PyProBE

PyProBE: Python Processing for Battery Experiments - Published in JOSS (2025)

https://github.com/imperialcollegelondon/pyprobe

Science Score: 95.0%

This score indicates how likely this project is to be science-related based on various indicators:

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CITATION.cff file
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codemeta.json file
Found codemeta.json file
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.zenodo.json file
Found .zenodo.json file
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DOI references
Found 6 DOI reference(s) in README and JOSS metadata
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Academic publication links
Links to: joss.theoj.org, zenodo.org
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Committers with academic emails
3 of 9 committers (33.3%) from academic institutions
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Institutional organization owner
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JOSS paper metadata
Published in Journal of Open Source Software

Keywords from Contributors

meshing standardization hydrology geoscience wavelets interpretability pde mathematics dynamics pypy

Scientific Fields

Earth and Environmental Sciences Physical Sciences - 83% confidence

Artificial Intelligence and Machine Learning Computer Science - 83% confidence

Last synced: 4 months ago · JSON representation

Repository

Python Processing for Battery Experiments

Basic Info

Host: GitHub
Owner: ImperialCollegeLondon
License: bsd-3-clause
Language: Python
Default Branch: main
Homepage: https://pyprobe.readthedocs.io
Size: 258 MB

Statistics

Stars: 29
Watchers: 2
Forks: 14
Open Issues: 29
Releases: 25

Created over 1 year ago · Last pushed 4 months ago

Metadata Files

Readme Changelog Contributing License Citation Zenodo

PyProBE

Python Version from PEP 621 TOML

PyProBE (Python Processing for Battery Experiments) is a Python package designed to simplify and accelerate the process of analysing data from battery cyclers.

PyProBE is documented here. Examples are stored in docs/source/examples and are integrated into the documentation here.

Installing PyProBE

Install PyProBE with pip:

bash pip install PyProBE-Data

For more detail see the user installation guide.

To install from source see the developer installation guide.

PyProBE Objectives

1. Ease of use

PyProBE breaks down complex battery data into simple, easy to understand objects that can be accessed with a few lines of code using natural language. The procedure shown below: ![Procedures and experiments](./docs/source/user_guide/images/Procedures_and_experiments.jpg) can be filtered into the experiments that make up the procedure: ```python cell.procedure['Reference Test'].experiment('Initial Charge') cell.procedure['Reference Test'].experiment('Discharge Pulses') ``` And filtered by cycle, step or step type: ```python cell.procedure['Reference Test'].step(1) cell.procedure['Reference Test'].experiment('Discharge Pulses').cycle(3).discharge(0) ``` This makes it easy to quickly access the data you need for analysis. See the [filtering data](https://pyprobe.readthedocs.io/en/latest/examples/filtering-data.html) example to see this in action. See the [documentation](https://pyprobe.readthedocs.io/en/latest/) for a detailed user guide. Start with the following pages to get PyProBE set up with your data: - [Importing data](https://pyprobe.readthedocs.io/en/latest/user_guide/importing_data.html) - [Accessing data](https://pyprobe.readthedocs.io/en/latest/user_guide/accessing_data.html) - [Plotting](https://pyprobe.readthedocs.io/en/latest/user_guide/plotting.html) PyProBE works with numerous cyclers. For guidance on how to export your data to work with PyProBE see the [Input Data Guidance](https://pyprobe.readthedocs.io/en/latest/user_guide/input_data_guidance.html).

2. Accelerate battery data exploration

PyProBE has built-in plotting methods that integrate with [matplotlib](https://matplotlib.org/), [hvplot](https://hvplot.holoviz.org/) and [seaborn](https://seaborn.pydata.org/index.html) for fast and flexible visualization of battery data. It also includes a graphical user interface (GUI) for exploring data interactively, with almost no code. Run the [getting started](./docs/source/examples/getting-started.ipynb) example locally to try the GUI. ![PyProBE Dashboard](./docs/source/user_guide/images/Dashboard.png) PyProBE is fast! Built on [Polars](https://docs.pola.rs/) dataframes, PyProBE out-performs manual filtering with Pandas and stores data efficiently in Parquet files: ![PyProBE performance](./docs/source/user_guide/images/execution_time.png)

