Metadata-Version: 1.1
Name: jelinekstat
Version: 0.1.0
Summary: Application software for applying the Second-order tensor statistical proposal of Jelínek (1978).
Home-page: https://github.com/eamontoyaa/jelinekstat
Author: Exneyder A. Montoya-Araque & Ludger O. Suarez-Burgoa
Author-email: eamontoyaa@gmail.com
License: BSD 2-Clause License
Description: ===============
        ``jelinekstat``
        ===============
        
        
        .. image:: https://img.shields.io/pypi/v/jelinekstat.svg
                :target: https://pypi.python.org/pypi/jelinekstat
        
        .. image:: https://readthedocs.org/projects/jelinekstat/badge/?version=latest
                :target: https://jelinekstat.readthedocs.io/en/latest/?badge=latest
                :alt: Documentation Status
        
        
        Application software in **Python 3** to apply the statistical proposal of
        `Jelínek (1978) <https://doi.org/10.1007/BF01613632>`_ for a sample of several
        second-order tensors in order to obtain the mean tensor of the sample, its
        principal values with their confidence intervals, and the principal directions
        with their confidence regions.
        
        This application program is able to plot the summary of the statistical model
        described above in a stereographic projection for a better understanding of the
        outcomes. Provided that, the next picture represents the aim of ``jelinekstat``.
        
        .. figure:: https://rawgit.com/eamontoyaa/jelinekstat/master/docs/otherFiles/my_image.svg
                :alt: Outcome plot example
        
        Features
        --------
        
        * `Documentation <https://jelinekstat.readthedocs.io>`_
        * `PyPI <https://pypi.org/project/jelinekstat>`_
        * `GitHub <https://github.com/eamontoyaa/jelinekstat>`_
        * Open source and free software: `BSD-2-Clause <https://opensource.org/licenses/BSD-2-Clause>`_.
        
        
        Requirements
        ------------
        
        The code was written in Python 3. The packages `numpy <http://www.numpy.org/>`_,
        `scipy <https://www.scipy.org/>`_, `matplotlib <https://matplotlib.org/>`_
        and `mplstereonet <https://pypi.python.org/pypi/mplstereonet>`_ are
        required for using ``jelinekstat``. All of them are
        downloadable from the PyPI repository by opening a terminal and typing the
        following code lines:
        
        
        ::
        
            pip install numpy
            pip install scipy
            pip install matplotlib
            pip install mplstereonet
        
        
        Installation
        ------------
        
        
        To install ``jelinekstat`` open a terminal and type:
        
        ::
        
            pip install jelinekstat
        
        
        Example
        -------
        
        To produce the plot shown above execute the following script
        
        ::
        
            from jelinekstat.jelinekstat import tensorStat
        
            # Input data
            sample = [[1.02327, 1.02946, 0.94727, -0.01495, -0.03599, -0.05574],
                      [1.02315, 1.01803, 0.95882, -0.00924, -0.02058, -0.03151],
                      [1.02801, 1.03572, 0.93627, -0.03029, -0.03491, -0.06088],
                      [1.02775, 1.00633, 0.96591, -0.01635, -0.04148, -0.02006],
                      [1.02143, 1.01775, 0.96082, -0.02798, -0.04727, -0.02384],
                      [1.01823, 1.01203, 0.96975, -0.01126, -0.02833, -0.03649],
                      [1.01486, 1.02067, 0.96446, -0.01046, -0.01913, -0.03864],
                      [1.04596, 1.01133, 0.94271, -0.01660, -0.04711, -0.03636]]
            confLevel = 0.95
        
            # Performing the calculation all in one function.
            jelinekStatsSummary, stereonetPlot = tensorStat(
                    sample, confLevel=0.95, want2plot=True, plotName='testForSCRshort',
                    ext='pdf')
            stereonetPlot.show()
        
        
        References
        ----------
        Jelínek, V (1978). Statistical processing of anisotropy of magnetic
        susceptibility measured on group of specimens. Studia Geophysica et Geodaetica,
        22 (1), pp. 50-62.
        
        
        
        
        
        
        =======
        History
        =======
        
        0.1.0 (2018-07-08)
        ------------------
        
        * First release on PyPI.
        
Keywords: Anisotropy of Magnetic Susceptibility,Jelínek,tensor,statistics,Python,application software
Platform: UNKNOWN
Classifier: Development Status :: 2 - Pre-Alpha
Classifier: Intended Audience :: Developers
Classifier: License :: OSI Approved :: BSD License
Classifier: Natural Language :: English
Classifier: Programming Language :: Python :: 3.6
