path: root/lib/stdlib/src/rand.erl

%%
%% %CopyrightBegin%
%%
%% Copyright Ericsson AB 2015-2016. All Rights Reserved.
%%
%% Licensed under the Apache License, Version 2.0 (the "License");
%% you may not use this file except in compliance with the License.
%% You may obtain a copy of the License at
%%
%%     http://www.apache.org/licenses/LICENSE-2.0
%%
%% Unless required by applicable law or agreed to in writing, software
%% distributed under the License is distributed on an "AS IS" BASIS,
%% WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
%% See the License for the specific language governing permissions and
%% limitations under the License.
%%
%% %CopyrightEnd%
%%
%% =====================================================================
%% Multiple PRNG module for Erlang/OTP
%% Copyright (c) 2015-2016 Kenji Rikitake
%% =====================================================================

-module(rand).

-export([seed_s/1, seed_s/2, seed/1, seed/2,
	 export_seed/0, export_seed_s/1,
         uniform/0, uniform/1, uniform_s/1, uniform_s/2,
         jump/0, jump/1,
	 normal/0, normal_s/1
	]).

-compile({inline, [exs64_next/1, exsplus_next/1,
		   exsplus_jump/1,
		   exs1024_next/1, exs1024_calc/2,
		   exs1024_jump/1,
		   get_52/1, normal_kiwi/1]}).

-define(DEFAULT_ALG_HANDLER, exsplus).
-define(SEED_DICT, rand_seed).

%% =====================================================================
%% Types
%% =====================================================================

%% This depends on the algorithm handler function
-type alg_seed() :: exs64_state() | exsplus_state() | exs1024_state().
%% This is the algorithm handler function within this module
-type alg_handler() :: #{type      := alg(),
			 max       := integer(),
			 next      := fun(),
			 uniform   := fun(),
			 uniform_n := fun(),
			 jump      := fun()}.

%% Internal state
-opaque state() :: {alg_handler(), alg_seed()}.
-type alg() :: exs64 | exsplus | exs1024.
-opaque export_state() :: {alg(), alg_seed()}.
-export_type([alg/0, state/0, export_state/0]).

%% =====================================================================
%% API
%% =====================================================================

%% Return algorithm and seed so that RNG state can be recreated with seed/1
-spec export_seed() -> undefined | export_state().
export_seed() ->
    case get(?SEED_DICT) of
	{#{type:=Alg}, Seed} -> {Alg, Seed};
	_ -> undefined
    end.

-spec export_seed_s(state()) -> export_state().
export_seed_s({#{type:=Alg}, Seed}) -> {Alg, Seed}.

%% seed(Alg) seeds RNG with runtime dependent values
%% and return the NEW state

%% seed({Alg,Seed}) setup RNG with a previously exported seed
%% and return the NEW state

-spec seed(AlgOrExpState::alg() | export_state()) -> state().
seed(Alg) ->
    seed_put(seed_s(Alg)).

-spec seed_s(AlgOrExpState::alg() | export_state()) -> state().
seed_s(Alg) when is_atom(Alg) ->
    seed_s(Alg, {erlang:phash2([{node(),self()}]),
		 erlang:system_time(),
		 erlang:unique_integer()});
seed_s({Alg0, Seed}) ->
    {Alg,_SeedFun} = mk_alg(Alg0),
    {Alg, Seed}.

%% seed/2: seeds RNG with the algorithm and given values
%% and returns the NEW state.

-spec seed(Alg :: alg(), {integer(), integer(), integer()}) -> state().
seed(Alg0, S0) ->
    seed_put(seed_s(Alg0, S0)).

-spec seed_s(Alg :: alg(), {integer(), integer(), integer()}) -> state().
seed_s(Alg0, S0 = {_, _, _}) ->
    {Alg, Seed} = mk_alg(Alg0),
    AS = Seed(S0),
    {Alg, AS}.

%%% uniform/0, uniform/1, uniform_s/1, uniform_s/2 are all
%%% uniformly distributed random numbers.

%% uniform/0: returns a random float X where 0.0 < X < 1.0,
%% updating the state in the process dictionary.

