% arg_ia_pairs.pl
%
% This is a synthetic database of
% training data. It defines pairs,
% for fictitious companies, for
% the independent variable, Annual
% Revenue Growth (ARG) and a dependent
% variable Investor Attractiveness (IA).
%
% Exports:
%   arg_ia_pairs( ArgIaPairs- )


/* arg_ia_pairs( ArgIaPairs- ):
     Returns a list of pairs
	 Arg-Ia .
*/
arg_ia_pairs( ArgIaPairs ) :-
  findall( Arg-Ia
         , arg_ia( Arg, Ia )
		 , ArgIaPairs
		 ).

test_arg_ias :-
  arg_ias( Pairs ),
  format( "ARG/IA pairs=~w~n", [Pairs] ).
  

/* arg_ia( Arg, Ia ):
     A company has Annual
	 Revenue Growth Arg and
	 Investor Attractiveness Ia.
*/

% Very low ARG corresponds to very unattractive IA.
arg_ia(-9, 0.2).
arg_ia(-7, 0.7).
arg_ia(-5, 1.0).
arg_ia(-3, 1.3).
arg_ia(-4, 1.1).
arg_ia(-6, 0.8).
arg_ia(-8, 0.4).
arg_ia(-1, 1.7).

% Low ARG corresponds to unattractive IA.
arg_ia(5, 3.0).
arg_ia(15, 3.5).
arg_ia(10, 4.0).
arg_ia(12, 3.8).
arg_ia(7, 3.2).
arg_ia(18, 4.1).
arg_ia(3, 2.7).
arg_ia(11, 3.9).

% Moderate ARG corresponds to neutral IA.
arg_ia(30, 5.0).
arg_ia(60, 5.5).
arg_ia(40, 5.0).
arg_ia(50, 5.3).
arg_ia(35, 5.1).
arg_ia(45, 5.2).
arg_ia(55, 5.4).
arg_ia(25, 4.8).

% High ARG corresponds to attractive IA.
arg_ia(85, 7.0).
arg_ia(90, 8.0).
arg_ia(80, 7.5).
arg_ia(82, 7.3).
arg_ia(87, 7.8).
arg_ia(92, 8.1).
arg_ia(75, 7.1).
arg_ia(78, 7.4).

% Very high ARG corresponds to very attractive IA.
arg_ia(105, 9.0).
arg_ia(110, 9.5).
arg_ia(100, 9.0).
arg_ia(102, 9.2).
arg_ia(108, 9.7).
arg_ia(115, 9.8).
arg_ia(103, 9.3).
arg_ia(109, 9.6).

% Additional samples for more granularity.
arg_ia(20, 4.5).
arg_ia(70, 6.5).
arg_ia(65, 6.0).
arg_ia(23, 4.6).
arg_ia(73, 6.8).
arg_ia(96, 8.5).
arg_ia(98, 8.7).
arg_ia(27, 4.9).
arg_ia(33, 5.1).
arg_ia(57, 5.7).
arg_ia(59, 5.8).
arg_ia(61, 6.1).
arg_ia(64, 6.3).
arg_ia(68, 6.7).
arg_ia(76, 7.2).
arg_ia(79, 7.6).
arg_ia(83, 7.9).
arg_ia(88, 8.2).
arg_ia(94, 8.6).
arg_ia(97, 8.9).
arg_ia(101, 9.1).
arg_ia(104, 9.4).