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User contributionsenMediaWiki 1.36.2Thu, 19 May 2022 12:41:56 GMTSciVisFall2008/Schedule
https://www.vistrails.org//index.php?title=SciVisFall2008/Schedule&diff=1515
https://www.vistrails.org//index.php?title=SciVisFall2008/Schedule&diff=1515<p>Stevec: /* 11/25: Information Visualization */</p>
<hr />
<div>== 8/26: Introduction to visualization ==<br />
<br />
Lecturer: Claudio<br />
<br />
Topics: Scientific Visualization<br />
<br />
Notes: [http://www.cs.utah.edu/~csilva/courses/cs5630/lec01-notes.pdf lec01-notes.pdf]<br />
<br />
Slides: [http://www.cs.utah.edu/~csilva/courses/cs5630/fall2008/lec01.pdf intro]<br />
<br />
Animations: [http://www.cs.utah.edu/~csilva/courses/cs5630/fall2007/SevereTstorm.mov NCSA storm animation]<br />
<br />
Further reading:<br />
<br />
(Optional reading) [http://www.sci.utah.edu/~csilva/papers/cise2008a.pdf Provenance for Computational Tasks: A Survey]<br />
<br />
== 8/28: The visualization pipeline ==<br />
<br />
Lecturer: Claudio<br />
<br />
Topics: Procedural vs. Dataflow programming; Using Dataflow for the Vis Pipeline; Dataflow programming with VTK; Dataflow programming with VisTrails; python.<br />
<br />
Notes: [http://www.cs.utah.edu/~csilva/courses/cs5630/lec02-notes.pdf lec02-notes.pdf]<br />
<br />
Slides: [http://www.cs.utah.edu/~csilva/courses/cs5630/lec02.pdf lec02.pdf]<br />
<br />
Further reading: <br />
<br />
(Optional reading) [http://www.cs.utah.edu/~csilva/courses/cs5630/reproducible_vis.pdf Provenance for Visualizations: Reproducibility and Beyond], C. Silva, J. Freire, and S. Callahan, IEEE Computing in Science and Engineering, 2008.<br />
<br />
== 9/2: Modeling Data for Visualization ==<br />
<br />
Lecturer: Claudio<br />
<br />
Topics: Discrete vs continous data; Sampling and interpolation; Point vs triangulated data; Meshing data types; Regular vs irregular data; Tabular data; Vector and tensor fields<br />
<br />
Notes: [http://www.vistrails.org/download/download.php?type=PUB&id=week2.pdf modeling data]<br />
<br />
Slides: [http://www.vistrails.org/download/download.php?type=PUB&id=processing.ppt processing.ppt] <br />
<br />
Further reading:<br />
<br />
[http://www.cs.wisc.edu/graphics/Courses/559-s2001/notes/hanrahan.pdf Basic Signal Processing]<br />
<br />
[http://graphics.cs.uiuc.edu/~garland/papers/quadrics.pdf Surface Simplification Using Quadric Error Metrics]<br />
<br />
(Optional Reading) [http://www.sci.utah.edu/~csilva/papers/vis2001b.pdf A Memory Insensitive Technique for Large Model Simplification]<br />
<br />
(Optional Reading) [http://graphics.cs.uiuc.edu/~garland/papers/TR-2004-2450.pdf Quadric-based Simplification in any Dimension]<br />
<br />
== 9/4: Modeling Data for Visualization == <br />
<br />
Lecturer: Claudio<br />
<br />
Topics: Geometry Processing: Reconstruction and meshing; Simplification; Smoothing; Other Filtering algorithms<br />
<br />
Notes: [http://www.vistrails.org/download/download.php?type=PUB&id=week2.pdf modeling data]<br />
<br />
Slides: [http://www.vistrails.org/download/download.php?type=PUB&id=processing.ppt processing.ppt] <br />
<br />
Further reading:<br />
<br />
http://en.wikipedia.org/wiki/Least_squares<br />
<br />
(Optional Reading) [http://www.sci.utah.edu/~csilva/papers/sig2005.pdf Robust Moving Least-squares Fitting with Sharp Features]<br />
<br />
(Optional Reading) [http://www.sci.utah.edu/~cscheid/pubs/band_mls.pdf Optimal Bandwidth Selection for MLS Surfaces]<br />
<br />
== 9/9: Elementary Plotting Techniques == <br />
<br />
Lecturer: Claudio<br />
<br />
Topics: Principles of Graph Construction<br />
<br />
Notes: [http://www.sci.utah.edu/~stevec/classes/cs5630/PlottingNotes.pdf PlottingNotes.pdf]<br />
<br />
Slides: [http://www.sci.utah.edu/~stevec/slides/SciVis/Plotting1.pdf Plotting1.pdf]<br />
<br />
Further Reading: There is no required reading for this lecture. For those interested in more depth, the following books are very useful:<br />
<br />
* The Elements of Graphing Data. William S. Cleveland, Hobart Press, 2nd Edition, 1994.<br />
<br />
* Visualizing Data. William S. Cleveland, Hobart Press, 1993.<br />
<br />
* The Visual Display of Quantitative Information. Edward R. Tufte, Graphics Press, 2001.<br />
<br />
* Visual Explanations: Images and Quantities, Evidence and Narrative. Edward R. Tufte, Graphics Press, 2997.<br />
<br />
== 9/11: Elementary Plotting Techniques ==<br />
<br />
Lecturer: Claudio<br />
<br />
Topics: Simple Plotting Methods: Dot Plots, Connected Symbol Plots, Scatter Plots, Histograms, Others. Advanced Plotting Methods: Multimodal, Higher Dimensional, Correlation, Uncertainty and Variation.<br />
<br />
Notes: [http://www.sci.utah.edu/~stevec/classes/cs5630/PlottingNotes.pdf PlottingNotes.pdf]<br />
<br />
Slides: [http://www.vistrails.org/download/download.php?type=PUB&id=Plotting2.pdf Plotting2.pdf]<br />
<br />
Vistrails: [http://www.sci.utah.edu/~stevec/classes/cs5630/PlottingVistrails.zip PlottingVistrails.zip] - Unzip this file in the examples directory of your VisTrails installation and it will add the vistrails along with their data sets (in the data directory). If you don't have permission to write to this directory (CADE users), then unzip the file where you want. Just be aware that in this case the paths for the data files may not be correct for most vistrails and will need to be fixed before they will execute properly.<br />
<br />
Further Reading: There is no required reading for this lecture. Some articles of interest:<br />
<br />
* [http://www.fmrib.ox.ac.uk/analysis/techrep/tr00mj2/tr00mj2/node24.html Histogram Bin Size]<br />
* [http://en.wikipedia.org/wiki/Correlation Correlation]<br />
* [http://en.wikipedia.org/wiki/Linear_regression Linear Regression]<br />
* [http://en.wikipedia.org/wiki/Box_plot Box Plots]<br />
<br />
== 9/16: Color and Human Perception ==<br />
<br />
Lecturer: Claudio<br />
<br />
Topics: Human vision system; Optical illusions<br />
<br />
Slides: [http://www.cs.utah.edu/~csilva/courses/cs5630/human-vision.pdf human-vision.pdf]<br />
<br />
Links:<br />
<br />
http://en.wikipedia.org/wiki/Eye<br />
<br />
http://www.grand-illusions.com/gregory2.htm (also, see the related book: [http://www.amazon.com/Eye-Brain-Richard-L-Gregory/dp/0691048371])<br />
<br />
http://en.wikipedia.org/wiki/Purkinje_effect<br />
<br />
http://www.handprint.com/HP/WCL/color2.html<br />
<br />
== 9/18: Color and Human Perception ==<br />
<br />
Lecturer: Jens Krueger<br />
<br />
Topics: Color Science; Color spaces; Color Blindness; Color maps; Tone mapping; <br />
<br />
Slides: [http://www.cs.utah.edu/~csilva/courses/cs5630/colorvision-jens.pdf colorvision-jens.pdf]<br />
<br />
Links:<br />
<br />
Further reading: <br />
<br />
[http://www.research.ibm.com/dx/proceedings/pravda/truevis.htm How Not to Lie with Visualization]<br />
<br />
http://en.wikipedia.org/wiki/Opponent_process<br />
<br />
http://en.wikipedia.org/wiki/Color_models<br />
<br />
http://en.wikipedia.org/wiki/Absolute_color_space<br />
<br />
http://en.wikipedia.org/wiki/Additive_color<br />
<br />
http://en.wikipedia.org/wiki/Subtractive_color<br />
<br />
http://en.wikipedia.org/wiki/RGB_color_model<br />
<br />
http://en.wikipedia.org/wiki/SRGB_color_space<br />
<br />
http://en.wikipedia.org/wiki/CIE_XYZ_color_space<br />
<br />
== 9/23: Math refresher ==<br />
<br />
Lecturer: Carlos Scheidegger<br />
<br />
Topics: Basic linear algebra; vectors; basic differential geometry (space curves, tangents, normals, surfaces); basic vector calculus (gradient, divergence, curl, gauss' theorem, green's theorem)<br />
<br />
Links:<br />
<br />
[http://www.falstad.com/vector Vector Field Applet]<br />
<br />
Further Reading:<br />
<br />
http://en.wikipedia.org/wiki/Vector_calculus<br />
<br />
Appendix A of these notes might be useful: [http://www.cs.ubc.ca/~rbridson/fluidsimulation/fluids_notes.pdf]<br />
<br />
Two books that take a very accessible approach at vector calculus:<br />
<br />
[http://www.amazon.com/Div-Grad-Curl-All-That/dp/0393969975 Div, Grad, Curl, and All That: An Informal Text on Vector Calculus]<br />
<br />
[http://www.cambridge.org/uk/catalogue/catalogue.asp?isbn=9780521877619 A Student's Guide to Maxwell's Equations]<br />
<br />
== 9/25 2D Visualization Techniques ==<br />
<br />
Lecturer: Claudio<br />
<br />
Topics: 2-D contours, marching quads, marching tris; Color mapping; height fields; NPR<br />
<br />
Slides: [http://www.vistrails.org/download/download.php?type=PUB&id=2d_scalar_vis.pdf pdf file]<br />
<br />
Notes: [http://www.vistrails.org/download/download.php?type=PUB&id=2d_scalar_vis_notes.pdf pdf file]<br />
<br />
Vistrails: [http://www.vistrails.org/download/download.php?type=DATA&id=ozone_and_data.zip zip file with ozone.vt and data] [http://www.vistrails.org/download/download.php?type=DATA&id=asymptotic_decider.vt asymptotic decider in 2d] [http://www.vistrails.org/download/download.php?type=DATA&id=elevation.zip heightfields]<br />
<br />
Note: These vistrails use relative file paths so you don't need to change each of them individually to match your directory structure. Simply unzip the file to whichever location is more convenient. Then, inside VisTrails, open the VisTrails shell, type:<br />
<br />
import os<br />
os.chdir("c:/directory/where/you/unzipped/it")<br />
<br />
This will change the directory so you should be able to just run the pipelines.<br />
<br />
Further reading:<br />
<br />
http://ieeexplore.ieee.org/iel5/4271943/4271944/04272091.pdf<br />
<br />
http://www.jstor.org/stable/pdfplus/2683294.pdf<br />
<br />
[http://www.inf.ufrgs.br/%7Eoliveira/pubs_files/Kuhn_Oliveira_Fernandes_Vis2008.pdf An Efﬁcient Naturalness-Preserving Image-Recoloring Method for Dichromats]<br />
<br />
== 9/30: 2D Visualization Techniques ==<br />
<br />
Lecturer: Jens Krueger and Claudio<br />
<br />
Topics: 2-D vector fields, div, grad, curl in 2D; Steady vs Unsteady flows; Glyphs; 2-D streamlines, streaklines, pathlines<br />
<br />
Slides: [http://www.vistrails.org/download/download.php?type=PUB&id=2d_vector_vis.pdf pdf file]<br />
<br />
Further reading:<br />
<br />
http://en.wikipedia.org/wiki/Streamlines,_streaklines_and_pathlines<br />
<br />
http://en.wikipedia.org/wiki/Euler's_method<br />
<br />
http://en.wikipedia.org/wiki/Runge-Kutta<br />
<br />
Demos:<br />
<br />
http://www.win.tue.nl/~vanwijk/ibfv/<br />
<br />
http://www.javaview.de/demo/PaLIC.html<br />
<br />
Vistrails: [http://www.vistrails.org/download/download.php?type=DATA&id=vector_vis_1.zip vistrail with steady vector field vis and data] [http://www.vistrails.org/download/download.php?type=DATA&id=unsteady.zip vistrail with unsteady vector field vis and data] '''Note:''' Because VTK does not support time-varying datasets directly, we had to create a reasonably ugly hack to simulate unsteady fields. This means the datasets are quite big (80MB in total).<br />
<br />
[http://wwwcg.in.tum.de/Download/PE "The Dx9 Particle Engine" as well as a few datasets]<br />
<br />
== 10/2: Volume Vis ==<br />
<br />
Lecturer: Carlos<br />
<br />
Topics: Slicing; Contours; Marching algorithms<br />
<br />
Slides: [http://www.cs.utah.edu/~csilva/courses/cs5630/iso-basic.pdf iso-basic.pdf]<br />
<br />
References:<br />
<br />
[http://portal.acm.org/citation.cfm?id=37401.37422 Marching cubes: A high resolution 3D surface construction algorithm]<br />
<br />
[http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=175782 The asymptotic decider: resolving the ambiguity in marching cubes]<br />
<br />
== 10/2: Volume Vis == <br />
<br />
Lecturer: Carlos<br />
<br />
Topics: Accelerating structures; High-quality contours<br />
<br />
Slides: <br />
<br />
[http://www.cs.utah.edu/~csilva/courses/cs5630/iso-speed.pdf iso-speed.pdf]<br />
<br />
[http://www.cs.utah.edu/~csilva/courses/cs5630/iso-speed-2.pdf iso-speed-2.pdf]<br />
<br />
References:<br />
<br />
[http://doi.ieeecomputersociety.org/10.1109/2945.489388 A Near Optimal Isosurface Extraction Algorithm Using the Span Space]<br />
<br />
[http://doi.ieeecomputersociety.org/10.1109/2945.485619 Automatic Isosurface Propagation Using an Extrema Graph and Sorted Boundary Cell Lists]<br />
<br />
[http://doi.ieeecomputersociety.org/10.1109/2945.597798 Speeding Up Isosurface Extraction Using Interval Trees]<br />
<br />
[http://doi.ieeecomputersociety.org/10.1109/SVVG.2004.5 Implicit Occluders]<br />
<br />
== 10/9: Volume Vis ==<br />
<br />
Lecturer: Carlos Scheidegger<br />
<br />
Topics: High quality isosurfaces<br />
<br />
Slides: [http://www.cs.utah.edu/~csilva/courses/cs5630/iso-quality.pdf iso-quality.pdf]<br />
<br />
References:<br />
<br />
[http://www.cs.utah.edu/~csilva/2007-sub/macet.pdf Edge Transformations for Improving Mesh Quality of Marching Cubes]<br />
<br />
[http://www.sci.utah.edu/~csilva/papers/tvcg2006acr.pdf High-Quality Extraction of Isosurfaces from Regular and Irregular Grids]<br />
<br />
[http://portal.acm.org/citation.cfm?id=566570.566586 Dual contouring of hermite data]<br />
<br />
[http://www.sci.utah.edu/%7Emiriah/research/meshing/vis07meyer.pdf Topology, Accuracy, and Quality of Isosurface Meshes Using Dynamic Particles]<br />
<br />
[http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=1260744 Material interface reconstruction]<br />
<br />
== 10/14: Fall break == <br />
<br />
== 10/16: Fall break == <br />
<br />
== 10/21: Direct Volume Rendering ==<br />
<br />
Lecturer: Huy Vo<br />
<br />
Topics: Introduction to volume rendering<br />
<br />
Slides: [http://www.sci.utah.edu/~stevec/classes/cs5630/VolumeRendering1.pdf VolumeRendering1.pdf]<br />
<br />
Notes: [http://www.sci.utah.edu/~stevec/classes/cs5630/dvr.pdf dvr.pdf]<br />
<br />
vistrails: [http://www.sci.utah.edu/~stevec/classes/cs5630/VolumeRenderingVistrails.zip VolumeRenderingVistrails.zip]<br />
<br />
References:<br />
[http://www.llnl.gov/graphics/docs/OpticalModelsLong.pdf Optical Models for Direct Volume Rendering]<br />
<br />
== 10/23: Midterm 1 ==<br />
<br />
== 10/28: Direct Volume Rendering ==<br />
<br />
Lecturer: Claudio<br />
<br />
Topics: Structured grid techniques: ray-casting, splatting, texture slicing, shear-warp<br />
<br />
Slides: [http://www.sci.utah.edu/~stevec/classes/cs5630/VolumeRendering2.pdf VolumeRendering2.pdf]<br />
<br />
Notes: same as previous class<br />
<br />
vistrails: same as previous class<br />
<br />
References:<br />
<br />
[http://graphics.stanford.edu/papers/volume-cga88/ Display of Surfaces from Volume Data] - Ray casting paper<br />
<br />
[http://portal.acm.org/citation.cfm?id=329138 Interactive Volume Rendering] - Splatting paper, paper requires ACM digital library access<br />
<br />
[http://portal.acm.org/citation.cfm?id=197972&dl=ACM&coll=GUIDE Accelerated volume rendering and tomographic reconstruction using texture mapping hardware] - Texture slicing paper, requires ACM digital library access<br />
<br />
[http://graphics.stanford.edu/papers/shear/ Fast Volume Rendering Using a Shear-Warp Factorization of the Viewing Transformation] - Shear-warp paper<br />
<br />
== 10/30: Invited Lecture by Professor Joao Comba ==<br />
Title: Edge Groups: An Approach to Understanding the Mesh Quality of Marching Methods<br />
<br />
Abstract: Marching Cubes is the most popular isosurface extraction algorithm due to its simplicity, efficiency and robustness. It has been widely studied, improved, and extended. While much early work was concerned with efficiency and correctness issues, lately there has been a push to improve the quality of Marching Cubes meshes so that they can be used in computational codes. In this work we present a new classification of MC cases that we call Edge Groups, which helps elucidate the issues that impact the triangle quality of the meshes that the method generates. This formulation allows a more systematic way to bound the triangle quality, and is general enough to extend to other polyhedral cell shapes used in other polygonization algorithms. Using this analysis, we also discuss ways to improve the quality of the resulting triangle mesh, including some that require only minor modifications of the original algorithm.<br />
<br />
This is joint work with Carlos A. Dietrich, Carlos E. Scheidegger, Luciana P. Nedel and Claudio T. Silva, and was presented last week at IEEE Visualization 2008.<br />
<br />
Slides: [http://www.vistrails.org/download/download.php?type=PUB&id=comba_talk.pdf pdf file]<br />
<br />
== 11/4: Direct Volume Rendering ==<br />
<br />
Lecturer: Jens Kruger<br />
<br />
Topics: Unstructured grid techniques<br />
<br />
Slides: [http://www.cs.utah.edu/~csilva/courses/cs5630/unstructured_grid_rendering.pdf unstructured_grid_rendering.pdf]<br />
<br />
References:<br />
<br />
[http://www.sci.utah.edu/~csilva/papers/rita2005.pdf A Survey of GPU-Based Volume Rendering of Unstructured Grid]<br />
<br />
[http://www.sci.utah.edu/~csilva/papers/tvcg2005cr.pdf Hardware-Assisted Visibility Sorting for Unstructured Volume Rendering] (This technique is implemented in VTK: http://www.vtk.org/doc/nightly/html/classvtkHAVSVolumeMapper.html)<br />
<br />
[http://www.sci.utah.edu/~csilva/papers/volvis2000.pdf ZSWEEP: An Efficient and Exact Projection Algorithm for Unstructured Volume Rendering] (This technique is implemented in VTK: http://www.vtk.org/doc/nightly/html/classvtkUnstructuredGridVolumeZSweepMapper.html)<br />
<br />
== 11/6: Direct Volume Rendering ==<br />
<br />
Lecturer: Claudio<br />
<br />
Topics: Unstructured grid techniques (continuation from last class)<br />
<br />
== 11/11: Direct Volume Rendering ==<br />
<br />
Lecturer: Claudio<br />
<br />
Topics: Transfer function specification<br />
<br />
Slides: [http://www.cs.utah.edu/~csilva/courses/cs5630/transfer_functions.pdf transfer_functions.pdf]<br />
<br />
References: <br />
<br />
[http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=920623 The transfer function bake-off]<br />
<br />
[http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=663875 The contour spectrum]<br />
<br />
[http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=1021579 Multidimensional transfer functions for interactive volume rendering]<br />
<br />
[http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=729588 Semi-automatic generation of transfer functions for direct volume rendering]<br />
<br />
Additional Question:<br />
<br />
[[Image:Synthetic_slice_tf.png]]<br />
<br />
The above image is the sphere data and joint histogram discussed in class. Which material boundary is highlighted by the small arc on the right-side of the histogram? The colors in the original dataset can be interpreted as:<br />
<br />
0 = Blue<br />
<br />
1 = Green<br />
<br />
2 = Red<br />
<br />
== 11/13: Direct Volume Rendering ==<br />
<br />
Lecturer: Claudio<br />
<br />
Topics: Transfer function specification<br />
<br />
References: <br />
<br />
[http://ieeexplore.ieee.org/search/wrapper.jsp?arnumber=568113 Generation of transfer functions with stochastic search techniques]<br />
<br />
[http://portal.acm.org/citation.cfm?id=258734.258887 Design galleries: a general approach to setting parameters for computer graphics and animation]<br />
<br />
[http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=4653210 Transfer-Function Specification for Rendering Disparate Volumes] (and corresponding [http://www.sci.utah.edu/~stevec/movies/TransferFunction-QT-H.264.mov video])<br />
<br />
== 11/18: Intro to Geometry Processing ==<br />
<br />
Lecturer: Claudio<br />
<br />
== 11/20: Information Visualization ==<br />
<br />
Lecturer: Steve Callahan<br />
<br />
Topics: Intro to InfoVis, clustering, parallel coordinates, graph vis, tree vis, cartograms<br />
<br />
Slides: [http://www.sci.utah.edu/~stevec/classes/cs5630/InfoVis.pdf InfoVis.pdf]<br />
<br />
References:<br />
<br />
[http://www.smartmoney.com/map-of-the-market/ Map of the Market]: Tree Map of Stock Market<br />
<br />
[http://itol.embl.de/itol.cgi Interactive Tree of Life]: Radial Phylogenetic Tree<br />
<br />
[http://www.derlien.com/ Disk Inventory X]: Tree Map Disk Utility for Mac<br />
<br />
[http://w3.win.tue.nl/nl/onderzoek/onderzoek_informatica/visualization/sequoiaview/ Sequoia View]: Tree Map Disk Utility for Windows<br />
<br />
[http://www.gg.caltech.edu/~zhukov/infovis/world_of_music.htm World of Music]: Music Clustering<br />
<br />
[http://www.graphviz.org/ Graphviz]: Graph layout project<br />
<br />
== 11/25: Information Visualization == <br />
<br />
Lecturer: Steve Callahan<br />
<br />
Topics: InfoVis examples; recent developments<br />
<br />
References: <br />
<br />
[http://www.cs.utah.edu/~draperg/research/papers/infovis2008.pdf Demographic Analysis]<br />
<br />
[http://manyeyes.alphaworks.ibm.com/manyeyes/ Many Eyes]<br />
<br />
[http://manyeyes.alphaworks.ibm.com/manyeyes/ Name Voyager]<br />
<br />
[http://www.gapminder.org/ Gap Minder]<br />
<br />
[http://www.nytimes.com/interactive/2008/02/23/movies/20080223_REVENUE_GRAPHIC.html?scp=1&sq=interactive%20movie&st=cse Ebb and Flow of Movies]<br />
<br />
[http://www.tableausoftware.com Tableau]<br />
<br />
[http://www.palantirtech.com Palantir]<br />
<br />
== 11/27: Thanksgiving == <br />
<br />
== 12/2: Aesthetic Issues in Vis ==<br />
<br />
Lecturer: Claudio<br />
<br />
Topics: Tufte principles<br />
<br />
== 12/4: Aesthetic Issues in Vis ==<br />
<br />
Lecturer: Claudio<br />
<br />
Topics: NPR and Illustrative techniques for Vis<br />
<br />
== 12/9: TBD ==<br />
<br />
== 12/11: TBD ==</div>Wed, 26 Nov 2008 00:14:24 GMTStevechttps://www.vistrails.org//index.php/Talk:SciVisFall2008/ScheduleSciVisFall2008/Schedule
https://www.vistrails.org//index.php?title=SciVisFall2008/Schedule&diff=1511
https://www.vistrails.org//index.php?title=SciVisFall2008/Schedule&diff=1511<p>Stevec: /* 11/20: Information Visualization */</p>
<hr />
<div>== 8/26: Introduction to visualization ==<br />
<br />
Lecturer: Claudio<br />
<br />
Topics: Scientific Visualization<br />
<br />
Notes: [http://www.cs.utah.edu/~csilva/courses/cs5630/lec01-notes.pdf lec01-notes.pdf]<br />
<br />
Slides: [http://www.cs.utah.edu/~csilva/courses/cs5630/fall2008/lec01.pdf intro]<br />
<br />
Animations: [http://www.cs.utah.edu/~csilva/courses/cs5630/fall2007/SevereTstorm.mov NCSA storm animation]<br />
<br />
Further reading:<br />
<br />
(Optional reading) [http://www.sci.utah.edu/~csilva/papers/cise2008a.pdf Provenance for Computational Tasks: A Survey]<br />
<br />
== 8/28: The visualization pipeline ==<br />
<br />
Lecturer: Claudio<br />
<br />
Topics: Procedural vs. Dataflow programming; Using Dataflow for the Vis Pipeline; Dataflow programming with VTK; Dataflow programming with VisTrails; python.<br />
<br />
Notes: [http://www.cs.utah.edu/~csilva/courses/cs5630/lec02-notes.pdf lec02-notes.pdf]<br />
<br />
Slides: [http://www.cs.utah.edu/~csilva/courses/cs5630/lec02.pdf lec02.pdf]<br />
<br />
Further reading: <br />
<br />
(Optional reading) [http://www.cs.utah.edu/~csilva/courses/cs5630/reproducible_vis.pdf Provenance for Visualizations: Reproducibility and Beyond], C. Silva, J. Freire, and S. Callahan, IEEE Computing in Science and Engineering, 2008.<br />
<br />
== 9/2: Modeling Data for Visualization ==<br />
<br />
Lecturer: Claudio<br />
<br />
Topics: Discrete vs continous data; Sampling and interpolation; Point vs triangulated data; Meshing data types; Regular vs irregular data; Tabular data; Vector and tensor fields<br />
<br />
Notes: [http://www.vistrails.org/download/download.php?type=PUB&id=week2.pdf modeling data]<br />
<br />
Slides: [http://www.vistrails.org/download/download.php?type=PUB&id=processing.ppt processing.ppt] <br />
<br />
Further reading:<br />
<br />
[http://www.cs.wisc.edu/graphics/Courses/559-s2001/notes/hanrahan.pdf Basic Signal Processing]<br />
<br />
[http://graphics.cs.uiuc.edu/~garland/papers/quadrics.pdf Surface Simplification Using Quadric Error Metrics]<br />
<br />
(Optional Reading) [http://www.sci.utah.edu/~csilva/papers/vis2001b.pdf A Memory Insensitive Technique for Large Model Simplification]<br />
<br />
(Optional Reading) [http://graphics.cs.uiuc.edu/~garland/papers/TR-2004-2450.pdf Quadric-based Simplification in any Dimension]<br />
<br />
== 9/4: Modeling Data for Visualization == <br />
<br />
Lecturer: Claudio<br />
<br />
Topics: Geometry Processing: Reconstruction and meshing; Simplification; Smoothing; Other Filtering algorithms<br />
<br />
Notes: [http://www.vistrails.org/download/download.php?type=PUB&id=week2.pdf modeling data]<br />
<br />
Slides: [http://www.vistrails.org/download/download.php?type=PUB&id=processing.ppt processing.ppt] <br />
<br />
Further reading:<br />
<br />
http://en.wikipedia.org/wiki/Least_squares<br />
<br />
(Optional Reading) [http://www.sci.utah.edu/~csilva/papers/sig2005.pdf Robust Moving Least-squares Fitting with Sharp Features]<br />
<br />
(Optional Reading) [http://www.sci.utah.edu/~cscheid/pubs/band_mls.pdf Optimal Bandwidth Selection for MLS Surfaces]<br />
<br />
== 9/9: Elementary Plotting Techniques == <br />
<br />
Lecturer: Claudio<br />
<br />
Topics: Principles of Graph Construction<br />
<br />
Notes: [http://www.sci.utah.edu/~stevec/classes/cs5630/PlottingNotes.pdf PlottingNotes.pdf]<br />
<br />
Slides: [http://www.sci.utah.edu/~stevec/slides/SciVis/Plotting1.pdf Plotting1.pdf]<br />
<br />
Further Reading: There is no required reading for this lecture. For those interested in more depth, the following books are very useful:<br />
<br />
* The Elements of Graphing Data. William S. Cleveland, Hobart Press, 2nd Edition, 1994.<br />
<br />
* Visualizing Data. William S. Cleveland, Hobart Press, 1993.<br />
<br />
* The Visual Display of Quantitative Information. Edward R. Tufte, Graphics Press, 2001.<br />
<br />
* Visual Explanations: Images and Quantities, Evidence and Narrative. Edward R. Tufte, Graphics Press, 2997.<br />
<br />
== 9/11: Elementary Plotting Techniques ==<br />
<br />
Lecturer: Claudio<br />
<br />
Topics: Simple Plotting Methods: Dot Plots, Connected Symbol Plots, Scatter Plots, Histograms, Others. Advanced Plotting Methods: Multimodal, Higher Dimensional, Correlation, Uncertainty and Variation.<br />
<br />
Notes: [http://www.sci.utah.edu/~stevec/classes/cs5630/PlottingNotes.pdf PlottingNotes.pdf]<br />
<br />
Slides: [http://www.vistrails.org/download/download.php?type=PUB&id=Plotting2.pdf Plotting2.pdf]<br />
<br />
Vistrails: [http://www.sci.utah.edu/~stevec/classes/cs5630/PlottingVistrails.zip PlottingVistrails.zip] - Unzip this file in the examples directory of your VisTrails installation and it will add the vistrails along with their data sets (in the data directory). If you don't have permission to write to this directory (CADE users), then unzip the file where you want. Just be aware that in this case the paths for the data files may not be correct for most vistrails and will need to be fixed before they will execute properly.<br />
<br />
Further Reading: There is no required reading for this lecture. Some articles of interest:<br />
<br />
* [http://www.fmrib.ox.ac.uk/analysis/techrep/tr00mj2/tr00mj2/node24.html Histogram Bin Size]<br />
* [http://en.wikipedia.org/wiki/Correlation Correlation]<br />
* [http://en.wikipedia.org/wiki/Linear_regression Linear Regression]<br />
* [http://en.wikipedia.org/wiki/Box_plot Box Plots]<br />
<br />
== 9/16: Color and Human Perception ==<br />
<br />
Lecturer: Claudio<br />
<br />
Topics: Human vision system; Optical illusions<br />
<br />
Slides: [http://www.cs.utah.edu/~csilva/courses/cs5630/human-vision.pdf human-vision.pdf]<br />
<br />
Links:<br />
<br />
http://en.wikipedia.org/wiki/Eye<br />
<br />
http://www.grand-illusions.com/gregory2.htm (also, see the related book: [http://www.amazon.com/Eye-Brain-Richard-L-Gregory/dp/0691048371])<br />
<br />
http://en.wikipedia.org/wiki/Purkinje_effect<br />
<br />
http://www.handprint.com/HP/WCL/color2.html<br />
<br />
== 9/18: Color and Human Perception ==<br />
<br />
Lecturer: Jens Krueger<br />
<br />
Topics: Color Science; Color spaces; Color Blindness; Color maps; Tone mapping; <br />
<br />
Slides: [http://www.cs.utah.edu/~csilva/courses/cs5630/colorvision-jens.pdf colorvision-jens.pdf]<br />
<br />
Links:<br />
<br />
Further reading: <br />
<br />
[http://www.research.ibm.com/dx/proceedings/pravda/truevis.htm How Not to Lie with Visualization]<br />
<br />
http://en.wikipedia.org/wiki/Opponent_process<br />
<br />
http://en.wikipedia.org/wiki/Color_models<br />
<br />
http://en.wikipedia.org/wiki/Absolute_color_space<br />
<br />
http://en.wikipedia.org/wiki/Additive_color<br />
<br />
http://en.wikipedia.org/wiki/Subtractive_color<br />
<br />
http://en.wikipedia.org/wiki/RGB_color_model<br />
<br />
http://en.wikipedia.org/wiki/SRGB_color_space<br />
<br />
http://en.wikipedia.org/wiki/CIE_XYZ_color_space<br />
<br />
== 9/23: Math refresher ==<br />
<br />
Lecturer: Carlos Scheidegger<br />
<br />
Topics: Basic linear algebra; vectors; basic differential geometry (space curves, tangents, normals, surfaces); basic vector calculus (gradient, divergence, curl, gauss' theorem, green's theorem)<br />
<br />
Links:<br />
<br />
[http://www.falstad.com/vector Vector Field Applet]<br />
<br />
Further Reading:<br />
<br />
http://en.wikipedia.org/wiki/Vector_calculus<br />
<br />
Appendix A of these notes might be useful: [http://www.cs.ubc.ca/~rbridson/fluidsimulation/fluids_notes.pdf]<br />
<br />
Two books that take a very accessible approach at vector calculus:<br />
<br />
[http://www.amazon.com/Div-Grad-Curl-All-That/dp/0393969975 Div, Grad, Curl, and All That: An Informal Text on Vector Calculus]<br />
<br />
[http://www.cambridge.org/uk/catalogue/catalogue.asp?isbn=9780521877619 A Student's Guide to Maxwell's Equations]<br />
<br />
== 9/25 2D Visualization Techniques ==<br />
<br />
Lecturer: Claudio<br />
<br />
Topics: 2-D contours, marching quads, marching tris; Color mapping; height fields; NPR<br />
<br />
Slides: [http://www.vistrails.org/download/download.php?type=PUB&id=2d_scalar_vis.pdf pdf file]<br />
<br />
Notes: [http://www.vistrails.org/download/download.php?type=PUB&id=2d_scalar_vis_notes.pdf pdf file]<br />
<br />
Vistrails: [http://www.vistrails.org/download/download.php?type=DATA&id=ozone_and_data.zip zip file with ozone.vt and data] [http://www.vistrails.org/download/download.php?type=DATA&id=asymptotic_decider.vt asymptotic decider in 2d] [http://www.vistrails.org/download/download.php?type=DATA&id=elevation.zip heightfields]<br />
<br />
Note: These vistrails use relative file paths so you don't need to change each of them individually to match your directory structure. Simply unzip the file to whichever location is more convenient. Then, inside VisTrails, open the VisTrails shell, type:<br />
<br />
import os<br />
os.chdir("c:/directory/where/you/unzipped/it")<br />
<br />
This will change the directory so you should be able to just run the pipelines.<br />
<br />
Further reading:<br />
<br />
http://ieeexplore.ieee.org/iel5/4271943/4271944/04272091.pdf<br />
<br />
http://www.jstor.org/stable/pdfplus/2683294.pdf<br />
<br />
[http://www.inf.ufrgs.br/%7Eoliveira/pubs_files/Kuhn_Oliveira_Fernandes_Vis2008.pdf An Efﬁcient Naturalness-Preserving Image-Recoloring Method for Dichromats]<br />
<br />
== 9/30: 2D Visualization Techniques ==<br />
<br />
Lecturer: Jens Krueger and Claudio<br />
<br />
Topics: 2-D vector fields, div, grad, curl in 2D; Steady vs Unsteady flows; Glyphs; 2-D streamlines, streaklines, pathlines<br />
<br />
Slides: [http://www.vistrails.org/download/download.php?type=PUB&id=2d_vector_vis.pdf pdf file]<br />
<br />
Further reading:<br />
<br />
http://en.wikipedia.org/wiki/Streamlines,_streaklines_and_pathlines<br />
<br />
http://en.wikipedia.org/wiki/Euler's_method<br />
<br />
http://en.wikipedia.org/wiki/Runge-Kutta<br />
<br />
Demos:<br />
<br />
http://www.win.tue.nl/~vanwijk/ibfv/<br />
<br />
http://www.javaview.de/demo/PaLIC.html<br />
<br />
Vistrails: [http://www.vistrails.org/download/download.php?type=DATA&id=vector_vis_1.zip vistrail with steady vector field vis and data] [http://www.vistrails.org/download/download.php?type=DATA&id=unsteady.zip vistrail with unsteady vector field vis and data] '''Note:''' Because VTK does not support time-varying datasets directly, we had to create a reasonably ugly hack to simulate unsteady fields. This means the datasets are quite big (80MB in total).<br />
<br />
[http://wwwcg.in.tum.de/Download/PE "The Dx9 Particle Engine" as well as a few datasets]<br />
<br />
== 10/2: Volume Vis ==<br />
<br />
Lecturer: Carlos<br />
<br />
Topics: Slicing; Contours; Marching algorithms<br />
<br />
Slides: [http://www.cs.utah.edu/~csilva/courses/cs5630/iso-basic.pdf iso-basic.pdf]<br />
<br />
References:<br />
<br />
[http://portal.acm.org/citation.cfm?id=37401.37422 Marching cubes: A high resolution 3D surface construction algorithm]<br />
<br />
[http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=175782 The asymptotic decider: resolving the ambiguity in marching cubes]<br />
<br />
== 10/2: Volume Vis == <br />
<br />
Lecturer: Carlos<br />
<br />
Topics: Accelerating structures; High-quality contours<br />
<br />
Slides: <br />
<br />
[http://www.cs.utah.edu/~csilva/courses/cs5630/iso-speed.pdf iso-speed.pdf]<br />
<br />
[http://www.cs.utah.edu/~csilva/courses/cs5630/iso-speed-2.pdf iso-speed-2.pdf]<br />
<br />
References:<br />
<br />
[http://doi.ieeecomputersociety.org/10.1109/2945.489388 A Near Optimal Isosurface Extraction Algorithm Using the Span Space]<br />
<br />
[http://doi.ieeecomputersociety.org/10.1109/2945.485619 Automatic Isosurface Propagation Using an Extrema Graph and Sorted Boundary Cell Lists]<br />
<br />
[http://doi.ieeecomputersociety.org/10.1109/2945.597798 Speeding Up Isosurface Extraction Using Interval Trees]<br />
<br />
[http://doi.ieeecomputersociety.org/10.1109/SVVG.2004.5 Implicit Occluders]<br />
<br />
== 10/9: Volume Vis ==<br />
<br />
Lecturer: Carlos Scheidegger<br />
<br />
Topics: High quality isosurfaces<br />
<br />
Slides: [http://www.cs.utah.edu/~csilva/courses/cs5630/iso-quality.pdf iso-quality.pdf]<br />
<br />
References:<br />
<br />
[http://www.cs.utah.edu/~csilva/2007-sub/macet.pdf Edge Transformations for Improving Mesh Quality of Marching Cubes]<br />
<br />
[http://www.sci.utah.edu/~csilva/papers/tvcg2006acr.pdf High-Quality Extraction of Isosurfaces from Regular and Irregular Grids]<br />
<br />
[http://portal.acm.org/citation.cfm?id=566570.566586 Dual contouring of hermite data]<br />
<br />
[http://www.sci.utah.edu/%7Emiriah/research/meshing/vis07meyer.pdf Topology, Accuracy, and Quality of Isosurface Meshes Using Dynamic Particles]<br />
<br />
[http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=1260744 Material interface reconstruction]<br />
<br />
== 10/14: Fall break == <br />
<br />
== 10/16: Fall break == <br />
<br />
== 10/21: Direct Volume Rendering ==<br />
<br />
Lecturer: Huy Vo<br />
<br />
Topics: Introduction to volume rendering<br />
<br />
Slides: [http://www.sci.utah.edu/~stevec/classes/cs5630/VolumeRendering1.pdf VolumeRendering1.pdf]<br />
<br />
Notes: [http://www.sci.utah.edu/~stevec/classes/cs5630/dvr.pdf dvr.pdf]<br />
<br />
vistrails: [http://www.sci.utah.edu/~stevec/classes/cs5630/VolumeRenderingVistrails.zip VolumeRenderingVistrails.zip]<br />
<br />
References:<br />
[http://www.llnl.gov/graphics/docs/OpticalModelsLong.pdf Optical Models for Direct Volume Rendering]<br />
<br />
== 10/23: Midterm 1 ==<br />
<br />
== 10/28: Direct Volume Rendering ==<br />
<br />
Lecturer: Claudio<br />
<br />
Topics: Structured grid techniques: ray-casting, splatting, texture slicing, shear-warp<br />
<br />
Slides: [http://www.sci.utah.edu/~stevec/classes/cs5630/VolumeRendering2.pdf VolumeRendering2.pdf]<br />
<br />
Notes: same as previous class<br />
<br />
vistrails: same as previous class<br />
<br />
References:<br />
<br />
[http://graphics.stanford.edu/papers/volume-cga88/ Display of Surfaces from Volume Data] - Ray casting paper<br />
<br />
[http://portal.acm.org/citation.cfm?id=329138 Interactive Volume Rendering] - Splatting paper, paper requires ACM digital library access<br />
<br />
[http://portal.acm.org/citation.cfm?id=197972&dl=ACM&coll=GUIDE Accelerated volume rendering and tomographic reconstruction using texture mapping hardware] - Texture slicing paper, requires ACM digital library access<br />
<br />
[http://graphics.stanford.edu/papers/shear/ Fast Volume Rendering Using a Shear-Warp Factorization of the Viewing Transformation] - Shear-warp paper<br />
<br />
== 10/30: Invited Lecture by Professor Joao Comba ==<br />
Title: Edge Groups: An Approach to Understanding the Mesh Quality of Marching Methods<br />
<br />
Abstract: Marching Cubes is the most popular isosurface extraction algorithm due to its simplicity, efficiency and robustness. It has been widely studied, improved, and extended. While much early work was concerned with efficiency and correctness issues, lately there has been a push to improve the quality of Marching Cubes meshes so that they can be used in computational codes. In this work we present a new classification of MC cases that we call Edge Groups, which helps elucidate the issues that impact the triangle quality of the meshes that the method generates. This formulation allows a more systematic way to bound the triangle quality, and is general enough to extend to other polyhedral cell shapes used in other polygonization algorithms. Using this analysis, we also discuss ways to improve the quality of the resulting triangle mesh, including some that require only minor modifications of the original algorithm.<br />
<br />
This is joint work with Carlos A. Dietrich, Carlos E. Scheidegger, Luciana P. Nedel and Claudio T. Silva, and was presented last week at IEEE Visualization 2008.<br />
<br />
Slides: [http://www.vistrails.org/download/download.php?type=PUB&id=comba_talk.pdf pdf file]<br />
<br />
== 11/4: Direct Volume Rendering ==<br />
<br />
Lecturer: Jens Kruger<br />
<br />
Topics: Unstructured grid techniques<br />
<br />
Slides: [http://www.cs.utah.edu/~csilva/courses/cs5630/unstructured_grid_rendering.pdf unstructured_grid_rendering.pdf]<br />
<br />
References:<br />
<br />
[http://www.sci.utah.edu/~csilva/papers/rita2005.pdf A Survey of GPU-Based Volume Rendering of Unstructured Grid]<br />
<br />
[http://www.sci.utah.edu/~csilva/papers/tvcg2005cr.pdf Hardware-Assisted Visibility Sorting for Unstructured Volume Rendering] (This technique is implemented in VTK: http://www.vtk.org/doc/nightly/html/classvtkHAVSVolumeMapper.html)<br />
<br />
[http://www.sci.utah.edu/~csilva/papers/volvis2000.pdf ZSWEEP: An Efficient and Exact Projection Algorithm for Unstructured Volume Rendering] (This technique is implemented in VTK: http://www.vtk.org/doc/nightly/html/classvtkUnstructuredGridVolumeZSweepMapper.html)<br />
<br />
== 11/6: Direct Volume Rendering ==<br />
<br />
Lecturer: Claudio<br />
<br />
Topics: Unstructured grid techniques (continuation from last class)<br />
<br />
== 11/11: Direct Volume Rendering ==<br />
<br />
Lecturer: Claudio<br />
<br />
Topics: Transfer function specification<br />
<br />
Slides: [http://www.cs.utah.edu/~csilva/courses/cs5630/transfer_functions.pdf transfer_functions.pdf]<br />
<br />
References: <br />
<br />
[http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=920623 The transfer function bake-off]<br />
<br />
[http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=663875 The contour spectrum]<br />
<br />
[http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=1021579 Multidimensional transfer functions for interactive volume rendering]<br />
<br />
[http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=729588 Semi-automatic generation of transfer functions for direct volume rendering]<br />
<br />
Additional Question:<br />
<br />
[[Image:Synthetic_slice_tf.png]]<br />
<br />
The above image is the sphere data and joint histogram discussed in class. Which material boundary is highlighted by the small arc on the right-side of the histogram? The colors in the original dataset can be interpreted as:<br />
<br />
0 = Blue<br />
<br />
1 = Green<br />
<br />
2 = Red<br />
<br />
== 11/13: Direct Volume Rendering ==<br />
<br />
Lecturer: Claudio<br />
<br />
Topics: Transfer function specification<br />
<br />
References: <br />
<br />
[http://ieeexplore.ieee.org/search/wrapper.jsp?arnumber=568113 Generation of transfer functions with stochastic search techniques]<br />
<br />
[http://portal.acm.org/citation.cfm?id=258734.258887 Design galleries: a general approach to setting parameters for computer graphics and animation]<br />
<br />
[http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=4653210 Transfer-Function Specification for Rendering Disparate Volumes] (and corresponding [http://www.sci.utah.edu/~stevec/movies/TransferFunction-QT-H.264.mov video])<br />
<br />
== 11/18: Intro to Geometry Processing ==<br />
<br />
Lecturer: Claudio<br />
<br />
== 11/20: Information Visualization ==<br />
<br />
Lecturer: Steve Callahan<br />
<br />
Topics: Intro to InfoVis, clustering, parallel coordinates, graph vis, tree vis, cartograms<br />
<br />
Slides: [http://www.sci.utah.edu/~stevec/classes/cs5630/InfoVis.pdf InfoVis.pdf]<br />
<br />
References:<br />
<br />
[http://www.smartmoney.com/map-of-the-market/ Map of the Market]: Tree Map of Stock Market<br />
<br />
[http://itol.embl.de/itol.cgi Interactive Tree of Life]: Radial Phylogenetic Tree<br />
<br />
[http://www.derlien.com/ Disk Inventory X]: Tree Map Disk Utility for Mac<br />
<br />
[http://w3.win.tue.nl/nl/onderzoek/onderzoek_informatica/visualization/sequoiaview/ Sequoia View]: Tree Map Disk Utility for Windows<br />
<br />
[http://www.gg.caltech.edu/~zhukov/infovis/world_of_music.htm World of Music]: Music Clustering<br />
<br />
[http://www.graphviz.org/ Graphviz]: Graph layout project<br />
<br />
== 11/25: Information Visualization == <br />
<br />
Lecturer: Steve Callahan<br />
<br />
Topics: InfoVis examples; recent developments<br />
<br />
== 11/27: Thanksgiving == <br />
<br />
== 12/2: Aesthetic Issues in Vis ==<br />
<br />
Lecturer: Claudio<br />
<br />
Topics: Tufte principles<br />
<br />
== 12/4: Aesthetic Issues in Vis ==<br />
<br />
Lecturer: Claudio<br />
<br />
Topics: NPR and Illustrative techniques for Vis<br />
<br />
== 12/9: TBD ==<br />
<br />
== 12/11: TBD ==</div>Thu, 20 Nov 2008 20:40:40 GMTStevechttps://www.vistrails.org//index.php/Talk:SciVisFall2008/ScheduleSciVisFall2008/Schedule
https://www.vistrails.org//index.php?title=SciVisFall2008/Schedule&diff=1510
https://www.vistrails.org//index.php?title=SciVisFall2008/Schedule&diff=1510<p>Stevec: /* 11/20: Information Visualization */</p>
<hr />
<div>== 8/26: Introduction to visualization ==<br />
<br />
Lecturer: Claudio<br />
<br />
Topics: Scientific Visualization<br />
<br />
Notes: [http://www.cs.utah.edu/~csilva/courses/cs5630/lec01-notes.pdf lec01-notes.pdf]<br />
<br />
Slides: [http://www.cs.utah.edu/~csilva/courses/cs5630/fall2008/lec01.pdf intro]<br />
<br />
Animations: [http://www.cs.utah.edu/~csilva/courses/cs5630/fall2007/SevereTstorm.mov NCSA storm animation]<br />
<br />
Further reading:<br />
<br />
(Optional reading) [http://www.sci.utah.edu/~csilva/papers/cise2008a.pdf Provenance for Computational Tasks: A Survey]<br />
<br />
== 8/28: The visualization pipeline ==<br />
<br />
Lecturer: Claudio<br />
<br />
Topics: Procedural vs. Dataflow programming; Using Dataflow for the Vis Pipeline; Dataflow programming with VTK; Dataflow programming with VisTrails; python.<br />
<br />
Notes: [http://www.cs.utah.edu/~csilva/courses/cs5630/lec02-notes.pdf lec02-notes.pdf]<br />
<br />
Slides: [http://www.cs.utah.edu/~csilva/courses/cs5630/lec02.pdf lec02.pdf]<br />
<br />
Further reading: <br />
<br />
(Optional reading) [http://www.cs.utah.edu/~csilva/courses/cs5630/reproducible_vis.pdf Provenance for Visualizations: Reproducibility and Beyond], C. Silva, J. Freire, and S. Callahan, IEEE Computing in Science and Engineering, 2008.<br />
<br />
== 9/2: Modeling Data for Visualization ==<br />
<br />
Lecturer: Claudio<br />
<br />
Topics: Discrete vs continous data; Sampling and interpolation; Point vs triangulated data; Meshing data types; Regular vs irregular data; Tabular data; Vector and tensor fields<br />
<br />
Notes: [http://www.vistrails.org/download/download.php?type=PUB&id=week2.pdf modeling data]<br />
<br />
Slides: [http://www.vistrails.org/download/download.php?type=PUB&id=processing.ppt processing.ppt] <br />
<br />
Further reading:<br />
<br />
[http://www.cs.wisc.edu/graphics/Courses/559-s2001/notes/hanrahan.pdf Basic Signal Processing]<br />
<br />
[http://graphics.cs.uiuc.edu/~garland/papers/quadrics.pdf Surface Simplification Using Quadric Error Metrics]<br />
<br />
(Optional Reading) [http://www.sci.utah.edu/~csilva/papers/vis2001b.pdf A Memory Insensitive Technique for Large Model Simplification]<br />
<br />
(Optional Reading) [http://graphics.cs.uiuc.edu/~garland/papers/TR-2004-2450.pdf Quadric-based Simplification in any Dimension]<br />
<br />
== 9/4: Modeling Data for Visualization == <br />
<br />
Lecturer: Claudio<br />
<br />
Topics: Geometry Processing: Reconstruction and meshing; Simplification; Smoothing; Other Filtering algorithms<br />
<br />
Notes: [http://www.vistrails.org/download/download.php?type=PUB&id=week2.pdf modeling data]<br />
<br />
Slides: [http://www.vistrails.org/download/download.php?type=PUB&id=processing.ppt processing.ppt] <br />
<br />
Further reading:<br />
<br />
http://en.wikipedia.org/wiki/Least_squares<br />
<br />
(Optional Reading) [http://www.sci.utah.edu/~csilva/papers/sig2005.pdf Robust Moving Least-squares Fitting with Sharp Features]<br />
<br />
(Optional Reading) [http://www.sci.utah.edu/~cscheid/pubs/band_mls.pdf Optimal Bandwidth Selection for MLS Surfaces]<br />
<br />
== 9/9: Elementary Plotting Techniques == <br />
<br />
Lecturer: Claudio<br />
<br />
Topics: Principles of Graph Construction<br />
<br />
Notes: [http://www.sci.utah.edu/~stevec/classes/cs5630/PlottingNotes.pdf PlottingNotes.pdf]<br />
<br />
Slides: [http://www.sci.utah.edu/~stevec/slides/SciVis/Plotting1.pdf Plotting1.pdf]<br />
<br />
Further Reading: There is no required reading for this lecture. For those interested in more depth, the following books are very useful:<br />
<br />
* The Elements of Graphing Data. William S. Cleveland, Hobart Press, 2nd Edition, 1994.<br />
<br />
* Visualizing Data. William S. Cleveland, Hobart Press, 1993.<br />
<br />
* The Visual Display of Quantitative Information. Edward R. Tufte, Graphics Press, 2001.<br />
<br />
* Visual Explanations: Images and Quantities, Evidence and Narrative. Edward R. Tufte, Graphics Press, 2997.<br />
<br />
== 9/11: Elementary Plotting Techniques ==<br />
<br />
Lecturer: Claudio<br />
<br />
Topics: Simple Plotting Methods: Dot Plots, Connected Symbol Plots, Scatter Plots, Histograms, Others. Advanced Plotting Methods: Multimodal, Higher Dimensional, Correlation, Uncertainty and Variation.<br />
<br />
Notes: [http://www.sci.utah.edu/~stevec/classes/cs5630/PlottingNotes.pdf PlottingNotes.pdf]<br />
<br />
Slides: [http://www.vistrails.org/download/download.php?type=PUB&id=Plotting2.pdf Plotting2.pdf]<br />
<br />
Vistrails: [http://www.sci.utah.edu/~stevec/classes/cs5630/PlottingVistrails.zip PlottingVistrails.zip] - Unzip this file in the examples directory of your VisTrails installation and it will add the vistrails along with their data sets (in the data directory). If you don't have permission to write to this directory (CADE users), then unzip the file where you want. Just be aware that in this case the paths for the data files may not be correct for most vistrails and will need to be fixed before they will execute properly.<br />
<br />
Further Reading: There is no required reading for this lecture. Some articles of interest:<br />
<br />
* [http://www.fmrib.ox.ac.uk/analysis/techrep/tr00mj2/tr00mj2/node24.html Histogram Bin Size]<br />
* [http://en.wikipedia.org/wiki/Correlation Correlation]<br />
* [http://en.wikipedia.org/wiki/Linear_regression Linear Regression]<br />
* [http://en.wikipedia.org/wiki/Box_plot Box Plots]<br />
<br />
== 9/16: Color and Human Perception ==<br />
<br />
Lecturer: Claudio<br />
<br />
Topics: Human vision system; Optical illusions<br />
<br />
Slides: [http://www.cs.utah.edu/~csilva/courses/cs5630/human-vision.pdf human-vision.pdf]<br />
<br />
Links:<br />
<br />
http://en.wikipedia.org/wiki/Eye<br />
<br />
http://www.grand-illusions.com/gregory2.htm (also, see the related book: [http://www.amazon.com/Eye-Brain-Richard-L-Gregory/dp/0691048371])<br />
<br />
http://en.wikipedia.org/wiki/Purkinje_effect<br />
<br />
http://www.handprint.com/HP/WCL/color2.html<br />
<br />
== 9/18: Color and Human Perception ==<br />
<br />
Lecturer: Jens Krueger<br />
<br />
Topics: Color Science; Color spaces; Color Blindness; Color maps; Tone mapping; <br />
<br />
Slides: [http://www.cs.utah.edu/~csilva/courses/cs5630/colorvision-jens.pdf colorvision-jens.pdf]<br />
<br />
Links:<br />
<br />
Further reading: <br />
<br />
[http://www.research.ibm.com/dx/proceedings/pravda/truevis.htm How Not to Lie with Visualization]<br />
<br />
http://en.wikipedia.org/wiki/Opponent_process<br />
<br />
http://en.wikipedia.org/wiki/Color_models<br />
<br />
http://en.wikipedia.org/wiki/Absolute_color_space<br />
<br />
http://en.wikipedia.org/wiki/Additive_color<br />
<br />
http://en.wikipedia.org/wiki/Subtractive_color<br />
<br />
http://en.wikipedia.org/wiki/RGB_color_model<br />
<br />
http://en.wikipedia.org/wiki/SRGB_color_space<br />
<br />
http://en.wikipedia.org/wiki/CIE_XYZ_color_space<br />
<br />
== 9/23: Math refresher ==<br />
<br />
Lecturer: Carlos Scheidegger<br />
<br />
Topics: Basic linear algebra; vectors; basic differential geometry (space curves, tangents, normals, surfaces); basic vector calculus (gradient, divergence, curl, gauss' theorem, green's theorem)<br />
<br />
Links:<br />
<br />
[http://www.falstad.com/vector Vector Field Applet]<br />
<br />
Further Reading:<br />
<br />
http://en.wikipedia.org/wiki/Vector_calculus<br />
<br />
Appendix A of these notes might be useful: [http://www.cs.ubc.ca/~rbridson/fluidsimulation/fluids_notes.pdf]<br />
<br />
Two books that take a very accessible approach at vector calculus:<br />
<br />
[http://www.amazon.com/Div-Grad-Curl-All-That/dp/0393969975 Div, Grad, Curl, and All That: An Informal Text on Vector Calculus]<br />
<br />
[http://www.cambridge.org/uk/catalogue/catalogue.asp?isbn=9780521877619 A Student's Guide to Maxwell's Equations]<br />
<br />
== 9/25 2D Visualization Techniques ==<br />
<br />
Lecturer: Claudio<br />
<br />
Topics: 2-D contours, marching quads, marching tris; Color mapping; height fields; NPR<br />
<br />
Slides: [http://www.vistrails.org/download/download.php?type=PUB&id=2d_scalar_vis.pdf pdf file]<br />
<br />
Notes: [http://www.vistrails.org/download/download.php?type=PUB&id=2d_scalar_vis_notes.pdf pdf file]<br />
<br />
Vistrails: [http://www.vistrails.org/download/download.php?type=DATA&id=ozone_and_data.zip zip file with ozone.vt and data] [http://www.vistrails.org/download/download.php?type=DATA&id=asymptotic_decider.vt asymptotic decider in 2d] [http://www.vistrails.org/download/download.php?type=DATA&id=elevation.zip heightfields]<br />
<br />
Note: These vistrails use relative file paths so you don't need to change each of them individually to match your directory structure. Simply unzip the file to whichever location is more convenient. Then, inside VisTrails, open the VisTrails shell, type:<br />
<br />
import os<br />
os.chdir("c:/directory/where/you/unzipped/it")<br />
<br />
This will change the directory so you should be able to just run the pipelines.<br />
<br />
Further reading:<br />
<br />
http://ieeexplore.ieee.org/iel5/4271943/4271944/04272091.pdf<br />
<br />
http://www.jstor.org/stable/pdfplus/2683294.pdf<br />
<br />
[http://www.inf.ufrgs.br/%7Eoliveira/pubs_files/Kuhn_Oliveira_Fernandes_Vis2008.pdf An Efﬁcient Naturalness-Preserving Image-Recoloring Method for Dichromats]<br />
<br />
== 9/30: 2D Visualization Techniques ==<br />
<br />
Lecturer: Jens Krueger and Claudio<br />
<br />
Topics: 2-D vector fields, div, grad, curl in 2D; Steady vs Unsteady flows; Glyphs; 2-D streamlines, streaklines, pathlines<br />
<br />
Slides: [http://www.vistrails.org/download/download.php?type=PUB&id=2d_vector_vis.pdf pdf file]<br />
<br />
Further reading:<br />
<br />
http://en.wikipedia.org/wiki/Streamlines,_streaklines_and_pathlines<br />
<br />
http://en.wikipedia.org/wiki/Euler's_method<br />
<br />
http://en.wikipedia.org/wiki/Runge-Kutta<br />
<br />
Demos:<br />
<br />
http://www.win.tue.nl/~vanwijk/ibfv/<br />
<br />
http://www.javaview.de/demo/PaLIC.html<br />
<br />
Vistrails: [http://www.vistrails.org/download/download.php?type=DATA&id=vector_vis_1.zip vistrail with steady vector field vis and data] [http://www.vistrails.org/download/download.php?type=DATA&id=unsteady.zip vistrail with unsteady vector field vis and data] '''Note:''' Because VTK does not support time-varying datasets directly, we had to create a reasonably ugly hack to simulate unsteady fields. This means the datasets are quite big (80MB in total).<br />
<br />
[http://wwwcg.in.tum.de/Download/PE "The Dx9 Particle Engine" as well as a few datasets]<br />
<br />
== 10/2: Volume Vis ==<br />
<br />
Lecturer: Carlos<br />
<br />
Topics: Slicing; Contours; Marching algorithms<br />
<br />
Slides: [http://www.cs.utah.edu/~csilva/courses/cs5630/iso-basic.pdf iso-basic.pdf]<br />
<br />
References:<br />
<br />
[http://portal.acm.org/citation.cfm?id=37401.37422 Marching cubes: A high resolution 3D surface construction algorithm]<br />
<br />
[http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=175782 The asymptotic decider: resolving the ambiguity in marching cubes]<br />
<br />
== 10/2: Volume Vis == <br />
<br />
Lecturer: Carlos<br />
<br />
Topics: Accelerating structures; High-quality contours<br />
<br />
Slides: <br />
<br />
[http://www.cs.utah.edu/~csilva/courses/cs5630/iso-speed.pdf iso-speed.pdf]<br />
<br />
[http://www.cs.utah.edu/~csilva/courses/cs5630/iso-speed-2.pdf iso-speed-2.pdf]<br />
<br />
References:<br />
<br />
[http://doi.ieeecomputersociety.org/10.1109/2945.489388 A Near Optimal Isosurface Extraction Algorithm Using the Span Space]<br />
<br />
[http://doi.ieeecomputersociety.org/10.1109/2945.485619 Automatic Isosurface Propagation Using an Extrema Graph and Sorted Boundary Cell Lists]<br />
