It would be great to be able to define a matrix-like abstraction
independent of 'matrix' and 'DelayedMatrix'. It could also encompass
objects from the Matrix package and potentially other things. So you
could define a parent class of 'matrix' using setClassUnion() and then
use setIs() to establish further derivations:
setClassUnion("MatrixLike", "matrix")
setIs("DelayedMatrix", "MatrixLike")
Michael
On Mon, Apr 30, 2018 at 11:35 AM, Hervé Pagès <hpa...@fredhutch.org> wrote:
> The class union should probably be:
>
> setClassUnion("matrixOrDelayed", c("matrix", "DelayedMatrix"))
>
> i.e. use DelayedMatrix instead of DelayedArray.
>
> So in addition to the class union and to Stephanie's solution, which
> IMO are both valid solutions, you could also go for something like this:
>
> myNewRowMeans <- function(x,...)
> {
> if (length(dim(x)) != 2)
> stop("'x' must be a matrix-like object")
> ...
> )
>
> that is, just a regular function that checks that 'x' is matrix-like
> based on its number of dimensions. If you really want to restrict to
> matrix and DelayedMatrix only, replace the test with
>
> if (!(is.matrix(x) || is(x, "DelayedMatrix")))
> stop("'x' must be a matrix or DelayedMatrix object")
>
> The difference being that now the function will reject matrix-like
> objects that are not matrix or DelayedMatrix objects (e.g. a Matrix
> derivative from the Matrix package).
>
> Cheers,
> H.
>
>
>
> On 04/30/2018 09:29 AM, Stephanie M. Gogarten wrote:
>>
>> Rather than a class union, how about an internal function that is called
>> by the methods for both matrix and DelayedArray:
>>
>>
>> setGeneric("myNewRowMeans", function(x,...) {
>> standardGeneric("myNewRowMeans")})
>>
>> #' @importFrom DelayedArray rowMeans
>> .myNewRowMeans <- function(x,...){
>> # a lot of code independent of x
>> print("This is a lot of code shared regardless of class of x\n")
>> # a lot of code that depends on x, but is dispatched by the functions
>> called
>> out<-rowMeans(x)
>> #a lot of code based on output of out
>> out<-out+1
>> return(out)
>> }
>>
>> setMethod("myNewRowMeans",
>> signature = "matrix",
>> definition = function(x,...){
>> .myNewRowMeans(x,...)
>> }
>> )
>>
>> setMethod("myNewRowMeans",
>> signature = "DelayedArray",
>> definition = function(x,...){
>> .myNewRowMeans(x,...)
>> }
>> )
>>
>>
>> On 4/30/18 9:10 AM, Tim Triche, Jr. wrote:
>>>
>>> But if you merge methods like that, the error method can be that much
>>> more
>>> difficult to identify. It took a couple of weeks to chase that bug down
>>> properly, and it ended up down to rowMeans2 vs rowMeans.
>>>
>>> I suppose the merged/abstracted method allows to centralize any such
>>> dispatch into one place and swap out ill-behaved methods once identified,
>>> so as long as DelayedArray/DelayedMatrixStats quirks are
>>> documented/understood, maybe it is better to create this union class?
>>>
>>> The Matrix/matrixStats/DelayedMatrix/DelayedMatrixStats situation has
>>> been
>>> "interesting" in practical terms, as seemingly simple abstractions appear
>>> to require more thought. That was my only point.
>>>
>>>
>>> --t
>>>
>>> On Mon, Apr 30, 2018 at 11:28 AM, Martin Morgan <
>>> martin.mor...@roswellpark.org> wrote:
>>>
>>>> But that issue will be fixed, so Tim's advice is inappropriate.
>>>>
>>>>
>>>> On 04/30/2018 10:42 AM, Tim Triche, Jr. wrote:
>>>>
>>>>> Don't do that. Seriously, just don't.
