VIDE: The Void IDentification and Examination toolkit

We present vide, the Void IDentification and Examination toolkit, an open-source Python/C++ code for finding cosmic voids in galaxy redshift surveys and N-body simulations, characterizing their properties, and providing a platform for more detailed analysis. At its core, vide  uses a substantially enhanced version of zobov (Neyinck 2008) to calculate a Voronoi tessellation for estimating the density field and performing a watershed transform to construct voids. Additionally, vide  provides significant functionality for both pre- and post-processing: for example, vide  can work with volume- or magnitude-limited galaxy samples with arbitrary survey geometries, or dark matter particles or halo catalogs in a variety of common formats. It can also randomly subsample inputs and includes a Halo Occupation Distribution model for constructing mock galaxy populations. vide  uses the watershed levels to place voids in a hierarchical tree, outputs a summary of void properties in plain ASCII, and provides a Python API to perform many analysis tasks, such as loading and manipulating void catalogs and particle members, filtering, plotting, computing clustering statistics, stacking, comparing catalogs, and fitting density profiles. While centered around ZOBOV, the toolkit is designed to be as modular as possible and accommodate other void finders. vide  has been in development for several years and has already been used to produce a wealth of results, which we summarize in this work to highlight the capabilities of the toolkit. vide  is publicly available at http://bitbucket.org/cosmicvoids/vide_public and http://www.cosmicvoids.net.