Get observations of a vector

This extends vctrs::vec_slice to S4Vectors::Vector class by masking vec_slice with S7::new_generic. Atomic vectors and other base S3 classes (list, data.frame, factor, Dat, POSIXct) will dispatch to the vctrs::vec_slice method as normal. Dispatch support on the S4Vectors::Vector and S4Vectors::DataFrame classes provides a unified framework for working with base R vectors and S4Vectors.

`S4Vectors::Vector` Implementation

This method will naively call the [ method for any S4 class that inherits from the S4Vectors::Vector class. This may not be a very efficient way to slice up an S4 class, but will work.

With this implementation, the x@mcol data is expected to be retained after a call to biocmask::vec_slice(x, i).

`S4Vectors::DataFrame` Implementation

The DataFrame implementation works similar to how vctrs::vec_slice works on a data.frame object. What is being sliced is the rows of x@listData. To maintain the size stability of the DataFrame object, we change @nrows to the appropriate value, and perform a recursive call if @elementMetadata is not NULL.

Performance

Depending on the size and complexity of your S4 Vector object, you may find the standard subset operation is extremely slow. For example, consider a SummarizedExperiment whose rowData contains a CompressedGRangesList object assigned to the name "exons" and whose length is 250,000 and underlying @unlistData is length 1,600,000. Performing a by .features grouping operation and attempting to evaluate the exons within the row context would force the CompressedGRangesList object to be chopped element-wise.

Unfortunately, there is a massive performance hit in attempting to construct 250,000 GRanges. Unless you do not mind waiting over an hour for each dplyr verb in which exons gets evaluated, consider biocmask_s4_proxy_vec(). This attempts to reconstruct certain standard S4Vectors::Vectors as standard vectors or tibbles. The equivalent exons object would require much more memory use, but at the advantage of only taking several seconds to construct.When you are done, you can attempt to restore the original S4 Vector with biocmask_restore_s4_proxy().

biocmask_s4_proxy_vec() is faster to work with because there are less checks on the object validity and all @elementMetadata and @metadata are dropped from the objects.

Usage

vec_slice(x, i, ...)

Arguments

x: A vector
i: An integer, character or logical vector specifying the locations or names of the observations to get/set. Specify TRUE to index all elements (as in x[]), or NULL, FALSE or integer() to index none (as in x[NULL]).
...: These dots are for future extensions and must be empty.

Value

a new S3 or S4 vector subsetted by i

Examples

vec_slice(1:10, i = 5)
#> [1] 5
vec_slice(S4Vectors::Rle(rep(1:3, each = 3)), i = 5)
#> integer-Rle of length 1 with 1 run
#>   Lengths: 1
#>   Values : 2

S4Vectors::Vector Implementation