# include "sandia_rules.hpp" # include "sandia_rules2.hpp" # include "sandia_sgmga.hpp" # include # include # include # include // // Two global variables needed to support the "parameter" function. // double *P; int *NP; int main ( ); void sandia_sgmga_size_tests ( ); void sandia_sgmga_size_test ( int dim_num, double importance[], double level_weight[], int level_max_min, int level_max_max, int growth, void ( *gw_compute_points[] ) ( int order, int dim, double w[] ), double tol, int ( *gw_compute_order[] ) ( int level, int growth ) ); typedef void ( *GWPointer ) ( int order, int dim, double w[] ); typedef int ( *GWPointer2 ) ( int level, int growth ); //****************************************************************************80 int main ( ) //****************************************************************************80 // // Purpose: // // MAIN is the main program for SANDIA_SGMGA_SIZE_TEST. // // Discussion: // // SANDIA_SGMGA_SIZE_TEST tests SANDIA_SGMGA_SIZE and SANDIA_SGMGA_SIZE_TOTAL. // // Licensing: // // This code is distributed under the GNU LGPL license. // // Modified: // // 13 April 2010 // // Author: // // John Burkardt // { webbur::timestamp ( ); std::cout << "\n"; std::cout << "SANDIA_SGMGA_SIZE_TEST\n"; std::cout << " C++ version\n"; std::cout << " Test SANDIA_SGMGA_SIZE and SANDIA_SGMGA_SIZE_TOTAL.\n"; sandia_sgmga_size_tests ( ); // // Terminate. // std::cout << "\n"; std::cout << "SANDIA_SGMGA_SIZE_TEST\n"; std::cout << " Normal end of execution.\n"; std::cout << "\n"; webbur::timestamp ( ); return 0; } namespace webbur { //****************************************************************************80 double parameter ( int dim, int offset ) //****************************************************************************80 // // Purpose: // // PARAMETER is a user-supplied routine to retrieve parameters. // // Discussion: // // The declaration for this function is in SANDIA_RULES.H // // Licensing: // // This code is distributed under the GNU LGPL license. // // Modified: // // 02 April 2010 // // Author: // // John Burkardt // // Parameters: // // Input, int DIM, the spatial dimension. // // Input, int OFFSET, the offset of the parameter within the // spatial dimension. // // Output, double PARAMETER, the value of the OFFSET-th parameter // associated with the DIM-th dimension. // { int i; int j; double value; j = 0; for ( i = 0; i < dim; i++ ) { j = j + NP[i]; } value = P[j+offset]; return value; } } //****************************************************************************80 void sandia_sgmga_size_tests ( ) //****************************************************************************80 // // Purpose: // // SANDIA_SGMGA_SIZE_TESTS calls SANDIA_SGMGA_SIZE_TEST. // // Licensing: // // This code is distributed under the GNU LGPL license. // // Modified: // // 15 January 2012 // // Author: // // John Burkardt // // Local Parameters: // // Local, double TOL, a tolerance for point equality. // A value of sqrt ( eps ) is reasonable, and will allow the code to // consolidate points which are equal, or very nearly so. A value of // -1.0, on the other hand, will force the code to use every point, // regardless of duplication. // { int dim; int dim_num; int growth; GWPointer2 *gw_compute_order; GWPointer *gw_compute_points; double *importance; int level_max_max; int level_max_min; double *level_weight; int np_sum; int *order_1d; int order_nd; double tol; std::cout << "\n"; std::cout << "SANDIA_SGMGA_SIZE_TESTS\n"; std::cout << " Call SANDIA_SGMGA_SIZE_TEST with various arguments.