moved the external graphing packages to Suggested in order to trim the dependencies

R-package/DESCRIPTION

@@ -18,7 +18,12 @@ License: Apache License (== 2.0) | file LICENSE
 URL: https://github.com/dmlc/xgboost
 BugReports: https://github.com/dmlc/xgboost/issues
 VignetteBuilder: knitr
-Suggests: knitr
+Suggests:
+    knitr,
+    ggplot2 (>= 1.0.0),
+    DiagrammeR (>= 0.4),
+    Ckmeans.1d.dp (>= 3.3.1),
+    vcd (>= 1.3)
 Depends:
     R (>= 2.10)
 Imports:
@@ -26,8 +31,4 @@ Imports:
     methods,
     data.table (>= 1.9.4),
     magrittr (>= 1.5),
-    stringr (>= 0.6.2),
-    DiagrammeR (>= 0.4),
-    ggplot2 (>= 1.0.0),
-    Ckmeans.1d.dp (>= 3.3.1),
-    vcd (>= 1.3)
+    stringr (>= 0.6.2)

R-package/NAMESPACE

@@ -21,8 +21,6 @@ exportMethods(predict)
 import(methods)
 importClassesFrom(Matrix,dgCMatrix)
 importClassesFrom(Matrix,dgeMatrix)
-importFrom(Ckmeans.1d.dp,Ckmeans.1d.dp)
-importFrom(DiagrammeR,mermaid)
 importFrom(Matrix,cBind)
 importFrom(Matrix,colSums)
 importFrom(Matrix,sparseVector)
@@ -34,16 +32,6 @@ importFrom(data.table,fread)
 importFrom(data.table,rbindlist)
 importFrom(data.table,set)
 importFrom(data.table,setnames)
-importFrom(ggplot2,aes)
-importFrom(ggplot2,coord_flip)
-importFrom(ggplot2,element_blank)
-importFrom(ggplot2,element_text)
-importFrom(ggplot2,geom_bar)
-importFrom(ggplot2,ggplot)
-importFrom(ggplot2,ggtitle)
-importFrom(ggplot2,theme)
-importFrom(ggplot2,xlab)
-importFrom(ggplot2,ylab)
 importFrom(magrittr,"%>%")
 importFrom(magrittr,add)
 importFrom(magrittr,not)

R-package/R/xgb.plot.importance.R

@@ -2,17 +2,6 @@
 #' 
 #' Read a data.table containing feature importance details and plot it.
 #' 
-#' @importFrom ggplot2 ggplot
-#' @importFrom ggplot2 aes
-#' @importFrom ggplot2 geom_bar
-#' @importFrom ggplot2 coord_flip
-#' @importFrom ggplot2 xlab
-#' @importFrom ggplot2 ylab
-#' @importFrom ggplot2 ggtitle
-#' @importFrom ggplot2 theme
-#' @importFrom ggplot2 element_text
-#' @importFrom ggplot2 element_blank
-#' @importFrom Ckmeans.1d.dp Ckmeans.1d.dp
 #' @importFrom magrittr %>%
 #' @param importance_matrix a \code{data.table} returned by the \code{xgb.importance} function.
 #' @param numberOfClusters a \code{numeric} vector containing the min and the max range of the possible number of clusters of bars.
@@ -44,11 +33,17 @@ xgb.plot.importance <- function(importance_matrix = NULL, numberOfClusters = c(1
   if (!"data.table" %in% class(importance_matrix))  {     
     stop("importance_matrix: Should be a data.table.")
   }
-    
+  if (!require(ggplot2, quietly = TRUE)) {
+    stop("ggplot2 package is required for plotting the importance", call. = FALSE)
+  }
+  if (!requireNamespace("Ckmeans.1d.dp", quietly = TRUE)) {
+    stop("Ckmeans.1d.dp package is required for plotting the importance", call. = FALSE)
+  }
+
   # To avoid issues in clustering when co-occurences are used
   importance_matrix <- importance_matrix[, .(Gain = sum(Gain)), by = Feature]
   
-  clusters <- suppressWarnings(Ckmeans.1d.dp(importance_matrix[,Gain], numberOfClusters))
+  clusters <- suppressWarnings(Ckmeans.1d.dp::Ckmeans.1d.dp(importance_matrix[,Gain], numberOfClusters))
   importance_matrix[,"Cluster":=clusters$cluster %>% as.character]
     
   plot <- ggplot(importance_matrix, aes(x=reorder(Feature, Gain), y = Gain, width= 0.05), environment = environment())+  geom_bar(aes(fill=Cluster), stat="identity", position="identity") + coord_flip() + xlab("Features") + ylab("Gain") + ggtitle("Feature importance") + theme(plot.title = element_text(lineheight=.9, face="bold"), panel.grid.major.y = element_blank() )

R-package/R/xgb.plot.tree.R

@@ -15,7 +15,6 @@
 #' @importFrom stringr str_split
 #' @importFrom stringr str_extract
 #' @importFrom stringr str_trim
-#' @importFrom DiagrammeR mermaid
 #' @param feature_names names of each feature as a character vector. Can be extracted from a sparse matrix (see example). If model dump already contains feature names, this argument should be \code{NULL}.
 #' @param filename_dump the path to the text file storing the model. Model dump must include the gain per feature and per tree (parameter \code{with.stats = T} in function \code{xgb.dump}). Possible to provide a model directly (see \code{model} argument).
 #' @param model generated by the \code{xgb.train} function. Avoid the creation of a dump file.
@@ -64,7 +63,11 @@ xgb.plot.tree <- function(feature_names = NULL, filename_dump = NULL, model = NU
   if (!class(model) %in% c("xgb.Booster", "NULL")) {
     stop("model: Has to be an object of class xgb.Booster model generaged by the xgb.train function.")
   }
-    
+  
+  if (!requireNamespace("DiagrammeR", quietly = TRUE)) {
+    stop("DiagrammeR package is required for xgb.plot.tree", call. = FALSE)
+  }
+  
   if(is.null(model)){
     allTrees <- xgb.model.dt.tree(feature_names = feature_names, filename_dump = filename_dump, n_first_tree = n_first_tree)  
   } else {
@@ -85,7 +88,7 @@ xgb.plot.tree <- function(feature_names = NULL, filename_dump = NULL, model = NU
   no <- allTrees[Feature!="Leaf", c(No)] %>% paste(collapse = ",") %>% paste("class ", ., " redNode", sep = "")
   
   path <- allTrees[Feature!="Leaf", c(yesPath, noPath)] %>% .[order(.)] %>% paste(sep = "", collapse = ";") %>% paste("graph LR", .,collapse = "", sep = ";") %>% paste(CSSstyle, yes, no, sep = ";")
-  mermaid(path, width, height)
+  DiagrammeR::mermaid(path, width, height)
 }
 
 # Avoid error messages during CRAN check.