Mercurial > octave
annotate liboctave/numeric/randpoisson.cc @ 30564:796f54d4ddbf stable
update Octave Project Developers copyright for the new year
In files that have the "Octave Project Developers" copyright notice,
update for 2021.
In all .txi and .texi files except gpl.txi and gpl.texi in the
doc/liboctave and doc/interpreter directories, change the copyright
to "Octave Project Developers", the same as used for other source
files. Update copyright notices for 2022 (not done since 2019). For
gpl.txi and gpl.texi, change the copyright notice to be "Free Software
Foundation, Inc." and leave the date at 2007 only because this file
only contains the text of the GPL, not anything created by the Octave
Project Developers.
Add Paul Thomas to contributors.in.
author | John W. Eaton <jwe@octave.org> |
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date | Tue, 28 Dec 2021 18:22:40 -0500 |
parents | 32f4357ac8d9 |
children | e88a07dec498 |
rev | line source |
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1 //////////////////////////////////////////////////////////////////////// |
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2 // |
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3 // Copyright (C) 2006-2022 The Octave Project Developers |
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4 // |
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5 // See the file COPYRIGHT.md in the top-level directory of this |
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6 // distribution or <https://octave.org/copyright/>. |
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7 // |
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8 // This file is part of Octave. |
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9 // |
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10 // Octave is free software: you can redistribute it and/or modify it |
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11 // under the terms of the GNU General Public License as published by |
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12 // the Free Software Foundation, either version 3 of the License, or |
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13 // (at your option) any later version. |
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14 // |
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15 // Octave is distributed in the hope that it will be useful, but |
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16 // WITHOUT ANY WARRANTY; without even the implied warranty of |
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17 // MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the |
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18 // GNU General Public License for more details. |
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19 // |
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20 // You should have received a copy of the GNU General Public License |
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21 // along with Octave; see the file COPYING. If not, see |
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22 // <https://www.gnu.org/licenses/>. |
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23 // |
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24 //////////////////////////////////////////////////////////////////////// |
7019 | 25 |
26 /* Original version written by Paul Kienzle distributed as free | |
27 software in the in the public domain. */ | |
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29 #if defined (HAVE_CONFIG_H) | |
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30 # include "config.h" |
5742 | 31 #endif |
32 | |
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33 #include <cmath> |
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34 #include <cstddef> |
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35 |
5742 | 36 #include "f77-fcn.h" |
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5742 | 38 #include "lo-ieee.h" |
39 #include "randmtzig.h" | |
40 #include "randpoisson.h" | |
41 | |
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42 namespace octave |
5742 | 43 { |
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44 static double xlgamma (double x) |
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45 { |
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46 return std::lgamma (x); |
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47 } |
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49 /* ---- pprsc.c from Stadloeber's winrand --- */ |
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50 |
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51 /* flogfak(k) = ln(k!) */ |
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52 static double flogfak (double k) |
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53 { |
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54 #define C0 9.18938533204672742e-01 |
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55 #define C1 8.33333333333333333e-02 |
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56 #define C3 -2.77777777777777778e-03 |
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57 #define C5 7.93650793650793651e-04 |
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58 #define C7 -5.95238095238095238e-04 |
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60 static double logfak[30L] = |
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61 { |
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62 0.00000000000000000, 0.00000000000000000, 0.69314718055994531, |
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63 1.79175946922805500, 3.17805383034794562, 4.78749174278204599, |
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64 6.57925121201010100, 8.52516136106541430, 10.60460290274525023, |
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65 12.80182748008146961, 15.10441257307551530, 17.50230784587388584, |
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66 19.98721449566188615, 22.55216385312342289, 25.19122118273868150, |
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67 27.89927138384089157, 30.67186010608067280, 33.50507345013688888, |
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68 36.39544520803305358, 39.33988418719949404, 42.33561646075348503, |
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69 45.38013889847690803, 48.47118135183522388, 51.60667556776437357, |
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70 54.78472939811231919, 58.00360522298051994, 61.26170176100200198, |
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71 64.55753862700633106, 67.88974313718153498, 71.25703896716800901 |
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72 }; |
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73 |
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74 double r, rr; |
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75 |
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76 if (k >= 30.0) |
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77 { |
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78 r = 1.0 / k; |
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79 rr = r * r; |
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80 return ((k + 0.5)*std::log (k) - k + C0 |
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81 + r*(C1 + rr*(C3 + rr*(C5 + rr*C7)))); |
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82 } |
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83 else |
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84 return (logfak[static_cast<int> (k)]); |
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85 } |
5742 | 86 |
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87 /****************************************************************** |
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88 * * |
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89 * Poisson Distribution - Patchwork Rejection/Inversion * |
