/// <summary>
/// See <see cref="IMatrixView.LinearCombination(double, IMatrixView, double)"/>.
/// </summary>
public IMatrix LinearCombination(double thisCoefficient, IMatrixView otherMatrix, double otherCoefficient)
{
if (otherMatrix is CscMatrix otherCSC) // In case both matrices have the exact same index arrays
{
if (HasSameIndexer(otherCSC))
{
// Do not copy the index arrays, since they are already spread around. TODO: is this a good idea?
double[] resultValues = new double[values.Length];
if (thisCoefficient == 1.0)
{
Array.Copy(this.values, resultValues, values.Length);
Blas.Daxpy(values.Length, otherCoefficient, otherCSC.values, 0, 1, this.values, 0, 1);
}
else if (otherCoefficient == 1.0)
{
Array.Copy(otherCSC.values, resultValues, values.Length);
Blas.Daxpy(values.Length, thisCoefficient, this.values, 0, 1, resultValues, 0, 1);
}
else
{
Array.Copy(this.values, resultValues, values.Length);
BlasExtensions.Daxpby(values.Length, otherCoefficient, otherCSC.values, 0, 1,
thisCoefficient, resultValues, 0, 1);
}
return(new CscMatrix(NumRows, NumColumns, resultValues, this.rowIndices, this.colOffsets));
}
}
// All entries must be processed. TODO: optimizations may be possible (e.g. only access the nnz in this matrix)
return(DenseStrategies.LinearCombination(this, thisCoefficient, otherMatrix, otherCoefficient));
}
/// <summary>
/// See <see cref="IVectorView.LinearCombination(double, IVectorView, double)"/>.
/// </summary>
public IVector LinearCombination(double thisCoefficient, IVectorView otherVector, double otherCoefficient)
{
Preconditions.CheckVectorDimensions(this, otherVector);
if (otherVector is SparseVector otherSparse) // In case both matrices have the exact same index arrays
{
if (HasSameIndexer(otherSparse))
{
// Do not copy the index arrays, since they are already spread around. TODO: is this a good idea?
double[] result = new double[this.values.Length];
if (thisCoefficient == 1.0)
{
Array.Copy(this.values, result, this.values.Length);
Blas.Daxpy(values.Length, otherCoefficient, otherSparse.values, 0, 1, result, 0, 1);
}
else if (otherCoefficient == 1.0)
{
Array.Copy(otherSparse.values, result, values.Length);
Blas.Daxpy(values.Length, thisCoefficient, this.values, 0, 1, result, 0, 1);
}
else
{
Array.Copy(this.values, result, this.values.Length);
BlasExtensions.Daxpby(values.Length, otherCoefficient, otherSparse.values, 0, 1,
thisCoefficient, result, 0, 1);
}
return(new SparseVector(Length, result, indices));
}
}
// All entries must be processed. TODO: optimizations may be possible (e.g. only access the nnz in this vector)
return(DenseStrategies.LinearCombination(this, thisCoefficient, otherVector, otherCoefficient));
}
/// <summary>
/// Performs the following operation for 0 <= i < <see cref="NumRows"/>, 0 <= j < <see cref="NumColumns"/>:
/// this[i, j] = <paramref name="otherCoefficient"/> * <paramref name="otherMatrix"/>[i, j] + this[i, j].
/// The resulting matrix overwrites the entries of this <see cref="CscMatrix"/> instance.
/// </summary>
/// <param name="otherMatrix">A matrix with the same indexing arrays as this <see cref="CscMatrix"/> instance.</param>
/// <param name="otherCoefficient">A scalar that multiplies each entry of <paramref name="otherMatrix"/>.</param>
/// <exception cref="SparsityPatternModifiedException">Thrown if <paramref name="otherMatrix"/> has different
/// indexing arrays than this instance.</exception>
public void AxpyIntoThis(CscMatrix otherMatrix, double otherCoefficient)
{
//Preconditions.CheckSameMatrixDimensions(this, other); // no need if the indexing arrays are the same
if (!HasSameIndexer(otherMatrix))
{
throw new SparsityPatternModifiedException("Only allowed if the indexing arrays are the same");
}
Blas.Daxpy(values.Length, otherCoefficient, otherMatrix.values, 0, 1, this.values, 0, 1);
}
public SymmetricMatrix Axpy(SymmetricMatrix otherMatrix, double otherCoefficient)
{
Preconditions.CheckSameMatrixDimensions(this, otherMatrix);
//TODO: Perhaps this should be done using mkl_malloc and BLAS copy.
double[] result = new double[data.Length];
Array.Copy(this.data, result, data.Length);
Blas.Daxpy(data.Length, otherCoefficient, otherMatrix.data, 0, 1, result, 0, 1);
return(new SymmetricMatrix(result, NumColumns, DefiniteProperty.Unknown));
}
/// <summary>
/// Performs the following operation for 0 <= i < this.<see cref="Length"/>:
/// result[i] = <paramref name="otherCoefficient"/> * <paramref name="otherVector"/>[i] + this[i].
