aboutsummaryrefslogtreecommitdiffstats
path: root/lib/stdlib/src/rand.erl
blob: 93409d95df2ebcad0df053aa9d2a44e910294205 (plain) (blame)
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
269
270
271
272
273
274
275
276
277
278
279
280
281
282
283
284
285
286
287
288
289
290
291
292
293
294
295
296
297
298
299
300
301
302
303
304
305
306
307
308
309
310
311
312
313
314
315
316
317
318
319
320
321
322
323
324
325
326
327
328
329
330
331
332
333
334
335
336
337
338
339
340
341
342
343
344
345
346
347
348
349
350
351
352
353
354
355
356
357
358
359
360
361
362
363
364
365
366
367
368
369
370
371
372
373
374
375
376
377
378
379
380
381
382
383
384
385
386
387
388
389
390
391
392
393
394
395
396
397
398
399
400
401
402
403
404
405
406
407
408
409
410
411
412
413
414
415
416
417
418
419
420
421
422
423
424
425
426
427
428
429
430
431
432
433
434
435
436
437
438
439
440
441
442
443
444
445
446
447
448
449
450
451
452
453
454
455
456
457
458
459
460
461
462
463
464
465
466
467
468
469
470
471
472
473
474
475
476
477
478
479
480
481
482
483
484
485
486
487
488
489
490
491
492
493
494
495
496
497
498
499
500
501
502
503
504
505
506
507
508
509
510
511
512
513
514
515
516
517
518
519
520
521
522
523
524
525
526
527
528
529
530
531
532
533
534
535
536
537
538
539
540
541
542
543
544
545
546
547
548
549
550
551
552
553
554
555
556
557
558
559
560
561
562
563
564
565
566
567
568
569
570
571
572
573
574
575
576
577
578
579
580
581
582
583
584
585
586
587
588
589
590
591
592
593
594
595
596
%%
%% %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 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,
	 normal/0, normal_s/1
	]).

-compile({inline, [exs64_next/1, exsplus_next/1,
		   exs1024_next/1, exs1024_calc/2,
		   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()}.

%% 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) ->
    R = seed_s(Alg),
    _ = seed_put(R),
    R.

-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) ->
    State = seed_s(Alg0, S0),
    _ = seed_put(State),
    State.

-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}.

%% 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()) -> undefined | state().
seed_put(Seed) ->
    put(?SEED_DICT, 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},
     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},
     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},
     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}}.

%% =====================================================================
%% 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}}.

%% =====================================================================
%% 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}}.

