madap

Python Package for electrochemical analysis

https://github.com/fuzhanrahmanian/madap

Science Score: 67.0%

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

  • CITATION.cff file
    Found CITATION.cff file
  • codemeta.json file
    Found codemeta.json file
  • .zenodo.json file
    Found .zenodo.json file
  • DOI references
    Found 4 DOI reference(s) in README
  • Academic publication links
    Links to: zenodo.org
  • Academic email domains
  • Institutional organization owner
  • JOSS paper metadata
  • Scientific vocabulary similarity
    Low similarity (12.0%) to scientific vocabulary
Last synced: 6 months ago · JSON representation ·

Repository

Python Package for electrochemical analysis

Basic Info
  • Host: GitHub
  • Owner: fuzhanrahmanian
  • License: mit
  • Language: Python
  • Default Branch: master
  • Homepage:
  • Size: 76.4 MB
Statistics
  • Stars: 24
  • Watchers: 2
  • Forks: 3
  • Open Issues: 6
  • Releases: 9
Created almost 4 years ago · Last pushed 10 months ago
Metadata Files
Readme Changelog Contributing License Citation Authors

README.rst


MADAP
~~~~~

.. image:: https://github.com/fuzhanrahmanian/MADAP/blob/master/logo.png?raw=true
    :align: center
    :width: 240px

Modular and Autonomous Data Analysis Platform (MADAP) is a
well-documented python package which can be used for electrochmeical
data analysis.

This package consists of 3 main classes for analysis:

-  Voltammetry
-  Impedance spectroscopy
-  Arrhenius

This package allows user to upload any common file format of data and
the select the data of choice. The user can use to scientifically plot
and get correspondence analysis from each procedure (i.e. by calling
“eis_analysis” , Nyquist, bode as well as the correspondence equivalent
circuit and its parameters will be drawn). This package can be installed
via pip/conda and can be utilized with a GUI, command line or just
directly importing the module in a python script.

Documentation
~~~~~~~~~~~~~

A documentation for the implementation and use of MADAP can be found
`here `__


Installation
~~~~~~~~~~~~

MADAP can be installed via pip:

.. code:: bash

   pip install MADAP


Usage
~~~~~

A brief tutorial video of the basic of MADAP usage can found  `here `_. 

MADAP can be used in a python script as follows: 

.. code:: python

    from madap.echem.arrhenius import arrhenius
    from madap.echem.e_impedance import e_impedance
    from madap.data_acquisition import data_acquisition as da


    # Load the data
    data = da.acquire_data('data.csv')
    # Define the desired plots for Arrhenius analysis
    plots_arr = ["arrhenius", "arrhenius_fit"]
    # Define the desired plots for impedance analysis
    plots_eis = ["nyquist", "nyquist_fit", "bode", "residual"]
    # Define a save location#
    save_dir = "/results"

    ### Arrhenius
    # Instantiate the Arrhenius class for analysis (column names do not have to match exactly, this is just an example)
    Arr = arrhenius.Arrhenius(da.format_data(data["temperature"], da.format_data(data["conductivity"])))
    # Perform analysis and plotting
    Arr.perform_all_actions(save_dir, plots = plots_arr)

    ### Impedance
    # Initialize the Impedance class for analysis (column names do not have to match exactly, this is just an example)
    Im = e_impedance.EImpedance(da.format_data(data["freq"]), da.format_data(data["real"]), da.format_data(data["img"]))
    # Initialis the EIS procedure. The initial value is the initial guess for the equivalent circuit (can also be left empty)
    Eis  = e_impedance.EIS(Im, suggested_circuit = "R0-p(R1,CPE1)",initial_value =[860, 3e+5, 1e-09, 0.90])
    # Analyze the data
    Eis.perform_all_actions(save_dir, plots = plots_eis)

    # More usages and options can be found in the documentation.

MADAP can also be used via command line:

.. code:: bash

   python -m madap_cli --file  --procedure  --results  --header_list  --plot 

MADAP can also be used via a GUI:

.. code:: bash

   python -m madap_gui

.. image:: https://github.com/fuzhanrahmanian/MADAP/raw/master/GUI.png
    :align: center
    :width: 800px


License
~~~~~~~

MADAP is licensed under the MIT license. See the LICENSE file for more
details.


Citation
~~~~~~~~

If you use MADAP in your research, please cite this GitHub repository https://github.com/fuzhanrahmanian/MADAP.

