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Project 7

Goal: Implement the S3 class ChlorReads.  Here is the ChlorReads UML diagram.

Relevent Examples: Kid in the 5/18 Notes and Die

1. Create a constructor ChlorReads that inputs the fields id, name, gender, ldl, hdl, and trigl and returns a ChlorReads object.
    
2. Define a print.ChlorReads method that prints a ChlorReads object like this:
   

   > p1 <- ChlorReads(9876, "Virgil", "M", 248, 45, 148)
   > print(p1) 
   ID: 9876  Name: Virgil  Gender: M
   LDL: 248* HDL: 45+  Triglycerides: 148
   

   * means high risk value, + means borderline.  Use these cutoff values the three chloresterol values:
   

   Type	Range	Meaning	Symbol
   LDL	0 to 200	Normal	""
   LDL	200 to 240	Borderline	"+"
   LDL	240 and up	High Risk	"*"
   HDL	0 to 40	High Risk	"*"
   HDL	40 to 60	Borderline	"+"
   HDL	60 and up	Normal	" "
   Trigl	0 to 150	Normal	""
   Trigl	150 to 200	Borderline	"+"
   Trigl	200 and up	High Risk	"*"

   
   You can use an if-else statement to obtain the symbol. However, be careful not to start a new line with else:
   

   # Correct
   if (score >= 90) {
      grade = "A"
   } else if (score >= 80) {
      grade = "B"
   } else {
      grade = "C"
   }
   
   # Incorrect
   if (score >= 90) {
      grade = "A"
   } 
   else if (score >= 80) {
      grade = "B"
   } 
   else {
      grade = "C"
   }
   

3. Define the method plot.ChlorReads that plots the data in the ChlorReads object like this:
    
   
    
4. Define the accessor methods getPatientInfo.ChlorReads and getChloresterol.ChlorReads. First define the generic methods getPatientInfo and getCholesterol and the default methods getPatientInfo.default and getCholesterol.default. For example:
   

   > getPatientInfo(p1)
   ID   Name   Gender 
   9876 Virgil M
   > getChloresterol(p1)
   LDL HDL Trigl
   208  45 148
   

5. Write an R script that does the following:
    
   
   1. Tests the methods defined in 1 through 4.
       
   2. Uses the data in chlor-reads.txt to create a list lst of ChlorReads objects indexed as [[1]], [[2]], ... , [[length(lst)]]. To do this, you can use a for loop to process the rows of the data frame:
      

      lst <- NULL
      chlor <- read.table("chlor-reads.txt")
      for(i in 1:nrow(chlor)) {
         lst[[i]] <- ChlorReads(chlor[i, ]$id, as.character(chlor[i, ]$name),
            as.character(chlor[i, ]$gender), chlor[i, ]$ldl,  
            chlor[i, ]$hdl, chlor[i, ]$trigl)
      }
      

      The as.character method calls for the name and gender components are because these components are stored as factor objects in a data frame.
       
   3. Uses a for loop to print all of the ChlorReads objects in lst.
       
   4. Uses a for loop to plot all of the ChlorReads objects in lst to a PDF file.