[Rd] Subsetting the "ROW"s of an object

Michael Lawrence l@wrence@mich@el @ending from gene@com
Fri Jun 8 22:56:36 CEST 2018


Actually, it's sort of the opposite. Everything becomes a sequence of
integers internally, even when the argument is missing. So the same
amount of work is done, basically. ALTREP will let us improve this
sort of thing.

Michael

On Fri, Jun 8, 2018 at 1:49 PM, Hadley Wickham <h.wickham using gmail.com> wrote:
> Hmmm, yes, there must be some special case in the C code to avoid
> recycling a length-1 logical vector:
>
> dims <- c(4, 4, 4, 1e5)
>
> arr <- array(rnorm(prod(dims)), dims)
> dim(arr)
> #> [1]      4      4      4 100000
> i <- c(1, 3)
>
> bench::mark(
>   arr[i, TRUE, TRUE, TRUE],
>   arr[i, , , ]
> )[c("expression", "min", "mean", "max")]
> #> # A tibble: 2 x 4
> #>   expression                    min     mean      max
> #>   <chr>                    <bch:tm> <bch:tm> <bch:tm>
> #> 1 arr[i, TRUE, TRUE, TRUE]   41.8ms   43.6ms   46.5ms
> #> 2 arr[i, , , ]               41.7ms   43.1ms   46.3ms
>
>
> On Fri, Jun 8, 2018 at 12:31 PM, Berry, Charles <ccberry using ucsd.edu> wrote:
>>
>>
>>> On Jun 8, 2018, at 11:52 AM, Hadley Wickham <h.wickham using gmail.com> wrote:
>>>
>>> On Fri, Jun 8, 2018 at 11:38 AM, Berry, Charles <ccberry using ucsd.edu> wrote:
>>>>
>>>>
>>>>> On Jun 8, 2018, at 10:37 AM, Hervé Pagès <hpages using fredhutch.org> wrote:
>>>>>
>>>>> Also the TRUEs cause problems if some dimensions are 0:
>>>>>
>>>>>> matrix(raw(0), nrow=5, ncol=0)[1:3 , TRUE]
>>>>> Error in matrix(raw(0), nrow = 5, ncol = 0)[1:3, TRUE] :
>>>>>   (subscript) logical subscript too long
>>>>
>>>> OK. But this is easy enough to handle.
>>>>
>>>>>
>>>>> H.
>>>>>
>>>>> On 06/08/2018 10:29 AM, Hadley Wickham wrote:
>>>>>> I suspect this will have suboptimal performance since the TRUEs will
>>>>>> get recycled. (Maybe there is, or could be, ALTREP, support for
>>>>>> recycling)
>>>>>> Hadley
>>>>
>>>>
>>>> AFAICS, it is not an issue. Taking
>>>>
>>>> arr <- array(rnorm(2^22),c(2^10,4,4,4))
>>>>
>>>> as a test case
>>>>
>>>> and using a function that will either use the literal code `x[i,,,,drop=FALSE]' or `eval(mc)':
>>>>
>>>> subset_ROW4 <-
>>>>     function(x, i, useLiteral=FALSE)
>>>> {
>>>>    literal <- quote(x[i,,,,drop=FALSE])
>>>>    mc <- quote(x[i])
>>>>    nd <- max(1L, length(dim(x)))
>>>>    mc[seq(4,length=nd-1L)] <- rep(TRUE, nd-1L)
>>>>    mc[["drop"]] <- FALSE
>>>>    if (useLiteral)
>>>>        eval(literal)
>>>>    else
>>>>        eval(mc)
>>>> }
>>>>
>>>> I get identical times with
>>>>
>>>> system.time(for (i in 1:10000) subset_ROW4(arr,seq(1,length=10,by=100),TRUE))
>>>>
>>>> and with
>>>>
>>>> system.time(for (i in 1:10000) subset_ROW4(arr,seq(1,length=10,by=100),FALSE))
>>>
>>> I think that's because you used a relatively low precision timing
>>> mechnaism, and included the index generation in the timing. I see:
>>>
>>> arr <- array(rnorm(2^22),c(2^10,4,4,4))
>>> i <- seq(1,length = 10, by = 100)
>>>
>>> bench::mark(
>>>  arr[i, TRUE, TRUE, TRUE],
>>>  arr[i, , , ]
>>> )
>>> #> # A tibble: 2 x 1
>>> #>   expression        min    mean   median      max  n_gc
>>> #>   <chr>         <bch:t> <bch:t> <bch:tm> <bch:tm> <dbl>
>>> #> 1 arr[i, TRUE,…   7.4µs  10.9µs  10.66µs   1.22ms     2
>>> #> 2 arr[i, , , ]   7.06µs   8.8µs   7.85µs 538.09µs     2
>>>
>>> So not a huge difference, but it's there.
>>
>>
>> Funny. I get similar results to yours above albeit with smaller differences. Usually < 5 percent.
>>
>> But with subset_ROW4 I see no consistent difference.
>>
>> In this example, it runs faster on average using `eval(mc)' to return the result:
>>
>>> arr <- array(rnorm(2^22),c(2^10,4,4,4))
>>> i <- seq(1,length=10,by=100)
>>> bench::mark(subset_ROW4(arr,i,FALSE), subset_ROW4(arr,i,TRUE))[,1:8]
>> # A tibble: 2 x 8
>>   expression                      min     mean   median      max `itr/sec` mem_alloc  n_gc
>>   <chr>                      <bch:tm> <bch:tm> <bch:tm> <bch:tm>     <dbl> <bch:byt> <dbl>
>> 1 subset_ROW4(arr, i, FALSE)   28.9µs   34.9µs   32.1µs   1.36ms    28686.    5.05KB     5
>> 2 subset_ROW4(arr, i, TRUE)    28.9µs     35µs   32.4µs 875.11µs    28572.    5.05KB     5
>>>
>>
>> And on subsequent reps the lead switches back and forth.
>>
>>
>> Chuck
>>
>
>
>
> --
> http://hadley.nz
>
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