Package 'filearray'

Title: File-Backed Array for Out-of-Memory Computation
Description: Stores large arrays in files to avoid occupying large memories. Implemented with super fast gigabyte-level multi-threaded reading/writing via 'OpenMP'. Supports multiple non-character data types (double, float, complex, integer, logical, and raw).
Authors: Zhengjia Wang [aut, cre, cph]
Maintainer: Zhengjia Wang <[email protected]>
License: LGPL-3
Version: 0.1.9
Built: 2024-11-08 17:15:11 UTC
Source: https://github.com/dipterix/filearray

Help Index


Apply functions over file array margins (extended)

Description

Apply functions over file array margins (extended)

Usage

apply(X, MARGIN, FUN, ..., simplify = TRUE)

## S4 method for signature 'FileArray'
apply(X, MARGIN, FUN, ..., simplify = TRUE)

## S4 method for signature 'FileArrayProxy'
apply(X, MARGIN, FUN, ..., simplify = TRUE)

Arguments

X

a file array

MARGIN

scalar giving the subscripts which the function will be applied over. Current implementation only allows margin size to be one

FUN

the function to be applied

...

optional arguments to FUN

simplify

a logical indicating whether results should be simplified if possible

Value

See Section 'Value' in apply;


Create or load existing file arrays

Description

Create or load existing file arrays

Usage

as_filearray(x, ...)

as_filearrayproxy(x, ...)

filearray_create(
  filebase,
  dimension,
  type = c("double", "float", "integer", "logical", "raw", "complex"),
  partition_size = NA,
  initialize = FALSE,
  ...
)

filearray_load(filebase, mode = c("readwrite", "readonly"))

filearray_checkload(
  filebase,
  mode = c("readonly", "readwrite"),
  ...,
  symlink_ok = TRUE
)

filearray_load_or_create(
  filebase,
  dimension,
  on_missing = NULL,
  type = NA,
  ...,
  mode = c("readonly", "readwrite"),
  symlink_ok = TRUE,
  initialize = FALSE,
  partition_size = NA,
  verbose = FALSE
)

Arguments

x

R object such as array, file array proxy, or character that can be transformed into file array

...

additional headers to check used by filearray_checkload (see 'Details'). This argument is ignored by filearray_create, reserved for future compatibility.

filebase

a directory path to store arrays in the local file system. When creating an array, the path must not exist.

dimension

dimension of the array, at least length of 2

type

storage type of the array; default is 'double'. Other options include 'integer', 'logical', and 'raw'.

partition_size

positive partition size for the last margin, or NA to automatically guess; see 'Details'.

initialize

whether to initialize partition files; default is false for performance considerations. However, if the array is dense, it is recommended to set to true

mode

whether allows writing to the file; choices are 'readwrite' and 'readonly'.

symlink_ok

whether arrays with symbolic-link partitions can pass the test; this is usually used on bound arrays with symbolic-links; see filearray_bind;

on_missing

function to handle file array (such as initialization) when a new array is created; must take only one argument, the array object

verbose

whether to print out some debug messages

Details

The file arrays partition out-of-memory array objects and store them separately in local file systems. Since R stores matrices/arrays in column-major style, file array uses the slowest margin (the last margin) to slice the partitions. This helps to align the elements within the files with the corresponding memory order. An array with dimension 100x200x300x400 has 4 margins. The length of the last margin is 400, which is also the maximum number of potential partitions. The number of partitions are determined by the last margin size divided by partition_size. For example, if the partition size is 1, then there will be 400 partitions. If the partition size if 3, there will be 134 partitions. The default partition sizes are determined internally following these priorities:

1.

the file size of each partition does not exceed 1GB

2.

the number of partitions do not exceed 100

These two rules are not hard requirements. The goal is to reduce the numbers of partitions as much as possible.

The arguments ... in filearray_checkload should be named arguments that provide additional checks for the header information. The check will fail if at least one header is not identical. For example, if an array contains header key-signature pair, one can use filearray_checkload(..., key = signature) to validate the signature. Note the comparison will be rigid, meaning the storage type of the headers will be considered as well. If the signature stored in the array is an integer while provided is a double, then the check will result in failure.