/// The resulting vector is written to a new <see cref="Vector"/> and then returned.
/// </summary>
/// <param name="otherVector">A vector with the same <see cref="Length"/> as this <see cref="Vector"/> instance.</param>
/// <param name="otherCoefficient">A scalar that multiplies each entry of <paramref name="otherVector"/>.</param>
/// <exception cref="NonMatchingDimensionsException">Thrown if <paramref name="otherVector"/> has different
/// <see cref="Length"/> than this.</exception>
public Vector Axpy(Vector otherVector, double otherCoefficient)
{
Preconditions.CheckVectorDimensions(this, otherVector);
//TODO: Perhaps this should be done using mkl_malloc and BLAS copy.
double[] result = new double[data.Length];
Array.Copy(data, result, data.Length);
Blas.Daxpy(Length, otherCoefficient, otherVector.data, 0, 1, result, 0, 1);
return(new Vector(result));
}
/// <summary>
/// Performs the following operation for 0 <= j < <see cref="Order"/>, 0 <= i <= j:
/// result[i, j] = <paramref name="otherCoefficient"/> * <paramref name="otherMatrix"/>[i, j] + this[i, j].
/// The resulting matrix is written to a new <see cref="TriangularUpper"/> and then returned.
/// </summary>
/// <param name="otherMatrix">A matrix with the same <see cref="Order"/> as this <see cref="TriangularUpper"/>
/// instance.</param>
/// <param name="otherCoefficient">A scalar that multiplies each entry of <paramref name="otherMatrix"/>.</param>
/// <exception cref="NonMatchingDimensionsException">Thrown if <paramref name="otherMatrix"/> has different
/// <see cref="Order"/> than this instance.</exception>
public TriangularUpper Axpy(TriangularUpper otherMatrix, double otherCoefficient)
{
Preconditions.CheckSameMatrixDimensions(this, otherMatrix);
//TODO: Perhaps this should be done using mkl_malloc and BLAS copy.
double[] result = new double[data.Length];
Array.Copy(this.data, result, data.Length);
Blas.Daxpy(data.Length, otherCoefficient, otherMatrix.data, 0, 1, result, 0, 1);
return(new TriangularUpper(result, NumColumns));
}
/// <summary>
/// Performs the following operation for all i:
/// this[i] = <paramref name="otherCoefficient"/> * <paramref name="otherVector"/>[i] + this[i].
/// Optimized version of <see cref="IVector.DoEntrywise(IVectorView, Func{double, double, double})"/> and
/// <see cref="IVector.LinearCombination(double, IVectorView, double)"/>. Named after BLAS axpy (y = a*x plus y).
/// The resulting vector overwrites the entries of this.
/// </summary>
/// <param name="otherVector">
/// A vector with the same <see cref="IIndexable1D.Length"/> as this.
/// </param>
/// <param name="otherCoefficient">
/// A scalar that multiplies each entry of <paramref name="otherVector"/>.
/// </param>
/// <exception cref="NonMatchingDimensionsException">
/// Thrown if <paramref name="otherVector"/> has different <see cref="IIndexable1D.Length"/> than this.
/// </exception>
/// <exception cref="SparsityPatternModifiedException">
/// Thrown if an entry this[i] needs to be overwritten, but that is not permitted by the vector storage format.
/// </exception>
public void AxpyIntoThis(SparseVector otherVector, double otherCoefficient)
{
Preconditions.CheckVectorDimensions(this, otherVector);
if (!HasSameIndexer(otherVector))
{
throw new SparsityPatternModifiedException(
"This operation is legal only if the other vector has the same sparsity pattern");
}
Blas.Daxpy(values.Length, otherCoefficient, otherVector.values, 0, 1, this.values, 0, 1);
}
/// <summary>
/// Performs the following operation for 0 <= j < <see cref="Order"/>, 0 <= i <= j:
/// this[i, j] = <paramref name="thisCoefficient"/> * this[i, j]
/// + <paramref name="otherCoefficient"/> * <paramref name="otherMatrix"/>[i, j].
