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Notebook","category":"Energy Storage","sub_category":"Battery","monthly_downloads":124,"total_dependent_repos":1,"total_dependent_packages":0,"readme":"\n\n\u003c!--\n[![Build Status](https://travis-ci.org/ECSHackWeek/impedance.py.svg?branch=master)](https://travis-ci.org/ECSHackWeek/impedance.py)\n\n[![Coverage Status](https://coveralls.io/repos/github/ECSHackWeek/impedance.py/badge.svg?branch=master)](https://coveralls.io/github/ECSHackWeek/impedance.py?branch=master)\n\n[![Documentation Status](https://readthedocs.org/projects/impedancepy/badge/?version=latest)](https://impedancepy.readthedocs.io/en/latest/?badge=latest)\n--\u003e\n\n\nAmpere - Advanced Model Package for ElectRochemical Experiments\n------------\n\n`Ampere` is a Python module for working with battery models.\n\nUsing a [scikit-learn-like API](https://arxiv.org/abs/1309.0238), we hope to make visualizing, fitting, and analyzing impedance spectra more intuitive and reproducible.\n\n\u003ci\u003eAmpere is currently in the alpha phase and new features are rapidly being added.\u003c/i\u003e\nIf you have a feature request or find a bug, please feel free to [file an issue](https://github.com/nealde/Ampere/issues) or, better yet, make the code improvements and [submit a pull request](https://help.github.com/articles/creating-a-pull-request-from-a-fork/)! The goal is to build an open-source tool that the entire electrochemical community can use and improve\n\nAmpere currently provides:\n- A simple API for fitting, predicting, and plotting discharge curves\n- A simple API for generating data, or fitting with arbitrary charge / discharge patterns.\n\n\n## Installation\n### Dependencies\n\nAmpere requires:\n\n- Python (\u003e=3.5)\n- SciPy (\u003e=1.0)\n- NumPy (\u003e=1.14)\n- Matplotlib (\u003e=2.0)\n- Cython (\u003e=0.29)\n\n\nSeveral example notebooks are provided in the examples/ directory. Opening these will require Jupyter notebook or Jupyter lab.\n\n### User Installation\n\nThe easiest way to install Ampere is using pip:\n\n`pip install ampere`\n\n\nHowever, it depends on Cython and Microsoft c++ libraries in order to install (on windows). Those should be added as follows:\n\n`pip install --upgrade cython setuptools`\n\nfollow [these instructions](https://docs.microsoft.com/en-us/answers/questions/136595/error-microsoft-visual-c-140-or-greater-is-require.html) to install the proper c++ libraries using Microsoft tools.\n\nThat may or may not work, depending upon your system. An alternative method of installation that works is:\n\n`git clone https://github.com/nealde/ampere`\n\nI've recently added the Cython-generated c files back to the repo, so it may be as simple as:\n\n`cd ampere`\n`python setup.py install`\n\nHowever, if that doesn't work, the following will rebuild the files:\n\n`cd ampere/models/P2D`\n\n`python setup.py build_ext --inplace`\n\n`cd ../SPM`\n\n`python setup.py build_ext --inplace`\n\nThis will build the local C code that is needed by the main compiler.  Then, you can cd back up to the main folder and\n\n`python setup.py install`\n\nThat will typically work.  I'm still working on getting pip installation working, and it will likely require some package modifications,\nfollowing SKLearn as a guide.\n\n## Examples and Documentation\n\nExamples and documentation will be provided after my Defense, which is set for the end of May.\n\n### On the Horizon\n\n- Currently, all models are solved with Finite Difference discretization.  I would love to use some higher order spatial discretizations.\n- 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.\n- Some of my published work regarding surrogate models for solving and fitting will be implemented once they are fully fleshed out.\n\n- Add ability to serialize / deserialize models from disk, to save the result of an optimization\n- add ability to have custom Up / Un functions for different battery chemistries\n- add documentation / fix docstrings to be accurate\n- add Latex equations and node spacings","funding_links":[],"readme_doi_urls":[],"works":{},"citation_counts":{},"total_citations":0,"keywords_from_contributors":[],"project_url":"https://ost.ecosyste.ms/api/v1/projects/19874","html_url":"https://ost.ecosyste.ms/projects/19874"}