merge bear and bear_scutil
diff --git a/src/bear.erl b/src/bear.erl
index 97bac0f..0afbe61 100644
--- a/src/bear.erl
+++ b/src/bear.erl
@@ -240,7 +240,7 @@
get_kendall_correlation(Values1, Values2) when length(Values1) /= length(Values2) ->
0.0;
get_kendall_correlation(Values1, Values2) ->
- bear_scutil:kendall_correlation(Values1, Values2).
+ bear:kendall_correlation(Values1, Values2).
get_spearman_correlation(Values, _) when length(Values) < ?STATS_MIN ->
0.0;
@@ -370,3 +370,68 @@
get_bin_count(Min, Max, Width) ->
%io:format("min: ~p, max: ~p, width ~p~n", [Min, Max, Width]),
round((Max - Min) / Width) + 1.
+
+%% taken from http://crunchyd.com/scutil/
+%% All code here is MIT Licensed
+%% http://scutil.com/license.html
+
+% seems to match the value returned by the 'cor' (method="kendal") R function
+% http://en.wikipedia.org/wiki/Kendall_tau_rank_correlation_coefficient
+kendall_correlation(List1, List2) when is_list(List1), is_list(List2) ->
+ {RA,_} = lists:unzip(tied_ordered_ranking(List1)),
+ {RB,_} = lists:unzip(tied_ordered_ranking(List2)),
+
+ Ordering = lists:keysort(1, lists:zip(RA,RB)),
+ {_,OrdB} = lists:unzip(Ordering),
+
+ N = length(List1),
+ P = lists:sum(kendall_right_of(OrdB, [])),
+
+ -(( (4*P) / (N * (N - 1))) - 1).
+
+simple_ranking(List) when is_list(List) ->
+ lists:zip(lists:seq(1,length(List)),lists:reverse(lists:sort(List))).
+
+tied_ranking(List) ->
+ tied_rank_worker(simple_ranking(List), [], no_prev_value).
+
+tied_ordered_ranking(List) when is_list(List) ->
+ tied_ordered_ranking(List, tied_ranking(List), []).
+
+tied_ordered_ranking([], [], Work) ->
+ lists:reverse(Work);
+
+tied_ordered_ranking([Front|Rem], Ranks, Work) ->
+ {value,Item} = lists:keysearch(Front,2,Ranks),
+ {IRank,Front} = Item,
+ tied_ordered_ranking(Rem, Ranks--[Item], [{IRank,Front}]++Work).
+
+kendall_right_of([], Work) ->
+ lists:reverse(Work);
+kendall_right_of([F|R], Work) ->
+ kendall_right_of(R, [kendall_right_of_item(F,R)]++Work).
+
+kendall_right_of_item(B, Rem) ->
+ length([R || R <- Rem, R < B]).
+
+tied_add_prev(Work, {FoundAt, NewValue}) ->
+ lists:duplicate( length(FoundAt), {lists:sum(FoundAt)/length(FoundAt), NewValue} ) ++ Work.
+
+tied_rank_worker([], Work, PrevValue) ->
+ lists:reverse(tied_add_prev(Work, PrevValue));
+
+tied_rank_worker([Item|Remainder], Work, PrevValue) ->
+ case PrevValue of
+ no_prev_value ->
+ {BaseRank,BaseVal} = Item,
+ tied_rank_worker(Remainder, Work, {[BaseRank],BaseVal});
+ {FoundAt,OldVal} ->
+ case Item of
+ {Id,OldVal} ->
+ tied_rank_worker(Remainder, Work, {[Id]++FoundAt,OldVal});
+ {Id,NewVal} ->
+ tied_rank_worker(Remainder, tied_add_prev(Work, PrevValue), {[Id],NewVal})
+
+ end
+ end.
+
diff --git a/src/bear_scutil.erl b/src/bear_scutil.erl
deleted file mode 100644
index e684fb7..0000000
--- a/src/bear_scutil.erl
+++ /dev/null
@@ -1,75 +0,0 @@
-%% taken from http://crunchyd.com/scutil/
-%% All code here is MIT Licensed
-%% http://scutil.com/license.html
-
--module(bear_scutil).
-
--export([
- kendall_correlation/2
- ]).
--compile([export_all]).
--compile([native]).
-
-% seems to match the value returned by the 'cor' (method="kendal") R function
-% http://en.wikipedia.org/wiki/Kendall_tau_rank_correlation_coefficient
-kendall_correlation(List1, List2) when is_list(List1), is_list(List2) ->
- {RA,_} = lists:unzip(tied_ordered_ranking(List1)),
- {RB,_} = lists:unzip(tied_ordered_ranking(List2)),
-
- Ordering = lists:keysort(1, lists:zip(RA,RB)),
- {_,OrdB} = lists:unzip(Ordering),
-
- N = length(List1),
- P = lists:sum(kendall_right_of(OrdB, [])),
-
- -(( (4*P) / (N * (N - 1))) - 1).
-
-%%%===================================================================
-%%% Internal functions
-%%%==================================================================
-
-simple_ranking(List) when is_list(List) ->
- lists:zip(lists:seq(1,length(List)),lists:reverse(lists:sort(List))).
-
-tied_ranking(List) ->
- tied_rank_worker(simple_ranking(List), [], no_prev_value).
-
-tied_ordered_ranking(List) when is_list(List) ->
- tied_ordered_ranking(List, tied_ranking(List), []).
-
-tied_ordered_ranking([], [], Work) ->
- lists:reverse(Work);
-
-tied_ordered_ranking([Front|Rem], Ranks, Work) ->
- {value,Item} = lists:keysearch(Front,2,Ranks),
- {IRank,Front} = Item,
- tied_ordered_ranking(Rem, Ranks--[Item], [{IRank,Front}]++Work).
-
-kendall_right_of([], Work) ->
- lists:reverse(Work);
-kendall_right_of([F|R], Work) ->
- kendall_right_of(R, [kendall_right_of_item(F,R)]++Work).
-
-kendall_right_of_item(B, Rem) ->
- length([R || R <- Rem, R < B]).
-
-tied_add_prev(Work, {FoundAt, NewValue}) ->
- lists:duplicate( length(FoundAt), {lists:sum(FoundAt)/length(FoundAt), NewValue} ) ++ Work.
-
-tied_rank_worker([], Work, PrevValue) ->
- lists:reverse(tied_add_prev(Work, PrevValue));
-
-tied_rank_worker([Item|Remainder], Work, PrevValue) ->
- case PrevValue of
- no_prev_value ->
- {BaseRank,BaseVal} = Item,
- tied_rank_worker(Remainder, Work, {[BaseRank],BaseVal});
- {FoundAt,OldVal} ->
- case Item of
- {Id,OldVal} ->
- tied_rank_worker(Remainder, Work, {[Id]++FoundAt,OldVal});
- {Id,NewVal} ->
- tied_rank_worker(Remainder, tied_add_prev(Work, PrevValue), {[Id],NewVal})
-
- end
- end.
