///<summary>Add a <c>ComplexDoubleVector</c> to another <c>ComplexDoubleVector</c></summary>
///<param name="lhs"><c>ComplexDoubleVector</c> to add to.</param>
///<param name="rhs"><c>ComplexDoubleVector</c> to add.</param>
///<returns><c>ComplexDoubleVector</c> with results.</returns>
public static ComplexDoubleVector operator +(ComplexDoubleVector lhs, ComplexDoubleVector rhs)
{
ComplexDoubleVector ret = new ComplexDoubleVector(lhs);
Blas.Axpy.Compute(ret.Length, 1, rhs.data, 1, ret.data, 1);
return(ret);
}
///<summary>Negate operator for <c>ComplexDoubleVector</c></summary>
///<returns><c>ComplexDoubleVector</c> with values to negate.</returns>
public static ComplexDoubleVector operator -(ComplexDoubleVector rhs)
{
ComplexDoubleVector ret = new ComplexDoubleVector(rhs);
Blas.Scal.Compute(ret.Length, -1, ret.data, 1);
return(ret);
}
///<summary>Multiply a <c>Complex</c> x with a <c>ComplexDoubleVector</c> y as x*y</summary>
///<param name="lhs"><c>Complex</c> as left hand operand.</param>
///<param name="rhs"><c>ComplexDoubleVector</c> as right hand operand.</param>
///<returns><c>ComplexDoubleVector</c> with results.</returns>
public static ComplexDoubleVector operator *(Complex lhs, ComplexDoubleVector rhs)
{
var ret = new ComplexDoubleVector(rhs);
Blas.Scal.Compute(ret.Length, lhs, ret.data, 1);
return(ret);
}
///<summary>Divide a <c>ComplexDoubleVector</c> x with a <c>Complex</c> y as x/y</summary>
///<param name="lhs"><c>ComplexDoubleVector</c> as left hand operand.</param>
///<param name="rhs"><c>Complex</c> as right hand operand.</param>
///<returns><c>ComplexDoubleVector</c> with results.</returns>
public static ComplexDoubleVector operator /(ComplexDoubleVector lhs, Complex rhs)
{
ComplexDoubleVector ret = new ComplexDoubleVector(lhs);
Blas.Scal.Compute(ret.Length, 1 / rhs, ret.data, 1);
return(ret);
}
/// <overloads>
/// There are two permuations of the constructor, both require a parameter corresponding
/// to the left-most column of a Toeplitz matrix.
/// </overloads>
/// <summary>
/// Constructor with <c>ComplexDoubleVector</c> parameter.
/// </summary>
/// <param name="T">The left-most column of the Toeplitz matrix.</param>
/// <exception cref="ArgumentNullException">
/// <B>T</B> is a null reference.
/// </exception>
/// <exception cref="RankException">
/// The length of <B>T</B> is zero.
/// </exception>
public ComplexDoubleSymmetricLevinson(IROComplexDoubleVector T)
{
// check parameter
if (T == null)
{
throw new System.ArgumentNullException("T");
}
else if (T.Length == 0)
{
throw new RankException("The length of T is zero.");
}
// save the vector
m_LeftColumn = new ComplexDoubleVector(T);
m_Order = m_LeftColumn.Length;
// allocate memory for lower triangular matrix
m_LowerTriangle = new Complex[m_Order][];
for (int i = 0; i < m_Order; i++)
{
m_LowerTriangle[i] = new Complex[i + 1];
}
// allocate memory for diagonal
m_Diagonal = new Complex[m_Order];
}
/// <summary>
/// Solve a square Toeplitz system with a right-side matrix.
/// </summary>
/// <param name="Y">The right-side matrix</param>
/// <returns>The solution matrix.</returns>
/// <exception cref="ArgumentNullException">
/// Parameter <B>Y</B> is a null reference.
/// </exception>
/// <exception cref="RankException">
/// The number of rows in <B>Y</B> is not equal to the number of rows in the Toeplitz matrix.
/// </exception>
/// <exception cref="SingularMatrixException">
/// The Toeplitz matrix or one of the the leading sub-matrices is singular.
/// </exception>
/// <remarks>
/// This member solves the linear system <B>TX</B> = <B>Y</B>, where <B>T</B> is
/// a square Toeplitz matrix, <B>X</B> is the unknown solution matrix
/// and <B>Y</B> is a known matrix.
/// <para>
/// The class implicitly decomposes the inverse Toeplitz matrix into a <b>UDL</b> factorisation
/// using the Levinson algorithm, before calculating the solution vector.
/// </para>
/// </remarks>
public ComplexDoubleMatrix Solve(IROComplexDoubleMatrix Y)
{
ComplexDoubleMatrix X;
Complex Inner;
Complex[] a, b, x, y;
int i, j, l;
// check parameters
if (Y == null)
{
throw new System.ArgumentNullException("Y");
}
else if (m_Order != Y.Columns)
{
throw new RankException("The numer of rows in Y is not equal to the number of rows in the Toeplitz matrix.");
}
Compute();
if (m_IsSingular == true)
{
throw new SingularMatrixException("One of the leading sub-matrices is singular.");
}
// allocate memory for solution
X = new ComplexDoubleMatrix(m_Order, Y.Rows);
x = new Complex[m_Order];
for (l = 0; l < Y.Rows; l++)
{
// get right-side column
y = ComplexDoubleVector.GetColumnAsArray(Y, l);
// solve left-side column
for (i = 0; i < m_Order; i++)
{
a = m_LowerTriangle[i];
b = m_UpperTriangle[i];
Inner = y[i];
for (j = 0; j < i; j++)
{
Inner += a[j] * y[j];
}
Inner *= m_Diagonal[i];
x[i] = Inner;
for (j = 0; j < i; j++)
{
x[j] += Inner * b[j];
}
}
// insert left-side column into the matrix
X.SetColumn(l, x);
}
return(X);
}
///<summary>Add a <c>ComplexDoubleVector</c> to this<c>ComplexDoubleVector</c></summary>
///<param name="vector"><c>ComplexDoubleVector</c> to add.</param>
///<exception cref="ArgumentNullException">Exception thrown if null given as argument.</exception>
public void Add(ComplexDoubleVector vector)
{
if (vector == null)
{
throw new System.ArgumentNullException("ComplexDoubleVector cannot be null.");
}
Blas.Axpy.Compute(Length, 1, vector.data, 1, data, 1);
}
public void CtorInitialValues()
{
ComplexDoubleVector test = new ComplexDoubleVector(2, new Complex(1,-1));
Assert.AreEqual(test.Length, 2);
Assert.AreEqual(test[0],new Complex(1,-1));
Assert.AreEqual(test[1],new Complex(1,-1));
}
public void CtorDimensions()
{
ComplexDoubleVector test = new ComplexDoubleVector(2);
Assert.AreEqual(test.Length, 2);
Assert.AreEqual(test[0],new Complex(0));
Assert.AreEqual(test[1],new Complex(0));
}
