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-rw-r--r--lib/stdlib/test/rand_SUITE.erl210
1 files changed, 203 insertions, 7 deletions
diff --git a/lib/stdlib/test/rand_SUITE.erl b/lib/stdlib/test/rand_SUITE.erl
index f69d42551e..0c7d8d842e 100644
--- a/lib/stdlib/test/rand_SUITE.erl
+++ b/lib/stdlib/test/rand_SUITE.erl
@@ -29,11 +29,14 @@
basic_stats_uniform_1/1, basic_stats_uniform_2/1,
basic_stats_standard_normal/1,
basic_stats_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).
@@ -46,7 +49,7 @@ all() ->
[seed, interval_int, interval_float,
api_eq,
reference,
- {group, basic_stats},
+ {group, basic_stats}, uniform_real_conv,
plugin, measure,
{group, reference_jump}
].
@@ -101,7 +104,7 @@ 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 +231,13 @@ 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 +339,13 @@ 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);
@@ -400,6 +411,137 @@ normal_s(Mean, Variance, State0) ->
rand:normal_s(Mean, Variance, State0).
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
+%% 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),$\s]||G<-Gen]]),
+ ct:fail({neq, FF, F})
+ catch
+ Error:Reason ->
+ ct:pal(
+ "~w:~p ~s: ~s~n",
+ [Error, Reason, rand:float2str(F),
+ [["16#",integer_to_list(G,16),$\s]||G<-Gen]]),
+ ct:fail({Error, Reason, F, erlang:get_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.
plugin(Config) when is_list(Config) ->
@@ -520,6 +662,21 @@ do_measure(_Config) ->
end,
Algs),
%%
+ ct:pal("~nRNG uniform integer half range performance~n",[]),
+ _ =
+ measure_1(
+ 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(
@@ -630,7 +787,8 @@ do_measure(_Config) ->
Algs),
%%
ct:pal("~nRNG uniform float performance~n",[]),
- _ = measure_1(
+ _ =
+ measure_1(
fun (_) -> 0 end,
fun (State, _, Mod) ->
measure_loop(
@@ -641,8 +799,22 @@ do_measure(_Config) ->
end,
Algs),
%%
+ ct:pal("~nRNG uniform_real float performance~n",[]),
+ _ =
+ 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",[]),
- _ = measure_1(
+ [TMarkNormalFloat|_] =
+ measure_1(
fun (_) -> 0 end,
fun (State, _, Mod) ->
measure_loop(
@@ -652,6 +824,30 @@ do_measure(_Config) ->
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_loop(Fun, State) ->
generated by cgit v1.2.3 (git 2.25.1) at 2024-11-05 21:10:51 +0000