public void MTreeAddTest()
{
MTree <IPoint> tree = new MTree <IPoint>(2, 3, (x, y) => GeometryDistanceAlgorithm.Distance(x, y));
tree.Add(this.geometries[0]);
tree.NumberOfDataItems.ShouldBe(1);
tree.Add(this.geometries[1]);
tree.NumberOfDataItems.ShouldBe(2);
tree.Add(this.geometries[2]);
tree.NumberOfDataItems.ShouldBe(3);
tree.Add(this.geometries[3]);
tree.NumberOfDataItems.ShouldBe(4);
for (int i = 4; i < this.geometries.Count; i++)
{
tree.Add(this.geometries[i]);
}
tree.NumberOfDataItems.ShouldBe(this.geometries.Count);
tree = new MTree <IPoint>(2, 3, (x, y) => GeometryDistanceAlgorithm.Distance(x, y));
tree.Add(this.geometries);
tree.NumberOfDataItems.ShouldBe(this.geometries.Count);
Should.Throw <ArgumentNullException>(() => tree.Add((IPoint)null));
Should.Throw <ArgumentNullException>(() => tree.Add((IEnumerable <IPoint>)null));
// try to insert item already in the tree
Should.Throw <ArgumentException>(() => tree.Add(this.geometries[0]));
}
private void PopulateTree <T>(MTree <T> tree, List <T> points)
{
foreach (T point in points)
{
tree.Add(point);
}
}
public void RangeSearchTest()
{
int maxItems = 10000;
int maxNodes = 25;
double distThreshold = 1000;
Random rand = new Random();
CartesianPoint testPoint = new CartesianPoint(0, 0);
MTree <CartesianPoint> tree = new MTree <CartesianPoint>(CartesianPoint.PythagoreanTheorem, maxNodes);
List <CartesianPoint> itemsInThreshold = new List <CartesianPoint>();
CartesianPoint newPoint;
for (int i = 0; i < maxItems; i++)
{
int xMultiplier = rand.Next(-2, 1);
while (xMultiplier == 0)
{
xMultiplier = rand.Next(-2, 1);
}
int yMultiplier = rand.Next(-2, 1);
while (yMultiplier == 0)
{
yMultiplier = rand.Next(-2, 1);
}
double x = maxItems * xMultiplier * rand.NextDouble() * 0.05;
double y = maxItems * yMultiplier * rand.NextDouble() * 0.05;
newPoint = new CartesianPoint(x, y);
tree.Add(newPoint);
double dist = tree.GetDistance(newPoint, testPoint);
if (dist <= distThreshold)
{
itemsInThreshold.Add(newPoint);
}
}
List <CartesianPoint> neighbors = tree.RangeSearch(testPoint, distThreshold);
Assert.AreEqual(itemsInThreshold.Count, neighbors.Count, "RangeSearch did not return the correct number of elements.");
foreach (var neighbor in neighbors)
{
double dist = tree.GetDistance(neighbor, testPoint);
Assert.IsTrue(dist <= distThreshold, "RangeSearch returned an item outside of the search radius.");
Assert.IsTrue(itemsInThreshold.Contains(neighbor), "RangeSearch returned an invalid item");
}
foreach (var closeItem in itemsInThreshold)
{
Assert.IsTrue(neighbors.Contains(closeItem), "RangeSearch did not return an item within the search radius.");
}
}
public void KNearestNeighborsTest()
{
int maxItems = 10000;
int k = 100;
Random rand = new Random();
CartesianPoint testPoint = new CartesianPoint(0, 0);
MTree <CartesianPoint> tree = new MTree <CartesianPoint>(CartesianPoint.PythagoreanTheorem);
PriorityQueue <CartesianPoint> kNeighbors = new PriorityQueue <CartesianPoint>(k);
CartesianPoint newPoint;
for (int i = 0; i < maxItems; i++)
{
int xMultiplier = rand.Next(-2, 1);
while (xMultiplier == 0)
{
xMultiplier = rand.Next(-2, 1);
}
int yMultiplier = rand.Next(-2, 1);
while (yMultiplier == 0)
{
yMultiplier = rand.Next(-2, 1);
}
double x = maxItems * xMultiplier * rand.NextDouble() * 0.05;
double y = maxItems * yMultiplier * rand.NextDouble() * 0.05;
