Merge branch 'dev'

Conflicts:
	include/GNGGraph.h
	include/SHGraphDefs.h
	scripts/GNGConvertToIGraph.r
	scripts/RcppInterface.r
	src/ExtGraphNodeManager.hpp
	src/RcppInterface.cpp
	tests/test_many_servers.r

.gitignore

@@ -1,6 +1,7 @@
+.depend/
 build/
 *.so
 *.o
 *.d
 *~
-data/
+data/

DESCRIPTION

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+Package: GrowingNeuralGas
+Version: 0.1
+Date: 2014-01-08
+Title: Online, very fast big-data clustering algorithm Growing Neural Gas implementation
+    for R written in C++. 
+Author: Stanislaw Jastrzebski <[email protected]>
+Maintainer: Stanislaw Jastrzebski <[email protected]>
+Depends: Rcpp (>= 0.10.4), BH(>= 1.54.0)
+LinkingTo: BH, Rcpp
+Suggests: RUnit
+Description: Cluster big amounts of data using online lightspeed implementation of Growing Neural Gas.
+OS_type: unix
+License: LGPL-3
+Packaged: 2014-01-08 22:39:25 UTC; staszek
+NeedsCompilation: yes

NAMESPACE

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+import(igraph, methods)
+useDynLib(GrowingNeuralGas)
+exportPattern("^[[:alpha:]]+")

R/gng-presets.R

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+.gng.box_point<-function(r, center, prob=-1){ 
+    point <- c()
+
+    if(prob == -1)
+      point<-center
+    else
+      point<-c(center, prob)
+
+    point[1:3] = point[1:3] + runif(3, min=-r/2.0, max=r/2.0)   
+
+    point
+}
+
+
+.gng.plane_point<-function(r,center){
+  if(!hasArg(r)) r<-1.0
+  if(!hasArg(center)) center<-c(0,0,0)
+
+  point<-center
+  point[1]<-point[1]+r*runif(1.0)
+  point[2]<-point[2]+r*runif(1.0)
+  point[3]<-point[3]
+
+  return(point)
+}
+
+.gng.sphere_point<-function(r,center){
+  if(!hasArg(r)) r<-1.0
+  if(!hasArg(center)) center<-c(0,0,0)
+
+  alpha<-runif(1)*2*pi
+  beta<-runif(1)*pi
+
+  point<-center
+  point[1]<-point[1]+r*cos(alpha)*sin(beta)
+  point[2]<-point[2]+r*sin(alpha)*sin(beta)
+  point[3]<-point[3]+r*cos(beta)
+
+  return(point)
+}
+
+gng.preset.box<-function(N, r=0.5, center=c(0.5,0.5,0.5), prob=-1){
+  mat<-NULL
+
+
+  if(prob == -1)
+    mat<-matrix(0,N,3)
+  else
+    mat<-matrix(0,N,4)
+
+  for(i in 1:N){
+    mat[i,] = .gng.box_point(r=r, center=center, prob=prob)
+  }
+
+  mat
+}
+
+
+
+gng.preset.plane<-function(N, side=0.5, center=c(0.5,0.5,0.5), prob=-1){
+
+
+  mat<-matrix(0,N,3)
+
+  for(i in 1:N){
+    mat[i,1:3] = .gng.plane_point(side, center)
+    mat[i,3] = mat[i,1]
+  }
+
+  mat
+}
+
+
+gng.preset.sphere<-function(N, r=0.5, center=c(0.5,0.5,0.5),prob=-1){
+  mat<-matrix(0,N,3)
+
+  for(i in 1:N){
+    mat[i,1:3] = .gng.sphere_point(r, center)
+  }
+
+  mat
+}
+
+
+.sigmoid <- function(x){
+   1./(1.+exp(-x))
+}
+
+gng.preset_potential<-function(N, r=0.5, center=c(0.5,0.5,0.5), prob=-1){
+  mat <- matrix(rnorm(20,mean=1), N,3)
+
+  for(j in 1:N){
+    t<-rnorm(1,mean=0,sd=1)
+    u<-rnorm(1,mean=0,sd=1)
+    val<-.sigmoid(t^2+u^2);
+    mat[j,1] = t
+    mat[j,2] = u
+    mat[j,3] = val 	
+
+  }
+
+  mat
+}
+
+
+
+
+
+
+

R/gng-utils.R

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+
+.plane.point<-function(r,center){
+  if(!hasArg(r)) r<-1.0
+  if(!hasArg(center)) center<-c(0,0,0)
+
+  point<-center
+  point[1]<-point[1]+r*runif(1.0)
+  point[2]<-point[2]+r*runif(1.0)
+  point[3]<-point[3]
+
+  return(point)
+}
+
+.sphere.point<-function(r,center){
+  if(!hasArg(r)) r<-1.0
+  if(!hasArg(center)) center<-c(0,0,0)
+
+  alpha<-runif(1)*2*pi
+  beta<-runif(1)*pi
+
+  point<-center
+  point[1]<-point[1]+r*cos(alpha)*sin(beta)
+  point[2]<-point[2]+r*sin(alpha)*sin(beta)
+  point[3]<-point[3]+r*cos(beta)
+
+  return(point)
+}

