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Some         1  10        RR RandomStateRk0 Rk1 Ŗ          Some   " $ #$  "#!  % ! %     &!Some  &  ( ) *    ()*'  , -    =,-+  u/0u2u.u./u.2u3.u 4.u  73v  84u 6 78u 5 6u 5 v! 9v! 9x ;xy  =3y  <=y  ?4y  >?y @y @x] x ķ;<>@:x]                  uv Aȍ         HashMap base ˶   ի ի  ի           NoneSome0񸑔Ä6                     uu  uuu uuuuuu uv v x]xy y y y yrng length amount cache  out iter i j tmp e x  x  &left_valu 3 right_valu  4kindv 9                                  rng         G      rng  G       I      rng  I       I      rng  I       I      rng  I                                rng         G      rng  G       I      rng  I      B    rng  B܀ ܀     B΀  ܀ ܀ rng  B        *  ) * *  0 * Some      NoneSome0񸑔Ä6 *       rng c      # #  #            Mӓ Ó       rngÓ  M  'ݙ ϙ  '             Some  Vբ բ  V ١ NoneSome0񸑔Ä6   V  V     rng ١                                              j jWrapping0 9 j j       ChaChaRng buffer state index͑       q           @Rangestartendʴ4   D       B                            g                                                  !  ! $  #$ &  %&  ƍ#%"   '  '" +  *+  *  )   ( () ,  ,( /  ./ 1  01  .0-   2  2- 5   45 7  67  ƍ463  8   83 <   ;<  ; :  9 9: =   =9 @  ?@ B   AB  ?A>  C  C> F  EF H  GH  ƍEGD  I  ID M  LM  L K  J JK N  NJ Q  PQ S  RS  PRO  T  TO W   VW Y  XY  ƍVXU  Z   ZU ^   ]^  ] \  [ [\ _   _[ b   ab d   cd  ac`  e   e` h  gh j   ij  ƍgif  k  kf o  no  n  m  l lm p  pl s  rs u  tu  rtq  v  vq y   xy {  z{  ƍxzw  |   |w       ~  } }~    }                        ƍ                                    ƍ           !               "              ƍ#           $              %            ƍ&          '               (              ƍ)          *              +            ƍ,          -               .              ƍ/           0              1            ƍ2          3               4              ƍ5          6              7            ƍ8          9               :              ƍ;           <              =            ƍ>          ?               @              ƍA          B              C             ƍD            E                 F              ƍG           H              I             ƍJ            K                 L              ƍM          N              O             ƍP            Q                R            ƍS           T              U             ƍV            W                X            ƍY          Z              [            ƍ\          ]               ^              ƍ_           `              a            ƍb          c               d              ƍe          f       D  Ih    i    ljk Some       m          n   o        p  Ih  D I 1              D                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                 Iի  Iի ի     I             output input iter iter i                                           %  % %    %    %             a   م         % % self value                                 ^    @UUIterMutUptrTUendTU_markerT׷   G        B        Some            RangeFull ۆK     G    م       G ,م         NoneSome0񸑔Ä6     G           other key iter word  ʜ ʜ   œ          ͜ *͜ *ޜ  ͜ *           2 2   2  բ բ բ բ բ բ բ        !΢ Ϣ Ϣ Ϣ Ѣ ΢                      { {¢  { { { { {         IsaacRng cnt rsl mem a b cޅ憨f ΢ Ϣ                        i                  i                i                i  `                                   ϙ   ^ϙ     @UUIterUptrTUendTU_markerTLϙ          Bњ      Some ϙ  Some          Bի             @Mapiterf5ի          Bԟ       Some " #"   #"   !#ʹ %ʹ ʹ  %  $ʹ   (! )  *()  *()  '*  +   , '+  ,+'  &'  /  0$  ƍ/0.   3!ź 4  534  534  25  6   7 26  762  12 &  &.1- & * -  ?&    ? >   =>  <=  @  1 ;<@ ; A ; ; B ;A ; BA; ; :;  C  :C9   D   9D8   E8  G! 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[  \Z[  \Z["  Y\  ]   ^ Y]  ^]Y#  YX ` a`   a` $ _aѽ  cѽ  ѽ c b%ѽ   f_ g  hfg  hfg&  eh  i   j ei  jie'  de m nb  ƍmnl( ž q_̾ rž sqrž  sqr)ž ps t  u pt  utp* op & &lok+ & *k }d  } |,  {| z{ ~  1yz~ ; ; ; y ; y- ;xy   xw.    wv/  v _    0       1 ׿ v׿ ׿ ܿ 2׿    3      1 ; ; ;  ; 4 ; dҿ ҿ 5ҿ ο   _    6       7       8 ʹ ʹ ʹ  9ʹ      :       ;     ƍ<  ź    =       >  & &? & *    @      1 ; ; ;  ; A ;   B    C       D       E л л л ջ Fл    G      1 ; ; ;  ; H ; ˻ ˻ I˻ ǻ       J       K       L ѽ ѽ ѽ  Mѽ      N       O     ƍP ž ̾ ž ž  Qž       R  & &S & *    T      1 ; ; ;  ; U ;   V    W       X       Y ׿ ׿ ׿ ܿ Z׿    [      1 ; ; ;  ; \ ; ҿ ҿ ]ҿ ο       ^       _     ݷ            ǽ          ǽ     ֌        ϙ ϙ ϙ њ њ    њ NoneSome0񸑔Ä6  њ      ԟ  ԟ  ի   ԟ   ԟ       Ĺ ʹ          &      ź        ; 1      ; ;         ˻  ; 1   л л   ; ;           ˽  ѽ          &    ž ž ̾ ž      ; 1      ; ;         ҿ  ; 1   ׿ ׿   ; ;           Ĺ ʹ         &      ź       ; 1      ; ;         ˻  ; 1   л л   ; ;           ˽ ѽ         &    ž ž ̾ ž      ; 1      ; ;         ҿ  ; 1   ׿ ׿   ; ;            self a b r  iter  mr_offset  m2_offset iter i  base !mixĹ  $x  &y  8base  _mix˽  bx dy vbase mixĹ x y base mix˽ x y        ջ     ܿ     ջ     ܿ      Ҷ       Ҷ  , ,   ,                   Ω&assertion failed: self.cnt < RAND_SIZE&&           )  ) )  )   +            +  +  +  ) )self               x     ֌        ^        3  \  3                                    o֌  ֗ ט      ê ט    ê      other ret ptr slice       " "  "         2 2   2              !                           w w  wWrapping0 9 w  w  w  w          Isaac64Rng cnt rsl mem a b c޸֩   Χ                      i                  i                i                i    Ƈ       Ƈ  * *   *                      ϙ  ч Bч B߇ ϙ ϙ ч B         ؚ  D      ޸ self  D  ٛ ٛ ޛ  ޛ           Ω)assertion failed: self.cnt < RAND_SIZE_64?))        ,  , ,   ,    .  Ν   ޸  ٛ ޸ ٛ     . " .  , ,self     ͟ џ ˟ П ͟    ˟  ̟ x͟ ˟      ͦ ׽ ͦ   ͦ զ  ^ զ ͦ ט     0    0ŧ  ֧  ŧ ˧   ˧                   Ȩ Ȩ ̨  Ѩ ̨  ץ   æ  l   ט Ǧ  ͦ  ͦ  ׽ ͦ ê ט  ŧ ŧ ê֧    Ȩ ޸ Ȩ other ret ptrǦ slice ץ             ƍ                  ƍ           ƍ   ƍ    )      Z    XorShiftRng x y z wӖu                   self x t w_                       x                      x                                F                      3 3 3 3 3    \     F  F  F       3  3  3  3  3  3  3  3  rng tuple x  y  z  w_               ggg Selfg gg g g g g g gg  g gg;hgi g  g g;g g;gg;gg; gg g;gg;gg; gselfg gisss s ss s+s sss  stt ttrssLs r r sss sssst tselfr tmpsresultsrs s r r r#r#rr#ssr!r!rr!yyy  y yy y+y zyy  yzz z?zxyyLy x x yyy yyyzz zselfx tmpyresultyxy y xx?x+x+xx+yyx(x(xx(  ^  @UUIterMutUptrTUendTU_markerT׷    B      Some        ݈܈ Ԉ             م Ȃ êӂ݅   ê NoneSome0񸑔Ä6      ܈ ݈  selfȂ destӂcount݅ numiterbyte    ʌR   self R55   Generator rng _marker? ǐ  5 self  <<<<<<<<     < <QQ'%Rng.gen_range called with low >= high%% Q՘՘՘ ژژژ ʘʘ  h   ʘʘ&   ʘ&  RangelowXrangeX accept_zoneX݋          Ǘ җڗ< QQʘ&  ʘ&ʘ& ʘʘ&՘ʘ&ژʘ& selfǗ lowҗhighڗ ####ƛ؛ƛ˛   ՛˛ƛ ޛ##u   ###ƛ#ƛ# ƛ#؛self nu   AsciiGenerator rng^    self  ^ }ȣ ȣ     ţ ' '   '   ((..Some.} NoneSome0񸑔Ä6   }}.(.(.. .ȣ .ȣ ''self valuesΥΥեӏ ե Υ˥  Ŧ צ Ŧʦ   Ԧ ʦ      # #))Some )˥WNoneSome0񸑔Ä6    ˥Υ˥Υ ) #) #)Ŧ) Ŧ)צself valueslen   (   ŭŭɭŭ ɭŭ    ­ ( ^   !ݭݫ  ֙  (֙ ( ŭŭŭself valuesi®®®ˮ ˮ ۮA  ®® self A  A   self AЯЯЯٯ ٯ A¯  ЯЯ self A  A   self A  S İ êϰêİ selfİ destϰSUniquepointer_marker,NonNullpointer  ձA Box01lۗ    self ձAIJIJ   IJIJͲͲ ݲA  IJIJ   self A     A     self Aҳҳ   ҳҳ۳ ۳ Aij  ҳҳ   self A    ĴS  êê   self destS SomeDNoneSome0񸑔Ä6    Generator rng _marker?  self D& & & /ƽ E ƽ08>>Some>ݽȻ ޻    AsciiGenerator rng^л >8>0>ݻ />NoneSome0񸑔Ä6ݻ &>&>>л selfл Ȼaaaa >aa a a    A   StdRng rng֜  ޸ self A   A  ޸ self A000   ))Rc)ptr()phantom(ڒC&&RefCell&borrow$&value$ý+  ReseedingRng rng generation_threshold bytes_generated reseederזS    ThreadRngReseeder Ƙ           t        &  ''' ''RefMut'value$'borrow$'marker$ '' '    bb    ThreadRng rngʿγ ê'  '' ''  '' '  ' ' 'êself bytesb      88   8 e' 'F J  F'FFFF rngiterableamountѱݱѱѱѱѱ ѱݱ ݱ ݱݱ  ݱ      ՇѱՇݱՇѱՇѱՇѱݱՇݱՇݱՇՇself __self_0_0ѱ __self_0_1ݱ __self_0_2ѱݱ Range  O  ѱѱlowѱ ѱѱѱѱ N L   ݱݱrangeݱݱݱݱݱ   accept_zone  "!" !  # L#$Ok0Err0Ũ͆Error ۿ6  NN FormatterNflagsLNfillLNalignLNwidthLN precisionLNbufLƒBՇѱՇݱՇ LL DebugStructLfmtLLresultLL has_fieldsLݞ    ѱѱ ѱ Շѱ ѱՇѱ  ݱݱ ݱ ݱ ݱՇݱ     Շ selff __self_0_0ѱ __self_0_1ݱ __self_0_2debug_trait_builder    ,, Wrapping0 9 ,.        # #   #  ٿRangelowXrangeX accept_zoneX݋  ,     #lowhighrange unsigned_max  zone ٿ         $ $  11 Wrapping0 9   13    1  $rrngv    ,, Wrapping0 9 ,.        # #   #  ٿRangelowXrangeX accept_zoneX݋  ,     #lowhighrange unsigned_max  zone ٿ          $ $  11 Wrapping0 9ى   13    ى 1ى ى $rrngv    ,, ,.        # #   #  ٿRangelowXrangeX accept_zoneX݋ ,   #lowhighrange unsigned_max  zone ٿ         $ $  11 Wrapping0 9   13  ֒  1  $rrngv    ,,   ,.        # #   #  ٿRangelowXrangeX accept_zoneX݋  ,     #lowhighrange unsigned_max  zone ٿ         $ $  11 Wrapping0 9   13    1  $rrngv    ,, Wrapping0 9 ,.        # #   #  ٿRangelowXrangeX accept_zoneX݋  ,     #lowhighrange unsigned_max  zone ٿ          $ $  11 Wrapping0 9Ƽ   13  ߴ  Ƽ 1Ƽ Ƽ $rrngv,, ,.            # #   #  ٿRangelowXrangeX accept_zoneX݋  ,      #lowhighrange unsigned_max  zone ٿ            $ $  11     13   1  $rrngv       , ,  , .                        #  #    #          ٿ   RangelowXrangeX accept_zoneX݋      ,              ń #      low high range  unsigned_max   zone  ٿ                              $ $   1 1      1 3               1   $    r rng v  !!!!!!!,!, !,!.! !!  ! !  ! !! !!  !  !# !#   !# !!! !!!!!!ٿ!!!! !!!!,!!!!! !! !! !!!#!!!!!!low!high!range! unsigned_max!  zone! !ٿ!!!!!!!! ! ! ! !  ! !! !!  !  !$ !$  !1!1  !1!3!!!!!!!!!!!!!1!!!$!!!!r!rng!v!!""""""",", ","." ""  " "  " "" ""  "  "# "#   "# """ """"""ٿ"""RangelowXrangeX accept_zoneX݋" """ ", "" """ "" "" """#""""""low"high"range" unsigned_max"  zone" "ٿ"""""""" " " " "  " "" ""  "  "$ "$  "1"1     "1"3"""  """"""""" "1 "" "$""""r"rng"v""#######,#, #,#.# ##  # #  # ## ##  #  ## ##   ## ### ######ٿ###RangelowXrangeX accept_zoneX݋# ### #, ## ### ## ## ##########low#high#range# unsigned_max#  zone# #ٿ##### ### # # # #  # ## ##  #  #$ #$  #1#1     #1#3###  ######### #1 ## #$####r#rng#v##$$$$$ $ $$"$$~ RangelowXrangeX accept_zoneX݋$$$"$$"$$"$$"$$"$r$rng$$~%%%%%݁% %%"%%~ RangelowXrangeX accept_zoneX݋%%%"%%"%%"%%"%%"%r%rng%%~&&&&&&self&&))))))) )self)),,,,,,,self,,////////self//:ʓ:ϓ:ʓ:ʓ:ʓ:ʓself:ʓ:ʓ===== =self==DDDDDDDDselfDDOOOOOOOselfOOVVVVήV ήVselfVVYYYYYYYselfYY``````self``ggggg gselfggjjjjגjjselfjjq) PhantomDataͦ. qqq RandSample  qqq qqq q) q)_markerq) q)q)q)q)  qq    qqqq qqqqqq qq q  q)  q qqq q qq)q) q) ן q) q)ן q)q qselfqfq __self_0_0q)debug_trait_builderqss ssss  s  s s  s ssssss WeightedweightitemŨ࿉+s  s s֢s sss ss sss s֢s s֢s selfs __self_0_0s __self_0_1s stt tt tWeightedt tt ttt t tweight?t tttt tt    ttt t itemt t t t t  tt tttt ttttttt t t t t֢t   t ttt t ttt t  t t t t tt t t ֢t  t ֢t t tselftft __self_0_0t __self_0_1t debug_trait_buildertuuuu uWeightedChoiceu uu uuu u uitemsu uuuu uu    uuuu weight_range  uuuuu uu uuuu uu uuuuu uu u uu  u uuu u uuu u  u u u u uuu u u uuu uselfufu __self_0_0u __self_0_1udebug_trait_builderu     NoTimer  CoarseTimer  NotMonotonic  TinyVariantions  TooManyStuck  __Nonexhaustive×        self                                                        self other  __self_vi  __arg_1_vi    self    ReadRng           reader? 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!Ɲ  "ŝ   "ŝ  "Ɲ  #ŝ   #ŝ  #Ɲ    $                                                                                                              *                    s  sȞ   *  *  *  *  *  *  *  *  *  *  *  *  *  *  *  *  *  *  *  *  *  *  *  *  *  *  *  * _rng  s                         ŝ     ŝ   ŝ   ŝ  Ɲ  ŝ   ŝ  Ɲ  ŝ   ŝ  Ɲ  ŝ   ŝ   Ɲ   ŝ    ŝ   Ɲ    ŝ    ŝ   Ɲ    ŝ    ŝ   Ɲ    ŝ    ŝ    Ɲ    ŝ    ŝ   Ɲ   ŝ   ŝ   Ɲ  ŝ   ŝ   Ɲ  ŝ   ŝ   Ɲ  ŝ   ŝ  Ɲ   ŝ    ŝ   Ɲ  !ŝ   !ŝ  !Ɲ  "ŝ   "ŝ  "Ɲ  #ŝ   #ŝ  #Ɲ    $                                                               ŝ     ŝ   ŝ   ŝ  Ɲ  ŝ   ŝ  Ɲ  ŝ   ŝ  Ɲ  ŝ   ŝ  Ɲ  ŝ   ŝ   Ɲ   ŝ    ŝ   Ɲ    ŝ    ŝ   Ɲ    ŝ    ŝ    Ɲ    ŝ    ŝ    Ɲ    ŝ    ŝ   Ɲ   ŝ   ŝ   Ɲ  ŝ   ŝ   Ɲ   ŝ    ŝ   Ɲ  !ŝ   !ŝ  !Ɲ  "ŝ   "ŝ  "Ɲ  #ŝ   #ŝ  #Ɲ  $ŝ   $ŝ  $Ɲ  %ŝ   %ŝ  %Ɲ    &                                                                                                           *                    s  s Ȟ   *  *  *  *  *  *  *  *  *  *  *  *  *  *  *  *  *  *  *  *  *  *  *  *  *  * _rng  s                          ŝ     ŝ   ŝ   ŝ  Ɲ  ŝ   ŝ  Ɲ  ŝ   ŝ  Ɲ  ŝ   ŝ  Ɲ  ŝ   ŝ   Ɲ   ŝ    ŝ   Ɲ    ŝ    ŝ   Ɲ    ŝ    ŝ    Ɲ    ŝ    ŝ    Ɲ    ŝ    ŝ   Ɲ   ŝ   ŝ   Ɲ  ŝ   ŝ   Ɲ   ŝ    ŝ   Ɲ  !ŝ   !ŝ  !Ɲ  "ŝ   "ŝ  "Ɲ  #ŝ   #ŝ  #Ɲ  $ŝ   $ŝ  $Ɲ  %ŝ   %ŝ  %Ɲ    &                                                                  ŝ     ŝ   ŝ   ŝ  Ɲ  ŝ   ŝ  Ɲ  ŝ   ŝ  Ɲ  ŝ   ŝ  Ɲ  ŝ   ŝ  Ɲ  ŝ   ŝ   Ɲ   ŝ    ŝ   Ɲ    ŝ    ŝ    Ɲ    ŝ    ŝ    Ɲ    ŝ    ŝ    Ɲ    ŝ    ŝ   Ɲ    ŝ    ŝ    Ɲ  !ŝ   !ŝ  !