Mercurial > octave
annotate libinterp/corefcn/rand.cc @ 22150:c4901d7a2d7d
Remove check for std::tr1::unordered_map because we depend on C++11.
* rand.cc: remove conditional include of unordered_map from std::tr1
if it's missing from std. Octave is already dependent on C++11 so it
is no longer needed.
* configure.ac: remove call to OCTAVE_UNORDERED_MAP_HEADERS.
* m4/acinclude.m4: remove unused OCTAVE_UNORDERED_MAP_HEADERS macro.
author | Carnë Draug <carandraug@octave.org> |
---|---|
date | Wed, 20 Jul 2016 15:32:53 +0100 |
parents | 973db845cb43 |
children | bac0d6f07a3e |
rev | line source |
---|---|
14655
43db83eff9db
Implement single precision rand, randn, rande, randg and randp generators (bug #34351, #36293)
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1 |
2928 | 2 /* |
3 | |
19697
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maint: Update copyright notices for 2015.
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4 Copyright (C) 1996-2015 John W. Eaton |
9647
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5 Copyright (C) 2009 VZLU Prague |
2928 | 6 |
7 This file is part of Octave. | |
8 | |
9 Octave is free software; you can redistribute it and/or modify it | |
10 under the terms of the GNU General Public License as published by the | |
7016 | 11 Free Software Foundation; either version 3 of the License, or (at your |
12 option) any later version. | |
2928 | 13 |
14 Octave is distributed in the hope that it will be useful, but WITHOUT | |
15 ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or | |
16 FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License | |
17 for more details. | |
18 | |
19 You should have received a copy of the GNU General Public License | |
7016 | 20 along with Octave; see the file COPYING. If not, see |
21 <http://www.gnu.org/licenses/>. | |
2928 | 22 |
23 */ | |
24 | |
21724
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use "#if ..." consistently instead of "#ifdef" and "#ifndef"
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25 #if defined (HAVE_CONFIG_H) |
21301
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Use '#include "config.h"' rather than <config.h>.
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26 # include "config.h" |
2928 | 27 #endif |
28 | |
29 #include <ctime> | |
22150
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30 #include <unordered_map> |
2928 | 31 #include <string> |
32 | |
33 #include "f77-fcn.h" | |
34 #include "lo-mappers.h" | |
4307 | 35 #include "oct-rand.h" |
4153 | 36 #include "quit.h" |
2928 | 37 |
15039
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38 #include "defun.h" |
2928 | 39 #include "error.h" |
21100
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Switch gripe_XXX to either err_XXX or warn_XXX naming scheme.
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40 #include "errwarn.h" |
20940
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maint: Rename oct-obj.[cc|h] to ovl.[cc|h] for clarity.
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41 #include "ovl.h" |
2928 | 42 #include "unwind-prot.h" |
43 #include "utils.h" | |
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optimize & extend randperm
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44 #include "ov-re-mat.h" |
2928 | 45 |
6437 | 46 /* |
47 %!shared __random_statistical_tests__ | |
17336
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48 %! ## Flag whether the statistical tests should be run in "make check" or not |
6437 | 49 %! __random_statistical_tests__ = 0; |
50 */ | |
51 | |
4307 | 52 static octave_value |
5730 | 53 do_rand (const octave_value_list& args, int nargin, const char *fcn, |
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54 const std::string& distribution, bool additional_arg = false) |
2928 | 55 { |
5730 | 56 NDArray a; |
57 int idx = 0; | |
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Implement single precision rand, randn, rande, randg and randp generators (bug #34351, #36293)
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58 bool is_single = false; |
2928 | 59 |
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60 if (nargin > 0 && args(nargin-1).is_string ()) |
14655
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61 { |
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62 std::string s_arg = args(nargin-1).string_value (); |
43db83eff9db
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63 |
43db83eff9db
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64 if (s_arg == "single") |
43db83eff9db
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65 { |
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66 is_single = true; |
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67 nargin--; |
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68 } |
43db83eff9db
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69 else if (s_arg == "double") |
43db83eff9db
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70 nargin--; |
43db83eff9db
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71 } |
43db83eff9db
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72 |
5730 | 73 if (additional_arg) |
74 { | |
75 if (nargin == 0) | |
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76 error ("%s: at least one argument is required", fcn); |
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77 else if (args(0).is_string ()) |
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78 additional_arg = false; |
5730 | 79 else |
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80 { |
20711
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Make error messages more specific about the variable and problem encountered.
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81 a = args(0).xarray_value ("%s: dimension must be a scalar integer", fcn); |
20704
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82 |
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83 idx++; |
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84 nargin--; |
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85 } |
5730 | 86 } |
2928 | 87 |
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88 octave_value retval; |
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89 dim_vector dims; |
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90 |
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91 octave::unwind_protect frame; |
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92 // Restore current distribution on any exit. |
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93 frame.add_fcn (octave_rand::distribution, |
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94 octave_rand::distribution ()); |
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95 |
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96 octave_rand::distribution (distribution); |
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97 |
4543 | 98 switch (nargin) |
2928 | 99 { |
4543 | 100 case 0: |
101 { | |
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102 if (additional_arg) |
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103 dims = a.dims (); |
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104 else |
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105 { |
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106 dims.resize (2); |
4543 | 107 |
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108 dims(0) = 1; |
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109 dims(1) = 1; |
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110 } |
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111 |
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112 goto gen_matrix; |
4543 | 113 } |
114 break; | |
2928 | 115 |
4543 | 116 case 1: |
117 { | |
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118 octave_value tmp = args(idx); |
4543 | 119 |
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120 if (tmp.is_string ()) |
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121 { |
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122 std::string s_arg = tmp.string_value (); |
2928 | 123 |
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124 if (s_arg == "dist") |
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125 retval = octave_rand::distribution (); |
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126 else if (s_arg == "seed") |
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127 retval = octave_rand::seed (); |
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128 else if (s_arg == "state" || s_arg == "twister") |
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129 retval = octave_rand::state (fcn); |
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130 else if (s_arg == "uniform") |
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131 octave_rand::uniform_distribution (); |
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132 else if (s_arg == "normal") |
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133 octave_rand::normal_distribution (); |
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134 else if (s_arg == "exponential") |
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135 octave_rand::exponential_distribution (); |
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136 else if (s_arg == "poisson") |
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137 octave_rand::poisson_distribution (); |
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138 else if (s_arg == "gamma") |
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139 octave_rand::gamma_distribution (); |
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140 else |
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141 error ("%s: unrecognized string argument", fcn); |
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142 } |
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143 else if (tmp.is_scalar_type ()) |
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144 { |
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145 double dval = tmp.double_value (); |
2928 | 146 |
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147 if (octave::math::isnan (dval)) |
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148 error ("%s: NaN is invalid matrix dimension", fcn); |
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149 |
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150 dims.resize (2); |
4543 | 151 |
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152 dims(0) = octave::math::nint_big (tmp.double_value ()); |
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153 dims(1) = octave::math::nint_big (tmp.double_value ()); |
2928 | 154 |
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155 goto gen_matrix; |
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156 } |
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157 else if (tmp.is_range ()) |
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158 { |
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159 Range r = tmp.range_value (); |
4543 | 160 |
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161 if (! r.all_elements_are_ints ()) |
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162 error ("%s: all elements of range must be integers", fcn); |
4543 | 163 |
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164 octave_idx_type n = r.numel (); |
4543 | 165 |
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166 dims.resize (n); |
2928 | 167 |
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168 octave_idx_type base = octave::math::nint_big (r.base ()); |
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169 octave_idx_type incr = octave::math::nint_big (r.inc ()); |
2928 | 170 |
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171 for (octave_idx_type i = 0; i < n; i++) |
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|
172 { |
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|
173 // Negative dimensions treated as zero for Matlab compatibility |
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|
174 dims(i) = base >= 0 ? base : 0; |
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|
175 base += incr; |
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|
176 } |
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177 |
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|
178 goto gen_matrix; |
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179 } |
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180 else if (tmp.is_matrix_type ()) |
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|
181 { |
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|
182 Array<int> iv; |
4543 | 183 |
20743
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|
184 try |
10154
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|
185 { |
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186 iv = tmp.int_vector_value (true); |
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|
187 } |
20785
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always throw exception after debugging with debug_on_error
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188 catch (octave_execution_exception& e) |
20743
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189 { |
20756
200ae1d650b7
propagate octave_execution_exception objects through try/catch blocks
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|
190 error (e, "%s: dimensions must be a scalar or array of integers", fcn); |
20743
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|
191 } |
4543 | 192 |
20743
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193 octave_idx_type len = iv.numel (); |
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194 |
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195 dims.resize (len); |
2928 | 196 |
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197 for (octave_idx_type i = 0; i < len; i++) |
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198 { |
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199 // Negative dimensions treated as zero for Matlab compatibility |
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200 octave_idx_type elt = iv(i); |
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201 dims(i) = elt >=0 ? elt : 0; |
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|
202 } |
20743
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203 |
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204 goto gen_matrix; |
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|
205 } |
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|
206 else |
21129
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maint: Eliminate useless statements after err_XXX.