>>>>>
>>>>>
>>>>> https://urldefense.proofpoint.com/v2/url?u=https-3A__github.com_Bioconductor_DelayedArray_issues_16&d=DwIDaQ&c=eRAMFD45gAfqt84VtBcfhQ&r=BK7q3XeAvimeWdGbWY_wJYbW0WYiZvSXAJJKaaPhzWA&m=Rhy4i6H9xaY8HzWv9v_jhOnp5OyEpJcG52RP3nHorU8&s=olbErqY3_l7i45-WeTkaUNGalrQQr-7i59rhJVF6OGQ&e=
>>>>>
>>>>> --t
>>>>>
>>>>> On Mon, Apr 30, 2018 at 10:02 AM, Elizabeth Purdom <
>>>>> epur...@stat.berkeley.edu> wrote:
>>>>>
>>>>> Hello,
>>>>>>
>>>>>>
>>>>>> I am trying to extend my package to handle `HDF5Matrix` class ( or
>>>>>> more
>>>>>> generally `DelayedArray`). I currently have S4 functions for `matrix`
>>>>>> class. Usually I have a method for `SummarizedExperiment`, which will
>>>>>> call
>>>>>> call the method on `assay(x)` and I want the method to be able to deal
>>>>>> with
>>>>>> if `assay(x)` is a `DelayedArray`.
>>>>>>
>>>>>> Most of my functions, however, do not require separate code depending
>>>>>> on
>>>>>> whether `x` is a `matrix` or `DelayedArray`. They are making use of
>>>>>> existing functions that will make that choice for me, e.g. rowMeans or
>>>>>> subsetting. My goal right now is compatibility, not cleverness, and
>>>>>> I'm
>>>>>> not
>>>>>> creating HDF5 methods to handle other cases. (If something doesn't
>>>>>> currently exist, then I just enclose `x` with `data.matrix` or
>>>>>> `as.matrix`
>>>>>> and call the matrix into memory — for cleanliness and ease in updating
>>>>>> with
>>>>>> appropriate methods in future, I could make separate S4 functions for
>>>>>> these
>>>>>> specific tasks to dispatch, but that's outside of the scope of my
>>>>>> question). So for simplicity assume I don't really need to dispatch
>>>>>> *my
>>>>>> code* -- that the methods I'm going to use do that.
>>>>>>
>>>>>> The natural solution for me seem to use `setClassUnion` and I was
>>>>>> wondering if such a virtual class already exists? Or is there a better
>>>>>> way
>>>>>> to handle this?
>>>>>>
>>>>>> Here's a simple example, using `rowMeans` as my example:
>>>>>>
>>>>>> ```
>>>>>> setGeneric("myNewRowMeans", function(x,...) { standardGeneric("
>>>>>> myNewRowMeans")})
>>>>>> setClassUnion("matrixOrDelayed",members=c("matrix", "DelayedArray"))
>>>>>>
>>>>>> #' @importFrom DelayedArray rowMeans
>>>>>> setMethod("myNewRowMeans",
>>>>>> signature = "matrixOrDelayed",
>>>>>> definition = function(x,...){
>>>>>> # a lot of code independent of x
>>>>>> print("This is a lot of code shared
>>>>>> regardless
>>>>>> of
>>>>>> class of x\n")
>>>>>> # a lot of code that depends on x, but is
>>>>>> dispatched by the functions called
>>>>>> out<-rowMeans(x)
>>>>>> #a lot of code based on output of out
>>>>>> out<-out+1
>>>>>> return(out)
>>>>>> }
>>>>>> )
>>>>>> ```
>>>>>>
>>>>>> _______________________________________________
>>>>>> Bioc-devel@r-project.org mailing list
>>>>>>
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>>>>>>
>>>>>>
>>>>> [[alternative HTML version deleted]]
>>>>>
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>>>>>
>>>>>
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>>
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>
>
> --
> Hervé Pagès
>
> 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: hpa...@fredhutch.org
> Phone: (206) 667-5791
> Fax: (206) 667-1319
>
> _______________________________________________
> Bioc-devel@r-project.org mailing list
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