This little library has been written in order to run energy+ simulation in linux and windows in a thread-safe way.
The main goal is to ensure a stable behavior across platform and version, and to make the link between the e+ building model tools written in python and the different analysis and optimization tools.
For now, the package is available on PyPI, and via the github repo.
pip install git+https://github.com/locie/energy_plus_wrapper
for the requirements.
There is two main classes in the library: the EPlusRunner and the Simulation.
The first one is linked with the EnergyPlus local installation and allow to run one or many simulation. It also ensure the compatibility between the executable and the IDF file.
The later is generated with the runner.run_one
and runner.run_many
. It
contains the EnergyPlus simulation reports and results.
A small utility routine ensure_eplus_root
allow to automatically download,
extract and install EnergyPlus (but only for linux for now).
from energyplus_wrapper import EPlusRunner, ensure_eplus_root
eplus_root = ensure_eplus_root("http://url/to/eplus/install.sh")
# or
eplus_root = "path/to/energyplus/install/dir"
runner = EPlusRunner(eplus_root)
simulation = runner.run("my/idf/file.idf", "my/weather/file.epw")
print(simulation.reports) # be aware that the result is a complex nested dict
print(simulation.time_series)
The runner.run is multi-process safe, allowing to run multiple EnergyPlus simulation at the same time.
The method runner.run_many
allow to run multiple simulation at the same
time. It uses joblib.parallel
under the hood : how the simulation are
ran and how many CPU are used can be controlled by joblib.parallel_backend
from energyplus_wrapper import EPlusRunner, ensure_eplus_root
eplus_root = ensure_eplus_root("http://url/to/eplus/install.sh")
# or
eplus_root = "path/to/energyplus/install/dir"
runner = EPlusRunner(eplus_root)
samples = {"sim01": ("idf01.idf", "weather01.epw"),
"sim02": ("idf02.idf", "weather01.epw"),
"sim03": ("idf03.idf", "weather02.epw"),
"sim04": ("idf04.idf", "weather02.epw")}
# run on 4 CPU
with joblib.parallel_backend("loky", n_jobs=4):
sims = runner.run_many(samples)
print(sims.keys())
run_one
, run_many
common mecanismeppy
compatibilityEvery time you need to provide an idf file, you can use a
eppy.modeleditor.IDF
object instead (as obtained using
eppy.openidf
). This allow dynamic change of the model
without the need to rewrite one file per simulation.
According to the backup_strategy
, the runner can save the
files generated by EnergyPlus in the backup
folder. It can
save the files 'always'
, 'on_error'
, or never (with None
).
According to version_mismatch_action
, a mismatch between the
e+ executable and the idf file version will raise
an error,
warn
the user or be ignore
d.
You can provide a custom simulation post process. By default,
the file eplus-table.htm
is parsed and put in the
simulation.reports
attribute, and all the csv files generated
by the run are parsed and put in simulation.time_series
.
For example, you could save all the files generated by the simulation with
from path import Path
import zipfile
archive_folder = Path("./archive/").abspath()
def save_and_compress(simulation):
with zipfile.ZipFile(archive_folder / f"{simulation.name}.gz", "w", zipfile.ZIP_DEFLATED) as zip_handler:
for file in simulation.working_dir.files("*"):
zip_handler.write(file)
runner.run_one(idf, wf, custom_process=save_and_compress)