3. Encourage data processing aligned with FAIR principles

PyProBE is designed to encourage good practice for storing and processing data PyProBE requires a README file to sit alongside your experimental data which is: **Human readable:** Sits alongside your data to allow others to quickly understand your experimental procedure. **Computer readable:** Simplifies the PyProBE backend, maximises flexibility to different input data and makes the setup process fast and intuitive for new data. ![README file](./docs/source/user_guide/images/Readme.jpg) See the [guidance](https://pyprobe.readthedocs.io/en/latest/user_guide/writing_a_readme_file.html) for writing README files for your experiments.

4. Host a library of analysis methods

PyProBE's [analysis](https://pyprobe.readthedocs.io/en/latest/_autosummary/pyprobe.analysis.html) module contains classes and methods to perform further analysis of battery data. It is designed to maintain compatibility with the PyProBE data format and plotting tools while ensuring functions are simply defined, portable and tested. The currently implemented analysis methods includes: - Summarise pulsing experiments with resistance information from each pulse - Summarise cycling experiments with SOH quantification for each cycle - Differentiation of any quantity - Finite-difference based method - Level Evaluation ANalysis method - Data smoothing - Level-based method - Spline fitting - Savitzky-Golay filtering - Degradation mode analysis - Curve fitting to pseudo-OCV, Incremental Capacity Analysis (ICA) or Differential Voltage Analysis (DVA) curves - Charge/discharge pseudo-OCV curve averaging for resistance compensation It is easy to contribute to the analysis module. See the [developer guide](https://pyprobe.readthedocs.io/en/latest/developer_guide/contributing_to_the_analysis_module.html) and [contributing guidelines](CONTRIBUTING.md).

Contributing to PyProBE

Contributions to PyProBE are welcome. Please see the contributing guidelines.

Citing PyProBE

If you use PyProBE for a scientific paper, please cite our paper:

Holland, T., Cummins, D., & Marinescu, M. (2025). PyProBE: Python Processing for Battery Experiments. Journal of Open Source Software, 10(106), 7474. https://doi.org/10.21105/joss.07474

License

PyProBE is fully open source. For more information about its license, see LICENSE.

Contributors

_{Tom Holland}

_{Felix Watson}

_{Mohammed Asheruddin (Asher)}

Owner

Name: Imperial College London
Login: ImperialCollegeLondon
Kind: organization
Email: icgithub-support@imperial.ac.uk
Location: Imperial College London

Repositories: 311
Profile: https://github.com/ImperialCollegeLondon

Imperial College main code repository

JOSS Publication

PyProBE: Python Processing for Battery Experiments

Published

February 04, 2025

DOI

10.21105/joss.07474

Volume 10, Issue 106, Page 7474

Authors

Thomas Holland
Department of Mechanical Engineering, Imperial College London, United Kingdom, The Faraday Institution, United Kingdom

Daniel Cummins
Research Computing Service, ICT, Imperial College London, United Kingdom

Monica Marinescu
Department of Mechanical Engineering, Imperial College London, United Kingdom, The Faraday Institution, United Kingdom

Editor

Sophie Beck

GitHub Events

Total

Create event: 151
Release event: 16
Issues event: 45
Watch event: 18
Delete event: 137
Issue comment event: 69
Push event: 384
Pull request review comment event: 5
Pull request review event: 10
Pull request event: 267
Fork event: 11

Last Year

Create event: 152
Release event: 16
Issues event: 45
Watch event: 18
Delete event: 137
Issue comment event: 69
Push event: 384
Pull request review comment event: 5
Pull request review event: 10
Pull request event: 267
Fork event: 11

Committers

Last synced: 5 months ago

All Time

Total Commits: 1,216
Total Committers: 9
Avg Commits per committer: 135.111
Development Distribution Score (DDS): 0.084

Past Year

Commits: 634
Committers: 7
Avg Commits per committer: 90.571
Development Distribution Score (DDS): 0.096

