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Commit 049c620f authored by Jakhes's avatar Jakhes
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Adding emst tests

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src/methods/emst/emst.cpp
+ 16
− 11
View file @ 049c620f
......@@ -12,31 +12,36 @@
// some of the most used namespaces
using namespace arma;
using namespace mlpack;
using namespace std;
using namespace mlpack::emst;
// TODO:
// input: const MatType & dataset,
// const bool naive = false,
// const MetricType metric = MetricType(),
// arma::mat & results <-
// output:
// description:
// Performs the MST calculation using the Dual-Tree Boruvka algorithm.
//
void emst(float *dataMatArr, SP_integer dataMatSize, SP_integer dataMatRowNum, SP_integer naive, float **resultsMatArr, SP_integer *resultsMatColNum, SP_integer *resultsMatRowNum)
{
// convert the Prolog arrays to arma::mat
mat data = convertArrayToMat(dataMatArr, dataMatSize, dataMatRowNum);
// create the ReturnMat
mat resultsReturnMat;
try
{
DualTreeBoruvka(data, (naive == 1)).ComputeMST(resultsReturnMat);
}
catch(const std::exception& e)
{
raisePrologSystemExeption(e.what());
}
// return the Matrix dimensions
*resultsMatColNum = resultsReturnMat.n_cols;
*resultsMatRowNum = resultsReturnMat.n_rows;
// return the Matrix as one long Array
*resultsMatArr = convertToArray(resultsReturnMat);
// return the Matrix
returnMatrixInformation(resultsReturnMat, resultsMatArr, resultsMatColNum, resultsMatRowNum);
}
\ No newline at end of file
src/methods/emst/emst.pl
+ 9
− 5
View file @ 049c620f
:- module(emst, [emst/7]).
:- module(emst, [emst/5]).
%% requirements of library(struct)
:- load_files(library(str_decl),
......@@ -16,7 +16,10 @@
%% definitions for the connected function
%% TODO:
foreign(emst, c, emstI( +pointer(float_array), +integer, +integer,
+integer,
-pointer(float_array), -integer, -integer)).
%% --Input--
%% mat dataset,
%% bool naive => (1)true / (0)false
......@@ -27,9 +30,10 @@
%% --Description--
%% Performs the MST calculation using the Dual-Tree Boruvka algorithm.
%%
foreign(emst, c, emst( +pointer(float_array), +integer, +integer,
+integer,
-pointer(float_array), -integer, -integer)).
emst(DataList, DataRows, Naive, ResultsList, YCols) :-
convert_list_to_float_array(DataList, DataRows, array(Xsize, Xrows, X)),
emstI(X, Xsize, Xrows, Naive, Y, YCols, YRows),
convert_float_array_to_2d_list(Y, YCols, YRows, ResultsList).
%% Defines the functions that get connected from main.cpp
......
src/methods/emst/emst_test.pl
+ 48
− 51
View file @ 049c620f
:- module(emst_tests, [run_emst_tests/0]).
:- use_module(library(plunit)).
:- use_module(emst).
:- use_module('../../helper_files/helper.pl').
reset_Model :-
initModel(1,0,50,0.0001).
:- begin_tests(lists).
%% alpha tests
test(alpha_std_init) :-
reset_Model,
alpha(0).
test(alpha_wrong_input, fail) :-
reset_Model,
alpha(1).
test(alpha_after_train, A =:= 9223372036854775808) :-
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)),
train(X,Xsize, Xrownum,Y, Ysize),
alpha(A).
%% train tests
test(correct_train) :-
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)),
train(X,Xsize, Xrownum,Y, Ysize).
test(false_train, fail) :-
reset_Model,
convert_list_to_float_array([],3, array(Xsize, Xrownum, X)),
convert_list_to_float_array([0.2,0.2,0.2,0.2], array(Ysize, Y)),
train(X,Xsize, Xrownum,Y, Ysize).
test(false_train2, fail) :-
reset_Model,
convert_list_to_float_array([],0, array(Xsize, Xrownum, X)),
convert_list_to_float_array([0.2,0.2,0.2,0.2], array(Ysize, Y)),
train(X,Xsize, Xrownum,Y, Ysize).
test(false_train3, fail) :-
reset_Model,
convert_list_to_float_array([1,2],0, array(Xsize, Xrownum, X)),
convert_list_to_float_array([0.2,0.2,0.2,0.2], array(Ysize, Y)),
train(X,Xsize, Xrownum,Y, Ysize).
test(false_train3, fail) :-
reset_Model,
convert_list_to_float_array([1,2,44,3],3, array(Xsize, Xrownum, X)),
convert_list_to_float_array([0.2,0.2,0.2,0.2], array(Ysize, Y)),
train(X,Xsize, Xrownum,Y, Ysize).
test(false_train4) :-
reset_Model,
convert_list_to_float_array([1,2,44,3],2, array(Xsize, Xrownum, X)),
convert_list_to_float_array([0.2,0.2,0.2,0.2], array(Ysize, Y)),
train(X,Xsize, Xrownum,Y, Ysize).
:- end_tests(lists).
\ No newline at end of file
%%
%% TESTING predicate emst/5
%%
:- begin_tests(emst).
%% Failure Tests
%% Successful Tests
test(emst_Direkt_Input_Use) :-
emst([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, 0, ResultsList, _),
print(ResultsList),
emst([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, 0, [[2.0,3.0,0.24494902789592743],
[1.0,2.0,0.30000022053718567],
[0.0,2.0,0.5099020004272461]], _).
test(emst_Direkt_Input_Use_Naive) :-
emst([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, 1, ResultsList, _),
print(ResultsList),
emst([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, 1, [[2.0,3.0,0.24494902789592743],
[1.0,2.0,0.30000022053718567],
[0.0,2.0,0.5099020004272461]], _).
test(emst_CSV_Input_Use) :-
open('/home/afkjakhes/eclipse-workspace/prolog-mlpack-libary/src/data_csv/iris2.csv', read, File),
take_csv_row(File, skipFirstRow,10, Data),
emst(Data, 4, 0, ResultsList, _),
print(ResultsList),
emst(Data, 4, 0, [[0.0,4.0,0.14142122864723206],
[0.0,7.0,0.17320498824119568],
[1.0,9.0,0.17320503294467926],
[2.0,3.0,0.24494902789592743],
[2.0,6.0,0.26457515358924866],
[3.0,8.0,0.29999974370002747],
[1.0,2.0,0.30000022053718567],
[7.0,9.0,0.3316626250743866],
[0.0,5.0,0.6164416074752808]], _).
:- end_tests(emst).
run_emst_tests :-
run_tests.
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