PyKrige: Development of a Kriging Toolkit for Python

Friday, 19 December 2014
Benjamin S Murphy, College of Earth, Ocean, and Atmospheric Sciences, Oregon State University, Corvallis, OR, United States
While Python continues to grow in popularity as a convenient and powerful means of data manipulation and analysis, the language still lacks a package that provides easy access to commonly utilized geostatistical routines. PyKrige is a new contribution that attempts to create a Python library that can be used for basic geostatistical tasks, such as creating water level maps using Ordinary and Universal Kriging. While written in pure Python, the code makes extensive use of NumPy in order to enable fast processing. Supported drift terms for Universal Kriging currently include a regional linear drift (such as would be used to simulate an overall groundwater gradient, as discussed in Tonkin and Larson, Groundwater, 2002), a point-logarithmic drift (such as would be used to simulate wells, as discussed in Tonkin and Larson, Groundwater, 2002), and an external digital elevation model drift (such as would be used to simulate a topographically controlled groundwater surface, as discussed in Desbarats et al., Journal of Hydrology, 2002). The package is intended primarily for kriging of two-dimensional data, but limited support for three-dimensional kriging is currently under development. Though similar tools already exist for other commonly utilized scientific languages, such as R and MATLAB, PyKrige is intended to ease data processing by providing further functionality in Python that can be implemented in a single analysis pipeline. The code will be made available on GitHub.