/// The resulting matrix overwrites the entries of this <see cref="TriangularUpper"/> instance.
/// </summary>
/// <param name="thisCoefficient">A scalar that multiplies each entry of this <see cref="TriangularUpper"/>.</param>
/// <param name="otherMatrix">A matrix with the same <see cref="Order"/> as this <see cref="TriangularUpper"/>
/// instance.</param>
/// <param name="otherCoefficient">A scalar that multiplies each entry of <paramref name="otherMatrix"/>.</param>
/// <exception cref="NonMatchingDimensionsException">Thrown if <paramref name="otherMatrix"/> has different
/// <see cref="Order"/> than this instance.</exception>
public void LinearCombinationIntoThis(double thisCoefficient, TriangularUpper otherMatrix, double otherCoefficient)
{
Preconditions.CheckSameMatrixDimensions(this, otherMatrix);
if (thisCoefficient == 1.0)
{
Blas.Daxpy(data.Length, otherCoefficient, otherMatrix.data, 0, 1, this.data, 0, 1);
}
else
{
BlasExtensions.Daxpby(data.Length, otherCoefficient, otherMatrix.data, 0, 1, thisCoefficient, this.data, 0, 1);
}
}
/// <summary>
/// Performs the following operation for 0 <= i < this.<see cref="Length"/>:
/// this[i] = <paramref name="thisCoefficient"/> * this[i] + <paramref name="otherCoefficient"/> *
/// <paramref name="otherVector"/>[i]. The resulting vector overwrites the entries of this <see cref="Vector"/> instance.
/// </summary>
/// <param name="thisCoefficient">A scalar that multiplies each entry of this <see cref="Vector"/>.</param>
/// <param name="otherVector">A vector with the same <see cref="Length"/> as this <see cref="Vector"/> instance.</param>
/// <param name="otherCoefficient">A scalar that multiplies each entry of <paramref name="otherVector"/>.</param>
/// <exception cref="NonMatchingDimensionsException">Thrown if <paramref name="otherVector"/> has different
/// <see cref="Length"/> than this.</exception>
public void LinearCombinationIntoThis(double thisCoefficient, Vector otherVector, double otherCoefficient)
{
Preconditions.CheckVectorDimensions(this, otherVector);
if (thisCoefficient == 1.0)
{
Blas.Daxpy(Length, otherCoefficient, otherVector.data, 0, 1, this.data, 0, 1);
}
else
{
BlasExtensions.Daxpby(Length, otherCoefficient, otherVector.data, 0, 1, thisCoefficient, this.data, 0, 1);
}
}
public void LinearCombinationIntoThis(double thisCoefficient, SymmetricMatrix otherMatrix, double otherCoefficient)
{
Preconditions.CheckSameMatrixDimensions(this, otherMatrix);
if (thisCoefficient == 1.0)
{
Blas.Daxpy(data.Length, otherCoefficient, otherMatrix.data, 0, 1, this.data, 0, 1);
}
else
{
BlasExtensions.Daxpby(data.Length, otherCoefficient, otherMatrix.data, 0, 1, thisCoefficient, this.data, 0, 1);
}
this.Definiteness = DefiniteProperty.Unknown;
}
/// <summary>
/// Performs the following operation for 0 <= i < <see cref="NumRows"/>, 0 <= j < <see cref="NumColumns"/>:
/// result[i, j] = <paramref name="otherCoefficient"/> * <paramref name="otherMatrix"/>[i, j] + this[i, j].
/// The resulting matrix is written to a new <see cref="CscMatrix"/> and then returned.
