%%
%% %CopyrightBegin%
%%
%% Copyright Ericsson AB 2000-2016. 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%
-module(rand_SUITE).
-export([all/0, suite/0,groups/0]).
-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_normal/1,
plugin/1, measure/1]).
-export([test/0, gen/1]).
-include_lib("common_test/include/ct.hrl").
-define(LOOP, 1000000).
suite() ->
[{ct_hooks,[ts_install_cth]},
{timetrap,{minutes,3}}].
all() ->
[seed, interval_int, interval_float,
api_eq,
reference,
{group, basic_stats},
plugin, measure].
groups() ->
[{basic_stats, [parallel],
[basic_stats_uniform_1, basic_stats_uniform_2, basic_stats_normal]}].
%% 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).
algs() ->
[exs64, exsplus, exs1024].
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%% Test that seed and seed_s and export_seed/0 is working.
seed(Config) when is_list(Config) ->
Algs = algs(),
Test = fun(Alg) ->
try seed_1(Alg)
catch _:Reason ->
ct:fail({Alg, Reason, erlang:get_stacktrace()})
end
end,
[Test(Alg) || Alg <- Algs],
ok.
seed_1(Alg) ->
%% Check that uniform seeds automatically,
_ = rand:uniform(),
S00 = get(rand_seed),
erase(),
_ = rand:uniform(),
false = S00 =:= get(rand_seed), %% hopefully
%% Choosing algo and seed
S0 = rand:seed(Alg, {0, 0, 0}),
%% Check that (documented?) process_dict variable is correct
S0 = get(rand_seed),
S0 = rand:seed_s(Alg, {0, 0, 0}),
%% Check that process_dict should not be used for seed_s functionality
_ = rand:seed_s(Alg, {1, 0, 0}),
S0 = get(rand_seed),
%% Test export
ES0 = rand:export_seed(),
ES0 = rand:export_seed_s(S0),
S0 = rand:seed(ES0),
S0 = rand:seed_s(ES0),
%% seed/1 calls should be unique
S1 = rand:seed(Alg),
false = (S1 =:= rand:seed_s(Alg)),
%% Negative integers works
_ = rand:seed_s(Alg, {-1,-1,-1}),
%% Check that export_seed/1 returns 'undefined' if there is no seed
erase(rand_seed),
undefined = rand:export_seed(),
%% Other term do not work
{'EXIT', _} = (catch rand:seed_s(foobar, os:timestamp())),
{'EXIT', _} = (catch rand:seed_s(Alg, {asd, 1, 1})),
{'EXIT', _} = (catch rand:seed_s(Alg, {0, 234.1234, 1})),
{'EXIT', _} = (catch rand:seed_s(Alg, {0, 234, [1, 123, 123]})),
ok.
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%% Check that both APIs are consistent with each other.
api_eq(_Config) ->
Algs = algs(),
Small = fun(Alg) ->
Seed = rand:seed(Alg),
io:format("Seed ~p~n",[rand:export_seed_s(Seed)]),
api_eq_1(Seed)
end,
_ = [Small(Alg) || Alg <- Algs],
ok.
api_eq_1(S00) ->
Check = fun(_, Seed) ->
{V0, S0} = rand:uniform_s(Seed),
V0 = rand:uniform(),
{V1, S1} = rand:uniform_s(1000000, S0),
V1 = rand:uniform(1000000),
{V2, S2} = rand:normal_s(S1),
V2 = rand:normal(),
S2
end,
S1 = lists:foldl(Check, S00, lists:seq(1, 200)),
S1 = get(rand_seed),
{V0, S2} = rand:uniform_s(S1),
V0 = rand:uniform(),
S2 = get(rand_seed),
Exported = rand:export_seed(),
Exported = rand:export_seed_s(S2),
S3 = lists:foldl(Check, S2, lists:seq(1, 200)),
S3 = get(rand_seed),
S4 = lists:foldl(Check, S3, lists:seq(1, 200)),
S4 = get(rand_seed),
%% Verify that we do not have loops
false = S1 =:= S2,
false = S2 =:= S3,
false = S3 =:= S4,
S2 = rand:seed(Exported),
S3 = lists:foldl(Check, S2, lists:seq(1, 200)),
ok.
