[R] Drop plot tree style support. (#10989)

Author: trivialfis

R-package/R/xgb.plot.multi.trees.R

@@ -23,6 +23,7 @@
 #' @inheritParams xgb.plot.tree
 #' @param features_keep Number of features to keep in each position of the multi trees,
 #'   by default 5.
+#' @param render Should the graph be rendered or not? The default is `TRUE`.
 #' @inherit xgb.plot.tree return
 #'
 #' @examples

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

@@ -3,63 +3,38 @@
 #' Read a tree model text dump and plot the model.
 #'
 #' @details
-#' When using `style="xgboost"`, the content of each node is visualized as follows:
-#' - For non-terminal nodes, it will display the split condition (number or name if
-#'   available, and the condition that would decide to which node to go next).
-#' - Those nodes will be connected to their children by arrows that indicate whether the
-#'   branch corresponds to the condition being met or not being met.
+#' The content of each node is visualized as follows:
+#' - For non-terminal nodes, it will display the split condition (number or name
+#'   if available, and the condition that would decide to which node to go
+#'   next).
+#' - Those nodes will be connected to their children by arrows that indicate
+#'   whether the branch corresponds to the condition being met or not being met.
 #' - Terminal (leaf) nodes contain the margin to add when ending there.
 #'
-#' When using `style="R"`, the content of each node is visualized like this:
-#' - *Feature name*.
-#' - *Cover:* The sum of second order gradients of training data.
-#'   For the squared loss, this simply corresponds to the number of instances in the node.
-#'   The deeper in the tree, the lower the value.
-#' - *Gain* (for split nodes): Information gain metric of a split
-#'        (corresponds to the importance of the node in the model).
-#' - *Value* (for leaves): Margin value that the leaf may contribute to the prediction.
-#'
-#' The tree root nodes also indicate the tree index (0-based).
-#'
 #' The "Yes" branches are marked by the "< split_value" label.
 #' The branches also used for missing values are marked as bold
 #' (as in "carrying extra capacity").
 #'
-#' This function uses [GraphViz](https://www.graphviz.org/) as DiagrammeR backend.
+#' This function uses [GraphViz](https://www.graphviz.org/) as DiagrammeR
+#' backend.
 #'
-#' @param model Object of class `xgb.Booster`. If it contains feature names (they can be set through
-#'   [setinfo()], they will be used in the output from this function.
-#' @param trees An integer vector of tree indices that should be used.
-#'   The default (`NULL`) uses all trees.
-#'   Useful, e.g., in multiclass classification to get only
-#'   the trees of one class. *Important*: the tree index in XGBoost models
-#'   is zero-based (e.g., use `trees = 0:2` for the first three trees).
+#' @param model Object of class `xgb.Booster`. If it contains feature names
+#'   (they can be set through [setinfo()], they will be used in the
+#'   output from this function.
+#' @param tree_idx An integer of the tree index that should be used. This
+#'   is an 1-based index.
 #' @param plot_width,plot_height Width and height of the graph in pixels.
 #'   The values are passed to `DiagrammeR::render_graph()`.
-#' @param render Should the graph be rendered or not? The default is `TRUE`.
-#' @param show_node_id a logical flag for whether to show node id's in the graph.
-#' @param style Style to use for the plot:
-#'   - `"xgboost"`: will use the plot style defined in the core XGBoost library,
-#'     which is shared between different interfaces through the 'dot' format. This
-#'     style was not available before version 2.1.0 in R. It always plots the trees
-#'     vertically (from top to bottom).
-#'   - `"R"`: will use the style defined from XGBoost's R interface, which predates
-#'     the introducition of the standardized style from the core library. It might plot
-#'     the trees horizontally (from left to right).
-#'
-#'   Note that `style="xgboost"` is only supported when all of the following conditions are met:
-#'   - Only a single tree is being plotted.
-#'   - Node IDs are not added to the graph.
-#'   - The graph is being returned as `htmlwidget` (`render=TRUE`).
+#' @param with_stats Whether to dump some additional statistics about the
+#'   splits.  When this option is on, the model dump contains two additional
+#'   values: gain is the approximate loss function gain we get in each split;
