# include "sandia_rules.hpp" # include "sgmga.hpp" # include # include # include # include int main ( ); void sgmga_size_tests ( ); void sgmga_size_test ( int dim_num, double importance[], double level_weight[], int level_max_min, int level_max_max, int rule[], int growth[], int np[], double p[], void ( *gw_compute_points[] ) ( int order, int np, double p[], double w[] ), double tol ); typedef void ( *GWPointer ) ( int order, int np, double p[], double w[] ); //****************************************************************************80 int main ( ) //****************************************************************************80 // // Purpose: // // MAIN is the main program for SGMGA_SIZE_PRB. // // Discussion: // // SGMGA_SIZE_PRB tests the SGMGA_SIZE and SGMGA_SIZE_TOTAL functions. // // Licensing: // // This code is distributed under the MIT license. // // Modified: // // 27 November 2009 // // Author: // // John Burkardt // { webbur::timestamp ( ); std::cout << "\n"; std::cout << "SGMGA_SIZE_PRB\n"; std::cout << " C++ version\n"; std::cout << " Test the SGMGA_SIZE and SGMGA_SIZE_TOTAL functions.\n"; sgmga_size_tests ( ); std::cout << "\n"; std::cout << "SGMGA__SIZE_PRB\n"; std::cout << " Normal end of execution.\n"; std::cout << "\n"; webbur::timestamp ( ); return 0; } //****************************************************************************80 void sgmga_size_tests ( ) //****************************************************************************80 // // Purpose: // // SGMGA_SIZE_TESTS calls SGMGA_SIZE_TEST. // // Licensing: // // This code is distributed under the MIT license. // // Modified: // // 20 June 2010 // // 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; GWPointer *gw_compute_points; double *importance; int level_max_max; int level_max_min; double *level_weight; int *np; int np_sum; int *order_1d; int order_nd; double *p; int *rule; double tol; std::cout << "\n"; std::cout << "SGMGA_SIZE_TESTS\n"; std::cout << " Call 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::sgmga_importance_to_aniso ( dim_num, importance, level_weight ); level_max_min = 0; level_max_max = 5; rule = new int[dim_num]; rule[0] = 1; rule[1] = 1; growth = new int[dim_num]; growth[0] = 6; growth[1] = 6; 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_compute_points_np; gw_compute_points[1] = webbur::clenshaw_curtis_compute_points_np; sgmga_size_test ( dim_num, importance, level_weight, level_max_min, level_max_max, rule, growth, np, p, gw_compute_points, tol ); delete [] growth; delete [] gw_compute_points; delete [] importance; delete [] level_weight; delete [] np; delete [] p; delete [] rule; 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::sgmga_importance_to_aniso ( dim_num, importance, level_weight ); level_max_min = 0; level_max_max = 5; rule = new int[dim_num]; rule[0] = 1; rule[1] = 1; growth = new int[dim_num]; growth[0] = 6; growth[1] = 6; 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_compute_points_np; gw_compute_points[1] = webbur::clenshaw_curtis_compute_points_np; sgmga_size_test ( dim_num, importance, level_weight, level_max_min, level_max_max, rule, growth, np, p, gw_compute_points, tol ); delete [] growth; delete [] gw_compute_points; delete [] importance; delete [] level_weight; delete [] np; delete [] p; delete [] rule; 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::sgmga_importance_to_aniso ( dim_num, importance, level_weight ); level_max_min = 0; level_max_max = 5; rule = new int[dim_num]; rule[0] = 1; rule[1] = 1; rule[2] = 1; growth = new int[dim_num]; growth[0] = 6; growth[1] = 6; growth[2] = 6; 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_compute_points_np; gw_compute_points[1] = webbur::clenshaw_curtis_compute_points_np; sgmga_size_test ( dim_num, importance, level_weight, level_max_min, level_max_max, rule, growth, np, p, gw_compute_points, tol ); delete [] growth; delete [] gw_compute_points; delete [] importance; delete [] level_weight; delete [] np; delete [] p; delete [] rule; 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::sgmga_importance_to_aniso ( dim_num, importance, level_weight ); level_max_min = 0; level_max_max = 5; rule = new int[dim_num]; rule[0] = 1; rule[1] = 1; rule[2] = 1; growth = new int[dim_num]; growth[0] = 6; growth[1] = 6; growth[2] = 6; 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_compute_points_np; gw_compute_points[1] = webbur::clenshaw_curtis_compute_points_np; sgmga_size_test ( dim_num, importance, level_weight, level_max_min, level_max_max, rule, growth, np, p, gw_compute_points, tol ); delete [] growth; delete [] gw_compute_points; delete [] importance; delete [] level_weight; delete [] np; delete [] p; delete [] rule; 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::sgmga_importance_to_aniso ( dim_num, importance, level_weight ); level_max_min = 0; level_max_max = 2; rule = new int[dim_num]; rule[0] = 1; rule[1] = 3; growth = new int[dim_num]; growth[0] = 6; growth[1] = 6; 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_compute_points_np; gw_compute_points[1] = webbur::patterson_lookup_points_np; sgmga_size_test ( dim_num, importance, level_weight, level_max_min, level_max_max, rule, growth, np, p, gw_compute_points, tol ); delete [] growth; delete [] gw_compute_points; delete [] importance; delete [] level_weight; delete [] np; delete [] p; delete [] rule; 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::sgmga_importance_to_aniso ( dim_num, importance, level_weight ); level_max_min = 0; level_max_max = 2; rule = new int[dim_num]; rule[0] = 1; rule[1] = 4; growth = new int[dim_num]; growth[0] = 6; growth[1] = 3; 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_compute_points_np; gw_compute_points[1] = webbur::legendre_compute_points_np; sgmga_size_test ( dim_num, importance, level_weight, level_max_min, level_max_max, rule, growth, np, p, gw_compute_points, tol ); delete [] growth; delete [] gw_compute_points; delete [] importance; delete [] level_weight; delete [] np; delete [] p; delete [] rule; 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::sgmga_importance_to_aniso ( dim_num, importance, level_weight ); level_max_min = 0; level_max_max = 2; rule = new int[dim_num]; rule[0] = 1; rule[1] = 7; growth = new int[dim_num]; growth[0] = 6; growth[1] = 3; 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_compute_points_np; gw_compute_points[1] = webbur::laguerre_compute_points_np; sgmga_size_test ( dim_num, importance, level_weight, level_max_min, level_max_max, rule, growth, np, p, gw_compute_points, tol ); delete [] growth; delete [] gw_compute_points; delete [] importance; delete [] level_weight; delete [] np; delete [] p; delete [] rule; 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::sgmga_importance_to_aniso ( dim_num, importance, level_weight ); level_max_min = 0; level_max_max = 2; rule = new int[dim_num]; rule[0] = 1; rule[1] = 8; growth = new int[dim_num]; growth[0] = 6; growth[1] = 3; 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_compute_points_np; gw_compute_points[1] = webbur::gen_laguerre_compute_points_np; sgmga_size_test ( dim_num, importance, level_weight, level_max_min, level_max_max, rule, growth, np, p, gw_compute_points, tol ); delete [] growth; delete [] gw_compute_points; delete [] importance; delete [] level_weight; delete [] np; delete [] p; delete [] rule; 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::sgmga_importance_to_aniso ( dim_num, importance, level_weight ); level_max_min = 0; level_max_max = 2; rule = new int[dim_num]; rule[0] = 2; rule[1] = 9; growth = new int[dim_num]; growth[0] = 6; growth[1] = 3; 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_compute_points_np; gw_compute_points[1] = webbur::jacobi_compute_points_np; sgmga_size_test ( dim_num, importance, level_weight, level_max_min, level_max_max, rule, growth, np, p, gw_compute_points, tol ); delete [] growth; delete [] gw_compute_points; delete [] importance; delete [] level_weight; delete [] np; delete [] p; delete [] rule; 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::sgmga_importance_to_aniso ( dim_num, importance, level_weight ); level_max_min = 0; level_max_max = 2; rule = new int[dim_num]; rule[0] = 6; rule[1] = 10; growth = new int[dim_num]; growth[0] = 3; growth[1] = 4; 