unary class union of an S3 class
On Fri, Mar 18, 2016 at 2:53 PM, Herv? Pag?s <hpages at fredhutch.org> wrote:
Hi,
Short story
-----------
setClassUnion("ArrayLike", "array")
showClass("ArrayLike") # no slot
setClass("MyArrayLikeConcreteSubclass",
contains="ArrayLike",
representation(stuff="ANY")
)
showClass("MyArrayLikeConcreteSubclass") # 2 slots!!
That doesn't seem right.
Long story
----------
S4 provides at least 3 ways to create a little class hierarchy
like this:
FooLike ............. virtual class with no slot
^ ^
| |
foo anotherfoo ..... 2 concrete subclasses
(1) The "standard" way: define FooLike first, then foo and anotherfoo
as subclasses of FooLike:
setClass("FooLike")
setClass("foo",
contains="FooLike",
representation(stuff="ANY")
)
setClass("anotherfoo",
contains="FooLike",
representation(stuff="ANY")
)
showClass("FooLike") # displays foo and anotherfoo as
# known subclasses
x1 <- new("foo")
is(x1, "foo") # TRUE
is(x1, "FooLike") # TRUE
is(x1, "anotherfoo") # FALSE
x2 <- new("anotherfoo")
is(x2, "anotherfoo") # TRUE
is(x2, "FooLike") # TRUE
is(x2, "foo") # FALSE
Everything works as expected.
(2) Using a class union: define foo and anotherfoo first, then FooLike
as the union of foo and anotherfoo:
setClass("foo", representation(stuff="ANY"))
setClass("anotherfoo", representation(stuff="ANY"))
setClassUnion("FooLike", c("foo", "anotherfoo"))
showClass("FooLike") # displays foo and anotherfoo as
# known subclasses
(3) Using a *unary* class union: define foo first, then FooLike as the
(unary) union of foo, then anotherfoo as a subclass of FooLike:
setClass("foo", representation(stuff="ANY"))
setClassUnion("FooLike", "foo")
showClass("FooLike") # displays foo as the only known subclass
setClass("anotherfoo",
contains="FooLike",
representation(stuff="ANY")
)
showClass("FooLike") # now displays foo and anotherfoo as
# known subclasses
The 3 ways lead to the same hierarchy. However the 3rd way is
interesting because it allows one to define the FooLike virtual
class as the parent of an existing foo class that s/he doesn't
control.
Why not use setIs() for this? Everything then behaves as expected. I don't think it makes much sense to "contain" a class union. Rather, you just want to establish the inheritance relationship.
For example, to define an ArrayLike class:
setClassUnion("ArrayLike", "array")
showClass("ArrayLike") # displays array as a known subclass
Note that ArrayLike is virtual with no slots (analog to a Java
Interface), which is what is expected.
setClass("MyArrayLikeConcreteSubclass",
contains="ArrayLike",
representation(stuff="ANY")
)
showClass("MyArrayLikeConcreteSubclass") # shows 2 slots!!
What is the .Data slot doing here? I would expect to see that slot
if MyArrayLikeConcreteSubclass was extending array but this is not
the case here.
a <- new("MyArrayLikeConcreteSubclass")
is(a, "MyArrayLikeConcreteSubclass") # TRUE --> ok
is(a, "ArrayLike") # TRUE --> ok
is(a, "array") # FALSE --> ok
But:
is.array(a) # TRUE --> not ok!
Is is.array() confused by the presence of the .Data slot?
It looks like the unary union somehow equates ArrayLike and array and thus makes ArrayLike confer a dim attribute (and thus is.array(a) returns TRUE). Since S4 objects cannot have attributes that are not slots, it must do this via a data part, thus the .Data slot.
I can fix it by defining an "is.array" method for
MyArrayLikeConcreteSubclass objects:
setMethod("is.array", "MyArrayLikeConcreteSubclass",
function(x) FALSE
)
However, it feels that I shouldn't have to do this.
Is the presence of the .Data slot in MyArrayLikeConcreteSubclass
objects an unintended feature?
Thanks,
H.
sessionInfo()
R Under development (unstable) (2016-01-07 r69884) Platform: x86_64-pc-linux-gnu (64-bit) Running under: Ubuntu 14.04.4 LTS locale: [1] LC_CTYPE=en_US.UTF-8 LC_NUMERIC=C [3] LC_TIME=en_US.UTF-8 LC_COLLATE=en_US.UTF-8 [5] LC_MONETARY=en_US.UTF-8 LC_MESSAGES=en_US.UTF-8 [7] LC_PAPER=en_US.UTF-8 LC_NAME=C [9] LC_ADDRESS=C LC_TELEPHONE=C [11] LC_MEASUREMENT=en_US.UTF-8 LC_IDENTIFICATION=C attached base packages: [1] stats graphics grDevices utils datasets methods base -- Herv? Pag?s Program in Computational Biology Division of Public Health Sciences Fred Hutchinson Cancer Research Center 1100 Fairview Ave. N, M1-B514 P.O. Box 19024 Seattle, WA 98109-1024 E-mail: hpages at fredhutch.org Phone: (206) 667-5791 Fax: (206) 667-1319
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