ebcpy

Provides generic functions and classes commonly used for the analysis and optimization of energy systems, buildings and indoor climate.
https://github.com/RWTH-EBC/ebcpy

Category: Consumption
Sub Category: Buildings and Heating

Keywords

hacktoberfest

Keywords from Contributors

fiware fiware-iot-agents fiware-ngsi-v2 fiware-orion fiware-quantum-leap buildings urban-energy-modeling modelica modelica-library

Last synced: about 2 hours ago
JSON representation

Repository metadata

Host: GitHub
URL: https://github.com/RWTH-EBC/ebcpy
Owner: RWTH-EBC
License: bsd-3-clause
Created: 2021-08-12T10:21:55.000Z (over 3 years ago)
Default Branch: master
Last Pushed: 2025-04-03T07:12:38.000Z (24 days ago)
Last Synced: 2025-04-10T04:41:01.076Z (17 days ago)
Topics: hacktoberfest
Language: Python
Homepage:
Size: 46.1 MB
Stars: 11
Watchers: 14
Forks: 2
Open Issues: 13
Releases: 16
Metadata Files:
- Readme: README.md
- Changelog: CHANGELOG.md
- License: LICENSE

ebcpy

This PYthon package provides generic functions and classes commonly
used for the analysis and optimization of energy systems, buildings and indoor climate (EBC).

Key features are:

TimeSeriesData
SimulationAPI's
Optimization wrapper
Pre-/Postprocessing
Modelica utilities

It was developed together with AixCaliBuHA, a framework for an automated calibration of dynamic building and HVAC models. During this development, we found several interfaces relevant to further research. We thus decoupled these interfaces into ebcpy and used the framework, for instance in the design optimization of heat pump systems (link).

Installation

To install, simply run

pip install ebcpy

In order to use all optional dependencies (e.g. pymoo optimization), install via:

pip install ebcpy[full]

If you encounter an error with the installation of scikit-learn, first install scikit-learn separatly and then install ebcpy:

pip install scikit-learn
pip install ebcpy

If this still does not work, we refer to the troubleshooting section of scikit-learn: https://scikit-learn.org/stable/install.html#troubleshooting. Also check issue 23 for updates.

In order to help development, install it as an egg:

git clone https://github.com/RWTH-EBC/ebcpy
pip install -e ebcpy

How to get started?

We recommend running our jupyter-notebook to be guided through a helpful tutorial.
For this, run the following code:

# If jupyter is not already installed:
pip install jupyter
# Go into your ebcpy-folder (cd \path_to_\ebcpy) or change the path to tutorial.ipynb and run:
jupyter notebook tutorial\tutorial.ipynb

Or, clone this repo and look at the examples\README.md file.
Here you will find several examples to execute.

How to cite ebcpy

Please use the following metadata to cite ebcpy in your research:

@article{Wuellhorst2022,
  doi = {10.21105/joss.03861},
  url = {https://doi.org/10.21105/joss.03861},
  year = {2022},
  publisher = {The Open Journal},
  volume = {7},
  number = {72},
  pages = {3861},
  author = {Fabian Wüllhorst and Thomas Storek and Philipp Mehrfeld and Dirk Müller},
  title = {AixCaliBuHA: Automated calibration of building and HVAC systems},
  journal = {Journal of Open Source Software}
}

TimeSeriesData

Note that we use our own TimeSeriesData object which inherits from pd.DataFrame. The aim is to make tasks like loading different filetypes or applying multiple tags to one variable more convenient, while conserving the powerful tools of the DataFrame.
Just a quick intro here:

Variables and tags

>>> from ebcpy.data_types import TimeSeriesData
>>> tsd = TimeSeriesData(r"path_to_a_supported_file")
>>> print(tsd)
Variables    T_heater              T_heater_1            
Tags             meas         sim        meas         sim
Time                                                     
0.0        313.165863  313.165863  293.173126  293.173126
1.0        312.090271  310.787750  293.233002  293.352448
2.0        312.090027  310.796753  293.385925  293.719055
3.0        312.109436  310.870331  293.589233  294.141754