-spec uniform() -> X::float().
uniform() ->
    {X, Seed} = uniform_s(seed_get()),
    _ = seed_put(Seed),
    X.

%% uniform/1: given an integer N >= 1,
%% uniform/1 returns a random integer X where 1 =< X =< N,
%% updating the state in the process dictionary.

-spec uniform(N :: pos_integer()) -> X::pos_integer().
uniform(N) ->
    {X, Seed} = uniform_s(N, seed_get()),
    _ = seed_put(Seed),
    X.

%% uniform_s/1: given a state, uniform_s/1
%% returns a random float X where 0.0 < X < 1.0,
%% and a new state.

-spec uniform_s(state()) -> {X::float(), NewS :: state()}.
uniform_s(State = {#{uniform:=Uniform}, _}) ->
    Uniform(State).

%% uniform_s/2: given an integer N >= 1 and a state, uniform_s/2
%% uniform_s/2 returns a random integer X where 1 =< X =< N,
%% and a new state.

-spec uniform_s(N::pos_integer(), state()) -> {X::pos_integer(), NewS::state()}.
uniform_s(N, State = {#{uniform_n:=Uniform, max:=Max}, _})
  when 0 < N, N =< Max ->
    Uniform(N, State);
uniform_s(N, State0 = {#{uniform:=Uniform}, _})
  when is_integer(N), 0 < N ->
    {F, State} = Uniform(State0),
    {trunc(F * N) + 1, State}.

%% jump/1: given a state, jump/1
%% returns a new state which is equivalent to that
%% after a large number of call defined for each algorithm.
%% The large number is algorithm dependent.

-spec jump(state()) -> {NewS :: state()}.
jump(State = {#{jump:=Jump}, _}) ->
    Jump(State).

%% jump/0: read the internal state and
%% apply the jump function for the state as in jump/1
%% and write back the new value to the internal state,
%% then returns the new value.

-spec jump() -> {NewS :: state()}.

jump() ->
    seed_put(jump(seed_get())).

%% normal/0: returns a random float with standard normal distribution
%% updating the state in the process dictionary.

-spec normal() -> float().
normal() ->
    {X, Seed} = normal_s(seed_get()),
    _ = seed_put(Seed),
    X.

%% normal_s/1: returns a random float with standard normal distribution
%% The Ziggurat Method for generating random variables - Marsaglia and Tsang
%% Paper and reference code: http://www.jstatsoft.org/v05/i08/

-spec normal_s(state()) -> {float(), NewS :: state()}.
normal_s(State0) ->
    {Sign, R, State} = get_52(State0),
    Idx = R band 16#FF,
    Idx1 = Idx+1,
    {Ki, Wi} = normal_kiwi(Idx1),
    X = R * Wi,
    case R < Ki of
	%% Fast path 95% of the time
	true when Sign =:= 0 -> {X, State};
	true -> {-X, State};
	%% Slow path
	false when Sign =:= 0 -> normal_s(Idx, Sign, X, State);
	false -> normal_s(Idx, Sign, -X, State)
    end.

%% =====================================================================
%% Internal functions

-define(UINT21MASK, 16#00000000001fffff).
-define(UINT32MASK, 16#00000000ffffffff).
-define(UINT33MASK, 16#00000001ffffffff).
-define(UINT39MASK, 16#0000007fffffffff).
-define(UINT58MASK, 16#03ffffffffffffff).
-define(UINT64MASK, 16#ffffffffffffffff).

-type uint64() :: 0..16#ffffffffffffffff.
-type uint58() :: 0..16#03ffffffffffffff.

-spec seed_put(state()) -> state().
seed_put(Seed) ->
    put(?SEED_DICT, Seed),
    Seed.

seed_get() ->
    case get(?SEED_DICT) of
        undefined -> seed(?DEFAULT_ALG_HANDLER);
        Old -> Old  % no type checking here
    end.