///<summary>Compute the sum y = alpha * x + y where y is this <c>ComplexDoubleVector</c></summary>
///<param name="alpha"><c>Complex</c> value to scale this <c>ComplexDoubleVector</c></param>
///<param name="X"><c>ComplexDoubleVector</c> to add to alpha * this <c>ComplexDoubleVector</c></param>
///<remarks>Results of computation replace data in this variable</remarks>
public void Axpy(Complex alpha, ComplexDoubleVector X)
{
if (X == null)
{
throw new System.ArgumentNullException("ComplexDoubleVector cannot be null.");
}
Blas.Axpy.Compute(data.Length, alpha, X.data, 1, this.data, 1);
}
///<summary>Compute the complex conjugate scalar product x^Hy and return as <c>Complex</c></summary>
///<param name="Y"><c>ComplexDoubleVector</c> to act as y operand in x^Hy.</param>
///<returns><c>Complex</c> results from x^Hy.</returns>
public Complex GetConjugateDotProduct(ComplexDoubleVector Y)
{
if (Y == null)
{
throw new System.ArgumentNullException("ComplexDoubleVector cannot be null.");
}
return(Blas.Dotc.Compute(this.Length, this.data, 1, Y.data, 1));
}
///<summary>Swap data in this <c>ComplexDoubleVector</c> with another <c>ComplexDoubleVector</c></summary>
///<param name="src"><c>ComplexDoubleVector</c> to swap data with.</param>
public void Swap(ComplexDoubleVector src)
{
if (src == null)
{
throw new System.ArgumentNullException("ComplexDoubleVector cannot be null.");
}
Blas.Swap.Compute(src.Length, src.data, 1, this.data, 1);
}
private static void zscalVector(ComplexDoubleVector A, int Start, Complex z)
{
// A part of vector A from Start to end multiply by z
for (int i = Start; i < A.Length; i++)
{
A[i] = A[i] * z;
}
}
///<summary>Subtract a <c>ComplexDoubleVector</c> from this<c>ComplexDoubleVector</c></summary>
///<param name="vector"><c>ComplexDoubleVector</c> to add.</param>
///<exception cref="ArgumentNullException">Exception thrown if null given as argument.</exception>
public void Subtract(ComplexDoubleVector vector)
{
if (vector == null)
{
throw new System.ArgumentNullException("ComplexDoubleVector cannot be null.");
}
Blas.Axpy.Compute(this.Length, -1, vector.data, 1, this.data, 1);
}
///<summary>Negate operator for <c>ComplexDoubleVector</c></summary>
///<returns><c>ComplexDoubleVector</c> with values to negate.</returns>
public static ComplexDoubleVector Negate(ComplexDoubleVector rhs)
{
if (rhs == null)
{
throw new ArgumentNullException("rhs", "rhs cannot be null");
}
return(-rhs);
}
/// <summary>Performs the QR factorization.</summary>
protected override void InternalCompute()
{
int m = matrix.Rows;
int n = matrix.Columns;
#if MANAGED
int minmn = m < n ? m : n;
r_ = new ComplexDoubleMatrix(matrix); // create a copy
ComplexDoubleVector[] u = new ComplexDoubleVector[minmn];
for (int i = 0; i < minmn; i++)
{
u[i] = Householder.GenerateColumn(r_, i, m - 1, i);
Householder.UA(u[i], r_, i, m - 1, i + 1, n - 1);
}
q_ = ComplexDoubleMatrix.CreateIdentity(m);
for (int i = minmn - 1; i >= 0; i--)
{
Householder.UA(u[i], q_, i, m - 1, i, m - 1);
}
#else
qr = ComplexDoubleMatrix.ToLinearComplexArray(matrix);
jpvt = new int[n];
jpvt[0] = 1;
Lapack.Geqp3.Compute(m, n, qr, m, jpvt, out tau);
r_ = new ComplexDoubleMatrix(m, n);
// Populate R
for (int i = 0; i < m; i++) {
for (int j = 0; j < n; j++) {
if (i <= j) {
r_.data[j * m + i] = qr[(jpvt[j]-1) * m + i];
}
else {
r_.data[j * m + i] = Complex.Zero;
}
}
}
q_ = new ComplexDoubleMatrix(m, m);
for (int i = 0; i < m; i++) {
for (int j = 0; j < m; j++) {
if (j < n)
q_.data[j * m + i] = qr[j * m + i];
else
q_.data[j * m + i] = Complex.Zero;
}
}
if( m < n ){
Lapack.Ungqr.Compute(m, m, m, q_.data, m, tau);
} else{
Lapack.Ungqr.Compute(m, m, n, q_.data, m, tau);
}
#endif
for (int i = 0; i < m; i++)
{
if (q_[i, i] == 0)
isFullRank = false;
}
}
public void CtorArray()
{
double[] testvector = new double[2]{0,1};
ComplexDoubleVector test = new ComplexDoubleVector(testvector);
Assert.AreEqual(test.Length,testvector.Length);
Assert.AreEqual(test[0],new Complex(testvector[0]));
Assert.AreEqual(test[1],new Complex(testvector[1]));
}
public void CurrentException2()
{
ComplexDoubleVector test = new ComplexDoubleVector(new Complex[2] { 1, 2 });
IEnumerator enumerator = test.GetEnumerator();
enumerator.MoveNext();
enumerator.MoveNext();
enumerator.MoveNext();
object value = enumerator.Current;
}
///<summary>Constructor for <c>ComplexDoubleVector</c> to deep copy another <c>ComplexDoubleVector</c></summary>
///<param name="src"><c>ComplexDoubleVector</c> to deep copy into <c>ComplexDoubleVector</c>.</param>
///<exception cref="ArgumentNullException">Exception thrown if null passed as 'src' parameter.</exception>
public ComplexDoubleVector(ComplexDoubleVector src)
{
if (src == null)
{
throw new ArgumentNullException("ComplexDoubleVector cannot be null");
}
data = new Complex[src.data.Length];
Array.Copy(src.data, 0, data, 0, data.Length);
}
/// <overloads>
/// Solve a symmetric square Toeplitz system.
/// </overloads>
/// <summary>
/// Solve a symmetric square Toeplitz system with a right-side vector.
/// </summary>
/// <param name="Y">The right-hand side of the system.</param>
/// <returns>The solution vector.</returns>
/// <exception cref="ArgumentNullException">
/// Parameter <B>Y</B> is a null reference.
/// </exception>
/// <exception cref="RankException">
/// The length of <B>Y</B> is not equal to the number of rows in the Toeplitz matrix.
/// </exception>
/// <exception cref="SingularMatrixException">
/// The Toeplitz matrix or one of the the leading sub-matrices is singular.
/// </exception>
/// <remarks>
/// This member solves the linear system <B>TX</B> = <B>Y</B>, where <B>T</B> is
/// the symmetric square Toeplitz matrix, <B>X</B> is the unknown solution vector
/// and <B>Y</B> is a known vector.
/// <para>
/// The class implicitly decomposes the inverse Toeplitz matrix into a <b>UDL</b> factorisation
/// using the Levinson algorithm, and then calculates the solution vector.
