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-rw-r--r--lib/stdlib/test/rand_SUITE.erl667
1 files changed, 536 insertions, 131 deletions
diff --git a/lib/stdlib/test/rand_SUITE.erl b/lib/stdlib/test/rand_SUITE.erl
index 098eefeb61..2ccd89a59f 100644
--- a/lib/stdlib/test/rand_SUITE.erl
+++ b/lib/stdlib/test/rand_SUITE.erl
@@ -1,7 +1,7 @@
%%
%% %CopyrightBegin%
%%
-%% Copyright Ericsson AB 2000-2016. All Rights Reserved.
+%% Copyright Ericsson AB 2000-2017. 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.
@@ -27,6 +27,7 @@
-export([interval_int/1, interval_float/1, seed/1,
api_eq/1, reference/1,
basic_stats_uniform_1/1, basic_stats_uniform_2/1,
+ basic_stats_standard_normal/1,
basic_stats_normal/1,
plugin/1, measure/1,
reference_jump_state/1, reference_jump_procdict/1]).
@@ -52,7 +53,8 @@ all() ->
groups() ->
[{basic_stats, [parallel],
- [basic_stats_uniform_1, basic_stats_uniform_2, basic_stats_normal]},
+ [basic_stats_uniform_1, basic_stats_uniform_2,
+ basic_stats_standard_normal, basic_stats_normal]},
{reference_jump, [parallel],
[reference_jump_state, reference_jump_procdict]}].
@@ -66,18 +68,19 @@ group(reference_jump) ->
%% A simple helper to test without test_server during dev
test() ->
Tests = all(),
- lists:foreach(fun(Test) ->
- try
- ok = ?MODULE:Test([]),
- io:format("~p: ok~n", [Test])
- catch _:Reason ->
- io:format("Failed: ~p: ~p ~p~n",
- [Test, Reason, erlang:get_stacktrace()])
- end
- end, Tests).
+ lists:foreach(
+ fun (Test) ->
+ try
+ ok = ?MODULE:Test([]),
+ io:format("~p: ok~n", [Test])
+ catch _:Reason ->
+ io:format("Failed: ~p: ~p ~p~n",
+ [Test, Reason, erlang:get_stacktrace()])
+ end
+ end, Tests).
algs() ->
- [exs64, exsplus, exs1024].
+ [exs64, exsplus, exsp, exrop, exs1024, exs1024s].
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
@@ -226,10 +229,10 @@ interval_float_1(0) -> ok;
interval_float_1(N) ->
X = rand:uniform(),
if
- 0.0 < X, X < 1.0 ->
+ 0.0 =< X, X < 1.0 ->
ok;
true ->
- io:format("X=~p 0<~p<1.0~n", [X,X]),
+ io:format("X=~p 0=<~p<1.0~n", [X,X]),
exit({X, rand:export_seed()})
end,
interval_float_1(N-1).
@@ -246,6 +249,8 @@ reference_1(Alg) ->
Testval = gen(Alg),
case Refval =:= Testval of
true -> ok;
+ false when Refval =:= not_implemented ->
+ exit({not_implemented,Alg});
false ->
io:format("Failed: ~p~n",[Alg]),
io:format("Length ~p ~p~n",[length(Refval), length(Testval)]),
@@ -254,25 +259,29 @@ reference_1(Alg) ->
end.
gen(Algo) ->
- Seed = case Algo of
- exsplus -> %% Printed with orig 'C' code and this seed
- rand:seed_s({exsplus, [12345678|12345678]});
- exs64 -> %% Printed with orig 'C' code and this seed
- rand:seed_s({exs64, 12345678});
- exs1024 -> %% Printed with orig 'C' code and this seed
- rand:seed_s({exs1024, {lists:duplicate(16, 12345678), []}});
- _ ->
- rand:seed(Algo, {100, 200, 300})
- end,
- gen(?LOOP, Seed, []).
-
-gen(N, State0 = {#{max:=Max}, _}, Acc) when N > 0 ->
+ State =
+ case Algo of
+ exs64 -> %% Printed with orig 'C' code and this seed
+ rand:seed_s({exs64, 12345678});
+ _ when Algo =:= exsplus; Algo =:= exsp; Algo =:= exrop ->
+ %% Printed with orig 'C' code and this seed
+ rand:seed_s({Algo, [12345678|12345678]});
+ _ when Algo =:= exs1024; Algo =:= exs1024s ->
+ %% Printed with orig 'C' code and this seed
+ rand:seed_s({Algo, {lists:duplicate(16, 12345678), []}});
+ _ ->
+ rand:seed(Algo, {100, 200, 300})
+ end,
+ Max = range(State),
+ gen(?LOOP, State, Max, []).