/// </summary>
/// <param name="otherMatrix">A matrix with the same <see cref="NumRows"/> and <see cref="NumColumns"/> as this
/// <see cref="CscMatrix"/> instance.</param>
/// <param name="otherCoefficient">A scalar that multiplies each entry of <paramref name="otherMatrix"/>.</param>
/// <exception cref="NonMatchingDimensionsException">Thrown if <paramref name="otherMatrix"/> has different
/// <see cref="NumRows"/> or <see cref="NumColumns"/> than this instance.</exception>
public CscMatrix Axpy(CscMatrix otherMatrix, double otherCoefficient)
{
// Conceptually it is not wrong to so this, even if the indexers are different, but how would I implement it.
if (!HasSameIndexer(otherMatrix))
{
throw new SparsityPatternModifiedException("Only allowed if the indexing arrays are the same");
}
//TODO: Perhaps this should be done using mkl_malloc and BLAS copy.
double[] resultValues = new double[values.Length];
Array.Copy(this.values, resultValues, values.Length);
Blas.Daxpy(values.Length, otherCoefficient, otherMatrix.values, 0, 1, resultValues, 0, 1);
// Do not copy the index arrays, since they are already spread around. TODO: is this a good idea?
return(new CscMatrix(NumRows, NumColumns, resultValues, this.rowIndices, this.colOffsets));
}
/// <summary>
/// See <see cref="IMatrixView.Axpy(IMatrixView, double)"/>.
/// </summary>
public IMatrix Axpy(IMatrixView otherMatrix, double otherCoefficient)
{
if ((otherMatrix is SymmetricCscMatrix otherCSC) && HaveSameIndexArrays(otherCSC))
{
// Unneeded if the indexers are identical, but worth it
Preconditions.CheckSameMatrixDimensions(this, otherMatrix);
//TODO: Perhaps this should be done using mkl_malloc and BLAS copy.
double[] resultValues = new double[values.Length];
Array.Copy(this.values, resultValues, values.Length);
Blas.Daxpy(values.Length, otherCoefficient, otherCSC.values, 0, 1, resultValues, 0, 1);
// Do not copy the index arrays, since they are already spread around. TODO: is this a good idea?
return(new SymmetricCscMatrix(NumRows, NumNonZerosUpper, resultValues, this.rowIndices, this.colOffsets));
}
/// <summary>
/// Performs the operation: this[<paramref name="destinationIdx"/> + i] = this[<paramref name="destinationIdx"/> + i]
/// + <paramref name="sourceVector"/>[<paramref name="sourceIdx"/> + j], for 0 <= j < <paramref name="length"/>.
/// </summary>
/// <param name="length">The number of entries to add.</param>
/// <param name="destinationIdx">
/// The index into this <see cref="Vector"/> instance, at which to start adding entries to. Constraints:
/// 0 <= <paramref name="destinationIdx"/>,
/// <paramref name="destinationIdx"/> + <paramref name="Length"/> <= this.<see cref="Length"/>.
/// </param>
/// <param name="sourceVector">The vector that will be added to a part of this <see cref="Vector"/> instance.</param>
/// <param name="sourceIdx">
/// The index into <paramref name="sourceVector"/>, at which to start adding entries from. Constraints:
/// 0 <= <paramref name="sourceIdx"/>,
/// <paramref name="sourceIdx"/> + <paramref name="length"/> <= <paramref name="sourceVector"/>.<see cref="Length"/>.
/// </param>
/// <exception cref="NonMatchingDimensionsException">
/// Thrown if <paramref name="destinationIdx"/>, <paramref name="sourceVector"/> or <paramref name="sourceIdx"/>
/// violate the described constraints.
/// </exception>
public void AddSubvectorIntoThis(int destinationIdx, IVectorView sourceVector, int sourceIdx, int length)
{
if (destinationIdx + sourceVector.Length > this.Length)
{
throw new NonMatchingDimensionsException(
"The entries to set exceed this vector's length");
}
if (sourceVector is Vector subvectorDense)
{
Blas.Daxpy(length, 1.0, subvectorDense.data, sourceIdx, 1, this.data, destinationIdx, 1);
}
else
{
this.AddSubvectorIntoThis(destinationIdx, sourceVector, 0, sourceVector.Length);
}
}
/// <summary>
/// See <see cref="IVector.CopySubvectorFrom(int, IVectorView, int, int)"/>.
