Implement Kruskal traversal iterator

src/iterators/kruskal.jl

@@ -0,0 +1,46 @@
+# The kruskal algorithms are largely copied from Graphs/src/spanningtrees/kruskal.jl
+
+struct KruskalIterator <: EdgeIterator
+    graph::AbstractGraph
+    connected_vs::IntDisjointSets
+    distmx::AbstractMatrix
+    edge_list
+
+    function KruskalIterator(graph, distmx=weights(g); minimize=true)
+        is_directed(graph) && throw(ArgumentError("Cannot use Kruskal on a directed graph."))
+        weights = Vector{eltype(distmx)}()
+        sizehint!(weights, ne(graph))
+        edge_list = collect(edges(graph))
+        for e in edge_list
+            push!(weights, distmx[src(e), dst(e)])
+        end
+        e = edge_list[sortperm(weights; rev=!minimize)]
+        new(graph, IntDisjointSets(nv(graph)), distmx, e)
+    end
+end
+
+Base.length(t::KruskalIterator) = nv(t.graph)-1
+Base.eltype(t::KruskalIterator) = edgetype(t.graph)
+
+
+"""
+    mutable struct KruskalIteratorState
+`KruskalIteratorState` is a struct to hold the current state of iteration which is need for the Base.iterate() function.
+"""
+mutable struct KruskalIteratorState <: AbstractIteratorState
+    edge_id::Int
+    mst_len::Int
+end
+
+
+function Base.iterate(t::KruskalIterator, state::KruskalIteratorState=KruskalIteratorState(1,1))
+    while state.mst_len <= (nv(t.graph)-1)
+        i = state.edge_id
+        if !in_same_set(t.connected_vs, src(t.edge_list[i]), dst(t.edge_list[i]))
+            union!(t.connected_vs, src(t.edge_list[i]), dst(t.edge_list[i]))
+            state.mst_len += 1
+            return (t.edge_list[i], state)
+        end
+        state.edge_id += 1
+    end
+end