diff options
Diffstat (limited to 'lib/stdlib/test/rand_SUITE.erl')
| -rw-r--r-- | lib/stdlib/test/rand_SUITE.erl | 803 |
1 files changed, 617 insertions, 186 deletions
diff --git a/lib/stdlib/test/rand_SUITE.erl b/lib/stdlib/test/rand_SUITE.erl index 432293b656..b76c9f5341 100644 --- a/lib/stdlib/test/rand_SUITE.erl +++ b/lib/stdlib/test/rand_SUITE.erl @@ -1,7 +1,7 @@ %% %% %CopyrightBegin% %% -%% Copyright Ericsson AB 2000-2017. All Rights Reserved. +%% Copyright Ericsson AB 2000-2018. 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. @@ -29,11 +29,17 @@ basic_stats_uniform_1/1, basic_stats_uniform_2/1, basic_stats_standard_normal/1, basic_stats_normal/1, + stats_standard_normal_box_muller/1, + stats_standard_normal_box_muller_2/1, + stats_standard_normal/1, + uniform_real_conv/1, plugin/1, measure/1, reference_jump_state/1, reference_jump_procdict/1]). -export([test/0, gen/1]). +-export([uniform_real_gen/1, uniform_gen/2]). + -include_lib("common_test/include/ct.hrl"). -define(LOOP, 1000000). @@ -47,6 +53,8 @@ all() -> api_eq, reference, {group, basic_stats}, + {group, distr_stats}, + uniform_real_conv, plugin, measure, {group, reference_jump} ]. @@ -55,12 +63,19 @@ groups() -> [{basic_stats, [parallel], [basic_stats_uniform_1, basic_stats_uniform_2, basic_stats_standard_normal]}, + {distr_stats, [parallel], + [stats_standard_normal_box_muller, + stats_standard_normal_box_muller_2, + stats_standard_normal]}, {reference_jump, [parallel], [reference_jump_state, reference_jump_procdict]}]. group(basic_stats) -> %% valgrind needs a lot of time [{timetrap,{minutes,10}}]; +group(distr_stats) -> + %% valgrind needs a lot of time + [{timetrap,{minutes,10}}]; group(reference_jump) -> %% valgrind needs a lot of time [{timetrap,{minutes,10}}]. @@ -73,14 +88,14 @@ test() -> try ok = ?MODULE:Test([]), io:format("~p: ok~n", [Test]) - catch _:Reason -> + catch _:Reason:Stacktrace -> io:format("Failed: ~p: ~p ~p~n", - [Test, Reason, erlang:get_stacktrace()]) + [Test, Reason, Stacktrace]) end end, Tests). algs() -> - [exs64, exsplus, exsp, exrop, exs1024, exs1024s]. + [exrop, exsp, exs1024s, exs64, exsplus, exs1024]. %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% @@ -89,8 +104,8 @@ seed(Config) when is_list(Config) -> Algs = algs(), Test = fun(Alg) -> try seed_1(Alg) - catch _:Reason -> - ct:fail({Alg, Reason, erlang:get_stacktrace()}) + catch _:Reason:Stacktrace -> + ct:fail({Alg, Reason, Stacktrace}) end end, [Test(Alg) || Alg <- Algs], @@ -101,7 +116,7 @@ seed_1(Alg) -> _ = rand:uniform(), S00 = get(rand_seed), erase(), - _ = rand:uniform(), + _ = rand:uniform_real(), false = S00 =:= get(rand_seed), %% hopefully %% Choosing algo and seed @@ -228,11 +243,13 @@ interval_float(Config) when is_list(Config) -> interval_float_1(0) -> ok; interval_float_1(N) -> X = rand:uniform(), + Y = rand:uniform_real(), if - 0.0 =< X, X < 1.0 -> + 0.0 =< X, X < 1.0, 0.0 < Y, Y < 1.0 -> ok; true -> - io:format("X=~p 0=<~p<1.0~n", [X,X]), + io:format("X=~p 0.0=<~p<1.0~n", [X,X]), + io:format("Y=~p 0.0<~p<1.0~n", [Y,Y]), exit({X, rand:export_seed()}) end, interval_float_1(N-1). @@ -334,7 +351,13 @@ basic_stats_normal(Config) when