/// </para>
/// </remarks>
public ComplexDoubleVector Solve(IROComplexDoubleVector Y)
{
ComplexDoubleVector X;
// check parameters
if (Y == null)
{
throw new System.ArgumentNullException("Y");
}
else if (m_Order != Y.Length)
{
throw new RankException("The length of Y is not equal to the number of rows in the Toeplitz matrix.");
}
Compute();
if (m_IsSingular == true)
{
throw new SingularMatrixException("The Toeplitz matrix or one of the the leading sub-matrices is singular.");
}
int i, j, l; // index/loop variables
Complex Inner; // inner product
Complex G; // scaling constant
Complex[] A; // reference to current order coefficients
// allocate memory for solution
X = new ComplexDoubleVector(m_Order)
{
// setup zero order solution
[0] = Y[0] / m_LeftColumn[0]
};
// solve systems of increasing order
for (i = 1; i < m_Order; i++)
{
// calculate inner product
Inner = Y[i];
for (j = 0, l = i; j < i; j++, l--)
{
Inner -= X[j] * m_LeftColumn[l];
}
// get the current predictor coefficients row
A = m_LowerTriangle[i];
// update the solution vector
G = Inner * m_Diagonal[i];
for (j = 0; j <= i; j++)
{
X[j] += G * A[j];
}
}
return(X);
}
///<summary>Sum the components in this <c>ComplexDoubleVector</c></summary>
///<returns><c>Complex</c> results from the summary of <c>ComplexDoubleVector</c> components.</returns>
public Complex GetSum()
{
Complex ret = 0;
for (int i = 0; i < data.Length; ++i)
{
ret += data[i];
}
return(ret);
}
private ComplexDoubleVector Pivot(IROComplexDoubleVector B)
{
ComplexDoubleVector ret = new ComplexDoubleVector(B.Length);
for (int i = 0; i < pivots.Length; i++)
{
ret.data[i] = B[pivots[i]];
}
return(ret);
}
/// <summary>
/// Returns the column of a <see cref="IROComplexDoubleMatrix" /> as a new <c>ComplexDoubleVector.</c>
/// </summary>
/// <param name="mat">The matrix to copy the column from.</param>
/// <param name="col">Number of column to copy from the matrix.</param>
/// <returns>A new <c>ComplexDoubleVector</c> with the same elements as the column of the given matrix.</returns>
public static ComplexDoubleVector GetColumn(IROComplexDoubleMatrix mat, int col)
{
ComplexDoubleVector result = new ComplexDoubleVector(mat.Rows);
for (int i = 0; i < result.data.Length; ++i)
{
result.data[i] = mat[i, col];
}
return(result);
}
///<summary>Implicit cast conversion to <c>ComplexDoubleVector</c> from <c>ComplexFloatVector</c></summary>
static public ComplexDoubleVector ToComplexDoubleVector(ComplexFloatVector src)
{
ComplexFloat[] temp = src.ToArray();
ComplexDoubleVector ret = new ComplexDoubleVector(temp.Length);
for (int i = 0; i < temp.Length; ++i)
{
ret.data[i] = temp[i];
}
return(ret);
}
/// <summary>
/// Returns the row of a <see cref="IROComplexDoubleMatrix" /> as a new <c>ComplexDoubleVector.</c>
/// </summary>
/// <param name="mat">The matrix to copy the column from.</param>
/// <param name="row">Number of row to copy from the matrix.</param>
/// <returns>A new <c>ComplexDoubleVector</c> with the same elements as the row of the given matrix.</returns>
public static ComplexDoubleVector GetRow(IROComplexDoubleMatrix mat, int row)
{
ComplexDoubleVector result = new ComplexDoubleVector(mat.Columns);
for (int i = 0; i < result.data.Length; ++i)
{
result.data[i] = mat[row, i];
}
return(result);
}
///<summary>Implicit cast conversion to <c>ComplexDoubleVector</c> from <c>DoubleVector</c></summary>
public static ComplexDoubleVector ToComplexDoubleVector(DoubleVector src)
{
double[] temp = src.ToArray();
var ret = new ComplexDoubleVector(temp.Length);
for (int i = 0; i < temp.Length; ++i)
{
ret.data[i] = temp[i];
}
return(ret);
}
private static double dznrm2Column(ComplexDoubleMatrix A, int Col, int Start)
{
// dznrm2Column returns the euclidean norm of a vector,
// which is a part of column Col in matrix A, beginning from Start to end of column
// so that dznrm2Column := sqrt( conjg( matrix' )*matrix )
double s = 0;
for (int i = Start; i < A.RowLength; i++)
{
s += (A[i, Col] * ComplexMath.Conjugate(A[i, Col])).Real;
}
return(System.Math.Sqrt(s));
}
private static double dznrm2Vector(ComplexDoubleVector A, int Start)
{
// dznrm2Vector returns the euclidean norm of a vector,
// which is a part of A, beginning from Start to end of vector
// so that dznrm2Vector := sqrt( conjg( matrix' )*matrix )
double s = 0;
for (int i = Start; i < A.Length; i++)
{
s += (A[i] * ComplexMath.Conjugate(A[i])).Real;
}
return(System.Math.Sqrt(s));
}
///<summary>Solves a system on linear equations, AX=B, where A is the factored matrixed.</summary>
///<param name="B">RHS side of the system.</param>
///<returns>the solution vector, X.</returns>
///<exception cref="ArgumentNullException">B is null.</exception>
///<exception cref="NotPositiveDefiniteException">A is not positive definite.</exception>
///<exception cref="ArgumentException">The number of rows of A and the length of B must be the same.</exception>
public ComplexDoubleVector Solve(IROComplexDoubleVector B)
{
if (B == null)
{
throw new System.ArgumentNullException("B cannot be null.");
}
Compute();
if (!ispd)
{
throw new NotPositiveDefiniteException();
}
else
{
if (B.Length != order)
{
throw new System.ArgumentException("The length of B must be the same as the order of the matrix.");
}
#if MANAGED
// Copy right hand side.
