v1.6.0 'Periodic Peach'

Release Notes

This release includes a new spatial random field generator called "Fourier" which can generate periodic random fields.

Installation

You can install GSTools with conda:

conda install -c conda-forge gstools

or with pip:

pip install gstools

Documentation

The documentation can be found at: https://gstools.readthedocs.io/

What's new?

Enhancements

• add a new spatial random field generator called Fourier (#302)
  • create periodic spatial random fields with Fourier, by setting the period length with the keyword periodic
  • add examples to showcase how to use the new generator

Bugfixes

• fix some Cython issues (#354)
  • update deprecated conditional compilation for OpenMP support
  • fix changing between Cython and Rust backends
  • improve documentation regarding parallelization
• fix deprecated license identifier, now Zenodo releases work again (#356)

Changes

• require gstools-core v1.0.0 at least (#361)

v1.5.2 'Nifty Neon'

Release Notes

This release brings better support for spatio-temporal models as well as some updates for models on geographic coordinates.

Installation

You can install GSTools with conda:

conda install -c conda-forge gstools

or with pip:

pip install gstools

Documentation

The documentation can be found at: https://gstools.readthedocs.io/

What's new?

Enhancements

• added global variable config.NUM_THREADS to select number of threads for parallel computation (#336)
• speed up sampling with emcee by setting vectorize=True in EnsembleSampler (#346)
• prepare numpy 2 support (#340)
  • at least numpy 2.0.0rc1 for building extensions (for Python 3.9 and above)
  • check multiple numpy and scipy versions in CI
  • fixed minimal versions for numpy
  • use np.asarray everywhere with np.atleast_(n)d
  • fix long/longlong integer issue in cython on windows by always using 64bit integers

Bugfixes

• build docs with latest sphinx version (#340)
• fixed zero division error in spectral density of Integral model (#347)
• minor pylint fixes for used-before-assignment issues (#350)

Changes

• require pyvista 0.40 at least (#340)
• require matplotlib 3.7 at least (#350)
• remove universal2 wheels for macos (we already provide separate intel and arm64 wheels) (#350)

v1.5.1 'Nifty Neon'

Release Notes

This release brings better support for spatio-temporal models as well as some updates for models on geographic coordinates.

Installation

You can install GSTools with conda:

conda install -c conda-forge gstools

or with pip:

pip install gstools

Documentation

The documentation can be found at: https://gstools.readthedocs.io/

What's new?

Enhancements

see #317

• added wheels for Python 3.12
• dropped support for Python 3.7 (EOL)
• linted Cython files with cython-lint
• use Cython 3 to build extensions

v1.5.0 'Nifty Neon'

Release Notes

This release brings better support for spatio-temporal models as well as some updates for models on geographic coordinates.

Installation

You can install GSTools with conda:

conda install -c conda-forge gstools

or with pip:

pip install gstools

Documentation

The documentation can be found at: https://gstools.readthedocs.io/

What's new?

Enhancements

• added temporal flag to CovModel to explicitly specify spatio-temporal models #308
  • rotation between spatial and temporal dimension will be ignored
  • added spatial_dim to CovModel to explicitly set spatial dimension for spatio-temporal models
    • if not using spatial_dim, the provided dim needs to include the possible temporal dimension
    • spatial_dim is always one less than field_dim for spatio-temporal models
  • also works with latlon=True to have a spatio-temporal model with geographic coordinates
  • all plotting routines respect this
  • the Field class now has a temporal attribute which forwards the model attribute
  • automatic variogram fitting in kriging classes for temporal=True and latlon=True will raise an error
• added geo_scale to CovModel to have a more consistent way to set the units of the model length scale for geographic coordinates #308
  • no need to use rescale for this anymore (was rather a hack)
  • added gs.KM_SCALE which is the same as gs.EARTH_RADIUS for kilometer scaling
  • added gs.DEGREE_SCALE for great circle distance in degrees
  • added gs.RADIAN_SCALE for great circle distance in radians (default and previous behavior)
  • yadrenko variogram respects this and assumes the great circle distances is given in the respective unit
  • vario_estimate also has geo_scale now to control the units of the bins
• vario_estimate now forwards additional kwargs to standard_bins (bin_no, max_dist) #308
• added low and high arguments to uniform transformation #310

Changes

• CovModels expect special arguments by keyword now #308
• always use f-strings internally #283
• removed verbose attribute from RandMeth classes #309
• all arguments for RandMeth classes key-word-only now except model #309
• rename "package" to "api" in doc structure #290

Bugfixes

• latex equations were not rendered correctly in docs #290

v1.4.1 'Sassy Sapphire'

Release Notes

This release brings Python 3.11 support, a new covariance model and provides some minor bugfixes.