Value

A FileArray-class instance.

Author(s)

Zhengjia Wang

Examples

# Prepare
library(filearray)
filebase <- tempfile()
if(file.exists(filebase)){ unlink(filebase, TRUE) }

# create array
x <- filearray_create(filebase, dimension = c(200, 30, 8))
print(x)

# Assign values
x[] <- rnorm(48000)

# Subset
x[1,2,]

# load existing array
filearray_load(filebase)

x$set_header("signature", "tom")
filearray_checkload(filebase, signature = "tom")

## Not run: 
# Trying to load with wrong signature
filearray_checkload(filebase, signature = "jerry")

## End(Not run)


# check-load, and create a new array if fail
x <- filearray_load_or_create(
    filebase = filebase, dimension = c(200, 30, 8),
    verbose = FALSE, signature = "henry"
)
x$get_header("signature")

# check-load with initialization
x <- filearray_load_or_create(
    filebase = filebase,
    dimension = c(3, 4, 5),
    verbose = FALSE, mode = "readonly",
    on_missing = function(array) {
        array[] <- seq_len(60)
    }
)

x[1:3,1,1]

# Clean up
unlink(filebase, recursive = TRUE)

Merge and bind homogeneous file arrays

Description

The file arrays to be merged must be homogeneous: same data type, partition size, and partition length

Usage

filearray_bind(
  ...,
  .list = list(),
  filebase = tempfile(),
  symlink = FALSE,
  overwrite = FALSE,
  cache_ok = FALSE
)

Arguments

..., .list

file array instances

filebase

where to create merged array

symlink

whether to use file.symlink; if true, then partition files will be symbolic-linked to the original arrays, otherwise the partition files will be copied over. If you want your data to be portable, do not use symbolic-links. The default value is FALSE

overwrite

whether to overwrite when filebase already exists; default is false, which raises errors

cache_ok

see 'Details', only used if overwrite is true.

Details

The input arrays must share the same data type and partition size. The dimension for each partition should also be the same. For example an array x1 has dimension 100x20x30100x20x30 with partition size 1, then each partition dimension is 100x20x1100x20x1, and there are 30 partitions. x1 can bind with another array of the same partition size. This means if x2 has dimension 100x20x40100x20x40 and each partition size is 1, then x1 and x2 can be merged.

If filebase exists and overwrite is FALSE, an error will always raise. If overwrite=TRUE and cache_ok=FALSE, then the existing filebase will be erased and any data stored within will be lost. If both overwrite and cache_ok are TRUE, then , before erasing filebase, the function validates the existing array header and compare the header signatures. If the existing header signature is the same as the array to be created, then the existing array will be returned. This cache_ok could be extremely useful when binding large arrays with symlink=FALSE as the cache might avoid moving files around. However, cache_ok should be enabled with caution. This is because only the header information will be compared, but the partition data will not be compared. If the existing array was generated from an old versions of the source arrays, but the data from the source arrays has been altered, then the cache_ok=TRUE is rarely proper as the cache is outdated.

The symlink option should be used with extra caution. Creating symbolic links is definitely faster than copying partition files. However, since the partition files are simply linked to the original partition files, changing to the input arrays will also affect the merged arrays, and vice versa; see 'Examples'. Also for arrays created from symbolic links, if the original arrays are deleted, while the merged arrays will not be invalidated, the corresponding partitions will no longer be accessible. Attempts to set deleted partitions will likely result in failure. Therefore symlink should be set to true when creating merged arrays are temporary for read-only purpose, and when speed and disk space is in consideration. For extended reading, please check files for details.

Value

A bound array in 'FileArray' class.

Examples

partition_size <- 1
type <- "double"
x1 <- filearray_create(
    tempfile(), c(2,2), type = type,
    partition_size = partition_size)
x1[] <- 1:4
x2 <- filearray_create(
    tempfile(), c(2,1), type = type,
    partition_size = partition_size)
x2[] <- 5:6

y1 <- filearray_bind(x1, x2, symlink = FALSE)
y2 <- filearray_bind(x1, x2)

# y1 copies partition files, and y2 simply creates links 
# if symlink is supported

y1[] - y2[]

# change x1
x1[1,1] <- NA

# y1 is not affected
y1[]

# y2 changes 
y2[]

Set or get file array threads

Description

Will enable/disable multi-threaded reading or writing at C++ level.

