Changelog
All notable changes to GSTools will be documented in this file.
1.4.1 - Sassy Sapphire - 2022-11
Enhancements
Changes
API documentation is polished and fully auto-generated now #271
Bugfixes
1.4.0 - Sassy Sapphire - 2022-08
Enhancements
added Youtube tutorial to documentation #239
add
valid_value_types
class variable to all field classes #250PyKrige: fix passed variogram in case of latlon models #254
add bounds checks for optional arguments of CovModel when resetting by class attribute #255
minor coverage improvements #255
documentation: readability improvements #257
Changes
drop Python 3.6 support (setuptools>60 needs py>3.7) #241
move to
src/
based package structure (better testing, building and structure) #241use extension-helpers for openmp support in
setup.py
#241increase minimal version of meshio to v5.1 #241
Bugfixes
1.3.5 - Pure Pink - 2022-01
Changes
remove caps for dependencies #229
build linux wheels with manylinux2014 for all versions (CIBW v2.3.1) #227
Bugfixes
1.3.4 - Pure Pink - 2021-11
Enhancements
Changes
remove unnecessary
dim
argument in Cython code #216
1.3.3 - Pure Pink - 2021-08
Enhancements
See: #197
gstools.transform
:add keywords
field
,store
,process
andkeep_mean
to all transformations to control storage and respectnormalizer
added
apply_function
transformationadded
apply
as wrapper for all transformationsadded
transform
method to allField
(sub)classes as interface totransform.apply
added checks for normal fields to work smoothly with recently added
normalizer
submodule
Field
:allow naming fields when generating and control storage with
store
keywordall subclasses now have the
post_process
keyword (apply mean, normalizer, trend)added subscription to access fields by name (
Field["field"]
)added
set_pos
method to set position tupleallow reusing present
pos
tupleadded
pos
,mesh_type
,field_names
,field_shape
,all_fields
properties
CondSRF
:memory optimization by forwarding
pos
from underlyingkrige
instanceonly recalculate kriging field if
pos
tuple changed (optimized ensemble generation)
performance improvement by using
np.asarray
instead ofnp.array
where possibleupdated examples to use new features
added incomplete lower gamma function
inc_gamma_low
(for TPLGaussian spectral density)filter
nan
values fromcond_val
array in all kriging routines #201
Bugfixes
inc_gamma
was defined wrong for integers < 0
1.3.2 - Pure Pink - 2021-07
Bugfixes
1.3.1 - Pure Pink - 2021-06
Enhancements
Bugfixes
use
oldest-supported-numpy
to build cython extensions #165
1.3.0 - Pure Pink - 2021-04
Topics
Geographical Coordinates Support (#113)
added boolean init parameter
latlon
to indicate a geographic model. When given, spatial dimension is fixed todim=3
,anis
andangles
will be ignored, since anisotropy is not well-defined on a sphere.add property
field_dim
to indicate the dimension of the resulting field. Will be 2 iflatlon=True
added yadrenko variogram, covariance and correlation method, since the geographic models are derived from standard models in 3D by plugging in the chordal distance of two points on a sphere derived from there great-circle distance
zeta
:vario_yadrenko
: given byvariogram(2 * np.sin(zeta / 2))
cov_yadrenko
: given bycovariance(2 * np.sin(zeta / 2))
cor_yadrenko
: given bycorrelation(2 * np.sin(zeta / 2))
added plotting routines for yadrenko methods described above
the
isometrize
andanisometrize
methods will convertlatlon
tuples (given in degree) to points on the unit-sphere in 3D and vice versarepresentation of geographical models don’t display the
dim
,anis
andangles
parameters, butlatlon=True
fit_variogram
will expect an estimated variogram with great-circle distances given in radiansVariogram estimation
latlon
switch implemented inestimate_vario
routinewill return a variogram estimated by the great-circle distance (haversine formula) given in radians
Field
added plotting routines for latlon fields
no vector fields possible on latlon fields
corretly handle pos tuple for latlon fields
Krige Unification (#97)
Swiss Army Knife for kriging: The
Krige
class now provides everything in one place“Kriging the mean” is now possible with the switch
only_mean
in the call routineSimple
/Ordinary
/Universal
/ExtDrift
/Detrended
are only shortcuts toKrige
with limited input parameter listWe now use the
covariance
function to build up the kriging matrix (instead of variogram)An
unbiased
switch was added to enable simple kriging (where the unbiased condition is not given)An
exact
switch was added to allow smother results, if anugget
is present in the modelAn
cond_err
parameter was added, where measurement error variances can be given for each conditional pointpseudo-inverse matrix is now used to solve the kriging system (can be disabled by the new switch
pseudo_inv
), this is equal to solving the system with least-squares and prevents numerical errorsadded options
fit_normalizer
andfit_variogram
to automatically fit normalizer and variogram to given data
Directional Variograms and Auto-binning (#87, #106, #131)
new routine name
vario_estimate
instead ofvario_estimate_unstructured
(old kept for legacy code) for simplicitynew routine name
vario_estimate_axis
instead ofvario_estimate_structured
(old kept for legacy code) for simplicityvario_estimate
added simple automatic binning routine to determine bins from given data (one third of box diameter as max bin distance, sturges rule for number of bins)
allow to pass multiple fields for joint variogram estimation (e.g. for daily precipitation) on same mesh
no_data
option added to allow missing valuesmasked fields
user can now pass a masked array (or a list of masked arrays) to deselect data points.