<br />
[http://doi.ieeecomputersociety.org/10.1109/2945.597798 Speeding Up Isosurface Extraction Using Interval Trees]<br />
<br />
[http://doi.ieeecomputersociety.org/10.1109/SVVG.2004.5 Implicit Occluders]<br />
<br />
== 10/9: Volume Vis ==<br />
<br />
Lecturer: Carlos Scheidegger<br />
<br />
Topics: High quality isosurfaces<br />
<br />
Slides: [http://www.cs.utah.edu/~csilva/courses/cs5630/iso-quality.pdf iso-quality.pdf]<br />
<br />
References:<br />
<br />
[http://www.cs.utah.edu/~csilva/2007-sub/macet.pdf Edge Transformations for Improving Mesh Quality of Marching Cubes]<br />
<br />
[http://www.sci.utah.edu/~csilva/papers/tvcg2006acr.pdf High-Quality Extraction of Isosurfaces from Regular and Irregular Grids]<br />
<br />
[http://portal.acm.org/citation.cfm?id=566570.566586 Dual contouring of hermite data]<br />
<br />
[http://www.sci.utah.edu/%7Emiriah/research/meshing/vis07meyer.pdf Topology, Accuracy, and Quality of Isosurface Meshes Using Dynamic Particles]<br />
<br />
[http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=1260744 Material interface reconstruction]<br />
<br />
== 10/14: Fall break == <br />
<br />
== 10/16: Fall break == <br />
<br />
== 10/21: Direct Volume Rendering ==<br />
<br />
Lecturer: Huy Vo<br />
<br />
Topics: Introduction to volume rendering<br />
<br />
Slides: [http://www.sci.utah.edu/~stevec/classes/cs5630/VolumeRendering1.pdf VolumeRendering1.pdf]<br />
<br />
Notes: [http://www.sci.utah.edu/~stevec/classes/cs5630/dvr.pdf dvr.pdf]<br />
<br />
vistrails: [http://www.sci.utah.edu/~stevec/classes/cs5630/VolumeRenderingVistrails.zip VolumeRenderingVistrails.zip]<br />
<br />
References:<br />
[http://www.llnl.gov/graphics/docs/OpticalModelsLong.pdf Optical Models for Direct Volume Rendering]<br />
<br />
== 10/23: Midterm 1 ==<br />
<br />
== 10/28: Direct Volume Rendering ==<br />
<br />
Lecturer: Claudio<br />
<br />
Topics: Structured grid techniques: ray-casting, splatting, texture slicing, shear-warp<br />
<br />
Slides: [http://www.sci.utah.edu/~stevec/classes/cs5630/VolumeRendering2.pdf VolumeRendering2.pdf]<br />
<br />
Notes: same as previous class<br />
<br />
vistrails: same as previous class<br />
<br />
References:<br />
<br />
[http://graphics.stanford.edu/papers/volume-cga88/ Display of Surfaces from Volume Data] - Ray casting paper<br />
<br />
[http://portal.acm.org/citation.cfm?id=329138 Interactive Volume Rendering] - Splatting paper, paper requires ACM digital library access<br />
<br />
[http://portal.acm.org/citation.cfm?id=197972&dl=ACM&coll=GUIDE Accelerated volume rendering and tomographic reconstruction using texture mapping hardware] - Texture slicing paper, requires ACM digital library access<br />
<br />
[http://graphics.stanford.edu/papers/shear/ Fast Volume Rendering Using a Shear-Warp Factorization of the Viewing Transformation] - Shear-warp paper<br />
<br />
== 10/30: Invited Lecture by Professor Joao Comba ==<br />
Title: Edge Groups: An Approach to Understanding the Mesh Quality of Marching Methods<br />
<br />
Abstract: Marching Cubes is the most popular isosurface extraction algorithm due to its simplicity, efficiency and robustness. It has been widely studied, improved, and extended. While much early work was concerned with efficiency and correctness issues, lately there has been a push to improve the quality of Marching Cubes meshes so that they can be used in computational codes. In this work we present a new classification of MC cases that we call Edge Groups, which helps elucidate the issues that impact the triangle quality of the meshes that the method generates. This formulation allows a more systematic way to bound the triangle quality, and is general enough to extend to other polyhedral cell shapes used in other polygonization algorithms. Using this analysis, we also discuss ways to improve the quality of the resulting triangle mesh, including some that require only minor modifications of the original algorithm.<br />
<br />
This is joint work with Carlos A. Dietrich, Carlos E. Scheidegger, Luciana P. Nedel and Claudio T. Silva, and was presented last week at IEEE Visualization 2008.<br />
<br />
Slides: [http://www.vistrails.org/download/download.php?type=PUB&id=comba_talk.pdf pdf file]<br />
<br />
== 11/4: Direct Volume Rendering ==<br />
<br />
Lecturer: Jens Kruger<br />
<br />
Topics: Unstructured grid techniques<br />
<br />
Slides: [http://www.cs.utah.edu/~csilva/courses/cs5630/unstructured_grid_rendering.pdf unstructured_grid_rendering.pdf]<br />
<br />
References:<br />
<br />
[http://www.sci.utah.edu/~csilva/papers/rita2005.pdf A Survey of GPU-Based Volume Rendering of Unstructured Grid]<br />
<br />
[http://www.sci.utah.edu/~csilva/papers/tvcg2005cr.pdf Hardware-Assisted Visibility Sorting for Unstructured Volume Rendering] (This technique is implemented in VTK: http://www.vtk.org/doc/nightly/html/classvtkHAVSVolumeMapper.html)<br />
<br />
[http://www.sci.utah.edu/~csilva/papers/volvis2000.pdf ZSWEEP: An Efficient and Exact Projection Algorithm for Unstructured Volume Rendering] (This technique is implemented in VTK: http://www.vtk.org/doc/nightly/html/classvtkUnstructuredGridVolumeZSweepMapper.html)<br />
<br />
== 11/6: Direct Volume Rendering ==<br />
<br />
Lecturer: Claudio<br />
<br />
Topics: Unstructured grid techniques (continuation from last class)<br />
<br />
== 11/11: Direct Volume Rendering ==<br />
<br />
Lecturer: Claudio<br />
<br />
Topics: Transfer function specification<br />
<br />
Slides: [http://www.cs.utah.edu/~csilva/courses/cs5630/transfer_functions.pdf transfer_functions.pdf]<br />
<br />
References: <br />
<br />
[http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=920623 The transfer function bake-off]<br />
<br />
[http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=663875 The contour spectrum]<br />
<br />
[http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=1021579 Multidimensional transfer functions for interactive volume rendering]<br />
<br />
[http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=729588 Semi-automatic generation of transfer functions for direct volume rendering]<br />
<br />
Additional Question:<br />
<br />
[[Image:Synthetic_slice_tf.png]]<br />
<br />
The above image is the sphere data and joint histogram discussed in class. Which material boundary is highlighted by the small arc on the right-side of the histogram? The colors in the original dataset can be interpreted as:<br />
<br />
0 = Blue<br />
<br />
1 = Green<br />
<br />
2 = Red<br />
<br />
== 11/13: Direct Volume Rendering ==<br />
<br />
Lecturer: Claudio<br />
<br />
Topics: Transfer function specification<br />
<br />
References: <br />
<br />
[http://ieeexplore.ieee.org/search/wrapper.jsp?arnumber=568113 Generation of transfer functions with stochastic search techniques]<br />
<br />
[http://portal.acm.org/citation.cfm?id=258734.258887 Design galleries: a general approach to setting parameters for computer graphics and animation]<br />
<br />
[http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=4653210 Transfer-Function Specification for Rendering Disparate Volumes] (and corresponding [http://www.sci.utah.edu/~stevec/movies/TransferFunction-QT-H.264.mov video])<br />
<br />
== 11/18: Intro to Geometry Processing ==<br />
<br />
Lecturer: Claudio<br />
<br />
== 11/20: Information Visualization ==<br />
<br />
Lecturer: Steve Callahan<br />
<br />
Topics: Intro to InfoVis, clustering, parallel coordinates, graph vis, tree vis, cartograms<br />
<br />
Slides: [http://www.sci.utah.edu/~stevec/classes/cs5630/InfoVis.pdf InfoVis.pdf]<br />
<br />
== 11/25: Information Visualization == <br />
<br />
Lecturer: Steve Callahan<br />
<br />
Topics: InfoVis examples; recent developments<br />
<br />
== 11/27: Thanksgiving == <br />
<br />
== 12/2: Aesthetic Issues in Vis ==<br />
<br />
Lecturer: Claudio<br />
<br />
Topics: Tufte principles<br />
<br />
== 12/4: Aesthetic Issues in Vis ==<br />
<br />
Lecturer: Claudio<br />
<br />
Topics: NPR and Illustrative techniques for Vis<br />
<br />
== 12/9: TBD ==<br />
<br />
== 12/11: TBD ==</div>Thu, 20 Nov 2008 20:35:43 GMTStevechttps://www.vistrails.org//index.php/Talk:SciVisFall2008/ScheduleSciVisFall2008/Schedule
https://www.vistrails.org//index.php?title=SciVisFall2008/Schedule&diff=1508
https://www.vistrails.org//index.php?title=SciVisFall2008/Schedule&diff=1508<p>Stevec: /* 11/20: Information Visualization */</p>
<hr />
<div>== 8/26: Introduction to visualization ==<br />
<br />
Lecturer: Claudio<br />
<br />
Topics: Scientific Visualization<br />
<br />
Notes: [http://www.cs.utah.edu/~csilva/courses/cs5630/lec01-notes.pdf lec01-notes.pdf]<br />
<br />
Slides: [http://www.cs.utah.edu/~csilva/courses/cs5630/fall2008/lec01.pdf intro]<br />
<br />
Animations: [http://www.cs.utah.edu/~csilva/courses/cs5630/fall2007/SevereTstorm.mov NCSA storm animation]<br />
<br />
Further reading:<br />
<br />
(Optional reading) [http://www.sci.utah.edu/~csilva/papers/cise2008a.pdf Provenance for Computational Tasks: A Survey]<br />
<br />
== 8/28: The visualization pipeline ==<br />
<br />
Lecturer: Claudio<br />
<br />
Topics: Procedural vs. Dataflow programming; Using Dataflow for the Vis Pipeline; Dataflow programming with VTK; Dataflow programming with VisTrails; python.<br />
<br />
Notes: [http://www.cs.utah.edu/~csilva/courses/cs5630/lec02-notes.pdf lec02-notes.pdf]<br />
<br />
Slides: [http://www.cs.utah.edu/~csilva/courses/cs5630/lec02.pdf lec02.pdf]<br />
<br />
Further reading: <br />
<br />
(Optional reading) [http://www.cs.utah.edu/~csilva/courses/cs5630/reproducible_vis.pdf Provenance for Visualizations: Reproducibility and Beyond], C. Silva, J. Freire, and S. Callahan, IEEE Computing in Science and Engineering, 2008.<br />
<br />
== 9/2: Modeling Data for Visualization ==<br />
<br />
Lecturer: Claudio<br />
<br />
Topics: Discrete vs continous data; Sampling and interpolation; Point vs triangulated data; Meshing data types; Regular vs irregular data; Tabular data; Vector and tensor fields<br />
<br />
Notes: [http://www.vistrails.org/download/download.php?type=PUB&id=week2.pdf modeling data]<br />
<br />
Slides: [http://www.vistrails.org/download/download.php?type=PUB&id=processing.ppt processing.ppt] <br />
<br />
Further reading:<br />
<br />
[http://www.cs.wisc.edu/graphics/Courses/559-s2001/notes/hanrahan.pdf Basic Signal Processing]<br />
<br />
[http://graphics.cs.uiuc.edu/~garland/papers/quadrics.pdf Surface Simplification Using Quadric Error Metrics]<br />
<br />
(Optional Reading) [http://www.sci.utah.edu/~csilva/papers/vis2001b.pdf A Memory Insensitive Technique for Large Model Simplification]<br />
<br />
(Optional Reading) [http://graphics.cs.uiuc.edu/~garland/papers/TR-2004-2450.pdf Quadric-based Simplification in any Dimension]<br />
<br />
== 9/4: Modeling Data for Visualization == <br />
<br />
Lecturer: Claudio<br />
<br />
Topics: Geometry Processing: Reconstruction and meshing; Simplification; Smoothing; Other Filtering algorithms<br />
<br />
Notes: [http://www.vistrails.org/download/download.php?type=PUB&id=week2.pdf modeling data]<br />
<br />
Slides: [http://www.vistrails.org/download/download.php?type=PUB&id=processing.ppt processing.ppt] <br />
<br />
Further reading:<br />
<br />
http://en.wikipedia.org/wiki/Least_squares<br />
<br />
(Optional Reading) [http://www.sci.utah.edu/~csilva/papers/sig2005.pdf Robust Moving Least-squares Fitting with Sharp Features]<br />
<br />
(Optional Reading) [http://www.sci.utah.edu/~cscheid/pubs/band_mls.pdf Optimal Bandwidth Selection for MLS Surfaces]<br />
<br />
== 9/9: Elementary Plotting Techniques == <br />
<br />
Lecturer: Claudio<br />
<br />
Topics: Principles of Graph Construction<br />
<br />
Notes: [http://www.sci.utah.edu/~stevec/classes/cs5630/PlottingNotes.pdf PlottingNotes.pdf]<br />
<br />
Slides: [http://www.sci.utah.edu/~stevec/slides/SciVis/Plotting1.pdf Plotting1.pdf]<br />
<br />
Further Reading: There is no required reading for this lecture. For those interested in more depth, the following books are very useful:<br />
<br />
* The Elements of Graphing Data. William S. Cleveland, Hobart Press, 2nd Edition, 1994.<br />
<br />
* Visualizing Data. William S. Cleveland, Hobart Press, 1993.<br />
<br />
* The Visual Display of Quantitative Information. Edward R. Tufte, Graphics Press, 2001.<br />
<br />
* Visual Explanations: Images and Quantities, Evidence and Narrative. Edward R. Tufte, Graphics Press, 2997.<br />
<br />
== 9/11: Elementary Plotting Techniques ==<br />
<br />
Lecturer: Claudio<br />
<br />
Topics: Simple Plotting Methods: Dot Plots, Connected Symbol Plots, Scatter Plots, Histograms, Others. Advanced Plotting Methods: Multimodal, Higher Dimensional, Correlation, Uncertainty and Variation.<br />
<br />
Notes: [http://www.sci.utah.edu/~stevec/classes/cs5630/PlottingNotes.pdf PlottingNotes.pdf]<br />
<br />
Slides: [http://www.vistrails.org/download/download.php?type=PUB&id=Plotting2.pdf Plotting2.pdf]<br />
<br />
Vistrails: [http://www.sci.utah.edu/~stevec/classes/cs5630/PlottingVistrails.zip PlottingVistrails.zip] - Unzip this file in the examples directory of your VisTrails installation and it will add the vistrails along with their data sets (in the data directory). If you don't have permission to write to this directory (CADE users), then unzip the file where you want. Just be aware that in this case the paths for the data files may not be correct for most vistrails and will need to be fixed before they will execute properly.<br />
<br />
Further Reading: There is no required reading for this lecture. Some articles of interest:<br />
<br />
* [http://www.fmrib.ox.ac.uk/analysis/techrep/tr00mj2/tr00mj2/node24.html Histogram Bin Size]<br />
* [http://en.wikipedia.org/wiki/Correlation Correlation]<br />
* [http://en.wikipedia.org/wiki/Linear_regression Linear Regression]<br />
* [http://en.wikipedia.org/wiki/Box_plot Box Plots]<br />
<br />
== 9/16: Color and Human Perception ==<br />
<br />
Lecturer: Claudio<br />
<br />
Topics: Human vision system; Optical illusions<br />
<br />
Slides: [http://www.cs.utah.edu/~csilva/courses/cs5630/human-vision.pdf human-vision.pdf]<br />
<br />
Links:<br />
<br />
http://en.wikipedia.org/wiki/Eye<br />
<br />
http://www.grand-illusions.com/gregory2.htm (also, see the related book: [http://www.amazon.com/Eye-Brain-Richard-L-Gregory/dp/0691048371])<br />
<br />
http://en.wikipedia.org/wiki/Purkinje_effect<br />
<br />
http://www.handprint.com/HP/WCL/color2.html<br />
<br />
== 9/18: Color and Human Perception ==<br />
<br />
Lecturer: Jens Krueger<br />
<br />
Topics: Color Science; Color spaces; Color Blindness; Color maps; Tone mapping; <br />
<br />
Slides: [http://www.cs.utah.edu/~csilva/courses/cs5630/colorvision-jens.pdf colorvision-jens.pdf]<br />
<br />
Links:<br />
<br />
Further reading: <br />
<br />
[http://www.research.ibm.com/dx/proceedings/pravda/truevis.htm How Not to Lie with Visualization]<br />
<br />
http://en.wikipedia.org/wiki/Opponent_process<br />
<br />
http://en.wikipedia.org/wiki/Color_models<br />
<br />
http://en.wikipedia.org/wiki/Absolute_color_space<br />
<br />
http://en.wikipedia.org/wiki/Additive_color<br />
<br />
http://en.wikipedia.org/wiki/Subtractive_color<br />
<br />
http://en.wikipedia.org/wiki/RGB_color_model<br />
<br />
http://en.wikipedia.org/wiki/SRGB_color_space<br />
<br />
http://en.wikipedia.org/wiki/CIE_XYZ_color_space<br />
<br />
== 9/23: Math refresher ==<br />
<br />
Lecturer: Carlos Scheidegger<br />
<br />
Topics: Basic linear algebra; vectors; basic differential geometry (space curves, tangents, normals, surfaces); basic vector calculus (gradient, divergence, curl, gauss' theorem, green's theorem)<br />
<br />
Links:<br />
<br />
[http://www.falstad.com/vector Vector Field Applet]<br />
<br />
Further Reading:<br />
<br />
http://en.wikipedia.org/wiki/Vector_calculus<br />
<br />
Appendix A of these notes might be useful: [http://www.cs.ubc.ca/~rbridson/fluidsimulation/fluids_notes.pdf]<br />
<br />
Two books that take a very accessible approach at vector calculus:<br />
<br />
[http://www.amazon.com/Div-Grad-Curl-All-That/dp/0393969975 Div, Grad, Curl, and All That: An Informal Text on Vector Calculus]<br />
<br />
[http://www.cambridge.org/uk/catalogue/catalogue.asp?isbn=9780521877619 A Student's Guide to Maxwell's Equations]<br />
<br />
== 9/25 2D Visualization Techniques ==<br />
<br />
Lecturer: Claudio<br />
<br />
Topics: 2-D contours, marching quads, marching tris; Color mapping; height fields; NPR<br />
<br />
Slides: [http://www.vistrails.org/download/download.php?type=PUB&id=2d_scalar_vis.pdf pdf file]<br />
<br />
Notes: [http://www.vistrails.org/download/download.php?type=PUB&id=2d_scalar_vis_notes.pdf pdf file]<br />
<br />
Vistrails: [http://www.vistrails.org/download/download.php?type=DATA&id=ozone_and_data.zip zip file with ozone.vt and data] [http://www.vistrails.org/download/download.php?type=DATA&id=asymptotic_decider.vt asymptotic decider in 2d] [http://www.vistrails.org/download/download.php?type=DATA&id=elevation.zip heightfields]<br />
<br />
Note: These vistrails use relative file paths so you don't need to change each of them individually to match your directory structure. Simply unzip the file to whichever location is more convenient. Then, inside VisTrails, open the VisTrails shell, type:<br />
<br />
import os<br />
os.chdir("c:/directory/where/you/unzipped/it")<br />
<br />
This will change the directory so you should be able to just run the pipelines.<br />
<br />
Further reading:<br />
<br />
http://ieeexplore.ieee.org/iel5/4271943/4271944/04272091.pdf<br />
<br />
http://www.jstor.org/stable/pdfplus/2683294.pdf<br />
<br />
[http://www.inf.ufrgs.br/%7Eoliveira/pubs_files/Kuhn_Oliveira_Fernandes_Vis2008.pdf An Efﬁcient Naturalness-Preserving Image-Recoloring Method for Dichromats]<br />
<br />
== 9/30: 2D Visualization Techniques ==<br />
<br />
Lecturer: Jens Krueger and Claudio<br />
<br />
Topics: 2-D vector fields, div, grad, curl in 2D; Steady vs Unsteady flows; Glyphs; 2-D streamlines, streaklines, pathlines<br />
<br />
Slides: [http://www.vistrails.org/download/download.php?type=PUB&id=2d_vector_vis.pdf pdf file]<br />
<br />
Further reading:<br />
<br />
http://en.wikipedia.org/wiki/Streamlines,_streaklines_and_pathlines<br />
<br />
http://en.wikipedia.org/wiki/Euler's_method<br />
<br />
http://en.wikipedia.org/wiki/Runge-Kutta<br />
<br />
Demos:<br />
<br />
http://www.win.tue.nl/~vanwijk/ibfv/<br />
<br />
http://www.javaview.de/demo/PaLIC.html<br />
<br />
Vistrails: [http://www.vistrails.org/download/download.php?type=DATA&id=vector_vis_1.zip vistrail with steady vector field vis and data] [http://www.vistrails.org/download/download.php?type=DATA&id=unsteady.zip vistrail with unsteady vector field vis and data] '''Note:''' Because VTK does not support time-varying datasets directly, we had to create a reasonably ugly hack to simulate unsteady fields. This means the datasets are quite big (80MB in total).<br />
<br />
[http://wwwcg.in.tum.de/Download/PE "The Dx9 Particle Engine" as well as a few datasets]<br />
<br />
== 10/2: Volume Vis ==<br />
<br />
Lecturer: Carlos<br />
<br />
Topics: Slicing; Contours; Marching algorithms<br />
<br />
Slides: [http://www.cs.utah.edu/~csilva/courses/cs5630/iso-basic.pdf iso-basic.pdf]<br />
<br />
References:<br />
<br />
[http://portal.acm.org/citation.cfm?id=37401.37422 Marching cubes: A high resolution 3D surface construction algorithm]<br />
<br />
[http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=175782 The asymptotic decider: resolving the ambiguity in marching cubes]<br />
<br />
== 10/2: Volume Vis == <br />
<br />
Lecturer: Carlos<br />
<br />
Topics: Accelerating structures; High-quality contours<br />
<br />
Slides: <br />
<br />
[http://www.cs.utah.edu/~csilva/courses/cs5630/iso-speed.pdf iso-speed.pdf]<br />
<br />
[http://www.cs.utah.edu/~csilva/courses/cs5630/iso-speed-2.pdf iso-speed-2.pdf]<br />
<br />
References:<br />
<br />
[http://doi.ieeecomputersociety.org/10.1109/2945.489388 A Near Optimal Isosurface Extraction Algorithm Using the Span Space]<br />
<br />
[http://doi.ieeecomputersociety.org/10.1109/2945.485619 Automatic Isosurface Propagation Using an Extrema Graph and Sorted Boundary Cell Lists]<br />
<br />
[http://doi.ieeecomputersociety.org/10.1109/2945.597798 Speeding Up Isosurface Extraction Using Interval Trees]<br />
<br />
[http://doi.ieeecomputersociety.org/10.1109/SVVG.2004.5 Implicit Occluders]<br />
<br />
== 10/9: Volume Vis ==<br />
<br />
Lecturer: Carlos Scheidegger<br />
<br />
Topics: High quality isosurfaces<br />
<br />
Slides: [http://www.cs.utah.edu/~csilva/courses/cs5630/iso-quality.pdf iso-quality.pdf]<br />
<br />
References:<br />
<br />
[http://www.cs.utah.edu/~csilva/2007-sub/macet.pdf Edge Transformations for Improving Mesh Quality of Marching Cubes]<br />
<br />
[http://www.sci.utah.edu/~csilva/papers/tvcg2006acr.pdf High-Quality Extraction of Isosurfaces from Regular and Irregular Grids]<br />
<br />
[http://portal.acm.org/citation.cfm?id=566570.566586 Dual contouring of hermite data]<br />
<br />
[http://www.sci.utah.edu/%7Emiriah/research/meshing/vis07meyer.pdf Topology, Accuracy, and Quality of Isosurface Meshes Using Dynamic Particles]<br />
<br />
[http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=1260744 Material interface reconstruction]<br />
<br />
== 10/14: Fall break == <br />
<br />
== 10/16: Fall break == <br />
<br />
== 10/21: Direct Volume Rendering ==<br />
<br />
Lecturer: Huy Vo<br />
<br />
Topics: Introduction to volume rendering<br />
<br />
Slides: [http://www.sci.utah.edu/~stevec/classes/cs5630/VolumeRendering1.pdf VolumeRendering1.pdf]<br />
<br />
Notes: [http://www.sci.utah.edu/~stevec/classes/cs5630/dvr.pdf dvr.pdf]<br />
<br />
vistrails: [http://www.sci.utah.edu/~stevec/classes/cs5630/VolumeRenderingVistrails.zip VolumeRenderingVistrails.zip]<br />
<br />
References:<br />
[http://www.llnl.gov/graphics/docs/OpticalModelsLong.pdf Optical Models for Direct Volume Rendering]<br />
<br />
== 10/23: Midterm 1 ==<br />
<br />
== 10/28: Direct Volume Rendering ==<br />
<br />
Lecturer: Claudio<br />
<br />
Topics: Structured grid techniques: ray-casting, splatting, texture slicing, shear-warp<br />
<br />
Slides: [http://www.sci.utah.edu/~stevec/classes/cs5630/VolumeRendering2.pdf VolumeRendering2.pdf]<br />
<br />
Notes: same as previous class<br />
<br />
vistrails: same as previous class<br />
<br />
References:<br />
<br />
[http://graphics.stanford.edu/papers/volume-cga88/ Display of Surfaces from Volume Data] - Ray casting paper<br />
<br />
[http://portal.acm.org/citation.cfm?id=329138 Interactive Volume Rendering] - Splatting paper, paper requires ACM digital library access<br />
<br />
[http://portal.acm.org/citation.cfm?id=197972&dl=ACM&coll=GUIDE Accelerated volume rendering and tomographic reconstruction using texture mapping hardware] - Texture slicing paper, requires ACM digital library access<br />
<br />
[http://graphics.stanford.edu/papers/shear/ Fast Volume Rendering Using a Shear-Warp Factorization of the Viewing Transformation] - Shear-warp paper<br />
<br />
== 10/30: Invited Lecture by Professor Joao Comba ==<br />
Title: Edge Groups: An Approach to Understanding the Mesh Quality of Marching Methods<br />
<br />
Abstract: Marching Cubes is the most popular isosurface extraction algorithm due to its simplicity, efficiency and robustness. It has been widely studied, improved, and extended. While much early work was concerned with efficiency and correctness issues, lately there has been a push to improve the quality of Marching Cubes meshes so that they can be used in computational codes. In this work we present a new classification of MC cases that we call Edge Groups, which helps elucidate the issues that impact the triangle quality of the meshes that the method generates. This formulation allows a more systematic way to bound the triangle quality, and is general enough to extend to other polyhedral cell shapes used in other polygonization algorithms. Using this analysis, we also discuss ways to improve the quality of the resulting triangle mesh, including some that require only minor modifications of the original algorithm.<br />
<br />
This is joint work with Carlos A. Dietrich, Carlos E. Scheidegger, Luciana P. Nedel and Claudio T. Silva, and was presented last week at IEEE Visualization 2008.<br />
<br />
Slides: [http://www.vistrails.org/download/download.php?type=PUB&id=comba_talk.pdf pdf file]<br />
<br />
== 11/4: Direct Volume Rendering ==<br />
<br />
Lecturer: Jens Kruger<br />
<br />
Topics: Unstructured grid techniques<br />
<br />
Slides: [http://www.cs.utah.edu/~csilva/courses/cs5630/unstructured_grid_rendering.pdf unstructured_grid_rendering.pdf]<br />
<br />
References:<br />
<br />
[http://www.sci.utah.edu/~csilva/papers/rita2005.pdf A Survey of GPU-Based Volume Rendering of Unstructured Grid]<br />
<br />
[http://www.sci.utah.edu/~csilva/papers/tvcg2005cr.pdf Hardware-Assisted Visibility Sorting for Unstructured Volume Rendering] (This technique is implemented in VTK: http://www.vtk.org/doc/nightly/html/classvtkHAVSVolumeMapper.html)<br />
<br />
[http://www.sci.utah.edu/~csilva/papers/volvis2000.pdf ZSWEEP: An Efficient and Exact Projection Algorithm for Unstructured Volume Rendering] (This technique is implemented in VTK: http://www.vtk.org/doc/nightly/html/classvtkUnstructuredGridVolumeZSweepMapper.html)<br />
<br />
== 11/6: Direct Volume Rendering ==<br />
<br />
Lecturer: Claudio<br />
<br />
Topics: Unstructured grid techniques (continuation from last class)<br />
<br />
== 11/11: Direct Volume Rendering ==<br />
<br />
Lecturer: Claudio<br />
<br />
Topics: Transfer function specification<br />
<br />
Slides: [http://www.cs.utah.edu/~csilva/courses/cs5630/transfer_functions.pdf transfer_functions.pdf]<br />
<br />
References: <br />
<br />
[http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=920623 The transfer function bake-off]<br />
<br />
[http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=663875 The contour spectrum]<br />
<br />
[http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=1021579 Multidimensional transfer functions for interactive volume rendering]<br />
<br />
[http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=729588 Semi-automatic generation of transfer functions for direct volume rendering]<br />
<br />
Additional Question:<br />
<br />
[[Image:Synthetic_slice_tf.png]]<br />
<br />
The above image is the sphere data and joint histogram discussed in class. Which material boundary is highlighted by the small arc on the right-side of the histogram? The colors in the original dataset can be interpreted as:<br />
<br />
0 = Blue<br />
<br />
1 = Green<br />
<br />
2 = Red<br />
<br />
== 11/13: Direct Volume Rendering ==<br />
<br />
Lecturer: Claudio<br />
<br />
Topics: Transfer function specification<br />
<br />
References: <br />
<br />
[http://ieeexplore.ieee.org/search/wrapper.jsp?arnumber=568113 Generation of transfer functions with stochastic search techniques]<br />
<br />
[http://portal.acm.org/citation.cfm?id=258734.258887 Design galleries: a general approach to setting parameters for computer graphics and animation]<br />
<br />
[http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=4653210 Transfer-Function Specification for Rendering Disparate Volumes] (and corresponding [http://www.sci.utah.edu/~stevec/movies/TransferFunction-QT-H.264.mov video])<br />
<br />
== 11/18: Intro to Geometry Processing ==<br />
<br />
Lecturer: Claudio<br />
<br />
== 11/20: Information Visualization ==<br />
<br />
Lecturer: Steve Callahan<br />
<br />
Topics: Intro to InfoVis, clustering, parallel coordinates, graph vis, tree vis, cartograms<br />
<br />
== 11/25: Information Visualization == <br />
<br />
Lecturer: Steve Callahan<br />
<br />
Topics: InfoVis examples; recent developments<br />
<br />
== 11/27: Thanksgiving == <br />
<br />
== 12/2: Aesthetic Issues in Vis ==<br />
<br />
Lecturer: Claudio<br />
<br />
Topics: Tufte principles<br />
<br />
== 12/4: Aesthetic Issues in Vis ==<br />
<br />
Lecturer: Claudio<br />
<br />
Topics: NPR and Illustrative techniques for Vis<br />
<br />
== 12/9: TBD ==<br />
<br />
== 12/11: TBD ==</div>Tue, 18 Nov 2008 23:31:38 GMTStevechttps://www.vistrails.org//index.php/Talk:SciVisFall2008/ScheduleSciVisFall2008/Schedule
https://www.vistrails.org//index.php?title=SciVisFall2008/Schedule&diff=1507
https://www.vistrails.org//index.php?title=SciVisFall2008/Schedule&diff=1507<p>Stevec: </p>
<hr />
<div>== 8/26: Introduction to visualization ==<br />
<br />
Lecturer: Claudio<br />
<br />
Topics: Scientific Visualization<br />
<br />
Notes: [http://www.cs.utah.edu/~csilva/courses/cs5630/lec01-notes.pdf lec01-notes.pdf]<br />
<br />
Slides: [http://www.cs.utah.edu/~csilva/courses/cs5630/fall2008/lec01.pdf intro]<br />
<br />
Animations: [http://www.cs.utah.edu/~csilva/courses/cs5630/fall2007/SevereTstorm.mov NCSA storm animation]<br />
<br />
Further reading:<br />
<br />
(Optional reading) [http://www.sci.utah.edu/~csilva/papers/cise2008a.pdf Provenance for Computational Tasks: A Survey]<br />
<br />
== 8/28: The visualization pipeline ==<br />
<br />
Lecturer: Claudio<br />
<br />
Topics: Procedural vs. Dataflow programming; Using Dataflow for the Vis Pipeline; Dataflow programming with VTK; Dataflow programming with VisTrails; python.<br />
<br />
Notes: [http://www.cs.utah.edu/~csilva/courses/cs5630/lec02-notes.pdf lec02-notes.pdf]<br />
<br />
Slides: [http://www.cs.utah.edu/~csilva/courses/cs5630/lec02.pdf lec02.pdf]<br />
<br />
Further reading: <br />
<br />
(Optional reading) [http://www.cs.utah.edu/~csilva/courses/cs5630/reproducible_vis.pdf Provenance for Visualizations: Reproducibility and Beyond], C. Silva, J. Freire, and S. Callahan, IEEE Computing in Science and Engineering, 2008.<br />
<br />
== 9/2: Modeling Data for Visualization ==<br />
<br />
Lecturer: Claudio<br />
<br />
Topics: Discrete vs continous data; Sampling and interpolation; Point vs triangulated data; Meshing data types; Regular vs irregular data; Tabular data; Vector and tensor fields<br />
<br />
Notes: [http://www.vistrails.org/download/download.php?type=PUB&id=week2.pdf modeling data]<br />
<br />
Slides: [http://www.vistrails.org/download/download.php?type=PUB&id=processing.ppt processing.ppt] <br />
<br />
Further reading:<br />
<br />
[http://www.cs.wisc.edu/graphics/Courses/559-s2001/notes/hanrahan.pdf Basic Signal Processing]<br />
<br />
[http://graphics.cs.uiuc.edu/~garland/papers/quadrics.pdf Surface Simplification Using Quadric Error Metrics]<br />
<br />
(Optional Reading) [http://www.sci.utah.edu/~csilva/papers/vis2001b.pdf A Memory Insensitive Technique for Large Model Simplification]<br />
<br />
(Optional Reading) [http://graphics.cs.uiuc.edu/~garland/papers/TR-2004-2450.pdf Quadric-based Simplification in any Dimension]<br />
<br />
== 9/4: Modeling Data for Visualization == <br />
<br />
Lecturer: Claudio<br />
<br />
Topics: Geometry Processing: Reconstruction and meshing; Simplification; Smoothing; Other Filtering algorithms<br />
<br />
Notes: [http://www.vistrails.org/download/download.php?type=PUB&id=week2.pdf modeling data]<br />
<br />
Slides: [http://www.vistrails.org/download/download.php?type=PUB&id=processing.ppt processing.ppt] <br />
<br />
Further reading:<br />
<br />
http://en.wikipedia.org/wiki/Least_squares<br />
<br />
(Optional Reading) [http://www.sci.utah.edu/~csilva/papers/sig2005.pdf Robust Moving Least-squares Fitting with Sharp Features]<br />
<br />
(Optional Reading) [http://www.sci.utah.edu/~cscheid/pubs/band_mls.pdf Optimal Bandwidth Selection for MLS Surfaces]<br />
<br />
== 9/9: Elementary Plotting Techniques == <br />
<br />
Lecturer: Claudio<br />
<br />
Topics: Principles of Graph Construction<br />
<br />
Notes: [http://www.sci.utah.edu/~stevec/classes/cs5630/PlottingNotes.pdf PlottingNotes.pdf]<br />
<br />
Slides: [http://www.sci.utah.edu/~stevec/slides/SciVis/Plotting1.pdf Plotting1.pdf]<br />
<br />
Further Reading: There is no required reading for this lecture. For those interested in more depth, the following books are very useful:<br />
<br />
* The Elements of Graphing Data. William S. Cleveland, Hobart Press, 2nd Edition, 1994.<br />
<br />
* Visualizing Data. William S. Cleveland, Hobart Press, 1993.<br />
<br />
* The Visual Display of Quantitative Information. Edward R. Tufte, Graphics Press, 2001.<br />
<br />
* Visual Explanations: Images and Quantities, Evidence and Narrative. Edward R. Tufte, Graphics Press, 2997.<br />
<br />
== 9/11: Elementary Plotting Techniques ==<br />
<br />
Lecturer: Claudio<br />
<br />
Topics: Simple Plotting Methods: Dot Plots, Connected Symbol Plots, Scatter Plots, Histograms, Others. Advanced Plotting Methods: Multimodal, Higher Dimensional, Correlation, Uncertainty and Variation.<br />
<br />
Notes: [http://www.sci.utah.edu/~stevec/classes/cs5630/PlottingNotes.pdf PlottingNotes.pdf]<br />
<br />
Slides: [http://www.vistrails.org/download/download.php?type=PUB&id=Plotting2.pdf Plotting2.pdf]<br />
<br />
Vistrails: [http://www.sci.utah.edu/~stevec/classes/cs5630/PlottingVistrails.zip PlottingVistrails.zip] - Unzip this file in the examples directory of your VisTrails installation and it will add the vistrails along with their data sets (in the data directory). If you don't have permission to write to this directory (CADE users), then unzip the file where you want. Just be aware that in this case the paths for the data files may not be correct for most vistrails and will need to be fixed before they will execute properly.<br />
<br />
Further Reading: There is no required reading for this lecture. Some articles of interest:<br />
<br />
* [http://www.fmrib.ox.ac.uk/analysis/techrep/tr00mj2/tr00mj2/node24.html Histogram Bin Size]<br />
* [http://en.wikipedia.org/wiki/Correlation Correlation]<br />
* [http://en.wikipedia.org/wiki/Linear_regression Linear Regression]<br />
* [http://en.wikipedia.org/wiki/Box_plot Box Plots]<br />
<br />
== 9/16: Color and Human Perception ==<br />
<br />
Lecturer: Claudio<br />
<br />
Topics: Human vision system; Optical illusions<br />
<br />
Slides: [http://www.cs.utah.edu/~csilva/courses/cs5630/human-vision.pdf human-vision.pdf]<br />
<br />
Links:<br />
<br />
http://en.wikipedia.org/wiki/Eye<br />
<br />
http://www.grand-illusions.com/gregory2.htm (also, see the related book: [http://www.amazon.com/Eye-Brain-Richard-L-Gregory/dp/0691048371])<br />
<br />
http://en.wikipedia.org/wiki/Purkinje_effect<br />
<br />
http://www.handprint.com/HP/WCL/color2.html<br />
<br />
== 9/18: Color and Human Perception ==<br />
<br />
Lecturer: Jens Krueger<br />
<br />
Topics: Color Science; Color spaces; Color Blindness; Color maps; Tone mapping; <br />
<br />
Slides: [http://www.cs.utah.edu/~csilva/courses/cs5630/colorvision-jens.pdf colorvision-jens.pdf]<br />
<br />
Links:<br />
<br />
Further reading: <br />
<br />
[http://www.research.ibm.com/dx/proceedings/pravda/truevis.htm How Not to Lie with Visualization]<br />
<br />
http://en.wikipedia.org/wiki/Opponent_process<br />
<br />
http://en.wikipedia.org/wiki/Color_models<br />
<br />
http://en.wikipedia.org/wiki/Absolute_color_space<br />
<br />
http://en.wikipedia.org/wiki/Additive_color<br />
<br />
http://en.wikipedia.org/wiki/Subtractive_color<br />
<br />
http://en.wikipedia.org/wiki/RGB_color_model<br />
<br />
http://en.wikipedia.org/wiki/SRGB_color_space<br />
<br />
http://en.wikipedia.org/wiki/CIE_XYZ_color_space<br />
<br />
== 9/23: Math refresher ==<br />
<br />
Lecturer: Carlos Scheidegger<br />
<br />
Topics: Basic linear algebra; vectors; basic differential geometry (space curves, tangents, normals, surfaces); basic vector calculus (gradient, divergence, curl, gauss' theorem, green's theorem)<br />
<br />
Links:<br />
<br />
[http://www.falstad.com/vector Vector Field Applet]<br />
<br />
Further Reading:<br />
<br />
http://en.wikipedia.org/wiki/Vector_calculus<br />
<br />
Appendix A of these notes might be useful: [http://www.cs.ubc.ca/~rbridson/fluidsimulation/fluids_notes.pdf]<br />
<br />
Two books that take a very accessible approach at vector calculus:<br />
<br />
[http://www.amazon.com/Div-Grad-Curl-All-That/dp/0393969975 Div, Grad, Curl, and All That: An Informal Text on Vector Calculus]<br />
<br />
[http://www.cambridge.org/uk/catalogue/catalogue.asp?isbn=9780521877619 A Student's Guide to Maxwell's Equations]<br />
<br />
== 9/25 2D Visualization Techniques ==<br />
<br />
Lecturer: Claudio<br />
<br />
Topics: 2-D contours, marching quads, marching tris; Color mapping; height fields; NPR<br />
<br />
Slides: [http://www.vistrails.org/download/download.php?type=PUB&id=2d_scalar_vis.pdf pdf file]<br />
<br />
Notes: [http://www.vistrails.org/download/download.php?type=PUB&id=2d_scalar_vis_notes.pdf pdf file]<br />
<br />
Vistrails: [http://www.vistrails.org/download/download.php?type=DATA&id=ozone_and_data.zip zip file with ozone.vt and data] [http://www.vistrails.org/download/download.php?type=DATA&id=asymptotic_decider.vt asymptotic decider in 2d] [http://www.vistrails.org/download/download.php?type=DATA&id=elevation.zip heightfields]<br />
<br />
Note: These vistrails use relative file paths so you don't need to change each of them individually to match your directory structure. Simply unzip the file to whichever location is more convenient. Then, inside VisTrails, open the VisTrails shell, type:<br />
<br />
import os<br />
os.chdir("c:/directory/where/you/unzipped/it")<br />
<br />
This will change the directory so you should be able to just run the pipelines.<br />
<br />
Further reading:<br />
<br />
http://ieeexplore.ieee.org/iel5/4271943/4271944/04272091.pdf<br />
<br />
http://www.jstor.org/stable/pdfplus/2683294.pdf<br />
<br />
[http://www.inf.ufrgs.br/%7Eoliveira/pubs_files/Kuhn_Oliveira_Fernandes_Vis2008.pdf An Efﬁcient Naturalness-Preserving Image-Recoloring Method for Dichromats]<br />
<br />
== 9/30: 2D Visualization Techniques ==<br />
<br />
Lecturer: Jens Krueger and Claudio<br />
<br />
Topics: 2-D vector fields, div, grad, curl in 2D; Steady vs Unsteady flows; Glyphs; 2-D streamlines, streaklines, pathlines<br />
<br />
Slides: [http://www.vistrails.org/download/download.php?type=PUB&id=2d_vector_vis.pdf pdf file]<br />
<br />
Further reading:<br />
<br />
http://en.wikipedia.org/wiki/Streamlines,_streaklines_and_pathlines<br />
<br />
http://en.wikipedia.org/wiki/Euler's_method<br />
<br />
http://en.wikipedia.org/wiki/Runge-Kutta<br />
<br />
Demos:<br />
<br />
http://www.win.tue.nl/~vanwijk/ibfv/<br />
<br />
http://www.javaview.de/demo/PaLIC.html<br />
<br />
Vistrails: [http://www.vistrails.org/download/download.php?type=DATA&id=vector_vis_1.zip vistrail with steady vector field vis and data] [http://www.vistrails.org/download/download.php?type=DATA&id=unsteady.zip vistrail with unsteady vector field vis and data] '''Note:''' Because VTK does not support time-varying datasets directly, we had to create a reasonably ugly hack to simulate unsteady fields. This means the datasets are quite big (80MB in total).<br />
<br />
[http://wwwcg.in.tum.de/Download/PE "The Dx9 Particle Engine" as well as a few datasets]<br />
<br />
== 10/2: Volume Vis ==<br />
<br />
Lecturer: Carlos<br />
<br />
Topics: Slicing; Contours; Marching algorithms<br />
<br />
Slides: [http://www.cs.utah.edu/~csilva/courses/cs5630/iso-basic.pdf iso-basic.pdf]<br />
<br />
References:<br />
<br />
[http://portal.acm.org/citation.cfm?id=37401.37422 Marching cubes: A high resolution 3D surface construction algorithm]<br />
<br />
[http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=175782 The asymptotic decider: resolving the ambiguity in marching cubes]<br />
<br />
== 10/2: Volume Vis == <br />
<br />
Lecturer: Carlos<br />
<br />
Topics: Accelerating structures; High-quality contours<br />
<br />
Slides: <br />
<br />
[http://www.cs.utah.edu/~csilva/courses/cs5630/iso-speed.pdf iso-speed.pdf]<br />
<br />
[http://www.cs.utah.edu/~csilva/courses/cs5630/iso-speed-2.pdf iso-speed-2.pdf]<br />
<br />
References:<br />
<br />
[http://doi.ieeecomputersociety.org/10.1109/2945.489388 A Near Optimal Isosurface Extraction Algorithm Using the Span Space]<br />
<br />
[http://doi.ieeecomputersociety.org/10.1109/2945.485619 Automatic Isosurface Propagation Using an Extrema Graph and Sorted Boundary Cell Lists]<br />
<br />
[http://doi.ieeecomputersociety.org/10.1109/2945.597798 Speeding Up Isosurface Extraction Using Interval Trees]<br />
<br />
[http://doi.ieeecomputersociety.org/10.1109/SVVG.2004.5 Implicit Occluders]<br />
<br />
== 10/9: Volume Vis ==<br />
<br />
Lecturer: Carlos Scheidegger<br />
<br />
Topics: High quality isosurfaces<br />
<br />
Slides: [http://www.cs.utah.edu/~csilva/courses/cs5630/iso-quality.pdf iso-quality.pdf]<br />
<br />
References:<br />
<br />
[http://www.cs.utah.edu/~csilva/2007-sub/macet.pdf Edge Transformations for Improving Mesh Quality of Marching Cubes]<br />
<br />
[http://www.sci.utah.edu/~csilva/papers/tvcg2006acr.pdf High-Quality Extraction of Isosurfaces from Regular and Irregular Grids]<br />
<br />
[http://portal.acm.org/citation.cfm?id=566570.566586 Dual contouring of hermite data]<br />
<br />
[http://www.sci.utah.edu/%7Emiriah/research/meshing/vis07meyer.pdf Topology, Accuracy, and Quality of Isosurface Meshes Using Dynamic Particles]<br />
<br />
[http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=1260744 Material interface reconstruction]<br />
<br />
== 10/14: Fall break == <br />
<br />
== 10/16: Fall break == <br />
<br />
== 10/21: Direct Volume Rendering ==<br />
<br />
Lecturer: Huy Vo<br />
<br />
Topics: Introduction to volume rendering<br />
<br />
Slides: [http://www.sci.utah.edu/~stevec/classes/cs5630/VolumeRendering1.pdf VolumeRendering1.pdf]<br />
<br />
Notes: [http://www.sci.utah.edu/~stevec/classes/cs5630/dvr.pdf dvr.pdf]<br />
<br />
vistrails: [http://www.sci.utah.edu/~stevec/classes/cs5630/VolumeRenderingVistrails.zip VolumeRenderingVistrails.zip]<br />
<br />
References:<br />
[http://www.llnl.gov/graphics/docs/OpticalModelsLong.pdf Optical Models for Direct Volume Rendering]<br />
<br />
== 10/23: Midterm 1 ==<br />
<br />
== 10/28: Direct Volume Rendering ==<br />
<br />
Lecturer: Claudio<br />
<br />
Topics: Structured grid techniques: ray-casting, splatting, texture slicing, shear-warp<br />
<br />
Slides: [http://www.sci.utah.edu/~stevec/classes/cs5630/VolumeRendering2.pdf VolumeRendering2.pdf]<br />
<br />
Notes: same as previous class<br />
<br />
vistrails: same as previous class<br />
<br />
References:<br />
<br />
[http://graphics.stanford.edu/papers/volume-cga88/ Display of Surfaces from Volume Data] - Ray casting paper<br />
<br />
[http://portal.acm.org/citation.cfm?id=329138 Interactive Volume Rendering] - Splatting paper, paper requires ACM digital library access<br />
<br />
[http://portal.acm.org/citation.cfm?id=197972&dl=ACM&coll=GUIDE Accelerated volume rendering and tomographic reconstruction using texture mapping hardware] - Texture slicing paper, requires ACM digital library access<br />
<br />
[http://graphics.stanford.edu/papers/shear/ Fast Volume Rendering Using a Shear-Warp Factorization of the Viewing Transformation] - Shear-warp paper<br />
<br />
== 10/30: Invited Lecture by Professor Joao Comba ==<br />
Title: Edge Groups: An Approach to Understanding the Mesh Quality of Marching Methods<br />
<br />
Abstract: Marching Cubes is the most popular isosurface extraction algorithm due to its simplicity, efficiency and robustness. It has been widely studied, improved, and extended. While much early work was concerned with efficiency and correctness issues, lately there has been a push to improve the quality of Marching Cubes meshes so that they can be used in computational codes. In this work we present a new classification of MC cases that we call Edge Groups, which helps elucidate the issues that impact the triangle quality of the meshes that the method generates. This formulation allows a more systematic way to bound the triangle quality, and is general enough to extend to other polyhedral cell shapes used in other polygonization algorithms. Using this analysis, we also discuss ways to improve the quality of the resulting triangle mesh, including some that require only minor modifications of the original algorithm.<br />
<br />
This is joint work with Carlos A. Dietrich, Carlos E. Scheidegger, Luciana P. Nedel and Claudio T. Silva, and was presented last week at IEEE Visualization 2008.<br />
<br />
Slides: [http://www.vistrails.org/download/download.php?type=PUB&id=comba_talk.pdf pdf file]<br />
<br />
== 11/4: Direct Volume Rendering ==<br />
<br />
Lecturer: Jens Kruger<br />
<br />
Topics: Unstructured grid techniques<br />
<br />
Slides: [http://www.cs.utah.edu/~csilva/courses/cs5630/unstructured_grid_rendering.pdf unstructured_grid_rendering.pdf]<br />
<br />
References:<br />
<br />
[http://www.sci.utah.edu/~csilva/papers/rita2005.pdf A Survey of GPU-Based Volume Rendering of Unstructured Grid]<br />
<br />
[http://www.sci.utah.edu/~csilva/papers/tvcg2005cr.pdf Hardware-Assisted Visibility Sorting for Unstructured Volume Rendering] (This technique is implemented in VTK: http://www.vtk.org/doc/nightly/html/classvtkHAVSVolumeMapper.html)<br />
<br />
[http://www.sci.utah.edu/~csilva/papers/volvis2000.pdf ZSWEEP: An Efficient and Exact Projection Algorithm for Unstructured Volume Rendering] (This technique is implemented in VTK: http://www.vtk.org/doc/nightly/html/classvtkUnstructuredGridVolumeZSweepMapper.html)<br />
<br />
== 11/6: Direct Volume Rendering ==<br />
<br />
Lecturer: Claudio<br />
<br />
Topics: Unstructured grid techniques (continuation from last class)<br />
<br />
== 11/11: Direct Volume Rendering ==<br />
<br />
Lecturer: Claudio<br />
<br />
Topics: Transfer function specification<br />
<br />
Slides: [http://www.cs.utah.edu/~csilva/courses/cs5630/transfer_functions.pdf transfer_functions.pdf]<br />
<br />
References: <br />
<br />
[http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=920623 The transfer function bake-off]<br />
<br />
[http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=663875 The contour spectrum]<br />
<br />
[http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=1021579 Multidimensional transfer functions for interactive volume rendering]<br />
<br />
[http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=729588 Semi-automatic generation of transfer functions for direct volume rendering]<br />
<br />
Additional Question:<br />
<br />
[[Image:Synthetic_slice_tf.png]]<br />
<br />
The above image is the sphere data and joint histogram discussed in class. Which material boundary is highlighted by the small arc on the right-side of the histogram? The colors in the original dataset can be interpreted as:<br />
<br />
0 = Blue<br />
<br />
1 = Green<br />
<br />
2 = Red<br />
<br />
== 11/13: Direct Volume Rendering ==<br />
<br />
Lecturer: Claudio<br />
<br />
Topics: Transfer function specification<br />
<br />
References: <br />
<br />
[http://ieeexplore.ieee.org/search/wrapper.jsp?arnumber=568113 Generation of transfer functions with stochastic search techniques]<br />
<br />
[http://portal.acm.org/citation.cfm?id=258734.258887 Design galleries: a general approach to setting parameters for computer graphics and animation]<br />
<br />
[http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=4653210 Transfer-Function Specification for Rendering Disparate Volumes] (and corresponding [http://www.sci.utah.edu/~stevec/movies/TransferFunction-QT-H.264.mov video])<br />
<br />
== 11/18: Intro to Geometry Processing ==<br />
<br />
Lecturer: Claudio<br />
<br />
== 11/20: Information Visualization ==<br />
<br />
Lecturer: Steve Callahan<br />
<br />
Topics: Parallel coordinates; graph and tree visualization<br />
<br />
== 11/25: Information Visualization == <br />
<br />
Lecturer: Steve Callahan<br />
<br />
Topics: InfoVis examples; recent developments<br />
<br />
== 11/27: Thanksgiving == <br />
<br />
== 12/2: Aesthetic Issues in Vis ==<br />
<br />
Lecturer: Claudio<br />
<br />
Topics: Tufte principles<br />
<br />
== 12/4: Aesthetic Issues in Vis ==<br />
<br />
Lecturer: Claudio<br />
<br />
Topics: NPR and Illustrative techniques for Vis<br />
<br />
== 12/9: TBD ==<br />
<br />
== 12/11: TBD ==</div>Tue, 18 Nov 2008 17:47:46 GMTStevechttps://www.vistrails.org//index.php/Talk:SciVisFall2008/ScheduleCise-jan-2008
https://www.vistrails.org//index.php?title=Cise-jan-2008&diff=959
https://www.vistrails.org//index.php?title=Cise-jan-2008&diff=959<p>Stevec: /* Supporting Material */</p>
<hr />
<div>==Direct Volume Rendering: A 3D Plotting Technique for Scientific Data==<br />
<br />
===Abstract===<br />
<br />
Direct volume rendering is an effective method for plotting 3D scientific data, but it's not as frequently used as it <br />
could be. Here, the authors summarize direct volume rendering and discuss barriers to taking advantage of this powerful technique.<br />
<br />
===Summary===<br />
The article describes the basics of volume rendering by contrasting it with other techniques using a dataset created using an implicit function. A sidebar also shows a case study using a volume that was aquired with a CT scanner of a torso. Both of these sets of images are fully reproducible.<br />
<br />
===Supporting Material===<br />
<br />
The exploration process that lead to the visualizations in the text were captured in a vistrail that can be loaded and executed with the [[Main_Page | VisTrails]] system. The vistrails can be obtained here:<br />
<br />
[http://www.vistrails.org/download/download.php?type=PUB&id=cise_jan08_implicit.vt Sep07 implicit function vistrail]<br />
<br />
[http://www.vistrails.org/download/download.php?type=PUB&id=cise_jan08_chest.vt Sep07 case study vistrail]<br />
<br />
and the datasets can be found here:<br />
<br />
[http://www.vistrails.org/download/download.php?type=PUB&id=pin_16.vtk pin_16.vtk]<br />
<br />
[http://www.vistrails.org/download/download.php?type=PUB&id=high_res_chest.vtk high_res_chest.vtk]<br />
<br />
For Windows/Linux platforms, if the datasets are placed in the VisTrails example/data directory the pipelines will work as is. For Mac, the SetFileName function of the readers will need to be modified to reflect the location of the file.<br />
<br />
===Discussion and Feedback===<br />
<br />
A [http://www.vistrails.org/blog blog] has been created for CiSE readers to provide discussion and feedback of the system and the article. Let us know what you think!<br />
<br />
<br />
Back to [[CiSE | CiSE articles]]</div>Wed, 02 Jan 2008 21:21:21 GMTStevechttps://www.vistrails.org//index.php/Talk:Cise-jan-2008Cise-jan-2008
https://www.vistrails.org//index.php?title=Cise-jan-2008&diff=958
https://www.vistrails.org//index.php?title=Cise-jan-2008&diff=958<p>Stevec: /* Supporting Material */</p>
<hr />
<div>==Direct Volume Rendering: A 3D Plotting Technique for Scientific Data==<br />
<br />
===Abstract===<br />
<br />
Direct volume rendering is an effective method for plotting 3D scientific data, but it's not as frequently used as it <br />
could be. Here, the authors summarize direct volume rendering and discuss barriers to taking advantage of this powerful technique.<br />
<br />
===Summary===<br />
The article describes the basics of volume rendering by contrasting it with other techniques using a dataset created using an implicit function. A sidebar also shows a case study using a volume that was aquired with a CT scanner of a torso. Both of these sets of images are fully reproducible.<br />
<br />
===Supporting Material===<br />
<br />
The exploration process that lead to the visualizations in the text were captured in a vistrail that can be loaded and executed with the [[Main_Page | VisTrails]] system. The vistrails can be obtained here:<br />
<br />
[http://www.vistrails.org/download/download.php?type=PUB&id=cise_jan08_implicit.vt Sep07 implicit function vistrail]<br />
<br />
[http://www.vistrails.org/download/download.php?type=PUB&id=cise_jan08_chest.vt Sep07 case study vistrail]<br />
<br />
and the datasets can be found here:<br />
<br />
[http://www.vistrails.org/download/download.php?type=PUB&id=pin_16.vtk pin_16.vtk]<br />
<br />
[http://www.vistrails.org/download/download.php?type=PUB&id=high_res_chest.vtk high_res_chest.vtk]<br />
<br />
For Windows/Linux platforms, if the datasets are placed in the VisTrails example/data directory the pipelines will work as is. For Mac, the SetFileName function of the readers will need to reflect the location of the file.<br />
<br />
===Discussion and Feedback===<br />
<br />
A [http://www.vistrails.org/blog blog] has been created for CiSE readers to provide discussion and feedback of the system and the article. Let us know what you think!<br />
<br />
<br />
Back to [[CiSE | CiSE articles]]</div>Wed, 02 Jan 2008 21:20:57 GMTStevechttps://www.vistrails.org//index.php/Talk:Cise-jan-2008Cise-jan-2008
https://www.vistrails.org//index.php?title=Cise-jan-2008&diff=957
https://www.vistrails.org//index.php?title=Cise-jan-2008&diff=957<p>Stevec: New page: ==Direct Volume Rendering: A 3D Plotting Technique for Scientific Data== ===Abstract=== Direct volume rendering is an effective method for plotting 3D scientific data, but it's not as fr...</p>
<hr />
<div>==Direct Volume Rendering: A 3D Plotting Technique for Scientific Data==<br />
<br />
===Abstract===<br />
<br />
Direct volume rendering is an effective method for plotting 3D scientific data, but it's not as frequently used as it <br />
could be. Here, the authors summarize direct volume rendering and discuss barriers to taking advantage of this powerful technique.<br />
<br />
===Summary===<br />
The article describes the basics of volume rendering by contrasting it with other techniques using a dataset created using an implicit function. A sidebar also shows a case study using a volume that was aquired with a CT scanner of a torso. Both of these sets of images are fully reproducible.<br />
<br />
===Supporting Material===<br />
<br />
The exploration process that lead to the visualizations in the text were captured in a vistrail that can be loaded and executed with the [[Main_Page | VisTrails]] system. The vistrails can be obtained here:<br />
<br />
[http://www.vistrails.org/download/download.php?type=PUB&id=cise_jan08.vis Sep07 implicit function vistrail]<br />
<br />
[http://www.vistrails.org/download/download.php?type=PUB&id=cise_jan08_mac.vis Sep07 case study vistrail]<br />
