Mayavi: 3D scientific data visualization and plotting in Python

		Using the Mayavi application Understanding and using the Mayavi interactive application
		Python scripting for 3D plotting The simple scripting API to Mayavi
		Gallery and examples Example gallery of visualizations, with the Python code that generates them

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.
• You know Python and want to use Mayavi as a Matlab or pylab replacement for 3D plotting and data visualization with numpy? Get started with the mlab section.
• Sources of inspiration may be found in the example_gallery, with example Python code.

User guide: full table of contents

• An overview of Mayavi
  • Introduction
    • What is Mayavi2?
    • Technical details
  • Using Mayavi as an application, or a library?
  • Scenes, data sources, and visualization modules: the pipeline model
  • Loading data into Mayavi
• Installation
  • Installing ready-made distributions
  • Requirements for manual installs
  • Doing it yourself: Python packages: Eggs
    • Installing with easy_install
    • Step-by-step instructions to install with eggs under Windows
  • Under Mac OSX Snow Leopard
  • The bleeding edge: SVN
  • Testing your installation
  • Troubleshooting
• Using the Mayavi application
  • Tutorial examples to learn Mayavi
    • Parametric surfaces: a simple introduction to visualization
    • Loading scalar data: the heart.vtk example
    • Visualizing rich datasets: the fire_ug.vtu example
    • Using Mayavi with scipy
    • Exploring a vector field
  • General layout of UI
  • Visualizing data
    • Modules
    • Filters
  • Interaction with the scene
    • Mouse interaction
    • Keyboard interaction
  • From interactive usage to scripting
    • The embedded Python interpreter
    • Recording Mayavi actions to a script
  • Command line arguments
• mlab: Python scripting for 3D plotting
  • A demo
  • 3D Plotting functions for numpy arrays
    • 0D and 1D data
    • 2D data
    • 3D data
  • Changing the looks of the visual objects created
    • Adding color or size variations
    • Changing the scale and position of objects
    • Changing object properties interactively
  • Figures, legends, camera and decorations
    • Handling several figures
    • Figure decorations
    • Moving the camera
  • Running mlab scripts
    • Using mlab interactively
    • Using together with Matplotlib’s pylab
    • In scripts
  • Animating the data
  • Assembling pipelines with mlab
    • Data sources
    • Modules and filters
  • Case studies of some visualizations
    • Visualizing volumetric scalar data
    • Visualizing a vector field
• Advanced use of Mayavi
  • Organisation of Mayavi visualizations: the pipeline
    • Anatomy of a Mayavi pipeline
    • The link between different Mayavi entry points
    • A pipeline example examined
  • Data representation in Mayavi
    • Introduction to TVTK datasets
    • The flow of data
    • Retrieving the data from Mayavi pipelines
    • Dissection of the different TVTK datasets
    • Inserting TVTK datasets in the Mayavi pipeline.
  • Objects populating the Mayavi pipeline
    • Scene
    • Source
    • Filter
    • ModuleManager: Colors and legends node
    • Module
    • Engine
    • Base class: PipelineBase
    • Class hierarchy
  • Advanced Scripting with Mayavi
    • Design Overview: Mayavi as a visualization framework
    • Scripting the mayavi2 application
    • Using the Mayavi envisage plugins
• Building applications using Mayavi
  • Custom interactive dialogs
    • Embedding a Mayavi scene in a Traits dialog
    • A scene, with mlab embedded
    • Making the visualization live
  • Integrating in a WxPython application
  • Integrating in a PyQt application
• Tips and Tricks
  • Off screen rendering
    • Avoiding the rendering window
    • Platform Summary
    • Rendering using the virtual framebuffer
    • Using VTK with Mesa for pure software rendering
  • Extending Mayavi with customizations
  • Customizing Mayavi2
  • Scripting Mayavi without using Envisage
  • Computing in a thread
  • Polling a file and auto-updating Mayavi
  • Serving Mayavi on the network
    • TCP server: the serve_tcp function
    • UDP server: the serve_udp function
  • Animating a visualization
    • Animating a series of images
    • Making movies from a stack of images
  • Scripting from the command line
  • Texture mapping actors
  • Shifting data and plotting
  • Using the UserDefined filter
  • Sharing the same data between scenes
    • Using mlab
    • Using the core Mayavi API
  • Changing the interaction with a scene
  • Accelerating a Mayavi script
• Miscellaneous
  • Getting help
  • Tests for Mayavi
  • Helping out
    • Development quick start
    • Improving the documentation
• Mayavi API reference
  • Pipeline base objects
    • Scene
    • Source
    • Filter
    • ModuleManager
    • Module
    • PipelineBase
    • Engine
  • Main view and UI objects
    • Scene UIs: DecoratedScene and MayaviScene
    • SceneEditor
    • MlabSceneModel
    • EngineView and EngineRichView
• Known bugs and issues
• Changelog
  • Mayavi 3.3.2 (not yet released)
  • Mayavi 3.3.1 (Feb 24, 2010)
    • Enhancements
    • Fixes
  • Mayavi 3.3.0 (July 15, 2009)
    • Enhancements
    • Fixes
  • Mayavi 3.2.0 (March 23, 2009)
  • Mayavi 3.1.0
  • Mayavi 3.0.3
  • Mayavi 3.0.1 and 3.0.2
  • Mayavi 3.0.0

Index and search

• Index
• Search Page

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