/// </summary>
public void AxpySubvectorIntoThis(int destinationIndex, IVectorView sourceVector, double sourceCoefficient,
int sourceIndex, int length)
{
Preconditions.CheckSubvectorDimensions(this, destinationIndex, length);
Preconditions.CheckSubvectorDimensions(sourceVector, sourceIndex, length);
if (sourceVector is Vector casted)
{
Blas.Daxpy(Length, sourceCoefficient, casted.data, sourceIndex, 1, this.data, destinationIndex, 1);
}
else
{
for (int i = 0; i < length; ++i)
{
data[i + destinationIndex] += sourceCoefficient * sourceVector[i + sourceIndex];
}
}
}
/// <summary>
/// See <see cref="IVector.LinearCombinationIntoThis(double, IVectorView, double)"/>
/// </summary>
public void LinearCombinationIntoThis(double thisCoefficient, IVectorView otherVector, double otherCoefficient)
{
Preconditions.CheckVectorDimensions(this, otherVector);
if ((otherVector is SparseVector otherSparse) && HasSameIndexer(otherSparse))
{
if (thisCoefficient == 1.0)
{
Blas.Daxpy(values.Length, otherCoefficient, otherSparse.values, 0, 1, this.values, 0, 1);
}
else
{
BlasExtensions.Daxpby(values.Length, otherCoefficient, otherSparse.values, 0, 1,
thisCoefficient, this.values, 0, 1);
}
}
throw new SparsityPatternModifiedException(
"This operation is legal only if the other vector has the same sparsity pattern");
}
public SymmetricMatrix LinearCombination(double thisCoefficient, SymmetricMatrix otherMatrix, double otherCoefficient)
{
Preconditions.CheckSameMatrixDimensions(this, otherMatrix);
//TODO: Perhaps this should be done using mkl_malloc and BLAS copy.
double[] result = new double[data.Length];
if (thisCoefficient == 1.0)
{
Array.Copy(this.data, result, data.Length);
Blas.Daxpy(data.Length, otherCoefficient, otherMatrix.data, 0, 1, result, 0, 1);
}
else if (otherCoefficient == 1.0)
{
Array.Copy(otherMatrix.data, result, data.Length);
Blas.Daxpy(data.Length, thisCoefficient, this.data, 0, 1, result, 0, 1);
}
else
{
Array.Copy(this.data, result, data.Length);
BlasExtensions.Daxpby(data.Length, otherCoefficient, otherMatrix.data, 0, 1, thisCoefficient, result, 0, 1);
}
return(new SymmetricMatrix(result, NumColumns, DefiniteProperty.Unknown));
}
/// <summary>
/// Performs the following operation for 0 <= i < this.<see cref="Length"/>:
/// result[i] = <paramref name="thisCoefficient"/> * this[i] + <paramref name="otherCoefficient"/> *
/// <paramref name="otherVector"/>[i]. The resulting vector is written to a new <see cref="Vector"/> and then returned.
/// </summary>
/// <param name="thisCoefficient">A scalar that multiplies each entry of this <see cref="Vector"/>.</param>
/// <param name="otherVector">A vector with the same <see cref="Length"/> as this <see cref="Vector"/> instance.</param>
/// <param name="otherCoefficient">A scalar that multiplies each entry of <paramref name="otherVector"/>.</param>
/// <exception cref="NonMatchingDimensionsException">Thrown if <paramref name="otherVector"/> has different
/// <see cref="Length"/> than this.</exception>
public Vector LinearCombination(double thisCoefficient, Vector otherVector, double otherCoefficient)
{
Preconditions.CheckVectorDimensions(this, otherVector);
//TODO: Perhaps this should be done using mkl_malloc and BLAS copy.
double[] result = new double[data.Length];
if (thisCoefficient == 1.0)
{
Array.Copy(data, result, data.Length);
Blas.Daxpy(Length, otherCoefficient, otherVector.data, 0, 1, result, 0, 1);
}
else if (otherCoefficient == 1.0)
{
Array.Copy(otherVector.data, result, data.Length);
Blas.Daxpy(data.Length, thisCoefficient, this.data, 0, 1, result, 0, 1);
}
else
{
Array.Copy(data, result, data.Length);
BlasExtensions.Daxpby(Length, otherCoefficient, otherVector.data, 0, 1, thisCoefficient, result, 0, 1);
}
return(new Vector(result));
}
/// <summary>
/// See <see cref="IVector.AxpySubvectorIntoThis(int, IVectorView, double, int, int)"/>.
/// </summary>
public void AxpySubvectorIntoThis(int destinationIndex, IVectorView sourceVector, double sourceCoefficient,
int sourceIndex, int length)
{
//TODO: needs testing for off-by-1 bugs and extension to cases where source and destination indices are different.