+
+gen(N, State0, Max, Acc) when N > 0 ->
{Random, State} = rand:uniform_s(Max, State0),
case N rem (?LOOP div 100) of
- 0 -> gen(N-1, State, [Random|Acc]);
- _ -> gen(N-1, State, Acc)
+ 0 -> gen(N-1, State, Max, [Random|Acc]);
+ _ -> gen(N-1, State, Max, Acc)
end;
-gen(_, _, Acc) -> lists:reverse(Acc).
+gen(_, _, _, Acc) -> lists:reverse(Acc).
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%% This just tests the basics so we have not made any serious errors
@@ -294,12 +303,36 @@ basic_stats_uniform_2(Config) when is_list(Config) ->
|| Alg <- algs()],
ok.
-basic_stats_normal(Config) when is_list(Config) ->
+basic_stats_standard_normal(Config) when is_list(Config) ->
ct:timetrap({minutes,6}), %% valgrind needs a lot of time
- io:format("Testing normal~n",[]),
- [basic_normal_1(?LOOP, rand:seed_s(Alg), 0, 0) || Alg <- algs()],
+ io:format("Testing standard normal~n",[]),
+ IntendedMean = 0,
+ IntendedVariance = 1,
+ [basic_normal_1(?LOOP, IntendedMean, IntendedVariance,
+ rand:seed_s(Alg), 0, 0)
+ || Alg <- algs()],
ok.
+basic_stats_normal(Config) when is_list(Config) ->
+ IntendedMeans = [-1.0e6, -50, -math:pi(), -math:exp(-1),
+ 0.12345678, math:exp(1), 100, 1.0e6],
+ IntendedVariances = [1.0e-6, math:exp(-1), 1, math:pi(), 1.0e6],
+ IntendedMeanVariancePairs =
+ [{Mean, Variance} || Mean <- IntendedMeans,
+ Variance <- IntendedVariances],
+
+ ct:timetrap({minutes, 6 * length(IntendedMeanVariancePairs)}), %% valgrind needs a lot of time
+ lists:foreach(
+ fun ({IntendedMean, IntendedVariance}) ->
+ ct:pal(
+ "Testing normal(~.2f, ~.2f)~n",
+ [float(IntendedMean), float(IntendedVariance)]),
+ [basic_normal_1(?LOOP, IntendedMean, IntendedVariance,
+ rand:seed_s(Alg), 0, 0)
+ || Alg <- algs()]
+ end,
+ IntendedMeanVariancePairs).
+
basic_uniform_1(N, S0, Sum, A0) when N > 0 ->
{X,S} = rand:uniform_s(S0),
I = trunc(X*100),
@@ -307,11 +340,11 @@ basic_uniform_1(N, S0, Sum, A0) when N > 0 ->
basic_uniform_1(N-1, S, Sum+X, A);
basic_uniform_1(0, {#{type:=Alg}, _}, Sum, A) ->
AverN = Sum / ?LOOP,
- io:format("~.10w: Average: ~.4f~n", [Alg, AverN]),
+ io:format("~.12w: Average: ~.4f~n", [Alg, AverN]),
Counters = array:to_list(A),
Min = lists:min(Counters),
Max = lists:max(Counters),
- io:format("~.10w: Min: ~p Max: ~p~n", [Alg, Min, Max]),
+ io:format("~.12w: Min: ~p Max: ~p~n", [Alg, Min, Max]),
%% Verify that the basic statistics are ok
%% be gentle we don't want to see to many failing tests
@@ -326,11 +359,11 @@ basic_uniform_2(N, S0, Sum, A0) when N > 0 ->
basic_uniform_2(N-1, S, Sum+X, A);
basic_uniform_2(0, {#{type:=Alg}, _}, Sum, A) ->
AverN = Sum / ?LOOP,
- io:format("~.10w: Average: ~.4f~n", [Alg, AverN]),
+ io:format("~.12w: Average: ~.4f~n", [Alg, AverN]),
Counters = tl(array:to_list(A)),
Min = lists:min(Counters),
Max = lists:max(Counters),
- io:format("~.10w: Min: ~p Max: ~p~n", [Alg, Min, Max]),
+ io:format("~.12w: Min: ~p Max: ~p~n", [Alg, Min, Max]),
%% Verify that the basic statistics are ok
%% be gentle we don't want to see to many failing tests
@@ -339,19 +372,33 @@ basic_uniform_2(0, {#{type:=Alg}, _}, Sum, A) ->
abs(?LOOP div 100 - Max) < 1000 orelse ct:fail({max, Alg, Max}),
ok.