in addition, a
mask
keyword was added to provide an external mask
directional variograms
diretional variograms can now be estimated
either provide a list of direction vectors or angles for directions (spherical coordinates)
can be controlled by given angle tolerance and (optional) bandwidth
prepared for nD
structured fields (pos tuple describes axes) can now be passed to estimate an isotropic or directional variogram
distance calculation in cython routines in now independent of dimension
vario_estimate_axis
estimation along array axis now possible in arbitrary dimensions
no_data
option added to allow missing values (sovles #83)axis can be given by name (
"x"
,"y"
,"z"
) or axis number (0
,1
,2
,3
, …)
Better Variogram fitting (#78, #145)
fixing sill possible now
loss
is now selectable for smoother handling of outliersr2 score can now be returned to get an impression of the goodness of fitting
weights can be passed
instead of deselecting parameters, one can also give fix values for each parameter
default init guess for
len_scale
is now mean of given bin-centersdefault init guess for
var
andnugget
is now mean of given variogram values
CovModel update (#109, #122, #157)
add new
rescale
argument and attribute to theCovModel
class to be able to rescale thelen_scale
(usefull for unit conversion or rescalinglen_scale
to coincide with theintegral_scale
like it’s the case with the Gaussian model) See: #90, GeoStat-Framework/PyKrige#119added new
len_rescaled
attribute to theCovModel
class, which is the rescaledlen_scale
:len_rescaled = len_scale / rescale
new method
default_rescale
to provide default rescale factor (can be overridden)remove
doctest
callsdocstring updates in CovModel and derived models
updated all models to use the
cor
routine and make use of therescale
argument (See: #90)TPL models got a separate base class to not repeat code
added new models (See: #88):
HyperSpherical
: (Replaces the oldIntersection
model) Derived from the intersection of hyper-spheres in arbitrary dimensions. Coincides with the linear model in 1D, the circular model in 2D and the classical spherical model in 3DSuperSpherical
: like the HyperSpherical, but the shape parameter derived from dimension can be set by the user. Coincides with the HyperSpherical model by defaultJBessel
: a hole model valid in all dimensions. The shape parameter controls the dimension it was derived from. Fornu=0.5
this model coincides with the well knownwave
hole model.TPLSimple
: a simple truncated power law controlled by a shape parameternu
. Coincides with the truncated linear model fornu=1
Cubic
: to be compatible with scikit-gstat in the future
all arguments are now stored as float internally (#157)
string representation of the
CovModel
class is now using a float precision (CovModel._prec=3
) to truncate longish outputstring representation of the
CovModel
class now only showsanis
andangles
if model is anisotropic resp. rotateddimension validity check: raise a warning, if given model is not valid in the desired dimension (See: #86)
Normalizer, Trend and Mean (#124)
new
normalize
submodule containing power-transforms for data to gain normalityBase-Class:
Normalizer
providing basic functionality including maximum likelihood fittingadded:
LogNormal
,BoxCox
,BoxCoxShift
,YeoJohnson
,Modulus
andManly
normalizer, trend and mean can be passed to SRF, Krige and variogram estimation routines
A trend can be a callable function, that represents a trend in input data. For example a linear decrease of temperature with height.
The normalizer will be applied after the data was detrended, i.e. the trend was substracted from the data, in order to gain normality.
The mean is now interpreted as the mean of the normalized data. The user could also provide a callable mean, but it is mostly meant to be constant.
Arbitrary dimensions (#112)
allow arbitrary dimensions in all routines (CovModel, Krige, SRF, variogram)
anisotropy and rotation following a generalization of tait-bryan angles
CovModel provides
isometrize
andanisometrize
routines to convert points
New Class for Conditioned Random Fields (#130)
THIS BREAKS BACKWARD COMPATIBILITY
CondSRF
replaces the conditioning feature of the SRF class, which was cumbersome and limited to Ordinary and Simple krigingCondSRF
behaves similar to theSRF
class, but instead of a covariance model, it takes a kriging class as input. With this kriging class, all conditioning related settings are defined.
