Package: mayavi
Mayavi docs:http://docs.enthought.com/mayavi/mayavi/TVTK docs:http://docs.enthought.com/mayavi/tvtkVisionMayavi 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).FeaturesMayavi 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 dimensionsEasy scriptability using PythonEasy extendability via custom sources, modules, and data filtersReading several file formats: VTK (legacy and XML), PLOT3D, etc.Saving of visualizationsSaving rendered visualization in a variety of image formatsConvenient functionality for rapid scientific plotting via mlab (see mlab
documentation)See the Mayavi Users Guide for more information.Unlike its predecessorMayaVi1, 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.Quick startIf you are new to Mayavi it is a good idea to read theonline user manualwhich 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 themayavi2application and also run any of the examples
in the examples directory.InstallationBy 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,VTKA GUI toolkit, eitherPyQt4,PySide,PySide2,PyQt5orwxPython.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 theGeneral
Build and Installation instructionsOn Python 3.x you will need to installPyQt5and wheels are available for
this. On 2.7.x you have more options, and can usePySide,PyQt4, andwxPython. 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.Latest stable releaseAs 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 viapipis the easiest and is as
follows:$ pip install mayavi

$ pip install PyQt5Thats 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 --userYou will also need to haveipywidgetsandipyeventsinstalled. These can be
installed viapipor your favorite package manager.Bleeding edgeIf 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 developAdd the jupyter nbextensions using the instructions in the section above and
you should be good to go.DocumentationMore documentation is available in theonline user manualor indocsdirectory of the sources. This includes a man page for themayavi2application, a users guide in HTML and PDF format and documentation formlab.More documentation in the form of workshop/tutorial material is available
here:https://github.com/prabhuramachandran/mayavi-tutorialhttps://github.com/prabhuramachandran/mayavi-workshopTutorial VideosHere are some tutorial videos that you can watch to learn Mayavi:SciPy 2018 Mayavi tutorial (3 hrs):Video:https://www.youtube.com/watch?v=r6OD07Qq2mwMaterial:https://github.com/prabhuramachandran/mayavi-tutorialExamplesExamples are all in theexamplesdirectory 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 suiteThe basic test suites for tvtk and mayavi can be run using nose:nosetests -v tvtk/tests
nosetests -v mayaviThe integration tests:cd integrationtests/mayavi
python run.pyBug tracker, mailing list etc.The bug tracker is available ingithubPlease 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 theMayavi-users mailing list. This is used by
some folks and is not too active. Another mailing list that may be of use is
theETS Users mailing list. This is a more general
list where a lot of folks experienced with the Enthought Tool Suite are
available.Authors and ContributorsCore 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.