- Mayavi: 3D scientific data visualization and plotting in Python
Mayavi: 3D scientific data visualization and plotting in Python ¶ 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
- Installation — mayavi 4. 8. 3 documentation - Enthought
Under Windows the best way to install Mayavi is to install a full Python distribution, such as Enthought Canopy, Pythonxy, or Anaconda Note that for Pythonxy, you need to check in ‘ETS’ in the installer, when selecting components
- Using the Mayavi application — mayavi 4. 8. 3 documentation - Enthought
Run Mayavi in off-screen mode without any graphical user interface This is most useful for scripts that need to render images off-screen (for an animation say) in the background without an intrusive user interface popping up
- mlab: Python scripting for 3D plotting — mayavi 4. 8. 3 documentation
The mayavi mlab module, that we call mlab, provides an easy way to visualize data in a script or from an interactive prompt with one-liners as done in the matplotlib pylab interface but with an emphasis on 3D visualization using Mayavi2 This allows users to perform quick 3D visualization while being able to use Mayavi’s powerful features
- An overview of Mayavi — mayavi 4. 8. 3 documentation - Enthought
Use Mayavi as a plotting engine from simple Python scripts, for example from Ipython, in combination with numpy The mlab scripting API provides a simple way of using Mayavi in batch-processing scripts, see mlab: Python scripting for 3D plotting for more information on this
- Data representation in Mayavi — mayavi 4. 8. 3 documentation - Enthought
To retrieve the data displayed by Mayavi, to modify it via Python code, or to benefit from the data processing steps performed by the Mayavi filters, it can be useful to “open up” the Mayavi pipeline and understand how the data flows in it
- Example gallery — mayavi 4. 8. 3 documentation - Enthought
Advanced visualization examples ¶ Data visualization using the core Mayavi API, object-oriented, and with more fine control than mlab
- Plotting functions — mayavi 4. 8. 3 documentation - Enthought
import numpy from mayavi mlab import * def test_surf(): """Test surf on regularly spaced co-ordinates like MayaVi """ def f(x, y): sin, cos = np sin, np cos return sin(x + y) + sin(2 * x - y) + cos(3 * x + 4 * y) x, y = np mgrid[-7 :7 05:0 1, -5 :5 05:0 05] s = surf(x, y, f) #cs = contour_surf(x, y, f, contour_z=0) return s
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