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正确设置随机种子以实现重复性

intel-fortran fortran90 gfortran fortran

JohnE · 技术社区 · 6 年前

random_seed 很直接。

call random_seed( put=seed )

但是我找不到任何关于设定种子的指导原则的信息(当你想要重复性时,这是绝对必要的)。我以前听过民间传说,标量种子应该很大。E、 123456789是比123更好的种子。我在网上能找到的对此的唯一支持是建议使用ifort扩展函数 ran() 那个使用 "large, odd integer value"

我知道这可能是特定于实现的,我使用的是gfortran 4.8.5,但我也对ifort和(如果可能的话)独立于实现的一般准则感兴趣。下面是一些示例代码:

# for compactness, assume seed size of 4, but it will depend on 
# the implementation (e.g. for my version of gfortran 4.8.5 it is 12)

seed1(1:4) = [ 123456789, 987654321, 456789123, 7891234567 ]
seed2(1:4) =   123456789
seed3(1:4) = [         1,         2,         3,          4 ]

seed1 很好,但是如果你手动设置它(就像我一样),因为种子长度可以是12或33或其他。我甚至不确定这是否合适,因为我还没有找到任何关于播种的指导方针。一、这些种子应该是负的,据我所知,或3位偶数,等等,虽然我想你会希望实现会警告你这个(?)。

seed2 和 seed3 种子2 事实上,他的回答很好: Random number generator (RNG/PRNG) that returns updated value of seed

种子1 到 种子3 可以接受吗?

2 回复 | 直到 6 年前

janneb 6 年前

设定种子的准则取决于PRNG算法 RANDOM_NUMBER 使用,但一般来说,你提供的“熵”越多越好。

如果只有一个标量值,可以使用一些简单的PRNG将其扩展到 RANDOM_SEED . 参见功能 lcg 在示例代码中 https://gcc.gnu.org/onlinedocs/gcc-4.9.1/gfortran/RANDOM_005fSEED.html

seed(:) 相同,或者所有值都很小,甚至为零),但是对于其他编译器的可移植性来说,遵循我上面建议的方法仍然是一个好主意。

Ross 6 年前

你提供给 random_seed( put=... ) 用于确定生成器的启动状态,该状态(作为janneb状态)应具有尽可能多的熵。你可以构造一些相对复杂的方法,从系统中获取熵,这是一个很好的选择。janneb链接代码就是一个很好的例子。

program main
   implicit none
   integer, parameter :: wp = selected_real_kind(15,307)
   integer, parameter :: n_discard = 100

   integer :: state_size, i
   integer, allocatable, dimension(:) :: state
   real(wp) :: ran, oldran

   call random_seed( size=state_size )
   write(*,*) '-- state size is: ', state_size

   allocate(state(state_size))

   ! -- Simple method of initializing seed from single scalar
   state = 20180815
   call random_seed( put=state )

   ! -- 'Prime' the generator by pulling the first few numbers
   ! -- In reality, these would be discarded but I will print them for demonstration
   ran = 0.5_wp
   do i=1,n_discard
      oldran = ran
      call random_number(ran)
      write(*,'(a,i3,2es26.18)') 'iter, ran, diff: ', i, ran, ran-oldran
   enddo

   ! Now the RNG is 'ready'
end program main

在这里,我给出一个种子,然后生成100次随机数。通常,我会丢弃这些初始的、可能损坏的数字。在本例中,我将打印它们以查看它们是否看起来是非随机的。使用PGI 15.10跑步:

