ParametricJob class provides a prototype of conducting parametric analysis
of EnergyPlus simulations.
param <- param_job(idf, epw) param$apply_measure(measure, ..., .names = NULL) param$run(dir = NULL, parallel_backend = future::multiprocess) param$kill(which = NULL) param$status(which = NULL) param$errors(info = FALSE) param$output_dir(which = NULL) param$locate_output(which = NULL, suffix = ".err", strict = TRUE) param$report_data_dict(which = NULL) param$report_data(which = NULL, key_value = NULL, name = NULL, year = NULL, tz = "GMT", case = "auto") param$tabular_data(which = NULL) param$print()
param <- param_job(idf, epw)
Arguments
idf: Path to EnergyPlus IDF or IMF file or an Idf object.
epw: Path to EnergyPlus EPW file or an Epw object.
param$seed() param$weather()
$seed() will return the input Idf object.
$weather() will return the input Epw object.
param$apply_measure(measure, ..., .names = NULL)
$apply_measure() allows to apply a measure to an Idf and creates
parametric models for analysis. Basically, a measure is just a function
that takes an Idf object and other arguments as input, and returns a
modified Idf object as output. Use ... to supply different arguments
to that measure. Under the hook, mapply() is used to create multiple
Idfs according to the input values.
Arguments
measure: A function that takes an Idf and other arguments as input and
returns an Idf object as output.
...: Other arguments passed to that measure.
.names: A character vector of the names of parametric Idfs. If NULL,
the new Idfs will be named in format measure_name + number.
param$run(dir = NULL, parallel_backend = future::multiprocess) param$kill(which = NULL) param$status(which = NULL) param$errors(info = FALSE) param$output_dir(which = NULL) param$locate_output(which = NULL, suffix = ".err", strict = TRUE) param$report_data_dict(which = NULL) param$report_data(which = NULL, key_value = NULL, name = NULL, year = NULL, tz = "GMT", case = "auto") param$tabular_data(which = NULL)
All those functions have the same meaning in EplusJob class, except that they only return the results of specified simulation.
Arguments
which: An integer vector of the indexes or a character vector or names of
parametric simulations.
parallel_backend: Any acceptable input for future::plan().
All other arguments have the same meanings as in EplusJob class.
Basically, it is a collection of multiple EplusJob objects.