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90 * * |
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91 ****************************************************************** |
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92 * * |
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93 * For parameter my < 10, Tabulated Inversion is applied. * |
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94 * For my >= 10, Patchwork Rejection is employed: * |
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95 * The area below the histogram function f(x) is rearranged in * |
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96 * its body by certain point reflections. Within a large center * |
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97 * interval variates are sampled efficiently by rejection from * |
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98 * uniform hats. Rectangular immediate acceptance regions speed * |
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99 * up the generation. The remaining tails are covered by * |
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100 * exponential functions. * |
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101 * * |
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102 ****************************************************************** |
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103 * * |
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104 * FUNCTION : - pprsc samples a random number from the Poisson * |
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105 * distribution with parameter my > 0. * |
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106 * REFERENCE : - H. Zechner (1994): Efficient sampling from * |
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107 * continuous and discrete unimodal distributions, * |
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108 * Doctoral Dissertation, 156 pp., Technical * |
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109 * University Graz, Austria. * |
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110 * SUBPROGRAM : - drand(seed) ... (0,1)-Uniform generator with * |
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111 * unsigned long integer *seed. * |
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112 * * |
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113 * Implemented by H. Zechner, January 1994 * |
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114 * Revised by F. Niederl, July 1994 * |
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115 * * |
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116 ******************************************************************/ |
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118 static double f (double k, double l_nu, double c_pm) |
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119 { |
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120 return exp (k * l_nu - flogfak (k) - c_pm); |
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121 } |
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123 static double pprsc (double my) |
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124 { |
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125 static double my_last = -1.0; |
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126 static double m, k2, k4, k1, k5; |
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127 static double dl, dr, r1, r2, r4, r5, ll, lr, l_my, c_pm, |
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128 f1, f2, f4, f5, p1, p2, p3, p4, p5, p6; |
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129 double Dk, X, Y; |
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130 double Ds, U, V, W; |
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131 |
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132 if (my != my_last) |
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133 { /* set-up */ |
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134 my_last = my; |
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135 /* approximate deviation of reflection points k2, k4 from my - 1/2 */ |
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136 Ds = std::sqrt (my + 0.25); |
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137 |
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138 /* mode m, reflection points k2 and k4, and points k1 and k5, */ |
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139 /* which delimit the centre region of h(x) */ |
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140 m = std::floor (my); |
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141 k2 = ceil (my - 0.5 - Ds); |
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142 k4 = std::floor (my - 0.5 + Ds); |
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143 k1 = k2 + k2 - m + 1L; |
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144 k5 = k4 + k4 - m; |
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145 |
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146 /* range width of the critical left and right centre region */ |
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147 dl = (k2 - k1); |
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148 dr = (k5 - k4); |
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149 |
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150 /* recurrence constants r(k)=p(k)/p(k-1) at k = k1, k2, k4+1, k5+1 */ |
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151 r1 = my / k1; |
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152 r2 = my / k2; |
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153 r4 = my / (k4 + 1.0); |
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154 r5 = my / (k5 + 1.0); |
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156 /* reciprocal values of the scale parameters of exp. tail envelope */ |
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157 ll = std::log (r1); /* expon. tail left */ |
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158 lr = -std::log (r5); /* expon. tail right*/ |
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159 |
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160 /* Poisson constants, necessary for computing function values f(k) */ |
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161 l_my = std::log (my); |
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162 c_pm = m * l_my - flogfak (m); |
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163 |
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164 /* function values f(k) = p(k)/p(m) at k = k2, k4, k1, k5 */ |
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165 f2 = f (k2, l_my, c_pm); |
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166 f4 = f (k4, l_my, c_pm); |
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167 f1 = f (k1, l_my, c_pm); |
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168 f5 = f (k5, l_my, c_pm); |
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169 |
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170 /* area of the two centre and the two exponential tail regions */ |
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171 /* area of the two immediate acceptance regions between k2, k4 */ |
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172 p1 = f2 * (dl + 1.0); /* immed. left */ |
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173 p2 = f2 * dl + p1; /* centre left */ |
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174 p3 = f4 * (dr + 1.0) + p2; /* immed. right */ |
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175 p4 = f4 * dr + p3; /* centre right */ |
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176 p5 = f1 / ll + p4; /* exp. tail left */ |
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177 p6 = f5 / lr + p5; /* exp. tail right*/ |
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178 } |