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%% Check that uniform/1 returns values within the proper interval.
interval_int(Config) when is_list(Config) ->
Algs = algs(),
Small = fun(Alg) ->
Seed = rand:seed(Alg),
io:format("Seed ~p~n",[rand:export_seed_s(Seed)]),
Max = interval_int_1(100000, 7, 0),
Max =:= 7 orelse exit({7, Alg, Max})
end,
_ = [Small(Alg) || Alg <- Algs],
%% Test large integers
Large = fun(Alg) ->
Seed = rand:seed(Alg),
io:format("Seed ~p~n",[rand:export_seed_s(Seed)]),
Max = interval_int_1(100000, 1 bsl 128, 0),
Max > 1 bsl 64 orelse exit({large, Alg, Max})
end,
[Large(Alg) || Alg <- Algs],
ok.
interval_int_1(0, _, Max) -> Max;
interval_int_1(N, Top, Max) ->
X = rand:uniform(Top),
if
0 < X, X =< Top ->
ok;
true ->
io:format("X=~p Top=~p 0<~p<~p~n", [X,Top,X,Top]),
exit({X, rand:export_seed()})
end,
interval_int_1(N-1, Top, max(X, Max)).
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%% Check that uniform/0 returns values within the proper interval.
interval_float(Config) when is_list(Config) ->
Algs = algs(),
Test = fun(Alg) ->
_ = rand:seed(Alg),
interval_float_1(100000)
end,
[Test(Alg) || Alg <- Algs],
ok.
interval_float_1(0) -> ok;
interval_float_1(N) ->
X = rand:uniform(),
if
0.0 < X, X < 1.0 ->
ok;
true ->
io:format("X=~p 0<~p<1.0~n", [X,X]),
exit({X, rand:export_seed()})
end,
interval_float_1(N-1).
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%% Check if exs64 algorithm generates the proper sequence.
reference(Config) when is_list(Config) ->
[reference_1(Alg) || Alg <- algs()],
ok.
reference_1(Alg) ->
Refval = reference_val(Alg),
Testval = gen(Alg),
case Refval =:= Testval of
true -> ok;
false ->
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)]),
ok
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 ->
{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)
end;
gen(_, _, Acc) -> lists:reverse(Acc).
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%% This just tests the basics so we have not made any serious errors
%% when making the conversion from the original algorithms.
%% The algorithms must have good properties to begin with
%%
%% Check that the algorithms generate sound values.
basic_stats_uniform_1(Config) when is_list(Config) ->
ct:timetrap({minutes,6}), %% valgrind needs a lot of time
[basic_uniform_1(?LOOP, rand:seed_s(Alg), 0.0, array:new([{default, 0}]))
|| Alg <- algs()],
ok.
basic_stats_uniform_2(Config) when is_list(Config) ->
ct:timetrap({minutes,6}), %% valgrind needs a lot of time
[basic_uniform_2(?LOOP, rand:seed_s(Alg), 0, array:new([{default, 0}]))
|| Alg <- algs()],
ok.
basic_stats_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()],
ok.
basic_uniform_1(N, S0, Sum, A0) when N > 0 ->
{X,S} = rand:uniform_s(S0),
I = trunc(X*100),
A = array:set(I, 1+array:get(I,A0), A0),
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]),
Counters = array:to_list(A),
Min = lists:min(Counters),
Max = lists:max(Counters),
io:format("~.10w: 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
abs(0.5 - AverN) < 0.005 orelse ct:fail({average, Alg, AverN}),
abs(?LOOP div 100 - Min) < 1000 orelse ct:fail({min, Alg, Min}),
abs(?LOOP div 100 - Max) < 1000 orelse ct:fail({max, Alg, Max}),
ok.
basic_uniform_2(N, S0, Sum, A0) when N > 0 ->
{X,S} = rand:uniform_s(100, S0),
A = array:set(X-1, 1+array:get(X-1,A0), A0),
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]),
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]),
%% Verify that the basic statistics are ok
%% be gentle we don't want to see to many failing tests
abs(50.5 - AverN) < 0.5 orelse ct:fail({average, Alg, AverN}),
abs(?LOOP div 100 - Min) < 1000 orelse ct:fail({min, Alg, Min}),
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]),
%% 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}),
ok.
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%% Test that the user can write algorithms.
plugin(Config) when is_list(Config) ->
_ = lists:foldl(fun(_, S0) ->
{V1, S1} = rand:uniform_s(10000, S0),
true = is_integer(V1),
{V2, S2} = rand:uniform_s(S1),
true = is_float(V2),
S2
end, crypto_seed(), lists:seq(1, 200)),
ok.
%% 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},
<<>>}.
