From 32dbbc9a3429a04689986e245f99ac86c68f30d3 Mon Sep 17 00:00:00 2001 From: CoprDistGit Date: Tue, 11 Apr 2023 15:13:35 +0000 Subject: automatic import of python-pykrige --- .gitignore | 1 + python-pykrige.spec | 448 ++++++++++++++++++++++++++++++++++++++++++++++++++++ sources | 1 + 3 files changed, 450 insertions(+) create mode 100644 python-pykrige.spec create mode 100644 sources diff --git a/.gitignore b/.gitignore index e69de29..4ef4d45 100644 --- a/.gitignore +++ b/.gitignore @@ -0,0 +1 @@ +/PyKrige-1.7.0.tar.gz diff --git a/python-pykrige.spec b/python-pykrige.spec new file mode 100644 index 0000000..301e4f2 --- /dev/null +++ b/python-pykrige.spec @@ -0,0 +1,448 @@ +%global _empty_manifest_terminate_build 0 +Name: python-PyKrige +Version: 1.7.0 +Release: 1 +Summary: Kriging Toolkit for Python. +License: BSD-3-Clause +URL: https://github.com/GeoStat-Framework/PyKrige +Source0: https://mirrors.nju.edu.cn/pypi/web/packages/2c/d4/712e81c60423a036442acd11f30590c101b579de5e3531633b93b84b0112/PyKrige-1.7.0.tar.gz + +Requires: python3-numpy +Requires: python3-scipy +Requires: python3-gstools +Requires: python3-scipy +Requires: python3-pillow +Requires: python3-scikit-learn +Requires: python3-m2r2 +Requires: python3-matplotlib +Requires: python3-numpydoc +Requires: python3-sphinx +Requires: python3-sphinx-gallery +Requires: python3-sphinx-rtd-theme +Requires: python3-matplotlib +Requires: python3-scikit-learn +Requires: python3-pytest-cov +Requires: python3-scikit-learn +Requires: python3-gstools + +%description +# PyKrige + +[![DOI](https://zenodo.org/badge/DOI/10.5281/zenodo.3738604.svg)](https://doi.org/10.5281/zenodo.3738604) +[![PyPI version](https://badge.fury.io/py/PyKrige.svg)](https://badge.fury.io/py/PyKrige) +[![Conda Version](https://img.shields.io/conda/vn/conda-forge/pykrige.svg)](https://anaconda.org/conda-forge/pykrige) +[![Build Status](https://github.com/GeoStat-Framework/PyKrige/workflows/Continuous%20Integration/badge.svg?branch=main)](https://github.com/GeoStat-Framework/PyKrige/actions) +[![Coverage Status](https://coveralls.io/repos/github/GeoStat-Framework/PyKrige/badge.svg?branch=main)](https://coveralls.io/github/GeoStat-Framework/PyKrige?branch=main) +[![Documentation Status](https://readthedocs.org/projects/pykrige/badge/?version=stable)](http://pykrige.readthedocs.io/en/stable/?badge=stable) +[![Code style: black](https://img.shields.io/badge/code%20style-black-000000.svg)](https://github.com/psf/black) + + +

+PyKrige-LOGO +

+ +Kriging Toolkit for Python. + +## Purpose + +The code supports 2D and 3D ordinary and universal kriging. Standard +variogram models (linear, power, spherical, gaussian, exponential) are +built in, but custom variogram models can also be used. The 2D universal +kriging code currently supports regional-linear, point-logarithmic, and +external drift terms, while the 3D universal kriging code supports a +regional-linear drift term in all three spatial dimensions. Both +universal kriging classes also support generic 'specified' and +'functional' drift capabilities. With the 'specified' drift capability, +the user may manually specify the values of the drift(s) at each data +point and all grid points. With the 'functional' drift capability, the +user may provide callable function(s) of the spatial coordinates that +define the drift(s). The package includes a module that contains +functions that should be useful in working with ASCII grid files (`\*.asc`). + +See the documentation at for more +details and examples. + +## Installation + +PyKrige requires Python 3.5+ as well as numpy, scipy. It can be +installed from PyPi with, + +``` bash +pip install pykrige +``` + +scikit-learn is an optional dependency needed