As you can see, our first column level is always a variable, and the second one a tag.
This is especially handy when dealing with calibration or processing tasks, where you will have multiple
versions (tags) for one variable. The default tag is raw to indicate the unmodified data.
To access a variable, you have to call .loc. To access multiple variables that all hold one tag use xs:

# All tags:
tsd.loc[:, "variable_name"]
# One specific tag:
tsd.loc[:, ("variable_name", "tag_name")]
# One tag, all variables:
tsd.xs("tag_name", axis=1, level=1)

FloatIndex and DateTimeIndex

Measured data typically holds a datetime stamps (DateTimeIndex) while simulation result files hold absolute seconds (FloatIndex).
You can easily convert back and forth using:

# From Datetime to float
tsd.to_float_index()
# From float to datetime
tsd.to_datetime_index()
# To clean your data and create a common frequency:
tsd.clean_and_space_equally(desired_freq="1s")

Documentation

Visit our official Documentation.

Problems?

Please raise an issue here.

Owner metadata

Name: RWTH Aachen University - E.ON Energy Research Center - Institute for Energy Efficient Buildings and Indoor Climate
Login: RWTH-EBC
Email: [email protected]
Kind: organization
Description:
Website: http://www.ebc.eonerc.rwth-aachen.de/
Location: RWTH Aachen University, Aachen, Germany
Twitter:
Company:
Icon url: https://avatars.githubusercontent.com/u/8121773?v=4
Repositories: 52
Last ynced at: 2024-03-27T11:18:30.715Z
Profile URL: https://github.com/RWTH-EBC

GitHub Events

Total

Create event: 5
Release event: 1
Issues event: 7
Delete event: 11
Issue comment event: 4
Push event: 35
Pull request review comment event: 1
Pull request review event: 5
Pull request event: 7
Fork event: 1

Last Year

Create event: 5
Release event: 1
Issues event: 7
Delete event: 11
Issue comment event: 4
Push event: 35
Pull request review comment event: 1
Pull request review event: 5
Pull request event: 7
Fork event: 1

Committers metadata

Last synced: 5 days ago

Total Commits: 638
Total Committers: 23
Avg Commits per committer: 27.739
Development Distribution Score (DDS): 0.393

Commits in past year: 62
Committers in past year: 7
Avg Commits per committer in past year: 8.857
Development Distribution Score (DDS) in past year: 0.484

Name	Email	Commits
fabian.wuellhorst	f**t@r**e	387
FWuellhorst	f**t@e**e	82
Hendrik van der Stok	h**k@r**e	70
Sebastian	S**s@r**e	15
Thomas Storek	t**k@e**e	15
jkriwet	j**t@e**e	15
Philipp Mehrfeld	p**d@r**e	10
Jonas Klingebiel	j**l@e**e	9
David Jansen	d**n@e**e	8
MichaMans	m**s@h**m	6
Tobias Schellen	t**n@e**e	3
jonas.michael.baumgaertner	j**r@r**e	3
FelixStege	3****e	3
Hannah Romberg	h**g@e**e	2
mre	H****3	2
Kai Droste	k**e@e**e	1
Larissa Kühn	l**n@r**e	1
Sebastian Blechmann	5****n	1
Tobias Spratte	1****e	1
saaiiravi	s**1@g**m	1
thomas.storek	t**k@r**e	1
Hendrik van der Stok	h**k@e**e	1
zhiyu.pan	z**n@r**e	1

Committer domains:

eonerc.rwth-aachen.de: 9
rwth-aachen.de: 8

Issue and Pull Request metadata

Last synced: 1 day ago

Total issues: 74
Total pull requests: 80
Average time to close issues: 4 months
Average time to close pull requests: 18 days
Total issue authors: 19
Total pull request authors: 15
Average comments per issue: 0.54
Average comments per pull request: 0.49
Merged pull request: 70
Bot issues: 0
Bot pull requests: 0