Usage

filearray_threads(n, ...)

Arguments

n

number of threads to set. If n is negative, then default to the number of cores that computer has.

...

internally used

Value

An integer of current number of threads


Definition of file array

Description

S4 class definition of FileArray. Please use filearray_create and filearray_load to create instances.

Public Methods

get_header(key, default = NULL)

Get header information; returns default if key is missing

set_header(key, value)

Set header information; the extra headers will be stored in meta file. Please do not store large headers as they will be loaded into memory frequently.

can_write()

Whether the array data can be altered

create(filebase, dimension, type = "double", partition_size = 1)

Create a file array instance

delete(force = FALSE)

Remove array from local file system and reset

dimension()

Get dimension vector

dimnames(v)

Set/get dimension names

element_size()

Internal storage: bytes per element

fill_partition(part, value)

Fill a partition with given scalar

get_partition(part, reshape = NULL)

Get partition data, and reshape (if not null) to desired dimension

expand(n)

Expand array along the last margin; returns true if expanded; if the dimnames have been assigned prior to expansion, the last dimension names will be filled with NA

initialize_partition()

Make sure a partition file exists; if not, create one and fill with NAs or 0 (type='raw')

load(filebase, mode = c("readwrite", "readonly"))

Load file array from existing directory

partition_path(part)

Get partition file path

partition_size()

Get partition size; see filearray

set_partition(part, value, ..., strict = TRUE)

Set partition value

sexp_type()

Get data SEXP type; see R internal manuals

show()

Print information

type()

Get data type

valid()

Check if the array is valid.

See Also

filearray


Map multiple file arrays and save results

Description

Advanced mapping function for multiple file arrays. fmap runs the mapping functions and stores the results in file arrays. fmap2 stores results in memory. This feature is experimental. There are several constraints to the input. Failure to meet these constraints may result in undefined results, or even crashes. Please read Section 'Details' carefully before using this function.

Usage

fmap(
  x,
  fun,
  .y = NULL,
  .buffer_count = NA_integer_,
  .output_size = NA_integer_,
  ...
)

fmap2(x, fun, .buffer_count = NA, .simplify = TRUE, ...)

fmap_element_wise(x, fun, .y, ..., .input_size = NA)

Arguments

x

a list of file arrays to map; each element of x must share the same dimensions.

fun

function that takes one list

.y

a file array object, used to save results

.buffer_count

number of total buffers (chunks) to run

.output_size

fun output vector length

...

other arguments passing to fun

.simplify

whether to apply simplify2array to the result

.input_size

number of elements to read from each array of x

Details

Denote the first argument of fun as input, The length of input equals the length of x. The size of each element of input is defined by .input_size, except for the last loop. For example, given dimension of each input array as 10x10x10x1010x10x10x10, if .input_size=100, then length(input[[1]])=100. The total number of runs equals to length(x[[1]])/100. If .input_size=300, then length(input[[1]]) will be 300 except for the last run. This is because 1000010000 cannot be divided by 300. The element length of the last run will be 100.

The returned variable length of fun will be checked by .output_size. If the output length exceed .output_size, an error will be raised.

Please make sure that length(.y)/length(x[[1]]) equals to .output_size/.input_size.

For fmap_element_wise, the input[[1]] and output length must be the consistent.

Value

File array instance .y

Examples

set.seed(1)
x1 <- filearray_create(tempfile(), dimension = c(100,20,3))
x1[] <- rnorm(6000)
x2 <- filearray_create(tempfile(), dimension = c(100,20,3))
x2[] <- rnorm(6000)

# Add two arrays
output <- filearray_create(tempfile(), dimension = c(100,20,3))
fmap(list(x1, x2), function(input){
    input[[1]] + input[[2]]
}, output)

# check
range(output[] - (x1[] + x2[]))

output$delete()

# Calculate the maximum of x1/x2 for every 100 elements
# total 60 batches/loops (`.buffer_count`)
output <- filearray_create(tempfile(), dimension = c(20,3))
fmap(list(x1, x2), function(input){
    max(input[[1]] / input[[2]])
}, .y = output, .buffer_count = 60)