Ɲ  "ŝ   "ŝ  "Ɲ  #ŝ   #ŝ  #Ɲ  $ŝ   $ŝ  $Ɲ  %ŝ   %ŝ  %Ɲ  &ŝ   &ŝ  &Ɲ  'ŝ   'ŝ  'Ɲ    (                                                                                                        *                   s  s Ȟ   *  *  *  *  *  *  *  *  *  *  *  *  *  *  *  *  *  *  *  *  *  *  *  * _rng  s                           ŝ     ŝ   ŝ   ŝ  Ɲ  ŝ   ŝ  Ɲ  ŝ   ŝ  Ɲ  ŝ   ŝ  Ɲ  ŝ   ŝ  Ɲ  ŝ   ŝ   Ɲ   ŝ    ŝ   Ɲ    ŝ    ŝ    Ɲ    ŝ    ŝ    Ɲ    ŝ    ŝ    Ɲ    ŝ    ŝ   Ɲ    ŝ    ŝ    Ɲ  !ŝ   !ŝ  !Ɲ  "ŝ   "ŝ  "Ɲ  #ŝ   #ŝ  #Ɲ  $ŝ   $ŝ  $Ɲ  %ŝ   %ŝ  %Ɲ  &ŝ   &ŝ  &Ɲ  'ŝ   'ŝ  'Ɲ    (                                                                     ŝ     ŝ   ŝ   ŝ  Ɲ  ŝ   ŝ  Ɲ  ŝ   ŝ  Ɲ  ŝ   ŝ  Ɲ  ŝ   ŝ  Ɲ  ŝ   ŝ  Ɲ  ŝ   ŝ   Ɲ   ŝ    ŝ    Ɲ    ŝ    ŝ    Ɲ    ŝ    ŝ    Ɲ     ŝ     ŝ     Ɲ   ! ŝ   ! ŝ   !Ɲ   "ŝ   "ŝ  "Ɲ  #ŝ   #ŝ  #Ɲ  $ŝ   $ŝ  $Ɲ  %ŝ   %ŝ  %Ɲ  &ŝ   &ŝ  &Ɲ  'ŝ   'ŝ  'Ɲ  (ŝ   (ŝ  (Ɲ  )ŝ   )ŝ  )Ɲ    *                                                                                                     *                   s  s Ȟ   *  *  *  *  *  *  *  *  *  *  *  *  *  *  *  *  *  *  *  *  *  * _rng  s                            ŝ     ŝ   ŝ   ŝ  Ɲ  ŝ   ŝ  Ɲ  ŝ   ŝ  Ɲ  ŝ   ŝ  Ɲ  ŝ   ŝ  Ɲ  ŝ   ŝ  Ɲ  ŝ   ŝ   Ɲ   ŝ    ŝ    Ɲ    ŝ    ŝ    Ɲ    ŝ    ŝ    Ɲ     ŝ     ŝ     Ɲ   ! ŝ   ! ŝ   !Ɲ   "ŝ   "ŝ  "Ɲ  #ŝ   #ŝ  #Ɲ  $ŝ   $ŝ  $Ɲ  %ŝ   %ŝ  %Ɲ  &ŝ   &ŝ  &Ɲ  'ŝ   'ŝ  'Ɲ  (ŝ   (ŝ  (Ɲ  )ŝ   )ŝ  )Ɲ    *                                                                        ŝ     ŝ   ŝ   ŝ  Ɲ  ŝ   ŝ  Ɲ  ŝ   ŝ  Ɲ  ŝ   ŝ  Ɲ  ŝ   ŝ  Ɲ  ŝ   ŝ  Ɲ  ŝ   ŝ  Ɲ  ŝ   ŝ    Ɲ   ŝ    ŝ    Ɲ     ŝ     ŝ     Ɲ   ! ŝ   ! ŝ    !Ɲ   " ŝ   " ŝ    "Ɲ   # ŝ   # ŝ  #Ɲ   $ŝ   $ŝ  $Ɲ  %ŝ   %ŝ  %Ɲ  &ŝ   &ŝ  &Ɲ  'ŝ   'ŝ  'Ɲ  (ŝ   (ŝ  (Ɲ  )ŝ   )ŝ  )Ɲ  *ŝ   *ŝ  *Ɲ  +ŝ   +ŝ  +Ɲ    ,                                                                                                  *                   s  s Ȟ   *  *  *  *  *  *  *  *  *  *  *  *  *  *  *  *  *  *  *  * _rng  s                             ŝ     ŝ   ŝ   ŝ  Ɲ  ŝ   ŝ  Ɲ  ŝ   ŝ  Ɲ  ŝ   ŝ  Ɲ  ŝ   ŝ  Ɲ  ŝ   ŝ  Ɲ  ŝ   ŝ  Ɲ  ŝ   ŝ    Ɲ   ŝ    ŝ    Ɲ     ŝ     ŝ     Ɲ   ! ŝ   ! ŝ    !Ɲ   " ŝ   " ŝ    "Ɲ   # ŝ   # ŝ  #Ɲ   $ŝ   $ŝ  $Ɲ  %ŝ   %ŝ  %Ɲ  &ŝ   &ŝ  &Ɲ  'ŝ   'ŝ  'Ɲ  (ŝ   (ŝ  (Ɲ  )ŝ   )ŝ  )Ɲ  *ŝ   *ŝ  *Ɲ  +ŝ   +ŝ  +Ɲ    ,                                                                           ŝ     ŝ   ŝ   ŝ  Ɲ  ŝ   ŝ  Ɲ  ŝ   ŝ  Ɲ  ŝ   ŝ  Ɲ  ŝ   ŝ  Ɲ  ŝ   ŝ  Ɲ  ŝ   ŝ  Ɲ  ŝ   ŝ   Ɲ   ŝ    ŝ     Ɲ  ! ŝ   ! ŝ    !Ɲ   " ŝ   " ŝ    "Ɲ   # ŝ   # ŝ    #Ɲ   $ ŝ   $ ŝ   $Ɲ   % ŝ   % ŝ  %Ɲ   &ŝ   &ŝ  &Ɲ  'ŝ   'ŝ  'Ɲ  (ŝ   (ŝ  (Ɲ  )ŝ   )ŝ  )Ɲ  *ŝ   *ŝ  *Ɲ  +ŝ   +ŝ  +Ɲ  ,ŝ   ,ŝ  ,Ɲ  -ŝ   -ŝ  -Ɲ    .                                                                                               *                  s  s Ȟ   *  *  *  *  *  *  *  *  *  *  *  *  *  *  *  *  *  * _rng  s                              ŝ     ŝ   ŝ   ŝ  Ɲ  ŝ   ŝ  Ɲ  ŝ   ŝ  Ɲ  ŝ   ŝ  Ɲ  ŝ   ŝ  Ɲ  ŝ   ŝ  Ɲ  ŝ   ŝ  Ɲ  ŝ   ŝ   Ɲ   ŝ    ŝ     Ɲ  ! ŝ   ! ŝ    !Ɲ   " ŝ   " ŝ    "Ɲ   # ŝ   # ŝ    #Ɲ   $ ŝ   $ ŝ   $Ɲ   % ŝ   % ŝ  %Ɲ   &ŝ   &ŝ  &Ɲ  'ŝ   'ŝ  'Ɲ  (ŝ   (ŝ  (Ɲ  )ŝ   )ŝ  )Ɲ  *ŝ   *ŝ  *Ɲ  +ŝ   +ŝ  +Ɲ  ,ŝ   ,ŝ  ,Ɲ  -ŝ   -ŝ  -Ɲ    .                                                                              ŝ     ŝ   ŝ   ŝ  Ɲ  ŝ   ŝ  Ɲ  ŝ   ŝ  Ɲ  ŝ   ŝ  Ɲ  ŝ   ŝ  Ɲ  ŝ   ŝ  Ɲ  ŝ   ŝ  Ɲ   ŝ    ŝ    Ɲ  !ŝ   !ŝ   !Ɲ  "ŝ   "ŝ    "Ɲ  # ŝ   # ŝ    #Ɲ   $ ŝ   $ ŝ    $Ɲ   % ŝ   % ŝ   %Ɲ   & ŝ   & ŝ   &Ɲ   ' ŝ   ' ŝ  'Ɲ   (ŝ   (ŝ  (Ɲ  )ŝ   )ŝ  )Ɲ  *ŝ   *ŝ  *Ɲ  +ŝ   +ŝ  +Ɲ  ,ŝ   ,ŝ  ,Ɲ  -ŝ   -ŝ  -Ɲ  .ŝ   .ŝ  .Ɲ  /ŝ   /ŝ  /Ɲ    0                                                                                             *                s  sȞ   *  *  *  *  *  *  *  *  *  *  *  *  *  *  *  * _rng  s                               ŝ     ŝ   ŝ   ŝ  Ɲ  ŝ   ŝ  Ɲ  ŝ   ŝ  Ɲ  ŝ   ŝ  Ɲ  ŝ   ŝ  Ɲ  ŝ   ŝ  Ɲ  ŝ   ŝ  Ɲ   ŝ    ŝ    Ɲ  !ŝ   !ŝ   !Ɲ  "ŝ   "ŝ    "Ɲ  # ŝ   # ŝ    #Ɲ   $ ŝ   $ ŝ    $Ɲ   % ŝ   % ŝ   %Ɲ   & ŝ   & ŝ   &Ɲ   ' ŝ   ' ŝ  'Ɲ   (ŝ   (ŝ  (Ɲ  )ŝ   )ŝ  )Ɲ  *ŝ   *ŝ  *Ɲ  +ŝ   +ŝ  +Ɲ  ,ŝ   ,ŝ  ,Ɲ  -ŝ   -ŝ  -Ɲ  .ŝ   .ŝ  .Ɲ  /ŝ   /ŝ  /Ɲ    0                                                                                 ŝ     ŝ   ŝ   ŝ  Ɲ  ŝ   ŝ  Ɲ  ŝ   ŝ  Ɲ  ŝ   ŝ  Ɲ  ŝ   ŝ  Ɲ  ŝ   ŝ  Ɲ   ŝ    ŝ   Ɲ  !ŝ   !ŝ   !Ɲ  "ŝ   "ŝ   "Ɲ  #ŝ   #ŝ   #Ɲ  $ŝ   $ŝ    $Ɲ  % ŝ   % ŝ    %Ɲ   & ŝ   & ŝ   &Ɲ   ' ŝ   ' ŝ   'Ɲ   ( ŝ   ( ŝ   (Ɲ   ) ŝ   ) ŝ  )Ɲ   *ŝ   *ŝ  *Ɲ  +ŝ   +ŝ  +Ɲ  ,ŝ   ,ŝ  ,Ɲ  -ŝ   -ŝ  -Ɲ  .ŝ   .ŝ  .Ɲ  /ŝ   /ŝ  /Ɲ  0ŝ   0ŝ  0Ɲ  1ŝ   1ŝ  1Ɲ    2                                                                                           *                s  sȞ   *  *  *  *  *  *  *  *  *  *  *  *  *  * _rng  s                                ŝ     ŝ   ŝ   ŝ  Ɲ  ŝ   ŝ  Ɲ  ŝ   ŝ  Ɲ  ŝ   ŝ  Ɲ  ŝ   ŝ  Ɲ  ŝ   ŝ  Ɲ   ŝ    ŝ   Ɲ  !ŝ   !ŝ   !Ɲ  "ŝ   "ŝ   "Ɲ  #ŝ   #ŝ   #Ɲ  $ŝ   $ŝ    $Ɲ  % ŝ   % ŝ    %Ɲ   & ŝ   & ŝ   &Ɲ   ' ŝ   ' ŝ   'Ɲ   ( ŝ   ( ŝ   (Ɲ   ) ŝ   ) ŝ  )Ɲ   *ŝ   *ŝ  *Ɲ  +ŝ   +ŝ  +Ɲ  ,ŝ   ,ŝ  ,Ɲ  -ŝ   -ŝ  -Ɲ  .ŝ   .ŝ  .Ɲ  /ŝ   /ŝ  /Ɲ  0ŝ   0ŝ  0Ɲ  1ŝ   1ŝ  1Ɲ    2                                                                                    ŝ     ŝ   ŝ   ŝ  Ɲ  ŝ   ŝ  Ɲ  ŝ   ŝ  Ɲ  ŝ   ŝ  Ɲ  ŝ   ŝ  Ɲ   ŝ    ŝ   Ɲ  !ŝ   !ŝ  !Ɲ  "ŝ   "ŝ   "Ɲ  #ŝ   #ŝ   #Ɲ  $ŝ   $ŝ   $Ɲ  %ŝ   %ŝ   %Ɲ  &ŝ   &ŝ    &Ɲ  ' ŝ   ' ŝ   'Ɲ   ( ŝ   ( ŝ   (Ɲ   ) ŝ   ) ŝ   )Ɲ   * ŝ   * ŝ   *Ɲ   + ŝ   + ŝ  +Ɲ   ,ŝ   ,ŝ  ,Ɲ  -ŝ   -ŝ  -Ɲ  .ŝ   .ŝ  .Ɲ  /ŝ   /ŝ  /Ɲ  0ŝ   0ŝ  0Ɲ  1ŝ   1ŝ  1Ɲ  2ŝ   2ŝ  2Ɲ  3ŝ   3ŝ  3Ɲ    4                                                                                        *               s  sȞ   *  *  *  *  *  *  *  *  *  *  *  * _rng  s                                 ŝ     ŝ   ŝ   ŝ  Ɲ  ŝ   ŝ  Ɲ  ŝ   ŝ  Ɲ  ŝ   ŝ  Ɲ  ŝ   ŝ  Ɲ   ŝ    ŝ   Ɲ  !ŝ   !ŝ  !Ɲ  "ŝ   "ŝ   "Ɲ  #ŝ   #ŝ   #Ɲ  $ŝ   $ŝ   $Ɲ  %ŝ   %ŝ   %Ɲ  &ŝ   &ŝ    &Ɲ  ' ŝ   ' ŝ   'Ɲ   ( ŝ   ( ŝ   (Ɲ   ) ŝ   ) ŝ   )Ɲ   * ŝ   * ŝ   *Ɲ   + ŝ   + ŝ  +Ɲ   ,ŝ   ,ŝ  ,Ɲ  -ŝ   -ŝ  -Ɲ  .ŝ   .ŝ  .Ɲ  /ŝ   /ŝ  /Ɲ  0ŝ   0ŝ  0Ɲ  1ŝ   1ŝ  1Ɲ  2ŝ   2ŝ  2Ɲ  3ŝ   3ŝ  3Ɲ    4                                                                                       ŝ     ŝ   ŝ   ŝ  Ɲ  ŝ   ŝ  Ɲ  ŝ   ŝ  Ɲ  ŝ   ŝ  Ɲ   ŝ    ŝ   Ɲ  !ŝ   !ŝ  !Ɲ  "ŝ   "ŝ  "Ɲ  #ŝ   #ŝ   #Ɲ  $ŝ   $ŝ   $Ɲ  %ŝ   %ŝ   %Ɲ  &ŝ   &ŝ   &Ɲ  'ŝ   'ŝ   'Ɲ  (ŝ   (ŝ   (Ɲ  ) ŝ   ) ŝ   )Ɲ   * ŝ   * ŝ   *Ɲ   + ŝ   + ŝ   +Ɲ   , ŝ   , ŝ   ,Ɲ   - ŝ   - ŝ  -Ɲ   .ŝ   .ŝ  .Ɲ  /ŝ   /ŝ  /Ɲ  0ŝ   0ŝ  0Ɲ  1ŝ   1ŝ  1Ɲ  2ŝ   2ŝ  2Ɲ  3ŝ   3ŝ  3Ɲ  4ŝ   4ŝ  4Ɲ  5ŝ   5ŝ  5Ɲ    6                                                                                  *          s  s Ȟ   *  *  *  *  *  *  *  *  *  * _rng  s                                  ŝ     ŝ   ŝ   ŝ  Ɲ  ŝ   ŝ  Ɲ  ŝ   ŝ  Ɲ  ŝ   ŝ  Ɲ   ŝ    ŝ   Ɲ  !ŝ   !ŝ  !Ɲ  "ŝ   "ŝ  "Ɲ  #ŝ   #ŝ   #Ɲ  $ŝ   $ŝ   $Ɲ  %ŝ   %ŝ   %Ɲ  &ŝ   &ŝ   &Ɲ  'ŝ   'ŝ   'Ɲ  (ŝ   (ŝ   (Ɲ  ) ŝ   ) ŝ   )Ɲ   * ŝ   * ŝ   *Ɲ   + ŝ   + ŝ   +Ɲ   , ŝ   , ŝ   ,Ɲ   - ŝ   - ŝ  -Ɲ   .ŝ   .ŝ  .Ɲ  /ŝ   /ŝ  /Ɲ  0ŝ   0ŝ  0Ɲ  1ŝ   1ŝ  1Ɲ  2ŝ   2ŝ  2Ɲ  3ŝ   3ŝ  3Ɲ  4ŝ   4ŝ  4Ɲ  5ŝ   5ŝ  5Ɲ    6                                                                                          ŝ     ŝ   ŝ   ŝ  Ɲ  ŝ   ŝ  Ɲ  ŝ   ŝ  Ɲ   ŝ    ŝ   Ɲ  !ŝ   !ŝ  !Ɲ  "ŝ   "ŝ  "Ɲ  #ŝ   #ŝ  #Ɲ  $ŝ   $ŝ   $Ɲ  %ŝ   %ŝ   %Ɲ  &ŝ   &ŝ   &Ɲ  'ŝ   'ŝ   'Ɲ  (ŝ   (ŝ   (Ɲ  )ŝ   )ŝ  )Ɲ  *ŝ   *ŝ   *Ɲ  + ŝ   + ŝ   +Ɲ   , ŝ   , ŝ   ,Ɲ   - ŝ   - ŝ   -Ɲ   . ŝ   . ŝ   .Ɲ   / ŝ   / ŝ  /Ɲ   0ŝ   0ŝ  0Ɲ  1ŝ   1ŝ  1Ɲ  2ŝ   2ŝ  2Ɲ  3ŝ   3ŝ  3Ɲ  4ŝ   4ŝ  4Ɲ  5ŝ   5ŝ  5Ɲ  6ŝ   6ŝ  6Ɲ  7ŝ   7ŝ  7Ɲ    8                                                                             *      s  s Ȟ   *  *  *  *  *  *  *  * _rng  s                                   ŝ     ŝ   ŝ   ŝ  Ɲ  ŝ   ŝ  Ɲ  ŝ   ŝ  Ɲ   ŝ    ŝ   Ɲ  !ŝ   !ŝ  !Ɲ  "ŝ   "ŝ  "Ɲ  #ŝ   #ŝ  #Ɲ  $ŝ   $ŝ   $Ɲ  %ŝ   %ŝ   %Ɲ  &ŝ   &ŝ   &Ɲ  'ŝ   'ŝ   'Ɲ  (ŝ   (ŝ   (Ɲ  )ŝ   )ŝ  )Ɲ  *ŝ   *ŝ   *Ɲ  + ŝ   + ŝ   +Ɲ   , ŝ   , ŝ   ,Ɲ   - ŝ   - ŝ   -Ɲ   . ŝ   . ŝ   .Ɲ   / ŝ   / ŝ  /Ɲ   0ŝ   0ŝ  0Ɲ  1ŝ   1ŝ  1Ɲ  2ŝ   2ŝ  2Ɲ  3ŝ   3ŝ  3Ɲ  4ŝ   4ŝ  4Ɲ  5ŝ   5ŝ  5Ɲ  6ŝ   6ŝ  6Ɲ  7ŝ   7ŝ  7Ɲ    8                                                                                             ŝ     ŝ   ŝ   ŝ  Ɲ  ŝ   ŝ  Ɲ   ŝ    ŝ   Ɲ  !ŝ   !ŝ  !Ɲ  "ŝ   "ŝ  "Ɲ  #ŝ   #ŝ  #Ɲ  $ŝ   $ŝ  $Ɲ  %ŝ   %ŝ   %Ɲ  &ŝ   &ŝ   &Ɲ  'ŝ   'ŝ   'Ɲ  (ŝ   (ŝ   (Ɲ  )ŝ   )ŝ   )Ɲ  *ŝ   *ŝ  *Ɲ  +ŝ   +ŝ  +Ɲ  ,ŝ   ,ŝ   ,Ɲ  - ŝ   - ŝ   -Ɲ   . ŝ   . ŝ   .Ɲ   / ŝ   / ŝ   /Ɲ   0 ŝ   0 ŝ   0Ɲ   1 ŝ   1 ŝ  1Ɲ   2ŝ   2ŝ  2Ɲ  3ŝ   3ŝ  3Ɲ  4ŝ   4ŝ  4Ɲ  5ŝ   5ŝ  5Ɲ  6ŝ   6ŝ  6Ɲ  7ŝ   7ŝ  7Ɲ  8ŝ   8ŝ  8Ɲ  9ŝ   9ŝ  9Ɲ    :                                                                        *     s  sȞ   *  *  *  *  *  * _rng  s                                    ŝ     ŝ   ŝ   ŝ  Ɲ  ŝ   ŝ  Ɲ   ŝ    ŝ   Ɲ  !ŝ   !ŝ  !Ɲ  "ŝ   "ŝ  "Ɲ  #ŝ   #ŝ  #Ɲ  $ŝ   $ŝ  $Ɲ  %ŝ   %ŝ   %Ɲ  &ŝ   &ŝ   &Ɲ  'ŝ   'ŝ   'Ɲ  (ŝ   (ŝ   (Ɲ  )ŝ   )ŝ   )Ɲ  *ŝ   *ŝ  *Ɲ  +ŝ   +ŝ  +Ɲ  ,ŝ   ,ŝ   ,Ɲ  - ŝ   - ŝ   -Ɲ   . ŝ   . ŝ   .Ɲ   / ŝ   / ŝ   /Ɲ   0 ŝ   0 ŝ   0Ɲ   1 ŝ   1 ŝ  1Ɲ   2ŝ   2ŝ  2Ɲ  3ŝ   3ŝ  3Ɲ  4ŝ   4ŝ  4Ɲ  5ŝ   5ŝ  5Ɲ  6ŝ   6ŝ  6Ɲ  7ŝ   7ŝ  7Ɲ  8ŝ   8ŝ  8Ɲ  9ŝ   9ŝ  9Ɲ    :                                                                                                ŝ     ŝ   ŝ   ŝ  Ɲ   ŝ    ŝ   Ɲ  !ŝ   !ŝ  !Ɲ  "ŝ   "ŝ  "Ɲ  #ŝ   #ŝ  #Ɲ  $ŝ   $ŝ  $Ɲ  %ŝ   %ŝ  %Ɲ  &ŝ   &ŝ   &Ɲ  'ŝ   'ŝ   'Ɲ  (ŝ   (ŝ   (Ɲ  )ŝ   )ŝ   )Ɲ  *ŝ   *ŝ   *Ɲ  +ŝ   +ŝ  +Ɲ  ,ŝ   ,ŝ  ,Ɲ  -ŝ   -ŝ  -Ɲ  .ŝ   .ŝ   .Ɲ  / ŝ   / ŝ   /Ɲ   0 ŝ   0 ŝ   0Ɲ   1 ŝ   1 ŝ   1Ɲ   2 ŝ   2 ŝ   2Ɲ   3 ŝ   3 ŝ  3Ɲ   4ŝ   4ŝ  4Ɲ  5ŝ   5ŝ  5Ɲ  6ŝ   6ŝ  6Ɲ  7ŝ   7ŝ  7Ɲ  8ŝ   8ŝ  8Ɲ  9ŝ   9ŝ  9Ɲ  :ŝ   :ŝ  :Ɲ  ;ŝ   ;ŝ  ;Ɲ    <                                                                      *    s  sȞ   *  *  *  * _rng  s                                     ŝ     ŝ   ŝ   ŝ  Ɲ   ŝ    ŝ   Ɲ  !ŝ   !ŝ  !Ɲ  "ŝ   "ŝ  "Ɲ  #ŝ   #ŝ  #Ɲ  $ŝ   $ŝ  $Ɲ  %ŝ   %ŝ  %Ɲ  &ŝ   &ŝ   &Ɲ  'ŝ   'ŝ   'Ɲ  (ŝ   (ŝ   (Ɲ  )ŝ   )ŝ   )Ɲ  *ŝ   *ŝ   *Ɲ  +ŝ   +ŝ  +Ɲ  ,ŝ   ,ŝ  ,Ɲ  -ŝ   -ŝ  -Ɲ  .ŝ   .ŝ   .Ɲ  / ŝ   / ŝ   /Ɲ   0 ŝ   0 ŝ   0Ɲ   1 ŝ   1 ŝ   1Ɲ   2 ŝ   2 ŝ   2Ɲ   3 ŝ   3 ŝ  3Ɲ   4ŝ   4ŝ  4Ɲ  5ŝ   5ŝ  5Ɲ  6ŝ   6ŝ  6Ɲ  7ŝ   7ŝ  7Ɲ  8ŝ   8ŝ  8Ɲ  9ŝ   9ŝ  9Ɲ  :ŝ   :ŝ  :Ɲ  ;ŝ   ;ŝ  ;Ɲ    <                                                                                                    ŝ     ŝ    ŝ    ŝ   Ɲ  !ŝ   !ŝ  !Ɲ  "ŝ   "ŝ  "Ɲ  #ŝ   #ŝ  #Ɲ  $ŝ   $ŝ  $Ɲ  %ŝ   %ŝ  %Ɲ  &ŝ   &ŝ  &Ɲ  'ŝ   'ŝ   'Ɲ  (ŝ   (ŝ   (Ɲ  )ŝ   )ŝ   )Ɲ  *ŝ   *ŝ   *Ɲ  +ŝ   +ŝ   +Ɲ  ,ŝ   ,ŝ  ,Ɲ  -ŝ   -ŝ  -Ɲ  .ŝ   .ŝ  .Ɲ  /ŝ   /ŝ  /Ɲ  0ŝ   0ŝ   0Ɲ  1 ŝ   1 ŝ   1Ɲ   2 ŝ   2 ŝ   2Ɲ   3 ŝ   3 ŝ   3Ɲ   4 ŝ   4 ŝ   4Ɲ   5 ŝ   5 ŝ  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       self  __self_0_0  __self_0_1  __self_0_2  __self_0_3  ֶ' PhantomDataͦ.   Generator     ֶ ֶrngֶ ֶֶֶֶ     ''_marker'''''         ֶ '     ֶֶ ֶ ֶֶֶ  '' ' ''' selff __self_0_0ֶ __self_0_1'debug_trait_builderAsciiGenerator   rng                      selff __self_0_0debug_trait_builderFOpen01? O      L   L      Open01 0 ⚷ޫ)΄  ΄ LL DebugTupleLfmtLLresultLLfieldsLL empty_nameLS   ߊselff __self_0_0debug_trait_builder΄Closed01     ц        Closed01 0 㗧Ʋ΄   ߊߊselff __self_0_0debug_trait_builder    self                     self __self_0_0     NoneSome0񸑔Ä6 NoneSome0񸑔Ä6 NoneSome0񸑔Ä6  &    &  o  o MLocalKeyinner/   &  o       Err         Ok    Q*  ArgumentV1valueL formatterLEQ* Q* Q*   Q*Q* N  Q*QAQ H QA  &  )        /  Ok0Err0Ũ͆   QAQAQAQ*QAQAQAQAQ*QA Q*QAQ*QAQ*QAQAQA     rrerng  No entropy available:  /  " NoneSome0񸑔Ä6 ė " Someݨ    E   #  # Some    ɒ.ɒ. ɒ. ɒ. ɒ.        ɒɒ  ɒɒɒɒɒ ɒɒɒɒɒ  ɒ¿" ¿"¿"¿" ¿"¿"   ¿"@ן  @             M       "ݨ  ė  ݨ  #  @¿"ɒ.ɒ.ɒ.¿"¿"¿"¿"ɒ ɒԳɒɒ   ɒɒɒɒ ɒ.init init value  ɒ ɒɒ  ɒɒɒ   missing default value       ɒ. ɒ.*internal error: entered unreachable code: **ɒ.ɒ.  ɒ.ɒ.ɒ.                #   Keyinner dtor_state͋    ջ   init   * (   * w  w׻ ' wOsRnginnerХ"OsRng0 P OsReadRng  ReadRng readerFileinnerAOsGetrandomRng OsReadRng0̋ OsReadRngLargeLargeOneגגOneגגSmallSmallDoFAnythingElseDoFAnythingElse####ή#######ή###΄ ΄΄ ΄΄ я΄΄ я΄ޮ' Utilities for random number generation*M The key functions are `random()` and `Rng::gen()`. These are polymorphic andPK so can be used to generate any type that implements `Rand`. Type inferenceNG means that often a simple call to `rand::random()` or `rng.gen()` willJ7 suffice, but sometimes an annotation is required, e.g.: `rand::random::()`.C See the `distributions` submodule for sampling random numbers fromF+ distributions like normal and exponential.. # Usage G This crate is [on crates.io](https://crates.io/crates/rand) and can beJJ used by adding `rand` to the dependencies in your project's `Cargo.toml`.M ```toml  [dependencies]  rand = "0.4"  ```   and this to your crate root:   ```rust  extern crate rand;  ```   # Thread-local RNG  G There is built-in support for a RNG associated with each thread stored JG in thread-local storage. This RNG can be accessed via `thread_rng`, or JC used implicitly via `random`. This RNG is normally randomly seeded FF from an operating-system source of randomness, e.g. `/dev/urandom` on ID Unix systems, and will automatically reseed itself from this source G( after generating 32 KiB of random data. +  # Cryptographic security  J An application that requires an entropy source for cryptographic purposes ML must use `OsRng`, which reads randomness from the source that the operatingOH system provides (e.g. `/dev/urandom` on Unixes or `CryptGenRandom()` onK Windows). L The other random number generators provided by this module are not suitableO for such purposes.K *Note*: many Unix systems provide `/dev/random` as well as `/dev/urandom`.N; This module uses `/dev/urandom` for the following reasons:>@ - On Linux, `/dev/random` may block if entropy pool is empty;CJ `/dev/urandom` will not block. This does not mean that `/dev/random`MM provides better output than `/dev/urandom`; the kernel internally runs aPM cryptographically secure pseudorandom number generator (CSPRNG) based onPC entropy pool for random number generation, so the "quality" ofFM `/dev/random` is not better than `/dev/urandom` in most cases. However,PM this means that `/dev/urandom` can yield somewhat predictable randomnessPG if the entropy pool is very small, such as immediately after firstJK booting. Linux 3.17 added the `getrandom(2)` system call which solvesNM the issue: it blocks if entropy pool is not initialized yet, but it doesPH not block once initialized. `OsRng` tries to use `getrandom(2)` ifKJ available, and use `/dev/urandom` fallback if not. If an applicationMM does not have `getrandom` and likely to be run soon after first booting,PL or on a system with very few entropy sources, one should consider usingO! `/dev/random` via `ReadRng`.$E - On some systems (e.g. FreeBSD, OpenBSD and Mac OS X) there is noHI difference between the two sources. (Also note that, on some systemsLK e.g. FreeBSD, both `/dev/random` and `/dev/urandom` may block once ifN$ the CSPRNG has not seeded yet.)' # Examples ```rust  use rand::Rng;" let mut rng = rand::thread_rng();% if rng.gen() { // random bool!E println!("i32: {}, u32: {}", rng.gen::(), rng.gen::())H } ``` ```rust + let tuple = rand::random::<(f64, char)>();. println!("{:?}", tuple) ``` ## Monte Carlo estimation of π#M For this example, imagine we have a square with sides of length 2 and a unitPL circle, both centered at the origin. Since the area of a unit circle is π, O we have:   ```text 6 (area of unit circle) / (area of square) = π / 4 9 ```!!M So if we sample many points randomly from the square, roughly π / 4 of them!P should be inside the circle." "K We can use the above fact to estimate the value of π: pick many points in"NJ the square at random, calculate the fraction that fall within the circle,"M! and multiply this fraction by 4.#$# ```#5 use rand::distributions::{IndependentSample, Range};#8$ fn main() {$( let between = Range::new(-1f64, 1.);$+% let mut rng = rand::thread_rng();$(% let total = 1_000_000;% let mut in_circle = 0;%% for _ in 0..total {%- let a = between.ind_sample(&mut rng);%0- let b = between.ind_sample(&mut rng);&0 if a*a + b*b <= 1. {& in_circle += 1;& }'  }''+ // prints something close to 3.14159...'.= println!("{}", 4. * (in_circle as f64) / (total as f64));'@ }( ```(( ## Monty Hall Problem((4 This is a simulation of the [Monty Hall Problem][]:(7)M > Suppose you're on a game show, and you're given the choice of three doors:)PK > Behind one door is a car; behind the others, goats. You pick a door, say)NH > No. 1, and the host, who knows what's behind the doors, opens another*KJ > door, say No. 3, which has a goat. He then says to you, "Do you want to*MC > pick door No. 2?" Is it to your advantage to switch your choice?+F,L The rather unintuitive answer is that you will have a 2/3 chance of winning,OJ if you switch and a 1/3 chance of winning if you don't, so it's better to,M switch.- -J This program will simulate the game show and with large enough simulation-M: steps it will indeed confirm that it is better to switch..=.F [Monty Hall Problem]: http://en.wikipedia.org/wiki/Monty_Hall_problem.I/ ```/ use rand::Rng;/5 use rand::distributions::{IndependentSample, Range};/8/ struct SimulationResult {/ win: bool,0 switch: bool,0 }006 // Run a single simulation of the Monty Hall problem.09; fn simulate(random_door: &Range, rng: &mut R)1>* -> SimulationResult {1-+ let car = random_door.ind_sample(rng);1.2" // This is our initial choice2%2 let mut choice = random_door.ind_sample(rng);253" // The game host opens a door3%1 let open = game_host_open(car, choice, rng);343 // Shall we switch?3 let switch = rng.gen();4 if switch {4, choice = switch_door(choice, open);4/ }4 4< SimulationResult { win: choice == car, switch: switch }4? }55J // Returns the door the game host opens given our choice and knowledge of5MJ // where the car is. The game host will never open the door with the car.6MG fn game_host_open(car: u32, choice: u32, rng: &mut R) -> u32 {6J. let choices = free_doors(&[car, choice]);711 rand::seq::sample_slice(rng, &choices, 1)[0]74 }88? // Returns the door we switch to, given our current choice and8B5 // the open door. There will only be one valid door.880 fn switch_door(choice: u32, open: u32) -> u32 {93# free_doors(&[choice, open])[0]9& }99- fn free_doors(blocked: &[u32]) -> Vec {906 (0..3).filter(|x| !blocked.contains(x)).collect():9 }:: fn main() {:B // The estimation will be more accurate with more simulations:E! let num_simulations = 10000;;$;& let mut rng = rand::thread_rng();;)( let random_door = Range::new(0, 3);<+<7 let (mut switch_wins, mut switch_losses) = (0, 0);<:3 let (mut keep_wins, mut keep_losses) = (0, 0);<6=< println!("Running {} simulations...", num_simulations);=?" for _ in 0..num_simulations {=%7 let result = simulate(&random_door, &mut rng);>:>, match (result.win, result.switch) {>/. (true, true) => switch_wins += 1,?1- (true, false) => keep_wins += 1,?01 (false, true) => switch_losses += 1,?40 (false, false) => keep_losses += 1,@3 }@  }@ @6 let total_switches = switch_wins + switch_losses;@9/ let total_keeps = keep_wins + keep_losses;A2AB println!("Switched door {} times with {} wins and {} losses",AE: total_switches, switch_wins, switch_losses);B=BD println!("Kept our choice {} times with {} wins and {} losses",BG3 total_keeps, keep_wins, keep_losses);C6CI // With a large number of simulations, the values should converge toCL% // 0.667 and 0.333 respectively.D(9 println!("Estimated chance to win if we switch: {}",D<: switch_wins as f32 / total_switches as f32);E=8 println!("Estimated chance to win if we don't: {}",E;5 keep_wins as f32 / total_keeps as f32);F8 }F ```FFdocFFH html_logo_urlF F9https://www.rust-lang.org/logos/rust-logo-128x128-blk.pngF;G html_favicon_urlGG%https://www.rust-lang.org/favicon.icoG'G html_root_urlH Hhttps://docs.rs/rand/0.4HFHdenyHHH missing_debug_implementationsHH'prelude_import macro_use JJcfgJ JJ featureJJstdJJJKKKLLLcfgLLL featureLLstdLLLL LcfgLLL featureLLstdLLLLLcfgL%LL featureLLstdLLMMM MMcfgM1MM featureMMstdMMMM&MMN N NN NN O%OcfgOKOO target_pointer_widthOO64OO#O O.PPPPP&P P$ Sampling from random distributions.'F This is a generalization of `Rand` to allow parameters to control theIE exact properties of the generated values, e.g. the mean and standardHC deviation of a normal distribution. The `Sample` trait is the mostʷFA general, and allows for generating values that change some stateDC internally. The `IndependentSample` trait is for generating valuesָF" that do not need to record state.%P Ĺι3׹3ܹܹ33<cfgv featurestdcfgv featurestd cfgv featurestd ĺcfgv featurestdĺͺcfgv featurestdͺ*ںcfgںݺ feature޺stdغںcfgںݺ feature޺stdغ ںcfgںݺ feature޺stdغ cfg featurestdʻл' Generating numbers between two others.ѧ*ػڨXèڨXިX/XXXXXggq  ': Create a new `Range` instance that samples uniformly from=( `[low, high)`. Panics if `low >= high`.+ffȴXSupjjʹqҴ ʹʹ0iRlliڵXSupnnߵ ߵߵ0 mRppm> The helper trait for types that have a sensible way to sampleA@ uniformly between two values. This should not be used directly,ȷC# and is only to facilitate `Range`.& Selfqq ˸˸ɺ91 Construct the `Range` object that `sample_range`׸4< requires. This should not ever be called directly, only via?: `Range::new`, which will check that `low < high`, so thisԹ=+ function doesn't have to repeat the check..̺qq>> Sample a value from the given `Range` with the given `Rng` asA a source of randomness.λ qRttq   cfg featurestd߻% The Gamma and derived distributions.(wwwwww"ww,wwwww+; Construct an object representing the `Gamma(shape, scale)`> distribution.( Panics if `shape <= 0` or `scale <= 0`.+w5wwՁ5؁wlw̃0σRރփكփփvwÄ0ƄRՄ̈́Є̈́̈́vw0R̅ąDžąąw0 RɆĆwӈ0ֈ Rw0 RϊNJʊNJNJÖw > Create a new chi-squared distribution with degrees-of-freedomٖA `k`. Panics if `k < 0`.Ɨޙqw0RКw0 Rw%4 Create a new `FisherF` distribution, with the given79 parameter. Panics if either `m` or `n` are not positive.<nw٦0ܦRwӧ0֧ Rw8 Create a new Student t distribution with `n` degrees of; freedom. Panics if `n <= 0`.Ѭ owخ0ۮRwӯ0֯ Rcfg  featurestd& The normal and derived distributions.ܿ)J -R/ R-> Construct a new `Normal` distribution with the given mean andA standard deviation. # Panics  Panics if `std_dev < 0`.m0R0 R0= Construct a new `LogNormal` distribution with the given mean@ and standard deviation. # Panics  Panics if `std_dev < 0`.p0R0 Rcfg  featurestd The exponential distribution.!ȼ J#R0 R5 Construct a new `Exp` with the given shape parameter8# `lambda`. Panics if `lambda <= 0`.&j0R0 Rؼcfgؼۼ featureܼstdּ3(1 ̉.׉ ̸.׸ 0 . . ǽA Types that can be used to create a random instance of `Support`.DѽSelfSupportSupportؽؽؽƾ59 Generate a random value of `Support`, using `rng` as the< source of randomness.ɾRؾоӾоо6 `Sample`s that do not require keeping track of state.9; Since no state is recorded, each sample is (statistically)>< independent of all others, assuming the `Rng` used has this? property. SelfSupport 0 Generate a random value. R%3SupM3Sup3Sup0R3Sup0 R}3Sup 3'aTA Create a new `WeightedChoice`." Panics if: - `items` is empty - the total weight is 07 - the total weight is larger than a `u32` can contain.:3'aT.R 3'aT. RC Sample a random number using the Ziggurat method (specifically theF= ZIGNOR variant from Doornik 2005). Most of the arguments are@ directly from the paper: * `rng`: source of randomness!Y * `symmetric`: whether this is a symmetric distribution, or one-sided with P(x < 0) = 0.\ * `X`: the $x_i$ abscissae.C * `F`: precomputed values of the PDF at the $x_i$, (i.e. $f(x_i)$)F8 * `F_DIFF`: precomputed values of $f(x_i) - f(x_{i+1})$;* * `pdf`: the probability density function-? * `zero_case`: manual sampling from the tail when we chose theB bottom box (i.e. i == 0)cfg featurestd3RPZ '_  '_ '_'3PB Non-physical true random number generator based on timing jitter.EPBcfg featurestd cfg featurestd cfg featurestdcfg featurestd  #< J A true random number generator based on jitter in the CPU execution time,M" and jitter in memory access time.%D This is a true random number generator, as opposed to pseudo-randomGI generators. Random numbers generated by `JitterRng` can be seen as freshLJ entropy. A consequence is that is orders of magnitude slower than `OsRng`M' and PRNGs (about 10^3 .. 10^6 slower).*M There are very few situations where using this RNG is appropriate. Only veryPJ few applications require true entropy. A normal PRNG can be statisticallyML indistinguishable, and a cryptographic PRNG should also be as impossible toO predict. L Use of `JitterRng` is recommended for initializing cryptographic PRNGs whenO `OsRng` is not available. This implementation is based on#@ [Jitterentropy](http://www.chronox.de/jent.html) version 2.1.0.C       4% 4pcfg featurestd 6cfg featurestd - Create a new `JitterRng`.& Makes use of `std::time` for a timer.)D During initialization CPU execution timing jitter is measured a fewGF hundred times. If this does not pass basic quality tests, an error isIE returned. The test result is cached to make subsequent calls faster.Hcfg featurestd6 Create a new `JitterRng`.I A custom timer can be supplied, making it possible to use `JitterRng` inL `no_std` environments.* The timer must have nanosecond precision.-H This method is more low-level than `new()`. It is the responsibility ofKG the caller to run `test_timer` before using any numbers generated withJ1 `JitterRng`, and optionally call `set_rounds()`.4 )C Configures how many rounds are used to generate each 64-bit value.FD This must be greater than zero, and has a big impact on performanceG and output quality.F `new_with_timer` conservatively uses 64 rounds, but often less roundsIG can be used. The `test_timer()` function returns the minimum number ofJG rounds required for full strength (platform dependent), so one may useJ9 `rng.set_rounds(rng.test_timer()?);` or cache the value.< 14 ۈ(ވ) /* )  7G Basic quality tests on the timer, by measuring CPU timing jitter a fewJ hundred times.H If succesful, this will return the estimated number of rounds necessaryKG to collect 64 bits of entropy. Otherwise a `TimerError` with the causeJ! of the failure will be returned.