Software Open Access
SciKit-Gstat is a scipy-styled geostatistical toolbox for variogram estimation. It includes two base classes
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!
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
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
Finally, SciKit-GStat has a
skgstat.data submodule, that can return sample data.
Changes since 0.5
MetricSpaceinstance used to calculate the distance matrix is now available as the
Variogram.metric_spaceis now read-only.
skgstat.datacontains sample random fields and methods for sampling these fields in a reproducible way at random locations and different sample sizes.
cross_validationutility module to cross-validate variograms with leave-one-out Kriging cross validations.
skgstat.MetricSpace.ProbabilisticMetricSpacethat extends the metric space by a stochastic element to draw samples from the input data, instead of using the full dataset.
skgstat.Variogram.to_gs_krige. This interface will return a
gstools.Krigeinstance from the fitted variogram.