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]; }