Adding fastmks tests

src/helper_files/helper.cpp

@@ -33,6 +33,21 @@ float *convertToArray(mat matrix)
 	return convertToArray(vector);
 }
 
+float *convertToArray(arma::Mat< unsigned long > matrix)
+{
+	int vectorSize =  matrix.size();
+
+	// using malloc so the memory is still valid outside of the function
+	float *arr = (float *)malloc (sizeof(float) * vectorSize);
+
+	// save the data in a normal array so it can be send to prolog
+	for(int i = 0; i < vectorSize; i++)
+	{
+		arr[i] = (double)matrix[i];
+	}
+	return arr;
+}
+
 float *convertToArray(vector<size_t> vec)
 {
 	colvec newVec = conv_to<colvec>::from(vec);
@@ -62,7 +77,6 @@ float *convertToArray(vector<vec> matrix)
 		vec c = arma::join_cols(a, b);
 		newVec = c;
 	}
-	cout << newVec << endl;
 	return convertToArray(newVec);
 }
 

src/helper_files/helper.hpp

@@ -13,6 +13,8 @@ float *convertToArray(rowvec vec);
 
 float *convertToArray(mat matrix);
 
+float *convertToArray(arma::Mat< size_t > matrix);
+
 float *convertToArray(vector<size_t> vec);
 
 float *convertToArray(vector<double> vec);

src/methods/fastmks/fastmks.cpp

@@ -18,8 +18,9 @@ using namespace mlpack::kernel;
 
 // Global Variable of the FastMKSModel object so it can be accessed from all functions
 FastMKSModel fastMKSModel;
+bool isModelTrained = false;
+
 
-// TODO: 
 // input:   util::Timers & 	timers,
 //          arma::mat && 	referenceData,
 //          TKernelType & 	kernel,
@@ -32,9 +33,16 @@ FastMKSModel fastMKSModel;
 //          const double 	base
 // output: 
 // description: 
-void initModel(float *referenceMatArr, SP_integer referenceMatSize, SP_integer referenceMatRowNum, char const *kernel, double degree, double offset, double bandwidth, double scale, SP_integer singleMode, SP_integer naive, double base)
+//          Initializes the model on the given reference set.
+//
+void initModel(float *referenceMatArr, SP_integer referenceMatSize, SP_integer referenceMatRowNum, 
+                char const *kernel, 
+                double degree, double offset, double bandwidth, double scale, 
+                SP_integer singleMode, 
+                SP_integer naive, 
+                double base)
 {
-    // convert the Prolog arrays to arma::mat
+    // convert the Prolog array to arma::mat
     mat reference = convertArrayToMat(referenceMatArr, referenceMatSize, referenceMatRowNum);
 
