Scientific Visualization with Para View Ray Gasser raygbu

Scientific Visualization with Para. View Ray Gasser rayg@bu. edu IS&T Scientific Visualization Tutorial – Spring 2010

Para. View Parallel Visualization Application – Multi-platform visualization application • • built on top of VTK extensible architecture via plugins rich scripting support through Python binaries available for Window, OSX, and Linux – Supports distributed computation of large datasets • runs on distributed and shared memory parallel systems • also runs on single processor system • Client/Server model – – Open source Standards based Active developer community Professional support services available from Kitware IS&T Scientific Visualization Tutorial – Spring 2010

Para. View - User Interface IS&T Scientific Visualization Tutorial – Spring 2010

IS&T Scientific Visualization Tutorial – Spring 2010

Para. View - Menus – File menu • handles various tasks such as opening data files, saving data files, loading state files, saving screenshots, saving animations, and fileserver connections. IS&T Scientific Visualization Tutorial – Spring 2010

Para. View - Menus – Edit menu • provides control settings for Para. View, undo and redo functions, allows you to change pipeline topology, and allows you to configure how the mouse interacts with the 3 D view. IS&T Scientific Visualization Tutorial – Spring 2010

Para. View - Menus – View menu • allows you to modify the camera and center of rotation for the 3 D view. The view menu also allows you to toggle the visibility of the toolbars, inspectors, and views. IS&T Scientific Visualization Tutorial – Spring 2010

Para. View - Menus – Sources menu • shows the various sources you can use to create a data set from within Para. View itself. A source is an object that creates data without using another data set or a data file as input. IS&T Scientific Visualization Tutorial – Spring 2010

Para. View - Menus – Filters menu • provides a list of available filters you can use to process data sets. • organized by recent, common, data analysis, temporal, and alphabetical. • The most commonly used filters, located under the Common subdirectory, are also located on the Common Filters Toolbar. • The filters are context sensitive and will only be available for selection if an appropriate data set has been loaded first and selected in the Pipeline Browser. IS&T Scientific Visualization Tutorial – Spring 2010

Para. View - Menus – Animation menu • provides controls for moving between frames in an animation that has been previously created. IS&T Scientific Visualization Tutorial – Spring 2010

Para. View - Menus – Tools menu • provides access to various tasks • creating and managing custom filters • creating a lookmark (a particular camera view) • linking properties of one object to another object • linking the camera in one view window to a camera in another view window • managing plugins, testing, and debugging. IS&T Scientific Visualization Tutorial – Spring 2010

Para. View - Menus – Help menu • provides information on the Para. View version, information on client server connections, and provides access to the online manual. • You can also visit the online version of the Para. View documentation: http: //paraview. org/Online. Help. Current/ IS&T Scientific Visualization Tutorial – Spring 2010

Para. View - Help IS&T Scientific Visualization Tutorial – Spring 2010

Para. View – Loading a state file Unix Shell: katana: % cd materials/Demos/Contours katana: % paraview Para. View: File -> Load State (isosurface. pvsm) IS&T Scientific Visualization Tutorial – Spring 2010

Para. View – Interface – Pipeline Browser • located in the upper left corner of the user interface • allows you to build a visualization pipeline • allows you to interact with the current visualization pipeline • top of the pipeline browser is the name of the server to which Para. View is connected • below the server name is a tree structure representing each of the reader, source, and filter objects that are in the visualization pipeline. IS&T Scientific Visualization Tutorial – Spring 2010

Para. View – Interface – Object Inspector • located beneath the Pipeline Browser in the user interface • contains controls and information for the reader, source, or filter object selected in the Pipeline Browser • allows you to interact with the current visualization pipeline • content changes based upon the specific object selected IS&T Scientific Visualization Tutorial – Spring 2010

Para. View – Interface – Object Inspector Tabs • There are three tabs in the Object Inspector: • Properties • Display • Information • The Properties Tab contains controls for specifying various parameters of the object selected in the Pipeline Browser. • Here is an example of what is shown in the Properties Tab for a Contour filter. IS&T Scientific Visualization Tutorial – Spring 2010