-basic_normal_1(N, S0, Sum, Sq) when N > 0 ->
- {X,S} = rand:normal_s(S0),
- basic_normal_1(N-1, S, X+Sum, X*X+Sq);
-basic_normal_1(0, {#{type:=Alg}, _}, Sum, SumSq) ->
- Mean = Sum / ?LOOP,
- StdDev = math:sqrt((SumSq - (Sum*Sum/?LOOP))/(?LOOP - 1)),
- io:format("~.10w: Average: ~7.4f StdDev ~6.4f~n", [Alg, Mean, StdDev]),
+basic_normal_1(N, IntendedMean, IntendedVariance, S0, StandardSum, StandardSq) when N > 0 ->
+ {X,S} = normal_s(IntendedMean, IntendedVariance, S0),
+ % We now shape X into a standard normal distribution (in case it wasn't already)
+ % in order to minimise the accumulated error on Sum / SumSq;
+ % otherwise said error would prevent us of making a fair judgment on
+ % the overall distribution when targeting large means and variances.
+ StandardX = (X - IntendedMean) / math:sqrt(IntendedVariance),
+ basic_normal_1(N-1, IntendedMean, IntendedVariance, S,
+ StandardX+StandardSum, StandardX*StandardX+StandardSq);
+basic_normal_1(0, _IntendedMean, _IntendedVariance, {#{type:=Alg}, _}, StandardSum, StandardSumSq) ->
+ StandardMean = StandardSum / ?LOOP,
+ StandardVariance = (StandardSumSq - (StandardSum*StandardSum/?LOOP))/(?LOOP - 1),
+ StandardStdDev = math:sqrt(StandardVariance),
+ io:format("~.12w: Standardised Average: ~7.4f, Standardised StdDev ~6.4f~n",
+ [Alg, StandardMean, StandardStdDev]),
%% Verify that the basic statistics are ok
%% be gentle we don't want to see to many failing tests
- abs(Mean) < 0.005 orelse ct:fail({average, Alg, Mean}),
- abs(StdDev - 1.0) < 0.005 orelse ct:fail({stddev, Alg, StdDev}),
+ abs(StandardMean) < 0.005 orelse ct:fail({average, Alg, StandardMean}),
+ abs(StandardStdDev - 1.0) < 0.005 orelse ct:fail({stddev, Alg, StandardStdDev}),
ok.
+normal_s(Mean, Variance, State0) when Mean == 0, Variance == 1 ->
+ % Make sure we're also testing the standard normal interface
+ rand:normal_s(State0);
+normal_s(Mean, Variance, State0) ->
+ rand:normal_s(Mean, Variance, State0).
+
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%% Test that the user can write algorithms.
@@ -365,7 +412,7 @@ plugin(Config) when is_list(Config) ->
{V2, S2} = rand:uniform_s(S1),
true = is_float(V2),
S2
- end, crypto_seed(), lists:seq(1, 200)),
+ end, crypto64_seed(), lists:seq(1, 200)),
ok
catch
error:low_entropy ->
@@ -375,86 +422,279 @@ plugin(Config) when is_list(Config) ->
end.
%% Test implementation
-crypto_seed() ->
- {#{type=>crypto,
- max=>(1 bsl 64)-1,
- next=>fun crypto_next/1,
- uniform=>fun crypto_uniform/1,
- uniform_n=>fun crypto_uniform_n/2},
+crypto64_seed() ->
+ {#{type=>crypto64,
+ bits=>64,
+ next=>fun crypto64_next/1,
+ uniform=>fun crypto64_uniform/1,
+ uniform_n=>fun crypto64_uniform_n/2},
<<>>}.
%% Be fair and create bignums i.e. 64bits otherwise use 58bits
-crypto_next(<<Num:64, Bin/binary>>) ->
+crypto64_next(<<Num:64, Bin/binary>>) ->
{Num, Bin};
-crypto_next(_) ->
- crypto_next(crypto:strong_rand_bytes((64 div 8)*100)).
+crypto64_next(_) ->
+ crypto64_next(crypto:strong_rand_bytes((64 div 8)*100)).
-crypto_uniform({Api, Data0}) ->
- {Int, Data} = crypto_next(Data0),
+crypto64_uniform({Api, Data0}) ->
+ {Int, Data} = crypto64_next(Data0),
{Int / (1 bsl 64), {Api, Data}}.
