GeoStat-Framework/GSTools: Reverberating Red

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 kriging.

Installation

You can install GSTools with:

pip install -U gstools

For parallel compilation try (maybe install the standard version of gstools first, to get all dependencies):

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

Enhancements

• 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 (bsmurphy/PyKrige#124)
• the srf class now provides a plot and a vtk_export routine
• incompressible flow fields can now be generated #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
• tutorials on all important features of GSTools have been written for you guys #20
• a new interface to pyvista is provided to export fields to python vtk representation, which can be used for plotting, exploring and exporting fields #29

Changes

• the license was changed from GPL to LGPL in order to promote the use of this library #25
• 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
• the position vector of 1D fields does not have to be provided in a list-like object with length 1 a6f5be8

Bugfixes

• several minor bugfixes