public void SetColumnArrayWrongRank()
 {
   ComplexFloatMatrix a = new ComplexFloatMatrix(2,2);
   ComplexFloat[] b = new ComplexFloat[3];
   a.SetColumn(1,b);
 }
 public void SetColumnArray()
 {
   ComplexFloatMatrix a = new ComplexFloatMatrix(2,2);
   ComplexFloat[] b = new ComplexFloat[2];
   b[0] = new ComplexFloat(1,1);
   b[1] = new ComplexFloat(2,2);
   a.SetColumn(0,b);
   Assert.AreEqual(b[0], a[0,0]);
   Assert.AreEqual(b[1], a[1,0]);
 }
 public void SetColumnArrayOutOfRange()
 {
   ComplexFloatMatrix a = new ComplexFloatMatrix(2,2);
   ComplexFloat[] b = new ComplexFloat[2];
   a.SetColumn(2,b);
 }
 public void SetColumnWrongRank()
 {
   ComplexFloatMatrix a = new ComplexFloatMatrix(2,2);
   ComplexFloatVector b = new ComplexFloatVector(3);
   a.SetColumn(1,b);
 }
 public void SetColumnOutOfRange()
 {
   ComplexFloatMatrix a = new ComplexFloatMatrix(2,2);
   ComplexFloatVector b = new ComplexFloatVector(2);
   a.SetColumn(2,b);
 }
 public void SetColumn()
 {
   ComplexFloatMatrix a = new ComplexFloatMatrix(2,2);
   ComplexFloatVector b = new ComplexFloatVector(2);
   b[0] = 1;
   b[1] = 2;
   a.SetColumn(0,b);
   Assert.AreEqual(b[0], a[0,0]);
   Assert.AreEqual(b[1], a[1,0]);
 }
Exemplo n.º 7
0
		/// <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 ComplexFloatMatrix Solve(IROComplexFloatMatrix Y)
		{
			ComplexFloatMatrix X;
			ComplexFloat Inner;
			ComplexFloat[] 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 ComplexFloatMatrix(m_Order, Y.Rows);
			x = new ComplexFloat[m_Order];

			for (l = 0; l < Y.Rows; l++)
			{
				// get right-side column
				y = ComplexFloatVector.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;
		}
Exemplo n.º 8
0
		/// <summary>
		/// Solve a square Toeplitz system with a right-side matrix.
		/// </summary>
		/// <param name="col">The left-most column of the Toeplitz matrix.</param>
		/// <param name="row">The top-most row of the Toeplitz matrix.</param>
		/// <param name="Y">The right-side matrix of the system.</param>
		/// <returns>The solution matrix.</returns>
		/// <exception cref="ArgumentNullException">
		/// <EM>col</EM> is a null reference,
		/// <para>or</para>
		/// <para><EM>row</EM> is a null reference,</para>
		/// <para>or</para>
		/// <para><EM>Y</EM> is a null reference.</para>
		/// </exception>
		/// <exception cref="RankException">
		/// The length of <EM>col</EM> is 0,
		/// <para>or</para>
		/// <para>the lengths of <EM>col</EM> and <EM>row</EM> are not equal,</para>
		/// <para>or</para>
		/// <para>the number of rows in <EM>Y</EM> does not the length of <EM>col</EM> and <EM>row</EM>.</para>
		/// </exception>
		/// <exception cref="SingularMatrixException">
		/// The Toeplitz matrix or one of the the leading sub-matrices is singular.
		/// </exception>
		/// <exception cref="ArithmeticException">
		/// The values of the first element of <EM>col</EM> and <EM>row</EM> are not equal.
		/// </exception>
		/// <remarks>
		/// This method solves the linear system <B>AX</B> = <B>Y</B>. Where
		/// <B>T</B> is a square Toeplitz matrix, <B>X</B> is an unknown
		/// matrix and <B>Y</B> is a known matrix.
		/// <para>
		/// The classic Levinson algorithm is used to solve the system. The algorithm
		/// assumes that all the leading sub-matrices of the Toeplitz matrix are
		/// non-singular. When a sub-matrix is near singular, accuracy will
		/// be degraded. This member requires approximately <B>N</B> squared
		/// FLOPS to calculate a solution, where <B>N</B> is the matrix order.
		/// </para>
		/// <para>
		/// This static method has minimal storage requirements as it combines
		/// the <b>UDL</b> decomposition with the calculation of the solution vector
		/// in a single algorithm.
		/// </para>
		/// </remarks>
		public static ComplexFloatMatrix Solve(IROComplexFloatVector col, IROComplexFloatVector row, IROComplexFloatMatrix Y)
		{
			// check parameters
			if (col == null)
			{
				throw new System.ArgumentNullException("col");
			}
			else if (col.Length == 0)
			{
				throw new RankException("The length of col is zero.");
			}
			else if (row == null)
			{
				throw new System.ArgumentNullException("row");
			}
			else if (col.Length != row.Length)
			{
				throw new RankException("The lengths of col and row are not equal.");
			}
			else if (col[0] != row[0])
			{
				throw new ArithmeticException("The values of the first element of col and row are not equal.");
			}
			else if (Y == null)
			{
				throw new System.ArgumentNullException("Y");
			}
			else if (col.Length != Y.Columns)
			{
				throw new RankException("The numer of rows in Y does not match the length of col and row.");
			}

