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1 /* |
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2 A C-program for MT19937, with initialization improved 2002/2/10. |
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3 Coded by Takuji Nishimura and Makoto Matsumoto. |
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4 This is a faster version by taking Shawn Cokus's optimization, |
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5 Matthe Bellew's simplification, Isaku Wada's real version. |
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6 David Bateman added normal and exponential distributions following |
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7 Marsaglia and Tang's Ziggurat algorithm. |
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8 |
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9 Copyright (C) 1997 - 2002, Makoto Matsumoto and Takuji Nishimura, |
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10 Copyright (C) 2004, David Bateman |
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11 All rights reserved. |
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12 |
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13 Redistribution and use in source and binary forms, with or without |
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14 modification, are permitted provided that the following conditions |
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15 are met: |
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16 |
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17 1. Redistributions of source code must retain the above copyright |
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18 notice, this list of conditions and the following disclaimer. |
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19 |
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20 2. Redistributions in binary form must reproduce the above copyright |
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21 notice, this list of conditions and the following disclaimer in the |
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22 documentation and/or other materials provided with the distribution. |
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23 |
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24 3. The names of its contributors may not be used to endorse or promote |
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25 products derived from this software without specific prior written |
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26 permission. |
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27 |
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28 THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS |
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29 "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT |
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30 LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR |
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31 A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER |
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32 OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, |
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33 EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, |
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34 PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR |
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35 PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF |
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36 LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING |
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37 NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS |
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38 SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. |
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39 |
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40 |
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41 Any feedback is very welcome. |
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42 http://www.math.keio.ac.jp/matumoto/emt.html |
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43 email: matumoto@math.keio.ac.jp |
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44 |
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45 * 2006-04-01 David Bateman |
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46 * * convert for use in octave, declaring static functions only used |
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47 * here and adding oct_ to functions visible externally |
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48 * * inverse sense of ALLBITS |
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49 * 2004-01-19 Paul Kienzle |
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50 * * comment out main |
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51 * add init_by_entropy, get_state, set_state |
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52 * * converted to allow compiling by C++ compiler |
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53 * |
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54 * 2004-01-25 David Bateman |
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55 * * Add Marsaglia and Tsang Ziggurat code |
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56 * |
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57 * 2004-07-13 Paul Kienzle |
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58 * * make into an independent library with some docs. |
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59 * * introduce new main and test code. |
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60 * |
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61 * 2004-07-28 Paul Kienzle & David Bateman |
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62 * * add -DALLBITS flag for 32 vs. 53 bits of randomness in mantissa |
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63 * * make the naming scheme more uniform |
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64 * * add -DHAVE_X86 for faster support of 53 bit mantissa on x86 arch. |
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65 * |
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66 * 2005-02-23 Paul Kienzle |
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67 * * fix -DHAVE_X86_32 flag and add -DUSE_X86_32=0|1 for explicit control |
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68 */ |
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69 |
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70 /* |
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71 === Build instructions === |
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72 |
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73 Compile with -DHAVE_GETTIMEOFDAY if the gettimeofday function is |
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74 available. This is not necessary if your architecture has |
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75 /dev/urandom defined. |
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76 |
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77 Compile with -DALLBITS to disable 53-bit random numbers. This is about |
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78 50% slower than using 32-bit random numbers. |
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79 |
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80 Uses implicit -Di386 or explicit -DHAVE_X86_32 to determine if CPU=x86. |
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81 You can force X86 behaviour with -DUSE_X86_32=1, or suppress it with |
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82 -DUSE_X86_32=0. You should also consider -march=i686 or similar for |
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83 extra performance. Check whether -DUSE_X86_32=0 is faster on 64-bit |
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84 x86 architectures. |
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85 |
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86 If you want to replace the Mersenne Twister with another |
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87 generator then redefine randi32 appropriately. |
