lars_test.pl

:- use_module(library(plunit)).
:- use_module(library(structs)).

:- use_module(lars).
:- use_module('../../helper_files/helper.pl').

reset_Model :-
        initModelNoDataNoGram(1, 0.1, 0.3, 0.001),
        convert_list_to_float_array([5.1,3.5,1.4,4.9,3.0,1.4,4.7,3.2,1.3,4.6,3.1,1.5],3, array(Xsize, Xrownum, X)),
        convert_list_to_float_array([0.2,0.2,0.2,0.2], array(Ysize, Y)),
        trainNoBetaReturn(X,Xsize, Xrownum,Y, Ysize, 1, _).

:- begin_tests(lists).


%% train tests
test(train, [true(A =:= 0)]) :-
        reset_Model,
        convert_list_to_float_array([5.1,3.5,1.4,4.9,3.0,1.4,4.7,3.2,1.3,4.6,3.1,1.5],3, array(Xsize, Xrownum, X)),
        convert_list_to_float_array([0.2,0.2,0.2,0.2], array(Ysize, Y)),
        trainNoBetaReturn(X,Xsize, Xrownum,Y, Ysize, 1, A),
        predict(X, Xsize,Xrownum, Predic, PredicSize,0),
        convert_float_array_to_list(Predic, PredicSize, Result),
        print(Result).

test(activeSet) :-
        reset_Model,
        activeSet(ActSet, ActSetSize),
        convert_float_array_to_list(ActSet, ActSetSize, Result),
        print(Result).

test(matUtriCholFactor) :-
        reset_Model,
        matUtriCholFactor(Matrix, MatrixColNum, MatrixRowNum),
        print(MatrixColNum),
        convert_float_array_to_2d_list(Matrix, MatrixColNum, MatrixRowNum, Results),
        print(Results).

test(betaPath) :-
        reset_Model,
        betaPath(Matrix, MatrixColNum, MatrixRowNum),
        print(MatrixColNum),
        convert_float_array_to_2d_list(Matrix, MatrixColNum, MatrixRowNum, Results),
        print(Results).


:- end_tests(lists).