Package 'arrayhelpers' reference manual

Title:	Convenience Functions for Arrays
Description:	Some convenient functions to work with arrays.
Authors:	C. Beleites <[email protected]>
Maintainer:	C. Beleites <[email protected]>
License:	GPL
Version:	1.1-0
Built:	2024-11-28 02:52:17 UTC
Source:	https://github.com/r-forge/arrayhelpers

Package arrayhelpers

Description

Little helper functions to work with arrays

Author(s)

C. Beleites

Maintainer: Claudia Beleites <[email protected]>

array2df

Description

array2df: Convert multidimensional array into matrix or data.frame The "wide-format" array is converted into a "long-format" matrix or data.frame.

Usage

array2df(
  x,
  levels,
  matrix = FALSE,
  label.x = deparse(substitute(x)),
  na.rm = FALSE
)
array2df(
  x,
  levels,
  matrix = FALSE,
  label.x = deparse(substitute(x)),
  na.rm = FALSE
)

Arguments

`x`	`array`
`levels`	`list` with the levels for the dimensions of `x`. If `levels[[i]]` is `NULL` no column is produced for this factor. If `levels[[i]]` is `NA`, the result column is a numeric with range from `1` to `dim (x)[i]` If `levels[[i]]` is `TRUE`, the levels are taken from the dimnames. `names(levels)` yield the resulting column names.
`matrix`	If `TRUE`, a numeric `matrix` rather than a `data.frame` is returned.
`label.x`	Name for the column containing the `x` values.
`na.rm`	should rows where the value of `x` is `NA` be removed?

Details

If the resulting data.frame is too large to fit in memory, a matrix might help.

The main benefit of this function is that it uses matrices as long as possible. This can give large advantages in terms of memory consumption.

Value

A data.frame or matrix with prod (dim (x)) rows and length (dim (x)) + 1 columns.

Author(s)

Claudia Beleites

Examples

a <- arrayhelpers:::a
a
array2df (a)
array2df (a, matrix = TRUE)

array2df (a, levels = list(NULL, x = NA, c = NULL), label.x = "value")

array2df (a, levels = list(NULL, x = TRUE, c = c ("foo", "bar")), label.x = "value")

summary (array2df (a,
                   levels = list(NULL, x = NA, c = c ("foo", "bar")),
                   label.x = "value"))

summary (array2df (a,
                   levels = list(NULL, x = NA, c = c ("foo", "bar")),
                   label.x = "value",
                   matrix = TRUE))

a <- arrayhelpers:::a
a
array2df (a)
array2df (a, matrix = TRUE)

array2df (a, levels = list(NULL, x = NA, c = NULL), label.x = "value")

array2df (a, levels = list(NULL, x = TRUE, c = c ("foo", "bar")), label.x = "value")

summary (array2df (a,
                   levels = list(NULL, x = NA, c = c ("foo", "bar")),
                   label.x = "value"))

summary (array2df (a,
                   levels = list(NULL, x = NA, c = c ("foo", "bar")),
                   label.x = "value",
                   matrix = TRUE))

Converting array and vector Indices Calculate the vector index from array indices, and vice versa.

Description

arrays are numerics with a dim attribute and are stored with the first index moving fastest (i.e. by column). They can be indexed both ways.

Usage

array2vec(iarr, dim)

vec2array(ivec, dim)
array2vec(iarr, dim)

vec2array(ivec, dim)

Arguments

`iarr`	vector with the indices into the array dimensions
`dim`	vector with the array dimensions, as returned by `dim (x)`
`ivec`	scalar with the index into the vector

Value

array2vec returns a scalar, vec2array a matrix.

Author(s)

C. Beleites

Examples


arr <- array (rnorm (24), dim = 2 : 4)
arr

v <- matrix(c(2, 2, 2), nrow = 1)
i <- array2vec (v, dim = dim (arr))
i
arr[v]
arr[i]

arr[c(2, 2, 2)] ## indexing with a vector
arr[2]

 
i <- 14
v <- vec2array (i, dim = dim (arr))
v
arr [v]
arr [i]

arr <- array (rnorm (24), dim = 2 : 4)
arr

v <- matrix(c(2, 2, 2), nrow = 1)
i <- array2vec (v, dim = dim (arr))
i
arr[v]
arr[i]

arr[c(2, 2, 2)] ## indexing with a vector
arr[2]

 
i <- 14
v <- vec2array (i, dim = dim (arr))
v
arr [v]
arr [i]

Run the unit tests

Description

Run the unit tests attached to the functions via svUnit

Usage

arrayhelpers.unittest()
arrayhelpers.unittest()

Value

invisibly TRUE if the tests pass, NA if svUnit is not available. Stops if errors are encountered.