Installation

You can install GSTools with conda:

conda install -c conda-forge gstools

or with pip:

pip install gstools

Documentation

The documentation can be found at: https://gstools.readthedocs.io/

What's new?

Enhancements

• new (Exponential-) Integral model added #243
• added wheels for Python 3.11 #272

Changes

• API documentation is polished and fully auto-generated now #271

Bugfixes

• fixed approximation of Matern.spectrum for big nu #243
• GSTools had wrong version when installed from git archive #272
• Field.plot: solve long-standing mpl slider bug #273

v1.4.0 'Sassy Sapphire'

Release Notes

This release drops Python 3.6 support, brings a new package structure, adds some usability improvements and provides some crucial bugfixes.

Installation

You can install GSTools with conda:

conda install -c conda-forge gstools

or with pip:

pip install gstools

Documentation

The documentation can be found at: https://gstools.readthedocs.io/

What's new?

Enhancements

• added Youtube tutorial to documentation #239
• better support for custom generators #250 #259
• add valid_value_types class variable to all field classes #250
• PyKrige: 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 setup.cfg content to pyproject.toml (PEP 621) #241
• move to src/ based package structure (better testing, building and structure) #241
• use extension-helpers for openmp support in setup.py #241
• increase minimal version of meshio to v5.1 #241

Bugfixes

• Pyvista v0.32 deprecation warning: use point_data instead of point_arrays #237
• remove deprecated scipy (v1.9) method pinv2 #247
• change float comparison in tests #248
• Cython: solve -Wsometimes-uninitialized warning #255

v1.3.5 'Pure Pink'

Release Notes

Bugfix release.

Installation

You can install GSTools with conda:

conda install -c conda-forge gstools

or with pip:

pip install gstools

Documentation

The documentation can be found at: https://gstools.readthedocs.io/

What's new?

Changes

• remove caps for dependencies #229
• build linux wheels with manylinux2014 for all versions (CIBW v2.3.1) #227

Bugfixes

• Field.mesh was not compatible with meshio v5.1+ #227

v1.3.4 'Pure Pink'

Release Notes

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.

Installation

You can install GSTools with conda:

conda install -c conda-forge gstools

or with pip:

pip install gstools

Documentation

The documentation can be found at: https://gstools.readthedocs.io/

What's new?

Enhancements

• add GSTools-Core as optional dependency #215
• provide wheels for Python 3.10 #211
• provide macOS wheels for Apple Silicon #211

Changes

• remove unnecessary dim argument in Cython code #216

v1.3.3 'Pure Pink'

Release Notes

This release comes with a new storage framework for all Field classes and a better transform sub-module.

Installation

You can install GSTools with conda:

conda install -c conda-forge gstools

or with pip:

pip install gstools

Documentation

The documentation can be found at: https://gstools.readthedocs.io/

What's new?

Enhancements

See: #197

• gstools.transform:
  • add keywords field, store, process and keep_mean to all transformations to control storage and respect normalizer
  • added apply_function transformation
  • added apply as wrapper for all transformations
  • added transform method to all Field (sub)classes as interface to transform.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 keyword
  • all 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 tuple
  • allow reusing present pos tuple
  • added pos, mesh_type, field_names, field_shape, all_fields properties
• CondSRF:
  • memory optimization by forwarding pos from underlying krige instance
  • only recalculate kriging field if pos tuple changed (optimized ensemble generation)
• performance improvement by using np.asarray instead of np.array where possible
• updated examples to use new features
• added incomplete lower gamma function inc_gamma_low (for TPLGaussian spectral density)
• filter nan values from cond_val array in all kriging routines #201

Bugfixes

• inc_gamma was defined wrong for integer s < 0

v1.3.2 'Pure Pink'

Release Notes

A bugfix release for GSTools v1.3.

Installation

You can install GSTools with conda:

conda install -c conda-forge gstools

or with pip:

pip install gstools

Documentation

The documentation can be found at: https://gstools.readthedocs.io/

What's new?

Bugfixes

• vario_estimate was altering the input field unter certain circumstances #180
• emcee v3.1 now requires nsteps in run_mcmc() to be integer (called in RNG.sample_ln_pdf) #184