public static void Full_Sys_Test_Alternative()
{
int dim = 32;
int testcases = 20;
int dws = 80;
int K = 20;
int maxSearch = 500;
int ntrees = 3;
int nrand = 100;
int ddeter = 1;
double ratio = .4;
double prune = 1.5;
Random random = new Random();
PointSet ps = new PointSet("ColorHistogram.asc", 1, ' ');
ps.NormalizePoints();
//Indexes
var bruteForce = new BruteForce(ps);
var standardTree = new KDTree(ps, false);
var standardForest = new KDTreeForestHolder(ps, ddeter, nrand, false, false);
//Result holders
var standardDist = new List <double>();
var queryDist = new List <double>();
var standardDist_f = new List <double>();
for (int i = 0; i < dws; i++)
{
Console.WriteLine(dim + " " + i);
var querydw = new DimWeight(dim, random);
var queryTree = new KDTree(ps, querydw, false);
for (int j = 0; j < testcases; j++)
{
var p = ps.Points[random.Next(ps.Points.Count())];
var bfd = bruteForce.GetKNN(p, K, querydw).GetMeanDistance(p, querydw);
standardDist.Add(standardTree.root.GetANN(p, K, maxSearch, querydw).GetMeanDistance(p, querydw) / bfd - 1);
queryDist.Add(queryTree.root.GetANN(p, K, maxSearch, querydw).GetMeanDistance(p, querydw) / bfd - 1);
standardDist_f.Add(standardForest.GetANN(p, querydw, K, ntrees, ratio, prune, maxSearch).GetMeanDistance(p, querydw) / bfd - 1);
}
}
Console.WriteLine(standardDist.Average() + "," + standardDist_f.Average() + "," + queryDist.Average());
}
public static void Full_Sys_Test_Nrand()
{
int dim = 8;
int npoint = 100000;
int testcases = 20;
int dws = 80;
int K = 20;
int maxSearch = 500;
int ntrees = 3;
var nrands = new List <int>()
{
20, 50, 100, 200, 400
};
int ddeter = 1;
double ratio = .4;
double prune = 1.5;
var lines = new List <string>();
string filename = "resultsnrand.csv";
Random random = new Random();
foreach (var nrand in nrands)
{
PointSet ps = new PointSet(dim);
for (int i = 0; i < npoint; i++)
{
ps.AddPoint(new Point(dim, random));
}
//Indexes
var bruteForce = new BruteForce(ps);
var standardTree = new KDTree(ps, false);
var standardForest = new KDTreeForestHolder(ps, ddeter, nrand, false, false);
//Result holders
var standardDist = new List <double>();
var queryDist = new List <double>();
var standardDist_f = new List <double>();
for (int i = 0; i < dws; i++)
{
Console.WriteLine(dim + " " + i);
var querydw = new DimWeight(dim, random);
var queryTree = new KDTree(ps, querydw, false);
for (int j = 0; j < testcases; j++)
{
var p = new Point(dim, random);
var bfd = bruteForce.GetKNN(p, K, querydw).GetMeanDistance(p, querydw);
standardDist.Add(standardTree.root.GetANN(p, K, maxSearch, querydw).GetMeanDistance(p, querydw) / bfd - 1);
queryDist.Add(queryTree.root.GetANN(p, K, maxSearch, querydw).GetMeanDistance(p, querydw) / bfd - 1);
double val = standardForest.GetANN(p, querydw, K, ntrees, ratio, prune, maxSearch).GetMeanDistance(p, querydw) / bfd - 1;
if (!Double.IsNaN(val) && val < 1000)
{
standardDist_f.Add(val);
}
}
}
lines.Add(standardDist.Average() + "," + standardDist_f.Average() + "," + queryDist.Average());
}
System.IO.File.WriteAllLines(filename, lines);
}
public static void Full_Sys_Test_nSearch()
{
int dim = 8;
int npoint = 100000;
int testcases = 20;
int dws = 80;
int K = 20;
var maxSearchs = new List <int>()
{
50, 200, 500, 2000, 8000
};
int ntrees = 3;
int nrand = 100;
int ddeter = 1;
double ratio = .4;
double prune = 1.5;
var lines = new List <string>();
string filename = "resultsnsearch.csv";
Random random = new Random();
PointSet ps = new PointSet(dim);
for (int i = 0; i < npoint; i++)
{
ps.AddPoint(new Point(dim, random));
}
//Indexes
var bruteForce = new BruteForce(ps);
var standardTree = new KDTree(ps, false);
var standardForest = new KDTreeForestHolder(ps, ddeter, nrand, false, false);
//Result holders
var standardDist = new List <List <double> >();