var X = new ComplexDoubleVector(B);
// Solve L*Y = B;
for (int i = 0; i < order; i++)
{
Complex sum = B[i];
for (int k = i - 1; k >= 0; k--)
{
sum -= l.data[i][k] * X.data[k];
}
X.data[i] = sum / l.data[i][i];
}
// Solve L'*X = Y;
for (int i = order - 1; i >= 0; i--)
{
Complex sum = X.data[i];
for (int k = i + 1; k < order; k++)
{
sum -= ComplexMath.Conjugate(l.data[k][i]) * X.data[k];
}
X.data[i] = sum / ComplexMath.Conjugate(l.data[i][i]);
}
return(X);
#else
Complex[] rhs = ComplexDoubleMatrix.ToLinearComplexArray(B);
Lapack.Potrs.Compute(Lapack.UpLo.Lower, order, 1, l.data, order, rhs, B.Length);
ComplexDoubleVector ret = new ComplexDoubleVector(order, B.Length);
ret.data = rhs;
return(ret);
#endif
}
}
///<summary>Explicit cast conversion to <c>ComplexFloatVector</c> from <c>double</c> array</summary>
static public ComplexFloatVector ToComplexFloatVector(ComplexDoubleVector src)
{
if (src == null)
{
return(null);
}
ComplexFloatVector ret = new ComplexFloatVector(src.Length);
for (int i = 0; i < src.Length; ++i)
{
ret.data[i] = (ComplexFloat)src[i];
}
return(ret);
}
///<summary>Implicit cast conversion to <c>ComplexDoubleVector</c> from <c>double</c> array</summary>
public static ComplexDoubleVector ToComplexDoubleVector(double[] src)
{
if (src == null)
{
return(null);
}
var ret = new ComplexDoubleVector(src.Length);
for (int i = 0; i < src.Length; ++i)
{
ret.data[i] = src[i];
}
return(ret);
}
///<summary>Compute the Infinity Norm of this <c>ComplexDoubleVector</c></summary>
///<returns><c>double</c> results from norm.</returns>
public double GetInfinityNorm()
{
double ret = 0;
for (int i = 0; i < data.Length; i++)
{
double tmp = ComplexMath.Absolute(data[i]);
if (tmp > ret)
{
ret = tmp;
}
}
return(ret);
}
public static ComplexDoubleVector GenerateRow(IComplexDoubleMatrix A, int r, int c1, int c2)
{
int cu = c2 - c1 + 1;
ComplexDoubleVector u = new ComplexDoubleVector(cu);
for (int j = c1; j <= c2; j++)
{
u[j - c1] = A[r, j];
A[r, j] = Complex.Zero;
}
double norm = u.GetNorm();
if (c1 == c2 || norm == 0)
{
A[r, c1] = new Complex(-u[0].Real, -u[0].Imag);
u[0] = System.Math.Sqrt(2);
return(u);
}
Complex scale = new Complex(1 / norm);
Complex t = Complex.Zero;
Complex t1 = Complex.Zero;
if (u[0].Real != 0 || u[0].Imag != 0)
{
t = u[0];
t1 = ComplexMath.Conjugate(u[0]);
t = ComplexMath.Absolute(t);
t = t1 / t;
scale = scale * t;
}
A[r, c1] = -Complex.One / scale;
for (int j = 0; j < cu; j++)
{
u[j] *= scale;
}
u[0] = new Complex(u[0].Real + 1);
double s = System.Math.Sqrt(1 / u[0].Real);
for (int j = 0; j < cu; j++)
{
u[j] = new Complex(s * u[j].Real, -s * u[j].Imag);
}
return(u);
}
public static ComplexDoubleVector GenerateColumn(IComplexDoubleMatrix A, int r1, int r2, int c)
{
int ru = r2 - r1 + 1;
ComplexDoubleVector u = new ComplexDoubleVector(r2 - r1 + 1);
for (int i = r1; i <= r2; i++)
{
u[i - r1] = A[i, c];
A[i, c] = Complex.Zero;
}
double norm = u.GetNorm();
if (r1 == r2 || norm == 0)
{
A[r1, c] = new Complex(-u[0]);
u[0] = System.Math.Sqrt(2);
return(u);
}
Complex scale = new Complex(1 / norm, 0);
Complex t = Complex.Zero;
Complex t1 = Complex.Zero;
if (u[0].Real != 0 || u[0].Imag != 0)
{
t = u[0];
t1 = ComplexMath.Conjugate(u[0]);
t = ComplexMath.Absolute(t);
t = t1 / t;
scale = scale * t;
}
A[r1, c] = -Complex.One / scale;
for (int i = 0; i < ru; i++)
{
u[i] = u[i] * scale;
}
u[0] = new Complex(u[0].Real + 1, 0);
double s = System.Math.Sqrt(1 / u[0].Real);
for (int i = 0; i < ru; i++)
{
u[i] = new Complex(s * u[i].Real, s * u[i].Imag);
}
return(u);
}
public static ComplexDoubleVector GenerateColumn(IComplexDoubleMatrix A, int r1, int r2, int c)
{
int ru = r2 - r1 + 1;
ComplexDoubleVector u = new ComplexDoubleVector(r2 - r1 + 1);
for (int i = r1; i <= r2; i++)
{
u[i - r1] = A[i, c];
A[i, c] = Complex.Zero;
}
double norm = u.GetNorm();
if (r1 == r2 || norm == 0)
{
A[r1, c] = new Complex(-u[0]);
u[0] = System.Math.Sqrt(2);
return u;
}
Complex scale = new Complex(1 / norm, 0);
Complex t = Complex.Zero;
Complex t1 = Complex.Zero;
if (u[0].Real != 0 || u[0].Imag != 0)
{
t = u[0];
t1 = ComplexMath.Conjugate(u[0]);
t = ComplexMath.Absolute(t);
t = t1 / t;
scale = scale * t;
}
A[r1, c] = -Complex.One / scale;
for (int i = 0; i < ru; i++)
{
u[i] = u[i] * scale;
}
u[0] = new Complex(u[0].Real + 1, 0);
double s = System.Math.Sqrt(1 / u[0].Real);
for (int i = 0; i < ru; i++)
{
u[i] = new Complex(s * u[i].Real, s * u[i].Imag);
}
return u;
}
/// <overloads>
/// Solve a square Toeplitz system.
/// </overloads>
/// <summary>
/// Solve a square Toeplitz system with a right-side vector.
/// </summary>
/// <param name="Y">The right-hand side of the system.</param>
/// <returns>The solution vector.</returns>
/// <exception cref="ArgumentNullException">
/// Parameter <B>Y</B> is a null reference.
/// </exception>
/// <exception cref="RankException">
/// The length of Y is not equal to the number of rows in the Toeplitz matrix.
/// </exception>
/// <exception cref="SingularMatrixException">
/// The Toeplitz matrix or one of the the leading sub-matrices is singular.
/// </exception>
/// <remarks>
/// This member solves the linear system <B>TX</B> = <B>Y</B>, where <B>T</B> is
/// the square Toeplitz matrix, <B>X</B> is the unknown solution vector
/// and <B>Y</B> is a known vector.
/// <para>
/// The class implicitly decomposes the inverse Toeplitz matrix into a <b>UDL</b> factorisation
/// using the Levinson algorithm, before calculating the solution vector.
