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_Details
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")
callsas.matrix(x)
. Ifstrict = TRUE
in the call toas()
, the method goes on to delete all other slots and attributes other than thedim
anddimnames
.- 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