<br />
and the datasets can be found here:<br />
<br />
[http://www.vistrails.org/download/download.php?type=PUB&id=pin_16.vtk pin_16.vtk]<br />
<br />
[http://www.vistrails.org/download/download.php?type=PUB&id=high_res_chest.vtk high_res_chest.vtk]<br />
<br />
For Windows/Linux platforms, if the datasets are placed in the VisTrails example/data directory the pipelines will work as is. For Mac, the SetFileName function of the readers will need to reflect the location of the file.<br />
<br />
===Discussion and Feedback===<br />
<br />
A [http://www.vistrails.org/blog blog] has been created for CiSE readers to provide discussion and feedback of the system and the article. Let us know what you think!<br />
<br />
<br />
Back to [[CiSE | CiSE articles]]</div>Wed, 02 Jan 2008 21:20:07 GMTStevechttps://www.vistrails.org//index.php/Talk:Cise-jan-2008CiSE
https://www.vistrails.org//index.php?title=CiSE&diff=956
https://www.vistrails.org//index.php?title=CiSE&diff=956<p>Stevec: </p>
<hr />
<div>We believe that reproducibility is a key component of the scientific discovery process. To this end, for each article in the Visualization Corner of Computing in Science & Engineering, we have posted the necessary information to reproduce all the figures. In addition, for each article, we have created a [http://www.vistrails.org/blog blog] entry that can be used as a forum for discussion and comments.<br />
<br />
Each article is described by a unique vistrail, the entire history of the exploration process, that can be loaded into the [[Main_Page | VisTrails]] system. Each figure in the text is represented by a version (pipeline) in the history tree. Precompiled binaries and source code for VisTrails can be obtained from our [[Downloads | Downloads]] site and [[Documentation | Documentation]] is provided to learn how to use the system. <br />
<br />
== [[cise-sep-2007 | Provenance for Visualizations: Reproducibility and Beyond (Sep/Oct 2007)]] ==<br />
== [[cise-jan-2008 | Direct Volume Rendering: A 3D Plotting Technique for Scientific Data (Jan/Feb 2008)]] ==</div>Wed, 02 Jan 2008 21:04:28 GMTStevechttps://www.vistrails.org//index.php/Talk:CiSEPublications and Presentations
https://www.vistrails.org//index.php?title=Publications_and_Presentations&diff=953
https://www.vistrails.org//index.php?title=Publications_and_Presentations&diff=953<p>Stevec: </p>
<hr />
<div>[http://www.sci.utah.edu/~cscheid/download.html?document=tackling.pdf Tackling the Provenance Challenge One Layer at a Time] (by Carlos E. Scheidegger, David Koop, Emanuele Santos, Huy T. Vo, Steven P. Callahan, Juliana Freire, and Claudio T. Silva). To appear in Concurrency and Computation: Practice and Experience.<br />
<br />
[http://www.cs.utah.edu/~juliana/pub/camera-ready-cise2007.pdf Provenance for Visualizations: Reproducibility and Beyond] (by Claudio Silva, Juliana Freire and Steven Callahan). IEEE Computing in Science & Engineering, 9(5):82-29, 2007. ''The vistrail to reproduce the images in the paper is available at http://www.vistrails.org/index.php/CiSE''<br />
<br />
[http://www.sci.utah.edu/~cscheid/download.html?document=vis_by_analogy.pdf Querying and Creating Visualizations by Analogy] (by Carlos E. Scheidegger, Huy T. Vo, David Koop, Juliana Freire and Claudio T. Silva. IEEE Trans. Vis. Comp. Graph (Proceedings of IEEE Vis 2007) 13(6):1560-1567, 2007. ''IEEE Vis 2007 Best Paper Award'' <br />
<br />
[http://www.vistrails.org/download/download.php?type=PUB&id=ipaw2006.pdf Managing Rapidly-Evolving Scientific Workflows] (by Juliana Freire, Claudio T. Silva, Steven P. Callahan, Emanuele Santos, Carlos E. Scheidegger and Huy T. Vo) Invited paper, in the proceedings of the International Provenance and Annotation Workshop (IPAW), 2006. [http://www.vistrails.org/download/download.php?type=PUB&id=ipaw2006-slides.pdf presentation]<br />
<br />
[http://www.sci.utah.edu/publications/SCITechReports/UUSCI-2006-017.pdf Visualization in Radiation Oncology: Towards Replacing the Laboratory Notebook] (by Erik W. Anderson, Steven P. Callahan, George T. Y. Chen, Juliana Freire, Emanuele Santos, Carlos E. Scheidegger, Claudio T. Silva and Huy T. Vo) SCI Institute Technical Report, No. UUSCI-2006-17, University of Utah, 2006.<br />
<br />
[http://www.sci.utah.edu/publications/SCITechReports/UUSCI-2006-016.pdf Using Provenance to Streamline Data Exploration through Visualization] (by Steven P. Callahan, Juliana Freire, Emanuele Santos, Carlos E. Scheidegger, Claudio T. Silva and Huy T. Vo) SCI Institute Technical Report, No. UUSCI-2006-016, University of Utah, 2006.<br />
<br />
[http://www.vistrails.org/download/download.php?type=PUB&id=sciflow2006.pdf Managing the Evolution of Dataflows with VisTrails] (by Steven P. Callahan, Juliana Freire, Emanuele Santos, Carlos E. Scheidegger, Claudio T. Silva and Huy T. Vo) IEEE Workshop on Workflow and Data Flow for Scientific Applications (SciFlow) 2006. [http://www.vistrails.org/download/download.php?type=PUB&id=sciflow2006-slides.pdf presentation]<br />
<br />
[http://www.vistrails.org/download/download.php?type=PUB&id=sigmod2006.pdf VisTrails: Visualization meets Data Management] (by Steven P. Callahan, Juliana Freire, Emanuele Santos, Carlos E. Scheidegger, Claudio T. Silva and Huy T. Vo) In Proceedings of ACM SIGMOD 2006. [http://www.vistrails.org/download/download.php?type=PUB&id=sigmod2006-slides.pdf presentation]<br />
<br />
[http://www.vistrails.org/download/download.php?type=PUB&id=vistrails-tutorial.pdf VisTrails: A Short Tutorial] (by Erik W. Anderson, Steven P. Callahan, Juliana Freire, Emanuele Santos, Carlos E. Scheidegger, Claudio T. Silva and Huy T. Vo) Technical Report. University of Utah, 2005.<br />
<br />
[http://www.vistrails.org/download/download.php?type=PUB&id=vis2005.pdf VisTrails: Enabling Interactive Multiple-View Visualizations] (by Louis Bavoil, Steven P. Callahan, Patricia J. Crossno, Juliana Freire, Carlos E. Scheidegger, Claudio T. Silva and Huy T. Vo) In Proceedings of IEEE Visualization, 2005. [http://www.vistrails.org/download/download.php?type=PUB&id=vis2005-slides.pdf presentation]<br />
<br />
[http://www.vistrails.org/download/download.php?type=PUB&id=poster.pdf A poster on VisTrails applications]<br />
<br />
[http://www.vistrails.org/download/download.php?type=PUB&id=dils07-poster.pdf A poster on VisTrails features]<br />
<br />
=== Other ===<br />
<br />
[[ImprovingMeshQualityOfMarchingCubes | Accompanying webpage for "Edge Transformations for Improving Mesh Quality of Marching Cubes"]]<br />
<br />
[http://www.cs.utah.edu/~juliana/videos/VizByAnalogy_Scheidegger-H.264_LAN_960x540.mov | Accompanying video for "Querying and Creating Visualizations by Analogy"]</div>Wed, 26 Dec 2007 18:58:18 GMTStevechttps://www.vistrails.org//index.php/Talk:Publications_and_PresentationsSciVisFall2007/Schedule
https://www.vistrails.org//index.php?title=SciVisFall2007/Schedule&diff=945
https://www.vistrails.org//index.php?title=SciVisFall2007/Schedule&diff=945<p>Stevec: </p>
<hr />
<div>== 8/21: Introduction to visualization ==<br />
<br />
Lecturer: Claudio<br />
<br />
Topics: Scientific Visualization<br />
<br />
Notes: [http://www.cs.utah.edu/~csilva/courses/cs5630/lec01-notes.pdf lec01-notes.pdf]<br />
<br />
Slides: [http://www.cs.utah.edu/~csilva/courses/cs5630/lec01.pdf lec01.pdf]<br />
<br />
Animations: [http://www.cs.utah.edu/~csilva/courses/cs5630/explosion_640x480-5.mov explosion_640x480-5.mov], [http://www.cs.utah.edu/~csilva/courses/cs5630/fig7.mov fig7.mov], [http://www.cs.utah.edu/~csilva/courses/cs5630/fig8.mov fig8.mov], [http://www.cs.utah.edu/~csilva/courses/cs5630/fig9.mov fig9.mov], [http://www.cs.utah.edu/~csilva/courses/cs5630/SevereTstorm.mov SevereTstorm.mov]<br />
<br />
Further reading: <br />
<br />
[http://www.sci.utah.edu/~csilva/papers/vis2003.pdf Visualizing Spatial and Temporal Variability in Coastal Observatories], W. Herrera-Jimenez, W. Correa, C. Silva, and A. Baptista, IEEE Visualization 2003.<br />
<br />
== 8/23: The visualization pipeline ==<br />
<br />
Lecturer: Claudio<br />
<br />
Topics: Procedural vs. Dataflow programming; Using Dataflow for the Vis Pipeline; Dataflow programming with VTK; Dataflow programming with VisTrails; python.<br />
<br />
Notes: [http://www.cs.utah.edu/~csilva/courses/cs5630/lec02-notes.pdf lec02-notes.pdf]<br />
<br />
Slides: [http://www.cs.utah.edu/~csilva/courses/cs5630/lec02.pdf lec02.pdf]<br />
<br />
VisTrails: During this class, we built a pipeline equivalent to the cone.tcl (see class slides). Here is the vistrails file: [http://www.cs.utah.edu/~csilva/courses/cs5630/cone.vt cone.vt]<br />
<br />
Further reading: <br />
<br />
[http://www.cs.utah.edu/~csilva/courses/cs5630/reproducible_vis.pdf Provenance for Visualizations: Reproducibility and Beyond], C. Silva, J. Freire, and S. Callahan, IEEE Computing in Science and Engineering, to appear.<br />
<br />
== 8/28: Modeling Data for Visualization ==<br />
<br />
Lecturer: Carlos<br />
<br />
Topics: Discrete vs continous data; Sampling and interpolation; Point vs triangulated data; Meshing data types; Regular vs irregular data; Tabular data; Vector and tensor fields<br />
<br />
Notes: TBA<br />
<br />
Slides: [http://www.sci.utah.edu/~cscheid/scivis_fall07/modelling_1.ppt .ppt file]<br />
<br />
Further reading: <br />
<br />
There is no required reading for this lecture. The notes will be available shortly. The following papers are there for people that are looking to get more advanced material that will not be covered in class.<br />
<br />
=== Interpolation ===<br />
<br />
[http://lmi.bwh.harvard.edu/papers/papers/geodesic-loxodromes-final.html Geodesic-loxodromes...] This is the fancy interpolation for diffusion tensors I mentioned in class.<br />
<br />
[http://en.wikipedia.org/wiki/Bernstein_polynomial Bernstein polynomials] These are the polynomials used for cubic Bezier curves that I mentioned in class.<br />
<br />
==== Separability ====<br />
<br />
[http://portal.acm.org/citation.cfm?id=1187793 Extensions of the Zwart-Powell Box spline...] This is a recent paper that shows a class of trivariate reconstruction techniques that are ''not'' separable.<br />
<br />
==== Tensors ====<br />
<br />
[http://www.cs.utah.edu/research/techreports/2004/pdf/UUCS-04-014.pdf Visualization and Analysis of Diffusion Tensor Fields] Gordon Kindlmann's PhD. thesis, with everything you ever wanted to know about DTI. Section 2.1 has a good primer in tensor algebra.<br />
<br />
== 8/30: Modeling Data for Visualization == <br />
<br />
Lecturer: Carlos<br />
<br />
Topics: Geometry Processing: Reconstruction and meshing; Simplification; Smoothing; Other Filtering algorithms<br />
<br />
Notes: [http://www.sci.utah.edu/~cscheid/scivis_fall07/week2.pdf .pdf file]. If you want to print these, you might want to wait for a week or two, until I finish polishing them.<br />
<br />
Slides: [http://www.sci.utah.edu/~cscheid/scivis_fall07/processing.ppt .ppt file] ''These slides include simplificatin algorithms, which I'll talk about next week.''<br />
<br />
== 9/4: Elementary Plotting Techniques == <br />
<br />
Lecturer: Steve<br />
<br />
Topics: Principles of Graph Construction<br />
<br />
Notes: [http://www.sci.utah.edu/~stevec/classes/cs5630/PlottingNotes.pdf PlottingNotes.pdf]<br />
<br />
Slides: [http://www.sci.utah.edu/~stevec/slides/SciVis/Plotting1.pdf Plotting1.pdf]<br />
<br />
Vistrails: See next lecture.<br />
<br />
Further Reading: There is no required reading for this lecture. For those interested in more depth, the following books are very useful:<br />
<br />
* The Elements of Graphing Data. William S. Cleveland, Hobart Press, 2nd Edition, 1994.<br />
* Visualizing Data. William S. Cleveland, Hobart Press, 1993.<br />
* The Visual Display of Quantitative Information. Edward R. Tufte, Graphics Press, 2001.<br />
* Visual Explanations: Images and Quantities, Evidence and Narrative. Edward R. Tufte, Graphics Press, 2997.<br />
<br />
== 9/6: Elementary Plotting Techniques ==<br />
<br />
Lecturer: Steve<br />
<br />
Topics: Simple Plotting Methods: Dot Plots, Connected Symbol Plots, Scatter Plots, Histograms, Others. Advanced Plotting Methods: Multimodal, Higher Dimensional, Correlation, Uncertainty and Variation.<br />
<br />
Notes: [http://www.sci.utah.edu/~stevec/classes/cs5630/PlottingNotes.pdf PlottingNotes.pdf]<br />
<br />
Slides: [http://www.sci.utah.edu/~stevec/slides/SciVis/Plotting2.pdf Plotting2.pdf]<br />
<br />
Vistrails: [http://www.sci.utah.edu/~stevec/classes/cs5630/PlottingVistrails.zip PlottingVistrails.zip] - Unzip this file in the examples directory of your VisTrails installation and it will add the vistrails along with their data sets (in the data directory). If you don't have permission to write to this directory (CADE users), then unzip the file where you want. Just be aware that in this case the paths for the data files may not be correct for most vistrails and will need to be fixed before they will execute properly.<br />
<br />
<br />
Further Reading: There is no required reading for this lecture. Some articles of interest:<br />
<br />
* [http://www.fmrib.ox.ac.uk/analysis/techrep/tr00mj2/tr00mj2/node24.html Histogram Bin Size]<br />
* [http://en.wikipedia.org/wiki/Correlation Correlation]<br />
* [http://en.wikipedia.org/wiki/Linear_regression Linear Regression]<br />
* [http://en.wikipedia.org/wiki/Box_plot Box Plots]<br />
<br />
== 9/11: Color and Human Perception ==<br />
<br />
Lecturer: Claudio<br />
<br />
Topics: Human vision system; Optical illusions<br />
<br />
Notes: TBA<br />
<br />
Slides: [http://www.cs.utah.edu/~csilva/courses/cs5630/human-vision.pdf human-vision.pdf]<br />
<br />
Links:<br />
<br />
http://en.wikipedia.org/wiki/Eye<br />
<br />
http://www.grand-illusions.com/gregory2.htm (also, see the related book: [http://www.amazon.com/Eye-Brain-Richard-L-Gregory/dp/0691048371])<br />
<br />
http://en.wikipedia.org/wiki/Purkinje_effect<br />
<br />
http://www.handprint.com/HP/WCL/color2.html<br />
<br />
== 9/13: Color and Human Perception ==<br />
<br />
Lecturer: Claudio<br />
<br />
Topics: Color Science; Color spaces; Color Blindness; Color maps; Tone mapping<br />
<br />
Notes: TBA<br />
<br />
Slides: [http://www.cs.utah.edu/~csilva/courses/cs5630/colorvision.pdf colorvision.pdf]<br />
<br />
Links:<br />
<br />
Further reading: <br />
<br />
[http://www.research.ibm.com/dx/proceedings/pravda/truevis.htm How Not to Lie with Visualization]<br />
<br />
http://en.wikipedia.org/wiki/Opponent_process<br />
<br />
http://en.wikipedia.org/wiki/Color_models<br />
<br />
http://en.wikipedia.org/wiki/Absolute_color_space<br />
<br />
http://en.wikipedia.org/wiki/Additive_color<br />
<br />
http://en.wikipedia.org/wiki/Subtractive_color<br />
<br />
http://en.wikipedia.org/wiki/RGB_color_model<br />
<br />
http://en.wikipedia.org/wiki/SRGB_color_space<br />
<br />
http://en.wikipedia.org/wiki/CIE_XYZ_color_space<br />
<br />
== 9/18 (a): Color and Human Perception ==<br />
<br />
Lecturer: Claudio<br />
<br />
Same material as previous lecture. <br />
<br />
== 9/18 (b): 2D Visualization Techniques ==<br />
<br />
Lecturer: Carlos<br />
<br />
Topics: 2-D contours, marching quads, marching tris; Color mapping; height fields; NPR<br />
<br />
Slides: [http://www.sci.utah.edu/~cscheid/scivis_fall07/2d_scalar_vis.pdf pdf file]<br />
<br />
Notes: [http://www.sci.utah.edu/~cscheid/scivis_fall07/2d_scalar_vis_notes.pdf pdf file]<br />
<br />
Vistrails: [http://www.sci.utah.edu/~cscheid/scivis_fall07/ozone_and_data.zip zip file with ozone.vt and data] [http://www.sci.utah.edu/~cscheid/scivis_fall07/asymptotic_decider.vt asymptotic decider in 2d] [http://www.sci.utah.edu/~cscheid/scivis_fall07/elevation.zip heightfields]<br />
<br />
Note: These vistrails use relative file paths so you don't need to change each of them individually to match your directory structure. Simply unzip the file to whichever location is more convenient. Then, inside VisTrails, open the VisTrails shell, type:<br />
<br />
import os<br />
os.chdir("c:/directory/where/you/unzipped/it")<br />
<br />
This will change the directory so you should be able to just run the pipelines.<br />
<br />
== 9/20: Math refresher ==<br />
<br />
Lecturer: Carlos<br />
<br />
Topics: Basic linear algebra; vectors; basic differential geometry (space curves, tangents, normals, surfaces); basic vector calculus (gradient, divergence, curl, gauss' theorem, green's theorem) <br />
<br />
== 9/25: 2D Visualization Techniques ==<br />
<br />
Lecturer: Carlos<br />
<br />
Topics: 2-D vector fields, div, grad, curl in 2D; Steady vs Unsteady flows; Glyphs; 2-D streamlines, streaklines, pathlines<br />
<br />
Slides: [http://www.sci.utah.edu/~cscheid/scivis_fall07/2d_vector_vis.pdf pdf file]<br />
<br />
Notes: coming soon<br />
<br />
Vistrails: [http://www.sci.utah.edu/~cscheid/scivis_fall07/vector_vis_1.zip vistrail with steady vector field vis and data] [http://www.sci.utah.edu/~cscheid/scivis_fall07/unsteady.zip vistrail with unsteady vector field vis and data] '''Note:''' Because VTK does not support time-varying datasets directly, we had to create a reasonably ugly hack to simulate unsteady fields. This means the datasets are quite big (80MB in total).<br />
<br />
== 9/27 (a): 2D Visualization Techniques ==<br />
<br />
Lecturer Carlos<br />
<br />
Same material as last lecture.<br />
<br />
== 9/27 (b): Volume Vis ==<br />
<br />
Lecturer: Claudio<br />
<br />
Topics: Slicing; Contours; Marching algorithms<br />
<br />
Slides: [http://www.cs.utah.edu/~csilva/courses/cs5630/iso-basic.pdf iso-basic.pdf]<br />
<br />
References:<br />
<br />
[http://portal.acm.org/citation.cfm?id=37401.37422 Marching cubes: A high resolution 3D surface construction algorithm]<br />
<br />
[http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=175782 The asymptotic decider: resolving the ambiguity in marching cubes]<br />
<br />
== 10/2: Volume Vis == <br />
<br />
Lecturer: Claudio<br />
<br />
Topics: Accelerating structures; High-quality contours<br />
<br />
Slides: <br />
<br />
[http://www.cs.utah.edu/~csilva/courses/cs5630/iso-speed.pdf iso-speed.pdf]<br />
<br />
[http://www.cs.utah.edu/~csilva/courses/cs5630/iso-speed-2.pdf iso-speed-2.pdf]<br />
<br />
References:<br />
<br />
[http://doi.ieeecomputersociety.org/10.1109/2945.489388 A Near Optimal Isosurface Extraction Algorithm Using the Span Space]<br />
<br />
[http://doi.ieeecomputersociety.org/10.1109/2945.485619 Automatic Isosurface Propagation Using an Extrema Graph and Sorted Boundary Cell Lists]<br />
<br />
[http://doi.ieeecomputersociety.org/10.1109/2945.597798 Speeding Up Isosurface Extraction Using Interval Trees]<br />
<br />
[http://doi.ieeecomputersociety.org/10.1109/SVVG.2004.5 Implicit Occluders]<br />
<br />
== 10/4: Volume Vis ==<br />
<br />
Lecturer: Claudio<br />
<br />
Topics: High quality isosurfaces<br />
<br />
Slides: [http://www.cs.utah.edu/~csilva/courses/cs5630/iso-quality.pdf iso-quality.pdf]<br />
<br />
References:<br />
<br />
[http://www.cs.utah.edu/~csilva/2007-sub/macet.pdf Edge Transformations for Improving Mesh Quality of Marching Cubes]<br />
<br />
[http://www.sci.utah.edu/~csilva/papers/tvcg2006acr.pdf High-Quality Extraction of Isosurfaces from Regular and Irregular Grids]<br />
<br />
[http://portal.acm.org/citation.cfm?id=566570.566586 Dual contouring of hermite data]<br />
<br />
[http://www.sci.utah.edu/%7Emiriah/research/meshing/vis07meyer.pdf Topology, Accuracy, and Quality of Isosurface Meshes Using Dynamic Particles]<br />
<br />
[http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=1260744 Material interface reconstruction]<br />
<br />
== 10/9: Fall break == <br />
<br />
== 10/11: Fall break == <br />
<br />
== 10/16: Volume Vis ==<br />
<br />
Lecturer: Claudio<br />
<br />
Topics: continued from last class<br />
<br />
== 10/18: Direct Volume Rendering ==<br />
<br />
Lecturer: Steve<br />
<br />
Topics: Introduction to volume rendering<br />
<br />
Slides: [http://www.sci.utah.edu/~stevec/classes/cs5630/VolumeRendering1.pdf VolumeRendering1.pdf]<br />
<br />
Notes: [http://www.sci.utah.edu/~stevec/classes/cs5630/dvr.pdf dvr.pdf]<br />
<br />
vistrails: [http://www.sci.utah.edu/~stevec/classes/cs5630/VolumeRenderingVistrails.zip VolumeRenderingVistrails.zip]<br />
<br />
References:<br />
[http://www.llnl.gov/graphics/docs/OpticalModelsLong.pdf Optical Models for Direct Volume Rendering]<br />
<br />
== 10/23: Midterm 1 ==<br />
<br />
== 10/25: Direct Volume Rendering ==<br />
<br />
Lecturer: Steve<br />
<br />
Topics: Structured grid techniques: ray-casting, splatting, texture slicing, shear-warp<br />
<br />
Slides: [http://www.sci.utah.edu/~stevec/classes/cs5630/VolumeRendering2.pdf VolumeRendering2.pdf]<br />
<br />
Notes: same as previous class<br />
<br />
vistrails: same as previous class<br />
<br />
References:<br />
<br />
[http://graphics.stanford.edu/papers/volume-cga88/ Display of Surfaces from Volume Data] - Ray casting paper<br />
<br />
[http://portal.acm.org/citation.cfm?id=329138 Interactive Volume Rendering] - Splatting paper, paper requires ACM digital library access<br />
<br />
[http://portal.acm.org/citation.cfm?id=197972&dl=ACM&coll=GUIDE Accelerated volume rendering and tomographic reconstruction using texture mapping hardware] - Texture slicing paper, requires ACM digital library access<br />
<br />
[http://graphics.stanford.edu/papers/shear/ Fast Volume Rendering Using a Shear-Warp Factorization of the Viewing Transformation] - Shear-warp paper<br />
<br />
== 10/30: Cosmology and EEG analysis ==<br />
<br />
Guest lecture: Erik Anderson<br />
<br />
Topics: Applications of Visualization Techniques, Multi-modal Visualization<br />
<br />
Slides: VisualizationApplications [http://www.sci.utah.edu/~eranders/talk/scivis_applications/applications.ppt ppt] | [http://www.sci.utah.edu/~eranders/talk/scivis_applications/applications.odp odp]<br />
<br />
VisTrail: Contact me [http://www.sci.utah.edu/~eranders here]<br />
<br />
References:<br />
<br />
[http://www.sci.utah.edu/~eranders/papers/embs2007_neuro.pdf Working Memory in Schizophrenia] - Overview of rTMS in EEG Analysis<br />
<br />
[http://arxiv.org/abs/0706.1270 Cosmology Code Comparison Project] - Cosmological Simulation Project<br />
<br />
== 11/1: Simplification Techniques == <br />
<br />
Guest lecture: Yuan Zhou<br />
<br />
Topics: Simplification techniques: vertex clustering, vertex decimation, iterative contraction, quadric error based surface and tetrahedral simplification<br />
<br />
Slides: [http://graphics.cs.uiuc.edu/~yuanzhou/class/SciVis2007_simplification Simplification]<br />
<br />
References:<br />
<br />
[http://graphics.cs.uiuc.edu/~garland/papers/quadrics.pdf Surface Simplification Using Quadric Error Metrics]<br />
<br />
[http://graphics.cs.uiuc.edu/~garland/papers/STAR99 Multiresolution Modeling : Survey & Future Opportunities]<br />
<br />
[http://graphics.cs.uiuc.edu/~garland/papers/TR-2004-2450 Quadric-Based Simplication in Any Dimension] <br />
<br />
[http://www.sci.utah.edu/~csilva/papers/tvcg2007cr Streaming Simplification of Tetrahedral Meshes]<br />
<br />
== 11/6: Direct Volume Rendering ==<br />
<br />
Lecturer: Claudio<br />
<br />
Topics: Unstructured grid techniques<br />
<br />
Slides: [http://www.cs.utah.edu/~csilva/courses/cs5630/unstructured_grid_rendering.pdf unstructured_grid_rendering.pdf]<br />
<br />
References:<br />
<br />
[http://www.sci.utah.edu/~csilva/papers/rita2005.pdf A Survey of GPU-Based Volume Rendering of Unstructured Grid]<br />
<br />
[http://www.sci.utah.edu/~csilva/papers/tvcg2005cr.pdf Hardware-Assisted Visibility Sorting for Unstructured Volume Rendering] (This technique is implemented in VTK: http://www.vtk.org/doc/nightly/html/classvtkHAVSVolumeMapper.html)<br />
<br />
[http://www.sci.utah.edu/~csilva/papers/volvis2000.pdf ZSWEEP: An Efficient and Exact Projection Algorithm for Unstructured Volume Rendering] (This technique is implemented in VTK: http://www.vtk.org/doc/nightly/html/classvtkUnstructuredGridVolumeZSweepMapper.html)<br />
<br />
== 11/8: Direct Volume Rendering ==<br />
<br />
Lecturer: Claudio<br />
<br />
Topics: Transfer function specification<br />
<br />
Slides: [http://www.cs.utah.edu/~csilva/courses/cs5630/transfer_functions.pdf transfer_functions.pdf]<br />
<br />
References: <br />
<br />
[http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=920623 The transfer function bake-off]<br />
<br />
[http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=663875 The contour spectrum]<br />
<br />
[http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=1021579 Multidimensional transfer functions for interactive volume rendering]<br />
<br />
[http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=729588 Semi-automatic generation of transfer functions for direct volumerendering]<br />
<br />
== 11/13: Tensor Visualization ==<br />
<br />
Lecturer: Carlos<br />
<br />
Topics: DT/MRI intro, glyphs, colormapping, volume rendering<br />
<br />
Slides: [http://www.sci.utah.edu/~cscheid/scivis_fall07/dti.html .html slideshow]<br />
<br />
References: [http://www.cs.utah.edu/research/techreports/2004/pdf/UUCS-04-014.pdf G. Kindlmann's PhD thesis], covering most of what we've seen in the slides.<br />
<br />
== 11/15: 3D Vector Vis and Topology ==<br />
<br />
Lecturer: Carlos<br />
<br />
Topics: 3D techniques, critical points<br />
<br />
Slides: [http://www.sci.utah.edu/~cscheid/scivis_fall07/3dvectorvis.pdf 3D vector vis, .pdf file] [http://www.sci.utah.edu/~cscheid/scivis_fall07/vftopology.pdf Vector field topology, .pdf file]<br />
<br />
== 11/20: Information Visualization ==<br />
<br />
Lecturer: Carlos<br />
<br />
Topics: Parallel coordinates; Graph visualization<br />
<br />
Slides: [http://www.sci.utah.edu/~cscheid/scivis_fall07/Infovis.pdf .pdf file]<br />
<br />
== 11/22: Thanksgiving == <br />
<br />
== 11/27: Information Visualization ==<br />
<br />
Lecturer: Carlos and Steve<br />
<br />
Topics: Trees and Graphs; InfoVis Examples<br />
<br />
Links:<br />
* [http://www.many-eyes.com Many Eyes]<br />
* [http://www.win.tue.nl/sequoiaview/ SequioaView]<br />
* [http://www.gg.caltech.edu/~zhukov/infovis/world_of_music.htm World Of Music]<br />
* [http://www.tableausoftware.com/ Tableau]<br />
* [http://http://www.gapminder.org/ GapMinder]<br />
* [http://www.babynamewizard.com/namevoyager/lnv0105.html Name Voyager]<br />
<br />
== 11/29: Aesthetic Issues in Vis ==<br />
<br />
Lecturer: Steve<br />
<br />
Topics: Tufte principles<br />
<br />
Slides: [http://www.sci.utah.edu/~stevec/classes/cs5630/Tufte.pdf Tufte.pdf]<br />
<br />
References:<br />
* Envisioning Information, Edward R. Tufte, Academic Press, 1990<br />
* Visual Explanations: Images and Quantities, Evidence and Narrative, Edward R. Tufte, Academic Press, 1997<br />
<br />
== 12/4: Aesthetic Issues in Vis ==<br />
<br />
Lecturer: Steve<br />
<br />
Topics: NPR and Illustrative techniques for Vis<br />
<br />
Slides: [http://www.sci.utah.edu/~stevec/classes/cs5630/illustrative.html illustrative.html]<br />
<br />
vistrails: [http://www.sci.utah.edu/~stevec/classes/cs5630/illustrative.zip illustrative.zip] includes DifferentialGeometry.vt as well as norm.120.vtk and angle.120.vtk volume datasets.<br />
<br />
References:<br />
<br />
*[http://www.cs.utah.edu/~gk/papers/vis03/ Curvature-based Transfer Functions], Gordon Kindlmann.<br />
*[http://www.cs.utah.edu/~gooch/NPRcourse_SIG99/NPRcourse.html SIGGRAPH 99 NPR course notes], Bruce and Amy Gooch.<br />
*[http://www.ii.uib.no/vis/research/tutorials/2007-vis-illustrative_vis/tutorial_notes.pdf Vis 07 Illustrative Vis course notes], Viola, Bruckner, Sousa, Ebert, and Correa.<br />
*[http://www.cs.princeton.edu/gfx/proj/sg05lines/ SIGGRAPH 05 Line Drawings course notes], Rusinkiewicz, DeCarlo, and Finkelstein.<br />
<br />
== 12/6: Misc ==<br />
<br />
Lecturer: Claudio<br />
<br />
Topics: Data Management for Vis, Vis for presentation/discovery<br />
<br />
== 12/10: Final Exam ==<br />
<br />
TBA</div>Tue, 04 Dec 2007 22:55:49 GMTStevechttps://www.vistrails.org//index.php/Talk:SciVisFall2007/ScheduleSciVisFall2007/Schedule
https://www.vistrails.org//index.php?title=SciVisFall2007/Schedule&diff=944
https://www.vistrails.org//index.php?title=SciVisFall2007/Schedule&diff=944<p>Stevec: /* 12/4: Aesthetic Issues in Vis */</p>
<hr />
<div>== 8/21: Introduction to visualization ==<br />
<br />
Lecturer: Claudio<br />
<br />
Topics: Scientific Visualization<br />
<br />
Notes: [http://www.cs.utah.edu/~csilva/courses/cs5630/lec01-notes.pdf lec01-notes.pdf]<br />
<br />
Slides: [http://www.cs.utah.edu/~csilva/courses/cs5630/lec01.pdf lec01.pdf]<br />
<br />
Animations: [http://www.cs.utah.edu/~csilva/courses/cs5630/explosion_640x480-5.mov explosion_640x480-5.mov], [http://www.cs.utah.edu/~csilva/courses/cs5630/fig7.mov fig7.mov], [http://www.cs.utah.edu/~csilva/courses/cs5630/fig8.mov fig8.mov], [http://www.cs.utah.edu/~csilva/courses/cs5630/fig9.mov fig9.mov], [http://www.cs.utah.edu/~csilva/courses/cs5630/SevereTstorm.mov SevereTstorm.mov]<br />
<br />
Further reading: <br />
<br />
[http://www.sci.utah.edu/~csilva/papers/vis2003.pdf Visualizing Spatial and Temporal Variability in Coastal Observatories], W. Herrera-Jimenez, W. Correa, C. Silva, and A. Baptista, IEEE Visualization 2003.<br />
<br />
== 8/23: The visualization pipeline ==<br />
<br />
Lecturer: Claudio<br />
<br />
Topics: Procedural vs. Dataflow programming; Using Dataflow for the Vis Pipeline; Dataflow programming with VTK; Dataflow programming with VisTrails; python.<br />
<br />
Notes: [http://www.cs.utah.edu/~csilva/courses/cs5630/lec02-notes.pdf lec02-notes.pdf]<br />
<br />
Slides: [http://www.cs.utah.edu/~csilva/courses/cs5630/lec02.pdf lec02.pdf]<br />
<br />
VisTrails: During this class, we built a pipeline equivalent to the cone.tcl (see class slides). Here is the vistrails file: [http://www.cs.utah.edu/~csilva/courses/cs5630/cone.vt cone.vt]<br />
<br />
Further reading: <br />
<br />
[http://www.cs.utah.edu/~csilva/courses/cs5630/reproducible_vis.pdf Provenance for Visualizations: Reproducibility and Beyond], C. Silva, J. Freire, and S. Callahan, IEEE Computing in Science and Engineering, to appear.<br />
<br />
== 8/28: Modeling Data for Visualization ==<br />
<br />
Lecturer: Carlos<br />
<br />
Topics: Discrete vs continous data; Sampling and interpolation; Point vs triangulated data; Meshing data types; Regular vs irregular data; Tabular data; Vector and tensor fields<br />
<br />
Notes: TBA<br />
<br />
Slides: [http://www.sci.utah.edu/~cscheid/scivis_fall07/modelling_1.ppt .ppt file]<br />
<br />
Further reading: <br />
<br />
There is no required reading for this lecture. The notes will be available shortly. The following papers are there for people that are looking to get more advanced material that will not be covered in class.<br />
<br />
=== Interpolation ===<br />
<br />
[http://lmi.bwh.harvard.edu/papers/papers/geodesic-loxodromes-final.html Geodesic-loxodromes...] This is the fancy interpolation for diffusion tensors I mentioned in class.<br />
<br />
[http://en.wikipedia.org/wiki/Bernstein_polynomial Bernstein polynomials] These are the polynomials used for cubic Bezier curves that I mentioned in class.<br />
<br />
==== Separability ====<br />
<br />
[http://portal.acm.org/citation.cfm?id=1187793 Extensions of the Zwart-Powell Box spline...] This is a recent paper that shows a class of trivariate reconstruction techniques that are ''not'' separable.<br />
<br />
==== Tensors ====<br />
<br />
[http://www.cs.utah.edu/research/techreports/2004/pdf/UUCS-04-014.pdf Visualization and Analysis of Diffusion Tensor Fields] Gordon Kindlmann's PhD. thesis, with everything you ever wanted to know about DTI. Section 2.1 has a good primer in tensor algebra.<br />
<br />
== 8/30: Modeling Data for Visualization == <br />
<br />
Lecturer: Carlos<br />
<br />
Topics: Geometry Processing: Reconstruction and meshing; Simplification; Smoothing; Other Filtering algorithms<br />
<br />
Notes: [http://www.sci.utah.edu/~cscheid/scivis_fall07/week2.pdf .pdf file]. If you want to print these, you might want to wait for a week or two, until I finish polishing them.<br />
<br />
Slides: [http://www.sci.utah.edu/~cscheid/scivis_fall07/processing.ppt .ppt file] ''These slides include simplificatin algorithms, which I'll talk about next week.''<br />
<br />
== 9/4: Elementary Plotting Techniques == <br />
<br />
Lecturer: Steve<br />
<br />
Topics: Principles of Graph Construction<br />
<br />
Notes: [http://www.sci.utah.edu/~stevec/classes/cs5630/PlottingNotes.pdf PlottingNotes.pdf]<br />
<br />
Slides: [http://www.sci.utah.edu/~stevec/slides/SciVis/Plotting1.pdf Plotting1.pdf]<br />
<br />
Vistrails: See next lecture.<br />
<br />
Further Reading: There is no required reading for this lecture. For those interested in more depth, the following books are very useful:<br />
<br />
* The Elements of Graphing Data. William S. Cleveland, Hobart Press, 2nd Edition, 1994.<br />
* Visualizing Data. William S. Cleveland, Hobart Press, 1993.<br />
* The Visual Display of Quantitative Information. Edward R. Tufte, Graphics Press, 2001.<br />
* Visual Explanations: Images and Quantities, Evidence and Narrative. Edward R. Tufte, Graphics Press, 2997.<br />
<br />
== 9/6: Elementary Plotting Techniques ==<br />
<br />
Lecturer: Steve<br />
<br />
Topics: Simple Plotting Methods: Dot Plots, Connected Symbol Plots, Scatter Plots, Histograms, Others. Advanced Plotting Methods: Multimodal, Higher Dimensional, Correlation, Uncertainty and Variation.<br />
<br />
Notes: [http://www.sci.utah.edu/~stevec/classes/cs5630/PlottingNotes.pdf PlottingNotes.pdf]<br />
<br />
Slides: [http://www.sci.utah.edu/~stevec/slides/SciVis/Plotting2.pdf Plotting2.pdf]<br />
<br />
Vistrails: [http://www.sci.utah.edu/~stevec/classes/cs5630/PlottingVistrails.zip PlottingVistrails.zip] - Unzip this file in the examples directory of your VisTrails installation and it will add the vistrails along with their data sets (in the data directory). If you don't have permission to write to this directory (CADE users), then unzip the file where you want. Just be aware that in this case the paths for the data files may not be correct for most vistrails and will need to be fixed before they will execute properly.<br />
<br />
<br />
Further Reading: There is no required reading for this lecture. Some articles of interest:<br />
<br />
* [http://www.fmrib.ox.ac.uk/analysis/techrep/tr00mj2/tr00mj2/node24.html Histogram Bin Size]<br />
* [http://en.wikipedia.org/wiki/Correlation Correlation]<br />
* [http://en.wikipedia.org/wiki/Linear_regression Linear Regression]<br />
* [http://en.wikipedia.org/wiki/Box_plot Box Plots]<br />
<br />
== 9/11: Color and Human Perception ==<br />
<br />
Lecturer: Claudio<br />
<br />
Topics: Human vision system; Optical illusions<br />
<br />
Notes: TBA<br />
<br />
Slides: [http://www.cs.utah.edu/~csilva/courses/cs5630/human-vision.pdf human-vision.pdf]<br />
<br />
Links:<br />
<br />
http://en.wikipedia.org/wiki/Eye<br />
<br />
http://www.grand-illusions.com/gregory2.htm (also, see the related book: [http://www.amazon.com/Eye-Brain-Richard-L-Gregory/dp/0691048371])<br />
<br />
http://en.wikipedia.org/wiki/Purkinje_effect<br />
<br />
http://www.handprint.com/HP/WCL/color2.html<br />
<br />
== 9/13: Color and Human Perception ==<br />
<br />
Lecturer: Claudio<br />
<br />
Topics: Color Science; Color spaces; Color Blindness; Color maps; Tone mapping<br />
<br />
Notes: TBA<br />
<br />
Slides: [http://www.cs.utah.edu/~csilva/courses/cs5630/colorvision.pdf colorvision.pdf]<br />
<br />
Links:<br />
<br />
Further reading: <br />
<br />
[http://www.research.ibm.com/dx/proceedings/pravda/truevis.htm How Not to Lie with Visualization]<br />
<br />
http://en.wikipedia.org/wiki/Opponent_process<br />
<br />
http://en.wikipedia.org/wiki/Color_models<br />
<br />
http://en.wikipedia.org/wiki/Absolute_color_space<br />
<br />
http://en.wikipedia.org/wiki/Additive_color<br />
<br />
http://en.wikipedia.org/wiki/Subtractive_color<br />
<br />
http://en.wikipedia.org/wiki/RGB_color_model<br />
<br />
http://en.wikipedia.org/wiki/SRGB_color_space<br />
<br />
http://en.wikipedia.org/wiki/CIE_XYZ_color_space<br />
<br />
== 9/18 (a): Color and Human Perception ==<br />
<br />
Lecturer: Claudio<br />
<br />
Same material as previous lecture. <br />
<br />
== 9/18 (b): 2D Visualization Techniques ==<br />
<br />
Lecturer: Carlos<br />
<br />
Topics: 2-D contours, marching quads, marching tris; Color mapping; height fields; NPR<br />
<br />
Slides: [http://www.sci.utah.edu/~cscheid/scivis_fall07/2d_scalar_vis.pdf pdf file]<br />
<br />
Notes: [http://www.sci.utah.edu/~cscheid/scivis_fall07/2d_scalar_vis_notes.pdf pdf file]<br />
<br />
Vistrails: [http://www.sci.utah.edu/~cscheid/scivis_fall07/ozone_and_data.zip zip file with ozone.vt and data] [http://www.sci.utah.edu/~cscheid/scivis_fall07/asymptotic_decider.vt asymptotic decider in 2d] [http://www.sci.utah.edu/~cscheid/scivis_fall07/elevation.zip heightfields]<br />
<br />
Note: These vistrails use relative file paths so you don't need to change each of them individually to match your directory structure. Simply unzip the file to whichever location is more convenient. Then, inside VisTrails, open the VisTrails shell, type:<br />
<br />
import os<br />
os.chdir("c:/directory/where/you/unzipped/it")<br />
<br />
This will change the directory so you should be able to just run the pipelines.<br />
<br />
== 9/20: Math refresher ==<br />
<br />
Lecturer: Carlos<br />
<br />
Topics: Basic linear algebra; vectors; basic differential geometry (space curves, tangents, normals, surfaces); basic vector calculus (gradient, divergence, curl, gauss' theorem, green's theorem) <br />
<br />
== 9/25: 2D Visualization Techniques ==<br />
<br />
Lecturer: Carlos<br />
<br />
Topics: 2-D vector fields, div, grad, curl in 2D; Steady vs Unsteady flows; Glyphs; 2-D streamlines, streaklines, pathlines<br />
<br />
Slides: [http://www.sci.utah.edu/~cscheid/scivis_fall07/2d_vector_vis.pdf pdf file]<br />
<br />
Notes: coming soon<br />
<br />
Vistrails: [http://www.sci.utah.edu/~cscheid/scivis_fall07/vector_vis_1.zip vistrail with steady vector field vis and data] [http://www.sci.utah.edu/~cscheid/scivis_fall07/unsteady.zip vistrail with unsteady vector field vis and data] '''Note:''' Because VTK does not support time-varying datasets directly, we had to create a reasonably ugly hack to simulate unsteady fields. This means the datasets are quite big (80MB in total).<br />
<br />
== 9/27 (a): 2D Visualization Techniques ==<br />
<br />
Lecturer Carlos<br />
<br />
Same material as last lecture.<br />
<br />
== 9/27 (b): Volume Vis ==<br />
<br />
Lecturer: Claudio<br />
<br />
Topics: Slicing; Contours; Marching algorithms<br />
<br />
Slides: [http://www.cs.utah.edu/~csilva/courses/cs5630/iso-basic.pdf iso-basic.pdf]<br />
<br />
References:<br />
<br />
[http://portal.acm.org/citation.cfm?id=37401.37422 Marching cubes: A high resolution 3D surface construction algorithm]<br />
<br />
[http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=175782 The asymptotic decider: resolving the ambiguity in marching cubes]<br />
<br />
== 10/2: Volume Vis == <br />
<br />
Lecturer: Claudio<br />
<br />
Topics: Accelerating structures; High-quality contours<br />
<br />
Slides: <br />
<br />
[http://www.cs.utah.edu/~csilva/courses/cs5630/iso-speed.pdf iso-speed.pdf]<br />
<br />
[http://www.cs.utah.edu/~csilva/courses/cs5630/iso-speed-2.pdf iso-speed-2.pdf]<br />
<br />
References:<br />
<br />
[http://doi.ieeecomputersociety.org/10.1109/2945.489388 A Near Optimal Isosurface Extraction Algorithm Using the Span Space]<br />
<br />
[http://doi.ieeecomputersociety.org/10.1109/2945.485619 Automatic Isosurface Propagation Using an Extrema Graph and Sorted Boundary Cell Lists]<br />
<br />
[http://doi.ieeecomputersociety.org/10.1109/2945.597798 Speeding Up Isosurface Extraction Using Interval Trees]<br />
<br />
[http://doi.ieeecomputersociety.org/10.1109/SVVG.2004.5 Implicit Occluders]<br />
<br />
== 10/4: Volume Vis ==<br />
<br />
Lecturer: Claudio<br />
<br />
Topics: High quality isosurfaces<br />
<br />
Slides: [http://www.cs.utah.edu/~csilva/courses/cs5630/iso-quality.pdf iso-quality.pdf]<br />
<br />
References:<br />
<br />
[http://www.cs.utah.edu/~csilva/2007-sub/macet.pdf Edge Transformations for Improving Mesh Quality of Marching Cubes]<br />
<br />
[http://www.sci.utah.edu/~csilva/papers/tvcg2006acr.pdf High-Quality Extraction of Isosurfaces from Regular and Irregular Grids]<br />
<br />
[http://portal.acm.org/citation.cfm?id=566570.566586 Dual contouring of hermite data]<br />
<br />
[http://www.sci.utah.edu/%7Emiriah/research/meshing/vis07meyer.pdf Topology, Accuracy, and Quality of Isosurface Meshes Using Dynamic Particles]<br />
<br />
[http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=1260744 Material interface reconstruction]<br />
<br />
== 10/9: Fall break == <br />
<br />
== 10/11: Fall break == <br />
<br />
== 10/16: Volume Vis ==<br />
<br />
Lecturer: Claudio<br />
<br />
Topics: continued from last class<br />
<br />
== 10/18: Direct Volume Rendering ==<br />
<br />
Lecturer: Steve<br />
<br />
Topics: Introduction to volume rendering<br />
<br />
Slides: [http://www.sci.utah.edu/~stevec/classes/cs5630/VolumeRendering1.pdf VolumeRendering1.pdf]<br />
<br />
Notes: [http://www.sci.utah.edu/~stevec/classes/cs5630/dvr.pdf dvr.pdf]<br />
<br />
vistrails: [http://www.sci.utah.edu/~stevec/classes/cs5630/VolumeRenderingVistrails.zip VolumeRenderingVistrails.zip]<br />
<br />
References:<br />
[http://www.llnl.gov/graphics/docs/OpticalModelsLong.pdf Optical Models for Direct Volume Rendering]<br />
<br />
== 10/23: Midterm 1 ==<br />
<br />
== 10/25: Direct Volume Rendering ==<br />
<br />
Lecturer: Steve<br />
<br />
Topics: Structured grid techniques: ray-casting, splatting, texture slicing, shear-warp<br />
<br />
Slides: [http://www.sci.utah.edu/~stevec/classes/cs5630/VolumeRendering2.pdf VolumeRendering2.pdf]<br />
<br />
Notes: same as previous class<br />
<br />
vistrails: same as previous class<br />
<br />
References:<br />
<br />
[http://graphics.stanford.edu/papers/volume-cga88/ Display of Surfaces from Volume Data] - Ray casting paper<br />
<br />
[http://portal.acm.org/citation.cfm?id=329138 Interactive Volume Rendering] - Splatting paper, paper requires ACM digital library access<br />
<br />
[http://portal.acm.org/citation.cfm?id=197972&dl=ACM&coll=GUIDE Accelerated volume rendering and tomographic reconstruction using texture mapping hardware] - Texture slicing paper, requires ACM digital library access<br />
<br />
[http://graphics.stanford.edu/papers/shear/ Fast Volume Rendering Using a Shear-Warp Factorization of the Viewing Transformation] - Shear-warp paper<br />
<br />
== 10/30: Cosmology and EEG analysis ==<br />
<br />
Guest lecture: Erik Anderson<br />
<br />
Topics: Applications of Visualization Techniques, Multi-modal Visualization<br />
<br />
Slides: VisualizationApplications [http://www.sci.utah.edu/~eranders/talk/scivis_applications/applications.ppt ppt] | [http://www.sci.utah.edu/~eranders/talk/scivis_applications/applications.odp odp]<br />
<br />
VisTrail: Contact me [http://www.sci.utah.edu/~eranders here]<br />
<br />
References:<br />
<br />
[http://www.sci.utah.edu/~eranders/papers/embs2007_neuro.pdf Working Memory in Schizophrenia] - Overview of rTMS in EEG Analysis<br />
<br />
[http://arxiv.org/abs/0706.1270 Cosmology Code Comparison Project] - Cosmological Simulation Project<br />
<br />
== 11/1: Simplification Techniques == <br />
<br />
Guest lecture: Yuan Zhou<br />
<br />
Topics: Simplification techniques: vertex clustering, vertex decimation, iterative contraction, quadric error based surface and tetrahedral simplification<br />
<br />
Slides: [http://graphics.cs.uiuc.edu/~yuanzhou/class/SciVis2007_simplification Simplification]<br />
<br />
References:<br />
<br />
[http://graphics.cs.uiuc.edu/~garland/papers/quadrics.pdf Surface Simplification Using Quadric Error Metrics]<br />
<br />
[http://graphics.cs.uiuc.edu/~garland/papers/STAR99 Multiresolution Modeling : Survey & Future Opportunities]<br />
<br />
[http://graphics.cs.uiuc.edu/~garland/papers/TR-2004-2450 Quadric-Based Simplication in Any Dimension] <br />
<br />
[http://www.sci.utah.edu/~csilva/papers/tvcg2007cr Streaming Simplification of Tetrahedral Meshes]<br />
<br />
== 11/6: Direct Volume Rendering ==<br />
<br />
Lecturer: Claudio<br />
<br />
Topics: Unstructured grid techniques<br />
<br />
Slides: [http://www.cs.utah.edu/~csilva/courses/cs5630/unstructured_grid_rendering.pdf unstructured_grid_rendering.pdf]<br />
<br />
References:<br />
<br />
[http://www.sci.utah.edu/~csilva/papers/rita2005.pdf A Survey of GPU-Based Volume Rendering of Unstructured Grid]<br />
<br />
[http://www.sci.utah.edu/~csilva/papers/tvcg2005cr.pdf Hardware-Assisted Visibility Sorting for Unstructured Volume Rendering] (This technique is implemented in VTK: http://www.vtk.org/doc/nightly/html/classvtkHAVSVolumeMapper.html)<br />
<br />
[http://www.sci.utah.edu/~csilva/papers/volvis2000.pdf ZSWEEP: An Efficient and Exact Projection Algorithm for Unstructured Volume Rendering] (This technique is implemented in VTK: http://www.vtk.org/doc/nightly/html/classvtkUnstructuredGridVolumeZSweepMapper.html)<br />
<br />
== 11/8: Direct Volume Rendering ==<br />
<br />
Lecturer: Claudio<br />
<br />
Topics: Transfer function specification<br />
<br />
Slides: [http://www.cs.utah.edu/~csilva/courses/cs5630/transfer_functions.pdf transfer_functions.pdf]<br />
<br />
References: <br />
<br />
[http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=920623 The transfer function bake-off]<br />
<br />
[http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=663875 The contour spectrum]<br />
<br />
[http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=1021579 Multidimensional transfer functions for interactive volume rendering]<br />
<br />
[http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=729588 Semi-automatic generation of transfer functions for direct volumerendering]<br />
<br />
== 11/13: Tensor Visualization ==<br />
<br />
Lecturer: Carlos<br />
<br />
Topics: DT/MRI intro, glyphs, colormapping, volume rendering<br />
<br />
Slides: [http://www.sci.utah.edu/~cscheid/scivis_fall07/dti.html .html slideshow]<br />
<br />
References: [http://www.cs.utah.edu/research/techreports/2004/pdf/UUCS-04-014.pdf G. Kindlmann's PhD thesis], covering most of what we've seen in the slides.<br />
<br />
== 11/15: 3D Vector Vis and Topology ==<br />
<br />
Lecturer: Carlos<br />
<br />
Topics: 3D techniques, critical points<br />
<br />
Slides: [http://www.sci.utah.edu/~cscheid/scivis_fall07/3dvectorvis.pdf 3D vector vis, .pdf file] [http://www.sci.utah.edu/~cscheid/scivis_fall07/vftopology.pdf Vector field topology, .pdf file]<br />
<br />
== 11/20: Information Visualization ==<br />
<br />
Lecturer: Carlos<br />
<br />
Topics: Parallel coordinates; Graph visualization<br />
<br />
Slides: [http://www.sci.utah.edu/~cscheid/scivis_fall07/Infovis.pdf .pdf file]<br />
<br />
== 11/22: Thanksgiving == <br />
<br />
== 11/27: Information Visualization ==<br />
<br />
Lecturer: Carlos and Steve<br />
<br />
Topics: Trees and Graphs; InfoVis Examples<br />
<br />
Links:<br />
* [http://www.many-eyes.com Many Eyes]<br />
* [http://www.win.tue.nl/sequoiaview/ SequioaView]<br />
* [http://www.gg.caltech.edu/~zhukov/infovis/world_of_music.htm World Of Music]<br />
* [http://www.tableausoftware.com/ Tableau]<br />
* [http://http://www.gapminder.org/ GapMinder]<br />
* [http://www.babynamewizard.com/namevoyager/lnv0105.html Name Voyager]<br />
<br />
== 11/29: Aesthetic Issues in Vis ==<br />
<br />
Lecturer: Steve<br />
<br />
Topics: Tufte principles<br />
<br />
Slides: [http://www.sci.utah.edu/~stevec/classes/cs5630/Tufte.pdf Tufte.pdf]<br />
<br />
References:<br />
* Envisioning Information, Edward R. Tufte, Academic Press, 1990<br />
* Visual Explanations: Images and Quantities, Evidence and Narrative, Edward R. Tufte, Academic Press, 1997<br />
<br />
== 12/4: Aesthetic Issues in Vis ==<br />
<br />
Lecturer: Steve<br />
<br />
Topics: NPR and Illustrative techniques for Vis<br />
<br />
Slides: [http://www.sci.utah.edu/~stevec/classes/cs5630/illustrative.html illustrative.html]<br />
<br />
vistrails: [http://www.sci.utah.edu/~stevec/classes/cs5630/illustrative.zip illustrative.zip] includes DifferentialGeometry.vt as well as norm.120.vtk and angle.120.vtk volume datasets.<br />
<br />
References:<br />
<br />
*[http://www.cs.utah.edu/~gk/papers/vis03/ Curvature-based Transfer Functions], Gordon Kindlmann.<br />
*[http://www.cs.utah.edu/~gooch/NPRcourse_SIG99/NPRcourse.html SIGGRAPH 99 NPR course notes], Bruce and Amy Gooch.<br />
*[http://www.ii.uib.no/vis/research/tutorials/2007-vis-illustrative_vis/tutorial_notes.pdf Vis 07 Illustrative Vis course notes], Viola, Bruckner, Sousa, Ebert, and Correa.<br />
*[http://www.cs.princeton.edu/gfx/proj/sg05lines/ SIGGRAPH 05 Line Drawings course notes], Rusinkiewicz, DeCarlo, and Finkelstein.<br />
<br />
== 12/6: Misc ==<br />
<br />
Lecturer: Claudio<br />
<br />
Topics: Data Management for Vis, Vis for presentation/discovery<br />
<br />
== 12/11: Misc ==<br />
<br />
Lecturer: Claudio<br />
<br />
Topics: Recap, Open research questions</div>Tue, 04 Dec 2007 21:52:54 GMTStevechttps://www.vistrails.org//index.php/Talk:SciVisFall2007/ScheduleSciVisFall2007/Schedule
https://www.vistrails.org//index.php?title=SciVisFall2007/Schedule&diff=943
https://www.vistrails.org//index.php?title=SciVisFall2007/Schedule&diff=943<p>Stevec: /* 12/4: Aesthetic Issues in Vis */</p>
<hr />
<div>== 8/21: Introduction to visualization ==<br />
<br />
Lecturer: Claudio<br />
<br />
Topics: Scientific Visualization<br />
<br />
Notes: [http://www.cs.utah.edu/~csilva/courses/cs5630/lec01-notes.pdf lec01-notes.pdf]<br />
<br />
Slides: [http://www.cs.utah.edu/~csilva/courses/cs5630/lec01.pdf lec01.pdf]<br />
<br />
Animations: [http://www.cs.utah.edu/~csilva/courses/cs5630/explosion_640x480-5.mov explosion_640x480-5.mov], [http://www.cs.utah.edu/~csilva/courses/cs5630/fig7.mov fig7.mov], [http://www.cs.utah.edu/~csilva/courses/cs5630/fig8.mov fig8.mov], [http://www.cs.utah.edu/~csilva/courses/cs5630/fig9.mov fig9.mov], [http://www.cs.utah.edu/~csilva/courses/cs5630/SevereTstorm.mov SevereTstorm.mov]<br />
<br />
Further reading: <br />
<br />
[http://www.sci.utah.edu/~csilva/papers/vis2003.pdf Visualizing Spatial and Temporal Variability in Coastal Observatories], W. Herrera-Jimenez, W. Correa, C. Silva, and A. Baptista, IEEE Visualization 2003.<br />
<br />
== 8/23: The visualization pipeline ==<br />
<br />
Lecturer: Claudio<br />
<br />
Topics: Procedural vs. Dataflow programming; Using Dataflow for the Vis Pipeline; Dataflow programming with VTK; Dataflow programming with VisTrails; python.<br />
<br />
Notes: [http://www.cs.utah.edu/~csilva/courses/cs5630/lec02-notes.pdf lec02-notes.pdf]<br />
<br />
Slides: [http://www.cs.utah.edu/~csilva/courses/cs5630/lec02.pdf lec02.pdf]<br />
<br />
VisTrails: During this class, we built a pipeline equivalent to the cone.tcl (see class slides). Here is the vistrails file: [http://www.cs.utah.edu/~csilva/courses/cs5630/cone.vt cone.vt]<br />
<br />
Further reading: <br />
<br />
[http://www.cs.utah.edu/~csilva/courses/cs5630/reproducible_vis.pdf Provenance for Visualizations: Reproducibility and Beyond], C. Silva, J. Freire, and S. Callahan, IEEE Computing in Science and Engineering, to appear.<br />
<br />
== 8/28: Modeling Data for Visualization ==<br />
<br />
Lecturer: Carlos<br />
<br />
Topics: Discrete vs continous data; Sampling and interpolation; Point vs triangulated data; Meshing data types; Regular vs irregular data; Tabular data; Vector and tensor fields<br />
<br />
Notes: TBA<br />
<br />
Slides: [http://www.sci.utah.edu/~cscheid/scivis_fall07/modelling_1.ppt .ppt file]<br />
<br />
Further reading: <br />
<br />
There is no required reading for this lecture. The notes will be available shortly. The following papers are there for people that are looking to get more advanced material that will not be covered in class.<br />
<br />
=== Interpolation ===<br />
<br />
[http://lmi.bwh.harvard.edu/papers/papers/geodesic-loxodromes-final.html Geodesic-loxodromes...] This is the fancy interpolation for diffusion tensors I mentioned in class.<br />
<br />
[http://en.wikipedia.org/wiki/Bernstein_polynomial Bernstein polynomials] These are the polynomials used for cubic Bezier curves that I mentioned in class.<br />
<br />
==== Separability ====<br />
<br />
[http://portal.acm.org/citation.cfm?id=1187793 Extensions of the Zwart-Powell Box spline...] This is a recent paper that shows a class of trivariate reconstruction techniques that are ''not'' separable.<br />
<br />
==== Tensors ====<br />
<br />
[http://www.cs.utah.edu/research/techreports/2004/pdf/UUCS-04-014.pdf Visualization and Analysis of Diffusion Tensor Fields] Gordon Kindlmann's PhD. thesis, with everything you ever wanted to know about DTI. Section 2.1 has a good primer in tensor algebra.<br />
<br />
== 8/30: Modeling Data for Visualization == <br />
<br />
Lecturer: Carlos<br />
<br />
Topics: Geometry Processing: Reconstruction and meshing; Simplification; Smoothing; Other Filtering algorithms<br />
<br />
Notes: [http://www.sci.utah.edu/~cscheid/scivis_fall07/week2.pdf .pdf file]. If you want to print these, you might want to wait for a week or two, until I finish polishing them.<br />
<br />
Slides: [http://www.sci.utah.edu/~cscheid/scivis_fall07/processing.ppt .ppt file] ''These slides include simplificatin algorithms, which I'll talk about next week.''<br />
<br />
== 9/4: Elementary Plotting Techniques == <br />
<br />
Lecturer: Steve<br />
<br />
Topics: Principles of Graph Construction<br />
<br />
Notes: [http://www.sci.utah.edu/~stevec/classes/cs5630/PlottingNotes.pdf PlottingNotes.pdf]<br />
<br />
Slides: [http://www.sci.utah.edu/~stevec/slides/SciVis/Plotting1.pdf Plotting1.pdf]<br />
<br />
Vistrails: See next lecture.<br />
<br />
Further Reading: There is no required reading for this lecture. For those interested in more depth, the following books are very useful:<br />
<br />
* The Elements of Graphing Data. William S. Cleveland, Hobart Press, 2nd Edition, 1994.<br />
* Visualizing Data. William S. Cleveland, Hobart Press, 1993.<br />
* The Visual Display of Quantitative Information. Edward R. Tufte, Graphics Press, 2001.<br />
