eisy

eisy is a Python module for simulating and classifying impedance data.

Using different combinations of circuit elements and their expression for impedance, the simulation module is able to reproduce the overall impedance response of the selected circuit. Look into the circuit.py page to see which configurations are already supported. The data_simulation.py module allows to simulate the impedance response in the frequency domain and saves the result as a pandas.DataFrame . The impedance response is presented both in its complex form, as well as separated in its real and imaginary parts. Additionally, the data_simulation.py module allows for the creation of a .csv file containing metadata of the simuation just performed (i.e. circuit used, circuit elements values, etc.), as well as appending the raw data of the simulation. Finally, the simulation module provides option of generating a plot of the impdance respose. This can be generated for immediate inspection of the data trend, or saved automaticallyin a .png file having the same file name as the raw .csv file.

An SQL database was created to preserv the simuation files produced and to allow for long term storage of electrochemical impedance spectroscopy data, as well as any data generate from future freatures added to the package. [ ## add more info on the database here ##]

Finally, eisy allows for a electrochemical impedance fingerprinting throught he euse of a Convolutional Neural Network(CNN). Through the generation of simulated data, the network was trained and abtain ana ccuracy of ## Add number here!!##. The classification for now allows to differentialte between single semicircle responses, double semicircle response, impedance respone with a tail end. Addionally, noisy data can be classified and flagged as such.

Note

eisy is a new Python model and will be continuously updated as more feature are developed.

For any suggestions or request for specific features, plese visit the eisy issue page Otherwise, there is always the ooption of submitting a pull request eisy pull request page

How to install eisy

The package can be easiliy installed by executing the following commands:

pip install eisy

conda install eisy (maybe?)

Dependencies

The following packages are required for using eisy

  • Python (>=3.5)
  • SciPy (>=1.0)
  • NumPy (>=1.14)
  • Matplotlib (>=3.0)

Some notebooks are available in the examples/ directory. In order to make use of them, jupyter notebook or alternatively jupyter lab will also be requred.

More requirements can be found in the requirements.txt file.

Future features

The folloowing are implemetations that are planned for the eisy package:

  • Expand the plotting.py module to include bode plots, as well as DRT
  • Expand the alterations.py module to allow the simulation of missing data points and interrupted data collection.
  • Train the Neural Network to being able to cathegorize the above mentioned fetures.
  • Add a model fitting module to allow to predict the equivalent electrcal circuit fr experimental data
  • Rewrite some of the modules to broaden their scope and be more inclusive in functionalities

Suggestions of modifications or additions are welcomed and incoraged. File an issue

Other Section

Contents:

Indices and tables