Author(s)

Claudia Beleites

Row and column sums and means for numeric arrays.

Description

These functions extend the respective base functions by (optionally) preserving the shape of the array (i.e. the summed dimensions have length 1).

Usage

## S4 method for signature 'matrix'
colSums(x, na.rm = FALSE, dims = 1L, drop = TRUE)

colSums.AsIs(x, ...)

## S4 method for signature 'array'
colSums(x, na.rm = FALSE, dims = 1L, drop = TRUE)

## S4 method for signature 'matrix'
colMeans(x, na.rm = FALSE, dims = 1L, drop = TRUE)

colMeans.AsIs(x, ...)

## S4 method for signature 'array'
colMeans(x, na.rm = FALSE, dims = 1L, drop = TRUE)

## S4 method for signature 'matrix'
rowSums(x, na.rm = FALSE, dims = 1L, drop = TRUE)

rowSums.AsIs(x, ...)

## S4 method for signature 'array'
rowSums(x, na.rm = FALSE, dims = 1L, drop = TRUE)

## S4 method for signature 'matrix'
rowMeans(x, na.rm = FALSE, dims = 1L, drop = TRUE)

rowMeans.AsIs(x, ...)

## S4 method for signature 'array'
rowMeans(x, na.rm = FALSE, dims = 1L, drop = TRUE)
## S4 method for signature 'matrix'
colSums(x, na.rm = FALSE, dims = 1L, drop = TRUE)

colSums.AsIs(x, ...)

## S4 method for signature 'array'
colSums(x, na.rm = FALSE, dims = 1L, drop = TRUE)

## S4 method for signature 'matrix'
colMeans(x, na.rm = FALSE, dims = 1L, drop = TRUE)

colMeans.AsIs(x, ...)

## S4 method for signature 'array'
colMeans(x, na.rm = FALSE, dims = 1L, drop = TRUE)

## S4 method for signature 'matrix'
rowSums(x, na.rm = FALSE, dims = 1L, drop = TRUE)

rowSums.AsIs(x, ...)

## S4 method for signature 'array'
rowSums(x, na.rm = FALSE, dims = 1L, drop = TRUE)

## S4 method for signature 'matrix'
rowMeans(x, na.rm = FALSE, dims = 1L, drop = TRUE)

rowMeans.AsIs(x, ...)

## S4 method for signature 'array'
rowMeans(x, na.rm = FALSE, dims = 1L, drop = TRUE)

Arguments

`x`	an array of two or more dimensions, containing numeric, complex, integer or logical values, or a numeric data frame.
`na.rm`	logical indicating treatment of missing values
`dims`	integer: Which dimensions are regarded as ‘rows’ or ‘columns’ to sum over. For `row`, the sum or mean is over dimensions `dims + 1, ...`; for `col` it is over dimensions `1 : dims`.
`drop`	If `FALSE`, the number of dimensions is retained: the length of the dimensions that are summed or averaged is set to 1. `TRUE` yield the same behaviour as `colSums`
`...`	the `signature = "AsIs"` methods hand on all parameters

Value

like colSums if drop = TRUE, otherwise an array where the summed dimensions have length 1.

Author(s)

Claudia Beleites

Examples

a <- array (1 : 24, 4 : 2)
a

rowSums (a)
rowSums (a, drop = FALSE)

colSums (a)
colSums (a, drop = FALSE)

colSums (a, dim = 2)
colSums (a, dim = 2, drop = FALSE)

a <- array (1 : 24, 4 : 2)
a

rowSums (a)
rowSums (a, drop = FALSE)

colSums (a)
colSums (a, drop = FALSE)

colSums (a, dim = 2)
colSums (a, dim = 2, drop = FALSE)

Count equal rows

Description

matrices are converted to data.frame.

Usage

countRows(x)
countRows(x)

Arguments

`x`	the matrix or data.frame

Value

data frame with unique rows, their counts and indices into the original data.frame

Note

this function is subject to changes in the future.

