// For almost all methods I should do checks for rank (length), but let's assume everything passed in is correct. This will expedite the program.
public static bool IsCompletelySeparatedWithDiscriminant <L>(List <LabeledVector <L> > v1, List <LabeledVector <L> > v2, out DiscriminantEx <L> discriminant)
{
// Direct calculation: Sw^-1 * (Mean1 - Mean2)
double[] m1 = v1.Select(v => v.Features).SpatialMean();
double[] m2 = v2.Select(v => v.Features).SpatialMean();
double[][] s1 = v1.Select(v => v.Features).ToArray().Covariance();
double[][] s2 = v2.Select(v => v.Features).ToArray().Covariance();
if (s1.All(r => r.All(c => double.IsNaN(c))))
{
foreach (double[] r in s1)
{
for (int i = 0; i < r.Length; i++)
{
r[i] = LDAEx.RND_GENERATOR.Next(10) * LDAEx.COVARIANCE_NAN_REPLACEMENT_MUTLIPLIER;
}
}
}
if (s2.All(r => r.All(c => double.IsNaN(c))))
{
foreach (double[] r in s2)
{
for (int i = 0; i < r.Length; i++)
{
r[i] = LDAEx.RND_GENERATOR.Next(10) * LDAEx.COVARIANCE_NAN_REPLACEMENT_MUTLIPLIER;
}
}
}
double[][] sw = s1.Add(s2);
double[][] sw_inv = Accord.Math.Matrix.Inverse(sw);
double[] w = Accord.Math.Matrix.Dot(sw_inv, m1.Subtract(m2));
w = Accord.Math.Matrix.Normalize(w); // Normalize it -- this step is ESSENTIAL
double v1_min = double.MaxValue;
double v1_max = double.MinValue;
foreach (LabeledVector <L> v in v1)
{
double proj = Accord.Math.Matrix.Dot(w, v.Features);
if (proj < v1_min)
{
v1_min = proj;
}
if (proj > v1_max)
{
v1_max = proj;
}
}
double v2_min = double.MaxValue;
double v2_max = double.MinValue;
foreach (LabeledVector <L> v in v2)
{
double proj = Accord.Math.Matrix.Dot(w, v.Features);
if (proj < v2_min)
{
v2_min = proj;
}
if (proj > v2_max)
{
v2_max = proj;
}
}
if (v2_max < v1_min)
{
// Data set 1 is RIGHT of the projected SET mean
// Data set 2 is LEFT of the projected SET mean
double[] m = v1.Select(v => v.Features).Concat(v2.Select(v => v.Features)).SpatialMean();
discriminant = new DiscriminantEx <L>(w, v2.First().Label, v1.First().Label, Accord.Math.Matrix.Dot(w, m), Accord.Math.Matrix.Dot(w, m2), Accord.Math.Matrix.Dot(w, m1));
return(true);
}
else if (v1_max < v2_min)
{
// Data set 1 is LEFT of the projected SET mean
// Data set 2 is RIGHT of the projected SET mean
double[] m = v1.Select(v => v.Features).Concat(v2.Select(v => v.Features)).SpatialMean();
discriminant = new DiscriminantEx <L>(w, v1.First().Label, v2.First().Label, Accord.Math.Matrix.Dot(w, m), Accord.Math.Matrix.Dot(w, m1), Accord.Math.Matrix.Dot(w, m2));
return(true);
}
else
{
discriminant = null;
return(false);
}
}
public int Spawn(LabeledVector <L> lvector, DistanceDelegate measure, ParallelStrategy parallelStrategy, bool spawnUsingLDA)
{
int nSpawnCount = 0;
if (this.DoesEncloseVector(lvector, measure))
{
if (parallelStrategy == ParallelStrategy.Multithreaded)
{
List <Task> lstSpawnThreads = new List <Task>();
foreach (SphereEx <L> child in this.Children)
{
lstSpawnThreads.Add(Task.Factory.StartNew(c =>
{
nSpawnCount += ((SphereEx <L>)c).Spawn(lvector, measure, ParallelStrategy.SingleThreaded, spawnUsingLDA);
}, child, TaskCreationOptions.LongRunning));
}
Task.WaitAll(lstSpawnThreads.ToArray());
}
else
{
foreach (SphereEx <L> child in this.Children)
{
nSpawnCount += child.Spawn(lvector, measure, ParallelStrategy.SingleThreaded, spawnUsingLDA);
}
}
if (!spawnUsingLDA)
{
#region Regular Spawn
if (!this.Label.Equals(lvector.Label) && !Vector.EqualsEx(this, lvector) && !this.DoesAtLeastOneChildEncloseVector(lvector, measure))
{
this.AddChild(new SphereEx <L>(this.Radius - measure(this, lvector), lvector));
nSpawnCount++;
}
#endregion
}
else
{
#region LDA Spawn
if (!this.DoesAtLeastOneChildEncloseVector(lvector, measure)) // Don't care about label as well as location of lvector
{
bool bContains = false;
List <LabeledVector <L> > lst;
if (!this.LDAVectors.TryGetValue(lvector.Label, out lst))
{
this.LDAVectors.Add(lvector.Label, (lst = new List <LabeledVector <L> >()));
}
else
{
bContains = lst.Any(v => Vector.EqualsEx(v, lvector));
}
if (!bContains)
{
lst.Add(lvector);
if (this.LDAVectors.Keys.Count == 2 && !this.Children.Any())
{
#region If the sphere contains exactly 2 classes, do the following...
