Metadata-Version: 2.1
Name: pastas
Version: 0.12.0
Summary: Python Applied System TimeSeries Analysis Software
Home-page: https://github.com/pastas/pastas
Author: R.A. Collenteur, M. Bakker, R. Calje, F. Schaars
Author-email: raoulcollenteur@gmail.com, markbak@gmail.com, r.calje@artesia-water.nl
License: MIT
Project-URL: Source, https://github.com/pastas/pastas
Project-URL: Documentation, http://pastas.readthedocs.io/en/latest/
Project-URL: Tracker, https://github.com/pastas/pastas/issues
Project-URL: Help, https://stackoverflow.com/questions/tagged/pastas
Description: PASTAS: HYDROLOGICAL TIME SERIES ANALYSIS
        =========================================
        
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        Pastas: what is it?
        ~~~~~~~~~~~~~~~~~~~
        Pastas is an open source python package for processing, simulating and analyzing 
        hydrological time series (models). The object oriented stucture allows for the 
        quick implementation of new model components. Time series models can be created,
        calibrated, and analysed with just a few lines of python code with the built-in 
        optimization, visualisation, and statistical analysis tools.
        
        Documentation & Examples
        ~~~~~~~~~~~~~~~~~~~~~~~~
        - Documentation is provided on a dedicated website: http://pastas.readthedocs.io/
        - Examples can be found on the `examples directory on the documentation website <http://pastas.readthedocs.io/en/dev/examples.html>`_.
        - View and edit a working example notebook of a Pastas model in `MyBinder <https://mybinder.org/v2/gh/pastas/pastas/master?filepath=examples%2Fnotebooks%2F1_basic_model.ipynb>`_
        - A list of Publications that used Pastas is available in a `dedicated GitHub repo <https://github.com/pastas/pastas_research>`_
        
        Get in Touch
        ~~~~~~~~~~~~
        - Questions on Pastas can be asked and answered on `StackOverFlow <https://stackoverflow.com/questions/tagged/pastas>`_.
        - Bugs, feature requests and other improvements can be posten as the `Github Issues <https://github.com/pastas/pastas/issues>`_.
        - Pull requests will only be accepted on the development branch (dev) of this repository. Please take a look at the `developers section <http://pastas.readthedocs.io/>`_ on the documentation website for more information on how to develop Pastas.
        
        Quick installation guide
        ~~~~~~~~~~~~~~~~~~~~~~~~
        To install Pastas, a working version of Python 3.5, 3.6, or 3.7 has to be installed on 
        your computer. We recommend using the `Anaconda Distribution <https://www.continuum.io/downloads>`_
        with Python 3.7 as it includes most of the python package dependencies and the Jupyter
        Notebook software to run the notebooks. However, you are free to install any
        Python distribution you want.
        
        Stable version
        --------------
        To get the latest stable version, use::
        
          pip install pastas
        
        Update
        ------
        To update pastas, use::
        
          pip install pastas --upgrade  
          
        Developers
        ----------
        To get the latest development version, use::
        
           pip install https://github.com/pastas/pastas/zipball/dev
          
        Dependencies
        ~~~~~~~~~~~~
        Pastas depends on a number of Python packages, of which all of the necessary are 
        automatically installed when using the pip install manager. To summarize, the 
        following pacakges are necessary for a minimal function installation of Pastas:
        
        - numpy>=1.15
        - matplotlib>=2.0
        - pandas>=0.23
        - scipy>=1.1
        
        How to Cite Pastas?
        ~~~~~~~~~~~~~~~~~~~
        If you use Pastas in one of your studies, please cite the Pastas article in Groundwater:
        
        - Collenteur, R.A., Bakker, M., Caljé, R., Klop, S.A., Schaars, F. (2019) `Pastas: open source software for the analysis of groundwater time series <https://ngwa.onlinelibrary.wiley.com/doi/abs/10.1111/gwat.12925>`_. Groundwater. doi: 10.1111/gwat.12925.
        
        To cite a specific version of Python, you can use the DOI provided for each official release (>0.9.7) through Zenodo. Click on the link to get a specific version and DOI, depending on the Pastas version.
        
        - Collenteur, R., Bakker, M., Caljé, R. & Schaars, F. (XXXX). Pastas: open-source software for time series analysis in hydrology (Version X.X.X). Zenodo. http://doi.org/10.5281/zenodo.1465866
        
        License (MIT License)
        ~~~~~~~~~~~~~~~~~~~~~
        Copyright (c) 2016-2018 R.A. Collenteur, M. Bakker, R. Calje, F. Schaars
        
        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.
        
        
Platform: Windows
Platform: Mac OS-X
Classifier: Development Status :: 4 - Beta
Classifier: Intended Audience :: Science/Research
Classifier: Intended Audience :: Other Audience
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python :: 3.5
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
Classifier: Topic :: Scientific/Engineering :: Hydrology
Description-Content-Type: text/x-rst
