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Henrik Bengtsson hb@maths.lth.se (MSc Computer Science, PhD candidate in Statistics)

Object-oriented programming and programming style guidelines for R. Henrik Bengtsson hb@maths.lth.se (MSc Computer Science, PhD candidate in Statistics) Mathematical Statistics Centre for Mathematical Sciences Lund University, Sweden. Outline. Objects and Classes

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Henrik Bengtsson hb@maths.lth.se (MSc Computer Science, PhD candidate in Statistics)

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  1. Object-oriented programming and programming style guidelines for R Henrik Bengtsson hb@maths.lth.se (MSc Computer Science, PhD candidate in Statistics) Mathematical Statistics Centre for Mathematical Sciences Lund University, Sweden

  2. Outline • Objects and Classes • Concepts of object-oriented programming • A complete example in [R] – Shapes • References in [R] • [R] Programming Style Guidelines with a few coding conventions.

  3. Part I:Object-oriented programming in [R]

  4. Methods MicroarrayData MicroarrayData MicroarrayData Layout Objects and Classes Class name Objects of different classes Fields A class is the recipe for a certain cake... ...and the objects are the actual cakes of that kind. a class is a data type - an object is an instance of a class

  5. Encapsulation, Inheritance, and Polymorphism Encapsulation means that a group of related properties, methods, and other members are treated as a single unit or object. Objects can control how properties are changed and methods are executed. Why: Makes it easier to change your implementation at a later date by letting you hide implementation details of your objects, a practice called data hiding.

  6. Encapsulation, Inheritance, and Polymorphism Inheritancedescribes the ability to create new classes based on an existing class. The new class inherits all the properties and methods and events of the base class, and can be customized with additional properties and methods. Why: Promotes code reuse since the code for the methods of the subclasses do not need to be rewritten.

  7. Encapsulation, Inheritance, and Polymorphism Polymorphism means that you can have multiple classes that can be used interchangeably, even though each class implements the same properties or methods in different ways. Polymorphism is essential to object-oriented programming because it allows you to use items with the same names, no matter what type of object is in use at the moment. Why: Inheritance becomes more flexible. Subclasses can keep some methods inherited from their super classes and override others.

  8. Overloading and Overriding Overloaded members are used to provide different versions of a property or method that have the same name, but that accept a different number of parameters, or parameters with different data types. Currently not supported in [R]. Overridden properties and methods are used to replace an inherited property or method that is not appropriate in a derived class. Overridden members must accept the same data type and number of arguments (not enforced in [R]). Derived classes inherit overridden members.

  9. association (“using”) abstract static 1 0..* private inheritance (“is a”) Unified Modeling Language (UML) class diagram

  10. polymorphism static method call Interactive example # Create different Shape objects and store them in a list allShapes <- list( Rectangle(Point(0,0), width=5, height=8, color="blue"), Square(Point(-2,-5), side=3, color="red"), Triangle(Point(3,3), width=10, height=12, color="orange"), Triangle(Point(-4,-2.5), width=12, height=3, color="purple"), Circle(Point(-4,4), radius=5, color="green") ) # Plot all shapes for shapein allShapes paint(shape) # Get first mouse click click <- getFromClick(Point) while click is inside plot region # Check with all shapes if they contains the click coordinates. for shapein allShapes if contains(shape, click) then paint(click, col=getColor(shape), style="disc") else paint(click, style="circle") # Get another mouse click click <- getFromClick(Point) Either shape$contains(click) or contains(shape, click)

  11. private class method static Code for a class setClassS3("Point", function(x=0, y=0) { extend(Object(), "Point", .x = x, # private .y = y # private ); }) setMethodS3("getX", "Point", function(this) { this$.x; }) setMethodS3("getY", "Point", function(this) { this$.y; }) setMethodS3("getXY", "Point", function(this) { c(this$.x, this$.y); }) setMethodS3("setX", "Point", function(this, newX) { this$.x <- newX; # Using reference! }) setMethodS3("setY", "Point", function(this, newY) { this$.y <- newY; }) setMethodS3("setXY", "Point", function(this, newXY) { this$.x <- newXY[1]; this$.y <- newXY[2]; }) setMethodS3("getFromClick", "Point", function(this) { xy <- locator(n=1); # Ask for one mouse click Point(x=xy$x, y=xy$y); }) setMethodS3("print", "Point", function(this) { print(sprintf("%s at (%.3f,%.3f).", getClass(this), this$.x, this$.y)); }) setMethodS3("paint", "Point", function(this, ...) { points(this$.x, this$.y, ...); })

  12. References • One reference can only refer to one object. • One object can have one or several references referring to it. c <- Circle(Point(0,0), radius=2);c1 <- c;setRadius(c1, 4);getRadius(c); # will give 4! • Results in more user-friendly packages for the end user! • Makes design and implementation much easier. • Saves memory.

  13. However, reference can be emulated by encapsulating such functionalities in a root class Object, which all classes are enforced to be derived from. Contact me to get the code for Object, setClassS3() and setMethodS3(). References, how? • References are not supported by [R] since everything is copy-by-value. Have to return new instance:setValue <- function(list, value) { list$value; return(list);} • What you really want to do:setValue <- function(list, value) { list$value;} • Why: For example, each of the Shape objects can use (refer to) the same Point object to specify its position. By moving the Point object, all Shape object will then move along. This is not possible without references.

  14. Part II:[R] Programming Style Guidelines

  15. Programming Style Guidelines • 80% of the lifetime cost of a piece of software goes to maintenance. • Hardly any software is maintained for its whole life by the original author. • Code conventions improve the readability of the software, allowing programmers to understand new code more quickly and thoroughly. • If you ship your source code as a product, you need to make sure it is as well packaged and clean as any other product you create.

  16. [R] Coding Convention • Currently there is no RCC and people invent their own conventions or not at all. • We suggest to adapt a modified version of the Java coding convention, which has proved to be successful and is a de facto standard.

  17. Class names

  18. Field and variable names

  19. Method names

  20. File names

  21. Where to start Tutorials and source code: • R Programming Style Guidelines • Programming with References in R • Implementing support for references in R http://www.maths.lth.se/help/R/

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