pyFFS 2.2.1

Fast Fourier Series library

pyFFS is a collection of efficient algorithms to compute Fourier Series and related transforms.

Installation

$ pip install pyFFS

Developer Install

Recommended setup using Anaconda, for optimized numerical libraries:

# Create Anaconda environment
$ conda create --name pyffs python=3
$ conda activate pyffs

# Clone repository
$ git clone https://github.com/imagingofthings/pyFFS.git
$ cd pyFFS
$ # git checkout <commit>

# Install requirements with conda
$ conda install --file requirements.txt

# Optionally install CuPy for GPU support
$ conda install -c conda-forge cupy

# Install pyFFS
$ pip install -e .[dev]
$ pytest                        # Run test suite
$ python setup.py build_sphinx  # Generate documentation

More information about CuPy setup can be found here.

New release

From master branch of original repo:

# Create tag and upload
$ git tag -a vX.X.X -m "Description."
$ git push origin vX.X.X

# Create package and upload to Pypi
$ python setup.py sdist
$ python -m twine upload  dist/pyFFS-X.X.X.tar.gz

You will need a username and password for uploading to PyPi.

Finally, on GitHub set the new tag as the latest release by pressing on it and at the bottom pressing “Create release”.

Remarks

pyFFS is developed and tested on x86_64 systems running Linux and macOS Catalina.