\n"; // // Set the point equality tolerance. // tol = std::sqrt ( webbur::r8_epsilon ( ) ); std::cout << "\n"; std::cout << " Point equality tolerance = " << tol << "\n"; dim_num = 2; importance = new double[dim_num]; for ( dim = 0; dim < dim_num; dim++ ) { importance[dim] = 1.0; } level_weight = new double[dim_num]; webbur::sandia_sgmga_importance_to_aniso ( dim_num, importance, level_weight ); level_max_min = 0; level_max_max = 5; growth = 2; NP = new int[dim_num]; NP[0] = 0; NP[1] = 0; np_sum = webbur::i4vec_sum ( dim_num, NP ); P = new double[np_sum]; gw_compute_points = new GWPointer[dim_num]; gw_compute_points[0] = webbur::clenshaw_curtis_points; gw_compute_points[1] = webbur::clenshaw_curtis_points; gw_compute_order = new GWPointer2[dim_num]; gw_compute_order[0] = webbur::level_to_order_exp_cc; gw_compute_order[1] = webbur::level_to_order_exp_cc; sandia_sgmga_size_test ( dim_num, importance, level_weight, level_max_min, level_max_max, growth, gw_compute_points, tol, gw_compute_order ); delete [] gw_compute_order; delete [] gw_compute_points; delete [] importance; delete [] level_weight; delete [] NP; delete [] P; dim_num = 2; importance = new double[dim_num]; for ( dim = 0; dim < dim_num; dim++ ) { importance[dim] = ( double ) ( dim + 1 ); } level_weight = new double[dim_num]; webbur::sandia_sgmga_importance_to_aniso ( dim_num, importance, level_weight ); level_max_min = 0; level_max_max = 5; growth = 2; NP = new int[dim_num]; NP[0] = 0; NP[1] = 0; np_sum = webbur::i4vec_sum ( dim_num, NP ); P = new double[np_sum]; gw_compute_points = new GWPointer[dim_num]; gw_compute_points[0] = webbur::clenshaw_curtis_points; gw_compute_points[1] = webbur::clenshaw_curtis_points; gw_compute_order = new GWPointer2[dim_num]; gw_compute_order[0] = webbur::level_to_order_exp_cc; gw_compute_order[1] = webbur::level_to_order_exp_cc; sandia_sgmga_size_test ( dim_num, importance, level_weight, level_max_min, level_max_max, growth, gw_compute_points, tol, gw_compute_order ); delete [] gw_compute_order; delete [] gw_compute_points; delete [] importance; delete [] level_weight; delete [] NP; delete [] P; dim_num = 3; importance = new double[dim_num]; for ( dim = 0; dim < dim_num; dim++ ) { importance[dim] = 1.0; } level_weight = new double[dim_num]; webbur::sandia_sgmga_importance_to_aniso ( dim_num, importance, level_weight ); level_max_min = 0; level_max_max = 5; growth = 2; NP = new int[dim_num]; NP[0] = 0; NP[1] = 0; NP[2] = 0; np_sum = webbur::i4vec_sum ( dim_num, NP ); P = new double[np_sum]; gw_compute_points = new GWPointer[dim_num]; gw_compute_points[0] = webbur::clenshaw_curtis_points; gw_compute_points[1] = webbur::clenshaw_curtis_points; gw_compute_points[2] = webbur::clenshaw_curtis_points; gw_compute_order = new GWPointer2[dim_num]; gw_compute_order[0] = webbur::level_to_order_exp_cc; gw_compute_order[1] = webbur::level_to_order_exp_cc; gw_compute_order[2] = webbur::level_to_order_exp_cc; sandia_sgmga_size_test ( dim_num, importance, level_weight, level_max_min, level_max_max, growth, gw_compute_points, tol, gw_compute_order ); delete [] gw_compute_order; delete [] gw_compute_points; delete [] importance; delete [] level_weight; delete [] NP; delete [] P; dim_num = 3; importance = new double[dim_num]; for ( dim = 0; dim < dim_num; dim++ ) { importance[dim] = ( double ) ( dim + 1 ); } level_weight = new double[dim_num]; webbur::sandia_sgmga_importance_to_aniso ( dim_num, importance, level_weight ); level_max_min = 0; level_max_max = 5; growth = 2; NP = new int[dim_num]; NP[0] = 0; NP[1] = 0; NP[2] = 0; np_sum = webbur::i4vec_sum ( dim_num, NP ); P = new double[np_sum]; gw_compute_points = new GWPointer[dim_num]; gw_compute_points[0] = webbur::clenshaw_curtis_points; gw_compute_points[1] = webbur::clenshaw_curtis_points; gw_compute_points[2] = webbur::clenshaw_curtis_points; gw_compute_order = new GWPointer2[dim_num]; gw_compute_order[0] = webbur::level_to_order_exp_cc; gw_compute_order[1] = webbur::level_to_order_exp_cc; gw_compute_order[2] = webbur::level_to_order_exp_cc; sandia_sgmga_size_test ( dim_num, importance, level_weight, level_max_min, level_max_max, growth, gw_compute_points, tol, gw_compute_order ); delete [] gw_compute_order; delete [] gw_compute_points; delete [] importance; delete [] level_weight; delete [] NP; delete [] P; dim_num = 2; importance = new double[dim_num]; for ( dim = 0; dim < dim_num; dim++ ) { importance[dim] = ( double ) ( dim + 1 ); } level_weight = new double[dim_num]; webbur::sandia_sgmga_importance_to_aniso ( dim_num, importance, level_weight ); level_max_min = 0; level_max_max = 2; growth = 2; NP = new int[dim_num]; NP[0] = 0; NP[1] = 0; np_sum = webbur::i4vec_sum ( dim_num, NP ); P = new double[np_sum]; gw_compute_points = new GWPointer[dim_num]; gw_compute_points[0] = webbur::clenshaw_curtis_points; gw_compute_points[1] = webbur::patterson_points; gw_compute_order = new GWPointer2[dim_num]; gw_compute_order[0] = webbur::level_to_order_exp_cc; gw_compute_order[1] = webbur::level_to_order_exp_gp; sandia_sgmga_size_test ( dim_num, importance, level_weight, level_max_min, level_max_max, growth, gw_compute_points, tol, gw_compute_order ); delete [] gw_compute_order; delete [] gw_compute_points; delete [] importance; delete [] level_weight; delete [] NP; delete [] P; dim_num = 2; importance = new double[dim_num]; for ( dim = 0; dim < dim_num; dim++ ) { importance[dim] = ( double ) ( dim + 1 ); } level_weight = new double[dim_num]; webbur::sandia_sgmga_importance_to_aniso ( dim_num, importance, level_weight ); level_max_min = 0; level_max_max = 2; growth = 1; NP = new int[dim_num]; NP[0] = 0; NP[1] = 0; np_sum = webbur::i4vec_sum ( dim_num, NP ); P = new double[np_sum]; gw_compute_points = new GWPointer[dim_num]; gw_compute_points[0] = webbur::clenshaw_curtis_points; gw_compute_points[1] = webbur::legendre_points; gw_compute_order = new GWPointer2[dim_num]; gw_compute_order[0] = webbur::level_to_order_exp_cc; gw_compute_order[1] = webbur::level_to_order_linear_wn; sandia_sgmga_size_test ( dim_num, importance, level_weight, level_max_min, level_max_max, growth, gw_compute_points, tol, gw_compute_order ); delete [] gw_compute_order; delete [] gw_compute_points; delete [] importance; delete [] level_weight; delete [] NP; delete [] P; dim_num = 2; importance = new double[dim_num]; for ( dim = 0; dim < dim_num; dim++ ) { importance[dim] = ( double ) ( dim + 1 ); } level_weight = new double[dim_num]; webbur::sandia_sgmga_importance_to_aniso ( dim_num, importance, level_weight ); level_max_min = 0; level_max_max = 2; growth = 1; NP = new int[dim_num]; NP[0] = 0; NP[1] = 0; np_sum = webbur::i4vec_sum ( dim_num, NP ); P = new double[np_sum]; gw_compute_points = new GWPointer[dim_num]; gw_compute_points[0] = webbur::clenshaw_curtis_points; gw_compute_points[1] = webbur::laguerre_points; gw_compute_order = new GWPointer2[dim_num]; gw_compute_order[0] = webbur::level_to_order_exp_cc; gw_compute_order[1] = webbur::level_to_order_linear_nn; sandia_sgmga_size_test ( dim_num, importance, level_weight, level_max_min, level_max_max, growth, gw_compute_points, tol, gw_compute_order ); delete [] gw_compute_order; delete [] gw_compute_points; delete [] importance; delete [] level_weight; delete [] NP; delete [] P; dim_num = 2; importance = new double[dim_num]; for ( dim = 0; dim < dim_num; dim++ ) { importance[dim] = ( double ) ( dim + 1 ); } level_weight = new double[dim_num]; webbur::sandia_sgmga_importance_to_aniso ( dim_num, importance, level_weight ); level_max_min = 0; level_max_max = 2; growth = 1; NP = new int[dim_num]; NP[0] = 0; NP[1] = 1; np_sum = webbur::i4vec_sum ( dim_num, NP ); P = new double[np_sum]; P[0] = 1.5; gw_compute_points = new GWPointer[dim_num]; gw_compute_points[0] = webbur::clenshaw_curtis_points; gw_compute_points[1] = webbur::gen_laguerre_points; gw_compute_order = new GWPointer2[dim_num]; gw_compute_order[0] = webbur::level_to_order_exp_cc; gw_compute_order[1] = webbur::level_to_order_linear_nn; sandia_sgmga_size_test ( dim_num, importance, level_weight, level_max_min, level_max_max, growth, gw_compute_points, tol, gw_compute_order ); delete [] gw_compute_order; delete [] gw_compute_points; delete [] importance; delete [] level_weight; delete [] NP; delete [] P; dim_num = 2; importance = new double[dim_num]; for ( dim = 0; dim < dim_num; dim++ ) { importance[dim] = ( double ) ( dim + 1 ); } level_weight = new double[dim_num]; webbur::sandia_sgmga_importance_to_aniso ( dim_num, importance, level_weight ); level_max_min = 0; level_max_max = 2; growth = 1; NP = new int[dim_num]; NP[0] = 0; NP[1] = 2; np_sum = webbur::i4vec_sum ( dim_num, NP ); P = new double[np_sum]; P[0] = 0.5; P[1] = 1.5; gw_compute_points = new GWPointer[dim_num]; gw_compute_points[0] = webbur::fejer2_points; gw_compute_points[1] = webbur::jacobi_points; gw_compute_order = new GWPointer2[dim_num]; gw_compute_order[0] = webbur::level_to_order_exp_f2; gw_compute_order[1] = webbur::level_to_order_linear_nn; sandia_sgmga_size_test ( dim_num, importance, level_weight, level_max_min, level_max_max, growth, gw_compute_points, tol, gw_compute_order ); delete [] gw_compute_order; delete [] gw_compute_points; delete [] importance; delete [] level_weight; delete [] NP; delete [] P; // // GEN HERMITE x HERMITE GENZ-KEISTER // dim_num = 2; importance = new double[dim_num]; for ( dim = 0; dim < dim_num; dim++ ) { importance[dim] = ( double ) ( dim + 1 ); } level_weight = new double[dim_num]; webbur::sandia_sgmga_importance_to_aniso ( dim_num, importance, level_weight ); level_max_min = 0; level_max_max = 2; growth = 1; NP = new int[dim_num]; NP[0] = 1; NP[1] = 0; np_sum = webbur::i4vec_sum ( dim_num, NP ); P = new double[np_sum]; P[0] = 2.0; gw_compute_points = new GWPointer[dim_num]; gw_compute_points[0] = webbur::gen_hermite_points; gw_compute_points[1] = webbur::hermite_genz_keister_points; gw_compute_order = new GWPointer2[dim_num]; gw_compute_order[0] = webbur::level_to_order_linear_wn; gw_compute_order[1] = webbur::level_to_order_exp_hgk; sandia_sgmga_size_test ( dim_num, importance, level_weight, level_max_min, level_max_max, growth, gw_compute_points, tol, gw_compute_order ); delete [] gw_compute_order; delete [] gw_compute_points; delete [] importance; delete [] level_weight; delete [] NP; delete [] P; dim_num = 3; importance = new double[dim_num]; for ( dim = 0; dim < dim_num; dim++ ) { importance[dim] = ( double ) ( dim + 1 ); } level_weight = new double[dim_num]; webbur::sandia_sgmga_importance_to_aniso ( dim_num, importance, level_weight ); level_max_min = 0; level_max_max = 2; growth = 1; NP = new int[dim_num]; NP[0] = 0; NP[1] = 0; NP[2] = 0; np_sum = webbur::i4vec_sum ( dim_num, NP ); P = new double[np_sum]; gw_compute_points = new GWPointer[dim_num]; gw_compute_points[0] = webbur::clenshaw_curtis_points; gw_compute_points[1] = webbur::legendre_points; gw_compute_points[2] = webbur::hermite_points; gw_compute_order = new GWPointer2[dim_num]; gw_compute_order[0] = webbur::level_to_order_exp_cc; gw_compute_order[1] = webbur::level_to_order_linear_wn; gw_compute_order[2] = webbur::level_to_order_linear_wn; sandia_sgmga_size_test ( dim_num, importance, level_weight, level_max_min, level_max_max, growth, gw_compute_points, tol, gw_compute_order ); delete [] gw_compute_order; delete [] gw_compute_points; delete [] importance; delete [] level_weight; delete [] NP; delete [] P; // // Try a case involving a dimension of "0" importance. // dim_num = 3; importance = new double[dim_num]; importance[0] = 1.0; importance[1] = 0.0; importance[2] = 1.0; level_weight = new double[dim_num]; webbur::sandia_sgmga_importance_to_aniso ( dim_num, importance, level_weight ); level_max_min = 0; level_max_max = 3; growth = 2; NP = new int[dim_num]; NP[0] = 0; NP[1] = 0; NP[2] = 0; np_sum = webbur::i4vec_sum ( dim_num, NP ); P = new double[np_sum]; gw_compute_points = new GWPointer[dim_num]; gw_compute_points[0] = webbur::clenshaw_curtis_points; gw_compute_points[1] = webbur::clenshaw_curtis_points; gw_compute_points[2] = webbur::clenshaw_curtis_points; gw_compute_order = new GWPointer2[dim_num]; gw_compute_order[0] = webbur::level_to_order_exp_cc; gw_compute_order[1] = webbur::level_to_order_exp_cc; gw_compute_order[2] = webbur::level_to_order_exp_cc; sandia_sgmga_size_test ( dim_num, importance, level_weight, level_max_min, level_max_max, growth, gw_compute_points, tol, gw_compute_order ); delete [] gw_compute_order; delete [] gw_compute_points; delete [] importance; delete [] level_weight; delete [] NP; delete [] P; return; } //***************************************************************************80 void sandia_sgmga_size_test ( int dim_num, double importance[], double level_weight[], int level_max_min, int level_max_max, int growth, void ( *gw_compute_points[] ) ( int order, int dim, double w[] ), double tol, int ( *gw_compute_order[] ) ( int level, int growth ) ) //***************************************************************************80 // // Purpose: // // SANDIA_SGMGA_SIZE_TEST tests SGMG_SIZE, SGMG_SIZE_TOTAL. // // Licensing: // // This code is distributed under the GNU LGPL license. // // Modified: // // 15 January 2012 // // Author: // // John Burkardt // // Parameters: // // Input, int DIM_NUM, the spatial dimension. // // Input, double IMPORTANCE[DIM_NUM], the importance for each dimension. // // Input, double LEVEL_WEIGHT[DIM_NUM], the weights for each dimension. // // Input, int LEVEL_MAX_MIN, LEVEL_MAX_MAX, the minimum and // maximum values of LEVEL_MAX. // // Input, int GROWTH, the growth rule. // 0, slow; // 1, moderate; // 2, full. // // Input, void ( *GW_COMPUTE_POINTS[] ) ( int order, int dim, double x[] ), // an array of pointers to functions which return the 1D quadrature points // associated with each spatial dimension for which a Golub Welsch rule // is used. // // Input, double TOL, a tolerance for point equality. // // Input, int ( *GW_COMPUTE_ORDER[] ) ( int level, int growth ), // an array of pointers to functions which return the order of the // 1D quadrature rule of a given level and growth rule. // { int dim; int level_max; int p_index; int point_num; int point_total_num; std::cout << "\n"; std::cout << "SANDIA_SGMGA_SIZE_TEST\n"; std::cout << " SANDIA_SGMGA_SIZE_TOTAL counts the total number of points,\n"; std::cout << " including duplications, in an SANDIA_SGMGA sparse grid.\n"; std::cout << " SANDIA_SGMGA_SIZE counts the total number of points,\n"; std::cout << " excluding duplications, in an SANDIA_SGMGA sparse grid.\n"; std::cout << "\n"; std::cout << " IMPORTANCE: "; for ( dim = 0; dim < dim_num; dim++ ) { std::cout << " " << std::setw(14) << importance[dim]; } std::cout << "\n"; std::cout << " LEVEL_WEIGHT:"; for ( dim = 0; dim < dim_num; dim++ ) { std::cout << " " << std::setw(14) << level_weight[dim]; } std::cout << "\n"; std::cout << " DIM_NUM LEVEL_MAX POINT_NUM POINT_NUM\n"; std::cout << " Unique Total\n"; std::cout << "\n"; for ( level_max = level_max_min; level_max <= level_max_max; level_max++ ) { point_total_num = webbur::sandia_sgmga_size_total ( dim_num, level_weight, level_max, growth, gw_compute_order ); point_num = webbur::sandia_sgmga_size ( dim_num, level_weight, level_max, gw_compute_points, tol, growth, gw_compute_order ); std::cout << " " << std::setw(8) << dim_num << " " << std::setw(8) << level_max << " " << std::setw(8) << point_num << " " << std::setw(8) << point_total_num << "\n"; } return; }