newPoint = new CartesianPoint(x, y);
tree.Add(newPoint);
double dist = tree.GetDistance(newPoint, testPoint);
kNeighbors.Enqueue(newPoint, dist);
}
PriorityQueue <CartesianPoint> queryReturns = tree.KNearestNeighborSearch(testPoint, k);
Assert.AreEqual(k, queryReturns.Count, "K neighor search did not return the correct number of items.");
while (kNeighbors.HasNext)
{
var neighbor = kNeighbors.Dequeue();
var result = queryReturns.Dequeue();
Assert.AreEqual(neighbor.Value, result.Value, "K neighbor search returned wrong item.");
Assert.AreEqual(neighbor.Key, result.Key, "K neighbor search returned correct item with wrong distance.");
}
Assert.IsFalse(queryReturns.HasNext, "K neighbor search returned too many items.");
}
public void MTreeSearchTest()
{
MTree <IPoint> tree = new MTree <IPoint>(2, 3, (x, y) => GeometryDistanceAlgorithm.Distance(x, y));
tree.Search(this.geometries[0]).ShouldBeEmpty();
IPoint[] points = new IPoint[9];
for (Int32 i = 0; i < 9; i++)
{
points[i] = this.factory.CreatePoint(i, 0);
tree.Add(points[i]);
}
// search without limits should return all items in the tree
tree.Search(this.factory.CreatePoint(2, 0)).Count().ShouldBe(9);
// search returns the correct data items in the correct order with correct distance information
List <ResultItem <IPoint> > results = new List <ResultItem <IPoint> >(tree.Search(this.factory.CreatePoint(8, 0)));
List <IPoint> expectedResults = new List <IPoint>(points.Reverse());
for (Int32 i = 0; i < points.Length; i++)
{
results[i].Item.ShouldBe(expectedResults[i]);
results[i].Distance.ShouldBe(i);
}
// search with a given radius should return only the elements within that radius
tree.Search(this.factory.CreatePoint(8, 0), 1.0D).Count().ShouldBe(2);
tree.Search(this.factory.CreatePoint(7, 0), 1.0D).Count().ShouldBe(3);
tree.Search(this.factory.CreatePoint(9, 0), 1.0D).Count().ShouldBe(1);
tree.Search(this.factory.CreatePoint(10, 0), 1.0D).Count().ShouldBe(0);
// search with a given limit should return only that amount of elements
tree.Search(this.factory.CreatePoint(2, 0), 0).Count().ShouldBe(0);
tree.Search(this.factory.CreatePoint(2, 0), 1).Count().ShouldBe(1);
tree.Search(this.factory.CreatePoint(2, 0), 5).Count().ShouldBe(5);
tree.Search(this.factory.CreatePoint(2, 0), 10).Count().ShouldBe(9);
// search with both radius and limit where radius contains less elements than limit
tree.Search(this.factory.CreatePoint(2, 0), 1.1D, 5).Count().ShouldBe(3);
// search with both radius and limit where radius contains more elements than limit
tree.Search(this.factory.CreatePoint(2, 0), 1.1D, 2).Count().ShouldBe(2);
// errors
Should.Throw <ArgumentNullException>(() => tree.Search(null));
}
public void ContainsTest()
{
int maxNodeSize = 25;
int numItems = 10000;
MTree <int> tree = new MTree <int>((x, y) => Math.Abs(x - y), maxNodeSize);
for (int i = 0; i < numItems; i++)
{
tree.Add(i);
Assert.AreEqual(i + 1, tree.Count, "Count is not returning the correct value.");
}
for (int i = 0; i < numItems; i++)
{
Assert.IsTrue(tree.Contains(i), "Contains is returning false for a value that has been inserted in the MTree.");
}
}
public static void Function()
{
MTree <int> mTree = new MTree <int>();
mTree.Add(123);
mTree.Add(324);
mTree.Add(45);
mTree.Add(78);
mTree.Add(126653);
mTree.Add(144523);
mTree.Add(1624444443);
mTree.Add(12 + 73);
mTree.MidOrder();
