/// <summary>
/// Missing mapping to P objects
/// KdTree could be refactored to use P object instead of Math.Net
///
/// O(k * log n)
/// </summary>
/// <param name="s"></param>
/// <param name="origin"></param>
/// <param name="k"></param>
/// <param name="conf"></param>
/// <returns></returns>
public long UpdateKnn(IAlgorithm s, IP origin, KnnConfiguration conf)
{
if (conf == null) conf = new KnnConfiguration();
if (conf.SameTypeOnly) throw new NotImplementedException();
if (conf.MaxDistance.HasValue) throw new NotImplementedException();
var sw = new Stopwatch();
sw.Start();
var vector = new DenseVector(new[] { origin.X, origin.Y });
var nn = Tree.FindNearestNNeighbors(vector, conf.K).ToList();
s.Knn.Clear();
s.Knn.Origin = origin;
s.Knn.K = conf.K;
foreach (var i in nn)
{
var p = new P { X = i[0], Y = i[1] };
var dist = origin.Distance(p.X,p.Y);
s.Knn.NNs.Add(new PDist {Point = p, Distance = dist});
}
sw.Stop();
return sw.ElapsedMilliseconds;
}
// K nearest neighbor
protected void UpdateKnnGridStrategy(IAlgorithm s, int max, KnnConfiguration conf)
{
var g = s.GridContainer;
var nn = s.Knn;
var square = s.Rectangle.Square;
var currRing = new List<IPDist>();
var nextRing = new List<IPDist>();
for (var i = 1; i <= max; i++)
{
var temp = new List<IPDist>();
foreach (var p in nextRing)
{
if (p.Distance < i * square) currRing.Add(p);
else temp.Add(p);
}
nextRing.Clear();
nextRing.AddRange(temp);
var list = g.GetRing(nn.Origin, i);
// First 9 squares, dont include origin
if (i == 1) list.AddRange(g.GetSet(nn.Origin).Where(a => !a.Equals(nn.Origin)).ToList());
// Only NN on same type if set
if (conf.SameTypeOnly) list = list.Where(a => a.Type == nn.Origin.Type).ToList();
var dataWasAdded = false;
foreach (var p in list)
{
var dist = nn.Origin.Distance(p.X, p.Y);
if(dist >= conf.MaxDistance) continue; // not within max distance
if (dist < i * square) currRing.Add(new PDist { Point = p, Distance = dist });
else nextRing.Add(new PDist { Point = p, Distance = dist });
dataWasAdded = true;
}
if(conf.MaxDistance.HasValue && !dataWasAdded) break; // max distance used and no new data was added, then we are done
if (currRing.Count >= nn.K) break; // enough neighbors? then done
}
if (currRing.Count < nn.K)
{
// Only NN on same type if set
currRing.AddRange(conf.SameTypeOnly
? nextRing.Where(a => a.Point.Type == nn.Origin.Type).ToList()
: nextRing);
if (conf.MaxDistance.HasValue) currRing = currRing.Where(i => i.Distance < conf.MaxDistance.Value).ToList();
}
currRing.Sort();
nn.NNs = currRing.Count > nn.K ? currRing.Take(nn.K).ToList() : currRing.ToList();
}
static void Run()
{
// Config
var rect = new Rectangle
{
XMin = -200,
XMax = 200,
YMin = -100,
YMax = 100,
MaxDistance = 20,
};
rect.Validate();
var conf = new KnnConfiguration { K = 100 };
// Random points
IPoints points = new Points();
var rand = new Random();
for (var i = 0; i < 500000; i++)
{
var x = rect.XMin + rand.NextDouble() * rect.Width;
var y = rect.YMin + rand.NextDouble() * rect.Height;
points.Data.Add(new P
{
X = x,
Y = y,
});
}
points.Round(3);
// Init algo
IAlgorithm algo =
new Algorithm(points, rect, StrategyType.Grid);
// Use algo
var origin = new P { X = 0, Y = 0 };
var duration = algo.UpdateKnn(origin, conf);
// Print result
WL(string.Format("{0} msec. {1}:", algo.Strategy.Name, duration));
WL("K Nearest Neighbors:");
WL(string.Format("Origin: {0}", origin));
WL(string.Format("Distance sum: {0}", algo.Knn.GetDistanceSum()));
algo.Knn.NNs.OrderBy(i => i.Distance).ToList().ForEach(WL);
// Update strategy
algo.SetAlgorithmStrategy(new NaiveStrategy());
// Use algo
duration = algo.UpdateKnn(origin, conf);
// Print result
WL(string.Format("\n{0} msec. {1}:", algo.Strategy.Name, duration));
WL("K Nearest Neighbors:");
WL(string.Format("Distance sum: {0}", algo.Knn.GetDistanceSum()));
algo.Knn.NNs.OrderBy(i => i.Distance).ToList().ForEach(WL);
}
// O(n * m) where m is grid cells
public long UpdateKnn(IAlgorithm s, IP p, KnnConfiguration conf)
