Пример #1
0
        public static void test_SparseCG_Precond()
        {
            // A test case where Jacobi preconditioner (ie M = diag(A)) provides some improvement
            // described in http://www.math.iit.edu/~fass/477577_Chapter_16.pdf

            int N = 10000;
            SymmetricSparseMatrix M = new SymmetricSparseMatrix();

            double[] B = new double[N];
            for (int i = 0; i < N; ++i)
            {
                for (int j = i; j < N; ++j)
                {
                    if (i == j)
                    {
                        M.Set(i, i, 0.5 + Math.Sqrt(i));
                    }
                    else if (Math.Abs(i - j) == 1)
                    {
                        M.Set(i, j, 1);
                    }
                    else if (Math.Abs(i - j) == 100)
                    {
                        M.Set(i, j, 1);
                    }
                }
                B[i] = 1;
            }

            SparseSymmetricCG Solver = new SparseSymmetricCG()
            {
                B = B, MultiplyF = M.Multiply
            };

            Solver.Solve();
            double[] BTest = new double[N];
            M.Multiply(Solver.X, BTest);
            double diff = BufferUtil.DistanceSquared(B, BTest);

            if (diff > MathUtil.ZeroTolerance)
            {
                System.Console.WriteLine("test_SparseCG: initial solve failed!");
            }

            PackedSparseMatrix PackedM = new PackedSparseMatrix(M);

            PackedM.Sort();
            SparseSymmetricCG Solver_PackedM = new SparseSymmetricCG()
            {
                B = B, MultiplyF = PackedM.Multiply
            };

            Solver_PackedM.Solve();
            PackedM.Multiply(Solver_PackedM.X, BTest);
            double diff_packed = BufferUtil.DistanceSquared(B, BTest);

            if (diff_packed > MathUtil.ZeroTolerance)
            {
                System.Console.WriteLine("test_SparseCG: Packed solve failed!");
            }

#if false
            SparseCholeskyDecomposition cholDecomp = new SparseCholeskyDecomposition(PackedM);
            cholDecomp.ComputeIncomplete();

            // factorization is filled with NaNs!! doing something wrong.

            double[] TmpX = new double[N], Y = new double[N];
            cholDecomp.Solve(BTest, TmpX, Y);

            // note: can also try just lower-triangular matrix - this is (L+D), Gauss-Seidel preconditioner?
            //   see http://www.math.iit.edu/~fass/477577_Chapter_16.pdf

            Action <double[], double[]> cholPrecond = (R, Z) => {
                cholDecomp.Solve(R, Z, Y);
            };

            SymmetricSparseMatrix diagPrecond = new SymmetricSparseMatrix(N);
            for (int k = 0; k < N; ++k)
            {
                diagPrecond[k, k] = 1.0 / M[k, k];
            }

            SparseSymmetricCG Solver_Precond = new SparseSymmetricCG()
            {
                B = B, MultiplyF = PackedM.Multiply, PreconditionMultiplyF = diagPrecond.Multiply
            };
            //SparseSymmetricCG Solver_Precond = new SparseSymmetricCG() { B = B, MultiplyF = PackedM.Multiply, PreconditionMultiplyF = cholPrecond };
            Solver_Precond.SolvePreconditioned();
            PackedM.Multiply(Solver_Precond.X, BTest);
            double diff_precond = BufferUtil.DistanceSquared(B, BTest);
            if (diff_precond > MathUtil.ZeroTolerance)
            {
                System.Console.WriteLine("test_SparseCG: cholesky-preconditioned solve failed!");
            }

            System.Console.WriteLine("Iterations regular {0}  precond {1}", Solver_PackedM.Iterations, Solver_Precond.Iterations);
            System.Console.WriteLine("Tol regular {0}  precond {1}", diff_packed, diff_precond);
#endif
        }
Пример #2
0
        // Result must be as large as Mesh.MaxVertexID
        public bool Solve(Vector3D[] Result)
        {
            if (WeightsM == null)
            {
                Initialize();       // force initialize...
            }
            UpdateForSolve();

            // use initial positions as initial solution.
            Array.Copy(Px, Sx, N);
            Array.Copy(Py, Sy, N);
            Array.Copy(Pz, Sz, N);

            Action <double[], double[]> CombinedMultiply = (X, B) => {
                // packed multiply is 3-4x faster...
                //M.Multiply(X, B);
                PackedM.Multiply(X, B);
                for (int i = 0; i < N; ++i)
                {
                    B[i] += WeightsM.D[i] * X[i];
                }
            };

