working version

.Rbuildignore

+^.*\.Rproj$
+^\.Rproj\.user$

.gitignore

+.Rproj.user
+.Rhistory
+.RData
+.Ruserdata
+src/*.o
+src/*.so
+src/*.dll

DESCRIPTION

 Package: deepwalker
 Type: Package
-Title: Learn Graph Embeddings with Deep Learning
+Title: Learn Graph Embeddings
 Version: 0.1
 Maintainer: Jan Wijffels <jwijffels@bnosac.be>
 Authors@R: c(person('Jan', 'Wijffels', role = c('aut', 'cre', 'cph'), email = 'jwijffels@bnosac.be'), 
@@ -9,10 +9,11 @@ Authors@R: c(person('Jan', 'Wijffels', role = c('aut', 'cre', 'cph'), email = 'j
 Description: Embeddings on graphs can be use to improve link prediction, node classification and node clustering. 
     The following algorithms which calculate the embedding for nodes in a graph are provided: 
     deepwalker, verse and node2vec.
-License: MIT
+License: MIT + file LICENSE
 URL: https://github.com/bnosac/deepwalker
 Encoding: UTF-8
 Depends: R (>= 2.10)
+Suggests: igraph, igraphdata, Matrix
 Imports: Rcpp (>= 0.11.5)
 LinkingTo: Rcpp
 SystemRequirements: C++11

NAMESPACE

+# Generated by roxygen2: do not edit by hand
+
+export(deepwalker_verse)
+importFrom(Rcpp,evalCpp)
+useDynLib(deepwalker)

R/RcppExports.R

+# Generated by using Rcpp::compileAttributes() -> do not edit by hand
+# Generator token: 10BE3573-1514-4C36-9D1C-5A225CD40393
+
+embeddings_verse <- function(dgrmatrix_p, dgrmatrix_j, n_epochs = 100000L) {
+    .Call('_deepwalker_embeddings_verse', PACKAGE = 'deepwalker', dgrmatrix_p, dgrmatrix_j, n_epochs)
+}
+

R/deepwalker_verse.R

+#' @title Versatile Graph Embeddings from Similarity Measures
+#' @description This function calculates node embeddings in a graph by using 
+#' VERSE (Versatile Graph Embeddings from Similarity Measures)
+#' @param x an object of class dgRMatrix
+#' @return TODO
+#' @export
+#' @examples
+#' library(igraphdata)
+#' library(igraph)
+#' library(Matrix)
+#' 
+#' data(karate, package = "igraphdata")
+#' x <- as_adj(karate)
+#' x <- as(x, "RsparseMatrix")
+#' 
+#' embeddings <- deepwalker_verse(x)
+deepwalker_verse <- function(x){
+  emb <- embeddings_verse(x@p, x@j, n_epochs = 10)
+  emb
+}
\ No newline at end of file

R/pkg.R

+#' @importFrom Rcpp evalCpp
+#' @useDynLib deepwalker
+NULL

deepwalker.Rproj

+Version: 1.0
+
+RestoreWorkspace: Default
+SaveWorkspace: Default
+AlwaysSaveHistory: Default
+
+EnableCodeIndexing: Yes
+UseSpacesForTab: Yes
+NumSpacesForTab: 2
+Encoding: UTF-8
+
+RnwWeave: Sweave
+LaTeX: pdfLaTeX
+
+BuildType: Package
+PackageUseDevtools: Yes
+PackageInstallArgs: --no-multiarch --with-keep.source
+PackageRoxygenize: rd,collate,namespace

man/deepwalker_verse.Rd

+% Generated by roxygen2: do not edit by hand
+% Please edit documentation in R/deepwalker_verse.R
+\name{deepwalker_verse}
+\alias{deepwalker_verse}
+\title{Versatile Graph Embeddings from Similarity Measures}
+\usage{
+deepwalker_verse(x)
+}
+\arguments{
+\item{x}{an object of class dgRMatrix}
+}
+\value{
+TODO
+}
+\description{
+This function calculates node embeddings in a graph by using 
+VERSE (Versatile Graph Embeddings from Similarity Measures)
+}
+\examples{
+library(igraphdata)
+library(igraph)
+library(Matrix)
+
+data(karate, package = "igraphdata")
+x <- as_adj(karate)
+x <- as(x, "RsparseMatrix")
+
+embeddings <- deepwalker_verse(x)
+}

src/RcppExports.cpp

@@ -5,21 +5,22 @@
 
 using namespace Rcpp;
 