Para. View – Interface – Object Inspector Tabs • The Display Tab contains controls for setting the appearance of the object selected in the Pipeline Browser. • grouped into several sections: View, Color, Slice, Style, Edge Style, Annotation, Lighting, and Transformation. • Here is an example of what is shown in the Display Tab for a Contour filter. IS&T Scientific Visualization Tutorial – Spring 2010

Para. View – Interface – Object Inspector Tabs • The Information Tab contains statistical information about the output of the object selected in the Pipeline Browser. • Here is an example of what is shown in the Information Tab for a Contour filter. IS&T Scientific Visualization Tutorial – Spring 2010

Para. View - Models Visualization Model – Same as VTK • Uses a data flow approach • Data Objects and Process Objects (filters) connected to form a visualization pipeline – Pipeline • Visible in the Pipeline Browser • Built by loading data and attaching filters from menu Graphics Model – Same as VTK • Transforms graphical data into pictures • core objects: Actors, Lights, Camera, Transforms, Lookup tables, Renderer – Controlled via object inspector and GUI IS&T Scientific Visualization Tutorial – Spring 2010

Characteristics of Data is discrete – Interpolation functions generate data values in between known points Structure may be regular or irregular – Regular (structured) • need to store only beginning position, spacing, number of points • smaller memory footprint per cell (topology can be generated on the fly) • examples: image data, rectilinear grid, structured grid – Irregular (unstructured) • information can be represented more densely where it changes quickly • higher memory footprint (topology must be explicitly written) but more freedom • examples: polygonal data, unstructured grid IS&T Scientific Visualization Tutorial – Spring 2010

Characteristics of Data has a topological dimension – determines methods for visualization – determines data representation – examples: • • 0 D - points 1 D - lines/Curves 2 D - surfaces 3 D - volumes Data is organized into datasets for visualization – Datasets consist of two pieces • organizing structure – cells (topology) – points (geometry) • data attributes associated with the structure – File format derived from organizing structure IS&T Scientific Visualization Tutorial – Spring 2010

Organizing Structure (Topology) Topology – the way in which constituent parts are interrelated or arranged – specified by one or more cells (types vary with visualization packages) • • • vertex - (0 D) point polyvertex - (0 D) arbitrarily ordered list of points line - (1 D) defined by two points polyline - (1 D) ordered list of one or more connected lines triangle - (2 D) ordered list of three points triangle strip - (2 D) ordered list of n + 2 points (n is the number of triangles) polygon - (2 D) ordered list of three or more points lying in a plane pixel - (2 D) ordered list of four points with geometric constraints quadrilateral - (2 D) - ordered list of four points lying in a plane tetrahedron - (3 D) ordered list of four nonplanar points voxel - (3 D) ordered list of eight nonplanar points with geometric constraints hexahedron - (3 D) ordered list of eight nonplanar points IS&T Scientific Visualization Tutorial – Spring 2010

Examples of Cell Types IS&T Scientific Visualization Tutorial – Spring 2010

Organizing Structure (Geometry) Geometry – point coordinates assigned to a topology in 3 D space – represented by points – example: (0 0 0), (0 1 0), (1 0 0) would be the geometry for a triangle IS&T Scientific Visualization Tutorial – Spring 2010

Examples of Dataset Types IS&T Scientific Visualization Tutorial – Spring 2010

Examples of Dataset Types (cont) Unstructured Points – no topology and irregular geometry – examples: vertex, polyvertex – applications: data with no inherent structure Polygonal Data – irregular in both topology and geometry – examples: vertices, polyvertices, lines, polygons, triangle strips Unstructured Grid – irregular in both topology and geometry – examples: any combination of cells – applications: finite element analysis, structural design, vibration IS&T Scientific Visualization Tutorial – Spring 2010

Examples of Dataset Types (cont) XML – much more complicated than the dataset types described above, but supports many more features – provides the user with the ability to extend a file format with application specific tags – the XML dataset has support for compression, portable binary encoding, random access, byte ordering, and multiple file representation of piece data IS&T Scientific Visualization Tutorial – Spring 2010