/// </para>
/// </remarks>
public ComplexDoubleVector Solve(IROComplexDoubleVector Y)
{
ComplexDoubleVector X;
Complex Inner;
int i, j;
// check parameters
if (Y == null)
{
throw new System.ArgumentNullException("Y");
}
else if (m_Order != Y.Length)
{
throw new RankException("The length of Y is not equal to the number of rows in the Toeplitz matrix.");
}
Compute();
if (m_IsSingular == true)
{
throw new SingularMatrixException("One of the leading sub-matrices is singular.");
}
// allocate memory for solution
Complex[] A, B;
X = new ComplexDoubleVector(m_Order);
for (i = 0; i < m_Order; i++)
{
A = m_LowerTriangle[i];
B = m_UpperTriangle[i];
Inner = Y[i];
for (j = 0; j < i; j++)
{
Inner += A[j] * Y[j];
}
Inner *= m_Diagonal[i];
X[i] = Inner;
for (j = 0; j < i; j++)
{
X[j] += Inner * B[j];
}
}
return(X);
}
public void Current()
{
ComplexDoubleVector test = new ComplexDoubleVector(new Complex[2] { 1, 2 });
IEnumerator enumerator = test.GetEnumerator();
bool movenextresult;
movenextresult = enumerator.MoveNext();
Assert.IsTrue(movenextresult);
Assert.AreEqual(enumerator.Current, test[0]);
movenextresult = enumerator.MoveNext();
Assert.IsTrue(movenextresult);
Assert.AreEqual(enumerator.Current, test[1]);
movenextresult = enumerator.MoveNext();
Assert.IsFalse(movenextresult);
}
public void GetNorm()
{
ComplexDoubleVector a = new ComplexDoubleVector(new double[4]{0,1,2,3});
ComplexDoubleVector b = new ComplexDoubleVector(new double[4]{4,5,6,7});
Assert.AreEqual(a.GetNorm(),System.Math.Sqrt(14));
Assert.AreEqual(a.GetNorm(),a.GetNorm(2));
Assert.AreEqual(a.GetNorm(0),3);
Assert.AreEqual(b.GetNorm(),3*System.Math.Sqrt(14));
Assert.AreEqual(b.GetNorm(),b.GetNorm(2));
Assert.AreEqual(b.GetNorm(0),7);
}
/// <overloads>
/// Solve a symmetric square Toeplitz system.
/// </overloads>
/// <summary>
/// Solve a symmetric square Toeplitz system with a right-side vector.
/// </summary>
/// <param name="Y">The right-hand side of the system.</param>
/// <returns>The solution vector.</returns>
/// <exception cref="ArgumentNullException">
/// Parameter <B>Y</B> is a null reference.
/// </exception>
/// <exception cref="RankException">
/// The length of <B>Y</B> is not equal to the number of rows in the Toeplitz matrix.
/// </exception>
/// <exception cref="SingularMatrixException">
/// The Toeplitz matrix or one of the the leading sub-matrices is singular.
/// </exception>
/// <remarks>
/// This member solves the linear system <B>TX</B> = <B>Y</B>, where <B>T</B> is
/// the symmetric square Toeplitz matrix, <B>X</B> is the unknown solution vector
/// and <B>Y</B> is a known vector.
/// <para>
/// The class implicitly decomposes the inverse Toeplitz matrix into a <b>UDL</b> factorisation
/// using the Levinson algorithm, and then calculates the solution vector.
/// </para>
/// </remarks>
public ComplexDoubleVector Solve(IROComplexDoubleVector Y)
{
ComplexDoubleVector X;
// check parameters
if (Y == null)
{
throw new System.ArgumentNullException("Y");
}
else if (m_Order != Y.Length)
{
throw new RankException("The length of Y is not equal to the number of rows in the Toeplitz matrix.");
}
Compute();
if (m_IsSingular == true)
{
throw new SingularMatrixException("The Toeplitz matrix or one of the the leading sub-matrices is singular.");
}
int i, j, l; // index/loop variables
Complex Inner; // inner product
Complex G; // scaling constant
Complex[] A; // reference to current order coefficients
// allocate memory for solution
X = new ComplexDoubleVector(m_Order);
// setup zero order solution
X[0] = Y[0] / m_LeftColumn[0];
// solve systems of increasing order
for (i = 1; i < m_Order; i++)
{
// calculate inner product
Inner = Y[i];
for (j = 0, l = i; j < i; j++, l--)
{
Inner -= X[j] * m_LeftColumn[l];
}
// get the current predictor coefficients row
A = m_LowerTriangle[i];
// update the solution vector
G = Inner * m_Diagonal[i];
for (j = 0; j <= i; j++)
{
X[j] += G * A[j];
}
}
return X;
}
/// <summary>
/// Solve the Yule-Walker equations for a symmetric square Toeplitz system
/// </summary>
/// <param name="R">The left-most column of the Toeplitz matrix.</param>
/// <returns>The solution vector.</returns>
/// <exception cref="ArgumentNullException">
/// <B>R</B> is a null reference.
/// </exception>
/// <exception cref="ArgumentOutOfRangeException">
/// The length of <B>R</B> must be greater than one.
/// </exception>
/// <exception cref="SingularMatrixException">
/// The Toeplitz matrix or one of the the leading sub-matrices is singular.
/// </exception>
/// <remarks>
/// This member is used to solve the Yule-Walker system <B>AX</B> = -<B>a</B>,
/// where <B>A</B> is a symmetric square Toeplitz matrix, constructed
/// from the elements <B>R[0]</B>, ..., <B>R[N-2]</B> and
/// the vector <B>a</B> is constructed from the elements
/// <B>R[1]</B>, ..., <B>R[N-1]</B>.
/// <para>
/// Durbin's algorithm is used to solve the linear system. It requires
/// approximately the <b>N</b> squared FLOPS to calculate the
/// solution (<b>N</b> is the matrix order).
/// </para>
/// </remarks>
public static ComplexDoubleVector YuleWalker(IROComplexDoubleVector R)
{
ComplexDoubleVector a;
// check parameters
if (R == null)
{
throw new System.ArgumentNullException("R");
}
else if (R.Length < 2)
{
throw new System.ArgumentOutOfRangeException("R", "The length of R must be greater than 1.");
}
else
{
int N = R.Length - 1;
a = new ComplexDoubleVector(N); // prediction coefficients
ComplexDoubleVector Z = new ComplexDoubleVector(N); // temporary storage vector
Complex e; // predictor error
Complex inner; // inner product
Complex g; // reflection coefficient
int i, j, l;
// setup first order solution
e = R[0];
if (e == Complex.Zero)
{
throw new SingularMatrixException("The Toeplitz matrix or one of the the leading sub-matrices is singular.");
}
g = -R[1] / R[0];
a[0] = g;
// calculate solution for successive orders
for (i = 1; i < N; i++)
{
e *= (Complex.One - g * g);
if (e == Complex.Zero)
{
throw new SingularMatrixException("The Toeplitz matrix or one of the the leading sub-matrices is singular.");
}
// calculate inner product
inner = R[i + 1];
for (j = 0, l = i; j < i; j++, l--)
{
inner += a[j] * R[l];
}
// update prediction coefficients
g = -(inner / e);
for (j = 0, l = i - 1; j < i; j++, l--)
{
Z[j] = a[j] + g * a[l];
}
// copy vector
for (j = 0; j < i; j++)
{
a[j] = Z[j];
}
a[i] = g;
}
}
return a;
}
public void GetDotProduct()
{
ComplexDoubleVector a = new ComplexDoubleVector(new double[4]{0,1,2,3});