     if (strcmp(kernel, "linear") == 0)        
@@ -42,46 +50,59 @@ void initModel(float *referenceMatArr, SP_integer referenceMatSize, SP_integer r
         fastMKSModel = FastMKSModel(0);
         LinearKernel lk;
         fastMKSModel.BuildModel(move(reference), lk, (singleMode == 1), (naive == 1), base);
+        isModelTrained = true;
     }
     else if (strcmp(kernel, "polynomial") == 0)
     {
         PolynomialKernel pk(degree, offset);
         fastMKSModel.KernelType() = FastMKSModel::POLYNOMIAL_KERNEL;
         fastMKSModel.BuildModel(move(reference), pk, (singleMode == 1), (naive == 1), base);
+        isModelTrained = true;
     }
     else if (strcmp(kernel, "cosine") == 0)
     {
         CosineDistance cd;
         fastMKSModel.KernelType() = FastMKSModel::COSINE_DISTANCE;
         fastMKSModel.BuildModel(move(reference), cd, (singleMode == 1), (naive == 1), base);
+        isModelTrained = true;
     }
     else if (strcmp(kernel, "gaussian") == 0)
     {
         GaussianKernel gk(bandwidth);
         fastMKSModel.KernelType() = FastMKSModel::GAUSSIAN_KERNEL;
         fastMKSModel.BuildModel(move(reference), gk, (singleMode == 1), (naive == 1), base);
+        isModelTrained = true;
     }
     else if (strcmp(kernel, "epanechnikov") == 0)
     {
         EpanechnikovKernel ek(bandwidth);
         fastMKSModel.KernelType() = FastMKSModel::EPANECHNIKOV_KERNEL;
         fastMKSModel.BuildModel(move(reference), ek, (singleMode == 1), (naive == 1), base);
+        isModelTrained = true;
     }
     else if (strcmp(kernel, "triangular") == 0)
     {
         TriangularKernel tk(bandwidth);
         fastMKSModel.KernelType() = FastMKSModel::TRIANGULAR_KERNEL;
         fastMKSModel.BuildModel(move(reference), tk, (singleMode == 1), (naive == 1), base);
+        isModelTrained = true;
     }
     else if (strcmp(kernel, "hyptan") == 0)
     {
+        
         HyperbolicTangentKernel htk(scale, offset);
         fastMKSModel.KernelType() = FastMKSModel::HYPTAN_KERNEL;
         fastMKSModel.BuildModel(move(reference), htk, (singleMode == 1), (naive == 1), base);
+        isModelTrained = true;
     }
+    else
+    {
+        raisePrologDomainExeption(kernel, 2, "The given kernel is unkown!", "initModel");
     }
 
-// TODO: 
+}
+
+
 // input:   util::Timers & 	        timers,
 //          const arma::mat & 	    querySet,
 //          const size_t 	        k,
@@ -90,62 +111,77 @@ void initModel(float *referenceMatArr, SP_integer referenceMatSize, SP_integer r
 //          const double 	        base
 // output: 
 // description: 
-void searchWithQuery(float *querySetMatArr, SP_integer querySetMatSize, SP_integer querySetMatRowNum, SP_integer k, float **indicesMatArr, SP_integer *indicesMatColNum, SP_integer *indicesMatRowNum, float **kernelsMatArr, SP_integer *kernelsMatColNum, SP_integer *kernelsMatRowNum, double base)
+//          Search with a different query set.
+//
+void searchWithQuery(float *querySetMatArr, SP_integer querySetMatSize, SP_integer querySetMatRowNum, 
+                        SP_integer k, 
+                        float **indicesMatArr, SP_integer *indicesMatColNum, SP_integer *indicesMatRowNum, 
+                        float **kernelsMatArr, SP_integer *kernelsMatColNum, SP_integer *kernelsMatRowNum, 
+                        double base)
+{
+    if (!isModelTrained)
     {
-    // convert the Prolog arrays to arma::mat
+        raisePrologSystemExeption("The Model hasnt been trained yet!");
+        return;
+    }
+    
+    // convert the Prolog array to arma::mat
     mat querySet = convertArrayToMat(querySetMatArr, querySetMatSize, querySetMatRowNum);
     
-    // create the ReturnMat
+    // create the ReturnMats
     arma::Mat< size_t > indicesReturnMat;
-
-    // create the ReturnMat
     mat kernelsReturnMat;
 
-    fastMKSModel.Search(querySet, k, indicesReturnMat, kernelsReturnMat, base);
     
-    // return the Matrix dimensions
-    *indicesMatColNum = indicesReturnMat.n_cols;
-    *indicesMatRowNum = indicesReturnMat.n_rows;
-    
-    // return the Matrix as one long Array
-    *indicesMatArr = convertToArray(indicesReturnMat);
+    try
+    {
+        fastMKSModel.Search(querySet, k, indicesReturnMat, kernelsReturnMat, base);
+    }
+    catch(const std::exception& e)
+    {
+        raisePrologSystemExeption(e.what());
+    }
 
