When does initialize check for object validity? - r

From Chambers' (excellent) Extending R (2016):
A validity method will be called automatically from the default method for initialize(). The recommended form of an initialize method ends with a callNextMethod() call, to ensure that subclass slots can be specified in a call to the generator for the class. If this convention is followed, initialization will end with a call to the default method, and the validity method will be called after all initialization has occurred.
I thought I understood, but the behavior I am getting does not seem to follow this convention.
setClass("A", slots = c(s1 = "numeric"))
setValidity("A", function(object) {
if (length(object#s1) > 5) {
return("s1 longer than 5")
}
TRUE
})
setMethod("initialize", "A", function(.Object, s1, ...) {
if (!missing(s1)) .Object#s1 <- s1 + 4
callNextMethod(.Object, ...)
})
A <- new("A", rep(1.0, 6))
A
# An object of class "A"
# Slot "s1":
# [1] 5 5 5 5 5 5
validObject(A)
# Error in validObject(A) : invalid class “A” object: s1 longer than 5
I expected the validity checking to be done by adding callNextMethod() to the end of the initialize method. Adding an explicit validObject(.Object) before callNextMethod() works, but I am clearly not understanding something here.
Obviously, I can also do all the same checks in the validity method, but ideally all of the validity checking would occur within setValidity so future edits live in one place.
Changing the initialize function slightly gives the desired result -- is there a reason to use one approach over the other? Chambers seems to prefer using .Object#<- whereas I have seen the following method elsewhere (Gentlemman & Hadley).
setMethod("initialize", "A", function(.Object, s1, ...) {
if (!missing(s1)) s1 + 4
else s1 <- numeric()
callNextMethod(.Object, s1 = s1, ...)
})

Perhaps the best guide comes from initialize itself — if you inspect the code for the default method
getMethod("initialize",signature(.Object="ANY"))
then you see that it does indeed contain an explicit call to validObject at the end:
...
validObject(.Object)
}
.Object
}
so if you define your own initialize method, the most similar thing you could do would be to call it at the end of your method, right before you call callNextMethod.
In your case, when you call callNextMethod, that is only checking that the slot you have created is a valid numeric object (which it is), rather than checking the validity of the larger object (which requires the s1 slot to be no longer than 5 elements)

Related

Modifying calls in function arguments

How can a function inspect and modify the arguments of a call that it received as argument?
Application: A user feeds a call to function a as an argument to function b, but they forget to specify one of the required arguments of a. How can function b detect the problem and fix it?
In this minimal example, function a requires two arguments:
a <- function(arg1, arg2) {
return(arg1 + arg2)
}
Function b accepts a call and an argument. The commented lines indicate what I need to do:
b <- function(CALL, arg3) {
# 1. check if `arg2` is missing from CALL
# 2. if `arg2` is missing, plug `arg3` in its place
# 3. return evaluated call
CALL
}
Expected behavior:
b(CALL = a(arg1 = 1, arg2 = 2), arg3 = 3)
> 3
b(CALL = a(arg1 = 1), arg3 = 3)
> 4
The second call currently fails because the user forgot to specify the required arg2 argument. How can function b fix this mistake automatically?
Can I exploit lazy evaluation to modify the call to a before it is evaluated? I looked into rlang::modify_call but couldn't figure it out.
Here's a method that would work
b <- function(CALL, arg3) {
scall <- substitute(CALL)
stopifnot(is.call(scall)) #check that it's a call
lcall <- as.list(scall)
if (!"arg2" %in% names(lcall)) {
lcall <- c(lcall, list(arg2 = arg3))
}
eval.parent(as.call(lcall))
}
We use substitute() to grab the unevaluated version the CALL parameter. We convert it to a list so we can modify it. Then we append to the list another list with the parameter name/value we want. Finally, we turn the list back into a call and then evaluate that call in the environment of the caller rather than in the function body itself.
If you wanted to use rlang::modify_call and other rlang functions you could use
b <- function(CALL, arg3) {
scall <- rlang::enquo(CALL)
stopifnot(rlang::quo_is_call(scall))
if (!"arg2" %in% names(rlang::quo_get_expr(scall))) {
scall <- rlang::call_modify(scall, arg2=arg3)
}
rlang::eval_tidy(scall, env = rlang::caller_env())
}
I don't see why fancy language manipulation is needed. The problem is what to do when a, which requires 2 arguments, is supplied only 1. Wrapping it with b, which has a default value for the 2nd argument, solves this.
b <- function(arg1, arg2=42)
{
a(arg1, arg2)
}
b(1)
# [1] 43
b(1, 2)
# [1] 3

Partial matching confusion when arguments passed through dots ('...')