%% Be fair and create bignums i.e. 64bits otherwise use 58bits
crypto_next(<<Num:64, Bin/binary>>) ->
{Num, Bin};
crypto_next(_) ->
crypto_next(crypto:strong_rand_bytes((64 div 8)*100)).
crypto_uniform({Api, Data0}) ->
{Int, Data} = crypto_next(Data0),
{Int / (1 bsl 64), {Api, Data}}.
crypto_uniform_n(N, {Api, Data0}) when N < (1 bsl 64) ->
{Int, Data} = crypto_next(Data0),
{(Int rem N)+1, {Api, Data}};
crypto_uniform_n(N, State0) ->
{F,State} = crypto_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,6}), %% valgrind needs a lot of time
Algos = [crypto64|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],
ok.
measure_1(Algo, 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),
receive
{Pid, Msg} -> Msg
end.
measure_2(N, State0, Fun) when N > 0 ->
case Fun(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);
{normal, {Random, State}} when is_float(Random) ->
measure_2(N-1, State, Fun);
Res ->
exit({error, Res, State0})
end;
measure_2(0, _, _) -> ok.
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%%% Data
reference_val(exs64) ->
[16#3737ad0c703ff6c3,16#3868a78fe71adbbd,16#1f01b62b4338b605,16#50876a917437965f,
16#b2edfe32a10e27fc,16#995924551d8ebae1,16#9f1e6b94e94e0b58,16#27ec029eb0e94f8e,
16#bf654e6df7fe5c,16#b7d5ef7b79be65e3,16#4bdba4d1c159126b,16#a9c816fdc701292c,
16#a377b6c89d85ac8b,16#7abb5cd0e5847a6,16#62666f1fc00a0a90,16#1edc3c3d255a8113,
16#dfc764073767f18e,16#381783d577ca4e34,16#49693588c085ddcb,16#da6fcb16dd5163f3,
16#e2357a703475b1b7,16#aaa84c4924b5985a,16#b8fe07bb2bac1e49,16#23973ac0160ff064,
16#1afbc7b023f5d618,16#9f510f7b7caa2a0f,16#d5b0a57f7f5f1084,16#d8c49b66c5f99a29,
16#e920ac3b598b5213,16#1090d7e27e7a7c76,16#81171917168ee74f,16#f08489a3eb6988e,
16#396260c4f0b2ed46,16#4fd0a6a6caefd5b2,16#423dff07a3b888a,16#12718773ebd99987,
16#e50991e540807cb,16#8cfa03bbaa6679d6,16#55bdf86dfbb92dbf,16#eb7145378cce74a8,
16#71856c224c846595,16#20461588dae6e24d,16#c73b3e63ced74bac,16#775b11813dda0c78,
16#91f358e51068ede0,16#399955ef36766bc2,16#4489ee072e8a38b1,16#ba77759d52321ca0,
16#14f519eab5c53db8,16#1f754bd08e4f34c4,16#99e25ca29b2fcfeb,16#da11927c0d9837f8,
16#1eeb0f87009f5a87,16#a7c444d3b0db1089,16#49c7fbf0714849ad,16#4f2b693e7f8265cb,
16#80e1493cbaa8f256,16#186f345bcac2661e,16#330065ae0c698d26,16#5235ed0432c42e93,
16#429792e31ddb10bb,16#8769054bb6533cff,16#1ab382483444201f,16#2216368786fc7b9,
16#1efea1155216da0b,16#782dc868ba595452,16#2b80f6d159617f48,16#407fc35121b2fa1b,
16#90e8be6e618873d1,16#40ad4ec92a8abf8e,16#34e2890f583f435,16#838c0aef0a5d8427,
16#ed4238f4bd6cbcfa,16#7feed11f7a8bb9f0,16#2b0636a93e26c89d,16#481ad4bea5180646,
16#673e5ad861afe1cc,16#298eeb519d69e74d,16#eb1dd06d168c856,16#4770651519ee7ef9,
16#7456ebf1bcf608f1,16#d6200f6fbd61ce05,16#c0695dfab11ab6aa,16#5bff449249983843,
16#7aba88471474c9ac,16#d7e9e4a21c989e91,16#c5e02ee67ccb7ce1,16#4ea8a3a912246153,
16#f2e6db7c9ce4ec43,16#39498a95d46d2470,16#c5294fcb8cce8aa9,16#a918fe444719f3dc,
