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

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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
line wrap: on
line diff
--- a/src/DLD-FUNCTIONS/rand.cc	Fri May 18 13:16:04 2012 -0700
+++ b/src/DLD-FUNCTIONS/rand.cc	Sat May 19 00:14:59 2012 +0200
@@ -1,3 +1,4 @@
+
 /*
 
 Copyright (C) 1996-2012 John W. Eaton
@@ -60,6 +61,7 @@
   NDArray a;
   int idx = 0;
   dim_vector dims;
+  bool is_single = false;
 
   unwind_protect frame;
   // Restore current distribution on any exit.
@@ -68,6 +70,19 @@
 
   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)
@@ -298,27 +313,54 @@
 
   dims.chop_trailing_singletons ();
 
-  if (additional_arg)
+  if (is_single)
     {
-      if (a.length() == 1)
-        return octave_rand::nd_array (dims, a(0));
-      else
+      if (additional_arg)
         {
-          if (a.dims() != dims)
+          if (a.length() == 1)
+            return octave_rand::float_nd_array (dims, a(0));
+          else
             {
-              error ("%s: mismatch in argument size", fcn);
-              return retval;
+              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;
             }
-          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::float_nd_array (dims);
     }
   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, ,
@@ -332,6 +374,8 @@
 @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\
@@ -402,6 +446,9 @@
 \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")
 {
@@ -499,6 +546,8 @@
 @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\
@@ -506,6 +555,9 @@
 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\
@@ -565,12 +617,17 @@
 @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\
@@ -632,6 +689,8 @@
 @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\
@@ -711,6 +770,9 @@
 @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")
 {
@@ -898,6 +960,8 @@
 @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\
@@ -928,6 +992,9 @@
 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")
 {