$   6B Statistical test: return the timer delta of one normal run of theE# `JitterEntropy` entropy collector.&F Setting `var_rounds` to `true` will execute the memory access and theIF CPU jitter noice sources a variable amount of times (just like a realI `JitterEntropy` round).C Setting `var_rounds` to `false` will execute the noice sources theFH minimal number of times. This can be used to measure the minimum amountKI of entropy one round of entropy collector can collect in the worst case.L # Example H Use `timer_stats` to run the [NIST SP 800-90B Entropy Estimation Suite]K< (https://github.com/usnistgov/SP800-90B_EntropyAssessment).?C This is the recommended way to test the quality of `JitterRng`. ItFG should be run before using the RNG on untested hardware, after changesJF that could effect how the code is optimised, and after major compilerI+ compiler changes, like a new LLVM version..H First generate two files `jitter_rng_var.bin` and `jitter_rng_var.min`.KI Execute `python noniid_main.py -v jitter_rng_var.bin 8`, and validate itL9 with `restart.py -v jitter_rng_var.bin 8 `.<I This number is the expected amount of entropy that is at least availableLG for each round of the entropy collector. This number should be greaterJ4 than the amount estimated with `64 / test_timer()`.ń7B Execute `python noniid_main.py -v -u 4 jitter_rng_var.bin 4`, andEJ validate it with `restart.py -v -u 4 jitter_rng_var.bin 4 `.ӅMG This number is the expected amount of entropy that is available in theJF last 4 bits of the timer delta after running noice sources. Note thatIF a value of 3.70 is the minimum estimated entropy for true randomness.‡IB Execute `python noniid_main.py -v -u 4 jitter_rng_var.bin 4`, andEJ validate it with `restart.py -v -u 4 jitter_rng_var.bin 4 `.MG This number is the expected amount of entropy that is available to theJI entropy collecter if both noice sources only run their minimal number ofLF times. This measures the absolute worst-case, and gives a lower boundԊI for the available entropy.ŋ ```rust,no_run͋ use rand::JitterRng; # use std::error::Error; # use std::fs::File; # use std::io::Write;nj #, # fn try_main() -> Result<(), Box> {/ fn get_nstime() -> u64 {- use std::time::{SystemTime, UNIX_EPOCH};č0E let dur = SystemTime::now().duration_since(UNIX_EPOCH).unwrap();H8 // The correct way to calculate the current time isΎ;C // `dur.as_secs() * 1_000_000_000 + dur.subsec_nanos() as u64`FE // But this is faster, and the difference in terms of entropy isُH( // negligible (log2(10^9) == 29.9).+4 dur.as_secs() << 30 | dur.subsec_nanos() as u64֐7 }G // Do not initialize with `JitterRng::new`, but with `new_with_timer`.J> // 'new' always runst `test_timer`, and can therefore fail toAF // initialize. We want to be able to get the statistics even when theI // timer test fails.5 let mut rng = JitterRng::new_with_timer(get_nstime);8B // 1_000_000 results are required for the NIST SP 800-90B EntropyE // Estimation SuiteJ // FIXME: this number is smaller here, otherwise the Doc-test is too slowϔM const ROUNDS: usize = 10_000;!? let mut deltas_variable: Vec = Vec::with_capacity(ROUNDS);ǕB> let mut deltas_minimal: Vec = Vec::with_capacity(ROUNDS);AԖ for _ in 0..ROUNDS {ܖ7 deltas_variable.push(rng.timer_stats(true) as u8);:7 deltas_minimal.push(rng.timer_stats(false) as u8);: }F // Write out after the statistics collection loop, to not disturb theI // test results.ט> File::create("jitter_rng_var.bin")?.write(&deltas_variable)?;A= File::create("jitter_rng_min.bin")?.write(&deltas_minimal)?;@ # # Ok(())  # } # # fn main() { # try_main().unwrap();š # } ```cfg% featurestd  cfg& featurestdߞѝcfgѝ&ԝ؞ not՝؝מ anyٝܝ֞ target_osݝ macos target_os ios target_os windows  all՞ target_arch wasm32 notԞ target_os ƞ emscriptenȞ ϝ (     T) ͲQ QcfgQ(QQ featureQQstdQQ: Interfaces to the operating system provided random numberظ= generators.Qܹ cfg(ٹ not¹Źع target_envƹ ѹsgxӹB A random number generator that retrieves randomness straight fromE( the operating system. Platform sources:+B - Unix-like systems (Linux, Android, Mac OSX): read directly fromEC `/dev/urandom`, or from `getrandom(2)` system call if available.F! - OpenBSD: calls `getentropy(2)`$3 - FreeBSD: uses the `kern.arandom` `sysctl(2)` mib6A - Windows: calls `RtlGenRandom`, exported from `advapi32.dll` asԼD `SystemFunction036`.@ - iOS: calls SecRandomCopyBytes as /dev/(u)random is sandboxed.C= - PNaCl: calls into the `nacl-irt-random-0.1` IRT interface.@E This usually does not block. On some systems (e.g. FreeBSD, OpenBSD,HB Max OS X, and modern Linux) this may block very early in the initE3 process, if the CSPRNG has not been seeded yet.[1]̿6? [1] See for a moreB in-depth discussion.B A random number generator that retrieves randomness straight fromE( the operating system. Platform sources:+B - Unix-like systems (Linux, Android, Mac OSX): read directly fromEC `/dev/urandom`, or from `getrandom(2)` system call if available.F! - OpenBSD: calls `getentropy(2)`$3 - FreeBSD: uses the `kern.arandom` `sysctl(2)` mib6A - Windows: calls `RtlGenRandom`, exported from `advapi32.dll` asԼD `SystemFunction036`.@ - iOS: calls SecRandomCopyBytes as /dev/(u)random is sandboxed.C= - PNaCl: calls into the `nacl-irt-random-0.1` IRT interface.@E This usually does not block. On some systems (e.g. FreeBSD, OpenBSD,HB Max OS X, and modern Linux) this may block very early in the initE3 process, if the CSPRNG has not been seeded yet.[1]̿6? [1] See for a moreB in-depth discussion.  ! Create a new `OsRng`.& ~43cfg) not target_env sgx3cfg) not target_env sgx"cfg* all unix not target_os ios not target_os nacl not target_os freebsd  not target_os fuchsia  not target_os openbsd  not target_os redox  ,cfg* all target_os linux any target_arch x86_64 target_arch x86 target_arch arm target_arch aarch64  target_arch powerpc  Y6'cfg* target_arch x86_64 %#cfg+ all target_os linux any target_arch x86_64 target_arch x86 target_arch arm target_arch aarch64  target_arch powerpc @  !  !0 3Q     !& Q QcfgQ-QQ featureQQstdQQ1 A wrapper around any Read to treat it as an RNG. 4Q         R #    & Create a new `ReadRng` from a `Read`. )  R             &   ;  Q6 A wrapper around another RNG that reseeds it after it 9, generates a certain number of random bytes. /Q         4C How many bytes of entropy the underling RNG is allowed to generate F before it is reseeded   RRsdr        U7 Create a new `ReseedingRng` with the given parameters. :  # Arguments  - * `rng`: the random number generator to use. 0U * `generation_threshold`: the number of bytes of entropy at which to reseed the RNG. X+ * `reseeder`: the reseeding object to use. .  %> Reseed the internal RNG if the number of bytes that have been A generated exceed the threshold. #   RRsdr              )   SRRsdr             -   >8 Create a new `ReseedingRng` from the given reseeder and ;< seed. This uses a default value for `generation_threshold`. ?  ^@ Something that can be used to reseed an RNG via `ReseedingRng`. C  # Example   ```rust & use rand::{Rng, SeedableRng, StdRng}; )/ use rand::reseeding::{Reseeder, ReseedingRng}; 2 ' struct TickTockReseeder { tick: bool } *- impl Reseeder for TickTockReseeder { 0- fn reseed(&mut self, rng: &mut StdRng) { 0- let val = if self.tick {0} else {1}; 0 rng.reseed(&[val]);  self.tick = !self.tick; # }  }  fn main() { 0 let rsdr = TickTockReseeder { tick: true }; 3 ( let inner = StdRng::new().unwrap(); +6 let mut rng = ReseedingRng::new(inner, 10, rsdr); 9 B // this will repeat, because it gets reseeded very regularly. E? let s: String = rng.gen_ascii_chars().take(100).collect(); B println!("{}", s);؀  }   ```  SelfR    " Reseed the given RNG.  Ɂ  R      !   bۄ !ބ R QcfgQ2QR anyQQR featureQQstdQQ featureQRallocRQ-9 Functions for randomly accessing and sampling sequences.՚ <R    cfg 2   feature  std  Ӝ  : Randomly sample `amount` elements from a finite iterator.ĝ =  The following can be returned: "\ - `Ok`: `Vec` of `amount` non-repeating randomly sampled elements. The order is not random. _^ - `Err`: `Vec` of all the elements from `iterable` in sequential order. This happens when the aY length of `iterable` was less than `amount`. This is considered an error since exactly \+ `amount` elements is typically expected.Ƞ . I This implementation uses `O(len(iterable))` time and `O(amount)` memory. Lȡ  # Example̡ ڡ  ```rustޡ  use rand::{thread_rng, seq};   let mut rng = thread_rng(); = let sample = seq::sample_iter(&mut rng, 1..100, 5).unwrap(); @ println!("{:?}", sample);  ```  TIR    @ @         q6 Randomly sample exactly `amount` values from `slice`.Ȫ 9 2 The values are non-repeating and in random order. 5 6 This implementation uses `O(amount)` time and memory. 9 ! Panics if `amount > slice.len()` $  # Example   ```rust  use rand::{thread_rng, seq};Ŭ   let mut rng = thread_rng(); ( let values = vec![5, 6, 1, 3, 4, 6, 7]; +; println!("{:?}", seq::sample_slice(&mut rng, &values, 3)); > ```  RT   ׮        l: Randomly sample exactly `amount` references from `slice`. = 6 The references are non-repeating and in random order. 9 6 This implementation uses `O(amount)` time and memory. 9ܱ ! Panics if `amount > slice.len()` $  # Example   ```rust  use rand::{thread_rng, seq}; Ȳ  let mut rng = thread_rng();̲ ( let values = vec![5, 6, 1, 3, 4, 6, 7]; +? println!("{:?}", seq::sample_slice_ref(&mut rng, &values, 3)); B ```۳  RT   ̴       ߵ  c; Randomly sample exactly `amount` indices from `0..length`. > 2 The values are non-repeating and in random order. 5 6 This implementation uses `O(amount)` time and memory. 9 ` This method is used internally by the slice sampling methods, but it can sometimes be useful to cC have the indices themselves so this is provided as an alternative. F  Panics if `amount > length`  R      gJ Sample an amount of indices using an inplace partial fisher yates method. M V This allocates the entire `length` of indices and randomizes only the first `amount`. Y+ It then truncates to `amount` and returns. . Z This is better than using a HashMap "cache" when `amount >= length / 2` since it does not ]6 require allocating an extra cache and is much faster. 9 R      tR This method performs a partial fisher-yates on a range of indices using a HashMap U+ as a cache to record potential collisions. . Z The cache avoids allocating the entire `length` of values. This is especially useful when ]@ `amount <<< length`, i.e. select 3 non-repeating from 1_000_000 C R     R[$ The ChaCha random number generator.S'RSS Sf# The ISAAC random number generator.S&ST%TTT T T6 The implementations of `Rand` for the built-in types. 9T             % R      n " R      q # R      q # R      q # R       % R      n " R      q # R      j # R      j # RÀ        $ R      #  v $ Rȓ        N ™ Rҙ Ǚ ʙ Ǚ Ǚ    T    ١ )ܡ R     T F Pseudo random number generators are algorithms to produce *apparentlyұ I? random* numbers deterministically, and usually fairly quickly. B ߲ H So long as the algorithm is computationally secure, is initialised with KL sufficient entropy (i.e. unknown by an attacker), and its internal state is OA also protected (unknown to an attacker), the output will also be DF *computationally secure*. Computationally Secure Pseudo Random NumberŴ IE Generators (CSPRNGs) are thus suitable sources of random numbers for HK cryptography. There are a couple of gotchas here, however. First, the seedص NL used for initialisation must be unknown. Usually this should be provided by OH the operating system and should usually be secure, however this may not KG always be the case (especially soon after startup). Second, user-space÷ JL memory may be vulnerable, for example when written to swap space, and after OK forking a child process should reinitialise any user-space PRNGs. For this޸ NJ reason it may be preferable to source random numbers directly from the OS M for cryptographic applications. #  B PRNGs are also widely used for non-cryptographic uses: randomised EH algorithms, simulations, games. In these applications it is usually not KF important for numbers to be cryptographically *unguessable*, but even II distribution and independence from other samples (from the point of view LL of someone unaware of the algorithm used, at least) may still be important.ͼ OE Good PRNGs should satisfy these properties, but do not take them for H! granted; Wikipedia's article on  $^ [Pseudorandom number generators](https://en.wikipedia.org/wiki/Pseudorandom_number_generator) a( provides some background on this topic. +  H Care should be taken when seeding (initialising) PRNGs. Some PRNGs have KK short periods for some seeds. If one PRNG is seeded from another using the NI same algorithm, it is possible that both will yield the same sequence of L values (with some lag). T $ The ChaCha random number generator. '             allow ;   bad_style               D    "; Create an ChaCha random number generator using the default > fixed key of 8 zero words.   # Examples   ```rust  use rand::{Rng, ChaChaRng};  ( let mut ra = ChaChaRng::new_unseeded(); +! println!("{:?}", ra.next_u32()); $! println!("{:?}", ra.next_u32()); $ ```  F Since this equivalent to a RNG with a fixed seed, repeated executions IG of an unseeded RNG will produce the same result. This code sample will J consistently produce:   - 2917185654  - 2419978656    B, Sets the internal 128-bit ChaCha counter to /, a user-provided value. This permits jumping /= arbitrarily ahead (or backwards) in the pseudorandom stream. @ B Since the nonce words are used to extend the counter to 128 bits, ED users wishing to obtain the conventional ChaCha pseudorandom stream G? associated with a particular nonce can call this function with B arguments `0, desired_nonce`. !  # Examples   ```rust  use rand::{Rng, ChaChaRng};  ( let mut ra = ChaChaRng::new_unseeded(); +% ra.set_counter(0u64, 1234567890u64); (! println!("{:?}", ra.next_u32()); $! println!("{:?}", ra.next_u32()); $ ```    *@ Initializes `self.state` with the appropriate key and constants C < We deviate slightly from the ChaCha specification regarding ?< the nonce, which is used to extend the counter to 128 bits. ?; This is provably as strong as the original cipher, though, >: since any distinguishing attack on our variant also works =9 against ChaCha with a chosen-nonce. See the XSalsa20 [1] <4 security proof for a more involved example of this. 7  The modified word layout is:  ```text $ constant constant constant constant ' key key key key " key key key key "# counter counter counter counter & ``` 2 [1]: Daniel J. Bernstein. [*Extending the Salsa20 5- nonce.*](http://cr.yp.to/papers.html#xsalsa) 0   2 Refill the internal output buffer (`self.buffer`) 5       'a   %    *' Create a ChaCha generator from a seed, *+ obtained from a variable-length u32 array. ., Only up to 8 words are used; if less than 8 // words are used, the remaining are set to zero. 2   + R       # The ISAAC random number generator.ƚ & allow @   non_camel_case_types        ӛ  ӛ ֛          allow @   bad_style    ͜ *Ӝ  2   բ    !: Create an ISAAC random number generator using the default = fixed seed.   !E Initialises `self`. If `use_rsl` is true, then use the current value HA of `rsl` as a seed, otherwise construct one algorithmically (notե D randomly).         ' Refills the output buffer (`self.rsl`)Ҵ *   , ޶ u ĸ Ѹ ˼ ؼ   Q        'a   %    )> Create an ISAAC random number generator with a seed. This can A? be any length, although the maximum number of elements used is B7 256 and any more will be silently ignored. A generator :> constructed with a given seed will generate the same sequence A> of values as all other generators constructed with that seed. A   * R       4   & The ISAAC-64 random number generator. )                   allow F   bad_style   "  2      $ #8 Create a 64-bit ISAAC random number generator using the ; default fixed seed.   !E Initialises `self`. If `use_rsl` is true, then use the current value HA of `rsl` as a seed, otherwise construct one algorithmically (not D randomly).           ' Refills the output buffer (`self.rsl`)Յ *   * ч Bׇ      ͊ א   U          ҝ 'aם ם  %  ˟  +> Create an ISAAC random number generator with a seed. This can A? be any length, although the maximum number of elements used is B7 256 and any more will be silently ignored. A generator :> constructed with a given seed will generate the same sequence A> of values as all other generators constructed with that seed. A  ץ ,ڥ R ߥ  ߥ ߥ   4    Xorshift generators              $8 Creates a new XorShiftRng instance which is not seeded. ; H The initial values of this RNG are constants, so all generators created KE by this function will yield the same stream of random numbers. It is HI highly recommended that this is created through `SeedableRng` instead of L this function         $@ Reseed an XorShiftRng. This will panic if `seed` is entirely 0. C    +C Create a new XorShiftRng. This will panic if `seed` is entirely 0. F    + R        " $ a6 A type that can be randomly generated using an `Rng`.T9U ## Built-in ImplementationsUUH This crate implements `Rand` for various primitive types. Assuming theUKK provided `Rng` is well-behaved, these implementations generate values withVN( the following ranges and distributions:V+WI * Integers (`i32`, `u32`, `isize`, `usize`, etc.): Uniformly distributedWL over all values of the type.W"I * `char`: Uniformly distributed over all Unicode scalar values, i.e. allWLA code points in the range `0...0x10_FFFF`, except for the rangeXD@ `0xD800...0xDFFF` (the surrogate code points). This includesYC# unassigned/reserved code points.Y&B * `bool`: Generates `false` or `true`, each with probability 0.5.YEG * Floating point types (`f32` and `f64`): Uniformly distributed in theZJJ half-open range `[0, 1)`. (The [`Open01`], [`Closed01`], [`Exp1`], and[MG [`StandardNormal`] wrapper types produce floating point numbers with[J( alternative ranges or distributions.)\+\ [`Open01`]: struct.Open01.html\"# [`Closed01`]: struct.Closed01.html\&5 [`Exp1`]: distributions/exponential/struct.Exp1.html]8D [`StandardNormal`]: distributions/normal/struct.StandardNormal.html]G^E The following aggregate types also implement `Rand` as long as their^H component types implement it:^!_E * Tuples and arrays: Each element of the tuple or array is generated_H6 independently, using its own `Rand` implementation._9J * `Option`: Returns `None` with probability 0.5; otherwise generates a`M$ random `T` and returns `Some(T)`.`'aSelfaab%G Generates a random instance of this type using the specified source ofaJ randomness.abRbbbbbbK A random number generator.bbSelfd Return the next random u32.bc= This rarely needs to be called directly, prefer `r.gen()` toc@ `r.next_u32()`.cddg Return the next random u64.de: By default this is implemented in terms of `next_u32`. Ane=: implementation of this trait must provide at least one ofe=> these two methods. Similarly to `next_u32`, this rarely needsfA; to be called directly, prefer `r.gen()` to `r.next_u64()`.f>ggr7 Return the next random f32 selected from the half-openh: interval `[0, 1)`.hh: This uses a technique described by Saito and Matsumoto ath=9 MCQMC'08. Given that the IEEE floating point numbers arei<: uniformly distributed over [1,2), we generate a number ini=8 this range and then offset it onto the range [0,1). Ourj;6 choice of bits (masking v. shifting) is arbitrary andj9: should be immaterial for high quality generators. For lowk=8 quality generators (ex. LCG), prefer bitshifting due tok;/ correlation between sequential low order bits.l2l See:lD A PRNG specialized in double precision floating point numbers usinglG an affine transitionmmG * mJK * nNo= By default this is implemented in terms of `next_u32`, but ao@> random number generator which can generate numbers satisfyingoA= the requirements directly can overload this for performance.p@7 It is required that the return value lies in `[0, 1)`.p:q4 See `Closed01` for the closed interval `[0,1]`, andq7( `Open01` for the open interval `(0,1)`.q+rrr#r r!r x7 Return the next random f64 selected from the half-opent: interval `[0, 1)`.tu= By default this is implemented in terms of `next_u64`, but au@> random number generator which can generate numbers satisfyinguA= the requirements directly can overload this for performance.v@7 It is required that the return value lies in `[0, 1)`.v:w4 See `Closed01` for the closed interval `[0,1]`, andw7( `Open01` for the open interval `(0,1)`.w+xxx+x x(x ) Fill `dest` with random data.z!z= This has a default implementation in terms of `next_u64` andz@= `next_u32`, but should be overridden by implementations that{@8 offer a more efficient solution than just calling those{; methods repeatedly.||< This method does *not* have a requirement to bear any fixed|?> relationship to the other methods, for example, it does *not*}A; have to result in the same output as progressively filling}>> `dest` with `self.gen::()`, and any such behaviour should~A not be relied upon.~~< This method should guarantee that `dest` is entirely filled~?3 with new data, and may panic if this is impossible6? (e.g. reading past the end of a file that is being used as theB source of randomness).À # Example  ```rust  use rand::{thread_rng, Rng};  let mut v = [0u8; 13579];! thread_rng().fill_bytes(&mut v);$ println!("{:?}", &v[..]); ``` Ȃ1( Return a random value of a `Rand` type.+ # Example  ```rust  use rand::{thread_rng, Rng};  let mut rng = thread_rng();Ê let x: u32 = rng.gen(); println!("{}", x);, println!("{:?}", rng.gen::<(f64, bool)>());/ ```֋TRB Return an iterator that will yield an infinite number of randomlyЌE generated items. # Example ͍ ```Ս use rand::{thread_rng, Rng};  let mut rng = thread_rng();> let x = rng.gen_iter::().take(10).collect::>();A println!("{:?}", x);7 println!("{:?}", rng.gen_iter::<(f64, bool)>().take(5):5 .collect::>());ԏ8 ```T \6 Generate a random value in the range [`low`, `high`).9% This is a convenience wrapper around(8 `distributions::Range`. If this function will be called;? repeatedly with the same arguments, one should use `Range`, asB; that will amortize the computations that allow for perfect>3 uniformity, as they only happen on initialization.6 # Panics ̔ Panics if `low >= high`.Ԕ # Example  ```rust  use rand::{thread_rng, Rng}; ̕ let mut rng = thread_rng();ԕ# let n: u32 = rng.gen_range(0, 10);& println!("{}", n);0 let m: f64 = rng.gen_range(-40.0f64, 1.3e5f64);3 println!("{}", m); ``` TǗ q A+ Return a bool with a 1 in n chance of true. # Example ə ```rustљ  use rand::{thread_rng, Rng};  let mut rng = thread_rng();* println!("{}", rng.gen_weighted_bool(3));- ```RB Return an iterator of random characters from the set A-Z,a-z,0-9.E # Example Ϝ ```rustל  use rand::{thread_rng, Rng}; C let s: String = thread_rng().gen_ascii_chars().take(10).collect();F println!("{}", s);ߝ ```ӞO' Return a random element from `values`.*$ Return `None` if `values` is empty.Ÿ' # Example  ``` use rand::{thread_rng, Rng}; $ let choices = [1, 2, 4, 8, 16, 32];ɠ' let mut rng = thread_rng();( println!("{:?}", rng.choose(&choices));+- assert_eq!(rng.choose(&choices[..0]), None);ɡ0 ```TԢ[< Return a mutable pointer to a random element from `values`.?$ Return `None` if `values` is empty.' T<" Shuffle a mutable slice in place.% This applies Durstenfeld's algorithm for the [Fisher–Yates shuffle](https://en.wikipedia.org/wiki/Fisher%E2%80%93Yates_shuffle#The_modern_algorithm)( which produces an unbiased permutation.Ĩ+ # Example  ```rust  use rand::{thread_rng, Rng}; ˩ let mut rng = thread_rng();ө let mut y = [1, 2, 3]; rng.shuffle(&mut y); println!("{:?}", y); rng.shuffle(&mut y);Ъ println!("{:?}", y); ```Tͫ'aR) İcfgT featurestdR˱ձر) 'aTR ׷ܷ'aRȻ"˻лھC A random number generator that can be explicitly seeded to produceF. the same stream of randomness multiple times.1 SelfSeed Seed!# Reseed an RNG with the given seed.& # Example ƿ ```rustο & use rand::{Rng, SeedableRng, StdRng};޿) let seed: &[_] = &[1, 2, 3, 4];#4 let mut rng: StdRng = SeedableRng::from_seed(seed);7" println!("{}", rng.gen::());% rng.reseed(&[5, 6, 7, 8]);" println!("{}", rng.gen::());% ```!& Create a new RNG with the given seed.) # Example  ```rust & use rand::{Rng, SeedableRng, StdRng};) let seed: &[_] = &[1, 2, 3, 4];#4 let mut rng: StdRng = SeedableRng::from_seed(seed);7" println!("{}", rng.gen::());% ``` "/ Create a randomly seeded instance of `StdRng`.25 This is a very expensive operation as it has to read88 randomness from the operating system and use this in an;? expensive seeding operation. If one is only generating a smallB? number of random numbers, or doesn't need the utmost speed forBA generating each number, `thread_rng` and/or `random` may be moreD appropriate.> Reading the randomness from the OS may fail, and any error isA. propagated via the `io::Result` return value.1cfgU featurestd'a')  I Create a weak random number generator with a default algorithm and seed.LK It returns the fastest `Rng` algorithm currently available in Rust withoutNJ consideration for cryptography or security. If you require a specificallyMI seeded `Rng` for consistency over time you should pick one algorithm andL create the `Rng` yourself.> This will seed the generator with randomness from thread_rng.AcfgW featurestdcfgW featurestd&0cfgW featurestdIcfgW featurestd ; Retrieve the lazily-initialized thread-local random number>? generator, seeded by the system. Intended to be used in methodB2 chaining style, e.g. `thread_rng().gen::()`.5L After generating a certain amount of randomness, the RNG will reseed itselfOL from the operating system or, if the operating system RNG returns an error,O) a seed based on the current system time.,C The internal RNG used is platform and architecture dependent, evenFB if the operating system random number generator is rigged to giveE? the same sequence always. If absolute consistency is required,B; explicitly select an RNG, e.g. `IsaacRng` or `Isaac64Rng`.