Release Notes

Woah! GSTools went parallel. And at the same time the humongous memory consumption of the field generation became very modest.

The second big news is that GSTools can now finally generate conditioned random fields and provides krging.

Installation

Since this is a pre-release you have to install it with:

pip install --pre -U gstools

For parallel compilation try:

pip install --pre --global-option="--openmp" -U gstools

by using Cython for all the heavy computations, we could achieve quite some speed ups and reduce the memory consumption significantly (#16)
parallel computation in Cython is now supported with the help of OpenMP and the performance increase is nearly linear with increasing cores (#16)
new submodule krige providing simple (known mean) and ordinary (estimated mean) kriging working analogous to the srf class
interface to pykrige to use the gstools CovModel with the pykrige routines (GeoStat-Framework/PyKrige#124)
the srf class now provides a plot and a vtk_export routine
in-compressible flow fields are now creatable (#14)
new submodule providing several field transformations like: Zinn&Harvey, log-normal, bimodal, ... (#13)
Python 3.4 and 3.7 wheel support (#19)
field can now be generated directly on meshes from meshio and ogs5py (f4a3439)
the srf and kriging classes now store the last pos, mesh_type and field values to keep them accessible (29f7f1b)

the rotation angles are now interpreted in positive direction (counter clock wise)
the force_moments keyword was removed from the SRF call method, it is now in provided as a field transformation (#13)
drop support of python implementations of the variogram estimators (#18)
the variogram_normed method was removed from the CovModel class due to redundance (25b1647)