Adding emst

Makefile

@@ -5,6 +5,7 @@ all:
 	make -C src/methods/ada_boost splfr=$(SPLFR_PATH)
 	make -C src/methods/bayesian_linear_regression splfr=$(SPLFR_PATH)
 	make -C src/methods/dbscan splfr=$(SPLFR_PATH)
+	make -C src/methods/emst splfr=$(SPLFR_PATH)
 	make -C src/methods/kmeans splfr=$(SPLFR_PATH)
 	make -C src/methods/lars splfr=$(SPLFR_PATH)
 	make -C src/methods/linear_regression splfr=$(SPLFR_PATH)
@@ -20,6 +21,7 @@ clean:
 	make -C src/methods/ada_boost clean
 	make -C src/methods/bayesian_linear_regression clean
 	make -C src/methods/dbscan clean
+	make -C src/methods/emst clean
 	make -C src/methods/kmeans clean
 	make -C src/methods/lars clean
 	make -C src/methods/linear_regression clean

src/methods/emst/Makefile

+splfr=/usr/local/sicstus4.7.1/bin/splfr
+
+METHOD_NAME=emst
+
+$(METHOD_NAME).so: $(METHOD_NAME).pl $(METHOD_NAME).cpp
+	$(splfr) -larmadillo -fopenmp -lmlpack -lstdc++ -cxx --struct $(METHOD_NAME).pl $(METHOD_NAME).cpp ../../helper_files/helper.cpp
+clean:
+	rm $(METHOD_NAME).so

src/methods/emst/emst.cpp

+#include <sicstus/sicstus.h>
+/* ex_glue.h is generated by splfr from the foreign/[2,3] facts.
+   Always include the glue header in your foreign resource code.
+*/
+#include "emst_glue.h"
+#include <mlpack/methods/emst/dtb.hpp>
+#include <mlpack/core.hpp>
+
+// including helper functions for converting between arma structures and arrays
+#include "../../helper_files/helper.hpp"
+
+// 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: 
+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;
+
+    DualTreeBoruvka(data, (naive == 1)).ComputeMST(resultsReturnMat);
+    
+    // return the Matrix dimensions
+    *resultsMatColNum = resultsReturnMat.n_cols;
+    *resultsMatRowNum = resultsReturnMat.n_rows;
+    
+    // return the Matrix as one long Array
+    *resultsMatArr = convertToArray(resultsReturnMat);
+}
\ No newline at end of file

src/methods/emst/emst.pl

+:- module(emst, [emst/7]).
+
+%% requirements of library(struct)
+:- load_files(library(str_decl),
+        [when(compile_time), if(changed)]).
+
+%% needed for using the array type
+:- use_module(library(structs)).
+:- use_module('../../helper_files/helper.pl').
+
+%% type definitions for the float array
+:- foreign_type
+        float32          = float_32,
+        float_array      = array(float32).
+
+%% definitions for the connected function
+
+%% TODO: 
+%% --Input--
+%%
+%% --Output--
+%%
+%% --Description--
+foreign(emst, c, emst(+pointer(float_array), +integer, +integer, +integer, -pointer(float_array), -integer, -integer)).
+
+
+
+%% +integer , +float32, +string
+%% [-integer] , [-float32], [-string]
+
+%% matrix input
+%% +pointer(float_array), +integer, +integer
+
+%% array input
+%% +pointer(float_array), +integer
+
+%% matrix return
+%% -pointer(float_array), -integer, -integer
+
+%% array return
+%% -pointer(float_array), -integer
+
+%% Defines the functions that get connected from main.cpp
+foreign_resource(emst, [emst]).
+
+:- load_foreign_resource(emst).
\ No newline at end of file

src/methods/emst/emst_test.pl

+:- 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