18. Quasi-Random Sequences

This chapter describes functions for generating quasi-random sequences in arbitrary dimensions. A quasi-random sequence progressively covers a -dimensional space with a set of points that are uniformly distributed. Quasi-random sequences are also known as low-discrepancy sequences. The quasi-random sequence generators use an interface that is similar to the interface for random number generators, except that seeding is not required—each generator produces a single sequence.

The functions described in this section are declared in the header file ‘gsl_qrng.h’.

18.1 Quasi-random number generator initialization

Function: gsl_qrng * gsl_qrng_alloc (const gsl_qrng_type * T, unsigned int d)

This function returns a pointer to a newly-created instance of a quasi-random sequence generator of type T and dimension d. If there is insufficient memory to create the generator then the function returns a null pointer and the error handler is invoked with an error code of GSL_ENOMEM.

Function: void gsl_qrng_free (gsl_qrng * q)

This function frees all the memory associated with the generator q.

Function: void gsl_qrng_init (gsl_qrng * q)

This function reinitializes the generator q to its starting point. Note that quasi-random sequences do not use a seed and always produce the same set of values.

18.2 Sampling from a quasi-random number generator

Function: int gsl_qrng_get (const gsl_qrng * q, double x[])

This function stores the next point from the sequence generator q in the array x. The space available for x must match the dimension of the generator. The point x will lie in the range for each .

18.3 Auxiliary quasi-random number generator functions

Function: const char * gsl_qrng_name (const gsl_qrng * q)

This function returns a pointer to the name of the generator.

Function: size_t gsl_qrng_size (const gsl_qrng * q)

Function: void * gsl_qrng_state (const gsl_qrng * q)

These functions return a pointer to the state of generator r and its size. You can use this information to access the state directly. For example, the following code will write the state of a generator to a stream,

void * state = gsl_qrng_state (q); size_t n = gsl_qrng_size (q); fwrite (state, n, 1, stream);

18.4 Saving and resorting quasi-random number generator state

Function: int gsl_qrng_memcpy (gsl_qrng * dest, const gsl_qrng * src)

This function copies the quasi-random sequence generator src into the pre-existing generator dest, making dest into an exact copy of src. The two generators must be of the same type.

Function: gsl_qrng * gsl_qrng_clone (const gsl_qrng * q)

This function returns a pointer to a newly created generator which is an exact copy of the generator q.

18.5 Quasi-random number generator algorithms

The following quasi-random sequence algorithms are available,

Generator: gsl_qrng_niederreiter_2

This generator uses the algorithm described in Bratley, Fox, Niederreiter, ACM Trans. Model. Comp. Sim. 2, 195 (1992). It is valid up to 12 dimensions.

Generator: gsl_qrng_sobol

This generator uses the Sobol sequence described in Antonov, Saleev, USSR Comput. Maths. Math. Phys. 19, 252 (1980). It is valid up to 40 dimensions.

18.6 Examples

The following program prints the first 1024 points of the 2-dimensional Sobol sequence.

#include <stdio.h>
#include <gsl/gsl_qrng.h>

int
main (void)
{
  int i;
  gsl_qrng * q = gsl_qrng_alloc (gsl_qrng_sobol, 2);

  for (i = 0; i < 1024; i++)
    {
      double v[2];
      gsl_qrng_get (q, v);
      printf ("%.5f %.5f\n", v[0], v[1]);
    }

  gsl_qrng_free (q);
  return 0;
}

Here is the output from the program,

$ ./a.out
0.50000 0.50000
0.75000 0.25000
0.25000 0.75000
0.37500 0.37500
0.87500 0.87500
0.62500 0.12500
0.12500 0.62500
....

It can be seen that successive points progressively fill-in the spaces between previous points.

18.7 References

The implementations of the quasi-random sequence routines are based on the algorithms described in the following paper,

• P. Bratley and B.L. Fox and H. Niederreiter, “Algorithm 738: Programs to Generate Niederreiter's Low-discrepancy Sequences”, ACM Transactions on Mathematical Software, Vol. 20, No. 4, December, 1994, p. 494–495.

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