Rik <rik@octave.org>
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21127
diff
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|
207 err_wrong_type_arg ("rand", tmp); |
4543 | 208 } |
209 break; | |
210 | |
211 default: | |
212 { | |
10154
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|
213 octave_value tmp = args(idx); |
4543 | 214 |
10154
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|
215 if (nargin == 2 && tmp.is_string ()) |
40dfc0c99116
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|
216 { |
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changeset
|
217 std::string ts = tmp.string_value (); |
5164 | 218 |
10154
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|
219 if (ts == "seed") |
40dfc0c99116
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|
220 { |
40dfc0c99116
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|
221 if (args(idx+1).is_real_scalar ()) |
40dfc0c99116
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|
222 { |
40dfc0c99116
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diff
changeset
|
223 double d = args(idx+1).double_value (); |
2928 | 224 |
20678
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20535
diff
changeset
|
225 octave_rand::seed (d); |
10154
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diff
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|
226 } |
11586
12df7854fa7c
strip trailing whitespace from source files
John W. Eaton <jwe@octave.org>
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11553
diff
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|
227 else if (args(idx+1).is_string () |
14846
460a3c6d8bf1
maint: Use Octave coding convention for cuddled parenthis in function calls with empty argument lists.
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diff
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|
228 && args(idx+1).string_value () == "reset") |
10709
92a85ed5b86e
Don't special case color_property type when emitting factory default (bug #30118)
David Bateman <dbateman@free.fr>
parents:
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diff
changeset
|
229 octave_rand::reset (); |
10154
40dfc0c99116
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|
230 else |
40dfc0c99116
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diff
changeset
|
231 error ("%s: seed must be a real scalar", fcn); |
40dfc0c99116
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|
232 } |
40dfc0c99116
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|
233 else if (ts == "state" || ts == "twister") |
40dfc0c99116
DLD-FUNCTIONS/*.cc: untabify
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diff
changeset
|
234 { |
10709
92a85ed5b86e
Don't special case color_property type when emitting factory default (bug #30118)
David Bateman <dbateman@free.fr>
parents:
10687
diff
changeset
|
235 if (args(idx+1).is_string () |
14846
460a3c6d8bf1
maint: Use Octave coding convention for cuddled parenthis in function calls with empty argument lists.
Rik <octave@nomad.inbox5.com>
parents:
14706
diff
changeset
|
236 && args(idx+1).string_value () == "reset") |
10709
92a85ed5b86e
Don't special case color_property type when emitting factory default (bug #30118)
David Bateman <dbateman@free.fr>
parents:
10687
diff
changeset
|
237 octave_rand::reset (fcn); |
92a85ed5b86e
Don't special case color_property type when emitting factory default (bug #30118)
David Bateman <dbateman@free.fr>
parents:
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diff
changeset
|
238 else |
92a85ed5b86e
Don't special case color_property type when emitting factory default (bug #30118)
David Bateman <dbateman@free.fr>
parents:
10687
diff
changeset
|
239 { |
11586
12df7854fa7c
strip trailing whitespace from source files
John W. Eaton <jwe@octave.org>
parents:
11553
diff
changeset
|
240 ColumnVector s = |
10709
92a85ed5b86e
Don't special case color_property type when emitting factory default (bug #30118)
David Bateman <dbateman@free.fr>
parents:
10687
diff
changeset
|
241 ColumnVector (args(idx+1).vector_value(false, true)); |
5730 | 242 |
20678
4b00afb5e9c3
eliminate more uses of error_state
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20535
diff
changeset
|
243 octave_rand::state (s, fcn); |
10709
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Don't special case color_property type when emitting factory default (bug #30118)
David Bateman <dbateman@free.fr>
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diff
changeset
|
244 } |
10154
40dfc0c99116
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diff
changeset
|
245 } |
40dfc0c99116
DLD-FUNCTIONS/*.cc: untabify
John W. Eaton <jwe@octave.org>
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diff
changeset
|
246 else |
40dfc0c99116
DLD-FUNCTIONS/*.cc: untabify
John W. Eaton <jwe@octave.org>
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diff
changeset
|
247 error ("%s: unrecognized string argument", fcn); |
40dfc0c99116
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diff
changeset
|
248 } |
40dfc0c99116
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diff
changeset
|
249 else |
40dfc0c99116
DLD-FUNCTIONS/*.cc: untabify
John W. Eaton <jwe@octave.org>
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10066
diff
changeset
|
250 { |
40dfc0c99116
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diff
changeset
|
251 dims.resize (nargin); |
4543 | 252 |
10154
40dfc0c99116
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diff
changeset
|
253 for (int i = 0; i < nargin; i++) |
40dfc0c99116
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diff
changeset
|
254 { |
21041
63374982750b
Usage of corresponding value extractor for octave_idx_type. Improves support
Kai T. Ohlhus <k.ohlhus@gmail.com>
parents:
20940
diff
changeset
|
255 octave_idx_type elt = |
63374982750b
Usage of corresponding value extractor for octave_idx_type. Improves support
Kai T. Ohlhus <k.ohlhus@gmail.com>
parents:
20940
diff
changeset
|
256 args(idx+i).xidx_type_value ( |
63374982750b
Usage of corresponding value extractor for octave_idx_type. Improves support
Kai T. Ohlhus <k.ohlhus@gmail.com>
parents:
20940
diff
changeset
|
257 "%s: dimension must be a scalar or array of integers", |
63374982750b
Usage of corresponding value extractor for octave_idx_type. Improves support
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parents:
20940
diff
changeset
|
258 fcn); |
20704
571508c1ed06
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20687
diff
changeset
|
259 |
20894
e528d7ab1cad
rand.cc: Overhaul file to make use of new C++ archetype.
Rik <rik@octave.org>
parents:
20853
diff
changeset
|
260 // Negative dimensions treated as zero for Matlab compatibility |
12905
f7a8d1dafda3
Let rand accept negative dimensions (bug #33301)
Jordi Gutiérrez Hermoso <jordigh@gmail.com>
parents:
12639
diff
changeset
|
261 dims(i) = elt >= 0 ? elt : 0; |
10154
40dfc0c99116
DLD-FUNCTIONS/*.cc: untabify
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diff
changeset
|
262 } |
4543 | 263 |
10154
40dfc0c99116
DLD-FUNCTIONS/*.cc: untabify
John W. Eaton <jwe@octave.org>
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10066
diff
changeset
|
264 goto gen_matrix; |
40dfc0c99116
DLD-FUNCTIONS/*.cc: untabify
John W. Eaton <jwe@octave.org>
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10066
diff
changeset
|
265 } |
4543 | 266 } |
267 break; | |
2928 | 268 } |
269 | |
21170
1edaf1ee65eb
maint: Replace some uses of goto in libinterp.
