fix for bug with dummy variables in growTree()

R/growTree.R

@@ -304,9 +304,16 @@ growTree <- function(model=NULL, mydata=NULL,
 
   # return values in result are:
   # LL.max		: numeric, log likelihood ratio of best split
-  # split.max 	: numeric, value to split best column on 
+  # split.max 	: numeric, split point; value to split best column on 
+  #               (for metric variables)
   # col.max		: index of best column
-  # cov.name	: name of best candidate
+  # name.max	: name of best candidate
+  # type.max  :
+  # btn.matrix : a matrix, which contains test statistics and
+  #              more information for
+  #              the various split points evaluated
+  # n.comp     : the (implicit) number of multiple tests evaluated for
+  #               determining the best split
 
   # store the value of the selected test statistic
   node$lr <- NA
@@ -435,18 +442,21 @@ growTree <- function(model=NULL, mydata=NULL,
       }
       test2 <- test2[,-1]
 
-      # if var.type==1, then split.max corresponds to the index of
+      # if level is categorical, then split.max corresponds to the index of
       # the best column in the matrix that represents all subsets
       # make sure that this is not casted to a string if there
       # are predictors of other types (esp., factors)
-      # browser()
+      #browser()
+      if (!all(is.na(result$btn.matrix))) {
       result$split.max <- as.integer(result$split.max)
 
       #named <- colnames(result1$columns)[result$split.max]
       #      node$caption <- paste(colnames(result1$columns)[result$split.max])
       best_subset_col_id = result$split.max
       best_values = result1$expressions[ (best_subset_col_id-1)*3 +1]$value
-
+      } else {
+        best_values <- result$split.max
+      }
       node$rule = list(variable=result$col.max, relation="%in%", 
                        value=best_values, 
                        name = result$name.max)

tests/testthat/test-dummy-split.R

@@ -5,7 +5,7 @@ set.seed(458)
 n <- 500
 var_unordered <- factor(sample(c("lightning","rain","sunshine","snow"),n,TRUE))
 var_grp <- factor((var_unordered %in% c("rain","sunshine"))) 
-x <- rnorm(n)+ifelse(var_grp,20,0)
+x <- rnorm(n)+ifelse(var_grp==TRUE,20,0)
 
 # data frame has only a dummy predictor
 df <- data.frame(x=x, var_grp)