{
if (conf == null) conf = new KnnConfiguration();
var sw = new Stopwatch();
sw.Start();
var max = Math.Max(s.Rectangle.XGrid, s.Rectangle.YGrid);
s.Knn.Clear();
s.Knn.Origin = p;
s.Knn.K = conf.K;
UpdateKnnGridStrategy(s, max, conf);
sw.Stop();
return sw.ElapsedMilliseconds;
}
/// <summary>
/// O(n * k * logk) // much faster than O(n logn) for k << n
/// </summary>
/// <param name="s"></param>
/// <param name="p"></param>
/// <param name="conf"></param>
/// <returns></returns>
public override long UpdateKnn(IAlgorithm s, IP p, KnnConfiguration conf)
{
if (conf == null) conf = new KnnConfiguration();
var sw = new Stopwatch();
sw.Start();
s.Knn.Clear();
s.Knn.Origin = p;
s.Knn.K = conf.K;
//var all = new List<IPDist>();
var sortedList2 = new SortedList2();
var n = s.Points.Count;
for (var i = 0; i < n; i++)
{
var p1 = s.Points[i];
if (p.Equals(p1)) continue; // don't include origin
if (conf.SameTypeOnly && p.Type != p1.Type) continue; // only same type used
var dist = p.Distance(p1.X, p1.Y);
if (dist >= conf.MaxDistance) continue;
var pdist = new PDist { Point = p1, Distance = dist };
//all.Add(pdist);
sortedList2.Add(pdist, conf.K);
}
//s.Knn.NNs = all.OrderBy(i => i.Distance).Take(conf.K).ToList(); // O(n logn)
s.Knn.NNs = sortedList2.GetAll(); // O(n * k * logk)
sw.Stop();
return sw.ElapsedMilliseconds;
}
public long UpdateKnn(IP p, KnnConfiguration configuration)
{
UpdateIndex(p);
return Strategy.UpdateKnn(this, p, configuration);
}
// Example of usage:
// Get 3 nearest -> /AreaGMC/gmc.svc/Knn/lat=8_5;lon=10_25;k=3
// Get 3 nearest type 1 -> /AreaGMC/gmc.svc/Knn/lat=8_5;lon=10_25;k=3;type=1
// Get nearest within 1 km -> /AreaGMC/gmc.svc/Knn/lat=8_5;lon=10_25;k=1000000;dist=1
public JsonKnnReply Knn(string s)
{
var sw = new Stopwatch();
sw.Start();
var invalid = new JsonKnnReply {};
if (string.IsNullOrEmpty(s))
{
invalid.EMsg = "param is empty";
return invalid;
}
var arr = s.Split(new[] { ";" }, StringSplitOptions.RemoveEmptyEntries);
if (arr.Length < 3)
{
invalid.EMsg = string.Format("param length is not valid: {0}",arr.Length);
return invalid;
}
var nvc = new NameValueCollection();
foreach (var a in arr)
{
var kv = a.Split(new[] { "=" }, StringSplitOptions.RemoveEmptyEntries);
if (kv.Length != 2) continue;
nvc.Add(kv[0], kv[1]);
}
foreach (var key in Ajax.KnnReq)
{
if (nvc[key] != null) continue;
invalid.EMsg = string.Format("param {0} is missing", key);
return invalid;
}
try
{
var y = nvc[Ajax.lat].Replace("_", ".").ToDouble();
var x = nvc[Ajax.lon].Replace("_", ".").ToDouble();
var k = int.Parse(nvc[Ajax.k]);
var type = nvc[Ajax.type] == null ? -1 : int.Parse(nvc[Ajax.type]);
double? dist = null;
if(! string.IsNullOrEmpty(nvc[Ajax.dist])) dist = nvc[Ajax.dist].Replace("_", ".").ToDouble();
// knn algo
var algo = MemoryDatabase.Data as IKnnAlgorithm;
if (algo == null)
{
invalid.EMsg = "algorithm is not available";
return invalid;
}
// Use algo
var origin = new SingleDetectLibrary.Code.Data.P { X = x, Y = y, Type = type };
var knnSameTypeOnly = type != -1;
var conf = new KnnConfiguration {K = k, SameTypeOnly = knnSameTypeOnly, MaxDistance = dist};
var duration = algo.UpdateKnn(origin, conf);
var nns = algo.Knn.NNs.Select(p => p as PDist).ToList();
var gmsNns = new List<GmcPDist>();
foreach (var i in nns)
{
//i.Distance = Math.Round(i.Distance, 7);
var pdist = new GmcPDist
{
Id = i.Point.Uid.ToString(),
Point = i.Point,
Distance = Math.Round(i.Distance, 7)
};
gmsNns.Add(pdist);
}
var result =
new JsonKnnReply
{
Data = string.Format("Distance in km, x: {0}; y: {1}; k: {2}; sameTypeOnly: {3}, algo msec: {4}",
x.DoubleToString(), y.DoubleToString(), k, knnSameTypeOnly, duration),
Nns = gmsNns, // cannot be interface, thus casting
Msec = Sw(sw),
};
return result;
}
catch (Exception ex)
{
invalid.EMsg = string.Format("Parsing error param: {0}",
ex.Message);
return invalid;
}
}
public abstract long UpdateKnn(IAlgorithm s, IP p, KnnConfiguration configuration);