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88 |
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89 === Usage instructions === |
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90 Before using any of the generators, initialize the state with one of |
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91 oct_init_by_int, oct_init_by_array or oct_init_by_entropy. |
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92 |
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93 All generators share the same state vector. |
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94 |
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95 === Mersenne Twister === |
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96 void oct_init_by_int(uint32_t s) 32-bit initial state |
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97 void oct_init_by_array(uint32_t k[],int m) m*32-bit initial state |
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98 void oct_init_by_entropy(void) random initial state |
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99 void oct_get_state(uint32_t save[MT_N+1]) saves state in array |
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100 void oct_set_state(uint32_t save[MT_N+1]) restores state from array |
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101 static uint32_t randmt(void) returns 32-bit unsigned int |
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102 |
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103 === inline generators === |
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104 static uint32_t randi32(void) returns 32-bit unsigned int |
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105 static uint64_t randi53(void) returns 53-bit unsigned int |
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106 static uint64_t randi54(void) returns 54-bit unsigned int |
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107 static uint64_t randi64(void) returns 64-bit unsigned int |
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108 static double randu32(void) returns 32-bit uniform in (0,1) |
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109 static double randu53(void) returns 53-bit uniform in (0,1) |
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110 |
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111 double oct_randu(void) returns M-bit uniform in (0,1) |
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112 double oct_randn(void) returns M-bit standard normal |
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113 double oct_rande(void) returns N-bit standard exponential |
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114 |
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115 === Array generators === |
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116 void oct_fill_randi32(octave_idx_type, uint32_t []) |
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117 void oct_fill_randi64(octave_idx_type, uint64_t []) |
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118 void oct_fill_randu(octave_idx_type, double []) |
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119 void oct_fill_randn(octave_idx_type, double []) |
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120 void oct_fill_rande(octave_idx_type, double []) |
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121 |
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122 */ |
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123 |
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124 #if defined (HAVE_CONFIG_H) |
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125 #include <config.h> |
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126 #endif |
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127 |
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128 #include <math.h> |
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129 #include <stdio.h> |
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130 #include <time.h> |
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131 |
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132 #ifdef HAVE_GETTIMEOFDAY |
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133 #include <sys/time.h> |
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134 #endif |
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135 |
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136 #include "randmtzig.h" |
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137 |
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138 /* XXX FIXME XXX may want to suppress X86 if sizeof(long)>4 */ |
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139 #if !defined(USE_X86_32) |
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140 # if defined(i386) || defined(HAVE_X86_32) |
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141 # define USE_X86_32 1 |
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142 # else |
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143 # define USE_X86_32 0 |
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144 # endif |
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145 #endif |
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146 |
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147 /* ===== Mersenne Twister 32-bit generator ===== */ |
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148 |
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149 #define MT_M 397 |
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150 #define MATRIX_A 0x9908b0dfUL /* constant vector a */ |
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151 #define UMASK 0x80000000UL /* most significant w-r bits */ |
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152 #define LMASK 0x7fffffffUL /* least significant r bits */ |
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153 #define MIXBITS(u,v) ( ((u) & UMASK) | ((v) & LMASK) ) |
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154 #define TWIST(u,v) ((MIXBITS(u,v) >> 1) ^ ((v)&1UL ? MATRIX_A : 0UL)) |
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155 |
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156 static uint32_t *next; |
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157 static uint32_t state[MT_N]; /* the array for the state vector */ |
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158 static int left = 1; |
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159 static int initf = 0; |
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160 static int initt = 1; |
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161 |
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162 /* initializes state[MT_N] with a seed */ |
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163 void |
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164 oct_init_by_int (uint32_t s) |
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165 { |
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166 int j; |
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167 state[0] = s & 0xffffffffUL; |
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168 for (j = 1; j < MT_N; j++) { |
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169 state[j] = (1812433253UL * (state[j-1] ^ (state[j-1] >> 30)) + j); |
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170 /* See Knuth TAOCP Vol2. 3rd Ed. P.106 for multiplier. */ |
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171 /* In the previous versions, MSBs of the seed affect */ |
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172 /* only MSBs of the array state[]. */ |
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173 /* 2002/01/09 modified by Makoto Matsumoto */ |
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174 state[j] &= 0xffffffffUL; /* for >32 bit machines */ |
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175 } |
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176 left = 1; |
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177 initf = 1; |
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178 } |
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179 |
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180 /* initialize by an array with array-length */ |
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181 /* init_key is the array for initializing keys */ |
