powerbox¶

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.

QuickLinks¶

Docs: https://powerbox.readthedocs.io
Quickstart: http://powerbox.readthedocs.io/en/latest/demos/getting_started.html

powerbox¶

Features¶

Installation¶

Acknowledgment¶

QuickLinks¶

Contents¶

Indices and tables¶