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_compute_points_np; gw_compute_points[1] = webbur::legendre_compute_points_np; sgmga_size_test ( dim_num, importance, level_weight, level_max_min, level_max_max, rule, growth, np, p, gw_compute_points, tol ); delete [] growth; delete [] gw_compute_points; delete [] importance; delete [] level_weight; delete [] np; delete [] p; delete [] rule; 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::sgmga_importance_to_aniso ( dim_num, importance, level_weight ); level_max_min = 0; level_max_max = 2; rule = new int[dim_num]; rule[0] = 1; rule[1] = 4; rule[2] = 5; growth = new int[dim_num]; growth[0] = 6; growth[1] = 3; growth[2] = 3; 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_compute_points_np; gw_compute_points[1] = webbur::legendre_compute_points_np; gw_compute_points[2] = webbur::hermite_compute_points_np; sgmga_size_test ( dim_num, importance, level_weight, level_max_min, level_max_max, rule, growth, np, p, gw_compute_points, tol ); delete [] growth; delete [] gw_compute_points; delete [] importance; delete [] level_weight; delete [] np; delete [] p; delete [] rule; // // Repeat, treating rules #2 and #3 as Golub Welsch rules. // 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::sgmga_importance_to_aniso ( dim_num, importance, level_weight ); level_max_min = 0; level_max_max = 2; rule = new int[dim_num]; rule[0] = 1; rule[1] = 11; rule[2] = 11; growth = new int[dim_num]; growth[0] = 6; growth[1] = 3; growth[2] = 3; 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_compute_points_np; gw_compute_points[1] = webbur::legendre_compute_points_np; gw_compute_points[2] = webbur::hermite_compute_points_np; sgmga_size_test ( dim_num, importance, level_weight, level_max_min, level_max_max, rule, growth, np, p, gw_compute_points, tol ); delete [] growth; delete [] gw_compute_points; delete [] importance; delete [] level_weight; delete [] np; delete [] p; delete [] rule; // // 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::sgmga_importance_to_aniso ( dim_num, importance, level_weight ); level_max_min = 0; level_max_max = 3; rule = new int[dim_num]; rule[0] = 1; rule[1] = 1; rule[2] = 1; growth = new int[dim_num]; growth[0] = 6; growth[1] = 6; growth[2] = 6; 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_compute_points_np; gw_compute_points[1] = webbur::clenshaw_curtis_compute_points_np; gw_compute_points[2] = webbur::clenshaw_curtis_compute_points_np; sgmga_size_test ( dim_num, importance, level_weight, level_max_min, level_max_max, rule, growth, np, p, gw_compute_points, tol ); delete [] growth; delete [] gw_compute_points; delete [] importance; delete [] level_weight; delete [] np; delete [] p; delete [] rule; return; } //***************************************************************************80 void sgmga_size_test ( int dim_num, double importance[], double level_weight[], int level_max_min, int level_max_max, int rule[], int growth[], int np[], double p[], void ( *gw_compute_points[] ) ( int order, int np, double p[], double w[] ), double tol ) //***************************************************************************80 // // Purpose: // // SGMGA_SIZE_TEST tests SGMG_SIZE, SGMG_SIZE_TOTAL. // // Discussion: // // The "level_to_order" argument for the SGMG_SIZE and SGMG_SIZE_TOTAL // functions is set to "LEVEL_TO_ORDER_DEFAULT", which uses exponential // growth for fully nested rules, and linear otherwise. // // Licensing: // // This code is distributed under the MIT license. // // Modified: // // 09 June 2010 // // 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 RULE[DIM_NUM], the rule in each dimension. // 1, "CC", Clenshaw Curtis, Closed Fully Nested. // 2, "F2", Fejer Type 2, Open Fully Nested. // 3, "GP", Gauss Patterson, Open Fully Nested. // 4, "GL", Gauss Legendre, Open Weakly Nested. // 5, "GH", Gauss Hermite, Open Weakly Nested. // 6, "GGH", Generalized Gauss Hermite, Open Weakly Nested. // 7, "LG", Gauss Laguerre, Open Non Nested. // 8, "GLG", Generalized Gauss Laguerre, Open Non Nested. // 9, "GJ", Gauss Jacobi, Open Non Nested. // 10, "HGK", Hermite Genz-Keister, Open Fully Nested. // 11, "UO", User supplied Open, presumably