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May 23, 2024 · Welcome, this is the user guide for Mayavi, a application and library for interactive scientific data visualization and 3D plotting in Python. Getting started. You want to use an interactive application to visualize your data in 3D? Read the Mayavi application section.
Jan 30, 2014 · 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.
- Overview
- Vision
- Features
- Quick start
- Installation
- Documentation
- Tutorial Videos
- Examples
- Test suite
- Bug tracker, mailing list etc.
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Mayavi docs: http://docs.enthought.com/mayavi/mayavi/ TVTK docs: http://docs.enthought.com/mayavi/tvtk
Mayavi seeks to provide easy and interactive visualization of 3D data. It does this by the following:
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 a general purpose, cross-platform tool for 2-D and 3-D scientific data visualization. Its features include:
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.
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.
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,
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
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.
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
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 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.
The basic test suites for tvtk and mayavi can be run using nose:
The integration tests:
The bug tracker is available in github 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. 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. This is a more general list where a lot of folks experienced with the Enthought Tool Suite are available.
Mayavi is a cross-platform tool for 2-D and 3-D data visualization, with easy scriptability and extensibility. Learn how to install, use, and customize Mayavi with the online user manual, examples, and tutorials.
MayaVi is a scientific data visualizer written in Python, which uses VTK and provides a GUI via Tkinter. MayaVi was developed by Prabhu Ramachandran, is free and distributed under the BSD License.
May 23, 2024 · This section details the various ways of installing Mayavi. If you already have Mayavi up and running, you can skip this section. By itself Mayavi is not a difficult package to install but its dependencies are unfortunately rather heavy. Fortunately, many of these dependencies are now available as wheels on PyPI. The two critical dependencies are,
MayaVi is a free, cross platform, easy to use scientific data visualizer. It provides a GUI, supports various data formats and filters, and can be scripted or embedded in Python applications.
