EPRAYA: Python package for EPR simulation

Python GitHub License PyPI version

EPRAYA offers tools for simulation, fitting and manipulation of EPR (Electron Paramagnetic Resonance) spectroscopic data (cw EPR) in Python. Using only three containers: Ham, Exp and Vary, users can insert hamiltonian parameters, experimental conditions and range for parameters' variation.

It also offers two modes for simulation:

Classic (CPU): Based in numpy arrays and scipy functions in parallel for simulation and fitting.

With JAX: Based in the JAX package for more efficient calculation and fitting with the ADAM algorithm (GPU use is recommended for faster results).

Installation

The recommended installation method is:

pip install epraya

We recommend to use code editors that support tkinter and plotly (VS Code, Jupyter) to take full advantage of the functions in the package. However, it's possible to use the package in any other code editors.

For further instructions on installation and common question, see the documentation.

Features

  • Simulation of cw EPR single or multiple spin systems of powder or cristal samples.
  • Interactive interface for data inspection and manipulation with ease.
  • Identification of energy levels and resonant fields.
  • Data fitting with Nelder Mead, Metropolis, Genetic Algorithm, Least Squares and ADAM.
  • Plots angular dependance, enegy diagrams, EPR intensity and Absorption curves.
  • JAX implemenetation for GPU compatability.

Documentation

Functions description, tutorials and more specific information, can be access in the documentation.

Limitations

  • Current version of EPRAYA only supports cw EPR. We are working in implementing ENDOR and pulse EPR.
  • EPRAYA supports the simulation to at most 4 interactive spin systems in classic mode and 2 systems with JAX. We expect to improve the calculation times and the possibility to simulate more systems following versions.
  • For easier data manipulation, plotly and tkinter support is required.

Contributions

EPRAYA is a open-code project and contributions are welcome. If you find an error or bug, would like to improve the code or make the documentation clearer, please let us know by opening an issue or pull request.

Authors

EPRAYA is a project of the Física Aplicada group of the Universidad Nacional de Colombia. The principal contributors to the project are: Juan Sebastián Castro, Ovidio Almanza and Miguel E. Gámez.

License

License: MIT

Key dates

PyPI data
Data sourced directly from PyPI's database.
  • Released:
Newer release available (0.1.41.14)

1 maintainer

PyPI data
Data sourced directly from PyPI's database.
Avatar for jcastromi from gravatar.com jcastromi

Credits

Author: Epraya developers

License expression

MIT
View SPDX License List

Requires

Python >=3.12

Classifiers

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