var queryDist = new List <List <double> >();
var standardDist_f = new List <List <double> >();
for (int i = 0; i < maxSearchs.Count(); i++)
{
standardDist.Add(new List <double>());
queryDist.Add(new List <double>());
standardDist_f.Add(new List <double>());
}
for (int i = 0; i < dws; i++)
{
Console.WriteLine(dim + " " + i);
var querydw = new DimWeight(dim, random);
var queryTree = new KDTree(ps, querydw, false);
for (int j = 0; j < testcases; j++)
{
var p = new Point(dim, random);
var bfd = bruteForce.GetKNN(p, K, querydw).GetMeanDistance(p, querydw);
foreach (var maxSearch in maxSearchs)
{
int indx = 0;
standardDist[indx].Add(standardTree.root.GetANN(p, K, maxSearch, querydw).GetMeanDistance(p, querydw) / bfd - 1);
queryDist[indx].Add(queryTree.root.GetANN(p, K, maxSearch, querydw).GetMeanDistance(p, querydw) / bfd - 1);
standardDist_f[indx].Add(standardForest.GetANN(p, querydw, K, ntrees, ratio, prune, maxSearch).GetMeanDistance(p, querydw) / bfd - 1);
indx++;
}
}
}
for (int i = 0; i < standardDist.Count(); i++)
{
lines.Add(standardDist[i].Average() + "," + queryDist[i].Average() + "," + standardDist_f[i].Average());
}
System.IO.File.WriteAllLines(filename, lines);
}
public static void Full_Sys_Test_ExtremeDRV()
{
int dim = 8;
int npoint = 100000;
int testcases = 10;
int dws = 50;
int K = 20;
int maxSearch = 500;
int ntrees = 3;
int nrand = 50;
int ddeter = 3;
double ratio = .4;
double prune = 1.5;
double selper = .125;
Random random = new Random();
PointSet ps = new PointSet(dim);
for (int i = 0; i < npoint; i++)
{
ps.AddPoint(new Point(dim, random));
}
////garbage
//var p2 = new Point(dim, random);
//var querydw2 = new DimWeight(dim, 0, random);
//var queryTree2 = new KDTree(ps, querydw2, false);
//var tmp = queryTree2.root.GetANN(p2, K, maxSearch, querydw2);
//Indexes
var bruteForce = new BruteForce(ps);
var standardTree = new KDTree(ps, false);
var standardForest = new KDTreeForestHolder(ps, ddeter, nrand, false, false);
var standardTree_r = new KDTree(ps, true);
var standardForest_r = new KDTreeForestHolder(ps, ddeter, nrand, false, true);
//Result holders
var standardDist = new List <double>();
var queryDist = new List <double>();
var standardDist_f = new List <double>();
var standardDist_r = new List <double>();
var queryDist_r = new List <double>();
var standardDist_f_r = new List <double>();
for (int i = 0; i < dws; i++)
{
Console.WriteLine(i);
var querydw = new DimWeight(dim, selper, random);
var queryTree = new KDTree(ps, querydw, false);
var queryTree_r = new KDTree(ps, querydw, true);
for (int j = 0; j < testcases; j++)
{
var p = new Point(dim, random);
var bfd = bruteForce.GetKNN(p, K, querydw).GetMeanDistance(p, querydw);
standardDist.Add(standardTree.root.GetANN(p, K, maxSearch, querydw).GetMeanDistance(p, querydw) / bfd - 1);
queryDist.Add(queryTree.root.GetANN(p, K, maxSearch, querydw).GetMeanDistance(p, querydw) / bfd - 1);
standardDist_f.Add(standardForest.GetANN(p, querydw, K, ntrees, ratio, prune, maxSearch).GetMeanDistance(p, querydw) / bfd - 1);
standardDist_r.Add(standardTree_r.root.GetANN(p, K, maxSearch, querydw).GetMeanDistance(p, querydw) / bfd - 1);
queryDist_r.Add(queryTree_r.root.GetANN(p, K, maxSearch, querydw).GetMeanDistance(p, querydw) / bfd - 1);
standardDist_f_r.Add(standardForest_r.GetANN(p, querydw, K, ntrees, ratio, prune, maxSearch).GetMeanDistance(p, querydw) / bfd - 1);
}
}
Console.WriteLine(standardDist.Average() + " " + standardDist_f.Average() + " " + queryDist.Average());
Console.WriteLine(standardDist_r.Average() + " " + standardDist_f_r.Average() + " " + queryDist_r.Average());
Console.WriteLine(stdev(standardDist) + " " + stdev(standardDist_f) + " " + stdev(queryDist));
Console.WriteLine(stdev(standardDist_r) + " " + stdev(standardDist_f_r) + " " + stdev(queryDist_r));
}