ComplexDoubleVector b = new ComplexDoubleVector(new double[4]{4,5,6,7});
Assert.AreEqual(a.GetDotProduct(),(Complex)14);
Assert.AreEqual(b.GetDotProduct(),(Complex)126);
Assert.AreEqual(a.GetDotProduct(b),(Complex)38);
Assert.AreEqual(a.GetDotProduct(b),b.GetDotProduct(a));
}
public void ICollection()
{
ComplexDoubleVector a = new ComplexDoubleVector(new Complex[4]{0,1,2,3});
Complex[] b = new Complex[5];
Assert.AreEqual(a.Count,a.Length);
a.CopyTo(b,1);
Assert.AreEqual(b[0],(Complex)0);
Assert.AreEqual(b[1],(Complex)0);
Assert.AreEqual(b[2],(Complex)1);
Assert.AreEqual(b[3],(Complex)2);
Assert.AreEqual(b[4],(Complex)3);
}
public void CtorDimensionsNegative()
{
ComplexDoubleVector test = new ComplexDoubleVector(-1);
}
public void Clone()
{
ComplexDoubleVector a = new ComplexDoubleVector(new double[4]{0,1,2,3});
ComplexDoubleVector b = a.Clone();
Assert.AreEqual(a[0],b[0]);
Assert.AreEqual(a[1],b[1]);
Assert.AreEqual(a[2],b[2]);
Assert.AreEqual(a[3],b[3]);
a=a*2;
Assert.AreEqual(a[0],b[0]*2);
Assert.AreEqual(a[1],b[1]*2);
Assert.AreEqual(a[2],b[2]*2);
Assert.AreEqual(a[3],b[3]*2);
}
public void Divide()
{
ComplexDoubleVector a = new ComplexDoubleVector(new double[4]{0,1,2,3});
ComplexDoubleVector c = new ComplexDoubleVector(a);
ComplexDoubleVector d = new ComplexDoubleVector(a);
double scal = -4;
c = a/scal;
d = ComplexDoubleVector.Divide(a,scal);
Assert.AreEqual(c[0],a[0]/scal);
Assert.AreEqual(c[1],a[1]/scal);
Assert.AreEqual(c[2],a[2]/scal);
Assert.AreEqual(c[3],a[3]/scal);
Assert.AreEqual(d[0],a[0]/scal);
Assert.AreEqual(d[1],a[1]/scal);
Assert.AreEqual(d[2],a[2]/scal);
Assert.AreEqual(d[3],a[3]/scal);
}
public void GetSum()
{
ComplexDoubleVector a = new ComplexDoubleVector(new double[4]{0,1,2,3});
ComplexDoubleVector b = new ComplexDoubleVector(new double[4]{4,5,6,7});
Assert.AreEqual(a.GetSum(),(Complex)6);
Assert.AreEqual(a.GetSumMagnitudes(),6);
Assert.AreEqual(b.GetSum(),(Complex)22);
Assert.AreEqual(b.GetSumMagnitudes(),22);
}
public void GetEnumeratorException()
{
ComplexDoubleVector a = new ComplexDoubleVector(new Complex[4]{0,1,2,3});
IEnumerator dve = a.GetEnumerator();
Complex b = (Complex)dve.Current;
}
public void Axpy()
{
ComplexDoubleVector a = new ComplexDoubleVector(new double[4]{0,1,2,3});
Double scal = 3;
ComplexDoubleVector b = new ComplexDoubleVector(4);
b.Axpy(scal,a);
a.Scale(scal);
Assert.AreEqual(a[0],b[0]);
Assert.AreEqual(a[1],b[1]);
Assert.AreEqual(a[2],b[2]);
Assert.AreEqual(a[3],b[3]);
}
public void GetEnumerator()
{
ComplexDoubleVector a = new ComplexDoubleVector(new Complex[4]{0,1,2,3});
IEnumerator dve = a.GetEnumerator();
Complex b;
bool c;
c = dve.MoveNext();
b = (Complex)dve.Current;
Assert.AreEqual(c,true);
Assert.AreEqual(b,(Complex)0);
c = dve.MoveNext();
b = (Complex)dve.Current;
Assert.AreEqual(c,true);
Assert.AreEqual(b,(Complex)1);
c = dve.MoveNext();
b = (Complex)dve.Current;
Assert.AreEqual(c,true);
Assert.AreEqual(b,(Complex)2);
c = dve.MoveNext();
b = (Complex)dve.Current;
Assert.AreEqual(c,true);
Assert.AreEqual(b,(Complex)3);
c = dve.MoveNext();
Assert.AreEqual(c,false);
}
public void Negate()
{
double[] vec = new double[4]{0,1,2,3};
ComplexDoubleVector a = new ComplexDoubleVector(vec);
ComplexDoubleVector b = -a;
a = ComplexDoubleVector.Negate(a);
Assert.AreEqual(-(Complex)vec[0],a[0]);
Assert.AreEqual(-(Complex)vec[1],a[1]);
Assert.AreEqual(-(Complex)vec[2],a[2]);
Assert.AreEqual(-(Complex)vec[3],a[3]);
Assert.AreEqual(-(Complex)vec[0],b[0]);
Assert.AreEqual(-(Complex)vec[1],b[1]);
Assert.AreEqual(-(Complex)vec[2],b[2]);
Assert.AreEqual(-(Complex)vec[3],b[3]);
}
public void IList()
{
ComplexDoubleVector a = new ComplexDoubleVector(new Complex[4]{0,1,2,3});
Assert.AreEqual(a.IsFixedSize,false);
Assert.AreEqual(a.IsReadOnly,false);
a.Add((Complex)4.0);
Assert.AreEqual(a.Length,5);
Assert.AreEqual(a[4],(Complex)4);
Assert.AreEqual(a.Contains((Complex)4.0),true);
a.Insert(1,(Complex)5.0);
Assert.AreEqual(a.Length,6);
Assert.AreEqual(a.Contains((Complex)5.0),true);
Assert.AreEqual(a[0],(Complex)0);
Assert.AreEqual(a[1],(Complex)5);
Assert.AreEqual(a[2],(Complex)1);
Assert.AreEqual(a[3],(Complex)2);
Assert.AreEqual(a[4],(Complex)3);
Assert.AreEqual(a[5],(Complex)4);
a.Remove((Complex)5.0);
Assert.AreEqual(a.Length,5);
Assert.AreEqual(a.Contains((Complex)5.0),false);
Assert.AreEqual(a[0],(Complex)0);
Assert.AreEqual(a[1],(Complex)1);
Assert.AreEqual(a[2],(Complex)2);
Assert.AreEqual(a[3],(Complex)3);
Assert.AreEqual(a[4],(Complex)4);
a.RemoveAt(2);
Assert.AreEqual(a.Length,4);
Assert.AreEqual(a.Contains((Complex)2.0),false);
Assert.AreEqual(a[0],(Complex)0);
Assert.AreEqual(a[1],(Complex)1);
Assert.AreEqual(a[2],(Complex)3);
Assert.AreEqual(a[3],(Complex)4);
}
public void Subtract()
{
ComplexDoubleVector a = new ComplexDoubleVector(new double[4]{0,1,2,3});
ComplexDoubleVector b = new ComplexDoubleVector(new double[4]{4,5,6,7});
ComplexDoubleVector c = new ComplexDoubleVector(a.Length);
ComplexDoubleVector d = new ComplexDoubleVector(b.Length);
c = a-b;
d = ComplexDoubleVector.Subtract(a,b);
Assert.AreEqual(c[0],a[0]-b[0]);
Assert.AreEqual(c[1],a[1]-b[1]);
Assert.AreEqual(c[2],a[2]-b[2]);
Assert.AreEqual(c[3],a[3]-b[3]);
Assert.AreEqual(d[0],c[0]);
Assert.AreEqual(d[1],c[1]);
Assert.AreEqual(d[2],c[2]);
Assert.AreEqual(d[3],c[3]);
a.Subtract(b);
Assert.AreEqual(c[0],a[0]);
Assert.AreEqual(c[1],a[1]);
Assert.AreEqual(c[2],a[2]);
Assert.AreEqual(c[3],a[3]);
}
public void CtorCopy()
{
ComplexDoubleVector a = new ComplexDoubleVector(new double[2]{0,1});
ComplexDoubleVector b = new ComplexDoubleVector(a);
Assert.AreEqual(b.Length,a.Length);
Assert.AreEqual(b[0],a[0]);
Assert.AreEqual(b[1],a[1]);
}
public void Add()
{
ComplexDoubleVector a = new ComplexDoubleVector(new double[4]{0,1,2,3});
ComplexDoubleVector b = new ComplexDoubleVector(new double[4]{4,5,6,7});
ComplexDoubleVector c = new ComplexDoubleVector(a.Length);
ComplexDoubleVector d = new ComplexDoubleVector(b.Length);
c = a+b;
d = ComplexDoubleVector.Add(a,b);
Assert.AreEqual(c[0],a[0]+b[0]);
Assert.AreEqual(c[1],a[1]+b[1]);
Assert.AreEqual(c[2],a[2]+b[2]);
Assert.AreEqual(c[3],a[3]+b[3]);
Assert.AreEqual(d[0],c[0]);
Assert.AreEqual(d[1],c[1]);
Assert.AreEqual(d[2],c[2]);
Assert.AreEqual(d[3],c[3]);
a.Add(b);
Assert.AreEqual(c[0],a[0]);
Assert.AreEqual(c[1],a[1]);
Assert.AreEqual(c[2],a[2]);
Assert.AreEqual(c[3],a[3]);
}
/// <summary>
/// Solve a symmetric square Toeplitz system with a right-side matrix.
