Adding pca

src/methods/pca/Makefile

+splfr=/usr/local/sicstus4.7.1/bin/splfr
+
+METHOD_NAME=pca
+
+$(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/pca/pca.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 "pca_glue.h"
+#include <mlpack/methods/pca/pca.hpp>
+#include <mlpack/core.hpp>
+
+#include <mlpack/methods/pca/decomposition_policies/randomized_svd_method.hpp>
+#include <mlpack/methods/pca/decomposition_policies/randomized_block_krylov_method.hpp>
+#include <mlpack/methods/pca/decomposition_policies/quic_svd_method.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::pca;
+
+
+// TODO: 
+// input:   const bool 	                    scaleData = false,
+//          const DecompositionPolicy & 	decomposition = DecompositionPolicy(),
+//          const arma::mat & 	            data,
+//          arma::mat & 	                transformedData,
+//          arma::vec & 	                eigVal,
+//          arma::mat & 	                eigvec
+// output: 
+// description: 
+void pca(SP_integer scaleData, char const *decompositionPolicy,
+            float *dataMatArr, SP_integer dataMatSize, SP_integer dataMatRowNum,
+            float **transformedMatArr, SP_integer *transformedMatColNum, SP_integer *transformedMatRowNum,
+            float **eigValArr, SP_integer *eigValArrSize,
+            float **eigVecMatArr, SP_integer *eigVecMatColNum, SP_integer *eigVecMatRowNum)
+{
+    // convert the Prolog arrays to arma::mat
+    mat data = convertArrayToMat(dataMatArr, dataMatSize, dataMatRowNum);
+
+    // create the ReturnMat
+    mat transformedReturnMat;
+
+    // create the ReturnVector
+    vec eigValReturnVector;
+
+    // create the ReturnMat
+    mat eigVecReturnMat;
+
+    // decide for the decomposition Policy
+    if (strcmp(decompositionPolicy, "exact") == 0)
+    {
+        PCA<ExactSVDPolicy>((scaleData == 1)).Apply(data, transformedReturnMat, eigValReturnVector, eigVecReturnMat);
+    }
+    else if (strcmp(decompositionPolicy, "randomized") == 0)
+    {
+        PCA<RandomizedSVDPolicy>((scaleData == 1)).Apply(data, transformedReturnMat, eigValReturnVector, eigVecReturnMat);
+    }
+    else if (strcmp(decompositionPolicy, "randomized-block-krylov") == 0)
+    {
+        PCA<RandomizedBlockKrylovSVDPolicy>((scaleData == 1)).Apply(data, transformedReturnMat, eigValReturnVector, eigVecReturnMat);
+    }
+    else if (strcmp(decompositionPolicy, "quic") == 0)
+    {
+        PCA<QUICSVDPolicy>((scaleData == 1)).Apply(data, transformedReturnMat, eigValReturnVector, eigVecReturnMat);
+    }
+    else
+    {
+        cout << "wrong decompositionPolicy input" << endl;
+    }
+
+    // return the Matrix
+    returnMatrixInformation(transformedReturnMat, transformedMatArr, transformedMatColNum, transformedMatRowNum);
+    
+    // return the Vector
+    returnVectorInformation(eigValReturnVector, eigValArr, eigValArrSize);
+    
+    // return the Matrix
+    returnMatrixInformation(eigVecReturnMat, eigVecMatArr, eigVecMatColNum, eigVecMatRowNum);
+}
+
+// TODO: 
+// input:   const bool 	                    scaleData = false,
+//          const DecompositionPolicy & 	decomposition = DecompositionPolicy(),
+//          arma::mat & 	                data,
+//          const size_t 	                newDimension 
+// output: 
+// description: 
+double pcaDimReduction(SP_integer scaleData, char const *decompositionPolicy,
+                        float *dataMatArr, SP_integer dataMatSize, SP_integer dataMatRowNum,
+                        SP_integer newDimension,
+                        float **transformedMatArr, SP_integer *transformedMatColNum, SP_integer *transformedMatRowNum)
+{
+    // convert the Prolog arrays to arma::mat
+    mat data = convertArrayToMat(dataMatArr, dataMatSize, dataMatRowNum);
+
+    double returnValue;
+
+    // decide for the decomposition Policy
+    if (strcmp(decompositionPolicy, "exact") == 0)
+    {
+        returnValue = PCA<ExactSVDPolicy>((scaleData == 1)).Apply(data, (size_t)newDimension);
+    }
+    else if (strcmp(decompositionPolicy, "randomized") == 0)
+    {
+        returnValue = PCA<RandomizedSVDPolicy>((scaleData == 1)).Apply(data, (size_t)newDimension);
+    }
+    else if (strcmp(decompositionPolicy, "randomized-block-krylov") == 0)
+    {
+        returnValue = PCA<RandomizedBlockKrylovSVDPolicy>((scaleData == 1)).Apply(data, (size_t)newDimension);
+    }
+    else if (strcmp(decompositionPolicy, "quic") == 0)
+    {
+        returnValue = PCA<QUICSVDPolicy>((scaleData == 1)).Apply(data, (size_t)newDimension);
+    }
+    else
+    {
+        cout << "wrong decompositionPolicy input" << endl;
+        returnValue = -1.0;
+    }
+
+    // return the Matrix
+    returnMatrixInformation(data, transformedMatArr, transformedMatColNum, transformedMatRowNum);
+
+    return returnValue;
+}
+
+// TODO: 
+// input:   const bool 	                    scaleData = false,
+//          const DecompositionPolicy & 	decomposition = DecompositionPolicy(),
+//          arma::mat & 	                data,
+//          const double 	                varRetained 
+// output: 
+// description: 
+double pcaVarianceDimReduction(SP_integer scaleData, char const *decompositionPolicy,
+                                float *dataMatArr, SP_integer dataMatSize, SP_integer dataMatRowNum,
+                                double varRetained,
+                                float **transformedMatArr, SP_integer *transformedMatColNum, SP_integer *transformedMatRowNum)
+{
+    // convert the Prolog arrays to arma::mat
+    mat data = convertArrayToMat(dataMatArr, dataMatSize, dataMatRowNum);
+
+    double returnValue;
+
+    // decide for the decomposition Policy
+    if (strcmp(decompositionPolicy, "exact") == 0)
+    {
+        returnValue = PCA<ExactSVDPolicy>((scaleData == 1)).Apply(data, varRetained);
+    }
+    else if (strcmp(decompositionPolicy, "randomized") == 0)
+    {
+        returnValue = PCA<RandomizedSVDPolicy>((scaleData == 1)).Apply(data, varRetained);
+    }
+    else if (strcmp(decompositionPolicy, "randomized-block-krylov") == 0)
+    {
+        returnValue = PCA<RandomizedBlockKrylovSVDPolicy>((scaleData == 1)).Apply(data, varRetained);
+    }
+    else if (strcmp(decompositionPolicy, "quic") == 0)
+    {
+        returnValue = PCA<QUICSVDPolicy>((scaleData == 1)).Apply(data, varRetained);
+    }
+    else
+    {
+        cout << "wrong decompositionPolicy input" << endl;
+        returnValue = -1.0;
+    }
+
+    // return the Matrix
+    returnMatrixInformation(data, transformedMatArr, transformedMatColNum, transformedMatRowNum);
+
+    return returnValue;
+}
\ No newline at end of file