+#'   cover is the sum of second order gradient in each node.
 #' @param ... Currently not used.
 #' @return
-#' The value depends on the `render` parameter:
-#' - If `render = TRUE` (default): Rendered graph object which is an htmlwidget of
-#'   class `grViz`. Similar to "ggplot" objects, it needs to be printed when not
-#'   running from the command line.
-#' - If `render = FALSE`: Graph object which is of DiagrammeR's class `dgr_graph`.
-#'   This could be useful if one wants to modify some of the graph attributes
-#'   before rendering the graph with `DiagrammeR::render_graph()`.
+#'
+#' Rendered graph object which is an htmlwidget of ' class `grViz`. Similar to
+#' "ggplot" objects, it needs to be printed when not running from the command
+#' line.
 #'
 #' @examples
 #' data(agaricus.train, package = "xgboost")
@@ -73,119 +48,35 @@
 #'   objective = "binary:logistic"
 #' )
 #'
-#' # plot the first tree, using the style from xgboost's core library
-#' # (this plot should look identical to the ones generated from other
-#' # interfaces like the python package for xgboost)
-#' xgb.plot.tree(model = bst, trees = 1, style = "xgboost")
-#'
-#' # plot all the trees
-#' xgb.plot.tree(model = bst, trees = NULL)
+#' # plot the first tree
+#' xgb.plot.tree(model = bst, tree_idx = 1)
 #'
-#' # plot only the first tree and display the node ID:
-#' xgb.plot.tree(model = bst, trees = 0, show_node_id = TRUE)
 #'
 #' \dontrun{
 #' # Below is an example of how to save this plot to a file.
-#' # Note that for export_graph() to work, the {DiagrammeRsvg}
-#' # and {rsvg} packages must also be installed.
 #'
 #' library(DiagrammeR)
 #'
-#' gr <- xgb.plot.tree(model = bst, trees = 0:1, render = FALSE)
-#' export_graph(gr, "tree.pdf", width = 1500, height = 1900)
-#' export_graph(gr, "tree.png", width = 1500, height = 1900)
+#' gr <- xgb.plot.tree(model = bst, tree_idx = 1)
+#' htmlwidgets::saveWidget(gr, 'plot.html')
 #' }
 #'
 #' @export
-xgb.plot.tree <- function(model = NULL, trees = NULL, plot_width = NULL, plot_height = NULL,
-                          render = TRUE, show_node_id = FALSE, style = c("R", "xgboost"), ...) {
+xgb.plot.tree <- function(model,
+                          tree_idx = 1,
+                          plot_width = NULL,
+                          plot_height = NULL,
+                          with_stats = FALSE, ...) {
   check.deprecation(...)
   if (!inherits(model, "xgb.Booster")) {
-    stop("model: Has to be an object of class xgb.Booster")
+    stop("model has to be an object of the class xgb.Booster")
   }
-
   if (!requireNamespace("DiagrammeR", quietly = TRUE)) {
-    stop("DiagrammeR package is required for xgb.plot.tree", call. = FALSE)
-  }
-
-  style <- as.character(head(style, 1L))
-  stopifnot(style %in% c("R", "xgboost"))
-  if (style == "xgboost") {
-    if (NROW(trees) != 1L || !render || show_node_id) {
-      stop("style='xgboost' is only supported for single, rendered tree, without node IDs.")
-    }
-
-    txt <- xgb.dump(model, dump_format = "dot")
-    return(DiagrammeR::grViz(txt[[trees + 1]], width = plot_width, height = plot_height))
-  }
-
-  dt <- xgb.model.dt.tree(model = model, trees = trees)
-
-  dt[, label := paste0(Feature, "\nCover: ", Cover, ifelse(Feature == "Leaf", "\nValue: ", "\nGain: "), Gain)]
-  if (show_node_id)
-    dt[, label := paste0(ID, ": ", label)]
-  dt[Node == 0, label := paste0("Tree ", Tree, "\n", label)]
-  dt[, shape := "rectangle"][Feature == "Leaf", shape := "oval"]
-  dt[, filledcolor := "Beige"][Feature == "Leaf", filledcolor := "Khaki"]
-  # in order to draw the first tree on top:
-  dt <- dt[order(-Tree)]
-
-  nodes <- DiagrammeR::create_node_df(
-    n         = nrow(dt),
-    ID        = dt$ID,
-    label     = dt$label,
-    fillcolor = dt$filledcolor,
-    shape     = dt$shape,
-    data      = dt$Feature,
-    fontcolor = "black")
-
-  if (nrow(dt[Feature != "Leaf"]) != 0) {
-    edges <- DiagrammeR::create_edge_df(
-      from  = match(rep(dt[Feature != "Leaf", c(ID)], 2), dt$ID),
-      to    = match(dt[Feature != "Leaf", c(Yes, No)], dt$ID),
-      label = c(
-        dt[Feature != "Leaf", paste("<", Split)],
-        rep("", nrow(dt[Feature != "Leaf"]))
-      ),
-      style = c(
-        dt[Feature != "Leaf", ifelse(Missing == Yes, "bold", "solid")],
-        dt[Feature != "Leaf", ifelse(Missing == No, "bold", "solid")]
-      ),
-      rel   = "leading_to")
-  } else {
-    edges <- NULL
+    stop("The DiagrammeR package is required for xgb.plot.tree", call. = FALSE)
   }
 
