Metadata-Version: 1.1
Name: yt
Version: 3.4.0
Summary: An analysis and visualization toolkit for volumetric data
Home-page: http://yt-project.org/
Author: The yt project
Author-email: yt-dev@lists.spacepope.org
License: BSD 3-Clause
Description: The yt Project
        ==============
        
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        yt is an open-source, permissively-licensed python package for analyzing
        and visualizing volumetric data.
        
        yt supports structured, variable-resolution meshes, unstructured meshes,
        and discrete or sampled data such as particles. Focused on driving
        physically-meaningful inquiry, yt has been applied in domains such as
        astrophysics, seismology, nuclear engineering, molecular dynamics, and
        oceanography. Composed of a friendly community of users and developers,
        we want to make it easy to use and develop - we'd love it if you got
        involved!
        
        We've written a `method
        paper <http://adsabs.harvard.edu/abs/2011ApJS..192....9T>`__ you may be
        interested in; if you use yt in the preparation of a publication, please
        consider citing it.
        
        Installation
        ------------
        
        If you're using conda with
        `conda-forge <http://conda-forge.github.io/>`__, you can install the
        most recent stable version by running:
        
        ::
        
            conda install -c conda-forge yt
        
        or by doing:
        
        ::
        
            pip install yt
        
        If you want the latest nightly build, you can manually install from our
        repository:
        
        ::
        
            conda install -c http://use.yt/with_conda yt
        
        To get set up with a development version, you can clone this repository
        and install like this:
        
        ::
        
            git clone https://github.com/yt-project/yt yt-git
            cd yt-git
            pip install -e .
        
        To set up yt in a virtualenv (and there are `many good
        reasons <https://packaging.python.org/installing/#creating-virtual-environments>`__
        to do so!) you can follow this prescription:
        
        ::
        
            # Assuming you have cd'd into yt-git
            # It is conventional to create virtualenvs at ~/.virtualenv/
            $ mkdir -p ~/.virtualenv
            # Assuming your version of Python 3 is 3.4 or higher,
            # create a virtualenv named yt
            $ python3 -m venv ~/.virtualenv/yt
            # Activate it
            $ source ~/.virtualenv/yt/bin/activate
            # Make sure you run the latest version of pip
            $ pip install --upgrade pip
            $ pip install -e .
            # Output installed packages
            $ pip freeze
        
        Getting Started
        ---------------
        
        yt is designed to provide meaningful analysis of data. We have some
        Quickstart example notebooks in the repository:
        
        -  `Introduction <doc/source/quickstart/1)_Introduction.ipynb>`__
        -  `Data Inspection <doc/source/quickstart/2)_Data_Inspection.ipynb>`__
        -  `Simple
           Visualization <doc/source/quickstart/3)_Simple_Visualization.ipynb>`__
        -  `Data Objects and Time
           Series <doc/source/quickstart/4)_Data_Objects_and_Time_Series.ipynb>`__
        -  `Derived Fields and
           Profiles <doc/source/quickstart/5)_Derived_Fields_and_Profiles.ipynb>`__
        -  `Volume
           Rendering <doc/source/quickstart/6)_Volume_Rendering.ipynb>`__
        
        If you'd like to try these online, you can visit our `yt
        Hub <https://hub.yt/>`__ and run a notebook next to some of our example
        data.
        
        Contributing
        ------------
        
        We love contributions! yt is open source, built on open source, and we'd
        love to have you hang out in our community.
        
        We have developed some `guidelines <CONTRIBUTING.rst>`__ for
        contributing to yt.
        
        **Imposter syndrome disclaimer**: We want your help. No, really.
        
        There may be a little voice inside your head that is telling you that
        you're not ready to be an open source contributor; that your skills
        aren't nearly good enough to contribute. What could you possibly offer a
        project like this one?
        
        We assure you - the little voice in your head is wrong. If you can write
        code at all, you can contribute code to open source. Contributing to
        open source projects is a fantastic way to advance one's coding skills.
        Writing perfect code isn't the measure of a good developer (that would
        disqualify all of us!); it's trying to create something, making
        mistakes, and learning from those mistakes. That's how we all improve,
        and we are happy to help others learn.
        
        Being an open source contributor doesn't just mean writing code, either.
        You can help out by writing documentation, tests, or even giving
        feedback about the project (and yes - that includes giving feedback
        about the contribution process). Some of these contributions may be the
        most valuable to the project as a whole, because you're coming to the
        project with fresh eyes, so you can see the errors and assumptions that
        seasoned contributors have glossed over.
        
        (This disclaimer was originally written by `Adrienne
        Lowe <https://github.com/adriennefriend>`__ for a `PyCon
        talk <https://www.youtube.com/watch?v=6Uj746j9Heo>`__, and was adapted
        by yt based on its use in the README file for the `MetPy
        project <https://github.com/Unidata/MetPy>`__)
        
        Resources
        ---------
        
        We have some community and documentation resources available.
        
        -  Our latest documentation is always at http://yt-project.org/docs/dev/
           and it includes recipes, tutorials, and API documentation
        -  The `discussion mailing
           list <http://lists.spacepope.org/listinfo.cgi/yt-users-spacepope.org/>`__
           should be your first stop for general questions
        -  The `development mailing
           list <http://lists.spacepope.org/listinfo.cgi/yt-dev-spacepope.org/>`__
           is better suited for more development issues
        -  You can also join us on Slack at yt-project.slack.com (`request an
           invite <http://yt-project.org/slack.html>`__)
        
        .. |Users' Mailing List| image:: https://img.shields.io/badge/Users-List-lightgrey.svg
           :target: http://lists.spacepope.org/listinfo.cgi/yt-users-spacepope.org/
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           :target: https://travis-ci.org/yt-project/yt
        .. |Latest Documentation| image:: https://img.shields.io/badge/docs-latest-brightgreen.svg
           :target: http://yt-project.org/docs/dev/
        .. |Data Hub| image:: https://img.shields.io/badge/data-hub-orange.svg
           :target: https://hub.yt/
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Keywords: astronomy astrophysics visualization amr adaptivemeshrefinement
Platform: UNKNOWN
Classifier: Development Status :: 5 - Production/Stable
Classifier: Environment :: Console
Classifier: Intended Audience :: Science/Research
Classifier: License :: OSI Approved :: BSD License
Classifier: Operating System :: MacOS :: MacOS X
Classifier: Operating System :: POSIX :: AIX
Classifier: Operating System :: POSIX :: Linux
Classifier: Programming Language :: C
Classifier: Programming Language :: Python :: 2
Classifier: Programming Language :: Python :: 2.7
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.4
Classifier: Programming Language :: Python :: 3.5
Classifier: Topic :: Scientific/Engineering :: Astronomy
Classifier: Topic :: Scientific/Engineering :: Physics
Classifier: Topic :: Scientific/Engineering :: Visualization