is_list(Config) -> IntendedMeanVariancePairs). basic_uniform_1(N, S0, Sum, A0) when N > 0 -> - {X,S} = rand:uniform_s(S0), + {X,S} = + case N band 1 of + 0 -> + rand:uniform_s(S0); + 1 -> + rand:uniform_real_s(S0) + end, I = trunc(X*100), A = array:set(I, 1+array:get(I,A0), A0), basic_uniform_1(N-1, S, Sum+X, A); @@ -399,6 +422,352 @@ normal_s(Mean, Variance, State0) when Mean == 0, Variance == 1 -> normal_s(Mean, Variance, State0) -> rand:normal_s(Mean, Variance, State0). + + +-dialyzer({no_improper_lists, stats_standard_normal_box_muller/1}). +stats_standard_normal_box_muller(Config) when is_list(Config) -> + try math:erfc(1.0) of + _ -> + TwoPi = 2.0 * math:pi(), + NormalS = + fun + ([S0]) -> + {U1, S1} = rand:uniform_real_s(S0), + R = math:sqrt(-2.0 * math:log(U1)), + {U2, S2} = rand:uniform_s(S1), + T = TwoPi * U2, + Z0 = R * math:cos(T), + Z1 = R * math:sin(T), + {Z0, [S2|Z1]}; + ([S|Z]) -> + {Z, [S]} + end, + State = [rand:seed(exrop)], + stats_standard_normal(NormalS, State, 3) + catch error:_ -> + {skip, "math:erfc/1 not supported"} + end. + +-dialyzer({no_improper_lists, stats_standard_normal_box_muller_2/1}). +stats_standard_normal_box_muller_2(Config) when is_list(Config) -> + try math:erfc(1.0) of + _ -> + TwoPi = 2.0 * math:pi(), + NormalS = + fun + ([S0]) -> + {U0, S1} = rand:uniform_s(S0), + U1 = 1.0 - U0, + R = math:sqrt(-2.0 * math:log(U1)), + {U2, S2} = rand:uniform_s(S1), + T = TwoPi * U2, + Z0 = R * math:cos(T), + Z1 = R * math:sin(T), + {Z0, [S2|Z1]}; + ([S|Z]) -> + {Z, [S]} + end, + State = [rand:seed(exrop)], + stats_standard_normal(NormalS, State, 3) + catch error:_ -> + {skip, "math:erfc/1 not supported"} + end. + + +stats_standard_normal(Config) when is_list(Config) -> + Retries = 7, + try math:erfc(1.0) of + _ -> + stats_standard_normal( + fun rand:normal_s/1, rand:seed_s(exrop), Retries) + catch error:_ -> + {skip, "math:erfc/1 not supported"} + end. +%% +stats_standard_normal(Fun, S, Retries) -> +%%% +%%% ct config: +%%% {rand_SUITE, [{stats_standard_normal,[{seconds, 8}, {std_devs, 4.0}]}]}. +%%% + Seconds = ct:get_config({?MODULE, ?FUNCTION_NAME, seconds}, 8), + StdDevs = + ct:get_config( + {?MODULE, ?FUNCTION_NAME, std_devs}, + 4.0), % probability erfc(4.0/sqrt(2)) (1/15787) to fail a bucket +%%% + ct:timetrap({seconds, Seconds + 120}), + %% Buckets is chosen to get a range where the the probability to land + %% in the top catch-all bucket is not vanishingly low, but with + %% these values it is about 1/25 of the probability for the low bucket + %% (closest to 0). + %% + %% Rounds is calculated so the expected value for the low + %% bucket will be at least TargetHits. + %% + InvDelta = 512, + Buckets = 4 * InvDelta, % 4 std devs range + TargetHits = 1024, + Sqrt2 = math:sqrt(2.0), + W = InvDelta * Sqrt2, + P0 = math:erf(1 / W), + Rounds = TargetHits * ceil(1.0 / P0), + Histogram = array:new({default, 0}), + ct:pal( + "Running standard normal test against ~w std devs for ~w seconds...", + [StdDevs, Seconds]), + StopTime = erlang:monotonic_time(second) + Seconds, + {PositiveHistogram, NegativeHistogram, Outlier, TotalRounds, NewS} = + stats_standard_normal( + InvDelta, Buckets, Histogram, Histogram, 