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179 |
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180 for (;;) |
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181 { |
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182 /* generate uniform number U -- U(0, p6) */ |
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183 /* case distinction corresponding to U */ |
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184 if ((U = rand_uniform<double> () * p6) < p2) |
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185 { /* centre left */ |
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186 |
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187 /* immediate acceptance region |
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188 R2 = [k2, m) *[0, f2), X = k2, ... m -1 */ |
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189 if ((V = U - p1) < 0.0) return (k2 + std::floor (U/f2)); |
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190 /* immediate acceptance region |
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191 R1 = [k1, k2)*[0, f1), X = k1, ... k2-1 */ |
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192 if ((W = V / dl) < f1 ) return (k1 + std::floor (V/f1)); |
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193 |
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194 /* computation of candidate X < k2, and its counterpart Y > k2 */ |
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195 /* either squeeze-acceptance of X or acceptance-rejection of Y */ |
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196 Dk = std::floor (dl * rand_uniform<double> ()) + 1.0; |
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197 if (W <= f2 - Dk * (f2 - f2/r2)) |
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198 { /* quick accept of */ |
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199 return (k2 - Dk); /* X = k2 - Dk */ |
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200 } |
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201 if ((V = f2 + f2 - W) < 1.0) |
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202 { /* quick reject of Y*/ |
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203 Y = k2 + Dk; |
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204 if (V <= f2 + Dk * (1.0 - f2)/(dl + 1.0)) |
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205 { /* quick accept of */ |
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206 return (Y); /* Y = k2 + Dk */ |
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207 } |
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208 if (V <= f (Y, l_my, c_pm)) return (Y); /* final accept of Y*/ |
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209 } |
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210 X = k2 - Dk; |
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211 } |
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212 else if (U < p4) |
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213 { /* centre right */ |
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214 /* immediate acceptance region |
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215 R3 = [m, k4+1)*[0, f4), X = m, ... k4 */ |
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216 if ((V = U - p3) < 0.0) return (k4 - std::floor ((U - p2)/f4)); |
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217 /* immediate acceptance region |
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218 R4 = [k4+1, k5+1)*[0, f5) */ |
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219 if ((W = V / dr) < f5 ) return (k5 - std::floor (V/f5)); |
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220 |
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221 /* computation of candidate X > k4, and its counterpart Y < k4 */ |
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222 /* either squeeze-acceptance of X or acceptance-rejection of Y */ |
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223 Dk = std::floor (dr * rand_uniform<double> ()) + 1.0; |
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224 if (W <= f4 - Dk * (f4 - f4*r4)) |
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225 { /* quick accept of */ |
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226 return (k4 + Dk); /* X = k4 + Dk */ |
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227 } |
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228 if ((V = f4 + f4 - W) < 1.0) |
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229 { /* quick reject of Y*/ |
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230 Y = k4 - Dk; |
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231 if (V <= f4 + Dk * (1.0 - f4)/ dr) |
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232 { /* quick accept of */ |
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233 return (Y); /* Y = k4 - Dk */ |
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234 } |
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235 if (V <= f (Y, l_my, c_pm)) return (Y); /* final accept of Y*/ |
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236 } |
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237 X = k4 + Dk; |
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238 } |
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239 else |
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240 { |
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241 W = rand_uniform<double> (); |
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242 if (U < p5) |
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243 { /* expon. tail left */ |
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244 Dk = std::floor (1.0 - std::log (W)/ll); |
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245 if ((X = k1 - Dk) < 0L) continue; /* 0 <= X <= k1 - 1 */ |
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246 W *= (U - p4) * ll; /* W -- U(0, h(x)) */ |
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247 if (W <= f1 - Dk * (f1 - f1/r1)) |
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248 return (X); /* quick accept of X*/ |
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249 } |
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250 else |
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251 { /* expon. tail right*/ |
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252 Dk = std::floor (1.0 - std::log (W)/lr); |
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253 X = k5 + Dk; /* X >= k5 + 1 */ |
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254 W *= (U - p5) * lr; /* W -- U(0, h(x)) */ |
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255 if (W <= f5 - Dk * (f5 - f5*r5)) |
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256 return (X); /* quick accept of X*/ |
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257 } |
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258 } |
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259 |
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260 /* acceptance-rejection test of candidate X from the original area */ |
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261 /* test, whether W <= f(k), with W = U*h(x) and U -- U(0, 1)*/ |
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262 /* log f(X) = (X - m)*log(my) - log X! + log m! */ |
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263 if (std::log (W) <= X * l_my - flogfak (X) - c_pm) return (X); |
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264 } |
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265 } |
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266 /* ---- pprsc.c end ------ */ |
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268 /* The remainder of the file is by Paul Kienzle */ |
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270 /* Table size is predicated on the maximum value of lambda |
