remove dependent variable name (not needed in R version)

R/RcppExports.R

@@ -1,8 +1,8 @@
 # Generated by using Rcpp::compileAttributes() -> do not edit by hand
 # Generator token: 10BE3573-1514-4C36-9D1C-5A225CD40393
 
-rangerCpp <- function(treetype, dependent_variable_name, input_x, input_y, variable_names, mtry, num_trees, verbose, seed, num_threads, write_forest, importance_mode_r, min_node_size, split_select_weights, use_split_select_weights, always_split_variable_names, use_always_split_variable_names, status_variable_name, prediction_mode, loaded_forest, snp_data, sample_with_replacement, probability, unordered_variable_names, use_unordered_variable_names, save_memory, splitrule_r, case_weights, use_case_weights, class_weights, predict_all, keep_inbag, sample_fraction, alpha, minprop, holdout, prediction_type_r, num_random_splits, sparse_x, use_sparse_data, order_snps, oob_error, max_depth, inbag, use_inbag) {
-    .Call(`_ranger_rangerCpp`, treetype, dependent_variable_name, input_x, input_y, variable_names, mtry, num_trees, verbose, seed, num_threads, write_forest, importance_mode_r, min_node_size, split_select_weights, use_split_select_weights, always_split_variable_names, use_always_split_variable_names, status_variable_name, prediction_mode, loaded_forest, snp_data, sample_with_replacement, probability, unordered_variable_names, use_unordered_variable_names, save_memory, splitrule_r, case_weights, use_case_weights, class_weights, predict_all, keep_inbag, sample_fraction, alpha, minprop, holdout, prediction_type_r, num_random_splits, sparse_x, use_sparse_data, order_snps, oob_error, max_depth, inbag, use_inbag)
+rangerCpp <- function(treetype, input_x, input_y, variable_names, mtry, num_trees, verbose, seed, num_threads, write_forest, importance_mode_r, min_node_size, split_select_weights, use_split_select_weights, always_split_variable_names, use_always_split_variable_names, prediction_mode, loaded_forest, snp_data, sample_with_replacement, probability, unordered_variable_names, use_unordered_variable_names, save_memory, splitrule_r, case_weights, use_case_weights, class_weights, predict_all, keep_inbag, sample_fraction, alpha, minprop, holdout, prediction_type_r, num_random_splits, sparse_x, use_sparse_data, order_snps, oob_error, max_depth, inbag, use_inbag) {
+    .Call(`_ranger_rangerCpp`, treetype, input_x, input_y, variable_names, mtry, num_trees, verbose, seed, num_threads, write_forest, importance_mode_r, min_node_size, split_select_weights, use_split_select_weights, always_split_variable_names, use_always_split_variable_names, prediction_mode, loaded_forest, snp_data, sample_with_replacement, probability, unordered_variable_names, use_unordered_variable_names, save_memory, splitrule_r, case_weights, use_case_weights, class_weights, predict_all, keep_inbag, sample_fraction, alpha, minprop, holdout, prediction_type_r, num_random_splits, sparse_x, use_sparse_data, order_snps, oob_error, max_depth, inbag, use_inbag)
 }
 
 numSmaller <- function(values, reference) {

R/predict.R

@@ -98,8 +98,7 @@ predict.ranger.forest <- function(object, data, predict.all = FALSE,
         is.null(forest$treetype)) {
     stop("Error: Invalid forest object.")
   }
-  if (forest$treetype == "Survival" && (is.null(forest$status.variable.name)  ||
-                                        is.null(forest$chf) || is.null(forest$unique.death.times))) {
+  if (forest$treetype == "Survival" && (is.null(forest$chf) || is.null(forest$unique.death.times))) {
     stop("Error: Invalid forest object.")
   }
 
@@ -213,15 +212,13 @@ predict.ranger.forest <- function(object, data, predict.all = FALSE,
   }
 
   ## Defaults for variables not needed
-  dependent.variable.name <- ""
   mtry <- 0
   importance <- 0
   min.node.size <- 0
   split.select.weights <- list(c(0, 0))
   use.split.select.weights <- FALSE
   always.split.variables <- c("0", "0")
   use.always.split.variables <- FALSE
-  status.variable.name <- "status"
   prediction.mode <- TRUE
   write.forest <- FALSE
   replace <- TRUE
@@ -258,11 +255,11 @@ predict.ranger.forest <- function(object, data, predict.all = FALSE,
   }
 
