Metadata-Version: 1.1
Name: gppeval
Version: 2018.2.1.0.9.dev1
Summary: Geothermal Power Potential assessment
Home-page: https://github.com/cpocasangre/gppeval
Author: Carlos O. POCASANGRE JIMENEZ
Author-email: carlos.pocasangre@mine.kyushu-u.ac.jp
License: MIT License
Description: TOPIC
        ===============================
        A Python stochastic library for assessing geothermal power potential by using the
        volumetric method in a liquid-dominated reservoir
        
        ABSTRACT
        ===============================
        ``Gppeval`` is a Python stochastic library for assessing geothermal power potential by using
        the volumetric method in a liquid dominated reservoir is presented in this
        application. More specifically, the purposes of this study are the use of the
        volumetric method **“heat in place”** to estimate ability to produce electrical
        energy from geothermal **liquid-dominated reservoir**, and to code a valuable Python
        stochastic library that has the helpful methods for running the simulation. Even
        though there are some kinds of licensed software for carrying out this simulation,
        for this task was selected Open-Source Programming Language, i.e., Python.
        
        The Geothermal Power Potential Evaluation stochastic library, Gppeval, is structured
        as three essential objects such as the geothermal power plant module, the Monte
        Carlo simulation module, and the module of tools.
        
        For testing the application, a **Jupyter Notebook** example has been included in the test
        folder.
        
        *HINT*: **For the moment, this application is available only for Python 2.7**
        
        INSTALLATION
        ============
        
        Required Packages
        -----------------
        
        The following packages should be installed automatically (if using 'pip'
        or 'easy_install'), otherwise they will need to be installed manually:
        
        - NumPy_ : Numeric Python
        - SciPy_ : Scientific Python
        - Matplotlib_ : Python plotting library
        - Mcerp_ : Monte Carlo Error Propagation
        - Beautifultable_ : Utility package to print visually appealing ASCII tables to terminal
        
        How to install
        --------------
        
        You have **several easy, convenient options** to install the 'gppeval'
        package (administrative privileges may be required). Keep in mind to use Python 2.7
        
        #. Simply copy the unzipped 'gppeval folder' directory to any other location that
           python can find it and rename it 'gppeval'.
        
        #. From the command-line, do one of the following:
        
           a. Manually download the package files below, unzip to any directory, and
              run:
        
               $ [sudo] python setup.py install
        
           b. If 'pip' is installed, run the command in the same folder 'gppeval':
        
               $ pip install [--upgrade] .
        
           c. If 'pip' is installed, run (internet connection is required):
        
               $ [sudo] pip install [--upgrade] --index-url https://test.pypi.org/simple/ gppeval
        
        CONTACT
        =======
        
        Please send **feature requests, bug reports, or feedback** to: `Carlos O. POCASANGRE JIMENEZ`_
        
        
        .. _Monte Carlo methods: http://en.wikipedia.org/wiki/Monte_Carlo_method
        .. _latin-hypercube sampling: http://en.wikipedia.org/wiki/Latin_hypercube_sampling
        .. _error propagation: http://en.wikipedia.org/wiki/Propagation_of_uncertainty
        .. _math: http://docs.python.org/library/math.html
        .. _NumPy: http://www.numpy.org/
        .. _SciPy: http://scipy.org
        .. _Matplotlib: http://matplotlib.org/
        .. _scipy.stats: http://docs.scipy.org/doc/scipy/reference/stats.html
        .. _uncertainties: http://pypi.python.org/pypi/uncertainties
        .. _Mcerp: http://github.com/tisimst/mcerp
        .. _Beautifultable: https://github.com/pri22296/beautifultable
        .. _Gppeval: http://github.com/cpocasangre/gppeval
        .. _Carlos O. POCASANGRE JIMENEZ: mailto:carlos.pocasangre@mine.kyushu-u.ac.jp
        
Keywords: monte carlo,latin hypercube,geothermal power potential,volumetric method,heat in place,geothermal reservoir
Platform: UNKNOWN
Classifier: Development Status :: 2 - Pre-Alpha
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python :: 2.7