I've been working on an R package that is just a REST API wrapper for a graph database. I have a function createNode that returns an object with class node and entity:
# Connect to the db.
graph = startGraph("http://localhost:7474/db/data/")
# Create two nodes in the db.
alice = createNode(graph, name = "Alice")
bob = createNode(graph, name = "Bob")
> class(alice)
[1] "node" "entity"
> class(bob)
[1] "node" "entity"
I have another function, createRel, that creates a relationship between two nodes in the database. It is specified as follows:
createRel = function(fromNode, type, toNode, ...) {
UseMethod("createRel")
}
createRel.default = function(fromNode, ...) {
stop("Invalid object. Must supply node object.")
}
createRel.node = function(fromNode, type, toNode, ...) {
params = list(...)
# Check if toNode is a node.
stopifnot("node" %in% class(toNode))
# Making REST API calls through RCurl and stuff.
}
The ... allows the user to add an arbitrary amount of properties to the relationship in the form key = value. For example,
rel = createRel(alice, "KNOWS", bob, since = 2000, through = "Work")
This creates an (Alice)-[KNOWS]->(Bob) relationship in the db, with the properties since and through and their respective values. However, if a user specifies properties with keys from or to in the ... argument, R gets confused about the classes of fromNode and toNode.
Specifying a property with key from creates confusion about the class of fromNode. It is using createRel.default:
> createRel(alice, "KNOWS", bob, from = "Work")
Error in createRel.default(alice, "KNOWS", bob, from = "Work") :
Invalid object. Must supply node object.
3 stop("Invalid object. Must supply node object.")
2 createRel.default(alice, "KNOWS", bob, from = "Work")
1 createRel(alice, "KNOWS", bob, from = "Work")
Similarly, if a user specifies a property with key to, there is confusion about the class of toNode, and stops at the stopifnot():
Error: "node" %in% class(toNode) is not TRUE
4 stop(sprintf(ngettext(length(r), "%s is not TRUE", "%s are not all TRUE"),
ch), call. = FALSE, domain = NA)
3 stopifnot("node" %in% class(toNode))
2 createRel.node(alice, "KNOWS", bob, to = "Something")
1 createRel(alice, "KNOWS", bob, to = "Something")
I've found that explicitly setting the parameters in createRel works fine:
rel = createRel(fromNode = alice,
type = "KNOWS",
toNode = bob,
from = "Work",
to = "Something")
# OK
But I am wondering how I need to edit my createRel function so that the following syntax will work without error:
rel = createRel(alice, "KNOWS", bob, from = "Work", to = "Something")
# Errors galore.
The GitHub user who opened the issue mentioned it is most likely a conflict with setAs on dispatch, which has arguments called from and to. One solution is to get rid of ... and change createRel to the following:
createRel = function(fromNode, type, toNode, params = list()) {
UseMethod("createRel")
}
createRel.default = function(fromNode, ...) {
stop("Invalid object. Must supply node object.")
}
createRel.node = function(fromNode, type, toNode, params = list()) {
# Check if toNode is a node.
stopifnot("node" %in% class(toNode))
# Making REST API calls through RCurl and stuff.
}
But, I wanted to see if I had any other options before making this change.
Not really an answer, but...
The problem is that the user-provided argument 'from' is being (partially) matched to the formal argument 'fromNode'.
f = function(fromNode, ...) fromNode
f(1, from=2)
## [1] 2
The rules are outlined in section 4.3.2 of RShowDoc('R-lang'), where named arguments are exact matched, then partial matched, and then unnamed arguments are assigned by position.
It's hard to know how to enforce exact matching, other than using single-letter argument names! Actually, for a generic this might not be as trite as it sounds -- x is a pretty generic variable name. If 'from' and 'to' were common arguments to ... you could change the argument list to "fromNode, , ..., from, to", check for missing(from) in the body of the function, and act accordingly; I don't think this would be pleasant, and the user would invariable provide an argument 'fro'.
While enforcing exact matching (and errors, via warn=2) by setting global options() might be helpful in debugging (though by then you'd probably know what you were looking for!) it doesn't help the package author who is trying to write code to work for users in general.
It might be reasonable to ask on the R-devel mailing list whether it might be time for this behavior to be changed (on the 'several releases' time scale); partial matching probably dates as a 'convenience' from the days before tab completion.

Validity checks for ReferenceClass

S4 classes allow you to define validity checks using validObject() or setValidity(). However, this does not appear to work for ReferenceClasses.
I have tried adding assert_that() or if (badness) stop(message) clauses to the $initialize() method of a ReferenceClass. However, when I simulate loading the package (using devtools::load_all()), it must try to create some prototype class because the initialize method executes and fails (because no fields have been set).
What am I doing wrong?
Implement a validity method on the reference class
A = setRefClass("A", fields=list(x="numeric", y="numeric"))
setValidity("A", function(object) {
if (length(object$x) != length(object$y)) {
"x, y lengths differ"
} else NULL
})
and invoke the validity method explicitly
> validObject(A())
[1] TRUE
> validObject(A(x=1:5, y=5:1))
[1] TRUE
> validObject(A(x=1:5, y=5:4))
Error in validObject(A(x = 1:5, y = 5:4)) :
invalid class "A" object: x, y lengths differ
Unfortunately, setValidity() would need to be called explicitly as the penultimate line of an initialize method or constructor.
Ok so you can do this in initialize. It should have the form:
initialize = function (...) {
if (nargs()) return ()
# Capture arguments in list
args <- list(...)
# If the field name is passed to the initialize function
# then check whether it is valid and assign it. Otherwise
# assign a zero length value (character if field_name has
# that type)
if (!is.null(args$field_name)) {
assert_that(check_field_name(args$field_name))
field_name <<- field_name
} else {
field_name <<- character()
}
# Make sure you callSuper as this will then assign other
# fields included in ... that weren't already specially
# processed like `field_name`
callSuper(...)
}
This is based on the strategy set out in the lme4 package.

