-module(test_sorting).

-compile(export_all).

-import(sorting, [p_qsort/1, qsort/1]).

%%
%% Examples
%%

example_p_qsort()  -> example_p_qsort(1000000).

example_p_qsort(N) ->
   random_seed(),
   L = mkList(N),
   benchmark:do(fun() -> sorting:p_qsort(L) end).

example_qsort()  -> example_qsort(1000000).

example_qsort(N) ->
   random_seed(),
   L = mkList(N),
   benchmark:do(fun() -> sorting:qsort(L) end).

%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%% Benchmark for list of variable size
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%

%% Executes a benchmark for sorting:qsort
bench_qsort()   ->
   bench_list_algorithm(fun sorting:qsort/1, "Results qsort.csv").
%% Executes a benchmark for sorting:p_qsort
bench_p_qsort() ->
   bench_list_algorithm(fun sorting:p_qsort/1, "Results p_qsort.csv").

%% Executes a benchmark for the algorithm indicated, F, and saves the results in Filename
%%
%% @type result() = {integer(), integer()}
%%
%% @spec bench_list_algorithm(fun(X) -> , string()) -> [result()]
bench_list_algorithm(F, Filename) ->
   Results = lists:map(
      fun(L) -> 
         { L, benchmark:do_silent(fun() -> io:format("Execute with a list of length = ~p~n", [L]), 
                                           F(mkList(L)) end ) } 
      end, bench_size_samples_lists()),
   save_to_csv_file(Filename, Results),
   Results.

bench_size_samples_lists() ->
   lists:seq(100000, 1000000, 100000) ++  % up to 1 million, each 100 thousand (size = 10)
   lists:seq(2000000, 10000000, 1000000). % up to 10 millions, each million (size = 10)

save_to_csv_file(File, L) ->
   {ok, S} = file:open(File, write),
   lists:foreach(fun(X) -> {N, Time} = X, io:format(S, "~p,~p~n", [N, Time]) end, L),
    file:close(S).

%%
%% Make a list of K random numbers
%%
mkList(K) -> mkList(K, [], K).

mkList(0, L, _) -> L;
mkList(N, L, K) -> mkList(N-1, [random:uniform(K)|L], K).

random_seed() ->
    {_,_,X} = erlang:now(),
    {H,M,S} = time(),
    H1 = H * X rem 32767,
    M1 = M * X rem 32767,
    S1 = S * X rem 32767,
    random:seed(H1,M1,S1).