Interesting. I tried something like that in the past i.e. start with
a unary setClassUnion() but then got into problems when I tried to add
new members to the union by **extending** the union class:
https://stat.ethz.ch/pipermail/r-devel/2016-March/072489.html
So it seems like I should have used setIs() instead.
Then later I realized that I could just do with having the 'seed' slot
of the DelayedArray class be "ANY" and having the validity method
checking that the slot actually contains something for which dim()
is not null. I actually adopted this "array-like == dim() is not NULL"
approach everywhere in the package. It's simple and works well.
H.
On 04/30/2018 01:33 PM, Michael Lawrence wrote:
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)
}
)
```
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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
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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
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