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Parametric patterns/shapes definition and sampling

Project description

Documentation

The documentation is available at https://src.koda.cnrs.fr/eric.debreuve/p-pattern/-/wikis/home.

Installation

This project is published on the Python Package Index (PyPI) at: https://pypi.org/project/p-pattern/. It should be installable from Python distribution platforms or Integrated Development Environments (IDEs). Otherwise, it can be installed from a command console using pip:

For all users (after acquiring administrative rights)

For the current user (no administrative rights required)

Installation

pip install p-pattern

pip install --user p-pattern

Update

pip install --upgrade p-pattern

pip install --user --upgrade p-pattern

Dependencies

The development relies on several packages:

  • Mandatory: logger_36, numpy, scikit-image, scipy

  • Optional: None

The mandatory dependencies, if any, are installed automatically by pip, if they are not already, as part of the installation of p-pattern. Python distribution platforms or Integrated Development Environments (IDEs) should also take care of this. The optional dependencies, if any, must be installed independently by following the related instructions, for added functionalities of p-pattern.

Acknowledgments

https://img.shields.io/badge/code%20style-black-000000.svg https://img.shields.io/badge/%20imports-isort-%231674b1?style=flat&labelColor=ef8336

The project is developed with PyCharm Community.

The code is formatted by Black, The Uncompromising Code Formatter.

The imports are ordered by isortyour imports, so you don’t have to.

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