update

Author: snoweye

DESCRIPTION

@@ -4,9 +4,9 @@ Date: 2013-05-13
 Title: Parallel Model-Based Clustering
 Authors@R: c(person("Wei-Chen", "Chen", role = c("aut", "cre"), email =
         "[email protected]"), person("George", "Ostrouchov", role = "aut"))
-Depends: R (>= 2.14.0), methods, MASS, MixSim, rlecuyer, pbdMPI (>=
-        0.1-6), pbdSLAP (>= 0.1-5), pbdBASE (>= 0.2-1), pbdDMAT (>=
-        0.2-1)
+Depends: R (>= 2.15.0), methods, rlecuyer, pbdMPI (>= 0.1-6), pbdSLAP
+        (>= 0.1-5), pbdBASE (>= 0.2-1), pbdDMAT (>= 0.2-1)
+Enhances: MixSim
 LazyLoad: yes
 LazyData: yes
 Description: The pmclust aims to utilize model-based clustering (unsupervised)
@@ -25,7 +25,7 @@ URL: http://r-pbd.org/
 BugReports: http://group.r-pbd.org/
 MailingList: Please send questions and comments regarding pbdR to
         [email protected]
-Packaged: 2013-06-19 18:32:45 UTC; snoweye
+Packaged: 2013-06-19 20:37:06 UTC; snoweye
 Author: Wei-Chen Chen [aut, cre],
   George Ostrouchov [aut]
 Maintainer: Wei-Chen Chen <[email protected]>

NAMESPACE

@@ -1,6 +1,6 @@
 useDynLib(pmclust)
 
-import(methods, MASS, MixSim, rlecuyer, pbdMPI, pbdSLAP, pbdBASE, pbdDMAT)
+import(methods, rlecuyer, pbdMPI, pbdSLAP, pbdBASE, pbdDMAT)
 
 # exportPattern("^[[:alpha:]]+")
 # exportPattern("^[\\.]")

R/00_pmclust.r

@@ -21,7 +21,7 @@ pmclust <- function(X = NULL, K = 2, MU = NULL,
     }
     # Check matrix type if dmat algorithm is used.
     if(B & algorithm[1] %in% .PMC.CT$algorithm.dmat){
-      if(! eval(is.ddmatrix(X.dmat), envir = .GlobalEnv)){
+      if(! is.ddmatrix(.GlobalEnv$X.dmat)){
         comm.stop("X.dmat is not a ddmatrix.")
       }
     }
@@ -86,7 +86,7 @@ pkmeans <- function(X = NULL, K = 2, MU = NULL,
     }
     # Check matrix type if dmat algorithm is used.
     if(B & algorithm[1] %in% .PMC.CT$algorithm.dmat){
-      if(! eval(is.ddmatrix(X.dmat), envir = .GlobalEnv)){
+      if(! is.ddmatrix(.GlobalEnv$X.dmat)){
         comm.stop("X.dmat is not a ddmatrix.")
       }
     }

R/00_pmclust_internal.r

@@ -16,7 +16,7 @@ pmclust.internal <- function(X = NULL, K = 2, MU = NULL,
   if(is.null(X)){
     if(exists("X.dmat", envir = .GlobalEnv)){
       # Assign X to .pmclustEnv and convert to spmdr.
-      convert.data(X.dmat, method.own.X[1], rank.own.X, comm)
+      convert.data(.GlobalEnv$X.dmat, method.own.X[1], rank.own.X, comm)
     } else{
       # Assume X.spmd in .GlobalEnv and no need for converting or check.
     }

R/00_pmclust_internal_dmat.r

@@ -11,7 +11,7 @@ pmclust.internal.dmat <- function(X = NULL, K = 2, MU = NULL,
 
   # Check X.
   if(is.null(X)){
-    if(! eval(is.ddmatrix(X.dmat), envir = .GlobalEnv)){
+    if(! is.ddmatrix(.GlobalEnv$X.dmat)){
       comm.stop("X.dmat is not a ddmatrix.")
     } else{
       # Assume X.dmat in .GlobalEnv and no need for converting.

R/pm_generate_MixSim.r

@@ -5,8 +5,8 @@ generate.MixSim.spmd <- function(N, p, K, MixSim.obj = NULL,
   ### Obtain a set of parameters from MixSim.
   if(spmd.comm.rank() == 0){
     if(is.null(MixSim.obj)){
-      MixSim.obj <- MixSim(BarOmega, MaxOmega, K = K, p = p, PiLow = PiLow,
-                           sph = sph, hom = hom)
+      MixSim.obj <- MixSim:::MixSim(BarOmega, MaxOmega, K = K, p = p,
+                                    PiLow = PiLow, sph = sph, hom = hom)
     }
     if(class(MixSim.obj) != "MixSim"){
       stop("MixSim.obj is not a MixSim class.")
@@ -20,7 +20,7 @@ generate.MixSim.spmd <- function(N, p, K, MixSim.obj = NULL,
   N.allspmds <- unlist(lapply(get.jid(N, all = TRUE), length),
                        use.names = FALSE)
   N.spmd <- N.allspmds[spmd.comm.rank() + 1]
-  ret.dataset <- simdataset(N.spmd, MixSim.obj$Pi, MixSim.obj$Mu, MixSim.obj$S)
+  ret.dataset <- MixSim:::simdataset(N.spmd, MixSim.obj$Pi, MixSim.obj$Mu, MixSim.obj$S)
 
   data.simu <- ret.dataset$X
   data.class <- ret.dataset$id

inst/doc/pmclust-guide.pdf

@@ -85,9 +85,6 @@
   \code{\link{apecma.step}},
   \code{\link{kmeans.step}}. \cr
   \code{\link{em.step.dmat}},
-  \code{\link{aecm.step.dmat}},
-  \code{\link{apecm.step.dmat}}, \cr
-  \code{\link{apecma.step.dmat}},
   \code{\link{kmeans.step.dmat}}. \cr
 }
 \examples{

man/00_pmclust-package.Rd

@@ -5,9 +5,6 @@
 \alias{apecma.step}
 \alias{kmeans.step}
 \alias{em.step.dmat}
-\alias{aecm.step.dmat}
-\alias{apecm.step.dmat}
-\alias{apecma.step.dmat}
 \alias{kmeans.step.dmat}
 \title{EM-like Steps for SPMD}
 \description{
@@ -24,9 +21,6 @@
   kmeans.step(PARAM.org)
 
   em.step.dmat(PARAM.org)
-  aecm.step.dmat(PARAM.org)
-  apecm.step.dmat(PARAM.org)
-  apecma.step.dmat(PARAM.org)
   kmeans.step.dmat(PARAM.org)
 }
 \arguments{

man/30-em_like.Rd

@@ -17,10 +17,11 @@
 
   get.N.CLASS.dmat(K)
 
-  get.CLASS()
+  get.CLASS(PARAM)
 }
 \arguments{
   \item{K}{the total number of clusters.}
+  \item{PARAM}{a set of parameters.}
 }
 \details{
   The final results are distributed in all processors including the total