-crypto_uniform_n(N, {Api, Data0}) when N < (1 bsl 64) ->
- {Int, Data} = crypto_next(Data0),
+crypto64_uniform_n(N, {Api, Data0}) when N < (1 bsl 64) ->
+ {Int, Data} = crypto64_next(Data0),
{(Int rem N)+1, {Api, Data}};
-crypto_uniform_n(N, State0) ->
- {F,State} = crypto_uniform(State0),
+crypto64_uniform_n(N, State0) ->
+ {F,State} = crypto64_uniform(State0),
{trunc(F * N) + 1, State}.
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%% Not a test but measures the time characteristics of the different algorithms
-measure(Suite) when is_atom(Suite) -> [];
-measure(_Config) ->
- ct:timetrap({minutes,15}), %% valgrind needs a lot of time
+measure(Config) ->
+ ct:timetrap({minutes,30}), %% valgrind needs a lot of time
+ case ct:get_timetrap_info() of
+ {_,{_,1}} -> % No scaling
+ do_measure(Config);
+ {_,{_,Scale}} ->
+ {skip,{will_not_run_in_scaled_time,Scale}}
+ end.
+
+do_measure(_Config) ->
Algos =
try crypto:strong_rand_bytes(1) of
- <<_>> -> [crypto64]
+ <<_>> -> [crypto64, crypto]
catch
error:low_entropy -> [];
error:undef -> []
end ++ algs(),
- io:format("RNG uniform integer performance~n",[]),
- _ = measure_1(random, fun(State) -> {int, random:uniform_s(10000, State)} end),
- _ = [measure_1(Algo, fun(State) -> {int, rand:uniform_s(10000, State)} end) || Algo <- Algos],
- io:format("RNG uniform float performance~n",[]),
- _ = measure_1(random, fun(State) -> {uniform, random:uniform_s(State)} end),
- _ = [measure_1(Algo, fun(State) -> {uniform, rand:uniform_s(State)} end) || Algo <- Algos],
- io:format("RNG normal float performance~n",[]),
- io:format("~.10w: not implemented (too few bits)~n", [random]),
- _ = [measure_1(Algo, fun(State) -> {normal, rand:normal_s(State)} end) || Algo <- Algos],
+ %%
+ ct:pal("RNG uniform integer performance~n",[]),
+ TMark1 =
+ measure_1(
+ random,
+ fun (_) -> 10000 end,
+ undefined,
+ fun (Range, State) ->
+ {int, random:uniform_s(Range, State)}
+ end),
+ _ =
+ [measure_1(
+ Algo,
+ fun (_) -> 10000 end,
+ TMark1,
+ fun (Range, State) ->
+ {int, rand:uniform_s(Range, State)}
+ end) || Algo <- Algos],
+ %%
+ ct:pal("~nRNG uniform integer half range performance~n",[]),
+ HalfRangeFun = fun (State) -> half_range(State) end,
+ TMark2 =
+ measure_1(
+ random,
+ HalfRangeFun,
+ undefined,
+ fun (Range, State) ->
+ {int, random:uniform_s(Range, State)}
+ end),
+ _ =
+ [measure_1(
+ Algo,
+ HalfRangeFun,
+ TMark2,
+ fun (Range, State) ->
+ {int, rand:uniform_s(Range, State)}
+ end) || Algo <- Algos],
+ %%
+ ct:pal("~nRNG uniform integer half range + 1 performance~n",[]),
+ HalfRangePlus1Fun = fun (State) -> half_range(State) + 1 end,
+ TMark3 =
+ measure_1(
+ random,
+ HalfRangePlus1Fun,
+ undefined,
+ fun (Range, State) ->
+ {int, random:uniform_s(Range, State)}
+ end),
+ _ =
+ [measure_1(
+ Algo,
+ HalfRangePlus1Fun,
+ TMark3,
+ fun (Range, State) ->
+ {int, rand:uniform_s(Range, State)}
+ end) || Algo <- Algos],
+ %%
+ ct:pal("~nRNG uniform integer full range - 1 performance~n",[]),
+ FullRangeMinus1Fun = fun (State) -> (half_range(State) bsl 1) - 1 end,
+ TMark4 =
+ measure_1(
+ random,
+ FullRangeMinus1Fun,
+ undefined,
+ fun (Range, State) ->
+ {int, random:uniform_s(Range, State)}
+ end),
+ _ =
+ [measure_1(
+ Algo,
+ FullRangeMinus1Fun,
+ TMark4,
+ fun (Range, State) ->
+ {int, rand:uniform_s(Range, State)}