Rik <rik@octave.org>
parents:
21129
diff
changeset
|
270 // No "goto gen_matrix" in code path. Must be done processing. |
2928 | 271 return retval; |
272 | |
17787
175b392e91fe
Use GNU style coding conventions for code in libinterp/
Rik <rik@octave.org>
parents:
17744
diff
changeset
|
273 gen_matrix: |
2928 | 274 |
5355 | 275 dims.chop_trailing_singletons (); |
276 | |
14655
43db83eff9db
Implement single precision rand, randn, rande, randg and randp generators (bug #34351, #36293)
David Bateman <dbateman@free.fr>
parents:
14620
diff
changeset
|
277 if (is_single) |
5730 | 278 { |
14655
43db83eff9db
Implement single precision rand, randn, rande, randg and randp generators (bug #34351, #36293)
David Bateman <dbateman@free.fr>
parents:
14620
diff
changeset
|
279 if (additional_arg) |
10154
40dfc0c99116
DLD-FUNCTIONS/*.cc: untabify
John W. Eaton <jwe@octave.org>
parents:
10066
diff
changeset
|
280 { |
20232
a9574e3c6e9e
Deprecate Array::length() and Sparse::length() in favour of ::numel().
Carnë Draug <carandraug@octave.org>
parents:
20228
diff
changeset
|
281 if (a.numel () == 1) |
14655
43db83eff9db
Implement single precision rand, randn, rande, randg and randp generators (bug #34351, #36293)
David Bateman <dbateman@free.fr>
parents:
14620
diff
changeset
|
282 return octave_rand::float_nd_array (dims, a(0)); |
43db83eff9db
Implement single precision rand, randn, rande, randg and randp generators (bug #34351, #36293)
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parents:
14620
diff
changeset
|
283 else |
10154
40dfc0c99116
DLD-FUNCTIONS/*.cc: untabify
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parents:
10066
diff
changeset
|
284 { |
14846
460a3c6d8bf1
maint: Use Octave coding convention for cuddled parenthis in function calls with empty argument lists.
Rik <octave@nomad.inbox5.com>
parents:
14706
diff
changeset
|
285 if (a.dims () != dims) |
20831
35241c4b696c
eliminate return statements after calls to error
John W. Eaton <jwe@octave.org>
parents:
20801
diff
changeset
|
286 error ("%s: mismatch in argument size", fcn); |
35241c4b696c
eliminate return statements after calls to error
John W. Eaton <jwe@octave.org>
parents:
20801
diff
changeset
|
287 |
20232
a9574e3c6e9e
Deprecate Array::length() and Sparse::length() in favour of ::numel().
Carnë Draug <carandraug@octave.org>
parents:
20228
diff
changeset
|
288 octave_idx_type len = a.numel (); |
14655
43db83eff9db
Implement single precision rand, randn, rande, randg and randp generators (bug #34351, #36293)
David Bateman <dbateman@free.fr>
parents:
14620
diff
changeset
|
289 FloatNDArray m (dims); |
43db83eff9db
Implement single precision rand, randn, rande, randg and randp generators (bug #34351, #36293)
David Bateman <dbateman@free.fr>
parents:
14620
diff
changeset
|
290 float *v = m.fortran_vec (); |
20894
e528d7ab1cad
rand.cc: Overhaul file to make use of new C++ archetype.
Rik <rik@octave.org>
parents:
20853
diff
changeset
|
291 |
14655
43db83eff9db
Implement single precision rand, randn, rande, randg and randp generators (bug #34351, #36293)
David Bateman <dbateman@free.fr>
parents:
14620
diff
changeset
|
292 for (octave_idx_type i = 0; i < len; i++) |
43db83eff9db
Implement single precision rand, randn, rande, randg and randp generators (bug #34351, #36293)
David Bateman <dbateman@free.fr>
parents:
14620
diff
changeset
|
293 v[i] = octave_rand::float_scalar (a(i)); |
20894
e528d7ab1cad
rand.cc: Overhaul file to make use of new C++ archetype.
Rik <rik@octave.org>
parents:
20853
diff
changeset
|
294 |
14655
43db83eff9db
Implement single precision rand, randn, rande, randg and randp generators (bug #34351, #36293)
David Bateman <dbateman@free.fr>
parents:
14620
diff
changeset
|
295 return m; |
10154
40dfc0c99116
DLD-FUNCTIONS/*.cc: untabify
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10066
diff
changeset
|
296 } |
40dfc0c99116
DLD-FUNCTIONS/*.cc: untabify
John W. Eaton <jwe@octave.org>
parents:
10066
diff
changeset
|
297 } |
14655
43db83eff9db
Implement single precision rand, randn, rande, randg and randp generators (bug #34351, #36293)
David Bateman <dbateman@free.fr>
parents:
14620
diff
changeset
|
298 else |
43db83eff9db
Implement single precision rand, randn, rande, randg and randp generators (bug #34351, #36293)
David Bateman <dbateman@free.fr>
parents:
14620
diff
changeset
|
299 return octave_rand::float_nd_array (dims); |
5730 | 300 } |
301 else | |
14655
43db83eff9db
Implement single precision rand, randn, rande, randg and randp generators (bug #34351, #36293)
David Bateman <dbateman@free.fr>
parents:
14620
diff
changeset
|
302 { |
43db83eff9db
Implement single precision rand, randn, rande, randg and randp generators (bug #34351, #36293)
David Bateman <dbateman@free.fr>
parents:
14620
diff
changeset
|
303 if (additional_arg) |
43db83eff9db
Implement single precision rand, randn, rande, randg and randp generators (bug #34351, #36293)
David Bateman <dbateman@free.fr>
parents:
14620
diff
changeset
|
304 { |
20232
a9574e3c6e9e
Deprecate Array::length() and Sparse::length() in favour of ::numel().
Carnë Draug <carandraug@octave.org>
parents:
20228
diff
changeset
|
305 if (a.numel () == 1) |
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306 return octave_rand::nd_array (dims, a(0)); |
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307 else |
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308 { |
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309 if (a.dims () != dims) |
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310 error ("%s: mismatch in argument size", fcn); |
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311 |
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312 octave_idx_type len = a.numel (); |
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313 NDArray m (dims); |
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314 double *v = m.fortran_vec (); |
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315 |
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316 for (octave_idx_type i = 0; i < len; i++) |
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317 v[i] = octave_rand::scalar (a(i)); |
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318 |
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319 return m; |
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320 } |
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321 } |
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322 else |
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323 return octave_rand::nd_array (dims); |
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324 } |
2928 | 325 } |
326 | |
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327 DEFUN (rand, args, , |
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328 doc: /* -*- texinfo -*- |
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329 @deftypefn {} {} rand (@var{n}) |
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330 @deftypefnx {} {} rand (@var{m}, @var{n}, @dots{}) |
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331 @deftypefnx {} {} rand ([@var{m} @var{n} @dots{}]) |
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332 @deftypefnx {} {@var{v} =} rand ("state") |
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333 @deftypefnx {} {} rand ("state", @var{v}) |
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334 @deftypefnx {} {} rand ("state", "reset") |
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335 @deftypefnx {} {@var{v} =} rand ("seed") |
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336 @deftypefnx {} {} rand ("seed", @var{v}) |
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337 @deftypefnx {} {} rand ("seed", "reset") |
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338 @deftypefnx {} {} rand (@dots{}, "single") |
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339 @deftypefnx {} {} rand (@dots{}, "double") |
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340 Return a matrix with random elements uniformly distributed on the |
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341 interval (0, 1). |
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342 |
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343 The arguments are handled the same as the arguments for @code{eye}. |
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344 |
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345 You can query the state of the random number generator using the form |
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346 |
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347 @example |
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348 v = rand ("state") |
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349 @end example |
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350 |
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351 This returns a column vector @var{v} of length 625. Later, you can restore |
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352 the random number generator to the state @var{v} using the form |
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353 |
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354 @example |
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355 rand ("state", v) |
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356 @end example |
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357 |
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358 @noindent |
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359 You may also initialize the state vector from an arbitrary vector of length |
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360 @leq{} 625 for @var{v}. This new state will be a hash based on the value of |
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361 @var{v}, not @var{v} itself. |
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362 |
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363 By default, the generator is initialized from @code{/dev/urandom} if it is |
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364 available, otherwise from CPU time, wall clock time, and the current |
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365 fraction of a second. Note that this differs from @sc{matlab}, which |
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366 always initializes the state to the same state at startup. To obtain |
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367 behavior comparable to @sc{matlab}, initialize with a deterministic state |
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368 vector in Octave's startup files (@pxref{Startup Files}). |
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369 |
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370 To compute the pseudo-random sequence, @code{rand} uses the Mersenne |
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371 Twister with a period of @math{2^{19937}-1} |
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372 (See @nospell{M. Matsumoto and T. Nishimura}, |
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373 @cite{Mersenne Twister: A 623-dimensionally equidistributed uniform |
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374 pseudorandom number generator}, |
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375 ACM Trans. on Modeling and Computer Simulation Vol. 8, No. 1, pp. 3--30, |
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376 January 1998, |
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377 @url{http://www.math.sci.hiroshima-u.ac.jp/~m-mat/MT/emt.html}). |
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378 Do @strong{not} use for cryptography without securely hashing several |
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379 returned values together, otherwise the generator state can be learned after |
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380 reading 624 consecutive values. |
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381 |
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382 Older versions of Octave used a different random number generator. |
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383 The new generator is used by default as it is significantly faster than the |
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384 old generator, and produces random numbers with a significantly longer cycle |
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385 time. However, in some circumstances it might be desirable to obtain the |
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386 same random sequences as produced by the old generators. To do this the |
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387 keyword @qcode{"seed"} is used to specify that the old generators should |
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388 be used, as in |