%% Setup alg record
mk_alg(exs64) ->
    {#{type=>exs64, max=>?UINT64MASK, next=>fun exs64_next/1,
       uniform=>fun exs64_uniform/1, uniform_n=>fun exs64_uniform/2,
       jump=>fun exs64_jump/1},
     fun exs64_seed/1};
mk_alg(exsplus) ->
    {#{type=>exsplus, max=>?UINT58MASK, next=>fun exsplus_next/1,
       uniform=>fun exsplus_uniform/1, uniform_n=>fun exsplus_uniform/2,
       jump=>fun exsplus_jump/1},
     fun exsplus_seed/1};
mk_alg(exs1024) ->
    {#{type=>exs1024, max=>?UINT64MASK, next=>fun exs1024_next/1,
       uniform=>fun exs1024_uniform/1, uniform_n=>fun exs1024_uniform/2,
       jump=>fun exs1024_jump/1},
     fun exs1024_seed/1}.

%% =====================================================================
%% exs64 PRNG: Xorshift64*
%% Algorithm by Sebastiano Vigna
%% Reference URL: http://xorshift.di.unimi.it/
%% =====================================================================

-type exs64_state() :: uint64().

exs64_seed({A1, A2, A3}) ->
    {V1, _} = exs64_next(((A1 band ?UINT32MASK) * 4294967197 + 1)),
    {V2, _} = exs64_next(((A2 band ?UINT32MASK) * 4294967231 + 1)),
    {V3, _} = exs64_next(((A3 band ?UINT32MASK) * 4294967279 + 1)),
    ((V1 * V2 * V3) rem (?UINT64MASK - 1)) + 1.

%% Advance xorshift64* state for one step and generate 64bit unsigned integer
-spec exs64_next(exs64_state()) -> {uint64(), exs64_state()}.
exs64_next(R) ->
    R1 = R bxor (R bsr 12),
    R2 = R1 bxor ((R1 band ?UINT39MASK) bsl 25),
    R3 = R2 bxor (R2 bsr 27),
    {(R3 * 2685821657736338717) band ?UINT64MASK, R3}.

exs64_uniform({Alg, R0}) ->
    {V, R1} = exs64_next(R0),
    {V / 18446744073709551616, {Alg, R1}}.

exs64_uniform(Max, {Alg, R}) ->
    {V, R1} = exs64_next(R),
    {(V rem Max) + 1, {Alg, R1}}.

exs64_jump(_) ->
    erlang:error(not_implemented).

%% =====================================================================
%% exsplus PRNG: Xorshift116+
%% Algorithm by Sebastiano Vigna
%% Reference URL: http://xorshift.di.unimi.it/
%% 58 bits fits into an immediate on 64bits erlang and is thus much faster.
%% Modification of the original Xorshift128+ algorithm to 116
%% by Sebastiano Vigna, a lot of thanks for his help and work.
%% =====================================================================
-type exsplus_state() :: nonempty_improper_list(uint58(), uint58()).

-dialyzer({no_improper_lists, exsplus_seed/1}).

exsplus_seed({A1, A2, A3}) ->
    {_, R1} = exsplus_next([(((A1 * 4294967197) + 1) band ?UINT58MASK)|
			    (((A2 * 4294967231) + 1) band ?UINT58MASK)]),
    {_, R2} = exsplus_next([(((A3 * 4294967279) + 1) band ?UINT58MASK)|
			    tl(R1)]),
    R2.

-dialyzer({no_improper_lists, exsplus_next/1}).

%% Advance xorshift116+ state for one step and generate 58bit unsigned integer
-spec exsplus_next(exsplus_state()) -> {uint58(), exsplus_state()}.
exsplus_next([S1|S0]) ->
    %% Note: members s0 and s1 are swapped here
    S11 = (S1 bxor (S1 bsl 24)) band ?UINT58MASK,
    S12 = S11 bxor S0 bxor (S11 bsr 11) bxor (S0 bsr 41),
    {(S0 + S12) band ?UINT58MASK, [S0|S12]}.

exsplus_uniform({Alg, R0}) ->
    {I, R1} = exsplus_next(R0),
    {I / (?UINT58MASK+1), {Alg, R1}}.

exsplus_uniform(Max, {Alg, R}) ->
    {V, R1} = exsplus_next(R),
    {(V rem Max) + 1, {Alg, R1}}.