Preconditions.CheckSubvectorDimensions(this, destinationIndex, length);
Preconditions.CheckSubvectorDimensions(sourceVector, sourceIndex, length);
if ((sourceVector is SparseVector otherSparse) && HasSameIndexer(otherSparse))
{
if (destinationIndex != sourceIndex)
{
throw new NotImplementedException();
}
int start = Array.FindIndex(this.indices, x => x >= destinationIndex);
int end = Array.FindIndex(this.indices, x => x >= destinationIndex + length);
int sparseLength = end - start;
Blas.Daxpy(sparseLength, sourceCoefficient, otherSparse.values, start, 1, this.values, start, 1);
}
throw new SparsityPatternModifiedException(
"This operation is legal only if the other vector has the same sparsity pattern");
}
/// <summary>
/// Performs the following operation for 0 <= j < <see cref="Order"/>, 0 <= i <= j:
/// result[i, j] = <paramref name="thisCoefficient"/> * this[i, j]
/// + <paramref name="otherCoefficient"/> * <paramref name="otherMatrix"/>[i, j].
/// The resulting matrix is written to a new <see cref="TriangularUpper"/> and then returned.
/// </summary>
/// <param name="thisCoefficient">A scalar that multiplies each entry of this <see cref="TriangularUpper"/>.</param>
/// <param name="otherMatrix">A matrix with the same <see cref="Order"/> as this <see cref="TriangularUpper"/>
/// instance.</param>
/// <param name="otherCoefficient">A scalar that multiplies each entry of <paramref name="otherMatrix"/>.</param>
/// <exception cref="NonMatchingDimensionsException">Thrown if <paramref name="otherMatrix"/> has different
/// <see cref="Order"/> than this instance.</exception>
public TriangularUpper LinearCombination(double thisCoefficient, TriangularUpper otherMatrix, double otherCoefficient)
{
Preconditions.CheckSameMatrixDimensions(this, otherMatrix);
//TODO: Perhaps this should be done using mkl_malloc and BLAS copy.
double[] result = new double[data.Length];
if (thisCoefficient == 1.0)
{
Array.Copy(this.data, result, data.Length);
Blas.Daxpy(data.Length, otherCoefficient, otherMatrix.data, 0, 1, result, 0, 1);
}
else if (otherCoefficient == 1.0)
{
Array.Copy(otherMatrix.data, result, data.Length);
Blas.Daxpy(data.Length, thisCoefficient, this.data, 0, 1, result, 0, 1);
}
else
{
Array.Copy(this.data, result, data.Length);
BlasExtensions.Daxpby(data.Length, otherCoefficient, otherMatrix.data, 0, 1, thisCoefficient, result, 0, 1);
}
return(new TriangularUpper(result, NumColumns));
}
/// <summary>
/// See <see cref="IVectorView.Axpy(IVectorView, double)"/>.
/// </summary>
public IVector Axpy(IVectorView otherVector, double otherCoefficient)
{
Preconditions.CheckVectorDimensions(this, otherVector);
if (otherVector is SparseVector otherSparse) // In case both matrices have the exact same index arrays
{
if (HasSameIndexer(otherSparse))
{
// Do not copy the index arrays, since they are already spread around. TODO: is this a good idea?
double[] result = new double[this.values.Length];
Array.Copy(this.values, result, this.values.Length);
Blas.Daxpy(values.Length, otherCoefficient, otherSparse.values, 0, 1, result, 0, 1);
return(new SparseVector(Length, result, indices));
}
}
else if (otherVector is Vector otherDense)
{
double[] result = otherDense.Scale(otherCoefficient).RawData;
SparseBlas.Daxpyi(this.indices.Length, 1.0, this.values, this.indices, 0, result, 0);
return(Vector.CreateFromArray(result, false));
}
// All entries must be processed. TODO: optimizations may be possible (e.g. only access the nnz in this vector)
return(DenseStrategies.LinearCombination(this, 1.0, otherVector, otherCoefficient));
}
// markov operation
public void DoBackward(double t, double[] x, int right, double[] prob)
{
//int right;
//if (t > maxt)
//{
// right = setMaxT(t);
//}
//else
//{
// right = PoiDist.getRightBound(lambda * t, epsi);
//}
double weight = PoiDist.CompProb(Lambda * t, 0, right, prob);
Blas.Dcopy(ndim, x, xi);
