RNG.i

   1 %module "Math::GSL::RNG"
   2 %{
   3     #include "gsl/gsl_rng.h"
   4 %}
   5 %import "gsl/gsl_types.h"
   6
   7 %include "gsl/gsl_rng.h"
   8
   9 %perlcode %{
  10 @EXPORT_OK = qw/
  11                  gsl_rng_alloc gsl_rng_set gsl_rng_get gsl_rng_free gsl_rng_memcpy
  12                  gsl_rng_fwrite gsl_rng_fread gsl_rng_clone gsl_rng_max gsl_rng_min
  13                  gsl_rng_name gsl_rng_size gsl_rng_state gsl_rng_print_state gsl_rng_uniform gsl_rng_uniform_pos gsl_rng_uniform_int
  14                 $gsl_rng_default $gsl_rng_knuthran $gsl_rng_ran0 $gsl_rng_borosh13
  15                 $gsl_rng_coveyou $gsl_rng_cmrg $gsl_rng_fishman18 $gsl_rng_fishman20 $gsl_rng_fishman2x
  16                 $gsl_rng_gfsr4 $gsl_rng_knuthran $gsl_rng_knuthran2 $gsl_rng_knuthran2002 $gsl_rng_lecuyer21
  17                 $gsl_rng_minstd $gsl_rng_mrg $gsl_rng_mt19937 $gsl_rng_mt19937_1999 $gsl_rng_mt19937_1998
  18                 $gsl_rng_r250 $gsl_rng_ran0 $gsl_rng_ran1 $gsl_rng_ran2 $gsl_rng_ran3
  19                 $gsl_rng_rand $gsl_rng_rand48 $gsl_rng_random128_bsd $gsl_rng_random128_gli $gsl_rng_random128_lib
  20                 $gsl_rng_random256_bsd $gsl_rng_random256_gli $gsl_rng_random256_lib $gsl_rng_random32_bsd
  21                 $gsl_rng_random32_glib $gsl_rng_random32_libc $gsl_rng_random64_bsd $gsl_rng_random64_glib
  22                 $gsl_rng_random64_libc $gsl_rng_random8_bsd $gsl_rng_random8_glibc $gsl_rng_random8_libc5
  23                 $gsl_rng_random_bsd $gsl_rng_random_glibc2 $gsl_rng_random_libc5 $gsl_rng_randu
  24                 $gsl_rng_ranf $gsl_rng_ranlux $gsl_rng_ranlux389 $gsl_rng_ranlxd1 $gsl_rng_ranlxd2 $gsl_rng_ranlxs0
  25                 $gsl_rng_ranlxs1 $gsl_rng_ranlxs2 $gsl_rng_ranmar $gsl_rng_slatec $gsl_rng_taus $gsl_rng_taus2
  26                 $gsl_rng_taus113 $gsl_rng_transputer $gsl_rng_tt800 $gsl_rng_uni $gsl_rng_uni32 $gsl_rng_vax
  27                 $gsl_rng_waterman14 $gsl_rng_zuf
  28               /;
  29 %EXPORT_TAGS = ( all => [ @EXPORT_OK ] );
  30
  31 =head1 NAME
  32
  33 Math::GSL::RNG - Random Number Generators
  34
  35 =head1 SYNOPSIS
  36
  37     use Math::GSL::RNG qw/:all/;
  38     my $rng = Math::GSL::RNG->new;
  39     my @random = map { $rng->get } (1..100);
  40
  41 =head2 Math::GSL::RNG->new($type, $seed)
  42
  43     my $rng = Math::GSL::RNG->new;
  44     my $rng = Math::GSL::RNG->new($gsl_rng_knuthran,5);
  45
  46 Creates a new RNG object of type $type, seeded with $seed. Both of these
  47 parameters are optional. The type $gsl_rng_default is used when no $type
  48 is given.