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389 |
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390 @example |
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391 rand ("seed", val) |
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392 @end example |
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393 |
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394 @noindent |
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395 which sets the seed of the generator to @var{val}. The seed of the |
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396 generator can be queried with |
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397 |
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398 @example |
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399 s = rand ("seed") |
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400 @end example |
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401 |
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402 However, it should be noted that querying the seed will not cause |
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403 @code{rand} to use the old generators, only setting the seed will. To cause |
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404 @code{rand} to once again use the new generators, the keyword |
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405 @qcode{"state"} should be used to reset the state of the @code{rand}. |
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406 |
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407 The state or seed of the generator can be reset to a new random value using |
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408 the @qcode{"reset"} keyword. |
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409 |
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410 The class of the value returned can be controlled by a trailing |
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411 @qcode{"double"} or @qcode{"single"} argument. These are the only valid |
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412 classes. |
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413 @seealso{randn, rande, randg, randp} |
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414 @end deftypefn */) |
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416 return do_rand (args, args.length (), "rand", "uniform"); |
2928 | 417 } |
418 | |
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419 // FIXME: The old generator (selected when "seed" is set) will not |
8871 | 420 // work properly if compiled to use 64-bit integers. |
421 | |
5730 | 422 /* |
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423 %!test # "state" can be a scalar |
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424 %! rand ("state", 12); x = rand (1,4); |
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425 %! rand ("state", 12); y = rand (1,4); |
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426 %! assert (x, y); |
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427 %!test # "state" can be a vector |
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428 %! rand ("state", [12,13]); x = rand (1,4); |
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429 %! rand ("state", [12;13]); y = rand (1,4); |
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430 %! assert (x, y); |
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431 %!test # querying "state" doesn't disturb sequence |
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432 %! rand ("state", 12); rand (1,2); x = rand (1,2); |
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433 %! rand ("state", 12); rand (1,2); |
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434 %! s = rand ("state"); y = rand (1,2); |
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435 %! assert (x, y); |
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436 %! rand ("state", s); z = rand (1,2); |
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437 %! assert (x, z); |
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438 %!test # "seed" must be a scalar |
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439 %! rand ("seed", 12); x = rand (1,4); |
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440 %! rand ("seed", 12); y = rand (1,4); |
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441 %! assert (x, y); |
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442 %!error <seed must be a real scalar> rand ("seed", [12,13]) |
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443 %!test # querying "seed" returns a value which can be used later |
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444 %! s = rand ("seed"); x = rand (1,2); |
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445 %! rand ("seed", s); y = rand (1,2); |
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446 %! assert (x, y); |
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447 %!test # querying "seed" doesn't disturb sequence |
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448 %! rand ("seed", 12); rand (1,2); x = rand (1,2); |
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449 %! rand ("seed", 12); rand (1,2); |
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450 %! s = rand ("seed"); y = rand (1,2); |
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451 %! assert (x, y); |
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452 %! rand ("seed", s); z = rand (1,2); |
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453 %! assert (x, z); |
5730 | 454 */ |
455 | |
456 /* | |
457 %!test | |
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458 %! ## Test fixed state |
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459 %! rand ("state", 1); |
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460 %! assert (rand (1,6), [0.1343642441124013 0.8474337369372327 0.763774618976614 0.2550690257394218 0.495435087091941 0.4494910647887382], 1e-6); |
6437 | 461 %!test |
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462 %! ## Test fixed seed |
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463 %! rand ("seed", 1); |
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464 %! assert (rand (1,6), [0.8668024251237512 0.9126510815694928 0.09366085007786751 0.1664607301354408 0.7408077004365623 0.7615650338120759], 1e-6); |
5730 | 465 %!test |
6437 | 466 %! if (__random_statistical_tests__) |
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467 %! ## statistical tests may fail occasionally. |
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468 %! rand ("state", 12); |
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469 %! x = rand (100000, 1); |
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470 %! assert (max (x) < 1); #*** Please report this!!! *** |
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471 %! assert (min (x) > 0); #*** Please report this!!! *** |
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472 %! assert (mean (x), 0.5, 0.0024); |
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473 %! assert (var (x), 1/48, 0.0632); |
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474 %! assert (skewness (x), 0, 0.012); |
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475 %! assert (kurtosis (x), -6/5, 0.0094); |
6437 | 476 %! endif |
477 %!test | |
478 %! if (__random_statistical_tests__) | |
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479 %! ## statistical tests may fail occasionally. |
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480 %! rand ("seed", 12); |
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481 %! x = rand (100000, 1); |
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482 %! assert (max (x) < 1); #*** Please report this!!! *** |
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483 %! assert (min (x) > 0); #*** Please report this!!! *** |
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484 %! assert (mean (x), 0.5, 0.0024); |
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485 %! assert (var (x), 1/48, 0.0632); |
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486 %! assert (skewness (x), 0, 0.012); |
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487 %! assert (kurtosis (x), -6/5, 0.0094); |
6437 | 488 %! endif |
5730 | 489 */ |
490 | |
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491 /* |
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492 %!# Test out-of-range values as rand() seeds. See oct-rand.cc: double2uint32(). |
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493 %!function v = __rand_sample__ (initval) |
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494 %! rand ("state", initval); |
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495 %! v = rand (1, 6); |
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496 %!endfunction |
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497 %! |
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498 %!assert (__rand_sample__ (0), __rand_sample__ (2^32)) |
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499 %!assert (__rand_sample__ (-2), __rand_sample__ (2^32-2)) |
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500 %!assert (__rand_sample__ (Inf), __rand_sample__ (NaN)) |
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501 %!assert (! isequal (__rand_sample__ (-1), __rand_sample__ (-2))) |
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502 */ |
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503 |
4307 | 504 static std::string current_distribution = octave_rand::distribution (); |
505 | |
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506 DEFUN (randn, args, , |
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507 doc: /* -*- texinfo -*- |
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508 @deftypefn {} {} randn (@var{n}) |
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509 @deftypefnx {} {} randn (@var{m}, @var{n}, @dots{}) |
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510 @deftypefnx {} {} randn ([@var{m} @var{n} @dots{}]) |
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511 @deftypefnx {} {@var{v} =} randn ("state") |
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512 @deftypefnx {} {} randn ("state", @var{v}) |
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513 @deftypefnx {} {} randn ("state", "reset") |
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514 @deftypefnx {} {@var{v} =} randn ("seed") |
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515 @deftypefnx {} {} randn ("seed", @var{v}) |
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516 @deftypefnx {} {} randn ("seed", "reset") |
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517 @deftypefnx {} {} randn (@dots{}, "single") |
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518 @deftypefnx {} {} randn (@dots{}, "double") |
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519 Return a matrix with normally distributed random elements having zero mean |
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520 and variance one. |
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521 |
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522 The arguments are handled the same as the arguments for @code{rand}. |
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523 |
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524 By default, @code{randn} uses the @nospell{Marsaglia and Tsang} |
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525 ``Ziggurat technique'' to transform from a uniform to a normal distribution. |
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526 |
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527 The class of the value returned can be controlled by a trailing |
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528 @qcode{"double"} or @qcode{"single"} argument. These are the only valid |
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529 classes. |
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530 |
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531 Reference: @nospell{G. Marsaglia and W.W. Tsang}, |
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532 @cite{Ziggurat Method for Generating Random Variables}, |
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533 J. Statistical Software, vol 5, 2000, |
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534 @url{http://www.jstatsoft.org/v05/i08/} |
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535 |
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536 @seealso{rand, rande, randg, randp} |
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537 @end deftypefn */) |
2928 | 538 { |
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539 return do_rand (args, args.length (), "randn", "normal"); |
2928 | 540 } |
541 | |
542 /* | |
5730 | 543 %!test |
