HsRangeCa CalculateHsRangeCa(string bucketCounts, int [] samplesCount, bool isVerbose)
{
ClusterTree rt = new ClusterTree();
Props parameters = GetParams(bucketCounts);
parameters.Set("IsCreatingClusterTree", "true");
HsRangeCa ca = new HsRangeCa(parameters);
CaMcGen gen = new CaMcGen
{
Clusterizer = ca,
IsVerbose = isVerbose,
// IsVerboseSamples = true,
RngSeed = 0,
SamplesCount = samplesCount
};
rt.Root = gen.Generate();
string fileName = Path.Combine(_outDir, bucketCounts.Replace(' ', 'x')) + ".dat";
rt.Write(fileName);
parameters.Set("ClusterTreeFile", fileName);
parameters.Set("IsCreatingClusterTree", "false");
HsRangeCa ca1 = new HsRangeCa(parameters);
return(ca1);
}
HsSdKMeansAdaptiveCa CalculateCa(Props parameters, int[] samplesCount, int rngSeed)
{
ClusterTree rt = new ClusterTree();
parameters.Set("IsCreatingClusterTree", "true");
HsSdKMeansAdaptiveCa ca = new HsSdKMeansAdaptiveCa(parameters);
CaMcGen gen = new CaMcGen
{
Clusterizer = ca,
IsVerbose = false,
// IsVerboseSamples = true,
RngSeed = rngSeed,
SamplesCount = samplesCount
};
rt.Root = gen.Generate();
string fileName = Path.Combine(_outDir, "ca-hssd-km.dat");
rt.Write(fileName);
parameters.Set("ClusterTreeFile", fileName);
parameters.Set("IsCreatingClusterTree", "false");
HsSdKMeansAdaptiveCa ca1 = new HsSdKMeansAdaptiveCa(parameters);
return(ca1);
}
public void Test_ReadWrite()
{
ClusterTree rt1 = new ClusterTree();
RangeNode root = new RangeNode(5);
rt1.Root = root;
for (int i = 0; i < 5; ++i)
{
root.Children[i] = new RangeNode(0)
{
UpperLimit = 0.1f * i
};
}
rt1.Version.UserDescription = "Bla bla";
string fileName = Path.Combine(_outDir, "ClusterTree.dat");
rt1.Write(fileName);
ClusterTree rt2 = ClusterTree.Read(fileName);
Assert.AreEqual(rt1.Version, rt2.Version);
Assert.IsTrue(CompareTrees <int, int> .Compare(rt1, rt1.Root, rt2, rt2.Root,
(t1, n1, t2, n2) =>
{
return(((RangeNode)n1).UpperLimit == ((RangeNode)n2).UpperLimit);
}));
}
static int Main(string[] args)
{
if (!Parser.ParseArgumentsWithUsage(args, _cmdLine))
{
return(1);
}
if (_cmdLine.DebuggerLaunch)
{
Debugger.Launch();
}
Props caProps = XmlSerializerExt.Deserialize <Props>(_cmdLine.ChanceAbstractionFile);
caProps.Set("IsCreatingClusterTree", "true");
IChanceAbstraction ca = ChanceAbstractionHelper.CreateFromProps(caProps);
Console.WriteLine("CA: {0}", ca.Name);
List <int> samplesCount = new List <int>();
foreach (string sc in _cmdLine.SamplesCount.Split(new char[] { ',' }, StringSplitOptions.RemoveEmptyEntries))
{
samplesCount.Add(int.Parse(sc));
}
int rngSeed = _cmdLine.RngSeed == 0 ? (int)DateTime.Now.Ticks : _cmdLine.RngSeed;
Console.WriteLine("RNG seed: {0}", rngSeed);
CaMcGen gen = new CaMcGen
{
Clusterizer = (IClusterizer)ca,
IsVerbose = true,
// IsVerboseSamples = true,
RngSeed = rngSeed,
SamplesCount = samplesCount.ToArray()
};
ClusterTree rt = new ClusterTree();
rt.Root = gen.Generate();
string dir = Path.GetDirectoryName(_cmdLine.ChanceAbstractionFile);
string file = Path.GetFileNameWithoutExtension(_cmdLine.ChanceAbstractionFile) + ".dat";
string fileName = Path.Combine(dir, file);
Console.WriteLine("Writing range tree to {0}", fileName);
rt.Write(fileName);
return(0);
}
public void TestBigClusterTree()
{
DbMongo sqlDB = new DbMongo("SingleFile");
List <Rectangle> rects = new List <Rectangle>();
List <string> coords = sqlDB.GetRectanglesFromLines();
foreach (string coord in coords)