* Visual Explanations: Images and Quantities, Evidence and Narrative. Edward R. Tufte, Graphics Press, 2997.<br />
<br />
== 9/6: Elementary Plotting Techniques ==<br />
<br />
Lecturer: Steve<br />
<br />
Topics: Simple Plotting Methods: Dot Plots, Connected Symbol Plots, Scatter Plots, Histograms, Others. Advanced Plotting Methods: Multimodal, Higher Dimensional, Correlation, Uncertainty and Variation.<br />
<br />
Notes: [http://www.sci.utah.edu/~stevec/classes/cs5630/PlottingNotes.pdf PlottingNotes.pdf]<br />
<br />
Slides: [http://www.sci.utah.edu/~stevec/slides/SciVis/Plotting2.pdf Plotting2.pdf]<br />
<br />
Vistrails: [http://www.sci.utah.edu/~stevec/classes/cs5630/PlottingVistrails.zip PlottingVistrails.zip] - Unzip this file in the examples directory of your VisTrails installation and it will add the vistrails along with their data sets (in the data directory). If you don't have permission to write to this directory (CADE users), then unzip the file where you want. Just be aware that in this case the paths for the data files may not be correct for most vistrails and will need to be fixed before they will execute properly.<br />
<br />
<br />
Further Reading: There is no required reading for this lecture. Some articles of interest:<br />
<br />
* [http://www.fmrib.ox.ac.uk/analysis/techrep/tr00mj2/tr00mj2/node24.html Histogram Bin Size]<br />
* [http://en.wikipedia.org/wiki/Correlation Correlation]<br />
* [http://en.wikipedia.org/wiki/Linear_regression Linear Regression]<br />
* [http://en.wikipedia.org/wiki/Box_plot Box Plots]<br />
<br />
== 9/11: Color and Human Perception ==<br />
<br />
Lecturer: Claudio<br />
<br />
Topics: Human vision system; Optical illusions<br />
<br />
Notes: TBA<br />
<br />
Slides: [http://www.cs.utah.edu/~csilva/courses/cs5630/human-vision.pdf human-vision.pdf]<br />
<br />
Links:<br />
<br />
http://en.wikipedia.org/wiki/Eye<br />
<br />
http://www.grand-illusions.com/gregory2.htm (also, see the related book: [http://www.amazon.com/Eye-Brain-Richard-L-Gregory/dp/0691048371])<br />
<br />
http://en.wikipedia.org/wiki/Purkinje_effect<br />
<br />
http://www.handprint.com/HP/WCL/color2.html<br />
<br />
== 9/13: Color and Human Perception ==<br />
<br />
Lecturer: Claudio<br />
<br />
Topics: Color Science; Color spaces; Color Blindness; Color maps; Tone mapping<br />
<br />
Notes: TBA<br />
<br />
Slides: [http://www.cs.utah.edu/~csilva/courses/cs5630/colorvision.pdf colorvision.pdf]<br />
<br />
Links:<br />
<br />
Further reading: <br />
<br />
[http://www.research.ibm.com/dx/proceedings/pravda/truevis.htm How Not to Lie with Visualization]<br />
<br />
http://en.wikipedia.org/wiki/Opponent_process<br />
<br />
http://en.wikipedia.org/wiki/Color_models<br />
<br />
http://en.wikipedia.org/wiki/Absolute_color_space<br />
<br />
http://en.wikipedia.org/wiki/Additive_color<br />
<br />
http://en.wikipedia.org/wiki/Subtractive_color<br />
<br />
http://en.wikipedia.org/wiki/RGB_color_model<br />
<br />
http://en.wikipedia.org/wiki/SRGB_color_space<br />
<br />
http://en.wikipedia.org/wiki/CIE_XYZ_color_space<br />
<br />
== 9/18 (a): Color and Human Perception ==<br />
<br />
Lecturer: Claudio<br />
<br />
Same material as previous lecture. <br />
<br />
== 9/18 (b): 2D Visualization Techniques ==<br />
<br />
Lecturer: Carlos<br />
<br />
Topics: 2-D contours, marching quads, marching tris; Color mapping; height fields; NPR<br />
<br />
Slides: [http://www.sci.utah.edu/~cscheid/scivis_fall07/2d_scalar_vis.pdf pdf file]<br />
<br />
Notes: [http://www.sci.utah.edu/~cscheid/scivis_fall07/2d_scalar_vis_notes.pdf pdf file]<br />
<br />
Vistrails: [http://www.sci.utah.edu/~cscheid/scivis_fall07/ozone_and_data.zip zip file with ozone.vt and data] [http://www.sci.utah.edu/~cscheid/scivis_fall07/asymptotic_decider.vt asymptotic decider in 2d] [http://www.sci.utah.edu/~cscheid/scivis_fall07/elevation.zip heightfields]<br />
<br />
Note: These vistrails use relative file paths so you don't need to change each of them individually to match your directory structure. Simply unzip the file to whichever location is more convenient. Then, inside VisTrails, open the VisTrails shell, type:<br />
<br />
import os<br />
os.chdir("c:/directory/where/you/unzipped/it")<br />
<br />
This will change the directory so you should be able to just run the pipelines.<br />
<br />
== 9/20: Math refresher ==<br />
<br />
Lecturer: Carlos<br />
<br />
Topics: Basic linear algebra; vectors; basic differential geometry (space curves, tangents, normals, surfaces); basic vector calculus (gradient, divergence, curl, gauss' theorem, green's theorem) <br />
<br />
== 9/25: 2D Visualization Techniques ==<br />
<br />
Lecturer: Carlos<br />
<br />
Topics: 2-D vector fields, div, grad, curl in 2D; Steady vs Unsteady flows; Glyphs; 2-D streamlines, streaklines, pathlines<br />
<br />
Slides: [http://www.sci.utah.edu/~cscheid/scivis_fall07/2d_vector_vis.pdf pdf file]<br />
<br />
Notes: coming soon<br />
<br />
Vistrails: [http://www.sci.utah.edu/~cscheid/scivis_fall07/vector_vis_1.zip vistrail with steady vector field vis and data] [http://www.sci.utah.edu/~cscheid/scivis_fall07/unsteady.zip vistrail with unsteady vector field vis and data] '''Note:''' Because VTK does not support time-varying datasets directly, we had to create a reasonably ugly hack to simulate unsteady fields. This means the datasets are quite big (80MB in total).<br />
<br />
== 9/27 (a): 2D Visualization Techniques ==<br />
<br />
Lecturer Carlos<br />
<br />
Same material as last lecture.<br />
<br />
== 9/27 (b): Volume Vis ==<br />
<br />
Lecturer: Claudio<br />
<br />
Topics: Slicing; Contours; Marching algorithms<br />
<br />
Slides: [http://www.cs.utah.edu/~csilva/courses/cs5630/iso-basic.pdf iso-basic.pdf]<br />
<br />
References:<br />
<br />
[http://portal.acm.org/citation.cfm?id=37401.37422 Marching cubes: A high resolution 3D surface construction algorithm]<br />
<br />
[http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=175782 The asymptotic decider: resolving the ambiguity in marching cubes]<br />
<br />
== 10/2: Volume Vis == <br />
<br />
Lecturer: Claudio<br />
<br />
Topics: Accelerating structures; High-quality contours<br />
<br />
Slides: <br />
<br />
[http://www.cs.utah.edu/~csilva/courses/cs5630/iso-speed.pdf iso-speed.pdf]<br />
<br />
[http://www.cs.utah.edu/~csilva/courses/cs5630/iso-speed-2.pdf iso-speed-2.pdf]<br />
<br />
References:<br />
<br />
[http://doi.ieeecomputersociety.org/10.1109/2945.489388 A Near Optimal Isosurface Extraction Algorithm Using the Span Space]<br />
<br />
[http://doi.ieeecomputersociety.org/10.1109/2945.485619 Automatic Isosurface Propagation Using an Extrema Graph and Sorted Boundary Cell Lists]<br />
<br />
[http://doi.ieeecomputersociety.org/10.1109/2945.597798 Speeding Up Isosurface Extraction Using Interval Trees]<br />
<br />
[http://doi.ieeecomputersociety.org/10.1109/SVVG.2004.5 Implicit Occluders]<br />
<br />
== 10/4: Volume Vis ==<br />
<br />
Lecturer: Claudio<br />
<br />
Topics: High quality isosurfaces<br />
<br />
Slides: [http://www.cs.utah.edu/~csilva/courses/cs5630/iso-quality.pdf iso-quality.pdf]<br />
<br />
References:<br />
<br />
[http://www.cs.utah.edu/~csilva/2007-sub/macet.pdf Edge Transformations for Improving Mesh Quality of Marching Cubes]<br />
<br />
[http://www.sci.utah.edu/~csilva/papers/tvcg2006acr.pdf High-Quality Extraction of Isosurfaces from Regular and Irregular Grids]<br />
<br />
[http://portal.acm.org/citation.cfm?id=566570.566586 Dual contouring of hermite data]<br />
<br />
[http://www.sci.utah.edu/%7Emiriah/research/meshing/vis07meyer.pdf Topology, Accuracy, and Quality of Isosurface Meshes Using Dynamic Particles]<br />
<br />
[http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=1260744 Material interface reconstruction]<br />
<br />
== 10/9: Fall break == <br />
<br />
== 10/11: Fall break == <br />
<br />
== 10/16: Volume Vis ==<br />
<br />
Lecturer: Claudio<br />
<br />
Topics: continued from last class<br />
<br />
== 10/18: Direct Volume Rendering ==<br />
<br />
Lecturer: Steve<br />
<br />
Topics: Introduction to volume rendering<br />
<br />
Slides: [http://www.sci.utah.edu/~stevec/classes/cs5630/VolumeRendering1.pdf VolumeRendering1.pdf]<br />
<br />
Notes: [http://www.sci.utah.edu/~stevec/classes/cs5630/dvr.pdf dvr.pdf]<br />
<br />
vistrails: [http://www.sci.utah.edu/~stevec/classes/cs5630/VolumeRenderingVistrails.zip VolumeRenderingVistrails.zip]<br />
<br />
References:<br />
[http://www.llnl.gov/graphics/docs/OpticalModelsLong.pdf Optical Models for Direct Volume Rendering]<br />
<br />
== 10/23: Midterm 1 ==<br />
<br />
== 10/25: Direct Volume Rendering ==<br />
<br />
Lecturer: Steve<br />
<br />
Topics: Structured grid techniques: ray-casting, splatting, texture slicing, shear-warp<br />
<br />
Slides: [http://www.sci.utah.edu/~stevec/classes/cs5630/VolumeRendering2.pdf VolumeRendering2.pdf]<br />
<br />
Notes: same as previous class<br />
<br />
vistrails: same as previous class<br />
<br />
References:<br />
<br />
[http://graphics.stanford.edu/papers/volume-cga88/ Display of Surfaces from Volume Data] - Ray casting paper<br />
<br />
[http://portal.acm.org/citation.cfm?id=329138 Interactive Volume Rendering] - Splatting paper, paper requires ACM digital library access<br />
<br />
[http://portal.acm.org/citation.cfm?id=197972&dl=ACM&coll=GUIDE Accelerated volume rendering and tomographic reconstruction using texture mapping hardware] - Texture slicing paper, requires ACM digital library access<br />
<br />
[http://graphics.stanford.edu/papers/shear/ Fast Volume Rendering Using a Shear-Warp Factorization of the Viewing Transformation] - Shear-warp paper<br />
<br />
== 10/30: Cosmology and EEG analysis ==<br />
<br />
Guest lecture: Erik Anderson<br />
<br />
Topics: Applications of Visualization Techniques, Multi-modal Visualization<br />
<br />
Slides: VisualizationApplications [http://www.sci.utah.edu/~eranders/talk/scivis_applications/applications.ppt ppt] | [http://www.sci.utah.edu/~eranders/talk/scivis_applications/applications.odp odp]<br />
<br />
VisTrail: Contact me [http://www.sci.utah.edu/~eranders here]<br />
<br />
References:<br />
<br />
[http://www.sci.utah.edu/~eranders/papers/embs2007_neuro.pdf Working Memory in Schizophrenia] - Overview of rTMS in EEG Analysis<br />
<br />
[http://arxiv.org/abs/0706.1270 Cosmology Code Comparison Project] - Cosmological Simulation Project<br />
<br />
== 11/1: Simplification Techniques == <br />
<br />
Guest lecture: Yuan Zhou<br />
<br />
Topics: Simplification techniques: vertex clustering, vertex decimation, iterative contraction, quadric error based surface and tetrahedral simplification<br />
<br />
Slides: [http://graphics.cs.uiuc.edu/~yuanzhou/class/SciVis2007_simplification Simplification]<br />
<br />
References:<br />
<br />
[http://graphics.cs.uiuc.edu/~garland/papers/quadrics.pdf Surface Simplification Using Quadric Error Metrics]<br />
<br />
[http://graphics.cs.uiuc.edu/~garland/papers/STAR99 Multiresolution Modeling : Survey & Future Opportunities]<br />
<br />
[http://graphics.cs.uiuc.edu/~garland/papers/TR-2004-2450 Quadric-Based Simplication in Any Dimension] <br />
<br />
[http://www.sci.utah.edu/~csilva/papers/tvcg2007cr Streaming Simplification of Tetrahedral Meshes]<br />
<br />
== 11/6: Direct Volume Rendering ==<br />
<br />
Lecturer: Claudio<br />
<br />
Topics: Unstructured grid techniques<br />
<br />
Slides: [http://www.cs.utah.edu/~csilva/courses/cs5630/unstructured_grid_rendering.pdf unstructured_grid_rendering.pdf]<br />
<br />
References:<br />
<br />
[http://www.sci.utah.edu/~csilva/papers/rita2005.pdf A Survey of GPU-Based Volume Rendering of Unstructured Grid]<br />
<br />
[http://www.sci.utah.edu/~csilva/papers/tvcg2005cr.pdf Hardware-Assisted Visibility Sorting for Unstructured Volume Rendering] (This technique is implemented in VTK: http://www.vtk.org/doc/nightly/html/classvtkHAVSVolumeMapper.html)<br />
<br />
[http://www.sci.utah.edu/~csilva/papers/volvis2000.pdf ZSWEEP: An Efficient and Exact Projection Algorithm for Unstructured Volume Rendering] (This technique is implemented in VTK: http://www.vtk.org/doc/nightly/html/classvtkUnstructuredGridVolumeZSweepMapper.html)<br />
<br />
== 11/8: Direct Volume Rendering ==<br />
<br />
Lecturer: Claudio<br />
<br />
Topics: Transfer function specification<br />
<br />
Slides: [http://www.cs.utah.edu/~csilva/courses/cs5630/transfer_functions.pdf transfer_functions.pdf]<br />
<br />
References: <br />
<br />
[http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=920623 The transfer function bake-off]<br />
<br />
[http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=663875 The contour spectrum]<br />
<br />
[http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=1021579 Multidimensional transfer functions for interactive volume rendering]<br />
<br />
[http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=729588 Semi-automatic generation of transfer functions for direct volumerendering]<br />
<br />
== 11/13: Tensor Visualization ==<br />
<br />
Lecturer: Carlos<br />
<br />
Topics: DT/MRI intro, glyphs, colormapping, volume rendering<br />
<br />
Slides: [http://www.sci.utah.edu/~cscheid/scivis_fall07/dti.html .html slideshow]<br />
<br />
References: [http://www.cs.utah.edu/research/techreports/2004/pdf/UUCS-04-014.pdf G. Kindlmann's PhD thesis], covering most of what we've seen in the slides.<br />
<br />
== 11/15: 3D Vector Vis and Topology ==<br />
<br />
Lecturer: Carlos<br />
<br />
Topics: 3D techniques, critical points<br />
<br />
Slides: [http://www.sci.utah.edu/~cscheid/scivis_fall07/3dvectorvis.pdf 3D vector vis, .pdf file] [http://www.sci.utah.edu/~cscheid/scivis_fall07/vftopology.pdf Vector field topology, .pdf file]<br />
<br />
== 11/20: Information Visualization ==<br />
<br />
Lecturer: Carlos<br />
<br />
Topics: Parallel coordinates; Graph visualization<br />
<br />
Slides: [http://www.sci.utah.edu/~cscheid/scivis_fall07/Infovis.pdf .pdf file]<br />
<br />
== 11/22: Thanksgiving == <br />
<br />
== 11/27: Information Visualization ==<br />
<br />
Lecturer: Carlos and Steve<br />
<br />
Topics: Trees and Graphs; InfoVis Examples<br />
<br />
Links:<br />
* [http://www.many-eyes.com Many Eyes]<br />
* [http://www.win.tue.nl/sequoiaview/ SequioaView]<br />
* [http://www.gg.caltech.edu/~zhukov/infovis/world_of_music.htm World Of Music]<br />
* [http://www.tableausoftware.com/ Tableau]<br />
* [http://http://www.gapminder.org/ GapMinder]<br />
* [http://www.babynamewizard.com/namevoyager/lnv0105.html Name Voyager]<br />
<br />
== 11/29: Aesthetic Issues in Vis ==<br />
<br />
Lecturer: Steve<br />
<br />
Topics: Tufte principles<br />
<br />
Slides: [http://www.sci.utah.edu/~stevec/classes/cs5630/Tufte.pdf Tufte.pdf]<br />
<br />
References:<br />
* Envisioning Information, Edward R. Tufte, Academic Press, 1990<br />
* Visual Explanations: Images and Quantities, Evidence and Narrative, Edward R. Tufte, Academic Press, 1997<br />
<br />
== 12/4: Aesthetic Issues in Vis ==<br />
<br />
Lecturer: Steve<br />
<br />
Topics: NPR and Illustrative techniques for Vis<br />
<br />
Slides: [http://www.sci.utah.edu/~stevec/classes/cs5630/illustrative.pdf illustrative.pdf]<br />
<br />
vistrails: [http://www.sci.utah.edu/~stevec/classes/cs5630/illustrative.zip illustrative.zip] includes DifferentialGeometry.vt as well as norm.120.vtk and angle.120.vtk volume datasets.<br />
<br />
References:<br />
<br />
*[http://www.cs.utah.edu/~gk/papers/vis03/ Curvature-based Transfer Functions], Gordon Kindlmann.<br />
*[http://www.cs.utah.edu/~gooch/NPRcourse_SIG99/NPRcourse.html SIGGRAPH 99 NPR course notes], Bruce and Amy Gooch.<br />
*[http://www.ii.uib.no/vis/research/tutorials/2007-vis-illustrative_vis/tutorial_notes.pdf Vis 07 Illustrative Vis course notes], Viola, Bruckner, Sousa, Ebert, and Correa.<br />
*[http://www.cs.princeton.edu/gfx/proj/sg05lines/ SIGGRAPH 05 Line Drawings course notes], Rusinkiewicz, DeCarlo, and Finkelstein.<br />
<br />
== 12/6: Misc ==<br />
<br />
Lecturer: Claudio<br />
<br />
Topics: Data Management for Vis, Vis for presentation/discovery<br />
<br />
== 12/11: Misc ==<br />
<br />
Lecturer: Claudio<br />
<br />
Topics: Recap, Open research questions</div>Tue, 04 Dec 2007 20:49:35 GMTStevechttps://www.vistrails.org//index.php/Talk:SciVisFall2007/ScheduleSciVisFall2007/Assignment 4
https://www.vistrails.org//index.php?title=SciVisFall2007/Assignment_4&diff=942
https://www.vistrails.org//index.php?title=SciVisFall2007/Assignment_4&diff=942<p>Stevec: </p>
<hr />
<div>The assignment is due at midnight on December 15th. <br />
The purpose of this assignment is to make sure you understand (and experiment with) the basic concepts involved in the visualization of Diffusion Tensor volumes as well as large graphs. As you work on the assignment, we greatly encourage you to read the available documentation on both python and VTK. Some of the problems will require you to use VTK modules you might not have previously seen. These are indicated in the problems.<br />
<br />
== Submitting your vistrails ==<br />
The assignment is broken into two distinct parts: DTI vis and graph vis. Two different vistrails should be used for these tasks, assignment4a.vt and assignment 4b.vt, respectively. You may start from an empty vistrail or from examples that are given. You will need to use the CADE handin functionality to turn in your assignment. The class account is "cs5630". Both vistrails will need to be submitted.<br />
<br />
== Assignment 4a: DTI Visualization ==<br />
<br />
The first part of the assignment is to perform some basic visualizations of diffusion tensor data. Because this is the final assignment, it will be a little more difficult because there are no examples given. It also combines many of the techniques covered in other assignments such as color mapping, isosurfacing, glyph visualization, and streamlines.<br />
<br />
This is a diffusion tensor dataset [http://www.sci.utah.edu/~stevec/classes/cs5630/gktbh.vtk gktbh.vtk], and a corresponding anisotropy volume [http://www.sci.utah.edu/~stevec/classes/cs5630/gktbhFA.vtk gktbhFA.vtk]. These volumes cover the right half of a [http://www.cs.utah.edu/~gk Gordon Kindlmann's] brain. They encode information about the structure of the brain matter. The anisotropy volume has high values in regions which are likely white matter in the brain, and these are the regions of interest.<br />
<br />
<br />
'''Problem 1a:''' Perform isosurface rendering of the anisotropy volume using multiple transparent, colored, isosurfaces. In the version tree notes for the node, describe (roughly) what the isosurfaces show are the regions that are highly anisotropic and those that are highly isotropic.<br />
<br />
<br />
'''Problem 1b:''' Perform glyph visualization of the DT dataset. Choose whatever glyph geometry you want (cube, sphere, cylinder, etc.) but make sure it is appropriate for the symmetry imposed by the sign ambiguity of eigenvectors. The glyphs should be color mapped by their anisotropy. In order to produce a clear visualization, you need to control the number of glyphs produced to show only regions of high anisotropy to reduce clutter. Here are a few possible ways of doing this:<br />
* Producing glyphs only in a region constrained to some simple geometry, such as on a plane which you use to probe the volume<br />
* Producing glyphs only within range of values defined by a threshold<br />
* Producing glyphs on the vertices of an invisible isosurface.<br />
In the notes for the node, describe why you chose the glyph representation that you did and how you limited the clutter.<br />
<br />
<br />
'''Problem 1c:''' (Grads Only) Based on your knowedge of where the highly directional features are, visualize them using several well-placed hyperstreamlines. In the notes for the node, describe how you chose the seed points<br />
<br />
<br />
'''Problem 1d:''' Create a composite visualization that combines all three techniques (or two techniques for U-Grads) described above.<br />
<br />
<br />
'''Hints:'''<br />
* Multiple isosurfaces can be easily defined using the GenerateValues method.<br />
* Combining two disjoint datasets (tensors and scalars) into one dataset requires a vtkMergeFilter.<br />
* See documentation on vtkTensorGlyphs for more info on tensor glyphs.<br />
* Combining a glyph represenatation with a colormap requires a vtkProbeFilter.<br />
* A scalar volume can be turned into a colormap using vtkImageMapToColors<br />
<br />
== Assignment 4b: Graph Visualization ==<br />
<br />
The goal of this assignement is to compare several different InfoVis graph layout strategies. InfoVis capabilities in VTK are very new (ie., unstable) and some of the features do not work to well, or crash (I recommend saving often). Thus, this assignment will be somewhat limited in what we can do. The graph we will be visualizing is the vtk class hierarchy, generated on-the-fly using a PythonSource and Python's introspection capabilities.<br />
An example vistrail that creates an interactive treemap can be found here: [http://www.sci.utah.edu/~stevec/classes/cs5630/assignment4b.vt assignment4b.vt].<br />
<br />
<br />
Problem 2a: Replace the tree map with a graph layout (see vtkGraphLayout). Be sure to keep the labels on the resulting trees.<br />
<br />
<br />
Problem 2b: Experiment with different graph layout strategies and tag the one you like best. In the notes, comment on why you chose the layout you did. Note: I could not get the vtkTreeLayoutStrategy to work correctly (it always wants to be radial), you may have more or less luck.<br />
<br />
<br />
Hints:<br />
* See the vtk documentation, tests, and examples for the graph layout classes to get the pipelines right.</div>Tue, 04 Dec 2007 18:02:33 GMTStevechttps://www.vistrails.org//index.php/Talk:SciVisFall2007/Assignment_4SciVisFall2007/Assignment 4
https://www.vistrails.org//index.php?title=SciVisFall2007/Assignment_4&diff=940
https://www.vistrails.org//index.php?title=SciVisFall2007/Assignment_4&diff=940<p>Stevec: </p>
<hr />
<div>The assignment is due at midnight on December ??th. <br />
The purpose of this assignment is to make sure you understand (and experiment with) the basic concepts involved in the visualization of Diffusion Tensor volumes as well as large graphs. As you work on the assignment, we greatly encourage you to read the available documentation on both python and VTK. Some of the problems will require you to use VTK modules you might not have previously seen. These are indicated in the problems.<br />
<br />
== Submitting your vistrails ==<br />
The assignment is broken into two distinct parts: DTI vis and graph vis. Two different vistrails should be used for these tasks, assignment4a.vt and assignment 4b.vt, respectively. You may start from an empty vistrail or from examples that are given. You will need to use the CADE handin functionality to turn in your assignment. The class account is "cs5630". Both vistrails will need to be submitted.<br />
<br />
== Assignment 4a: DTI Visualization ==<br />
<br />
The first part of the assignment is to perform some basic visualizations of diffusion tensor data. Because this is the final assignment, it will be a little more difficult because there are no examples given. It also combines many of the techniques covered in other assignments such as color mapping, isosurfacing, glyph visualization, and streamlines.<br />
<br />
This is a diffusion tensor dataset [http://www.sci.utah.edu/~stevec/classes/cs5630/gktbh.vtk gktbh.vtk], and a corresponding anisotropy volume [http://www.sci.utah.edu/~stevec/classes/cs5630/gktbhFA.vtk gktbhFA.vtk]. These volumes cover the right half of a [http://www.cs.utah.edu/~gk Gordon Kindlmann's] brain. They encode information about the structure of the brain matter. The anisotropy volume has high values in regions which are likely white matter in the brain, and these are the regions of interest.<br />
<br />
<br />
'''Problem 1a:''' Perform isosurface rendering of the anisotropy volume using multiple transparent, colored, isosurfaces. In the version tree notes for the node, describe (roughly) what the isosurfaces show are the regions that are highly anisotropic and those that are highly isotropic.<br />
<br />
<br />
'''Problem 1b:''' Perform glyph visualization of the DT dataset. Choose whatever glyph geometry you want (cube, sphere, cylinder, etc.) but make sure it is appropriate for the symmetry imposed by the sign ambiguity of eigenvectors. The glyphs should be color mapped by their anisotropy. In order to produce a clear visualization, you need to control the number of glyphs produced to show only regions of high anisotropy to reduce clutter. Here are a few possible ways of doing this:<br />
* Producing glyphs only in a region constrained to some simple geometry, such as on a plane which you use to probe the volume<br />
* Producing glyphs only within range of values defined by a threshold<br />
* Producing glyphs on the vertices of an invisible isosurface.<br />
In the notes for the node, describe why you chose the glyph representation that you did and how you limited the clutter.<br />
<br />
<br />
'''Problem 1c:''' (Grads Only) Based on your knowedge of where the highly directional features are, visualize them using several well-placed hyperstreamlines. In the notes for the node, describe how you chose the seed points<br />
<br />
<br />
'''Problem 1d:''' Create a composite visualization that combines all three techniques (or two techniques for U-Grads) described above.<br />
<br />
<br />
'''Hints:'''<br />
* Multiple isosurfaces can be easily defined using the GenerateValues method.<br />
* Combining two disjoint datasets (tensors and scalars) into one dataset requires a vtkMergeFilter.<br />
* See documentation on vtkTensorGlyphs for more info on tensor glyphs.<br />
* Combining a glyph represenatation with a colormap requires a vtkProbeFilter.<br />
* A scalar volume can be turned into a colormap using vtkImageMapToColors<br />
<br />
== Assignment 4b: Graph Visualization ==<br />
<br />
The goal of this assignement is to compare several different InfoVis graph layout strategies. InfoVis capabilities in VTK are very new (ie., unstable) and some of the features do not work to well, or crash (I recommend saving often). Thus, this assignment will be somewhat limited in what we can do. The graph we will be visualizing is the vtk class hierarchy, generated on-the-fly using a PythonSource and Python's introspection capabilities.<br />
An example vistrail that creates an interactive treemap can be found here: [http://www.sci.utah.edu/~stevec/classes/cs5630/assignment4b.vt assignment4b.vt].<br />
<br />
<br />
Problem 2a: Replace the tree map with a graph layout (see vtkGraphLayout). Be sure to keep the labels on the resulting trees.<br />
<br />
<br />
Problem 2b: Experiment with different graph layout strategies and tag the one you like best. In the notes, comment on why you chose the layout you did. Note: I could not get the vtkTreeLayoutStrategy to work correctly (it always wants to be radial), you may have more or less luck.<br />
<br />
<br />
Hints:<br />
* See the vtk documentation, tests, and examples for the graph layout classes to get the pipelines right.</div>Tue, 04 Dec 2007 00:13:42 GMTStevechttps://www.vistrails.org//index.php/Talk:SciVisFall2007/Assignment_4SciVisFall2007
https://www.vistrails.org//index.php?title=SciVisFall2007&diff=939
https://www.vistrails.org//index.php?title=SciVisFall2007&diff=939<p>Stevec: /* Assignments */</p>
<hr />
<div>This page contains information on the Scientific Visualization course (CS 5630/6630) taught by [http://www.cs.utah.edu/~csilva Professor Cl&aacute;udio Silva] during Fall 2007 in the [http://www.cs.utah.edu School of Computing], [http://www.utah.edu University of Utah].<br />
<br />
This class meets on Tuesday and Thursdays, 10:45am-12:05am, WEB 112.<br />
<br />
== Course Overview == <br />
<br />
The demand for the construction of [http://en.wikipedia.org/wiki/Scientific_visualization complex visualizations] is growing in many disciplines of science, as users are faced with ever increasing volumes of data to analyze. In this class, we will cover the principles and techniques necessary to generate these visualizations. <br />
<br />
There will be no required textbook, although we recommend that students get a copy of the [http://www.amazon.com/Visualization-Handbook-Charles-D-Hansen/dp/012387582X Visualization Handbook] as a "reference at large". Also, Kitware's [http://www.kitware.com/products/vtkguide.html VTK User's Guide] might be useful. We will be providing a detailed set of course notes for the class.<br />
<br />
For the assignments, we will be using [http://www.vistrails.org VisTrails], [http://www.vtk.org VTK], and [http://matplotlib.sourceforge.net matplotlib] in this class. For each assignment, the students will need to turn in their complete "vistrail" for the work. <br />
<br />
Besides the assignments, there will be one midterm and one final. <br />
<br />
The latest version of VisTrails for this class can be downloaded here: {{zip<br />
|link=http://www.vistrails.org/download/download.php?id=vistrails-setup-1.0brev954-cs5630.zip<br />
|text=vistrails-setup-1.0brev954-cs5630.zip}}<br />
== Lectures, and consulting hours ==<br />
<br />
We will meet twice a week: Tuesday, Thursday, 10:45am-12:05pm, WEB 112.<br />
<br />
The instructor for the class is Claudio Silva.<br />
<br />
The lectures (and corresponding notes) will be giving by Claudio Silva, Steve Callahan, and Carlos Scheidegger.<br />
<br />
The TA for the course is Harsh Doshi.<br />
<br />
Silva office hours: Tuesdays and Thursdays (9:45 - 10:45 am), WEB 4893.<br />
<br />
Doshi office hours: Mondays and Wednesdays (1:00 - 4:00 pm), MEB 3115.<br />
<br />
== Schedule ==<br />
<br />
[http://www.vistrails.org/index.php/SciVisFall2007/Schedule Schedule]<br />
<br />
== Reading ==<br />
<br />
The class wiki page will contain up-to-date notes that reflect the material covered in class. We will also add pointers to supplementary material.<br />
<br />
In the tentative schedule, there are hints on what to read before attending the class. <br />
<br />
[http://www.vistrails.org/index.php/SciVisFall2007/VTK_Tips Tips for converting VTK pipelines]<br />
<br />
== Assignments ==<br />
<br />
For the assignments, you will be turning in ".vt" files produced with VisTrails. Here is a link to a Windows XP (also works for Vista) installer with the version that you will need: [http://www.vistrails.org/download/download.php?id=vistrails-setup-1.0brev921.zip VisTrails 1.0 beta]<br />
<br />
[http://www.vistrails.org/index.php/SciVisFall2007/Assignment_0 Assignment_0]<br />
<br />
[http://www.vistrails.org/index.php/SciVisFall2007/Assignment_1 Assignment_1]<br />
<br />
[http://www.vistrails.org/index.php/SciVisFall2007/Assignment_2 Assignment_2]<br />
<br />
[http://www.vistrails.org/index.php/SciVisFall2007/Assignment_3 Assignment_3]<br />
<br />
[http://www.vistrails.org/index.php/SciVisFall2007/Assignment_4 Assignment_4]<br />
<br />
== Late Assignments ==<br />
<br />
Assignments will not be accepted late. Students will be given a one-time two-day exemption for an unexpected event.<br />
<br />
== Grading ==<br />
<br />
Your grade will be a combination of assignments (70%) and midterm (15%) and final (15%).<br />
<br />
== Mailing List ==<br />
<br />
http://mailman.cs.utah.edu/mailman/listinfo/cs5630<br />
<br />
== Students With Disabilities ==<br />
<br />
The University of Utah seeks to provide equal access to its programs, services and activities for people with disabilities. If you will need accommodations in the class, reasonable prior notice needs to be given to the Center for Disability Services, 162 Olpin Union Building, 581-5020 (V/TDD). CDS will work with you and the instructor to make arrangements for accommodations.<br />
<br />
All written information in this course can be made available in alternative format with prior notification to the Center for Disability Services.</div>Mon, 03 Dec 2007 17:35:04 GMTStevechttps://www.vistrails.org//index.php/Talk:SciVisFall2007SciVisFall2007/Assignment 4
https://www.vistrails.org//index.php?title=SciVisFall2007/Assignment_4&diff=938
https://www.vistrails.org//index.php?title=SciVisFall2007/Assignment_4&diff=938<p>Stevec: /* Assignment 4b: Graph Visualization */</p>
<hr />
<div>The assignment is due at midnight on December 11th. <br />
The purpose of this assignment is to make sure you understand (and experiment with) the basic concepts involved in the visualization of Diffusion Tensor volumes as well as large graphs. As you work on the assignment, we greatly encourage you to read the available documentation on both python and VTK. Some of the problems will require you to use VTK modules you might not have previously seen. These are indicated in the problems.<br />
<br />
== Submitting your vistrails ==<br />
The assignment is broken into two distinct parts: DTI vis and graph vis. Two different vistrails should be used for these tasks, assignment4a.vt and assignment 4b.vt, respectively. You may start from an empty vistrail or from examples that are given. You will need to use the CADE handin functionality to turn in your assignment. The class account is "cs5630". Both vistrails will need to be submitted.<br />
<br />
== Assignment 4a: DTI Visualization ==<br />
<br />
The first part of the assignment is to perform some basic visualizations of diffusion tensor data. Because this is the final assignment, it will be a little more difficult because there are no examples given. It also combines many of the techniques covered in other assignments such as color mapping, isosurfacing, glyph visualization, and streamlines.<br />
<br />
This is a diffusion tensor dataset [http://www.sci.utah.edu/~stevec/classes/cs5630/gktbh.vtk gktbh.vtk], and a corresponding anisotropy volume [http://www.sci.utah.edu/~stevec/classes/cs5630/gktbhFA.vtk gktbhFA.vtk]. These volumes cover the right half of a [http://www.cs.utah.edu/~gk Gordon Kindlmann's] brain. They encode information about the structure of the brain matter. The anisotropy volume has high values in regions which are likely white matter in the brain, and these are the regions of interest.<br />
<br />
<br />
'''Problem 1a:''' Perform isosurface rendering of the anisotropy volume using multiple transparent, colored, isosurfaces. In the version tree notes for the node, describe (roughly) what the isosurfaces show are the regions that are highly anisotropic and those that are highly isotropic.<br />
<br />
<br />
'''Problem 1b:''' Perform glyph visualization of the DT dataset. Choose whatever glyph geometry you want (cube, sphere, cylinder, etc.) but make sure it is appropriate for the symmetry imposed by the sign ambiguity of eigenvectors. The glyphs should be color mapped by their anisotropy. In order to produce a clear visualization, you need to control the number of glyphs produced to show only regions of high anisotropy to reduce clutter. Here are a few possible ways of doing this:<br />
* Producing glyphs only in a region constrained to some simple geometry, such as on a plane which you use to probe the volume<br />
* Producing glyphs only within range of values defined by a threshold<br />
* Producing glyphs on the vertices of an invisible isosurface.<br />
In the notes for the node, describe why you chose the glyph representation that you did and how you limited the clutter.<br />
<br />
<br />
'''Problem 1c:''' (Grads Only) Based on your knowedge of where the highly directional features are, visualize them using several well-placed hyperstreamlines. In the notes for the node, describe how you chose the seed points<br />
<br />
<br />
'''Problem 1d:''' Create a composite visualization that combines all three techniques (or two techniques for U-Grads) described above.<br />
<br />
<br />
'''Hints:'''<br />
* Multiple isosurfaces can be easily defined using the GenerateValues method.<br />
* Combining two disjoint datasets (tensors and scalars) into one dataset requires a vtkMergeFilter.<br />
* See documentation on vtkTensorGlyphs for more info on tensor glyphs.<br />
* Combining a glyph represenatation with a colormap requires a vtkProbeFilter.<br />
* A scalar volume can be turned into a colormap using vtkImageMapToColors<br />
<br />
== Assignment 4b: Graph Visualization ==<br />
<br />
The goal of this assignement is to compare several different InfoVis graph layout strategies. InfoVis capabilities in VTK are very new (ie., unstable) and some of the features do not work to well, or crash (I recommend saving often). Thus, this assignment will be somewhat limited in what we can do. The graph we will be visualizing is the vtk class hierarchy, generated on-the-fly using a PythonSource and Python's introspection capabilities.<br />
An example vistrail that creates an interactive treemap can be found here: [http://www.sci.utah.edu/~stevec/classes/cs5630/assignment4b.vt assignment4b.vt].<br />
<br />
<br />
Problem 2a: Replace the tree map with a graph layout (see vtkGraphLayout). Be sure to keep the labels on the resulting trees.<br />
<br />
<br />
Problem 2b: Experiment with different graph layout strategies and tag the one you like best. In the notes, comment on why you chose the layout you did. Note: I could not get the vtkTreeLayoutStrategy to work correctly (it always wants to be radial), you may have more or less luck.<br />
<br />
<br />
Hints:<br />
* See the vtk documentation, tests, and examples for the graph layout classes to get the pipelines right.</div>Sat, 01 Dec 2007 19:55:31 GMTStevechttps://www.vistrails.org//index.php/Talk:SciVisFall2007/Assignment_4SciVisFall2007/Assignment 4
https://www.vistrails.org//index.php?title=SciVisFall2007/Assignment_4&diff=937
https://www.vistrails.org//index.php?title=SciVisFall2007/Assignment_4&diff=937<p>Stevec: </p>
<hr />
<div>The assignment is due at midnight on December 11th. <br />
The purpose of this assignment is to make sure you understand (and experiment with) the basic concepts involved in the visualization of Diffusion Tensor volumes as well as large graphs. As you work on the assignment, we greatly encourage you to read the available documentation on both python and VTK. Some of the problems will require you to use VTK modules you might not have previously seen. These are indicated in the problems.<br />
<br />
== Submitting your vistrails ==<br />
The assignment is broken into two distinct parts: DTI vis and graph vis. Two different vistrails should be used for these tasks, assignment4a.vt and assignment 4b.vt, respectively. You may start from an empty vistrail or from examples that are given. You will need to use the CADE handin functionality to turn in your assignment. The class account is "cs5630". Both vistrails will need to be submitted.<br />
<br />
== Assignment 4a: DTI Visualization ==<br />
<br />
The first part of the assignment is to perform some basic visualizations of diffusion tensor data. Because this is the final assignment, it will be a little more difficult because there are no examples given. It also combines many of the techniques covered in other assignments such as color mapping, isosurfacing, glyph visualization, and streamlines.<br />
<br />
This is a diffusion tensor dataset [http://www.sci.utah.edu/~stevec/classes/cs5630/gktbh.vtk gktbh.vtk], and a corresponding anisotropy volume [http://www.sci.utah.edu/~stevec/classes/cs5630/gktbhFA.vtk gktbhFA.vtk]. These volumes cover the right half of a [http://www.cs.utah.edu/~gk Gordon Kindlmann's] brain. They encode information about the structure of the brain matter. The anisotropy volume has high values in regions which are likely white matter in the brain, and these are the regions of interest.<br />
<br />
<br />
'''Problem 1a:''' Perform isosurface rendering of the anisotropy volume using multiple transparent, colored, isosurfaces. In the version tree notes for the node, describe (roughly) what the isosurfaces show are the regions that are highly anisotropic and those that are highly isotropic.<br />
<br />
<br />
'''Problem 1b:''' Perform glyph visualization of the DT dataset. Choose whatever glyph geometry you want (cube, sphere, cylinder, etc.) but make sure it is appropriate for the symmetry imposed by the sign ambiguity of eigenvectors. The glyphs should be color mapped by their anisotropy. In order to produce a clear visualization, you need to control the number of glyphs produced to show only regions of high anisotropy to reduce clutter. Here are a few possible ways of doing this:<br />
* Producing glyphs only in a region constrained to some simple geometry, such as on a plane which you use to probe the volume<br />
* Producing glyphs only within range of values defined by a threshold<br />
* Producing glyphs on the vertices of an invisible isosurface.<br />
In the notes for the node, describe why you chose the glyph representation that you did and how you limited the clutter.<br />
<br />
<br />
'''Problem 1c:''' (Grads Only) Based on your knowedge of where the highly directional features are, visualize them using several well-placed hyperstreamlines. In the notes for the node, describe how you chose the seed points<br />
<br />
<br />
'''Problem 1d:''' Create a composite visualization that combines all three techniques (or two techniques for U-Grads) described above.<br />
<br />
<br />
'''Hints:'''<br />
* Multiple isosurfaces can be easily defined using the GenerateValues method.<br />
* Combining two disjoint datasets (tensors and scalars) into one dataset requires a vtkMergeFilter.<br />
* See documentation on vtkTensorGlyphs for more info on tensor glyphs.<br />
* Combining a glyph represenatation with a colormap requires a vtkProbeFilter.<br />
* A scalar volume can be turned into a colormap using vtkImageMapToColors<br />
<br />
== Assignment 4b: Graph Visualization ==<br />
<br />
The goal of this assignement is to compare several different InfoVis graph layout strategies. InfoVis capabilities in VTK are very new (ie., unstable) and some of the features do not work to well, or crash (I recommend saving often). Thus, this assignment will be somewhat limited in what we can do. The graph we will be visualizing is the vtk class hierarchy, generated on-the-fly using a PythonSource and Python's introspection capabilities.<br />
An example vistrail that creates an interactive treemap can be found here: [http://www.sci.utah.edu/~stevec/classes/cs5630/assignment3b.vt assignment3b.vt].<br />
<br />
<br />
Problem 2a: Replace the tree map with a graph layout (see vtkGraphLayout). Be sure to keep the labels on the resulting trees.<br />
<br />
<br />
Problem 2b: Experiment with different graph layout strategies and tag the one you like best. In the notes, comment on why you chose the layout you did. Note: I could not get the vtkTreeLayoutStrategy to work correctly (it always wants to be radial), you may have more or less luck.<br />
<br />
<br />
Hints:<br />
* See the vtk documentation, tests, and examples for the graph layout classes to get the pipelines right.</div>Sat, 01 Dec 2007 19:54:31 GMTStevechttps://www.vistrails.org//index.php/Talk:SciVisFall2007/Assignment_4SciVisFall2007/Assignment 4
https://www.vistrails.org//index.php?title=SciVisFall2007/Assignment_4&diff=936
https://www.vistrails.org//index.php?title=SciVisFall2007/Assignment_4&diff=936<p>Stevec: /* Assignment 4b: Graph Visualization */</p>
<hr />
<div>The assignment is due at midnight on December 11th. You will need to use the CADE handin functionality to turn in your assignment. The class account is "cs5630".<br />
The purpose of this assignment is to make sure you understand (and experiment with) the basic concepts involved in the visualization of Diffusion Tensor volumes as well as large graphs. As you work on the assignment, we greatly encourage you to read the available documentation on both python and VTK. Some of the problems will require you to use VTK modules you might not have previously seen. These are indicated in the problems.<br />
<br />
== Submitting your vistrails ==<br />
The assignment is broken into two distinct parts: DTI vis and graph vis. Two different vistrails should be used for these tasks, assignment4a.vt and assignment 4b.vt, respectively. You may start from an empty vistrail or from examples that are given.<br />
<br />
== Assignment 4a: DTI Visualization ==<br />
<br />
The first part of the assignment is to perform some basic visualizations of diffusion tensor data. Because this is the final assignment, it will be a little more difficult because there are no examples given. It also combines many of the techniques covered in other assignments such as color mapping, isosurfacing, glyph visualization, and streamlines.<br />
<br />
This is a diffusion tensor dataset [http://www.sci.utah.edu/~stevec/classes/cs5630/gktbh.vtk gktbh.vtk], and a corresponding anisotropy volume [http://www.sci.utah.edu/~stevec/classes/cs5630/gktbhFA.vtk gktbhFA.vtk]. These volumes cover the right half of a [http://www.cs.utah.edu/~gk Gordon Kindlmann's] brain. They encode information about the structure of the brain matter. The anisotropy volume has high values in regions which are likely white matter in the brain, and these are the regions of interest.<br />
<br />
<br />
'''Problem 1a:''' Perform isosurface rendering of the anisotropy volume using multiple transparent, colored, isosurfaces. In the version tree notes for the node, describe (roughly) what the isosurfaces show are the regions that are highly anisotropic and those that are highly isotropic.<br />
<br />
<br />
'''Problem 1b:''' Perform glyph visualization of the DT dataset. Choose whatever glyph geometry you want (cube, sphere, cylinder, etc.) but make sure it is appropriate for the symmetry imposed by the sign ambiguity of eigenvectors. The glyphs should be color mapped by their anisotropy. In order to produce a clear visualization, you need to control the number of glyphs produced to show only regions of high anisotropy to reduce clutter. Here are a few possible ways of doing this:<br />
* Producing glyphs only in a region constrained to some simple geometry, such as on a plane which you use to probe the volume<br />
* Producing glyphs only within range of values defined by a threshold<br />
* Producing glyphs on the vertices of an invisible isosurface.<br />
In the notes for the node, describe why you chose the glyph representation that you did and how you limited the clutter.<br />
<br />
<br />
'''Problem 1c:''' (Grads Only) Based on your knowedge of where the highly directional features are, visualize them using several well-placed hyperstreamlines. In the notes for the node, describe how you chose the seed points<br />
<br />
<br />
'''Problem 1d:''' Create a composite visualization that combines all three techniques (or two techniques for U-Grads) described above.<br />
<br />
<br />
'''Hints:'''<br />
* Multiple isosurfaces can be easily defined using the GenerateValues method.<br />
* Combining two disjoint datasets (tensors and scalars) into one dataset requires a vtkMergeFilter.<br />
* See documentation on vtkTensorGlyphs for more info on tensor glyphs.<br />
* Combining a glyph represenatation with a colormap requires a vtkProbeFilter.<br />
* A scalar volume can be turned into a colormap using vtkImageMapToColors<br />
<br />
== Assignment 4b: Graph Visualization ==<br />
<br />
The goal of this assignement is to compare several different InfoVis graph layout strategies. InfoVis capabilities in VTK are very new (ie., unstable) and some of the features do not work to well, or crash (I recommend saving often). Thus, this assignment will be somewhat limited in what we can do. The graph we will be visualizing is the vtk class hierarchy, generated on-the-fly using a PythonSource and Python's introspection capabilities.<br />
An example vistrail that creates an interactive treemap can be found here: [http://www.sci.utah.edu/~stevec/classes/cs5630/assignment3b.vt assignment3b.vt].<br />
<br />
<br />
Problem 2a: Replace the tree map with a graph layout (see vtkGraphLayout). Be sure to keep the labels on the resulting trees.<br />
<br />
<br />
Problem 2b: Experiment with different graph layout strategies and tag the one you like best. In the notes, comment on why you chose the layout you did. Note: I could not get the vtkTreeLayoutStrategy to work correctly (it always wants to be radial), you may have more or less luck.<br />
<br />
<br />
Hints:<br />
* See the vtk documentation, tests, and examples for the graph layout classes to get the pipelines right.</div>Sat, 01 Dec 2007 19:51:15 GMTStevechttps://www.vistrails.org//index.php/Talk:SciVisFall2007/Assignment_4SciVisFall2007/Assignment 4
https://www.vistrails.org//index.php?title=SciVisFall2007/Assignment_4&diff=935
https://www.vistrails.org//index.php?title=SciVisFall2007/Assignment_4&diff=935<p>Stevec: /* Assignment 4a: DTI Visualization */</p>
<hr />
<div>The assignment is due at midnight on December 11th. You will need to use the CADE handin functionality to turn in your assignment. The class account is "cs5630".<br />
The purpose of this assignment is to make sure you understand (and experiment with) the basic concepts involved in the visualization of Diffusion Tensor volumes as well as large graphs. As you work on the assignment, we greatly encourage you to read the available documentation on both python and VTK. Some of the problems will require you to use VTK modules you might not have previously seen. These are indicated in the problems.<br />
<br />
== Submitting your vistrails ==<br />
The assignment is broken into two distinct parts: DTI vis and graph vis. Two different vistrails should be used for these tasks, assignment4a.vt and assignment 4b.vt, respectively. You may start from an empty vistrail or from examples that are given.<br />
<br />
== Assignment 4a: DTI Visualization ==<br />
<br />
The first part of the assignment is to perform some basic visualizations of diffusion tensor data. Because this is the final assignment, it will be a little more difficult because there are no examples given. It also combines many of the techniques covered in other assignments such as color mapping, isosurfacing, glyph visualization, and streamlines.<br />
<br />
This is a diffusion tensor dataset [http://www.sci.utah.edu/~stevec/classes/cs5630/gktbh.vtk gktbh.vtk], and a corresponding anisotropy volume [http://www.sci.utah.edu/~stevec/classes/cs5630/gktbhFA.vtk gktbhFA.vtk]. These volumes cover the right half of a [http://www.cs.utah.edu/~gk Gordon Kindlmann's] brain. They encode information about the structure of the brain matter. The anisotropy volume has high values in regions which are likely white matter in the brain, and these are the regions of interest.<br />
<br />
<br />
'''Problem 1a:''' Perform isosurface rendering of the anisotropy volume using multiple transparent, colored, isosurfaces. In the version tree notes for the node, describe (roughly) what the isosurfaces show are the regions that are highly anisotropic and those that are highly isotropic.<br />
<br />
<br />
'''Problem 1b:''' Perform glyph visualization of the DT dataset. Choose whatever glyph geometry you want (cube, sphere, cylinder, etc.) but make sure it is appropriate for the symmetry imposed by the sign ambiguity of eigenvectors. The glyphs should be color mapped by their anisotropy. In order to produce a clear visualization, you need to control the number of glyphs produced to show only regions of high anisotropy to reduce clutter. Here are a few possible ways of doing this:<br />
* Producing glyphs only in a region constrained to some simple geometry, such as on a plane which you use to probe the volume<br />
* Producing glyphs only within range of values defined by a threshold<br />
* Producing glyphs on the vertices of an invisible isosurface.<br />
In the notes for the node, describe why you chose the glyph representation that you did and how you limited the clutter.<br />
<br />
<br />
'''Problem 1c:''' (Grads Only) Based on your knowedge of where the highly directional features are, visualize them using several well-placed hyperstreamlines. In the notes for the node, describe how you chose the seed points<br />
<br />
<br />
'''Problem 1d:''' Create a composite visualization that combines all three techniques (or two techniques for U-Grads) described above.<br />
<br />
<br />
'''Hints:'''<br />
* Multiple isosurfaces can be easily defined using the GenerateValues method.<br />
* Combining two disjoint datasets (tensors and scalars) into one dataset requires a vtkMergeFilter.<br />
* See documentation on vtkTensorGlyphs for more info on tensor glyphs.<br />
* Combining a glyph represenatation with a colormap requires a vtkProbeFilter.<br />
* A scalar volume can be turned into a colormap using vtkImageMapToColors<br />
<br />
== Assignment 4b: Graph Visualization ==</div>Sat, 01 Dec 2007 18:52:39 GMTStevechttps://www.vistrails.org//index.php/Talk:SciVisFall2007/Assignment_4SciVisFall2007/Assignment 4
https://www.vistrails.org//index.php?title=SciVisFall2007/Assignment_4&diff=934
https://www.vistrails.org//index.php?title=SciVisFall2007/Assignment_4&diff=934<p>Stevec: /* Assignment 4a: DTI Visualization */</p>
<hr />
<div>The assignment is due at midnight on December 11th. You will need to use the CADE handin functionality to turn in your assignment. The class account is "cs5630".<br />
The purpose of this assignment is to make sure you understand (and experiment with) the basic concepts involved in the visualization of Diffusion Tensor volumes as well as large graphs. As you work on the assignment, we greatly encourage you to read the available documentation on both python and VTK. Some of the problems will require you to use VTK modules you might not have previously seen. These are indicated in the problems.<br />
<br />
== Submitting your vistrails ==<br />
The assignment is broken into two distinct parts: DTI vis and graph vis. Two different vistrails should be used for these tasks, assignment4a.vt and assignment 4b.vt, respectively. You may start from an empty vistrail or from examples that are given.<br />
<br />
== Assignment 4a: DTI Visualization ==<br />
<br />
The first part of the assignment is to perform some basic visualizations of diffusion tensor data. Because this is the final assignment, it will be a little more difficult because there are no examples given. It also combines many of the techniques covered in other assignments such as color mapping, isosurfacing, glyph visualization, and streamlines.<br />