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182 /* key_length is its length */ |
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183 void |
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184 oct_init_by_array (uint32_t init_key[], int key_length) |
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185 { |
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186 int i, j, k; |
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187 oct_init_by_int (19650218UL); |
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188 i = 1; |
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189 j = 0; |
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190 k = (MT_N > key_length ? MT_N : key_length); |
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191 for (; k; k--) |
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192 { |
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193 state[i] = (state[i] ^ ((state[i-1] ^ (state[i-1] >> 30)) * 1664525UL)) |
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194 + init_key[j] + j; /* non linear */ |
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195 state[i] &= 0xffffffffUL; /* for WORDSIZE > 32 machines */ |
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196 i++; |
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197 j++; |
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198 if (i >= MT_N) |
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199 { |
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200 state[0] = state[MT_N-1]; |
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201 i = 1; |
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202 } |
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203 if (j >= key_length) |
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204 j = 0; |
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205 } |
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206 for (k = MT_N - 1; k; k--) |
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207 { |
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208 state[i] = (state[i] ^ ((state[i-1] ^ (state[i-1] >> 30)) * 1566083941UL)) |
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209 - i; /* non linear */ |
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210 state[i] &= 0xffffffffUL; /* for WORDSIZE > 32 machines */ |
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211 i++; |
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212 if (i >= MT_N) |
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213 { |
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214 state[0] = state[MT_N-1]; |
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215 i = 1; |
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216 } |
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217 } |
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218 |
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219 state[0] = 0x80000000UL; /* MSB is 1; assuring non-zero initial array */ |
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220 left = 1; |
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221 initf = 1; |
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222 } |
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223 |
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224 void |
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225 oct_init_by_entropy (void) |
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226 { |
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227 uint32_t entropy[MT_N]; |
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228 int n = 0; |
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229 |
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230 /* Look for entropy in /dev/urandom */ |
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231 FILE* urandom =fopen("/dev/urandom", "rb"); |
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232 if (urandom) |
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233 { |
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234 while (n < MT_N) |
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235 { |
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236 unsigned char word[4]; |
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237 if (fread(word, 4, 1, urandom) != 1) |
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238 break; |
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239 entropy[n++] = word[0]+(word[1]<<8)+(word[2]<<16)+(word[3]<<24); |
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240 } |
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241 fclose(urandom); |
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242 } |
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243 |
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244 /* If there isn't enough entropy, gather some from various sources */ |
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245 if (n < MT_N) |
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246 entropy[n++] = time(NULL); /* Current time in seconds */ |
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247 if (n < MT_N) |
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248 entropy[n++] = clock(); /* CPU time used (usec) */ |
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249 #ifdef HAVE_GETTIMEOFDAY |
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250 if (n < MT_N) |
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251 { |
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252 struct timeval tv; |
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253 if (gettimeofday(&tv, NULL) != -1) |
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254 entropy[n++] = tv.tv_usec; /* Fractional part of current time */ |
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255 } |
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256 #endif |
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257 /* Send all the entropy into the initial state vector */ |
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258 oct_init_by_array(entropy,n); |
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259 } |
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260 |
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261 void |
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262 oct_set_state (uint32_t save[]) |
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263 { |
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264 int i; |
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265 for (i=0; i < MT_N; i++) |
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266 state[i] = save[i]; |
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267 left = save[MT_N]; |
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268 next = state + (MT_N - left + 1); |
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269 } |
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270 |
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271 void |
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272 oct_get_state (uint32_t save[]) |
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273 { |
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274 int i; |
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275 for (i = 0; i < MT_N; i++) |
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276 save[i] = state[i]; |
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277 save[MT_N] = left; |
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278 } |
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279 |
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280 static void |
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281 next_state (void) |
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282 { |
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283 uint32_t *p = state; |
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284 int j; |
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285 |
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286 /* if init_by_int() has not been called, */ |
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287 /* a default initial seed is used */ |
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288 /* if (initf==0) init_by_int(5489UL); */ |
