Jobs and Experiments are abstract objects which hold all information necessary to execute a single computational
job for a
They can be created using the constructor
makeJob which takes a single job id.
Jobs and Experiments are passed to reduce functions like
Furthermore, Experiments can be used in the functions of the
Jobs and Experiments hold these information:
Job ID as integer.
Job parameters as named list.
ExperimentRegistry, the parameters are divided into the sublists “prob.pars” and “algo.pars”.
Seed which is set via
doJobCollection as scalar integer.
Computational resources which were set for this job as named list.
Path to a directory which is created exclusively for this job. You can store external files here.
Directory is persistent between multiple restarts of the job and can be cleaned by calling
Job only: User function passed to
Experiments only: Problem id.
Experiments only: Algorithm id.
Experiments only: Problem instance.
Experiments only: Replication number.
Note that the slots “pars”, “fun”, “algorithm” and “problem” lazy-load required files from the file system and construct the object on the first access. The realizations are cached for all slots except “instance” (which might be stochastic).
Jobs and Experiments can be executed manually with
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tmp = makeRegistry(file.dir = NA, make.default = FALSE) batchMap(function(x, y) x + y, x = 1:2, more.args = list(y = 99), reg = tmp) submitJobs(resources = list(foo = "bar"), reg = tmp) job = makeJob(1, reg = tmp) print(job) # Get the parameters: job$pars # Get the job resources: job$resources # Execute the job locally: execJob(job)
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