<br />
This is a diffusion tensor dataset [http://www.sci.utah.edu/~stevec/classes/cs5630/gktbh.vtk gktbh.vtk], and a corresponding anisotropy volume [http://www.sci.utah.edu/~stevec/classes/cs5630/gktbhFA.vtk gktbhFA.vtk]. These volumes cover the right half of a [http://www.cs.utah.edu/~gk Gordon Kindlmann's] brain. They encode information about the structure of the brain matter. The anisotropy volume has high values in regions which are likely white matter in the brain, and these are the regions of interest.<br />
<br />
<br />
'''Problem 1a:''' Perform isosurface rendering of the anisotropy volume using multiple transparent, colored, isosurfaces. In the version tree notes for the node, describe (roughly) what the isosurfaces show are the regions that are highly anisotropic and those that are highly isotropic.<br />
<br />
<br />
'''Problem 1b:''' Perform glyph visualization of the DT dataset. Choose whatever glyph geometry you want (cube, sphere, cylinder, etc.) but make sure it is appropriate for the symmetry imposed by the sign ambiguity of eigenvectors. The glyphs should be color mapped by their anisotropy. In order to produce a clear visualization, you need to control the number of glyphs produced to show only regions of high anisotropy to reduce clutter. Here are a few possible ways of doing this:<br />
* Producing glyphs only in a region constrained to some simple geometry, such as on a plane which you use to probe the volume<br />
* Producing glyphs only within range of values defined by a threshold<br />
* Producing glyphs on the vertices of an invisible isosurface.<br />
In the notes for the node, describe why you chose the glyph representation that you did and how you limited the clutter.<br />
<br />
<br />
'''Problem 1c:''' Based on your knowedge of where the highly directional features are, visualize them using several well-placed hyperstreamlines. In the notes for the node, describe how you chose the seed points<br />
<br />
<br />
'''Problem 1d:''' Create a composite visualization that combines all three techniques described above.<br />
<br />
<br />
'''Hints:'''<br />
* Multiple isosurfaces can be easily defined using the GenerateValues method.<br />
* Combining two disjoint datasets (tensors and scalars) into one dataset requires a vtkMergeFilter.<br />
* See documentation on vtkTensorGlyphs for more info on tensor glyphs.<br />
* Combining a glyph represenatation with a colormap requires a vtkProbeFilter.<br />
* A scalar volume can be turned into a colormap using vtkImageMapToColors<br />
<br />
== Assignment 4b: Graph Visualization ==</div>Sat, 01 Dec 2007 18:51:38 GMTStevechttps://www.vistrails.org//index.php/Talk:SciVisFall2007/Assignment_4SciVisFall2007/Assignment 4
https://www.vistrails.org//index.php?title=SciVisFall2007/Assignment_4&diff=933
https://www.vistrails.org//index.php?title=SciVisFall2007/Assignment_4&diff=933<p>Stevec: /* Assignment 4a: DTI Visualization */</p>
<hr />
<div>The assignment is due at midnight on December 11th. You will need to use the CADE handin functionality to turn in your assignment. The class account is "cs5630".<br />
The purpose of this assignment is to make sure you understand (and experiment with) the basic concepts involved in the visualization of Diffusion Tensor volumes as well as large graphs. As you work on the assignment, we greatly encourage you to read the available documentation on both python and VTK. Some of the problems will require you to use VTK modules you might not have previously seen. These are indicated in the problems.<br />
<br />
== Submitting your vistrails ==<br />
The assignment is broken into two distinct parts: DTI vis and graph vis. Two different vistrails should be used for these tasks, assignment4a.vt and assignment 4b.vt, respectively. You may start from an empty vistrail or from examples that are given.<br />
<br />
== Assignment 4a: DTI Visualization ==<br />
<br />
This is a diffusion tensor dataset [http://www.sci.utah.edu/~stevec/classes/cs5630/gktbh.vtk gktbh.vtk], and a corresponding anisotropy volume [http://www.sci.utah.edu/~stevec/classes/cs5630/gktbhFA.vtk gktbhFA.vtk]. These volumes cover the right half of a [http://www.cs.utah.edu/~gk Gordon Kindlmann's] brain. They encode information about the structure of the brain matter. The anisotropy volume has high values in regions which are likely white matter in the brain, and these are the regions of interest.<br />
<br />
<br />
'''Problem 1a:''' Perform isosurface rendering of the anisotropy volume using multiple transparent, colored, isosurfaces. In the version tree notes for the node, describe (roughly) what the isosurfaces show are the regions that are highly anisotropic and those that are highly isotropic.<br />
<br />
<br />
'''Problem 1b:''' Perform glyph visualization of the DT dataset. Choose whatever glyph geometry you want (cube, sphere, cylinder, etc.) but make sure it is appropriate for the symmetry imposed by the sign ambiguity of eigenvectors. The glyphs should be color mapped by their anisotropy. In order to produce a clear visualization, you need to control the number of glyphs produced to show only regions of high anisotropy to reduce clutter. Here are a few possible ways of doing this:<br />
* Producing glyphs only in a region constrained to some simple geometry, such as on a plane which you use to probe the volume<br />
* Producing glyphs only within range of values defined by a threshold<br />
* Producing glyphs on the vertices of an invisible isosurface.<br />
In the notes for the node, describe why you chose the glyph representation that you did and how you limited the clutter.<br />
<br />
<br />
'''Problem 1c:''' Based on your knowedge of where the highly directional features are, visualize them using several well-placed hyperstreamlines. In the notes for the node, describe how you chose the seed points<br />
<br />
<br />
'''Problem 1d:''' Create a composite visualization that combines all three techniques described above.<br />
<br />
<br />
'''Hints:'''<br />
* Multiple isosurfaces can be easily defined using the GenerateValues method.<br />
* Combining two disjoint datasets (tensors and scalars) into one dataset requires a vtkMergeFilter.<br />
* See documentation on vtkTensorGlyphs for more info on tensor glyphs.<br />
* Combining a glyph represenatation with a colormap requires a vtkProbeFilter.<br />
* A scalar volume can be turned into a colormap using vtkImageMapToColors<br />
<br />
== Assignment 4b: Graph Visualization ==</div>Sat, 01 Dec 2007 18:47:13 GMTStevechttps://www.vistrails.org//index.php/Talk:SciVisFall2007/Assignment_4SciVisFall2007/Assignment 4
https://www.vistrails.org//index.php?title=SciVisFall2007/Assignment_4&diff=932
https://www.vistrails.org//index.php?title=SciVisFall2007/Assignment_4&diff=932<p>Stevec: /* Assignment 4a: DTI Visualization */</p>
<hr />
<div>The assignment is due at midnight on December 11th. You will need to use the CADE handin functionality to turn in your assignment. The class account is "cs5630".<br />
The purpose of this assignment is to make sure you understand (and experiment with) the basic concepts involved in the visualization of Diffusion Tensor volumes as well as large graphs. As you work on the assignment, we greatly encourage you to read the available documentation on both python and VTK. Some of the problems will require you to use VTK modules you might not have previously seen. These are indicated in the problems.<br />
<br />
== Submitting your vistrails ==<br />
The assignment is broken into two distinct parts: DTI vis and graph vis. Two different vistrails should be used for these tasks, assignment4a.vt and assignment 4b.vt, respectively. You may start from an empty vistrail or from examples that are given.<br />
<br />
== Assignment 4a: DTI Visualization ==<br />
<br />
This is a diffusion tensor dataset [http://www.sci.utah.edu/~stevec/classes/cs5630/gktbh.vtk gktbh.vtk], and a corresponding anisotropy volume [http://www.sci.utah.edu/~stevec/classes/cs5630/gktbhFA.vtk gktbhFA.vtk]. These volumes cover the right half of a [http://www.cs.utah.edu/~gk Gordon Kindlmann's] brain. They encode information about the structure of the brain matter. The anisotropy volume has high values in regions which are likely white matter in the brain, and these are the regions of interest.<br />
<br />
<br />
'''Problem 1a:''' Perform isosurface rendering of the anisotropy volume using multiple transparent, colored, isosurfaces. In the version tree notes for the node, describe (roughly) what the isosurfaces show are the regions that are highly anisotropic and those that are highly isotropic.<br />
<br />
<br />
'''Problem 1b:''' Perform glyph visualization of the DT dataset. Choose whatever glyph geometry you want (cube, sphere, cylinder, etc.) but make sure it is appropriate for the symmetry imposed by the sign ambiguity of eigenvectors. The glyphs should be color mapped by their anisotropy. In order to produce a clear visualization, you need to control the number of glyphs produced to show only regions of high anisotropy to reduce clutter. Here are a few possible ways of doing this:<br />
* Producing glyphs only in a region constrained to some simple geometry, such as on a plane which you use to probe the volume<br />
* Producing glyphs only within range of values defined by a threshold<br />
* Producing glyphs on the vertices of an invisible isosurface.<br />
In the notes for the node, describe why you chose the glyph representation that you did and how you limited the clutter.<br />
<br />
<br />
'''Problem 1c:''' Based on your knowedge of where the highly directional features are, visualize them using several well-placed hyperstreamlines. In the notes for the node, describe how you chose the seed points<br />
<br />
<br />
'''Problem 1d:''' Create a composite visualization that combines all three techniques described above.<br />
<br />
'''Hints:'''<br />
* Multiple isosurfaces can be easily defined using the GenerateValues method.<br />
* Combining two disjoint datasets (tensors and scalars) into one dataset requires a vtkMergeFilter.<br />
* See documentation on vtkTensorGlyphs for more info on tensor glyphs.<br />
* Combining a glyph represenatation with a colormap requires a vtkProbeFilter.<br />
* A scalar volume can be turned into a colormap using vtkImageMapToColors<br />
<br />
== Assignment 4b: Graph Visualization ==</div>Sat, 01 Dec 2007 18:46:35 GMTStevechttps://www.vistrails.org//index.php/Talk:SciVisFall2007/Assignment_4SciVisFall2007/Assignment 4
https://www.vistrails.org//index.php?title=SciVisFall2007/Assignment_4&diff=931
https://www.vistrails.org//index.php?title=SciVisFall2007/Assignment_4&diff=931<p>Stevec: /* Assignment 4a: DTI Visualization */</p>
<hr />
<div>The assignment is due at midnight on December 11th. You will need to use the CADE handin functionality to turn in your assignment. The class account is "cs5630".<br />
The purpose of this assignment is to make sure you understand (and experiment with) the basic concepts involved in the visualization of Diffusion Tensor volumes as well as large graphs. As you work on the assignment, we greatly encourage you to read the available documentation on both python and VTK. Some of the problems will require you to use VTK modules you might not have previously seen. These are indicated in the problems.<br />
<br />
== Submitting your vistrails ==<br />
The assignment is broken into two distinct parts: DTI vis and graph vis. Two different vistrails should be used for these tasks, assignment4a.vt and assignment 4b.vt, respectively. You may start from an empty vistrail or from examples that are given.<br />
<br />
== Assignment 4a: DTI Visualization ==<br />
<br />
This is a diffusion tensor dataset [http://www.sci.utah.edu/~stevec/classes/cs5630/gktbh.vtk gktbh.vtk], and a corresponding anisotropy volume [http://www.sci.utah.edu/~stevec/classes/cs5630/gktbhFA.vtk gktbhFA.vtk]. These volumes cover the right half of a [http://www.cs.utah.edu/~gk Gordon Kindlmann's] brain. They encode information about the structure of the brain matter. The anisotropy volume has high values in regions which are likely white matter in the brain, and these are the regions of interest.<br />
<br />
<br />
'''Problem 1a:''' Perform isosurface rendering of the anisotropy volume using multiple transparent, colored, isosurfaces. In the version tree notes for the node, describe (roughly) what the isosurfaces show are the regions that are highly anisotropic and those that are highly isotropic.<br />
<br />
<br />
'''Problem 1b:''' Perform glyph visualization of the DT dataset. Choose whatever glyph geometry you want (cube, sphere, cylinder, etc.) but make sure it is appropriate for the symmetry imposed by the sign ambiguity of eigenvectors. The glyphs should be color mapped by their anisotropy. In order to produce a clear visualization, you need to control the number of glyphs produced to show only regions of high anisotropy to reduce clutter. Here are a few possible ways of doing this:<br />
* Producing glyphs only in a region constrained to some simple geometry, such as on a plane which you use to probe the volume<br />
* Producing glyphs only within range of values defined by a threshold<br />
* Producing glyphs on the vertices of an invisible isosurface.<br />
In the notes for the node, describe why you chose the glyph representation that you did and how you limited the clutter.<br />
<br />
<br />
'''Problem 1c:''' Based on your knowedge of where the highly directional features are, visualize them using several well-placed hyperstreamlines. In the notes for the node, describe how you chose the seed points<br />
<br />
<br />
'''Problem 1d:''' Create a composite visualization that combines all three techniques described above.<br />
<br />
"Hints:"<br />
* Multiple isosurfaces can be easily defined using the GenerateValues method.<br />
* Combining two disjoint datasets (tensors and scalars) into one dataset requires a vtkMergeFilter.<br />
* See documentation on vtkTensorGlyphs for more info on tensor glyphs.<br />
* Combining a glyph represenatation with a colormap requires a vtkProbeFilter.<br />
* A scalar volume can be turned into a colormap using vtkImageMapToColors<br />
<br />
== Assignment 4b: Graph Visualization ==</div>Sat, 01 Dec 2007 18:46:19 GMTStevechttps://www.vistrails.org//index.php/Talk:SciVisFall2007/Assignment_4SciVisFall2007/Assignment 4
https://www.vistrails.org//index.php?title=SciVisFall2007/Assignment_4&diff=930
https://www.vistrails.org//index.php?title=SciVisFall2007/Assignment_4&diff=930<p>Stevec: /* Assignment 4a: DTI Visualization */</p>
<hr />
<div>The assignment is due at midnight on December 11th. You will need to use the CADE handin functionality to turn in your assignment. The class account is "cs5630".<br />
The purpose of this assignment is to make sure you understand (and experiment with) the basic concepts involved in the visualization of Diffusion Tensor volumes as well as large graphs. As you work on the assignment, we greatly encourage you to read the available documentation on both python and VTK. Some of the problems will require you to use VTK modules you might not have previously seen. These are indicated in the problems.<br />
<br />
== Submitting your vistrails ==<br />
The assignment is broken into two distinct parts: DTI vis and graph vis. Two different vistrails should be used for these tasks, assignment4a.vt and assignment 4b.vt, respectively. You may start from an empty vistrail or from examples that are given.<br />
<br />
== Assignment 4a: DTI Visualization ==<br />
<br />
This is a diffusion tensor dataset [http://www.sci.utah.edu/~stevec/classes/cs5630/gktbh.vtk gktbh.vtk], and a corresponding anisotropy volume [http://www.sci.utah.edu/~stevec/classes/cs5630/gktbhFA.vtk gktbhFA.vtk]. These volumes cover the right half of a [http://www.cs.utah.edu/~gk Gordon Kindlmann's] brain. They encode information about the structure of the brain matter. The anisotropy volume has high values in regions which are likely white matter in the brain, and these are the regions of interest.<br />
<br />
<br />
'''Problem 1a:''' Perform isosurface rendering of the anisotropy volume using multiple transparent, colored, isosurfaces. In the version tree notes for the node, describe (roughly) what the isosurfaces show are the regions that are highly anisotropic and those that are highly isotropic.<br />
<br />
<br />
'''Problem 1b:''' Perform glyph visualization of the DT dataset. Choose whatever glyph geometry you want (cube, sphere, cylinder, etc.) but make sure it is appropriate for the symmetry imposed by the sign ambiguity of eigenvectors. In order to produce a clear visualization, you need to control the number of glyphs produced to show only regions of high anisotropy to reduce clutter. Here are a few possible ways of doing this:<br />
* Producing glyphs only in a region constrained to some simple geometry, such as on a plane which you use to probe the volume<br />
* Producing glyphs only within range of values defined by a threshold<br />
* Producing glyphs on the vertices of an invisible isosurface.<br />
In the notes for the node, describe why you chose the glyph representation that you did and how you limited the clutter.<br />
<br />
<br />
'''Problem 1c:''' Based on your knowedge of where the highly directional features are, visualize them using several well-placed hyperstreamlines. In the notes for the node, describe how you chose the seed points<br />
<br />
<br />
'''Problem 1d:''' Create a composite visualization that combines all three techniques described above.<br />
<br />
== Assignment 4b: Graph Visualization ==</div>Sat, 01 Dec 2007 18:26:46 GMTStevechttps://www.vistrails.org//index.php/Talk:SciVisFall2007/Assignment_4SciVisFall2007/Assignment 4
https://www.vistrails.org//index.php?title=SciVisFall2007/Assignment_4&diff=929
https://www.vistrails.org//index.php?title=SciVisFall2007/Assignment_4&diff=929<p>Stevec: /* Assignment 4a: DTI Visualization */</p>
<hr />
<div>The assignment is due at midnight on December 11th. You will need to use the CADE handin functionality to turn in your assignment. The class account is "cs5630".<br />
The purpose of this assignment is to make sure you understand (and experiment with) the basic concepts involved in the visualization of Diffusion Tensor volumes as well as large graphs. As you work on the assignment, we greatly encourage you to read the available documentation on both python and VTK. Some of the problems will require you to use VTK modules you might not have previously seen. These are indicated in the problems.<br />
<br />
== Submitting your vistrails ==<br />
The assignment is broken into two distinct parts: DTI vis and graph vis. Two different vistrails should be used for these tasks, assignment4a.vt and assignment 4b.vt, respectively. You may start from an empty vistrail or from examples that are given.<br />
<br />
== Assignment 4a: DTI Visualization ==<br />
<br />
This is a diffusion tensor dataset [http://www.sci.utah.edu/~stevec/classes/cs5630/gktbh.vtk gktbh.vtk], and a corresponding anisotropy volume [http://www.sci.utah.edu/~stevec/classes/cs5630/gktbhFA.vtk gktbhFA.vtk]. These volumes cover the right half of a [http://www.cs.utah.edu/~gk Gordon Kindlmann's] brain. They encode information about the structure of the brain matter. The anisotropy volume has high values in regions which are likely white matter in the brain, and these are the regions of interest.<br />
<br />
'''Problem 1a:''' Perform isosurface rendering of the anisotropy volume using multiple transparent, colored, isosurfaces. In the version tree notes for the node, describe (roughly) what the isosurfaces show are the regions that are highly anisotropic and those that are highly isotropic.<br />
<br />
'''Problem 1b:''' Perform glyph visualization of the DT dataset. Choose whatever glyph geometry you want (cube, sphere, cylinder, etc.) but make sure it is appropriate for the symmetry imposed by the sign ambiguity of eigenvectors. In order to produce a clear visualization, you need to control the number of glyphs produced to show only regions of high anisotropy to reduce clutter. Here are a few possible ways of doing this:<br />
* Producing glyphs only in a region constrained to some simple geometry, such as on a plane which you use to probe the volume<br />
* Producing glyphs only within range of values defined by a threshold<br />
* Producing glyphs on the vertices of an invisible isosurface.<br />
In the notes for the node, describe why you chose the glyph representation that you did and how you limited the clutter.<br />
<br />
'''Problem 1c:''' Based on your knowedge of where the highly directional features are, visualize them using several well-placed hyperstreamlines. In the notes for the node, describe how you chose the seed points<br />
<br />
'''Problem 1d:''' Create a composite visualization that combines all three techniques described above.<br />
<br />
== Assignment 4b: Graph Visualization ==</div>Sat, 01 Dec 2007 18:26:19 GMTStevechttps://www.vistrails.org//index.php/Talk:SciVisFall2007/Assignment_4SciVisFall2007/Assignment 4
https://www.vistrails.org//index.php?title=SciVisFall2007/Assignment_4&diff=928
https://www.vistrails.org//index.php?title=SciVisFall2007/Assignment_4&diff=928<p>Stevec: </p>
<hr />
<div>The assignment is due at midnight on December 11th. You will need to use the CADE handin functionality to turn in your assignment. The class account is "cs5630".<br />
The purpose of this assignment is to make sure you understand (and experiment with) the basic concepts involved in the visualization of Diffusion Tensor volumes as well as large graphs. As you work on the assignment, we greatly encourage you to read the available documentation on both python and VTK. Some of the problems will require you to use VTK modules you might not have previously seen. These are indicated in the problems.<br />
<br />
== Submitting your vistrails ==<br />
The assignment is broken into two distinct parts: DTI vis and graph vis. Two different vistrails should be used for these tasks, assignment4a.vt and assignment 4b.vt, respectively. You may start from an empty vistrail or from examples that are given.<br />
<br />
== Assignment 4a: DTI Visualization ==<br />
<br />
== Assignment 4b: Graph Visualization ==</div>Sat, 01 Dec 2007 17:58:27 GMTStevechttps://www.vistrails.org//index.php/Talk:SciVisFall2007/Assignment_4SciVisFall2007/Assignment 4
https://www.vistrails.org//index.php?title=SciVisFall2007/Assignment_4&diff=927
https://www.vistrails.org//index.php?title=SciVisFall2007/Assignment_4&diff=927<p>Stevec: New page: The assignment is due at midnight on December 11th. You will need to use the CADE handin functionality to turn in your assignment. The class account is "cs5630". The purpose of this assign...</p>
<hr />
<div>The assignment is due at midnight on December 11th. You will need to use the CADE handin functionality to turn in your assignment. The class account is "cs5630".<br />
The purpose of this assignment is to make sure you understand (and experiment with) the basic concepts involved in the visualization of Diffusion Tensor volumes as well as large graphs. As you work on the assignment, we greatly encourage you to read the available documentation on both python and VTK. Some of the problems will require you to use VTK modules you might not have previously seen. These are indicated in the problems.</div>Sat, 01 Dec 2007 17:54:13 GMTStevechttps://www.vistrails.org//index.php/Talk:SciVisFall2007/Assignment_4SciVisFall2007/Schedule
https://www.vistrails.org//index.php?title=SciVisFall2007/Schedule&diff=923
https://www.vistrails.org//index.php?title=SciVisFall2007/Schedule&diff=923<p>Stevec: /* 11/29: Aesthetic Issues in Vis */</p>
<hr />
<div>== 8/21: Introduction to visualization ==<br />
<br />
Lecturer: Claudio<br />
<br />
Topics: Scientific Visualization<br />
<br />
Notes: [http://www.cs.utah.edu/~csilva/courses/cs5630/lec01-notes.pdf lec01-notes.pdf]<br />
<br />
Slides: [http://www.cs.utah.edu/~csilva/courses/cs5630/lec01.pdf lec01.pdf]<br />
<br />
Animations: [http://www.cs.utah.edu/~csilva/courses/cs5630/explosion_640x480-5.mov explosion_640x480-5.mov], [http://www.cs.utah.edu/~csilva/courses/cs5630/fig7.mov fig7.mov], [http://www.cs.utah.edu/~csilva/courses/cs5630/fig8.mov fig8.mov], [http://www.cs.utah.edu/~csilva/courses/cs5630/fig9.mov fig9.mov], [http://www.cs.utah.edu/~csilva/courses/cs5630/SevereTstorm.mov SevereTstorm.mov]<br />
<br />
Further reading: <br />
<br />
[http://www.sci.utah.edu/~csilva/papers/vis2003.pdf Visualizing Spatial and Temporal Variability in Coastal Observatories], W. Herrera-Jimenez, W. Correa, C. Silva, and A. Baptista, IEEE Visualization 2003.<br />
<br />
== 8/23: The visualization pipeline ==<br />
<br />
Lecturer: Claudio<br />
<br />
Topics: Procedural vs. Dataflow programming; Using Dataflow for the Vis Pipeline; Dataflow programming with VTK; Dataflow programming with VisTrails; python.<br />
<br />
Notes: [http://www.cs.utah.edu/~csilva/courses/cs5630/lec02-notes.pdf lec02-notes.pdf]<br />
<br />
Slides: [http://www.cs.utah.edu/~csilva/courses/cs5630/lec02.pdf lec02.pdf]<br />
<br />
VisTrails: During this class, we built a pipeline equivalent to the cone.tcl (see class slides). Here is the vistrails file: [http://www.cs.utah.edu/~csilva/courses/cs5630/cone.vt cone.vt]<br />
<br />
Further reading: <br />
<br />
[http://www.cs.utah.edu/~csilva/courses/cs5630/reproducible_vis.pdf Provenance for Visualizations: Reproducibility and Beyond], C. Silva, J. Freire, and S. Callahan, IEEE Computing in Science and Engineering, to appear.<br />
<br />
== 8/28: Modeling Data for Visualization ==<br />
<br />
Lecturer: Carlos<br />
<br />
Topics: Discrete vs continous data; Sampling and interpolation; Point vs triangulated data; Meshing data types; Regular vs irregular data; Tabular data; Vector and tensor fields<br />
<br />
Notes: TBA<br />
<br />
Slides: [http://www.sci.utah.edu/~cscheid/scivis_fall07/modelling_1.ppt .ppt file]<br />
<br />
Further reading: <br />
<br />
There is no required reading for this lecture. The notes will be available shortly. The following papers are there for people that are looking to get more advanced material that will not be covered in class.<br />
<br />
=== Interpolation ===<br />
<br />
[http://lmi.bwh.harvard.edu/papers/papers/geodesic-loxodromes-final.html Geodesic-loxodromes...] This is the fancy interpolation for diffusion tensors I mentioned in class.<br />
<br />
[http://en.wikipedia.org/wiki/Bernstein_polynomial Bernstein polynomials] These are the polynomials used for cubic Bezier curves that I mentioned in class.<br />
<br />
==== Separability ====<br />
<br />
[http://portal.acm.org/citation.cfm?id=1187793 Extensions of the Zwart-Powell Box spline...] This is a recent paper that shows a class of trivariate reconstruction techniques that are ''not'' separable.<br />
<br />
==== Tensors ====<br />
<br />
[http://www.cs.utah.edu/research/techreports/2004/pdf/UUCS-04-014.pdf Visualization and Analysis of Diffusion Tensor Fields] Gordon Kindlmann's PhD. thesis, with everything you ever wanted to know about DTI. Section 2.1 has a good primer in tensor algebra.<br />
<br />
== 8/30: Modeling Data for Visualization == <br />
<br />
Lecturer: Carlos<br />
<br />
Topics: Geometry Processing: Reconstruction and meshing; Simplification; Smoothing; Other Filtering algorithms<br />
<br />
Notes: [http://www.sci.utah.edu/~cscheid/scivis_fall07/week2.pdf .pdf file]. If you want to print these, you might want to wait for a week or two, until I finish polishing them.<br />
<br />
Slides: [http://www.sci.utah.edu/~cscheid/scivis_fall07/processing.ppt .ppt file] ''These slides include simplificatin algorithms, which I'll talk about next week.''<br />
<br />
== 9/4: Elementary Plotting Techniques == <br />
<br />
Lecturer: Steve<br />
<br />
Topics: Principles of Graph Construction<br />
<br />
Notes: [http://www.sci.utah.edu/~stevec/classes/cs5630/PlottingNotes.pdf PlottingNotes.pdf]<br />
<br />
Slides: [http://www.sci.utah.edu/~stevec/slides/SciVis/Plotting1.pdf Plotting1.pdf]<br />
<br />
Vistrails: See next lecture.<br />
<br />
Further Reading: There is no required reading for this lecture. For those interested in more depth, the following books are very useful:<br />
<br />
* The Elements of Graphing Data. William S. Cleveland, Hobart Press, 2nd Edition, 1994.<br />
* Visualizing Data. William S. Cleveland, Hobart Press, 1993.<br />
* The Visual Display of Quantitative Information. Edward R. Tufte, Graphics Press, 2001.<br />
* Visual Explanations: Images and Quantities, Evidence and Narrative. Edward R. Tufte, Graphics Press, 2997.<br />
<br />
== 9/6: Elementary Plotting Techniques ==<br />
<br />
Lecturer: Steve<br />
<br />
Topics: Simple Plotting Methods: Dot Plots, Connected Symbol Plots, Scatter Plots, Histograms, Others. Advanced Plotting Methods: Multimodal, Higher Dimensional, Correlation, Uncertainty and Variation.<br />
<br />
Notes: [http://www.sci.utah.edu/~stevec/classes/cs5630/PlottingNotes.pdf PlottingNotes.pdf]<br />
<br />
Slides: [http://www.sci.utah.edu/~stevec/slides/SciVis/Plotting2.pdf Plotting2.pdf]<br />
<br />
Vistrails: [http://www.sci.utah.edu/~stevec/classes/cs5630/PlottingVistrails.zip PlottingVistrails.zip] - Unzip this file in the examples directory of your VisTrails installation and it will add the vistrails along with their data sets (in the data directory). If you don't have permission to write to this directory (CADE users), then unzip the file where you want. Just be aware that in this case the paths for the data files may not be correct for most vistrails and will need to be fixed before they will execute properly.<br />
<br />
<br />
Further Reading: There is no required reading for this lecture. Some articles of interest:<br />
<br />
* [http://www.fmrib.ox.ac.uk/analysis/techrep/tr00mj2/tr00mj2/node24.html Histogram Bin Size]<br />
* [http://en.wikipedia.org/wiki/Correlation Correlation]<br />
* [http://en.wikipedia.org/wiki/Linear_regression Linear Regression]<br />
* [http://en.wikipedia.org/wiki/Box_plot Box Plots]<br />
<br />
== 9/11: Color and Human Perception ==<br />
<br />
Lecturer: Claudio<br />
<br />
Topics: Human vision system; Optical illusions<br />
<br />
Notes: TBA<br />
<br />
Slides: [http://www.cs.utah.edu/~csilva/courses/cs5630/human-vision.pdf human-vision.pdf]<br />
<br />
Links:<br />
<br />
http://en.wikipedia.org/wiki/Eye<br />
<br />
http://www.grand-illusions.com/gregory2.htm (also, see the related book: [http://www.amazon.com/Eye-Brain-Richard-L-Gregory/dp/0691048371])<br />
<br />
http://en.wikipedia.org/wiki/Purkinje_effect<br />
<br />
http://www.handprint.com/HP/WCL/color2.html<br />
<br />
== 9/13: Color and Human Perception ==<br />
<br />
Lecturer: Claudio<br />
<br />
Topics: Color Science; Color spaces; Color Blindness; Color maps; Tone mapping<br />
<br />
Notes: TBA<br />
<br />
Slides: [http://www.cs.utah.edu/~csilva/courses/cs5630/colorvision.pdf colorvision.pdf]<br />
<br />
Links:<br />
<br />
Further reading: <br />
<br />
[http://www.research.ibm.com/dx/proceedings/pravda/truevis.htm How Not to Lie with Visualization]<br />
<br />
http://en.wikipedia.org/wiki/Opponent_process<br />
<br />
http://en.wikipedia.org/wiki/Color_models<br />
<br />
http://en.wikipedia.org/wiki/Absolute_color_space<br />
<br />
http://en.wikipedia.org/wiki/Additive_color<br />
<br />
http://en.wikipedia.org/wiki/Subtractive_color<br />
<br />
http://en.wikipedia.org/wiki/RGB_color_model<br />
<br />
http://en.wikipedia.org/wiki/SRGB_color_space<br />
<br />
http://en.wikipedia.org/wiki/CIE_XYZ_color_space<br />
<br />
== 9/18 (a): Color and Human Perception ==<br />
<br />
Lecturer: Claudio<br />
<br />
Same material as previous lecture. <br />
<br />
== 9/18 (b): 2D Visualization Techniques ==<br />
<br />
Lecturer: Carlos<br />
<br />
Topics: 2-D contours, marching quads, marching tris; Color mapping; height fields; NPR<br />
<br />
Slides: [http://www.sci.utah.edu/~cscheid/scivis_fall07/2d_scalar_vis.pdf pdf file]<br />
<br />
Notes: [http://www.sci.utah.edu/~cscheid/scivis_fall07/2d_scalar_vis_notes.pdf pdf file]<br />
<br />
Vistrails: [http://www.sci.utah.edu/~cscheid/scivis_fall07/ozone_and_data.zip zip file with ozone.vt and data] [http://www.sci.utah.edu/~cscheid/scivis_fall07/asymptotic_decider.vt asymptotic decider in 2d] [http://www.sci.utah.edu/~cscheid/scivis_fall07/elevation.zip heightfields]<br />
<br />
Note: These vistrails use relative file paths so you don't need to change each of them individually to match your directory structure. Simply unzip the file to whichever location is more convenient. Then, inside VisTrails, open the VisTrails shell, type:<br />
<br />
import os<br />
os.chdir("c:/directory/where/you/unzipped/it")<br />
<br />
This will change the directory so you should be able to just run the pipelines.<br />
<br />
== 9/20: Math refresher ==<br />
<br />
Lecturer: Carlos<br />
<br />
Topics: Basic linear algebra; vectors; basic differential geometry (space curves, tangents, normals, surfaces); basic vector calculus (gradient, divergence, curl, gauss' theorem, green's theorem) <br />
<br />
== 9/25: 2D Visualization Techniques ==<br />
<br />
Lecturer: Carlos<br />
<br />
Topics: 2-D vector fields, div, grad, curl in 2D; Steady vs Unsteady flows; Glyphs; 2-D streamlines, streaklines, pathlines<br />
<br />
Slides: [http://www.sci.utah.edu/~cscheid/scivis_fall07/2d_vector_vis.pdf pdf file]<br />
<br />
Notes: coming soon<br />
<br />
Vistrails: [http://www.sci.utah.edu/~cscheid/scivis_fall07/vector_vis_1.zip vistrail with steady vector field vis and data] [http://www.sci.utah.edu/~cscheid/scivis_fall07/unsteady.zip vistrail with unsteady vector field vis and data] '''Note:''' Because VTK does not support time-varying datasets directly, we had to create a reasonably ugly hack to simulate unsteady fields. This means the datasets are quite big (80MB in total).<br />
<br />
== 9/27 (a): 2D Visualization Techniques ==<br />
<br />
Lecturer Carlos<br />
<br />
Same material as last lecture.<br />
<br />
== 9/27 (b): Volume Vis ==<br />
<br />
Lecturer: Claudio<br />
<br />
Topics: Slicing; Contours; Marching algorithms<br />
<br />
Slides: [http://www.cs.utah.edu/~csilva/courses/cs5630/iso-basic.pdf iso-basic.pdf]<br />
<br />
References:<br />
<br />
[http://portal.acm.org/citation.cfm?id=37401.37422 Marching cubes: A high resolution 3D surface construction algorithm]<br />
<br />
[http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=175782 The asymptotic decider: resolving the ambiguity in marching cubes]<br />
<br />
== 10/2: Volume Vis == <br />
<br />
Lecturer: Claudio<br />
<br />
Topics: Accelerating structures; High-quality contours<br />
<br />
Slides: <br />
<br />
[http://www.cs.utah.edu/~csilva/courses/cs5630/iso-speed.pdf iso-speed.pdf]<br />
<br />
[http://www.cs.utah.edu/~csilva/courses/cs5630/iso-speed-2.pdf iso-speed-2.pdf]<br />
<br />
References:<br />
<br />
[http://doi.ieeecomputersociety.org/10.1109/2945.489388 A Near Optimal Isosurface Extraction Algorithm Using the Span Space]<br />
<br />
[http://doi.ieeecomputersociety.org/10.1109/2945.485619 Automatic Isosurface Propagation Using an Extrema Graph and Sorted Boundary Cell Lists]<br />
<br />
[http://doi.ieeecomputersociety.org/10.1109/2945.597798 Speeding Up Isosurface Extraction Using Interval Trees]<br />
<br />
[http://doi.ieeecomputersociety.org/10.1109/SVVG.2004.5 Implicit Occluders]<br />
<br />
== 10/4: Volume Vis ==<br />
<br />
Lecturer: Claudio<br />
<br />
Topics: High quality isosurfaces<br />
<br />
Slides: [http://www.cs.utah.edu/~csilva/courses/cs5630/iso-quality.pdf iso-quality.pdf]<br />
<br />
References:<br />
<br />
[http://www.cs.utah.edu/~csilva/2007-sub/macet.pdf Edge Transformations for Improving Mesh Quality of Marching Cubes]<br />
<br />
[http://www.sci.utah.edu/~csilva/papers/tvcg2006acr.pdf High-Quality Extraction of Isosurfaces from Regular and Irregular Grids]<br />
<br />
[http://portal.acm.org/citation.cfm?id=566570.566586 Dual contouring of hermite data]<br />
<br />
[http://www.sci.utah.edu/%7Emiriah/research/meshing/vis07meyer.pdf Topology, Accuracy, and Quality of Isosurface Meshes Using Dynamic Particles]<br />
<br />
[http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=1260744 Material interface reconstruction]<br />
<br />
== 10/9: Fall break == <br />
<br />
== 10/11: Fall break == <br />
<br />
== 10/16: Volume Vis ==<br />
<br />
Lecturer: Claudio<br />
<br />
Topics: continued from last class<br />
<br />
== 10/18: Direct Volume Rendering ==<br />
<br />
Lecturer: Steve<br />
<br />
Topics: Introduction to volume rendering<br />
<br />
Slides: [http://www.sci.utah.edu/~stevec/classes/cs5630/VolumeRendering1.pdf VolumeRendering1.pdf]<br />
<br />
Notes: [http://www.sci.utah.edu/~stevec/classes/cs5630/dvr.pdf dvr.pdf]<br />
<br />
vistrails: [http://www.sci.utah.edu/~stevec/classes/cs5630/VolumeRenderingVistrails.zip VolumeRenderingVistrails.zip]<br />
<br />
References:<br />
[http://www.llnl.gov/graphics/docs/OpticalModelsLong.pdf Optical Models for Direct Volume Rendering]<br />
<br />
== 10/23: Midterm 1 ==<br />
<br />
== 10/25: Direct Volume Rendering ==<br />
<br />
Lecturer: Steve<br />
<br />
Topics: Structured grid techniques: ray-casting, splatting, texture slicing, shear-warp<br />
<br />
Slides: [http://www.sci.utah.edu/~stevec/classes/cs5630/VolumeRendering2.pdf VolumeRendering2.pdf]<br />
<br />
Notes: same as previous class<br />
<br />
vistrails: same as previous class<br />
<br />
References:<br />
<br />
[http://graphics.stanford.edu/papers/volume-cga88/ Display of Surfaces from Volume Data] - Ray casting paper<br />
<br />
[http://portal.acm.org/citation.cfm?id=329138 Interactive Volume Rendering] - Splatting paper, paper requires ACM digital library access<br />
<br />
[http://portal.acm.org/citation.cfm?id=197972&dl=ACM&coll=GUIDE Accelerated volume rendering and tomographic reconstruction using texture mapping hardware] - Texture slicing paper, requires ACM digital library access<br />
<br />
[http://graphics.stanford.edu/papers/shear/ Fast Volume Rendering Using a Shear-Warp Factorization of the Viewing Transformation] - Shear-warp paper<br />
<br />
== 10/30: Cosmology and EEG analysis ==<br />
<br />
Guest lecture: Erik Anderson<br />
<br />
Topics: Applications of Visualization Techniques, Multi-modal Visualization<br />
<br />
Slides: VisualizationApplications [http://www.sci.utah.edu/~eranders/talk/scivis_applications/applications.ppt ppt] | [http://www.sci.utah.edu/~eranders/talk/scivis_applications/applications.odp odp]<br />
<br />
VisTrail: Contact me [http://www.sci.utah.edu/~eranders here]<br />
<br />
References:<br />
<br />
[http://www.sci.utah.edu/~eranders/papers/embs2007_neuro.pdf Working Memory in Schizophrenia] - Overview of rTMS in EEG Analysis<br />
<br />
[http://arxiv.org/abs/0706.1270 Cosmology Code Comparison Project] - Cosmological Simulation Project<br />
<br />
== 11/1: Simplification Techniques == <br />
<br />
Guest lecture: Yuan Zhou<br />
<br />
Topics: Simplification techniques: vertex clustering, vertex decimation, iterative contraction, quadric error based surface and tetrahedral simplification<br />
<br />
Slides: [http://graphics.cs.uiuc.edu/~yuanzhou/class/SciVis2007_simplification Simplification]<br />
<br />
References:<br />
<br />
[http://graphics.cs.uiuc.edu/~garland/papers/quadrics.pdf Surface Simplification Using Quadric Error Metrics]<br />
<br />
[http://graphics.cs.uiuc.edu/~garland/papers/STAR99 Multiresolution Modeling : Survey & Future Opportunities]<br />
<br />
[http://graphics.cs.uiuc.edu/~garland/papers/TR-2004-2450 Quadric-Based Simplication in Any Dimension] <br />
<br />
[http://www.sci.utah.edu/~csilva/papers/tvcg2007cr Streaming Simplification of Tetrahedral Meshes]<br />
<br />
== 11/6: Direct Volume Rendering ==<br />
<br />
Lecturer: Claudio<br />
<br />
Topics: Unstructured grid techniques<br />
<br />
Slides: [http://www.cs.utah.edu/~csilva/courses/cs5630/unstructured_grid_rendering.pdf unstructured_grid_rendering.pdf]<br />
<br />
References:<br />
<br />
[http://www.sci.utah.edu/~csilva/papers/rita2005.pdf A Survey of GPU-Based Volume Rendering of Unstructured Grid]<br />
<br />
[http://www.sci.utah.edu/~csilva/papers/tvcg2005cr.pdf Hardware-Assisted Visibility Sorting for Unstructured Volume Rendering] (This technique is implemented in VTK: http://www.vtk.org/doc/nightly/html/classvtkHAVSVolumeMapper.html)<br />
<br />
[http://www.sci.utah.edu/~csilva/papers/volvis2000.pdf ZSWEEP: An Efficient and Exact Projection Algorithm for Unstructured Volume Rendering] (This technique is implemented in VTK: http://www.vtk.org/doc/nightly/html/classvtkUnstructuredGridVolumeZSweepMapper.html)<br />
<br />
== 11/8: Direct Volume Rendering ==<br />
<br />
Lecturer: Claudio<br />
<br />
Topics: Transfer function specification<br />
<br />
Slides: [http://www.cs.utah.edu/~csilva/courses/cs5630/transfer_functions.pdf transfer_functions.pdf]<br />
<br />
References: <br />
<br />
[http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=920623 The transfer function bake-off]<br />
<br />
[http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=663875 The contour spectrum]<br />
<br />
[http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=1021579 Multidimensional transfer functions for interactive volume rendering]<br />
<br />
[http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=729588 Semi-automatic generation of transfer functions for direct volumerendering]<br />
<br />
== 11/13: Tensor Visualization ==<br />
<br />
Lecturer: Carlos<br />
<br />
Topics: DT/MRI intro, glyphs, colormapping, volume rendering<br />
<br />
Slides: TBA<br />
<br />
References: TBA<br />
<br />
== 11/15: 3D Vector Vis and Topology ==<br />
<br />
Lecturer: Carlos<br />
<br />
Topics: 3D techniques, critical points<br />
<br />
== 11/20: Information Visualization ==<br />
<br />
Lecturer: Carlos<br />
<br />
Topics: Parallel coordinates; Graph visualization<br />
<br />
== 11/22: Thanksgiving == <br />
<br />
== 11/27: Information Visualization ==<br />
<br />
Lecturer: Carlos and Steve<br />
<br />
Topics: Trees and Graphs; InfoVis Examples<br />
<br />
Links:<br />
* [http://www.many-eyes.com Many Eyes]<br />
* [http://www.win.tue.nl/sequoiaview/ SequioaView]<br />
* [http://www.gg.caltech.edu/~zhukov/infovis/world_of_music.htm World Of Music]<br />
* [http://www.tableausoftware.com/ Tableau]<br />
* [http://http://www.gapminder.org/ GapMinder]<br />
* [http://www.babynamewizard.com/namevoyager/lnv0105.html Name Voyager]<br />
<br />
== 11/29: Aesthetic Issues in Vis ==<br />
<br />
Lecturer: Steve<br />
<br />
Topics: Tufte principles<br />
<br />
Slides: [http://www.sci.utah.edu/~stevec/classes/cs5630/Tufte.pdf Tufte.pdf]<br />
<br />
References:<br />
* Envisioning Information, Edward R. Tufte, Academic Press, 1990<br />
* Visual Explanations: Images and Quantities, Evidence and Narrative, Edward R. Tufte, Academic Press, 1997<br />
<br />
== 12/4: Aesthetic Issues in Vis ==<br />
<br />
Lecturer: Steve<br />
<br />
Topics: NPR and Illustrative techniques for Vis<br />
<br />
<br />
== 12/6: Misc ==<br />
<br />
Lecturer: Claudio<br />
<br />
Topics: Data Management for Vis, Vis for presentation/discovery<br />
<br />
== 12/11: Misc ==<br />
<br />
Lecturer: Claudio<br />
<br />
Topics: Recap, Open research questions</div>Thu, 29 Nov 2007 22:00:38 GMTStevechttps://www.vistrails.org//index.php/Talk:SciVisFall2007/ScheduleSciVisFall2007/Schedule
https://www.vistrails.org//index.php?title=SciVisFall2007/Schedule&diff=921
https://www.vistrails.org//index.php?title=SciVisFall2007/Schedule&diff=921<p>Stevec: /* 11/27: Information Visualization */</p>
<hr />
<div>== 8/21: Introduction to visualization ==<br />
<br />
Lecturer: Claudio<br />
<br />
Topics: Scientific Visualization<br />
<br />
Notes: [http://www.cs.utah.edu/~csilva/courses/cs5630/lec01-notes.pdf lec01-notes.pdf]<br />
<br />
Slides: [http://www.cs.utah.edu/~csilva/courses/cs5630/lec01.pdf lec01.pdf]<br />
<br />
Animations: [http://www.cs.utah.edu/~csilva/courses/cs5630/explosion_640x480-5.mov explosion_640x480-5.mov], [http://www.cs.utah.edu/~csilva/courses/cs5630/fig7.mov fig7.mov], [http://www.cs.utah.edu/~csilva/courses/cs5630/fig8.mov fig8.mov], [http://www.cs.utah.edu/~csilva/courses/cs5630/fig9.mov fig9.mov], [http://www.cs.utah.edu/~csilva/courses/cs5630/SevereTstorm.mov SevereTstorm.mov]<br />
<br />
Further reading: <br />
<br />
[http://www.sci.utah.edu/~csilva/papers/vis2003.pdf Visualizing Spatial and Temporal Variability in Coastal Observatories], W. Herrera-Jimenez, W. Correa, C. Silva, and A. Baptista, IEEE Visualization 2003.<br />
<br />
== 8/23: The visualization pipeline ==<br />
<br />
Lecturer: Claudio<br />
<br />
Topics: Procedural vs. Dataflow programming; Using Dataflow for the Vis Pipeline; Dataflow programming with VTK; Dataflow programming with VisTrails; python.<br />
<br />
Notes: [http://www.cs.utah.edu/~csilva/courses/cs5630/lec02-notes.pdf lec02-notes.pdf]<br />
<br />
Slides: [http://www.cs.utah.edu/~csilva/courses/cs5630/lec02.pdf lec02.pdf]<br />
<br />
VisTrails: During this class, we built a pipeline equivalent to the cone.tcl (see class slides). Here is the vistrails file: [http://www.cs.utah.edu/~csilva/courses/cs5630/cone.vt cone.vt]<br />
<br />
Further reading: <br />
<br />
[http://www.cs.utah.edu/~csilva/courses/cs5630/reproducible_vis.pdf Provenance for Visualizations: Reproducibility and Beyond], C. Silva, J. Freire, and S. Callahan, IEEE Computing in Science and Engineering, to appear.<br />
<br />
== 8/28: Modeling Data for Visualization ==<br />
<br />
Lecturer: Carlos<br />
<br />
Topics: Discrete vs continous data; Sampling and interpolation; Point vs triangulated data; Meshing data types; Regular vs irregular data; Tabular data; Vector and tensor fields<br />
<br />
Notes: TBA<br />
<br />
Slides: [http://www.sci.utah.edu/~cscheid/scivis_fall07/modelling_1.ppt .ppt file]<br />
<br />
Further reading: <br />
<br />
There is no required reading for this lecture. The notes will be available shortly. The following papers are there for people that are looking to get more advanced material that will not be covered in class.<br />
<br />
=== Interpolation ===<br />
<br />
[http://lmi.bwh.harvard.edu/papers/papers/geodesic-loxodromes-final.html Geodesic-loxodromes...] This is the fancy interpolation for diffusion tensors I mentioned in class.<br />
<br />
[http://en.wikipedia.org/wiki/Bernstein_polynomial Bernstein polynomials] These are the polynomials used for cubic Bezier curves that I mentioned in class.<br />
<br />
==== Separability ====<br />
<br />
[http://portal.acm.org/citation.cfm?id=1187793 Extensions of the Zwart-Powell Box spline...] This is a recent paper that shows a class of trivariate reconstruction techniques that are ''not'' separable.<br />
<br />
==== Tensors ====<br />
<br />
[http://www.cs.utah.edu/research/techreports/2004/pdf/UUCS-04-014.pdf Visualization and Analysis of Diffusion Tensor Fields] Gordon Kindlmann's PhD. thesis, with everything you ever wanted to know about DTI. Section 2.1 has a good primer in tensor algebra.<br />
<br />
== 8/30: Modeling Data for Visualization == <br />
<br />
Lecturer: Carlos<br />
<br />
Topics: Geometry Processing: Reconstruction and meshing; Simplification; Smoothing; Other Filtering algorithms<br />
<br />
Notes: [http://www.sci.utah.edu/~cscheid/scivis_fall07/week2.pdf .pdf file]. If you want to print these, you might want to wait for a week or two, until I finish polishing them.<br />
<br />
Slides: [http://www.sci.utah.edu/~cscheid/scivis_fall07/processing.ppt .ppt file] ''These slides include simplificatin algorithms, which I'll talk about next week.''<br />
<br />
== 9/4: Elementary Plotting Techniques == <br />
<br />
Lecturer: Steve<br />
<br />
Topics: Principles of Graph Construction<br />
<br />
Notes: [http://www.sci.utah.edu/~stevec/classes/cs5630/PlottingNotes.pdf PlottingNotes.pdf]<br />
<br />
Slides: [http://www.sci.utah.edu/~stevec/slides/SciVis/Plotting1.pdf Plotting1.pdf]<br />
<br />
Vistrails: See next lecture.<br />
<br />
Further Reading: There is no required reading for this lecture. For those interested in more depth, the following books are very useful:<br />
<br />
* The Elements of Graphing Data. William S. Cleveland, Hobart Press, 2nd Edition, 1994.<br />
* Visualizing Data. William S. Cleveland, Hobart Press, 1993.<br />
* The Visual Display of Quantitative Information. Edward R. Tufte, Graphics Press, 2001.<br />
* Visual Explanations: Images and Quantities, Evidence and Narrative. Edward R. Tufte, Graphics Press, 2997.<br />
<br />
== 9/6: Elementary Plotting Techniques ==<br />
<br />
Lecturer: Steve<br />
<br />
Topics: Simple Plotting Methods: Dot Plots, Connected Symbol Plots, Scatter Plots, Histograms, Others. Advanced Plotting Methods: Multimodal, Higher Dimensional, Correlation, Uncertainty and Variation.<br />
<br />
Notes: [http://www.sci.utah.edu/~stevec/classes/cs5630/PlottingNotes.pdf PlottingNotes.pdf]<br />
<br />
Slides: [http://www.sci.utah.edu/~stevec/slides/SciVis/Plotting2.pdf Plotting2.pdf]<br />
<br />
Vistrails: [http://www.sci.utah.edu/~stevec/classes/cs5630/PlottingVistrails.zip PlottingVistrails.zip] - Unzip this file in the examples directory of your VisTrails installation and it will add the vistrails along with their data sets (in the data directory). If you don't have permission to write to this directory (CADE users), then unzip the file where you want. Just be aware that in this case the paths for the data files may not be correct for most vistrails and will need to be fixed before they will execute properly.<br />
<br />
<br />
Further Reading: There is no required reading for this lecture. Some articles of interest:<br />
<br />
* [http://www.fmrib.ox.ac.uk/analysis/techrep/tr00mj2/tr00mj2/node24.html Histogram Bin Size]<br />
* [http://en.wikipedia.org/wiki/Correlation Correlation]<br />
* [http://en.wikipedia.org/wiki/Linear_regression Linear Regression]<br />
* [http://en.wikipedia.org/wiki/Box_plot Box Plots]<br />
<br />
== 9/11: Color and Human Perception ==<br />
<br />
Lecturer: Claudio<br />
<br />
Topics: Human vision system; Optical illusions<br />
<br />
Notes: TBA<br />
<br />
Slides: [http://www.cs.utah.edu/~csilva/courses/cs5630/human-vision.pdf human-vision.pdf]<br />
<br />
Links:<br />
<br />
http://en.wikipedia.org/wiki/Eye<br />
<br />
http://www.grand-illusions.com/gregory2.htm (also, see the related book: [http://www.amazon.com/Eye-Brain-Richard-L-Gregory/dp/0691048371])<br />
<br />
http://en.wikipedia.org/wiki/Purkinje_effect<br />
<br />
http://www.handprint.com/HP/WCL/color2.html<br />
<br />
== 9/13: Color and Human Perception ==<br />
<br />
Lecturer: Claudio<br />
<br />
Topics: Color Science; Color spaces; Color Blindness; Color maps; Tone mapping<br />
<br />
Notes: TBA<br />
<br />
Slides: [http://www.cs.utah.edu/~csilva/courses/cs5630/colorvision.pdf colorvision.pdf]<br />
<br />
Links:<br />
<br />
Further reading: <br />
<br />
[http://www.research.ibm.com/dx/proceedings/pravda/truevis.htm How Not to Lie with Visualization]<br />
<br />
http://en.wikipedia.org/wiki/Opponent_process<br />
<br />
http://en.wikipedia.org/wiki/Color_models<br />
<br />
http://en.wikipedia.org/wiki/Absolute_color_space<br />
<br />
http://en.wikipedia.org/wiki/Additive_color<br />
<br />
http://en.wikipedia.org/wiki/Subtractive_color<br />
<br />
http://en.wikipedia.org/wiki/RGB_color_model<br />
<br />
http://en.wikipedia.org/wiki/SRGB_color_space<br />
<br />
http://en.wikipedia.org/wiki/CIE_XYZ_color_space<br />
<br />
== 9/18 (a): Color and Human Perception ==<br />
<br />
Lecturer: Claudio<br />
<br />
Same material as previous lecture. <br />
<br />
== 9/18 (b): 2D Visualization Techniques ==<br />
<br />
Lecturer: Carlos<br />
<br />
Topics: 2-D contours, marching quads, marching tris; Color mapping; height fields; NPR<br />
<br />
Slides: [http://www.sci.utah.edu/~cscheid/scivis_fall07/2d_scalar_vis.pdf pdf file]<br />
<br />
Notes: [http://www.sci.utah.edu/~cscheid/scivis_fall07/2d_scalar_vis_notes.pdf pdf file]<br />
<br />
Vistrails: [http://www.sci.utah.edu/~cscheid/scivis_fall07/ozone_and_data.zip zip file with ozone.vt and data] [http://www.sci.utah.edu/~cscheid/scivis_fall07/asymptotic_decider.vt asymptotic decider in 2d] [http://www.sci.utah.edu/~cscheid/scivis_fall07/elevation.zip heightfields]<br />
<br />
Note: These vistrails use relative file paths so you don't need to change each of them individually to match your directory structure. Simply unzip the file to whichever location is more convenient. Then, inside VisTrails, open the VisTrails shell, type:<br />
<br />
import os<br />
os.chdir("c:/directory/where/you/unzipped/it")<br />
<br />
This will change the directory so you should be able to just run the pipelines.<br />
<br />
== 9/20: Math refresher ==<br />
<br />
Lecturer: Carlos<br />
<br />
Topics: Basic linear algebra; vectors; basic differential geometry (space curves, tangents, normals, surfaces); basic vector calculus (gradient, divergence, curl, gauss' theorem, green's theorem) <br />
<br />
== 9/25: 2D Visualization Techniques ==<br />
<br />
Lecturer: Carlos<br />
<br />
Topics: 2-D vector fields, div, grad, curl in 2D; Steady vs Unsteady flows; Glyphs; 2-D streamlines, streaklines, pathlines<br />
<br />
Slides: [http://www.sci.utah.edu/~cscheid/scivis_fall07/2d_vector_vis.pdf pdf file]<br />
<br />
Notes: coming soon<br />
<br />
Vistrails: [http://www.sci.utah.edu/~cscheid/scivis_fall07/vector_vis_1.zip vistrail with steady vector field vis and data] [http://www.sci.utah.edu/~cscheid/scivis_fall07/unsteady.zip vistrail with unsteady vector field vis and data] '''Note:''' Because VTK does not support time-varying datasets directly, we had to create a reasonably ugly hack to simulate unsteady fields. This means the datasets are quite big (80MB in total).<br />
<br />
== 9/27 (a): 2D Visualization Techniques ==<br />
<br />
Lecturer Carlos<br />
<br />
Same material as last lecture.<br />
<br />
== 9/27 (b): Volume Vis ==<br />
<br />
Lecturer: Claudio<br />
<br />
Topics: Slicing; Contours; Marching algorithms<br />
<br />
Slides: [http://www.cs.utah.edu/~csilva/courses/cs5630/iso-basic.pdf iso-basic.pdf]<br />
<br />
References:<br />
<br />
[http://portal.acm.org/citation.cfm?id=37401.37422 Marching cubes: A high resolution 3D surface construction algorithm]<br />
