pyKriging#
pyKriging is a Python interface to a high-performance Fortran kriging and Sequential Gaussian Simulation engine, parallelised with OpenMP.
Get from installation to your first kriging map in five minutes.
Full reference for every class, method, and convenience function.
Task-oriented walkthroughs for ordinary kriging, co-kriging, SGSIM, and more.
Coordinate shapes, dtype expectations, and result array layouts.
What pyKriging does#
Capability |
Notes |
|---|---|
Ordinary and simple kriging |
Point and block support |
Co-kriging |
Multiple variables, Linear Model of Coregionalisation |
Universal kriging / KED |
External drift variables |
Sequential Gaussian Simulation |
Reproducible random paths, multi-realisation |
Space-time kriging |
Sum-metric and product-sum ST covariance models |
Spatially Varying Anisotropy |
Per-block variogram (SVA mode) |
Cross-validation |
Leave-one-out |
Kriging weight reuse |
Store and replay weights for fast value updates |
OpenMP parallelism |
Thread count controllable per |
Why pyKriging?#
pyKriging is designed for workflows that need Python usability with a compiled-Fortran backend. Its Fortran core handles large grids, SGSIM realisation paths, space-time systems, and OpenMP scheduling in a single library. The Python layer is a thin ctypes wrapper — no heavy dependencies, no JIT compilation step.