Metadata-Version: 2.1
Name: mayavi
Version: 4.7.2
Summary: 3D scientific data visualization library and application
Home-page: http://docs.enthought.com/mayavi/mayavi/
Author: Prabhu Ramachandran, et al.
Author-email: prabhu@aero.iitb.ac.in
Maintainer: ETS Developers
Maintainer-email: mayavi-users@lists.sf.net
License: BSD
Download-URL: https://www.github.com/enthought/mayavi
Description: ======================================================
        Mayavi: 3D visualization of scientific data in Python
        ======================================================
        
        Mayavi docs: http://docs.enthought.com/mayavi/mayavi/
        TVTK docs: http://docs.enthought.com/mayavi/tvtk
        
        .. image:: https://img.shields.io/pypi/v/mayavi.svg
           :target: https://pypi.org/project/mayavi/
           :alt: Package on PyPI
        
        .. image:: https://api.travis-ci.org/enthought/mayavi.png?branch=master
           :target: https://travis-ci.org/enthought/mayavi
           :alt: Build status
        
        .. image:: https://ci.appveyor.com/api/projects/status/lnb24gj70yidfnrl/branch/master
           :target: https://ci.appveyor.com/project/EnthoughtOSS/mayavi
           :alt: Appveyor build status
        
        .. image:: http://codecov.io/github/enthought/mayavi/coverage.svg?branch=master
           :target: http://codecov.io/github/enthought/mayavi?branch=master
           :alt: Code coverage status
        
        .. image:: https://img.shields.io/badge/License-BSD%203--Clause-blue.svg
           :target: https://opensource.org/licenses/BSD-3-Clause
           :alt: BSD 3 Clause
        
        Vision
        ======
        
        Mayavi seeks to provide easy and interactive visualization of 3D data. It does
        this by the following:
        
            - an (optional) rich user interface with dialogs to interact with all data
              and objects in the visualization.
        
            - a simple and clean scripting interface in Python, including one-liners,
              a-la mlab, or object-oriented programming interface.
        
            - harnesses the power of the VTK toolkit without forcing you to learn it.
        
        Additionally Mayavi strives to be a reusable tool that can be embedded in your
        applications in different ways or combined with the envisage
        application-building framework to assemble domain-specific tools.
        
        Mayavi is part of the Enthought Tool Suite (ETS).
        
        
        Features
        ===========
        
        Mayavi is a general purpose, cross-platform tool for 2-D and 3-D scientific
        data visualization. Its features include:
        
            * Visualization of scalar, vector and tensor data in 2 and 3 dimensions
        
            * Easy scriptability using Python
        
            * Easy extendability via custom sources, modules, and data filters
        
            * Reading several file formats: VTK (legacy and XML), PLOT3D, etc.
        
            * Saving of visualizations
        
            * Saving rendered visualization in a variety of image formats
        
            * Convenient functionality for rapid scientific plotting via mlab (see mlab
              documentation)
        
            * See the Mayavi Users Guide for more information.
        
        Unlike its predecessor MayaVi1_, Mayavi has been designed with scriptability
        and extensibility in mind from the ground up.  While the mayavi2 application
        is usable by itself, it may be used as an Envisage plugin which allows it to
        be embedded in user applications natively. Alternatively, it may be used as a
        visualization engine for any application.
        
        .. _MayaVi1: http://mayavi.sf.net
        
        
        Quick start
        ===========
        
        If you are new to Mayavi it is a good idea to read the `online user manual`_
        which should introduce you to how to install and use it.
        
        If you have installed Mayavi as described in the next section, you should be
        able to launch the ``mayavi2`` application and also run any of the examples
        in the examples directory.
        
        
        .. _online user manual: http://docs.enthought.com/mayavi/mayavi/
        
        Installation
        =============
        
        By itself Mayavi is not a difficult package to install but its dependencies
        are unfortunately rather heavy. However, many of these dependencies are now
        available as wheels on PyPI.  The two critical dependencies are,
        
          1. VTK_
          2. A GUI toolkit, either PyQt4_, PySide_, PySide2_, PyQt5_ or wxPython_.
        
        The latest VTK wheels are available on all the major platforms (Windows,
        MacOS, and Linux), but only for 64 bit machines. Python 3.x is fully supported
        on all these operating systems and Python 2.7.x on MacOS and Linux. If you are
        out of luck, and your platform is not supported then you will need to install
        VTK yourself using your particular distribution as discussed in the `General
        Build and Installation instructions
        <http://docs.enthought.com/mayavi/mayavi/installation.html#installing-ready-made-distributions>`_
        
        On Python 3.x you will need to install PyQt5_ and wheels are available for
        this. On 2.7.x you have more options, and can use PySide_, PyQt4_, and
        wxPython_. These can be installed from pip or from your package manager.
        
        Currently, Mayavi itself should work with the new wxPython 4.x. However,
        traitsui_, pyface_, and other ETS packages do not yet support it so the UI
        will not work correctly. Older versions should work. PyQt/PySide/PySide2
        should work largely out of the box.
        