for parameter tuning and +regression kriging. matplotlib is an optional dependency needed for +plotting. + +If you use conda, PyKrige can be installed from the conda-forge channel with, + +``` bash +conda install -c conda-forge pykrige +``` + +## Features + +### Kriging algorithms + +- `OrdinaryKriging`: 2D ordinary kriging with estimated mean +- `UniversalKriging`: 2D universal kriging providing drift terms +- `OrdinaryKriging3D`: 3D ordinary kriging +- `UniversalKriging3D`: 3D universal kriging +- `RegressionKriging`: An implementation of Regression-Kriging +- `ClassificationKriging`: An implementation of Simplicial Indicator + Kriging + +### Wrappers + +- `rk.Krige`: A scikit-learn wrapper class for Ordinary and Universal + Kriging + +### Tools + +- `kriging_tools.write_asc_grid`: Writes gridded data to ASCII grid file (`\*.asc`) +- `kriging_tools.read_asc_grid`: Reads ASCII grid file (`\*.asc`) +- `kriging_tools.write_zmap_grid`: Writes gridded data to zmap file (`\*.zmap`) +- `kriging_tools.read_zmap_grid`: Reads zmap file (`\*.zmap`) + +### Kriging Parameters Tuning + +A scikit-learn compatible API for parameter tuning by cross-validation +is exposed in +[sklearn.model\_selection.GridSearchCV](http://scikit-learn.org/stable/modules/generated/sklearn.model_selection.GridSearchCV.html). +See the [Krige +CV](http://pykrige.readthedocs.io/en/latest/examples/08_krige_cv.html#sphx-glr-examples-08-krige-cv-py) +example for a more practical illustration. + +### Regression Kriging + +[Regression kriging](https://en.wikipedia.org/wiki/Regression-Kriging) +can be performed with +[pykrige.rk.RegressionKriging](http://pykrige.readthedocs.io/en/latest/examples/07_regression_kriging2d.html). +This class takes as parameters a scikit-learn regression model, and +details of either the `OrdinaryKriging` or the `UniversalKriging` +class, and performs a correction step on the ML regression prediction. + +A demonstration of the regression kriging is provided in the +[corresponding +example](http://pykrige.readthedocs.io/en/latest/examples/07_regression_kriging2d.html#sphx-glr-examples-07-regression-kriging2d-py). + +### Classification Kriging + +[Simplifical Indicator +kriging](https://www.sciencedirect.com/science/article/abs/pii/S1002070508600254) +can be performed with +[pykrige.ck.ClassificationKriging](http://pykrige.readthedocs.io/en/latest/examples/10_classification_kriging2d.html). +This class takes as parameters a scikit-learn classification model, and +details of either the `OrdinaryKriging` or the `UniversalKriging` class, +and performs a correction step on the ML classification prediction. + +A demonstration of the classification kriging is provided in the +[corresponding +example](http://pykrige.readthedocs.io/en/latest/examples/10_classification_kriging2d.html#sphx-glr-examples-10-classification-kriging2d-py). + +## License + +PyKrige uses the BSD 3-Clause License. + + +%package -n python3-PyKrige +Summary: Kriging Toolkit for Python. +Provides: python-PyKrige +BuildRequires: python3-devel +BuildRequires: python3-setuptools +BuildRequires: python3-pip +BuildRequires: python3-cffi +BuildRequires: gcc +BuildRequires: gdb +%description -n python3-PyKrige +# PyKrige + +[![DOI](https://zenodo.org/badge/DOI/10.5281/zenodo.3738604.svg)](https://doi.org/10.5281/zenodo.3738604) +[![PyPI version](https://badge.fury.io/py/PyKrige.svg)](https://badge.fury.io/py/PyKrige) +[![Conda Version](https://img.shields.io/conda/vn/conda-forge/pykrige.svg)](https://anaconda.org/conda-forge/pykrige) +[![Build Status](https://github.com/GeoStat-Framework/PyKrige/workflows/Continuous%20Integration/badge.svg?branch=main)](https://github.com/GeoStat-Framework/PyKrige/actions) +[![Coverage Status](https://coveralls.io/repos/github/GeoStat-Framework/PyKrige/badge.svg?branch=main)](https://coveralls.io/github/GeoStat-Framework/PyKrige?branch=main) +[![Documentation Status](https://readthedocs.org/projects/pykrige/badge/?version=stable)](http://pykrige.readthedocs.io/en/stable/?badge=stable) +[![Code style: black](https://img.shields.io/badge/code%20style-black-000000.svg)](https://github.com/psf/black) + + +