            SparseSymmetricCG SolverX = new SparseSymmetricCG()
            {
                B                  = Bx, X = Sx,
                MultiplyF          = CombinedMultiply, PreconditionMultiplyF = Preconditioner.Multiply,
                UseXAsInitialGuess = true
            };
            SparseSymmetricCG SolverY = new SparseSymmetricCG()
            {
                B                  = By, X = Sy,
                MultiplyF          = CombinedMultiply, PreconditionMultiplyF = Preconditioner.Multiply,
                UseXAsInitialGuess = true
            };
            SparseSymmetricCG SolverZ = new SparseSymmetricCG()
            {
                B                  = Bz, X = Sz,
                MultiplyF          = CombinedMultiply, PreconditionMultiplyF = Preconditioner.Multiply,
                UseXAsInitialGuess = true
            };

            SparseSymmetricCG[] solvers = new SparseSymmetricCG[3] {
                SolverX, SolverY, SolverZ
            };
            bool[] ok      = new bool[3];
            int[]  indices = new int[3] {
                0, 1, 2
            };

            // preconditioned solve is slower =\
            //Action<int> SolveF = (i) => {  ok[i] = solvers[i].SolvePreconditioned(); };
            Action <int> SolveF = (i) => { ok[i] = solvers[i].Solve(); };

            gParallel.ForEach(indices, SolveF);

            if (ok[0] == false || ok[1] == false || ok[2] == false)
            {
                return(false);
            }

            for (int i = 0; i < N; ++i)
            {
                int vid = ToMeshV[i];
                Result[vid] = new Vector3D(Sx[i], Sy[i], Sz[i]);
            }

            // apply post-fixed constraints
            if (HavePostFixedConstraints)
            {
                foreach (var constraint in SoftConstraints)
                {
                    if (constraint.Value.PostFix)
                    {
                        int vid = constraint.Key;
                        Result[vid] = constraint.Value.Position;
                    }
                }
            }

            return(true);
        }
Пример #3
0
        public static void test_SparseCG()
        {
            Random r = new Random(31337);

            int N   = 100;
            var pts = TestUtil.RandomScalars(N, r, new Interval1d(1, 10));
            SymmetricSparseMatrix M = new SymmetricSparseMatrix();

            double[] B = new double[N];
            for (int i = 0; i < N; ++i)
            {
                for (int j = i; j < N; ++j)
                {
                    if (i == j)
                    {
                        M.Set(i, j, pts[i]);
                    }
                    else
                    {
                        M.Set(i, j, (double)(i + j) / 10.0);
                    }
                }
                B[i] = i + 1;
            }

            SparseSymmetricCG Solver = new SparseSymmetricCG()
            {
                B = B, MultiplyF = M.Multiply
            };

            Solver.Solve();
            double[] BTest = new double[N];
            M.Multiply(Solver.X, BTest);
            double diff = BufferUtil.DistanceSquared(B, BTest);

            if (diff > MathUtil.ZeroTolerance)
            {
                System.Console.WriteLine("test_SparseCG: initial solve failed!");
            }

            PackedSparseMatrix PackedM = new PackedSparseMatrix(M);

            PackedM.Sort();
            SparseSymmetricCG Solver_PackedM = new SparseSymmetricCG()
            {
                B = B, MultiplyF = PackedM.Multiply
            };

            Solver_PackedM.Solve();
            PackedM.Multiply(Solver_PackedM.X, BTest);
            double diff_packed = BufferUtil.DistanceSquared(B, BTest);

            if (diff_packed > MathUtil.ZeroTolerance)
            {
                System.Console.WriteLine("test_SparseCG: Packed solve failed!");
            }

#if false
            SparseCholeskyDecomposition decomp = new SparseCholeskyDecomposition(PackedM);
            decomp.ComputeIncomplete();
            PackedSparseMatrix choleskyPrecond = decomp.L.Square();

            SymmetricSparseMatrix diagPrecond = new SymmetricSparseMatrix(N);
            for (int k = 0; k < N; ++k)
            {
                diagPrecond[k, k] = 1.0 / M[k, k];
            }

            SparseSymmetricCG Solver_Precond = new SparseSymmetricCG()
            {
                B = B, MultiplyF = PackedM.Multiply, PreconditionMultiplyF = diagPrecond.Multiply
            };
            Solver_Precond.SolvePreconditioned();
            PackedM.Multiply(Solver_Precond.X, BTest);
            double diff_precond = BufferUtil.DistanceSquared(B, BTest);
            if (diff_precond > MathUtil.ZeroTolerance)
            {
                System.Console.WriteLine("test_SparseCG: cholesky-preconditioned solve failed!");
            }

            System.Console.WriteLine("Iterations regular {0}  precond {1}", Solver_PackedM.Iterations, Solver_Precond.Iterations);
            System.Console.WriteLine("Tol regular {0}  precond {1}", diff_packed, diff_precond);
#endif
        }