<br />
[http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=175782 The asymptotic decider: resolving the ambiguity in marching cubes]<br />
<br />
== 10/2: Volume Vis == <br />
<br />
Lecturer: Claudio<br />
<br />
Topics: Accelerating structures; High-quality contours<br />
<br />
Slides: <br />
<br />
[http://www.cs.utah.edu/~csilva/courses/cs5630/iso-speed.pdf iso-speed.pdf]<br />
<br />
[http://www.cs.utah.edu/~csilva/courses/cs5630/iso-speed-2.pdf iso-speed-2.pdf]<br />
<br />
References:<br />
<br />
[http://doi.ieeecomputersociety.org/10.1109/2945.489388 A Near Optimal Isosurface Extraction Algorithm Using the Span Space]<br />
<br />
[http://doi.ieeecomputersociety.org/10.1109/2945.485619 Automatic Isosurface Propagation Using an Extrema Graph and Sorted Boundary Cell Lists]<br />
<br />
[http://doi.ieeecomputersociety.org/10.1109/2945.597798 Speeding Up Isosurface Extraction Using Interval Trees]<br />
<br />
[http://doi.ieeecomputersociety.org/10.1109/SVVG.2004.5 Implicit Occluders]<br />
<br />
== 10/4: Volume Vis ==<br />
<br />
Lecturer: Claudio<br />
<br />
Topics: High quality isosurfaces<br />
<br />
Slides: [http://www.cs.utah.edu/~csilva/courses/cs5630/iso-quality.pdf iso-quality.pdf]<br />
<br />
References:<br />
<br />
[http://www.cs.utah.edu/~csilva/2007-sub/macet.pdf Edge Transformations for Improving Mesh Quality of Marching Cubes]<br />
<br />
[http://www.sci.utah.edu/~csilva/papers/tvcg2006acr.pdf High-Quality Extraction of Isosurfaces from Regular and Irregular Grids]<br />
<br />
[http://portal.acm.org/citation.cfm?id=566570.566586 Dual contouring of hermite data]<br />
<br />
[http://www.sci.utah.edu/%7Emiriah/research/meshing/vis07meyer.pdf Topology, Accuracy, and Quality of Isosurface Meshes Using Dynamic Particles]<br />
<br />
[http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=1260744 Material interface reconstruction]<br />
<br />
== 10/9: Fall break == <br />
<br />
== 10/11: Fall break == <br />
<br />
== 10/16: Volume Vis ==<br />
<br />
Lecturer: Claudio<br />
<br />
Topics: continued from last class<br />
<br />
== 10/18: Direct Volume Rendering ==<br />
<br />
Lecturer: Steve<br />
<br />
Topics: Introduction to volume rendering<br />
<br />
Slides: [http://www.sci.utah.edu/~stevec/classes/cs5630/VolumeRendering1.pdf VolumeRendering1.pdf]<br />
<br />
Notes: [http://www.sci.utah.edu/~stevec/classes/cs5630/dvr.pdf dvr.pdf]<br />
<br />
vistrails: [http://www.sci.utah.edu/~stevec/classes/cs5630/VolumeRenderingVistrails.zip VolumeRenderingVistrails.zip]<br />
<br />
References:<br />
[http://www.llnl.gov/graphics/docs/OpticalModelsLong.pdf Optical Models for Direct Volume Rendering]<br />
<br />
== 10/23: Midterm 1 ==<br />
<br />
== 10/25: Direct Volume Rendering ==<br />
<br />
Lecturer: Steve<br />
<br />
Topics: Structured grid techniques: ray-casting, splatting, texture slicing, shear-warp<br />
<br />
Slides: [http://www.sci.utah.edu/~stevec/classes/cs5630/VolumeRendering2.pdf VolumeRendering2.pdf]<br />
<br />
Notes: same as previous class<br />
<br />
vistrails: same as previous class<br />
<br />
References:<br />
<br />
[http://graphics.stanford.edu/papers/volume-cga88/ Display of Surfaces from Volume Data] - Ray casting paper<br />
<br />
[http://portal.acm.org/citation.cfm?id=329138 Interactive Volume Rendering] - Splatting paper, paper requires ACM digital library access<br />
<br />
[http://portal.acm.org/citation.cfm?id=197972&dl=ACM&coll=GUIDE Accelerated volume rendering and tomographic reconstruction using texture mapping hardware] - Texture slicing paper, requires ACM digital library access<br />
<br />
[http://graphics.stanford.edu/papers/shear/ Fast Volume Rendering Using a Shear-Warp Factorization of the Viewing Transformation] - Shear-warp paper<br />
<br />
== 10/30: Cosmology and EEG analysis ==<br />
<br />
Guest lecture: Erik Anderson<br />
<br />
Topics: Applications of Visualization Techniques, Multi-modal Visualization<br />
<br />
Slides: VisualizationApplications [http://www.sci.utah.edu/~eranders/talk/scivis_applications/applications.ppt ppt] | [http://www.sci.utah.edu/~eranders/talk/scivis_applications/applications.odp odp]<br />
<br />
VisTrail: Contact me [http://www.sci.utah.edu/~eranders here]<br />
<br />
References:<br />
<br />
[http://www.sci.utah.edu/~eranders/papers/embs2007_neuro.pdf Working Memory in Schizophrenia] - Overview of rTMS in EEG Analysis<br />
<br />
[http://arxiv.org/abs/0706.1270 Cosmology Code Comparison Project] - Cosmological Simulation Project<br />
<br />
== 11/1: Simplification Techniques == <br />
<br />
Guest lecture: Yuan Zhou<br />
<br />
Topics: Simplification techniques: vertex clustering, vertex decimation, iterative contraction, quadric error based surface and tetrahedral simplification<br />
<br />
Slides: [http://graphics.cs.uiuc.edu/~yuanzhou/class/SciVis2007_simplification Simplification]<br />
<br />
References:<br />
<br />
[http://graphics.cs.uiuc.edu/~garland/papers/quadrics.pdf Surface Simplification Using Quadric Error Metrics]<br />
<br />
[http://graphics.cs.uiuc.edu/~garland/papers/STAR99 Multiresolution Modeling : Survey & Future Opportunities]<br />
<br />
[http://graphics.cs.uiuc.edu/~garland/papers/TR-2004-2450 Quadric-Based Simplication in Any Dimension] <br />
<br />
[http://www.sci.utah.edu/~csilva/papers/tvcg2007cr Streaming Simplification of Tetrahedral Meshes]<br />
<br />
== 11/6: Direct Volume Rendering ==<br />
<br />
Lecturer: Claudio<br />
<br />
Topics: Unstructured grid techniques<br />
<br />
Slides: [http://www.cs.utah.edu/~csilva/courses/cs5630/unstructured_grid_rendering.pdf unstructured_grid_rendering.pdf]<br />
<br />
References:<br />
<br />
[http://www.sci.utah.edu/~csilva/papers/rita2005.pdf A Survey of GPU-Based Volume Rendering of Unstructured Grid]<br />
<br />
[http://www.sci.utah.edu/~csilva/papers/tvcg2005cr.pdf Hardware-Assisted Visibility Sorting for Unstructured Volume Rendering] (This technique is implemented in VTK: http://www.vtk.org/doc/nightly/html/classvtkHAVSVolumeMapper.html)<br />
<br />
[http://www.sci.utah.edu/~csilva/papers/volvis2000.pdf ZSWEEP: An Efficient and Exact Projection Algorithm for Unstructured Volume Rendering] (This technique is implemented in VTK: http://www.vtk.org/doc/nightly/html/classvtkUnstructuredGridVolumeZSweepMapper.html)<br />
<br />
== 11/8: Direct Volume Rendering ==<br />
<br />
Lecturer: Claudio<br />
<br />
Topics: Transfer function specification<br />
<br />
Slides: [http://www.cs.utah.edu/~csilva/courses/cs5630/transfer_functions.pdf transfer_functions.pdf]<br />
<br />
References: <br />
<br />
[http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=920623 The transfer function bake-off]<br />
<br />
[http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=663875 The contour spectrum]<br />
<br />
[http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=1021579 Multidimensional transfer functions for interactive volume rendering]<br />
<br />
[http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=729588 Semi-automatic generation of transfer functions for direct volumerendering]<br />
<br />
== 11/13: Tensor Visualization ==<br />
<br />
Lecturer: Carlos<br />
<br />
Topics: DT/MRI intro, glyphs, colormapping, volume rendering<br />
<br />
Slides: TBA<br />
<br />
References: TBA<br />
<br />
== 11/15: 3D Vector Vis and Topology ==<br />
<br />
Lecturer: Carlos<br />
<br />
Topics: 3D techniques, critical points<br />
<br />
== 11/20: Information Visualization ==<br />
<br />
Lecturer: Carlos<br />
<br />
Topics: Parallel coordinates; Graph visualization<br />
<br />
== 11/22: Thanksgiving == <br />
<br />
== 11/27: Information Visualization ==<br />
<br />
Lecturer: Carlos and Steve<br />
<br />
Topics: Trees and Graphs; InfoVis Examples<br />
<br />
Links:<br />
* [http://www.many-eyes.com Many Eyes]<br />
* [http://www.win.tue.nl/sequoiaview/ SequioaView]<br />
* [http://www.gg.caltech.edu/~zhukov/infovis/world_of_music.htm World Of Music]<br />
* [http://www.tableausoftware.com/ Tableau]<br />
* [http://http://www.gapminder.org/ GapMinder]<br />
* [http://www.babynamewizard.com/namevoyager/lnv0105.html Name Voyager]<br />
<br />
== 11/29: Aesthetic Issues in Vis ==<br />
<br />
Lecturer: Steve<br />
<br />
Topics: Tufte principles<br />
<br />
<br />
== 12/4: Aesthetic Issues in Vis ==<br />
<br />
Lecturer: Steve<br />
<br />
Topics: NPR and Illustrative techniques for Vis<br />
<br />
<br />
== 12/6: Misc ==<br />
<br />
Lecturer: Claudio<br />
<br />
Topics: Data Management for Vis, Vis for presentation/discovery<br />
<br />
== 12/11: Misc ==<br />
<br />
Lecturer: Claudio<br />
<br />
Topics: Recap, Open research questions</div>Wed, 28 Nov 2007 17:28:17 GMTStevechttps://www.vistrails.org//index.php/Talk:SciVisFall2007/ScheduleSciVisFall2007/Schedule
https://www.vistrails.org//index.php?title=SciVisFall2007/Schedule&diff=905
https://www.vistrails.org//index.php?title=SciVisFall2007/Schedule&diff=905<p>Stevec: </p>
<hr />
<div>== 8/21: Introduction to visualization ==<br />
<br />
Lecturer: Claudio<br />
<br />
Topics: Scientific Visualization<br />
<br />
Notes: [http://www.cs.utah.edu/~csilva/courses/cs5630/lec01-notes.pdf lec01-notes.pdf]<br />
<br />
Slides: [http://www.cs.utah.edu/~csilva/courses/cs5630/lec01.pdf lec01.pdf]<br />
<br />
Animations: [http://www.cs.utah.edu/~csilva/courses/cs5630/explosion_640x480-5.mov explosion_640x480-5.mov], [http://www.cs.utah.edu/~csilva/courses/cs5630/fig7.mov fig7.mov], [http://www.cs.utah.edu/~csilva/courses/cs5630/fig8.mov fig8.mov], [http://www.cs.utah.edu/~csilva/courses/cs5630/fig9.mov fig9.mov], [http://www.cs.utah.edu/~csilva/courses/cs5630/SevereTstorm.mov SevereTstorm.mov]<br />
<br />
Further reading: <br />
<br />
[http://www.sci.utah.edu/~csilva/papers/vis2003.pdf Visualizing Spatial and Temporal Variability in Coastal Observatories], W. Herrera-Jimenez, W. Correa, C. Silva, and A. Baptista, IEEE Visualization 2003.<br />
<br />
== 8/23: The visualization pipeline ==<br />
<br />
Lecturer: Claudio<br />
<br />
Topics: Procedural vs. Dataflow programming; Using Dataflow for the Vis Pipeline; Dataflow programming with VTK; Dataflow programming with VisTrails; python.<br />
<br />
Notes: [http://www.cs.utah.edu/~csilva/courses/cs5630/lec02-notes.pdf lec02-notes.pdf]<br />
<br />
Slides: [http://www.cs.utah.edu/~csilva/courses/cs5630/lec02.pdf lec02.pdf]<br />
<br />
VisTrails: During this class, we built a pipeline equivalent to the cone.tcl (see class slides). Here is the vistrails file: [http://www.cs.utah.edu/~csilva/courses/cs5630/cone.vt cone.vt]<br />
<br />
Further reading: <br />
<br />
[http://www.cs.utah.edu/~csilva/courses/cs5630/reproducible_vis.pdf Provenance for Visualizations: Reproducibility and Beyond], C. Silva, J. Freire, and S. Callahan, IEEE Computing in Science and Engineering, to appear.<br />
<br />
== 8/28: Modeling Data for Visualization ==<br />
<br />
Lecturer: Carlos<br />
<br />
Topics: Discrete vs continous data; Sampling and interpolation; Point vs triangulated data; Meshing data types; Regular vs irregular data; Tabular data; Vector and tensor fields<br />
<br />
Notes: TBA<br />
<br />
Slides: [http://www.sci.utah.edu/~cscheid/scivis_fall07/modelling_1.ppt .ppt file]<br />
<br />
Further reading: <br />
<br />
There is no required reading for this lecture. The notes will be available shortly. The following papers are there for people that are looking to get more advanced material that will not be covered in class.<br />
<br />
=== Interpolation ===<br />
<br />
[http://lmi.bwh.harvard.edu/papers/papers/geodesic-loxodromes-final.html Geodesic-loxodromes...] This is the fancy interpolation for diffusion tensors I mentioned in class.<br />
<br />
[http://en.wikipedia.org/wiki/Bernstein_polynomial Bernstein polynomials] These are the polynomials used for cubic Bezier curves that I mentioned in class.<br />
<br />
==== Separability ====<br />
<br />
[http://portal.acm.org/citation.cfm?id=1187793 Extensions of the Zwart-Powell Box spline...] This is a recent paper that shows a class of trivariate reconstruction techniques that are ''not'' separable.<br />
<br />
==== Tensors ====<br />
<br />
[http://www.cs.utah.edu/research/techreports/2004/pdf/UUCS-04-014.pdf Visualization and Analysis of Diffusion Tensor Fields] Gordon Kindlmann's PhD. thesis, with everything you ever wanted to know about DTI. Section 2.1 has a good primer in tensor algebra.<br />
<br />
== 8/30: Modeling Data for Visualization == <br />
<br />
Lecturer: Carlos<br />
<br />
Topics: Geometry Processing: Reconstruction and meshing; Simplification; Smoothing; Other Filtering algorithms<br />
<br />
Notes: [http://www.sci.utah.edu/~cscheid/scivis_fall07/week2.pdf .pdf file]. If you want to print these, you might want to wait for a week or two, until I finish polishing them.<br />
<br />
Slides: [http://www.sci.utah.edu/~cscheid/scivis_fall07/processing.ppt .ppt file] ''These slides include simplificatin algorithms, which I'll talk about next week.''<br />
<br />
== 9/4: Elementary Plotting Techniques == <br />
<br />
Lecturer: Steve<br />
<br />
Topics: Principles of Graph Construction<br />
<br />
Notes: [http://www.sci.utah.edu/~stevec/classes/cs5630/PlottingNotes.pdf PlottingNotes.pdf]<br />
<br />
Slides: [http://www.sci.utah.edu/~stevec/slides/SciVis/Plotting1.pdf Plotting1.pdf]<br />
<br />
Vistrails: See next lecture.<br />
<br />
Further Reading: There is no required reading for this lecture. For those interested in more depth, the following books are very useful:<br />
<br />
* The Elements of Graphing Data. William S. Cleveland, Hobart Press, 2nd Edition, 1994.<br />
* Visualizing Data. William S. Cleveland, Hobart Press, 1993.<br />
* The Visual Display of Quantitative Information. Edward R. Tufte, Graphics Press, 2001.<br />
* Visual Explanations: Images and Quantities, Evidence and Narrative. Edward R. Tufte, Graphics Press, 2997.<br />
<br />
== 9/6: Elementary Plotting Techniques ==<br />
<br />
Lecturer: Steve<br />
<br />
Topics: Simple Plotting Methods: Dot Plots, Connected Symbol Plots, Scatter Plots, Histograms, Others. Advanced Plotting Methods: Multimodal, Higher Dimensional, Correlation, Uncertainty and Variation.<br />
<br />
Notes: [http://www.sci.utah.edu/~stevec/classes/cs5630/PlottingNotes.pdf PlottingNotes.pdf]<br />
<br />
Slides: [http://www.sci.utah.edu/~stevec/slides/SciVis/Plotting2.pdf Plotting2.pdf]<br />
<br />
Vistrails: [http://www.sci.utah.edu/~stevec/classes/cs5630/PlottingVistrails.zip PlottingVistrails.zip] - Unzip this file in the examples directory of your VisTrails installation and it will add the vistrails along with their data sets (in the data directory). If you don't have permission to write to this directory (CADE users), then unzip the file where you want. Just be aware that in this case the paths for the data files may not be correct for most vistrails and will need to be fixed before they will execute properly.<br />
<br />
<br />
Further Reading: There is no required reading for this lecture. Some articles of interest:<br />
<br />
* [http://www.fmrib.ox.ac.uk/analysis/techrep/tr00mj2/tr00mj2/node24.html Histogram Bin Size]<br />
* [http://en.wikipedia.org/wiki/Correlation Correlation]<br />
* [http://en.wikipedia.org/wiki/Linear_regression Linear Regression]<br />
* [http://en.wikipedia.org/wiki/Box_plot Box Plots]<br />
<br />
== 9/11: Color and Human Perception ==<br />
<br />
Lecturer: Claudio<br />
<br />
Topics: Human vision system; Optical illusions<br />
<br />
Notes: TBA<br />
<br />
Slides: [http://www.cs.utah.edu/~csilva/courses/cs5630/human-vision.pdf human-vision.pdf]<br />
<br />
Links:<br />
<br />
http://en.wikipedia.org/wiki/Eye<br />
<br />
http://www.grand-illusions.com/gregory2.htm (also, see the related book: [http://www.amazon.com/Eye-Brain-Richard-L-Gregory/dp/0691048371])<br />
<br />
http://en.wikipedia.org/wiki/Purkinje_effect<br />
<br />
http://www.handprint.com/HP/WCL/color2.html<br />
<br />
== 9/13: Color and Human Perception ==<br />
<br />
Lecturer: Claudio<br />
<br />
Topics: Color Science; Color spaces; Color Blindness; Color maps; Tone mapping<br />
<br />
Notes: TBA<br />
<br />
Slides: [http://www.cs.utah.edu/~csilva/courses/cs5630/colorvision.pdf colorvision.pdf]<br />
<br />
Links:<br />
<br />
Further reading: <br />
<br />
[http://www.research.ibm.com/dx/proceedings/pravda/truevis.htm How Not to Lie with Visualization]<br />
<br />
http://en.wikipedia.org/wiki/Opponent_process<br />
<br />
http://en.wikipedia.org/wiki/Color_models<br />
<br />
http://en.wikipedia.org/wiki/Absolute_color_space<br />
<br />
http://en.wikipedia.org/wiki/Additive_color<br />
<br />
http://en.wikipedia.org/wiki/Subtractive_color<br />
<br />
http://en.wikipedia.org/wiki/RGB_color_model<br />
<br />
http://en.wikipedia.org/wiki/SRGB_color_space<br />
<br />
http://en.wikipedia.org/wiki/CIE_XYZ_color_space<br />
<br />
== 9/18 (a): Color and Human Perception ==<br />
<br />
Lecturer: Claudio<br />
<br />
Same material as previous lecture. <br />
<br />
== 9/18 (b): 2D Visualization Techniques ==<br />
<br />
Lecturer: Carlos<br />
<br />
Topics: 2-D contours, marching quads, marching tris; Color mapping; height fields; NPR<br />
<br />
Slides: [http://www.sci.utah.edu/~cscheid/scivis_fall07/2d_scalar_vis.pdf pdf file]<br />
<br />
Notes: [http://www.sci.utah.edu/~cscheid/scivis_fall07/2d_scalar_vis_notes.pdf pdf file]<br />
<br />
Vistrails: [http://www.sci.utah.edu/~cscheid/scivis_fall07/ozone_and_data.zip zip file with ozone.vt and data] [http://www.sci.utah.edu/~cscheid/scivis_fall07/asymptotic_decider.vt asymptotic decider in 2d] [http://www.sci.utah.edu/~cscheid/scivis_fall07/elevation.zip heightfields]<br />
<br />
Note: These vistrails use relative file paths so you don't need to change each of them individually to match your directory structure. Simply unzip the file to whichever location is more convenient. Then, inside VisTrails, open the VisTrails shell, type:<br />
<br />
import os<br />
os.chdir("c:/directory/where/you/unzipped/it")<br />
<br />
This will change the directory so you should be able to just run the pipelines.<br />
<br />
== 9/20: Math refresher ==<br />
<br />
Lecturer: Carlos<br />
<br />
Topics: Basic linear algebra; vectors; basic differential geometry (space curves, tangents, normals, surfaces); basic vector calculus (gradient, divergence, curl, gauss' theorem, green's theorem) <br />
<br />
== 9/25: 2D Visualization Techniques ==<br />
<br />
Lecturer: Carlos<br />
<br />
Topics: 2-D vector fields, div, grad, curl in 2D; Steady vs Unsteady flows; Glyphs; 2-D streamlines, streaklines, pathlines<br />
<br />
Slides: [http://www.sci.utah.edu/~cscheid/scivis_fall07/2d_vector_vis.pdf pdf file]<br />
<br />
Notes: coming soon<br />
<br />
Vistrails: [http://www.sci.utah.edu/~cscheid/scivis_fall07/vector_vis_1.zip vistrail with steady vector field vis and data] [http://www.sci.utah.edu/~cscheid/scivis_fall07/unsteady.zip vistrail with unsteady vector field vis and data] '''Note:''' Because VTK does not support time-varying datasets directly, we had to create a reasonably ugly hack to simulate unsteady fields. This means the datasets are quite big (80MB in total).<br />
<br />
== 9/27 (a): 2D Visualization Techniques ==<br />
<br />
Lecturer Carlos<br />
<br />
Same material as last lecture.<br />
<br />
== 9/27 (b): Volume Vis ==<br />
<br />
Lecturer: Claudio<br />
<br />
Topics: Slicing; Contours; Marching algorithms<br />
<br />
Slides: [http://www.cs.utah.edu/~csilva/courses/cs5630/iso-basic.pdf iso-basic.pdf]<br />
<br />
References:<br />
<br />
[http://portal.acm.org/citation.cfm?id=37401.37422 Marching cubes: A high resolution 3D surface construction algorithm]<br />
<br />
[http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=175782 The asymptotic decider: resolving the ambiguity in marching cubes]<br />
<br />
== 10/2: Volume Vis == <br />
<br />
Lecturer: Claudio<br />
<br />
Topics: Accelerating structures; High-quality contours<br />
<br />
Slides: <br />
<br />
[http://www.cs.utah.edu/~csilva/courses/cs5630/iso-speed.pdf iso-speed.pdf]<br />
<br />
[http://www.cs.utah.edu/~csilva/courses/cs5630/iso-speed-2.pdf iso-speed-2.pdf]<br />
<br />
References:<br />
<br />
[http://doi.ieeecomputersociety.org/10.1109/2945.489388 A Near Optimal Isosurface Extraction Algorithm Using the Span Space]<br />
<br />
[http://doi.ieeecomputersociety.org/10.1109/2945.485619 Automatic Isosurface Propagation Using an Extrema Graph and Sorted Boundary Cell Lists]<br />
<br />
[http://doi.ieeecomputersociety.org/10.1109/2945.597798 Speeding Up Isosurface Extraction Using Interval Trees]<br />
<br />
[http://doi.ieeecomputersociety.org/10.1109/SVVG.2004.5 Implicit Occluders]<br />
<br />
== 10/4: Volume Vis ==<br />
<br />
Lecturer: Claudio<br />
<br />
Topics: High quality isosurfaces<br />
<br />
Slides: [http://www.cs.utah.edu/~csilva/courses/cs5630/iso-quality.pdf iso-quality.pdf]<br />
<br />
References:<br />
<br />
[http://www.cs.utah.edu/~csilva/2007-sub/macet.pdf Edge Transformations for Improving Mesh Quality of Marching Cubes]<br />
<br />
[http://www.sci.utah.edu/~csilva/papers/tvcg2006acr.pdf High-Quality Extraction of Isosurfaces from Regular and Irregular Grids]<br />
<br />
[http://portal.acm.org/citation.cfm?id=566570.566586 Dual contouring of hermite data]<br />
<br />
[http://www.sci.utah.edu/%7Emiriah/research/meshing/vis07meyer.pdf Topology, Accuracy, and Quality of Isosurface Meshes Using Dynamic Particles]<br />
<br />
[http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=1260744 Material interface reconstruction]<br />
<br />
== 10/9: Fall break == <br />
<br />
== 10/11: Fall break == <br />
<br />
== 10/16: Volume Vis ==<br />
<br />
Lecturer: Claudio<br />
<br />
Topics: continued from last class<br />
<br />
== 10/18: Direct Volume Rendering ==<br />
<br />
Lecturer: Steve<br />
<br />
Topics: Introduction to volume rendering<br />
<br />
Slides: [http://www.sci.utah.edu/~stevec/classes/cs5630/VolumeRendering1.pdf VolumeRendering1.pdf]<br />
<br />
Notes: [http://www.sci.utah.edu/~stevec/classes/cs5630/dvr.pdf dvr.pdf]<br />
<br />
vistrails: [http://www.sci.utah.edu/~stevec/classes/cs5630/VolumeRenderingVistrails.zip VolumeRenderingVistrails.zip]<br />
<br />
References:<br />
[http://www.llnl.gov/graphics/docs/OpticalModelsLong.pdf Optical Models for Direct Volume Rendering]<br />
<br />
== 10/23: Midterm 1 ==<br />
<br />
== 10/25: Direct Volume Rendering ==<br />
<br />
Lecturer: Steve<br />
<br />
Topics: Structured grid techniques: ray-casting, splatting, texture slicing, shear-warp<br />
<br />
Slides: [http://www.sci.utah.edu/~stevec/classes/cs5630/VolumeRendering2.pdf VolumeRendering2.pdf]<br />
<br />
Notes: same as previous class<br />
<br />
vistrails: same as previous class<br />
<br />
References:<br />
<br />
[http://graphics.stanford.edu/papers/volume-cga88/ Display of Surfaces from Volume Data] - Ray casting paper<br />
<br />
[http://portal.acm.org/citation.cfm?id=329138 Interactive Volume Rendering] - Splatting paper, paper requires ACM digital library access<br />
<br />
[http://portal.acm.org/citation.cfm?id=197972&dl=ACM&coll=GUIDE Accelerated volume rendering and tomographic reconstruction using texture mapping hardware] - Texture slicing paper, requires ACM digital library access<br />
<br />
[http://graphics.stanford.edu/papers/shear/ Fast Volume Rendering Using a Shear-Warp Factorization of the Viewing Transformation] - Shear-warp paper<br />
<br />
== 10/30: Cosmology and EEG analysis ==<br />
<br />
Guest lecture: Erik Anderson<br />
<br />
Topics: Applications of Visualization Techniques, Multi-modal Visualization<br />
<br />
Slides: VisualizationApplications [http://www.sci.utah.edu/~eranders/talk/scivis_applications/applications.ppt ppt] | [http://www.sci.utah.edu/~eranders/talk/scivis_applications/applications.odp odp]<br />
<br />
VisTrail: Contact me [http://www.sci.utah.edu/~eranders here]<br />
<br />
References:<br />
<br />
[http://www.sci.utah.edu/~eranders/papers/embs2007_neuro.pdf Working Memory in Schizophrenia] - Overview of rTMS in EEG Analysis<br />
<br />
[http://arxiv.org/abs/0706.1270 Cosmology Code Comparison Project] - Cosmological Simulation Project<br />
<br />
== 11/1: Simplification Techniques == <br />
<br />
Guest lecture: Yuan Zhou<br />
<br />
Topics: Simplification techniques: vertex clustering, vertex decimation, iterative contraction, quadric error based surface and tetrahedral simplification<br />
<br />
Slides: [http://graphics.cs.uiuc.edu/~yuanzhou/class/SciVis2007_simplification Simplification]<br />
<br />
References:<br />
<br />
[http://graphics.cs.uiuc.edu/~garland/papers/quadrics.pdf Surface Simplification Using Quadric Error Metrics]<br />
<br />
[http://graphics.cs.uiuc.edu/~garland/papers/STAR99 Multiresolution Modeling : Survey & Future Opportunities]<br />
<br />
[http://graphics.cs.uiuc.edu/~garland/papers/TR-2004-2450 Quadric-Based Simplication in Any Dimension] <br />
<br />
[http://www.sci.utah.edu/~csilva/papers/tvcg2007cr Streaming Simplification of Tetrahedral Meshes]<br />
<br />
== 11/6: Direct Volume Rendering ==<br />
<br />
Lecturer: Claudio<br />
<br />
Topics: Unstructured grid techniques<br />
<br />
Slides: TBA<br />
<br />
References: TBA<br />
<br />
== 11/8: Direct Volume Rendering ==<br />
<br />
Lecturer: Claudio<br />
<br />
Topics: Transfer function specification<br />
<br />
Slides: TBA<br />
<br />
References: TBA<br />
<br />
== 11/13: Tensor Visualization ==<br />
<br />
Lecturer: Carlos<br />
<br />
Topics: DT/MRI intro, glyphs, colormapping, volume rendering<br />
<br />
Slides: TBA<br />
<br />
References: TBA<br />
<br />
== 11/15: 3D Vector Vis and Toplogy ==<br />
<br />
Lecturer: Carlos<br />
<br />
Topics: 3D techniques, critical points<br />
<br />
== 11/20: Information Visualization ==<br />
<br />
Lecturer: Carlos<br />
<br />
Topics: Parallel coordinates; Graph visualization<br />
<br />
== 11/22: Thanksgiving == <br />
<br />
== 11/27: Information Visualization ==<br />
<br />
Lecturer: Steve<br />
<br />
Topics: Hierarchical data vis; brushing; sizing text<br />
<br />
== 11/29: Aesthetic Issues in Vis ==<br />
<br />
Lecturer: Steve<br />
<br />
Topics: Tufte principles<br />
<br />
<br />
== 12/4: Aesthetic Issues in Vis ==<br />
<br />
Lecturer: Steve<br />
<br />
Topics: NPR and Illustrative techniques for Vis<br />
<br />
<br />
== 12/6: Misc ==<br />
<br />
Lecturer: Claudio<br />
<br />
Topics: Data Management for Vis, Vis for presentation/discovery<br />
<br />
== 12/11: Misc ==<br />
<br />
Lecturer: Claudio<br />
<br />
Topics: Recap, Open research questions</div>Wed, 14 Nov 2007 22:23:27 GMTStevechttps://www.vistrails.org//index.php/Talk:SciVisFall2007/ScheduleSciVisFall2007/Schedule
https://www.vistrails.org//index.php?title=SciVisFall2007/Schedule&diff=904
https://www.vistrails.org//index.php?title=SciVisFall2007/Schedule&diff=904<p>Stevec: </p>
<hr />
<div>== 8/21: Introduction to visualization ==<br />
<br />
Lecturer: Claudio<br />
<br />
Topics: Scientific Visualization<br />
<br />
Notes: [http://www.cs.utah.edu/~csilva/courses/cs5630/lec01-notes.pdf lec01-notes.pdf]<br />
<br />
Slides: [http://www.cs.utah.edu/~csilva/courses/cs5630/lec01.pdf lec01.pdf]<br />
<br />
Animations: [http://www.cs.utah.edu/~csilva/courses/cs5630/explosion_640x480-5.mov explosion_640x480-5.mov], [http://www.cs.utah.edu/~csilva/courses/cs5630/fig7.mov fig7.mov], [http://www.cs.utah.edu/~csilva/courses/cs5630/fig8.mov fig8.mov], [http://www.cs.utah.edu/~csilva/courses/cs5630/fig9.mov fig9.mov], [http://www.cs.utah.edu/~csilva/courses/cs5630/SevereTstorm.mov SevereTstorm.mov]<br />
<br />
Further reading: <br />
<br />
[http://www.sci.utah.edu/~csilva/papers/vis2003.pdf Visualizing Spatial and Temporal Variability in Coastal Observatories], W. Herrera-Jimenez, W. Correa, C. Silva, and A. Baptista, IEEE Visualization 2003.<br />
<br />
== 8/23: The visualization pipeline ==<br />
<br />
Lecturer: Claudio<br />
<br />
Topics: Procedural vs. Dataflow programming; Using Dataflow for the Vis Pipeline; Dataflow programming with VTK; Dataflow programming with VisTrails; python.<br />
<br />
Notes: [http://www.cs.utah.edu/~csilva/courses/cs5630/lec02-notes.pdf lec02-notes.pdf]<br />
<br />
Slides: [http://www.cs.utah.edu/~csilva/courses/cs5630/lec02.pdf lec02.pdf]<br />
<br />
VisTrails: During this class, we built a pipeline equivalent to the cone.tcl (see class slides). Here is the vistrails file: [http://www.cs.utah.edu/~csilva/courses/cs5630/cone.vt cone.vt]<br />
<br />
Further reading: <br />
<br />
[http://www.cs.utah.edu/~csilva/courses/cs5630/reproducible_vis.pdf Provenance for Visualizations: Reproducibility and Beyond], C. Silva, J. Freire, and S. Callahan, IEEE Computing in Science and Engineering, to appear.<br />
<br />
== 8/28: Modeling Data for Visualization ==<br />
<br />
Lecturer: Carlos<br />
<br />
Topics: Discrete vs continous data; Sampling and interpolation; Point vs triangulated data; Meshing data types; Regular vs irregular data; Tabular data; Vector and tensor fields<br />
<br />
Notes: TBA<br />
<br />
Slides: [http://www.sci.utah.edu/~cscheid/scivis_fall07/modelling_1.ppt .ppt file]<br />
<br />
Further reading: <br />
<br />
There is no required reading for this lecture. The notes will be available shortly. The following papers are there for people that are looking to get more advanced material that will not be covered in class.<br />
<br />
=== Interpolation ===<br />
<br />
[http://lmi.bwh.harvard.edu/papers/papers/geodesic-loxodromes-final.html Geodesic-loxodromes...] This is the fancy interpolation for diffusion tensors I mentioned in class.<br />
<br />
[http://en.wikipedia.org/wiki/Bernstein_polynomial Bernstein polynomials] These are the polynomials used for cubic Bezier curves that I mentioned in class.<br />
<br />
==== Separability ====<br />
<br />
[http://portal.acm.org/citation.cfm?id=1187793 Extensions of the Zwart-Powell Box spline...] This is a recent paper that shows a class of trivariate reconstruction techniques that are ''not'' separable.<br />
<br />
==== Tensors ====<br />
<br />
[http://www.cs.utah.edu/research/techreports/2004/pdf/UUCS-04-014.pdf Visualization and Analysis of Diffusion Tensor Fields] Gordon Kindlmann's PhD. thesis, with everything you ever wanted to know about DTI. Section 2.1 has a good primer in tensor algebra.<br />
<br />
== 8/30: Modeling Data for Visualization == <br />
<br />
Lecturer: Carlos<br />
<br />
Topics: Geometry Processing: Reconstruction and meshing; Simplification; Smoothing; Other Filtering algorithms<br />
<br />
Notes: [http://www.sci.utah.edu/~cscheid/scivis_fall07/week2.pdf .pdf file]. If you want to print these, you might want to wait for a week or two, until I finish polishing them.<br />
<br />
Slides: [http://www.sci.utah.edu/~cscheid/scivis_fall07/processing.ppt .ppt file] ''These slides include simplificatin algorithms, which I'll talk about next week.''<br />
<br />
== 9/4: Elementary Plotting Techniques == <br />
<br />
Lecturer: Steve<br />
<br />
Topics: Principles of Graph Construction<br />
<br />
Notes: [http://www.sci.utah.edu/~stevec/classes/cs5630/PlottingNotes.pdf PlottingNotes.pdf]<br />
<br />
Slides: [http://www.sci.utah.edu/~stevec/slides/SciVis/Plotting1.pdf Plotting1.pdf]<br />
<br />
Vistrails: See next lecture.<br />
<br />
Further Reading: There is no required reading for this lecture. For those interested in more depth, the following books are very useful:<br />
<br />
* The Elements of Graphing Data. William S. Cleveland, Hobart Press, 2nd Edition, 1994.<br />
* Visualizing Data. William S. Cleveland, Hobart Press, 1993.<br />
* The Visual Display of Quantitative Information. Edward R. Tufte, Graphics Press, 2001.<br />
* Visual Explanations: Images and Quantities, Evidence and Narrative. Edward R. Tufte, Graphics Press, 2997.<br />
<br />
== 9/6: Elementary Plotting Techniques ==<br />
<br />
Lecturer: Steve<br />
<br />
Topics: Simple Plotting Methods: Dot Plots, Connected Symbol Plots, Scatter Plots, Histograms, Others. Advanced Plotting Methods: Multimodal, Higher Dimensional, Correlation, Uncertainty and Variation.<br />
<br />
Notes: [http://www.sci.utah.edu/~stevec/classes/cs5630/PlottingNotes.pdf PlottingNotes.pdf]<br />
<br />
Slides: [http://www.sci.utah.edu/~stevec/slides/SciVis/Plotting2.pdf Plotting2.pdf]<br />
<br />
Vistrails: [http://www.sci.utah.edu/~stevec/classes/cs5630/PlottingVistrails.zip PlottingVistrails.zip] - Unzip this file in the examples directory of your VisTrails installation and it will add the vistrails along with their data sets (in the data directory). If you don't have permission to write to this directory (CADE users), then unzip the file where you want. Just be aware that in this case the paths for the data files may not be correct for most vistrails and will need to be fixed before they will execute properly.<br />
<br />
<br />
Further Reading: There is no required reading for this lecture. Some articles of interest:<br />
<br />
* [http://www.fmrib.ox.ac.uk/analysis/techrep/tr00mj2/tr00mj2/node24.html Histogram Bin Size]<br />
* [http://en.wikipedia.org/wiki/Correlation Correlation]<br />
* [http://en.wikipedia.org/wiki/Linear_regression Linear Regression]<br />
* [http://en.wikipedia.org/wiki/Box_plot Box Plots]<br />
<br />
== 9/11: Color and Human Perception ==<br />
<br />
Lecturer: Claudio<br />
<br />
Topics: Human vision system; Optical illusions<br />
<br />
Notes: TBA<br />
<br />
Slides: [http://www.cs.utah.edu/~csilva/courses/cs5630/human-vision.pdf human-vision.pdf]<br />
<br />
Links:<br />
<br />
http://en.wikipedia.org/wiki/Eye<br />
<br />
http://www.grand-illusions.com/gregory2.htm (also, see the related book: [http://www.amazon.com/Eye-Brain-Richard-L-Gregory/dp/0691048371])<br />
<br />
http://en.wikipedia.org/wiki/Purkinje_effect<br />
<br />
http://www.handprint.com/HP/WCL/color2.html<br />
<br />
== 9/13: Color and Human Perception ==<br />
<br />
Lecturer: Claudio<br />
<br />
Topics: Color Science; Color spaces; Color Blindness; Color maps; Tone mapping<br />
<br />
Notes: TBA<br />
<br />
Slides: [http://www.cs.utah.edu/~csilva/courses/cs5630/colorvision.pdf colorvision.pdf]<br />
<br />
Links:<br />
<br />
Further reading: <br />
<br />
[http://www.research.ibm.com/dx/proceedings/pravda/truevis.htm How Not to Lie with Visualization]<br />
<br />
http://en.wikipedia.org/wiki/Opponent_process<br />
<br />
http://en.wikipedia.org/wiki/Color_models<br />
<br />
http://en.wikipedia.org/wiki/Absolute_color_space<br />
<br />
http://en.wikipedia.org/wiki/Additive_color<br />
<br />
http://en.wikipedia.org/wiki/Subtractive_color<br />
<br />
http://en.wikipedia.org/wiki/RGB_color_model<br />
<br />
http://en.wikipedia.org/wiki/SRGB_color_space<br />
<br />
http://en.wikipedia.org/wiki/CIE_XYZ_color_space<br />
<br />
== 9/18 (a): Color and Human Perception ==<br />
<br />
Lecturer: Claudio<br />
<br />
Same material as previous lecture. <br />
<br />
== 9/18 (b): 2D Visualization Techniques ==<br />
<br />
Lecturer: Carlos<br />
<br />
Topics: 2-D contours, marching quads, marching tris; Color mapping; height fields; NPR<br />
<br />
Slides: [http://www.sci.utah.edu/~cscheid/scivis_fall07/2d_scalar_vis.pdf pdf file]<br />
<br />
Notes: [http://www.sci.utah.edu/~cscheid/scivis_fall07/2d_scalar_vis_notes.pdf pdf file]<br />
<br />
Vistrails: [http://www.sci.utah.edu/~cscheid/scivis_fall07/ozone_and_data.zip zip file with ozone.vt and data] [http://www.sci.utah.edu/~cscheid/scivis_fall07/asymptotic_decider.vt asymptotic decider in 2d] [http://www.sci.utah.edu/~cscheid/scivis_fall07/elevation.zip heightfields]<br />
<br />
Note: These vistrails use relative file paths so you don't need to change each of them individually to match your directory structure. Simply unzip the file to whichever location is more convenient. Then, inside VisTrails, open the VisTrails shell, type:<br />
<br />
import os<br />
os.chdir("c:/directory/where/you/unzipped/it")<br />
<br />
This will change the directory so you should be able to just run the pipelines.<br />
<br />
== 9/20: Math refresher ==<br />
<br />
Lecturer: Carlos<br />
<br />
Topics: Basic linear algebra; vectors; basic differential geometry (space curves, tangents, normals, surfaces); basic vector calculus (gradient, divergence, curl, gauss' theorem, green's theorem) <br />
<br />
== 9/25: 2D Visualization Techniques ==<br />
<br />
Lecturer: Carlos<br />
<br />
Topics: 2-D vector fields, div, grad, curl in 2D; Steady vs Unsteady flows; Glyphs; 2-D streamlines, streaklines, pathlines<br />
<br />
Slides: [http://www.sci.utah.edu/~cscheid/scivis_fall07/2d_vector_vis.pdf pdf file]<br />
<br />
Notes: coming soon<br />
<br />
Vistrails: [http://www.sci.utah.edu/~cscheid/scivis_fall07/vector_vis_1.zip vistrail with steady vector field vis and data] [http://www.sci.utah.edu/~cscheid/scivis_fall07/unsteady.zip vistrail with unsteady vector field vis and data] '''Note:''' Because VTK does not support time-varying datasets directly, we had to create a reasonably ugly hack to simulate unsteady fields. This means the datasets are quite big (80MB in total).<br />
<br />
== 9/27 (a): 2D Visualization Techniques ==<br />
<br />
Lecturer Carlos<br />
<br />
Same material as last lecture.<br />
<br />
== 9/27 (b): Volume Vis ==<br />
<br />
Lecturer: Claudio<br />
<br />
Topics: Slicing; Contours; Marching algorithms<br />
<br />
Slides: [http://www.cs.utah.edu/~csilva/courses/cs5630/iso-basic.pdf iso-basic.pdf]<br />
<br />
References:<br />
<br />
[http://portal.acm.org/citation.cfm?id=37401.37422 Marching cubes: A high resolution 3D surface construction algorithm]<br />
<br />
[http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=175782 The asymptotic decider: resolving the ambiguity in marching cubes]<br />
<br />
== 10/2: Volume Vis == <br />
<br />
Lecturer: Claudio<br />
<br />
Topics: Accelerating structures; High-quality contours<br />
<br />
Slides: <br />
<br />
[http://www.cs.utah.edu/~csilva/courses/cs5630/iso-speed.pdf iso-speed.pdf]<br />
<br />
[http://www.cs.utah.edu/~csilva/courses/cs5630/iso-speed-2.pdf iso-speed-2.pdf]<br />
<br />
References:<br />
<br />
[http://doi.ieeecomputersociety.org/10.1109/2945.489388 A Near Optimal Isosurface Extraction Algorithm Using the Span Space]<br />
<br />
[http://doi.ieeecomputersociety.org/10.1109/2945.485619 Automatic Isosurface Propagation Using an Extrema Graph and Sorted Boundary Cell Lists]<br />
<br />
[http://doi.ieeecomputersociety.org/10.1109/2945.597798 Speeding Up Isosurface Extraction Using Interval Trees]<br />
<br />
[http://doi.ieeecomputersociety.org/10.1109/SVVG.2004.5 Implicit Occluders]<br />
<br />
== 10/4: Volume Vis ==<br />
<br />
Lecturer: Claudio<br />
<br />
Topics: High quality isosurfaces<br />
<br />
Slides: [http://www.cs.utah.edu/~csilva/courses/cs5630/iso-quality.pdf iso-quality.pdf]<br />
<br />
References:<br />
<br />
[http://www.cs.utah.edu/~csilva/2007-sub/macet.pdf Edge Transformations for Improving Mesh Quality of Marching Cubes]<br />
<br />
[http://www.sci.utah.edu/~csilva/papers/tvcg2006acr.pdf High-Quality Extraction of Isosurfaces from Regular and Irregular Grids]<br />
<br />
[http://portal.acm.org/citation.cfm?id=566570.566586 Dual contouring of hermite data]<br />
<br />
[http://www.sci.utah.edu/%7Emiriah/research/meshing/vis07meyer.pdf Topology, Accuracy, and Quality of Isosurface Meshes Using Dynamic Particles]<br />
<br />
[http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=1260744 Material interface reconstruction]<br />
<br />
== 10/9: Fall break == <br />
<br />
== 10/11: Fall break == <br />
<br />
== 10/16: Volume Vis ==<br />
<br />
Lecturer: Claudio<br />
<br />
Topics: continued from last class<br />
<br />
== 10/18: Direct Volume Rendering ==<br />
<br />
Lecturer: Steve<br />
<br />
Topics: Introduction to volume rendering<br />
<br />
Slides: [http://www.sci.utah.edu/~stevec/classes/cs5630/VolumeRendering1.pdf VolumeRendering1.pdf]<br />
<br />
Notes: [http://www.sci.utah.edu/~stevec/classes/cs5630/dvr.pdf dvr.pdf]<br />
<br />
vistrails: [http://www.sci.utah.edu/~stevec/classes/cs5630/VolumeRenderingVistrails.zip VolumeRenderingVistrails.zip]<br />
<br />
References:<br />
[http://www.llnl.gov/graphics/docs/OpticalModelsLong.pdf Optical Models for Direct Volume Rendering]<br />
<br />
== 10/23: Midterm 1 ==<br />
<br />
== 10/25: Direct Volume Rendering ==<br />
<br />
Lecturer: Steve<br />
<br />
Topics: Structured grid techniques: ray-casting, splatting, texture slicing, shear-warp<br />
<br />
Slides: [http://www.sci.utah.edu/~stevec/classes/cs5630/VolumeRendering2.pdf VolumeRendering2.pdf]<br />
<br />
Notes: same as previous class<br />
<br />
vistrails: same as previous class<br />
<br />
References:<br />
<br />
[http://graphics.stanford.edu/papers/volume-cga88/ Display of Surfaces from Volume Data] - Ray casting paper<br />
<br />
[http://portal.acm.org/citation.cfm?id=329138 Interactive Volume Rendering] - Splatting paper, paper requires ACM digital library access<br />
<br />
[http://portal.acm.org/citation.cfm?id=197972&dl=ACM&coll=GUIDE Accelerated volume rendering and tomographic reconstruction using texture mapping hardware] - Texture slicing paper, requires ACM digital library access<br />
<br />
[http://graphics.stanford.edu/papers/shear/ Fast Volume Rendering Using a Shear-Warp Factorization of the Viewing Transformation] - Shear-warp paper<br />
<br />
== 10/30: Cosmology and EEG analysis ==<br />
<br />
Guest lecture: Erik Anderson<br />
<br />
Topics: Applications of Visualization Techniques, Multi-modal Visualization<br />
<br />
Slides: VisualizationApplications [http://www.sci.utah.edu/~eranders/talk/scivis_applications/applications.ppt ppt] | [http://www.sci.utah.edu/~eranders/talk/scivis_applications/applications.odp odp]<br />
<br />
VisTrail: Contact me [http://www.sci.utah.edu/~eranders here]<br />
<br />
References:<br />
<br />
[http://www.sci.utah.edu/~eranders/papers/embs2007_neuro.pdf Working Memory in Schizophrenia] - Overview of rTMS in EEG Analysis<br />
<br />
[http://arxiv.org/abs/0706.1270 Cosmology Code Comparison Project] - Cosmological Simulation Project<br />
<br />
== 11/1: Simplification Techniques == <br />
<br />
Guest lecture: Yuan Zhou<br />
<br />
Topics: Simplification techniques: vertex clustering, vertex decimation, iterative contraction, quadric error based surface and tetrahedral simplification<br />
<br />
Slides: [http://graphics.cs.uiuc.edu/~yuanzhou/class/SciVis2007_simplification Simplification]<br />
<br />
References:<br />
<br />
[http://graphics.cs.uiuc.edu/~garland/papers/quadrics.pdf Surface Simplification Using Quadric Error Metrics]<br />
<br />
[http://graphics.cs.uiuc.edu/~garland/papers/STAR99 Multiresolution Modeling : Survey & Future Opportunities]<br />
<br />
[http://graphics.cs.uiuc.edu/~garland/papers/TR-2004-2450 Quadric-Based Simplication in Any Dimension] <br />
<br />
[http://www.sci.utah.edu/~csilva/papers/tvcg2007cr Streaming Simplification of Tetrahedral Meshes]<br />
<br />
== 11/6: Direct Volume Rendering ==<br />
<br />
Lecturer: Claudio<br />
<br />
Topics: Unstructured grid techniques<br />
<br />
Slides: TBA<br />
<br />
References: TBA<br />
<br />
== 11/8: Direct Volume Rendering ==<br />
<br />
Lecturer: Claudio<br />
<br />
Topics: Transfer function specification<br />
<br />
Slides: TBA<br />
<br />
References: TBA<br />
<br />
== 11/13: Tensor Visualization ==<br />
<br />
Lecturer: Carlos<br />
<br />
Topics: DT/MRI intro, glyphs, colormapping, volume rendering<br />
<br />
Slides: TBA<br />
<br />
References: TBA<br />
<br />
== 11/15: 3D Vector Vis and Toplogy ==<br />
<br />
Lecturer: Claudio<br />
<br />
Topics: 3D techniques, critical points<br />
<br />
== 11/20: Aesthetic Issues in Vis ==<br />
<br />
Lecturer: Steve<br />
<br />
Topics: Tufte principles<br />
<br />
== 11/22: Thanksgiving == <br />
<br />
== 11/27: Aesthetic Issues in Vis ==<br />
<br />
Lecturer: Steve<br />
<br />
Topics: Tufte principles<br />
<br />
== 11/29: Aesthetic Issues in Vis ==<br />
<br />
Lecturer: Steve<br />
<br />
Topics: NPR and Illustrative techniques for vis<br />
<br />
== 11/4: Information Visualization ==<br />
<br />
Lecturer: Carlos<br />
<br />
Topics: Parallel coordinates; Graph visualization<br />
<br />
== 12/6: Information Visualization ==<br />
<br />
Lecturer: Claudio<br />
<br />
Topics: Hierarchical data vis; brushing; sizing text<br />
<br />
== 12/11: Misc ==<br />
<br />
Lecturer: TBA<br />
<br />
Topics: Data Management for Vis, Vis for presentation/discovery, Open research questions</div>Wed, 14 Nov 2007 20:31:46 GMTStevechttps://www.vistrails.org//index.php/Talk:SciVisFall2007/ScheduleSciVisFall2007/Schedule
https://www.vistrails.org//index.php?title=SciVisFall2007/Schedule&diff=866
https://www.vistrails.org//index.php?title=SciVisFall2007/Schedule&diff=866<p>Stevec: /* 10/18: Direct Volume Rendering */</p>
<hr />
<div>== 8/21: Introduction to visualization ==<br />
<br />
Lecturer: Claudio<br />
<br />
Topics: Scientific Visualization<br />
<br />
Notes: [http://www.cs.utah.edu/~csilva/courses/cs5630/lec01-notes.pdf lec01-notes.pdf]<br />
<br />
Slides: [http://www.cs.utah.edu/~csilva/courses/cs5630/lec01.pdf lec01.pdf]<br />
<br />
Animations: [http://www.cs.utah.edu/~csilva/courses/cs5630/explosion_640x480-5.mov explosion_640x480-5.mov], [http://www.cs.utah.edu/~csilva/courses/cs5630/fig7.mov fig7.mov], [http://www.cs.utah.edu/~csilva/courses/cs5630/fig8.mov fig8.mov], [http://www.cs.utah.edu/~csilva/courses/cs5630/fig9.mov fig9.mov], [http://www.cs.utah.edu/~csilva/courses/cs5630/SevereTstorm.mov SevereTstorm.mov]<br />
<br />
Further reading: <br />
<br />
[http://www.sci.utah.edu/~csilva/papers/vis2003.pdf Visualizing Spatial and Temporal Variability in Coastal Observatories], W. Herrera-Jimenez, W. Correa, C. Silva, and A. Baptista, IEEE Visualization 2003.<br />
<br />
== 8/23: The visualization pipeline ==<br />
<br />
Lecturer: Claudio<br />
<br />
Topics: Procedural vs. Dataflow programming; Using Dataflow for the Vis Pipeline; Dataflow programming with VTK; Dataflow programming with VisTrails; python.<br />
<br />
Notes: [http://www.cs.utah.edu/~csilva/courses/cs5630/lec02-notes.pdf lec02-notes.pdf]<br />
<br />
Slides: [http://www.cs.utah.edu/~csilva/courses/cs5630/lec02.pdf lec02.pdf]<br />
<br />
VisTrails: During this class, we built a pipeline equivalent to the cone.tcl (see class slides). Here is the vistrails file: [http://www.cs.utah.edu/~csilva/courses/cs5630/cone.vt cone.vt]<br />
<br />
Further reading: <br />
<br />
[http://www.cs.utah.edu/~csilva/courses/cs5630/reproducible_vis.pdf Provenance for Visualizations: Reproducibility and Beyond], C. Silva, J. Freire, and S. Callahan, IEEE Computing in Science and Engineering, to appear.<br />
<br />
== 8/28: Modeling Data for Visualization ==<br />
<br />
Lecturer: Carlos<br />
<br />
Topics: Discrete vs continous data; Sampling and interpolation; Point vs triangulated data; Meshing data types; Regular vs irregular data; Tabular data; Vector and tensor fields<br />
<br />
Notes: TBA<br />
<br />
Slides: [http://www.sci.utah.edu/~cscheid/scivis_fall07/modelling_1.ppt .ppt file]<br />
<br />
Further reading: <br />
<br />
There is no required reading for this lecture. The notes will be available shortly. The following papers are there for people that are looking to get more advanced material that will not be covered in class.<br />
<br />
=== Interpolation ===<br />
<br />
[http://lmi.bwh.harvard.edu/papers/papers/geodesic-loxodromes-final.html Geodesic-loxodromes...] This is the fancy interpolation for diffusion tensors I mentioned in class.<br />
<br />
[http://en.wikipedia.org/wiki/Bernstein_polynomial Bernstein polynomials] These are the polynomials used for cubic Bezier curves that I mentioned in class.<br />
<br />
==== Separability ====<br />
<br />
[http://portal.acm.org/citation.cfm?id=1187793 Extensions of the Zwart-Powell Box spline...] This is a recent paper that shows a class of trivariate reconstruction techniques that are ''not'' separable.<br />
<br />
==== Tensors ====<br />
<br />
[http://www.cs.utah.edu/research/techreports/2004/pdf/UUCS-04-014.pdf Visualization and Analysis of Diffusion Tensor Fields] Gordon Kindlmann's PhD. thesis, with everything you ever wanted to know about DTI. Section 2.1 has a good primer in tensor algebra.<br />
<br />
== 8/30: Modeling Data for Visualization == <br />
<br />
Lecturer: Carlos<br />
<br />
Topics: Geometry Processing: Reconstruction and meshing; Simplification; Smoothing; Other Filtering algorithms<br />
<br />
Notes: [http://www.sci.utah.edu/~cscheid/scivis_fall07/week2.pdf .pdf file]. If you want to print these, you might want to wait for a week or two, until I finish polishing them.<br />
<br />
Slides: [http://www.sci.utah.edu/~cscheid/scivis_fall07/processing.ppt .ppt file] ''These slides include simplificatin algorithms, which I'll talk about next week.''<br />
<br />
== 9/4: Elementary Plotting Techniques == <br />
<br />
Lecturer: Steve<br />
<br />
Topics: Principles of Graph Construction<br />
<br />
Notes: [http://www.sci.utah.edu/~stevec/classes/cs5630/PlottingNotes.pdf PlottingNotes.pdf]<br />
<br />
Slides: [http://www.sci.utah.edu/~stevec/slides/SciVis/Plotting1.pdf Plotting1.pdf]<br />
<br />
Vistrails: See next lecture.<br />
<br />
Further Reading: There is no required reading for this lecture. For those interested in more depth, the following books are very useful:<br />
<br />
* The Elements of Graphing Data. William S. Cleveland, Hobart Press, 2nd Edition, 1994.<br />
* Visualizing Data. William S. Cleveland, Hobart Press, 1993.<br />
* The Visual Display of Quantitative Information. Edward R. Tufte, Graphics Press, 2001.<br />
* Visual Explanations: Images and Quantities, Evidence and Narrative. Edward R. Tufte, Graphics Press, 2997.<br />
<br />
== 9/6: Elementary Plotting Techniques ==<br />
<br />
Lecturer: Steve<br />
<br />
Topics: Simple Plotting Methods: Dot Plots, Connected Symbol Plots, Scatter Plots, Histograms, Others. Advanced Plotting Methods: Multimodal, Higher Dimensional, Correlation, Uncertainty and Variation.<br />
<br />
Notes: [http://www.sci.utah.edu/~stevec/classes/cs5630/PlottingNotes.pdf PlottingNotes.pdf]<br />
<br />
Slides: [http://www.sci.utah.edu/~stevec/slides/SciVis/Plotting2.pdf Plotting2.pdf]<br />
<br />
Vistrails: [http://www.sci.utah.edu/~stevec/classes/cs5630/PlottingVistrails.zip PlottingVistrails.zip] - Unzip this file in the examples directory of your VisTrails installation and it will add the vistrails along with their data sets (in the data directory). If you don't have permission to write to this directory (CADE users), then unzip the file where you want. Just be aware that in this case the paths for the data files may not be correct for most vistrails and will need to be fixed before they will execute properly.<br />
<br />
<br />
Further Reading: There is no required reading for this lecture. Some articles of interest:<br />
<br />
* [http://www.fmrib.ox.ac.uk/analysis/techrep/tr00mj2/tr00mj2/node24.html Histogram Bin Size]<br />
* [http://en.wikipedia.org/wiki/Correlation Correlation]<br />
* [http://en.wikipedia.org/wiki/Linear_regression Linear Regression]<br />
* [http://en.wikipedia.org/wiki/Box_plot Box Plots]<br />
<br />
== 9/11: Color and Human Perception ==<br />
<br />
Lecturer: Claudio<br />
<br />
Topics: Human vision system; Optical illusions<br />
<br />
Notes: TBA<br />
<br />
Slides: [http://www.cs.utah.edu/~csilva/courses/cs5630/human-vision.pdf human-vision.pdf]<br />
<br />
Links:<br />
<br />
http://en.wikipedia.org/wiki/Eye<br />
<br />
http://www.grand-illusions.com/gregory2.htm (also, see the related book: [http://www.amazon.com/Eye-Brain-Richard-L-Gregory/dp/0691048371])<br />
<br />
http://en.wikipedia.org/wiki/Purkinje_effect<br />
<br />
http://www.handprint.com/HP/WCL/color2.html<br />
<br />
== 9/13: Color and Human Perception ==<br />
<br />
Lecturer: Claudio<br />
<br />
Topics: Color Science; Color spaces; Color Blindness; Color maps; Tone mapping<br />
<br />
Notes: TBA<br />
<br />
Slides: [http://www.cs.utah.edu/~csilva/courses/cs5630/colorvision.pdf colorvision.pdf]<br />
<br />
Links:<br />
<br />
Further reading: <br />
<br />
[http://www.research.ibm.com/dx/proceedings/pravda/truevis.htm How Not to Lie with Visualization]<br />
<br />
http://en.wikipedia.org/wiki/Opponent_process<br />
<br />
http://en.wikipedia.org/wiki/Color_models<br />
<br />
http://en.wikipedia.org/wiki/Absolute_color_space<br />
<br />
http://en.wikipedia.org/wiki/Additive_color<br />
<br />
http://en.wikipedia.org/wiki/Subtractive_color<br />
<br />
http://en.wikipedia.org/wiki/RGB_color_model<br />
<br />
http://en.wikipedia.org/wiki/SRGB_color_space<br />
<br />
http://en.wikipedia.org/wiki/CIE_XYZ_color_space<br />
<br />
== 9/18 (a): Color and Human Perception ==<br />
<br />
Lecturer: Claudio<br />
<br />
Same material as previous lecture. <br />
<br />
== 9/18 (b): 2D Visualization Techniques ==<br />
<br />
Lecturer: Carlos<br />
<br />
Topics: 2-D contours, marching quads, marching tris; Color mapping; height fields; NPR<br />
<br />
Slides: [http://www.sci.utah.edu/~cscheid/scivis_fall07/2d_scalar_vis.pdf pdf file]<br />
<br />
Notes: [http://www.sci.utah.edu/~cscheid/scivis_fall07/2d_scalar_vis_notes.pdf pdf file]<br />
<br />
Vistrails: [http://www.sci.utah.edu/~cscheid/scivis_fall07/ozone_and_data.zip zip file with ozone.vt and data] [http://www.sci.utah.edu/~cscheid/scivis_fall07/asymptotic_decider.vt asymptotic decider in 2d] [http://www.sci.utah.edu/~cscheid/scivis_fall07/elevation.zip heightfields]<br />
<br />
Note: These vistrails use relative file paths so you don't need to change each of them individually to match your directory structure. Simply unzip the file to whichever location is more convenient. Then, inside VisTrails, open the VisTrails shell, type:<br />
<br />
import os<br />
os.chdir("c:/directory/where/you/unzipped/it")<br />
<br />
This will change the directory so you should be able to just run the pipelines.<br />
<br />
== 9/20: Math refresher ==<br />
<br />
Lecturer: Carlos<br />
<br />
Topics: Basic linear algebra; vectors; basic differential geometry (space curves, tangents, normals, surfaces); basic vector calculus (gradient, divergence, curl, gauss' theorem, green's theorem) <br />
<br />
== 9/25: 2D Visualization Techniques ==<br />
<br />
Lecturer: Carlos<br />
<br />