-// deepwalker_verse
-SEXP deepwalker_verse(Rcpp::IntegerVector dgrmatrix_p, Rcpp::IntegerVector dgrmatrix_j);
-RcppExport SEXP _deepwalker_deepwalker_verse(SEXP dgrmatrix_pSEXP, SEXP dgrmatrix_jSEXP) {
+// embeddings_verse
+SEXP embeddings_verse(Rcpp::IntegerVector dgrmatrix_p, Rcpp::IntegerVector dgrmatrix_j, int n_epochs);
+RcppExport SEXP _deepwalker_embeddings_verse(SEXP dgrmatrix_pSEXP, SEXP dgrmatrix_jSEXP, SEXP n_epochsSEXP) {
 BEGIN_RCPP
     Rcpp::RObject rcpp_result_gen;
     Rcpp::RNGScope rcpp_rngScope_gen;
     Rcpp::traits::input_parameter< Rcpp::IntegerVector >::type dgrmatrix_p(dgrmatrix_pSEXP);
     Rcpp::traits::input_parameter< Rcpp::IntegerVector >::type dgrmatrix_j(dgrmatrix_jSEXP);
-    rcpp_result_gen = Rcpp::wrap(deepwalker_verse(dgrmatrix_p, dgrmatrix_j));
+    Rcpp::traits::input_parameter< int >::type n_epochs(n_epochsSEXP);
+    rcpp_result_gen = Rcpp::wrap(embeddings_verse(dgrmatrix_p, dgrmatrix_j, n_epochs));
     return rcpp_result_gen;
 END_RCPP
 }
 
 static const R_CallMethodDef CallEntries[] = {
-    {"_deepwalker_deepwalker_verse", (DL_FUNC) &_deepwalker_deepwalker_verse, 2},
+    {"_deepwalker_embeddings_verse", (DL_FUNC) &_deepwalker_embeddings_verse, 3},
     {NULL, NULL, 0}
 };
 

src/verse.cpp

@@ -203,12 +203,13 @@ void Train() {
 
 
 // [[Rcpp::export]]
-SEXP deepwalker_verse(Rcpp::IntegerVector dgrmatrix_p, Rcpp::IntegerVector dgrmatrix_j) {
+SEXP embeddings_verse(Rcpp::IntegerVector dgrmatrix_p, Rcpp::IntegerVector dgrmatrix_j,
+                      int n_epochs = 100000) {
   step = 0;
   silent = false;
   n_threads = 1;
   global_lr = 0.0025f;
-  n_epochs = 100000;
+  //n_epochs = ;
   n_hidden = 128;
   n_samples = 3;
   ppralpha = 0.85f;
@@ -269,17 +270,25 @@ SEXP deepwalker_verse(Rcpp::IntegerVector dgrmatrix_p, Rcpp::IntegerVector dgrma
   for (int i = 0; i < (int)(nv+1); i++)
     _offsets[i] = offsets[i];
   
+  /*
   Rcpp::NumericVector embeddings(nv * n_hidden);  
   for (int i = 0; i < (int)(nv * n_hidden); i++){
     embeddings[i] = w0[i];
   }
+   */
+  Rcpp::NumericMatrix embeddings(nv, n_hidden);
+  for (int i = 0; i < nv; i++){
+    for (int j = 0; j < n_hidden; j++){
+      embeddings(i, j) = w0[i*nv + j];
+    }
+  }
 
   // Return
   Rcpp::List go = Rcpp::List::create(Rcpp::Named("vertices") = nv,
-                                     Rcpp::Named("vertices_embeddings") = embeddings,
-                                     Rcpp::Named("edges_nr") = ne, 
-                                     Rcpp::Named("edges") = _edges, 
-                                     Rcpp::Named("offsets") = _offsets
-                                     );
+                                     Rcpp::Named("edges") = ne, 
+                                     Rcpp::Named("dimension") = n_hidden, 
+                                     Rcpp::Named("embedding") = embeddings,
+                                     Rcpp::Named("edges_data") = _edges, 
+                                     Rcpp::Named("offsets_data") = _offsets);
   return go;
 }