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289 /* Or better yet, a random seed! */ |
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290 if (initf == 0) |
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291 oct_init_by_entropy(); |
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292 |
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293 left = MT_N; |
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294 next = state; |
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295 |
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296 for (j = MT_N - MT_M + 1; --j; p++) |
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297 *p = p[MT_M] ^ TWIST(p[0], p[1]); |
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298 |
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299 for (j = MT_M; --j; p++) |
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300 *p = p[MT_M-MT_N] ^ TWIST(p[0], p[1]); |
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301 |
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302 *p = p[MT_M-MT_N] ^ TWIST(p[0], state[0]); |
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303 } |
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304 |
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305 /* generates a random number on [0,0xffffffff]-interval */ |
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306 static uint32_t |
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307 randmt (void) |
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308 { |
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309 register uint32_t y; |
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310 |
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311 if (--left == 0) |
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312 next_state(); |
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313 y = *next++; |
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314 |
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315 /* Tempering */ |
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316 y ^= (y >> 11); |
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317 y ^= (y << 7) & 0x9d2c5680UL; |
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318 y ^= (y << 15) & 0xefc60000UL; |
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319 return (y ^ (y >> 18)); |
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320 } |
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321 |
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322 /* ===== Uniform generators ===== */ |
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323 |
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324 /* Select which 32 bit generator to use */ |
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325 #define randi32 randmt |
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326 |
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327 static uint64_t |
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328 randi53 (void) |
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329 { |
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330 const uint32_t lo = randi32(); |
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331 const uint32_t hi = randi32()&0x1FFFFF; |
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332 #if HAVE_X86_32 |
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333 uint64_t u; |
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334 uint32_t *p = (uint32_t *)&u; |
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335 p[0] = lo; |
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336 p[1] = hi; |
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337 return u; |
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338 #else |
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339 return (((uint64_t)hi<<32)|lo); |
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340 #endif |
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341 } |
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342 |
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343 static uint64_t |
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344 randi54 (void) |
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345 { |
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346 const uint32_t lo = randi32(); |
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347 const uint32_t hi = randi32()&0x3FFFFF; |
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348 #if HAVE_X86_32 |
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349 uint64_t u; |
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350 uint32_t *p = (uint32_t *)&u; |
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351 p[0] = lo; |
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352 p[1] = hi; |
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353 return u; |
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354 #else |
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355 return (((uint64_t)hi<<32)|lo); |
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356 #endif |
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357 } |
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358 |
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359 static uint64_t |
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360 randi64 (void) |
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361 { |
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362 const uint32_t lo = randi32(); |
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363 const uint32_t hi = randi32(); |
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364 #if HAVE_X86_32 |
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365 uint64_t u; |
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366 uint32_t *p = (uint32_t *)&u; |
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367 p[0] = lo; |
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368 p[1] = hi; |
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369 return u; |
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370 #else |
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371 return (((uint64_t)hi<<32)|lo); |
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372 #endif |
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373 } |
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374 |
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375 /* generates a random number on (0,1)-real-interval */ |
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376 static double |
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377 randu32 (void) |
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378 { |
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379 return ((double)randi32() + 0.5) * (1.0/4294967296.0); |
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380 /* divided by 2^32 */ |
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381 } |
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382 |
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383 /* generates a random number on (0,1) with 53-bit resolution */ |
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384 static double |
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385 randu53 (void) |
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386 { |
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387 const uint32_t a=randi32()>>5; |
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388 const uint32_t b=randi32()>>6; |
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389 return(a*67108864.0+b+0.4) * (1.0/9007199254740992.0); |
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390 } |
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391 |
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392 /* Determine mantissa for uniform doubles */ |
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393 #ifdef ALLBITS |
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394 double |
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395 oct_randu (void) |
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396 { |
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397 return randu32(); |
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398 } |
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399 #else |