+ end) || Algo <- Algos],
+ %%
+ ct:pal("~nRNG uniform integer full range performance~n",[]),
+ FullRangeFun = fun (State) -> half_range(State) bsl 1 end,
+ TMark5 =
+ measure_1(
+ random,
+ FullRangeFun,
+ undefined,
+ fun (Range, State) ->
+ {int, random:uniform_s(Range, State)}
+ end),
+ _ =
+ [measure_1(
+ Algo,
+ FullRangeFun,
+ TMark5,
+ fun (Range, State) ->
+ {int, rand:uniform_s(Range, State)}
+ end) || Algo <- Algos],
+ %%
+ ct:pal("~nRNG uniform integer full range + 1 performance~n",[]),
+ FullRangePlus1Fun = fun (State) -> (half_range(State) bsl 1) + 1 end,
+ TMark6 =
+ measure_1(
+ random,
+ FullRangePlus1Fun,
+ undefined,
+ fun (Range, State) ->
+ {int, random:uniform_s(Range, State)}
+ end),
+ _ =
+ [measure_1(
+ Algo,
+ FullRangePlus1Fun,
+ TMark6,
+ fun (Range, State) ->
+ {int, rand:uniform_s(Range, State)}
+ end) || Algo <- Algos],
+ %%
+ ct:pal("~nRNG uniform integer double range performance~n",[]),
+ DoubleRangeFun = fun (State) -> half_range(State) bsl 2 end,
+ TMark7 =
+ measure_1(
+ random,
+ DoubleRangeFun,
+ undefined,
+ fun (Range, State) ->
+ {int, random:uniform_s(Range, State)}
+ end),
+ _ =
+ [measure_1(
+ Algo,
+ DoubleRangeFun,
+ TMark7,
+ fun (Range, State) ->
+ {int, rand:uniform_s(Range, State)}
+ end) || Algo <- Algos],
+ %%
+ ct:pal("~nRNG uniform integer double range + 1 performance~n",[]),
+ DoubleRangePlus1Fun = fun (State) -> (half_range(State) bsl 2) + 1 end,
+ TMark8 =
+ measure_1(
+ random,
+ DoubleRangePlus1Fun,
+ undefined,
+ fun (Range, State) ->
+ {int, random:uniform_s(Range, State)}
+ end),
+ _ =
+ [measure_1(
+ Algo,
+ DoubleRangePlus1Fun,
+ TMark8,
+ fun (Range, State) ->
+ {int, rand:uniform_s(Range, State)}
+ end) || Algo <- Algos],
+ %%
+ ct:pal("~nRNG uniform float performance~n",[]),
+ TMark9 =
+ measure_1(
+ random,
+ fun (_) -> 0 end,
+ undefined,
+ fun (_, State) ->
+ {uniform, random:uniform_s(State)}
+ end),
+ _ =
+ [measure_1(
+ Algo,
+ fun (_) -> 0 end,
+ TMark9,
+ fun (_, State) ->
+ {uniform, rand:uniform_s(State)}
+ end) || Algo <- Algos],
+ %%
+ ct:pal("~nRNG normal float performance~n",[]),
+ io:format("~.12w: not implemented (too few bits)~n", [random]),
+ _ = [measure_1(
+ Algo,
+ fun (_) -> 0 end,
+ TMark9,
+ fun (_, State) ->
+ {normal, rand:normal_s(State)}
+ end) || Algo <- Algos],
ok.
-measure_1(Algo, Gen) ->
+measure_1(Algo, RangeFun, TMark, Gen) ->
Parent = self(),
- Seed = fun(crypto64) -> crypto_seed();
- (random) -> random:seed(os:timestamp()), get(random_seed);
- (Alg) -> rand:seed_s(Alg)
- end,
-
- Pid = spawn_link(fun() ->
- Fun = fun() -> measure_2(?LOOP, Seed(Algo), Gen) end,
- {Time, ok} = timer:tc(Fun),
- io:format("~.10w: ~pµs~n", [Algo, Time]),
- Parent ! {self(), ok},
- normal
- end),
+ Seed =
+ case Algo of
+ crypto64 ->
+ crypto64_seed();
+ crypto ->
+ crypto:rand_seed_s();
+ random ->
+ random:seed(os:timestamp()), get(random_seed);
+ _ ->
+ rand:seed_s(Algo)
+ end,
+ Range = RangeFun(Seed),
+ Pid = spawn_link(
+ fun() ->
+ Fun = fun() -> measure_2(?LOOP, Range, Seed, Gen) end,
+ {Time, ok} = timer:tc(Fun),
+ Percent =
+ case TMark of
+ undefined -> 100;
+ _ -> (Time * 100 + 50) div TMark
+ end,
+ io:format(
+ "~.12w: ~p ns ~p% [16#~.16b]~n",
+ [Algo, (Time * 1000 + 500) div ?LOOP, Percent, Range]),
+ Parent ! {self(), Time},
+ normal
+ end),
receive
{Pid, Msg} -> Msg
end.
