Introduction to Scientific Visualization with VTK

1. Introduction to Scientific Visualization with VTK November 16 University of Chicago, CS-341 Terrence L. Disz Math and Computer Science Division Argonne National Laboratory disz@mcs.anl.gov

2. Visualization • Interpreting data in visual terms • Data is too complex • Too much data • Not a substitute for statistical analysis, sampling, filtering and other quantitative methods • Make use of human sensory abilities • Pattern Recognition • Trend discovery

3. Graphs are one kind of visualization

4. We are interested in more complex data • Multi-dimensional • Complex geometry • Computed or collected • Simulations • MRI, CAT, etc • Microscopic to Galactic data collections

5. Some examples Nuclear, Quantum, and Molecular Modeling Structures, Fluids and Fields Advanced Imaging and Data Management

6. More Examples Surface Rendering with vTK Volume Rendering with SGI Infinite Reality Engine

7. Even More Examples: Astro Physics

8. And, Computational Fluid Dynamics

9. Some Clarification • Imaging • Computer Graphics • Visualization • Virtual Reality • Stereo 3D, Immersion, User tracking

10. Large Scale Virtual Reality Projection Wall The CAVE Immersadesk

11. Immersive Virtual Reality Visualization

12. Imaging, or Image Processing • Digital Image - set of discrete sample points • Picture elements (Pixel) • Gray level value • Captured or computer generated • Represents a continuous function • Processing • Edge detection, Feature extraction • Contrast enhancement • Projections, transformations

13. Image Processing; Edge Detection Original Image Vertical Edges Norm of the gradient Horizontal Edges http://robotics.eecs.berkeley.edu/~mayi/imgproc/cademo.html

14. Computer Graphics • Creating images with a computer - Paint and draw Red Boots Tom Nast Run Run Run Douglas Lockyer Paper Cranes George Ho

15. Computer Graphics • Creating images with a computer - 3d © 1998 Pixar Animation Studios, All Rights Reserved. www.pixar.com http://www.websharx.com:80/~dfarmer/gallry1.htm

16. Computer Graphics • Components • Model • Geometry • Surface properties • Objects or abstract volumes • Lighting • Number, position, properties • Viewpoint • Projection

17. Rendering • Converting graphical data into images • Visualization • Transforms data into graphical data (primitives) • Points, triangles, etc • Graphical primitives are rendered • Image rendering, Object rendering, Volume rendering

18. Image Based Rendering • Painters Algorithm • Draw polygons from back to front • Scan Line • Look through each pixel to find first ploygon intersected • Z-buffer • Assign z-value to each polygon, draw closest one, pixel by pixel

19. Object Based Rendering: Ray Tracing http://gandalf.iuk.tu-harburg.de/hypgraph/raytrace/rtrace1.htm

20. Volume Rendering • Displays all of the 3-D data at once, like an X-ray: Denser parts are more opaque. • User controls the density of various data values.

21. Computer Graphics: Coordinate Systems • Model • local coordinate system • World • Where the models are placed • View • Logical Image Plane • Display • X,Y Pixel locations

22. Computer Graphics: Transformations Translation Scaling Rotation

23. Transformation Matrix To translate the point (x,y,z) by the vector (tx, ty, tz) Transformation Matrix for Translation

24. Scaling, Rotation Rotate about x Scaling Matrix

25. Visualization is more than computer graphics • Data is 3 Dimensional or greater • Data transformations occur frequently • Feedback from vis system causes data transformations • Interactive • Exploration, discovery, understanding

26. Using VTK for Scientific Visualization • The VisualizationToolkit, 2nd edition • Schroeder, Martin, Lorenson • Prentice Hall • VTK Software • http://www.kitware.com/vtk.html • Software, book, FAQ’s, discussion lists, examples, etc • /opt/courses/anl/vtk • graphics/examplesCxx

27. VTK - An OO Scientific Visualization, Processing and Graphics System • The VTK Model - a visualization pipeline Data Object Process Object Display (Computational Methods, Measured Data) Source Filter Mapper Procedural, Reader Transforms the data Creates Geometric Primitives

28. The VTK Model - A simple example Sphere Source Elevation Filter Mapper vtkSphereSource *sphere = vtkSphereSource::new(); vtkElevationFilter *colorIt = vtkElevationFilter::New(); colorIt->SetInput(Sphere->GetOutput()); vtkDataSetMapper *mapper = vtkDataSetMapper::New(); mapper->SetInput(colorIt->GetOutput()); vtkActor *actor = vtkActor::New(); actor->SetMapper(mapper);