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400 double |
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401 oct_randu (void) |
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402 { |
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403 return randu53(); |
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404 } |
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405 #endif |
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406 |
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407 /* ===== Ziggurat normal and exponential generators ===== */ |
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408 #ifdef ALLBITS |
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409 # define ZIGINT uint32_t |
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410 # define EMANTISSA 4294967296.0 /* 32 bit mantissa */ |
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411 # define ERANDI randi32() /* 32 bits for mantissa */ |
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412 # define NMANTISSA 2147483648.0 /* 31 bit mantissa */ |
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413 # define NRANDI randi32() /* 31 bits for mantissa + 1 bit sign */ |
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414 # define RANDU randu32() |
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415 #else |
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416 # define ZIGINT uint64_t |
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417 # define EMANTISSA 9007199254740992.0 /* 53 bit mantissa */ |
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418 # define ERANDI randi53() /* 53 bits for mantissa */ |
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419 # define NMANTISSA EMANTISSA |
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420 # define NRANDI randi54() /* 53 bits for mantissa + 1 bit sign */ |
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421 # define RANDU randu53() |
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422 #endif |
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423 |
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424 #define ZIGGURAT_TABLE_SIZE 256 |
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425 |
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426 #define ZIGGURAT_NOR_R 3.6541528853610088 |
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427 #define ZIGGURAT_NOR_INV_R 0.27366123732975828 |
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428 #define NOR_SECTION_AREA 0.00492867323399 |
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429 |
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430 #define ZIGGURAT_EXP_R 7.69711747013104972 |
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431 #define ZIGGURAT_EXP_INV_R 0.129918765548341586 |
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432 #define EXP_SECTION_AREA 0.0039496598225815571993 |
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433 |
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434 static ZIGINT ki[ZIGGURAT_TABLE_SIZE]; |
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435 static double wi[ZIGGURAT_TABLE_SIZE], fi[ZIGGURAT_TABLE_SIZE]; |
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436 static ZIGINT ke[ZIGGURAT_TABLE_SIZE]; |
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437 static double we[ZIGGURAT_TABLE_SIZE], fe[ZIGGURAT_TABLE_SIZE]; |
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438 |
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439 /* |
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440 This code is based on the paper Marsaglia and Tsang, "The ziggurat method |
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441 for generating random variables", Journ. Statistical Software. Code was |
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442 presented in this paper for a Ziggurat of 127 levels and using a 32 bit |
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443 integer random number generator. This version of the code, uses the |
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444 Mersenne Twister as the integer generator and uses 256 levels in the |
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445 Ziggurat. This has several advantages. |
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446 |
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447 1) As Marsaglia and Tsang themselves states, the more levels the few |
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448 times the expensive tail algorithm must be called |
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449 2) The cycle time of the generator is determined by the integer |
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450 generator, thus the use of a Mersenne Twister for the core random |
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451 generator makes this cycle extremely long. |
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452 3) The license on the original code was unclear, thus rewriting the code |
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453 from the article means we are free of copyright issues. |
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454 4) Compile flag for full 53-bit random mantissa. |
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455 |
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456 It should be stated that the authors made my life easier, by the fact that |
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457 the algorithm developed in the text of the article is for a 256 level |
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458 ziggurat, even if the code itself isn't... |
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459 |
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460 One modification to the algorithm developed in the article, is that it is |
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461 assumed that 0 <= x < Inf, and "unsigned long"s are used, thus resulting in |
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462 terms like 2^32 in the code. As the normal distribution is defined between |
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463 -Inf < x < Inf, we effectively only have 31 bit integers plus a sign. Thus |
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464 in Marsaglia and Tsang, terms like 2^32 become 2^31. We use NMANTISSA for |
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465 this term. The exponential distribution is one sided so we use the |
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466 full 32 bits. We use EMANTISSA for this term. |
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467 |
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468 It appears that I'm slightly slower than the code in the article, this |
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469 is partially due to a better generator of random integers than they |
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470 use. But might also be that the case of rapid return was optimized by |
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471 inlining the relevant code with a #define. As the basic Mersenne |
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472 Twister is only 25% faster than this code I suspect that the main |
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473 reason is just the use of the Mersenne Twister and not the inlining, |
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474 so I'm not going to try and optimize further. |
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475 */ |
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476 |
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477 static void |
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478 create_ziggurat_tables (void) |
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479 { |
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480 int i; |
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481 double x, x1; |
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482 |
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483 /* Ziggurat tables for the normal distribution */ |
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484 x1 = ZIGGURAT_NOR_R; |