%% This is the jump function for the exsplus generator, equivalent
%% to 2^64 calls to next/1; it can be used to generate 2^52
%% non-overlapping subsequences for parallel computations.
%% Note: the jump function takes 116 times of the execution time of
%% next/1.

%% -define(JUMPCONST, 16#000d174a83e17de2302f8ea6bc32c797).
%% split into 58-bit chunks
%% and two iterative executions

-define(JUMPCONST1, 16#02f8ea6bc32c797).
-define(JUMPCONST2, 16#345d2a0f85f788c).
-define(JUMPELEMLEN, 58).

-spec exsplus_jump(exsplus_state()) -> exsplus_state().

exsplus_jump({Alg, S}) ->
    {S1, AS1} = exsplus_jump(S, [0|0], ?JUMPCONST1, ?JUMPELEMLEN),
    {_,  AS2} = exsplus_jump(S1, AS1,  ?JUMPCONST2, ?JUMPELEMLEN),
    {Alg, AS2}.

-spec exsplus_jump(state(), state(), pos_integer(), pos_integer()) ->
           {state(), state()}.

exsplus_jump(S, AS, _, 0) ->
    {S, AS};
exsplus_jump(S, [AS0|AS1], J, N) ->
    {_, NS} = exsplus_next(S),
    case (J band 1) of
        1 ->
            [S0|S1] = S,
            exsplus_jump(NS, [(AS0 bxor S0)|(AS1 bxor S1)], J bsr 1, N-1);
        0 ->
            exsplus_jump(NS, [AS0|AS1], J bsr 1, N-1)
    end.

%% =====================================================================
%% exs1024 PRNG: Xorshift1024*
%% Algorithm by Sebastiano Vigna
%% Reference URL: http://xorshift.di.unimi.it/
%% =====================================================================

-type exs1024_state() :: {list(uint64()), list(uint64())}.

exs1024_seed({A1, A2, A3}) ->
    B1 = (((A1 band ?UINT21MASK) + 1) * 2097131) band ?UINT21MASK,
    B2 = (((A2 band ?UINT21MASK) + 1) * 2097133) band ?UINT21MASK,
    B3 = (((A3 band ?UINT21MASK) + 1) * 2097143) band ?UINT21MASK,
    {exs1024_gen1024((B1 bsl 43) bor (B2 bsl 22) bor (B3 bsl 1) bor 1),
     []}.

%% Generate a list of 16 64-bit element list
%% of the xorshift64* random sequence
%% from a given 64-bit seed.
%% Note: dependent on exs64_next/1
-spec exs1024_gen1024(uint64()) -> list(uint64()).
exs1024_gen1024(R) ->
    exs1024_gen1024(16, R, []).

exs1024_gen1024(0, _, L) ->
    L;
exs1024_gen1024(N, R, L) ->
    {X, R2} = exs64_next(R),
    exs1024_gen1024(N - 1, R2, [X|L]).

%% Calculation of xorshift1024*.
%% exs1024_calc(S0, S1) -> {X, NS1}.
%% X: random number output
-spec exs1024_calc(uint64(), uint64()) -> {uint64(), uint64()}.
exs1024_calc(S0, S1) ->
    S11 = S1 bxor ((S1 band ?UINT33MASK) bsl 31),
    S12 = S11 bxor (S11 bsr 11),
    S01 = S0 bxor (S0 bsr 30),
    NS1 = S01 bxor S12,
    {(NS1 * 1181783497276652981) band ?UINT64MASK, NS1}.

%% Advance xorshift1024* state for one step and generate 64bit unsigned integer
-spec exs1024_next(exs1024_state()) -> {uint64(), exs1024_state()}.
exs1024_next({[S0,S1|L3], RL}) ->
    {X, NS1} = exs1024_calc(S0, S1),
    {X, {[NS1|L3], [S0|RL]}};
exs1024_next({[H], RL}) ->
    NL = [H|lists:reverse(RL)],
    exs1024_next({NL, []}).

exs1024_uniform({Alg, R0}) ->
    {V, R1} = exs1024_next(R0),
    {V / 18446744073709551616, {Alg, R1}}.

exs1024_uniform(Max, {Alg, R}) ->
    {V, R1} = exs1024_next(R),
    {(V rem Max) + 1, {Alg, R1}}.

