octave: src/DLD-FUNCTIONS/rand.cc comparison

comparison src/DLD-FUNCTIONS/rand.cc @ 14655:43db83eff9db

Implement single precision rand, randn, rande, randg and randp generators (bug #34351, #36293) * oct-rand.cc (octave_rand:do_matrix): Remove method. (octave_rand::do_float_scalar, octave_rand::do_float_nd_array, octave_rand::do_float_vector): New methods. * oct-rand.h (octave_rand:do_matrix, octave_rand::matrix): Remove methods. (octave_rand::do_float_scalar, octave_rand::do_float_nd_array, octave_rand::do_float_vector, octave_rand::float_scalar, octave_rand::do_nd_array, octave_rand::float_vector): Declare new methods. * randgamma.c (oct_fill_float_randg, oct_float_randg): New functions. * randgamma.h (oct_fill_float_randg, oct_float_randg): Declare new functions. * randpoisson.c (oct_fill_float_randp, oct_float_randp): New functions. (poisson_cdf_lookup_float, poisson_rejection_float): New static functions. * randpoisson.h (oct_fill_float_randp, oct_float_randp): Declare new functions. * randmtzig.c (randu64) : Remove static function. (ALLBITS): Remove compile flag logic. (randu32): Change return type to float. (oct_float_randu, oct_float_randn, oct_float_rande, oct_fill_float_randu, oct_fill_float_randn, oct_fill_float_rande): New functions. (create_ziggurat_float_tables): New static function. * randmtzig.h (oct_float_randu, oct_float_randn, oct_float_rande, oct_fill_float_randu, oct_fill_float_randn, oct_fill_float_rande): Declare new functions. * rand.cc (do_rand): Add logic to parse "double" or "single" as final argument.

author	David Bateman <dbateman@free.fr>
date	Sat, 19 May 2012 00:14:59 +0200
parents	cd375519eab0
children	52c5fb67fa5f

