public void Test1()
        {
            MatrixF A = new MatrixF(new float[,] { { 4 } });
              VectorF b = new VectorF(new float[] { 20 });

              GaussSeidelMethodF solver = new GaussSeidelMethodF();
              VectorF x = solver.Solve(A, null, b);

              Assert.IsTrue(VectorF.AreNumericallyEqual(new VectorF(1, 5), x));
              Assert.AreEqual(2, solver.NumberOfIterations);
        }
        public void Test4()
        {
            MatrixF A = new MatrixF(new float[,] { { -12, 2 },
                                             { 2, 3 }});
              VectorF b = new VectorF(new float[] { 20, 28 });

              GaussSeidelMethodF solver = new GaussSeidelMethodF();
              VectorF x = solver.Solve(A, null, b);

              VectorF solution = MatrixF.SolveLinearEquations(A, b);
              Assert.IsTrue(VectorF.AreNumericallyEqual(solution, x));
        }
        public void Test5()
        {
            MatrixF A = new MatrixF(new float[,] { { -21, 2, -4, 0 },
                                             { 2, 3, 0.1f, -1 },
                                             { 2, 10, 111.1f, -11 },
                                             { 23, 112, 111.1f, -143 }});
              VectorF b = new VectorF(new float[] { 20, 28, -12, 0.1f });

              GaussSeidelMethodF solver = new GaussSeidelMethodF();
              VectorF x = solver.Solve(A, null, b);

              VectorF solution = MatrixF.SolveLinearEquations(A, b);
              Assert.IsTrue(VectorF.AreNumericallyEqual(solution, x));
        }
Example #4
0
        public void Test9()
        {
            MatrixF A = new MatrixF(new float[,] { { -21, 2, -4, 0 },
                                             { 2, 3, 0.1f, -1 },
                                             { 2, 10, 111.1f, -11 },
                                             { 23, 112, 111.1f, -143 }});
              VectorF b = new VectorF(new float[] { 20, 28, -12, 0.1f });

              SorMethodF solver = new SorMethodF();
              solver.RelaxationFactor = 1.5f;
              solver.MaxNumberOfIterations = 4;
              VectorF x = solver.Solve(A, null, b);

              VectorF solution = MatrixF.SolveLinearEquations(A, b);
              Assert.IsFalse(VectorF.AreNumericallyEqual(solution, x));
              Assert.AreEqual(4, solver.NumberOfIterations);

              // Compare with Gauss-Seidel. Should be unequal because the relaxation factor is not 1.
              GaussSeidelMethodF gsSolver = new GaussSeidelMethodF();
              solver.MaxNumberOfIterations = 4;
              VectorF gsSolution = gsSolver.Solve(A, null, b);
              Assert.IsFalse(VectorF.AreNumericallyEqual(gsSolution, x));
        }
 public void TestArgumentNullException2()
 {
     GaussSeidelMethodF solver = new GaussSeidelMethodF();
       VectorF x = solver.Solve(new MatrixF(), null, null);
 }
 public void TestArgumentNullException()
 {
     GaussSeidelMethodF solver = new GaussSeidelMethodF();
       VectorF x = solver.Solve(null, null, new VectorF());
 }
 public void TestArgumentException3()
 {
     GaussSeidelMethodF solver = new GaussSeidelMethodF();
       VectorF x = solver.Solve(new MatrixF(3, 3), new VectorF(4), new VectorF(3));
 }
        public void Test7()
        {
            MatrixF A = new MatrixF(new float[,] { { -21, 2, -4, 0 },
                                             { 2, 3, 0.1f, -1 },
                                             { 2, 10, 111.1f, -11 },
                                             { 23, 112, 111.1f, -143 }});
              VectorF b = new VectorF(new float[] { 20, 28, -12, 0.1f });

              GaussSeidelMethodF solver = new GaussSeidelMethodF();
              solver.Epsilon = 0.1f;
              VectorF x = solver.Solve(A, null, b);

              VectorF solution = MatrixF.SolveLinearEquations(A, b);
              Assert.IsTrue(VectorF.AreNumericallyEqual(solution, x, 0.1f));
              Assert.IsFalse(VectorF.AreNumericallyEqual(solution, x));
              Assert.Greater(12, solver.NumberOfIterations); // For normal accuracy (EpsilonF) we need 12 iterations.
        }