Generates a data.frame
with one row per job id. The columns are: ids of problem and algorithm
(named “prob” and “algo”), one column per parameter of problem or algorithm (named by the parameter name),
the replication number (named “repl”) and all columns defined in the function to collect the values.
Note that you cannot rely on the order of the columns.
If a parameter does not have a setting for a certain job / experiment it is set to NA
.
Have a look at getResultVars
if you want to use something like ddply
on the
results.
The rows are ordered as ids
and named with ids
, so one can easily index them.
reduceResultsExperiments(
reg,
ids,
part = NA_character_,
fun,
...,
strings.as.factors = FALSE,
block.size,
impute.val,
apply.on.missing = FALSE,
progressbar = TRUE
)
[ExperimentRegistry
]
Registry.
[integer
]
Ids of selected experiments.
Default is all jobs for which results are available.
[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.
[function(job, res, ...)
]
Function to collect values from job
and result res
object, the latter from stored result file.
Must return a named object which can be coerced to a data.frame
(e.g. a list
).
Default is a function that simply returns res
which may or may not work, depending on the type
of res
. We recommend to always return a named list.
[any]
Additional arguments to fun
.
[logical(1)
]
Should all character columns in result be converted to factors?
Default is FALSE
.
[integer(1)
]
Results will be fetched in blocks of this size.
Default is max(100, 5 percent of ids).
[named list
]
If not missing, the value of impute.val
is used as a replacement for the
return value of function fun
on missing results. An empty list is allowed.
[logical(1)
]
Apply the function on jobs with missing results? The argument “res” will be NULL
and must be handled in the function.
This argument has no effect if impute.val
is set.
Default ist FALSE
.
[logical(1)
]
Set to FALSE
to disable the progress bar.
To disable all progress bars, see makeProgressBar
.
[data.frame
]. Aggregated results, containing problem and algorithm paramaters and collected values.