Data Attributes Data attributes associated with the organizing structure – Scalars • single valued • examples: temperature, pressure, density, elevation – Vectors • magnitude and direction • examples: velocity, momentum – Normals • direction vectors (magnitude of 1) used for shading – Texture Coordinates • used to map a point in Cartesian space into 1, 2, or 3 D texture space • used for texture mapping – Tensors (generalizations of scalars, vectors and matrices) • rank 0 ( scalar), rank 1 (vector), rank 2 (matrix), rank 3 (3 D rectangular array) • examples: stress, strain IS&T Scientific Visualization Tutorial – Spring 2010

File Format – Structured Grid Editor density. vtk: # vtk Data. File Version 3. 0 vtk output ASCII DATASET STRUCTURED_GRID DIMENSIONS 57 33 25 POINTS 47025 float 2. 667 -3. 77476 23. 8329 2. 94346 -3. 74825 23. 6656 3. 21986 -3. 72175 23. 4982 3. 50007 -3. 70204 23. 3738 3. 9116 -3. 72708 23. 5319 4. 1656 -3. 69529 23. 3312. . . POINT_DATA 47025 SCALARS Density float LOOKUP_TABLE default 0. 498983 0. 376668 0. 333115 0. 311612 0. 267114 0. 639897 0. 479756 0. 477011 0. 461867 0. 428373 0. 639897 0. 608989 0. 570884 0. 510595 0. 443823 0. 407467 0. 376066 0. 34614. . . VECTORS Momentum float 00000 0 0 0 64. 5673 0 0 00000. . . IS&T Scientific Visualization Tutorial – Spring 2010

Example – Loading data Para. View: 1. disconnect from Server File -> Disconnect this clears the pipeline 2. open data file File -> Open (density. vtk) 3. click Apply in Object Inspector IS&T Scientific Visualization Tutorial – Spring 2010

Clipping, Cutting, Subsampling Modeling Algorithms - Clipping • can reveal internal details of surface • Para. View - Clip Filter - Cutting/Slicing • cutting through a dataset with a surface • Para. View - Slice Filter - Subsampling • reduces data size by selecting a subset of the original data • Para. View - Extract. Subset Filter IS&T Scientific Visualization Tutorial – Spring 2010

Example – Clipping Para. View: 1. disconnect from Server File -> Disconnect 2. open data file File -> Open (density. vtk) 3. apply Clip filter to density. vtk click on density. vtk in pipeline Filter -> Clip IS&T Scientific Visualization Tutorial – Spring 2010

Example – Cutting/Slicing Para. View: 1. disconnect from Server File -> Disconnect 2. open data file File -> Open (density. vtk) 3. apply Slice filter to density. vtk click on density. vtk in pipeline Filter -> Slice IS&T Scientific Visualization Tutorial – Spring 2010

Example – Subsampling Para. View: 1. disconnect from Server File -> Disconnect 2. open data file File -> Open (density. vtk) 3. apply Extract Subset filter to density. vtk click on density. vtk in pipeline Filter -> Extract Subset 4. apply Threshold filter to Extract. Subset click on Extract. Subset filter Filter -> Threshold IS&T Scientific Visualization Tutorial – Spring 2010

Color Mapping Scalar Algorithms – Color Mapping • maps scalar data to colors • implemented by using scalar values as an index into a color lookup table • specify a HSVA (Hue-Saturation-Value-Alpha) ramp and then generate the colors in the table by using linear interpolation into the HSVA space – Para. View • Color panel in Display tab of object inspector of data – Color by – Edit Color Map IS&T Scientific Visualization Tutorial – Spring 2010

Example – Color Mapping 1. disconnect from Server File -> Disconnect 2. open data file File -> Open (subset. vtk) 3. go to the color section in the Display Tab in the Object Inspector The "Color by" menu lists the names of the attribute arrays. Selecting an array name causes the dataset to be colored based on the underlying scalar values in that array. *** make sure the Compute Scalars checkbox in the Contour section of Property Tab is selected IS&T Scientific Visualization Tutorial – Spring 2010

