Create arbitrary boxes with isotropic power spectra
Project description
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
powerbox only depends on numpy >= 1.6.2, which will be installed automatically if powerbox is installed using pip (see below). Furthermore, it has the optional dependency of pyfftw, which if installed will offer ~2x performance increase in large fourier transforms. This will be seamlessly used if installed.
To install pyfftw, simply do:
pip install pyfftw
To install powerbox, do:
pip install powerbox
Alternatively, the bleeding-edge version from git can be installed with:
pip install git+git://github.com/steven-murray/powerbox.git
Finally, for a development installation, download the source code and then run (in the top-level directory):
pip install -e .
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.
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