-    // return the Matrix dimensions
-    *kernelsMatColNum = kernelsReturnMat.n_cols;
-    *kernelsMatRowNum = kernelsReturnMat.n_rows;
     
-    // return the Matrix as one long Array
-    *kernelsMatArr = convertToArray(kernelsReturnMat);
+    // return the Matrices
+    returnMatrixInformation(indicesReturnMat, indicesMatArr, indicesMatColNum, indicesMatRowNum);
+    returnMatrixInformation(kernelsReturnMat, kernelsMatArr, kernelsMatColNum, kernelsMatRowNum);
 }
 
-// TODO: 
+
 // input:   util::Timers & 	        timers,
 //          const size_t 	        k,
 //          arma::Mat< size_t > & 	indices <-,
 //          arma::mat & 	        kernels <-
 // output: 
 // description: 
-void searchNoQuery(SP_integer k, float **indicesMatArr, SP_integer *indicesMatColNum, SP_integer *indicesMatRowNum, float **kernelsMatArr, SP_integer *kernelsMatColNum, SP_integer *kernelsMatRowNum)
+//          Search with the reference set as the query set.
+//
+void searchNoQuery(SP_integer k, 
+                    float **indicesMatArr, SP_integer *indicesMatColNum, SP_integer *indicesMatRowNum, 
+                    float **kernelsMatArr, SP_integer *kernelsMatColNum, SP_integer *kernelsMatRowNum)
 {
-    // create the ReturnMat
+    if (!isModelTrained)
+    {
+        raisePrologSystemExeption("The Model hasnt been trained yet!");
+        return;
+    }
+    // create the ReturnMats
     arma::Mat< size_t > indicesReturnMat;
+    arma::mat kernelsReturnMat;
     
-    // create the ReturnMat
-    mat kernelsReturnMat;
     
-    fastMKSModel.Search(k, indicesReturnMat, kernelsReturnMat);
-    
-    // return the Matrix dimensions
-    *indicesMatColNum = indicesReturnMat.n_cols;
-    *indicesMatRowNum = indicesReturnMat.n_rows;
-    
-    // return the Matrix as one long Array
-    *indicesMatArr = convertToArray(indicesReturnMat);
+    try
+    {
+        fastMKSModel.Search((size_t)k, indicesReturnMat, kernelsReturnMat);
+    }
+    catch(const std::exception& e)
+    {
+        raisePrologSystemExeption(e.what());
+        return;
+    }
 
-    // return the Matrix dimensions
-    *kernelsMatColNum = kernelsReturnMat.n_cols;
-    *kernelsMatRowNum = kernelsReturnMat.n_rows;
 
-    // return the Matrix as one long Array
-    *kernelsMatArr = convertToArray(kernelsReturnMat);
+    returnMatrixInformation(indicesReturnMat, indicesMatArr, indicesMatColNum, indicesMatRowNum);
+    returnMatrixInformation(kernelsReturnMat, kernelsMatArr, kernelsMatColNum, kernelsMatRowNum);
 }

src/methods/fastmks/fastmks.pl

 
-:- module(fastmks, [    initModel/11,
-                        searchWithQuery/11,
-                        searchNoQuery/7]).
+:- module(fastmks, [    initModel/10,
+                        searchWithQuery/8,
+                        searchNoQuery/5]).
 
 %% requirements of library(struct)
 :- load_files(library(str_decl),
@@ -19,6 +19,11 @@
 %% definitions for the connected function
 