Modify contents of object with "call by reference"

I am trying to modify the contents of an object defined by a self-written class with a function that takes two objects of this class and adds the contents.
setClass("test",representation(val="numeric"),prototype(val=1))
I know that R not really works with "call by reference" but can mimic that behaviour with a method like this one:
setGeneric("value<-", function(test,value) standardGeneric("value<-"))
setReplaceMethod("value",signature = c("test","numeric"),
definition=function(test,value) {
test#val <- value
test
})
foo = new("test") #foo#val is 1 per prototype
value(foo)<-2 #foo#val is now set to 2
Until here, anything I did and got as result is consitent with my research here on stackexchange,
Call by reference in R (using function to modify an object)
and with this code from a lecture (commented and written in German)
What I wish to achieve now is a similar result with the following method:
setGeneric("add<-", function(testA,testB) standardGeneric("add<-"))
setReplaceMethod("add",signature = c("test","test"),
definition=function(testA,testB) {
testA#val <- testA#val + testB#val
testA
})
bar = new("test")
add(foo)<-bar #should add the value slot of both objects and save the result to foo
Instead I get the following error:
Error in `add<-`(`*tmp*`, value = <S4 object of class "test">) :
unused argument (value = <S4 object of class "test">)
The function call works with:
"add<-"(foo,bar)
But this does not save the value into foo. Using
foo <- "add<-"(foo,bar)
#or using
setMethod("add",signature = c("test","test"), definition= #as above... )
foo <- add(foo,bar)
works but this is inconsistent with the modifying method value(foo)<-2
I have the feeling that I am missing something simple here.
Any help is very much appreciated!
I do not remember why, but for <- functions, the last argument must be named 'value'.
So in your case:
setGeneric("add<-", function(testA,value) standardGeneric("add<-"))
setReplaceMethod("add",signature = c("test","test"),
definition=function(testA,value) {
testA#val <- testA#val + value#val
testA
})
bar = new("test")
add(foo)<-bar
You may also use a Reference class ig you want to avoid the traditional arguments as values thing.

Advanced error handling: systematically try a range of handlers

Another follow up to this and this.
Actual question
Question 1
Upon running into some condition (say a simpleError), how can I invoke a respective restart handler that systematically tests a range of actual handler functions until one is found that does not result in another condition? If the last available handler has been tried, the default abortion restart handler should be invoked (invokeRestart("abort")). The implementation should allow for a flexible specification of the actual "handler suite" to use.
Question 2
I don't understand how a) the a test function that is specified alongside a restart handler works and b) where it would make sense to use it. Any suggestions? A short example would be great!
The help page of withRestarts says:
The most flexible form of a restart specification is as a list that can include several fields, including handler, description, and test. The test field should contain a function of one argument, a condition, that returns TRUE if the restart applies to the condition and FALSE if it does not; the default function returns TRUE for all conditions.
For those interested in more details
Below you'll find my first approach with respect to question 1, but I'm sure there's something much more cleaner/more straight-forward out there ;-)
foo <- function(x, y) x + y
fooHandled <- function(
x,
y,
warning=function(cond, ...) {
invokeRestart("warninghandler", cond=cond, ...)},
error=function(
cond,
handlers=list(
expr=expression(x+"b"),
expr=expression(x+"c"),
expr=expression(x+100)
),
...) {
invokeRestart("errorhandler", cond=cond, handlers=handlers, ...)
}
) {
expr <- expression(foo(x=x, y=y))
withRestarts(
withCallingHandlers(
expr=eval(expr),
warning=warning,
error=error
),
warninghandler=function(cond, ...) warning(cond),
errorhandler=function(cond, handlers, ...) {
idx <- 1
do.continue <- TRUE
while (do.continue) {
message(paste("handler:", idx))
expr <- handlers[[idx]]
out <- withRestarts(
tryCatch(
expr=eval(expr),
error=function(cond, ...) {
print(cond)
message("trying next handler ...")
return(cond)
}
)
)
idx <- idx + 1
do.continue <- inherits(out, "simpleError")
}
return(out)
}
)
}
> fooHandled(x=1, y=1)
[1] 2
> fooHandled(x=1, y="a")
handler: 1
<simpleError in x + "b": non-numeric argument to binary operator>
trying next handler ...
handler: 2
<simpleError in x + "c": non-numeric argument to binary operator>
trying next handler ...
handler: 3
[1] 101
EDIT
I'd also be interested in hearing how to substitute the tryCatch part with a withCallingHandlers part. Seems like withCallingHandlers() doesn't really return anything that could be picked up to determine the value of do.continue

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