PyAnt

Release:

0.11.1

Date:

Aug 09, 2023

PyAnt is a standardization of implementing radar gain pattern in Python. Nothing more, nothing less.

Getting started

To install

pip install pyant

or the nightly build

git clone --branch develop git@github.com:danielk333/pyant.git
cd pyant
pip install .

Tutorials

• Getting started
  • Instansiate and use a model
  • Vectorized parameters
  • Plotting

Examples

Example gallery of the different modular functionality of the toolbox.

• Examples

API Reference

• pyant
  • beam
    • Classes
  • clib
  • coordinates
    • Functions
  • plotting
    • Functions
  • profiling
    • Functions
  • registry
    • Classes
  • statistics
    • Functions
  • beams
    • arrays
    • beams
    • eiscat_3d
    • eiscat_uhf
    • esr
    • radar_parameters
    • tsdr
  • data
  • models
    • airy
    • array
    • cassegrain
    • finite_cylindrical_parabola
    • gaussian
    • interpolated
    • interpolated_array
    • measured
    • phased_finite_cylindrical_parabola

Developing

Please refer to the style and contribution guidelines documented in the [IRF Software Contribution Guide](https://danielk.developer.irf.se/software_contribution_guide/). Generally external code-contributions are made trough a “Fork-and-pull” workflow, while internal contributions follow the branching strategy outlined in the contribution guide.

Docs

To make the docs, use the Makefile by running

make html

Notebooks

To develop notebooks for documentation in Jupyter-lab, install the following

pip install notebook jupytext

Then run notebooks in the appropriate folder docs/source/notebooks using jupyter-notebook and pair the new notebook with a MyST file.

For more information on how to pair notebooks in order to have persistent plain-text versions, see the [jupytext docs](https://jupytext.readthedocs.io/en/latest/paired-notebooks.html).

Indices and tables

• Index

• Module Index

• Search Page