   ## Call Ranger
-  result <- rangerCpp(treetype, dependent.variable.name, x, y, forest$independent.variable.names, mtry,
+  result <- rangerCpp(treetype, x, y, forest$independent.variable.names, mtry,
                       num.trees, verbose, seed, num.threads, write.forest, importance,
                       min.node.size, split.select.weights, use.split.select.weights,
                       always.split.variables, use.always.split.variables,
-                      status.variable.name, prediction.mode, forest, snp.data, replace, probability,
+                      prediction.mode, forest, snp.data, replace, probability,
                       unordered.factor.variables, use.unordered.factor.variables, save.memory, splitrule,
                       case.weights, use.case.weights, class.weights, 
                       predict.all, keep.inbag, sample.fraction, alpha, minprop, holdout, 

R/ranger.R

@@ -226,8 +226,6 @@ ranger <- function(formula = NULL, data = NULL, num.trees = 500, mtry = NULL,
     if (is.null(x) | is.null(y)) {
       stop("Error: Either data or x and y is required.")
     }
-    dependent.variable.name <- ""
-    status.variable.name <- ""
   }  else {
     ## GenABEL GWA data
     if ("gwaa.data" %in% class(data)) {
@@ -246,12 +244,9 @@ ranger <- function(formula = NULL, data = NULL, num.trees = 500, mtry = NULL,
       if (is.null(dependent.variable.name)) {
         if (is.null(y) | is.null(x)) {
           stop("Error: Please give formula, dependent variable name or x/y.")
-        } else {
-          dependent.variable.name <- colnames(y)[1]
-        }
+        } 
       } else {
         if (is.null(status.variable.name)) {
-          status.variable.name <- ""
           y <- data[, dependent.variable.name, drop = TRUE]
           x <- data[, !(colnames(data) %in% dependent.variable.name), drop = FALSE]
         } else {
@@ -267,13 +262,6 @@ ranger <- function(formula = NULL, data = NULL, num.trees = 500, mtry = NULL,
       data.selected <- parse.formula(formula, data, env = parent.frame())
       y <- data.selected[, 1]
       x <- data.selected[, -1, drop = FALSE]
-      if (survival::is.Surv(y)) {
-        dependent.variable.name <- colnames(y)[1]
-        status.variable.name <- colnames(y)[2]
-      } else {
-        dependent.variable.name <- colnames(data.selected)[1]
-        status.variable.name <- ""
-      }
     }
   }
 
@@ -789,11 +777,11 @@ ranger <- function(formula = NULL, data = NULL, num.trees = 500, mtry = NULL,
   }
 
   ## Call Ranger
-  result <- rangerCpp(treetype, dependent.variable.name, x, y.mat, independent.variable.names, mtry,
+  result <- rangerCpp(treetype, x, y.mat, independent.variable.names, mtry,
                       num.trees, verbose, seed, num.threads, write.forest, importance.mode,
                       min.node.size, split.select.weights, use.split.select.weights,
                       always.split.variables, use.always.split.variables,
-                      status.variable.name, prediction.mode, loaded.forest, snp.data,
+                      prediction.mode, loaded.forest, snp.data,
                       replace, probability, unordered.factor.variables, use.unordered.factor.variables, 
                       save.memory, splitrule.num, case.weights, use.case.weights, class.weights, 
                       predict.all, keep.inbag, sample.fraction, alpha, minprop, holdout, prediction.type, 

R/treeInfo.R

@@ -68,14 +68,13 @@ treeInfo <- function(object, tree = 1) {
   if (is.null(forest)) {
     stop("Error: No saved forest in ranger object. Please set write.forest to TRUE when calling ranger.")
   }
-  if (is.null(forest$dependent.variable.name) || is.null(forest$num.trees) ||
+  if (is.null(forest$num.trees) ||
       is.null(forest$child.nodeIDs) || is.null(forest$split.varIDs) ||
       is.null(forest$split.values) || is.null(forest$independent.variable.names) ||
       is.null(forest$treetype)) {
     stop("Error: Invalid forest object.")
   }
-  if (forest$treetype == "Survival" && (is.null(forest$status.variable.name)  ||
-                                        is.null(forest$chf) || is.null(forest$unique.death.times))) {
+  if (forest$treetype == "Survival" && (is.null(forest$chf) || is.null(forest$unique.death.times))) {
     stop("Error: Invalid forest object.")
   }
   if (length(forest$child.nodeIDs) != forest$num.trees || length(forest$child.nodeIDs[[1]]) != 2) {