-measure_2(N, State0, Fun) when N > 0 ->
- case Fun(State0) of
+measure_2(N, Range, State0, Fun) when N > 0 ->
+ case Fun(Range, State0) of
{int, {Random, State}}
- when is_integer(Random), Random >= 1, Random =< 100000 ->
- measure_2(N-1, State, Fun);
- {uniform, {Random, State}} when is_float(Random), Random > 0, Random < 1 ->
- measure_2(N-1, State, Fun);
+ when is_integer(Random), Random >= 1, Random =< Range ->
+ measure_2(N-1, Range, State, Fun);
+ {uniform, {Random, State}}
+ when is_float(Random), 0.0 =< Random, Random < 1.0 ->
+ measure_2(N-1, Range, State, Fun);
{normal, {Random, State}} when is_float(Random) ->
- measure_2(N-1, State, Fun);
+ measure_2(N-1, Range, State, Fun);
Res ->
exit({error, Res, State0})
end;
-measure_2(0, _, _) -> ok.
+measure_2(0, _, _, _) -> ok.
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%% The jump sequence tests has two parts
@@ -479,36 +719,43 @@ reference_jump_1(Alg) ->
io:format("Failed: ~p~n",[Alg]),
io:format("Length ~p ~p~n",[length(Refval), length(Testval)]),
io:format("Head ~p ~p~n",[hd(Refval), hd(Testval)]),
+ io:format("Vals ~p ~p~n",[Refval, Testval]),
exit(wrong_value)
end.
gen_jump_1(Algo) ->
- Seed = case Algo of
- exsplus -> %% Printed with orig 'C' code and this seed
- rand:seed_s({exsplus, [12345678|12345678]});
- exs1024 -> %% Printed with orig 'C' code and this seed
- rand:seed_s({exs1024, {lists:duplicate(16, 12345678), []}});
- exs64 -> %% Test exception of not_implemented notice
- try rand:jump(rand:seed_s(exs64))
- catch
- error:not_implemented -> not_implemented
- end;
- _ -> % unimplemented
- not_implemented
- end,
- case Seed of
+ State =
+ case Algo of
+ exs64 -> %% Test exception of not_implemented notice
+ try rand:jump(rand:seed_s(exs64))
+ catch
+ error:not_implemented -> not_implemented
+ end;
+ _ when Algo =:= exsplus; Algo =:= exsp; Algo =:= exrop ->
+ %% Printed with orig 'C' code and this seed
+ rand:seed_s({Algo, [12345678|12345678]});
+ _ when Algo =:= exs1024; Algo =:= exs1024s ->
+ %% Printed with orig 'C' code and this seed
+ rand:seed_s({Algo, {lists:duplicate(16, 12345678), []}});
+ _ -> % unimplemented
+ not_implemented
+ end,
+ case State of
not_implemented -> [not_implemented];
- S -> gen_jump_1(?LOOP_JUMP, S, [])
+ _ ->
+ Max = range(State),
+ gen_jump_1(?LOOP_JUMP, State, Max, [])
end.
-gen_jump_1(N, State0 = {#{max:=Max}, _}, Acc) when N > 0 ->
+gen_jump_1(N, State0, Max, Acc) when N > 0 ->
{_, State1} = rand:uniform_s(Max, State0),
{Random, State2} = rand:uniform_s(Max, rand:jump(State1)),
case N rem (?LOOP_JUMP div 100) of
- 0 -> gen_jump_1(N-1, State2, [Random|Acc]);
- _ -> gen_jump_1(N-1, State2, Acc)
+ 0 -> gen_jump_1(N-1, State2, Max, [Random|Acc]);
+ _ -> gen_jump_1(N-1, State2, Max, Acc)
end;
-gen_jump_1(_, _, Acc) -> lists:reverse(Acc).
+gen_jump_1(_, _, _, Acc) -> lists:reverse(Acc).
+
%% Check if each algorithm generates the proper jump sequence
%% with the internal state in the process dictionary.
