Mayavi: a package for 3D visualization of scientific data Prabhu Ramachandran ∗ Ga¨el Varoquaux †‡ Introduction graphical application, along with simple but full- Mayavi is an open-source, general-purpose, 3D featured scripting is important because visualiza- scientific visualization package. It seeks to pro- tion of complex datasets is best done interactively, vide easy and interactive tools for data visual- as the user can examine the data visually, tweak ization that fit with the scientific user’s work- parameters and build the visualization to suit the flow. For this purpose, Mayavi provides several data. In addition, to enable batch processing and entry points: a full-blown interactive application; non-interactive use, Mayavi visualizations can be a Python library with both a MATLAB-like inter- driven without a user interface. The use of the face focused on easy scripting and a feature-rich Python language is central to answering multi- object hierarchy; widgets associated with these ple scientific use cases, as it is a powerful, yet objects for assembling in a domain-specific ap- easy-to-learn, programming language [1]. Thanks plication, and plugins that work with a general- to a growing number of high-quality scientific li- purpose application-building framework. braries [2, 3], Python has recently garnered sig- In this article, we present an overview of the var- nificant mind-share among scientists. Indeed, it ious features of Mayavi, we then provide insight lends itself to interactive use with simultaneous on the design and engineering decisions made in plotting [4, 5] that is ideal for scientific and data- implementing Mayavi, and finally discuss a few processing development. Mayavi brings power- novel applications. ful 3D scientific data visualization to this tightly- integrated environment. What is Mayavi? There are several excellent general-purpose 3D visualization programs that expose high-quality A unique integration with a scientific workflow Python interfaces, such as ParaView [6] or Mayavi is unlike most other visualization tools VisIt [7]. Unlike Mayavi, these tools support through a combination of factors. First of all, parallel data visualization as well as 4D datasets. the Mayavi project avoids domain-specific cases However, Mayavi differs from these tools by a and strives to build reusable, general-purpose, ab- tighter integration with the workflow of a typical arXiv:1010.4891v1 [cs.SE] 23 Oct 2010 stractions. This is important since different re- scientist using Python for numerical computation: search fields often need to solve similar problems. it uses familiar data structures and exposes all its Second, Mayavi exposes tools and objects that fit graphical user interfaces as components . First closely with a naive user’s expectation, and also of all, Mayavi operates naturally on numpy arrays, allows expert users to handle complex visualiza- the core data structure used in the main scientific tions. Finally, and most important, the project is Python projects. As detailed below, the entire more than just a visualization library since it pro- VTK API is wrapped with implicit conversion be- vides, in addition to the library, widgets, dialogs, tween VTK arrays and numpy arrays and the mlab plugins, and an application, to fit in various as- interface provides convenient functions to visu- pects of the scientific workflow. A rich interactive alize 3D data described by numpy arrays. This, ∗Department of Aerospace Engineering, IIT Bombay, along with the fact that Mayavi integrates well Mumbai, INDIA - 400 076 with IPython, makes it highly convenient for in- † Parietal team, INRIA Saclay Ile de France, Parc Orsay teractive work. Second, Mayavi relies on a reflex- Universit´e, 4 rue J. Monod, 91893 Orsay FRANCE ‡NeuroSpin/CEA Saclay, Bˆat 145, 91191 Gif-sur-Yvette ive object model in which each object can be used FRANCE as a component to create custom dialogs that em- 1 bed a Mayavi visualization. (ETS [8]) enables chy that maps with some simple rules to VTK users to create rich, interactive scientific applica- and forms the foundation of Mayavi. tions that support 2D and 3D plotting requiring TraitsUI/Envisage : The user interface of the only the knowledge of Python and object-oriented end-user application relies entirely on Traits programming. Thus Mayavi fills a valuable need and optionally on Envisage. Envisage is in the scientific computing ecosystem. an application-building framework, `ala the Eclipse framework , which is used for the ap- Powerful underlying technologies plication. At its core, Envisage is a system Mayavi is part of the ETS [8] and builds upon a for defining, registering, and using plugins. powerful stack of existing libraries. In this section Both Traits and Envisage can use wxPython we provide a very brief overview of these. or PyQt as a backend. Thus Mayavi can be used with both toolkits, although currently the VTK : The Visualization ToolKit [9] is one of wxPython backend is more developed and thus the