private static void PlaceLabels(MapSegment segment)
{
Console.WriteLine("==== " + segment.name + " ====");
int num_prefs = Constants.tower_preference_positions.Length;
// My Linear Algebra library is apparently quite slow, so if you cache these, then it makes a
// massive increase to the program's speed, particularly in the Simulated Annealing stage.
Rect2 [] influenced_region = new Rect2 [segment.towers.Count];
Rect2 [] point_rects = new Rect2 [segment.towers.Count];
Rect2 [,] label_pref_rects = new Rect2 [segment.towers.Count, num_prefs];
Vector2 [,] label_pref_rect_centres = new Vector2 [segment.towers.Count, num_prefs];
#region Populate caches
for (int i = 0; i < segment.towers.Count; i++)
{
segment.towers [i].ComputeLabelSize();
for (int j = 0; j < num_prefs; j++)
{
label_pref_rects [i, j] = segment.towers [i].GetLabelRectByPreference(j);
label_pref_rect_centres [i, j] = label_pref_rects [i, j].centre;
}
influenced_region [i] = segment.towers [i].affected_region;
point_rects [i] = Rect2.FromCentreAndSize(segment.towers [i].map_position, Vector2.one * Constants.point_radius_outer * 2);
if (influenced_region [i].w >= Chunk.chunk_size.x)
{
Console.WriteLine("!!! CHUNK SIZE NOT WIDE ENOUGH !!! : " + segment.towers [i].name);
}
if (influenced_region [i].h >= Chunk.chunk_size.y)
{
Console.WriteLine("!!! CHUNK SIZE NOT TALL ENOUGH !!! : " + segment.towers [i].name);
}
}
#endregion
/* Note that this list/relation is symmetric; if (a, b) is in the list then so is (b, a).
* This way, in order to check every combination symmetrically, only one iteration over the list
* is required with no code duplication.
*/
List <(Tower, Tower)> close_tower_pairs = new List <(Tower, Tower)> ();
#region Generate a list of close tower pairs to speed up comparisons
int p = 0;
int q = 0;
int r = 0;
int [] ref_counts = new int [segment.towers.Count];
foreach (Chunk chunk in segment.chunks)
{
foreach (Tower tower_2 in chunk.towers_to_compare)
{
foreach (Tower tower_1 in chunk.towers)
{
if (tower_1 == tower_2)
{
continue;
}
p++;
if (Rect2.Overlaps(
influenced_region [tower_1.index],
influenced_region [tower_2.index]
))
{
q++;
close_tower_pairs.Add((tower_1, tower_2));
ref_counts [tower_1.index]++;
if (tower_1.index < tower_2.index)
{
r++;
}
}
}
}
}
#endregion
Console.WriteLine(" >> " + p + " comparisons normally.");
Console.WriteLine(" >> " + q + " comparisons with reductions (" + r + " unique comparisons).");
Console.WriteLine(" >> " + ref_counts.Where(x => x == 0).Count() + " towers will be completely ignored.");
int [,] label_pref_orders = new int [segment.towers.Count, num_prefs];
#region Decide on the order of preference for label positions
float [,] label_pref_weights = new float [segment.towers.Count, num_prefs];
foreach (Chunk chunk in segment.chunks)
{
foreach (Tower tower_2 in chunk.towers_to_compare)
{
foreach (Tower tower_1 in chunk.towers)
{
if (tower_1.index == tower_2.index)
{
continue;
}
if (Vector2.SquareDistanceBetween(tower_1.map_position, tower_2.map_position) > 900)
{
continue;
}
for (int i = 0; i < num_prefs; i++)
{
float d = label_pref_rects [tower_1.index, i].ClosestDistanceTo(tower_2.map_position);
float dx = label_pref_rect_centres [tower_1.index, i].x - tower_2.map_position.x;
float dy = label_pref_rect_centres [tower_1.index, i].y - tower_2.map_position.y;
label_pref_weights [tower_1.index, i] += 1f / (dx * dx + dy * dy + 0.01f);
}
}
}
}
// Sort weights
for (int i = 0; i < segment.towers.Count; i++)
{
List <(int, float)> indices_in_order = Enumerable.Range(0, num_prefs).Select(x => (x, label_pref_weights [i, x])).ToList();