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485 wi[255] = x1 / NMANTISSA; |
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486 fi[255] = exp (-0.5 * x1 * x1); |
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487 |
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488 /* Index zero is special for tail strip, where Marsaglia and Tsang |
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489 * defines this as |
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490 * k_0 = 2^31 * r * f(r) / v, w_0 = 0.5^31 * v / f(r), f_0 = 1, |
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491 * where v is the area of each strip of the ziggurat. |
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492 */ |
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493 ki[0] = (ZIGINT) (x1 * fi[255] / NOR_SECTION_AREA * NMANTISSA); |
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494 wi[0] = NOR_SECTION_AREA / fi[255] / NMANTISSA; |
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495 fi[0] = 1.; |
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496 |
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497 for (i = 254; i > 0; i--) |
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498 { |
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499 /* New x is given by x = f^{-1}(v/x_{i+1} + f(x_{i+1})), thus |
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500 * need inverse operator of y = exp(-0.5*x*x) -> x = sqrt(-2*ln(y)) |
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501 */ |
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502 x = sqrt(-2. * log(NOR_SECTION_AREA / x1 + fi[i+1])); |
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503 ki[i+1] = (ZIGINT)(x / x1 * NMANTISSA); |
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504 wi[i] = x / NMANTISSA; |
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505 fi[i] = exp (-0.5 * x * x); |
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506 x1 = x; |
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507 } |
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508 |
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509 ki[1] = 0; |
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510 |
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511 /* Zigurrat tables for the exponential distribution */ |
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512 x1 = ZIGGURAT_EXP_R; |
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513 we[255] = x1 / EMANTISSA; |
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514 fe[255] = exp (-x1); |
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515 |
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516 /* Index zero is special for tail strip, where Marsaglia and Tsang |
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517 * defines this as |
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518 * k_0 = 2^32 * r * f(r) / v, w_0 = 0.5^32 * v / f(r), f_0 = 1, |
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519 * where v is the area of each strip of the ziggurat. |
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520 */ |
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521 ke[0] = (ZIGINT) (x1 * fe[255] / EXP_SECTION_AREA * EMANTISSA); |
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522 we[0] = EXP_SECTION_AREA / fe[255] / EMANTISSA; |
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523 fe[0] = 1.; |
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524 |
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525 for (i = 254; i > 0; i--) |
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526 { |
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527 /* New x is given by x = f^{-1}(v/x_{i+1} + f(x_{i+1})), thus |
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528 * need inverse operator of y = exp(-x) -> x = -ln(y) |
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529 */ |
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530 x = - log(EXP_SECTION_AREA / x1 + fe[i+1]); |
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531 ke[i+1] = (ZIGINT)(x / x1 * EMANTISSA); |
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532 we[i] = x / EMANTISSA; |
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533 fe[i] = exp (-x); |
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534 x1 = x; |
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535 } |
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536 ke[1] = 0; |
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537 |
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538 initt = 0; |
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539 } |
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540 |
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541 /* |
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542 * Here is the guts of the algorithm. As Marsaglia and Tsang state the |
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543 * algorithm in their paper |
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544 * |
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545 * 1) Calculate a random signed integer j and let i be the index |
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546 * provided by the rightmost 8-bits of j |
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547 * 2) Set x = j * w_i. If j < k_i return x |
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548 * 3) If i = 0, then return x from the tail |
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549 * 4) If [f(x_{i-1}) - f(x_i)] * U < f(x) - f(x_i), return x |
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550 * 5) goto step 1 |
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551 * |
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552 * Where f is the functional form of the distribution, which for a normal |
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553 * distribution is exp(-0.5*x*x) |
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554 */ |
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555 |
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556 double |
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557 oct_randn (void) |
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558 { |
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559 if (initt) |
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560 create_ziggurat_tables(); |
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561 |
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562 while (1) |
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563 { |
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564 /* The following code is specialized for 32-bit mantissa. |
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565 * Compared to the arbitrary mantissa code, there is a performance |
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566 * gain for 32-bits: PPC: 2%, MIPS: 8%, x86: 40% |
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567 * There is a bigger performance gain compared to using a full |
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568 * 53-bit mantissa: PPC: 60%, MIPS: 65%, x86: 240% |
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569 * Of course, different compilers and operating systems may |
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570 * have something to do with this. |
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571 */ |
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572 #if !defined(ALLBITS) |
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573 # if HAVE_X86_32 |
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574 /* 53-bit mantissa, 1-bit sign, x86 32-bit architecture */ |
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575 double x; |
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576 int si,idx; |
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577 register uint32_t lo, hi; |
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578 int64_t rabs; |
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579 uint32_t *p = (uint32_t *)&rabs; |
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580 lo = randi32(); |
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581 idx = lo&0xFF; |
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582 hi = randi32(); |