# check
range(output[] - apply(x1[] / x2[], c(2,3), max))

output$delete()

# A large array example
if(interactive()){
    x <- filearray_create(tempfile(), dimension = c(287, 100, 301, 4))
    dimnames(x) <- list(
        Trial = 1:287,
        Marker = 1:100,
        Time = 1:301,
        Location = 1:4
    )

    for(i in 1:4){
        x[,,,i] <- runif(8638700)
    }
    # Step 1:
    # for each location, trial, and marker, calibrate (baseline)
    # according to first 50 time-points

    output <- filearray_create(tempfile(), dimension = dim(x))

    # baseline-percentage change
    fmap(
        list(x),
        function(input){
            # get locational data
            location_data <- input[[1]]
            dim(location_data) <- c(287, 100, 301)

            # collapse over first 50 time points for
            # each trial, and marker
            baseline <- apply(location_data[,,1:50], c(1,2), mean)

            # calibrate
            calibrated <- sweep(location_data, c(1,2), baseline,
                                FUN = function(data, bl){
                                    (data / bl - 1) * 100
                                })
            return(calibrated)
        },

        .y = output,

        # input dimension is 287 x 100 x 301 for each location
        # hence 4 loops in total
        .buffer_count = 4
    )

    # cleanup
    x$delete()

}

# cleanup
x1$delete()
x2$delete()
output$delete()

A generic function of which that is 'FileArray' compatible

Description

A generic function of which that is 'FileArray' compatible

Usage

fwhich(x, val, arr.ind = FALSE, ret.values = FALSE, ...)

## Default S3 method:
fwhich(x, val, arr.ind = FALSE, ret.values = FALSE, ...)

## S3 method for class 'FileArray'
fwhich(x, val, arr.ind = FALSE, ret.values = FALSE, ...)

Arguments

x

any R vector, matrix, array or file-array

val

values to find, or a function taking one argument (a slice of data vector) and returns either logical vector with the same length as the slice or index of the slice; see 'Examples'

arr.ind

logical; should array indices be returned when x is an array?

ret.values

whether to return the values of corresponding indices as an attributes; default is false

...

passed to val if val is a function

Value

The indices of x elements that are listed in val.

Examples

# ---- Default case ------------------------------------
x <- array(1:27 + 2, rep(3,3))

# find index of `x` equal to either 4 or 5
fwhich(x, c(4,5))
res <- fwhich(x, c(4,5), ret.values = TRUE)
res
attr(res, "values")

# ---- file-array case --------------------------------
arr <- filearray_create(tempfile(), dim(x))
arr[] <- x
fwhich(arr, c(4,5))
fwhich(arr, c(4,5), arr.ind = TRUE, ret.values = TRUE)

arr[2:3, 1, 1]

# Clean up this example
arr$delete()

# ---- `val` is a function ----------------------------
x <- as_filearray(c(sample(15), 15), dimension = c(4,4))

ret <- fwhich(x, val = which.max, 
              ret.values = TRUE, arr.ind = FALSE)

# ret is the index
ret == which.max(x[])

# attr(ret, "values") is the max value
max(x[]) == attr(ret, "values")

# customize `val`
fwhich(x, ret.values = TRUE, arr.ind = FALSE,
       val = function( slice ) {
           slice > 10 # or which(slice > 10)
       })

A map-reduce method to iterate blocks of file-array data with little memory usage

Description

A map-reduce method to iterate blocks of file-array data with little memory usage

Usage

mapreduce(x, map, reduce, ...)

## S4 method for signature 'FileArray,ANY,function'
mapreduce(x, map, reduce, buffer_size = NA, ...)

## S4 method for signature 'FileArray,ANY,NULL'
mapreduce(x, map, reduce, buffer_size = NA, ...)

## S4 method for signature 'FileArray,ANY,missing'
mapreduce(x, map, reduce, buffer_size = NA, ...)

Arguments

x

a file array object

map

mapping function that receives 3 arguments; see 'Details'

reduce

NULL, or a function that takes a list as input

...

passed to other methods

buffer_size

control how we split the array; see 'Details'

Details

When handling out-of-memory arrays, it is recommended to load a block of array at a time and execute on block level. See apply for a implementation. When an array is too large, and when there are too many blocks, this operation will become very slow if computer memory is low. This is because the R will perform garbage collection frequently. Implemented in C++, mapreduce creates a buffer to store the block data. By reusing the memory over and over again, it is possible to iterate through the array with minimal garbage collections. Many statistics, including min, max, sum, mean, ... These statistics can be calculated in this way efficiently.

