GSTools - A geostatistical toolbox: random fields, variogram estimation, covariance models, kriging and much more
This release brings better support for spatio-temporal models as well as some updates for models on geographic coordinates.
You can install GSTools with conda:
conda install -c conda-forge gstools
or with pip:
pip install gstools
The documentation can be found at: https://gstools.readthedocs.io/
config.NUM_THREADS to select number of threads for parallel computation (#336)vectorize=True in EnsembleSampler (#346)np.asarray everywhere with np.atleast_(n)d
This release brings better support for spatio-temporal models as well as some updates for models on geographic coordinates.
You can install GSTools with conda:
conda install -c conda-forge gstools
or with pip:
pip install gstools
The documentation can be found at: https://gstools.readthedocs.io/
see #317
This release brings better support for spatio-temporal models as well as some updates for models on geographic coordinates.
You can install GSTools with conda:
conda install -c conda-forge gstools
or with pip:
pip install gstools
The documentation can be found at: https://gstools.readthedocs.io/
temporal flag to CovModel to explicitly specify spatio-temporal models #308
spatial_dim to CovModel to explicitly set spatial dimension for spatio-temporal models
spatial_dim, the provided dim needs to include the possible temporal dimensionspatial_dim is always one less than field_dim for spatio-temporal modelslatlon=True to have a spatio-temporal model with geographic coordinatesField class now has a temporal attribute which forwards the model attributetemporal=True and latlon=True will raise an errorgeo_scale to CovModel to have a more consistent way to set the units of the model length scale for geographic coordinates #308
rescale for this anymore (was rather a hack)gs.KM_SCALE which is the same as gs.EARTH_RADIUS for kilometer scalinggs.DEGREE_SCALE for great circle distance in degreesgs.RADIAN_SCALE for great circle distance in radians (default and previous behavior)vario_estimate also has geo_scale now to control the units of the binsvario_estimate now forwards additional kwargs to standard_bins (bin_no, max_dist) #308
low and high arguments to uniform transformation #310
CovModels expect special arguments by keyword now #308
verbose attribute from RandMeth classes #309
RandMeth classes key-word-only now except model #309
This release brings Python 3.11 support, a new covariance model and provides some minor bugfixes.
You can install GSTools with conda:
conda install -c conda-forge gstools
or with pip:
pip install gstools
The documentation can be found at: https://gstools.readthedocs.io/
This release drops Python 3.6 support, brings a new package structure, adds some usability improvements and provides some crucial bugfixes.
You can install GSTools with conda:
conda install -c conda-forge gstools
or with pip:
pip install gstools
The documentation can be found at: https://gstools.readthedocs.io/
valid_value_types class variable to all field classes #250
setup.cfg content to pyproject.toml (PEP 621) #241
src/ based package structure (better testing, building and structure) #241
setup.py #241
Bugfix release.
You can install GSTools with conda:
conda install -c conda-forge gstools
or with pip:
pip install gstools
The documentation can be found at: https://gstools.readthedocs.io/
This release comes with wheels for Python 3.10 and a new optional package with re-implementations of the Cython routines in Rust called GSTools-Core.
You can install the rust package as an option with
pip install gstools[rust]
Or simply by
pip install gstools-core
If the package is present it will be used instead of the Cython routines.
You can install GSTools with conda:
conda install -c conda-forge gstools
or with pip:
pip install gstools
The documentation can be found at: https://gstools.readthedocs.io/
dim argument in Cython code #216
This release comes with a new storage framework for all Field classes and a better transform sub-module.
You can install GSTools with conda:
conda install -c conda-forge gstools
or with pip:
pip install gstools
The documentation can be found at: https://gstools.readthedocs.io/
See: #197
gstools.transform:
field, store, process and keep_mean to all transformations to control storage and respect normalizer
apply_function transformationapply as wrapper for all transformationstransform method to all Field (sub)classes as interface to transform.apply
normalizer submoduleField:
store keywordpost_process keyword (apply mean, normalizer, trend)Field["field"])set_pos method to set position tuplepos tuplepos, mesh_type, field_names, field_shape, all_fields propertiesCondSRF:
pos from underlying krige instancepos tuple changed (optimized ensemble generation)np.asarray instead of np.array where possibleinc_gamma_low (for TPLGaussian spectral density)nan values from cond_val array in all kriging routines #201
inc_gamma was defined wrong for integer s < 0
A bugfix release for GSTools v1.3.
You can install GSTools with conda:
conda install -c conda-forge gstools
or with pip:
pip install gstools
The documentation can be found at: https://gstools.readthedocs.io/
A bugfix release for GSTools v1.3.
You can install GSTools with conda:
conda install -c conda-forge gstools
or with pip:
pip install gstools
The documentation can be found at: https://gstools.readthedocs.io/
oldest-supported-numpy to build cython extensions #165