powerbox 0.2.1

Create arbitrary boxes with isotropic power spectra

Make arbitrarily structured, arbitrary-dimension boxes.

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 lognormal 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.

Installation

Clone/Download then python setup.py install. Or just pip install powerbox.

Basic Usage

There are two useful classes: the basic PowerBox and one for log-normal fields: LogNormalPowerBox. You can import them like

from powerbox import PowerBox, LogNormalPowerBox

Once imported, to see all the options, just use help:

help(PowerBox)

For a basic 2D Gaussian field with a power-law power-spectrum, one can use the following:

pb = PowerBox(N=512,                     # Number of grid-points in the box
              dim=2,                     # 2D box
              pk = lambda k: 0.1*k**-2., # The power-spectrum
              boxlength = 1.0)           # Size of the box (sets the units of k in pk)
import matplotlib.pyplot as plt
plt.imshow(pb.delta_x)

Other attributes of the box can be accessed also – check them out with tab completion in an interpreter! The LogNormalPowerBox class is called in exactly the same way, but the resulting field has a log-normal pdf with the same power spectrum.

TODO

• At this point, log-normal transforms are done by back-and-forward FFTs on the grid, which could be slow for higher dimensions. Soon I will implement a more efficient way of doing this using numerical Hankel transforms.

• Some more tests might be nice.