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next version preparation (0.2.8 on pypi now)
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0.2.8 | ||
0.2.9 |
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MIT License | ||
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Copyright (c) 2017 Mirko Mälicke | ||
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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: | ||
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The above copyright notice and this permission notice shall be included in all | ||
copies or substantial portions of the Software. | ||
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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. |
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SciKit-GStat | ||
============ | ||
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Info: scikit-gstat needs Python >= 3.5! | ||
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.. image:: https://img.shields.io/badge/pypi%20package-0.2.7-green.svg | ||
:target: https://pypi.org/project/scikit-gstat/0.2.7/ | ||
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.. image:: https://img.shields.io/badge/version-0.2.8-green.svg | ||
:target: https://github.com/mmaelicke/scikit-gstat | ||
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.. image:: https://travis-ci.org/mmaelicke/scikit-gstat.svg?branch=master | ||
:target: https://travis-ci.org/mmaelicke/scikit-gstat | ||
:alt: Build Status | ||
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.. 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 | ||
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.. image:: https://codecov.io/gh/mmaelicke/scikit-gstat/branch/master/graph/badge.svg | ||
:target: https://codecov.io/gh/mmaelicke/scikit-gstat | ||
:alt: Codecov | ||
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.. image:: https://zenodo.org/badge/98853365.svg | ||
:target: https://zenodo.org/badge/latestdoi/98853365 | ||
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How to cite | ||
----------- | ||
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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: | ||
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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 | ||
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Full Documentation | ||
------------------ | ||
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The full documentation can be found at: https://mmaelicke.github.io/scikit-gstat | ||
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Description | ||
----------- | ||
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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: | ||
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- matheron | ||
- cressie | ||
- dowd | ||
- genton | ||
- entropy | ||
- two experimental ones: quantiles, minmax | ||
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The models include: | ||
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- sperical | ||
- exponential | ||
- gaussian | ||
- cubic | ||
- stable | ||
- matérn | ||
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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. | ||
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Installation | ||
~~~~~~~~~~~~ | ||
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PyPI: | ||
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.. code-block:: bash | ||
pip install scikit-gstat | ||
GIT: | ||
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.. 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: | ||
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.. code-block:: bash | ||
conda install shapely numpy | ||
Usage | ||
~~~~~ | ||
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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: | ||
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.. 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 | ||
--------------- | ||
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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. |
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from . import interfaces | ||
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# set some stuff | ||
__version__ = '0.2.8' | ||
__version__ = '0.2.9' | ||
__author__ = 'Mirko Maelicke <[email protected]>' |