.. image:: https://zenodo.org/badge/494354435.svg
   :target: https://zenodo.org/badge/latestdoi/494354435

Please also cite the following work:
`[Rahmanian2023] `_ Rahmanian, F., Vogler, M., Wölke, C. et al. "Conductivity experiments for electrolyte formulations and their automated analysis." Sci Data 10, 43 (2023).

References
~~~~~~~~~~

This package is based relies on the following packages and papers:
- Impedance GitHub repository by Matthew D. Murbach and Brian Gerwe and Neal Dawson-Elli and Lok-kun Tsui: `link `__
- A Method for Improving the Robustness of linear Kramers-Kronig Validity Tests DOI: https://doi.org/10.1016/j.electacta.2014.01.034

Acknowledgement
~~~~~~~~~~~~~~~

This project has received funding from the European Union’s [Horizon 2020 research and innovation programme](https://ec.europa.eu/programmes/horizon2020/en) under grant agreement [No 957189](https://cordis.europa.eu/project/id/957189). The project is part of BATTERY 2030+, the large-scale European research initiative for inventing the sustainable batteries of the future.

Owner

  • Name: Fuzhan R
  • Login: fuzhanrahmanian
  • Kind: user
  • Location: Neu-Ulm, Germany
  • Company: Karlsruhe University (KIT)

Citation (CITATION.cff)

cff-version: 1.2.0
message: "If you use this software, please cite it as below."
authors:
  - family-names: Rahmanian
    given-names: Fuzahn
    orcid: https://orcid.org/0000-0003-3996-4213
title: Modular and Autonomous Data Analysis Platform (MADAP)"
version: 1.0.0
doi: 10.5281/zenodo.7374383
date-released: 2022-11-28
url: "https://github.com/fuzhanrahmanian/MADAP"

GitHub Events

Total
  • Release event: 1
  • Watch event: 3
  • Push event: 5
  • Create event: 1
Last Year
  • Release event: 1
  • Watch event: 3
  • Push event: 5
  • Create event: 1

Issues and Pull Requests

Last synced: 7 months ago

All Time
  • Total issues: 18
  • Total pull requests: 19
  • Average time to close issues: 2 months
  • Average time to close pull requests: 21 days
  • Total issue authors: 2
  • Total pull request authors: 3
  • Average comments per issue: 0.22
  • Average comments per pull request: 0.11
  • Merged pull requests: 17
  • Bot issues: 0
  • Bot pull requests: 0
Past Year
  • Issues: 0
  • Pull requests: 1
  • Average time to close issues: N/A
  • Average time to close pull requests: 21 days
  • Issue authors: 0
  • Pull request authors: 1
  • Average comments per issue: 0
  • Average comments per pull request: 0.0
  • Merged pull requests: 1
  • Bot issues: 0
  • Bot pull requests: 0
Top Authors
Issue Authors
  • fuzhanrahmanian (16)
  • fuchsstefan (1)
Pull Request Authors
  • fuzhanrahmanian (16)
  • kmarchais (2)
  • leonmerker (1)
Top Labels
Issue Labels
enhancement (8) documentation (2) help wanted (2) bug (2) test (1)
Pull Request Labels

Packages

  • Total packages: 1
  • Total downloads:
    • pypi 95 last-month
  • Total dependent packages: 0
  • Total dependent repositories: 0
  • Total versions: 13
  • Total maintainers: 1
pypi.org: madap

This is MADAP, a software package for the analysis of electrochemical data.

  • Versions: 13
  • Dependent Packages: 0
  • Dependent Repositories: 0
  • Downloads: 95 Last month
Rankings
Dependent packages count: 6.6%
Average: 18.6%
Dependent repos count: 30.6%
Maintainers (1)
Last synced: 7 months ago

Dependencies

requirements.txt pypi
  • PySimpleGUI ==4.60.3
  • attrs ==21.4.0
  • impedance ==1.4.1
  • matplotlib ==3.5.3
  • numpy ==1.22.4
  • pandas ==1.4.2
  • pytest ==7.1.2
  • scikit_learn ==1.1.2
setup.py pypi