  49
  50 =cut
  51
  52 sub new {
  53     my ($class, $type, $seed) = @_;
  54     $type ||= $gsl_rng_default;
  55     $seed ||= int 100*rand;
  56
  57     my $self = {};
  58     my $rng  = gsl_rng_alloc($type);
  59     gsl_rng_set($rng, $seed);
  60
  61     $self->{_rng} = $rng;
  62     bless $self, $class;
  63 }
  64
  65 =head2 copy()
  66
  67     my $copy = $rng->copy;
  68
  69 Make a copy of a RNG object.
  70
  71 =cut
  72
  73 sub copy {
  74     my ($self)    = @_;
  75     my $copy      = Math::GSL::RNG->new;
  76     $copy->{_rng} = gsl_rng_clone($self->{_rng});
  77
  78     return $copy;
  79 }
  80
  81 =head2 free()
  82
  83     $rng->free();
  84
  85 Free memory associated with RNG object.
  86
  87 =cut
  88
  89 sub free {
  90     my ($self)    = @_;
  91     gsl_rng_free($self->{_rng});
  92 }
  93
  94 =head2 name()
  95
  96    my $name = $rng->name();
  97
  98 Get the name of the RNG object as a string.
  99
 100 =cut
 101
 102 sub name {
 103     my ($self)    = @_;
 104     gsl_rng_name($self->{_rng});
 105 }
 106
 107 =head2 get()
 108
 109     my $nextval = $rng->get();
 110
 111 Get the next random value from the RNG object.
 112
 113 =cut
 114
 115 sub get {
 116     my ($self) = @_;
 117
 118     gsl_rng_get($self->{_rng});
 119 }
 120
 121 __END__
 122
 123
 124 =head1 DESCRIPTION
 125
 126 =over 1
 127
 128 =item gsl_rng_alloc($T) - This function returns a pointer to a newly-created instance of a random number generator of type $T. $T must be one of the constants below. The generator is automatically initialized with the default seed, $gsl_rng_default.
 129
 130 =item gsl_rng_set($r, $s) - This function initializes (or `seeds') the random number generator. If the generator is seeded with the same value of $s on two different runs, the same stream of random numbers will be generated by successive calls to the routines below. If different values of $s are supplied, then the generated streams of random numbers should be completely different. If the seed $s is zero then the standard seed from the original implementation is used instead. For example, the original Fortran source code for the ranlux generator used a seed of 314159265, and so choosing $s equal to zero reproduces this when using $gsl_rng_ranlux.
 131
 132 =item gsl_rng_get($r) - This function returns a random integer from the generator $r. The minimum and maximum values depend on the algorithm used, but all integers in the range [min,max] are equally likely. The values of min and max can determined using the auxiliary functions gsl_rng_max($r) and gsl_rng_min($r).
 133
 134 =item gsl_rng_free($r) - This function frees all the memory associated with the generator $r.
 135
 136 =item gsl_rng_memcpy($dest, $src) - This function copies the random number generator $src into the pre-existing generator $dest, making $dest into an exact copy of $src. The two generators must be of the same type.
 137
 138 =item gsl_rng_uniform($r) - This function returns a double precision floating point number uniformly distributed in the range [0,1). The range includes 0.0 but excludes 1.0. The value is typically obtained by dividing the result of gsl_rng_get($r) by gsl_rng_max($r) + 1.0 in double precision. Some generators compute this ratio internally so that they can provide floating point numbers with more than 32 bits of randomness (the maximum number of bits that can be portably represented in a single unsigned long int).
 139
 140 =item gsl_rng_uniform_pos($r) - This function returns a positive double precision floating point number uniformly distributed in the range (0,1), excluding both 0.0 and 1.0. The number is obtained by sampling the generator with the algorithm of gsl_rng_uniform until a non-zero value is obtained. You can use this function if you need to avoid a singularity at 0.0.
 141
 142 =item gsl_rng_uniform_int($r, $n) - This function returns a random integer from 0 to $n-1 inclusive by scaling down and/or discarding samples from the generator $r. All integers in the range [0,$n-1] are produced with equal probability. For generators with a non-zero minimum value an offset is applied so that zero is returned with the correct probability. Note that this function is designed for sampling from ranges smaller than the range of the underlying generator. The parameter $n must be less than or equal to the range of the generator $r. If $n is larger than the range of the generator then the function calls the error handler with an error code of $GSL_EINVAL and returns zero. In particular, this function is not intended for generating the full range of unsigned integer values [0,2^32-1]. Instead choose a generator with the maximal integer range and zero mimimum value, such as $gsl_rng_ranlxd1, $gsl_rng_mt19937 or $gsl_rng_taus, and sample it directly using gsl_rng_get. The range of each generator can be found using the auxiliary functions described in the next section.
 143
 144 =item gsl_rng_fwrite($stream, $r) - This function writes the random number state of the random number generator $r to the stream $stream (opened with the gsl_fopen function from the Math::GSL module) in binary format. The return value is 0 for success and $GSL_EFAILED if there was a problem writing to the file. Since the data is written in the native binary format it may not be portable between different architectures.
