error for self loops with coloring. fixes #112 (#113)

JuliaGraphs · May 13, 2022 · 5608e49 · 5608e49
1 parent cc041b8
commit 5608e49
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Showing 2 changed files with 17 additions and 11 deletions.
diff --git a/src/traversals/greedy_color.jl b/src/traversals/greedy_color.jl
@@ -18,13 +18,13 @@ Color graph `g` according to an order specified by `seq` using a greedy heuristi
 """
 function perm_greedy_color(g::AbstractGraph, seq::Vector{T}) where {T <: Integer}
     nvg::T = nv(g)
-    cols = Vector{T}(undef, nvg)  
+    cols = Vector{T}(undef, nvg)
     seen = zeros(Bool, nvg + 1)
 
+    has_self_loops(g) && throw(ArgumentError("graph must not have self loops"))
+
     for v in seq
-        seen[v] = true
         colors_used = zeros(Bool, nvg)
-
         for w in neighbors(g, v)
             if seen[w]
                 colors_used[cols[w]] = true
@@ -37,6 +37,8 @@ function perm_greedy_color(g::AbstractGraph, seq::Vector{T}) where {T <: Integer
                 break;
             end
         end
+
+        seen[v] = true
     end
 
     return Coloring{T}(maximum(cols), cols)
@@ -47,8 +49,8 @@ end
 
 Color graph `g` iteratively in the descending order of the degree of the vertices.
 """
-function degree_greedy_color(g::AbstractGraph{T}) where {T <: Integer} 
-    seq = convert(Vector{T}, sortperm(degree(g), rev=true)) 
+function degree_greedy_color(g::AbstractGraph{T}) where {T <: Integer}
+    seq = convert(Vector{T}, sortperm(degree(g), rev=true))
     return perm_greedy_color(g, seq)
 end
 
@@ -59,7 +61,7 @@ end
 Color the graph `g` iteratively in a random order using a greedy heuristic
 and choose the best coloring out of `reps` such random colorings.
 """
-function random_greedy_color(g::AbstractGraph{T}, reps::Integer) where {T <: Integer} 
+function random_greedy_color(g::AbstractGraph{T}, reps::Integer) where {T <: Integer}
 
     seq = shuffle(vertices(g))
     best = perm_greedy_color(g, seq)
@@ -76,7 +78,7 @@ end
 
 Color graph `g` based on [Greedy Coloring Heuristics](https://en.wikipedia.org/wiki/Greedy_coloring)
 
-The heuristics can be described as choosing a permutation of the vertices and assigning the 
+The heuristics can be described as choosing a permutation of the vertices and assigning the
 lowest color index available iteratively in that order.
 
 If `sort_degree` is true then the permutation is chosen in reverse sorted order of the degree of the vertices.

diff --git a/test/traversals/greedy_color.jl b/test/traversals/greedy_color.jl
@@ -1,5 +1,5 @@
 @testset "Greedy Coloring" begin
-  
+
     g3 = star_graph(10)
 
     for g in testgraphs(g3)
@@ -8,15 +8,15 @@
             @test C.num_colors == 2
         end
     end
-    
+
     g4 = path_graph(20)
     g5 = complete_graph(20)
 
     for graph in [g4, g5]
         for g in testgraphs(graph)
             for op_sort in (true, false)
                 C = @inferred(greedy_color(g, reps=5, sort_degree=op_sort))
-        
+
                 @test C.num_colors <= maximum(degree(g))+1
                 correct = true
                 for e in edges(g)
@@ -26,5 +26,9 @@
             end
         end
     end
-end
 
+    # non-regression test for #112
+    g = Graph(1)
+    add_edge!(g, 1, 1)
+    @test_throws ArgumentError greedy_color(g)
+end