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271 * we want to store in the table, and the maximum value of |
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272 * returned by the uniform random number generator on [0,1). |
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273 * With lambda==10 and u_max = 1 - 1/(2^32+1), we |
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274 * have poisson_pdf(lambda,36) < 1-u_max. If instead our |
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275 * generator uses more bits of mantissa or returns a value |
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276 * in the range [0,1], then for lambda==10 we need a table |
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277 * size of 46 instead. For long doubles, the table size |
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278 * will need to be longer still. */ |
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279 #define TABLESIZE 46 |
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280 |
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281 /* Given uniform u, find x such that CDF(L,x)==u. Return x. */ |
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282 |
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283 template <typename T> |
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284 static void |
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285 poisson_cdf_lookup (double lambda, T *p, std::size_t n) |
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286 { |
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287 double t[TABLESIZE]; |
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288 |
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289 /* Precompute the table for the u up to and including 0.458. |
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290 * We will almost certainly need it. */ |
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291 int intlambda = static_cast<int> (std::floor (lambda)); |
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292 double P; |
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293 int tableidx; |
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294 std::size_t i = n; |
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295 |
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296 t[0] = P = exp (-lambda); |
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297 for (tableidx = 1; tableidx <= intlambda; tableidx++) |
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298 { |
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299 P = P*lambda/static_cast<double> (tableidx); |
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300 t[tableidx] = t[tableidx-1] + P; |
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301 } |
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302 |
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303 while (i-- > 0) |
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304 { |
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305 double u = rand_uniform<double> (); |
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306 |
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307 /* If u > 0.458 we know we can jump to floor(lambda) before |
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308 * comparing (this observation is based on Stadlober's winrand |
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309 * code). For lambda >= 1, this will be a win. Lambda < 1 |
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310 * is already fast, so adding an extra comparison is not a |
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311 * problem. */ |
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312 int k = (u > 0.458 ? intlambda : 0); |
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313 |
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314 /* We aren't using a for loop here because when we find the |
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315 * right k we want to jump to the next iteration of the |
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316 * outer loop, and the continue statement will only work for |
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317 * the inner loop. */ |
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318 nextk: |
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319 if (u <= t[k]) |
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320 { |
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321 p[i] = static_cast<T> (k); |
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322 continue; |
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323 } |
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324 if (++k < tableidx) |
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325 goto nextk; |
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326 |
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327 /* We only need high values of the table very rarely so we |
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328 * don't automatically compute the entire table. */ |
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329 while (tableidx < TABLESIZE) |
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330 { |
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331 P = P*lambda/static_cast<double> (tableidx); |
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332 t[tableidx] = t[tableidx-1] + P; |
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333 /* Make sure we converge to 1.0 just in case u is uniform |
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334 * on [0,1] rather than [0,1). */ |
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335 if (t[tableidx] == t[tableidx-1]) t[tableidx] = 1.0; |
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336 tableidx++; |
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337 if (u <= t[tableidx-1]) break; |
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338 } |
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339 |
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340 /* We are assuming that the table size is big enough here. |
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341 * This should be true even if rand_uniform is returning values in |
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342 * the range [0,1] rather than [0,1). */ |
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343 p[i] = static_cast<T> (tableidx-1); |
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344 } |
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345 } |
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346 |
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347 /* From Press, et al., Numerical Recipes */ |
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348 template <typename T> |
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349 static void |
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350 poisson_rejection (double lambda, T *p, std::size_t n) |
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351 { |
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352 double sq = std::sqrt (2.0*lambda); |
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353 double alxm = std::log (lambda); |
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354 double g = lambda*alxm - xlgamma (lambda+1.0); |
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355 std::size_t i; |
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356 |
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357 for (i = 0; i < n; i++) |
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358 { |
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359 double y, em, t; |
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360 do |
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361 { |
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362 do |