+PyKrige-LOGO +

+ +Kriging Toolkit for Python. + +## Purpose + +The code supports 2D and 3D ordinary and universal kriging. Standard +variogram models (linear, power, spherical, gaussian, exponential) are +built in, but custom variogram models can also be used. The 2D universal +kriging code currently supports regional-linear, point-logarithmic, and +external drift terms, while the 3D universal kriging code supports a +regional-linear drift term in all three spatial dimensions. Both +universal kriging classes also support generic 'specified' and +'functional' drift capabilities. With the 'specified' drift capability, +the user may manually specify the values of the drift(s) at each data +point and all grid points. With the 'functional' drift capability, the +user may provide callable function(s) of the spatial coordinates that +define the drift(s). The package includes a module that contains +functions that should be useful in working with ASCII grid files (`\*.asc`). + +See the documentation at for more +details and examples. + +## Installation + +PyKrige requires Python 3.5+ as well as numpy, scipy. It can be +installed from PyPi with, + +``` bash +pip install pykrige +``` + +scikit-learn is an optional dependency needed for parameter tuning and +regression kriging. matplotlib is an optional dependency needed for +plotting. + +If you use conda, PyKrige can be installed from the conda-forge channel with, + +``` bash +conda install -c conda-forge pykrige +``` + +## Features + +### Kriging algorithms + +- `OrdinaryKriging`: 2D ordinary kriging with estimated mean +- `UniversalKriging`: 2D universal kriging providing drift terms +- `OrdinaryKriging3D`: 3D ordinary kriging +- `UniversalKriging3D`: 3D universal kriging +- `RegressionKriging`: An implementation of Regression-Kriging +- `ClassificationKriging`: An implementation of Simplicial Indicator + Kriging + +### Wrappers + +- `rk.Krige`: A scikit-learn wrapper class for Ordinary and Universal + Kriging + +### Tools + +- `kriging_tools.write_asc_grid`: Writes gridded data to ASCII grid file (`\*.asc`) +- `kriging_tools.read_asc_grid`: Reads ASCII grid file (`\*.asc`) +- `kriging_tools.write_zmap_grid`: Writes gridded data to zmap file (`\*.zmap`) +- `kriging_tools.read_zmap_grid`: Reads zmap file (`\*.zmap`) + +### Kriging Parameters Tuning + +A scikit-learn compatible API for parameter tuning by cross-validation +is exposed in +[sklearn.model\_selection.GridSearchCV](http://scikit-learn.org/stable/modules/generated/sklearn.model_selection.GridSearchCV.html). +See the [Krige +CV](http://pykrige.readthedocs.io/en/latest/examples/08_krige_cv.html#sphx-glr-examples-08-krige-cv-py) +example for a more practical illustration. + +### Regression Kriging + +[Regression kriging](https://en.wikipedia.org/wiki/Regression-Kriging) +can be performed with +[pykrige.rk.RegressionKriging](http://pykrige.readthedocs.io/en/latest/examples/07_regression_kriging2d.html). +This class takes as parameters a scikit-learn regression model, and +details of either the `OrdinaryKriging` or the `UniversalKriging` +class, and performs a correction step on the ML regression prediction. + +A demonstration of the regression kriging is provided in the +[corresponding +example](http://pykrige.readthedocs.io/en/latest/examples/07_regression_kriging2d.html#sphx-glr-examples-07-regression-kriging2d-py). + +### Classification Kriging + +[Simplifical Indicator +kriging](https://www.sciencedirect.com/science/article/abs/pii/S1002070508600254) +can be performed with +[pykrige.ck.ClassificationKriging](http://pykrige.readthedocs.io/en/latest/examples/10_classification_kriging2d.html). +This class takes as parameters a scikit-learn classification model, and +details of either the `OrdinaryKriging` or the `UniversalKriging` class, +and performs a correction step on the ML classification prediction. + +A demonstration of the classification kriging is provided in the +[corresponding +example](http://pykrige.readthedocs.io/en/latest/examples/10_classification_kriging2d.html#sphx-glr-examples-10-classification-kriging2d-py). + +## License + +PyKrige uses the BSD 3-Clause License. + + +%package help +Summary: Development documents and examples for PyKrige +Provides: python3-PyKrige-doc +%description help +# PyKrige + +[![DOI](https://zenodo.org/badge/DOI/10.5281/zenodo.3738604.svg)](https://doi.org/10.5281/zenodo.3738604) +[![PyPI version](https://badge.fury.io/py/PyKrige.svg)](https://badge.fury.io/py/PyKrige) +[![Conda Version](https://img.shields.io/conda/vn/conda-forge/pykrige.svg)](https://anaconda.org/conda-forge/pykrige) +[![Build Status](https://github.com/GeoStat-Framework/PyKrige/workflows/Continuous%20Integration/badge.svg?branch=main)](https://github.com/GeoStat-Framework/PyKrige/actions) +[![Coverage Status](https://coveralls.io/repos/github/GeoStat-Framework/PyKrige/badge.svg?branch=main)](https://coveralls.io/github/GeoStat-Framework/PyKrige?branch=main) +[![Documentation Status](https://readthedocs.org/projects/pykrige/badge/?version=stable)](http://pykrige.readthedocs.io/en/stable/?badge=stable) +[![Code style: black](https://img.shields.io/badge/code%20style-black-000000.svg)](https://github.com/psf/black) + + +

+PyKrige-LOGO +

+ +Kriging Toolkit for Python. + +## Purpose + +The code supports 2D and 3D ordinary and universal kriging. Standard +variogram models (linear, power, spherical, gaussian, exponential) are +built in, but custom variogram models can also be used. The 2D universal +kriging code currently supports regional-linear, point-logarithmic, and +external drift terms, while the 3D universal kriging code supports a +regional-linear drift term in all three spatial dimensions. Both +universal kriging classes also support generic 'specified' and +'functional' drift capabilities. With the 'specified' drift capability, +the user may manually specify the values of the drift(s) at each data +point and all grid points. With the 'functional' drift capability, the +user may provide callable function(s) of the spatial coordinates that +define the drift(s). The package includes a module that contains +functions that should be useful in working with ASCII grid files (`\*.asc`). + +See the documentation at for more +details and examples. + +## Installation + +PyKrige requires Python 3.5+ as well as numpy, scipy. It can be +installed from PyPi with, + +``` bash +pip install pykrige +``` + +scikit-learn is an optional dependency needed for parameter tuning and +regression kriging. matplotlib is an optional dependency needed for +plotting. + +If you use conda, PyKrige can be installed from the conda-forge channel with, + +``` bash +conda install -c conda-forge pykrige +``` + +## Features + +### Kriging algorithms + +- `OrdinaryKriging`: 2D ordinary kriging with estimated mean +- `UniversalKriging`: 2D universal kriging providing drift terms +- `OrdinaryKriging3D`: 3D ordinary kriging +- `UniversalKriging3D`: 3D universal kriging +- `RegressionKriging`: An implementation of