 
+foreign(initModel, c, initModelI(       +pointer(float_array), +integer, +integer, 
+                                        +string, 
+                                        +float32, +float32, +float32, +float32, 
+                                        +integer, +integer, 
+                                        +float32)).
 %% --Input--
 %%              mat     referenceData,
 %%              string  kernel          "linear", "polynomial", "cosine", "gaussian", "epanechnikov", "triangular", "hyptan"
@@ -35,13 +40,19 @@
 %% --Description--
 %%              Initializes the model on the given reference set.
 %%
-foreign(initModel, c, initModel(+pointer(float_array), +integer, +integer, 
-                                +string, 
-                                +float32, +float32, +float32, +float32, 
-                                +integer, +integer, 
-                                +float32)).
+initModel(DataList, DataRows, Kernel, Degree, Offset, Bandwidth, Scale, SingleMode, Naive, Base) :-
+        Base > 1.0,
+        Bandwidth > 0.0,
+        convert_list_to_float_array(DataList, DataRows, array(Xsize, Xrows, X)),
+        initModelI(X, Xsize, Xrows, Kernel, Degree, Offset, Bandwidth, Scale, SingleMode, Naive, Base).
+
 
 
+foreign(searchWithQuery, c, searchWithQueryI(   +pointer(float_array), +integer, +integer, 
+                                                +integer, 
+                                                -pointer(float_array), -integer, -integer, 
+                                                -pointer(float_array), -integer, -integer, 
+                                                +float32)).
 %% --Input--
 %%              mat     querySet,
 %%              int     k,
@@ -54,13 +65,19 @@ foreign(initModel, c, initModel(+pointer(float_array), +integer, +integer,
 %% --Description--
 %%              Search with a different query set.
 %%
-foreign(searchWithQuery, c, searchWithQuery(    +pointer(float_array), +integer, +integer, 
-                                                +integer, 
-                                                -pointer(float_array), -integer, -integer, 
-                                                -pointer(float_array), -integer, -integer, 
-                                                +float32)).
+searchWithQuery(DataList, DataRows, K, IndicesList, YCols, KernelsList, ZCols, Base) :-
+        K > 0,
+        Base > 1.0,
+        convert_list_to_float_array(DataList, DataRows, array(Xsize, Xrows, X)),
+        searchWithQueryI(X, Xsize, Xrows, K, Y, YCols, YRows, Z, ZCols, ZRows, Base),
+        convert_float_array_to_2d_list(Y, YCols, YRows, IndicesList),
+        convert_float_array_to_2d_list(Z, ZCols, ZRows, KernelsList).
+
 
 
+foreign(searchNoQuery, c, searchNoQueryI(       +integer, 
+                                                -pointer(float_array), -integer, -integer, 
+                                                -pointer(float_array), -integer, -integer)).
 %% --Input--
 %%              int     k
 %%
@@ -71,9 +88,11 @@ foreign(searchWithQuery, c, searchWithQuery(    +pointer(float_array), +integer,
 %% --Description--
 %%              Search with the reference set as the query set.
 %%
-foreign(searchNoQuery, c, searchNoQuery(+integer, 
-                                        -pointer(float_array), -integer, -integer, 
-                                        -pointer(float_array), -integer, -integer)).
+searchNoQuery(K, IndicesList, YCols, KernelsList, ZCols) :-
+        K > 0,
+        searchNoQueryI(K, Y, YCols, YRows, Z, ZCols, ZRows),
+        convert_float_array_to_2d_list(Y, YCols, YRows, IndicesList),
+        convert_float_array_to_2d_list(Z, ZCols, ZRows, KernelsList).
 
 
 %% Defines the functions that get connected from main.cpp
@@ -81,4 +100,5 @@ foreign_resource(fastmks, [     initModel,
                                 searchWithQuery,
                                 searchNoQuery]).
 
+
 :- load_foreign_resource(fastmks).

src/methods/fastmks/fastmks_test.pl

+
+:- module(fastmks_tests, [run_fastmks_tests/0]).
+
 :- use_module(library(plunit)).
 
 :- use_module(fastmks).
 :- use_module('../../helper_files/helper.pl').
 
 reset_Model :-
-        initModel(1,0,50,0.0001).
+        open('/home/afkjakhes/eclipse-workspace/prolog-mlpack-libary/src/data_csv/iris2.csv', read, File),
+        take_csv_row(File, skipFirstRow,10, Data),
+        initModel(Data, 4, linear, 0.0, 0.0, 1.0, 0.0, 0, 0, 1.2).
 