0.0, + Fun, S, Rounds, StopTime, Rounds, 0), + Precision = math:sqrt(TotalRounds * P0) / StdDevs, + TopP = math:erfc(Buckets / W), + TopPrecision = math:sqrt(TotalRounds * TopP) / StdDevs, + OutlierProbability = math:erfc(Outlier / Sqrt2) * TotalRounds, + InvOP = 1.0 / OutlierProbability, + ct:pal( + "Total rounds: ~w, tolerance: 1/~.2f..1/~.2f, " + "outlier: ~.2f, probability 1/~.2f.", + [TotalRounds, Precision, TopPrecision, Outlier, InvOP]), + case + {bucket_error, TotalRounds, + check_histogram( + W, TotalRounds, StdDevs, PositiveHistogram, Buckets), + check_histogram( + W, TotalRounds, StdDevs, NegativeHistogram, Buckets)} + of + {_, _, [], []} when InvOP < 100 -> + {comment, {tp, TopPrecision, op, InvOP}}; + {_, _, [], []} -> + %% If the probability for getting this Outlier is lower than + %% 1/100, then this is fishy! + stats_standard_normal( + Fun, NewS, Retries, {outlier_fishy, InvOP}); + BucketErrors -> + stats_standard_normal( + Fun, NewS, Retries, BucketErrors) + end. +%% +stats_standard_normal(Fun, S, Retries, Failure) -> + case Retries - 1 of + 0 -> + ct:fail(Failure); + NewRetries -> + ct:pal("Retry due to TC glitch: ~p", [Failure]), + stats_standard_normal(Fun, S, NewRetries) + end. +%% +stats_standard_normal( + InvDelta, Buckets, PositiveHistogram, NegativeHistogram, Outlier, + Fun, S, 0, StopTime, Rounds, TotalRounds) -> + case erlang:monotonic_time(second) of + Now when Now < StopTime -> + stats_standard_normal( + InvDelta, Buckets, + PositiveHistogram, NegativeHistogram, Outlier, + Fun, S, Rounds, StopTime, Rounds, TotalRounds + Rounds); + _ -> + {PositiveHistogram, NegativeHistogram, + Outlier, TotalRounds + Rounds, S} + end; +stats_standard_normal( + InvDelta, Buckets, PositiveHistogram, NegativeHistogram, Outlier, + Fun, S, Count, StopTime, Rounds, TotalRounds) -> + case Fun(S) of + {X, NewS} when 0.0 =< X -> + Bucket = min(Buckets, floor(X * InvDelta)), + stats_standard_normal( + InvDelta, Buckets, + increment_bucket(Bucket, PositiveHistogram), + NegativeHistogram, max(Outlier, X), + Fun, NewS, Count - 1, StopTime, Rounds, TotalRounds); + {MinusX, NewS} -> + X = -MinusX, + Bucket = min(Buckets, floor(X * InvDelta)), + stats_standard_normal( + InvDelta, Buckets, + PositiveHistogram, + increment_bucket(Bucket, NegativeHistogram), max(Outlier, X), + Fun, NewS, Count - 1, StopTime, Rounds, TotalRounds) + end. + +increment_bucket(Bucket, Array) -> + array:set(Bucket, array:get(Bucket, Array) + 1, Array). + +check_histogram(W, Rounds, StdDevs, Histogram, Buckets) -> + TargetP = 0.5 * math:erfc(Buckets / W), + P = 0.0, + N = 0, + check_histogram( + W, Rounds, StdDevs, Histogram, TargetP, + Buckets, Buckets, P, N). +%% +check_histogram( + _W, _Rounds, _StdDevs, _Histogram, _TargetP, + 0, _PrevBucket, _PrevP, _PrevN) -> + []; +check_histogram( + W, Rounds, StdDevs, Histogram, TargetP, + Bucket, PrevBucket, PrevP, PrevN) -> + N = PrevN + array:get(Bucket, Histogram), + P = 0.5 * math:erfc(Bucket / W), + BucketP = P - PrevP, + if + BucketP < TargetP -> + check_histogram( + W, Rounds, StdDevs, Histogram, TargetP, + Bucket - 1, PrevBucket, PrevP, N); + true -> + Exp = BucketP * Rounds, + Var = Rounds * BucketP*(1.0 - BucketP), + Threshold = StdDevs * math:sqrt(Var), + LowerLimit = floor(Exp - Threshold), + UpperLimit = ceil(Exp + Threshold), + if + N < LowerLimit; UpperLimit < N -> + [#{bucket => {Bucket, PrevBucket}, n => N, + lower => LowerLimit, upper => UpperLimit} | + check_histogram( + W, Rounds, StdDevs, Histogram, TargetP, + Bucket - 1, Bucket, P, 0)]; + true -> + check_histogram( + W, Rounds, StdDevs, Histogram, TargetP, + Bucket - 1, Bucket, P, 0) + end + end. + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%% White box test of the conversion to float + +uniform_real_conv(Config) when is_list(Config) -> + [begin +%% ct:pal("~13.16.0bx~3.16.0b: ~p~n", [M,E,Gen]), + uniform_real_conv_check(M, E, Gen) + end || {M, E, Gen} <- uniform_real_conv_data()], + uniform_real_scan(0), + uniform_real_scan(3). + +uniform_real_conv_data() -> + [{16#fffffffffffff, -1, [16#3ffffffffffffff]}, + {16#fffffffffffff, -1, [16#3ffffffffffffe0]}, + {16#ffffffffffffe, -1, [16#3ffffffffffffdf]}, + %% + {16#0000000000000, -1, [16#200000000000000]}, + {16#fffffffffffff, -2, [16#1ffffffffffffff]}, + {16#fffffffffffff, -2, [16#1fffffffffffff0]}, + {16#ffffffffffffe, -2, [16#1ffffffffffffef]}, + %% + {16#0000000000000, -2, [16#100000000000000]}, + {16#fffffffffffff, -3, [16#0ffffffffffffff]}, + {16#fffffffffffff, -3, [16#0fffffffffffff8]}, + {16#ffffffffffffe, -3, [16#0fffffffffffff7]}, + %% + {16#0000000000000, -3, [16#080000000000000]}, + {16#fffffffffffff, -4, [16#07fffffffffffff]}, + {16#fffffffffffff, -4, [16#07ffffffffffffc]}, + {16#ffffffffffffe, -4, [16#07ffffffffffffb]}, + %% + {16#0000000000000, -4, [16#040000000000000]}, + {16#fffffffffffff, -5, [16#03fffffffffffff,16#3ffffffffffffff]}, + {16#fffffffffffff, -5, [16#03ffffffffffffe,16#200000000000000]}, + {16#ffffffffffffe, -5, [16#03fffffffffffff,16#1ffffffffffffff]}, + {16#ffffffffffffe, -5, [16#03fffffffffffff,16#100000000000000]}, + %% + {16#0000000000001, -56, [16#000000000000007,16#00000000000007f]}, + {16#0000000000001, -56, [16#000000000000004,16#000000000000040]}, + {16#0000000000000, -57, [16#000000000000003,16#20000000000001f]}, + {16#0000000000000, -57, [16#000000000000000,16#200000000000000]}, + {16#fffffffffffff, -58, [16#000000000000003,16#1ffffffffffffff]}, + {16#fffffffffffff, -58, [16#000000000000000,16#1fffffffffffff0]}, + {16#ffffffffffffe, -58, [16#000000000000000,16#1ffffffffffffef]}, + {16#ffffffffffffe, -58, [16#000000000000000,16#1ffffffffffffe0]}, + %% + {16#0000000000000, -58, [16#000000000000000,16#10000000000000f]}, + {16#0000000000000, -58, [16#000000000000000,16#100000000000000]}, + {2#11001100000000000000000000000000000000000011000000011, % 53 bits + -1022, + [0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0, % 18 zeros + 2#1100110000000000000000000000000000000000001 bsl 2, % 43 bits + 2#1000000011 bsl (56-10+2)]}, % 10 bits + {0, -1, % 0.5 after retry + [0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0, % 18 zeros + 2#111111111111111111111111111111111111111111 bsl 2, % 42 bits - retry + 16#200000000000003]}]. % 0.5 + +-define(UNIFORM_REAL_SCAN_PATTERN, (16#19000000000009)). % 53 bits +-define(UNIFORM_REAL_SCAN_NUMBER, (1021)). + +uniform_real_scan_template(K) -> + <<0:?UNIFORM_REAL_SCAN_NUMBER, + ?UNIFORM_REAL_SCAN_PATTERN:53,K:2,0:1>>. + +uniform_real_scan(K) -> + Templ = uniform_real_scan_template(K), + N = ?UNIFORM_REAL_SCAN_NUMBER, + uniform_real_scan(Templ, N, K). + +uniform_real_scan(Templ, N, K) when 0 =< N -> + <<_:N/bits,T/bits>> = Templ, + Data = uniform_real_scan_data(T, K), + uniform_real_conv_check( + ?UNIFORM_REAL_SCAN_PATTERN, N - 1 - ?UNIFORM_REAL_SCAN_NUMBER, Data), + uniform_real_scan(Templ, N - 1, K); +uniform_real_scan(_, _, _) -> + ok. + +uniform_real_scan_data(Templ, K) -> + case Templ of + <<X:56, T/bits>> -> + B = rand:bc64(X), + [(X bsl 2) bor K | + if + 53 =< B -> + []; + true -> + uniform_real_scan_data(T, K) + end]; + _ -> + <<X:56, _/bits>> = <<Templ/bits, 0:56>>, + [(X bsl 2) bor K] + end. + +uniform_real_conv_check(M, E, Gen) -> + <<F/float>> = <<0:1, (E + 16#3ff):11, M:52>>, + try uniform_real_gen(Gen) of + F -> F; + FF -> + ct:pal( + "~s =/= ~s: ~s~n", + [rand:float2str(FF), rand:float2str(F), + [["16#",integer_to_list(G,16),$\s]||G<-Gen]]), + ct:fail({neq, FF, F}) + catch + Error:Reason:Stacktrace -> + ct:pal( + "~w:~p ~s: ~s~n", + [Error, Reason, rand:float2str(F), + [["16#",integer_to_list(G,16),$\s]||G<-Gen]]), + ct:fail({Error, Reason, F, Stacktrace}) + end. + + +uniform_real_gen(Gen) -> + State = rand_state(Gen), + {F, {#{type := rand_SUITE_list},[]}} = rand:uniform_real_s(State), + F. + +uniform_gen(Range, Gen) -> + State = rand_state(Gen), + {N, {#{type := rand_SUITE_list},[]}} = rand:uniform_s(Range, State), + N. + +%% Loaded dice for white box tests +rand_state(Gen) -> + {#{type => rand_SUITE_list, bits => 58, weak_low_bits => 1, + next => fun ([H|T]) -> {H, T} end}, + Gen}. + %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% %% Test that the user can write algorithms. @@ -459,213 +828,289 @@ measure(Config) -> {skip,{will_not_run_in_scaled_time,Scale}} end. +-define(CHECK_UNIFORM_RANGE(Gen, Range, X, St), + case (Gen) of + {(X), (St)} when is_integer(X), 1 =< (X), (X) =< (Range) -> + St + end). +-define(CHECK_UNIFORM(Gen, X, St), + case (Gen) of + {(X), (St)} when is_float(X), 0.0 =< (X), (X) < 1.0 -> + St + end). +-define(CHECK_UNIFORM_NZ(Gen, X, St), + case (Gen) of + {(X), (St)} when is_float(X), 0.0 < (X), (X) =< 1.0 -> + St + end). +-define(CHECK_NORMAL(Gen, X, St), + case (Gen) of + {(X), (St)} when is_float(X) -> + St + end). + do_measure(_Config) -> - Algos = + Algs = + algs() ++ try crypto:strong_rand_bytes(1) of - <<_>> -> [crypto64, crypto] + <<_>> -> [crypto64, crypto_cache, crypto] catch error:low_entropy -> []; error:undef -> [] - end ++ algs(), + end, %% - ct:pal("RNG uniform integer performance~n",[]), - TMark1 = + ct:pal("~nRNG uniform integer range 10000 performance~n",[]), + _ = measure_1( - random, fun (_) -> 10000 end, - undefined, - fun (Range, State) -> - {int, random:uniform_s(Range, State)} - end), + fun (State, Range, Mod) -> + measure_loop( + fun (St0) -> + ?CHECK_UNIFORM_RANGE( + Mod:uniform_s(Range, St0), Range, + X, St1) + end, + State) + end, + Algs), + %% + ct:pal("~nRNG uniform integer 32 bit performance~n",[]), _ = - [measure_1( - Algo, - fun (_) -> 10000 end, - TMark1, - fun (Range, State) -> - {int, rand:uniform_s(Range, State)} - end) || Algo <- Algos], + measure_1( + fun (_) -> 1 bsl 32 end, + fun (State, Range, Mod) -> + measure_loop( + fun (St0) -> + ?CHECK_UNIFORM_RANGE( + Mod:uniform_s(Range, St0), Range, + X, St1) + end, + State) + end, + Algs), %% 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), + fun (State) -> half_range(State) end, + fun (State, Range, Mod) -> + measure_loop( + fun (St0) -> + ?CHECK_UNIFORM_RANGE( + Mod:uniform_s(Range, St0), Range, + X, St1) + end, + State) + end, + Algs), + %% + ct:pal("~nRNG uniform integer half range + 1 performance~n",[]), _ = - [measure_1( - Algo, - HalfRangePlus1Fun, - TMark3, - fun (Range, State) -> - {int, rand:uniform_s(Range, State)} - end) || Algo <- Algos], + measure_1( + fun (State) -> half_range(State) + 1 end, + fun (State, Range, Mod) -> + measure_loop( + fun (St0) -> + ?CHECK_UNIFORM_RANGE( + Mod:uniform_s(Range, St0), Range, + X, St1) + end, + State) + end, + Algs), %% 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], + measure_1( + fun (State) -> (half_range(State) bsl 1) - 1 end, + fun (State, Range, Mod) -> + measure_loop( + fun (St0) -> + ?CHECK_UNIFORM_RANGE( + Mod:uniform_s(Range, St0), Range, + X, St1) + end, + State) + end, + Algs), %% 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], + measure_1( + fun (State) -> half_range(State) bsl 1 end, + fun (State, Range, Mod) -> + measure_loop( + fun (St0) -> + ?CHECK_UNIFORM_RANGE( + Mod:uniform_s(Range, St0), Range, + X, St1) + end, + State) + end, + Algs), %% 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], + measure_1( + fun (State) -> (half_range(State) bsl 1) + 1 end, + fun (State, Range, Mod) -> + measure_loop( + fun (St0) -> + ?CHECK_UNIFORM_RANGE( + Mod:uniform_s(Range, St0), Range, + X, St1) + end, + State) + end, + Algs), %% 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], + measure_1( + fun (State) -> + half_range(State) bsl 2 + end, + fun (State, Range, Mod) -> + measure_loop( + fun (St0) -> + ?CHECK_UNIFORM_RANGE( + Mod:uniform_s(Range, St0), Range, + X, St1) + end, + State) + end, + Algs), %% 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), + fun (State) -> + (half_range(State) bsl 2) + 1 + end, + fun (State, Range, Mod) -> + measure_loop( + fun (St0) -> + ?CHECK_UNIFORM_RANGE( + Mod:uniform_s(Range, St0), Range, + X, St1) + end, + State) + end, + Algs), + %% + ct:pal("~nRNG uniform integer 64 bit performance~n",[]), _ = - [measure_1( - Algo, - DoubleRangePlus1Fun, - TMark8, - fun (Range, State) -> - {int, rand:uniform_s(Range, State)} - end) || Algo <- Algos], + measure_1( + fun (_) -> 1 bsl 64 end, + fun (State, Range, Mod) -> + measure_loop( + fun (St0) -> + ?CHECK_UNIFORM_RANGE( + Mod:uniform_s(Range, St0), Range, + X, St1) + end, + State) + end, + Algs), %% ct:pal("~nRNG uniform float performance~n",[]), - TMark9 = + _ = measure_1( - random, fun (_) -> 0 end, - undefined, - fun (_, State) -> - {uniform, random:uniform_s(State)} - end), + fun (State, _, Mod) -> + measure_loop( + fun (St0) -> + ?CHECK_UNIFORM(Mod:uniform_s(St0), X, St) + end, + State) + end, + Algs), + %% + ct:pal("~nRNG uniform_real float performance~n",[]), _ = - [measure_1( - Algo, - fun (_) -> 0 