Pykrige

Latest version: v1.7.2

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1.5.0

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*April 04, 2020*

**New features**

* support for GSTools covariance models (125)
* pre-build wheels for py35-py38 on Linux, Windows and MacOS (142)
* GridSerachCV from the compat module sets iid=False by default (if present in sklearn)
to be future prove (iid will be deprecated) (144)

**Changes**

* dropped py2* and py<3.5 support (142)
* installation now requires cython (142)
* codebase was formatted with black (144)
* internally use of scipys lapack/blas bindings (142)
* PyKrige is now part of the GeoStat-Framework

1.4.1

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*January 13, 2019*

**New features**

* Added method to obtain variogram model points. PR[94](https://github.com/GeoStat-Framework/PyKrige/pull/94) by [Daniel Mejía Raigosa](https://github.com/Daniel-M)

**Bug fixes**

* Fixed OrdinaryKriging readme example. PR[107](https://github.com/GeoStat-Framework/PyKrige/pull/107) by [Harry Matchette-Downes](https://github.com/harrymd)
* Fixed kriging matrix not being calculated correctly for geographic coordinates. PR[99](https://github.com/GeoStat-Framework/PyKrige/pull/99) by [Mike Rilee](https://github.com/michaelleerilee)

1.4.0

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*April 24, 2018*

**New features**

* Regression kriging algotithm. PR [27](https://github.com/GeoStat-Framework/PyKrige/pull/27) by [Sudipta Basaks](https://github.com/basaks).
* Support for spherical coordinates. PR [23](https://github.com/GeoStat-Framework/PyKrige/pull/23) by [Malte Ziebarth](https://github.com/mjziebarth)
* Kriging parameter tuning with scikit-learn. PR [24](https://github.com/GeoStat-Framework/PyKrige/pull/24) by [Sudipta Basaks](https://github.com/basaks).
* Variogram model parameters can be specified using a list or a dict. Allows for directly feeding in the partial sill rather than the full sill. PR [47](https://github.com/GeoStat-Framework/PyKrige/pull/47) by [Benjamin Murphy](https://github.com/bsmurphy).

**Enhancements**

* Improved memory usage in variogram calculations. PR [42](https://github.com/GeoStat-Framework/PyKrige/pull/42) by [Sudipta Basaks](https://github.com/basaks).
* Added benchmark scripts. PR [36](https://github.com/GeoStat-Framework/PyKrige/pull/36) by [Roman Yurchak](https://github.com/rth)
* Added an extensive example using the meusegrids dataset. PR [28](https://github.com/GeoStat-Framework/PyKrige/pull/28) by [kvanlombeek](https://github.com/kvanlombeek).

**Bug fixes**

* Statistics calculations in 3D kriging. PR [45](https://github.com/GeoStat-Framework/PyKrige/pull/45) by [Will Chang](https://github.com/whdc).
* Automatic variogram estimation robustified. PR [47](https://github.com/GeoStat-Framework/PyKrige/pull/47) by [Benjamin Murphy](https://github.com/bsmurphy).

1.3.1

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*December 10, 2016*

* More robust setup for building Cython extensions

1.3.0

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*October 23, 2015*

* Added support for Python 3.
* Updated the setup script to handle problems with trying to build the Cython extensions. If the appropriate compiler hasn't been installed on Windows, then the extensions won't work (see [this discussion of using Cython extensions on Windows] for how to deal with this problem). The setup script now attempts to build the Cython extensions and automatically falls back to pure Python if the build fails. **NOTE that the Cython extensions currently are not set up to work in Python 3** (see [discussion in issue 10]), so they are not built when installing with Python 3. This will be changed in the future.

* [closed issue 2]: https://github.com/GeoStat-Framework/PyKrige/issues/2
* [this discussion of using Cython extensions on Windows]: https://github.com/cython/cython/wiki/CythonExtensionsOnWindows
* [discussion in issue 10]: https://github.com/GeoStat-Framework/PyKrige/issues/10

1.2.0

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*August 1, 2015*

* Updated the execution portion of each class to streamline processing and reduce redundancy in the code.
* Integrated kriging with a moving window for two-dimensional ordinary kriging. Thanks to Roman Yurchak for this addition. This can be very useful for working with very large datasets, as it limits the size of the kriging matrix system. However, note that this approach can also produce unexpected oddities if the spatial covariance of the data does not decay quickly or if the window is too small. (See Kitanidis 1997 for a discussion of potential problems in kriging with a moving window; also see [closed issue 2] for a brief note about important considerations when kriging with a moving window.)
* Integrated a Cython backend for two-dimensional ordinary kriging. Again, thanks to Roman Yurchak for this addition. Note that currently the Cython backend is only implemented for two-dimensional ordinary kriging; it is not implemented in any of the other kriging classes. (I'll gladly accept any pull requests to extend the Cython backend to the other classes.)
* Implemented two new generic drift capabilities that should allow for use of arbitrary user-designed drifts. These generic drifts are referred to as 'specified' and 'functional' in the code. They are available for both two-dimensional and three-dimensional universal kriging (see below). With the 'specified' drift capability, the user specifies the values of the drift term at every data point and every point at which the kriging system is to be evaluated. With the 'functional' drift capability, the user provides callable function(s) of the two or three spatial coordinates that define the drift term(s). The functions must only take the spatial coordinates as arguments. An arbitrary number of 'specified' or 'functional' drift terms may be used. See `UniversalKriging.__doc__` or `UniversalKriging3D.__doc__` for more information.
* Made a few changes to how the drift terms are implemented when the problem is anisotropic. The regional linear drift is applied in the adjusted coordinate frame. For the point logarithmic drift, the point coordinates are transformed into the adjusted coordinate frame and the drift values are calculated in the transformed frame. The external scalar drift values are extracted using the original (i.e., unadjusted) coordinates. Any functions that are used with the 'functional' drift capability are evaluated in the adjusted coordinate frame. Specified drift values are not adjusted as they are taken to be for the exact points provided.
* Added support for three-dimensional universal kriging. The previous three-dimensional kriging class has been renamed OrdinaryKriging3D within module ok3d, and the new class is called UniversalKriging3D within module uk3d. See `UniversalKriging3D.__doc__` for usage information. A regional linear drift ('regional_linear') is the only code-internal drift that is currently supported, but the 'specified' and 'functional' generic drift capabilities are also implemented here (see above). The regional linear drift is applied in all three spatial dimensions.

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