The function map contains three arguments: data (mandate), size (optional), and first_index (optional). The data is the buffer, whose length is consistent across iterations. size indicates the effective size of the buffer. If the partition size is not divisible by the buffer size, only first size elements of the data are from array, and the rest elements will be NA. This situation could only occurs when buffer_size is manually specified. By default, all of data should belong to arrays. The last argument first_index is the index of the first element data[1] in the whole array. It is useful when positional data is needed.

The buffer size, specified by buffer_size is an additional optional argument in .... Its default is NA, and will be calculated automatically. If manually specified, a large buffer size would be desired to speed up the calculation. The default buffer size will not exceed nThreadsx2MBnThreads x 2MB, where nThreads is the number of threads set by filearray_threads. When partition length cannot be divided by the buffer size, instead of trimming the buffer, NAs will be filled to the buffer, passed to map function; see previous paragraph for treatments.

The function mapreduce ignores the missing partitions. That means if a partition is missing, its data will not be read nor passed to map function. Please run x$initialize_partition() to make sure partition files exist.

Value

If reduce is NULL, return mapped results, otherwise return reduced results from reduce function

Examples

x <- filearray_create(tempfile(), c(100, 100, 10))
x[] <- rnorm(1e5)

## calculate summation
# identical to sum(x[]), but is more feasible in large cases

mapreduce(x, map = function(data, size){
    # make sure `data` is all from array
    if(length(data) != size){
        data <- data[1:size]
    }
    sum(data)
}, reduce = function(mapped_list){
    do.call(sum, mapped_list)
})


## Find elements are less than -3
positions <- mapreduce(
    x,
    map = function(data, size, first_index) {
        if (length(data) != size) {
            data <- data[1:size]
        }
        which(data < -3) + (first_index - 1)
    },
    reduce = function(mapped_list) {
        do.call(c, mapped_list)
    }
)

if(length(positions)){
    x[[positions[1]]]
}

'S3' methods for 'FileArray'

Description

These are 'S3' methods for 'FileArray'

Usage

## S3 method for class 'FileArray'

  x[
  i,
  ...,
  drop = TRUE,
  reshape = NULL,
  strict = TRUE,
  dimnames = TRUE,
  split_dim = 0
]

## S3 replacement method for class 'FileArray'
x[i, ..., lazy = FALSE] <- value

## S3 method for class 'FileArray'
x[[i]]

## S3 method for class 'FileArray'
as.array(x, reshape = NULL, drop = FALSE, ...)

## S3 method for class 'FileArray'
dim(x)

## S3 method for class 'FileArray'
dimnames(x)

## S3 replacement method for class 'FileArray'
dimnames(x) <- value

## S3 method for class 'FileArray'
length(x)

## S3 method for class 'FileArray'
max(x, na.rm = FALSE, ...)

## S3 method for class 'FileArray'
min(x, na.rm = FALSE, ...)

## S3 method for class 'FileArray'
range(x, na.rm = FALSE, ...)

## S3 method for class 'FileArray'
sum(x, na.rm = FALSE, ...)

## S3 method for class 'FileArray'
subset(x, ..., drop = FALSE, .env = parent.frame())

Arguments

x

a file array

i, ...

index set, or passed to other methods

drop

whether to drop dimensions; see topic Extract

reshape

a new dimension to set before returning subset results; default is NULL (use default dimensions)

strict

whether to allow indices to exceed bound; currently only accept TRUE

dimnames

whether to preserve dimnames

split_dim

internally used; split dimension and calculate indices to manually speed up the subset; value ranged from 0 to size of dimension minus one.

lazy

whether to lazy-evaluate the method, only works when assigning arrays with logical array index

value

value to substitute or set

na.rm

whether to remove NA values during the calculation

.env

environment to evaluate formula when evaluating subset margin indices.

