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next version preparation (0.2.8 on pypi now)
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mmaelicke committed Sep 18, 2020
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2 changes: 1 addition & 1 deletion VERSION
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0.2.8
0.2.9
4 changes: 2 additions & 2 deletions docs/conf.py
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author = 'Mirko Mälicke'

# The short X.Y version
version = '0.2.8'
version = '0.2.9'
# The full version, including alpha/beta/rc tags
release = '0.2.8'
release = '0.2.9'


# -- General configuration ---------------------------------------------------
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21 changes: 21 additions & 0 deletions scikit-gstat-0.2.8/LICENSE
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MIT License

Copyright (c) 2017 Mirko Mälicke

Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
in the Software without restriction, including without limitation the rights
to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
copies of the Software, and to permit persons to whom the Software is
furnished to do so, subject to the following conditions:

The above copyright notice and this permission notice shall be included in all
copies or substantial portions of the Software.

THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
SOFTWARE.
137 changes: 137 additions & 0 deletions scikit-gstat-0.2.8/README.rst
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SciKit-GStat
============

Info: scikit-gstat needs Python >= 3.5!

.. image:: https://img.shields.io/badge/pypi%20package-0.2.7-green.svg
:target: https://pypi.org/project/scikit-gstat/0.2.7/

.. image:: https://img.shields.io/badge/version-0.2.8-green.svg
:target: https://github.com/mmaelicke/scikit-gstat

.. image:: https://travis-ci.org/mmaelicke/scikit-gstat.svg?branch=master
:target: https://travis-ci.org/mmaelicke/scikit-gstat
:alt: Build Status

.. image:: https://api.codacy.com/project/badge/Grade/34022fb8b795435b8eeb5431159fa7c6
:alt: Codacy Badge
:target: https://app.codacy.com/app/mmaelicke/scikit-gstat?utm_source=github.com&utm_medium=referral&utm_content=mmaelicke/scikit-gstat&utm_campaign=Badge_Grade_Dashboard

.. image:: https://codecov.io/gh/mmaelicke/scikit-gstat/branch/master/graph/badge.svg
:target: https://codecov.io/gh/mmaelicke/scikit-gstat
:alt: Codecov

.. image:: https://zenodo.org/badge/98853365.svg
:target: https://zenodo.org/badge/latestdoi/98853365

How to cite
-----------

In case you use SciKit-GStat in other software or scientific publications,
please reference this module. It is published and has a DOI. It can be cited
as:

Mirko Mälicke, & Helge David Schneider. (2019, November 25). Scikit-GStat 0.2.7: A scipy flavored geostatistical analysis toolbox written in Python. (Version v.0.2.7). Zenodo. http://doi.org/10.5281/zenodo.3552235



Full Documentation
------------------

The full documentation can be found at: https://mmaelicke.github.io/scikit-gstat

Description
-----------

SciKit-Gstat is a scipy-styled analysis module for geostatistics. It includes
two base classes ``Variogram`` and ``OrdinaryKriging``. Additionally, various
variogram classes inheriting from ``Variogram`` are available for solving
directional or space-time related tasks.
The module makes use of a rich selection of semi-variance
estimators and variogram model functions, while being extensible at the same
time.
The estimators include:

- matheron
- cressie
- dowd
- genton
- entropy
- two experimental ones: quantiles, minmax

The models include:

- sperical
- exponential
- gaussian
- cubic
- stable
- matérn

with all of them in a nugget and no-nugget variation. All the estimator are
implemented using numba's jit decorator. The usage of numba might be subject
to change in future versions.


Installation
~~~~~~~~~~~~

PyPI:

.. code-block:: bash
pip install scikit-gstat
GIT:

.. code-block:: bash
git clone https://github.com/mmaelicke/scikit-gstat.git
cd scikit-gstat
pip install -r requirements.txt
pip install -e .
**Note:** It can happen that the installation of shapely, numba or numpy is failing using pip. Especially on Windows systems. Usually, a missing Dll (see eg. `#31 <https://github.com/mmaelicke/scikit-gstat/issues/31>`_) or visual c++ redistributable is the reason. These errors are not caused by pip, scikit-gstat or the respective packages and there are a lot of issues in the shapely and numpy repo concerning these problems. Usually, the best workaround is to install especially shapely independent from scikit-gstat. As far as I know, these problems do not apply if anaconda is used like:

.. code-block:: bash
conda install shapely numpy
Usage
~~~~~

The `Variogram` class needs at least a list of coordiantes and values.
All other attributes are set by default.
You can easily set up an example by generating some random data:

.. code-block:: python
import numpy as np
import skgstat as skg
coordinates = np.random.gamma(0.7, 2, (30,2))
values = np.random.gamma(2, 2, 30)
V = skg.Variogram(coordinates=coordinates, values=values)
print(V)
.. code-block:: bash
spherical Variogram
-------------------
Estimator: matheron
Range: 1.64
Sill: 5.35
Nugget: 0.00
New Version 0.2
---------------

Scikit-gstat was rewritten in major parts. Most of the changes are internal,
but the attributes and behaviour of the `Variogram` has also changed
substantially.
A detailed description of of the new versions usage will follow. The last
version of the old Variogram class, 0.1.8, is kept in the `version-0.1.8`
branch on GitHub, but not developed any further. Those two versions are not
compatible.
2 changes: 1 addition & 1 deletion skgstat/__init__.py
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from . import interfaces

# set some stuff
__version__ = '0.2.8'
__version__ = '0.2.9'
__author__ = 'Mirko Maelicke <[email protected]>'

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