The code was developped for fast fitting of EIS data during my PhD from 2012 to 2015. The documentation is incompleted and the code is no more under active development.
Generate symbolic and lambda functions from the string representation of an electronic circuit in order to compute EIS data.
The module aims to make the computation of EIS data or fitting of experimental data easier and faster by abstracting the procedure of computing the analytic (complex) expressions of the immittance (Z(w) or Y(w)) and turning them into lambda functions. The module contains also a fully operational procedure for fitting experimental data based on the least square method.
Sympy allows to generate the symbolic expressions and turns them into lambda functions. The fitting procedure uses extensively Numpy+Scipy. Plots are generated with matplotlib and console outputs of the results are put together with PrettyTables.
Download the zip or tarball file and extract it locally. Install the package by using the setup.py file. It works with Python 2 and 3.
.. code-block:: python
python setup.py install
Numpy, Scipy, Sympy, Matplotlib and PrettyTable are required dependencies:
- Numpy >=1.8
- Scipy >=0.14
- Sympy >=0.7.5
- Matplotlib >=1.2
- PrettyTables >=0.7.2
See the file LICENSE for information on the history of this
software, terms & conditions for usage, and a DISCLAIMER OF ALL
WARRANTIES.