enet-mach5% pgfortran --version

pgfortran 15.10-0 64-bit target on x86-64 Linux -tp sandybridge 
The Portland Group - PGI Compilers and Tools
Copyright (c) 2015, NVIDIA CORPORATION.  All rights reserved.
enet-mach5% pgfortran main.f90 && ./a.out
 -- state size is:            34
iter, ran, diff:   1  8.114813341476008191E-01  3.114813341476008191E-01
iter, ran, diff:   2  8.114813341476008191E-01  0.000000000000000000E+00
iter, ran, diff:   3  8.114813341476008191E-01  0.000000000000000000E+00
iter, ran, diff:   4  8.114813341476008191E-01  0.000000000000000000E+00
iter, ran, diff:   5  8.114813341476008191E-01  0.000000000000000000E+00
iter, ran, diff:   6  2.172220012214012286E-01 -5.942593329261995905E-01
iter, ran, diff:   7  2.172220012214012286E-01  0.000000000000000000E+00
iter, ran, diff:   8  2.172220012214012286E-01  0.000000000000000000E+00
iter, ran, diff:   9  2.172220012214012286E-01  0.000000000000000000E+00
iter, ran, diff:  10  2.172220012214012286E-01  0.000000000000000000E+00
iter, ran, diff:  11  6.229626682952016381E-01  4.057406670738004095E-01
iter, ran, diff:  12  6.229626682952016381E-01  0.000000000000000000E+00
iter, ran, diff:  13  6.229626682952016381E-01  0.000000000000000000E+00
iter, ran, diff:  14  6.229626682952016381E-01  0.000000000000000000E+00
iter, ran, diff:  15  6.229626682952016381E-01  0.000000000000000000E+00
iter, ran, diff:  16  2.870333536900204763E-02 -5.942593329261995905E-01
iter, ran, diff:  17  2.870333536900204763E-02  0.000000000000000000E+00
iter, ran, diff:  18  4.344440024428024572E-01  4.057406670738004095E-01
iter, ran, diff:  19  4.344440024428024572E-01  0.000000000000000000E+00
iter, ran, diff:  20  4.344440024428024572E-01  0.000000000000000000E+00
iter, ran, diff:  21  8.401846695166028667E-01  4.057406670738004095E-01
iter, ran, diff:  22  8.401846695166028667E-01  0.000000000000000000E+00
iter, ran, diff:  23  6.516660036642036857E-01 -1.885186658523991809E-01
iter, ran, diff:  24  6.516660036642036857E-01  0.000000000000000000E+00
iter, ran, diff:  25  6.516660036642036857E-01  0.000000000000000000E+00
iter, ran, diff:  26  5.740667073800409526E-02 -5.942593329261995905E-01
iter, ran, diff:  27  5.740667073800409526E-02  0.000000000000000000E+00
iter, ran, diff:  28  2.746286719594053238E-01  2.172220012214012286E-01
iter, ran, diff:  29  2.746286719594053238E-01  0.000000000000000000E+00
iter, ran, diff:  30  2.746286719594053238E-01  0.000000000000000000E+00
iter, ran, diff:  31  6.803693390332057334E-01  4.057406670738004095E-01
iter, ran, diff:  32  6.803693390332057334E-01  0.000000000000000000E+00
iter, ran, diff:  33  3.033320073284073715E-01 -3.770373317047983619E-01
iter, ran, diff:  34  3.033320073284073715E-01  0.000000000000000000E+00
iter, ran, diff:  35  7.090726744022077810E-01  4.057406670738004095E-01
iter, ran, diff:  36  1.148133414760081905E-01 -5.942593329261995905E-01
iter, ran, diff:  37  1.148133414760081905E-01  0.000000000000000000E+00
iter, ran, diff:  38  1.435166768450102381E-01  2.870333536900204763E-02
iter, ran, diff:  39  1.435166768450102381E-01  0.000000000000000000E+00
iter, ran, diff:  40  3.607386780664114667E-01  2.172220012214012286E-01
iter, ran, diff:  41  7.664793451402118762E-01  4.057406670738004095E-01
iter, ran, diff:  42  7.664793451402118762E-01  0.000000000000000000E+00
iter, ran, diff:  43  2.009233475830143334E-01 -5.655559975571975428E-01
iter, ran, diff:  44  2.009233475830143334E-01  0.000000000000000000E+00
iter, ran, diff:  45  6.353673500258167905E-01  4.344440024428024572E-01
iter, ran, diff:  46  4.110801709961720007E-02 -5.942593329261995905E-01
iter, ran, diff:  47  4.110801709961720007E-02  0.000000000000000000E+00
iter, ran, diff:  48  8.812926866162200668E-01  8.401846695166028667E-01
iter, ran, diff:  49  8.812926866162200668E-01  0.000000000000000000E+00