Functions

  • [: subset array

  • `[`(FileArray) <- value: subset assign array

  • [[: get element by index

  • as.array(FileArray): converts file array to native array in R

  • dim(FileArray): get dimensions

  • dimnames(FileArray): get dimension names

  • dimnames(FileArray) <- value: set dimension names

  • length(FileArray): get array length

  • max(FileArray): get max value

  • min(FileArray): get min value

  • range(FileArray): get value range

  • sum(FileArray): get summation

  • subset(FileArray): get subset file array with formulae


'S4' methods for FileArray

Description

'S4' methods for FileArray

Usage

## S4 method for signature 'FileArray,FileArray'
e1 + e2

## S4 method for signature 'FileArray,numeric'
e1 + e2

## S4 method for signature 'numeric,FileArray'
e1 + e2

## S4 method for signature 'FileArray,complex'
e1 + e2

## S4 method for signature 'complex,FileArray'
e1 + e2

## S4 method for signature 'FileArray,logical'
e1 + e2

## S4 method for signature 'logical,FileArray'
e1 + e2

## S4 method for signature 'FileArray,array'
e1 + e2

## S4 method for signature 'array,FileArray'
e1 + e2

## S4 method for signature 'FileArray,FileArray'
e1 - e2

## S4 method for signature 'FileArray,numeric'
e1 - e2

## S4 method for signature 'numeric,FileArray'
e1 - e2

## S4 method for signature 'FileArray,complex'
e1 - e2

## S4 method for signature 'complex,FileArray'
e1 - e2

## S4 method for signature 'FileArray,logical'
e1 - e2

## S4 method for signature 'logical,FileArray'
e1 - e2

## S4 method for signature 'FileArray,array'
e1 - e2

## S4 method for signature 'array,FileArray'
e1 - e2

## S4 method for signature 'FileArray,FileArray'
e1 * e2

## S4 method for signature 'FileArray,numeric'
e1 * e2

## S4 method for signature 'numeric,FileArray'
e1 * e2

## S4 method for signature 'FileArray,complex'
e1 * e2

## S4 method for signature 'complex,FileArray'
e1 * e2

## S4 method for signature 'FileArray,logical'
e1 * e2

## S4 method for signature 'logical,FileArray'
e1 * e2

## S4 method for signature 'FileArray,array'
e1 * e2

## S4 method for signature 'array,FileArray'
e1 * e2

## S4 method for signature 'FileArray,FileArray'
e1 / e2

## S4 method for signature 'FileArray,numeric'
e1 / e2

## S4 method for signature 'numeric,FileArray'
e1 / e2

## S4 method for signature 'FileArray,complex'
e1 / e2

## S4 method for signature 'complex,FileArray'
e1 / e2

## S4 method for signature 'FileArray,logical'
e1 / e2

## S4 method for signature 'logical,FileArray'
e1 / e2

## S4 method for signature 'FileArray,array'
e1 / e2

## S4 method for signature 'array,FileArray'
e1 / e2

## S4 method for signature 'FileArray,FileArray'
e1 ^ e2

## S4 method for signature 'FileArray,numeric'
e1 ^ e2

## S4 method for signature 'numeric,FileArray'
e1 ^ e2

## S4 method for signature 'FileArray,complex'
e1 ^ e2

## S4 method for signature 'complex,FileArray'
e1 ^ e2

## S4 method for signature 'FileArray,logical'
e1 ^ e2

## S4 method for signature 'logical,FileArray'
e1 ^ e2

## S4 method for signature 'FileArray,array'
e1 ^ e2

## S4 method for signature 'array,FileArray'
e1 ^ e2

## S4 method for signature 'FileArray,FileArray'
e1 %% e2

## S4 method for signature 'FileArray,numeric'
e1 %% e2

## S4 method for signature 'numeric,FileArray'
e1 %% e2

## S4 method for signature 'FileArray,complex'
e1 %% e2

## S4 method for signature 'complex,FileArray'
e1 %% e2

## S4 method for signature 'FileArray,logical'
e1 %% e2

## S4 method for signature 'logical,FileArray'
e1 %% e2

