# include "sandia_rules.hpp"
# include "sgmg.hpp"

# include <cstdlib>
# include <iomanip>
# include <iostream>
# include <cmath>

int main ( );

void sgmg_cc_sl_tests ( );
void sgmg_create_rule ( int dim_num, int level_max, 
  int rule[], int growth[], int np[], double p[], 
  void ( *gw_compute_points[] ) ( int order, int np, double p[], double w[] ),
  void ( *gw_compute_weights[] ) ( int order, int np, double p[], double w[] ),
  double tol, std::string file_name );

typedef void ( *GWPointer ) ( int order, int np, double p[], double w[] );

//****************************************************************************80

int main ( )

//****************************************************************************80
//
//  Purpose:
//
//    SGMG_CC_SL tests SGMG with Clenshaw-Curtis rules with slow linear growth.
//
//  Licensing:
//
//    This code is distributed under the MIT license.
//
//  Modified:
//
//    02 July 2013
//
//  Author:
//
//    John Burkardt
//
//  Reference:
//
//    Fabio Nobile, Raul Tempone, Clayton Webster,
//    A Sparse Grid Stochastic Collocation Method for Partial Differential
//    Equations with Random Input Data,
//    SIAM Journal on Numerical Analysis,
//    Volume 46, Number 5, 2008, pages 2309-2345.
//
{
  webbur::timestamp ( );
  std::cout << "\n";
  std::cout << "SGMG_CC_SL():\n";
  std::cout << "  C++ version\n";
//
//  Generate sparse grid rules and write them to files.
//
  sgmg_cc_sl_tests ( );
//
//  Terminate.
//
  std::cout << "\n";
  std::cout << "SGMG_CC_SL():\n";
  std::cout << "  Normal end of execution.\n";

  std::cout << "\n";
  webbur::timestamp ( );
  
  return 0;
}
//****************************************************************************80

void sgmg_cc_sl_tests ( )

//****************************************************************************80
//
//  Purpose:
//
//    SGMG_CC_SL_TESTS calls SGMG_CC_SL_TEST.
//
//  Licensing:
//
//    This code is distributed under the MIT license.
//
//  Modified:
//
//    02 July 2013
//
//  Author:
//
//    John Burkardt
//
{
  int dim_num;
  std::string file_name;
  int *growth;
  GWPointer *gw_compute_points;
  GWPointer *gw_compute_weights;
  int level_max;
  int *np;
  int np_sum;
  double *p;
  int *rule;
  double tol;

  std::cout << "\n";
  std::cout << "SGMG_WRITE_TESTS\n";
  std::cout << "  Call SGMG_WRITE_TEST with various arguments.\n";

  dim_num = 2;

  level_max= 2;

  rule = new int[dim_num];
  rule[0] = 1;
  rule[1] = 1;

  growth = new int[dim_num];
  growth[0] = 1;
  growth[1] = 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_compute_points_np;
  gw_compute_points[1] = webbur::clenshaw_curtis_compute_points_np;

  gw_compute_weights = new GWPointer[dim_num];
  gw_compute_weights[0] = webbur::clenshaw_curtis_compute_weights_np;
  gw_compute_weights[1] = webbur::clenshaw_curtis_compute_weights_np;

  tol = 0.0000001;

  file_name = "sgmg_cc_sl";

  sgmg_create_rule ( dim_num, level_max, rule, growth, np, 
    p, gw_compute_points, gw_compute_weights, tol, file_name );

  delete [] growth;
  delete [] gw_compute_points;
  delete [] gw_compute_weights;
  delete [] np;
  delete [] p;
  delete [] rule;

  return;
}
//***************************************************************************80

void sgmg_create_rule ( int dim_num, int level_max, 
  int rule[], int growth[], int np[], double p[], 
  void ( *gw_compute_points[] ) ( int order, int np, double p[], double w[] ),
  void ( *gw_compute_weights[] ) ( int order, int np, double p[], double w[] ),
  double tol, std::string file_name )

//***************************************************************************80
//
//  Purpose:
//
//    SGMG_CREATE_RULE creates the requested rule and writes it to a file.
//
//  Licensing:
//
//    This code is distributed under the MIT license.
//
//  Modified:
//
//    02 July 2013
//
//  Author:
//
//    John Burkardt
//
//  Parameters:
//
//    Input, integer DIM_NUM, the spatial dimension.
//
//    Input, integer LEVEL_MAX, the level that defines the grid.
//
//    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 growth rule 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, void ( *GW_COMPUTE_WEIGHTS[] ) ( int order, int np, double p[], double w[] ),
//    an array of pointers to functions which return the 1D quadrature weights 
//    associated with each spatial dimension for which a Golub Welsch rule 
//    is used.
//
//    Input, double TOL, a tolerance for point equality.
//
//    Input, string FILE_NAME, the main name of the output files.
//
{
  int point_num;
  int point_total_num;
  int *sparse_index;
  int *sparse_order;
  double *sparse_point;
  int *sparse_unique_index;
  double *sparse_weight;

  std::cout << "\n";
  std::cout << "SGMG_CREATE_RULE\n";
  std::cout << "  Create the requested sparse grid rule, and write it\n";
  std::cout << "  to X, W and R files.\n";
//
//  Compute necessary data.
//
  point_total_num = webbur::sgmg_size_total ( dim_num, 
    level_max, rule, growth );

  point_num = webbur::sgmg_size ( dim_num, level_max, 
    rule, np, p, gw_compute_points, tol, growth );

  sparse_unique_index = new int[point_total_num];

  webbur::sgmg_unique_index ( dim_num, level_max, rule, 
    np, p, gw_compute_points, tol, point_num, point_total_num, 
    growth, sparse_unique_index );

  sparse_order = new int[dim_num*point_num];
  sparse_index = new int[dim_num*point_num];

  webbur::sgmg_index ( dim_num, level_max, rule, point_num, 
    point_total_num, sparse_unique_index, growth, sparse_order, sparse_index );
//
//  Compute points and weights.
//
  sparse_point = new double [ dim_num * point_num ];

  webbur::sgmg_point ( dim_num, level_max, rule, np, 
    p, gw_compute_points, point_num, sparse_order, sparse_index, 
    growth, sparse_point );

  sparse_weight = new double[point_num];

  webbur::sgmg_weight ( dim_num, level_max, rule, np, 
    p, gw_compute_weights, point_num, point_total_num, sparse_unique_index, 
    growth, sparse_weight );
//
//  Write points and weights to files.
//
  webbur::sgmg_write ( dim_num, rule, np, p, 
    point_num, sparse_weight, sparse_point, file_name );

  delete [] sparse_index;
  delete [] sparse_order;
  delete [] sparse_point;
  delete [] sparse_unique_index;
  delete [] sparse_weight;

  return;
}