// 1. Create another discriminant
// 2. If the discrimant CANNOT separate the classes, do the following...
// 2a. Remove the lvector from the list it was just added to
// 2b. Create new children from the classes
// 2c. Try to spawn the presented LVector in the NEW children
// 2d. Clear the dictionary, LDAVectors
// 2e. If you can't spawn WITHIN the NEW children, add the vector to the this.LDAVectors
// 3. Else (If the discrimant CAN separate the classes), do nothing but assign the property.
bool bIsSeparable = false;
DiscriminantEx <L> discriminant = null;
try
{
//bIsSeparable = LDA.IsCompletelySeparatedWithDiscriminant(this.LDAVectors.ElementAt(0).Value, this.LDAVectors.ElementAt(1).Value, this, out discriminant);
bIsSeparable = LDAEx.IsCompletelySeparatedWithDiscriminant(this.LDAVectors.ElementAt(0).Value, this.LDAVectors.ElementAt(1).Value, out discriminant);
}
catch
{
// Just consume, leaving bIsSeparable = false
}
if (!bIsSeparable)
{
lst.RemoveAt(lst.Count - 1); // Faster than .Remove() as I am not linearly searching
List <SphereEx <L> > lstNewChildren = new List <SphereEx <L> >();
foreach (KeyValuePair <L, List <LabeledVector <L> > > kvp in this.LDAVectors)
{
if (kvp.Value.Any() && !kvp.Key.Equals(this.Label))
{
//Vector vectorCentroid = Vector.Centroid(kvp.Value);
//if (!Vector.EqualsEx(this, vectorCentroid))
//{
// SphereEx<L> child = new SphereEx<L>(this.Radius - measure(this, vectorCentroid), kvp.Key, (IVector)vectorCentroid);
// this.AddChild(child);
// lstNewChildren.Add(child);
// nSpawnCount++;
//}
}
}
//bool hasSpawned = false;
//foreach (SphereEx<L> child in lstNewChildren)
//{
// if (child.DoesEncloseVector(lvector, measure))
// {
// nSpawnCount += child.Spawn(lvector, measure, ParallelStrategy.SingleThreaded, spawnUsingLDA);
// hasSpawned = true;
// }
//}
this.LDAVectors.Clear();
//if (!hasSpawned)
//{
// this.LDAVectors.Add(lvector.Label, new List<LabeledVector<L>>() { lvector });
//}
}
else
{
this.DiscriminantEx = discriminant;
}
#endregion
}
else if (this.LDAVectors.Keys.Count > 2)
{
#region If the sphere contains 3 or more classes, do the following...
// 1. Create children from the OLDER label-sets
// 2. Try to spawn the presented LVector IN the NEW children just created
// 3. Clear the dictionary, LDAVectors
// 4. If you can't spawn WITHIN the NEW children, add the vector to this.LDAVectors
List <SphereEx <L> > lstNewChildren = new List <SphereEx <L> >();
foreach (KeyValuePair <L, List <LabeledVector <L> > > kvp in this.LDAVectors)
{
if (!kvp.Key.Equals(lvector.Label))
{
Vector vectorCentroid = Vector.Centroid(kvp.Value);
if (!Vector.EqualsEx(this, vectorCentroid))
{
SphereEx <L> child = new SphereEx <L>(this.Radius - measure(this, vectorCentroid), kvp.Key, (IVector)vectorCentroid);
this.AddChild(child);
lstNewChildren.Add(child);
nSpawnCount++;
}
}
}
//bool hasSpawned = false;
//foreach (SphereEx<L> child in lstNewChildren)
//{
// if (child.DoesEncloseVector(lvector, measure))
// {
// nSpawnCount += child.Spawn(lvector, measure, ParallelStrategy.SingleThreaded, spawnUsingLDA);
// hasSpawned = true;
// }
//}
this.LDAVectors.Clear();
//if (!hasSpawned)
//{
// this.LDAVectors.Add(lvector.Label, new List<LabeledVector<L>>() { lvector });
//}
#endregion
}
// Note: If this.LDAVectors.Keys.Count == 1, don't do anything additional.