Topics: 2-D vector fields, div, grad, curl in 2D; Steady vs Unsteady flows; Glyphs; 2-D streamlines, streaklines, pathlines<br />
<br />
Slides: [http://www.sci.utah.edu/~cscheid/scivis_fall07/2d_vector_vis.pdf pdf file]<br />
<br />
Notes: coming soon<br />
<br />
Vistrails: [http://www.sci.utah.edu/~cscheid/scivis_fall07/vector_vis_1.zip vistrail with steady vector field vis and data] [http://www.sci.utah.edu/~cscheid/scivis_fall07/unsteady.zip vistrail with unsteady vector field vis and data] '''Note:''' Because VTK does not support time-varying datasets directly, we had to create a reasonably ugly hack to simulate unsteady fields. This means the datasets are quite big (80MB in total).<br />
<br />
== 9/27 (a): 2D Visualization Techniques ==<br />
<br />
Lecturer Carlos<br />
<br />
Same material as last lecture.<br />
<br />
== 9/27 (b): Volume Vis ==<br />
<br />
Lecturer: Claudio<br />
<br />
Topics: Slicing; Contours; Marching algorithms<br />
<br />
Slides: [http://www.cs.utah.edu/~csilva/courses/cs5630/iso-basic.pdf iso-basic.pdf]<br />
<br />
References:<br />
<br />
[http://portal.acm.org/citation.cfm?id=37401.37422 Marching cubes: A high resolution 3D surface construction algorithm]<br />
<br />
[http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=175782 The asymptotic decider: resolving the ambiguity in marching cubes]<br />
<br />
== 10/2: Volume Vis == <br />
<br />
Lecturer: Claudio<br />
<br />
Topics: Accelerating structures; High-quality contours<br />
<br />
Slides: <br />
<br />
[http://www.cs.utah.edu/~csilva/courses/cs5630/iso-speed.pdf iso-speed.pdf]<br />
<br />
[http://www.cs.utah.edu/~csilva/courses/cs5630/iso-speed-2.pdf iso-speed-2.pdf]<br />
<br />
References:<br />
<br />
[http://doi.ieeecomputersociety.org/10.1109/2945.489388 A Near Optimal Isosurface Extraction Algorithm Using the Span Space]<br />
<br />
[http://doi.ieeecomputersociety.org/10.1109/2945.485619 Automatic Isosurface Propagation Using an Extrema Graph and Sorted Boundary Cell Lists]<br />
<br />
[http://doi.ieeecomputersociety.org/10.1109/2945.597798 Speeding Up Isosurface Extraction Using Interval Trees]<br />
<br />
[http://doi.ieeecomputersociety.org/10.1109/SVVG.2004.5 Implicit Occluders]<br />
<br />
== 10/4: Volume Vis ==<br />
<br />
Lecturer: Claudio<br />
<br />
Topics: High quality isosurfaces<br />
<br />
Slides: [http://www.cs.utah.edu/~csilva/courses/cs5630/iso-quality.pdf iso-quality.pdf]<br />
<br />
References:<br />
<br />
[http://www.cs.utah.edu/~csilva/2007-sub/macet.pdf Edge Transformations for Improving Mesh Quality of Marching Cubes]<br />
<br />
[http://www.sci.utah.edu/~csilva/papers/tvcg2006acr.pdf High-Quality Extraction of Isosurfaces from Regular and Irregular Grids]<br />
<br />
[http://portal.acm.org/citation.cfm?id=566570.566586 Dual contouring of hermite data]<br />
<br />
[http://www.sci.utah.edu/%7Emiriah/research/meshing/vis07meyer.pdf Topology, Accuracy, and Quality of Isosurface Meshes Using Dynamic Particles]<br />
<br />
[http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=1260744 Material interface reconstruction]<br />
<br />
== 10/9: Fall break == <br />
<br />
== 10/11: Fall break == <br />
<br />
== 10/16: Volume Vis ==<br />
<br />
Lecturer: Claudio<br />
<br />
Topics: continued from last class<br />
<br />
== 10/18: Direct Volume Rendering ==<br />
<br />
Lecturer: Steve<br />
<br />
Topics: Introduction to volume rendering<br />
<br />
Slides: [http://www.sci.utah.edu/~stevec/classes/cs5630/VolumeRendering1.pdf VolumeRendering1.pdf]<br />
<br />
Notes: [http://www.sci.utah.edu/~stevec/classes/cs5630/dvr.pdf dvr.pdf]<br />
<br />
vistrails: [http://www.sci.utah.edu/~stevec/classes/cs5630/VolumeRenderingVistrails.zip VolumeRenderingVistrails.zip]<br />
<br />
References:<br />
[http://www.llnl.gov/graphics/docs/OpticalModelsLong.pdf Optical Models for Direct Volume Rendering]<br />
<br />
== 10/23: Midterm 1 ==<br />
<br />
== 10/25: Direct Volume Rendering ==<br />
<br />
Lecturer: Steve<br />
<br />
Topics: Structured grid techniques: ray-casting, splatting, texture slicing, shear-warp<br />
<br />
Slides: [http://www.sci.utah.edu/~stevec/classes/cs5630/VolumeRendering2.pdf VolumeRendering2.pdf]<br />
<br />
Notes: same as previous class<br />
<br />
vistrails: same as previous class<br />
<br />
References:<br />
<br />
[http://graphics.stanford.edu/papers/volume-cga88/ Display of Surfaces from Volume Data] - Ray casting paper<br />
<br />
[http://portal.acm.org/citation.cfm?id=329138 Interactive Volume Rendering] - Splatting paper, paper requires ACM digital library access<br />
<br />
[http://portal.acm.org/citation.cfm?id=197972&dl=ACM&coll=GUIDE Accelerated volume rendering and tomographic reconstruction using texture mapping hardware] - Texture slicing paper, requires ACM digital library access<br />
<br />
[http://graphics.stanford.edu/papers/shear/ Fast Volume Rendering Using a Shear-Warp Factorization of the Viewing Transformation] - Shear-warp paper<br />
<br />
== 10/30: Cosmology and EEG analysis ==<br />
<br />
Guest lecture: Erik Anderson<br />
<br />
== 11/1: Simplification Techniques == <br />
<br />
Guest lecture: Yuan Zhou<br />
<br />
== 11/6: Vector and Tensor Visualization ==<br />
<br />
Lecturer: Claudio<br />
<br />
Topics: LIC; hyper LIC; Topology-based techniques<br />
<br />
== 11/8: Vector and Tensor Vis ==<br />
<br />
Lecturer: Carlos<br />
<br />
Topics: Glyphs; DTI techniques<br />
<br />
== 11/13: Aesthetic Issues in Vis ==<br />
<br />
Lecturer: Claudio<br />
<br />
Topics: Volume Illustration and NPR<br />
<br />
== 11/15: Aesthetic Issues in Vis ==<br />
<br />
Lecturer: Steve<br />
<br />
Topics: Tufte<br />
<br />
== 11/20: Aesthetic Issues in Vis ==<br />
<br />
Lecturer: Steve<br />
<br />
Topics: Tufte<br />
<br />
== 11/22: Thanksgiving == <br />
<br />
== 11/27: Information Visualization ==<br />
<br />
Lecturer: Carlos<br />
<br />
Topics: Parallel coordinates; Graph visualization<br />
<br />
== 11/29: Information Visualization ==<br />
<br />
Lecturer: Claudio<br />
<br />
Topics: Hierarchical data vis; brushing; sizing text<br />
<br />
== 12/4: Data Management for Vis ==<br />
<br />
== 12/6: Vis for presentation/discovery ==<br />
<br />
== 12/11: Open research questions ==</div>Sat, 03 Nov 2007 01:15:12 GMTStevechttps://www.vistrails.org//index.php/Talk:SciVisFall2007/ScheduleSciVisFall2007/Schedule
https://www.vistrails.org//index.php?title=SciVisFall2007/Schedule&diff=863
https://www.vistrails.org//index.php?title=SciVisFall2007/Schedule&diff=863<p>Stevec: </p>
<hr />
<div>== 8/21: Introduction to visualization ==<br />
<br />
Lecturer: Claudio<br />
<br />
Topics: Scientific Visualization<br />
<br />
Notes: [http://www.cs.utah.edu/~csilva/courses/cs5630/lec01-notes.pdf lec01-notes.pdf]<br />
<br />
Slides: [http://www.cs.utah.edu/~csilva/courses/cs5630/lec01.pdf lec01.pdf]<br />
<br />
Animations: [http://www.cs.utah.edu/~csilva/courses/cs5630/explosion_640x480-5.mov explosion_640x480-5.mov], [http://www.cs.utah.edu/~csilva/courses/cs5630/fig7.mov fig7.mov], [http://www.cs.utah.edu/~csilva/courses/cs5630/fig8.mov fig8.mov], [http://www.cs.utah.edu/~csilva/courses/cs5630/fig9.mov fig9.mov], [http://www.cs.utah.edu/~csilva/courses/cs5630/SevereTstorm.mov SevereTstorm.mov]<br />
<br />
Further reading: <br />
<br />
[http://www.sci.utah.edu/~csilva/papers/vis2003.pdf Visualizing Spatial and Temporal Variability in Coastal Observatories], W. Herrera-Jimenez, W. Correa, C. Silva, and A. Baptista, IEEE Visualization 2003.<br />
<br />
== 8/23: The visualization pipeline ==<br />
<br />
Lecturer: Claudio<br />
<br />
Topics: Procedural vs. Dataflow programming; Using Dataflow for the Vis Pipeline; Dataflow programming with VTK; Dataflow programming with VisTrails; python.<br />
<br />
Notes: [http://www.cs.utah.edu/~csilva/courses/cs5630/lec02-notes.pdf lec02-notes.pdf]<br />
<br />
Slides: [http://www.cs.utah.edu/~csilva/courses/cs5630/lec02.pdf lec02.pdf]<br />
<br />
VisTrails: During this class, we built a pipeline equivalent to the cone.tcl (see class slides). Here is the vistrails file: [http://www.cs.utah.edu/~csilva/courses/cs5630/cone.vt cone.vt]<br />
<br />
Further reading: <br />
<br />
[http://www.cs.utah.edu/~csilva/courses/cs5630/reproducible_vis.pdf Provenance for Visualizations: Reproducibility and Beyond], C. Silva, J. Freire, and S. Callahan, IEEE Computing in Science and Engineering, to appear.<br />
<br />
== 8/28: Modeling Data for Visualization ==<br />
<br />
Lecturer: Carlos<br />
<br />
Topics: Discrete vs continous data; Sampling and interpolation; Point vs triangulated data; Meshing data types; Regular vs irregular data; Tabular data; Vector and tensor fields<br />
<br />
Notes: TBA<br />
<br />
Slides: [http://www.sci.utah.edu/~cscheid/scivis_fall07/modelling_1.ppt .ppt file]<br />
<br />
Further reading: <br />
<br />
There is no required reading for this lecture. The notes will be available shortly. The following papers are there for people that are looking to get more advanced material that will not be covered in class.<br />
<br />
=== Interpolation ===<br />
<br />
[http://lmi.bwh.harvard.edu/papers/papers/geodesic-loxodromes-final.html Geodesic-loxodromes...] This is the fancy interpolation for diffusion tensors I mentioned in class.<br />
<br />
[http://en.wikipedia.org/wiki/Bernstein_polynomial Bernstein polynomials] These are the polynomials used for cubic Bezier curves that I mentioned in class.<br />
<br />
==== Separability ====<br />
<br />
[http://portal.acm.org/citation.cfm?id=1187793 Extensions of the Zwart-Powell Box spline...] This is a recent paper that shows a class of trivariate reconstruction techniques that are ''not'' separable.<br />
<br />
==== Tensors ====<br />
<br />
[http://www.cs.utah.edu/research/techreports/2004/pdf/UUCS-04-014.pdf Visualization and Analysis of Diffusion Tensor Fields] Gordon Kindlmann's PhD. thesis, with everything you ever wanted to know about DTI. Section 2.1 has a good primer in tensor algebra.<br />
<br />
== 8/30: Modeling Data for Visualization == <br />
<br />
Lecturer: Carlos<br />
<br />
Topics: Geometry Processing: Reconstruction and meshing; Simplification; Smoothing; Other Filtering algorithms<br />
<br />
Notes: [http://www.sci.utah.edu/~cscheid/scivis_fall07/week2.pdf .pdf file]. If you want to print these, you might want to wait for a week or two, until I finish polishing them.<br />
<br />
Slides: [http://www.sci.utah.edu/~cscheid/scivis_fall07/processing.ppt .ppt file] ''These slides include simplificatin algorithms, which I'll talk about next week.''<br />
<br />
== 9/4: Elementary Plotting Techniques == <br />
<br />
Lecturer: Steve<br />
<br />
Topics: Principles of Graph Construction<br />
<br />
Notes: [http://www.sci.utah.edu/~stevec/classes/cs5630/PlottingNotes.pdf PlottingNotes.pdf]<br />
<br />
Slides: [http://www.sci.utah.edu/~stevec/slides/SciVis/Plotting1.pdf Plotting1.pdf]<br />
<br />
Vistrails: See next lecture.<br />
<br />
Further Reading: There is no required reading for this lecture. For those interested in more depth, the following books are very useful:<br />
<br />
* The Elements of Graphing Data. William S. Cleveland, Hobart Press, 2nd Edition, 1994.<br />
* Visualizing Data. William S. Cleveland, Hobart Press, 1993.<br />
* The Visual Display of Quantitative Information. Edward R. Tufte, Graphics Press, 2001.<br />
* Visual Explanations: Images and Quantities, Evidence and Narrative. Edward R. Tufte, Graphics Press, 2997.<br />
<br />
== 9/6: Elementary Plotting Techniques ==<br />
<br />
Lecturer: Steve<br />
<br />
Topics: Simple Plotting Methods: Dot Plots, Connected Symbol Plots, Scatter Plots, Histograms, Others. Advanced Plotting Methods: Multimodal, Higher Dimensional, Correlation, Uncertainty and Variation.<br />
<br />
Notes: [http://www.sci.utah.edu/~stevec/classes/cs5630/PlottingNotes.pdf PlottingNotes.pdf]<br />
<br />
Slides: [http://www.sci.utah.edu/~stevec/slides/SciVis/Plotting2.pdf Plotting2.pdf]<br />
<br />
Vistrails: [http://www.sci.utah.edu/~stevec/classes/cs5630/PlottingVistrails.zip PlottingVistrails.zip] - Unzip this file in the examples directory of your VisTrails installation and it will add the vistrails along with their data sets (in the data directory). If you don't have permission to write to this directory (CADE users), then unzip the file where you want. Just be aware that in this case the paths for the data files may not be correct for most vistrails and will need to be fixed before they will execute properly.<br />
<br />
<br />
Further Reading: There is no required reading for this lecture. Some articles of interest:<br />
<br />
* [http://www.fmrib.ox.ac.uk/analysis/techrep/tr00mj2/tr00mj2/node24.html Histogram Bin Size]<br />
* [http://en.wikipedia.org/wiki/Correlation Correlation]<br />
* [http://en.wikipedia.org/wiki/Linear_regression Linear Regression]<br />
* [http://en.wikipedia.org/wiki/Box_plot Box Plots]<br />
<br />
== 9/11: Color and Human Perception ==<br />
<br />
Lecturer: Claudio<br />
<br />
Topics: Human vision system; Optical illusions<br />
<br />
Notes: TBA<br />
<br />
Slides: [http://www.cs.utah.edu/~csilva/courses/cs5630/human-vision.pdf human-vision.pdf]<br />
<br />
Links:<br />
<br />
http://en.wikipedia.org/wiki/Eye<br />
<br />
http://www.grand-illusions.com/gregory2.htm (also, see the related book: [http://www.amazon.com/Eye-Brain-Richard-L-Gregory/dp/0691048371])<br />
<br />
http://en.wikipedia.org/wiki/Purkinje_effect<br />
<br />
http://www.handprint.com/HP/WCL/color2.html<br />
<br />
== 9/13: Color and Human Perception ==<br />
<br />
Lecturer: Claudio<br />
<br />
Topics: Color Science; Color spaces; Color Blindness; Color maps; Tone mapping<br />
<br />
Notes: TBA<br />
<br />
Slides: [http://www.cs.utah.edu/~csilva/courses/cs5630/colorvision.pdf colorvision.pdf]<br />
<br />
Links:<br />
<br />
Further reading: <br />
<br />
[http://www.research.ibm.com/dx/proceedings/pravda/truevis.htm How Not to Lie with Visualization]<br />
<br />
http://en.wikipedia.org/wiki/Opponent_process<br />
<br />
http://en.wikipedia.org/wiki/Color_models<br />
<br />
http://en.wikipedia.org/wiki/Absolute_color_space<br />
<br />
http://en.wikipedia.org/wiki/Additive_color<br />
<br />
http://en.wikipedia.org/wiki/Subtractive_color<br />
<br />
http://en.wikipedia.org/wiki/RGB_color_model<br />
<br />
http://en.wikipedia.org/wiki/SRGB_color_space<br />
<br />
http://en.wikipedia.org/wiki/CIE_XYZ_color_space<br />
<br />
== 9/18 (a): Color and Human Perception ==<br />
<br />
Lecturer: Claudio<br />
<br />
Same material as previous lecture. <br />
<br />
== 9/18 (b): 2D Visualization Techniques ==<br />
<br />
Lecturer: Carlos<br />
<br />
Topics: 2-D contours, marching quads, marching tris; Color mapping; height fields; NPR<br />
<br />
Slides: [http://www.sci.utah.edu/~cscheid/scivis_fall07/2d_scalar_vis.pdf pdf file]<br />
<br />
Notes: [http://www.sci.utah.edu/~cscheid/scivis_fall07/2d_scalar_vis_notes.pdf pdf file]<br />
<br />
Vistrails: [http://www.sci.utah.edu/~cscheid/scivis_fall07/ozone_and_data.zip zip file with ozone.vt and data] [http://www.sci.utah.edu/~cscheid/scivis_fall07/asymptotic_decider.vt asymptotic decider in 2d] [http://www.sci.utah.edu/~cscheid/scivis_fall07/elevation.zip heightfields]<br />
<br />
Note: These vistrails use relative file paths so you don't need to change each of them individually to match your directory structure. Simply unzip the file to whichever location is more convenient. Then, inside VisTrails, open the VisTrails shell, type:<br />
<br />
import os<br />
os.chdir("c:/directory/where/you/unzipped/it")<br />
<br />
This will change the directory so you should be able to just run the pipelines.<br />
<br />
== 9/20: Math refresher ==<br />
<br />
Lecturer: Carlos<br />
<br />
Topics: Basic linear algebra; vectors; basic differential geometry (space curves, tangents, normals, surfaces); basic vector calculus (gradient, divergence, curl, gauss' theorem, green's theorem) <br />
<br />
== 9/25: 2D Visualization Techniques ==<br />
<br />
Lecturer: Carlos<br />
<br />
Topics: 2-D vector fields, div, grad, curl in 2D; Steady vs Unsteady flows; Glyphs; 2-D streamlines, streaklines, pathlines<br />
<br />
Slides: [http://www.sci.utah.edu/~cscheid/scivis_fall07/2d_vector_vis.pdf pdf file]<br />
<br />
Notes: coming soon<br />
<br />
Vistrails: [http://www.sci.utah.edu/~cscheid/scivis_fall07/vector_vis_1.zip vistrail with steady vector field vis and data] [http://www.sci.utah.edu/~cscheid/scivis_fall07/unsteady.zip vistrail with unsteady vector field vis and data] '''Note:''' Because VTK does not support time-varying datasets directly, we had to create a reasonably ugly hack to simulate unsteady fields. This means the datasets are quite big (80MB in total).<br />
<br />
== 9/27 (a): 2D Visualization Techniques ==<br />
<br />
Lecturer Carlos<br />
<br />
Same material as last lecture.<br />
<br />
== 9/27 (b): Volume Vis ==<br />
<br />
Lecturer: Claudio<br />
<br />
Topics: Slicing; Contours; Marching algorithms<br />
<br />
Slides: [http://www.cs.utah.edu/~csilva/courses/cs5630/iso-basic.pdf iso-basic.pdf]<br />
<br />
References:<br />
<br />
[http://portal.acm.org/citation.cfm?id=37401.37422 Marching cubes: A high resolution 3D surface construction algorithm]<br />
<br />
[http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=175782 The asymptotic decider: resolving the ambiguity in marching cubes]<br />
<br />
== 10/2: Volume Vis == <br />
<br />
Lecturer: Claudio<br />
<br />
Topics: Accelerating structures; High-quality contours<br />
<br />
Slides: <br />
<br />
[http://www.cs.utah.edu/~csilva/courses/cs5630/iso-speed.pdf iso-speed.pdf]<br />
<br />
[http://www.cs.utah.edu/~csilva/courses/cs5630/iso-speed-2.pdf iso-speed-2.pdf]<br />
<br />
References:<br />
<br />
[http://doi.ieeecomputersociety.org/10.1109/2945.489388 A Near Optimal Isosurface Extraction Algorithm Using the Span Space]<br />
<br />
[http://doi.ieeecomputersociety.org/10.1109/2945.485619 Automatic Isosurface Propagation Using an Extrema Graph and Sorted Boundary Cell Lists]<br />
<br />
[http://doi.ieeecomputersociety.org/10.1109/2945.597798 Speeding Up Isosurface Extraction Using Interval Trees]<br />
<br />
[http://doi.ieeecomputersociety.org/10.1109/SVVG.2004.5 Implicit Occluders]<br />
<br />
== 10/4: Volume Vis ==<br />
<br />
Lecturer: Claudio<br />
<br />
Topics: High quality isosurfaces<br />
<br />
Slides: [http://www.cs.utah.edu/~csilva/courses/cs5630/iso-quality.pdf iso-quality.pdf]<br />
<br />
References:<br />
<br />
[http://www.cs.utah.edu/~csilva/2007-sub/macet.pdf Edge Transformations for Improving Mesh Quality of Marching Cubes]<br />
<br />
[http://www.sci.utah.edu/~csilva/papers/tvcg2006acr.pdf High-Quality Extraction of Isosurfaces from Regular and Irregular Grids]<br />
<br />
[http://portal.acm.org/citation.cfm?id=566570.566586 Dual contouring of hermite data]<br />
<br />
[http://www.sci.utah.edu/%7Emiriah/research/meshing/vis07meyer.pdf Topology, Accuracy, and Quality of Isosurface Meshes Using Dynamic Particles]<br />
<br />
[http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=1260744 Material interface reconstruction]<br />
<br />
== 10/9: Fall break == <br />
<br />
== 10/11: Fall break == <br />
<br />
== 10/16: Volume Vis ==<br />
<br />
Lecturer: Claudio<br />
<br />
Topics: continued from last class<br />
<br />
== 10/18: Direct Volume Rendering ==<br />
<br />
Lecturer: Steve<br />
<br />
Topics: Introduction to volume rendering<br />
<br />
Slides: [http://www.sci.utah.edu/~stevec/classes/cs5630/VolumeRendering1.pdf VolumeRendering1.pdf]<br />
<br />
Notes: [http://www.sci.utah.edu/~stevec/classes/cs5630/dvr.pdf dvr.pdf]<br />
<br />
vistrails: to appear<br />
<br />
References:<br />
[http://www.llnl.gov/graphics/docs/OpticalModelsLong.pdf Optical Models for Direct Volume Rendering]<br />
<br />
== 10/23: Midterm 1 ==<br />
<br />
== 10/25: Direct Volume Rendering ==<br />
<br />
Lecturer: Steve<br />
<br />
Topics: Structured grid techniques: ray-casting, splatting, texture slicing, shear-warp<br />
<br />
Slides: [http://www.sci.utah.edu/~stevec/classes/cs5630/VolumeRendering2.pdf VolumeRendering2.pdf]<br />
<br />
Notes: same as previous class<br />
<br />
vistrails: same as previous class<br />
<br />
References:<br />
<br />
[http://graphics.stanford.edu/papers/volume-cga88/ Display of Surfaces from Volume Data] - Ray casting paper<br />
<br />
[http://portal.acm.org/citation.cfm?id=329138 Interactive Volume Rendering] - Splatting paper, paper requires ACM digital library access<br />
<br />
[http://portal.acm.org/citation.cfm?id=197972&dl=ACM&coll=GUIDE Accelerated volume rendering and tomographic reconstruction using texture mapping hardware] - Texture slicing paper, requires ACM digital library access<br />
<br />
[http://graphics.stanford.edu/papers/shear/ Fast Volume Rendering Using a Shear-Warp Factorization of the Viewing Transformation] - Shear-warp paper<br />
<br />
== 10/30: Cosmology and EEG analysis ==<br />
<br />
Guest lecture: Erik Anderson<br />
<br />
== 11/1: Simplification Techniques == <br />
<br />
Guest lecture: Yuan Zhou<br />
<br />
== 11/6: Vector and Tensor Visualization ==<br />
<br />
Lecturer: Claudio<br />
<br />
Topics: LIC; hyper LIC; Topology-based techniques<br />
<br />
== 11/8: Vector and Tensor Vis ==<br />
<br />
Lecturer: Carlos<br />
<br />
Topics: Glyphs; DTI techniques<br />
<br />
== 11/13: Aesthetic Issues in Vis ==<br />
<br />
Lecturer: Claudio<br />
<br />
Topics: Volume Illustration and NPR<br />
<br />
== 11/15: Aesthetic Issues in Vis ==<br />
<br />
Lecturer: Steve<br />
<br />
Topics: Tufte<br />
<br />
== 11/20: Aesthetic Issues in Vis ==<br />
<br />
Lecturer: Steve<br />
<br />
Topics: Tufte<br />
<br />
== 11/22: Thanksgiving == <br />
<br />
== 11/27: Information Visualization ==<br />
<br />
Lecturer: Carlos<br />
<br />
Topics: Parallel coordinates; Graph visualization<br />
<br />
== 11/29: Information Visualization ==<br />
<br />
Lecturer: Claudio<br />
<br />
Topics: Hierarchical data vis; brushing; sizing text<br />
<br />
== 12/4: Data Management for Vis ==<br />
<br />
== 12/6: Vis for presentation/discovery ==<br />
<br />
== 12/11: Open research questions ==</div>Thu, 25 Oct 2007 21:34:44 GMTStevechttps://www.vistrails.org//index.php/Talk:SciVisFall2007/ScheduleSciVisFall2007/Schedule
https://www.vistrails.org//index.php?title=SciVisFall2007/Schedule&diff=862
https://www.vistrails.org//index.php?title=SciVisFall2007/Schedule&diff=862<p>Stevec: /* 10/18: Volume Vis */</p>
<hr />
<div>== 8/21: Introduction to visualization ==<br />
<br />
Lecturer: Claudio<br />
<br />
Topics: Scientific Visualization<br />
<br />
Notes: [http://www.cs.utah.edu/~csilva/courses/cs5630/lec01-notes.pdf lec01-notes.pdf]<br />
<br />
Slides: [http://www.cs.utah.edu/~csilva/courses/cs5630/lec01.pdf lec01.pdf]<br />
<br />
Animations: [http://www.cs.utah.edu/~csilva/courses/cs5630/explosion_640x480-5.mov explosion_640x480-5.mov], [http://www.cs.utah.edu/~csilva/courses/cs5630/fig7.mov fig7.mov], [http://www.cs.utah.edu/~csilva/courses/cs5630/fig8.mov fig8.mov], [http://www.cs.utah.edu/~csilva/courses/cs5630/fig9.mov fig9.mov], [http://www.cs.utah.edu/~csilva/courses/cs5630/SevereTstorm.mov SevereTstorm.mov]<br />
<br />
Further reading: <br />
<br />
[http://www.sci.utah.edu/~csilva/papers/vis2003.pdf Visualizing Spatial and Temporal Variability in Coastal Observatories], W. Herrera-Jimenez, W. Correa, C. Silva, and A. Baptista, IEEE Visualization 2003.<br />
<br />
== 8/23: The visualization pipeline ==<br />
<br />
Lecturer: Claudio<br />
<br />
Topics: Procedural vs. Dataflow programming; Using Dataflow for the Vis Pipeline; Dataflow programming with VTK; Dataflow programming with VisTrails; python.<br />
<br />
Notes: [http://www.cs.utah.edu/~csilva/courses/cs5630/lec02-notes.pdf lec02-notes.pdf]<br />
<br />
Slides: [http://www.cs.utah.edu/~csilva/courses/cs5630/lec02.pdf lec02.pdf]<br />
<br />
VisTrails: During this class, we built a pipeline equivalent to the cone.tcl (see class slides). Here is the vistrails file: [http://www.cs.utah.edu/~csilva/courses/cs5630/cone.vt cone.vt]<br />
<br />
Further reading: <br />
<br />
[http://www.cs.utah.edu/~csilva/courses/cs5630/reproducible_vis.pdf Provenance for Visualizations: Reproducibility and Beyond], C. Silva, J. Freire, and S. Callahan, IEEE Computing in Science and Engineering, to appear.<br />
<br />
== 8/28: Modeling Data for Visualization ==<br />
<br />
Lecturer: Carlos<br />
<br />
Topics: Discrete vs continous data; Sampling and interpolation; Point vs triangulated data; Meshing data types; Regular vs irregular data; Tabular data; Vector and tensor fields<br />
<br />
Notes: TBA<br />
<br />
Slides: [http://www.sci.utah.edu/~cscheid/scivis_fall07/modelling_1.ppt .ppt file]<br />
<br />
Further reading: <br />
<br />
There is no required reading for this lecture. The notes will be available shortly. The following papers are there for people that are looking to get more advanced material that will not be covered in class.<br />
<br />
=== Interpolation ===<br />
<br />
[http://lmi.bwh.harvard.edu/papers/papers/geodesic-loxodromes-final.html Geodesic-loxodromes...] This is the fancy interpolation for diffusion tensors I mentioned in class.<br />
<br />
[http://en.wikipedia.org/wiki/Bernstein_polynomial Bernstein polynomials] These are the polynomials used for cubic Bezier curves that I mentioned in class.<br />
<br />
==== Separability ====<br />
<br />
[http://portal.acm.org/citation.cfm?id=1187793 Extensions of the Zwart-Powell Box spline...] This is a recent paper that shows a class of trivariate reconstruction techniques that are ''not'' separable.<br />
<br />
==== Tensors ====<br />
<br />
[http://www.cs.utah.edu/research/techreports/2004/pdf/UUCS-04-014.pdf Visualization and Analysis of Diffusion Tensor Fields] Gordon Kindlmann's PhD. thesis, with everything you ever wanted to know about DTI. Section 2.1 has a good primer in tensor algebra.<br />
<br />
== 8/30: Modeling Data for Visualization == <br />
<br />
Lecturer: Carlos<br />
<br />
Topics: Geometry Processing: Reconstruction and meshing; Simplification; Smoothing; Other Filtering algorithms<br />
<br />
Notes: [http://www.sci.utah.edu/~cscheid/scivis_fall07/week2.pdf .pdf file]. If you want to print these, you might want to wait for a week or two, until I finish polishing them.<br />
<br />
Slides: [http://www.sci.utah.edu/~cscheid/scivis_fall07/processing.ppt .ppt file] ''These slides include simplificatin algorithms, which I'll talk about next week.''<br />
<br />
== 9/4: Elementary Plotting Techniques == <br />
<br />
Lecturer: Steve<br />
<br />
Topics: Principles of Graph Construction<br />
<br />
Notes: [http://www.sci.utah.edu/~stevec/classes/cs5630/PlottingNotes.pdf PlottingNotes.pdf]<br />
<br />
Slides: [http://www.sci.utah.edu/~stevec/slides/SciVis/Plotting1.pdf Plotting1.pdf]<br />
<br />
Vistrails: See next lecture.<br />
<br />
Further Reading: There is no required reading for this lecture. For those interested in more depth, the following books are very useful:<br />
<br />
* The Elements of Graphing Data. William S. Cleveland, Hobart Press, 2nd Edition, 1994.<br />
* Visualizing Data. William S. Cleveland, Hobart Press, 1993.<br />
* The Visual Display of Quantitative Information. Edward R. Tufte, Graphics Press, 2001.<br />
* Visual Explanations: Images and Quantities, Evidence and Narrative. Edward R. Tufte, Graphics Press, 2997.<br />
<br />
== 9/6: Elementary Plotting Techniques ==<br />
<br />
Lecturer: Steve<br />
<br />
Topics: Simple Plotting Methods: Dot Plots, Connected Symbol Plots, Scatter Plots, Histograms, Others. Advanced Plotting Methods: Multimodal, Higher Dimensional, Correlation, Uncertainty and Variation.<br />
<br />
Notes: [http://www.sci.utah.edu/~stevec/classes/cs5630/PlottingNotes.pdf PlottingNotes.pdf]<br />
<br />
Slides: [http://www.sci.utah.edu/~stevec/slides/SciVis/Plotting2.pdf Plotting2.pdf]<br />
<br />
Vistrails: [http://www.sci.utah.edu/~stevec/classes/cs5630/PlottingVistrails.zip PlottingVistrails.zip] - Unzip this file in the examples directory of your VisTrails installation and it will add the vistrails along with their data sets (in the data directory). If you don't have permission to write to this directory (CADE users), then unzip the file where you want. Just be aware that in this case the paths for the data files may not be correct for most vistrails and will need to be fixed before they will execute properly.<br />
<br />
<br />
Further Reading: There is no required reading for this lecture. Some articles of interest:<br />
<br />
* [http://www.fmrib.ox.ac.uk/analysis/techrep/tr00mj2/tr00mj2/node24.html Histogram Bin Size]<br />
* [http://en.wikipedia.org/wiki/Correlation Correlation]<br />
* [http://en.wikipedia.org/wiki/Linear_regression Linear Regression]<br />
* [http://en.wikipedia.org/wiki/Box_plot Box Plots]<br />
<br />
== 9/11: Color and Human Perception ==<br />
<br />
Lecturer: Claudio<br />
<br />
Topics: Human vision system; Optical illusions<br />
<br />
Notes: TBA<br />
<br />
Slides: [http://www.cs.utah.edu/~csilva/courses/cs5630/human-vision.pdf human-vision.pdf]<br />
<br />
Links:<br />
<br />
http://en.wikipedia.org/wiki/Eye<br />
<br />
http://www.grand-illusions.com/gregory2.htm (also, see the related book: [http://www.amazon.com/Eye-Brain-Richard-L-Gregory/dp/0691048371])<br />
<br />
http://en.wikipedia.org/wiki/Purkinje_effect<br />
<br />
http://www.handprint.com/HP/WCL/color2.html<br />
<br />
== 9/13: Color and Human Perception ==<br />
<br />
Lecturer: Claudio<br />
<br />
Topics: Color Science; Color spaces; Color Blindness; Color maps; Tone mapping<br />
<br />
Notes: TBA<br />
<br />
Slides: [http://www.cs.utah.edu/~csilva/courses/cs5630/colorvision.pdf colorvision.pdf]<br />
<br />
Links:<br />
<br />
Further reading: <br />
<br />
[http://www.research.ibm.com/dx/proceedings/pravda/truevis.htm How Not to Lie with Visualization]<br />
<br />
http://en.wikipedia.org/wiki/Opponent_process<br />
<br />
http://en.wikipedia.org/wiki/Color_models<br />
<br />
http://en.wikipedia.org/wiki/Absolute_color_space<br />
<br />
http://en.wikipedia.org/wiki/Additive_color<br />
<br />
http://en.wikipedia.org/wiki/Subtractive_color<br />
<br />
http://en.wikipedia.org/wiki/RGB_color_model<br />
<br />
http://en.wikipedia.org/wiki/SRGB_color_space<br />
<br />
http://en.wikipedia.org/wiki/CIE_XYZ_color_space<br />
<br />
== 9/18 (a): Color and Human Perception ==<br />
<br />
Lecturer: Claudio<br />
<br />
Same material as previous lecture. <br />
<br />
== 9/18 (b): 2D Visualization Techniques ==<br />
<br />
Lecturer: Carlos<br />
<br />
Topics: 2-D contours, marching quads, marching tris; Color mapping; height fields; NPR<br />
<br />
Slides: [http://www.sci.utah.edu/~cscheid/scivis_fall07/2d_scalar_vis.pdf pdf file]<br />
<br />
Notes: [http://www.sci.utah.edu/~cscheid/scivis_fall07/2d_scalar_vis_notes.pdf pdf file]<br />
<br />
Vistrails: [http://www.sci.utah.edu/~cscheid/scivis_fall07/ozone_and_data.zip zip file with ozone.vt and data] [http://www.sci.utah.edu/~cscheid/scivis_fall07/asymptotic_decider.vt asymptotic decider in 2d] [http://www.sci.utah.edu/~cscheid/scivis_fall07/elevation.zip heightfields]<br />
<br />
Note: These vistrails use relative file paths so you don't need to change each of them individually to match your directory structure. Simply unzip the file to whichever location is more convenient. Then, inside VisTrails, open the VisTrails shell, type:<br />
<br />
import os<br />
os.chdir("c:/directory/where/you/unzipped/it")<br />
<br />
This will change the directory so you should be able to just run the pipelines.<br />
<br />
== 9/20: Math refresher ==<br />
<br />
Lecturer: Carlos<br />
<br />
Topics: Basic linear algebra; vectors; basic differential geometry (space curves, tangents, normals, surfaces); basic vector calculus (gradient, divergence, curl, gauss' theorem, green's theorem) <br />
<br />
== 9/25: 2D Visualization Techniques ==<br />
<br />
Lecturer: Carlos<br />
<br />
Topics: 2-D vector fields, div, grad, curl in 2D; Steady vs Unsteady flows; Glyphs; 2-D streamlines, streaklines, pathlines<br />
<br />
Slides: [http://www.sci.utah.edu/~cscheid/scivis_fall07/2d_vector_vis.pdf pdf file]<br />
<br />
Notes: coming soon<br />
<br />
Vistrails: [http://www.sci.utah.edu/~cscheid/scivis_fall07/vector_vis_1.zip vistrail with steady vector field vis and data] [http://www.sci.utah.edu/~cscheid/scivis_fall07/unsteady.zip vistrail with unsteady vector field vis and data] '''Note:''' Because VTK does not support time-varying datasets directly, we had to create a reasonably ugly hack to simulate unsteady fields. This means the datasets are quite big (80MB in total).<br />
<br />
== 9/27 (a): 2D Visualization Techniques ==<br />
<br />
Lecturer Carlos<br />
<br />
Same material as last lecture.<br />
<br />
== 9/27 (b): Volume Vis ==<br />
<br />
Lecturer: Claudio<br />
<br />
Topics: Slicing; Contours; Marching algorithms<br />
<br />
Slides: [http://www.cs.utah.edu/~csilva/courses/cs5630/iso-basic.pdf iso-basic.pdf]<br />
<br />
References:<br />
<br />
[http://portal.acm.org/citation.cfm?id=37401.37422 Marching cubes: A high resolution 3D surface construction algorithm]<br />
<br />
[http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=175782 The asymptotic decider: resolving the ambiguity in marching cubes]<br />
<br />
== 10/2: Volume Vis == <br />
<br />
Lecturer: Claudio<br />
<br />
Topics: Accelerating structures; High-quality contours<br />
<br />
Slides: <br />
<br />
[http://www.cs.utah.edu/~csilva/courses/cs5630/iso-speed.pdf iso-speed.pdf]<br />
<br />
[http://www.cs.utah.edu/~csilva/courses/cs5630/iso-speed-2.pdf iso-speed-2.pdf]<br />
<br />
References:<br />
<br />
[http://doi.ieeecomputersociety.org/10.1109/2945.489388 A Near Optimal Isosurface Extraction Algorithm Using the Span Space]<br />
<br />
[http://doi.ieeecomputersociety.org/10.1109/2945.485619 Automatic Isosurface Propagation Using an Extrema Graph and Sorted Boundary Cell Lists]<br />
<br />
[http://doi.ieeecomputersociety.org/10.1109/2945.597798 Speeding Up Isosurface Extraction Using Interval Trees]<br />
<br />
[http://doi.ieeecomputersociety.org/10.1109/SVVG.2004.5 Implicit Occluders]<br />
<br />
== 10/4: Volume Vis ==<br />
<br />
Lecturer: Claudio<br />
<br />
Topics: High quality isosurfaces<br />
<br />
Slides: [http://www.cs.utah.edu/~csilva/courses/cs5630/iso-quality.pdf iso-quality.pdf]<br />
<br />
References:<br />
<br />
[http://www.cs.utah.edu/~csilva/2007-sub/macet.pdf Edge Transformations for Improving Mesh Quality of Marching Cubes]<br />
<br />
[http://www.sci.utah.edu/~csilva/papers/tvcg2006acr.pdf High-Quality Extraction of Isosurfaces from Regular and Irregular Grids]<br />
<br />
[http://portal.acm.org/citation.cfm?id=566570.566586 Dual contouring of hermite data]<br />
<br />
[http://www.sci.utah.edu/%7Emiriah/research/meshing/vis07meyer.pdf Topology, Accuracy, and Quality of Isosurface Meshes Using Dynamic Particles]<br />
<br />
[http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=1260744 Material interface reconstruction]<br />
<br />
== 10/9: Fall break == <br />
<br />
== 10/11: Fall break == <br />
<br />
== 10/16: Volume Vis ==<br />
<br />
Lecturer: Claudio<br />
<br />
Topics: continued from last class<br />
<br />
== 10/18: Direct Volume Rendering ==<br />
<br />
Lecturer: Steve<br />
<br />
Topics: Introduction to volume rendering<br />
<br />
Slides: [http://www.sci.utah.edu/~stevec/classes/cs5630/VolumeRendering1.pdf VolumeRendering1.pdf]<br />
<br />
Notes: [http://www.sci.utah.edu/~stevec/classes/cs5630/dvr.pdf dvr.pdf]<br />
<br />
vistrails: to appear<br />
<br />
References:<br />
[http://www.llnl.gov/graphics/docs/OpticalModelsLong.pdf Optical Models for Direct Volume Rendering]<br />
<br />
== 10/23: Midterm 1 ==<br />
<br />
== 10/25: Direct Volume Rendering ==<br />
<br />
Lecturer: Steve<br />
<br />
Topics: Structured grid techniques: ray-casting, splatting, texture slicing, shear-warp<br />
<br />
Slides: [http://www.sci.utah.edu/~stevec/classes/cs5630/VolumeRendering2.pdf VolumeRendering2.pdf]<br />
<br />
Notes: same as previous class<br />
<br />
vistrails: same as previous class<br />
<br />
References:<br />
<br />
[http://graphics.stanford.edu/papers/volume-cga88/ Display of Surfaces from Volume Data] - Ray casting paper<br />
<br />
[http://portal.acm.org/citation.cfm?id=329138 Interactive Volume Rendering] - Splatting paper, paper requires ACM digital library access<br />
<br />
[http://portal.acm.org/citation.cfm?id=197972&dl=ACM&coll=GUIDE Accelerated volume rendering and tomographic reconstruction using texture mapping hardware] - Texture slicing paper, requires ACM digital library access<br />
<br />
[http://graphics.stanford.edu/papers/shear/ Fast Volume Rendering Using a Shear-Warp Factorization of the Viewing Transformation] - Shear-warp paper<br />
<br />
== 10/30: Vector and Tensor Visualization ==<br />
<br />
Lecturer: Claudio<br />
<br />
Topics: LIC; hyper LIC; Topology-based techniques<br />
<br />
== 11/1: Simplification Techniques == <br />
<br />
Guest lecture: Yuan Zhou<br />
<br />
== 11/6: Cosmology and EEG analysis ==<br />
<br />
Guest lecture: Erik Anderson<br />
<br />
== 11/8: Vector and Tensor Vis ==<br />
<br />
Lecturer: Carlos<br />
<br />
Topics: Glyphs; DTI techniques<br />
<br />
== 11/13: Aesthetic Issues in Vis ==<br />
<br />
Lecturer: Claudio<br />
<br />
Topics: Volume Illustration and NPR<br />
<br />
== 11/15: Aesthetic Issues in Vis ==<br />
<br />
Lecturer: Steve<br />
<br />
Topics: Tufte<br />
<br />
== 11/20: Aesthetic Issues in Vis ==<br />
<br />
Lecturer: Steve<br />
<br />
Topics: Tufte<br />
<br />
== 11/22: Thanksgiving == <br />
<br />
== 11/27: Information Visualization ==<br />
<br />
Lecturer: Carlos<br />
<br />
Topics: Parallel coordinates; Graph visualization<br />
<br />
== 11/29: Information Visualization ==<br />
<br />
Lecturer: Claudio<br />
<br />
Topics: Hierarchical data vis; brushing; sizing text<br />
<br />
== 12/4: Data Management for Vis ==<br />
<br />
== 12/6: Vis for presentation/discovery ==<br />
<br />
== 12/11: Open research questions ==</div>Thu, 25 Oct 2007 21:31:53 GMTStevechttps://www.vistrails.org//index.php/Talk:SciVisFall2007/ScheduleSciVisFall2007/Schedule
https://www.vistrails.org//index.php?title=SciVisFall2007/Schedule&diff=861
https://www.vistrails.org//index.php?title=SciVisFall2007/Schedule&diff=861<p>Stevec: /* 10/25: Vector and Tensor Visualization */</p>
<hr />
<div>== 8/21: Introduction to visualization ==<br />
<br />
Lecturer: Claudio<br />
<br />
Topics: Scientific Visualization<br />
<br />
Notes: [http://www.cs.utah.edu/~csilva/courses/cs5630/lec01-notes.pdf lec01-notes.pdf]<br />
<br />
Slides: [http://www.cs.utah.edu/~csilva/courses/cs5630/lec01.pdf lec01.pdf]<br />
<br />
Animations: [http://www.cs.utah.edu/~csilva/courses/cs5630/explosion_640x480-5.mov explosion_640x480-5.mov], [http://www.cs.utah.edu/~csilva/courses/cs5630/fig7.mov fig7.mov], [http://www.cs.utah.edu/~csilva/courses/cs5630/fig8.mov fig8.mov], [http://www.cs.utah.edu/~csilva/courses/cs5630/fig9.mov fig9.mov], [http://www.cs.utah.edu/~csilva/courses/cs5630/SevereTstorm.mov SevereTstorm.mov]<br />
<br />
Further reading: <br />
<br />
[http://www.sci.utah.edu/~csilva/papers/vis2003.pdf Visualizing Spatial and Temporal Variability in Coastal Observatories], W. Herrera-Jimenez, W. Correa, C. Silva, and A. Baptista, IEEE Visualization 2003.<br />
<br />
== 8/23: The visualization pipeline ==<br />
<br />
Lecturer: Claudio<br />
<br />
Topics: Procedural vs. Dataflow programming; Using Dataflow for the Vis Pipeline; Dataflow programming with VTK; Dataflow programming with VisTrails; python.<br />
<br />
Notes: [http://www.cs.utah.edu/~csilva/courses/cs5630/lec02-notes.pdf lec02-notes.pdf]<br />
<br />
Slides: [http://www.cs.utah.edu/~csilva/courses/cs5630/lec02.pdf lec02.pdf]<br />
<br />
VisTrails: During this class, we built a pipeline equivalent to the cone.tcl (see class slides). Here is the vistrails file: [http://www.cs.utah.edu/~csilva/courses/cs5630/cone.vt cone.vt]<br />
<br />
Further reading: <br />
<br />
[http://www.cs.utah.edu/~csilva/courses/cs5630/reproducible_vis.pdf Provenance for Visualizations: Reproducibility and Beyond], C. Silva, J. Freire, and S. Callahan, IEEE Computing in Science and Engineering, to appear.<br />
<br />
== 8/28: Modeling Data for Visualization ==<br />
<br />
Lecturer: Carlos<br />
<br />
Topics: Discrete vs continous data; Sampling and interpolation; Point vs triangulated data; Meshing data types; Regular vs irregular data; Tabular data; Vector and tensor fields<br />
<br />
Notes: TBA<br />
<br />
Slides: [http://www.sci.utah.edu/~cscheid/scivis_fall07/modelling_1.ppt .ppt file]<br />
<br />
Further reading: <br />
<br />
There is no required reading for this lecture. The notes will be available shortly. The following papers are there for people that are looking to get more advanced material that will not be covered in class.<br />
<br />
=== Interpolation ===<br />
<br />
[http://lmi.bwh.harvard.edu/papers/papers/geodesic-loxodromes-final.html Geodesic-loxodromes...] This is the fancy interpolation for diffusion tensors I mentioned in class.<br />
<br />
[http://en.wikipedia.org/wiki/Bernstein_polynomial Bernstein polynomials] These are the polynomials used for cubic Bezier curves that I mentioned in class.<br />
<br />
==== Separability ====<br />
<br />
[http://portal.acm.org/citation.cfm?id=1187793 Extensions of the Zwart-Powell Box spline...] This is a recent paper that shows a class of trivariate reconstruction techniques that are ''not'' separable.<br />
<br />
==== Tensors ====<br />
<br />
[http://www.cs.utah.edu/research/techreports/2004/pdf/UUCS-04-014.pdf Visualization and Analysis of Diffusion Tensor Fields] Gordon Kindlmann's PhD. thesis, with everything you ever wanted to know about DTI. Section 2.1 has a good primer in tensor algebra.<br />
<br />
== 8/30: Modeling Data for Visualization == <br />
<br />
Lecturer: Carlos<br />
<br />
Topics: Geometry Processing: Reconstruction and meshing; Simplification; Smoothing; Other Filtering algorithms<br />
<br />
Notes: [http://www.sci.utah.edu/~cscheid/scivis_fall07/week2.pdf .pdf file]. If you want to print these, you might want to wait for a week or two, until I finish polishing them.<br />
<br />
Slides: [http://www.sci.utah.edu/~cscheid/scivis_fall07/processing.ppt .ppt file] ''These slides include simplificatin algorithms, which I'll talk about next week.''<br />
<br />
== 9/4: Elementary Plotting Techniques == <br />
<br />
Lecturer: Steve<br />
<br />
Topics: Principles of Graph Construction<br />
<br />
Notes: [http://www.sci.utah.edu/~stevec/classes/cs5630/PlottingNotes.pdf PlottingNotes.pdf]<br />
<br />
Slides: [http://www.sci.utah.edu/~stevec/slides/SciVis/Plotting1.pdf Plotting1.pdf]<br />
<br />
Vistrails: See next lecture.<br />
<br />
Further Reading: There is no required reading for this lecture. For those interested in more depth, the following books are very useful:<br />
<br />
* The Elements of Graphing Data. William S. Cleveland, Hobart Press, 2nd Edition, 1994.<br />
* Visualizing Data. William S. Cleveland, Hobart Press, 1993.<br />
* The Visual Display of Quantitative Information. Edward R. Tufte, Graphics Press, 2001.<br />
* Visual Explanations: Images and Quantities, Evidence and Narrative. Edward R. Tufte, Graphics Press, 2997.<br />
<br />
== 9/6: Elementary Plotting Techniques ==<br />
<br />
Lecturer: Steve<br />
<br />
Topics: Simple Plotting Methods: Dot Plots, Connected Symbol Plots, Scatter Plots, Histograms, Others. Advanced Plotting Methods: Multimodal, Higher Dimensional, Correlation, Uncertainty and Variation.<br />
<br />
Notes: [http://www.sci.utah.edu/~stevec/classes/cs5630/PlottingNotes.pdf PlottingNotes.pdf]<br />
<br />
Slides: [http://www.sci.utah.edu/~stevec/slides/SciVis/Plotting2.pdf Plotting2.pdf]<br />
<br />
Vistrails: [http://www.sci.utah.edu/~stevec/classes/cs5630/PlottingVistrails.zip PlottingVistrails.zip] - Unzip this file in the examples directory of your VisTrails installation and it will add the vistrails along with their data sets (in the data directory). If you don't have permission to write to this directory (CADE users), then unzip the file where you want. Just be aware that in this case the paths for the data files may not be correct for most vistrails and will need to be fixed before they will execute properly.<br />
<br />
<br />
Further Reading: There is no required reading for this lecture. Some articles of interest:<br />
<br />
* [http://www.fmrib.ox.ac.uk/analysis/techrep/tr00mj2/tr00mj2/node24.html Histogram Bin Size]<br />
* [http://en.wikipedia.org/wiki/Correlation Correlation]<br />
* [http://en.wikipedia.org/wiki/Linear_regression Linear Regression]<br />
* [http://en.wikipedia.org/wiki/Box_plot Box Plots]<br />
<br />
== 9/11: Color and Human Perception ==<br />
<br />
Lecturer: Claudio<br />
<br />
Topics: Human vision system; Optical illusions<br />
<br />
Notes: TBA<br />
<br />
Slides: [http://www.cs.utah.edu/~csilva/courses/cs5630/human-vision.pdf human-vision.pdf]<br />
<br />
Links:<br />
<br />
http://en.wikipedia.org/wiki/Eye<br />
<br />
http://www.grand-illusions.com/gregory2.htm (also, see the related book: [http://www.amazon.com/Eye-Brain-Richard-L-Gregory/dp/0691048371])<br />
<br />
http://en.wikipedia.org/wiki/Purkinje_effect<br />
<br />
http://www.handprint.com/HP/WCL/color2.html<br />
<br />
== 9/13: Color and Human Perception ==<br />
<br />
Lecturer: Claudio<br />
<br />
Topics: Color Science; Color spaces; Color Blindness; Color maps; Tone mapping<br />
<br />
Notes: TBA<br />
<br />
Slides: [http://www.cs.utah.edu/~csilva/courses/cs5630/colorvision.pdf colorvision.pdf]<br />
<br />
Links:<br />
<br />
Further reading: <br />
<br />
[http://www.research.ibm.com/dx/proceedings/pravda/truevis.htm How Not to Lie with Visualization]<br />
<br />
http://en.wikipedia.org/wiki/Opponent_process<br />
<br />
http://en.wikipedia.org/wiki/Color_models<br />
<br />
http://en.wikipedia.org/wiki/Absolute_color_space<br />
<br />
http://en.wikipedia.org/wiki/Additive_color<br />
<br />
http://en.wikipedia.org/wiki/Subtractive_color<br />
<br />
http://en.wikipedia.org/wiki/RGB_color_model<br />
<br />
http://en.wikipedia.org/wiki/SRGB_color_space<br />
<br />
http://en.wikipedia.org/wiki/CIE_XYZ_color_space<br />
<br />
== 9/18 (a): Color and Human Perception ==<br />
<br />
Lecturer: Claudio<br />
<br />
Same material as previous lecture. <br />
<br />
== 9/18 (b): 2D Visualization Techniques ==<br />
<br />
Lecturer: Carlos<br />
<br />
Topics: 2-D contours, marching quads, marching tris; Color mapping; height fields; NPR<br />
<br />
Slides: [http://www.sci.utah.edu/~cscheid/scivis_fall07/2d_scalar_vis.pdf pdf file]<br />
<br />
Notes: [http://www.sci.utah.edu/~cscheid/scivis_fall07/2d_scalar_vis_notes.pdf pdf file]<br />
<br />
Vistrails: [http://www.sci.utah.edu/~cscheid/scivis_fall07/ozone_and_data.zip zip file with ozone.vt and data] [http://www.sci.utah.edu/~cscheid/scivis_fall07/asymptotic_decider.vt asymptotic decider in 2d] [http://www.sci.utah.edu/~cscheid/scivis_fall07/elevation.zip heightfields]<br />
<br />
Note: These vistrails use relative file paths so you don't need to change each of them individually to match your directory structure. Simply unzip the file to whichever location is more convenient. Then, inside VisTrails, open the VisTrails shell, type:<br />
<br />
import os<br />
os.chdir("c:/directory/where/you/unzipped/it")<br />
<br />
This will change the directory so you should be able to just run the pipelines.<br />
<br />
== 9/20: Math refresher ==<br />
<br />
Lecturer: Carlos<br />
<br />
Topics: Basic linear algebra; vectors; basic differential geometry (space curves, tangents, normals, surfaces); basic vector calculus (gradient, divergence, curl, gauss' theorem, green's theorem) <br />
<br />
== 9/25: 2D Visualization Techniques ==<br />
<br />
Lecturer: Carlos<br />
<br />
Topics: 2-D vector fields, div, grad, curl in 2D; Steady vs Unsteady flows; Glyphs; 2-D streamlines, streaklines, pathlines<br />
<br />
Slides: [http://www.sci.utah.edu/~cscheid/scivis_fall07/2d_vector_vis.pdf pdf file]<br />
<br />
Notes: coming soon<br />
<br />
Vistrails: [http://www.sci.utah.edu/~cscheid/scivis_fall07/vector_vis_1.zip vistrail with steady vector field vis and data] [http://www.sci.utah.edu/~cscheid/scivis_fall07/unsteady.zip vistrail with unsteady vector field vis and data] '''Note:''' Because VTK does not support time-varying datasets directly, we had to create a reasonably ugly hack to simulate unsteady fields. This means the datasets are quite big (80MB in total).<br />
<br />
== 9/27 (a): 2D Visualization Techniques ==<br />
<br />
Lecturer Carlos<br />
<br />
Same material as last lecture.<br />
<br />
== 9/27 (b): Volume Vis ==<br />
<br />
Lecturer: Claudio<br />
<br />
Topics: Slicing; Contours; Marching algorithms<br />
<br />
Slides: [http://www.cs.utah.edu/~csilva/courses/cs5630/iso-basic.pdf iso-basic.pdf]<br />
<br />
References:<br />
<br />
[http://portal.acm.org/citation.cfm?id=37401.37422 Marching cubes: A high resolution 3D surface construction algorithm]<br />
<br />
[http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=175782 The asymptotic decider: resolving the ambiguity in marching cubes]<br />
<br />
== 10/2: Volume Vis == <br />
<br />
Lecturer: Claudio<br />
<br />
Topics: Accelerating structures; High-quality contours<br />
<br />
Slides: <br />
<br />
[http://www.cs.utah.edu/~csilva/courses/cs5630/iso-speed.pdf iso-speed.pdf]<br />
<br />
[http://www.cs.utah.edu/~csilva/courses/cs5630/iso-speed-2.pdf iso-speed-2.pdf]<br />
<br />
References:<br />
<br />
[http://doi.ieeecomputersociety.org/10.1109/2945.489388 A Near Optimal Isosurface Extraction Algorithm Using the Span Space]<br />
<br />
[http://doi.ieeecomputersociety.org/10.1109/2945.485619 Automatic Isosurface Propagation Using an Extrema Graph and Sorted Boundary Cell Lists]<br />
<br />
[http://doi.ieeecomputersociety.org/10.1109/2945.597798 Speeding Up Isosurface Extraction Using Interval Trees]<br />
<br />
[http://doi.ieeecomputersociety.org/10.1109/SVVG.2004.5 Implicit Occluders]<br />
<br />
== 10/4: Volume Vis ==<br />
<br />
Lecturer: Claudio<br />
<br />
Topics: High quality isosurfaces<br />
<br />
Slides: [http://www.cs.utah.edu/~csilva/courses/cs5630/iso-quality.pdf iso-quality.pdf]<br />
<br />
References:<br />
<br />
[http://www.cs.utah.edu/~csilva/2007-sub/macet.pdf Edge Transformations for Improving Mesh Quality of Marching Cubes]<br />
<br />
[http://www.sci.utah.edu/~csilva/papers/tvcg2006acr.pdf High-Quality Extraction of Isosurfaces from Regular and Irregular Grids]<br />
<br />
[http://portal.acm.org/citation.cfm?id=566570.566586 Dual contouring of hermite data]<br />
<br />
[http://www.sci.utah.edu/%7Emiriah/research/meshing/vis07meyer.pdf Topology, Accuracy, and Quality of Isosurface Meshes Using Dynamic Particles]<br />
<br />
[http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=1260744 Material interface reconstruction]<br />
<br />
== 10/9: Fall break == <br />
<br />
== 10/11: Fall break == <br />
<br />
== 10/16: Volume Vis ==<br />
<br />
Lecturer: Claudio<br />
<br />
Topics: continued from last class<br />
<br />
== 10/18: Volume Vis ==<br />
<br />
Lecturer: Steve<br />
<br />
Topics: Introduction to volume rendering<br />
<br />
Slides: [http://www.sci.utah.edu/~stevec/classes/cs5630/VolumeRendering1.pdf VolumeRendering1.pdf]<br />
<br />
Notes: [http://www.sci.utah.edu/~stevec/classes/cs5630/dvr.pdf dvr.pdf]<br />
<br />
vistrails: to appear<br />
<br />
References:<br />
[http://www.llnl.gov/graphics/docs/OpticalModelsLong.pdf Optical Models for Direct Volume Rendering]<br />
<br />
== 10/23: Midterm 1 ==<br />
<br />
== 10/25: Direct Volume Rendering ==<br />
<br />
Lecturer: Steve<br />
<br />
Topics: Structured grid techniques: ray-casting, splatting, texture slicing, shear-warp<br />
<br />
Slides: [http://www.sci.utah.edu/~stevec/classes/cs5630/VolumeRendering2.pdf VolumeRendering2.pdf]<br />
<br />
Notes: same as previous class<br />
<br />
vistrails: same as previous class<br />
<br />
References:<br />
<br />
[http://graphics.stanford.edu/papers/volume-cga88/ Display of Surfaces from Volume Data] - Ray casting paper<br />
<br />
[http://portal.acm.org/citation.cfm?id=329138 Interactive Volume Rendering] - Splatting paper, paper requires ACM digital library access<br />
<br />
[http://portal.acm.org/citation.cfm?id=197972&dl=ACM&coll=GUIDE Accelerated volume rendering and tomographic reconstruction using texture mapping hardware] - Texture slicing paper, requires ACM digital library access<br />
<br />
[http://graphics.stanford.edu/papers/shear/ Fast Volume Rendering Using a Shear-Warp Factorization of the Viewing Transformation] - Shear-warp paper<br />
<br />
== 10/30: Vector and Tensor Visualization ==<br />
<br />
Lecturer: Claudio<br />
<br />
Topics: LIC; hyper LIC; Topology-based techniques<br />
<br />
== 11/1: Simplification Techniques == <br />
<br />
Guest lecture: Yuan Zhou<br />
<br />
== 11/6: Cosmology and EEG analysis ==<br />
<br />
Guest lecture: Erik Anderson<br />
<br />
== 11/8: Vector and Tensor Vis ==<br />
<br />
Lecturer: Carlos<br />
<br />
Topics: Glyphs; DTI techniques<br />
<br />
== 11/13: Aesthetic Issues in Vis ==<br />
<br />
Lecturer: Claudio<br />
<br />
Topics: Volume Illustration and NPR<br />
<br />
== 11/15: Aesthetic Issues in Vis ==<br />
<br />
Lecturer: Steve<br />
<br />
Topics: Tufte<br />
<br />
== 11/20: Aesthetic Issues in Vis ==<br />
<br />
Lecturer: Steve<br />
<br />
Topics: Tufte<br />
<br />
== 11/22: Thanksgiving == <br />
<br />
== 11/27: Information Visualization ==<br />
<br />
Lecturer: Carlos<br />
<br />
Topics: Parallel coordinates; Graph visualization<br />
<br />
== 11/29: Information Visualization ==<br />
<br />
Lecturer: Claudio<br />
<br />
Topics: Hierarchical data vis; brushing; sizing text<br />
<br />
== 12/4: Data Management for Vis ==<br />
<br />
== 12/6: Vis for presentation/discovery ==<br />
<br />
== 12/11: Open research questions ==</div>Thu, 25 Oct 2007 21:31:38 GMTStevechttps://www.vistrails.org//index.php/Talk:SciVisFall2007/ScheduleSciVisFall2007/Schedule
https://www.vistrails.org//index.php?title=SciVisFall2007/Schedule&diff=860
https://www.vistrails.org//index.php?title=SciVisFall2007/Schedule&diff=860<p>Stevec: /* 10/18: Volume Vis */</p>
<hr />
