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
        public void Initialize()
        {
            ToMeshV = new int[Mesh.MaxVertexID];
            ToIndex = new int[Mesh.MaxVertexID];
            N       = 0;
            foreach (int vid in Mesh.VertexIndices())
            {
                ToMeshV[N]   = vid;
                ToIndex[vid] = N;
                N++;
            }

            Px         = new double[N];
            Py         = new double[N];
            Pz         = new double[N];
            nbr_counts = new int[N];
            M          = new SymmetricSparseMatrix();

            for (int i = 0; i < N; ++i)
            {
                int      vid = ToMeshV[i];
                Vector3D v   = Mesh.GetVertex(vid);
                Px[i]         = v.x; Py[i] = v.y; Pz[i] = v.z;
                nbr_counts[i] = Mesh.GetVtxEdgeCount(vid);
            }

            // construct laplacian matrix
            for (int i = 0; i < N; ++i)
            {
                int vid = ToMeshV[i];
                int n   = nbr_counts[i];

                double sum_w = 0;
                foreach (int nbrvid in Mesh.VtxVerticesItr(vid))
                {
                    int j  = ToIndex[nbrvid];
                    int n2 = nbr_counts[j];

                    // weight options
                    //double w = -1;
                    double w = -1.0 / Math.Sqrt(n + n2);
                    //double w = -1.0 / n;

                    M.Set(i, j, w);
                    sum_w += w;
                }
                sum_w = -sum_w;
                M.Set(vid, vid, sum_w);
            }

            // transpose(L) * L, but matrix is symmetric...
            if (UseSoftConstraintNormalEquations)
            {
                //M = M.Multiply(M);
                M = M.Square();        // only works if M is symmetric
            }

            // construct packed version of M matrix
            PackedM = new PackedSparseMatrix(M);

            // compute laplacian vectors of initial mesh positions
            MLx = new double[N];
            MLy = new double[N];
            MLz = new double[N];
            M.Multiply(Px, MLx);
            M.Multiply(Py, MLy);
            M.Multiply(Pz, MLz);

            // zero out...
            for (int i = 0; i < Px.Length; ++i)
            {
                MLx[i] = 0;
                MLy[i] = 0;
                MLz[i] = 0;
            }

            // allocate memory for internal buffers
            Preconditioner = new DiagonalMatrix(N);
            WeightsM       = new DiagonalMatrix(N);
            Cx             = new double[N]; Cy = new double[N]; Cz = new double[N];
            Bx             = new double[N]; By = new double[N]; Bz = new double[N];
            Sx             = new double[N]; Sy = new double[N]; Sz = new double[N];

            UpdateForSolve();
        }
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
        }