R/gng-visualize.R

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+library(igraph)
+
+
+
+if("rgl" %in% rownames(installed.packages()) == TRUE){
+  .gng.plot3d<-function(gngServer){
+    tmp_name <- paste("tmp",sample(1:1000, 1),".graphml", sep="")
+    gngServer$export_to_graphml(tmp_name)
+    print("Reading GraphML dumped")
+    .visualizeIGraphRGL(.readFromGraphML(tmp_name))
+    file.remove(tmp_name)
+  }
+  #' Draw igraph using rgl - assumes >=3 dimensions and draws 3 first
+  .visualizeIGraphRGL<-function(g, radius=NULL){
+    library(multicore)
+    library(rgl)
+    library(igraph)
+
+    if(length(V(g))==0) return
+
+    iteration<-0
+    nodes <- length(V(g))
+
+    # Init 3d data
+    x_lines <- c(1:2*length(E(g)))
+    y_lines <- c(1:2*length(E(g)))
+    z_lines <- c(1:2*length(E(g)))
+    k<-1
+    m<-1
+    x<-c(1:nodes)
+    y<-c(1:nodes)
+    z<-c(1:nodes)
+
+    # Write 3d positions
+    for(i in 1:nodes){
+
+      x[i]=V(g)[i]$v0
+      y[i]=V(g)[i]$v1
+      z[i]=V(g)[i]$v2
+    }
+
+    # TODO: edges might be huge..
+    for(edg_idx in 1:length(E(g)))
+    {
+      edg <- get.edges(g, E(g)[edg_idx])
+      x_lines[k] = V(g)[edg[1]]$v0
+      y_lines[k] = V(g)[edg[1]]$v1
+      z_lines[k] = V(g)[edg[1]]$v2
+
+      x_lines[k+1] = V(g)[edg[2]]$v0
+      y_lines[k+1] = V(g)[edg[2]]$v1
+      z_lines[k+1] = V(g)[edg[2]]$v2
+      k = k + 2
+    }  
+
+    if(is.null(radius)){
+      radius <- 8.0*(0.3333* (abs(max(x) - min(x))+abs(max(y) - min(y))+abs(max(z) - min(z)))/(nodes+0.0))
+    }
+
+    cx <- V(g)$error
+    cx <- abs(cx)/max(abs(cx)) 
+    cy <- c(1:(nodes))
+    cz <- c(1:(nodes))
+
+    cy <- 0.1
+    cz <- 0.1
+    print(cx)
+
+
+    ### Draw graph ###
+    rgl.clear()
+    rgl.light()
+    rgl.bg(color="white")
+    axes3d(edges="bbox")
+
+
+    rgl.spheres(x,y,z, 
+                radius = rep(radius, length(cx)), 
+                col=rgb(cx,cy, cz))
+
+    rgl.lines(x_lines[1:k-1],y_lines[1:k-1],z_lines[1:k-1],color="bisque")
+  }
+}
+.gng.plot2d.errors<-function(gngServer, cluster, layout_2d, start_s=2){
+  tmp_name <- paste("tmp",sample(1:1000, 1),".graphml", sep="")
+  gngServer$export_to_graphml(tmp_name)
+  .visualizeIGraph2dWithErrors(.readFromGraphML(tmp_name ), cluster, layout_2d, start_s)
+  file.remove(tmp_name)
+}
+
+.gng.plot2d<-function(gngServer, cluster, layout_2d){
+  tmp_name <- paste("tmp",sample(1:1000, 1),".graphml", sep="")
+  gngServer$export_to_graphml(tmp_name)
+  .visualizeIGraph2d(.readFromGraphML(tmp_name ), cluster, layout_2d)
+  file.remove(tmp_name)
+}
+#' Visualize igraph using igraph plot
+#' It will layout graph using v0 and v1 coordinates
+#' @note It is quite slow, works for graphs < 2000 nodes, and for graphs <400 when using layout
+.visualizeIGraph2d<-function(g, cluster, layout_2d){
+  #g<-as.undirected(g)
+  L<-NULL
+
+  if(layout_2d){
+    L<-cbind(V(g)$v0, V(g)$v1)
+  }else{
+    L <- layout.auto(g)
+    #     L<-layout.fruchterman.reingold(g, niter=10000, area=4*vcount(g)^2)
+  }
+
+  if(cluster){
+    l = fastgreedy.community(g)#as.undirected(g))
+    col<-rainbow(length(l))
+    plot.igraph(g,vertex.size=3.0,vertex.label=NA,vertex.color=col[membership(l)],layout=L)
+  }else{
+    plot.igraph(g,vertex.size=3.0,vertex.label=NA,layout=L)
+  }
+}
+
+.visualizeIGraph2dWithErrors<-function(ig, cluster, layout_2d, start_s=2){
+  plot.new()
+  par(mfrow=c(1,2))
+  .visualizeIGraph2d(ig, cluster, layout_2d)
+  title("Graph visualization")
+  errors_raw = gng$get_error_statistics()
+  errors = log((errors_raw+1)/min(errors_raw+1))[start_s:length(errors_raw)]
+  plot(errors, type="l", lty=2, lwd=2, xlab="Time  [s]", ylab="Mean error (log)", frame.plot=F)
+  title("Mean error (log)")
+}