is the case (in terms of reap and sow functioning)?

This list is just the return value of BreadthFirstScan. It has absolutely nothing to do with Sow and Reap.

According to the documentation, it is the list of the predecessors of the BFS tree.

The first element of the list is 2. This means that 2 -> 1 belongs to the tree, where 1 is the first vertex. The second is 5, so 5 -> 2 also belong to the tree (where 2 is the second vertex). And so on.

The one tricky thing about this representation is that for those vertices that do not have a predecessor, the "predecessor" is given as the same vertex. This is always the case for the root vertex (the vertex where the search starts), and can happen for vertices that are not scanned at all (in non-connected graphs). The predecessor lists produced from a connected graph is compatible with TreeGraph (see below).

You can reconstruct the tree using TreeGraph:

g = GridGraph[{3, 5}, VertexSize -> {5 -> Medium}]


• @Mike That's because the "predecessor" of the root vertex (5) is given as the root itself. This is also how TreeGraph works. – Szabolcs Feb 21 at 9:35