Ampere

A python package for battery models

https://github.com/nealde/Ampere

Science Score: 20.0%

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  • Academic publication links
    Links to: arxiv.org
  • Committers with academic emails
    1 of 1 committers (100.0%) from academic institutions
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    Low similarity (18.9%) to scientific vocabulary
Last synced: 11 months ago · JSON representation

Repository

A python package for battery models

Basic Info
  • Host: GitHub
  • Owner: nealde
  • License: mit
  • Language: Jupyter Notebook
  • Default Branch: master
  • Size: 3.43 MB
Statistics
  • Stars: 22
  • Watchers: 5
  • Forks: 7
  • Open Issues: 8
  • Releases: 0
Created almost 8 years ago · Last pushed about 3 years ago
Metadata Files
Readme License Code of conduct

README.md

Ampere - Advanced Model Package for ElectRochemical Experiments

Ampere is a Python module for working with battery models.

Using a scikit-learn-like API, we hope to make visualizing, fitting, and analyzing impedance spectra more intuitive and reproducible.

Ampere is currently in the alpha phase and new features are rapidly being added. If you have a feature request or find a bug, please feel free to file an issue or, better yet, make the code improvements and submit a pull request! The goal is to build an open-source tool that the entire electrochemical community can use and improve

Ampere currently provides: - A simple API for fitting, predicting, and plotting discharge curves - A simple API for generating data, or fitting with arbitrary charge / discharge patterns.

Installation

Dependencies

Ampere requires:

  • Python (>=3.5)
  • SciPy (>=1.0)
  • NumPy (>=1.14)
  • Matplotlib (>=2.0)
  • Cython (>=0.29)

Several example notebooks are provided in the examples/ directory. Opening these will require Jupyter notebook or Jupyter lab.

User Installation

The easiest way to install Ampere is using pip:

pip install ampere

However, it depends on Cython and Microsoft c++ libraries in order to install (on windows). Those should be added as follows:

pip install --upgrade cython setuptools

follow these instructions to install the proper c++ libraries using Microsoft tools.

That may or may not work, depending upon your system. An alternative method of installation that works is:

git clone https://github.com/nealde/ampere

I've recently added the Cython-generated c files back to the repo, so it may be as simple as:

cd ampere python setup.py install

However, if that doesn't work, the following will rebuild the files:

cd ampere/models/P2D

python setup.py build_ext --inplace

cd ../SPM

python setup.py build_ext --inplace

This will build the local C code that is needed by the main compiler. Then, you can cd back up to the main folder and

python setup.py install

That will typically work. I'm still working on getting pip installation working, and it will likely require some package modifications, following SKLearn as a guide.

Examples and Documentation

Examples and documentation will be provided after my Defense, which is set for the end of May.

On the Horizon

  • Currently, all models are solved with Finite Difference discretization. I would love to use some higher order spatial discretizations.
  • Currently, the results have not been verified with external models. That is still on the to-do list, and to incorporate those values into the test suite would be excellent.
  • Some of my published work regarding surrogate models for solving and fitting will be implemented once they are fully fleshed out.

  • Add ability to serialize / deserialize models from disk, to save the result of an optimization

  • add ability to have custom Up / Un functions for different battery chemistries

  • add documentation / fix docstrings to be accurate

  • add Latex equations and node spacings

Owner

  • Name: Neal
  • Login: nealde
  • Kind: user
  • Location: Boston, MA

I'm the Machine Learning Team Lead at Nanoramic Labs, where I build analytics pipelines and tooling to make battery research faster and easier.

GitHub Events

Total
Last Year

Committers

Last synced: 12 months ago

All Time
  • Total Commits: 30
  • Total Committers: 1
  • Avg Commits per committer: 30.0
  • Development Distribution Score (DDS): 0.0
Past Year
  • Commits: 0
  • Committers: 0
  • Avg Commits per committer: 0.0
  • Development Distribution Score (DDS): 0.0
Top Committers
Name Email Commits
Neal n****e@u****u 30
Committer Domains (Top 20 + Academic)
uw.edu: 1

Issues and Pull Requests

Last synced: 11 months ago

All Time
  • Total issues: 9
  • Total pull requests: 2
  • Average time to close issues: 4 months
  • Average time to close pull requests: N/A
  • Total issue authors: 3
  • Total pull request authors: 1
  • Average comments per issue: 0.78
  • Average comments per pull request: 0.0
  • Merged pull requests: 0
  • Bot issues: 0
  • Bot pull requests: 2
Past Year
  • Issues: 0
  • Pull requests: 0
  • Average time to close issues: N/A
  • Average time to close pull requests: N/A
  • Issue authors: 0
  • Pull request authors: 0
  • Average comments per issue: 0
  • Average comments per pull request: 0
  • Merged pull requests: 0
  • Bot issues: 0
  • Bot pull requests: 0
Top Authors
Issue Authors
  • nealde (7)
  • tvanyo (1)
  • kepeng (1)
Pull Request Authors
  • dependabot[bot] (2)
Top Labels
Issue Labels
Pull Request Labels
dependencies (2)

Packages

  • Total packages: 1
  • Total downloads:
    • pypi 137 last-month
  • Total dependent packages: 0
  • Total dependent repositories: 1
  • Total versions: 25
  • Total maintainers: 1
pypi.org: ampere

A Python package for working with battery discharge data and physics-based battery models

  • Versions: 25
  • Dependent Packages: 0
  • Dependent Repositories: 1
  • Downloads: 137 Last month
Rankings
Dependent packages count: 7.4%
Forks count: 12.6%
Stargazers count: 13.6%
Average: 14.8%
Downloads: 18.1%
Dependent repos count: 22.2%
Maintainers (1)
Last synced: 11 months ago

Dependencies

requirements.txt pypi
  • matplotlib ==2.2.2
  • nbsphinx *
  • nose ==1.3.7
  • numpy ==1.14.2
  • numpydoc ==0.8.0
  • scipy ==1.0.1
setup.py pypi
  • cython *
  • matplotlib *
  • numpy *
  • scipy *