@@ -530,25 +777,26 @@ reference_jump_0(Alg) ->
gen_jump_0(Algo) ->
Seed = case Algo of
- exsplus -> %% Printed with orig 'C' code and this seed
- rand:seed({exsplus, [12345678|12345678]});
- exs1024 -> %% Printed with orig 'C' code and this seed
- rand:seed({exs1024, {lists:duplicate(16, 12345678), []}});
exs64 -> %% Test exception of not_implemented notice
- try
- _ = rand:seed(exs64),
- rand:jump()
- catch
- error:not_implemented -> not_implemented
- end;
+ try
+ _ = rand:seed(exs64),
+ rand:jump()
+ catch
+ error:not_implemented -> not_implemented
+ end;
+ _ when Algo =:= exsplus; Algo =:= exsp; Algo =:= exrop ->
+ %% Printed with orig 'C' code and this seed
+ rand:seed({Algo, [12345678|12345678]});
+ _ when Algo =:= exs1024; Algo =:= exs1024s ->
+ %% Printed with orig 'C' code and this seed
+ rand:seed({Algo, {lists:duplicate(16, 12345678), []}});
_ -> % unimplemented
not_implemented
end,
case Seed of
not_implemented -> [not_implemented];
- S ->
- {Seedmap=#{}, _} = S,
- Max = maps:get(max, Seedmap),
+ _ ->
+ Max = range(Seed),
gen_jump_0(?LOOP_JUMP, Max, [])
end.
@@ -643,9 +891,77 @@ reference_val(exsplus) ->
16#6c6145ffa1169d,16#18ec2c393d45359,16#1f1a5f256e7130c,16#131cc2f49b8004f,
16#36f715a249f4ec2,16#1c27629826c50d3,16#914d9a6648726a,16#27f5bf5ce2301e8,
16#3dd493b8012970f,16#be13bed1e00e5c,16#ceef033b74ae10,16#3da38c6a50abe03,
- 16#15cbd1a421c7a8c,16#22794e3ec6ef3b1,16#26154d26e7ea99f,16#3a66681359a6ab6].
+ 16#15cbd1a421c7a8c,16#22794e3ec6ef3b1,16#26154d26e7ea99f,16#3a66681359a6ab6];
+
+reference_val(exsp) ->
+ reference_val(exsplus);
+reference_val(exs1024s) ->
+ reference_val(exs1024);
+reference_val(exrop) ->
+%% #include <stdint.h>
+%% #include <stdio.h>
+%%
+%% uint64_t s[2];
+%% uint64_t next(void);
+%% /* Xoroshiro116+ PRNG here */
+%%
+%% int main(char *argv[]) {
+%% int n;
+%% uint64_t r;
+%% s[0] = 12345678;
+%% s[1] = 12345678;
+%%
+%% for (n = 1000000; n > 0; n--) {
+%% r = next();
+%% if ((n % 10000) == 0) {
+%% printf("%llu,", (unsigned long long) (r + 1));
+%% }
+%% }
+%% printf("\n");
+%% }
+ [24691357,29089185972758626,135434857127264790,
+ 277209758236304485,101045429972817342,
+ 241950202080388093,283018380268425711,268233672110762489,
+ 173241488791227202,245038518481669421,
+ 253627577363613736,234979870724373477,115607127954560275,
+ 96445882796968228,166106849348423677,
+ 83614184550774836,109634510785746957,68415533259662436,
+ 12078288820568786,246413981014863011,
+ 96953486962147513,138629231038332640,206078430370986460,
+ 11002780552565714,238837272913629203,
+ 60272901610411077,148828243883348685,203140738399788939,
+ 131001610760610046,30717739120305678,
+ 262903815608472425,31891125663924935,107252017522511256,
+ 241577109487224033,263801934853180827,
+ 155517416581881714,223609336630639997,112175917931581716,
+ 16523497284706825,201453767973653420,
+ 35912153101632769,211525452750005043,96678037860996922,
+ 70962216125870068,107383886372877124,
+ 223441708670831233,247351119445661499,233235283318278995,
+ 280646255087307741,232948506631162445,
+ %%
+ 117394974124526779,55395923845250321,274512622756597759,
+ 31754154862553492,222645458401498438,
+ 161643932692872858,11771755227312868,93933211280589745,
+ 92242631276348831,197206910466548143,
+ 150370169849735808,229903773212075765,264650708561842793,
+ 30318996509793571,158249985447105184,
+ 220423733894955738,62892844479829080,112941952955911674,
+ 203157000073363030,54175707830615686,
+ 50121351829191185,115891831802446962,62298417197154985,
+ 6569598473421167,69822368618978464,
+ 176271134892968134,160793729023716344,271997399244980560,
+ 59100661824817999,150500611720118722,
+ 23707133151561128,25156834940231911,257788052162304719,
+ 176517852966055005,247173855600850875,
+ 83440973524473396,94711136045581604,154881198769946042,
+ 236537934330658377,152283781345006019,
+ 250789092615679985,78848633178610658,72059442721196128,
+ 98223942961505519,191144652663779840,
+ 102425686803727694,89058927716079076,80721467542933080,
+ 8462479817391645,2774921106204163].
