ParaView Today we will:. Create isosurfaces for a scalar variable. Clip and slice the isosurfaces. Use glyphs to display a vector field. Use streamlines to show flow through a vector field. Edit color maps. Add slices to show variable values over a plane. Adjust opacities of filters. Add color legends. ParaView is an open-source, multi-platform data analysis and visualization application. ParaView users can quickly build visualizations to analyze their data using qualitative and quantitative techniques. The data exploration can be done interactively in 3D or programmatically using ParaView. Tutorial practice files here: VTK file format information for those.

Overview
Paraview Glance
ParaView is a Open Source software in the category Miscellaneous developed by Kitware Inc..
The latest version of ParaView is 3.2.1, released on 10/21/2008. It was initially added to our database on 10/29/2007.
ParaView runs on the following operating systems: Windows.
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GoalsThis tutorial is intended to be a hands-on resource for users interested in learning the basic concepts of ParaView. The examples can easily be run on a laptop, using the example data set provided.
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DataThe data used for this tutorial is:
| The data is available for download here (~27MB compressed, ~39MB uncompressed): |
Load Multi-component Dataset
| With all of the default settings, you should see something like this: |
Select which data to viewLet's start by looking at the continuum.000** data. This is an unstructured mesh that has velocity and count (density) values.
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Manipulating the Color MapTo change the colors used to represent the Velocity:
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Data RepresentationIn order to be able to see the particles and red blood cells inside the cylinder, we need to be able to see through it. If we scroll down a bit in the Object Inspector view:
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Generate Streamlines
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Streamlines as TubesThe streamlines are just that, lines. We can use the Tubes filter to represent them as 3D objects, rather than just lines.
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Cutting Planes (Slices)Now let's add some cutting plans, or slices, to see what the cross-section of the continuum data looks like.
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Data Representation: OpacityEven with the continuum data represented as wireframe, there is still considerable occlusion of the interior structures. In order to further reduce this occlusion by the wireframe, we can make it more transparent.
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Animating Simulation DataSince our data has multiple time steps, we can easily animate through them to see how the data changes over time.
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AnimationsAnimations can be saved to disk as a movie file, to be played back later.
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Particles as GlyphsGlyphs are another way of visually representing data where the attributes of a graphical element are dictated by attributes of the data. All of the particles are displayed as red points in the graphics window. There are ~39K particles in this particular data set, which makes the display a bit cluttered. In order to both filter some of these out, and create 3D representations for them, let's apply a glyph filter to this data. Now let's add some of our other data back into the scene. Let's start with the particle data. All of the particles are displayed as red points in the graphics window. There are ~39K particles in this particular data set, which makes the display rather cluttered. In order to both filter some of these out, and create 3D representations for them, we will apply the glyph filter to this data. Notice that the particles.000* is still visible.
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Enter: Red Blood CellsNow let's add in both of the other data sets, which are polygonal meshes which make up Red Blood Cells (RBCs). These two data sets are essentially the same kind of data, so we can apply the same filters and make the same types of representation changes to each of them. However, some of the RBCs are marked by the simulation that generated them as healthy (rbc.000*) and some of them are marked as diseased (bad_rbc.000*).
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Using Color to Differentiate DataTo enable us to distinguish these two types of data from one other, we can vary their representations. One way to do this is by setting the color of the two data sets to different colors. Repeat this process for each of rbc.000* and bad_rbc.000*, picking different colors.
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Further Exploration: Highlight the MeshChange the representation of one of the RBC data sets. In this example, the continuum.000* data is also hidden to reduce confusion with showing multiple overlapping meshes.
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Further Exploration: Highlight the VerticesAdd glyphs to illustrate the position of the vertices of one of the RBC data sets.
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Further Exploration: Color by VariableTry playing around with the viewing options and representations of the other data objects. Change the:
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Background Color
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This tutorial was developed with support from National Science Foundation Grant OCI-0904190, and from the Argonne Leadership Computing Facility at Argonne National Laboratory, which is supported by the Office of Science of the U.S. Department of Energy under contract DE-AC02-06CH11357. |