Author(s)

Claudia Beleites

Strip the attributes keeping track of the former shape

Description

Convenient for printing

Usage

delold(a)
delold(a)

Arguments

a

the array

Value

a stripped of the old.* attributes.

Author(s)

Claudia Beleites

Examples


a <- arrayhelpers:::a
makeNd (a, 2)
delold (makeNd (a, 2))


a <- arrayhelpers:::a
makeNd (a, 2)
delold (makeNd (a, 2))

Drop dimnames if all elements are `NULL`

Description

Drop dimnames if all elements are NULL

Usage

dropdimnames(x)

lon(l)
dropdimnames(x)

lon(l)

Arguments

`x`	object
`l`	list

Value

object without empty dimnames

lon: NULL if all elements of dn are NULL, otherwise dn

Author(s)

Claudia Beleites

Enforce array and convert to vector if appropriate

Description

ensuredim turns vectors into 1d-arrays, and leaves arrays unchanged. drop1d is the inverse: it converts 1d arrays into vectors.

Usage

ensuredim(x)

drop1d(x, drop = TRUE)
ensuredim(x)

drop1d(x, drop = TRUE)

Arguments

`x`	vector (or array)
`drop`	if `TRUE`, 1d arrays are converted into vectors

Value

esuredim array of at least one dimension

drop1d vector, if x had only 1 dimension

Author(s)

Claudia Beleites

Extension of `rowsum`

Description

groupsum extends rowsum: it allows group to be an array of the same shape as x.

Usage

groupsum(
  x,
  group = NULL,
  dim = 1L,
  reorder = TRUE,
  na.rm = FALSE,
  ...,
  drop = !is.array(x)
)
groupsum(
  x,
  group = NULL,
  dim = 1L,
  reorder = TRUE,
  na.rm = FALSE,
  ...,
  drop = !is.array(x)
)

Arguments

`x`	array to be `rowsum`med
`group`	grouping variable (integer or factor) indicating groups of samples.
`dim`	along which dimension should the group sums be taken? (default: rows)
`reorder`	should the groups be ordered? see `rowsum`
`na.rm`	shoud `NA`s be removed?
`...`	ignored
`drop`	should 1d arrays drop to vectors?

Value

like rowsum, but further dimensions of the array are preserved.

Author(s)

Claudia Beleites

Ensure/collapse an array into `n` dimensions and restore the old dimensions

Description

nameNd ensures a given number of dimensions: If a has less than N dimensions, new dimensions of length 1 are appended. If a has more than N dimensions, the supernumerary dimensions are collapsed onto the last dimension.

Attributes old.dim and old.dimnames are used by default. restoredim is the inverse of makeNd.

Usage

makeNd(a, N)

restoredim(
  a,
  old = NULL,
  n = 1L,
  ...,
  usedim = TRUE,
  fromend = FALSE,
  drop = FALSE
)
makeNd(a, N)

restoredim(
  a,
  old = NULL,
  n = 1L,
  ...,
  usedim = TRUE,
  fromend = FALSE,
  drop = FALSE
)

Arguments

`a`	an array (matrix, vector)
`N`	the desired number of dimensions, 0 to remove the `dim` and `dimnames` attributes (i.e. to create a vector).
`old`	list containing a list with (possibly) elements `dim`, `dimnames`, and `names`. The nth last element of this list is used.
`n`	how many makeNdim steps to go back?
`...`	ignored
`usedim`	use only the specified dimensions
`fromend`	if `TRUE`, numeric `usedim` are counted from the end, see details.
`drop`	should 1d arrays drop to vectors?

Details

Note that missing attributes as well as old.dim = NULL produce a (dimensionless) vector. This is also the case if a lost the old.* attributes during computations like as.numeric, c, etc..

fromend together with numeric usedim specifies dimensions counting from the end. E.g. fromend = TRUE and usedim = 1 : 3 for an array to be restored to 10d means restoring dimensions 8 : 10. fromend = TRUE and usedim = -(1 : 3) restores dimensions 1 to 7.