end, - TMark9, - fun (_, State) -> - {uniform, rand:uniform_s(State)} - end) || Algo <- Algos], + measure_1( + fun (_) -> 0 end, + fun (State, _, Mod) -> + measure_loop( + fun (St0) -> + ?CHECK_UNIFORM(Mod:uniform_real_s(St0), X, St) + end, + State) + end, + Algs), %% 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], + [TMarkNormalFloat|_] = + measure_1( + fun (_) -> 0 end, + fun (State, _, Mod) -> + measure_loop( + fun (St0) -> + ?CHECK_NORMAL(Mod:normal_s(St0), X, St1) + end, + State) + end, + Algs), + %% Just for fun try an implementation of the Box-Muller + %% transformation for creating normal distribution floats + %% to compare with our Ziggurat implementation. + %% Generates two numbers per call that we add so they + %% will not be optimized away. Hence the benchmark time + %% is twice what it should be. + TwoPi = 2 * math:pi(), + _ = + measure_1( + fun (_) -> 0 end, + fun (State, _, Mod) -> + measure_loop( + fun (State0) -> + {U1, State1} = Mod:uniform_real_s(State0), + {U2, State2} = Mod:uniform_s(State1), + R = math:sqrt(-2.0 * math:log(U1)), + T = TwoPi * U2, + Z0 = R * math:cos(T), + Z1 = R * math:sin(T), + ?CHECK_NORMAL({Z0 + Z1, State2}, X, State3) + end, + State) + end, + exrop, TMarkNormalFloat), ok. -measure_1(Algo, RangeFun, TMark, Gen) -> +-define(LOOP_MEASURE, (?LOOP div 5)). + +measure_loop(Fun, State) -> + measure_loop(Fun, State, ?LOOP_MEASURE). +%% +measure_loop(Fun, State, N) when 0 < N -> + measure_loop(Fun, Fun(State), N-1); +measure_loop(_, _, _) -> + ok. + +measure_1(RangeFun, Fun, Algs) -> + TMark = measure_1(RangeFun, Fun, hd(Algs), undefined), + [TMark] ++ + [measure_1(RangeFun, Fun, Alg, TMark) || Alg <- tl(Algs)]. + +measure_1(RangeFun, Fun, Alg, TMark) -> Parent = self(), - Seed = - case Algo of + {Mod, State} = + case Alg of crypto64 -> - crypto64_seed(); + {rand, crypto64_seed()}; + crypto_cache -> + {rand, crypto:rand_seed_alg(crypto_cache)}; crypto -> - crypto:rand_seed_s(); + {rand, crypto:rand_seed_s()}; random -> - random:seed(os:timestamp()), get(random_seed); + {random, random:seed(os:timestamp()), get(random_seed)}; _ -> - rand:seed_s(Algo) + {rand, rand:seed_s(Alg)} end, - Range = RangeFun(Seed), + Range = RangeFun(State), Pid = spawn_link( fun() -> - Fun = fun() -> measure_2(?LOOP, Range, Seed, Gen) end, - {Time, ok} = timer:tc(Fun), + {Time, ok} = timer:tc(fun () -> Fun(State, Range, Mod) end), Percent = case TMark of undefined -> 100; @@ -673,7 +1118,8 @@ measure_1(Algo, RangeFun, TMark, Gen) -> end, io:format( "~.12w: ~p ns ~p% [16#~.16b]~n", - [Algo, (Time * 1000 + 500) div ?LOOP, Percent, Range]), + [Alg, (Time * 1000 + 500) div ?LOOP_MEASURE, + Percent, Range]), Parent ! {self(), Time}, normal end), @@ -681,21 +1127,6 @@ measure_1(Algo, RangeFun, TMark, Gen) -> {Pid, Msg} -> Msg end. -measure_2(N, Range, State0, Fun) when N > 0 -> - case Fun(Range, State0) of - {int, {Random, State}} - 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, Range, State, Fun); - Res -> - exit({error, Res, State0}) - end; -measure_2(0, _, _, _) -> ok. - %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% %% The jump sequence tests has two parts %% for those with the functional API (jump/1) |