Example – Color Mapping (cont) Para. View: 1. The color map may be edited in the Color Scale Editor window which appears when you click the Edit Color Map button in the Color section of the Display Tab. 2. Another way to change the mapping of data values to colors is by setting the Data Range. -- The default Data Range is set from the minimum data value in the data set to the maximum data value. -- click on the Rescale Range button to explicitly set these values. The values between the minimum and maximum are then linearly interpolated into the color table. IS&T Scientific Visualization Tutorial – Spring 2010

Contouring Scalar Algorithms (cont) – Contouring • construct a boundary between distinct regions, two steps: – explore space to find points near contour – connect points into contour (2 D) or surface (3 D) • 2 D contour map (isoline): – applications: elevation contours from topography, pressure contours (weather maps) from meteorology 3 D isosurface: • 3 D isosurface: – applications: tissue surfaces from tomography, constant pressure or temperature in fluid flow, implicit surfaces from math and CAD – Para. View • Contour Filter IS&T Scientific Visualization Tutorial – Spring 2010

Example – Isoline / 2 D Contours Para. View: 1. disconnect from Server File -> Disconnect 2. open data file File -> Open (subset. vtk) 3. apply Contour filter to subset. vtk click on subset. vtk in pipeline Filter -> Contour 4. to color the contour line based upon its scalar value and the current color map, make sure the Compute Scalars checkbox in the Contour section of the Properties tab is selected IS&T Scientific Visualization Tutorial – Spring 2010

Example – Isosurface / 3 D Contours Para. View: 1. disconnect from Server File -> Disconnect 2. open data file File -> Open (density. vtk) 3. apply Contour filter to density. vtk click on density. vtk in pipeline Filter -> Contour IS&T Scientific Visualization Tutorial – Spring 2010

Scalar Generation Scalar Algorithms (cont) – Scalar Generation • extract scalars from part of data • example: extracting z coordinate (elevation) from terrain data to create scalar values – Para. View • Elevation Filter IS&T Scientific Visualization Tutorial – Spring 2010

Example – Scalar Generation Para. View: 1. disconnect from Server File -> Disconnect 2. open data file File -> Open (honolulu. vtk) 3. apply Elevation filter to density. vtk click on honolulu. vtk in pipeline Filter -> Elevation IS&T Scientific Visualization Tutorial – Spring 2010

Hedgehogs Vector Algorithms – Hedgehogs • oriented scaled line for each vector • scale indicates magnitude • color indicates magnitude, pressure, temperature, or any variable – Para. View • Glyph Filter – Set type to line IS&T Scientific Visualization Tutorial – Spring 2010

Example – Hedge. Hogs Para. View: 1. disconnect from Server File -> Disconnect 2. open data file File -> Open (density. vtk) 3. apply Glyph filter to density. vtk click on density. vtk in pipeline Filter -> Glyph 4. in the Object Inspector (Properties Tab) set the “Scalars” menu to Density set the “Vectors” menu to Momentum set the “Glyph Type” to Line IS&T Scientific Visualization Tutorial – Spring 2010

Oriented Glyphs Vector Algorithms (cont) – Oriented Glyphs • orientation indicates direction • scale indicates magnitude • color indicates magnitude, pressure, temperature, or any variable – Para. View • Glyph Filter – Set type to arrow IS&T Scientific Visualization Tutorial – Spring 2010

Example – Oriented Glyphs Para. View: 1. disconnect from Server File -> Disconnect 2. open data file File -> Open (density. vtk) 3. apply Glyph filter to density. vtk click on density. vtk in pipeline Filter -> Glyph 4. in the Object Inspector (Properties Tab) set the “Scalars” menu to Density set the “Vectors” menu to Momentum set the “Glyph Type” to Arrow IS&T Scientific Visualization Tutorial – Spring 2010