%% This is the jump function for the exs1024 generator, equivalent
%% to 2^512 calls to next(); it can be used to generate 2^512
%% non-overlapping subsequences for parallel computations.
%% Note: the jump function takes ~2000 times of the execution time of
%% next/1.

%% Jump constant here split into 58 bits for speed
-define(JUMPCONSTHEAD, 16#00242f96eca9c41d).
-define(JUMPCONSTTAIL,
        [16#0196e1ddbe5a1561,
         16#0239f070b5837a3c,
         16#03f393cc68796cd2,
         16#0248316f404489af,
         16#039a30088bffbac2,
         16#02fea70dc2d9891f,
         16#032ae0d9644caec4,
         16#0313aac17d8efa43,
         16#02f132e055642626,
         16#01ee975283d71c93,
         16#00552321b06f5501,
         16#00c41d10a1e6a569,
         16#019158ecf8aa1e44,
         16#004e9fc949d0b5fc,
         16#0363da172811fdda,
         16#030e38c3b99181f2,
         16#0000000a118038fc]).
-define(JUMPTOTALLEN, 1024).
-define(RINGLEN, 16).

-spec exs1024_jump(state()) -> state().

exs1024_jump({Alg, {L, RL}}) ->
    P = length(RL),
    AS = exs1024_jump({L, RL},
         [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
         ?JUMPCONSTTAIL, ?JUMPCONSTHEAD, ?JUMPELEMLEN, ?JUMPTOTALLEN),
    {ASL, ASR} = lists:split(?RINGLEN - P, AS),
    {Alg, {ASL, lists:reverse(ASR)}}.

-spec exs1024_jump(state(), list(non_neg_integer()),
           list(non_neg_integer()), non_neg_integer(),
           non_neg_integer(), non_neg_integer()) -> list(non_neg_integer()).

exs1024_jump(_, AS, _, _, _, 0) ->
    AS;
exs1024_jump(S, AS, [H|T], _, 0, TN) ->
    exs1024_jump(S, AS, T, H, ?JUMPELEMLEN, TN);
exs1024_jump({L, RL}, AS, JL, J, N, TN) ->
    {_, NS} = exs1024_next({L, RL}),
    case (J band 1) of
        1 ->
            AS2 = lists:zipwith(fun(X, Y) -> X bxor Y end,
                        AS, L ++ lists:reverse(RL)),
            exs1024_jump(NS, AS2, JL, J bsr 1, N-1, TN-1);
        0 ->
            exs1024_jump(NS, AS, JL, J bsr 1, N-1, TN-1)
    end.

%% =====================================================================
%% Ziggurat cont
%% =====================================================================
-define(NOR_R, 3.6541528853610087963519472518).
-define(NOR_INV_R, 1/?NOR_R).

%% return a {sign, Random51bits, State}
get_52({Alg=#{next:=Next}, S0}) ->
    {Int,S1} = Next(S0),
    {((1 bsl 51) band Int), Int band ((1 bsl 51)-1), {Alg, S1}}.

%% Slow path
normal_s(0, Sign, X0, State0) ->
    {U0, S1} = uniform_s(State0),
    X = -?NOR_INV_R*math:log(U0),
    {U1, S2} = uniform_s(S1),
    Y = -math:log(U1),
    case Y+Y > X*X of
	false ->
	    normal_s(0, Sign, X0, S2);
	true when Sign =:= 0 ->
	    {?NOR_R + X, S2};
	true ->
	    {-?NOR_R - X, S2}
    end;
normal_s(Idx, _Sign, X, State0) ->
    Fi2 = normal_fi(Idx+1),
    {U0, S1} = uniform_s(State0),
    case ((normal_fi(Idx) - Fi2)*U0 + Fi2) < math:exp(-0.5*X*X) of
	true ->  {X, S1};
	false -> normal_s(S1)
    end.