/// </summary>
/// <param name="T">The left-most column of the Toeplitz matrix.</param>
/// <param name="Y">The right-side matrix of the system.</param>
/// <returns>The solution matrix.</returns>
/// <exception cref="ArgumentNullException">
/// <B>T</B> and/or <B>Y</B> are null references
/// </exception>
/// <exception cref="RankException">
/// The length of <B>T</B> does not match the number of rows in <B>Y</B>.
/// </exception>
/// <exception cref="SingularMatrixException">
/// The Toeplitz matrix or one of the the leading sub-matrices is singular.
/// </exception>
/// <remarks>
/// This method solves the linear system <B>AX</B> = <B>Y</B>. Where
/// <B>T</B> is a symmetric square Toeplitz matrix, <B>X</B> is an unknown
/// matrix and <B>Y</B> is a known matrix.
/// <para>
/// This static member combines the <b>UDL</b> decomposition and the calculation of the solution into a
/// single algorithm. When compared to the non-static member it requires minimal data storage
/// and suffers from no speed penalty.
/// </para>
/// </remarks>
public static ComplexDoubleMatrix Solve(IROComplexDoubleVector T, IROComplexDoubleMatrix Y)
{
ComplexDoubleMatrix X;
// check parameters
if (T == null)
{
throw new System.ArgumentNullException("T");
}
else if (Y == null)
{
throw new System.ArgumentNullException("Y");
}
else if (T.Length != Y.Columns)
{
throw new RankException("The length of T and Y are not equal.");
}
else
{
// allocate memory
int N = T.Length;
int M = Y.Rows;
X = new ComplexDoubleMatrix(N, M); // solution matrix
ComplexDoubleVector Z = new ComplexDoubleVector(N); // temporary storage vector
Complex e; // prediction error
int i, j, l, m;
// setup zero order solution
e = T[0];
if (e == Complex.Zero)
{
throw new SingularMatrixException("The Toeplitz matrix or one of the the leading sub-matrices is singular.");
}
for (m = 0; m < M; m++)
{
X[0, m] = Y[0,m] / T[0];
}
if (N > 1)
{
ComplexDoubleVector a = new ComplexDoubleVector(N - 1); // prediction coefficients
Complex p; // reflection coefficient
Complex inner; // inner product
Complex k;
// calculate solution for successive orders
for (i = 1; i < N; i++)
{
// calculate first inner product
inner = T[i];
for (j = 0, l = i - 1; j < i - 1; j++, l--)
{
inner += a[j] * T[l];
}
// update predictor coefficients
p = -(inner / e);
for (j = 0, l = i - 2; j < i - 1; j++, l--)
{
Z[j] = a[j] + p * a[l];
}
// copy vector
for (j = 0; j < i - 1; j++)
{
a[j] = Z[j];
}
a[i - 1] = p;
e *= (Complex.One - p * p);
if (e == Complex.Zero)
{
throw new SingularMatrixException("The Toeplitz matrix or one of the the leading sub-matrices is singular.");
}
// update the solution matrix
for (m = 0; m < M; m++)
{
// retrieve a copy of solution column
for (j = 0; j < i; j++)
{
Z[j] = X[j, m];
}
// calculate second inner product
inner = Y[i, m];
for (j = 0, l = i; j < i; j++, l--)
{
inner -= Z[j] * T[l];
}
// update solution vector
k = inner / e;
for (j = 0, l = i - 1; j < i; j++, l--)
{
Z[j] = Z[j] + k * a[l];
}
Z[j] = k;
// store solution column in matrix
for (j = 0; j <= i; j++)
{
X[j, m] = Z[j];
}
}
}
}
}
return X;
}
public void CtorDimensionsZero()
{
ComplexDoubleVector test = new ComplexDoubleVector(0);
}
/// <overloads>
/// There are two permuations of the constructor, both require a parameter corresponding
/// to the left-most column of a Toeplitz matrix.
/// </overloads>
/// <summary>
/// Constructor with <c>ComplexDoubleVector</c> parameter.
/// </summary>
/// <param name="T">The left-most column of the Toeplitz matrix.</param>
/// <exception cref="ArgumentNullException">
/// <B>T</B> is a null reference.
/// </exception>
/// <exception cref="RankException">
/// The length of <B>T</B> is zero.
