SciKit-GStat 1.0: a SciPy-flavored geostatistical variogram estimation toolbox written in Python

Abstract. Geostatistical methods are widely used in almost all geoscientific disciplines, i.e., for interpolation, rescaling, data assimilation or modeling. At its core, geostatistics aims to detect, quantify, describe, analyze and model spatial covariance of observations. The variogram, a tool describe this formalized way, is at the heart every such method. Unfortunately, many applications focus on interpolation method result rather than quality estimated variogram. Not least because estimating variogram commonly left as task computers, some software implementations do not even show user. This miss, largely determines whether application makes sense all. Furthermore, Python programming language was missing mature, well-established tested package estimation couple years ago. Here I present SciKit-GStat, an open-source that fits well into established frameworks scientific computing puts before more sophisticated about be applied. SciKit-GStat written mutable, object-oriented way mimics typical geostatistical analysis workflow. Its main strength ease use interactivity, it therefore usable with only little no knowledge Python. During last few years, other libraries covering developed along SciKit-GStat. Today, most important ones can interfaced by Additionally, structures reused internally, keep user from learning complex models, just using Common powerful interfaces enable packages workflows forcing stick author's paradigms. ships large number predefined procedures, algorithms estimators, theoretical models binning algorithms. approaches estimate variograms covered out box. same time, base class very flexible adjusted less common problems, well. Last but least, made sure aided implementing new procedures extending core functionality much possible, extend uncovered cases. With broad documentation, guide, tutorials good unit-test coverage, enables implementation details.