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Metadata-Version: 2.1
Name: yt
Version: 3.6.1
Summary: An analysis and visualization toolkit for volumetric data
Home-page: https://github.com/yt-project/yt
Author: The yt project
Author-email: yt-dev@python.org
License: BSD 3-Clause
Project-URL: Homepage, https://yt-project.org/
Project-URL: Documentation, https://yt-project.org/doc/
Project-URL: Source, https://github.com/yt-project/yt/
Project-URL: Tracker, https://github.com/yt-project/yt/issues
Description: # The yt Project
        
        [![Users' Mailing List](https://img.shields.io/badge/Users-List-lightgrey.svg)](https://mail.python.org/archives/list/yt-users@python.org//)
        [![Devel Mailing List](https://img.shields.io/badge/Devel-List-lightgrey.svg)](https://mail.python.org/archives/list/yt-dev@python.org//)
        [![Build Status](https://img.shields.io/travis/yt-project/yt.svg?branch=master)](https://travis-ci.org/yt-project/yt)
        [![codecov](https://codecov.io/gh/yt-project/yt/branch/master/graph/badge.svg)](https://codecov.io/gh/yt-project/yt)
        [![Latest Documentation](https://img.shields.io/badge/docs-latest-brightgreen.svg)](http://yt-project.org/docs/dev/)
        [![Data Hub](https://img.shields.io/badge/data-hub-orange.svg)](https://hub.yt/)
        [![Powered by NumFOCUS](https://img.shields.io/badge/powered%20by-NumFOCUS-orange.svg?style=flat&colorA=E1523D&colorB=007D8A)](http://numfocus.org)
        [![Sponsor our Project](https://img.shields.io/badge/donate-to%20yt-blueviolet)](https://numfocus.salsalabs.org/donate-to-yt/index.html)
                        
        <a href="http://yt-project.org"><img src="doc/source/_static/yt_logo.png" width="300"></a>
        
        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](https://ui.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.
        
        ## Code of Conduct
        
        yt abides by a code of conduct partially modified from the PSF code of conduct,
        and is found [in our contributing
        guide](http://yt-project.org/docs/dev/developing/developing.html#yt-community-code-of-conduct).
        
        ## Installation
        
        You can install the most recent stable version of yt either with conda from
        [conda-forge](https://conda-forge.org/):
        
        ```
        conda install -c conda-forge yt
        ```
        
        or with pip:
        
        ```
        pip install yt
        ```
        
        If you want the latest nightly build, you can manually install from our
        repository:
        
        ```
        conda install -c yt-project/label/dev yt
        ```
        
        To get set up with a development version, you want to clone this repository:
        
        ```
        git clone https://github.com/yt-project/yt yt-git
        cd yt-git
        ```
        
        and work within a conda environment:
        
        ```
        # Create a conda environment named yt-git
        $ conda create -n yt-git python=3.6
        # Activate it
        $ source activate yt-git
        # Make sure you run the latest version of conda
        $ conda update conda
        # Install yt's runtime dependencies
        $ conda install -c conda-forge yt --only-deps
        # Install yt's build dependencies
        $ conda install -c conda-forge cython
        # Make sure you run the latest version of pip
        $ pip install --upgrade pip
        $ pip install -v -e .
        # Output installed packages
        $ conda env export
        ```
        
        Alternatively, you can install yt in a
        [virtualenv](https://packaging.python.org/installing/#creating-virtual-environments):
        
        ```
        # 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-git
        $ python3 -m venv ~/.virtualenv/yt-git
        # Activate it
        $ source ~/.virtualenv/yt-git/bin/activate
        # Make sure you run the latest version of pip
        $ pip install --upgrade pip
        # Assuming you have cd'd into yt-git
        $ 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](https://mail.python.org/archives/list/yt-users@python.org//)
           should be your first stop for general questions
         * The [development mailing
           list](https://mail.python.org/archives/list/yt-dev@python.org//) is
           better suited for more development issues
         * You can also join us on Slack at yt-project.slack.com ([request an
           invite](https://yt-project.org/slack.html))
        
        ## Powered by NumFOCUS
        
        yt is a fiscally sponsored project of [NumFOCUS](https://numfocus.org/). 
        If you're interested in
        supporting the active maintenance and development of this project, consider
        [donating to the project](https://numfocus.salsalabs.org/donate-to-yt/index.html). 
        
        
        
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
Classifier: Framework :: Matplotlib
Requires-Python: >=2.7,!=3.0.*,!=3.1.*,!=3.2.*,!=3.3.*,!=3.4.*
Description-Content-Type: text/markdown
Provides-Extra: hub
Provides-Extra: mapserver