Top Committers

Name	Email	Commits
Tom Holland	t**7@o**m	1,114
Holland Tom	t**7@i**k	32
pre-commit-ci[bot]	6****]	24
renovate[bot]	2****]	16
dependabot[bot]	4****]	13
Felix Watson	f**1@i**k	8
github-actions[bot]	4****]	4
Tom Holland	t**2@g**m	4
mohammedasher	m**u@i**k	1

Committer Domains (Top 20 + Academic)

ic.ac.uk: 2 ic-fb685n3.ic.ac.uk: 1

Issues and Pull Requests

Last synced: 4 months ago

All Time

Total issues: 70
Total pull requests: 324
Average time to close issues: 2 months
Average time to close pull requests: 6 days
Total issue authors: 5
Total pull request authors: 8
Average comments per issue: 0.19
Average comments per pull request: 0.32
Merged pull requests: 243
Bot issues: 1
Bot pull requests: 153

Past Year

Issues: 31
Pull requests: 271
Average time to close issues: about 2 months
Average time to close pull requests: 6 days
Issue authors: 5
Pull request authors: 8
Average comments per issue: 0.29
Average comments per pull request: 0.35
Merged pull requests: 197
Bot issues: 1
Bot pull requests: 141

View more stats

Top Authors

Issue Authors

tomjholland (64)
jakobhaervig (2)
cfolkson (2)
renovate[bot] (1)
DrIVIinotaur (1)

Pull Request Authors

tomjholland (164)
dependabot[bot] (47)
github-actions[bot] (39)
pre-commit-ci[bot] (34)
renovate[bot] (33)
haydenrodrigues (4)
mohammedasher (2)
FW-Coding (1)

Top Labels

Issue Labels

feature (20) frontend (16) backend (15) MVP (10) documentation (8) bug (7) refactor (3) dependencies (2) good first issue (2) optimisation (1) infrastructure (1) umbrella (1) breaking (1)

Pull Request Labels

dependencies (57) documentation (55) bug (38) infrastructure (33) feature (22) backend (19) refactor (17) frontend (12) breaking (11) python:uv (10) optimisation (3) github_actions (2) umbrella (1)

Packages

Total packages: 1
Total downloads:
- pypi 172 last-month

Total dependent packages: 0
Total dependent repositories: 0
Total versions: 12
Total maintainers: 1

pypi.org: pyprobe-data

Homepage: https://github.com/ImperialCollegeLondon/PyProBE
Documentation: https://https://pyprobe.readthedocs.io/PyProBE/
License: BSD 3-Clause License Copyright (c) 2024, Thomas Holland Redistribution and use in source and binary forms, with or without modification, are permitted provided that the following conditions are met: 1. Redistributions of source code must retain the above copyright notice, this list of conditions and the following disclaimer. 2. Redistributions in binary form must reproduce the above copyright notice, this list of conditions and the following disclaimer in the documentation and/or other materials provided with the distribution. 3. Neither the name of the copyright holder nor the names of its contributors may be used to endorse or promote products derived from this software without specific prior written permission. THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
Latest release: 2.3.1
published 5 months ago

Versions: 12
Dependent Packages: 0
Dependent Repositories: 0
Downloads: 172 Last month

Rankings

Dependent packages count: 9.8%

Average: 32.6%

Dependent repos count: 55.3%

Maintainers (1)

tomjholland

Last synced: 4 months ago

Dependencies

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184 dependencies

PyProBE

Science Score: 95.0%

Keywords from Contributors

Scientific Fields

Repository

Basic Info

Statistics

Metadata Files

README.md

PyProBE

Installing PyProBE

PyProBE Objectives

Contributing to PyProBE

Citing PyProBE

License

Contributors

Owner

JOSS Publication

PyProBE: Python Processing for Battery Experiments

Authors

Editor

Tags

GitHub Events

Total

Last Year

Committers

All Time

Past Year

Top Committers

Committer Domains (Top 20 + Academic)

Issues and Pull Requests

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Past Year

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Issue Labels

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Packages

pypi.org: pyprobe-data

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Maintainers (1)

Dependencies