Skip to main content

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

Project description

MADAP

https://github.com/fuzhanrahmanian/MADAP/blob/master/logo.png?raw=true

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:

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:

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:

python -m madap_cli --file <path_to_file> --procedure <procedure> --results <path_to_results> --header_list <header_list> --plot <list_of_plots>

MADAP can also be used via a GUI:

python -m madap_gui

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.

https://zenodo.org/badge/494354435.svg

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.

History

1.2.1 (2023-12-11)

  • Added Ciclic Voltammetry to the functions

  • CA, CP and CV can be used with multiple plots to chose from

  • New and Imrpoved GUI

  • Fixed saving bug

1.1.0 (2023-08-07)

  • Fixes issue with mismatch array length when positive imaginary data is given

0.11.0 (2022-10-16)

  • Fixed bugs concering the package installation.

  • Improved the documentation.

  • Imrpoved the file structure.

  • madap_gui and madap_cli are now in the same package and can be used as standalone scripts/commands.

0.10.0 (2022-10-03)

  • Updated support of the python versions

0.9.0 (2022-10-02)

  • Update documentation

0.8.0 (2022-10-02)

  • First release on PyPI.

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

MADAP-1.2.1.tar.gz (62.3 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

MADAP-1.2.1-py3-none-any.whl (66.0 kB view details)

Uploaded Python 3

File details

Details for the file MADAP-1.2.1.tar.gz.

File metadata

  • Download URL: MADAP-1.2.1.tar.gz
  • Upload date:
  • Size: 62.3 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.1 CPython/3.9.12

File hashes

Hashes for MADAP-1.2.1.tar.gz
Algorithm Hash digest
SHA256 790d5c05f19f6f147e96a203766503aa8f1792332abc45039184429b224f0c26
MD5 e9ba0b53f311e6ae811e1e6a17b600e7
BLAKE2b-256 f3a7825accba89df60835f6d6bd4cb1e01ae0092cbff2d2eb3812de4158592b4

See more details on using hashes here.

File details

Details for the file MADAP-1.2.1-py3-none-any.whl.

File metadata

  • Download URL: MADAP-1.2.1-py3-none-any.whl
  • Upload date:
  • Size: 66.0 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.1 CPython/3.9.12

File hashes

Hashes for MADAP-1.2.1-py3-none-any.whl
Algorithm Hash digest
SHA256 a7b37275d0ca21abf22798a1c8123f8374ec90bde22a08662c3df178869f1a54
MD5 a59f24fff6d8d70931f3652823d9a53e
BLAKE2b-256 8cf5bc845913a756e0df1d79c97d6848e69bc4ae42091ffc6df6d15b7523b2f0

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page