Tutorials

Field transformations

The generated fields of gstools are ordinary Gaussian random fields. In application there are several transformations to describe real world problems in an appropriate manner.

GStools provides a submodule gstools.transform with a range of common transformations:

• binary
• discrete
• boxcox
• zinnharvey
• normal_force_moments
• normal_to_lognormal
• normal_to_uniform
• normal_to_arcsin
• normal_to_uquad
• apply_function

All the transformations take a field class, that holds a generated field, as input and will manipulate this field inplace or store it with a given name.

Simply apply a transformation to a field class:

import gstools as gs
...
srf = gs.SRF(model)
srf(...)
gs.transform.normal_to_lognormal(srf)

Or use the provided wrapper in all Field classes:

import gstools as gs
...
srf = gs.SRF(model)
srf(...)
srf.transform("lognormal")