%% Tables for generating normal_s
%% ki is zipped with wi (slightly faster)
normal_kiwi(Indx) ->
    element(Indx,
	{{2104047571236786,1.736725412160263e-15}, {0,9.558660351455634e-17},
	 {1693657211986787,1.2708704834810623e-16},{1919380038271141,1.4909740962495474e-16},
	 {2015384402196343,1.6658733631586268e-16},{2068365869448128,1.8136120810119029e-16},
	 {2101878624052573,1.9429720153135588e-16},{2124958784102998,2.0589500628482093e-16},
	 {2141808670795147,2.1646860576895422e-16},{2154644611568301,2.2622940392218116e-16},
	 {2164744887587275,2.353271891404589e-16},{2172897953696594,2.438723455742877e-16},
	 {2179616279372365,2.5194879829274225e-16},{2185247251868649,2.5962199772528103e-16},
	 {2190034623107822,2.6694407473648285e-16},{2194154434521197,2.7395729685142446e-16},
	 {2197736978774660,2.8069646002484804e-16},{2200880740891961,2.871905890411393e-16},
	 {2203661538010620,2.9346417484728883e-16},{2206138681109102,2.9953809336782113e-16},
	 {2208359231806599,3.054303000719244e-16},{2210361007258210,3.111563633892157e-16},
	 {2212174742388539,3.1672988018581815e-16},{2213825672704646,3.2216280350549905e-16},
	 {2215334711002614,3.274657040793975e-16},{2216719334487595,3.326479811684171e-16},
	 {2217994262139172,3.377180341735323e-16},{2219171977965032,3.4268340353119356e-16},
	 {2220263139538712,3.475508873172976e-16},{2221276900117330,3.523266384600203e-16},
	 {2222221164932930,3.5701624633953494e-16},{2223102796829069,3.616248057159834e-16},
	 {2223927782546658,3.661569752965354e-16},{2224701368170060,3.7061702777236077e-16},
	 {2225428170204312,3.75008892787478e-16},{2226112267248242,3.7933619401549554e-16},
	 {2226757276105256,3.836022812967728e-16},{2227366415328399,3.8781025861250247e-16},
	 {2227942558554684,3.919630085325768e-16},{2228488279492521,3.9606321366256378e-16},
	 {2229005890047222,4.001133755254669e-16},{2229497472775193,4.041158312414333e-16},
	 {2229964908627060,4.080727683096045e-16},{2230409900758597,4.119862377480744e-16},
	 {2230833995044585,4.1585816580828064e-16},{2231238597816133,4.1969036444740733e-16},
	 {2231624991250191,4.234845407152071e-16},{2231994346765928,4.272423051889976e-16},
	 {2232347736722750,4.309651795716294e-16},{2232686144665934,4.346546035512876e-16},
	 {2233010474325959,4.383119410085457e-16},{2233321557544881,4.4193848564470665e-16},
	 {2233620161276071,4.455354660957914e-16},{2233906993781271,4.491040505882875e-16},
	 {2234182710130335,4.52645351185714e-16},{2234447917093496,4.561604276690038e-16},
	 {2234703177503020,4.596502910884941e-16},{2234949014150181,4.631159070208165e-16},
	 {2235185913274316,4.665581985600875e-16},{2235414327692884,4.699780490694195e-16},
	 {2235634679614920,4.733763047158324e-16},{2235847363174595,4.767537768090853e-16},
	 {2236052746716837,4.8011124396270155e-16},{2236251174862869,4.834494540935008e-16},
	 {2236442970379967,4.867691262742209e-16},{2236628435876762,4.900709524522994e-16},
	 {2236807855342765,4.933555990465414e-16},{2236981495548562,4.966237084322178e-16},
	 {2237149607321147,4.998759003240909e-16},{2237312426707209,5.031127730659319e-16},
	 {2237470176035652,5.0633490483427195e-16},{2237623064889403,5.095428547633892e-16},
	 {2237771290995388,5.127371639978797e-16},{2237915041040597,5.159183566785736e-16},