iter, ran, diff:  50  9.386993573542241620E-01  5.740667073800409526E-02
iter, ran, diff:  51  3.444400244280245715E-01 -5.942593329261995905E-01
iter, ran, diff:  52  7.501806915018249811E-01  4.057406670738004095E-01
iter, ran, diff:  53  9.961060280922282573E-01  2.459253365904032762E-01
iter, ran, diff:  54  9.961060280922282573E-01  0.000000000000000000E+00
iter, ran, diff:  55  8.221603419923440015E-02 -9.138899938929938571E-01
iter, ran, diff:  56  4.879567012730348097E-01  4.057406670738004095E-01
iter, ran, diff:  57  1.109193695682364478E-01 -3.770373317047983619E-01
iter, ran, diff:  58  7.625853732324401335E-01  6.516660036642036857E-01
iter, ran, diff:  59  7.625853732324401335E-01  0.000000000000000000E+00
iter, ran, diff:  60  2.831393817822487335E-01 -4.794459914501914000E-01
iter, ran, diff:  61  6.888800488560491431E-01  4.057406670738004095E-01
iter, ran, diff:  62  7.462867195940532383E-01  5.740667073800409526E-02
iter, ran, diff:  63  8.036933903320573336E-01  5.740667073800409526E-02
iter, ran, diff:  64  8.036933903320573336E-01  0.000000000000000000E+00
iter, ran, diff:  65  1.644320683984688003E-01 -6.392613219335885333E-01
iter, ran, diff:  66  5.701727354722692098E-01  4.057406670738004095E-01
iter, ran, diff:  67  6.849860769482774003E-01  1.148133414760081905E-01
iter, ran, diff:  68  1.481334147600819051E-01 -5.368526621881954952E-01
iter, ran, diff:  69  5.538740818338823146E-01  4.057406670738004095E-01
iter, ran, diff:  70  1.605380964906970576E-01 -3.933359853431852571E-01
iter, ran, diff:  71  5.662787635644974671E-01  4.057406670738004095E-01
iter, ran, diff:  72  7.672021111475118005E-01  2.009233475830143334E-01
iter, ran, diff:  73  6.360901160331167148E-01 -1.311119951143950857E-01
iter, ran, diff:  74  6.647934514021187624E-01  2.870333536900204763E-02
iter, ran, diff:  75  9.231234697231371911E-01  2.583300183210184287E-01
iter, ran, diff:  76  3.288641367969376006E-01 -5.942593329261995905E-01
iter, ran, diff:  77  5.034149292976053403E-02 -2.785226438671770666E-01
iter, ran, diff:  78  3.249701648891658579E-01  2.746286719594053238E-01
iter, ran, diff:  79  4.110801709961720007E-01  8.611000610700614288E-02
iter, ran, diff:  80  7.268168600551945246E-01  3.157366890590225239E-01
iter, ran, diff:  81  1.325575271289949342E-01 -5.942593329261995905E-01
iter, ran, diff:  82  2.147735613282293343E-01  8.221603419923440015E-02
iter, ran, diff:  83  8.951429003614350677E-01  6.803693390332057334E-01
iter, ran, diff:  84  9.606624794444940107E-02 -7.990766524169856666E-01
iter, ran, diff:  85  8.749502748152764298E-01  7.788840268708270287E-01
iter, ran, diff:  86  6.864316089628772488E-01 -1.885186658523991809E-01
iter, ran, diff:  87  3.753116578189263919E-01 -3.111199511439508569E-01
iter, ran, diff:  88  4.614216639259325348E-01  8.611000610700614288E-02
iter, ran, diff:  89  8.632683590919612016E-01  4.018466951660286668E-01
iter, ran, diff:  90  5.110403908483931446E-01 -3.522279682435680570E-01
iter, ran, diff:  91  3.512250603649960112E-01 -1.598153304833971333E-01
iter, ran, diff:  92  2.984351275420635830E-01 -5.278993282293242828E-02
iter, ran, diff:  93  7.902858007228701354E-01  4.918506731808065524E-01
iter, ran, diff:  94  9.136098520217217356E-01  1.233240512988516002E-01
iter, ran, diff:  95  8.360105557375590024E-01 -7.759929628416273317E-02
iter, ran, diff:  96  7.623052313611680120E-01 -7.370532437639099044E-02
iter, ran, diff:  97  2.525198759725810760E-02 -7.370532437639099044E-01
iter, ran, diff:  98  9.228433278518650695E-01  8.975913402546069619E-01
iter, ran, diff:  99  1.283834133499510699E-01 -7.944599145019139996E-01
iter, ran, diff: 100  7.311534560989940701E-01  6.027700427490430002E-01

生成的前10个数字中有8个是重复的!这很好地说明了为什么一些发生器首先需要高熵状态。然而,经过“一段时间”后,这些数字开始显得合理。

从注释中可以看出,一些编译器试图通过以某种方式处理输入状态以产生实际的内部状态来消除不良行为。Gfortran使用“异或密码”。操作在 get .