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Python/numba code for manipulating time-dependent functions of spin-weighted spherical harmonics on future null infinity

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Test and deploy Documentation Status PyPI Version Conda Version MIT License DOI

Scri

Python/numba code for manipulating time-dependent functions of spin-weighted spherical harmonics on future null infinity

Citing this code

If you use this code for academic work (I can't actually imagine any other use for it), please cite the latest version that you used in your publication. The DOI is:

Also please cite the papers for/by which it was produced:

Bibtex entries for these articles can be found here. It might also be nice of you to provide a link directly to this source code.

Quick start

Note that installation is not possible on Windows due to missing FFTW support.

Installation is as simple as

conda install -c conda-forge scri

or

python -m pip install scri

If the latter command complains about permissions, you're probably using your operating system's version of python, which can cause serious conflicts with essential OS functions. To avoid these issues, install conda/mamba. This will create a separate copy of python inside your home directory (avoiding issues with permissions) which you can update independently of your OS.

Then, in python, you can check to make sure installation worked with

import scri
w = scri.WaveformModes()

Note that scri can take a few seconds to import the first time as it compiles some code automatically. Here, w is an object to contain time and waveform data, as well as various related pieces of information -- though it is trivial in this case, because we haven't given it any data. For more information, see the docstrings of scri, scri.WaveformModes, etc.

Documentation

Tutorials and automatically generated API documentation are available on Read the Docs: scri.

Acknowledgments

Every change to this code is recompiled automatically, bundled into a conda package, and made available for download from anaconda.org.

The work of creating this code was supported in part by the Sherman Fairchild Foundation and by NSF Grants No. PHY-1306125 and AST-1333129.