R: Classes Corresponding to Basic Structures

StructureClasses {methods} | R Documentation

## Classes Corresponding to Basic Structures

### Description

The virtual class `structure` and classes that extend it are formal classes analogous to S language structures such as arrays and time-series.

### Usage

    ## The following class names can appear in method signatures,
    ## as the class in as() and is() expressions, and, except for
    ## the classes commented as VIRTUAL, in calls to new()

    "matrix"
    "array"
    "ts"

    "structure" ## VIRTUAL

### Objects from the Classes

Objects can be created by calls of the form `new(Class, ...)`, where `Class` is the quoted name of the specific class (e.g., `"matrix"`), and the other arguments, if any, are interpreted as arguments to the corresponding function, e.g., to function `matrix()`. There is no particular advantage over calling those functions directly, unless you are writing software designed to work for multiple classes, perhaps with the class name and the arguments passed in.

Objects created from the classes `"matrix"` and `"array"` are unusual, to put it mildly, and have been for some time. Although they may appear to be objects from these classes, they do not have the internal structure of either an S3 or S4 class object. In particular, they have no `"class"` attribute and are not recognized as objects with classes (that is, both `is.object` and `isS4` will return `FALSE` for such objects). However, methods (both S4 and S3) can be defined for these pseudo-classes and new classes (both S4 and S3) can inherit from them.

That the objects still behave as if they came from the corresponding class (most of the time, anyway) results from special code recognizing such objects being built into the base code of R. For most purposes, treating the classes in the usual way will work, fortunately. One consequence of the special treatment is that these two classesmay be used as the data part of an S4 class; for example, you can get away with `contains = "matrix"` in a call to `setGeneric` to create an S4 class that is a subclass of `"matrix"`. There is no guarantee that everything will work perfectly, but a number of classes have been written in this form successfully.

Note that a class containing `"matrix"` or `"array"` will have a `.Data` slot with that class. This is the only use of `.Data` other than as a pseudo-class indicating the type of the object. In this case the type of the object will be the type of the contained matrix or array. See `Classes` for a general discussion.

The class `"ts"` is basically an S3 class that has been registered with S4, using the `setOldClass` mechanism. Versions of R through 2.7.0 treated this class as a pure S4 class, which was in principal a good idea, but in practice did not allow subclasses to be defined and had other intrinsic problems. (For example, setting the `"tsp"` parameters as a slot often fails because the built-in implementation does not allow the slot to be temporarily inconsistent with the length of the data. Also, the S4 class prevented the correct specification of the S3 inheritance for class `"mts"`.)

Time-series objects, in contrast to matrices and arrays, have a valid S3 class, `"ts"`, registered using an S4-style definition (see the documentation for `setOldClass` in the examples section for an abbreviated listing of how this is done. The S3 inheritance of `"mts"` in package stats is also registered. These classes, as well as `"matrix"` and `"array"` should be valid in most examples as superclasses for new S4 class definitions.

All of these classes have special S4 methods for `initialize` that accept the same arguments as the basic generator functions, `matrix`, `array`, and `ts`, in so far as possible. The limitation is that a class that has more than one non-virtual superclass must accept objects from that superclass in the call to `new`; therefore, a such a class (what is called a “mixin” in some languages) uses the default method for `initialize`, with no special arguments.

### Extends

The specific classes all extend class `"structure"`, directly, and class `"vector"`, by class `"structure"`.

### Methods

coerce

  Methods are defined to coerce arbitrary objects to these classes, by calling the corresponding basic function, for example, `as(x, "matrix")` calls `as.matrix(x)`. If `strict = TRUE` in the call to `as()`, the method goes on to delete all other slots and attributes other than the `dim` and `dimnames`.

Ops

  Group methods (see, e.g., `S4groupGeneric`) are defined for combinations of structures and vectors (including special cases for array and matrix), implementing the concept of vector structures as in the reference. Essentially, structures combined with vectors retain the structure as long as the resulting object has the same length. Structures combined with other structures remove the structure, since there is no automatic way to determine what should happen to the slots defining the structure.

  Note that these methods will be activated when a package is loaded containing a class that inherits from any of the structure classes or class `"vector"`.

### References

Chambers, John M. (2008) Software for Data Analysis: Programming with R Springer. (For the R version.)

Chambers, John M. (1998) Programming with Data Springer (For the original S4 version.)

Becker, R. A., Chambers, J. M. and Wilks, A. R. (1988) The New S Language. Wadsworth & Brooks/Cole (for the original vector structures).

### See Also

Class nonStructure, which enforces the alternative model, in which all slots are dropped if any math transformation or operation is applied to an object from a class extending one of the basic classes.

### Examples

    showClass("structure")

    ## explore a bit :
    showClass("ts")
    (ts0 <- new("ts"))
    str(ts0)

    showMethods("Ops") # six methods from these classes, but maybe many more

[Package methods version 3.1.2 Index]