Non Nested. // 12, "UC", User supplied Closed, presumably Non Nested. // // Input, int GROWTH[DIM_NUM], the desired growth in each dimension. // 0, "DF", default growth associated with this quadrature rule; // 1, "SL", slow linear, L+1; // 2 "SO", slow linear odd, O=1+2((L+1)/2) // 3, "ML", moderate linear, 2L+1; // 4, "SE", slow exponential; // 5, "ME", moderate exponential; // 6, "FE", full exponential. // // Input, int NP[RULE_NUM], the number of parameters used by each rule. // // Input, double P[sum(NP[*])], the parameters needed by each rule. // // Input, void ( *GW_COMPUTE_POINTS[] ) ( int order, int np, double p[], 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. // { double alpha; double beta; int dim; int i; int level_max; int p_index; int point_num; int point_total_num; std::cout << "\n"; std::cout << "SGMGA_SIZE_TEST\n"; std::cout << " SGMGA_SIZE_TOTAL counts the total number of points,\n"; std::cout << " including duplications, in an SGMGA sparse grid.\n"; std::cout << " SGMGA_SIZE counts the total number of points,\n"; std::cout << " excluding duplications, in an 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 << "\n"; std::cout << " Dimension Rule Growth rate Parameters\n"; std::cout << "\n"; p_index = 0; for ( dim = 0; dim < dim_num; dim++ ) { if ( rule[dim] == 1 ) { std::cout << " " << std::setw(8) << dim << " " << std::setw(8) << rule[dim] << " " << std::setw(8) << growth[dim] << "\n"; } else if ( rule[dim] == 2 ) { std::cout << " " << std::setw(8) << dim << " " << std::setw(8) << rule[dim] << " " << std::setw(8) << growth[dim] << "\n"; } else if ( rule[dim] == 3 ) { std::cout << " " << std::setw(8) << dim << " " << std::setw(8) << rule[dim] << " " << std::setw(8) << growth[dim] << "\n"; } else if ( rule[dim] == 4 ) { std::cout << " " << std::setw(8) << dim << " " << std::setw(8) << rule[dim] << " " << std::setw(8) << growth[dim] << "\n"; } else if ( rule[dim] == 5 ) { std::cout << " " << std::setw(8) << dim << " " << std::setw(8) << rule[dim] << " " << std::setw(8) << growth[dim] << "\n"; } else if ( rule[dim] == 6 ) { alpha = p[p_index]; p_index = p_index + 1; std::cout << " " << std::setw(8) << dim << " " << std::setw(8) << rule[dim] << " " << std::setw(8) << growth[dim] << " " << std::setw(14) << alpha << "\n"; } else if ( rule[dim] == 7 ) { std::cout << " " << std::setw(8) << dim << " " << std::setw(8) << rule[dim] << " " << std::setw(8) << growth[dim] << "\n"; } else if ( rule[dim] == 8 ) { alpha = p[p_index]; p_index = p_index + 1; std::cout << " " << std::setw(8) << dim << " " << std::setw(8) << rule[dim] << " " << std::setw(8) << growth[dim] << " " << std::setw(14) << alpha << "\n"; } else if ( rule[dim] == 9 ) { alpha = p[p_index]; p_index = p_index + 1; beta = p[p_index]; p_index = p_index + 1; std::cout << " " << std::setw(8) << dim << " " << std::setw(8) << rule[dim] << " " << std::setw(8) << growth[dim] << " " << std::setw(14) << alpha << " " << std::setw(14) << beta << "\n"; } else if ( rule[dim] == 10 ) { std::cout << " " << std::setw(8) << dim << " " << std::setw(8) << rule[dim] << " " << std::setw(8) << growth[dim] << "\n"; } else if ( rule[dim] == 11 ) { std::cout << " " << std::setw(8) << dim << " " << std::setw(8) << rule[dim] << " " << std::setw(8) << growth[dim]; for ( i = 0; i < np[dim]; i++ ) { alpha = p[p_index]; p_index = p_index + 1; std::cout << " " << std::setw(14) << alpha; } std::cout << "\n"; } else if ( rule[dim] == 12 ) { std::cout << " " << std::setw(8) << dim << " " << std::setw(8) << rule[dim] << " " << std::setw(8) << growth[dim]; for ( i = 0; i < np[dim]; i++ ) { alpha = p[p_index]; p_index = p_index + 1; std::cout << " " << std::setw(14) << alpha; } std::cout << "\n"; } else { std::cerr << "\n"; std::cerr << "SGMGA_SIZE_TEST - Fatal error!\n"; std::cerr << " Unexpected value of RULE = " << rule[dim] << "\n"; std::exit ( 1 ); } } 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::sgmga_size_total ( dim_num, level_weight, level_max, rule, growth ); point_num = webbur::sgmga_size ( dim_num, level_weight, level_max, rule, np, p, gw_compute_points, tol, growth ); 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; }