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544 %! ## Test fixed state |
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545 %! randn ("state", 1); |
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546 %! assert (randn (1, 6), [-2.666521678978671 -0.7381719971724564 1.507903992673601 0.6019427189162239 -0.450661261143348 -0.7054431351574116], 1e-6); |
6437 | 547 %!test |
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548 %! ## Test fixed seed |
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549 %! randn ("seed", 1); |
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550 %! assert (randn (1, 6), [-1.039402365684509 -1.25938892364502 0.1968704611063004 0.3874166905879974 -0.5976632833480835 -0.6615074276924133], 1e-6); |
5730 | 551 %!test |
6437 | 552 %! if (__random_statistical_tests__) |
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553 %! ## statistical tests may fail occasionally. |
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554 %! randn ("state", 12); |
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555 %! x = randn (100000, 1); |
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556 %! assert (mean (x), 0, 0.01); |
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557 %! assert (var (x), 1, 0.02); |
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558 %! assert (skewness (x), 0, 0.02); |
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559 %! assert (kurtosis (x), 0, 0.04); |
6437 | 560 %! endif |
561 %!test | |
562 %! if (__random_statistical_tests__) | |
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563 %! ## statistical tests may fail occasionally. |
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564 %! randn ("seed", 12); |
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565 %! x = randn (100000, 1); |
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566 %! assert (mean (x), 0, 0.01); |
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567 %! assert (var (x), 1, 0.02); |
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568 %! assert (skewness (x), 0, 0.02); |
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569 %! assert (kurtosis (x), 0, 0.04); |
6437 | 570 %! endif |
5730 | 571 */ |
572 | |
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573 DEFUN (rande, args, , |
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574 doc: /* -*- texinfo -*- |
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575 @deftypefn {} {} rande (@var{n}) |
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576 @deftypefnx {} {} rande (@var{m}, @var{n}, @dots{}) |
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577 @deftypefnx {} {} rande ([@var{m} @var{n} @dots{}]) |
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578 @deftypefnx {} {@var{v} =} rande ("state") |
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579 @deftypefnx {} {} rande ("state", @var{v}) |
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580 @deftypefnx {} {} rande ("state", "reset") |
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581 @deftypefnx {} {@var{v} =} rande ("seed") |
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582 @deftypefnx {} {} rande ("seed", @var{v}) |
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583 @deftypefnx {} {} rande ("seed", "reset") |
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584 @deftypefnx {} {} rande (@dots{}, "single") |
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585 @deftypefnx {} {} rande (@dots{}, "double") |
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586 Return a matrix with exponentially distributed random elements. |
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587 |
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588 The arguments are handled the same as the arguments for @code{rand}. |
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589 |
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590 By default, @code{rande} uses the @nospell{Marsaglia and Tsang} |
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591 ``Ziggurat technique'' to transform from a uniform to an exponential |
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592 distribution. |
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593 |
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594 The class of the value returned can be controlled by a trailing |
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595 @qcode{"double"} or @qcode{"single"} argument. These are the only valid |
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596 classes. |
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597 |
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598 Reference: @nospell{G. Marsaglia and W.W. Tsang}, |
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599 @cite{Ziggurat Method for Generating Random Variables}, |
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600 J. Statistical Software, vol 5, 2000, |
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601 @url{http://www.jstatsoft.org/v05/i08/} |
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602 |
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603 @seealso{rand, randn, randg, randp} |
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604 @end deftypefn */) |
5730 | 605 { |
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606 return do_rand (args, args.length (), "rande", "exponential"); |
5730 | 607 } |
608 | |
609 /* | |
610 %!test | |
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611 %! ## Test fixed state |
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612 %! rande ("state", 1); |
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613 %! assert (rande (1, 6), [3.602973885835625 0.1386190677555021 0.6743112889616958 0.4512830847258422 0.7255744741233175 0.3415969205292291], 1e-6); |
6437 | 614 %!test |
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615 %! ## Test fixed seed |
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616 %! rande ("seed", 1); |
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617 %! assert (rande (1, 6), [0.06492075175653866 1.717980206012726 0.4816154008731246 0.5231300676241517 0.103910739364359 1.668931916356087], 1e-6); |
5730 | 618 %!test |
6437 | 619 %! if (__random_statistical_tests__) |
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620 %! ## statistical tests may fail occasionally |
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621 %! rande ("state", 1); |
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622 %! x = rande (100000, 1); |
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623 %! assert (min (x) > 0); # *** Please report this!!! *** |
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624 %! assert (mean (x), 1, 0.01); |
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625 %! assert (var (x), 1, 0.03); |
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626 %! assert (skewness (x), 2, 0.06); |
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627 %! assert (kurtosis (x), 6, 0.7); |
6437 | 628 %! endif |
629 %!test | |
630 %! if (__random_statistical_tests__) | |
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631 %! ## statistical tests may fail occasionally |
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632 %! rande ("seed", 1); |
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633 %! x = rande (100000, 1); |
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634 %! assert (min (x)>0); # *** Please report this!!! *** |
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635 %! assert (mean (x), 1, 0.01); |
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636 %! assert (var (x), 1, 0.03); |
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637 %! assert (skewness (x), 2, 0.06); |
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638 %! assert (kurtosis (x), 6, 0.7); |
6437 | 639 %! endif |
5730 | 640 */ |
641 | |
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642 DEFUN (randg, args, , |
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643 doc: /* -*- texinfo -*- |
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644 @deftypefn {} {} randg (@var{n}) |
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645 @deftypefnx {} {} randg (@var{m}, @var{n}, @dots{}) |
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646 @deftypefnx {} {} randg ([@var{m} @var{n} @dots{}]) |
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647 @deftypefnx {} {@var{v} =} randg ("state") |
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648 @deftypefnx {} {} randg ("state", @var{v}) |
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649 @deftypefnx {} {} randg ("state", "reset") |
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650 @deftypefnx {} {@var{v} =} randg ("seed") |
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651 @deftypefnx {} {} randg ("seed", @var{v}) |
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652 @deftypefnx {} {} randg ("seed", "reset") |
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653 @deftypefnx {} {} randg (@dots{}, "single") |
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654 @deftypefnx {} {} randg (@dots{}, "double") |
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655 Return a matrix with @code{gamma (@var{a},1)} distributed random elements. |
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656 |
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657 The arguments are handled the same as the arguments for @code{rand}, except |
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658 for the argument @var{a}. |
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659 |
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660 This can be used to generate many distributions: |
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661 |
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662 @table @asis |
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663 @item @code{gamma (a, b)} for @code{a > -1}, @code{b > 0} |
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664 |
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665 @example |
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666 r = b * randg (a) |
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667 @end example |
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668 |
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669 @item @code{beta (a, b)} for @code{a > -1}, @code{b > -1} |
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670 |
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671 @example |
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672 @group |
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673 r1 = randg (a, 1) |
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674 r = r1 / (r1 + randg (b, 1)) |
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675 @end group |
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676 @end example |
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677 |
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678 @item @code{Erlang (a, n)} |
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679 |
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680 @example |
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681 r = a * randg (n) |
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682 @end example |
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683 |
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684 @item @code{chisq (df)} for @code{df > 0} |
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685 |
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686 @example |
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687 r = 2 * randg (df / 2) |
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688 @end example |
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689 |
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690 @item @code{t (df)} for @code{0 < df < inf} (use randn if df is infinite) |
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691 |
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692 @example |
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693 r = randn () / sqrt (2 * randg (df / 2) / df) |
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694 @end example |
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695 |
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696 @item @code{F (n1, n2)} for @code{0 < n1}, @code{0 < n2} |
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697 |
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698 @example |
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699 @group |
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700 ## r1 equals 1 if n1 is infinite |
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701 r1 = 2 * randg (n1 / 2) / n1 |