Field Lines Vector Algorithms (cont) – Field Lines • Fluid flow is described by a vector field in three dimensions for steady (fixed time) flows or four dimensions for unsteady (time varying) flows • Three techniques for determining flow – Pathline (Trace) • tracks particle through unsteady (time-varying) flow • shows particle trajectories over time • rake releases particles from multiple positions at the same time instant • reveals compression, vorticity – Streamline • tracks particle through steady (fixed-time) flow • holds flow steady at a fixed time • snapshot of flow at a given time instant – Streakline • particles released from the same position over a time interval (time-varying) • snapshot of the variation of flow over time • example: dye steadily injected into fluid at a fixed point IS&T Scientific Visualization Tutorial – Spring 2010

Field Lines Streamlines • Lines show particle flow • Para. View - Stream. Tracer Filter Streamlets • half way between streamlines and glyphs • Para. View - Stream. Tracer and Glyph Filters Streamribbon • rake of two particles to create a ribbon • Para. View - Stream. Tracer and Ribbon Filters Streamtube • circular rake of particles to create a tube • Para. View - Stream. Tracer and Tube Filters IS&T Scientific Visualization Tutorial – Spring 2010

Stream Tracer Filter Stream. Tracer Filter • generates streamlines in vector field from collection of seed points • first need to set up the integrator to do the numerical integration • next need to specify the seeds points IS&T Scientific Visualization Tutorial – Spring 2010

Example – Streamlines Para. View: 1. open data file File -> Open (density. vtk) 2. apply Stream. Tracer filter to density. vtk click on density. vtk in pipeline Filter -> Stream Tracer 3. in the Object Inspector (Properties Tab) set “Vectors” menu to Momentum set “Max Propagation” to Time 100 set “Initial Step Length” to Cell Length 0. 1 set “Integration Direction” to Both set “Max Steps” to 1000 set “Integrator Type” to Runge-Kutta 4 set “Seed Type” to Point Source, Center on Bounds set “Number of Points” to 100 IS&T Scientific Visualization Tutorial – Spring 2010

Annotation – used for annotating visualizations – Para. View • Text Source • Source -> Text • Color Legend • “Edit Color Map” button in Display tab • “Show Color Legend” box in color legend tab of the Color Scale Editor • Axes • Edit -> View Settings IS&T Scientific Visualization Tutorial – Spring 2010

Example – Annotation Para. View: 1. open data file File -> Open (density. vtk) 2. apply Clip filter to density. vtk click on density. vtk in pipeline Filter -> Clip 3. Create a Text source Sources -> Text 4. Turn on Color Legend Edit Color Map for Clip in Display Tab Color Legend tab in Color Scale Editor select “Show Color Legend” check box 5. Turn on orientation axis Edit -> View Settings select “Orientation Axes” check box IS&T Scientific Visualization Tutorial – Spring 2010

Saving Images – common formats: • jpg (lossy) • png (lossless) • pdf • tiff (lossless) – Para. View • File -> Save Screenshot IS&T Scientific Visualization Tutorial – Spring 2010

Example – Saving Images Para. View: 1. open data file File -> Open (density. vtk) 2. apply Clip filter to density. vtk click on density. vtk in pipeline Filter -> Clip 3. save Screenshot File -> Save Screenshot 4. set Resolution 5. set File Type to JPG IS&T Scientific Visualization Tutorial – Spring 2010

Para. View - Resources IS&T Tutorials – Using Para. View to Visualize Scientific Data http: //scv. bu. edu/documentation/tutorials/Para. View/ – Para. View Examples help/scivis/paraview_examples/index. html Text – www. paraview. org http: //paraview. org/Online. Help. Current/ www. kitware. com Wiki – The Para. View Guide, v 3 Edition, Kitware, Inc, 2006. Websites – – – http: //scv. bu. edu/documentation/software- www. paraview. org/Wiki/Para. View Mailing Lists – www. paraview. org/praview/help/mailing. html IS&T Scientific Visualization Tutorial – Spring 2010

Sources IS&T Scientific Visualization Tutorial – Spring 2010