-:- 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) :-
+%%
+%% TESTING predicate initModel/10
+%%
+:- begin_tests(initModel).      
+
+%% Failure Tests
+
+test(searchWithQuery_Fastmks_Search_Before_Init, [error(_,system_error('The Model hasnt been trained yet!'))]) :-
+        open('/home/afkjakhes/eclipse-workspace/prolog-mlpack-libary/src/data_csv/iris2.csv', read, File),
+        take_csv_row(File, skipFirstRow,5, Data),
+        searchWithQuery(Data, 4, 2, _, _, _, _, 1.1).
+
+test(searchNoQuery_Fastmks_Search_Before_Init, [error(_,system_error('The Model hasnt been trained yet!'))]) :-
+        searchNoQuery(2, _, _, _, _).
+                                            
+test(initModel_Fatsmks_WrongKernel_Input, [error(domain_error('The given kernel is unkown!' , wrongKernel), _)]) :-
+        initModel([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, wrongKernel, 0.0, 0.0, 1.0, 0.0, 0, 0, 1.2).
+
+test(initModel_Fatsmks_Bad_Base_Input, fail) :-
+        initModel([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, linear, 0.0, 0.0, 1.0, 0.0, 0, 0, -0.1).
+        
+
+%% Successful Tests
+
+test(iniModel_Fastmks_Linear) :-
+        open('/home/afkjakhes/eclipse-workspace/prolog-mlpack-libary/src/data_csv/iris2.csv', read, File),
+        take_csv_row(File, skipFirstRow,10, Data),
+        initModel(Data, 4, linear, 0.0, 0.0, 1.0, 0.0, 0, 0, 1.5).
+
+test(iniModel_Fastmks_Polynomial) :-
+        open('/home/afkjakhes/eclipse-workspace/prolog-mlpack-libary/src/data_csv/iris2.csv', read, File),
+        take_csv_row(File, skipFirstRow,10, Data),
+        initModel(Data, 4, polynomial, 0.0, 0.0, 1.0, 0.0, 0, 0, 1.5).
+
+test(iniModel_Fastmks_Cosine) :-
+        open('/home/afkjakhes/eclipse-workspace/prolog-mlpack-libary/src/data_csv/iris2.csv', read, File),
+        take_csv_row(File, skipFirstRow,10, Data),
+        initModel(Data, 4, cosine, 0.0, 0.0, 1.0, 0.0, 0, 0, 1.5).
+
+test(iniModel_Fastmks_Gaussian) :-
+        open('/home/afkjakhes/eclipse-workspace/prolog-mlpack-libary/src/data_csv/iris2.csv', read, File),
+        take_csv_row(File, skipFirstRow,10, Data),
+        initModel(Data, 4, gaussian, 0.5, 0.5, 0.5, 0.5, 0, 0, 1.5).
+
+test(iniModel_Fastmks_Epanechnikov) :-
+        open('/home/afkjakhes/eclipse-workspace/prolog-mlpack-libary/src/data_csv/iris2.csv', read, File),
+        take_csv_row(File, skipFirstRow,10, Data),
+        initModel(Data, 4, epanechnikov, 0.0, 0.0, 1.0, 0.0, 0, 0, 1.5).
+
+test(iniModel_Fastmks_Triangular) :-
+        open('/home/afkjakhes/eclipse-workspace/prolog-mlpack-libary/src/data_csv/iris2.csv', read, File),
+        take_csv_row(File, skipFirstRow,10, Data),
+        initModel(Data, 4, triangular, 0.0, 0.0, 1.0, 0.0, 0, 0, 1.5).
+
+test(iniModel_Fastmks_Hyptan) :-
+        open('/home/afkjakhes/eclipse-workspace/prolog-mlpack-libary/src/data_csv/iris2.csv', read, File),
+        take_csv_row(File, skipFirstRow,10, Data),
+        initModel(Data, 4, hyptan, 0.0, 0.0, 1.0, 1.0, 0, 0, 1.5).
+
+:- end_tests(initModel).
+
+
+%%
+%% TESTING predicate searchWithQuery/8
+%%
+:- begin_tests(searchWithQuery).      
+
+%% Failure Tests
+                                            
+test(searchWithQuery_Fastmks_Negative_K, fail) :-
         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).
+        open('/home/afkjakhes/eclipse-workspace/prolog-mlpack-libary/src/data_csv/iris2.csv', read, File),
+        take_csv_row(File, skipFirstRow,5, Data),
+        searchWithQuery(Data, 4, -2, _, _, _, _, 1.1).
 
