public GPOut Compute(Matrix <double> mTr, Matrix <double> mTeTr, Vector <double> vTrY)
{
var Mtr = (mTr).RowCount;
var gpOut = new GPOut();
var Kte = _kernel.Main(DistanceMatrix.Instance.Matrix, _length);
if (Mtr > 0)
{
var Kxx_p_noise = _kernel.Main(mTr, _length);
for (int i = 0; i < Mtr; i++)
{
Kxx_p_noise[i, i] += _noise;
}
var svd1 = Kxx_p_noise.Svd();
for (int i = 0; i < Mtr; i++)
{
svd1.S[i] = svd1.S[i] > Double.Epsilon ? 1.0 / svd1.S[i] : 0;
}
var tmp = _kernel.Main(mTeTr, _length) * svd1.U;
gpOut.mu = tmp * (svd1.S.PointwiseMultiply(svd1.U.Transpose() * (vTrY)));
var cov = tmp * Matrix <double> .Build.DenseOfDiagonalVector(svd1.S.PointwiseSqrt());
cov = cov * cov.Transpose();
cov = Kte /*.SubMatrix(0,100,0,100) */ - cov;
var svd2 = cov.Svd();
for (int i = 0; i < Mte; i++)
{
if (svd2.S[i] < Double.Epsilon)
{
svd2.S[i] = 0.0;
}
}
gpOut.proj = svd2.U * Matrix <double> .Build.DenseOfDiagonalVector(svd2.S.PointwiseSqrt());
gpOut.sd95 = 1.98 * (gpOut.proj * gpOut.proj.Transpose()).Diagonal().PointwiseSqrt();
}
else
{
gpOut.sd95 = 1.98 * (Kte.Diagonal()).PointwiseSqrt();
var svd = Kte.Svd();
gpOut.proj = svd.U * Matrix <double> .Build.DenseOfDiagonalVector(svd.S.PointwiseSqrt());
gpOut.mu = Vector <double> .Build.DenseOfArray(Enumerable.Range(0, Mte).Select(_ => 0d).ToArray());
}
return(gpOut);
}
public GPOut Predict(double TestPointX, Svd <double> svd1 = null, int results = 1)
{
//if(results< TrainingPointsX.Count)
// results = TrainingPointsX.Count;
double[] TestPointsX;
if (results > 1)
{
TestPointsX = MathNet.Numerics.Generate.LinearSpaced(results, TrainingPointsX.Min(), TestPointX);
}
else
{
TestPointsX = new double[] { TestPointX }
};
if (Kte == null || results != Kte.ColumnCount)
{
if (results == 1)
{
Kte = kernel.Main(Matrix <double> .Build.Dense(1, 1), length);
}
else
{
Kte = kernel.Main(DistanceMatrix.Instance.Matrix.SubMatrix(0, results, 0, results), length);
}
}
var gpOut = new GPOut();
Svd <double> svd;
if (TrainingPointsX.Count > 0 && svd1 != null /* && TestPointsX.Length>= TrainingPointsX.Count*/)
{
(gpOut.mu, svd) = MathHelper.Evaluate(TestPointsX, TrainingPointsY.ToArray(), TrainingPointsX.ToArray(), kernel, length, svd1, Kte);
}
else
{
gpOut.mu = Vector <double> .Build.DenseOfArray(Enumerable.Range(0, results).Select(_ => 0d).ToArray());
//gpOut.sd95 = 1.98 * (Kte.Diagonal()).PointwiseSqrt();
svd = Kte.Svd();
}
gpOut.proj = svd.U * Matrix <double> .Build.DenseOfDiagonalVector(svd.S.PointwiseSqrt());
gpOut.sd95 = 1.98 * (gpOut.proj * gpOut.proj.Transpose()).Diagonal().PointwiseSqrt();
gpOut.X = TestPointsX;
return(gpOut);
}
}
public static (Vector <double>, Svd <double>) Evaluate(double[] testPointsX, double[] trainingPointsX, double[] trainingPointsY, IMatrixkernel kernel, double length, Svd <double> svd1, Matrix <double> Kte)
{
var gpOut = new GPOut();
Svd <double> svd;
var dmTeTr = MathHelper.ComputeDistanceMatrix(testPointsX, trainingPointsX.ToArray());
var tmp = kernel.Main(dmTeTr, length) * svd1.U;
Vector <double> v = Vector <double> .Build.DenseOfEnumerable(trainingPointsY);
var mu = tmp * (svd1.S.PointwiseMultiply(svd1.U.Transpose() * v));
var cov = tmp * Matrix <double> .Build.DenseOfDiagonalVector(svd1.S.PointwiseSqrt());
cov = cov * cov.Transpose();
cov = Kte - cov;
svd = cov.Svd();
for (int i = 0; i < svd.S.Count; i++)
{
svd.S[i] = svd.S[i] < Double.Epsilon ? 0 : svd.S[i];
}
return(mu, svd);
}
public GPOut Predict(double[] trainingPointsX, double[] trainingPointsY, params double[] TestPointsX)
{
if (TestPointsX.Count() == 1)
{
