Metadata-Version: 1.1
Name: scikit-gstat
Version: 0.1.1
Summary: Geostatistical expansion in the scipy style
Home-page: UNKNOWN
Author: Mirko Maelicke
Author-email: mirko.maelicke@kit.edu
License: UNKNOWN
Description: Scikit-Gstat
        ============
        
        This module offers at the current state a scipy-styled `Variogram` class for performing geostatistical analysis.
        This class is can be used to derive variograms. Key benefits are a number of semivariance estimators and theoretical
        variogram functions. The module is planned to be hold in the manner of scikit modules and be based upon `numpy` and
        `scipy` whenever possible. There is also a distance matrix extension available, with a function for calculating
        n.dimensional distance matrices for the variogram.
        The estimators include:
        
        - matheron
        - cressie
        - dowd
        - genton (still buggy)
        - entropy (not tested)
        
        The models include:
        
        - sperical
        - exponential
        - gaussian
        - cubic
        - stable
        - matérn
        
        with all of them in a nugget and no-nugget variation. All the estimator functions are written `numba` compatible,
        therefore you can just download it and include the `@jit` decorator. This can speed up the calculation for bigger
        data sets up to 100x. Nevertheless, this is not included in this sckit-gstat version as these functions might be
        re-implemented using Cython. This is still under evaluation.
        
        At the current stage, the package does not inlcude any kriging. This is planned for a future release.
        
        
        Installation
        ~~~~~~~~~~~~
        
        You can either install scikit-gstat using pip or you download the latest version from github.
        
        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 .
        
        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
Platform: UNKNOWN
Classifier: Development Status :: 4 - Beta
Classifier: Intended Audience :: Science/Research
Classifier: License :: OSI Approved :: MIT License
Classifier: Natural Language :: English
Classifier: Programming Language :: Python :: 3.3
Classifier: Programming Language :: Python :: 3.4
Classifier: Programming Language :: Python :: 3.5
Classifier: Programming Language :: Python :: 3.6
Classifier: Topic :: Scientific/Engineering :: Information Analysis
