public static double CalculateSsu()
{
// Stopwatch start
Timer.Restart();
var evector = new DenseVector(Length);
for (var i = 0; i < Length; i++ )
{
QMatrix[i, 0] = 1;
evector[i] = 0;
}
evector[0] = 1.0;
var qtilde = new SparseMatrix(QMatrix.Transpose().ToArray());
var v = new BiCgStab().Solve(qtilde, evector);
var result = v.Sum() - UpStates.Sum(i => v[i]);
// Stopwatch stop and store statistic
_timeToSSU = (ulong)Timer.ElapsedTicks;
Timer.Stop();
return result;
}
/// <summary>
/// Run example
/// </summary>
/// <seealso cref="http://en.wikipedia.org/wiki/Biconjugate_gradient_stabilized_method">Biconjugate gradient stabilized method</seealso>
public void Run()
{
// Format matrix output to console
var formatProvider = (CultureInfo)CultureInfo.InvariantCulture.Clone();
formatProvider.TextInfo.ListSeparator = " ";
// Solve next system of linear equations (Ax=b):
// 5*x + 2*y - 4*z = -7
// 3*x - 7*y + 6*z = 38
// 4*x + 1*y + 5*z = 43
// Create matrix "A" with coefficients
var matrixA = new DenseMatrix(new[,] { { 5.00, 2.00, -4.00 }, { 3.00, -7.00, 6.00 }, { 4.00, 1.00, 5.00 } });
Console.WriteLine(@"Matrix 'A' with coefficients");
Console.WriteLine(matrixA.ToString("#0.00\t", formatProvider));
Console.WriteLine();
// Create vector "b" with the constant terms.
var vectorB = new DenseVector(new[] { -7.0, 38.0, 43.0 });
Console.WriteLine(@"Vector 'b' with the constant terms");
Console.WriteLine(vectorB.ToString("#0.00\t", formatProvider));
Console.WriteLine();
// Create stop criteriums to monitor an iterative calculation. There are next available stop criteriums:
// - DivergenceStopCriterium: monitors an iterative calculation for signs of divergence;
// - FailureStopCriterium: monitors residuals for NaN's;
// - IterationCountStopCriterium: monitors the numbers of iteration steps;
// - ResidualStopCriterium: monitors residuals if calculation is considered converged;
// Stop calculation if 1000 iterations reached during calculation
var iterationCountStopCriterium = new IterationCountStopCriterium(1000);
// Stop calculation if residuals are below 1E-10 --> the calculation is considered converged
var residualStopCriterium = new ResidualStopCriterium(1e-10);
// Create monitor with defined stop criteriums
var monitor = new Iterator(new IIterationStopCriterium[] { iterationCountStopCriterium, residualStopCriterium });
// Create Bi-Conjugate Gradient Stabilized solver
var solver = new BiCgStab(monitor);
// 1. Solve the matrix equation
var resultX = solver.Solve(matrixA, vectorB);
Console.WriteLine(@"1. Solve the matrix equation");
Console.WriteLine();
// 2. Check solver status of the iterations.
// Solver has property IterationResult which contains the status of the iteration once the calculation is finished.
// Possible values are:
// - CalculationCancelled: calculation was cancelled by the user;
// - CalculationConverged: calculation has converged to the desired convergence levels;
// - CalculationDiverged: calculation diverged;
// - CalculationFailure: calculation has failed for some reason;
// - CalculationIndetermined: calculation is indetermined, not started or stopped;
// - CalculationRunning: calculation is running and no results are yet known;
// - CalculationStoppedWithoutConvergence: calculation has been stopped due to reaching the stopping limits, but that convergence was not achieved;
Console.WriteLine(@"2. Solver status of the iterations");
Console.WriteLine(solver.IterationResult);
Console.WriteLine();
// 3. Solution result vector of the matrix equation
Console.WriteLine(@"3. Solution result vector of the matrix equation");
Console.WriteLine(resultX.ToString("#0.00\t", formatProvider));
Console.WriteLine();
// 4. Verify result. Multiply coefficient matrix "A" by result vector "x"
var reconstructVecorB = matrixA * resultX;
Console.WriteLine(@"4. Multiply coefficient matrix 'A' by result vector 'x'");
Console.WriteLine(reconstructVecorB.ToString("#0.00\t", formatProvider));
Console.WriteLine();
}
public static double CalculateMttf()
{
Timer.Restart();
// Store necessary variables of formula
var partialLength = (ushort)UpStates.Count();
var pmatrix = new DenseMatrix(partialLength, partialLength);
var hvector = new DenseVector(partialLength);
// Convert QMatrix to PMatrix
for( var i = 0; i < partialLength; i++ )
{
var diagonal = QMatrix[UpStates[i], UpStates[i]];
hvector[i] = diagonal;
for( var j = 0; j < partialLength; j++ )
{
pmatrix[i, j] = -QMatrix[UpStates[i], UpStates[j]]/diagonal;
}
}
// Invert PMatrix and multiply by H-vector to get MTTF
var result = new BiCgStab().Solve(pmatrix, hvector);
_timeToMTTF = (ulong)Timer.ElapsedTicks;
return result[0];
}