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583 si = hi&UMASK; |
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584 p[0] = lo; |
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585 p[1] = hi&0x1FFFFF; |
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586 x = ( si ? -rabs : rabs ) * wi[idx]; |
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587 # else /* !HAVE_X86_32 */ |
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588 /* arbitrary mantissa (selected by NRANDI, with 1 bit for sign) */ |
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589 const uint64_t r = NRANDI; |
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590 const int64_t rabs=r>>1; |
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591 const int idx = (int)(rabs&0xFF); |
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592 const double x = ( r&1 ? -rabs : rabs) * wi[idx]; |
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593 # endif /* !HAVE_X86_32 */ |
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594 if (rabs < (int64_t)ki[idx]) |
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595 #else /* ALLBITS */ |
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596 /* 32-bit mantissa */ |
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597 const uint32_t r = randi32(); |
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598 const uint32_t rabs = r&LMASK; |
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599 const int idx = (int)(r&0xFF); |
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600 const double x = ((int32_t)r) * wi[idx]; |
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601 if (rabs < ki[idx]) |
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602 #endif /* ALLBITS */ |
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603 return x; /* 99.3% of the time we return here 1st try */ |
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604 else if (idx == 0) |
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605 { |
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606 /* As stated in Marsaglia and Tsang |
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607 * |
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608 * For the normal tail, the method of Marsaglia[5] provides: |
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609 * generate x = -ln(U_1)/r, y = -ln(U_2), until y+y > x*x, |
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610 * then return r+x. Except that r+x is always in the positive |
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611 * tail!!!! Any thing random might be used to determine the |
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612 * sign, but as we already have r we might as well use it |
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613 * |
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614 * [PAK] but not the bottom 8 bits, since they are all 0 here! |
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615 */ |
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616 double xx, yy; |
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617 do |
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618 { |
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619 xx = - ZIGGURAT_NOR_INV_R * log (RANDU); |
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620 yy = - log (RANDU); |
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621 } |
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622 while ( yy+yy <= xx*xx); |
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623 return (rabs&0x100 ? -ZIGGURAT_NOR_R-xx : ZIGGURAT_NOR_R+xx); |
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624 } |
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625 else if ((fi[idx-1] - fi[idx]) * RANDU + fi[idx] < exp(-0.5*x*x)) |
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626 return x; |
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627 } |
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628 } |
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629 |
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630 double |
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631 oct_rande (void) |
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632 { |
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633 if (initt) |
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634 create_ziggurat_tables(); |
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635 |
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636 while (1) |
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637 { |
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638 ZIGINT ri = ERANDI; |
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639 const int idx = (int)(ri & 0xFF); |
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640 const double x = ri * we[idx]; |
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641 if (ri < ke[idx]) |
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642 return x; // 98.9% of the time we return here 1st try |
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643 else if (idx == 0) |
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644 { |
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645 /* As stated in Marsaglia and Tsang |
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646 * |
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647 * For the exponential tail, the method of Marsaglia[5] provides: |
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648 * x = r - ln(U); |
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649 */ |
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650 return ZIGGURAT_EXP_R - log(RANDU); |
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651 } |
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652 else if ((fe[idx-1] - fe[idx]) * RANDU + fe[idx] < exp(-x)) |
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653 return x; |
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654 } |
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655 } |
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656 |
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657 /* Array generators */ |
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658 void |
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659 oct_fill_randu (octave_idx_type n, double *p) |
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660 { |
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661 octave_idx_type i; |
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662 for (i = 0; i < n; i++) |
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663 p[i] = oct_randu(); |
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664 } |
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665 |
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666 void |
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667 oct_fill_randn (octave_idx_type n, double *p) |
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668 { |
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669 octave_idx_type i; |
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670 for (i = 0; i < n; i++) |
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671 p[i] = oct_randn(); |
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672 } |
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673 |
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674 void |
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675 oct_fill_rande (octave_idx_type n, double *p) |
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676 { |
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677 octave_idx_type i; |
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678 for (i = 0; i < n; i++) |
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679 p[i] = oct_rande(); |
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680 } |
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681 |
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682 /* |
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683 ;;; Local Variables: *** |
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684 ;;; mode: C *** |
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685 ;;; End: *** |
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686 */ |
