R Under development (unstable) (2024-02-25 r85988 ucrt) -- "Unsuffered Consequences"
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> # test.rpart.plot.R
> # Check for porting problems by building a few simple models.
> # For much more comprehensive tests see rpart.plot\inst\slowtests.
> library(rpart.plot)
Loading required package: rpart
> data(trees)     # anova model
> Volume <- rpart(Volume~., data=trees)
> print(rpart.rules(Volume, digits=5))
 Volume                             
 17.933 when Girth <  12.45         
 30.533 when Girth is 12.45 to 16.15
 55.929 when Girth >=          16.15
> data(ptitanic)  # binomial model
> ptitanic1 <- ptitanic
> ptitanic1$female <- ptitanic1$sex == "female" # logical variable
> ptitanic1$sex <- NULL
> ptitanic1$parch <- NULL
> survived <- rpart(survived ~ ., data=ptitanic1, method="class")
> print(rpart.rules(survived, clip.facs=TRUE))
 survived                                                                
     0.05 when not female & age <   9.5         & sibsp >= 3             
     0.14 when female                           & sibsp >= 3 &        3rd
     0.17 when not female & age >=          9.5                          
     0.38 when female     & age >=         27.5 & sibsp <  3 &        3rd
     0.39 when female     & age is 16.5 to 21.5 & sibsp <  3 &        3rd
     0.61 when female     & age is 21.5 to 27.5 & sibsp <  3 &        3rd
     0.73 when female     & age <  16.5         & sibsp <  3 &        3rd
     0.89 when not female & age <   9.5         & sibsp <  3             
     0.93 when female                                        & 1st or 2nd
> options(digits=4) # avoid numerical discrepancies across machines and R versions
> options(width=1e3)
> print(head(rpart.predict(survived, rules=TRUE)))
    died survived                                                                              
1 0.0680   0.9320 because female is 1                                    & pclass is 1st or 2nd
2 0.1111   0.8889 because female is 0 & age <   9.5         & sibsp <  3                       
3 0.0680   0.9320 because female is 1                                    & pclass is 1st or 2nd
4 0.8291   0.1709 because female is 0 & age >=          9.5                                    
5 0.0680   0.9320 because female is 1                                    & pclass is 1st or 2nd
6 0.8291   0.1709 because female is 0 & age >=          9.5                                    
> ptitanic1 <- NULL # delete the data, will affect male and sibsp in printed rules
> print(rpart.rules(survived, roundint=FALSE)) # roundint=FALSE else warning
 survived                                                                               
     0.05 when female <  0.5 & age <   9.5         & sibsp >= 2.5                       
     0.14 when female >= 0.5                       & sibsp >= 2.5 & pclass is        3rd
     0.17 when female <  0.5 & age >=          9.5                                      
     0.38 when female >= 0.5 & age >=         27.5 & sibsp <  2.5 & pclass is        3rd
     0.39 when female >= 0.5 & age is 16.5 to 21.5 & sibsp <  2.5 & pclass is        3rd
     0.61 when female >= 0.5 & age is 21.5 to 27.5 & sibsp <  2.5 & pclass is        3rd
     0.73 when female >= 0.5 & age <  16.5         & sibsp <  2.5 & pclass is        3rd
     0.89 when female <  0.5 & age <   9.5         & sibsp <  2.5                       
     0.93 when female >= 0.5                                      & pclass is 1st or 2nd
> data(iris)      # multiclass model
> Species <- rpart(Species ~ ., data=iris, method="class")
> print(rpart.rules(Species))
    Species  seto vers virg                                               
     setosa [1.00  .00  .00] when Petal.Length <  2.5                     
 versicolor [ .00  .91  .09] when Petal.Length >= 2.5 & Petal.Width <  1.8
  virginica [ .00  .02  .98] when Petal.Length >= 2.5 & Petal.Width >= 1.8
> 
> proc.time()
   user  system elapsed 
   0.32    0.14    0.40