>cfgW featurestd  cfgW featurestd* I Generates a random value using the thread-local random number generator.LK `random()` can generate various types of random things, and so may requireN5 type hinting to generate the specific type you want.8H This function uses the thread local random number generator. This meansKG that if you're calling `random()` in a loop, caching the generator canJ1 increase performance. An example is shown below.4 # Examples ``` let x = rand::random::();! println!("{}", x); let y = rand::random::();" println!("{}", y);+ if rand::random() { // generates a boolean.) println!("Better lucky than good!");, } ```2 Caching the thread local random number generator:5 ``` use rand::Rng; let mut v = vec![1, 2, 3]; for x in v.iter_mut() { *x = rand::random() }, // can be made faster by caching thread_rng/" let mut rng = rand::thread_rng();% for x in v.iter_mut() { *x = rng.gen(); } ```cfgX featurestdT~, DEPRECATED: use `seq::sample_iter` instead./@ Randomly sample up to `amount` elements from a finite iterator.C3 The order of elements in the sample is not random.6 # Example  ```rust  use rand::{thread_rng, sample};# let mut rng = thread_rng();* let sample = sample(&mut rng, 1..100, 5);- println!("{:?}", sample); ```cfgX featurestd  deprecated X since0.4.0 noterenamed to seq::sample_iter@0.4.0renamed to seq::sample_iterTIRԷD, Sample values uniformly between two bounds./ȩC This gives a uniform distribution (assuming the RNG used to sample̩F@ it is itself uniform & the `SampleRange` implementation for theC> given type is correct), even for edge cases like `low = 0u8`,תA@ `high = 170u8`, for which a naive modulo operation would returnCB numbers less than 85 with double the probability to those greaterݫE than 85. ; Types should attempt to sample in `[low, high)`, i.e., not>: including `high`, but this may be very difficult. All the=C primitive integer types satisfy this property, and the float typesF= normally satisfy it, but rounding may mean `high` can occur.@ # Example ˮ ```rustϮ 5 use rand::distributions::{IndependentSample, Range};ۮ8 fn main() {) let between = Range::new(10, 10000);,& let mut rng = rand::thread_rng();կ) let mut sum = 0; for _ in 0..1000 {- sum += between.ind_sample(&mut rng);0 }  println!("{}", sum); } ```±XȱȱȱѱѱXݱݱX Xautomatically_derivedXallowX unused_qualificationsyXXȱȱyȱyautomatically_derivedYallowY unused_qualificationszXXȱȱzȱautomatically_derivedYallowY unused_qualifications{XXȱNȱ{ȱ{ Xٿ5ܿ; R Xٿ5ܿ; R Xٿ5ܿ; R Xٿ5ܿ; R Xٿ5ܿ; R Xٿ5 ܿ;  R   X ٿ5 ܿ ;  R     ! X!ٿ5 !ܿ!; ! R!!!! !" X"ٿ5 "ܿ"; " R"""" "# X#ٿ5 #ܿ#; # R#### #$X$5$$;$ R$$$$$%X%5%%;% R%%%%%); The Gamma distribution `Gamma(shape, scale)` distribution.>- The density function of this distribution is0 ```text 2 f(x) = x^(k - 1) * exp(-x / θ) / (Γ(k) * θ^k)5 ```C where `Γ` is the Gamma function, `k` is the shape and `θ` is theF3 scale and both `k` and `θ` are strictly positive.6C The algorithm used is that described by Marsaglia & Tsang 2000[1],FA falling back to directly sampling from an Exponential for `shapeD= == 1`, and using the boosting technique described in [1] for@ `shape < 1`. # Example  ```rust 5 use rand::distributions::{IndependentSample, Gamma};8" let gamma = Gamma::new(2.0, 5.0);%3 let v = gamma.ind_sample(&mut rand::thread_rng());66 println!("{} is from a Gamma(2, 5) distribution", v);9 ```@ [1]: George Marsaglia and Wai Wan Tsang. 2000. "A Simple MethodC@ for Generating Gamma Variables" *ACM Trans. Math. Softw.* 26, 3C (September 2000),O 363-372. DOI:[10.1145/358407.358414](http://doi.acm.org/10.1145/358407.358414)Rw&&automatically_derived&g&&allow&g&& unused_qualifications&&~w&~&&''automatically_derived'g''allow'g'' unused_qualifications''w((automatically_derived(g((allow(g(( unused_qualifications((w(((W wwwwwwwwww))automatically_derived)h))allow)h)) unused_qualifications))w)))**automatically_derived*i**allow*i** unused_qualifications**w++automatically_derived+i++allow+i++ unused_qualifications++w+++O= Gamma distribution where the shape parameter is less than 1.@B Note, samples from this require a compulsory floating-point `pow`E? call, which makes it significantly slower than sampling from aB@ gamma distribution where the shape parameter is greater than orC equal to 1.@ See `Gamma` for sampling from a Gamma distribution with generalC shape parameters.w w w,,automatically_derived,j,,allow,j,, unused_qualifications,,w,,,--automatically_derived-j--allow-j-- unused_qualifications--w..automatically_derived.k..allow.k.. unused_qualifications..w...A? Gamma distribution where the shape parameter is larger than 1.B@ See `Gamma` for sampling from a Gamma distribution with generalC shape parameters.w www//automatically_derived/k//allow/k// unused_qualifications//w///00automatically_derived0l00allow0l00 unused_qualifications00w11automatically_derived1l11allow1l11 unused_qualifications11w111ߓ3D The chi-squared distribution `χ²(k)`, where `k` is the degrees ofG freedom.ُ B For `k > 0` integral, this distribution is the sum of the squaresE? of `k` independent standard normal random variables. For otherB/ `k`, this uses the equivalent characterisation2 `χ²(k) = Gamma(k/2, 2)`.ő # Exampleɑ ב ```rustۑ : use rand::distributions::{ChiSquared, IndependentSample};=! let chi = ChiSquared::new(11.0);$1 let v = chi.ind_sample(&mut rand::thread_rng());Β42 println!("{} is from a χ²(11) distribution", v)5 ``` w:ʓ:ʓautomatically_derived:ʓm:ʓ:ʓallow:ʓm:ʓ:ʓ unused_qualifications:ʓ:ʓw:ʓ:ʓ:ʓ;ѓ;ѓautomatically_derived;ѓm;ѓ;ѓallow;ѓm;ѓ;ѓ unused_qualifications;ѓ;ѓw<ד<דautomatically_derived<דm<ד<דallow<דm<ד<ד unused_qualifications<ד<דw<ד<ד<דw  w  wwww==automatically_derived=n==allow=n== unused_qualifications==w===>>automatically_derived>n>>allow>n>> unused_qualifications>>w??automatically_derived?n??allow?n?? unused_qualifications??w???% The Fisher F distribution `F(m, n)`.Н(? This distribution is equivalent to the ratio of two normalisedB< chi-squared distributions, that is, `F(m,n) = (χ²(m)/m) /? (χ²(n)/n)`. # Example  ```rust 7 use rand::distributions::{FisherF, IndependentSample};:! let f = FisherF::new(2.0, 32.0);$/ let v = f.ind_sample(&mut rand::thread_rng());23 println!("{} is from an F(2, 32) distribution", v)ˠ6 ```wءءwߢߢ wDDautomatically_derivedDoDDallowDoDD unused_qualificationsDDwDDDEEautomatically_derivedEpEEallowEpEE unused_qualificationsEEwFFautomatically_derivedFpFFallowFpFF unused_qualificationsFFwFFF«9B The Student t distribution, `t(nu)`, where `nu` is the degrees ofE freedom.  # Example ũ ```rustɩ 8 use rand::distributions::{StudentT, IndependentSample};թ; let t = StudentT::new(11.0); / let v = t.ind_sample(&mut rand::thread_rng());2/ println!("{} is from a t(11) distribution", v)2 ```ͫܫܫwwOOautomatically_derivedOqOOallowOqOO unused_qualificationsOOwOOOPPautomatically_derivedPqPPallowPqPP unused_qualificationsPPwQQautomatically_derivedQrQQallowQrQQ unused_qualificationsQQwQQQ#= A wrapper around an `f64` to generate N(0, 1) random numbers@* (a.k.a. a standard normal, or Gaussian).-2 See `Normal` for the general normal distribution.5> Implemented via the ZIGNOR variant[1] of the Ziggurat method.A@ [1]: Jurgen A. Doornik (2005). [*An Improved Ziggurat Method toC Generate Normal RandomB Samples*](http://www.doornik.com/research/ziggurat.pdf). NuffieldE College, Oxford # Example  ```rust 1 use rand::distributions::normal::StandardNormal;4( let StandardNormal(x) = rand::random();+ println!("{}", x); ```#= A wrapper around an `f64` to generate N(0, 1) random numbers@* (a.k.a. a standard normal, or Gaussian).-2 See `Normal` for the general normal distribution.5> Implemented via the ZIGNOR variant[1] of the Ziggurat method.A@ [1]: Jurgen A. Doornik (2005). [*An Improved Ziggurat Method toC Generate Normal RandomB Samples*](http://www.doornik.com/research/ziggurat.pdf). NuffieldE College, Oxford # Example  ```rust 1 use rand::distributions::normal::StandardNormal;4( let StandardNormal(x) = rand::random();+ println!("{}", x); ```VVautomatically_derivedVrVVallowVrVV unused_qualificationsVVVVVWWautomatically_derivedWsWWallowWsWW unused_qualificationsWWXXautomatically_derivedXsXXallowXsXX unused_qualificationsXXXXX6/ The normal distribution `N(mean, std_dev**2)`.29 This uses the ZIGNOR variant of the Ziggurat method, see<# `StandardNormal` for more details.& # Example  ```rust 6 use rand::distributions::{Normal, IndependentSample};9 // mean 2, standard deviation 3#$ let normal = Normal::new(2.0, 3.0);'4 let v = normal.ind_sample(&mut rand::thread_rng());71 println!("{} is from a N(2, 9) distribution", v)4 ```  YYautomatically_derivedYsYYallowYsYY unused_qualificationsYYYYYZZautomatically_derivedZtZZallowZtZZ unused_qualificationsZZ[[automatically_derived[t[[allow[t[[ unused_qualifications[[[[[)6 The log-normal distribution `ln N(mean, std_dev**2)`.9; If `X` is log-normal distributed, then `ln(X)` is `N(mean,> std_dev**2)` distributed. # Example  ```rust 9 use rand::distributions::{LogNormal, IndependentSample};< // mean 2, standard deviation 3#+ let log_normal = LogNormal::new(2.0, 3.0);.8 let v = log_normal.ind_sample(&mut rand::thread_rng());;5 println!("{} is from an ln N(2, 9) distribution", v)8 ```!  !``automatically_derived`u``allow`u`` unused_qualifications`````aaautomatically_derivedauaaallowauaa unused_qualificationsaabbautomatically_derivedbubballowbubb unused_qualificationsbbbbb= A wrapper around an `f64` to generate Exp(1) random numbers.@4 See `Exp` for the general exponential distribution.7B Implemented via the ZIGNOR variant[1] of the Ziggurat method. TheEB exact description in the paper was adjusted to use tables for theE- exponential distribution rather than normal.0@ [1]: Jurgen A. Doornik (2005). [*An Improved Ziggurat Method toC Generate Normal RandomB Samples*](http://www.doornik.com/research/ziggurat.pdf). NuffieldE College, Oxford # Example  ```rust , use rand::distributions::exponential::Exp1;/ let Exp1(x) = rand::random();! println!("{}", x); ```#= A wrapper around an `f64` to generate Exp(1) random numbers.@4 See `Exp` for the general exponential distribution.7B Implemented via the ZIGNOR variant[1] of the Ziggurat method. TheEB exact description in the paper was adjusted to use tables for theE- exponential distribution rather than normal.0@ [1]: Jurgen A. Doornik (2005). [*An Improved Ziggurat Method toC Generate Normal RandomB Samples*](http://www.doornik.com/research/ziggurat.pdf). NuffieldE College, Oxford # Example  ```rust , use rand::distributions::exponential::Exp1;/ let Exp1(x) = rand::random();! println!("{}", x); ```##ggautomatically_derivedgvggallowgvgg unused_qualificationsggggghhautomatically_derivedhvhhallowhvhh unused_qualificationshhiiautomatically_derivediviiallowivii unused_qualificationsiiiiiq, The exponential distribution `Exp(lambda)`./9 This distribution has density function: `f(x) = lambda *< exp(-lambda * x)` for `x > 0`." # Example  ```rust 3 use rand::distributions::{Exp, IndependentSample};6 let exp = Exp::new(2.0);1 let v = exp.ind_sample(&mut rand::thread_rng());41 println!("{} is from a Exp(2) distribution", v);4 ```$? `lambda` stored as `1/lambda`, since this is what we scale by.B$jjautomatically_derivedjwjjallowjwjj unused_qualificationsjjjjjkkautomatically_derivedkwkkallowkwkk unused_qualificationskkllautomatically_derivedlwllallowlwll unused_qualificationslllllM= A wrapper for generating types that implement `Rand` via the@' `Sample` & `IndependentSample` traits.*& Sup&)&3qqautomatically_derivedqxqqallowqxqq unused_qualificationsqq3SupNqqqq@ A value with a particular weight for use with `WeightedChoice`.C'T'" The numerical weight of this item%' ( The actual item which is being weighted+'rrautomatically_derivedryrrallowryrr unused_qualificationsrr3Trssautomatically_derivedsyssallowsyss unused_qualificationsss3Tssssttautomatically_derivedtyttallowtytt unused_qualificationstt3TNttttfH A distribution that selects from a finite collection of weighted items.KA Each item has an associated weight that influences how likely itD/ is to be chosen: higher weight is more likely.2< The `Clone` restriction is a limitation of the `Sample` and?D `IndependentSample` traits. Note that `&T` is (cheaply) `Clone` forGB all `T`, as is `u32`, so one can store references or indices intoE another vector. # Example  ```rust H use rand::distributions::{Weighted, WeightedChoice, IndependentSample};K8 let mut items = vec!(Weighted { weight: 2, item: 'a' },;8 Weighted { weight: 4, item: 'b' },;9 Weighted { weight: 1, item: 'c' });<* let wc = WeightedChoice::new(&mut items);-" let mut rng = rand::thread_rng();% for _ in 0..16 {< // on average prints 'a' 4 times, 'b' 8 and 'c' twice.?. println!("{}", wc.ind_sample(&mut rng));1 } ```('aT'a#(((3( 3uuautomatically_deriveduzuuallowuzuu unused_qualificationsuu3'a T    'aNuuu u 1 An error that can occur when `test_timer` fails.4-  No timer available.