{
rects.Add(new Rectangle(coord));
}
Stopwatch timer = Stopwatch.StartNew();
ClusterTree ct = new ClusterTree(rects.ToArray());
timer.Stop();
Assert.IsTrue(timer.ElapsedMilliseconds < 3 * rects.Count);
for (int i = 0; i < ct.Clusters.Count; i++)
{
for (int j = 0; j < ct.Clusters.Count; j++)
{
Rectangle rec1 = ct.Clusters[i].BoundBox;
Rectangle rec2 = ct.Clusters[j].BoundBox;
if (rec1.Equals(rec2))
{
continue;
}
Rectangle notRound1 = new Rectangle(9571.0563, 11257.8221, 12095.1892, 13879.5525);
Rectangle notRound2 = new Rectangle(6559.4258, 4018.8264, 16465.4917, 13169.6058);
if (Math.Round(rec1.MinPoint.X, 0) == 3704)
{
//throw new System.ExecutionEngineException();
if (Math.Round(rec2.MinPoint.X, 0) == 9571)
{
Debug.WriteLine("Here we should intersect");
}
}
if (rec1.Intersects(rec2))
{
Assert.Fail("There's an interesection between clusters");
}
}
}
}
private static void Visualize(string rtFile)
{
ClusterTree rt = ClusterTree.Read(rtFile);
string fileName = rtFile + ".gv";
using (TextWriter output = new StreamWriter(fileName))
{
var vis = new ClusterTree.Vis
{
Output = output,
ShowDealPath = _cmdLine.ShowPath
};
vis.Walk(rt, rt.Root);
}
}
public void TestClustersSmall()
{
// at level1:
// ((0, 0) (150, 350))
// rectangles[0..1]
// ((550, 250) (650, 350))
// rectangles[2..3]
// ((750, 50) (900, 250))
// rectangles[4..6]
Rectangle[] rectangles1 = new Rectangle[7];
for (int i = 0; i < rectangles.Length; i++)
{
rectangles1[rectangles.Length - i - 1] = rectangles[i];
}
ct = new ClusterTree(rectangles1);
// Getting clusters at level 1
List <ClusterTree.Cluster> clusters = ct.Clusters;
// Check number of clusters in
int rectCount = clusters.Count;
Assert.AreEqual(4, rectCount);
int grade = 0;
Rectangle rect1 = new Rectangle(0, 0, 350, 150);
Rectangle rect2 = new Rectangle(550, 250, 650, 350);
Rectangle rect3 = new Rectangle(750, 50, 900, 250);
Rectangle rect4 = new Rectangle(575, 275, 625, 325);
foreach (ClusterTree.Cluster cluster in clusters)
{
// Gain grage++ if current cluster equals one of rectangles
if (rect1.Equals(cluster.BoundBox))
{
// Check contents match
List <Rectangle> expectedContents = new List <Rectangle>();
expectedContents.Add(rectangles[0]);
expectedContents.Add(rectangles[1]);
foreach (var rect in expectedContents)
{
Assert.IsTrue(cluster.Contains(rect));
}
// Increase grade
grade++;
}
if (rect2.Equals(cluster.BoundBox))
{
// Check contents match
List <Rectangle> expectedContents = new List <Rectangle>();
expectedContents.Add(rectangles[2]);
foreach (var rect in expectedContents)
{
Assert.IsTrue(cluster.Contains(rect));
}
// Increase grade
grade++;
}
if (rect3.Equals(cluster.BoundBox))
{
// Check contents match
List <Rectangle> expectedContents = new List <Rectangle>();
expectedContents.Add(rectangles[4]);
expectedContents.Add(rectangles[5]);
expectedContents.Add(rectangles[6]);
foreach (var rect in expectedContents)
{
Assert.IsTrue(cluster.Contains(rect));
}
// Increase grade
grade++;
}
if (rect4.Equals(cluster.BoundBox))
{
// Check contents match
List <Rectangle> expectedContents = new List <Rectangle>();
expectedContents.Add(rectangles[3]);
foreach (var rect in expectedContents)
{
Assert.IsTrue(cluster.Contains(rect));
}
// Increase grade
grade++;
}
}
// Check whether we have enough grade to pass
// If each rectangle in list was met, grade will have
Assert.AreEqual(4, grade);
}