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702 ## r2 equals 1 if n2 is infinite |
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703 r2 = 2 * randg (n2 / 2) / n2 |
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704 r = r1 / r2 |
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705 @end group |
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706 @end example |
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707 |
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708 @item negative @code{binomial (n, p)} for @code{n > 0}, @code{0 < p <= 1} |
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709 |
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710 @example |
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711 r = randp ((1 - p) / p * randg (n)) |
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712 @end example |
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713 |
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714 @item non-central @code{chisq (df, L)}, for @code{df >= 0} and @code{L > 0} |
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715 (use chisq if @code{L = 0}) |
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716 |
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717 @example |
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718 @group |
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719 r = randp (L / 2) |
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720 r(r > 0) = 2 * randg (r(r > 0)) |
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721 r(df > 0) += 2 * randg (df(df > 0)/2) |
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722 @end group |
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723 @end example |
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724 |
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725 @item @code{Dirichlet (a1, @dots{} ak)} |
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726 |
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727 @example |
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728 @group |
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729 r = (randg (a1), @dots{}, randg (ak)) |
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730 r = r / sum (r) |
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731 @end group |
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732 @end example |
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733 |
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734 @end table |
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735 |
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736 The class of the value returned can be controlled by a trailing |
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737 @qcode{"double"} or @qcode{"single"} argument. These are the only valid |
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738 classes. |
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739 @seealso{rand, randn, rande, randp} |
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740 @end deftypefn */) |
5730 | 741 { |
742 int nargin = args.length (); | |
743 | |
744 if (nargin < 1) | |
745 error ("randg: insufficient arguments"); | |
746 | |
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747 return do_rand (args, nargin, "randg", "gamma", true); |
5730 | 748 } |
749 | |
750 /* | |
751 %!test | |
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752 %! randg ("state", 12); |
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753 %! assert (randg ([-inf, -1, 0, inf, nan]), [nan, nan, nan, nan, nan]); # *** Please report |
6437 | 754 |
755 %!test | |
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756 %! ## Test fixed state |
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757 %! randg ("state", 1); |
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758 %! assert (randg (0.1, 1, 6), [0.0103951513331241 8.335671459898252e-05 0.00138691397249762 0.000587308416993855 0.495590518784736 2.3921917414795e-12], 1e-6); |
6437 | 759 %!test |
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760 %! ## Test fixed state |
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761 %! randg ("state", 1); |
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762 %! assert (randg (0.95, 1, 6), [3.099382433255327 0.3974529788871218 0.644367450750855 1.143261091802246 1.964111762696822 0.04011915547957939], 1e-6); |
6437 | 763 %!test |
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764 %! ## Test fixed state |
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765 %! randg ("state", 1); |
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766 %! assert (randg (1, 1, 6), [0.2273389379645993 1.288822625058359 0.2406335209340746 1.218869553370733 1.024649860162554 0.09631230343599533], 1e-6); |
6437 | 767 %!test |
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768 %! ## Test fixed state |
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769 %! randg ("state", 1); |
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770 %! assert (randg (10, 1, 6), [3.520369644331133 15.15369864472106 8.332112081991205 8.406211067432674 11.81193475187611 10.88792728177059], 1e-5); |
6437 | 771 %!test |
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772 %! ## Test fixed state |
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773 %! randg ("state", 1); |
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774 %! assert (randg (100, 1, 6), [75.34570255262264 115.4911985594699 95.23493031356388 95.48926019250911 106.2397448229803 103.4813150404118], 1e-4); |
6437 | 775 %!test |
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776 %! ## Test fixed seed |
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777 %! randg ("seed", 1); |
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778 %! assert (randg (0.1, 1, 6), [0.07144210487604141 0.460641473531723 0.4749028384685516 0.06823389977216721 0.000293838675133884 1.802567535340305e-12], 1e-6); |
6437 | 779 %!test |
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780 %! ## Test fixed seed |
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781 %! randg ("seed", 1); |
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782 %! assert (randg (0.95, 1, 6), [1.664905071258545 1.879976987838745 1.905677795410156 0.9948706030845642 0.5606933236122131 0.0766092911362648], 1e-6); |
6437 | 783 %!test |
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784 %! ## Test fixed seed |
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785 %! randg ("seed", 1); |
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786 %! assert (randg (1, 1, 6), [0.03512085229158401 0.6488978862762451 0.8114678859710693 0.1666885763406754 1.60791552066803 1.90356981754303], 1e-6); |
6437 | 787 %!test |
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788 %! ## Test fixed seed |
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789 %! randg ("seed", 1); |
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790 %! assert (randg (10, 1, 6), [6.566435813903809 10.11648464202881 10.73162078857422 7.747178077697754 6.278522491455078 6.240195751190186], 1e-5); |
6437 | 791 %!test |
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792 %! ## Test fixed seed |
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793 %! randg ("seed", 1); |
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794 %! assert (randg (100, 1, 6), [89.40208435058594 101.4734725952148 103.4020004272461 93.62763214111328 88.33104705810547 88.1871337890625], 1e-4); |
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795 %!test |
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796 %! ## Test out-of-bounds values produce NaN w/old-style generators & floats |
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797 %! randg ("seed", 1); |
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798 %! result = randg ([-2 Inf], "single"); |
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799 %! assert (result, single ([NaN NaN])); |
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800 |
6437 | 801 %!test |
802 %! if (__random_statistical_tests__) | |
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803 %! ## statistical tests may fail occasionally. |
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804 %! randg ("state", 12); |
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805 %! a = 0.1; |
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806 %! x = randg (a, 100000, 1); |
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807 %! assert (mean (x), a, 0.01); |
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808 %! assert (var (x), a, 0.01); |
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809 %! assert (skewness (x), 2/sqrt (a), 1); |
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810 %! assert (kurtosis (x), 6/a, 50); |
6437 | 811 %! endif |
812 %!test | |
813 %! if (__random_statistical_tests__) | |
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814 %! ## statistical tests may fail occasionally. |
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815 %! randg ("state", 12); |
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816 %! a = 0.95; |
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817 %! x = randg (a, 100000, 1); |
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818 %! assert (mean (x), a, 0.01); |
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819 %! assert (var (x), a, 0.04); |
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820 %! assert (skewness (x), 2/sqrt (a), 0.2); |
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821 %! assert (kurtosis (x), 6/a, 2); |
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822 %! endif |
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823 %!test |
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824 %! if (__random_statistical_tests__) |
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825 %! ## statistical tests may fail occasionally. |
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826 %! randg ("state", 12); |
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827 %! a = 1; |
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828 %! x = randg (a, 100000, 1); |
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829 %! assert (mean (x), a, 0.01); |
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830 %! assert (var (x), a, 0.04); |
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831 %! assert (skewness (x), 2/sqrt (a), 0.2); |
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832 %! assert (kurtosis (x), 6/a, 2); |
6437 | 833 %! endif |
834 %!test | |
835 %! if (__random_statistical_tests__) | |
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836 %! ## statistical tests may fail occasionally. |
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837 %! randg ("state", 12); |
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838 %! a = 10; |
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839 %! x = randg (a, 100000, 1); |
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840 %! assert (mean (x), a, 0.1); |
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841 %! assert (var (x), a, 0.5); |
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842 %! assert (skewness (x), 2/sqrt (a), 0.1); |
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843 %! assert (kurtosis (x), 6/a, 0.5); |
6437 | 844 %! endif |
845 %!test | |
846 %! if (__random_statistical_tests__) | |
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847 %! ## statistical tests may fail occasionally. |
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848 %! randg ("state", 12); |
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849 %! a = 100; |
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850 %! x = randg (a, 100000, 1); |
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851 %! assert (mean (x), a, 0.2); |
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852 %! assert (var (x), a, 2); |
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853 %! assert (skewness (x), 2/sqrt (a), 0.05); |
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854 %! assert (kurtosis (x), 6/a, 0.2); |
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855 %! endif |
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856 %!test |
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857 %! randg ("seed", 12); |
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858 %!assert (randg ([-inf, -1, 0, inf, nan]), [nan, nan, nan, nan, nan]) # *** Please report |
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859 %!test |
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860 %! if (__random_statistical_tests__) |
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861 %! ## statistical tests may fail occasionally. |
