batchtools (version 0.9.17)

reduceResults: Reduce Results

Description

A version of Reduce for Registry objects which iterates over finished jobs and aggregates them. All jobs must have terminated, an error is raised otherwise.

Usage

reduceResults(fun, ids = NULL, init, ..., reg = getDefaultRegistry())

Value

Aggregated results in the same order as provided ids. Return type depends on the user function. If ids

is empty, reduceResults returns init (if available) or NULL otherwise.

Arguments

fun

[function]
A function to reduce the results. The result of previous iterations (or the init) will be passed as first argument, the result of of the i-th iteration as second. See Reduce for some examples. If the function has the formal argument “job”, the Job/Experiment is also passed to the function (named).

ids

[data.frame or integer]
A data.frame (or data.table) with a column named “job.id”. Alternatively, you may also pass a vector of integerish job ids. If not set, defaults to the return value of findDone. Invalid ids are ignored.

init

[ANY]
Initial element, as used in Reduce. If missing, the reduction uses the result of the first job as init and the reduction starts with the second job.

...

[ANY]
Additional arguments passed to function fun.

reg

[Registry]
Registry. If not explicitly passed, uses the default registry (see setDefaultRegistry).

See Also

Other Results: batchMapResults(), loadResult(), reduceResultsList()

Examples

 batchtools:::example_push_temp(1) 
tmp = makeRegistry(file.dir = NA, make.default = FALSE)
batchMap(function(a, b) list(sum = a+b, prod = a*b), a = 1:3, b = 1:3, reg = tmp)
submitJobs(reg = tmp)
waitForJobs(reg = tmp)

# Extract element sum from each result
reduceResults(function(aggr, res) c(aggr, res$sum), init = list(), reg = tmp)

# Aggregate element sum via '+'
reduceResults(function(aggr, res) aggr + res$sum, init = 0, reg = tmp)

# Aggregate element prod via '*' where parameter b < 3
reduce = function(aggr, res, job) {
  if (job$pars$b >= 3)
    return(aggr)
  aggr * res$prod
}
reduceResults(reduce, init = 1, reg = tmp)

# Reduce to data.frame() (inefficient, use reduceResultsDataTable() instead)
reduceResults(rbind, init = data.frame(), reg = tmp)

# Reduce to data.frame by collecting results first, then utilize vectorization of rbind:
res = reduceResultsList(fun = as.data.frame, reg = tmp)
do.call(rbind, res)

# Reduce with custom combine function:
comb = function(x, y) list(sum = x$sum + y$sum, prod = x$prod * y$prod)
reduceResults(comb, reg = tmp)

# The same with neutral element NULL
comb = function(x, y) if (is.null(x)) y else list(sum = x$sum + y$sum, prod = x$prod * y$prod)
reduceResults(comb, init = NULL, reg = tmp)

# Alternative: Reduce in list, reduce manually in a 2nd step
res = reduceResultsList(reg = tmp)
Reduce(comb, res)