# include # include # include # include # include using namespace std; # include "square_monte_carlo.hpp" //****************************************************************************80 double *monomial_value ( int m, int n, int e[], double x[] ) //****************************************************************************80 // // Purpose: // // MONOMIAL_VALUE evaluates a monomial. // // Discussion: // // This routine evaluates a monomial of the form // // product ( 1 <= i <= m ) x(i)^e(i) // // where the exponents are nonnegative integers. Note that // if the combination 0^0 is encountered, it should be treated // as 1. // // Licensing: // // This code is distributed under the GNU LGPL license. // // Modified: // // 05 May 2007 // // Author: // // John Burkardt // // Parameters: // // Input, int M, the spatial dimension. // // Input, int POINT_NUM, the number of points at which the // monomial is to be evaluated. // // Input, int E[M], the exponents. // // Input, double X[M*N], the point coordinates. // // Output, double MONOMIAL_VALUE[N], the value of the monomial. // { int i; int j; double *v; v = new double[n]; for ( j = 0; j < n; j++ ) { v[j] = 1.0; } for ( i = 0; i < m; i++ ) { if ( 0 != e[i] ) { for ( j = 0; j < n; j++ ) { v[j] = v[j] * pow ( x[i+j*m], e[i] ); } } } return v; } //****************************************************************************80 double *r8mat_uniform_01_new ( int m, int n, int &seed ) //****************************************************************************80 // // Purpose: // // R8MAT_UNIFORM_01_NEW returns a unit pseudorandom R8MAT. // // Discussion: // // An R8MAT is a doubly dimensioned array of R8's, stored as a vector // in column-major order. // // This routine implements the recursion // // seed = 16807 * seed mod ( 2^31 - 1 ) // unif = seed / ( 2^31 - 1 ) // // The integer arithmetic never requires more than 32 bits, // including a sign bit. // // Licensing: // // This code is distributed under the GNU LGPL license. // // Modified: // // 03 October 2005 // // Author: // // John Burkardt // // Reference: // // Paul Bratley, Bennett Fox, Linus Schrage, // A Guide to Simulation, // Springer Verlag, pages 201-202, 1983. // // Bennett Fox, // Algorithm 647: // Implementation and Relative Efficiency of Quasirandom // Sequence Generators, // ACM Transactions on Mathematical Software, // Volume 12, Number 4, pages 362-376, 1986. // // Philip Lewis, Allen Goodman, James Miller, // A Pseudo-Random Number Generator for the System/360, // IBM Systems Journal, // Volume 8, pages 136-143, 1969. // // Parameters: // // Input, int M, N, the number of rows and columns. // // Input/output, int &SEED, the "seed" value. Normally, this // value should not be 0, otherwise the output value of SEED // will still be 0, and R8_UNIFORM will be 0. On output, SEED has // been updated. // // Output, double R8MAT_UNIFORM_01_NEW[M*N], a matrix of pseudorandom values. // { int i; int j; int k; double *r; r = new double[m*n]; for ( j = 0; j < n; j++ ) { for ( i = 0; i < m; i++ ) { k = seed / 127773; seed = 16807 * ( seed - k * 127773 ) - k * 2836; if ( seed < 0 ) { seed = seed + 2147483647; } r[i+j*m] = ( double ) ( seed ) * 4.656612875E-10; } } return r; } //****************************************************************************80 double r8vec_sum ( int n, double a[] ) //****************************************************************************80 // // Purpose: // // R8VEC_SUM returns the sum of an R8VEC. // // Discussion: // // An R8VEC is a vector of R8's. // // Licensing: // // This code is distributed under the GNU LGPL license. // // Modified: // // 15 October 2004 // // Author: // // John Burkardt // // Parameters: // // Input, int N, the number of entries in the vector. // // Input, double A[N], the vector. // // Output, double R8VEC_SUM, the sum of the vector. // { int i; double value; value = 0.0; for ( i = 0; i < n; i++ ) { value = value + a[i]; } return value; } //****************************************************************************80 double square01_area ( ) //****************************************************************************80 // // Purpose: // // SQUARE01_AREA: area of the unit square in 2D. // // Licensing: // // This code is distributed under the GNU LGPL license. // // Modified: // // 19 January 2014 // // Author: // // John Burkardt // // Parameters: // // Output, double SQUARE01_AREA, the area // { double area; area = 1.0; return area; } //****************************************************************************80 double square01_monomial_integral ( int e[] ) //****************************************************************************80 // // Purpose: // // SQUARE01_MONOMIAL_INTEGRAL: monomial integrals on the unit square in 2D. // // Discussion: // // The integration region is // // 0 <= X <= 1, // 0 <= Y <= 1. // // The monomial is F(X,Y) = X^E(1) * Y^E(2). // // Licensing: // // This code is distributed under the GNU LGPL license. // // Modified: // // 19 January 2014 // // Author: // // John Burkardt // // Reference: // // Philip Davis, Philip Rabinowitz, // Methods of Numerical Integration, // Second Edition, // Academic Press, 1984, page 263. // // Parameters: // // Input, int E[2], the exponents. // Each exponent must be nonnegative. // // Output, double SQUARE01_MONOMIAL_INTEGRAL, the integral. // { double arg; int i; double integral; const int m = 2; for ( i = 0; i < m; i++ ) { if ( e[i] < 0 ) { cout << "\n"; cout << "SQUARE01_MONOMIAL_INTEGRAL - Fatal error!\n"; cout << " All exponents must be nonnegative.\n"; cout << " E[" << i << "] = " << e[i] << "\n"; exit ( 1 ); } } integral = 1.0; for ( i = 0; i < m; i++ ) { integral = integral / ( double ) ( e[i] + 1 ); } return integral; } //****************************************************************************80 double *square01_sample ( int n, int &seed ) //****************************************************************************80 // // Purpose: // // SQUARE01_SAMPLE samples the unit square in 2D. // // Licensing: // // This code is distributed under the GNU LGPL license. // // Modified: // // 19 January 2014 // // Author: // // John Burkardt // // Reference: // // Russell Cheng, // Random Variate Generation, // in Handbook of Simulation, // edited by Jerry Banks, // Wiley, 1998, pages 168. // // Reuven Rubinstein, // Monte Carlo Optimization, Simulation, and Sensitivity // of Queueing Networks, // Krieger, 1992, // ISBN: 0894647644, // LC: QA298.R79. // // Parameters: // // Input, int N, the number of points. // // Input/output, int &SEED, a seed for the random // number generator. // // Output, double X[2*N], the points. // { const int m = 2; double *x; x = r8mat_uniform_01_new ( m, n, seed ); return x; } //****************************************************************************80 void timestamp ( ) //****************************************************************************80 // // Purpose: // // TIMESTAMP prints the current YMDHMS date as a time stamp. // // Example: // // 31 May 2001 09:45:54 AM // // Licensing: // // This code is distributed under the GNU LGPL license. // // Modified: // // 08 July 2009 // // Author: // // John Burkardt // // Parameters: // // None // { # define TIME_SIZE 40 static char time_buffer[TIME_SIZE]; const struct std::tm *tm_ptr; size_t len; std::time_t now; now = std::time ( NULL ); tm_ptr = std::localtime ( &now ); len = std::strftime ( time_buffer, TIME_SIZE, "%d %B %Y %I:%M:%S %p", tm_ptr ); std::cout << time_buffer << "\n"; return; # undef TIME_SIZE }