/// </exception>
public ComplexDoubleSymmetricLevinson(IROComplexDoubleVector T)
{
// check parameter
if (T == null)
{
throw new System.ArgumentNullException("T");
}
else if (T.Length == 0)
{
throw new RankException("The length of T is zero.");
}
// save the vector
m_LeftColumn = new ComplexDoubleVector(T);
m_Order = m_LeftColumn.Length;
// allocate memory for lower triangular matrix
m_LowerTriangle = new Complex[m_Order][];
for (int i = 0; i < m_Order; i++)
{
m_LowerTriangle[i] = new Complex[i+1];
}
// allocate memory for diagonal
m_Diagonal = new Complex[m_Order];
}
public void ScalarMultiplyAndDivide()
{
ComplexDoubleVector a = new ComplexDoubleVector(new double[4]{0,1,2,3});
ComplexDoubleVector c = new ComplexDoubleVector(a);
ComplexDoubleVector d = new ComplexDoubleVector(a);
double scal = -4;
c.Multiply(scal);
d.Divide(scal);
Assert.AreEqual(c[0],a[0]*scal);
Assert.AreEqual(c[1],a[1]*scal);
Assert.AreEqual(c[2],a[2]*scal);
Assert.AreEqual(c[3],a[3]*scal);
Assert.AreEqual(d[0],a[0]/scal);
Assert.AreEqual(d[1],a[1]/scal);
Assert.AreEqual(d[2],a[2]/scal);
Assert.AreEqual(d[3],a[3]/scal);
c = a*scal;
Assert.AreEqual(c[0],a[0]*scal);
Assert.AreEqual(c[1],a[1]*scal);
Assert.AreEqual(c[2],a[2]*scal);
Assert.AreEqual(c[3],a[3]*scal);
c = scal*a;
Assert.AreEqual(c[0],a[0]*scal);
Assert.AreEqual(c[1],a[1]*scal);
Assert.AreEqual(c[2],a[2]*scal);
Assert.AreEqual(c[3],a[3]*scal);
}
/// <overloads>
/// Solve a symmetric square Toeplitz system.
/// </overloads>
/// <summary>
/// Solve a symmetric square Toeplitz system with a right-side vector.
/// </summary>
/// <param name="T">The left-most column of the Toeplitz matrix.</param>
/// <param name="Y">The right-side vector of the system.</param>
/// <returns>The solution vector.</returns>
/// <exception cref="ArgumentNullException">
/// <B>T</B> and/or <B>Y</B> are null references
/// </exception>
/// <exception cref="RankException">
/// The length of <B>T</B> does not match the length of <B>Y</B>.
/// </exception>
/// <exception cref="SingularMatrixException">
/// The Toeplitz matrix or one of the the leading sub-matrices is singular.
/// </exception>
/// <remarks>
/// This method solves the linear system <B>AX</B> = <B>Y</B>. Where
/// <B>T</B> is a symmetric square Toeplitz matrix, <B>X</B> is an unknown
/// vector and <B>Y</B> is a known vector.
/// <para>
/// This static member combines the <b>UDL</b> decomposition and the calculation of the solution into a
/// single algorithm. When compared to the non-static member it requires minimal data storage
/// and suffers from no speed penalty.
/// </para>
/// </remarks>
public static ComplexDoubleVector Solve(IROComplexDoubleVector T, IROComplexDoubleVector Y)
{
ComplexDoubleVector X;
// check parameters
if (T == null)
{
throw new System.ArgumentNullException("T");
}
else if (Y == null)
{
throw new System.ArgumentNullException("Y");
}
else if (T.Length != Y.Length)
{
throw new RankException("The length of T and Y are not equal.");
}
else
{
// allocate memory
int N = T.Length;
X = new ComplexDoubleVector(N); // solution vector
Complex e; // prediction error
// setup zero order solution
e = T[0];
if (e == Complex.Zero)
{
throw new SingularMatrixException("The Toeplitz matrix or one of the the leading sub-matrices is singular.");
}
X[0] = Y[0] / T[0];
if (N > 1)
{
ComplexDoubleVector a = new ComplexDoubleVector(N - 1); // prediction coefficients
ComplexDoubleVector Z = new ComplexDoubleVector(N - 1); // temporary storage vector
Complex g; // reflection coefficient
Complex inner; // inner product
Complex k;
int i, j, l;
// calculate solution for successive orders
for (i = 1; i < N; i++)
{
// calculate first inner product
inner = T[i];
for (j = 0, l = i - 1; j < i - 1; j++, l--)
{
inner += a[j] * T[l];
}
// update predictor coefficients
g = -(inner / e);
for (j = 0, l = i - 2; j < i - 1; j++, l--)
{
Z[j] = a[j] + g * a[l];
}
// copy vector
for (j = 0; j < i - 1; j++)
{
a[j] = Z[j];
}
a[i - 1] = g;
e *= (Complex.One - g * g);
if (e == Complex.Zero)
{
throw new SingularMatrixException("The Toeplitz matrix or one of the the leading sub-matrices is singular.");
}
// calculate second inner product
inner = Y[i];
for (j = 0, l = i; j < i; j++, l--)
{
inner -= X[j] * T[l];
}
// update solution vector
k = inner / e;
for (j = 0, l = i - 1; j < i; j++, l--)
{
X[j] = X[j] + k * a[l];
}
X[j] = k;
}
}
}
return X;
}
public void Multiply()
{
ComplexDoubleVector a = new ComplexDoubleVector(new double[4]{0,1,2,3});
ComplexDoubleVector b = new ComplexDoubleVector(new double[4]{4,5,6,7});
ComplexDoubleMatrix c = new ComplexDoubleMatrix(a.Length,b.Length);
ComplexDoubleMatrix d = new ComplexDoubleMatrix(a.Length,b.Length);
c = a*b;
d = ComplexDoubleVector.Multiply(a,b);
Assert.AreEqual(c[0,0],a[0]*b[0]);
Assert.AreEqual(c[0,1],a[0]*b[1]);
Assert.AreEqual(c[0,2],a[0]*b[2]);
Assert.AreEqual(c[0,3],a[0]*b[3]);
Assert.AreEqual(c[1,0],a[1]*b[0]);
Assert.AreEqual(c[1,1],a[1]*b[1]);
Assert.AreEqual(c[1,2],a[1]*b[2]);
Assert.AreEqual(c[1,3],a[1]*b[3]);
Assert.AreEqual(c[2,0],a[2]*b[0]);
Assert.AreEqual(c[2,1],a[2]*b[1]);
Assert.AreEqual(c[2,2],a[2]*b[2]);
Assert.AreEqual(c[2,3],a[2]*b[3]);
Assert.AreEqual(c[3,0],a[3]*b[0]);
Assert.AreEqual(c[3,1],a[3]*b[1]);
Assert.AreEqual(c[3,2],a[3]*b[2]);
Assert.AreEqual(c[3,3],a[3]*b[3]);
Assert.AreEqual(d[0,0],a[0]*b[0]);
Assert.AreEqual(d[0,1],a[0]*b[1]);
Assert.AreEqual(d[0,2],a[0]*b[2]);
Assert.AreEqual(d[0,3],a[0]*b[3]);
Assert.AreEqual(d[1,0],a[1]*b[0]);
Assert.AreEqual(d[1,1],a[1]*b[1]);
Assert.AreEqual(d[1,2],a[1]*b[2]);
Assert.AreEqual(d[1,3],a[1]*b[3]);
Assert.AreEqual(d[2,0],a[2]*b[0]);
Assert.AreEqual(d[2,1],a[2]*b[1]);
Assert.AreEqual(d[2,2],a[2]*b[2]);
Assert.AreEqual(d[2,3],a[2]*b[3]);
Assert.AreEqual(d[3,0],a[3]*b[0]);
Assert.AreEqual(d[3,1],a[3]*b[1]);
Assert.AreEqual(d[3,2],a[3]*b[2]);
Assert.AreEqual(d[3,3],a[3]*b[3]);
}