			// check if leading diagonal is zero
			if (col[0] == ComplexFloat.Zero)
			{
				throw new SingularMatrixException("One of the leading sub-matrices is singular.");
			}

			// decompose matrix
			int order = col.Length;
			ComplexFloat[] A = new ComplexFloat[order];
			ComplexFloat[] B = new ComplexFloat[order];
			ComplexFloat[] Z = new ComplexFloat[order];
			ComplexFloatMatrix X = new ComplexFloatMatrix(order);
			ComplexFloat Q, S, Ke, Kr, e;
			ComplexFloat Inner;
			int i, j, l;

			// setup the zero order solution
			A[0] = ComplexFloat.One;
			B[0] = ComplexFloat.One;
			e = ComplexFloat.One / col[0];
			X.SetRow(0, e * ComplexFloatVector.GetRow(Y, 0));

			for (i = 1; i < order; i++)
			{
				// calculate inner products
				Q = ComplexFloat.Zero;
				for (j = 0, l = 1; j < i; j++, l++)
				{
					Q += col[l] * A[j];
				}

				S = ComplexFloat.Zero;
				for (j = 0, l = 1; j < i; j++, l++)
				{
					S += row[l] * B[j];
				}

				// reflection coefficients
				Kr = -S * e;
				Ke = -Q * e;

				// update lower triangle (in temporary storage)
				Z[0] = ComplexFloat.Zero;
				Array.Copy(A, 0, Z, 1, i);
				for (j = 0, l = i - 1; j < i; j++, l--)
				{
					Z[j] += Ke * B[l];
				}

				// update upper triangle
				for (j = i; j > 0; j--)
				{
					B[j] = B[j - 1];
				}

				B[0] = ComplexFloat.Zero;
				for (j = 0, l = i - 1; j < i; j++, l--)
				{
					B[j] += Kr * A[l];
				}

				// copy from temporary storage to lower triangle
				Array.Copy(Z, 0, A, 0, i + 1);

				// check for singular sub-matrix)
				if (Ke * Kr == ComplexFloat.One)
				{
					throw new SingularMatrixException("One of the leading sub-matrices is singular.");
				}

				// update diagonal
				e = e / (ComplexFloat.One - Ke * Kr);

				for (l = 0; l < Y.Rows; l++)
				{
					ComplexFloatVector W = X.GetColumn(l);
					ComplexFloatVector M = ComplexFloatVector.GetColumn(Y, l);

					Inner = M[i];
					for (j = 0; j < i; j++)
					{
						Inner += A[j] * M[j];
					}
					Inner *= e;

					W[i] = Inner;
					for (j = 0; j < i; j++)
					{
						W[j] += Inner * B[j];
					}

					X.SetColumn(l, W);
				}
			}

			return X;
		}