MiSTree: a Python package for constructing and analysing Minimum Spanning Trees
Abstract
The minimum spanning tree (MST), a graph constructed from a distribution of points, draws lines between pairs of points so that all points are linked in a single skeletal structure that contains no loops and has minimal total edge length. The MST has been used in a broad range of scientific fields such as particle physics (to distinguish classes of events in collider collisions), in astronomy (to detect mass segregation in star clusters) and cosmology (to search for filaments in the cosmic web). Its success in these fields has been driven by its sensitivity to the spatial distribution of points and the patterns within. MiSTree, a public Python package, allows a user to construct the MST in a variety of coordinates systems, including Celestial coordinates used in astronomy. The package enables the MST to be constructed quickly by initially using a knearest neighbour graph (kNN, rather than a matrix of pairwise distances) which is then fed to Kruskal's algorithm to construct the MST. MiSTree enables a user to measure the statistics of the MST and provides classes for binning the MST statistics (into histograms) and plotting the distributions. Applying the MST will enable the inclusion of highorder statistics information from the cosmic web which can provide additional information to improve cosmological parameter constraints. This information has not been fully exploited due to the computational cost of calculating Npoint statistics. MiSTree was designed to be used in cosmology but could be used in any field which requires extracting nonGaussian information from point distributions. The source code for MiSTree is available on GitHub at https://github.com/knaidoo29/mistree
 Publication:

The Journal of Open Source Software
 Pub Date:
 October 2019
 DOI:
 10.21105/joss.01721
 arXiv:
 arXiv:1910.08562
 Bibcode:
 2019JOSS....4.1721N
 Keywords:

 Fortran;
 Python;
 cosmology;
 graphs;
 Jupyter Notebook;
 astronomy;
 Astrophysics  Instrumentation and Methods for Astrophysics
 EPrint:
 4 pages, 2 figures, Published in the Journal of Open Source Software