        
        .. _PyQt5: https://pypi.org/project/PyQt5/
        .. _PySide: https://pypi.org/project/PySide
        .. _PySide2: https://wiki.qt.io/Qt_for_Python
        .. _PyQt4: https://pypi.org/project/PyQt4/
        .. _wxPython: https://pypi.org/project/wxPython/
        .. _VTK: https://www.vtk.org
        .. _traitsui: https://github.com/enthought/traitsui
        .. _pyface: https://github.com/enthought/pyface
        
        Latest stable release
        -----------------------
        
        As of the latest release, i.e. 4.6.0 and above, if you are using Python 3.x
        and are on a 64 bit machine, installation via pip_ is the easiest and is as
        follows::
        
          $ pip install mayavi
        
          $ pip install PyQt5
        
        Thats it!
        
        If you are unable to do this, read the documentation above and find a way to
        install VTK and a suitable UI toolkit and then repeat the above.
        
        If you are interested in the jupyter notebook support as well, do the
        following (after ensuring that you have jupyter installed of course)::
        
          $ jupyter nbextension install --py mayavi --user
          $ jupyter nbextension enable --py mayavi --user
        
        You will also need to have ipywidgets_ and ipyevents_ installed. These can be
        installed via pip_ or your favorite package manager.
        
        .. _pip: https://pip.pypa.io/en/stable/
        .. _ipywidgets: https://ipywidgets.readthedocs.io
        .. _ipyevents: https://github.com/mwcraig/ipyevents
        
        Bleeding edge
        --------------
        
        If you want to install the latest version of Mayavi from github, you can
        simply do the following::
        
          $ git clone https://github.com/enthought/mayavi.git
          $ cd mayavi
          $ pip install -r requirements.txt
          $ pip install PyQt5  # replace this with any supported toolkit
          $ python setup.py install  # or develop
        
        Add the jupyter nbextensions using the instructions in the section above and
        you should be good to go.
        
        Documentation
        ==============
        
        More documentation is available in the `online user manual`_ or in ``docs``
        directory of the sources. This includes a man page for the ``mayavi2``
        application, a users guide in HTML and PDF format and documentation for
        ``mlab``.
        
        More documentation in the form of workshop/tutorial material is available
        here:
        
        - https://github.com/prabhuramachandran/mayavi-tutorial
        - https://github.com/prabhuramachandran/mayavi-workshop
        
        Tutorial Videos
        ===============
        
        Here are some tutorial videos that you can watch to learn Mayavi:
        
        - SciPy 2018 Mayavi tutorial (3 hrs):
        
          - Video: https://www.youtube.com/watch?v=r6OD07Qq2mw
          - Material: https://github.com/prabhuramachandran/mayavi-tutorial
        
        
        Examples
        ========
        
        Examples are all in the ``examples`` directory of the source or the git clone.
        The docs and examples do not ship with the binary eggs. The examples directory
        also contains some sample data.
        
        
        Test suite
        ==========
        
        The basic test suites for tvtk and mayavi can be run using nose::
        
          nosetests -v tvtk/tests
          nosetests -v mayavi
        
        The integration tests::
        
          cd integrationtests/mayavi
          python run.py
        
        
        Bug tracker, mailing list etc.
        ==============================
        
        The bug tracker is available in `github
        <https://github.com/enthought/mayavi/issues>`_ Please provide info and details
        on platform, python, vtk and gui backends and their versions. If possible, a
        small example replicating the the problem.
        
        If you have questions you could ask on the `Mayavi-users mailing list
        <https://sourceforge.net/p/mayavi/mailman/mayavi-users/>`_. This is used by
        some folks and is not too active. Another mailing list that may be of use is
        the `ETS Users mailing list
        <https://groups.google.com/forum/#!forum/ets-users>`_. This is a more general
        list where a lot of folks experienced with the Enthought Tool Suite are
        available.
        
        Authors and Contributors
        ========================
        
        * Core contributors:
        
          Prabhu Ramachandran: primary author.
        
        * Previous contributors:
        
          Gaël Varoquaux: mlab, icons, many general improvements and maintenance.
        
          Deepak Surti: Upgrade to VTK 5.10.1, VTK 6.x with new pipeline.
        
        * Support and code contributions from Enthought Inc.
        
        * Patches from many people (see the release notes), including K K Rai and
          R A Ambareesha for tensor support, parametric source and image data.
        
          Many thanks to all those who have submitted bug reports and suggestions for
          further enhancements.
        
Platform: Windows
Platform: Linux
Platform: Mac OS-X
Platform: Unix
Platform: Solaris
Classifier: Development Status :: 5 - Production/Stable
Classifier: Intended Audience :: Developers
Classifier: Intended Audience :: Science/Research
Classifier: License :: OSI Approved :: BSD License
Classifier: Operating System :: MacOS
Classifier: Operating System :: Microsoft :: Windows
Classifier: Operating System :: OS Independent
Classifier: Operating System :: POSIX
Classifier: Operating System :: Unix
Classifier: Programming Language :: C
Classifier: Programming Language :: Python
Classifier: Topic :: Scientific/Engineering
Classifier: Topic :: Software Development
Classifier: Topic :: Software Development :: Libraries
Provides-Extra: app