## S4 method for signature 'FileArray,array'
e1 %% e2

## S4 method for signature 'array,FileArray'
e1 %% e2

## S4 method for signature 'FileArray,FileArray'
e1 %/% e2

## S4 method for signature 'FileArray,numeric'
e1 %/% e2

## S4 method for signature 'numeric,FileArray'
e1 %/% e2

## S4 method for signature 'FileArray,complex'
e1 %/% e2

## S4 method for signature 'complex,FileArray'
e1 %/% e2

## S4 method for signature 'FileArray,logical'
e1 %/% e2

## S4 method for signature 'logical,FileArray'
e1 %/% e2

## S4 method for signature 'FileArray,array'
e1 %/% e2

## S4 method for signature 'array,FileArray'
e1 %/% e2

## S4 method for signature 'FileArray,FileArray'
e1 == e2

## S4 method for signature 'FileArray,numeric'
e1 == e2

## S4 method for signature 'numeric,FileArray'
e1 == e2

## S4 method for signature 'FileArray,complex'
e1 == e2

## S4 method for signature 'complex,FileArray'
e1 == e2

## S4 method for signature 'FileArray,logical'
e1 == e2

## S4 method for signature 'logical,FileArray'
e1 == e2

## S4 method for signature 'FileArray,array'
e1 == e2

## S4 method for signature 'array,FileArray'
e1 == e2

## S4 method for signature 'FileArray,FileArray'
e1 > e2

## S4 method for signature 'FileArray,numeric'
e1 > e2

## S4 method for signature 'numeric,FileArray'
e1 > e2

## S4 method for signature 'FileArray,complex'
e1 > e2

## S4 method for signature 'complex,FileArray'
e1 > e2

## S4 method for signature 'FileArray,logical'
e1 > e2

## S4 method for signature 'logical,FileArray'
e1 > e2

## S4 method for signature 'FileArray,array'
e1 > e2

## S4 method for signature 'array,FileArray'
e1 > e2

## S4 method for signature 'FileArray,FileArray'
e1 < e2

## S4 method for signature 'FileArray,numeric'
e1 < e2

## S4 method for signature 'numeric,FileArray'
e1 < e2

## S4 method for signature 'FileArray,complex'
e1 < e2

## S4 method for signature 'complex,FileArray'
e1 < e2

## S4 method for signature 'FileArray,logical'
e1 < e2

## S4 method for signature 'logical,FileArray'
e1 < e2

## S4 method for signature 'FileArray,array'
e1 < e2

## S4 method for signature 'array,FileArray'
e1 < e2

## S4 method for signature 'FileArray,FileArray'
e1 != e2

## S4 method for signature 'FileArray,numeric'
e1 != e2

## S4 method for signature 'numeric,FileArray'
e1 != e2

## S4 method for signature 'FileArray,complex'
e1 != e2

## S4 method for signature 'complex,FileArray'
e1 != e2

## S4 method for signature 'FileArray,logical'
e1 != e2

## S4 method for signature 'logical,FileArray'
e1 != e2

## S4 method for signature 'FileArray,array'
e1 != e2

## S4 method for signature 'array,FileArray'
e1 != e2

## S4 method for signature 'FileArray,FileArray'
e1 >= e2

## S4 method for signature 'FileArray,numeric'
e1 >= e2

## S4 method for signature 'numeric,FileArray'
e1 >= e2

## S4 method for signature 'FileArray,complex'
e1 >= e2

## S4 method for signature 'complex,FileArray'
e1 >= e2

## S4 method for signature 'FileArray,logical'
e1 >= e2

## S4 method for signature 'logical,FileArray'
e1 >= e2

## S4 method for signature 'FileArray,array'
e1 >= e2

## S4 method for signature 'array,FileArray'
e1 >= e2

## S4 method for signature 'FileArray,FileArray'
e1 <= e2

## S4 method for signature 'FileArray,numeric'
e1 <= e2

## S4 method for signature 'numeric,FileArray'
e1 <= e2

## S4 method for signature 'FileArray,complex'
e1 <= e2

## S4 method for signature 'complex,FileArray'
e1 <= e2

## S4 method for signature 'FileArray,logical'
e1 <= e2

## S4 method for signature 'logical,FileArray'
e1 <= e2