Value

N-dimensional array

an array

Author(s)

Claudia Beleites

Examples

v <- arrayhelpers:::v
v
makeNd (v, 1)
dim (makeNd (v, 1))
dim (makeNd (v, 3))

m <- arrayhelpers:::m
m
makeNd (m, 1)
dim (makeNd (m, 1))
makeNd (m, 0) 
dim (makeNd (m, 0))
makeNd (m, 3)

a <- arrayhelpers:::a
a
dim (makeNd (a, 1))
dim (makeNd (a, 0))
makeNd (a,  2)          
makeNd (a, -2)
makeNd (a, -4)
makeNd (a, 3);


a <- array (1 : 24, 4 : 3)
a
restoredim (makeNd (a, 0))

x <- makeNd (a, 0)
attr (x, "old")

v <- arrayhelpers:::v
v
makeNd (v, 1)
dim (makeNd (v, 1))
dim (makeNd (v, 3))

m <- arrayhelpers:::m
m
makeNd (m, 1)
dim (makeNd (m, 1))
makeNd (m, 0) 
dim (makeNd (m, 0))
makeNd (m, 3)

a <- arrayhelpers:::a
a
dim (makeNd (a, 1))
dim (makeNd (a, 0))
makeNd (a,  2)          
makeNd (a, -2)
makeNd (a, -4)
makeNd (a, 3);


a <- array (1 : 24, 4 : 3)
a
restoredim (makeNd (a, 0))

x <- makeNd (a, 0)
attr (x, "old")

number of dimensions

Description

number of dimensions

Usage

ndim(a)
ndim(a)

Arguments

`a`	vector, matrix, or array

Value

integer: length of dim attribute

Author(s)

Claudia Beleites

Convert character or logical indices to numeric

Description

Convert character or logical indices to numeric

Usage

numericindex(x, i, n = names(x))
numericindex(x, i, n = names(x))

Arguments

`x`	the object that is to be indexed
`i`	the indices to be converted
`n`	names of the object

Value

numeric indices

Author(s)

Claudia Beleites

A little stack.

Description

TODO: implement as reference class? Note: pop only removes elements. To retrieve them, use peek.

Usage

peek(x, an, n = 1L)

pop(x, an, n = 1L)

push (x, an) <- value
peek(x, an, n = 1L)

pop(x, an, n = 1L)

push (x, an) <- value

Arguments

`x`	the object
`an`	attribute holding the stack
`n`	numer of element to peek at and numer of elements to pop (delete), respectively
`value`	list of things to push on the stack.

Value

push and pop: the object with stack in list an pushed/popped by the n elements

peek: the nth stack element (without popping!)

Author(s)

Claudia Beleites

rowsum for arrays

Description

This function extends the base function rowsum.

Usage

## S4 method for signature 'array'
rowsum(x, group, reorder = TRUE, na.rm = FALSE, ...)
## S4 method for signature 'array'
rowsum(x, group, reorder = TRUE, na.rm = FALSE, ...)

Arguments

`x`	array to be `rowsum`med
`group`	grouping variable (integer or factor) indicating groups of samples.
`reorder`	should the groups be ordered? see `rowsum`
`na.rm`	shoud `NA`s be removed?
`...`	ignored

Value

like rowsum, but further dimensions of the array are preserved.

Author(s)

Claudia Beleites

alternative to index an array

Description

slice is an alternative interface to [ (extract). Dimensions to index must be given by name, i for the first, j for the second and so on.

Usage

slice(a, ..., drop = TRUE)

slice (a, ...) <- value
slice(a, ..., drop = TRUE)

slice (a, ...) <- value

Arguments

`a`	vector, matrix, or array
`...`	indexing instructions. The names of the arguments specify the dimension (i = 1st, j = 2nd, ...). The indexing expressions are the same as for `[`
`drop`	see `[`
`value`	the values to assign

Value

array

Author(s)

Claudia Beleites

Examples

slice (arrayhelpers:::a, j = 3 : 2)
tmp <- arrayhelpers:::a
slice (tmp, j = 2 : 3) <- 0
tmp
slice (arrayhelpers:::a, j = 3 : 2)
tmp <- arrayhelpers:::a
slice (tmp, j = 2 : 3) <- 0
tmp

Transpose arrays

Description

This function provides transposing of arrays or vectors as swapping their first two dimensions. t (array) can be enabled via setMethod, see the example.

Usage

ta(x)
ta(x)

Arguments

x

an array

Value

the array with the first two dimensions swapped.

Author(s)

Claudia Beleites

Examples

a <- array (1 : 24, 4:2)
a
ta (a)

setMethod ("t", "array", ta)
t (a)
removeMethod ("t", "array")

a <- array (1 : 24, 4:2)
a
ta (a)

setMethod ("t", "array", ta)
t (a)
removeMethod ("t", "array")

Package 'arrayhelpers'

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