Blas.Fill(ndim, x, 0.0);
Blas.Daxpy(ndim, prob[0], xi, x);
for (int l = 1; l <= right; l++)
{
Blas.Dcopy(ndim, xi, tmp);
DgemvNoTrans(1.0, tmp, 0.0, xi);
Blas.Daxpy(ndim, prob[l], xi, x);
}
Blas.Dscal(ndim, 1.0 / weight, x);
}
public void DoSojournForward(double t, double[] f, double[] b, double[] h, int right, double[] prob, double[][] vc)
{
//int right;
//if (t > maxt)
//{
// right = setMaxT(t);
//}
//else
//{
// right = PoiDist.getRightBound(lambda * t, epsi);
//}
double weight = PoiDist.CompProb(Lambda * t, 0, right + 1, prob);
// forward and backward
Blas.Fill(ndim, vc[right + 1], 0.0);
Blas.Daxpy(ndim, prob[right + 1], b, vc[right + 1]);
for (int l = right; l >= 1; l--)
{
DgemvNoTrans(1.0, vc[l + 1], 0.0, vc[l]);
Blas.Daxpy(ndim, prob[l], b, vc[l]);
}
Blas.Dcopy(ndim, f, xi);
Blas.Fill(ndim, f, 0.0);
Blas.Daxpy(ndim, prob[0], xi, f);
Blas.Fill(ndim * 2, h, 0.0);
Dger(1.0, xi, vc[1], h);
for (int l = 1; l <= right; l++)
{
Blas.Dcopy(ndim, xi, tmp);
DgemvTrans(1.0, tmp, 0.0, xi);
Blas.Daxpy(ndim, prob[l], xi, f);
Dger(1.0, xi, vc[l + 1], h);
}
Blas.Dscal(ndim, 1.0 / weight, f);
Blas.Dscal(ndim * 2, 1.0 / Lambda / weight, h);
}
} // private constructor for singleton pattern
#region BLAS Level 1
/// <summary>
/// See https://software.intel.com/en-us/mkl-developer-reference-fortran-axpy#E25D8E10-0440-4827-BC58-BC71128EA6EE
/// </summary>
public void Daxpy(int n, double alpha, double[] x, int offsetX, int incX, double[] y, int offsetY, int incY)
=> Blas.Daxpy(ref n, ref alpha, ref x[offsetX], ref incX, ref y[offsetY], ref incY);
public double Emstep(SRMData data)
{
int dsize = data.Size;
double[] time = data.Time;
int[] num = data.Fault;
int[] type = data.Type;
int x;
double t, llf, tmpv;
int right = PoiDist.GetRightBound(param.Lambda * NMath.Max(time), epsi);
double[] prob = new double[right + 2];
double[][] vc = Array2.Create(right + 2, ndim);
// initialize for estep
eno = 0.0;
Blas.Fill(ndim, eb, 0.0);
Blas.Fill(ndim, eb2, 0.0);
Blas.Fill(ndim * 2, en, 0.0);
// backward: compute eb
Blas.Fill(ndim, vb[0], 1.0);
Blas.Fill(ndim, vb2[0], 0.0);
vb2[0][ndim - 1] = param.Rate[ndim - 1];
llf = 0.0;
for (int k = 1; k <= dsize; k++)
{
t = time[k - 1]; // dat.getTime(k);
x = num[k - 1]; // dat.getNumber(k);
Blas.Dcopy(ndim, vb[k - 1], vb[k]);
cuni.DoBackward(t, vb[k], right, prob);
if (x != 0)
{
Blas.Dcopy(ndim, vb[k - 1], tmp);
Blas.Daxpy(ndim, -1.0, vb[k], tmp);
blf[k] = Blas.Ddot(ndim, param.Alpha, tmp);
llf += x * NMath.Log(param.Omega * blf[k]) - NMath.Lgamma(x + 1);
eno += x;
Blas.Daxpy(ndim, x / blf[k], tmp, eb);
}
else
{
blf[k] = 1.0; // to avoid NaN
}
Blas.Dcopy(ndim, vb2[k - 1], vb2[k]);
cuni.DoBackward(t, vb2[k], right, prob);
if (type[k - 1] == 1) // (dat.getType(k) == 1)
{
blf2[k] = Blas.Ddot(ndim, param.Alpha, vb2[k]);
llf += NMath.Log(param.Omega * blf2[k]);
eno += 1.0;
Blas.Daxpy(ndim, 1.0 / blf2[k], vb2[k], eb2);
}
}
barblf = Blas.Ddot(ndim, param.Alpha, vb[dsize]);
llf += -param.Omega * (1.0 - barblf);
Blas.Daxpy(ndim, param.Omega, vb[dsize], eb);
// compute pi2
tmpv = 0.0;
for (int i = 0; i < ndim - 1; i++)
{
tmpv += param.Alpha[i];
pi2[i] = tmpv / param.Rate[i];
}
pi2[ndim - 1] = 1.0 / param.Rate[ndim - 1];
// sojourn:
Blas.Fill(ndim, tmp, 0.0);
Blas.Daxpy(ndim, -num[dsize - 1] / blf[dsize] + param.Omega, pi2, tmp);
if (type[dsize - 1] == 1)
{
Blas.Daxpy(ndim, 1.0 / blf2[dsize], param.Alpha, tmp);
}
cuni.DoSojournForward(time[dsize - 1], tmp, vb2[dsize - 1], h0, right, prob, vc);
Blas.Daxpy(ndim * 2, 1.0, h0, en);
for (int k = dsize - 1; k >= 1; k--)
{
Blas.Daxpy(ndim, num[k] / blf[k + 1] - num[k - 1] / blf[k], pi2, tmp);
if (type[k - 1] == 1)
{
Blas.Daxpy(ndim, 1.0 / blf2[k], param.Alpha, tmp);
}
cuni.DoSojournForward(time[k - 1], tmp, vb2[k - 1], h0, right, prob, vc);
Blas.Daxpy(ndim * 2, 1.0, h0, en);
}
/* concrete algorithm: M-step */
for (int i = 0; i < ndim - 1; i++)
{ // <-- not <=ndim!