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363 { |
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364 y = tan (M_PI*rand_uniform<double> ()); |
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365 em = sq * y + lambda; |
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366 } while (em < 0.0); |
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367 em = std::floor (em); |
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368 t = 0.9*(1.0+y*y)*exp (em*alxm-flogfak (em)-g); |
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369 } while (rand_uniform<double> () > t); |
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370 p[i] = em; |
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371 } |
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372 } |
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373 |
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374 /* The cutoff of L <= 1e8 in the following two functions before using |
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375 * the normal approximation is based on: |
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376 * > L=1e8; x=floor(linspace(0,2*L,1000)); |
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377 * > max(abs(normal_pdf(x,L,L)-poisson_pdf(x,L))) |
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378 * ans = 1.1376e-28 |
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379 * For L=1e7, the max is around 1e-9, which is within the step size of |
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380 * rand_uniform. For L>1e10 the pprsc function breaks down, as I saw |
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381 * from the histogram of a large sample, so 1e8 is both small enough |
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382 * and large enough. */ |
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384 /* Generate a set of poisson numbers with the same distribution */ |
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385 template <typename T> void rand_poisson (T L_arg, octave_idx_type n, T *p) |
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386 { |
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387 double L = L_arg; |
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388 octave_idx_type i; |
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389 if (L < 0.0 || lo_ieee_isinf (L)) |
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390 { |
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391 for (i=0; i<n; i++) |
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392 p[i] = numeric_limits<T>::NaN (); |
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393 } |
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394 else if (L <= 10.0) |
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395 { |
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396 poisson_cdf_lookup<T> (L, p, n); |
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397 } |
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398 else if (L <= 1e8) |
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399 { |
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400 for (i=0; i<n; i++) |
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401 p[i] = pprsc (L); |
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402 } |
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403 else |
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404 { |
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405 /* normal approximation: from Phys. Rev. D (1994) v50 p1284 */ |
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406 const double sqrtL = std::sqrt (L); |
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407 for (i = 0; i < n; i++) |
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408 { |
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409 p[i] = std::floor (rand_normal<T> () * sqrtL + L + 0.5); |
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410 if (p[i] < 0.0) |
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411 p[i] = 0.0; /* will probably never happen */ |
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412 } |
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413 } |
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414 } |
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416 template void rand_poisson<double> (double, octave_idx_type, double *); |
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417 template void rand_poisson<float> (float, octave_idx_type, float *); |
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418 |
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419 /* Generate one poisson variate */ |
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420 template <typename T> T rand_poisson (T L_arg) |
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421 { |
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422 double L = L_arg; |
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423 T ret; |
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424 if (L < 0.0) ret = numeric_limits<T>::NaN (); |
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425 else if (L <= 12.0) |
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426 { |
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427 /* From Press, et al. Numerical recipes */ |
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428 double g = exp (-L); |
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429 int em = -1; |
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430 double t = 1.0; |
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431 do |
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432 { |
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433 ++em; |
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434 t *= rand_uniform<T> (); |
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435 } while (t > g); |
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436 ret = em; |
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437 } |
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438 else if (L <= 1e8) |
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439 { |
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440 /* numerical recipes */ |
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441 poisson_rejection<T> (L, &ret, 1); |
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442 } |
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443 else if (lo_ieee_isinf (L)) |
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444 { |
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445 /* FIXME: R uses NaN, but the normal approximation suggests that |
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446 * limit should be Inf. Which is correct? */ |
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447 ret = numeric_limits<T>::NaN (); |
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448 } |
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449 else |
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450 { |
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451 /* normal approximation: from Phys. Rev. D (1994) v50 p1284 */ |
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452 ret = std::floor (rand_normal<T> () * std::sqrt (L) + L + 0.5); |
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453 if (ret < 0.0) ret = 0.0; /* will probably never happen */ |
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454 } |
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455 return ret; |
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456 } |
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457 |
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458 template OCTAVE_API double rand_poisson<double> (double); |
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459 template OCTAVE_API float rand_poisson<float> (float); |
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460 } |