best, actively-developed, general-purpose, more mature. open-source, visualization and graphics li- braries available. Packaging and licensing Numpy : The workhorse of scientific comput- A simple pipeline model for visualization ing with Python is the numpy array structure. VTK relies on an elaborate pipeline model that is This multidimensional numerical array trans- assembled to create a visualization. In an effort to forms Python into a high-level array language, to the user, Mayavi exposes a basic pipeline inter- similar to MATLAB. It is used as a common face: data is obtained from a data source, and the data container in most scientific libraries and user can add visualization modules to display the projects relying on Python. data in various ways, or filters to modify the data Traits : The Traits library before eventual visualization. Mayavi connects (http://code.enthought.com/projects/traits), the various components of the pipeline and, to an is the cornerstone of the ETS. Traits extend extent, also takes care of which components can Python object attributes and provide an be inter-connected. For example, a cloud of scat- elegant mechanism for attribute initialization, tered points cannot be visualized with a grid plane validation, delegation, notification (efficient since there is no fixed grid for these points. The callbacks on attribute modification), and visu- different sources, modules and filters are traited alization (through dialogs using wxPython or objects that all have associated dialogs and meth- Qt4). Henceforth, we refer to an object with ods that expose the underlying TVTK objects traits as a “traited object”. as much as possible without requiring a detailed knowledge of VTK. The Mayavi pipeline collapses TVTK : The Traited VTK library (TVTK) is an together several elements of a VTK pipeline, for automatically generated wrapper of VTK com- instance the Mayavi modules are made of VTK bined with Traits This is done by wrapping mappers, actors, and eventually widgets or even VTK-Python objects and providing a traits- filters when their use helps representing the data. enabled API with a more “Pythonic” feel . Finally, although loops in the pipeline are possi- All C++-style getters and setters are replaced ble, Mayavi the pipeline as a tree rather than by traits. VTK has its own C++-based ar- a graph (see Figure 1), to facilitate its manipula- ray structures, and the VTK-Python bindings tion, both through the interactive user interface, require tedious manipulations to copy or refer- and programmatically. ence the data from numpy arrays to VTK ar- rays. TVTK provides a seamless API where VTK arrays are converted dynamically from History of the project and to numpy arrays, using a view of the same Mayavi was created in 2001 [10] by P. Ramachan- memory where possible. In addition, because dran as an end-user application for scientific visu- of the use of Traits, all TVTK objects pro- alization. The name is a Sanskrit word meaning vide a default dialog to edit their properties. “magician”. The application was appreciated for TVTK is thus a very powerful object hierar- its ease of use and interactivity. However, it was 2 not easy to script from Python. During 2004– 2005, Enthought Inc. hired P. Ramachandran to write TVTK [11] and start work on a new ver- sion of Mayavi. The new version, “Mayavi2” [12], uses the tools developed at Enthought to focus on reuse and embedding. In 2007, G. Varoquaux joined the project. The project is rapidly gaining features and documentation while the usability is improved based on user feedback. In early 2008, TVTK and Mayavi were each awarded FOSS In- dia awards. Using Mayavi Mayavi can be used in different ways, and as such has several entry points. The mayavi2 application The interactive application, mayavi2, is an end- user tool that can be used without any program- ming knowledge. It provides an interface with Figure1: A view of the mayavi2 application showing menus and several panels to guide the user while the Mayavi logo: a Boy mathematical surface. On creating a visualization (see Figure 1). As de- the bottom right, an interactive IPython prompt, for scribed earlier in the overview, Mayavi presents prototyping scripts or exploring objects, can be seen. a simplified pipeline view of the visualization. On the upper left stands the tree representing the vi- Through the menus, data can be loaded from files, sualization pipeline. It features a source, here a grid of points created by numpy arrays, a PolyDataNormal or created with predefined objects such as a lay- filter used to calculate normals of the surface for a out of the Earth’s continents, parametric surfaces smooth rendering, and the Surface module, with defining for example a Klein bottle, etc. Subse- its corresponding module-manager node, used to quently, optional filtering may be performed on change the colors and legend of the surface. The the data, and visualization modules are added to dialog below the tree can be used to modify the se- create the visualization.