ey[i] = param.Rate[i]
* (en[2 * i + 1] + eb[i + 1] * pi2[i])
/ (en[2 * i] + eb[i] * pi2[i]);
}
tmpv = en[2 * (ndim - 1)] + eb[ndim - 1] * pi2[ndim - 1];
double sum = 0.0;
for (int i = 0; i < ndim; i++)
{
eb[i] = param.Alpha[i] * (eb[i] + eb2[i]);
sum += eb[i];
}
ey[ndim - 1] = sum / tmpv;
for (int i = 0; i < ndim; i++)
{
eb[i] /= sum;
}
param.Update(eno + param.Omega * barblf, eb, ey);
return(llf);
}
/// <summary>
/// Performs the following operation for 0 <= i < this.<see cref="Length"/>:
/// this[i] = <paramref name="otherCoefficient"/> * <paramref name="otherVector"/>[i] + this[i].
/// The resulting vector overwrites the entries of this <see cref="Vector"/> instance.
/// </summary>
/// <param name="otherVector">A vector with the same <see cref="Length"/> as this <see cref="Vector"/> instance.</param>
/// <param name="otherCoefficient">A scalar that multiplies each entry of <paramref name="otherVector"/>.</param>
/// <exception cref="NonMatchingDimensionsException">Thrown if <paramref name="otherVector"/> has different
/// <see cref="Length"/> than this.</exception>
public void AxpyIntoThis(Vector otherVector, double otherCoefficient)
{
Preconditions.CheckVectorDimensions(this, otherVector);
Blas.Daxpy(Length, otherCoefficient, otherVector.data, 0, 1, this.data, 0, 1);
}
/// <summary>
/// Performs the following operation for 0 <= j < <see cref="Order"/>, 0 <= i <= j:
/// this[i, j] = <paramref name="otherCoefficient"/> * <paramref name="otherMatrix"/>[i, j] + this[i, j].
/// The resulting matrix overwrites the entries of this <see cref="TriangularUpper"/> instance.
/// </summary>
/// <param name="otherMatrix">A matrix with the same <see cref="Order"/> as this <see cref="TriangularUpper"/>
/// instance.</param>
/// <param name="otherCoefficient">A scalar that multiplies each entry of <paramref name="otherMatrix"/>.</param>
/// <exception cref="NonMatchingDimensionsException">Thrown if <paramref name="otherMatrix"/> has different
/// <see cref="Order"/> than this instance.</exception>
public void AxpyIntoThis(TriangularUpper otherMatrix, double otherCoefficient)
{
Preconditions.CheckSameMatrixDimensions(this, otherMatrix);
Blas.Daxpy(data.Length, otherCoefficient, otherMatrix.data, 0, 1, this.data, 0, 1);
}
public void AxpyIntoThis(SymmetricMatrix otherMatrix, double otherCoefficient)
{
Preconditions.CheckSameMatrixDimensions(this, otherMatrix);
Blas.Daxpy(data.Length, otherCoefficient, otherMatrix.data, 0, 1, this.data, 0, 1);
this.Definiteness = DefiniteProperty.Unknown;
}
