Version 0.5
Description
SciKit-Gstat is a scipy-styled analysis module for geostatistics. It includes two base classes Variogram and 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.
Version 0.5 brings two major improvements: Instead of passing a numpy.ndarray, you can now use the new class skgstat.MetricSpace, which can pre-calculate distances in case they are used all over the place. Secondly, the new interface functions Variogram.to_gstools and Variogram.to_empirical can be used to export a Variogram to gstools and use their field generation, kriging and all the other fancy stuff there.
Documentation
- Full Documentation https://mmaelicke.github.io/scikit-gstat
- User Guide https://mmaelicke.github.io/scikit-gstat/userguide/userguide.html
- Tutorials https://mmaelicke.github.io/scikit-gstat/tutorials/tutorials.html
Changes since 0.4
- [MetricSpace] A new class :class:
MetricSpace <skgstat.MetricSpace>was introduced. This class can be passed
to any class that accepted coordinates so far. This wrapper can be used to pre-calculate large distance
matrices and pass it to a lot of Variograms. - [MetricSpacePair] A new class :class:
MetricSpacePair <skgstat.MetricSpacePair>was introduced.
This is a pair of two :class:MetricSpaces <skgstat.MetricSpace>and pre-calculates all distances between
the two spaces. This is i.e. used in Kriging to pre-calcualte all distance between the input coordinates and
the interpolation grid only once.
Version 0.4.4
- [models] the changes to :func:
matern <skgstat.models.matern>introduced in0.3.2are reversed.
The Matérn model does not adapt the smoothness scaling to effective range anymore, as the behavior was too
inconsistent. - [interface] minor bugfix of circular import in
variogram_estimatorinterface - [models] :func:
matern(0, ...) <skgstat.models.matern>now returns the nugget instead ofnumpy.NaN - [models] :func:
stable(0, ...) <skgstat.models.stable>now returns the nugget instead ofnumpy.NaNor a
ZeroDivisionError.
Version 0.4.3
- [Variogram] :func:
dim <skgstat.Variogram.dim>now returns the spatial dimensionality of the input data. - [Variogram] fixed a numpy depreaction warning in
_calc_distances
Version 0.4.2
- [Variogram] :func:
bins <skgstat.Variogram.bins>now cases manual setted bin edges automatically
to a :func:numpy.array. - [Variogram] :func:
get_empirical <skgstat.Variogram.get_empirical>returns the empirical variogram.
That is a tuple of the current :func:bins <skgstat.Variogram.bins>and
:func:experimental <skgstat.Variogram.experimental>arrays, with the option to move the bin to the
lag classes centers.
Version 0.4.1
- [Variogram] moved the bin function setting into a wrapper instance method, which was an anonymous lambda before.
This makes the Variogram serializable again. - [Variogram] a list of pylint errors were solved. Still enough left.
- [binning] added
'stable_entropy'option that will optimize the lag class edges to be of comparable Shannon Entropy.