public int[] GetSolution(IChromosome chromosome)
{
var shapes =
chromosome.GetGenes()
.Select(x => (int)x.Value)
.Batch(GenesPerShape, x => x.ToArray())
.Index();
// Determine which grid cells each shape would occupy if placed
var shapeCells =
shapes
.Select(x => SolutionFactory.GetIndexes(
shapeId: x.Key,
shapeValue: x.Value[0],
xValue: x.Value[1],
yValue: x.Value[2]))
.ToArray();
int[] solution = EmptySolutionWithBlockers.ToArray();
int placedShapes = 0;
// Try to place each shape if no part of the shape would cover another (already-placed)
// shape or blocker. We try to place the more "difficult" shapes first.
// Note: Originally overlapping was allowed, but the UI looked a mess and performance
// was no better than without overlaps
for (int i = 0; i < shapeCells.Length; i++)
{
if (shapeCells[i].All(x => solution[x] == 0))
{
placedShapes++;
foreach (int index in shapeCells[i])
{
solution[index] = i + ShapeStartIndex;
}
}
}
bool IsAdjacent(int i1, int i2)
{
var(r1, c1) = (i1 / GridWidth, i1 % GridWidth);
var(r2, c2) = (i2 / GridWidth, i2 % GridWidth);
return(Math.Abs(r1 - r2) + Math.Abs(c1 - c2) == 1);
}
// The single and double unit shapes are the easiest to place
// so handle these last. It's more efficient to find the gaps and
// place them there than to wait for mutation to move them to the
// correct place.
if (placedShapes == GeniusSquareSolver.Shapes)
{
var empty =
solution
.Index()
.Where(x => x.Value == 0)
.Select(x => x.Key)
.ToList();
var sol = empty.Permutations().FirstOrDefault(x => IsAdjacent(x[0], x[1]));
if (sol != null)
{
solution[sol[0]] = DoubleUnitShapeIndex;
solution[sol[1]] = DoubleUnitShapeIndex;
solution[sol[2]] = SingleUnitShapeIndex;
}
}
return(solution);
}