For example, they can be used to specify a look-up table for coloring scientific data. Mappers transform data into graphics primitives.All the processing algorithms that come with VTK are implemented as filters and can be freely chained together. For example a vtkCuttercuts the output of the previous object in the algorithms using an implicit function, e.g., a plane. Filters transform the output of either sources or other filters to something new.For example, a vtkConeSource creates a 3D cone, and a vtkSTLReader reads *.stl 3D geometry files. Sources are at the very beginning of the pipeline and create “something out of nothing”.The basic outline of this concept is shown here: The architecture of VTK revolves around a powerful pipeline concept. The VTK case studies show the wide range of suitable applications.
In my current project with a dental research company, I’m utilizing VTK for mesh based processing tasks within a Qt-based, CAD-like application. It’s capabilities, however, don’t stop there, as over time image and mesh processing algorithms have been added as well. The open source library VTK contains a solid processing and rendering pipeline with many sophisticated visualization algorithms. Finally I’ll list the strong points of the library, as well as the weak spots I encountered. In this tutorial I will give a quick introduction to VTK and its pipeline architecture, and go on to discuss a real-life 3D visualization example using data from a simulated fluid in an impeller pump. How do we understand and interpret the huge amounts of data coming out of these simulations? How do we visualize potential gigabytes of data, such as data with millions of grid points within a large simulation?ĭuring my work on similar problems for my Master’s Thesis, I came into contact with the Visualization Toolkit, or VTK – a powerful graphics library specialized for data visualization. His tutorial makes an important point about open source tools and the role they can play in easily processing data and acquiring results.īut as soon as we’ve solved all these complex differential equations another problems comes up. In his recent article on Toptal’s blog, skilled data scientist Charles Cook wrote about scientific computing with open source tools.
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