navani

Module for processing and plotting electrochemical data from battery cyclers, combining other open source libraries to create pandas dataframes with a normalized schema across multiple cycler brands. Contains functions to compute dQ/dV and dV/dQ.

Currently supports:

• BioLogic MPR (.mpr)
• Arbin res files (.res)
• Simple .txt and Excel .xls/.xlsx formats produced by e.g., Arbin, Ivium and Lanhe/Lande
• Neware NDA and NDAX (.nda, .ndax)

The main dependencies are :

• pandas
• galvani (BioLogic MPR)
• mdbtools (for reading Arbin's .res files with galvani).
• NewareNDA (for reading Neware's NDA and NDAx formats).

Installation

It is stronly recommended to use a fresh Python environment to install navani, using e.g., conda create or python -m venv <chosen directory. To install navani, either clone this repository and install from your local copy:

git clone git@github.com/BenSmithGreyGroup/navani
cd navani
pip install .

or install directly from GitHub with pip:

pip install git+https://github.com/BenSmithGreyGroup/navani

The additional non-Python mdbtools dependency to galvani that is required to read Arbin's .res format can be installed on Ubuntu via sudo apt install mdbtools, with similar instructions available for other Linux distributions.

Usage

The main entry point to navani is the navani.echem.echem_file_loader function, which will do file type detection and return a pandas dataframe. Many different plot types are then available, as shown below:

import pandas as pd
import navani.echem as ec

df = ec.echem_file_loader(filepath)
fig, ax = ec.charge_discharge_plot(df, 1)

for cycle in [1, 2]:
    mask = df['half cycle'] == cycle
    voltage, dqdv, capacity = ec.dqdv_single_cycle(df['Capacity'][mask], df['Voltage'][mask],
                                                   window_size_1=51,
                                                    polyorder_1=5,
                                                    s_spline=0.0,
                                                    window_size_2=51,
                                                    polyorder_2=5,
                                                    final_smooth=True)
    plt.plot(voltage, dqdv)

plt.xlim(0, 0.5)
plt.xlabel('Voltage / V')
plt.ylabel('dQ/dV / mAhV$^{-1}$')

fig, ax = ec.multi_dqdv_plot(df, cycles=cycles,
                    colormap='plasma',
                    window_size_1=51,
                    polyorder_1=5,
                    s_spline=1e-7,
                    window_size_2=251,
                    polyorder_2=5,
                    final_smooth=True)