This package provides consistent utility functions for array programming with arbitrary dimensions (summary below).
We recommend to load this package in its own namespace to not shadow
base R functions using box
or import
.
stack()
is like cbind
/rbind
,
but along arbitrary axes, and taking care of (1) names along each
dimension and (2) padding partial matching arrays.
A = matrix(1:4, nrow=2, ncol=2, dimnames=list(c('a','b'),c('x','y')))
B = matrix(5:6, nrow=2, ncol=1, dimnames=list(c('b','a'),'z'))
C = stack(A, B, along=2)
C
#> x y z
#> a 1 3 6
#> b 2 4 5
D = stack(m=A, n=C, along=3) # we can also introduce new dimensions
D
#> , , m
#>
#> x y z
#> a 1 3 NA
#> b 2 4 NA
#>
#> , , n
#>
#> x y z
#> a 1 3 6
#> b 2 4 5
split()
splits an array along a given axis; can do each
element or defined subsets.
Like apply
, but not reordering array dimensions and
allowing to specify subsets that the function should be applied on. The
function must either return a vector of the same length as the input
(returns matrix of same dimension) or of length 1 (drops current
dimension or returns subsets).
map(C, along=2, function(x) x*2) # return same length vector
#> x y z
#> a 2 6 12
#> b 4 8 10
map(C, along=2, mean, subsets=c('s1', 's1', 's2')) # summarize each subset to scalar
#> s1 s2
#> a 2 6
#> b 3 5
We can also index multiple arrays using the lambda
function. If the result is a scalar we will get back an array, and an
index with result column otherwise.
Takes a number of arrays, intersects their names along a given
dimension, and returns sub-arrays that match in their names;
intersect_list
takes a list of arrays and returns a list of
subsets.
data.frame
sconstruct()
takes a data frame and a formula specifying
dependent (values) and independent (axes) of the resulting array.