29. Data Representation - Cells & Points • Topology • Shape such as triangle, tetrahedron • Geometry • Point Coordinates assigned to a topology • Data Attributes • Data associated with topology or geometry

30. Vertex Polyvertex Line Polyline Triangle Triangle Strip Quadrilateral Polygon Tetrahedron Hexahedron Voxel Cells specify Topology

31. Cells • Cell is defined by an ordered list of points • Triangle, quadrilateral points specified counter clockwise • Others as shown 6 3 7 5 4 1 3 2 2 Hexahedron 1 Tetrahedron 0 0

32. Meshes are made of Cells • Cells can be many different shapes and sizes • e.g. in 2D: Triangles, Quadrilaterals, etc • e.g. in 3D Tetrahedra, Hexahedra, Pyramids, etc. • Meshes can consist of one or more types of cells Quadrilateral Prism Triangle Tetrahedron Hexahedron Mesh

33. VTK Dataset Types • vtkStructuredPoints • vtkRectilinearGrid • vtkStructuredGrid • vtkPolyData • vtkUnstructuredGrid • Methods for reading and writing

34. Datasets • Organizing structure plus attributes • Structured points • Rectilinear Grid • Structured Grid

35. Unstructured Grid A collection of vertices, edges, faces and cells whose connectivity information must be explicitly stored

36. How are unstructured meshes different than regular grids? • Regular Grids • e.g., Cartesian grids, logically rectangular grids • mesh info accessed implicitly using grid point indices • Efficient in both computation and storage • typically use finite difference discretization • Unstructured Meshes • mesh connectivity information must be stored • Incurs memory and computational cost • handles complex geometries and grid adaptivity • typically use finite volume or finite element discretization • mesh quality becomes a concern

37. Data Attributes Assigned to points(VTK) or cells • Scalars • Vector • Magnitude and direction • Normal • a vector of magnitude 1 • Used for lighting • Texture Coordinate • Mapping data points into a texture space • Tensor

38. 1 10 4 8 Visualization of Attributes • Scalar • Color Mapping • Countouring • 3D Isosurface Contour Value of 5

39. Visualization of Attributes • Vectors • Oriented Lines • Oriented Glyphs • Streamlines

40. The VTK Model - a visualization pipeline Data Object Process Object Display (Computational Methods, Measured Data) Source Filter Mapper Procedural, Reader Transforms the data Creates Geometric Primitives

41. Some Transformations • Decimation • Reduce polygon count, preserving topology

42. Some Transformations • Contouring • Create boundaries (contours) between regions • Triangulate • Create topology from unstructured points

43. #include "vtk.h" main () { vtkRenderer *renderer = vtkRenderer::New(); vtkRenderWindow *renWin = vtkRenderWindow::New(); renWin->AddRenderer(renderer); vtkRenderWindowInteractor *iren = vtkRenderWindowInteractor::New(); iren->SetRenderWindow(renWin); vtkSphereSource *sphere = vtkSphereSource::New(); sphere->SetPhiResolution(12); sphere->SetThetaResolution(12); vtkElevationFilter *colorIt = vtkElevationFilter::New(); colorIt->SetInput(sphere->GetOutput()); colorIt->SetLowPoint(0,0,-1); colorIt->SetHighPoint(0,0,1); vtkDataSetMapper *mapper = vtkDataSetMapper::New(); mapper->SetInput(colorIt->GetOutput()); vtkActor *actor = vtkActor::New(); actor->SetMapper(mapper); renderer->AddActor(actor); renderer->SetBackground(1,1,1); renWin->SetSize(450,450); renWin->Render(); A VTK PROGRAM

44. // interact with data iren->Start(); // Clean up renderer->Delete(); renWin->Delete(); iren->Delete(); sphere->Delete(); colorIt->Delete(); mapper->Delete(); actor->Delete(); }

45. Your Assignment • Use output from the 11/2 assignment or use our data • sol.22.22.22.out • Compile and run the converter program to transform the data into a vtk dataset • converter sol.22.22.22.out 22 22 22 • Compile and Run the supplied VTK vis program on the data • Sample.C

46. Your Assignment • Make more runs, modifying the thresholds • Add a third cutting plane and rerun your test data • Write a short report explaining what happened

47. The Output

48. Assignment Resource Location • ~disz/assignment • Sample data • makefile • converter program • Vis app