src/methods/pca/pca.pl

+:- module(pca, [pca/13,
+                pcaDimReduction/10,
+                pcaVarianceDimReduction/10]).
+
+%% 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--
+%%              bool    scaleData                    => (1)true / (0)false,
+%%              string  decompositionPolicy     "exact", "randomized", "randomized-block-krylov", "quic",
+%%              mat     data,
+%%
+%% --Output--
+%%              mat     transformedData,
+%%              vec     eigValues,
+%%              mat     eigVectors
+%%
+%% --Description--
+foreign(pca, c, pca(    +integer, +string,
+                        +pointer(float_array), +integer, +integer,
+                        -pointer(float_array), -integer, -integer,
+                        -pointer(float_array), -integer,
+                        -pointer(float_array), -integer, -integer)).
+
+%% TODO: 
+%% --Input--
+%%              bool    scaleData               => (1)true / (0)false,
+%%              string  decompositionPolicy     "exact", "randomized", "randomized-block-krylov", "quic",
+%%              mat     data,
+%%              int     newDimension
+%%
+%% --Output--
+%%              mat     transformedData,
+%%              float32 Amount of Variance retained => [0,1]
+%%
+%% --Description--
+foreign(pcaDimReduction, c, pcaDimReduction(    +integer, +string,
+                                                +pointer(float_array), +integer, +integer,
+                                                +integer,
+                                                -pointer(float_array), -integer, -integer,
+                                                [-float32])).
+
+%% TODO: 
+%% --Input--
+%%              bool    scaleData               => (1)true / (0)false,
+%%              string  decompositionPolicy     "exact", "randomized", "randomized-block-krylov", "quic",
+%%              mat     data,
+%%              float32 varRetained             => [0,1]
+%%
+%% --Output--
+%%              mat     transformedData,
+%%              float32 Amount of Variance retained => [0,1]
+%%
+%% --Description--
+foreign(pcaVarianceDimReduction, c, pcaVarianceDimReduction(    +integer, +string,
+                                                                +pointer(float_array), +integer, +integer,
+                                                                +float32,
+                                                                -pointer(float_array), -integer, -integer,
+                                                                [-float32])).
+
+
+%% Defines the functions that get connected from main.cpp
+foreign_resource(pca, [ pca,
+                        pcaDimReduction,
+                        pcaVarianceDimReduction]).
+
+:- load_foreign_resource(pca).
\ No newline at end of file

src/methods/pca/pca_test.pl

+:- use_module(library(plunit)).
+
+:- use_module(pca).
+:- 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