%% =====================================================================
%% 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},
	 {2238572501115169,5.316448383216618e-16},{2238692784207942,5.34757496126473e-16},
	 {2238809644895133,5.378603012945235e-16},{2238923204068402,5.409536709623993e-16},
	 {2239033576548190,5.440380118655467e-16},{2239140871448443,5.471137208817361e-16},
	 {2239245192514958,5.501811855460336e-16},{2239346638439541,5.532407845392784e-16},
	 {2239445303151952,5.56292888151909e-16},{2239541276091442,5.593378587248462e-16},
	 {2239634642459498,5.623760510690043e-16},{2239725483455293,5.65407812864896e-16},
	 {2239813876495186,5.684334850436814e-16},{2239899895417494,5.714534021509204e-16},
	 {2239983610673676,5.744678926941961e-16},{2240065089506935,5.774772794756965e-16},
	 {2240144396119183,5.804818799107686e-16},{2240221591827230,5.834820063333892e-16},
	 {2240296735208969,5.864779662894365e-16},{2240369882240293,5.894700628185872e-16},
	 {2240441086423386,5.924585947256134e-16},{2240510398907004,5.95443856841806e-16},
	 {2240577868599305,5.984261402772028e-16},{2240643542273726,6.014057326642664e-16},
	 {2240707464668391,6.043829183936125e-16},{2240769678579486,6.073579788423606e-16},
	 {2240830224948980,6.103311925956439e-16},{2240889142947082,6.133028356617911e-16},
	 {2240946470049769,6.162731816816596e-16},{2241002242111691,6.192425021325847e-16},
	 {2241056493434746,6.222110665273788e-16},{2241109256832602,6.251791426088e-16},
	 {2241160563691400,6.281469965398895e-16},{2241210444026879,6.311148930905604e-16},
	 {2241258926538122,6.34083095820806e-16},{2241306038658137,6.370518672608815e-16},
	 {2241351806601435,6.400214690888025e-16},{2241396255408788,6.429921623054896e-16},
	 {2241439408989313,6.459642074078832e-16},{2241481290160038,6.489378645603397e-16},
	 {2241521920683062,6.519133937646159e-16},{2241561321300462,6.548910550287415e-16},
	 {2241599511767028,6.578711085350741e-16},{2241636510880960,6.608538148078259e-16},
	 {2241672336512612,6.638394348803506e-16},{2241707005631362,6.668282304624746e-16},
	 {2241740534330713,6.698204641081558e-16},{2241772937851689,6.728163993837531e-16},
	 {2241804230604585,6.758163010371901e-16},{2241834426189161,6.78820435168298e-16},
	 {2241863537413311,6.818290694006254e-16},{2241891576310281,6.848424730550038e-16},
	 {2241918554154466,6.878609173251664e-16},{2241944481475843,6.908846754557169e-16},
	 {2241969368073071,6.939140229227569e-16},{2241993223025298,6.969492376174829e-16},
	 {2242016054702685,6.999906000330764e-16},{2242037870775710,7.030383934552151e-16},
	 {2242058678223225,7.060929041565482e-16},{2242078483339331,7.091544215954873e-16},
	 {2242097291739040,7.122232386196779e-16},{2242115108362774,7.152996516745303e-16},
	 {2242131937479672,7.183839610172063e-16},{2242147782689725,7.214764709364707e-16},
	 {2242162646924736,7.245774899788387e-16},{2242176532448092,7.276873311814693e-16},
	 {2242189440853337,7.308063123122743e-16},{2242201373061537,7.339347561177405e-16},
	 {2242212329317416,7.370729905789831e-16},{2242222309184237,7.4022134917658e-16},
	 {2242231311537397,7.433801711647648e-16},{2242239334556717,7.465498018555889e-16},
	 {2242246375717369,7.497305929136979e-16},{2242252431779415,7.529229026624058e-16},
	 {2242257498775893,7.561270964017922e-16},{2242261571999416,7.5934354673958895e-16},
	 {2242264645987196,7.625726339356756e-16},{2242266714504453,7.658147462610487e-16},
	 {2242267770526109,7.690702803721919e-16},{2242267806216711,7.723396417018299e-16},
	 {2242266812908462,7.756232448671174e-16},{2242264781077289,7.789215140963852e-16},
	 {2242261700316818,7.822348836756411e-16},{2242257559310145,7.855637984161084e-16},
	 {2242252345799276,7.889087141441755e-16},{2242246046552082,7.922700982152271e-16},
	 {2242238647326615,7.956484300529366e-16},{2242230132832625,7.99044201715713e-16},
	 {2242220486690076,8.024579184921259e-16},{2242209691384458,8.058900995272657e-16},
	 {2242197728218684,8.093412784821501e-16},{2242184577261310,8.128120042284501e-16},
	 {2242170217290819,8.163028415809877e-16},{2242154625735679,8.198143720706533e-16},
	 {2242137778609839,8.23347194760605e-16},{2242119650443327,8.26901927108847e-16},
	 {2242100214207556,8.304792058805374e-16},{2242079441234906,8.340796881136629e-16},
	 {2242057301132135,8.377040521420222e-16},{2242033761687079,8.413529986798028e-16},
	 {2242008788768107,8.450272519724097e-16},{2241982346215682,8.487275610186155e-16},
	 {2241954395725356,8.524547008695596e-16},{2241924896721443,8.562094740106233e-16},
	 {2241893806220517,8.599927118327665e-16},{2241861078683830,8.638052762005259e-16},
	 {2241826665857598,8.676480611245582e-16},{2241790516600041,8.715219945473698e-16},