Past year issues: 11
Past year pull requests: 14
Past year average time to close issues: 4 days
Past year average time to close pull requests: 4 days
Past year issue authors: 6
Past year pull request authors: 6
Past year average comments per issue: 0.27
Past year average comments per pull request: 0.57
Past year merged pull request: 12
Past year bot issues: 0
Past year bot pull requests: 0

More stats: https://issues.ecosyste.ms/repositories/lookup?url=https://github.com/RWTH-EBC/ebcpy

Top Issue Authors

FWuellhorst (38)
HvanderStok (11)
tstorek (3)
jkriwet (3)
FelixNienaber (2)
HannahRomberg (2)
FelixStege (2)
MichaMans (2)
Cudok (1)
KaiDroste (1)
larissakuehn (1)
MZuschlag (1)
Maghnie (1)
SBlechmann (1)
DaJansenGit (1)

Top Pull Request Authors

FWuellhorst (47)
HvanderStok (13)
jkriwet (3)
FelixStege (3)
MichaMans (2)
HannahRomberg (2)
DaJansenGit (2)
KaiDroste (1)
saaiiravi (1)
larissakuehn (1)
MZuschlag (1)
SBlechmann (1)
KBeeser (1)
tosch4 (1)
tstorek (1)

Top Issue Labels

enhancement (7)
bug (6)
persistent (2)
good first issue (1)
refactor (1)
documentation (1)

Top Pull Request Labels

hackday (1)
hacktoberfest-accepted (1)
bug (1)
documentation (1)

Package metadata

Total packages: 1
Total downloads:
- pypi: 1,677 last-month
Total dependent packages: 0
Total dependent repositories: 1
Total versions: 17
Total maintainers: 1

pypi.org: ebcpy

Python Library used for different python modules for the analysis and optimization of energy systems, buildings and indoor climate

Homepage: https://github.com/RWTH-EBC/ebcpy
Documentation: https://ebcpy.readthedocs.io/
Licenses: BSD 3-Clause
Latest release: 0.5.2 (published 4 months ago)
Last Synced: 2025-04-26T12:35:00.606Z (1 day ago)
Versions: 17
Dependent Packages: 0
Dependent Repositories: 1
Downloads: 1,677 Last month
Rankings:
- Dependent packages count: 10.052%
- Downloads: 15.04%
- Average: 16.469%
- Stargazers count: 16.507%
- Forks count: 19.104%
- Dependent repos count: 21.642%
Maintainers (1)
- erc_ebc

Dependencies

requirements.txt pypi

fmpy >=0.2.27
h5py >=3.1.0
matplotlib >=3.3.4
numpy >=1.19.5
openpyxl >=3.0.5
pandas >=1.1.5
pydantic >=1.8.2
pymoo >=0.4.2
scikit-learn >=0.24.2
scipy >=1.5.4
tables >=3.6.1
xlrd >=2.0.1

docs/requirements.txt pypi

autodoc_pydantic *
m2r2 *
sphinx ==6.2.1
sphinx-material *
sphinx-rtd-theme *

setup.py pypi

Score: 13.739501703354636

ecosyste.ms

Data

Tools

Indexes

Applications

Experiments

Open Sustainable Technology

ebcpy

Keywords

Keywords from Contributors

Repository metadata

README.md

ebcpy

Installation

How to get started?

How to cite ebcpy

TimeSeriesData

Variables and tags

FloatIndex and DateTimeIndex

Documentation

Problems?

Owner metadata

GitHub Events

Total

Last Year

Committers metadata

Committer domains:

Issue and Pull Request metadata

Top Issue Authors

Top Pull Request Authors

Top Issue Labels

Top Pull Request Labels

Package metadata

pypi.org: ebcpy

Dependencies