	 {2238054491421305,5.190869408670343e-16},{2238189808931712,5.222434094134042e-16},
	 {2238321151397660,5.253882407719454e-16},{2238448668260432,5.285218997682382e-16},
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	 {2241599511767028,6.578711085350741e-16},{2241636510880960,6.608538148078259e-16},
	 {2241672336512612,6.638394348803506e-16},{2241707005631362,6.668282304624746e-16},
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	 {2241863537413311,6.818290694006254e-16},{2241891576310281,6.848424730550038e-16},
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	 {2241954395725356,8.524547008695596e-16},{2241924896721443,8.562094740106233e-16},
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	 {2241260098640860,9.164968996219135e-16},{2241197758920538,9.208324163262308e-16},
	 {2241132642244704,9.252153239095693e-16},{2241064627262652,9.296473063086417e-16},
	 {2240993584191742,9.341301313425265e-16},{2240919374095536,9.38665656618666e-16},
	 {2240841848084890,9.432558359676707e-16},{2240760846432232,9.479027264651738e-16},
	 {2240676197587784,9.526084961066279e-16},{2240587717084782,9.57375432209745e-16},
	 {2240495206318753,9.622059506294838e-16},{2240398451183567,9.671026058823054e-16},
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	 {2240080312570155,9.822172599190541e-16},{2239964071293331,9.874071960480671e-16},
	 {2239842221996530,9.926785548807976e-16},{2239714417896699,9.980350026183645e-16},
	 {2239580280957725,1.003480452143618e-15},{2239439398282193,1.0090190861637457e-15},
	 {2239291317986196,1.0146553831467086e-15},{2239135544468203,1.0203941464683124e-15},
	 {2238971532964979,1.0262405372613567e-15},{2238798683265269,1.0322001115486456e-15},
	 {2238616332424351,1.03827886235154e-15},{2238423746288095,1.044483267600047e-15},
	 {2238220109591890,1.0508203448355195e-15},{2238004514345216,1.057297713900989e-15},
	 {2237775946143212,1.06392366906768e-15},{2237533267957822,1.0707072623632994e-15},
	 {2237275200846753,1.0776584002668106e-15},{2237000300869952,1.0847879564403425e-15},
	 {2236706931309099,1.0921079038149563e-15},{2236393229029147,1.0996314701785628e-15},
	 {2236057063479501,1.1073733224935752e-15},{2235695986373246,1.1153497865853155e-15},
	 {2235307169458859,1.1235791107110833e-15},{2234887326941578,1.1320817840164846e-15},
	 {2234432617919447,1.140880924258278e-15},{2233938522519765,1.1500027537839792e-15},
	 {2233399683022677,1.159477189144919e-15},{2232809697779198,1.169338578691096e-15},
	 {2232160850599817,1.17962663529558e-15},{2231443750584641,1.190387629928289e-15},
	 {2230646845562170,1.2016759392543819e-15},{2229755753817986,1.2135560818666897e-15},
	 {2228752329126533,1.2261054417450561e-15},{2227613325162504,1.2394179789163251e-15},
	 {2226308442121174,1.2536093926602567e-15},{2224797391720399,1.268824481425501e-15},
	 {2223025347823832,1.2852479319096109e-15},{2220915633329809,1.3031206634689985e-15},
	 {2218357446087030,1.3227655770195326e-15},{2215184158448668,1.3446300925011171e-15},
	 {2211132412537369,1.3693606835128518e-15},{2205758503851065,1.397943667277524e-15},
	 {2198248265654987,1.4319989869661328e-15},{2186916352102141,1.4744848603597596e-15},
	 {2167562552481814,1.5317872741611144e-15},{2125549880839716,1.6227698675312968e-15}}).