-  graph <- DiagrammeR::create_graph(
-      nodes_df = nodes,
-      edges_df = edges,
-      attr_theme = NULL
-  )
-  graph <- DiagrammeR::add_global_graph_attrs(
-      graph = graph,
-      attr_type = "graph",
-      attr  = c("layout", "rankdir"),
-      value = c("dot", "LR")
+  txt <- xgb.dump(model, dump_format = "dot", with_stats = with_stats)
+  DiagrammeR::grViz(
+    txt[[tree_idx]], width = plot_width, height = plot_height
   )
-  graph <- DiagrammeR::add_global_graph_attrs(
-      graph = graph,
-      attr_type = "node",
-      attr  = c("color", "style", "fontname"),
-      value = c("DimGray", "filled", "Helvetica")
-  )
-  graph <- DiagrammeR::add_global_graph_attrs(
-      graph = graph,
-      attr_type = "edge",
-      attr  = c("color", "arrowsize", "arrowhead", "fontname"),
-      value = c("DimGray", "1.5", "vee", "Helvetica")
-  )
-
-  if (!render) return(invisible(graph))
-
-  DiagrammeR::render_graph(graph, width = plot_width, height = plot_height)
 }
-
-# Avoid error messages during CRAN check.
-# The reason is that these variables are never declared
-# They are mainly column names inferred by Data.table...
-globalVariables(c("Feature", "ID", "Cover", "Gain", "Split", "Yes", "No", "Missing", ".", "shape", "filledcolor", "label"))

R-package/R/xgb.train.R

@@ -103,7 +103,7 @@
 #'      objective is non-convex.
 #'
 #'      See the tutorials [Custom Objective and Evaluation Metric](https://xgboost.readthedocs.io/en/stable/tutorials/custom_metric_obj.html)
-#'      and [Advanced Usage of Custom Objectives](https://xgboost.readthedocs.io/en/stable/tutorials/advanced_custom_obj)
+#'      and [Advanced Usage of Custom Objectives](https://xgboost.readthedocs.io/en/latest/tutorials/advanced_custom_obj.html)
 #'      for more information about custom objectives.
 #'
 #'   - `base_score`: The initial prediction score of all instances, global bias. Default: 0.5.