// Graph coloring backtrack,
// search heuristics are set based on heuristc flag
func colorMapBacktrack(g graph.Graph, height int, h *nh.Heap) bool {
// Have all nodes been colored?
if height == len(g) {
return true
}
// Assign current node by MRV heap or sequentally
var currNode *graph.Node
if Heuristic.MRV {
// Top from the heap has the Minimum Remaining Values
currNode = heap.Pop(h).(nh.NodeItem).Node
} else {
currNode = g[height]
}
colors := ColorsCache.Colors[height]
for _, color := range colors {
// Is this color avaliable for use?
if currNode.TakenColors[color] == 0 {
// Update currNode color and warn adjacents
impossible := updateColorAndAdj(currNode, color, h)
// Forward Checking
if Heuristic.FC {
if impossible {
resetColorAndAdj(currNode)
continue
}
}
// Proceed with recursion
if colorMapBacktrack(g, height+1, h) {
return true
}
resetColorAndAdj(currNode)
}
}
// Need to backtrack
if Heuristic.MRV {
heap.Push(h, nh.NewNodeItem(currNode))
}
return false
}
// Setup for graph coloring backtracking algorithm,
// search heuristics are set based on heuristc flag
func colorMap(g graph.Graph) bool {
// For MRV, we'll use a heap
var h nh.Heap
if Heuristic.MRV {
h = nh.NewNodeHeap(len(g), Heuristic.Degree)
for _, n := range g {
h.Items = append(h.Items, nh.NewNodeItem(n))
}
heap.Init(&h)
}
// Init colors cache
ColorsCache.Colors = make([][]graph.NodeColor, len(g))
for i := range g {
ColorsCache.Colors[i] = make([]graph.NodeColor, 0, graph.NumColors-1)
for color := graph.Blank + 1; color < graph.NumColors; color++ {
ColorsCache.Colors[i] = append(ColorsCache.Colors[i], graph.NodeColor(color))
}
}
return colorMapBacktrack(g, 0, &h)
}
