R CMD check cleanup

DESCRIPTION

@@ -1,7 +1,7 @@
 Package: BoolTraineR
 Type: Package
 Title: Tools For Training and Analysing Asynchronous Boolean Models
-Version: 1.1.1
+Version: 1.1.2
 Date: 2015-10-22
 Author: Chee Yee Lim
 Maintainer: Chee Yee Lim <cyl49@cam.ac.uk>
@@ -22,6 +22,7 @@ LinkingTo: Rcpp
 License: GPL-3
 LazyData: true
 Suggests:
+    bnlearn (>= 3.8.1),
     knitr,
     rmarkdown
 VignetteBuilder: knitr

NAMESPACE

@@ -9,8 +9,6 @@ export(calc_roc)
 export(compress_bmodel)
 export(decompress_bmodel)
 export(df_to_bm)
-export(gen_randata)
-export(gen_randata_bn)
 export(gen_two_rmodel)
 export(gen_two_rmodel_dag)
 export(get_encodings)

R/data_desc.R

@@ -96,15 +96,41 @@ NULL
 #' @usage data(wilson_raw_rnaseq)
 NULL
 
-#' @title Example Boolean Models used in the vignette
+#' @title Example Boolean Model used in the vignette
 #' 
 #' @description
-#' 3 Boolean models used in the examples of the vignette.
+#' A Boolean model used in the examples of the vignette.
 #' 
 #' @format
 #' Each Boolean model is a BoolModel object.
 #' 
 #' @docType data
-#' @name example_models
+#' @name emodel1
 #' @usage data(example_models)
-NULL
+NULL
+
+#' @title Example Boolean Model used in the vignette
+#' 
+#' @description
+#' A Boolean model used in the examples of the vignette.
+#' 
+#' @format
+#' Each Boolean model is a BoolModel object.
+#' 
+#' @docType data
+#' @name emodel2
+#' @usage data(example_models)
+NULL
+
+#' @title Example Boolean Model used in the vignette
+#' 
+#' @description
+#' A Boolean model used in the examples of the vignette.
+#' 
+#' @format
+#' Each Boolean model is a BoolModel object.
+#' 
+#' @docType data
+#' @name emodel3
+#' @usage data(example_models)
+NULL

R/initialisation.R

@@ -12,8 +12,6 @@
 #' @export
 initialise_raw_data = function(x, data_type='qpcr', uni_thre=0.2, scale=T)
 {
-  require(diptest)
-  
   #(1) Convert negative to positive values.
   if(min(x)<0)
   {
@@ -53,7 +51,7 @@ initialise_raw_data = function(x, data_type='qpcr', uni_thre=0.2, scale=T)
   for(i in 1:ncol(x))
   {
     #Perform unimodality test for each gene.
-    uni_test = dip.test(x[,i])$p.value
+    uni_test = diptest::dip.test(x[,i])$p.value
     
     if(uni_test > uni_thre)
     {

R/methods.R

@@ -66,6 +66,7 @@ writeBM = function(bmodel, file, gene.names=F, rownames=F)
 #' 
 #' @description
 #' This method plots the network underlying Boolean models by using igraph for quick visualisation.
+#' Require igraph.
 #' 
 #' @param bmodel S4 BoolModel object.
 #' @param makePlot logical. Whether to make plot or just return the object. Default to T.
@@ -74,29 +75,27 @@ writeBM = function(bmodel, file, gene.names=F, rownames=F)
 #' @export
 plotBM = function(bmodel, makePlot=T, ...)
 {
-  require(igraph)
-  
   #Convert to amat.
   am = bm_to_amat(bmodel)
   
   #Convert into a graph.
-  g = graph.adjacency(am, mode='directed', weighted=T)
+  g = igraph::graph.adjacency(am, mode='directed', weighted=T)
   
   #Setup edge colour for plotting.
   #Activation = black, inhibition = red
-  E(g)$color = sapply(E(g)$weight, function(x) ifelse(x==1, 'black', 'red'))
+  igraph::E(g)$color = sapply(igraph::E(g)$weight, function(x) ifelse(x==1, 'black', 'red'))
   
   #Setup other colours.
-  V(g)$frame.color = "white"
-  V(g)$color = rgb(255, 165, 0, 200, maxColorValue = 255)
+  igraph::V(g)$frame.color = "white"
+  igraph::V(g)$color = rgb(255, 165, 0, 200, maxColorValue = 255)
   
   #Setup vertex font size.
-  V(g)$label.cex = 1.5
+  igraph::V(g)$label.cex = 1.5
   
   if(makePlot)
   {
     #Make the plot.
-    plot(g, layout=layout_in_circle, ...)
+    igraph::plot.igraph(g, layout=igraph::layout_in_circle, ...)
   }
   
   invisible(g)
@@ -265,7 +264,7 @@ bm_to_df = function(bmodel)
 #' This method converts a data frame into a BoolModel object.
 #' Note that the model should only has 1 NOT operator. More than 1 is STRICTLY NOT allowed.
 #' 
-#' @param df data frame with 2 columns, targets and factors
+#' @param in_df data frame with 2 columns, targets and factors
 #' 
 #' @export
 df_to_bm = function(in_df)