comparison

equal deleted inserted replaced

-:389f49a88656
+:43db83eff9db
 /*
 Copyright (C) 1996-2012 John W. Eaton
 Copyright (C) 2009 VZLU Prague
 {
 octave_value retval;
 NDArray a;
 int idx = 0;
 dim_vector dims;
+bool is_single = false;
 unwind_protect frame;
 // Restore current distribution on any exit.
 frame.add_fcn (octave_rand::distribution,
 octave_rand::distribution ());
 octave_rand::distribution (distribution);
+if (nargin > 0 && args(nargin-1).is_string())
+{
+std::string s_arg = args(nargin-1).string_value ();
+if (s_arg == "single")
+{
+is_single = true;
+nargin--;
+}
+else if (s_arg == "double")
+nargin--;
+}
 if (additional_arg)
 {
 if (nargin == 0)
 {
 gen_matrix:
 dims.chop_trailing_singletons ();
-if (additional_arg)
+if (is_single)
 {
-if (a.length() == 1)
+if (additional_arg)
-return octave_rand::nd_array (dims, a(0));
+{
+if (a.length() == 1)
+return octave_rand::float_nd_array (dims, a(0));
+else
+{
+if (a.dims() != dims)
+{
+error ("%s: mismatch in argument size", fcn);
+return retval;
+}
+octave_idx_type len = a.length ();
+FloatNDArray m (dims);
+float *v = m.fortran_vec ();
+for (octave_idx_type i = 0; i < len; i++)
+v[i] = octave_rand::float_scalar (a(i));
+return m;
+}
+}
 else
-{
+return octave_rand::float_nd_array (dims);
-if (a.dims() != dims)
-{
-error ("%s: mismatch in argument size", fcn);
-return retval;
-}
-octave_idx_type len = a.length ();
-NDArray m (dims);
-double *v = m.fortran_vec ();
-for (octave_idx_type i = 0; i < len; i++)
-v[i] = octave_rand::scalar (a(i));
-return m;
-}
 }
 else
-return octave_rand::nd_array (dims);
+{
+if (additional_arg)
+{
+if (a.length() == 1)
+return octave_rand::nd_array (dims, a(0));
+else
+{
+if (a.dims() != dims)
+{
+error ("%s: mismatch in argument size", fcn);
+return retval;
+}
+octave_idx_type len = a.length ();
+NDArray m (dims);
+double *v = m.fortran_vec ();
+for (octave_idx_type i = 0; i < len; i++)
+v[i] = octave_rand::scalar (a(i));
+return m;
+}
+}
+else
+return octave_rand::nd_array (dims);
+}
 }
 DEFUN_DLD (rand, args, ,
 "-*- texinfo -*-\n\
 @deftypefn  {Loadable Function} {} rand (@var{n})\n\
 @deftypefnx {Loadable Function} {} rand (\"state\", @var{v})\n\
 @deftypefnx {Loadable Function} {} rand (\"state\", \"reset\")\n\
 @deftypefnx {Loadable Function} {@var{v} =} rand (\"seed\")\n\
 @deftypefnx {Loadable Function} {} rand (\"seed\", @var{v})\n\
 @deftypefnx {Loadable Function} {} rand (\"seed\", \"reset\")\n\
+@deftypefnx {Loadable Function} {} rand (@dots{}, \"single\")\n\
+@deftypefnx {Loadable Function} {} rand (@dots{}, \"double\")\n\
 Return a matrix with random elements uniformly distributed on the\n\
 interval (0, 1).  The arguments are handled the same as the arguments\n\
 for @code{eye}.\n\
 \n\
 You can query the state of the random number generator using the\n\
 To cause @code{rand} to once again use the new generators, the\n\
 keyword \"state\" should be used to reset the state of the @code{rand}.\n\
 \n\
 The state or seed of the generator can be reset to a new random value\n\
 using the \"reset\" keyword.\n\
+\n\
+The class of the value returned can be controlled by a trailing \"double\"\n\
+or \"single\" argument. These are the only valid classes.\n\
 @seealso{randn, rande, randg, randp}\n\
 @end deftypefn")
 {
 octave_value retval;
 @deftypefnx {Loadable Function} {} randn (\"state\", @var{v})\n\
 @deftypefnx {Loadable Function} {} randn (\"state\", \"reset\")\n\
 @deftypefnx {Loadable Function} {@var{v} =} randn (\"seed\")\n\
 @deftypefnx {Loadable Function} {} randn (\"seed\", @var{v})\n\
 @deftypefnx {Loadable Function} {} randn (\"seed\", \"reset\")\n\
+@deftypefnx {Loadable Function} {} randn (@dots{}, \"single\")\n\
+@deftypefnx {Loadable Function} {} randn (@dots{}, \"double\")\n\
 Return a matrix with normally distributed random\n\
 elements having zero mean and variance one.  The arguments are\n\
 handled the same as the arguments for @code{rand}.\n\
 \n\
 By default, @code{randn} uses the Marsaglia and Tsang ``Ziggurat technique''\n\
 to transform from a uniform to a normal distribution.\n\
+\n\
+The class of the value returned can be controlled by a trailing \"double\"\n\
+or \"single\" argument. These are the only valid classes.\n\
 \n\
 Reference: G. Marsaglia and W.W. Tsang,\n\
 @cite{Ziggurat Method for Generating Random Variables},\n\
 J. Statistical Software, vol 5, 2000,\n\
 @url{http://www.jstatsoft.org/v05/i08/})\n\
 @deftypefnx {Loadable Function} {} rande (\"state\", @var{v})\n\
 @deftypefnx {Loadable Function} {} rande (\"state\", \"reset\")\n\
 @deftypefnx {Loadable Function} {@var{v} =} rande (\"seed\")\n\
 @deftypefnx {Loadable Function} {} rande (\"seed\", @var{v})\n\
 @deftypefnx {Loadable Function} {} rande (\"seed\", \"reset\")\n\
+@deftypefnx {Loadable Function} {} rande (@dots{}, \"single\")\n\
+@deftypefnx {Loadable Function} {} rande (@dots{}, \"double\")\n\
 Return a matrix with exponentially distributed random elements.  The\n\
 arguments are handled the same as the arguments for @code{rand}.\n\
 \n\
 By default, @code{randn} uses the Marsaglia and Tsang ``Ziggurat technique''\n\
 to transform from a uniform to an exponential distribution.\n\
+\n\
+The class of the value returned can be controlled by a trailing \"double\"\n\
+or \"single\" argument. These are the only valid classes.\n\
 \n\
 Reference: G. Marsaglia and W.W. Tsang,\n\
 @cite{Ziggurat Method for Generating Random Variables},\n\
 J. Statistical Software, vol 5, 2000,\n\
 @url{http://www.jstatsoft.org/v05/i08/})\n\
 @deftypefnx {Loadable Function} {} randg (\"state\", @var{v})\n\
 @deftypefnx {Loadable Function} {} randg (\"state\", \"reset\")\n\
 @deftypefnx {Loadable Function} {@var{v} =} randg (\"seed\")\n\
 @deftypefnx {Loadable Function} {} randg (\"seed\", @var{v})\n\
 @deftypefnx {Loadable Function} {} randg (\"seed\", \"reset\")\n\
+@deftypefnx {Loadable Function} {} randg (@dots{}, \"single\")\n\
+@deftypefnx {Loadable Function} {} randg (@dots{}, \"double\")\n\
 Return a matrix with @code{gamma(@var{a},1)} distributed random elements.\n\
 The arguments are handled the same as the arguments for @code{rand},\n\
 except for the argument @var{a}.\n\
 \n\
 This can be used to generate many distributions:\n\
 r = r / sum (r)\n\
 @end group\n\
 @end example\n\
 \n\
 @end table\n\
+\n\
+The class of the value returned can be controlled by a trailing \"double\"\n\
+or \"single\" argument. These are the only valid classes.\n\
 @seealso{rand, randn, rande, randp}\n\
 @end deftypefn")
 {
 octave_value retval;
 @deftypefnx {Loadable Function} {} randp (\"state\", @var{v})\n\
 @deftypefnx {Loadable Function} {} randp (\"state\", \"reset\")\n\
 @deftypefnx {Loadable Function} {@var{v} =} randp (\"seed\")\n\
 @deftypefnx {Loadable Function} {} randp (\"seed\", @var{v})\n\
 @deftypefnx {Loadable Function} {} randp (\"seed\", \"reset\")\n\
+@deftypefnx {Loadable Function} {} randp (@dots{}, \"single\")\n\
+@deftypefnx {Loadable Function} {} randp (@dots{}, \"double\")\n\
 Return a matrix with Poisson distributed random elements with mean value\n\
 parameter given by the first argument, @var{l}.  The arguments\n\
 are handled the same as the arguments for @code{rand}, except for the\n\
 argument @var{l}.\n\
 \n\
 \n\
 @item For @var{l} > 1e8, use normal approximation.\n\
 L. Montanet, et al., @cite{Review of Particle Properties}, Physical Review\n\
 D 50 p1284, 1994.\n\
 @end table\n\
+\n\
+The class of the value returned can be controlled by a trailing \"double\"\n\
+or \"single\" argument. These are the only valid classes.\n\
 @seealso{rand, randn, rande, randg}\n\
 @end deftypefn")
 {
 octave_value retval;

Mercurial > octave

comparison src/DLD-FUNCTIONS/rand.cc @ 14655:43db83eff9db