private static IEnumerable <IEnumerable <Vector2> > FindSpecialBuildingsWithinDistanceFromHouse(
IEnumerable <Vector2> specialBuildings,
IEnumerable <Tuple <Vector2, float> > housesAndDistances)
{
Func <Tuple <Vector2, float>, Predicate <Vector2> > predicate = t => v => Euclosure.Invoke(t.Item1).Invoke(v) < t.Item2;
var specialBuildingsTree = Tree2D.FromEnumerable(specialBuildings);
var newSpecialBuildings = new List <List <Vector2> >();
foreach (var tuple in housesAndDistances)
{
var p = predicate.Invoke(tuple);
newSpecialBuildings.Add(Tree2D.FilterTree(specialBuildingsTree, p));
}
return(newSpecialBuildings);
}
//----------------------------------------------------------------------
private static IntSet <PartyId> SearchNearLocation(
Timer t,
int desiredResultCount,
Location centroid,
double nonGeoMatchAbsDensity,
out double?maxRadiusMi)
{
double searchRadiusMi = InitialGeoSearchRadiusMi;
maxRadiusMi = searchRadiusMi;
// KLUDGE: Scale the desired result count up by the non-geographic
// match absolute density in the database. In doing so, we attempt
// to return enough results that we'll get close to the desired
// result count in the end.
desiredResultCount = (int)(desiredResultCount / nonGeoMatchAbsDensity);
// Allocate an initial list large enough that we'll (hopefully)
// avoid re-allocating space as we iterate.
List <int> partyIds = new List <int>(2 * desiredResultCount);
Tree2D <int> tree2d = Snap.Cache.Cache.PartyLocation;
int iterationCount = 0;
Timer tree2dTimer = new Timer(t, String.Format(
"Expand MBR to fit {0} Parties", desiredResultCount));
while ((partyIds.Count < desiredResultCount) &&
(searchRadiusMi < MaxGeoSearchRadiusMi))
{
iterationCount++;
maxRadiusMi = searchRadiusMi;
partyIds.Clear();
tree2d.Search(
new BoundingBox(centroid, searchRadiusMi),
(partyId) => partyIds.Add(partyId));
searchRadiusMi *= GeoSearchRadiusScalar;
}
tree2dTimer.Stop(String.Format("in {0} iterations", iterationCount));
return(IntSet <PartyId> .CreateFromUnsorted(partyIds));
}