本文整理汇总了C#中MathNet.Numerics.LinearAlgebra.Single.SparseMatrix.Multiply方法的典型用法代码示例。如果您正苦于以下问题：C# SparseMatrix.Multiply方法的具体用法？C# SparseMatrix.Multiply怎么用？C# SparseMatrix.Multiply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MathNet.Numerics.LinearAlgebra.Single.SparseMatrix的用法示例。
在下文中一共展示了SparseMatrix.Multiply方法的3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: CheckResult
/// <summary>
/// Check the result.
/// </summary>
/// <param name="preconditioner">Specific preconditioner.</param>
/// <param name="matrix">Source matrix.</param>
/// <param name="vector">Initial vector.</param>
/// <param name="result">Result vector.</param>
protected override void CheckResult(IPreconditioner<float> preconditioner, SparseMatrix matrix, Vector<float> vector, Vector<float> result)
{
Assert.AreEqual(typeof (DiagonalPreconditioner), preconditioner.GetType(), "#01");
// Compute M * result = product
// compare vector and product. Should be equal
var product = new DenseVector(result.Count);
matrix.Multiply(result, product);
for (var i = 0; i < product.Count; i++)
{
Assert.IsTrue(((double) vector[i]).AlmostEqualNumbersBetween(product[i], -Epsilon.Magnitude()), "#02-" + i);
}
}示例2: SolvePoissonMatrixAndBackMultiply
public void SolvePoissonMatrixAndBackMultiply()
{
// Create the matrix
var matrix = new SparseMatrix(25);
// Assemble the matrix. We assume we're solving the Poisson equation
// on a rectangular 5 x 5 grid
const int GridSize = 5;
// The pattern is:
// 0 .... 0 -1 0 0 0 0 0 0 0 0 -1 4 -1 0 0 0 0 0 0 0 0 -1 0 0 ... 0
for (var i = 0; i < matrix.RowCount; i++)
{
// Insert the first set of -1's
if (i > (GridSize - 1))
{
matrix[i, i - GridSize] = -1;
}
// Insert the second set of -1's
if (i > 0)
{
matrix[i, i - 1] = -1;
}
// Insert the centerline values
matrix[i, i] = 4;
// Insert the first trailing set of -1's
if (i < matrix.RowCount - 1)
{
matrix[i, i + 1] = -1;
}
// Insert the second trailing set of -1's
if (i < matrix.RowCount - GridSize)
{
matrix[i, i + GridSize] = -1;
}
}
// Create the y vector
var y = DenseVector.Create(matrix.RowCount, i => 1);
// Create an iteration monitor which will keep track of iterative convergence
var monitor = new Iterator<float>(
new IterationCountStopCriterium<float>(MaximumIterations),
new ResidualStopCriterium(ConvergenceBoundary),
new DivergenceStopCriterium(),
new FailureStopCriterium());
var solver = new TFQMR();
// Solve equation Ax = y
var x = matrix.SolveIterative(y, solver, monitor);
// Now compare the results
Assert.IsNotNull(x, "#02");
Assert.AreEqual(y.Count, x.Count, "#03");
// Back multiply the vector
var z = matrix.Multiply(x);
// Check that the solution converged
Assert.IsTrue(monitor.Status == IterationStatus.Converged, "#04");
// Now compare the vectors
for (var i = 0; i < y.Count; i++)
{
Assert.IsTrue(Math.Abs(y[i] - z[i]).IsSmaller(ConvergenceBoundary, 1), "#05-" + i);
}
}示例3: SolvePoissonMatrixAndBackMultiply
public void SolvePoissonMatrixAndBackMultiply()
{
// Create the matrix
var matrix = new SparseMatrix(25);
// Assemble the matrix. We assume we're solving the Poisson equation
// on a rectangular 5 x 5 grid
const int GridSize = 5;
// The pattern is:
// 0 .... 0 -1 0 0 0 0 0 0 0 0 -1 4 -1 0 0 0 0 0 0 0 0 -1 0 0 ... 0
for (var i = 0; i < matrix.RowCount; i++)
{
// Insert the first set of -1's
if (i > (GridSize - 1))
{
matrix[i, i - GridSize] = -1;
}
// Insert the second set of -1's
if (i > 0)
{
matrix[i, i - 1] = -1;
}
// Insert the centerline values
matrix[i, i] = 4;
// Insert the first trailing set of -1's
if (i < matrix.RowCount - 1)
{
matrix[i, i + 1] = -1;
}
// Insert the second trailing set of -1's
if (i < matrix.RowCount - GridSize)
{
matrix[i, i + GridSize] = -1;
}
}
// Create the y vector
var y = DenseVector.Create(matrix.RowCount, i => 1);
// Due to datatype "float" it can happen that solution will not converge for specific random starting vectors
// That's why we will do 3 tries
for (var iteration = 0; iteration <= 3; iteration++)
{
// Create an iteration monitor which will keep track of iterative convergence
var monitor = new Iterator<float>(
new IterationCountStopCriterium<float>(MaximumIterations),
new ResidualStopCriterium<float>(ConvergenceBoundary),
new DivergenceStopCriterium<float>(),
new FailureStopCriterium<float>());
var solver = new MlkBiCgStab();
// Solve equation Ax = y
Vector<float> x;
try
{
x = matrix.SolveIterative(y, solver, monitor);
}
catch (Exception)
{
continue;
}
if (monitor.Status != IterationStatus.Converged)
{
continue;
}
// Now compare the results
Assert.IsNotNull(x, "#02");
Assert.AreEqual(y.Count, x.Count, "#03");
// Back multiply the vector
var z = matrix.Multiply(x);
// Now compare the vectors
for (var i = 0; i < y.Count; i++)
{
Assert.GreaterOrEqual(ConvergenceBoundary, Math.Abs(y[i] - z[i]), "#05-" + i);
}
return;
}
}