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862 %! randg ("seed", 12); |
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863 %! a = 0.1; |
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864 %! x = randg (a, 100000, 1); |
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865 %! assert (mean (x), a, 0.01); |
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866 %! assert (var (x), a, 0.01); |
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867 %! assert (skewness (x), 2/sqrt (a), 1); |
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868 %! assert (kurtosis (x), 6/a, 50); |
6437 | 869 %! endif |
870 %!test | |
871 %! if (__random_statistical_tests__) | |
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872 %! ## statistical tests may fail occasionally. |
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873 %! randg ("seed", 12); |
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874 %! a = 0.95; |
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875 %! x = randg (a, 100000, 1); |
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876 %! assert (mean (x), a, 0.01); |
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877 %! assert (var (x), a, 0.04); |
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878 %! assert (skewness (x), 2/sqrt (a), 0.2); |
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879 %! assert (kurtosis (x), 6/a, 2); |
6437 | 880 %! endif |
881 %!test | |
882 %! if (__random_statistical_tests__) | |
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883 %! ## statistical tests may fail occasionally. |
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884 %! randg ("seed", 12); |
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885 %! a = 1; |
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886 %! x = randg (a, 100000, 1); |
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887 %! assert (mean (x), a, 0.01); |
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888 %! assert (var (x), a, 0.04); |
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889 %! assert (skewness (x), 2/sqrt (a), 0.2); |
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890 %! assert (kurtosis (x), 6/a, 2); |
6437 | 891 %! endif |
5730 | 892 %!test |
6437 | 893 %! if (__random_statistical_tests__) |
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894 %! ## statistical tests may fail occasionally. |
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895 %! randg ("seed", 12); |
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896 %! a = 10; |
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897 %! x = randg (a, 100000, 1); |
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898 %! assert (mean (x), a, 0.1); |
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899 %! assert (var (x), a, 0.5); |
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900 %! assert (skewness (x), 2/sqrt (a), 0.1); |
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901 %! assert (kurtosis (x), 6/a, 0.5); |
6437 | 902 %! endif |
5730 | 903 %!test |
6437 | 904 %! if (__random_statistical_tests__) |
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905 %! ## statistical tests may fail occasionally. |
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906 %! randg ("seed", 12); |
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907 %! a = 100; |
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908 %! x = randg (a, 100000, 1); |
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909 %! assert (mean (x), a, 0.2); |
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910 %! assert (var (x), a, 2); |
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911 %! assert (skewness (x), 2/sqrt (a), 0.05); |
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912 %! assert (kurtosis (x), 6/a, 0.2); |
6437 | 913 %! endif |
5730 | 914 */ |
915 | |
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916 DEFUN (randp, args, , |
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917 doc: /* -*- texinfo -*- |
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918 @deftypefn {} {} randp (@var{l}, @var{n}) |
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919 @deftypefnx {} {} randp (@var{l}, @var{m}, @var{n}, @dots{}) |
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920 @deftypefnx {} {} randp (@var{l}, [@var{m} @var{n} @dots{}]) |
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921 @deftypefnx {} {@var{v} =} randp ("state") |
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922 @deftypefnx {} {} randp ("state", @var{v}) |
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923 @deftypefnx {} {} randp ("state", "reset") |
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924 @deftypefnx {} {@var{v} =} randp ("seed") |
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925 @deftypefnx {} {} randp ("seed", @var{v}) |
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926 @deftypefnx {} {} randp ("seed", "reset") |
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927 @deftypefnx {} {} randp (@dots{}, "single") |
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928 @deftypefnx {} {} randp (@dots{}, "double") |
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929 Return a matrix with Poisson distributed random elements with mean value |
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930 parameter given by the first argument, @var{l}. |
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931 |
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932 The arguments are handled the same as the arguments for @code{rand}, except |
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933 for the argument @var{l}. |
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934 |
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935 Five different algorithms are used depending on the range of @var{l} and |
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936 whether or not @var{l} is a scalar or a matrix. |
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937 |
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938 @table @asis |
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939 @item For scalar @var{l} @leq{} 12, use direct method. |
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940 W.H. Press, et al., @cite{Numerical Recipes in C}, |
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941 Cambridge University Press, 1992. |
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942 |
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943 @item For scalar @var{l} > 12, use rejection method.[1] |
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944 W.H. Press, et al., @cite{Numerical Recipes in C}, |
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945 Cambridge University Press, 1992. |
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946 |
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947 @item For matrix @var{l} @leq{} 10, use inversion method.[2] |
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948 @nospell{E. Stadlober, et al., WinRand source code}, available via FTP. |
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949 |
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950 @item For matrix @var{l} > 10, use patchwork rejection method. |
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951 @nospell{E. Stadlober, et al., WinRand source code}, available via FTP, or |
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952 @nospell{H. Zechner}, @cite{Efficient sampling from continuous and discrete |
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953 unimodal distributions}, Doctoral Dissertation, 156pp., Technical |
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954 University @nospell{Graz}, Austria, 1994. |
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955 |
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956 @item For @var{l} > 1e8, use normal approximation. |
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957 @nospell{L. Montanet}, et al., @cite{Review of Particle Properties}, |
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958 Physical Review D 50 p1284, 1994. |
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959 @end table |
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960 |
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961 The class of the value returned can be controlled by a trailing |
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962 @qcode{"double"} or @qcode{"single"} argument. These are the only valid |
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963 classes. |
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964 @seealso{rand, randn, rande, randg} |
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965 @end deftypefn */) |
5730 | 966 { |
967 int nargin = args.length (); | |
968 | |
969 if (nargin < 1) | |
970 error ("randp: insufficient arguments"); | |
971 | |
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972 return do_rand (args, nargin, "randp", "poisson", true); |
5730 | 973 } |
974 | |
975 /* | |
976 %!test | |
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977 %! randp ("state", 12); |
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978 %! assert (randp ([-inf, -1, 0, inf, nan]), [nan, nan, 0, nan, nan]); # *** Please report |
6437 | 979 %!test |
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980 %! ## Test fixed state |
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981 %! randp ("state", 1); |
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982 %! assert (randp (5, 1, 6), [5 5 3 7 7 3]); |
6437 | 983 %!test |
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984 %! ## Test fixed state |
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985 %! randp ("state", 1); |
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986 %! assert (randp (15, 1, 6), [13 15 8 18 18 15]); |
6437 | 987 %!test |
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988 %! ## Test fixed state |
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989 %! randp ("state", 1); |
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990 %! assert (randp (1e9, 1, 6), [999915677 999976657 1000047684 1000019035 999985749 999977692], -1e-6); |
6437 | 991 %!test |
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992 %! ## Test fixed state |
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993 %! randp ("seed", 1); |
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994 %! %%assert (randp (5, 1, 6), [8 2 3 6 6 8]) |
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995 %! assert (randp (5, 1, 5), [8 2 3 6 6]); |
6437 | 996 %!test |
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997 %! ## Test fixed state |
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998 %! randp ("seed", 1); |
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999 %! assert (randp (15, 1, 6), [15 16 12 10 10 12]); |
6437 | 1000 %!test |
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1001 %! ## Test fixed state |
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1002 %! randp ("seed", 1); |
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1003 %! assert (randp (1e9, 1, 6), [1000006208 1000012224 999981120 999963520 999963072 999981440], -1e-6); |
6437 | 1004 %!test |
1005 %! if (__random_statistical_tests__) | |
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1006 %! ## statistical tests may fail occasionally. |
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1007 %! randp ("state", 12); |
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1008 %! for a = [5, 15, 1e9; 0.03, 0.03, -5e-3; 0.03, 0.03, 0.03] |
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1009 %! x = randp (a (1), 100000, 1); |
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1010 %! assert (min (x) >= 0); # *** Please report this!!! *** |
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1011 %! assert (mean (x), a(1), a(2)); |
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1012 %! assert (var (x), a(1), 0.02*a(1)); |
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1013 %! assert (skewness (x), 1/sqrt (a(1)), a(3)); |
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1014 %! assert (kurtosis (x), 1/a(1), 3*a(3)); |
6437 | 1015 %! endfor |
1016 %! endif | |
1017 %!test | |
1018 %! if (__random_statistical_tests__) | |
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1019 %! ## statistical tests may fail occasionally. |
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1020 %! randp ("state", 12); |
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1021 %! for a = [5, 15, 1e9; 0.03, 0.03, -5e-3; 0.03, 0.03, 0.03] |
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1022 %! x = randp (a(1)*ones (100000, 1), 100000, 1); |