Regression-Kriging +- `ClassificationKriging`: An implementation of Simplicial Indicator + Kriging + +### Wrappers + +- `rk.Krige`: A scikit-learn wrapper class for Ordinary and Universal + Kriging + +### Tools + +- `kriging_tools.write_asc_grid`: Writes gridded data to ASCII grid file (`\*.asc`) +- `kriging_tools.read_asc_grid`: Reads ASCII grid file (`\*.asc`) +- `kriging_tools.write_zmap_grid`: Writes gridded data to zmap file (`\*.zmap`) +- `kriging_tools.read_zmap_grid`: Reads zmap file (`\*.zmap`) + +### Kriging Parameters Tuning + +A scikit-learn compatible API for parameter tuning by cross-validation +is exposed in +[sklearn.model\_selection.GridSearchCV](http://scikit-learn.org/stable/modules/generated/sklearn.model_selection.GridSearchCV.html). +See the [Krige +CV](http://pykrige.readthedocs.io/en/latest/examples/08_krige_cv.html#sphx-glr-examples-08-krige-cv-py) +example for a more practical illustration. + +### Regression Kriging + +[Regression kriging](https://en.wikipedia.org/wiki/Regression-Kriging) +can be performed with +[pykrige.rk.RegressionKriging](http://pykrige.readthedocs.io/en/latest/examples/07_regression_kriging2d.html). +This class takes as parameters a scikit-learn regression model, and +details of either the `OrdinaryKriging` or the `UniversalKriging` +class, and performs a correction step on the ML regression prediction. + +A demonstration of the regression kriging is provided in the +[corresponding +example](http://pykrige.readthedocs.io/en/latest/examples/07_regression_kriging2d.html#sphx-glr-examples-07-regression-kriging2d-py). + +### Classification Kriging + +[Simplifical Indicator +kriging](https://www.sciencedirect.com/science/article/abs/pii/S1002070508600254) +can be performed with +[pykrige.ck.ClassificationKriging](http://pykrige.readthedocs.io/en/latest/examples/10_classification_kriging2d.html). +This class takes as parameters a scikit-learn classification model, and +details of either the `OrdinaryKriging` or the `UniversalKriging` class, +and performs a correction step on the ML classification prediction. + +A demonstration of the classification kriging is provided in the +[corresponding +example](http://pykrige.readthedocs.io/en/latest/examples/10_classification_kriging2d.html#sphx-glr-examples-10-classification-kriging2d-py). + +## License + +PyKrige uses the BSD 3-Clause License. + + +%prep +%autosetup -n PyKrige-1.7.0 + +%build +%py3_build + +%install +%py3_install +install -d -m755 %{buildroot}/%{_pkgdocdir} +if [ -d doc ]; then cp -arf doc %{buildroot}/%{_pkgdocdir}; fi +if [ -d docs ]; then cp -arf docs %{buildroot}/%{_pkgdocdir}; fi +if [ -d example ]; then cp -arf example %{buildroot}/%{_pkgdocdir}; fi +if [ -d examples ]; then cp -arf examples %{buildroot}/%{_pkgdocdir}; fi +pushd %{buildroot} +if [ -d usr/lib ]; then + find usr/lib -type f -printf "/%h/%f\n" >> filelist.lst +fi +if [ -d usr/lib64 ]; then + find usr/lib64 -type f -printf "/%h/%f\n" >> filelist.lst +fi +if [ -d usr/bin ]; then + find usr/bin -type f -printf "/%h/%f\n" >> filelist.lst +fi +if [ -d usr/sbin ]; then + find usr/sbin -type f -printf "/%h/%f\n" >> filelist.lst +fi +touch doclist.lst +if [ -d usr/share/man ]; then + find usr/share/man -type f -printf "/%h/%f.gz\n" >> doclist.lst +fi +popd +mv %{buildroot}/filelist.lst . +mv %{buildroot}/doclist.lst . + +%files -n python3-PyKrige -f filelist.lst +%dir %{python3_sitearch}/* + +%files help -f doclist.lst +%{_docdir}/* + +%changelog +* Tue Apr 11 2023 Python_Bot - 1.7.0-1 +- Package Spec generated diff --git a/sources b/sources new file mode 100644 index 0000000..27a4228 --- /dev/null +++ b/sources @@ -0,0 +1 @@ +0bac9788900734a4fe3f54752f572e6e PyKrige-1.7.0.tar.gz -- cgit v1.2.3