Metadata-Version: 2.1
Name: Ekidna
Version: 0.0.9
Summary: Electrochemistry data analysis tools
Home-page: 
Author: OzymandiasTheDead
Author-email: jacob@ekidnasensing.com
License: MIT
Keywords: Ekidna
Classifier: Development Status :: 2 - Pre-Alpha
Classifier: Intended Audience :: Science/Research
Classifier: Operating System :: Microsoft :: Windows :: Windows 10
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python :: 3
License-File: LICENSE.txt

This library contains functions and classes for analysis of, primarily, data collected from 
electrochemistry experiments. Various functions may be useful beyond the scope of electrochemistry.

Examples of tools include: baseline subtraction, pairplots, histograms, standard curve creators, smoothing, etc . . . 

The code is developed by researchers at Ekidna Sensing.



Change Log
===========
0.0.9 (February 14, 2024)
-------------------------
- Ninth Release

Notes:
------
Adjusted existing moving_average_baseline_subtraction function to take a new input, max_iter, which
specifies the maximum number of iterations to be performed by the baseline subtraction algorithm.


Added functions (see "module contents" document for descriptions of these functions):
- running_sd 
- running_mean 
- fitRandlesSevcikModels 
- RS_solution_resistance
- RS_linear_self_blocking
- RS_anomalous_diffusion
- RS_linear_self_blocking_anomalous_diffusion
- RS_basic
- plotRSModels


Added classes (see "module contents" document for descriptions of classes)
- double_power_std_curve
- self_resistance_std_curve