normal_fi(Indx) ->
    element(Indx,
	    {1.0000000000000000e+00,9.7710170126767082e-01,9.5987909180010600e-01,
	     9.4519895344229909e-01,9.3206007595922991e-01,9.1999150503934646e-01,
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	     8.5134625845867751e-01,8.4291565311220373e-01,8.3471629298688299e-01,
	     8.2672683394622093e-01,8.1892919160370192e-01,8.1130787431265572e-01,
	     8.0384948317096383e-01,7.9654233042295841e-01,7.8937614356602404e-01,
	     7.8234183265480195e-01,7.7543130498118662e-01,7.6863731579848571e-01,
	     7.6195334683679483e-01,7.5537350650709567e-01,7.4889244721915638e-01,
	     7.4250529634015061e-01,7.3620759812686210e-01,7.2999526456147568e-01,
	     7.2386453346862967e-01,7.1781193263072152e-01,7.1183424887824798e-01,
	     7.0592850133275376e-01,7.0009191813651117e-01,6.9432191612611627e-01,
	     6.8861608300467136e-01,6.8297216164499430e-01,6.7738803621877308e-01,
	     6.7186171989708166e-01,6.6639134390874977e-01,6.6097514777666277e-01,
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	     6.3982027745305614e-01,6.3465179928762327e-01,6.2952877992483625e-01,
	     6.2445001554702606e-01,6.1941436060583399e-01,6.1442072388891344e-01,
	     6.0946806492577310e-01,6.0455539069746733e-01,5.9968175261912482e-01,
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	     5.8055999610079034e-01,5.7586868297235316e-01,5.7121150673525267e-01,
	     5.6658776325616389e-01,5.6199677581452390e-01,5.5743789361876550e-01,
	     5.5291049042583185e-01,5.4841396325526537e-01,5.4394773119002582e-01,
	     5.3951123425695158e-01,5.3510393238045717e-01,5.3072530440366150e-01,
	     5.2637484717168403e-01,5.2205207467232140e-01,5.1775651722975591e-01,
	     5.1348772074732651e-01,5.0924524599574761e-01,5.0502866794346790e-01,
	     5.0083757512614835e-01,4.9667156905248933e-01,4.9253026364386815e-01,
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	     4.7620473271950547e-01,4.7218153846772976e-01,4.6818096140569321e-01,
	     4.6420268904817391e-01,4.6024641781284248e-01,4.5631185267871610e-01,
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	     4.2935454102944126e-01,4.2558393133802180e-01,4.2183270922949573e-01,
	     4.1810064983784795e-01,4.1438753404089090e-01,4.1069314827018799e-01,
	     4.0701728432947315e-01,4.0335973922111429e-01,3.9972031498019700e-01,
	     3.9609881851583223e-01,3.9249506145931540e-01,3.8890886001878855e-01,
	     3.8534003484007706e-01,3.8178841087339344e-01,3.7825381724561896e-01,
	     3.7473608713789086e-01,3.7123505766823922e-01,3.6775056977903225e-01,
	     3.6428246812900372e-01,3.6083060098964775e-01,3.5739482014578022e-01,
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	     3.4380971314685055e-01,3.4045225704452164e-01,3.3711006663700588e-01,
	     3.3378301583071823e-01,3.3047098137916342e-01,3.2717384281360129e-01,
	     3.2389148237639104e-01,3.2062378495690530e-01,3.1737063802991350e-01,
	     3.1413193159633707e-01,3.1090755812628634e-01,3.0769741250429189e-01,
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	     2.7635698929566810e-01,2.7329705406857691e-01,2.7025025636587519e-01,
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	     1.5844461415592431e-01,1.5588826472447920e-01,1.5334316106026283e-01,
	     1.5080929068184568e-01,1.4828664273257453e-01,1.4577520800599403e-01,
	     1.4327497897351341e-01,1.4078594981444470e-01,1.3830811644855071e-01,
	     1.3584147657125373e-01,1.3338602969166913e-01,1.3094177717364430e-01,
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	     1.1414597782783835e-01,1.1179156816383801e-01,1.0944845714681163e-01,
	     1.0711666777468364e-01,1.0479622562248690e-01,1.0248715894193508e-01,
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	     5.5224032992509968e-03,4.0379725933630305e-03,2.6090727461021627e-03,
	     1.2602859304985975e-03}).