mmaelicke/scikit-gstat: A scipy flavoured geostatistical variogram analysis toolbox

Description SciKit-Gstat is a scipy-styled geostatistical toolbox for variogram estimation. It includes two base classes Variogram and OrdinaryKriging. Additionally, various variogram classes inheriting from Variogram are available for solving directional or space-time related tasks. The module makes use of a rich selection of semi-variance estimators and variogram model functions while being extensible at the same time. This version may be the last minor version before the first stable release 1.0 is released! Version 0.6 brings several smaller adjustments. A new interface was introduced to export a Variogram directly into a gstools.Krige instance. This makes kriging even more seamless between scikit-gstat and gstools. The Variogram has a new method called cross_validate to validate variograms by a leave-one-out Kriging interpolation. This is accompanied by some internals to estimate observation uncertainty and plot error bars in the default plot. Proper uncertainty estimation is still a long way to go and possible a good objective for version 1.1. Finally, SciKit-GStat has a skgstat.data submodule, that can return sample data. Documentation Full Documentation https://mmaelicke.github.io/scikit-gstat User Guide https://mmaelicke.github.io/scikit-gstat/userguide/userguide.html Tutorials https://mmaelicke.github.io/scikit-gstat/tutorials/tutorials.html Changes since 0.5 The util and data submodule are now always loaded at top-level fixed a potential circular import added uncertainty tools to util. This is not yet finished and may change the signature before it gets stable with Version 1.0.0 Version 0.5.6 [Variogram] the interal MetricSpace instance used to calculate the distance matrix is now available as the Variogram.metric_space property. [Variogram] Variogram.metric_space is now read-only. [unittest] two unittests are changed (linting, not functionality) Version 0.5.5 [data] new submodule skgstat.data contains sample random fields and methods for sampling these fields in a reproducible way at random locations and different sample sizes. Version 0.5.4 [util] added a new cross_validation utility module to cross-validate variograms with leave-one-out Kriging cross validations. Version 0.5.3 [MetricSpace] new class skgstat.MetricSpace.ProbabilisticMetricSpace that extends the metric space by a stochastic element to draw samples from the input data, instead of using the full dataset. Version 0.5.2 [interface] new interface function added: skgstat.Variogram.to_gs_krige. This interface will return a gstools.Krige instance from the fitted variogram. some typos were corrected some code refactored (mainly linting errors) Version 0.5.1 [plotting] the spatio-temporal 2D and 3D plots now label the axis correctly. [plotting] fixed swapped plotting axes for spatio-temporal plots