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1023 %! assert (min (x) >= 0); # *** Please report this!!! *** |
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1024 %! assert (mean (x), a(1), a(2)); |
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1025 %! assert (var (x), a(1), 0.02*a(1)); |
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1026 %! assert (skewness (x), 1/sqrt (a(1)), a(3)); |
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1027 %! assert (kurtosis (x), 1/a(1), 3*a(3)); |
6437 | 1028 %! endfor |
1029 %! endif | |
1030 %!test | |
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1031 %! randp ("seed", 12); |
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1032 %! assert (randp ([-inf, -1, 0, inf, nan]), [nan, nan, 0, nan, nan]); # *** Please report |
5730 | 1033 %!test |
6449 | 1034 %! if (__random_statistical_tests__) |
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1035 %! ## statistical tests may fail occasionally. |
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1036 %! randp ("seed", 12); |
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1037 %! for a = [5, 15, 1e9; 0.03, 0.03, -5e-3; 0.03, 0.03, 0.03] |
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1038 %! x = randp (a(1), 100000, 1); |
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1039 %! assert (min (x) >= 0); # *** Please report this!!! *** |
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1040 %! assert (mean (x), a(1), a(2)); |
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1041 %! assert (var (x), a(1), 0.02*a(1)); |
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1042 %! assert (skewness (x), 1/sqrt (a(1)), a(3)); |
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1043 %! assert (kurtosis (x), 1/a(1), 3*a(3)); |
6449 | 1044 %! endfor |
1045 %! endif | |
5730 | 1046 %!test |
6449 | 1047 %! if (__random_statistical_tests__) |
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1048 %! ## statistical tests may fail occasionally. |
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1049 %! randp ("seed", 12); |
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1050 %! for a = [5, 15, 1e9; 0.03, 0.03, -5e-3; 0.03, 0.03, 0.03] |
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1051 %! x = randp (a(1)*ones (100000, 1), 100000, 1); |
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1052 %! assert (min (x) >= 0); # *** Please report this!!! *** |
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1053 %! assert (mean (x), a(1), a(2)); |
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1054 %! assert (var (x), a(1), 0.02*a(1)); |
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1055 %! assert (skewness (x), 1/sqrt (a(1)), a(3)); |
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1056 %! assert (kurtosis (x), 1/a(1), 3*a(3)); |
6449 | 1057 %! endfor |
1058 %! endif | |
5730 | 1059 */ |
1060 | |
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1061 DEFUN (randperm, args, , |
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1062 doc: /* -*- texinfo -*- |
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1063 @deftypefn {} {} randperm (@var{n}) |
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1064 @deftypefnx {} {} randperm (@var{n}, @var{m}) |
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1065 Return a row vector containing a random permutation of @code{1:@var{n}}. |
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1066 |
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1067 If @var{m} is supplied, return @var{m} unique entries, sampled without |
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1068 replacement from @code{1:@var{n}}. |
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1069 |
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1070 The complexity is O(@var{n}) in memory and O(@var{m}) in time, unless |
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1071 @var{m} < @var{n}/5, in which case O(@var{m}) memory is used as well. The |
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1072 randomization is performed using rand(). All permutations are equally |
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1073 likely. |
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1074 @seealso{perms} |
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1075 @end deftypefn */) |
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1076 { |
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1077 int nargin = args.length (); |
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1078 |
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1079 if (nargin < 1 || nargin > 2) |
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1080 print_usage (); |
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1081 |
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1082 octave_idx_type n = args(0).idx_type_value (true); |
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1083 octave_idx_type m = (nargin == 2) ? args(1).idx_type_value (true) : n; |
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1084 |
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1085 if (m < 0 || n < 0) |
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1086 error ("randperm: M and N must be non-negative"); |
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1087 |
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1088 if (m > n) |
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1089 error ("randperm: M must be less than or equal to N"); |
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1090 |
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1091 // Quick and dirty heuristic to decide if we allocate or not the |
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1092 // whole vector for tracking the truncated shuffle. |
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1093 bool short_shuffle = m < n/5; |
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1094 |
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1095 // Generate random numbers. |
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1096 NDArray r = octave_rand::nd_array (dim_vector (1, m)); |
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1097 double *rvec = r.fortran_vec (); |
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1098 |
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1099 octave_idx_type idx_len = short_shuffle ? m : n; |
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1100 Array<octave_idx_type> idx; |
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1101 try |
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1102 { |
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1103 idx = Array<octave_idx_type> (dim_vector (1, idx_len)); |
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1104 } |
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1105 catch (const std::bad_alloc&) |
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1106 { |
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1107 // Looks like n is too big and short_shuffle is false. |
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1108 // Let's try again, but this time with the alternative. |
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1109 idx_len = m; |
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1110 short_shuffle = true; |
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1111 idx = Array<octave_idx_type> (dim_vector (1, idx_len)); |
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1112 } |
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1113 |
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1114 octave_idx_type *ivec = idx.fortran_vec (); |
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1115 |
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1116 for (octave_idx_type i = 0; i < idx_len; i++) |
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1117 ivec[i] = i; |
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1118 |
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1119 if (short_shuffle) |
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1120 { |
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1121 std::unordered_map<octave_idx_type, octave_idx_type> map (m); |
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1122 |
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1123 // Perform the Knuth shuffle only keeping track of moved |
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1124 // entries in the map |
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1125 for (octave_idx_type i = 0; i < m; i++) |
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1126 { |
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1127 octave_idx_type k = i + |
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1128 std::floor (rvec[i] * (n - i)); |
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1129 |
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1130 // For shuffling first m entries, no need to use extra |
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1131 // storage |
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1132 if (k < m) |
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1133 { |
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1134 std::swap (ivec[i], ivec[k]); |
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1135 } |
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1136 else |
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1137 { |
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1138 if (map.find (k) == map.end ()) |
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1139 map[k] = k; |
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1140 |
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1141 std::swap (ivec[i], map[k]); |
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1142 } |
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1143 } |
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1144 } |
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1145 else |
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1146 { |
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1147 // Perform the Knuth shuffle of the first m entries |
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1148 for (octave_idx_type i = 0; i < m; i++) |
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1149 { |
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1150 octave_idx_type k = i + |
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1151 std::floor (rvec[i] * (n - i)); |
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1152 std::swap (ivec[i], ivec[k]); |
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1153 } |
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1154 } |
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1155 |
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1156 // Convert to doubles, reusing r. |
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1157 for (octave_idx_type i = 0; i < m; i++) |
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1158 rvec[i] = ivec[i] + 1; |
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1159 |
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1160 if (m < n) |
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1161 idx.resize (dim_vector (1, m)); |
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1162 |
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1163 // Now create an array object with a cached idx_vector. |
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1164 return ovl (new octave_matrix (r, idx_vector (idx))); |
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1165 } |
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1166 |
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1167 /* |
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1168 %!assert (sort (randperm (20)), 1:20) |
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1169 %!assert (length (randperm (20,10)), 10) |
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1170 |
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1171 ## Test biggish N (bug #39378) |
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1172 %!assert (length (randperm (30000^2, 100000)), 100000) |
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1173 |
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1174 %!test |
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1175 %! rand ("seed", 0); |
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1176 %! for i = 1:100 |
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1177 %! p = randperm (305, 30); |
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1178 %! assert (length (unique (p)), 30); |
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1179 %! endfor |
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1180 */ |