protected override bool IsChildBoardBetter(Knowledge knowledge, Board board, Board childBoard)
{
var x = MetaKnowledge.GetColorGraphs(childBoard.Stacks, childBoard.Pot).Select(c => c.Count).ToList();
var y = MetaKnowledge.GetColorGraphs(board.Stacks, board.Pot).Select(c => c.Count).ToList();
return(StandardDeviation(x) < StandardDeviation(y));
}
public static bool IsKierstead(Knowledge knowledge, Board board, int edgeIndex, List <int> ordering)
{
var gn = knowledge.GraphKnowledge;
return(gn.LineGraph.IsChoosable(Enumerable.Range(0, gn.LineGraph.N).Select(e =>
{
if (e == edgeIndex)
{
return -1;
}
var edge = gn.Edges[e];
var j = Math.Max(ordering.IndexOf(edge.Item1), ordering.IndexOf(edge.Item2));
var priorStacks = board.Stacks.Where((stack, i) => ordering.IndexOf(i) < j).ToList();
long allowedList = 0;
var list = knowledge.GetEdgeColorList(board, e);
foreach (var alpha in list.EnumerateBits())
{
if (MetaKnowledge.d_H(alpha, priorStacks) % 2 == 0)
{
allowedList = allowedList.SetBit(alpha);
}
}
return allowedList;
}).ToList()));
}
public IEnumerable <KnowledgeTree> EnumerateKnowledgeTrees(Template template)
{
var templateKnowledge = Knowledge[template];
var colorCount = MetaKnowledge.Naturals().First(n => templateKnowledge.KnowledgeExists(n) && !templateKnowledge.KnowledgeExists(n + 1));
return(templateKnowledge[colorCount].EnumerateBoardKnowledge().Select(kvp => GenerateKnowledgeTree(kvp.Key)));
}
void FillKnowledgeTree(KnowledgeTree knowledgeTree, Board board, Dictionary <Board, Tuple <int, Board> > seenCache)
{
knowledgeTree.Board = board.ToString();
knowledgeTree.Number = TreeNodeNumber++;
var knowledge = Knowledge[board.Template.Value][board.ColorCount][board];
if (knowledge.Exists())
{
if (knowledge.Reason != "good swap")
{
knowledgeTree.Note = knowledge.Reason;
}
else
{
Tuple <int, Board> seenBoard;
if (seenCache.TryGetValue(board, out seenBoard))
{
knowledgeTree.Note = "same as #" + seenBoard.Item1;
return;
}
var f = knowledge.Board.FindPermutation(board);
var colors = Board.ApplyMapping(f, new[] { knowledge.ColorPair.Item1, knowledge.ColorPair.Item2 }).ToList();
var colorPair = new Tuple <int, int>(colors[0], colors[1]);
foreach (var swap in knowledge.Swaps)
{
var tempBoard = board.Clone();
var moves = swap.Item2.Select(m => MetaKnowledge.MapMove(f, m)).ToList();
tempBoard.DoMoveCombination(moves);
var childKnowledgeTree = knowledgeTree.AddChild(swap);
childKnowledgeTree.ColorPair = colorPair;
FillKnowledgeTree(childKnowledgeTree, tempBoard, seenCache);
}
}
}
else
{
throw new Exception("something went wrong in building search tree");
}
seenCache[board] = new Tuple <int, Board>(knowledgeTree.Number, board);
}
public bool Analyze(Template template, Action <ThoughtProgress> progress = null)
{
TotalPositions = 0;
FixerWonAllNearlyColorableBoards = true;
EnsureSwapAnalyzerExistence();
var minimumColorCount = Math.Max(MinPot, template.Sizes.Max());
var maximumColorCount = Math.Min(MaxPot, template.Sizes.Sum());
var foundAtLeastOneBoard = false;
foreach (var colorCount in MetaKnowledge.Interval(minimumColorCount, maximumColorCount))
{
if (progress != null)
{
progress(new ThoughtProgress()
{
IsInitialThought = true
});
}
var boards = GenerateAllBoards(template, colorCount, progress).ToList();
if (foundAtLeastOneBoard && boards.Count <= 0)
{
break;
}
TotalPositions += boards.Count;
foundAtLeastOneBoard = true;
var breakerWin = !Analyze(boards, progress);
if (breakerWin && StopAnalysisOnBreakerWin)
{
return(false);
}
Knowledge[template].Promote(colorCount);
}
return(Knowledge[template].LostBoards.Count() <= 0);
}
List <List <int> > GetVectors(Board b)
{
return(MetaKnowledge.GetColorGraphs(b.Stacks, b.Pot).OrderByDescending(c => c.Count).ToList());
}
public Tuple <Graph, Dictionary <int, KeyValuePair <Board, BoardKnowledge> >, Dictionary <Tuple <int, int>, Tuple <List <List <int> >, List <Move>, string> > > GenerateTemplateKnowledgeGraph(Template template)
{
var templateKnowledge = Knowledge[template];
var colorCount = MetaKnowledge.Naturals().First(n => templateKnowledge.KnowledgeExists(n) && !templateKnowledge.KnowledgeExists(n + 1));
var nextVertexID = 0;
var vertexLookup = new Dictionary <Board, int>();
var swapLookup = new Dictionary <Tuple <int, int>, Tuple <List <List <int> >, List <Move>, string> >();
var boardLookup = new Dictionary <int, KeyValuePair <Board, BoardKnowledge> >();
var outEdges = new Dictionary <int, List <int> >();
foreach (var kvp in templateKnowledge[colorCount].EnumerateBoardKnowledge())
{
vertexLookup[kvp.Key] = nextVertexID;
boardLookup[nextVertexID] = kvp;
outEdges[nextVertexID] = new List <int>();
nextVertexID++;
}
foreach (var b in templateKnowledge.LostBoards)
{
vertexLookup[b] = nextVertexID;
boardLookup[nextVertexID] = new KeyValuePair <Board, BoardKnowledge>(b, new BoardKnowledge(b, "breaker wins"));
outEdges[nextVertexID] = new List <int>();
nextVertexID++;
}
foreach (var kvp in templateKnowledge[colorCount].EnumerateBoardKnowledge())
{
if (kvp.Value.Reason == "good swap")
{
var v = vertexLookup[kvp.Key];
var f = kvp.Value.Board.FindPermutation(kvp.Key);
var colors = Board.ApplyMapping(f, new[] { kvp.Value.ColorPair.Item1, kvp.Value.ColorPair.Item2 }).ToList();
var colorPair = new Tuple <int, int>(colors[0], colors[1]);
foreach (var swap in kvp.Value.Swaps)
{
var tempBoard = kvp.Key.Clone();
var moves = swap.Item2.Select(m => MetaKnowledge.MapMove(f, m)).ToList();
tempBoard.DoMoveCombination(moves);
var w = vertexLookup[tempBoard];
outEdges[v].Add(w);
swapLookup[new Tuple <int, int>(v, w)] = swap;
}
}
}
var edgeWeights = new List <int>();
for (int i = 0; i < nextVertexID; i++)
{
for (int j = i + 1; j < nextVertexID; j++)
{
if (outEdges[i].Contains(j))
{
edgeWeights.Add(1);
}
else if (outEdges[j].Contains(i))
{
edgeWeights.Add(-1);
}
else
{
edgeWeights.Add(0);
}
}
}
return(new Tuple <Graph, Dictionary <int, KeyValuePair <Board, BoardKnowledge> >, Dictionary <Tuple <int, int>, Tuple <List <List <int> >, List <Move>, string> > >(new Graph(edgeWeights), boardLookup, swapLookup));
}