-%%%
+%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
reference_jump_val(exsplus) ->
[82445318862816932, 145810727464480743, 16514517716894509, 247642377064868650,
@@ -701,4 +1017,93 @@ reference_jump_val(exs1024) ->
17936751184378118743, 4224632875737239207, 15888641556987476199, 9586888813112229805,
9476861567287505094, 14909536929239540332, 17996844556292992842, 2699310519182298856];
-reference_jump_val(exs64) -> [not_implemented].
+reference_jump_val(exsp) ->
+ reference_jump_val(exsplus);
+reference_jump_val(exs1024s) ->
+ reference_jump_val(exs1024);
+reference_jump_val(exs64) -> [not_implemented];
+reference_jump_val(exrop) ->
+%% #include <stdint.h>
+%% #include <stdio.h>
+%%
+%% uint64_t s[2];
+%% uint64_t next(void);
+%% /* Xoroshiro116+ PRNG here */
+%%
+%% int main(char *argv[]) {
+%% int n;
+%% uint64_t r;
+%% s[0] = 12345678;
+%% s[1] = 12345678;
+
+%% for (n = 1000; n > 0; n--) {
+%% next();
+%% jump();
+%% r = next();
+%% if ((n % 10) == 0) {
+%% printf("%llu,", (unsigned long long) (r + 1));
+%% }
+%% }
+%% printf("\n");
+%% }
+ [60301713907476001,135397949584721850,4148159712710727,
+ 110297784509908316,18753463199438866,
+ 106699913259182846,2414728156662676,237591345910610406,
+ 48519427605486503,38071665570452612,
+ 235484041375354592,45428997361037927,112352324717959775,
+ 226084403445232507,270797890380258829,
+ 160587966336947922,80453153271416820,222758573634013699,
+ 195715386237881435,240975253876429810,
+ 93387593470886224,23845439014202236,235376123357642262,
+ 22286175195310374,239068556844083490,
+ 120126027410954482,250690865061862527,113265144383673111,
+ 57986825640269127,206087920253971490,
+ 265971029949338955,40654558754415167,185972161822891882,
+ 72224917962819036,116613804322063968,
+ 129103518989198416,236110607653724474,98446977363728314,
+ 122264213760984600,55635665885245081,
+ 42625530794327559,288031254029912894,81654312180555835,
+ 261800844953573559,144734008151358432,
+ 77095621402920587,286730580569820386,274596992060316466,
+ 97977034409404188,5517946553518132,
+ %%
+ 56460292644964432,252118572460428657,38694442746260303,
+ 165653145330192194,136968555571402812,
+ 64905200201714082,257386366768713186,22702362175273017,
+ 208480936480037395,152926769756967697,
+ 256751159334239189,130982960476845557,21613531985982870,
+ 87016962652282927,130446710536726404,
+ 188769410109327420,282891129440391928,251807515151187951,
+ 262029034126352975,30694713572208714,
+ 46430187445005589,176983177204884508,144190360369444480,
+ 14245137612606100,126045457407279122,
+ 169277107135012393,42599413368851184,130940158341360014,
+ 113412693367677211,119353175256553456,
+ 96339829771832349,17378172025472134,110141940813943768,
+ 253735613682893347,234964721082540068,
+ 85668779779185140,164542570671430062,18205512302089755,
+ 282380693509970845,190996054681051049,
+ 250227633882474729,171181147785250210,55437891969696407,
+ 241227318715885854,77323084015890802,
+ 1663590009695191,234064400749487599,222983191707424780,
+ 254956809144783896,203898972156838252].
+
+%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
+
+%% The old algorithms used a range 2^N - 1 for their reference val
+%% tests, which was incorrect but works as long as you do not draw
+%% the value 2^N, which is very unlikely. It was not possible
+%% to simply correct the range to 2^N due to another incorrectness
+%% in that the old algorithms changed to using the broken
+%% (multiply a float approach with too few bits) approach for
+%% ranges >= 2^N. This function digs out the range to use
+%% for the reference tests for old and new algorithms.
+range({#{bits:=Bits}, _}) -> 1 bsl Bits;
+range({#{max:=Max}, _}) -> Max; %% Old incorrect range
+range({_, _, _}) -> 51. % random
+
+
+half_range({#{bits:=Bits}, _}) -> 1 bsl (Bits - 1);
+half_range({#{max:=Max}, _}) -> (Max bsr 1) + 1;
+half_range({#{}, _}) -> 1 bsl 63; % crypto
+half_range({_, _, _}) -> 1 bsl 50. % random
generated by cgit v1.2.3 (git 2.25.1) at 2024-12-12 08:21:59 +0000