 145
 146 =item gsl_rng_fread($stream, $r) - This function reads the random number state into the random number generator $r from the open stream $stream (opened with the gsl_fopen function from the Math::GSL module) in binary format. The random number generator $r must be preinitialized with the correct random number generator type since type information is not saved. The return value is 0 for success and $GSL_EFAILED if there was a problem reading from the file. The data is assumed to have been written in the native binary format on the same architecture.
 147
 148 =item gsl_rng_clone($r) - This function returns a pointer to a newly created generator which is an exact copy of the generator $r.
 149
 150 =item gsl_rng_max($r) - This function returns the largest value that gsl_rng_get can return.
 151
 152 =item gsl_rng_min($r) - gsl_rng_min returns the smallest value that gsl_rng_get can return. Usually this value is zero. There are some generators with algorithms that cannot return zero, and for these generators the minimum value is 1.
 153
 154 =item gsl_rng_name($r) - This function returns a pointer to the name of the generator. For example,
 155
 156 =over
 157
 158 =item print "r is a " . gsl_rng_name($r) . "generator\n";
 159
 160 =item would print something like r is a 'taus' generator.
 161
 162 =back
 163
 164 =item gsl_rng_size($r) - This function returns the size of the state of generator $r. You can use this information to access the state directly.
 165
 166 =item gsl_rng_state($r) - This function returns a pointer to the state of generator $r. You can use this information to access the state directly.
 167
 168 =item gsl_rng_print_state($r)
 169
 170 =back
 171
 172 =head1 Random Number Generator Types
 173
 174 =over 1
 175
 176 =item $gsl_rng_default
 177
 178 =item $gsl_rng_knuthran
 179
 180 =item $gsl_rng_ran0
 181
 182 =item $gsl_rng_borosh13
 183
 184 =item $gsl_rng_coveyou
 185
 186 =item $gsl_rng_cmrg
 187
 188 =item $gsl_rng_fishman18
 189
 190 =item $gsl_rng_fishman20
 191
 192 =item $gsl_rng_fishman2x - This is the L'Ecuyer–Fishman random number generator. It is taken from Knuth's Seminumerical Algorithms, 3rd Ed., page 108. Its sequence is, z_{n+1} = (x_n - y_n) mod m with m = 2^31 - 1. x_n and y_n are given by the fishman20 and lecuyer21 algorithms. The seed specifies the initial value, x_1.
 193
 194 =item $gsl_rng_gfsr4
 195
 196 =item $gsl_rng_knuthran
 197
 198 =item $gsl_rng_knuthran2
 199
 200 =item $gsl_rng_knuthran2002
 201
 202 =item $gsl_rng_lecuyer21
 203
 204 =item $gsl_rng_minstd
 205
 206 =item $gsl_rng_mrg
 207
 208 =item $gsl_rng_mt19937
 209
 210 =item $gsl_rng_mt19937_1999
 211
 212 =item $gsl_rng_mt19937_1998
 213
 214 =item $gsl_rng_r250
 215
 216 =item $gsl_rng_ran0
 217
 218 =item $gsl_rng_ran1
 219
 220 =item $gsl_rng_ran2
 221
 222 =item $gsl_rng_ran3
 223
 224 =item $gsl_rng_rand - This is the BSD rand generator. Its sequence is x_{n+1} = (a x_n + c) mod m with a = 1103515245, c = 12345 and m = 2^31. The seed specifies the initial value, x_1. The period of this generator is 2^31, and it uses 1 word of storage per generator.
 225
 226 =item $gsl_rng_rand48
 227
 228 =item $gsl_rng_random128_bsd
 229
 230 =item $gsl_rng_random128_gli
 231
 232 =item $gsl_rng_random128_lib
 233
 234 =item $gsl_rng_random256_bsd
 235
 236 =item $gsl_rng_random256_gli
 237
 238 =item $gsl_rng_random256_lib
 239
 240 =item $gsl_rng_random32_bsd
 241
 242 =item $gsl_rng_random32_glib
 243
 244 =item $gsl_rng_random32_libc
 245
 246 =item $gsl_rng_random64_bsd
 247
 248 =item $gsl_rng_random64_glib
 249
 250 =item $gsl_rng_random64_libc
 251
 252 =item $gsl_rng_random8_bsd
 253
 254 =item $gsl_rng_random8_glibc
 255
 256 =item $gsl_rng_random8_libc5
 257
 258 =item $gsl_rng_random_bsd
 259
 260 =item $gsl_rng_random_glibc2
 261
 262 =item $gsl_rng_random_libc5
 263
 264 =item $gsl_rng_randu
 265
 266 =item $gsl_rng_ranf
 267
 268 =item $gsl_rng_ranlux
 269
 270 =item $gsl_rng_ranlux389
 271
 272 =item $gsl_rng_ranlxd1
 273
 274 =item $gsl_rng_ranlxd2
 275
 276 =item $gsl_rng_ranlxs0
 277
 278 =item $gsl_rng_ranlxs1
 279
 280 =item $gsl_rng_ranlxs2
 281
 282 =item $gsl_rng_ranmar - This is the RANMAR lagged-fibonacci generator of Marsaglia, Zaman and Tsang. It is a 24-bit generator, originally designed for single-precision IEEE floating point numbers. It was included in the CERNLIB high-energy physics library.