Kte = kernel.Main(Matrix <double> .Build.Dense(1, 1), length);
}
else
{
Kte = kernel.Main(DistanceMatrix.Instance.Matrix.SubMatrix(0, TestPointsX.Count(), 0, TestPointsX.Count()), length);
}
var svd1 = Task.Run(() =>
trainingPointsX.Length > 0 ? Update(trainingPointsX, trainingPointsY) : GetDefaultSvd());
var gpOut = new GPOut();
Svd <double> svd;
(gpOut.mu, svd) = Task.Run(() =>
{
if (trainingPointsX.Count() > 0)
{
return(Evaluate(TestPointsX, trainingPointsX.ToArray(), trainingPointsY.ToArray(), kernel, length, svd1.Result, Kte));
}
else
{
return(Vector <double> .Build.DenseOfArray(Enumerable.Range(0, TestPointsX.Count()).Select(_ => 0d).ToArray()), Kte.Svd());
//gpOut.sd95 = 1.98 * (Kte.Diagonal()).PointwiseSqrt();
}
}).Result;
gpOut.proj = svd.U * Matrix <double> .Build.DenseOfDiagonalVector(svd.S.PointwiseSqrt());
gpOut.sd95 = 1.98 * (gpOut.proj * gpOut.proj.Transpose()).Diagonal().PointwiseSqrt();
gpOut.X = TestPointsX;
return(gpOut);
}
public static IEnumerable <KeyValuePair <DateTime, Tuple <double, double>[]> > GetPositionsAndVelocities(this GPOut gpout, DateTime start, double control)
{
double lasttime = 0;
double lastvariance;
double lastposition;
double velocity = 0;
using (IEnumerator <double> i2 = gpout.mu.ToList().GetEnumerator())
//using (IEnumerator<double> i1 = gpout.X.ToList().GetEnumerator())
using (IEnumerator <double> i3 = gpout.sd95.ToList().GetEnumerator())
foreach (double time in gpout.X.ToArray())
{
lastposition = i2.Current;
//lasttime = i1.Current;
lastvariance = i3.Current;
/* while (i1.MoveNext() &&*/
i2.MoveNext(); i3.MoveNext();
//{
//double time=i1.Current;
if ((time - lasttime) != 0)
{
velocity = (i2.Current - lastposition) / (time - lasttime);
}
yield return(new KeyValuePair <DateTime, Tuple <double, double>[]>(start + TimeSpan.FromSeconds(time),
new[] {
Tuple.Create(i2.Current + control, i3.Current),
Tuple.Create(velocity, i3.Current)
//});
}));
lastposition = i2.Current;
lasttime = time;// i1.Current;
lastvariance = i3.Current;
}
}
public static IEnumerable <KeyValuePair <DateTime, Tuple <double, double> > > GetVelocities(this GPOut gpout, DateTime dt)
{
double lastposition = 0;
double lasttime = 0;
double lastvariance = 0;
using (var i1 = gpout.X.ToList().GetEnumerator())
using (var i2 = gpout.mu.ToList().GetEnumerator())
using (var i3 = gpout.sd95.ToList().GetEnumerator())
{
lastposition = i2.Current;
lasttime = i1.Current;
lastvariance = i3.Current;
while (i1.MoveNext() && i2.MoveNext() && i3.MoveNext())
{
var velocity = (i2.Current - lastposition) / TimeSpan.FromDays(i1.Current - lasttime).TotalSeconds;
yield return(new KeyValuePair <DateTime, Tuple <double, double> >(dt + TimeSpan.FromSeconds(i1.Current), Tuple.Create(i2.Current, i3.Current)));
lastposition = i2.Current;
lasttime = i1.Current;
lastvariance = i3.Current;
}
}
}
public static IEnumerable <KeyValuePair <DateTime, Tuple <double, double> > > GetPositions(this GPOut gpout, DateTime dt)
{
using (var i1 = gpout.X.ToList().GetEnumerator())
using (var i2 = gpout.mu.ToList().GetEnumerator())
using (var i3 = gpout.sd95.ToList().GetEnumerator())
{
while (i1.MoveNext() && i2.MoveNext() && i3.MoveNext())
{
yield return(new KeyValuePair <DateTime, Tuple <double, double> >(dt + TimeSpan.FromSeconds(i1.Current), Tuple.Create(i2.Current, i3.Current)));
}
}
}
public static KeyValuePair <DateTime, Tuple <double, double> > Last(this GPOut gpout, DateTime dt)
{
return(new KeyValuePair <DateTime, Tuple <double, double> >
(dt + TimeSpan.FromDays(gpout.X.Last()), Tuple.Create(gpout.mu.Last(), gpout.sd95.Last())));
}