-%% train tests
-test(correct_train) :-
+test(searchWithQuery_Fastmks_Negative_Base, fail) :-
         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) :-
+        open('/home/afkjakhes/eclipse-workspace/prolog-mlpack-libary/src/data_csv/iris2.csv', read, File),
+        take_csv_row(File, skipFirstRow,5, Data),
+        searchWithQuery(Data, 4, 2, _, _, _, _, -1.1).
+        
+
+%% Successful Tests
+
+test(searchWithQuery_Fastmks_New_Query) :-
         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) :-
+        searchWithQuery([3, 2, 0, 5, 1, 4, 0, 0, 4, 3, 3, 5, 0, 5, 5, 2, 5, 5, 0, 2], 4, 2, IndicesList, _, KernelsList, _, 1.1),
+        print('Indices:\n'),
+        print(IndicesList),
+        print('Kernels:\n'),
+        print(KernelsList).
+
+test(searchWithQuery_Fastmks_Training_Data_Query) :-
         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) :-
+        open('/home/afkjakhes/eclipse-workspace/prolog-mlpack-libary/src/data_csv/iris2.csv', read, File),
+        take_csv_row(File, skipFirstRow,5, Data),
+        searchWithQuery(Data, 4, 2, IndicesList, _, KernelsList, _, 1.1),
+        print('Indices:\n'),
+        print(IndicesList),
+        print('Kernels:\n'),
+        print(KernelsList).
+
+:- end_tests(searchWithQuery).
+
+
+%%
+%% TESTING predicate searchNoQuery/5
+%%
+:- begin_tests(searchNoQuery).      
+
+%% Failure Tests
+                                            
+test(searchNoQuery_Fastmks_Negative_K, 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) :-
+        searchNoQuery(-2, _, _, _, _).
+        
+
+%% Successful Tests
+
+test(testDescription) :-
         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) :-
+        searchNoQuery(2, IndicesList, _, KernelsList, _),
+        print('Indices:\n'),
+        print(IndicesList),
+        print('Kernels:\n'),
+        print(KernelsList).
+
+test(testDescription) :-
         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).
+        searchNoQuery(5, IndicesList, _, KernelsList, _),
+        print('Indices:\n'),
+        print(IndicesList),
+        print('Kernels:\n'),
\ No newline at end of file
+        print(KernelsList).
+
+:- end_tests(searchNoQuery).
+
+run_fastmks_tests :-
+        run_tests.
+

test_all.pl

@@ -6,6 +6,10 @@
 
 :- use_module('src/methods/decision_tree/decision_tree_test.pl').
 
+:- use_module('src/methods/emst/emst_test.pl').
+
+:- use_module('src/methods/fastmks/fastmks_test.pl').
+
 :- use_module('src/methods/sparse_coding/sparse_coding_test.pl').
 
 :- use_module('src/helper_files/helper_tests.pl').
@@ -14,5 +18,7 @@ run :-
         run_adaboost_tests,
         run_dbscan_tests,
         run_decision_tree_tests,
+        run_emst_tests,
+        run_fastmks_tests,
         run_sparse_coding_tests,
         run_helper_tests.
\ No newline at end of file