 283
 284 =item $gsl_rng_slatec - This is the SLATEC random number generator RAND. It is ancient. The original source code is available from NETLIB.
 285
 286 =item $gsl_rng_taus
 287
 288 =item $gsl_rng_taus2
 289
 290 =item $gsl_rng_taus113
 291
 292 =item $gsl_rng_transputer
 293
 294 =item $gsl_rng_tt800
 295
 296 =item $gsl_rng_uni
 297
 298 =item $gsl_rng_uni32
 299
 300 =item $gsl_rng_vax - This is the VAX generator MTH$RANDOM. Its sequence is, x_{n+1} = (a x_n + c) mod m with a = 69069, c = 1 and m = 2^32. The seed specifies the initial value, x_1. The period of this generator is 2^32 and it uses 1 word of storage per generator.
 301
 302 =item $gsl_rng_waterman14
 303
 304 =item $gsl_rng_zuf - This is the ZUFALL lagged Fibonacci series generator of Peterson. Its sequence is,
 305
 306 =over
 307
 308 =item          t = u_{n-273} + u_{n-607}
 309
 310 =item          u_n  = t - floor(t)
 311
 312 =back
 313
 314  The original source code is available from NETLIB. For more information see,
 315
 316  * W. Petersen, “Lagged Fibonacci Random Number Generators for the NEC SX-3”, International Journal of High Speed Computing (1994).
 317
 318 =back
 319
 320 For more informations on the functions, we refer you to the GSL offcial documentation:
 321
 322 L<http://www.gnu.org/software/gsl/manual/html_node/>
 323
 324 Tip : search on google: site:http://www.gnu.org/software/gsl/manual/html_node/ name_of_the_function_you_want
 325
 326 =head1 EXAMPLES
 327
 328 The following example will print out a list a random integers between certain
 329 minimum and maximum values. The command line arguments are first the number of
 330 random numbers wanted, the minimum and then maximum. The defaults are 10, 0 and
 331 100, respectively.
 332
 333     use Math::GSL::RNG qw/:all/;
 334     my $seed = int rand(100);
 335     my $rng  = Math::GSL::RNG->new($gsl_rng_knuthran, $seed );
 336     my ($num,$min,$max) = @ARGV;
 337     $num ||= 10;
 338     $min ||= 0;
 339     $max ||= 100;
 340     print join "\n", map { $min + $rng->get % ($max-$min+1)  } (1..$num);
 341     print "\n";
 342
 343 The C<$seed> argument is optional but encouraged. This program is available in
 344 the B<examples/> directory that comes with the source of this module.
 345
 346 If you would like a series of random non-integer numbers, then you can generate one "scaling factor"
 347 and multiple by that, such as
 348
 349     use Math::GSL::RNG qw/:all/;
 350     my $scale= rand(10);
 351     my $seed = int rand(100);
 352     my $rng  = Math::GSL::RNG->new($gsl_rng_knuthran, $seed );
 353     my ($num,$min,$max) = (10,0,100);
 354     print join "\n", map { $scale*($min + $rng->get % ($max-$min+1))  } (1..$num);
 355     print "\n";
 356
 357 =head1 AUTHORS
 358
 359 Jonathan Leto <jonathan@leto.net> and Thierry Moisan <thierry.moisan@gmail.com>
 360
 361 =head1 COPYRIGHT AND LICENSE
 362
 363 Copyright (C) 2008 Jonathan Leto and Thierry Moisan
 364
 365 This program is free software; you can redistribute it and/or modify it
 366 under the same terms as Perl itself.
 367
 368 =cut
 369
 370 %}