Powerbox
A python package for making arbitrarily structured, arbitrary-dimension boxes
Install / Use
/learn @steven-murray/PowerboxREADME
======== powerbox
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Make arbitrarily structured, arbitrary-dimension boxes and log-normal mocks.
powerbox is a pure-python code for creating density grids (or boxes) that have an
arbitrary two-point distribution (i.e. power spectrum). Primary motivations for creating
the code were the simple creation of log-normal mock galaxy distributions, but the
methodology can be used for other applications.
Features
- Works in any number of dimensions.
- Really simple.
- Arbitrary isotropic power-spectra.
- Create Gaussian or Log-Normal fields
- Create discrete samples following the field, assuming it describes an over-density.
- Measure power spectra of output fields to ensure consistency.
- Seamlessly uses pyFFTW if available for ~double the speed.
Installation
Simply pip install powerbox. If you want ~2x speedup for large boxes, you can also
install pyfftw by doing pip install powerbox[all]. If you are a conda user, you
may want to install numpy with conda first. If you want to develop powerbox,
clone the repo and install with python -m pip install -e ".[dev]".
Acknowledgment
If you find powerbox useful in your research, please cite the Journal of Open Source Software paper at
https://doi.org/10.21105/joss.00850.
QuickLinks
- Docs: https://powerbox.readthedocs.io
- Quickstart: http://powerbox.readthedocs.io/en/latest/demos/getting_started.html
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