Repository for code used and referenced in 2024 feature extraction paper submission titled "Computation-efficient Approach to EIS Feature Extraction for Battery Informatics and Big Data"
This repository contains the python source code for extracting key features from electrochemical impedance spectroscopy (EIS) data.
There are two python source code files found in this repository
- EIS_feature_extraction - (same code but as a .py and as a .ipynb file type)
- PCA_analysis_for_EIS_features - (same code but as a .py and as a .ipynb file type)
The EIS_feature_extraction code works to parameterize and extract key features that can be used for chemometric and/or machine learning.
The PCA_analysis_for_EIS_features code loads parameterized data that was generated from the EIS_feature_extraction code and provides a principal component analysis (PCA).
Supporting Data can be found in the 3 subfolders
- Data - location raw data .csv files can be found
- Generated Features - location of extracted feature files
- Figures - location of figures generated from code
#Credits Project Lead - Xueying Li Quinn Project Manager - David Shock
The MIT License (MIT)
Copyright (c) 2024 Powerit
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