MultiFactor S7 container class

MultiFactor is an S7 class to organize and manage multiple sets of factors, for instance when tracing or converting feature IDs across databases. Methods for MultiFactor aim to follow factor behaviour.

Usage

MultiFactor(x, levels = NULL, drop.unmatched = FALSE)

## Constructor for `MultiFactor` objects
MultiFactor(x, levels = NULL, drop.unmatched = FALSE)

Arguments

x

MultiFactor

levels

an optional named list of vectors of the unique values (as character strings) that x might have taken. The default is the unique set of values taken by lapply(x, as.character), sorted into increasing order of x.

drop.unmatched

Logical scalar If TRUE (Default), for feature types that are seen at least twice, exclude features that only present in one of their respective link data frames.

Value

a MultiFactor object.

Details

The most straightforward way to construct a MultiFactor object is as a named list of named data.frames. The columns of the data.frames indicate the category of factor in that column.

A MultiFactor object presents itself similar to a data.frame, in the sense that level types can be called as columns and individual data.frame components can be called as rows.

Slots

index

Named list of named integer data frames of at least two columns each. The column names correspond to names in the levels slot. Similar to factors, the integers in those columns correspond to the characters in that level. Accessed through regular list methods (e.g., [, [[).

levels

Named list of character vectors. Accessed through levels(x)

map

(sparse) Matrix specifying which elements contain which levels. Accesses through x@dictionary.

See also

MultiFactor-methods()

• kegg_link(): for an example of valid input.

Examples

# Generate some random linkage input
x <- data.frame(
    a = sample(letters[seq(3)], 10, replace = TRUE),
    A = sample(LETTERS[seq(3)], 10, replace = TRUE)
)
MultiFactor(x)
#> An anansi::MultiFactor S7_object,
#>     2 feature types across 1 edge lists.
#> 
#>   a A
#> x 3 3
#> 
#> Values represent unique feature names in that edge list.
#> 
#> Levels:
#> 
#> a : 3 Levels: b c a 
#> A : 3 Levels: C B A