16#98225f754762c0c0,16#f0721204f2cb43f5,16#b98e77b099d1f2d1,16#691d6f75aee3386,
16#860c7b2354ec24fd,16#33e007bd0fbcb609,16#7170ae9c20fb3d0,16#31d46938fe383a60];
reference_val(exs1024) ->
[16#9c61311d0d4a01fd,16#ce963ef5803b703e,16#545dcffb7b644e1a,16#edd56576a8d778d5,
16#16bee799783c6b45,16#336f0b3caeb417fa,16#29291b8be26dedfa,16#1efed996d2e1b1a8,
16#c5c04757bd2dadf9,16#11aa6d194009c616,16#ab2b3e82bdb38a91,16#5011ee46fd2609eb,
16#766db7e5b701a9bb,16#d42cb2632c419f35,16#107c6a2667bf8557,16#3ffbf922cb306967,
16#1e71e3d024ac5131,16#6fdb368ec67a5f06,16#b0d8e72e7aa6d1c1,16#e5705a02dae89e3b,
16#9c24eb68c086a1d3,16#418de330f55f71f0,16#2917ddeb278bc8d2,16#aeba7fba67208f39,
16#10ceaf40f6af1d8d,16#47a6d06811d33132,16#603a661d6caf720a,16#a28bd0c9bcdacb3c,
16#f44754f006909762,16#6e25e8e67ccc43bc,16#174378ce374a549e,16#b5598ae9f57c4e50,
16#ca85807fbcd51dd,16#1816e58d6c3cc32a,16#1b4d630d3c8e96a6,16#c19b1e92b4efc5bd,
16#665597b20ddd721a,16#fdab4eb21b75c0ae,16#86a612dcfea0756c,16#8fc2da192f9a55f0,
16#d7c954eb1af31b5,16#6f5ee45b1b80101b,16#ebe8ea4e5a67cbf5,16#1cb952026b4c1400,
16#44e62caffe7452c0,16#b591d8f3e6d7cbcf,16#250303f8d77b6f81,16#8ef2199aae4c9b8d,
16#a16baa37a14d7b89,16#c006e4d2b2da158b,16#e6ec7abd54c93b31,16#e6b0d79ae2ab6fa7,
16#93e4b30e4ab7d4cd,16#42a01b6a4ef63033,16#9ab1e94fe94976e,16#426644e1de302a1f,
16#8e58569192200139,16#744f014a090107c1,16#15d056801d467c6c,16#51bdad3a8c30225f,
16#abfc61fb3104bd45,16#c610607122272df7,16#905e67c63116ebfc,16#1e4fd5f443bdc18,
16#1945d1745bc55a4c,16#f7cd2b18989595bb,16#f0d273b2c646a038,16#ee9a6fdc6fd5d734,
16#541a518bdb700518,16#6e67ab9a65361d76,16#bcfadc9bfe5b2e06,16#69fa334cf3c11496,
16#9657df3e0395b631,16#fc0d0442160108ec,16#2ee538da7b1f7209,16#8b20c9fae50a5a9e,
16#a971a4b5c2b3b6a,16#ff6241e32489438e,16#8fd6433f45255777,16#6e6c82f10818b0dc,
16#59a8fad3f6af616b,16#7eac34f43f12221c,16#6e429ec2951723ec,16#9a65179767a45c37,
16#a5f8127d1e6fdf35,16#932c50bc633d8d5c,16#f3bbea4e7ebecb8,16#efc3a2bbf6a8674,
16#451644a99971cb6,16#cf70776d652c150d,16#c1fe0dcb87a25403,16#9523417132b2452e,
16#8f98bc30d06b980e,16#bb4b288ecb8daa9a,16#59e54beb32f78045,16#f9ab1562456b9d66,
16#6435f4130304a793,16#b4bb94c2002e1849,16#49a86d1e4bade982,16#457d63d60ed52b95];
reference_val(exsplus) ->
[16#bc76c2e638db,16#15ede2ebb16c9fb,16#185ee2c27d6b88d,16#15d5ee9feafc3a5,
16#1862e91dfce3e6b,16#2c9744b0fb69e46,16#78b21bc01cef6b,16#2d16a2fae6c76ba,
16#13dfccb8ff86bce,16#1d9474c59e23f4d,16#d2f67dcd7f0dd6,16#2b6d489d51a0725,
16#1fa52ef484861d8,16#1ae9e2a38f966d4,16#2264ab1e193acca,16#23bbca085039a05,
16#2b6eea06a0af0e1,16#3ad47fa8866ea20,16#1ec2802d612d855,16#36c1982b134d50,
16#296b6a23f5b75e0,16#c5eeb600a9875c,16#2a3fd51d735f9d4,16#56fafa3593a070,
16#13e9d416ec0423e,16#28101a91b23e9dc,16#32e561eb55ce15a,16#94a7dbba66fe4a,
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16#15cbd1a421c7a8c,16#22794e3ec6ef3b1,16#26154d26e7ea99f,16#3a66681359a6ab6].