-   No timer available.-   . Timer too coarse to use as an entropy source.1-    . Timer too coarse to use as an entropy source.1-    ' Timer is not monotonically increasing.*-    ' Timer is not monotonically increasing.*-   ( Variations of deltas of time too small.+-  ( Variations of deltas of time too small.+-   6 Too many stuck results (indicating no added entropy).9-    6 Too many stuck results (indicating no added entropy).9-   doc| hidden-  doc| hidden-  automatically_derived|allow| unused_qualifications  automatically_derived}allow} unused_qualifications     automatically_derived ~  allow ~   unused_qualifications      automatically_derived~allow~ unused_qualificationsdoc~ hidden no_coverage~  'A An RNG that reads random bytes straight from a `Read`. This will D= work best with an infinite reader, but this is not required. @  # Panics  E It will panic if it there is insufficient data to fulfill a request. H  # Example   ```rust  use rand::{read, Rng};  ) let data = vec![1, 2, 3, 4, 5, 6, 7, 8]; ,- let mut rng = read::ReadRng::new(&data[..]); 0$ println!("{:x}", rng.gen::()); ' ``` 4 R    4  4     automatically_derived   allow    unused_qualifications  R   N        C A wrapper around any RNG which reseeds the underlying RNG after it F0 has generated a certain number of random bytes. 36 R Rsdr     6  6  6   6   6   / Controls the behaviour when reseeding the RNG. 26     automatically_derived   allow    unused_qualifications  R Rsdr     # N          : Reseed an RNG using a `Default` instance. This reseeds by =@ replacing the RNG with the result of a `Default::default` call. C7  : Reseed an RNG using a `Default` instance. This reseeds by =@ replacing the RNG with the result of a `Default::default` call. C7     automatically_derived   allow    unused_qualifications         automatically_derived   allow    unused_qualifications    automatically_derived ł  allow Ƃ   unused_qualifications        =  "=  =  ǃ =ǃ  ̃ =̃  ̃ =̃  ԃ =ԃ  ԃ =ԃ   3=   =  #2 Generate a floating point number in the half-openф 5 interval `[0,1)`.  0 See `Closed01` for the closed interval `[0,1]`,х 3, and `Open01` for the open interval `(0,1)`. /=  R       =  =  +=  R  È     = Nj =  -=  R       =  >ߎ  ">  >  ǃ >ǃ  ̃ >̃  ̃ >̃  ԃ >ԃ  ԃ >ԃ   3>   >  #2 Generate a floating point number in the half-openф 5 interval `[0,1)`.  0 See `Closed01` for the closed interval `[0,1]`,х 3, and `Open01` for the open interval `(0,1)`. />  R       >  >  +>  R  È     > Nj >  ->  R       >  ?A    ͕  ?  4?  R       ?  @A B  #  #͕  ͕  @  @  4@  R       @  AA B C    # #  #͕ #͕  ͕  A  A  A  4A  R         A  BA B C D    # # #  #͕ #͕ #͕  ͕  B  B  B  B  4B  R         B  CA B C D E      #Ú #ƚ #ɚ #̚  Ϛ #͕ #͕ #͕ #͕  ͕ Ú CÚ ƚ Cƚ ɚ Cɚ ̚ C̚ Ϛ CϚ  4C  R         C  DA B C D E F       #ޚ # # # #  #͕ #͕ #͕ #͕ #͕  ͕ ޚ Dޚ  D  D  D  D  D  4D  R         D  EA B C D E F G       # # # # # # ו #͕ #͕ #͕ #͕ #͕ #͕ ו ͕  E  E  E  E  E  E  E  4E  R         E  FA B C D E F G H        # # # # # # #  #͕ #͕ #͕ #͕ #͕ #͕ #͕  ͕  F  F  F  F  F  F  F  F  4F  R         F  G A B C D E F G H I         # #ě #Ǜ #ʛ #͛ #Л #ӛ #֛  ٛ #͕ #͕ #͕ #͕ #͕ #͕ #͕ #͕  ͕  G ě Gě Ǜ GǛ ʛ Gʛ ͛ G͛ Л GЛ ӛ Gӛ ֛ G֛ ٛ Gٛ  4G  R         G  H A B C D E F G H I J         # # # # # # # # #  #͕ #͕ #͕ #͕ #͕ #͕ #͕ #͕ #͕  ͕  H  H  H  H  H  H  H  H  H  H  4H  R         H  I A B C D E F G H I J K         # # # # # # # # # #  #͕ #͕ #͕ #͕ #͕ #͕ #͕ #͕ #͕ #͕  ͕  I  I  I  I  I  I  I  I  I  I  I  4I  R         I  J A B C D E F G H I J K L          # #œ #Ŝ #Ȝ #˜ #Μ #ќ #Ԝ #ל #ڜ #ݜ  #͕ #͕ #͕ #͕ #͕ #͕ #͕ #͕ #͕ #͕ #͕  ͕  J œ Jœ Ŝ JŜ Ȝ JȜ ˜ J˜ Μ JΜ ќ Jќ Ԝ JԜ ל Jל ڜ Jڜ ݜ Jݜ  J  4J  R         J ܝ KT     K  K (K  R       K  Kܝ T        (  R         ܝ T        (  R         ܝ T        (  R         ܝ T        (  R         ܝ T        (  R         ܝ T        (  R         ܝ T        (  R         ܝ T        (  R         ܝ T        (  R         ܝ T        (  R         ܝ T        (  R         ܝ T        (  R         ܝ T        (  R         ܝ T        (  R         ܝ T        (  R         ܝ T        (  R         ܝ T        (  R         ܝ T        (  R         ܝ T        (  R         ܝ T        (  R         ܝ T        (  R         ܝ T        (  R         ܝ T        (  R         ܝ T        (  R         ܝ T        (  R         ܝ T        (  R         ܝ T        (  R         ܝ T        (  R         ܝ T        (  R         ܝ T        (  R         ܝ T        (  R         ȟ `T  ͟ ͟ ͟   (  R          @ A random number generator that uses the ChaCha20 algorithm [1]. C 8 The ChaCha algorithm is widely accepted as suitable for ;= cryptographic purposes, but this implementation has not been @A verified as such. Prefer a generator like `OsRng` that defers to D8 the operating system for cases that need high security. ; - [1]: D. J. Bernstein, [*ChaCha, a variant of 0' Salsa20*](http://cr.yp.to/chacha.html) *L L   L L   L L     automatically_derived   allow    unused_qualifications    automatically_derived   allow    unused_qualifications          automatically_derived   allow    unused_qualifications       < A random number generator that uses the ISAAC algorithm[1]. ? : The ISAAC algorithm is generally accepted as suitable for =; cryptographic purposes, but this implementation has not be >A verified as such. Prefer a generator like `OsRng` that defers to D8 the operating system for cases that need high security. ; > [1]: Bob Jenkins, [*ISAAC: A fast cryptographic random number A@ generator*](http://www.burtleburtle.net/bob/rand/isaacafa.html) CN  N   N   Nѡ Nѡ   ܡ N N   N   N     automatically_derived   allow    unused_qualifications   P     Q     < A random number generator that uses ISAAC-64[1], the 64-bit ? variant of the ISAAC algorithm. # : The ISAAC algorithm is generally accepted as suitable for =; cryptographic purposes, but this implementation has not be >A verified as such. Prefer a generator like `OsRng` that defers to D8 the operating system for cases that need high security. ; > [1]: Bob Jenkins, [*ISAAC: A fast cryptographic random number A@ generator*](http://www.burtleburtle.net/bob/rand/isaacafa.html) CY Y   Y   Y Y   Y Y   Y   Y     automatically_derived   allow    unused_qualifications   c     d     V An Xorshift[1] random number  generator.  B The Xorshift algorithm is not suitable for cryptographic purposes E@ but is very fast. If you do not know for sure that it fits your CC requirements, use a more secure one such as `IsaacRng` or `OsRng`. F / [1]: Marsaglia, George (July 2003). ["Xorshift 2< RNGs"](http://www.jstatsoft.org/v08/i14/paper). *Journal of ?* Statistical Software*. Vol. 8 (Issue 14). - allow    missing_copy_implementations  &l l   l   l   l     automatically_derived   allow    unused_qualifications   allow    missing_copy_implementations  &       automatically_derived   allow    unused_qualifications   allow    missing_copy_implementations  &     m     n    f7 Iterator which will generate a stream of random items.ȴ:A This iterator is created via the [`gen_iter`] method on [`Rng`].D̵- [`gen_iter`]: trait.Rng.html#method.gen_iterе0 [`Rng`]: trait.Rng.htmlp 'a T R    Ƕʶ 'a̶$ֶöpöǶpǶʶpʶֶpֶ  'p  automatically_derivedallow unused_qualifications'a T R   Ƕʶ̌# 'a̶NööǶǶʶʶ  ;C Iterator which will continuously generate random ascii characters.FH This iterator is created via the [`gen_ascii_chars`] method on [`Rng`].Kʹ; [`gen_ascii_chars`]: trait.Rng.html#method.gen_ascii_charsι> [`Rng`]: trait.Rng.htmlqź'a R   غ 'aں$ԺqԺغqغq  automatically_derivedallow unused_qualifications'a R  غ 'aںNԺԺغغ  A A wrapper for generating floating point numbers uniformly in theD7 open interval `(0,1)` (not including either endpoint).:@ Use `Closed01` for the closed interval `[0,1]`, and the defaultC< `Rand` implementation for `f32` and `f64` for the half-open? `[0,1)`.  # Example  ```rust  use rand::{random, Open01};+ let Open01(val) = random::>();.% println!("f32 from (0,1): {}", val);( ```rF  ΄A A wrapper for generating floating point numbers uniformly in theD7 open interval `(0,1)` (not including either endpoint).:@ Use `Closed01` for the closed interval `[0,1]`, and the defaultC< `Rand` implementation for `f32` and `f64` for the half-open? `[0,1)`.  # Example  ```rust  use rand::{random, Open01};+ let Open01(val) = random::>();.% println!("f32 from (0,1): {}", val);( ```r  rr  automatically_derivedallow unused_qualificationsF  $N΄  A A wrapper for generating floating point numbers uniformly in theD4 closed interval `[0,1]` (including both endpoints).7> Use `Open01` for the closed interval `(0,1)`, and the defaultA; `Rand` implementation of `f32` and `f64` for the half-open> `[0,1)`.  # Example  ```rust  use rand::{random, Closed01};!/ let Closed01(val) = random::>();2% println!("f32 from [0,1]: {}", val);( ```sF  $A A wrapper for generating floating point numbers uniformly in theD4 closed interval `[0,1]` (including both endpoints).7> Use `Open01` for the closed interval `(0,1)`, and the defaultA; `Rand` implementation of `f32` and `f64` for the half-open> `[0,1)`.  # Example  ```rust  use rand::{random, Closed01};!/ let Closed01(val) = random::>();2% println!("f32 from [0,1]: {}", val);( ```s  ss  automatically_derivedallow unused_qualificationsF  $$  ,B The standard RNG. This is designed to be efficient on the currentE platform. tt  automatically_derivedallow unused_qualificationsautomatically_derivedallow unused_qualifications  automatically_derivedallow unused_qualifications  / Controls how the thread-local RNG is reseeded.2cfg featurestdu/ Controls how the thread-local RNG is reseeded.2cfg featurestdu  automatically_derivedallow unused_qualifications  > The thread-local RNG.cfg featurestdw  w  automatically_derivedallow unused_qualifications  automatically_derivedallow unused_qualifications   o      w  thread_local   cfg    all    target_thread_local   not    all    target_family  wasm   not    target_feature  atomics           fstdcoreJJmarkerKK memLL RefCellL&LioLLRcM)L JitterRngM MOsRngMM IsaacRngM M Isaac64RngN  N ChaChaRngN  N XorShiftRngN  N IsaacWordRngO  O RangePPIndependentSamplePP SampleRangeP qP!3    markerι3ȹ Rngܹ3ܹRand3RangeGamma ChiSquared  FisherFĺĺStudentTͺͺNormal LogNormal  Expʻ XwwڨXèwڨXèRngXSampleXIndependentSampleXquvhlowhigh hkselfrng k  oselfrng o %qrslowܺhigh r  RangelowXrangeX accept_zoneX݋ rrng s  %% ʼм Ѽ tyҼԼ tyռ׼ټ unsignedڼ ident impl SampleRange for tyÿĿ˿ inlineſ fnٿ construct_rangeܿ low ty high ty Range ty let range w high as unsigned  w low as unsigned0 let unsigned_max  unsigned core unsigned MAX let zone unsigned_max  unsigned_max  range Range low low range range as ty accept_zone  zone as ty inline fn sample_range  R Rng r  Range ty rng  mut R ty loop let v rng gen unsigned if v r accept_zone as unsigned return w r low  w v  r range as unsigned as ty0 ty ty impl SampleRange for ty fn construct_range low ty high ty Range ty Range low low range high  low accept_zone 0.0 fn sample_range  R Rng r  Range ty rng  mut R ty r low  r range  rng gen ty RngwOpen01 wOpen01 wStandardNormalwStandardNormalwIndependentSamplewSamplewExpwLargewLargewOnewOnewSmallwSmallw DoFExactlyOne w DoFExactlyOne wDoFAnythingElsewDoFAnythingElsewshapescale shapescaleޓshapescaleselfrng   selfڄrng  %selfхrngׅ  %selfʆrngІ  %selfrng  %selfЊrng֊  %kʗ selfrng  %selfrng  %mn selfrng  %selfrng  %n selfrng  %selfrng  %RngRandOpen01 Open01 ziggurat ziggurat_tablesSampleIndependentSampleήήrng  ήxrngu%meanstd_devselfrng  %selfrng  %meanstd_dev selfrng  %selfrng  %RngRandziggurat ziggurat_tablesSampleIndependentSamplerng %xrng_u%גlambdaّגגגselfrng  ג%גגselfrng  ג%257 3.6541528853610087962572577.697117470131050077257257selfݾrng    self    %self  selfrng  %selfrng %% WeightedChoice items3 weight_range3ޱ'aitems 'a 'a%WeightedChoice items3 weight_range3ޱ'a%selfrng 'a %%WeightedChoice items3 weight_range3ޱ'a%selfrng 'a %%rng symmetric x_tabf_tabpdf zero_case  %%%(1u64 << 53) as f64Rngfmt'memptr AtomicUsize  ATOMIC_USIZE_INIT Ordering 6432 MEMORY_BLOCKS * MEMORY_BLOCKSIZE MEMORY_SIZE JitterRng dataroundstimer prev_time last_delta last_delta2mem_prev_indexmemdata_remaining         %N%selff  % NN FormatterNflagsLNfillLNalignLNwidthLN precisionLNbufLƒB  self     O selff %%   self % % Ok0Err0Ũ͆% timer %%selfrounds  %selfn_bits %selftime var_rounds  %self var_rounds  %self current_delta  %self %NoneSome0񸑔Ä6self %self %self %Ok0Err0Ũ͆ self var_rounds  % MEMORY_SIZEdatatime 74413924505247855453001003x  dummy %%self %self %selfïdestɯ % Ū88iofmt'memRngkP P  Ok0Err0Ũ͆self  self %selfv %%Nselff  % 444fill_buf   '_  '_Ū '_%888fill_buf   '_  '_Ū '_%libcnext_u32 next_u64 ioFile RngReadRng  OsGetrandomRngOsGetrandomRng OsReadRng  OsReadRng  bufߪ Ūnumber 318v %0ݰ ήХ" ̋         Ok0Err0Ũ͆self  self %selfv %%io  Read # mem  Rng  l ǹr  ǹǹǹself   ǹself  %self v  %%48r buf ϼ #%Default  Default  Rng   SeedableRng  }  32 * 1024rng generation_threshold reseeder  self  self  &self  &self dest  &%self    self΁ rngԁ   %%self rng   % Rng  HashMapӜ   :rng iterable amounṭ   rng slice amount  % rng slice amount  'a  'a<<Vec<buf6<len6 'arng length amount %ȍrng length amount %ȍrng length amount %ȍ ChaChaRngS  SIsaacRngT T Isaac64RngT  T 8char ( mem  Rand  Rng  n rng  %rng  %rng  %rng  %rng  %rng  %rng  %rng  %rng  %rng  %ʂ  Ђ  т  mod_name҂ ڂ  identۂ    ty   ty    mantissa_bits   expr    method_name   ident     mod   mod_name   & use  ܃  Rand Ń  Rngǃ ʃ  Open01̃ ҃  Closed01ԃ ݃  const  SCALE    ty    1u64     mantissa_bits as   ty   impl  Rand  for   ty  ڇ #2 Generate a floating point number in the half-openф 5# interval `[0,1)`. # #0 See `Closed01` for the closed interval `[0,1]`,х 3#, and `Open01` for the open interval `(0,1)`. /Ն ֆ ݆  inline׆  fn  rand   R   Rng     rng     mut  R    ty  ̇  rng    method_name    impl  Rand  for  Open01    ty        inline  fn  rand   R   Rng   Ɉ  rng   È  mutĈ  RȈ ˈ  Open01Έ Ԉ Ո  tyֈ ؈ ڈ   Open01    rng    method_name    0.25    SCALE  implNj  Rand̋  forы  Closed01Ջ ݋ ދ  tyߋ        inline  fn  rand   R   Rng     rng     mut  R   Closed01    ty     Closed01    rng  Í  method_nameč ύ Ѝ  ҍ  SCALEԍ  ڍ ܍   SCALEݍ   1.0 rng  %2097151rngÓ  %  ڔ  ۔ ܔ  ݔ  tyvarޔ   ident        impl   • ҕ ĕ  tyvarŕ ˕  Rand͕ ӕ  ԕ   Rand  for        tyvar            inline  fn  rand   R   Rng   –  _rng     mut  R Ė ǖ ٖ ɖ ʖ Ӗ ̖  tyvar͖ Ԗ  Ֆ ז ۖ      ͘  _rng   gen     tyvar    Θ  Ϙ   %       n   expr    t   ident       ts   ident        array_impl   ѝ  Ɲ   n  Ý 1ŝ ǝ ɝ ʝ ϝ ˝  ts̝ Ν  Н  implܝ   T   Rand  for    T    n  where  T   Rand        inline  fn  rand   R   Rng   Þ  _rng     mut  Rž Ş Ȟ Ξ  Tɞ ʞ ̞  n͞ О     _rng   gen     t         _rng   gen     ts            n   expr      implȟ ̟  T͟ Ο  RandП  for՟ ٟ ߟ  Tڟ ۟ ݟ  nޟ    fn  rand   R   Rng     _rng     mut  R     T    n       rng    ChaChaRng  IsaacRng   Isaac64Rng   XorShiftRng  zw  w  Rng   SeedableRng  Rand   81620 STATE_WORDS STATE_WORDSم      a   expr    b   expr    c   expr    d   expr      `  a    a    b    d    d     a    d   w     d  0   rotate_left   16    c    c    d    b    b     c    b   w     b  0   rotate_left   12    a    a    b    d    d     a    d   w     d  0   rotate_left   8    c    c    d    b    b     c    b   w     b  0   rotate_left   7         x   expr       quarter_round      x   0    x   4    x   8    x   12   quarter_round      x   1    x   5    x   9    x   13   quarter_round      x   2    x   6    x   10    x   14   quarter_round      x   3    x   7    x   11    x   15   quarter_round      x   0    x   5    x   10    x   15   quarter_round      x   1    x   6    x   11    x   12   quarter_round      x   2    x   7    x   8    x   13   quarter_round      x   3    x   4    x   9    x   14   STATE_WORDS STATE_WORDSoutput input    م مself  counter_low counter_high   مself key  & self & KEY_WORDS KEY_WORDSممself  &مم 'aself seed  'a&&seed  'a&م KEY_WORDSممother  %م KEY_WORDS KEY_WORDSslice + repeat  ? wӛ  wӛ  fmt 'ڛ Rng   SeedableRng  Rand   81 << RAND_SIZE_LEN1 << RAND_SIZE_LENRAND_SIZE_USIZERAND_SIZE_USIZE֌֌ ֌self use_rslĦ   ֌self ӏ &   ¨ Ĩ Ǩ  Ȩ   aڨ ۨ  aܨ  ݨ ި   bߨ   11   d   d   a   b   b   c   b   b      c  2   e   e   b   c   c   d   c   c      d   8   f   f   c ©  dĩ ũ  dƩ  ǩ  eȩ ɩ  d۩ ܩ  dݩ  ީ ߩ   e  16   g   g   d   e   e   f   e   e      f   10   h   h   e   f   f   g   f   f      g  4   a   a   fª ê  gŪ ƪ  gǪ  Ȫ  hɪ ʪ  gܪ ݪ  gު  ߪ    h   8   b   b   g   h   h   a   h   h      a  9   c   c   h   a   a   b     Ŭ   arr   expr Ǭ ʬ  ˬ   for  i  in   0   RAND_SIZE_USIZE   8   map      i    i   8   | a   a    arr    i   b   b    arr  ŭ  i­  í 1ĭ ƭ  c   c    arr    i  2   d   d    arr    i  3   e   e    arr    i  4   f   f    arr    i  5   g̮ ͮ  gή  Ϯ Ю  arrѮ Ԯ خ  iծ  ֮ 6׮ ٮ  hۮ ܮ  hݮ  ޮ ߮  arr    i  7   mix      self   mem    i   a   self   mem    i  1   b ¯  selfܯ   mem    i  2   c   self   mem    i  3   d   self   mem    i  4   e   self   mem    i  5   f   selfа ԰  memհ ذ ܰ  iٰ  ڰ 6۰ ݰ  gް ߰  self   mem    i  7   h  RAND_SIZE_USIZE / 2 ҷ     x   expr   ȷ  self   mem  Ʒ     x  2usize  0  as  usize    ŷ  RAND_SIZE_USIZE  · 1ķ ڸ       j   expr    shift   expr      @ let  base    j   let  mixĹ ȹ  aʹ  ̹ Ϲ  shiftй չ  let  x   self   mem    base   mr_offset   a     a    mix   self   mem  κ  base  ú  m2_offsetź Ϻ  let  y   ind     x   a   b   self   mem    base   mr_offset  y   bǻ ɻ  ind˻  λ ϻ   yл  һ  RAND_SIZE_LENջ  x   self   rsl    base   mr_offset  b          j   expr    shift   expr      @ let  base    j   letǽ  mix˽ Ͻ  aѽ  ӽ ֽ  shift׽ ܽ  let  x   self   mem    base   mr_offset   a     a    mix   self   mem ľ վ  basež  ʾ  m2_offset̾ ־  let  y   ind     x   a   b   self   mem    base   mr_offset  y   bο п  indҿ  տ ֿ   y׿  ٿ  RAND_SIZE_LENܿ  x   self   rsl    base   mr_offset  b   ֌֌self   ֌֌֌֌self  &֌֌ 'aself seed  'a&'seed  'a'֌  ֌֌other  %֌֌N֌self f  '% slice + repeat  ? w  w  fmt ' Rng   SeedableRng  Rand    81 << RAND_SIZE_64_LEN RAND_SIZE_64 RAND_SIZE_64    self use_rsl    self  '         var   ident     let  mut   var   w   0x9e3779b97f4a7c13            a   a    e   f   f      h  9   h   h   a   b   b    f   g   g      a   9   a   a   b   c   c    g   h   h      b  23   b   b   c   d   d    h   a   a      c   15   c   c   d   e   e    a   b   b      d  14   d   d   e   f   f    b   c   c      e   20   e   e   f   g   g    c   d   d      f  17   f   f   g   h   h    d   e   e      g   14   g   g   h        arr   expr       for  i  in   0   RAND_SIZE_64  8   map      i    i   8   | a   a    arr    i   b   b    arr    i  1   c   c    arr    i  2   d   d    arr    i  3   e   e    arr    i  4   f   f    arr    i  5   g   g    arr    i  6   h   h    arr    i  7   mix      self   mem    i   a   self   mem    i  1 €  bÀ Ā  selfހ   mem    i  2   c   self   mem    i  3   d   self   mem    i  4   e   self   mem    i  5   f   selfҁ ց  memׁ ځ ށ  iہ  ܁ 6݁ ߁  g   self   mem    i  7   h   RAND_SIZE_64 / 22[(0, MIDPOINT), (MIDPOINT, 0)]   È   x   expr ň Ȉ   ڈ  selfۈ ߈  mem   get_unchecked         x  3usize  0  as  usize      RAND_SIZE_64  1 ֊ Đ      j   expr    shift   expr       let  base   base    j   letϋ  mixӋ ׋  aً  ۋ ݋   aދ     shift   let  mix   if   j  0     mix  else    mix   unsafeŌ ̌  > let  x     self   mem   get_unchecked    base   mr_offset   a   mix   Í  selfč ȍ  memɍ ̍  get_unchecked͍ ڍ   baseۍ   m2_offset   let  y   ind     x   a   b     self Ď  memŎ Ȏ  get_unchecked_mutɎ ڎ   baseێ   mr_offset  y   b   ind     y   RAND_SIZE_64_LEN   x   Џ  selfя Տ  rsl֏ ُ  get_unchecked_mutڏ    base   mr_offset  b    ۖ      j   expr    shift   expr   ɖ  Ȗ  let  base   baseÑ  ȑ ʑ  jˑ ̑  let  mix   a      a    shift   let  mix   if   j  0     mix  else    mix   unsafeܒ   > let  x     self   mem   get_unchecked    base   mr_offset   aГ ғ  mixԓ  ؓ  ړ  selfۓ ߓ  mem   get_unchecked    base   m2_offset   let  y   ind     x   a   b   ֔  selfה ۔  memܔ ߔ  get_unchecked_mut    base   mr_offset  y   b   ind   ĕ  y   RAND_SIZE_64_LEN  ƕ  xȕ ɕ    self   rsl   get_unchecked_mut    base   mr_offset  b     self       self  'self  '   'a self seed  'a''seedȤ  'a'     other  %  N self f  '% w  w  Rng   SeedableRng  Rand        self    4  self seed  ''seed  ' 4  4    rng  % rngb  & selfd %selfg %selfr  %selfx  %self͂destӂ  %%self  %self  'a 'a   Generator rng _marker?'a self̗lowҗhighڗ  %selfn  %self  'a 'a   AsciiGenerator rng^'a selfvalues  'a  'aNoneSome0񸑔Ä6 'aselfvalues  'a' 'aNoneSome0񸑔Ä6 'aselfvalues  %  1065353216838860746071824188000174084503599627370495 'a'self 'a 'self 'a'self 'a'self 'a'selfɰdestϰ 'a'%  self   self 'self 'self 'selfdest '%  Generator rng _marker?'aB(self 'a (   AsciiGenerator rng^'aB(selfջ 'a (Ab"ABCDEFGHIJKLMNOPQRSTUVWXYZabcdefghijklmnopqrstuvwxyz0123456789" Ūself  !%!seed  !!  Ӛ  self   self (   'aselfseed 'a((seed 'a(      selfrng    32768       self   self (selfbytes (%   rngiterableamount &݋   self  Nselff (% qlowhigh  rrng   %qlowhigh  rrng   %qlowhigh ֒ rrng  ֒ %qlowhigh  rrng   %qlowhigh ߴ rrng  ߴ %qlowhigh  rrng   %qlow high   r rng    %qlow!high! r!rng!  %qlow"high"  r"rng"   %qlow#high#  r#rng#   %qlow$high$  r$rng$   %qlow%high% Ɍ r%rng%  Ɍ %< self %Nselff( %% ڠ   ג       ג  ג    self  Nselff+ Ș(% Ӿʑ  self %Nselff. %%    self %Nselff1 %% 㰙 selfʓ %Nselfדf<ד %% ہۼ        self  Nselff? (% s   self %NselffF %%   self %NselffQ %% ݪή ݪ ήήήself  ήήήήήNήselffX (% ӧڅƧt  self %Nselff[ %% Ŷ詓 self %Nselffb %%   self  Nselffi (% ŋ਍oג גגself %גגגגNגselffl %% 뛠W Nselffq %% Ũ࿉+      self     N selfft (% ޱ WeightedChoice items3 weight_range3ޱ'a 'a  WeightedChoice items3 weight_range3ޱ 'aN߫(selffu  'a ߫(% ×                          N selff %%   self %      self other  %      self % ǹ  ǹNǹself f   ǹ% זS      Nself f   % 㭵Œr 㭵Œr  self    Nself f  (% Rand   Rngǃ  ǃ Open01̃   ̃ Open01̃   ̃ Closed01ԃ   ԃ Closed01ԃ   ԃ  (1u64 << 53) as f64 rng  % ©©rng  %©  rng  % Rand   Rngǃ  ǃ Open01̃   ̃ Open01̃   ̃ Closed01ԃ   ԃ Closed01ԃ   ԃ  (1u64 << 24) as f32 rng  %  rng  %   rng  %   _rng   &   _rng    &   _rng          _rng           _rng           َ َ _rng           َ   _rng        ו      _rng        ו       _rng        ו       ټ ټ _rng        ו       ټ   _rng        ו          _rng        ו         32  _rng  & 3232 - 1  (_rng  & 32 - 1 32 - 1 - 1  (_rng  &  32 - 1 - 132 - 1 - 1 - 1  (_rng  & 32 - 1 - 1 - 132 - 1 - 1 - 1 - 1  (_rng  & 32 - 1 - 1 - 1 - 132 - 1 - 1 - 1 - 1 - 1  (_rng  & 32 - 1 - 1 - 1 - 1 - 132 - 1 - 1 - 1 - 1 - 1 - 1  (_rng  & 32 - 1 - 1 - 1 - 1 - 1 - 132 - 1 - 1 - 1 - 1 - 1 - 1 - 1  (_rng  & 32 - 1 - 1 - 1 - 1 - 1 - 1 - 1"32 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1  (_rng  & "32 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1&32 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1  (_rng  & &32 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1*32 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1  (_rng  & *32 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1.32 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1  (_rng  & .32 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1232 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1  (_rng  & 232 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1632 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1  (_rng  & 632 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1:32 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1  (_rng  & :32 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1>32 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1  (_rng  & >32 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1B32 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1  (_rng  & B32 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1F32 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1  (_rng  & F32 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1J32 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1  (_rng  & J32 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1N32 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1  (_rng  & N32 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1V32 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1  (_rng  & V32 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1^32 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1  (_rng  & ^32 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1f32 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1  (_rng  & f32 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1n32 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1  (_rng  & n32 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1v32 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1  (_rng  & v32 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1~32 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1  (_rng  & ~32 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 132 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1  (_rng  & 32 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 132 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1  (_rng  & 32 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 132 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1  (_rng  & 32 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 132 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1  (_rng  & 32 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 132 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1  (_rng  & 32 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 132 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1  (_rng  & 32 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 132 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1  )_rng  & 32 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 - 1 STATE_WORDS STATE_WORDS͑ م   مم ممself   مم STATE_WORDS STATE_WORDS مNمself f  )% RAND_SIZE_USIZERAND_SIZE_USIZEޅ憨f ֌      ֌֌ RAND_SIZE_64 RAND_SIZE_64޸֩        Ӗu      self      N self f  )% ?   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