BatchJobs: reduceResults – R documentation

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reduceResults

Reduce results from result directory.

Description

The following functions provide ways to reduce result files into either specific R objects (like vectors, lists, matrices or data.frames) or to arbitrarily aggregate them, which is a more general operation.

Usage

reduceResults(reg, ids, part = NA_character_, fun, init, impute.val,
  progressbar = TRUE, ...)

reduceResultsList(reg, ids, part = NA_character_, fun, ...,
  use.names = "ids", impute.val, progressbar = TRUE)

reduceResultsVector(reg, ids, part = NA_character_, fun, ...,
  use.names = "ids", impute.val)

reduceResultsMatrix(reg, ids, part = NA_character_, fun, ...,
  rows = TRUE, use.names = "ids", impute.val)

reduceResultsDataFrame(reg, ids, part = NA_character_, fun, ...,
  use.names = "ids", impute.val,
  strings.as.factors = default.stringsAsFactors())

reduceResultsDataTable(reg, ids, part = NA_character_, fun, ...,
  use.names = "ids", impute.val)

Arguments

`reg`	[`Registry`] Registry.
`ids`	[`integer`] Ids of selected jobs. Default is all jobs for which results are available.
`part`	[`character`] Only useful for multiple result files, then defines which result file part(s) should be loaded. `NA` means all parts are loaded, which is the default.
`fun`	[`function`] For `reduceResults`, a function `function(aggr, job, res, ...)` to reduce things, for all others, a function `function(job, res, ...)` to select stuff. Here, `job` is the current job descriptor (see `Job`), `result` is the current result object and `aggr` are the so far aggregated results. When using `reduceResults`, your function should add the stuff you want to have from `job` and `result` to `aggr` and return that. When using the other reductions, you should select the stuff you want to have from `job` and `result` and return something that can be coerced to an element of the selected return data structure (reasonable conversion is tried internally). Default behavior for this argument is to return `res`, except for `reduceResults` where no default is available.
`init`	[`ANY`] Initial element, as used in `Reduce`. Default is first result.
`impute.val`	[any] For `reduceResults`: If not missing, the value of `impute.val` is passed to function `fun` as argument `res` for jobs with missing results. For the specialized reduction functions `reduceResults[Type]`: If not missing, `impute.val` is used as a replacement for the return value of `fun` on missing results.
`progressbar`	[`logical(1)`] Set to `FALSE` to disable the progress bar. To disable all progress bars, see `makeProgressBar`.
`...`	[any] Additional arguments to `fun`.
`use.names`	[`character(1)`] Name the results with job ids (“ids”), stored job names (“names”) or return a unnamed result (“none”). Default is `ids`.
`rows`	[`logical(1)`] Should the selected vectors be used as rows (or columns) in the result matrix? Default is `TRUE`.
`strings.as.factors`	[`logical(1)`] Should all character columns in result be converted to factors? Default is `default.stringsAsFactors()`.

Value

Aggregated results, return type depends on function. If ids is empty: reduceResults returns init (if available) or NULL, reduceResultsVector returns c(), reduceResultsList returns list(), reduceResultsMatrix returns matrix(0,0,0), reduceResultsDataFrame returns data.frame().

Examples

# generate results:
reg = makeRegistry(id = "BatchJobsExample", file.dir = tempfile(), seed = 123)
f = function(x) x^2
batchMap(reg, f, 1:5)
submitJobs(reg)
waitForJobs(reg)

# reduce results to a vector
reduceResultsVector(reg)
# reduce results to sum
reduceResults(reg, fun = function(aggr, job, res) aggr+res)

reg = makeRegistry(id = "BatchJobsExample", file.dir = tempfile(), seed = 123)
f = function(x) list(a = x, b = as.character(2*x), c = x^2)
batchMap(reg, f, 1:5)
submitJobs(reg)
waitForJobs(reg)

# reduce results to a vector
reduceResultsVector(reg, fun = function(job, res) res$a)
reduceResultsVector(reg, fun = function(job, res) res$b)
# reduce results to a list
reduceResultsList(reg)
# reduce results to a matrix
reduceResultsMatrix(reg, fun = function(job, res) res[c(1,3)])
reduceResultsMatrix(reg, fun = function(job, res) c(foo = res$a, bar = res$c), rows = TRUE)
reduceResultsMatrix(reg, fun = function(job, res) c(foo = res$a, bar = res$c), rows = FALSE)
# reduce results to a data.frame
print(str(reduceResultsDataFrame(reg)))
# reduce results to a sum
reduceResults(reg, fun = function(aggr, job, res) aggr+res$a, init = 0)

BatchJobs

Batch Computing with R

v1.8

BSD_2_clause + file LICENSE

Authors

Bernd Bischl <bernd_bischl@gmx.net>, Michel Lang <michellang@gmail.com>, Henrik Bengtsson <henrikb@braju.com>

Initial release