## S4 method for signature 'FileArray,array'
e1 <= e2

## S4 method for signature 'array,FileArray'
e1 <= e2

## S4 method for signature 'FileArray,FileArray'
e1 & e2

## S4 method for signature 'FileArray,numeric'
e1 & e2

## S4 method for signature 'numeric,FileArray'
e1 & e2

## S4 method for signature 'FileArray,complex'
e1 & e2

## S4 method for signature 'complex,FileArray'
e1 & e2

## S4 method for signature 'FileArray,logical'
e1 & e2

## S4 method for signature 'logical,FileArray'
e1 & e2

## S4 method for signature 'FileArray,array'
e1 & e2

## S4 method for signature 'array,FileArray'
e1 & e2

## S4 method for signature 'FileArray,FileArray'
e1 | e2

## S4 method for signature 'FileArray,numeric'
e1 | e2

## S4 method for signature 'numeric,FileArray'
e1 | e2

## S4 method for signature 'FileArray,complex'
e1 | e2

## S4 method for signature 'complex,FileArray'
e1 | e2

## S4 method for signature 'FileArray,logical'
e1 | e2

## S4 method for signature 'logical,FileArray'
e1 | e2

## S4 method for signature 'FileArray,array'
e1 | e2

## S4 method for signature 'array,FileArray'
e1 | e2

## S4 method for signature 'FileArray'
!x

## S4 method for signature 'FileArray'
exp(x)

## S4 method for signature 'FileArray'
expm1(x)

## S4 method for signature 'FileArray'
log(x, base = exp(1))

## S4 method for signature 'FileArray'
log10(x)

## S4 method for signature 'FileArray'
log2(x)

## S4 method for signature 'FileArray'
log1p(x)

## S4 method for signature 'FileArray'
abs(x)

## S4 method for signature 'FileArray'
sqrt(x)

## S4 method for signature 'FileArray'
sign(x)

## S4 method for signature 'FileArray'
signif(x, digits = 6)

## S4 method for signature 'FileArray'
trunc(x, ...)

## S4 method for signature 'FileArray'
floor(x)

## S4 method for signature 'FileArray'
ceiling(x)

## S4 method for signature 'FileArray'
round(x, digits = 0)

## S4 method for signature 'FileArray'
acos(x)

## S4 method for signature 'FileArray'
acosh(x)

## S4 method for signature 'FileArray'
asin(x)

## S4 method for signature 'FileArray'
asinh(x)

## S4 method for signature 'FileArray'
atan(x)

## S4 method for signature 'FileArray'
atanh(x)

## S4 method for signature 'FileArray'
cos(x)

## S4 method for signature 'FileArray'
cosh(x)

## S4 method for signature 'FileArray'
cospi(x)

## S4 method for signature 'FileArray'
sin(x)

## S4 method for signature 'FileArray'
sinh(x)

## S4 method for signature 'FileArray'
sinpi(x)

## S4 method for signature 'FileArray'
tan(x)

## S4 method for signature 'FileArray'
tanh(x)

## S4 method for signature 'FileArray'
tanpi(x)

## S4 method for signature 'FileArray'
gamma(x)

## S4 method for signature 'FileArray'
lgamma(x)

## S4 method for signature 'FileArray'
digamma(x)

## S4 method for signature 'FileArray'
trigamma(x)

## S4 method for signature 'FileArray'
Arg(z)

## S4 method for signature 'FileArray'
Conj(z)

## S4 method for signature 'FileArray'
Im(z)

## S4 method for signature 'FileArray'
Mod(z)

## S4 method for signature 'FileArray'
Re(z)

## S4 method for signature 'FileArray'
is.na(x)

Arguments

x, z, e1, e2

FileArray or compatible data

base, digits, ...

passed to other methods

Value

See S4groupGeneric


The type of a file array (extended)

Description

The type of a file array (extended)

Usage

typeof(x)

## S4 method for signature 'FileArray'
typeof(x)

## S4 method for signature 'FileArrayProxy'
typeof(x)

Arguments

x

any file array

Value

A character string. The possible values are "double", "integer", "logical", and "raw"