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spectral

This is a collection of various spectral methods for numerical appraches.

• Available Methods:

  • Chebyshev

  • Fourier

  • Sphercical Harmonics

  • Spin weighted spherical harmonics

Installing

pip install spectools

That gives the import-light part of the package -- spectools.chebyshev and spectools.fourier -- which needs only numpy. It installs anywhere numpy does, including Windows.

The spherical-harmonic and interpolation modules need more:

pip install spectools[spherical]     # spectools.spherical, spectools.interpolation
pip install spectools[docs]          # to build the documentation

Changed in 2026.09: waveformtools and sxstools used to be unconditional requirements, so pip install spectools pulled them in even for a user who only wanted a Chebyshev basis. They pull lalsuite, which publishes no Windows wheel and no source distribution, and scri -> spinsfast, which has no Windows wheel and does not build under MSVC -- so the whole package was uninstallable on Windows. They are now the [spherical] extra. recommonmark and sphinx-rtd-theme were also runtime requirements and are documentation-build tools; they are now [docs]. numpy was never declared at all and now is.

If you use spectools.spherical or spectools.interpolation, install spectools[spherical]; a bare pip install spectools will no longer bring their dependencies.

Citing this code

Please cite the latest version of this code if used in your work. This code was developed for use in the following works:

1. News from Horizons in Binary Black Hole Mergers
2. Tidal deformation of dynamical horizons in binary black hole mergers

We request you to also cite these. Thanks!

Installing this package

Dependencies

This module has the following dependencies:

• Standard packages (come with full anaconda installation)
  • numpy
  • scipy
  • statistics
  • matplotlib
  • h5py
  • termcolor
• Optional dependencies (labelled [EXT])
  • For use with PyCBC data analysis packages.
    • pyCBC
    • lalsuite
    • ligo-common
  • gmpy2

Recommended method

I recommend installing this module through pypi:

pip install spectral

Alternate method

Manual install directly from the git repo:

pip install git+https://github.com/vaishakp/spectral@main

Or from a clone:

• First, clone this repository:

git clone https://github.com/vaishakp/spectral.git

• Second, run python setup from the spectral directory:

cd spectral
python setup.py install --prefix="<path to your preferred installation dir>"

Manually setup conda environment

• To create an environment with automatic dependency resolution and activate it, run

conda create env -f docs/environment.yml
conda activate wftools

Using this code

# Documentation

The documentation for this module is available at [Link to the Documentation](https://spectral.readthedocs.io/en/latest/). This was built automatically using Read the Docs.

In some case where the repo has run out of github CI minutes, the documentation is not automatically built. In such cases, we request the user to access the documentation through the `index.html` file in `docs` directory.


# Bug tracker
If you run into any issues while using this package, please report the issue on the [issue tracker](https://github.com/vaishakp/spectral/-/issues).

 
# Acknowledgements

This project has been hosted, as you can see, on github. Several github tools are used in the deployment of the code, its testing, version control.

The work of this was developed in aiding my PhD work at Inter-University Centre for Astronomy and Astrophysics (IUCAA, Pune, India)](https://www.iucaa.in/). The PhD is in part supported by the [Shyama Prasad Nukherjee Fellowship](https://csirhrdg.res.in/Home/Index/1/Default/2006/59) awarded to me by the [Council of Scientific and Industrial Research (CSIR, India)](https://csirhrdg.res.in/). Resources of the [Inter-University Centre for Astronomy and Astrophysics (IUCAA, Pune, India)](https://www.iucaa.in/) were are used in part.