WriteLine("--------------------------------------------------");
mTree.PreOrder();
WriteLine("--------------------------------------------------");
mTree.PostOrder();
WriteLine("--------------------------------------------------");
WriteLine(mTree.Max());
}
public void ItemInsertVerification()
{
int maxItems = 1000;
int maxNodes = 25;
Random rand = new Random();
MTree <CartesianPoint> tree = new MTree <CartesianPoint>(CartesianPoint.PythagoreanTheorem, maxNodes);
CartesianPoint newPoint;
for (int i = 1; i <= maxItems; i++)
{
int xMultiplier = rand.Next(-2, 1);
while (xMultiplier == 0)
{
xMultiplier = rand.Next(-2, 1);
}
int yMultiplier = rand.Next(-2, 1);
while (yMultiplier == 0)
{
yMultiplier = rand.Next(-2, 1);
}
double x = maxItems * xMultiplier * rand.NextDouble() * 0.05;
double y = maxItems * yMultiplier * rand.NextDouble() * 0.05;
newPoint = new CartesianPoint(x, y);
tree.Add(newPoint);
Assert.AreEqual(i, tree.Count, "MTree does not give correct Count after adding a new element.");
Assert.IsTrue(tree.Contains(newPoint), "MTree does not say it Contains new item that has been added.");
NodeDescentAssert(tree.Root, 1, maxNodes);
}
}
static void Main(string[] args)
{
var mtreeStopwatch = new Stopwatch();
var fastMtreeStopWatch = new Stopwatch();
var originalTimes = new List <long>();
var fastTimes = new List <long>();
var dataSize = 100000;
var testDataSize = 50;
var range = 1000000;
var neighbors = 10;
var dimensions = 1000;
Console.WriteLine($"{nameof(dataSize)}: {dataSize}");
Console.WriteLine($"{nameof(dimensions)}: {dimensions}");
Console.WriteLine($"{nameof(neighbors)}: {neighbors}");
Console.WriteLine();
var testData = Supercluster.Tests.Utilities.GenerateDoubles(testDataSize, range, dimensions);
for (int index = 0; index < testData.Length; index++)
{
var treeData = Supercluster.Tests.Utilities.GenerateDoubles(dataSize, range, dimensions);
var target = testData[index];
// 1. Build Trees
var fastMtree = new FastMTree <double[]> {
Capacity = 3, Metric = Metrics.L2Norm_Double
};
foreach (var point in treeData)
{
fastMtree.Add(point);
}
var mtree = new MTree <double[]> {
Capacity = 3, Metric = Metrics.L2Norm_Double
};
foreach (var point in treeData)
{
mtree.Add(point);
}
GC.Collect();
GCLatencyMode oldMode = GCSettings.LatencyMode;
// Make sure we can always go to the catch block,
// so we can set the latency mode back to `oldMode`
RuntimeHelpers.PrepareConstrainedRegions();
try
{
GCSettings.LatencyMode = GCLatencyMode.LowLatency;
// Measure Trees
mtreeStopwatch.Start();
var resultsList = mtree.NearestNeighbors(target, neighbors).ToArray();
mtreeStopwatch.Stop();
fastMtreeStopWatch.Start();
var fastResults = fastMtree.NearestNeighbors(target, neighbors).ToArray();
fastMtreeStopWatch.Stop();
// Generation 2 garbage collection is now
// deferred, except in extremely low-memory situations
}
finally
{
// ALWAYS set the latency mode back
GCSettings.LatencyMode = oldMode;
}
// Print times
if (index != 0) // We skip first run because of jitting
{
// Record Times
originalTimes.Add(mtreeStopwatch.ElapsedTicks);
fastTimes.Add(fastMtreeStopWatch.ElapsedTicks);
Console.WriteLine(mtreeStopwatch.ElapsedTicks + " " + fastMtreeStopWatch.ElapsedTicks);
}
// reset stopwatches
mtreeStopwatch.Reset();
fastMtreeStopWatch.Reset();
}
Console.WriteLine("Average: " + originalTimes.Average() + " " + fastTimes.Average());
Console.Read();
}
