Skip to main content

EPRAYA: Python package for EPR simulation

Python GitHub License PyPI version

EPRAYA offers the tools for simulations, 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

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

epraya-0.1.40.1685.tar.gz (117.8 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

epraya-0.1.40.1685-py3-none-any.whl (122.3 kB view details)

Uploaded Python 3

File details

Details for the file epraya-0.1.40.1685.tar.gz.

File metadata

  • Download URL: epraya-0.1.40.1685.tar.gz
  • Upload date:
  • Size: 117.8 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? Yes
  • Uploaded via: twine/7.0.0 CPython/3.13.14

File hashes

Hashes for epraya-0.1.40.1685.tar.gz
Algorithm Hash digest
SHA256 416d2a67fd5a2bc84535b9831f0efb024f8e0b35b7935f758d6de82116f8c0fb
MD5 406aa6f7d6a87278055123eb0338619c
BLAKE2b-256 f5138c4925e229ecc4a83ab8f1e16b9dd61e0cbfb52a7a741db0a7933f07cd93

See more details on using hashes here.

Provenance

The following attestation bundles were made for epraya-0.1.40.1685.tar.gz:

Publisher: python-publish.yml on eprayadev/EPRAYA

Attestations: Values shown here reflect the state when the release was signed and may no longer be current.

File details

Details for the file epraya-0.1.40.1685-py3-none-any.whl.

File metadata

  • Download URL: epraya-0.1.40.1685-py3-none-any.whl
  • Upload date:
  • Size: 122.3 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? Yes
  • Uploaded via: twine/7.0.0 CPython/3.13.14

File hashes

Hashes for epraya-0.1.40.1685-py3-none-any.whl
Algorithm Hash digest
SHA256 ef949d72131c85250ff3acae80c84c25a2dd2f21207695f4a997e5451a46d6e8
MD5 8da2b9e0d6233d0d861e6a825e235f5c
BLAKE2b-256 b6626a500cec7a9e33b83ef5866952fe8ba0947fac4b2f44292421be31b16ea4

See more details on using hashes here.

Provenance

The following attestation bundles were made for epraya-0.1.40.1685-py3-none-any.whl:

Publisher: python-publish.yml on eprayadev/EPRAYA

Attestations: Values shown here reflect the state when the release was signed and may no longer be current.

Release history Release notifications | RSS feed

0.1.41.14

2 files

0.1.41.13

2 files

0.1.41.11

2 files

0.1.41.10

2 files

0.1.41.9

2 files

0.1.41.8

2 files

0.1.41.7

2 files

0.1.41.6

2 files

0.1.41.5

2 files

0.1.41.4

2 files

0.1.41.3

2 files

0.1.41.2

2 files

0.1.41.1

2 files

0.1.41

2 files

0.1.40.1814

2 files

0.1.40.1813

2 files

0.1.40.1812

2 files

0.1.40.1811

2 files

0.1.40.1810

2 files

0.1.40.1809

2 files

0.1.40.1808

2 files

0.1.40.1807

2 files

0.1.40.1806

2 files

0.1.40.1805

2 files

0.1.40.1804

2 files

0.1.40.1803

2 files

0.1.40.1802

2 files

0.1.40.1801

2 files

0.1.40.1800

2 files

0.1.40.1730

2 files

0.1.40.1725

2 files

0.1.40.1720

2 files

0.1.40.1710

2 files

This release

0.1.40.1685 This release

2 files

0.1.40.169

2 files

0.1.40.168

2 files

0.1.40.167

2 files

0.1.40.166

2 files

0.1.40.165

2 files

0.1.40.164

2 files

0.1.40.162

2 files

0.1.40.161

2 files

0.1.40.50

2 files

0.1.40.17

2 files

0.1.40.15

2 files

0.1.40.1

2 files

0.1.35.659

2 files

0.1.35.658

2 files

0.1.35.657

2 files

0.1.35.656

2 files

0.1.35.654

2 files

0.1.35.653

2 files

0.1.35.652

2 files

0.1.35.651

2 files

0.1.35.72

2 files

0.1.35.65

2 files

0.1.35.7

2 files

0.1.35.6

2 files

0.1.35.5

2 files

0.1.35.4

2 files

0.1.35

2 files

0.1.34.99.5

2 files

0.1.34.99

2 files

0.1.34.98

2 files

0.1.34.97

2 files

0.1.34.96

2 files

0.1.34.95

2 files

0.1.34.9

2 files

0.1.34.8

2 files

0.1.34.7

2 files

0.1.34.6

2 files

0.1.34.5

2 files

0.1.34

2 files

0.1.33.5

2 files

0.1.33

2 files

0.1.32

2 files

0.1.31

2 files

0.1.30

2 files

0.1.29

2 files

0.1.27

2 files

Anthropic, PBC Visionary sponsor Bloomberg Visionary sponsor Hudson River Trading Visionary sponsor Meta Visionary sponsor NVIDIA Visionary sponsor Microsoft Sustainability sponsor Depot Continuous Integration AWS Cloud computing and Security Sponsor Datadog Monitoring Fastly CDN Google Download Analytics Sentry Error logging StatusPage Status page