MayaVi

A screenshot of the main window, with an example visualization

Developer(s)| Enthought
Initial release| 2019; 7 years ago (2019)
Stable release|

4.8.1 / October 18, 2022; 3 years ago (2022-10-18)[1]

Written in| Python, VTK, wxPython/Qt
Operating system| Linux, Mac OS X, Microsoft Windows
Available in| English
Type| Data visualization
License| BSD License
Website| docs.enthought.com/mayavi/mayavi/

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. It is cross-platform and runs on any platform where both Python and VTK are available (almost any Unix, Mac OS X, or Windows). MayaVi is pronounced as a single name, "Ma-ya-vee", meaning "magical" in Sanskrit. The code of MayaVi has nothing in common with that of Autodesk Maya or the Vi text editor.[2]

The latest version of MayaVi, called Mayavi2, is a component of the Enthought suite of scientific Python programs. It differs from the original MayaVi by its strong focus on making an interactive program and a reusable component for 3D plotting in Python. Although it exposes a slightly different interface and API than the original MayaVi, it now has more features.[3][4]

## Contents

* 1 Major features
* 2 Examples
* 2.1 Spherical harmonics
* 3 References
* 4 External links

## Major features

* visualizes computational grids and scalar, vector, and tensor data
* an easy-to-use GUI
* can be imported as a Python module from other Python programs or can be scripted from the Python interpreter
* supports volume visualization of data via texture and ray cast mappers
* support for any VTK dataset using the VTK data format
* support for PLOT3D data
* multiple datasets can be used simultaneously
* provides a pipeline browser, with which objects in the VTK pipeline can be browsed and edited
* imports simple VRML and 3D Studio scenes
* custom modules and data filters can be added
* exporting to PostScript files, PPM/BMP/TIFF/JPEG/PNG images, Open Inventor, Geomview OOGL, VRML files, Wavefront .obj files, or RenderMan RIB file

## Examples

### Spherical harmonics

The spherical harmonic function Y30(θ,φ)

from numpy import linspace, meshgrid, array, sin, cos, pi, abs
from scipy.special import sph_harm
from mayavi import mlab

theta_1d = linspace(0,   pi,  91)
phi_1d   = linspace(0, 2*pi, 181)

theta_2d, phi_2d = meshgrid(theta_1d, phi_1d)
xyz_2d = array([sin(theta_2d) * sin(phi_2d),
sin(theta_2d) * cos(phi_2d),
cos(theta_2d)])
l = 3
m = 0

Y_lm = sph_harm(m, l, phi_2d, theta_2d)
r = abs(Y_lm.real) * xyz_2d

mlab.figure(size=(700, 830))
mlab.mesh(r[0], r[1], r[2], scalars=Y_lm.real, colormap="cool")
mlab.view(azimuth=0, elevation=75, distance=2.4, roll=-50)
mlab.savefig("Y_%i_%i.jpg" % (l, m))
mlab.show()

## References

1. ↑ "mayavi · PyPI". https://www.pypi.org/project/mayavi/#history.
2. ↑ "MayaVi project page". SourceForge. http://mayavi.sourceforge.net/.
3. ↑ "MayaVi2 wiki page". http://scipy.org/Cookbook/MayaVi.
4. ↑ "MayaVi2 project page". http://docs.enthought.com/mayavi/mayavi/.

## External links

* on GitHub
* MayaVi on SourceForge.net

* v
* t
* e

Scientific software in Python

* NumPy
* SciPy
* matplotlib
* pandas
* scikit-learn
* scikit-image
* statsmodels
* MayaVi
* more

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