/// <summary>
/// Build the index
/// </summary>
public virtual void Build(MetricDB db, int bsize, Random rand)
{
this.DB = db;
var n = this.DB.Count;
// randomized has very good performance, even compared with more "intelligent" strategies
var dseq = new DynamicSequentialOrdered ();
dseq.Build (db, rand);
this.NODES = new List<Node> (n / bsize + 1);
var L = new List<ItemPair> (n);
while (dseq.Count > 0) {
if (this.NODES.Count % 100 == 0) {
Console.WriteLine ("XXX {0}, bucketSize: {1}, remain {2}/{3}, db: {4}, date-time: {5}",
this, bsize, dseq.Count, db.Count, Path.GetFileName(db.Name), DateTime.Now);
}
var refID = dseq.GetAnyItem ();
dseq.Remove (refID);
L.Clear ();
dseq.ComputeDistances (this.DB[refID], L);
var near = new Result(bsize);
var far = new Result (1);
dseq.AppendKExtremes (near, far, L);
var node = new Node (refID);
this.NODES.Add (node);
dseq.Remove (near);
foreach (var p in near) {
node.Add(p.ObjID, p.Dist);
}
}
}