}
}
#endregion
}
}
return(nSpawnCount);
}
public int Spawn(LabeledVector <L> lvector, DistanceDelegate measure, ParallelStrategy parallelStrategy, bool spawnUsingLDA)
{
int nSpawnCount = 0;
if (this.DoesEncloseVector(lvector, measure))
{
if (parallelStrategy == ParallelStrategy.Multithreaded)
{
List <Task> lstSpawnThreads = new List <Task>();
foreach (SphereEx <L> child in this.Children)
{
lstSpawnThreads.Add(Task.Factory.StartNew(c =>
{
nSpawnCount += ((SphereEx <L>)c).Spawn(lvector, measure, ParallelStrategy.SingleThreaded, spawnUsingLDA);
}, child, TaskCreationOptions.LongRunning));
}
Task.WaitAll(lstSpawnThreads.ToArray());
}
else
{
foreach (SphereEx <L> child in this.Children)
{
nSpawnCount += child.Spawn(lvector, measure, ParallelStrategy.SingleThreaded, spawnUsingLDA);
}
}
if (!spawnUsingLDA)
{
#region Regular Spawn
if (!this.Label.Equals(lvector.Label) && !Vector.EqualsEx(this, lvector) && !this.DoesAtLeastOneChildEncloseVector(lvector, measure))
{
SphereEx <L> child = new SphereEx <L>(this.Radius - measure(this, lvector), lvector);
child.LDAVectors.Add(child.Label, new List <KeyValuePair <int, LabeledVector <L> > >()
{
new KeyValuePair <int, LabeledVector <L> >(0, lvector)
});
this.AddChild(child);
nSpawnCount++;
}
#endregion
}
else
{
#region LDA Spawn
// Note that LDA Spawn doesn't work with SquaredEuclideanDistance. I may -- in the future -- do an additional check to see if the vector is contained by the hypersphere with SquaredEuclideanDistance and EuclideanDistance. If so, this will work. Until then, I'll leave it as is.
if (this.Children.Any())
{
// Next if-statement a duplicate of the region "Regular Spawn"
// Remember, LDA is only applied at nodes with no children (leaf)
if (!this.Label.Equals(lvector.Label) && !Vector.EqualsEx(this, lvector) && !this.DoesAtLeastOneChildEncloseVector(lvector, measure))
{
SphereEx <L> child = new SphereEx <L>(this.Radius - measure(this, lvector), lvector);
child.LDAVectors.Add(child.Label, new List <KeyValuePair <int, LabeledVector <L> > >()
{
new KeyValuePair <int, LabeledVector <L> >(0, lvector)
});
this.AddChild(child);
nSpawnCount++;
}
}
else
{
bool bContains = false;
List <KeyValuePair <int, LabeledVector <L> > > lst;
if (!this.LDAVectors.TryGetValue(lvector.Label, out lst))
{
this.LDAVectors.Add(lvector.Label, (lst = new List <KeyValuePair <int, LabeledVector <L> > >()));
}
else
{
bContains = lst.Any(kvp => Vector.EqualsEx(kvp.Value, lvector));
}
if (!bContains)
{
lst.Add(new KeyValuePair <int, LabeledVector <L> >(this.LDAVectors.Sum(kvp => kvp.Value.Count), lvector));
if (this.LDAVectors.Keys.Count == 2)
{
#region If the sphere contains exactly 2 classes, do the following...
bool bIsSeparable = false;
DiscriminantEx <L> discriminant = null;
try
{
bIsSeparable = LDAEx.IsCompletelySeparatedWithDiscriminant(this.LDAVectors.ElementAt(0).Value.Select(kvp => kvp.Value).ToList(), this.LDAVectors.ElementAt(1).Value.Select(kvp => kvp.Value).ToList(), out discriminant);
}
catch
{
// Just consume, leaving bIsSeparable = false
}
if (!bIsSeparable)
{
bool spawnedAtLeastOnce = false;
List <LabeledVector <L> > lstCache = this.LDAVectors.SelectMany(kvp => kvp.Value).OrderBy(kvp => kvp.Key).Select(kvp => kvp.Value).ToList();
this.LDAVectors.Clear();
this.DiscriminantEx = null;
foreach (LabeledVector <L> v in lstCache)
{
if (!spawnedAtLeastOnce)
{
int count = this.Spawn(v, measure, ParallelStrategy.SingleThreaded, false);
nSpawnCount += count;
spawnedAtLeastOnce = count > 0;
}
else
{
nSpawnCount += this.Spawn(v, measure, ParallelStrategy.SingleThreaded, true);
}
}
}
else
{
if (discriminant != null)
{
this.DiscriminantEx = discriminant;
}
}
#endregion
}
else if (this.LDAVectors.Keys.Count > 2)
{
#region If the sphere contains 3 or more classes, do the following...
bool spawnedAtLeastOnce = false;
List <LabeledVector <L> > lstCache = this.LDAVectors.SelectMany(kvp => kvp.Value).OrderBy(kvp => kvp.Key).Select(kvp => kvp.Value).ToList();
this.LDAVectors.Clear();
this.DiscriminantEx = null;
foreach (LabeledVector <L> v in lstCache)
{
if (!spawnedAtLeastOnce)
{
int count = this.Spawn(v, measure, ParallelStrategy.SingleThreaded, false);
nSpawnCount += count;
spawnedAtLeastOnce = count > 0;
}
else
{
nSpawnCount += this.Spawn(v, measure, ParallelStrategy.SingleThreaded, true);
}
}
#endregion
}
// Note: If this.LDAVectors.Keys.Count == 1, don't do anything additional.
}
}
#endregion
}
}
return(nSpawnCount);
}
