Fix #18 and for cran

Author: root

inst/include/RcppMLPACK.h

@@ -1,14 +1,7 @@
 #ifndef RcppMLPACK__RcppMLPACK__h
 #define RcppMLPACK__RcppMLPACK__h
 
-#if _WIN64
-#ifndef ARMA_64BIT_WORD
-#define ARMA_64BIT_WORD
-#endif
-#endif
-
 #include <mlpack/core.hpp>
-
 #include <mlpack/core/kernels/cosine_distance.hpp>
 #include <mlpack/core/kernels/epanechnikov_kernel.hpp>
 #include <mlpack/core/kernels/gaussian_kernel.hpp>
@@ -66,10 +59,10 @@
 #include <mlpack/methods/lsh/lsh_search.hpp>
 #include <mlpack/methods/local_coordinate_coding/lcc.hpp>
 #include <mlpack/methods/mvu/mvu.hpp>
-//#include <mlpack/methods/naive_bayes/naive_bayes_classifier.hpp>
 #include <mlpack/methods/nca/nca.hpp>
 #include <mlpack/methods/neighbor_search/neighbor_search.hpp>
 #include <mlpack/methods/neighbor_search/unmap.hpp>
+#include <mlpack/methods/neighbor_search/typedef.hpp>
 #include <mlpack/methods/nystroem_method/ordered_selection.hpp>
 #include <mlpack/methods/nystroem_method/random_selection.hpp>
 #include <mlpack/methods/nystroem_method/kmeans_selection.hpp>

man/mlKmeans.Rd

@@ -24,8 +24,6 @@ mlKmeans(X, y)
   For MLPACK: Ryan Curtin
 }
 \examples{
-\dontrun{
   data(trees, package="datasets")
   mlKmeans(t(trees),3)
 }
-}

src/RcppExports.cpp

@@ -4,18 +4,14 @@
 using namespace Rcpp;
 
 // kmeans
-List kmeans(const arma::mat& data, const int& clusters);
+List kmeans(SEXP data, const int& clusters);
 RcppExport SEXP RcppMLPACK_kmeans(SEXP dataSEXP, SEXP clustersSEXP) {
 BEGIN_RCPP
-    SEXP __sexp_result;
-    {
-        Rcpp::RNGScope __rngScope;
-        Rcpp::traits::input_parameter< const arma::mat& >::type data(dataSEXP );
-        Rcpp::traits::input_parameter< const int& >::type clusters(clustersSEXP );
-        List __result = kmeans(data, clusters);
-        PROTECT(__sexp_result = Rcpp::wrap(__result));
-    }
-    UNPROTECT(1);
-    return __sexp_result;
+  Rcpp::RObject rcpp_result_gen;
+  Rcpp::RNGScope rcpp_rngScope_gen;
+  Rcpp::traits::input_parameter< SEXP >::type data(dataSEXP);
+  Rcpp::traits::input_parameter< const int& >::type clusters(clustersSEXP);
+  rcpp_result_gen = Rcpp::wrap(kmeans(data, clusters));
+  return rcpp_result_gen;
 END_RCPP
 }

src/RcppMLPACK.h

@@ -1,16 +1,6 @@
 #ifndef RcppMLPACK__RcppMLPACK__h
 #define RcppMLPACK__RcppMLPACK__h
 
-#if _WIN64
-#ifndef ARMA_64BIT_WORD
-#define ARMA_64BIT_WORD
-#endif
-#endif
-
-#if defined(__MINGW32__)
-#define ARMA_DONT_USE_CXX11
-#endif
-
 #include <mlpack/core.hpp>
 #include <mlpack/core/kernels/cosine_distance.hpp>
 #include <mlpack/core/kernels/epanechnikov_kernel.hpp>

src/kmeans.cpp

@@ -4,15 +4,17 @@ using namespace mlpack::kmeans;
 using namespace Rcpp;
 
 // [[Rcpp::export]]
-List kmeans(const arma::mat& data, const int& clusters) {
-    
-    arma::Col<size_t> assignments;
+List kmeans(SEXP data, const int& clusters) {
 
-	// Initialize with the default arguments.
-	KMeans<> k;
+  NumericMatrix Xr(data);
+  arma::mat X(Xr.begin(), Xr.nrow(), Xr.ncol(), false); 
+  arma::Col<size_t> assignments;
 
-	k.Cluster(data, clusters, assignments); 
+  // Initialize with the default arguments.
+  KMeans<> k;
 
-    return List::create(_["clusters"]	= clusters,
-                        _["result"]		= assignments);
+  k.Cluster(X, clusters, assignments); 
+
+  return List::create(_["clusters"]	= clusters,
+                      _["result"]		= assignments);
 }