	 {2241752576693881,8.754280402517175e-16},{2241712788642916,8.793671999021043e-16},
	 {2241671091451078,8.833405152308408e-16},{2241627420382235,8.873490703813135e-16},
	 {2241581706698773,8.913939944224086e-16},{2241533877376767,8.954764640495068e-16},
	 {2241483854795281,8.9959770648911e-16},{2241431556397035,9.037590026260118e-16},
	 {2241376894317345,9.079616903740068e-16},{2241319774977817,9.122071683134846e-16},
	 {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},
	 {2240297220544165,9.720681022901626e-16},{2240191264522612,9.771053062707209e-16},
	 {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,
	     9.0872644005213032e-01,8.9809592189834297e-01,8.8798466075583282e-01,
	     8.7830965580891684e-01,8.6900868803685649e-01,8.6003362119633109e-01,
	     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,
	     6.5561147057969693e-01,6.5029874311081637e-01,6.4503548082082196e-01,
	     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,
	     5.9484624376798689e-01,5.9004799633282545e-01,5.8528617926337090e-01,
	     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,
	     4.8841328470545758e-01,4.8432026942668288e-01,4.8025086590904642e-01,
	     4.7620473271950547e-01,4.7218153846772976e-01,4.6818096140569321e-01,
	     4.6420268904817391e-01,4.6024641781284248e-01,4.5631185267871610e-01,
	     4.5239870686184824e-01,4.4850670150720273e-01,4.4463556539573912e-01,
	     4.4078503466580377e-01,4.3695485254798533e-01,4.3314476911265209e-01,
	     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,
	     3.5397498080007656e-01,3.5057094148140588e-01,3.4718256395679348e-01,
	     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,
	     3.0450139197664983e-01,3.0131939610080288e-01,2.9815132669668531e-01,
	     2.9499708779996164e-01,2.9185658561709499e-01,2.8872972848218270e-01,
	     2.8561642681550159e-01,2.8251659308370741e-01,2.7943014176163772e-01,
	     2.7635698929566810e-01,2.7329705406857691e-01,2.7025025636587519e-01,
	     2.6721651834356114e-01,2.6419576399726080e-01,2.6118791913272082e-01,
	     2.5819291133761890e-01,2.5521066995466168e-01,2.5224112605594190e-01,
	     2.4928421241852824e-01,2.4633986350126363e-01,2.4340801542275012e-01,
	     2.4048860594050039e-01,2.3758157443123795e-01,2.3468686187232990e-01,
	     2.3180441082433859e-01,2.2893416541468023e-01,2.2607607132238020e-01,
	     2.2323007576391746e-01,2.2039612748015194e-01,2.1757417672433113e-01,
	     2.1476417525117358e-01,2.1196607630703015e-01,2.0917983462112499e-01,
	     2.0640540639788071e-01,2.0364274931033485e-01,2.0089182249465656e-01,
	     1.9815258654577511e-01,1.9542500351413428e-01,1.9270903690358912e-01,
	     1.9000465167046496e-01,1.8731181422380025e-01,1.8463049242679927e-01,
	     1.8196065559952254e-01,1.7930227452284767e-01,1.7665532144373500e-01,
	     1.7401977008183875e-01,1.7139559563750595e-01,1.6878277480121151e-01,
	     1.6618128576448205e-01,1.6359110823236570e-01,1.6101222343751107e-01,
	     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,
	     1.2850872227999952e-01,1.2608687022018586e-01,1.2367622820159654e-01,
	     1.2127680548479021e-01,1.1888861344290998e-01,1.1651166562561080e-01,
	     1.1414597782783835e-01,1.1179156816383801e-01,1.0944845714681163e-01,
	     1.0711666777468364e-01,1.0479622562248690e-01,1.0248715894193508e-01,
	     1.0018949876880981e-01,9.7903279038862284e-02,9.5628536713008819e-02,
	     9.3365311912690860e-02,9.1113648066373634e-02,8.8873592068275789e-02,
	     8.6645194450557961e-02,8.4428509570353374e-02,8.2223595813202863e-02,
	     8.0030515814663056e-02,7.7849336702096039e-02,7.5680130358927067e-02,
	     7.3522973713981268e-02,7.1377949058890375e-02,6.9245144397006769e-02,
	     6.7124653827788497e-02,6.5016577971242842e-02,6.2921024437758113e-02,
	     6.0838108349539864e-02,5.8767952920933758e-02,5.6710690106202902e-02,
	     5.4666461324888914e-02,5.2635418276792176e-02,5.0617723860947761e-02,
	     4.8613553215868521e-02,4.6623094901930368e-02,4.4646552251294443e-02,
	     4.2684144916474431e-02,4.0736110655940933e-02,3.8802707404526113e-02,
	     3.6884215688567284e-02,3.4980941461716084e-02,3.3093219458578522e-02,
	     3.1221417191920245e-02,2.9365939758133314e-02,2.7527235669603082e-02,
	     2.5705804008548896e-02,2.3902203305795882e-02,2.2117062707308864e-02,
	     2.0351096230044517e-02,1.8605121275724643e-02,1.6880083152543166e-02,
	     1.5177088307935325e-02,1.3497450601739880e-02,1.1842757857907888e-02,
	     1.0214971439701471e-02,8.6165827693987316e-03,7.0508754713732268e-03,
	     5.5224032992509968e-03,4.0379725933630305e-03,2.6090727461021627e-03,
	     1.2602859304985975e-03}).