SciVisFall2007/Final

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This is the final for the Scientific Visualization class. You will need to use the CADE handin functionality to turn in your assignment. The class account is "cs5630". The due date is Dec 11th at noon.

Submitting your vistrail

You should name your vistrail scivis_final.vt

Labelling your visualizations

Your visualizations should be labeled "Problem 1a", "Problem 1b", "Problem 1c", "Problem 2a", etc.

General Hints

These questions are designed to be very open-ended. There is no single "right" solution, but there are definitely varying degrees of correctness. To maximize your score, you should form a series of visualizations for each of the datasets being explored. For each visualization you create, label your version "Problem 1a", "Problem 2c", etc. where unique visualizations you wish to have looked at are given increasing letters associated with the problem they are for. 'Versions labeled incorrectly will NOT be considered!'

Problem 1

Design an effective visualization for this 3D vector field. For your convenience, we have already computed many derived field from the vector field that you can use. Remember that in 3D curl is a vector.

Feel free to use glyphs, streamlines, isosurfaces, and anything else you might need. Your visualization should portray as much interesting information as possible (vector magnitude, directions, critical points of the field, etc)

You might want to play with simpler datasets first to get a feeling for 3D vector field visualization. These are:

   TestVec0.vtk: vector field 1
   TestMag0.vtk: vector magnitudes (scalar field)
   TestDMag0.vtk: divergences (scalar field)
   TestCur0.vtk: curl (vector field)
   TestCMag0.vtk: curl magnitude (vector field)
   TestVec1.vtk: vector field 2
   TestMag1.vtk: vector magnitudes (scalar field)
   TestDMag1.vtk: divergences (scalar field)
   TestCur1.vtk: curl (vector field)
   TestCMag1.vtk: curl magnitude (vector field)

The vector field you should visualize for your final submission is:

   ChalVec1.vtk: final vector field
   ChalMag1.vtk: vector magnitudes (scalar field)
   ChalDMag1.vtk: divergences (scalar field)
   ChalCur1.vtk: curl (vector field)
   ChalCMag1.vtk: curl magnitude (vector field)

The datasets are available at http://www.sci.utah.edu/~cscheid/scivis_fall07/3DVecField.zip

Problem 2

Design a series of effective visualizations for cosmological data. This data is the same data we had previously discussed in class. For your convenience, we have provided it to you as a series of 4 distinct vtk volumes. It is important to note here, that although particle data is contained in a vector field, it is not meant to streamline. Each particle in the dataset is represented by a 3D velocity combined with a 3D position.

   AllParticles.vtk:        Particle field representing all particles in the simulation (vector field)
   AllParticleDensity.vtk:  Density field induced using all partciles in the simulation (scalar field)
   Halos.vtk:               Particle field representing only particles belonging to halos (vector field)
   HaloDensity.vtk:         Density field induced by partciles belonging to halos (scalar field)

To refresh your memory, Cosmology is the study of the universe as a whole and matter and energy interaction at a macro-scale. The datasets in this problem reflect these studies. Of particular interest to cosmologists are the shapes of regions of high and low particle densities. These regions are called halos and voids, respectively. When Cosmologists look at these data, they have a density field induced by all particles in the simulation as well as a density field induced by only the particles belonging to halos. One of the things they are exploring now are the differences between these two density fields. There are several properties of the density fields that they are looking at, two of them are the shape of the fields (or the shape of some important density value) and the difference between the volume that is enclosed by each field given the same density value.

When creating your series of visualizations, comment on why each visualization created is unique and what it best illustrates. Good visualizations will be able to convey multiple properties of the data.

The datasets are available at http://www.sci.utah.edu/~eranders/scivis_fall07/final and at http://www.sci.utah.edu/~eranders/scivis_fall07/final/cosmo_data.tar.gz for an archive containing all 4 datasets.