# include # include # include # include # include using namespace std; # include "line_integrals.hpp" //****************************************************************************80 int *i4vec_uniform_ab_new ( int n, int a, int b, int &seed ) //****************************************************************************80 // // Purpose: // // I4VEC_UNIFORM_AB_NEW returns a scaled pseudorandom I4VEC. // // Discussion: // // An I4VEC is a vector of I4's. // // The pseudorandom numbers should be uniformly distributed // between A and B. // // Licensing: // // This code is distributed under the GNU LGPL license. // // Modified: // // 24 May 2012 // // Author: // // John Burkardt // // Reference: // // Paul Bratley, Bennett Fox, Linus Schrage, // A Guide to Simulation, // Second Edition, // Springer, 1987, // ISBN: 0387964673, // LC: QA76.9.C65.B73. // // Bennett Fox, // Algorithm 647: // Implementation and Relative Efficiency of Quasirandom // Sequence Generators, // ACM Transactions on Mathematical Software, // Volume 12, Number 4, December 1986, pages 362-376. // // Pierre L'Ecuyer, // Random Number Generation, // in Handbook of Simulation, // edited by Jerry Banks, // Wiley, 1998, // ISBN: 0471134031, // LC: T57.62.H37. // // Peter Lewis, Allen Goodman, James Miller, // A Pseudo-Random Number Generator for the System/360, // IBM Systems Journal, // Volume 8, Number 2, 1969, pages 136-143. // // Parameters: // // Input, int N, the dimension of the vector. // // Input, int A, B, the limits of the interval. // // Input/output, int &SEED, the "seed" value, which should NOT be 0. // On output, SEED has been updated. // // Output, int IVEC_UNIFORM_AB_NEW[N], a vector of random values // between A and B. // { int c; int i; const int i4_huge = 2147483647; int k; float r; int value; int *x; if ( seed == 0 ) { cerr << "\n"; cerr << "I4VEC_UNIFORM_AB_NEW - Fatal error!\n"; cerr << " Input value of SEED = 0.\n"; exit ( 1 ); } // // Guarantee A <= B. // if ( b < a ) { c = a; a = b; b = c; } x = new int[n]; for ( i = 0; i < n; i++ ) { k = seed / 127773; seed = 16807 * ( seed - k * 127773 ) - k * 2836; if ( seed < 0 ) { seed = seed + i4_huge; } r = ( float ) ( seed ) * 4.656612875E-10; // // Scale R to lie between A-0.5 and B+0.5. // r = ( 1.0 - r ) * ( ( float ) a - 0.5 ) + r * ( ( float ) b + 0.5 ); // // Use rounding to convert R to an integer between A and B. // value = round ( r ); // // Guarantee A <= VALUE <= B. // if ( value < a ) { value = a; } if ( b < value ) { value = b; } x[i] = value; } return x; } //****************************************************************************80 double line01_length ( ) //****************************************************************************80 // // Purpose: // // LINE01_LENGTH: length of the unit line in 1D. // // Licensing: // // This code is distributed under the GNU LGPL license. // // Modified: // // 17 January 2014 // // Author: // // John Burkardt // // Parameters: // // Output, double LINE01_LENGTH, the length. // { double length; length = 1.0; return length; } //****************************************************************************80 double line01_monomial_integral ( int e ) //****************************************************************************80 // // Purpose: // // LINE01_MONOMIAL_INTEGRAL returns monomial integrals on the unit line. // // Discussion: // // The integration region is // // 0 <= X <= 1. // // The monomial is F(X) = X^E. // // Licensing: // // This code is distributed under the GNU LGPL license. // // Modified: // // 17 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, the exponent. E must be nonnegative. // // Output, double LINE01_MONOMIAL_INTEGRAL, the integral. // { double integral; if ( e == -1 ) { cout << "\n"; cout << "LINE01_MONOMIAL_INTEGRAL - Fatal error!\n"; cout << " E = -1.\n"; exit ( 1 ); } integral = 1.0 / ( double ) ( e + 1 ); return integral; } //****************************************************************************80 double *line01_sample ( int n, int &seed ) //****************************************************************************80 // // Purpose: // // LINE01_SAMPLE samples the unit line in 1D. // // Licensing: // // This code is distributed under the GNU LGPL license. // // Modified: // // 17 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[N], the points. // { double *x; x = r8vec_uniform_01_new ( n, seed ); return x; } //****************************************************************************80 double *monomial_value_1d ( int n, int e, double x[] ) //****************************************************************************80 // // Purpose: // // MONOMIAL_VALUE_1D evaluates a monomial in 1D. // // 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: // // 17 January 2014 // // Author: // // John Burkardt // // Parameters: // // Input, int N, the number of points at which the // monomial is to be evaluated. // // Input, int E, the exponents. // // Input, double X[N], the point coordinates. // // Output, double MONOMIAL_VALUE_1D[N], the value of the monomial. // { int j; double *v; v = new double[n]; for ( j = 0; j < n; j++ ) { v[j] = pow ( x[j], e ); } return v; } //****************************************************************************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 *r8vec_uniform_01_new ( int n, int &seed ) //****************************************************************************80 // // Purpose: // // R8VEC_UNIFORM_01_NEW returns a new unit pseudorandom R8VEC. // // Discussion: // // This routine implements the recursion // // seed = ( 16807 * seed ) mod ( 2^31 - 1 ) // u = 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: // // 19 August 2004 // // Author: // // John Burkardt // // Reference: // // Paul Bratley, Bennett Fox, Linus Schrage, // A Guide to Simulation, // Second Edition, // Springer, 1987, // ISBN: 0387964673, // LC: QA76.9.C65.B73. // // Bennett Fox, // Algorithm 647: // Implementation and Relative Efficiency of Quasirandom // Sequence Generators, // ACM Transactions on Mathematical Software, // Volume 12, Number 4, December 1986, pages 362-376. // // Pierre L'Ecuyer, // Random Number Generation, // in Handbook of Simulation, // edited by Jerry Banks, // Wiley, 1998, // ISBN: 0471134031, // LC: T57.62.H37. // // Peter Lewis, Allen Goodman, James Miller, // A Pseudo-Random Number Generator for the System/360, // IBM Systems Journal, // Volume 8, Number 2, 1969, pages 136-143. // // Parameters: // // Input, int N, the number of entries in the vector. // // Input/output, int &SEED, a seed for the random number generator. // // Output, double R8VEC_UNIFORM_01_NEW[N], the vector of pseudorandom values. // { int i; int i4_huge = 2147483647; int k; double *r; if ( seed == 0 ) { cerr << "\n"; cerr << "R8VEC_UNIFORM_01_NEW - Fatal error!\n"; cerr << " Input value of SEED = 0.\n"; exit ( 1 ); } r = new double[n]; for ( i = 0; i < n; i++ ) { k = seed / 127773; seed = 16807 * ( seed - k * 127773 ) - k * 2836; if ( seed < 0 ) { seed = seed + i4_huge; } r[i] = ( double ) ( seed ) * 4.656612875E-10; } return r; } //****************************************************************************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 }