本文整理汇总了C#中DenseVector.Norm方法的典型用法代码示例。如果您正苦于以下问题：C# DenseVector.Norm方法的具体用法？C# DenseVector.Norm怎么用？C# DenseVector.Norm使用的例子？那么恭喜您, 这里精选的方法代码示例或许可以为您提供帮助。您也可以进一步了解该方法所在类DenseVector的用法示例。
在下文中一共展示了DenseVector.Norm方法的2个代码示例，这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞，您的评价将有助于系统推荐出更棒的C#代码示例。
示例1: Initialize
/// <summary>
/// Initializes the preconditioner and loads the internal data structures.
/// </summary>
/// <param name="matrix">
/// The <see cref="Matrix"/> upon which this preconditioner is based. Note that the
/// method takes a general matrix type. However internally the data is stored
/// as a sparse matrix. Therefore it is not recommended to pass a dense matrix.
/// </param>
/// <exception cref="ArgumentNullException"> If <paramref name="matrix"/> is <see langword="null" />.</exception>
/// <exception cref="ArgumentException">If <paramref name="matrix"/> is not a square matrix.</exception>
public void Initialize(Matrix matrix)
{
if (matrix == null)
{
throw new ArgumentNullException("matrix");
}
if (matrix.RowCount != matrix.ColumnCount)
{
throw new ArgumentException(Resources.ArgumentMatrixSquare, "matrix");
}
var sparseMatrix = (matrix is SparseMatrix) ? matrix as SparseMatrix : new SparseMatrix(matrix);
// The creation of the preconditioner follows the following algorithm.
// spaceLeft = lfilNnz * nnz(A)
// for i = 1, .. , n
// {
// w = a(i,*)
// for j = 1, .. , i - 1
// {
// if (w(j) != 0)
// {
// w(j) = w(j) / a(j,j)
// if (w(j) < dropTol)
// {
// w(j) = 0;
// }
// if (w(j) != 0)
// {
// w = w - w(j) * U(j,*)
// }
// }
// }
//
// for j = i, .. ,n
// {
// if w(j) <= dropTol * ||A(i,*)||
// {
// w(j) = 0
// }
// }
//
// spaceRow = spaceLeft / (n - i + 1) // Determine the space for this row
// lfil = spaceRow / 2 // space for this row of L
// l(i,j) = w(j) for j = 1, .. , i -1 // only the largest lfil elements
//
// lfil = spaceRow - nnz(L(i,:)) // space for this row of U
// u(i,j) = w(j) for j = i, .. , n // only the largest lfil - 1 elements
// w = 0
//
// if max(U(i,i + 1: n)) > U(i,i) / pivTol then // pivot if necessary
// {
// pivot by swapping the max and the diagonal entries
// Update L, U
// Update P
// }
// spaceLeft = spaceLeft - nnz(L(i,:)) - nnz(U(i,:))
// }
// Create the lower triangular matrix
_lower = new SparseMatrix(sparseMatrix.RowCount);
// Create the upper triangular matrix and copy the values
_upper = new SparseMatrix(sparseMatrix.RowCount);
// Create the pivot array
_pivots = new int[sparseMatrix.RowCount];
for (var i = 0; i < _pivots.Length; i++)
{
_pivots[i] = i;
}
Vector workVector = new DenseVector(sparseMatrix.RowCount);
Vector rowVector = new DenseVector(sparseMatrix.ColumnCount);
var indexSorting = new int[sparseMatrix.RowCount];
// spaceLeft = lfilNnz * nnz(A)
var spaceLeft = (int)_fillLevel * sparseMatrix.NonZerosCount;
// for i = 1, .. , n
for (var i = 0; i < sparseMatrix.RowCount; i++)
{
// w = a(i,*)
sparseMatrix.Row(i, workVector);
// pivot the row
PivotRow(workVector);
var vectorNorm = workVector.Norm(Double.PositiveInfinity);
// for j = 1, .. , i - 1)
//.........这里部分代码省略.........
示例2: Solve
/// <summary>
/// Solves the matrix equation Ax = b, where A is the coefficient matrix, b is the
/// solution vector and x is the unknown vector.
/// </summary>
/// <param name="matrix">The coefficient matrix, <c>A</c>.</param>
/// <param name="input">The solution vector, <c>b</c></param>
/// <param name="result">The result vector, <c>x</c></param>
public void Solve(Matrix matrix, Vector input, Vector result)
{
// If we were stopped before, we are no longer
// We're doing this at the start of the method to ensure
// that we can use these fields immediately.
_hasBeenStopped = false;
// Error checks
if (matrix == null)
{
throw new ArgumentNullException("matrix");
}
if (matrix.RowCount != matrix.ColumnCount)
{
throw new ArgumentException(Resources.ArgumentMatrixSquare, "matrix");
}
if (input == null)
{
throw new ArgumentNullException("input");
}
if (result == null)
{
throw new ArgumentNullException("result");
}
if (result.Count != input.Count)
{
throw new ArgumentException(Resources.ArgumentVectorsSameLength);
}
if (input.Count != matrix.RowCount)
{
throw Matrix.DimensionsDontMatch<ArgumentException>(input, matrix);
}
// Initialize the solver fields
// Set the convergence monitor
if (_iterator == null)
{
_iterator = Iterator.CreateDefault();
}
if (_preconditioner == null)
{
_preconditioner = new UnitPreconditioner();
}
_preconditioner.Initialize(matrix);
var d = new DenseVector(input.Count);
var r = new DenseVector(input);
var uodd = new DenseVector(input.Count);
var ueven = new DenseVector(input.Count);
var v = new DenseVector(input.Count);
var pseudoResiduals = new DenseVector(input);
var x = new DenseVector(input.Count);
var yodd = new DenseVector(input.Count);
var yeven = new DenseVector(input);
// Temp vectors
var temp = new DenseVector(input.Count);
var temp1 = new DenseVector(input.Count);
var temp2 = new DenseVector(input.Count);
// Initialize
var startNorm = input.Norm(2);
// Define the scalars
double alpha = 0;
double eta = 0;
double theta = 0;
var tau = startNorm;
var rho = tau * tau;
// Calculate the initial values for v
// M temp = yEven
_preconditioner.Approximate(yeven, temp);
// v = A temp
matrix.Multiply(temp, v);
// Set uOdd
v.CopyTo(ueven);
// Start the iteration
var iterationNumber = 0;
//.........这里部分代码省略.........