Enhancements
Python 3.9 Support #107
add routines to format struct. pos tuple by given
dim
orshape
add routine to format struct. pos tuple by given
shape
(variogram helper)remove
field.tools
subpackagesupport
meshio>=4.0
and add as dependencyPyVista mesh support #59
added
EARTH_RADIUS
as constant providing earths radius in km (can be used to rescale models)add routines
latlon2pos
andpos2latlon
to convert lat-lon coordinates to points on unit-sphere and vice versaa lot of new examples and tutorials
RandMeth
class got a switch to select the sampling strategyplotter for n-D fields added #141
antialias for contour plots of 2D fields #141
building from source is now configured with
pyproject.toml
to care about build dependencies, see #154
Changes
drop support for Python 3.5 #146
added a finit limit for shape-parameters in some CovModels #147
drop usage of
pos2xyz
andxyz2pos
remove structured option from generators (structured pos need to be converted first)
explicitly assert dim=2,3 when generating vector fields
simplify
pre_pos
routine to save pos tuple and reformat it an unstructured tuplesimplify field shaping
simplify plotting routines
only the
"unstructured"
keyword is recognized everywhere, everything else is interpreted as"structured"
(e.g."rectilinear"
)use GitHub-Actions instead of TravisCI
parallel build now controlled by env-var
GSTOOLS_BUILD_PARALLEL=1
, see #154install extra target for
[dev]
dropped, can be reproduced bypip install gstools[test, doc]
, see #154
Bugfixes
1.2.1 - Volatile Violet - 2020-04-14
Bugfixes
ModuleNotFoundError
is not present in py35Fixing Cressie-Bug #76
Adding analytical formula for integral scales of rational and stable model
remove prange from IncomprRandMeth summators to prevent errors on Win and macOS
1.2.0 - Volatile Violet - 2020-03-20
Enhancements
different variogram estimator functions can now be used #51
the TPLGaussian and TPLExponential now have analytical spectra #67
added property
is_isotropic
to CovModel #67reworked the whole krige sub-module to provide multiple kriging methods #67
Simple
Ordinary
Universal
External Drift Kriging
Detrended Kriging
a new transformation function for discrete fields has been added #70
reworked tutorial section in the documentation #63
pyvista interface #29
Changes
Python versions 2.7 and 3.4 are no longer supported #40 #43
CovModel: in 3D the input of anisotropy is now treated slightly different: #67
single given anisotropy value [e] is converted to [1, e] (it was [e, e] before)
two given length-scales [l_1, l_2] are converted to [l_1, l_2, l_2] (it was [l_1, l_2, l_1] before)
Bugfixes
a race condition in the structured variogram estimation has been fixed #51
1.1.1 - Reverberating Red - 2019-11-08
Enhancements
added a changelog. See: commit fbea883
Changes
deprecation warnings are now printed if Python versions 2.7 or 3.4 are used #40 #41
Bugfixes
define spectral_density instead of spectrum in covariance models since Cov-base derives spectrum. See: commit 00f2747
better boundaries for CovModel parameters. See: https://github.com/GeoStat-Framework/GSTools/issues/37
1.1.0 - Reverberating Red - 2019-10-01
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 classinterface to pykrige to use the gstools CovModel with the pykrige routines (https://github.com/bsmurphy/PyKrige/issues/124)
the srf class now provides a
plot
and avtk_export
routineincompressible 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, see: commit f4a3439
the srf and kriging classes now store the last
pos
,mesh_type
andfield
values to keep them accessible, see: commit 29f7f1btutorials 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 #13drop support of python implementations of the variogram estimators #18
the
variogram_normed
method was removed from theCovModel
class due to redundance commit 25b1647the position vector of 1D fields does not have to be provided in a list-like object with length 1 commit a6f5be8
Bugfixes
several minor bugfixes
1.0.1 - Bouncy Blue - 2019-01-18
Bugfixes
fixed Numpy and Cython version during build process
1.0.0 - Bouncy Blue - 2019-01-16
Enhancements
added a new covariance class, which allows the easy usage of arbitrary covariance models
added many predefined covariance models, including truncated power law models
added tutorials and examples, showing and explaining the main features of GSTools
variogram models can be fitted to data
prebuilt binaries for many Linux distributions, Mac OS and Windows, making the installation, especially of the Cython code, much easier
the generated fields can now easily be exported to vtk files
variance scaling is supported for coarser grids
added pure Python versions of the variogram estimators, in case somebody has problems compiling Cython code
the documentation is now a lot cleaner and easier to use
the code is a lot cleaner and more consistent now
unit tests are now automatically tested when new code is pushed
test coverage of code is shown
GeoStat Framework now has a website, visit us: https://geostat-framework.github.io/
Changes
release is not downwards compatible with release v0.4.0
SRF creation has been adapted for the CovModel
a tuple
pos
is now used instead ofx
,y
, andz
for the axesrenamed
estimate_unstructured
andestimate_structured
tovario_estimate_unstructured
andvario_estimate_structured
for less ambiguity
Bugfixes
several minor bugfixes
0.4.0 - Glorious Green - 2018-07-17
Bugfixes
import of cython functions put into a try-block
0.3.6 - Original Orange - 2018-07-17
First release of GSTools.