<div>== 8/21: Introduction to visualization ==<br />
<br />
Lecturer: Claudio<br />
<br />
Topics: Scientific Visualization<br />
<br />
Notes: [http://www.cs.utah.edu/~csilva/courses/cs5630/lec01-notes.pdf lec01-notes.pdf]<br />
<br />
Slides: [http://www.cs.utah.edu/~csilva/courses/cs5630/lec01.pdf lec01.pdf]<br />
<br />
Animations: [http://www.cs.utah.edu/~csilva/courses/cs5630/explosion_640x480-5.mov explosion_640x480-5.mov], [http://www.cs.utah.edu/~csilva/courses/cs5630/fig7.mov fig7.mov], [http://www.cs.utah.edu/~csilva/courses/cs5630/fig8.mov fig8.mov], [http://www.cs.utah.edu/~csilva/courses/cs5630/fig9.mov fig9.mov], [http://www.cs.utah.edu/~csilva/courses/cs5630/SevereTstorm.mov SevereTstorm.mov]<br />
<br />
Further reading: <br />
<br />
[http://www.sci.utah.edu/~csilva/papers/vis2003.pdf Visualizing Spatial and Temporal Variability in Coastal Observatories], W. Herrera-Jimenez, W. Correa, C. Silva, and A. Baptista, IEEE Visualization 2003.<br />
<br />
== 8/23: The visualization pipeline ==<br />
<br />
Lecturer: Claudio<br />
<br />
Topics: Procedural vs. Dataflow programming; Using Dataflow for the Vis Pipeline; Dataflow programming with VTK; Dataflow programming with VisTrails; python.<br />
<br />
Notes: [http://www.cs.utah.edu/~csilva/courses/cs5630/lec02-notes.pdf lec02-notes.pdf]<br />
<br />
Slides: [http://www.cs.utah.edu/~csilva/courses/cs5630/lec02.pdf lec02.pdf]<br />
<br />
VisTrails: During this class, we built a pipeline equivalent to the cone.tcl (see class slides). Here is the vistrails file: [http://www.cs.utah.edu/~csilva/courses/cs5630/cone.vt cone.vt]<br />
<br />
Further reading: <br />
<br />
[http://www.cs.utah.edu/~csilva/courses/cs5630/reproducible_vis.pdf Provenance for Visualizations: Reproducibility and Beyond], C. Silva, J. Freire, and S. Callahan, IEEE Computing in Science and Engineering, to appear.<br />
<br />
== 8/28: Modeling Data for Visualization ==<br />
<br />
Lecturer: Carlos<br />
<br />
Topics: Discrete vs continous data; Sampling and interpolation; Point vs triangulated data; Meshing data types; Regular vs irregular data; Tabular data; Vector and tensor fields<br />
<br />
Notes: TBA<br />
<br />
Slides: [http://www.sci.utah.edu/~cscheid/scivis_fall07/modelling_1.ppt .ppt file]<br />
<br />
Further reading: <br />
<br />
There is no required reading for this lecture. The notes will be available shortly. The following papers are there for people that are looking to get more advanced material that will not be covered in class.<br />
<br />
=== Interpolation ===<br />
<br />
[http://lmi.bwh.harvard.edu/papers/papers/geodesic-loxodromes-final.html Geodesic-loxodromes...] This is the fancy interpolation for diffusion tensors I mentioned in class.<br />
<br />
[http://en.wikipedia.org/wiki/Bernstein_polynomial Bernstein polynomials] These are the polynomials used for cubic Bezier curves that I mentioned in class.<br />
<br />
==== Separability ====<br />
<br />
[http://portal.acm.org/citation.cfm?id=1187793 Extensions of the Zwart-Powell Box spline...] This is a recent paper that shows a class of trivariate reconstruction techniques that are ''not'' separable.<br />
<br />
==== Tensors ====<br />
<br />
[http://www.cs.utah.edu/research/techreports/2004/pdf/UUCS-04-014.pdf Visualization and Analysis of Diffusion Tensor Fields] Gordon Kindlmann's PhD. thesis, with everything you ever wanted to know about DTI. Section 2.1 has a good primer in tensor algebra.<br />
<br />
== 8/30: Modeling Data for Visualization == <br />
<br />
Lecturer: Carlos<br />
<br />
Topics: Geometry Processing: Reconstruction and meshing; Simplification; Smoothing; Other Filtering algorithms<br />
<br />
Notes: [http://www.sci.utah.edu/~cscheid/scivis_fall07/week2.pdf .pdf file]. If you want to print these, you might want to wait for a week or two, until I finish polishing them.<br />
<br />
Slides: [http://www.sci.utah.edu/~cscheid/scivis_fall07/processing.ppt .ppt file] ''These slides include simplificatin algorithms, which I'll talk about next week.''<br />
<br />
== 9/4: Elementary Plotting Techniques == <br />
<br />
Lecturer: Steve<br />
<br />
Topics: Principles of Graph Construction<br />
<br />
Notes: [http://www.sci.utah.edu/~stevec/classes/cs5630/PlottingNotes.pdf PlottingNotes.pdf]<br />
<br />
Slides: [http://www.sci.utah.edu/~stevec/slides/SciVis/Plotting1.pdf Plotting1.pdf]<br />
<br />
Vistrails: See next lecture.<br />
<br />
Further Reading: There is no required reading for this lecture. For those interested in more depth, the following books are very useful:<br />
<br />
* The Elements of Graphing Data. William S. Cleveland, Hobart Press, 2nd Edition, 1994.<br />
* Visualizing Data. William S. Cleveland, Hobart Press, 1993.<br />
* The Visual Display of Quantitative Information. Edward R. Tufte, Graphics Press, 2001.<br />
* Visual Explanations: Images and Quantities, Evidence and Narrative. Edward R. Tufte, Graphics Press, 2997.<br />
<br />
== 9/6: Elementary Plotting Techniques ==<br />
<br />
Lecturer: Steve<br />
<br />
Topics: Simple Plotting Methods: Dot Plots, Connected Symbol Plots, Scatter Plots, Histograms, Others. Advanced Plotting Methods: Multimodal, Higher Dimensional, Correlation, Uncertainty and Variation.<br />
<br />
Notes: [http://www.sci.utah.edu/~stevec/classes/cs5630/PlottingNotes.pdf PlottingNotes.pdf]<br />
<br />
Slides: [http://www.sci.utah.edu/~stevec/slides/SciVis/Plotting2.pdf Plotting2.pdf]<br />
<br />
Vistrails: [http://www.sci.utah.edu/~stevec/classes/cs5630/PlottingVistrails.zip PlottingVistrails.zip] - Unzip this file in the examples directory of your VisTrails installation and it will add the vistrails along with their data sets (in the data directory). If you don't have permission to write to this directory (CADE users), then unzip the file where you want. Just be aware that in this case the paths for the data files may not be correct for most vistrails and will need to be fixed before they will execute properly.<br />
<br />
<br />
Further Reading: There is no required reading for this lecture. Some articles of interest:<br />
<br />
* [http://www.fmrib.ox.ac.uk/analysis/techrep/tr00mj2/tr00mj2/node24.html Histogram Bin Size]<br />
* [http://en.wikipedia.org/wiki/Correlation Correlation]<br />
* [http://en.wikipedia.org/wiki/Linear_regression Linear Regression]<br />
* [http://en.wikipedia.org/wiki/Box_plot Box Plots]<br />
<br />
== 9/11: Color and Human Perception ==<br />
<br />
Lecturer: Claudio<br />
<br />
Topics: Human vision system; Optical illusions<br />
<br />
Notes: TBA<br />
<br />
Slides: [http://www.cs.utah.edu/~csilva/courses/cs5630/human-vision.pdf human-vision.pdf]<br />
<br />
Links:<br />
<br />
http://en.wikipedia.org/wiki/Eye<br />
<br />
http://www.grand-illusions.com/gregory2.htm (also, see the related book: [http://www.amazon.com/Eye-Brain-Richard-L-Gregory/dp/0691048371])<br />
<br />
http://en.wikipedia.org/wiki/Purkinje_effect<br />
<br />
http://www.handprint.com/HP/WCL/color2.html<br />
<br />
== 9/13: Color and Human Perception ==<br />
<br />
Lecturer: Claudio<br />
<br />
Topics: Color Science; Color spaces; Color Blindness; Color maps; Tone mapping<br />
<br />
Notes: TBA<br />
<br />
Slides: [http://www.cs.utah.edu/~csilva/courses/cs5630/colorvision.pdf colorvision.pdf]<br />
<br />
Links:<br />
<br />
Further reading: <br />
<br />
[http://www.research.ibm.com/dx/proceedings/pravda/truevis.htm How Not to Lie with Visualization]<br />
<br />
http://en.wikipedia.org/wiki/Opponent_process<br />
<br />
http://en.wikipedia.org/wiki/Color_models<br />
<br />
http://en.wikipedia.org/wiki/Absolute_color_space<br />
<br />
http://en.wikipedia.org/wiki/Additive_color<br />
<br />
http://en.wikipedia.org/wiki/Subtractive_color<br />
<br />
http://en.wikipedia.org/wiki/RGB_color_model<br />
<br />
http://en.wikipedia.org/wiki/SRGB_color_space<br />
<br />
http://en.wikipedia.org/wiki/CIE_XYZ_color_space<br />
<br />
== 9/18 (a): Color and Human Perception ==<br />
<br />
Lecturer: Claudio<br />
<br />
Same material as previous lecture. <br />
<br />
== 9/18 (b): 2D Visualization Techniques ==<br />
<br />
Lecturer: Carlos<br />
<br />
Topics: 2-D contours, marching quads, marching tris; Color mapping; height fields; NPR<br />
<br />
Slides: [http://www.sci.utah.edu/~cscheid/scivis_fall07/2d_scalar_vis.pdf pdf file]<br />
<br />
Notes: [http://www.sci.utah.edu/~cscheid/scivis_fall07/2d_scalar_vis_notes.pdf pdf file]<br />
<br />
Vistrails: [http://www.sci.utah.edu/~cscheid/scivis_fall07/ozone_and_data.zip zip file with ozone.vt and data] [http://www.sci.utah.edu/~cscheid/scivis_fall07/asymptotic_decider.vt asymptotic decider in 2d] [http://www.sci.utah.edu/~cscheid/scivis_fall07/elevation.zip heightfields]<br />
<br />
Note: These vistrails use relative file paths so you don't need to change each of them individually to match your directory structure. Simply unzip the file to whichever location is more convenient. Then, inside VisTrails, open the VisTrails shell, type:<br />
<br />
import os<br />
os.chdir("c:/directory/where/you/unzipped/it")<br />
<br />
This will change the directory so you should be able to just run the pipelines.<br />
<br />
== 9/20: Math refresher ==<br />
<br />
Lecturer: Carlos<br />
<br />
Topics: Basic linear algebra; vectors; basic differential geometry (space curves, tangents, normals, surfaces); basic vector calculus (gradient, divergence, curl, gauss' theorem, green's theorem) <br />
<br />
== 9/25: 2D Visualization Techniques ==<br />
<br />
Lecturer: Carlos<br />
<br />
Topics: 2-D vector fields, div, grad, curl in 2D; Steady vs Unsteady flows; Glyphs; 2-D streamlines, streaklines, pathlines<br />
<br />
Slides: [http://www.sci.utah.edu/~cscheid/scivis_fall07/2d_vector_vis.pdf pdf file]<br />
<br />
Notes: coming soon<br />
<br />
Vistrails: [http://www.sci.utah.edu/~cscheid/scivis_fall07/vector_vis_1.zip vistrail with steady vector field vis and data] [http://www.sci.utah.edu/~cscheid/scivis_fall07/unsteady.zip vistrail with unsteady vector field vis and data] '''Note:''' Because VTK does not support time-varying datasets directly, we had to create a reasonably ugly hack to simulate unsteady fields. This means the datasets are quite big (80MB in total).<br />
<br />
== 9/27 (a): 2D Visualization Techniques ==<br />
<br />
Lecturer Carlos<br />
<br />
Same material as last lecture.<br />
<br />
== 9/27 (b): Volume Vis ==<br />
<br />
Lecturer: Claudio<br />
<br />
Topics: Slicing; Contours; Marching algorithms<br />
<br />
Slides: [http://www.cs.utah.edu/~csilva/courses/cs5630/iso-basic.pdf iso-basic.pdf]<br />
<br />
References:<br />
<br />
[http://portal.acm.org/citation.cfm?id=37401.37422 Marching cubes: A high resolution 3D surface construction algorithm]<br />
<br />
[http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=175782 The asymptotic decider: resolving the ambiguity in marching cubes]<br />
<br />
== 10/2: Volume Vis == <br />
<br />
Lecturer: Claudio<br />
<br />
Topics: Accelerating structures; High-quality contours<br />
<br />
Slides: <br />
<br />
[http://www.cs.utah.edu/~csilva/courses/cs5630/iso-speed.pdf iso-speed.pdf]<br />
<br />
[http://www.cs.utah.edu/~csilva/courses/cs5630/iso-speed-2.pdf iso-speed-2.pdf]<br />
<br />
References:<br />
<br />
[http://doi.ieeecomputersociety.org/10.1109/2945.489388 A Near Optimal Isosurface Extraction Algorithm Using the Span Space]<br />
<br />
[http://doi.ieeecomputersociety.org/10.1109/2945.485619 Automatic Isosurface Propagation Using an Extrema Graph and Sorted Boundary Cell Lists]<br />
<br />
[http://doi.ieeecomputersociety.org/10.1109/2945.597798 Speeding Up Isosurface Extraction Using Interval Trees]<br />
<br />
[http://doi.ieeecomputersociety.org/10.1109/SVVG.2004.5 Implicit Occluders]<br />
<br />
== 10/4: Volume Vis ==<br />
<br />
Lecturer: Claudio<br />
<br />
Topics: High quality isosurfaces<br />
<br />
Slides: [http://www.cs.utah.edu/~csilva/courses/cs5630/iso-quality.pdf iso-quality.pdf]<br />
<br />
References:<br />
<br />
[http://www.cs.utah.edu/~csilva/2007-sub/macet.pdf Edge Transformations for Improving Mesh Quality of Marching Cubes]<br />
<br />
[http://www.sci.utah.edu/~csilva/papers/tvcg2006acr.pdf High-Quality Extraction of Isosurfaces from Regular and Irregular Grids]<br />
<br />
[http://portal.acm.org/citation.cfm?id=566570.566586 Dual contouring of hermite data]<br />
<br />
[http://www.sci.utah.edu/%7Emiriah/research/meshing/vis07meyer.pdf Topology, Accuracy, and Quality of Isosurface Meshes Using Dynamic Particles]<br />
<br />
[http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=1260744 Material interface reconstruction]<br />
<br />
== 10/9: Fall break == <br />
<br />
== 10/11: Fall break == <br />
<br />
== 10/16: Volume Vis ==<br />
<br />
Lecturer: Claudio<br />
<br />
Topics: continued from last class<br />
<br />
== 10/18: Volume Vis ==<br />
<br />
Lecturer: Steve<br />
<br />
Topics: Introduction to volume rendering<br />
<br />
Slides: [http://www.sci.utah.edu/~stevec/classes/cs5630/VolumeRendering1.pdf VolumeRendering1.pdf]<br />
<br />
Notes: [http://www.sci.utah.edu/~stevec/classes/cs5630/dvr.pdf dvr.pdf]<br />
<br />
vistrails: to appear<br />
<br />
References:<br />
[http://www.llnl.gov/graphics/docs/OpticalModelsLong.pdf Optical Models for Direct Volume Rendering]<br />
<br />
== 10/23: Midterm 1 ==<br />
<br />
== 10/25: Vector and Tensor Visualization ==<br />
<br />
Lecturer: Carlos<br />
<br />
Topics: Differential Geometry in 3D: Div, Grad, Curl; Revisit Unsteady vs. Steady flows; Streamribbons, surfaces, tubes, streamlines and streaklines<br />
<br />
== 10/30: Vector and Tensor Visualization ==<br />
<br />
Lecturer: Claudio<br />
<br />
Topics: LIC; hyper LIC; Topology-based techniques<br />
<br />
== 11/1: Simplification Techniques == <br />
<br />
Guest lecture: Yuan Zhou<br />
<br />
== 11/6: Cosmology and EEG analysis ==<br />
<br />
Guest lecture: Erik Anderson<br />
<br />
== 11/8: Vector and Tensor Vis ==<br />
<br />
Lecturer: Carlos<br />
<br />
Topics: Glyphs; DTI techniques<br />
<br />
== 11/13: Aesthetic Issues in Vis ==<br />
<br />
Lecturer: Claudio<br />
<br />
Topics: Volume Illustration and NPR<br />
<br />
== 11/15: Aesthetic Issues in Vis ==<br />
<br />
Lecturer: Steve<br />
<br />
Topics: Tufte<br />
<br />
== 11/20: Aesthetic Issues in Vis ==<br />
<br />
Lecturer: Steve<br />
<br />
Topics: Tufte<br />
<br />
== 11/22: Thanksgiving == <br />
<br />
== 11/27: Information Visualization ==<br />
<br />
Lecturer: Carlos<br />
<br />
Topics: Parallel coordinates; Graph visualization<br />
<br />
== 11/29: Information Visualization ==<br />
<br />
Lecturer: Claudio<br />
<br />
Topics: Hierarchical data vis; brushing; sizing text<br />
<br />
== 12/4: Data Management for Vis ==<br />
<br />
== 12/6: Vis for presentation/discovery ==<br />
<br />
== 12/11: Open research questions ==</div>Thu, 25 Oct 2007 21:19:02 GMTStevechttps://www.vistrails.org//index.php/Talk:SciVisFall2007/ScheduleSciVisFall2007/Schedule
https://www.vistrails.org//index.php?title=SciVisFall2007/Schedule&diff=859
https://www.vistrails.org//index.php?title=SciVisFall2007/Schedule&diff=859<p>Stevec: /* 10/18: Volume Vis */</p>
<hr />
<div>== 8/21: Introduction to visualization ==<br />
<br />
Lecturer: Claudio<br />
<br />
Topics: Scientific Visualization<br />
<br />
Notes: [http://www.cs.utah.edu/~csilva/courses/cs5630/lec01-notes.pdf lec01-notes.pdf]<br />
<br />
Slides: [http://www.cs.utah.edu/~csilva/courses/cs5630/lec01.pdf lec01.pdf]<br />
<br />
Animations: [http://www.cs.utah.edu/~csilva/courses/cs5630/explosion_640x480-5.mov explosion_640x480-5.mov], [http://www.cs.utah.edu/~csilva/courses/cs5630/fig7.mov fig7.mov], [http://www.cs.utah.edu/~csilva/courses/cs5630/fig8.mov fig8.mov], [http://www.cs.utah.edu/~csilva/courses/cs5630/fig9.mov fig9.mov], [http://www.cs.utah.edu/~csilva/courses/cs5630/SevereTstorm.mov SevereTstorm.mov]<br />
<br />
Further reading: <br />
<br />
[http://www.sci.utah.edu/~csilva/papers/vis2003.pdf Visualizing Spatial and Temporal Variability in Coastal Observatories], W. Herrera-Jimenez, W. Correa, C. Silva, and A. Baptista, IEEE Visualization 2003.<br />
<br />
== 8/23: The visualization pipeline ==<br />
<br />
Lecturer: Claudio<br />
<br />
Topics: Procedural vs. Dataflow programming; Using Dataflow for the Vis Pipeline; Dataflow programming with VTK; Dataflow programming with VisTrails; python.<br />
<br />
Notes: [http://www.cs.utah.edu/~csilva/courses/cs5630/lec02-notes.pdf lec02-notes.pdf]<br />
<br />
Slides: [http://www.cs.utah.edu/~csilva/courses/cs5630/lec02.pdf lec02.pdf]<br />
<br />
VisTrails: During this class, we built a pipeline equivalent to the cone.tcl (see class slides). Here is the vistrails file: [http://www.cs.utah.edu/~csilva/courses/cs5630/cone.vt cone.vt]<br />
<br />
Further reading: <br />
<br />
[http://www.cs.utah.edu/~csilva/courses/cs5630/reproducible_vis.pdf Provenance for Visualizations: Reproducibility and Beyond], C. Silva, J. Freire, and S. Callahan, IEEE Computing in Science and Engineering, to appear.<br />
<br />
== 8/28: Modeling Data for Visualization ==<br />
<br />
Lecturer: Carlos<br />
<br />
Topics: Discrete vs continous data; Sampling and interpolation; Point vs triangulated data; Meshing data types; Regular vs irregular data; Tabular data; Vector and tensor fields<br />
<br />
Notes: TBA<br />
<br />
Slides: [http://www.sci.utah.edu/~cscheid/scivis_fall07/modelling_1.ppt .ppt file]<br />
<br />
Further reading: <br />
<br />
There is no required reading for this lecture. The notes will be available shortly. The following papers are there for people that are looking to get more advanced material that will not be covered in class.<br />
<br />
=== Interpolation ===<br />
<br />
[http://lmi.bwh.harvard.edu/papers/papers/geodesic-loxodromes-final.html Geodesic-loxodromes...] This is the fancy interpolation for diffusion tensors I mentioned in class.<br />
<br />
[http://en.wikipedia.org/wiki/Bernstein_polynomial Bernstein polynomials] These are the polynomials used for cubic Bezier curves that I mentioned in class.<br />
<br />
==== Separability ====<br />
<br />
[http://portal.acm.org/citation.cfm?id=1187793 Extensions of the Zwart-Powell Box spline...] This is a recent paper that shows a class of trivariate reconstruction techniques that are ''not'' separable.<br />
<br />
==== Tensors ====<br />
<br />
[http://www.cs.utah.edu/research/techreports/2004/pdf/UUCS-04-014.pdf Visualization and Analysis of Diffusion Tensor Fields] Gordon Kindlmann's PhD. thesis, with everything you ever wanted to know about DTI. Section 2.1 has a good primer in tensor algebra.<br />
<br />
== 8/30: Modeling Data for Visualization == <br />
<br />
Lecturer: Carlos<br />
<br />
Topics: Geometry Processing: Reconstruction and meshing; Simplification; Smoothing; Other Filtering algorithms<br />
<br />
Notes: [http://www.sci.utah.edu/~cscheid/scivis_fall07/week2.pdf .pdf file]. If you want to print these, you might want to wait for a week or two, until I finish polishing them.<br />
<br />
Slides: [http://www.sci.utah.edu/~cscheid/scivis_fall07/processing.ppt .ppt file] ''These slides include simplificatin algorithms, which I'll talk about next week.''<br />
<br />
== 9/4: Elementary Plotting Techniques == <br />
<br />
Lecturer: Steve<br />
<br />
Topics: Principles of Graph Construction<br />
<br />
Notes: [http://www.sci.utah.edu/~stevec/classes/cs5630/PlottingNotes.pdf PlottingNotes.pdf]<br />
<br />
Slides: [http://www.sci.utah.edu/~stevec/slides/SciVis/Plotting1.pdf Plotting1.pdf]<br />
<br />
Vistrails: See next lecture.<br />
<br />
Further Reading: There is no required reading for this lecture. For those interested in more depth, the following books are very useful:<br />
<br />
* The Elements of Graphing Data. William S. Cleveland, Hobart Press, 2nd Edition, 1994.<br />
* Visualizing Data. William S. Cleveland, Hobart Press, 1993.<br />
* The Visual Display of Quantitative Information. Edward R. Tufte, Graphics Press, 2001.<br />
* Visual Explanations: Images and Quantities, Evidence and Narrative. Edward R. Tufte, Graphics Press, 2997.<br />
<br />
== 9/6: Elementary Plotting Techniques ==<br />
<br />
Lecturer: Steve<br />
<br />
Topics: Simple Plotting Methods: Dot Plots, Connected Symbol Plots, Scatter Plots, Histograms, Others. Advanced Plotting Methods: Multimodal, Higher Dimensional, Correlation, Uncertainty and Variation.<br />
<br />
Notes: [http://www.sci.utah.edu/~stevec/classes/cs5630/PlottingNotes.pdf PlottingNotes.pdf]<br />
<br />
Slides: [http://www.sci.utah.edu/~stevec/slides/SciVis/Plotting2.pdf Plotting2.pdf]<br />
<br />
Vistrails: [http://www.sci.utah.edu/~stevec/classes/cs5630/PlottingVistrails.zip PlottingVistrails.zip] - Unzip this file in the examples directory of your VisTrails installation and it will add the vistrails along with their data sets (in the data directory). If you don't have permission to write to this directory (CADE users), then unzip the file where you want. Just be aware that in this case the paths for the data files may not be correct for most vistrails and will need to be fixed before they will execute properly.<br />
<br />
<br />
Further Reading: There is no required reading for this lecture. Some articles of interest:<br />
<br />
* [http://www.fmrib.ox.ac.uk/analysis/techrep/tr00mj2/tr00mj2/node24.html Histogram Bin Size]<br />
* [http://en.wikipedia.org/wiki/Correlation Correlation]<br />
* [http://en.wikipedia.org/wiki/Linear_regression Linear Regression]<br />
* [http://en.wikipedia.org/wiki/Box_plot Box Plots]<br />
<br />
== 9/11: Color and Human Perception ==<br />
<br />
Lecturer: Claudio<br />
<br />
Topics: Human vision system; Optical illusions<br />
<br />
Notes: TBA<br />
<br />
Slides: [http://www.cs.utah.edu/~csilva/courses/cs5630/human-vision.pdf human-vision.pdf]<br />
<br />
Links:<br />
<br />
http://en.wikipedia.org/wiki/Eye<br />
<br />
http://www.grand-illusions.com/gregory2.htm (also, see the related book: [http://www.amazon.com/Eye-Brain-Richard-L-Gregory/dp/0691048371])<br />
<br />
http://en.wikipedia.org/wiki/Purkinje_effect<br />
<br />
http://www.handprint.com/HP/WCL/color2.html<br />
<br />
== 9/13: Color and Human Perception ==<br />
<br />
Lecturer: Claudio<br />
<br />
Topics: Color Science; Color spaces; Color Blindness; Color maps; Tone mapping<br />
<br />
Notes: TBA<br />
<br />
Slides: [http://www.cs.utah.edu/~csilva/courses/cs5630/colorvision.pdf colorvision.pdf]<br />
<br />
Links:<br />
<br />
Further reading: <br />
<br />
[http://www.research.ibm.com/dx/proceedings/pravda/truevis.htm How Not to Lie with Visualization]<br />
<br />
http://en.wikipedia.org/wiki/Opponent_process<br />
<br />
http://en.wikipedia.org/wiki/Color_models<br />
<br />
http://en.wikipedia.org/wiki/Absolute_color_space<br />
<br />
http://en.wikipedia.org/wiki/Additive_color<br />
<br />
http://en.wikipedia.org/wiki/Subtractive_color<br />
<br />
http://en.wikipedia.org/wiki/RGB_color_model<br />
<br />
http://en.wikipedia.org/wiki/SRGB_color_space<br />
<br />
http://en.wikipedia.org/wiki/CIE_XYZ_color_space<br />
<br />
== 9/18 (a): Color and Human Perception ==<br />
<br />
Lecturer: Claudio<br />
<br />
Same material as previous lecture. <br />
<br />
== 9/18 (b): 2D Visualization Techniques ==<br />
<br />
Lecturer: Carlos<br />
<br />
Topics: 2-D contours, marching quads, marching tris; Color mapping; height fields; NPR<br />
<br />
Slides: [http://www.sci.utah.edu/~cscheid/scivis_fall07/2d_scalar_vis.pdf pdf file]<br />
<br />
Notes: [http://www.sci.utah.edu/~cscheid/scivis_fall07/2d_scalar_vis_notes.pdf pdf file]<br />
<br />
Vistrails: [http://www.sci.utah.edu/~cscheid/scivis_fall07/ozone_and_data.zip zip file with ozone.vt and data] [http://www.sci.utah.edu/~cscheid/scivis_fall07/asymptotic_decider.vt asymptotic decider in 2d] [http://www.sci.utah.edu/~cscheid/scivis_fall07/elevation.zip heightfields]<br />
<br />
Note: These vistrails use relative file paths so you don't need to change each of them individually to match your directory structure. Simply unzip the file to whichever location is more convenient. Then, inside VisTrails, open the VisTrails shell, type:<br />
<br />
import os<br />
os.chdir("c:/directory/where/you/unzipped/it")<br />
<br />
This will change the directory so you should be able to just run the pipelines.<br />
<br />
== 9/20: Math refresher ==<br />
<br />
Lecturer: Carlos<br />
<br />
Topics: Basic linear algebra; vectors; basic differential geometry (space curves, tangents, normals, surfaces); basic vector calculus (gradient, divergence, curl, gauss' theorem, green's theorem) <br />
<br />
== 9/25: 2D Visualization Techniques ==<br />
<br />
Lecturer: Carlos<br />
<br />
Topics: 2-D vector fields, div, grad, curl in 2D; Steady vs Unsteady flows; Glyphs; 2-D streamlines, streaklines, pathlines<br />
<br />
Slides: [http://www.sci.utah.edu/~cscheid/scivis_fall07/2d_vector_vis.pdf pdf file]<br />
<br />
Notes: coming soon<br />
<br />
Vistrails: [http://www.sci.utah.edu/~cscheid/scivis_fall07/vector_vis_1.zip vistrail with steady vector field vis and data] [http://www.sci.utah.edu/~cscheid/scivis_fall07/unsteady.zip vistrail with unsteady vector field vis and data] '''Note:''' Because VTK does not support time-varying datasets directly, we had to create a reasonably ugly hack to simulate unsteady fields. This means the datasets are quite big (80MB in total).<br />
<br />
== 9/27 (a): 2D Visualization Techniques ==<br />
<br />
Lecturer Carlos<br />
<br />
Same material as last lecture.<br />
<br />
== 9/27 (b): Volume Vis ==<br />
<br />
Lecturer: Claudio<br />
<br />
Topics: Slicing; Contours; Marching algorithms<br />
<br />
Slides: [http://www.cs.utah.edu/~csilva/courses/cs5630/iso-basic.pdf iso-basic.pdf]<br />
<br />
References:<br />
<br />
[http://portal.acm.org/citation.cfm?id=37401.37422 Marching cubes: A high resolution 3D surface construction algorithm]<br />
<br />
[http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=175782 The asymptotic decider: resolving the ambiguity in marching cubes]<br />
<br />
== 10/2: Volume Vis == <br />
<br />
Lecturer: Claudio<br />
<br />
Topics: Accelerating structures; High-quality contours<br />
<br />
Slides: <br />
<br />
[http://www.cs.utah.edu/~csilva/courses/cs5630/iso-speed.pdf iso-speed.pdf]<br />
<br />
[http://www.cs.utah.edu/~csilva/courses/cs5630/iso-speed-2.pdf iso-speed-2.pdf]<br />
<br />
References:<br />
<br />
[http://doi.ieeecomputersociety.org/10.1109/2945.489388 A Near Optimal Isosurface Extraction Algorithm Using the Span Space]<br />
<br />
[http://doi.ieeecomputersociety.org/10.1109/2945.485619 Automatic Isosurface Propagation Using an Extrema Graph and Sorted Boundary Cell Lists]<br />
<br />
[http://doi.ieeecomputersociety.org/10.1109/2945.597798 Speeding Up Isosurface Extraction Using Interval Trees]<br />
<br />
[http://doi.ieeecomputersociety.org/10.1109/SVVG.2004.5 Implicit Occluders]<br />
<br />
== 10/4: Volume Vis ==<br />
<br />
Lecturer: Claudio<br />
<br />
Topics: High quality isosurfaces<br />
<br />
Slides: [http://www.cs.utah.edu/~csilva/courses/cs5630/iso-quality.pdf iso-quality.pdf]<br />
<br />
References:<br />
<br />
[http://www.cs.utah.edu/~csilva/2007-sub/macet.pdf Edge Transformations for Improving Mesh Quality of Marching Cubes]<br />
<br />
[http://www.sci.utah.edu/~csilva/papers/tvcg2006acr.pdf High-Quality Extraction of Isosurfaces from Regular and Irregular Grids]<br />
<br />
[http://portal.acm.org/citation.cfm?id=566570.566586 Dual contouring of hermite data]<br />
<br />
[http://www.sci.utah.edu/%7Emiriah/research/meshing/vis07meyer.pdf Topology, Accuracy, and Quality of Isosurface Meshes Using Dynamic Particles]<br />
<br />
[http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=1260744 Material interface reconstruction]<br />
<br />
== 10/9: Fall break == <br />
<br />
== 10/11: Fall break == <br />
<br />
== 10/16: Volume Vis ==<br />
<br />
Lecturer: Claudio<br />
<br />
Topics: continued from last class<br />
<br />
== 10/18: Volume Vis ==<br />
<br />
Lecturer: Steve<br />
<br />
Topics: Introduction to volume rendering<br />
<br />
Slides: [http://www.sci.utah.edu/~stevec/classes/cs5630/VolumeRendering1.pdf VolumeRendering1.pdf]<br />
<br />
Notes: [http://www.sci.utah.edu/~stevec/classes/cs5630/dvr.pdf dvr.pdf]<br />
<br />
vistrails: to appear<br />
<br />
References:<br />
Optical Models for Direct Volume Rendering<br />
<br />
== 10/23: Midterm 1 ==<br />
<br />
== 10/25: Vector and Tensor Visualization ==<br />
<br />
Lecturer: Carlos<br />
<br />
Topics: Differential Geometry in 3D: Div, Grad, Curl; Revisit Unsteady vs. Steady flows; Streamribbons, surfaces, tubes, streamlines and streaklines<br />
<br />
== 10/30: Vector and Tensor Visualization ==<br />
<br />
Lecturer: Claudio<br />
<br />
Topics: LIC; hyper LIC; Topology-based techniques<br />
<br />
== 11/1: Simplification Techniques == <br />
<br />
Guest lecture: Yuan Zhou<br />
<br />
== 11/6: Cosmology and EEG analysis ==<br />
<br />
Guest lecture: Erik Anderson<br />
<br />
== 11/8: Vector and Tensor Vis ==<br />
<br />
Lecturer: Carlos<br />
<br />
Topics: Glyphs; DTI techniques<br />
<br />
== 11/13: Aesthetic Issues in Vis ==<br />
<br />
Lecturer: Claudio<br />
<br />
Topics: Volume Illustration and NPR<br />
<br />
== 11/15: Aesthetic Issues in Vis ==<br />
<br />
Lecturer: Steve<br />
<br />
Topics: Tufte<br />
<br />
== 11/20: Aesthetic Issues in Vis ==<br />
<br />
Lecturer: Steve<br />
<br />
Topics: Tufte<br />
<br />
== 11/22: Thanksgiving == <br />
<br />
== 11/27: Information Visualization ==<br />
<br />
Lecturer: Carlos<br />
<br />
Topics: Parallel coordinates; Graph visualization<br />
<br />
== 11/29: Information Visualization ==<br />
<br />
Lecturer: Claudio<br />
<br />
Topics: Hierarchical data vis; brushing; sizing text<br />
<br />
== 12/4: Data Management for Vis ==<br />
<br />
== 12/6: Vis for presentation/discovery ==<br />
<br />
== 12/11: Open research questions ==</div>Thu, 25 Oct 2007 21:18:04 GMTStevechttps://www.vistrails.org//index.php/Talk:SciVisFall2007/ScheduleSciVisFall2007/Schedule
https://www.vistrails.org//index.php?title=SciVisFall2007/Schedule&diff=858
https://www.vistrails.org//index.php?title=SciVisFall2007/Schedule&diff=858<p>Stevec: /* 10/18: Volume Vis */</p>
<hr />
<div>== 8/21: Introduction to visualization ==<br />
<br />
Lecturer: Claudio<br />
<br />
Topics: Scientific Visualization<br />
<br />
Notes: [http://www.cs.utah.edu/~csilva/courses/cs5630/lec01-notes.pdf lec01-notes.pdf]<br />
<br />
Slides: [http://www.cs.utah.edu/~csilva/courses/cs5630/lec01.pdf lec01.pdf]<br />
<br />
Animations: [http://www.cs.utah.edu/~csilva/courses/cs5630/explosion_640x480-5.mov explosion_640x480-5.mov], [http://www.cs.utah.edu/~csilva/courses/cs5630/fig7.mov fig7.mov], [http://www.cs.utah.edu/~csilva/courses/cs5630/fig8.mov fig8.mov], [http://www.cs.utah.edu/~csilva/courses/cs5630/fig9.mov fig9.mov], [http://www.cs.utah.edu/~csilva/courses/cs5630/SevereTstorm.mov SevereTstorm.mov]<br />
<br />
Further reading: <br />
<br />
[http://www.sci.utah.edu/~csilva/papers/vis2003.pdf Visualizing Spatial and Temporal Variability in Coastal Observatories], W. Herrera-Jimenez, W. Correa, C. Silva, and A. Baptista, IEEE Visualization 2003.<br />
<br />
== 8/23: The visualization pipeline ==<br />
<br />
Lecturer: Claudio<br />
<br />
Topics: Procedural vs. Dataflow programming; Using Dataflow for the Vis Pipeline; Dataflow programming with VTK; Dataflow programming with VisTrails; python.<br />
<br />
Notes: [http://www.cs.utah.edu/~csilva/courses/cs5630/lec02-notes.pdf lec02-notes.pdf]<br />
<br />
Slides: [http://www.cs.utah.edu/~csilva/courses/cs5630/lec02.pdf lec02.pdf]<br />
<br />
VisTrails: During this class, we built a pipeline equivalent to the cone.tcl (see class slides). Here is the vistrails file: [http://www.cs.utah.edu/~csilva/courses/cs5630/cone.vt cone.vt]<br />
<br />
Further reading: <br />
<br />
[http://www.cs.utah.edu/~csilva/courses/cs5630/reproducible_vis.pdf Provenance for Visualizations: Reproducibility and Beyond], C. Silva, J. Freire, and S. Callahan, IEEE Computing in Science and Engineering, to appear.<br />
<br />
== 8/28: Modeling Data for Visualization ==<br />
<br />
Lecturer: Carlos<br />
<br />
Topics: Discrete vs continous data; Sampling and interpolation; Point vs triangulated data; Meshing data types; Regular vs irregular data; Tabular data; Vector and tensor fields<br />
<br />
Notes: TBA<br />
<br />
Slides: [http://www.sci.utah.edu/~cscheid/scivis_fall07/modelling_1.ppt .ppt file]<br />
<br />
Further reading: <br />
<br />
There is no required reading for this lecture. The notes will be available shortly. The following papers are there for people that are looking to get more advanced material that will not be covered in class.<br />
<br />
=== Interpolation ===<br />
<br />
[http://lmi.bwh.harvard.edu/papers/papers/geodesic-loxodromes-final.html Geodesic-loxodromes...] This is the fancy interpolation for diffusion tensors I mentioned in class.<br />
<br />
[http://en.wikipedia.org/wiki/Bernstein_polynomial Bernstein polynomials] These are the polynomials used for cubic Bezier curves that I mentioned in class.<br />
<br />
==== Separability ====<br />
<br />
[http://portal.acm.org/citation.cfm?id=1187793 Extensions of the Zwart-Powell Box spline...] This is a recent paper that shows a class of trivariate reconstruction techniques that are ''not'' separable.<br />
<br />
==== Tensors ====<br />
<br />
[http://www.cs.utah.edu/research/techreports/2004/pdf/UUCS-04-014.pdf Visualization and Analysis of Diffusion Tensor Fields] Gordon Kindlmann's PhD. thesis, with everything you ever wanted to know about DTI. Section 2.1 has a good primer in tensor algebra.<br />
<br />
== 8/30: Modeling Data for Visualization == <br />
<br />
Lecturer: Carlos<br />
<br />
Topics: Geometry Processing: Reconstruction and meshing; Simplification; Smoothing; Other Filtering algorithms<br />
<br />
Notes: [http://www.sci.utah.edu/~cscheid/scivis_fall07/week2.pdf .pdf file]. If you want to print these, you might want to wait for a week or two, until I finish polishing them.<br />
<br />
Slides: [http://www.sci.utah.edu/~cscheid/scivis_fall07/processing.ppt .ppt file] ''These slides include simplificatin algorithms, which I'll talk about next week.''<br />
<br />
== 9/4: Elementary Plotting Techniques == <br />
<br />
Lecturer: Steve<br />
<br />
Topics: Principles of Graph Construction<br />
<br />
Notes: [http://www.sci.utah.edu/~stevec/classes/cs5630/PlottingNotes.pdf PlottingNotes.pdf]<br />
<br />
Slides: [http://www.sci.utah.edu/~stevec/slides/SciVis/Plotting1.pdf Plotting1.pdf]<br />
<br />
Vistrails: See next lecture.<br />
<br />
Further Reading: There is no required reading for this lecture. For those interested in more depth, the following books are very useful:<br />
<br />
* The Elements of Graphing Data. William S. Cleveland, Hobart Press, 2nd Edition, 1994.<br />
* Visualizing Data. William S. Cleveland, Hobart Press, 1993.<br />
* The Visual Display of Quantitative Information. Edward R. Tufte, Graphics Press, 2001.<br />
* Visual Explanations: Images and Quantities, Evidence and Narrative. Edward R. Tufte, Graphics Press, 2997.<br />
<br />
== 9/6: Elementary Plotting Techniques ==<br />
<br />
Lecturer: Steve<br />
<br />
Topics: Simple Plotting Methods: Dot Plots, Connected Symbol Plots, Scatter Plots, Histograms, Others. Advanced Plotting Methods: Multimodal, Higher Dimensional, Correlation, Uncertainty and Variation.<br />
<br />
Notes: [http://www.sci.utah.edu/~stevec/classes/cs5630/PlottingNotes.pdf PlottingNotes.pdf]<br />
<br />
Slides: [http://www.sci.utah.edu/~stevec/slides/SciVis/Plotting2.pdf Plotting2.pdf]<br />
<br />
Vistrails: [http://www.sci.utah.edu/~stevec/classes/cs5630/PlottingVistrails.zip PlottingVistrails.zip] - Unzip this file in the examples directory of your VisTrails installation and it will add the vistrails along with their data sets (in the data directory). If you don't have permission to write to this directory (CADE users), then unzip the file where you want. Just be aware that in this case the paths for the data files may not be correct for most vistrails and will need to be fixed before they will execute properly.<br />
<br />
<br />
Further Reading: There is no required reading for this lecture. Some articles of interest:<br />
<br />
* [http://www.fmrib.ox.ac.uk/analysis/techrep/tr00mj2/tr00mj2/node24.html Histogram Bin Size]<br />
* [http://en.wikipedia.org/wiki/Correlation Correlation]<br />
* [http://en.wikipedia.org/wiki/Linear_regression Linear Regression]<br />
* [http://en.wikipedia.org/wiki/Box_plot Box Plots]<br />
<br />
== 9/11: Color and Human Perception ==<br />
<br />
Lecturer: Claudio<br />
<br />
Topics: Human vision system; Optical illusions<br />
<br />
Notes: TBA<br />
<br />
Slides: [http://www.cs.utah.edu/~csilva/courses/cs5630/human-vision.pdf human-vision.pdf]<br />
<br />
Links:<br />
<br />
http://en.wikipedia.org/wiki/Eye<br />
<br />
http://www.grand-illusions.com/gregory2.htm (also, see the related book: [http://www.amazon.com/Eye-Brain-Richard-L-Gregory/dp/0691048371])<br />
<br />
http://en.wikipedia.org/wiki/Purkinje_effect<br />
<br />
http://www.handprint.com/HP/WCL/color2.html<br />
<br />
== 9/13: Color and Human Perception ==<br />
<br />
Lecturer: Claudio<br />
<br />
Topics: Color Science; Color spaces; Color Blindness; Color maps; Tone mapping<br />
<br />
Notes: TBA<br />
<br />
Slides: [http://www.cs.utah.edu/~csilva/courses/cs5630/colorvision.pdf colorvision.pdf]<br />
<br />
Links:<br />
<br />
Further reading: <br />
<br />
[http://www.research.ibm.com/dx/proceedings/pravda/truevis.htm How Not to Lie with Visualization]<br />
<br />
http://en.wikipedia.org/wiki/Opponent_process<br />
<br />
http://en.wikipedia.org/wiki/Color_models<br />
<br />
http://en.wikipedia.org/wiki/Absolute_color_space<br />
<br />
http://en.wikipedia.org/wiki/Additive_color<br />
<br />
http://en.wikipedia.org/wiki/Subtractive_color<br />
<br />
http://en.wikipedia.org/wiki/RGB_color_model<br />
<br />
http://en.wikipedia.org/wiki/SRGB_color_space<br />
<br />
http://en.wikipedia.org/wiki/CIE_XYZ_color_space<br />
<br />
== 9/18 (a): Color and Human Perception ==<br />
<br />
Lecturer: Claudio<br />
<br />
Same material as previous lecture. <br />
<br />
== 9/18 (b): 2D Visualization Techniques ==<br />
<br />
Lecturer: Carlos<br />
<br />
Topics: 2-D contours, marching quads, marching tris; Color mapping; height fields; NPR<br />
<br />
Slides: [http://www.sci.utah.edu/~cscheid/scivis_fall07/2d_scalar_vis.pdf pdf file]<br />
<br />
Notes: [http://www.sci.utah.edu/~cscheid/scivis_fall07/2d_scalar_vis_notes.pdf pdf file]<br />
<br />
Vistrails: [http://www.sci.utah.edu/~cscheid/scivis_fall07/ozone_and_data.zip zip file with ozone.vt and data] [http://www.sci.utah.edu/~cscheid/scivis_fall07/asymptotic_decider.vt asymptotic decider in 2d] [http://www.sci.utah.edu/~cscheid/scivis_fall07/elevation.zip heightfields]<br />
<br />
Note: These vistrails use relative file paths so you don't need to change each of them individually to match your directory structure. Simply unzip the file to whichever location is more convenient. Then, inside VisTrails, open the VisTrails shell, type:<br />
<br />
import os<br />
os.chdir("c:/directory/where/you/unzipped/it")<br />
<br />
This will change the directory so you should be able to just run the pipelines.<br />
<br />
== 9/20: Math refresher ==<br />
<br />
Lecturer: Carlos<br />
<br />
Topics: Basic linear algebra; vectors; basic differential geometry (space curves, tangents, normals, surfaces); basic vector calculus (gradient, divergence, curl, gauss' theorem, green's theorem) <br />
<br />
== 9/25: 2D Visualization Techniques ==<br />
<br />
Lecturer: Carlos<br />
<br />
Topics: 2-D vector fields, div, grad, curl in 2D; Steady vs Unsteady flows; Glyphs; 2-D streamlines, streaklines, pathlines<br />
<br />
Slides: [http://www.sci.utah.edu/~cscheid/scivis_fall07/2d_vector_vis.pdf pdf file]<br />
<br />
Notes: coming soon<br />
<br />
Vistrails: [http://www.sci.utah.edu/~cscheid/scivis_fall07/vector_vis_1.zip vistrail with steady vector field vis and data] [http://www.sci.utah.edu/~cscheid/scivis_fall07/unsteady.zip vistrail with unsteady vector field vis and data] '''Note:''' Because VTK does not support time-varying datasets directly, we had to create a reasonably ugly hack to simulate unsteady fields. This means the datasets are quite big (80MB in total).<br />
<br />
== 9/27 (a): 2D Visualization Techniques ==<br />
<br />
Lecturer Carlos<br />
<br />
Same material as last lecture.<br />
<br />
== 9/27 (b): Volume Vis ==<br />
<br />
Lecturer: Claudio<br />
<br />
Topics: Slicing; Contours; Marching algorithms<br />
<br />
Slides: [http://www.cs.utah.edu/~csilva/courses/cs5630/iso-basic.pdf iso-basic.pdf]<br />
<br />
References:<br />
<br />
[http://portal.acm.org/citation.cfm?id=37401.37422 Marching cubes: A high resolution 3D surface construction algorithm]<br />
<br />
[http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=175782 The asymptotic decider: resolving the ambiguity in marching cubes]<br />
<br />
== 10/2: Volume Vis == <br />
<br />
Lecturer: Claudio<br />
<br />
Topics: Accelerating structures; High-quality contours<br />
<br />
Slides: <br />
<br />
[http://www.cs.utah.edu/~csilva/courses/cs5630/iso-speed.pdf iso-speed.pdf]<br />
<br />
[http://www.cs.utah.edu/~csilva/courses/cs5630/iso-speed-2.pdf iso-speed-2.pdf]<br />
<br />
References:<br />
<br />
[http://doi.ieeecomputersociety.org/10.1109/2945.489388 A Near Optimal Isosurface Extraction Algorithm Using the Span Space]<br />
<br />
[http://doi.ieeecomputersociety.org/10.1109/2945.485619 Automatic Isosurface Propagation Using an Extrema Graph and Sorted Boundary Cell Lists]<br />
<br />
[http://doi.ieeecomputersociety.org/10.1109/2945.597798 Speeding Up Isosurface Extraction Using Interval Trees]<br />
<br />
[http://doi.ieeecomputersociety.org/10.1109/SVVG.2004.5 Implicit Occluders]<br />
<br />
== 10/4: Volume Vis ==<br />
<br />
Lecturer: Claudio<br />
<br />
Topics: High quality isosurfaces<br />
<br />
Slides: [http://www.cs.utah.edu/~csilva/courses/cs5630/iso-quality.pdf iso-quality.pdf]<br />
<br />
References:<br />
<br />
[http://www.cs.utah.edu/~csilva/2007-sub/macet.pdf Edge Transformations for Improving Mesh Quality of Marching Cubes]<br />
<br />
[http://www.sci.utah.edu/~csilva/papers/tvcg2006acr.pdf High-Quality Extraction of Isosurfaces from Regular and Irregular Grids]<br />
<br />
[http://portal.acm.org/citation.cfm?id=566570.566586 Dual contouring of hermite data]<br />
<br />
[http://www.sci.utah.edu/%7Emiriah/research/meshing/vis07meyer.pdf Topology, Accuracy, and Quality of Isosurface Meshes Using Dynamic Particles]<br />
<br />
[http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=1260744 Material interface reconstruction]<br />
<br />
== 10/9: Fall break == <br />
<br />
== 10/11: Fall break == <br />
<br />
== 10/16: Volume Vis ==<br />
<br />
Lecturer: Claudio<br />
<br />
Topics: continued from last class<br />
<br />
== 10/18: Volume Vis ==<br />
<br />
Lecturer: Steve<br />
<br />
Topics: Introduction to volume rendering<br />
<br />
Slides: [http://www.sci.utah.edu/~stevec/classes/cs5630/VolumeRendering1.pdf VolumeRendering1.pdf]<br />
<br />
Notes: [http://www.sci.utah.edu/~stevec/classes/cs5630/dvr.pdf dvr.pdf]<br />
<br />
vistrails: to appear<br />
<br />
References:<br />
<br />
== 10/23: Midterm 1 ==<br />
<br />
== 10/25: Vector and Tensor Visualization ==<br />
<br />
Lecturer: Carlos<br />
<br />
Topics: Differential Geometry in 3D: Div, Grad, Curl; Revisit Unsteady vs. Steady flows; Streamribbons, surfaces, tubes, streamlines and streaklines<br />
<br />
== 10/30: Vector and Tensor Visualization ==<br />
<br />
Lecturer: Claudio<br />
<br />
Topics: LIC; hyper LIC; Topology-based techniques<br />
<br />
== 11/1: Simplification Techniques == <br />
<br />
Guest lecture: Yuan Zhou<br />
<br />
== 11/6: Cosmology and EEG analysis ==<br />
<br />
Guest lecture: Erik Anderson<br />
<br />
== 11/8: Vector and Tensor Vis ==<br />
<br />
Lecturer: Carlos<br />
<br />
Topics: Glyphs; DTI techniques<br />
<br />
== 11/13: Aesthetic Issues in Vis ==<br />
<br />
Lecturer: Claudio<br />
<br />
Topics: Volume Illustration and NPR<br />
<br />
== 11/15: Aesthetic Issues in Vis ==<br />
<br />
Lecturer: Steve<br />
<br />
Topics: Tufte<br />
<br />
== 11/20: Aesthetic Issues in Vis ==<br />
<br />
Lecturer: Steve<br />
<br />
Topics: Tufte<br />
<br />
== 11/22: Thanksgiving == <br />
<br />
== 11/27: Information Visualization ==<br />
<br />
Lecturer: Carlos<br />
<br />
Topics: Parallel coordinates; Graph visualization<br />
<br />
== 11/29: Information Visualization ==<br />
<br />
Lecturer: Claudio<br />
<br />
Topics: Hierarchical data vis; brushing; sizing text<br />
<br />
== 12/4: Data Management for Vis ==<br />
<br />
== 12/6: Vis for presentation/discovery ==<br />
<br />
== 12/11: Open research questions ==</div>Thu, 25 Oct 2007 21:17:37 GMTStevechttps://www.vistrails.org//index.php/Talk:SciVisFall2007/ScheduleSciVisFall2007/Schedule
https://www.vistrails.org//index.php?title=SciVisFall2007/Schedule&diff=857
https://www.vistrails.org//index.php?title=SciVisFall2007/Schedule&diff=857<p>Stevec: /* 10/16: Volume Vis */</p>
<hr />
<div>== 8/21: Introduction to visualization ==<br />
<br />
Lecturer: Claudio<br />
<br />
Topics: Scientific Visualization<br />
<br />
Notes: [http://www.cs.utah.edu/~csilva/courses/cs5630/lec01-notes.pdf lec01-notes.pdf]<br />
<br />
Slides: [http://www.cs.utah.edu/~csilva/courses/cs5630/lec01.pdf lec01.pdf]<br />
<br />
Animations: [http://www.cs.utah.edu/~csilva/courses/cs5630/explosion_640x480-5.mov explosion_640x480-5.mov], [http://www.cs.utah.edu/~csilva/courses/cs5630/fig7.mov fig7.mov], [http://www.cs.utah.edu/~csilva/courses/cs5630/fig8.mov fig8.mov], [http://www.cs.utah.edu/~csilva/courses/cs5630/fig9.mov fig9.mov], [http://www.cs.utah.edu/~csilva/courses/cs5630/SevereTstorm.mov SevereTstorm.mov]<br />
<br />
Further reading: <br />
<br />
[http://www.sci.utah.edu/~csilva/papers/vis2003.pdf Visualizing Spatial and Temporal Variability in Coastal Observatories], W. Herrera-Jimenez, W. Correa, C. Silva, and A. Baptista, IEEE Visualization 2003.<br />
<br />
== 8/23: The visualization pipeline ==<br />
<br />
Lecturer: Claudio<br />
<br />
Topics: Procedural vs. Dataflow programming; Using Dataflow for the Vis Pipeline; Dataflow programming with VTK; Dataflow programming with VisTrails; python.<br />
<br />
Notes: [http://www.cs.utah.edu/~csilva/courses/cs5630/lec02-notes.pdf lec02-notes.pdf]<br />
<br />
Slides: [http://www.cs.utah.edu/~csilva/courses/cs5630/lec02.pdf lec02.pdf]<br />
<br />
VisTrails: During this class, we built a pipeline equivalent to the cone.tcl (see class slides). Here is the vistrails file: [http://www.cs.utah.edu/~csilva/courses/cs5630/cone.vt cone.vt]<br />
<br />
Further reading: <br />
<br />
[http://www.cs.utah.edu/~csilva/courses/cs5630/reproducible_vis.pdf Provenance for Visualizations: Reproducibility and Beyond], C. Silva, J. Freire, and S. Callahan, IEEE Computing in Science and Engineering, to appear.<br />
<br />
== 8/28: Modeling Data for Visualization ==<br />
<br />
Lecturer: Carlos<br />
<br />
Topics: Discrete vs continous data; Sampling and interpolation; Point vs triangulated data; Meshing data types; Regular vs irregular data; Tabular data; Vector and tensor fields<br />
<br />
Notes: TBA<br />
<br />
Slides: [http://www.sci.utah.edu/~cscheid/scivis_fall07/modelling_1.ppt .ppt file]<br />
<br />
Further reading: <br />
<br />
There is no required reading for this lecture. The notes will be available shortly. The following papers are there for people that are looking to get more advanced material that will not be covered in class.<br />
<br />
=== Interpolation ===<br />
<br />
[http://lmi.bwh.harvard.edu/papers/papers/geodesic-loxodromes-final.html Geodesic-loxodromes...] This is the fancy interpolation for diffusion tensors I mentioned in class.<br />
<br />
[http://en.wikipedia.org/wiki/Bernstein_polynomial Bernstein polynomials] These are the polynomials used for cubic Bezier curves that I mentioned in class.<br />
<br />
==== Separability ====<br />
<br />
[http://portal.acm.org/citation.cfm?id=1187793 Extensions of the Zwart-Powell Box spline...] This is a recent paper that shows a class of trivariate reconstruction techniques that are ''not'' separable.<br />
<br />
==== Tensors ====<br />
<br />
[http://www.cs.utah.edu/research/techreports/2004/pdf/UUCS-04-014.pdf Visualization and Analysis of Diffusion Tensor Fields] Gordon Kindlmann's PhD. thesis, with everything you ever wanted to know about DTI. Section 2.1 has a good primer in tensor algebra.<br />
<br />
== 8/30: Modeling Data for Visualization == <br />
<br />
Lecturer: Carlos<br />
<br />
Topics: Geometry Processing: Reconstruction and meshing; Simplification; Smoothing; Other Filtering algorithms<br />
<br />
Notes: [http://www.sci.utah.edu/~cscheid/scivis_fall07/week2.pdf .pdf file]. If you want to print these, you might want to wait for a week or two, until I finish polishing them.<br />
<br />
Slides: [http://www.sci.utah.edu/~cscheid/scivis_fall07/processing.ppt .ppt file] ''These slides include simplificatin algorithms, which I'll talk about next week.''<br />
<br />
== 9/4: Elementary Plotting Techniques == <br />
<br />
Lecturer: Steve<br />
<br />
Topics: Principles of Graph Construction<br />
<br />
Notes: [http://www.sci.utah.edu/~stevec/classes/cs5630/PlottingNotes.pdf PlottingNotes.pdf]<br />
<br />
Slides: [http://www.sci.utah.edu/~stevec/slides/SciVis/Plotting1.pdf Plotting1.pdf]<br />
<br />
Vistrails: See next lecture.<br />
<br />
Further Reading: There is no required reading for this lecture. For those interested in more depth, the following books are very useful:<br />
<br />
* The Elements of Graphing Data. William S. Cleveland, Hobart Press, 2nd Edition, 1994.<br />
* Visualizing Data. William S. Cleveland, Hobart Press, 1993.<br />
* The Visual Display of Quantitative Information. Edward R. Tufte, Graphics Press, 2001.<br />
* Visual Explanations: Images and Quantities, Evidence and Narrative. Edward R. Tufte, Graphics Press, 2997.<br />
<br />
== 9/6: Elementary Plotting Techniques ==<br />
<br />
Lecturer: Steve<br />
<br />
Topics: Simple Plotting Methods: Dot Plots, Connected Symbol Plots, Scatter Plots, Histograms, Others. Advanced Plotting Methods: Multimodal, Higher Dimensional, Correlation, Uncertainty and Variation.<br />
<br />
Notes: [http://www.sci.utah.edu/~stevec/classes/cs5630/PlottingNotes.pdf PlottingNotes.pdf]<br />
<br />
Slides: [http://www.sci.utah.edu/~stevec/slides/SciVis/Plotting2.pdf Plotting2.pdf]<br />
<br />
Vistrails: [http://www.sci.utah.edu/~stevec/classes/cs5630/PlottingVistrails.zip PlottingVistrails.zip] - Unzip this file in the examples directory of your VisTrails installation and it will add the vistrails along with their data sets (in the data directory). If you don't have permission to write to this directory (CADE users), then unzip the file where you want. Just be aware that in this case the paths for the data files may not be correct for most vistrails and will need to be fixed before they will execute properly.<br />
<br />
<br />
Further Reading: There is no required reading for this lecture. Some articles of interest:<br />
<br />
* [http://www.fmrib.ox.ac.uk/analysis/techrep/tr00mj2/tr00mj2/node24.html Histogram Bin Size]<br />
* [http://en.wikipedia.org/wiki/Correlation Correlation]<br />
* [http://en.wikipedia.org/wiki/Linear_regression Linear Regression]<br />
* [http://en.wikipedia.org/wiki/Box_plot Box Plots]<br />
<br />
== 9/11: Color and Human Perception ==<br />
<br />
Lecturer: Claudio<br />
<br />
Topics: Human vision system; Optical illusions<br />
<br />
Notes: TBA<br />
<br />
Slides: [http://www.cs.utah.edu/~csilva/courses/cs5630/human-vision.pdf human-vision.pdf]<br />
<br />
Links:<br />
<br />
http://en.wikipedia.org/wiki/Eye<br />
<br />
http://www.grand-illusions.com/gregory2.htm (also, see the related book: [http://www.amazon.com/Eye-Brain-Richard-L-Gregory/dp/0691048371])<br />
<br />
http://en.wikipedia.org/wiki/Purkinje_effect<br />
<br />
http://www.handprint.com/HP/WCL/color2.html<br />
<br />
== 9/13: Color and Human Perception ==<br />
<br />
Lecturer: Claudio<br />
<br />
Topics: Color Science; Color spaces; Color Blindness; Color maps; Tone mapping<br />
<br />
Notes: TBA<br />
<br />
Slides: [http://www.cs.utah.edu/~csilva/courses/cs5630/colorvision.pdf colorvision.pdf]<br />
<br />
Links:<br />
<br />
Further reading: <br />
<br />
[http://www.research.ibm.com/dx/proceedings/pravda/truevis.htm How Not to Lie with Visualization]<br />
<br />
http://en.wikipedia.org/wiki/Opponent_process<br />
<br />
http://en.wikipedia.org/wiki/Color_models<br />
<br />
http://en.wikipedia.org/wiki/Absolute_color_space<br />
<br />
http://en.wikipedia.org/wiki/Additive_color<br />
<br />
http://en.wikipedia.org/wiki/Subtractive_color<br />
<br />
http://en.wikipedia.org/wiki/RGB_color_model<br />
<br />
http://en.wikipedia.org/wiki/SRGB_color_space<br />
<br />
http://en.wikipedia.org/wiki/CIE_XYZ_color_space<br />
<br />
== 9/18 (a): Color and Human Perception ==<br />
<br />
Lecturer: Claudio<br />
<br />
Same material as previous lecture. <br />
<br />
== 9/18 (b): 2D Visualization Techniques ==<br />
<br />
Lecturer: Carlos<br />
<br />
Topics: 2-D contours, marching quads, marching tris; Color mapping; height fields; NPR<br />
<br />
Slides: [http://www.sci.utah.edu/~cscheid/scivis_fall07/2d_scalar_vis.pdf pdf file]<br />
<br />
Notes: [http://www.sci.utah.edu/~cscheid/scivis_fall07/2d_scalar_vis_notes.pdf pdf file]<br />
<br />
Vistrails: [http://www.sci.utah.edu/~cscheid/scivis_fall07/ozone_and_data.zip zip file with ozone.vt and data] [http://www.sci.utah.edu/~cscheid/scivis_fall07/asymptotic_decider.vt asymptotic decider in 2d] [http://www.sci.utah.edu/~cscheid/scivis_fall07/elevation.zip heightfields]<br />
<br />
Note: These vistrails use relative file paths so you don't need to change each of them individually to match your directory structure. Simply unzip the file to whichever location is more convenient. Then, inside VisTrails, open the VisTrails shell, type:<br />
<br />
import os<br />
os.chdir("c:/directory/where/you/unzipped/it")<br />
<br />
This will change the directory so you should be able to just run the pipelines.<br />
<br />
== 9/20: Math refresher ==<br />
<br />
Lecturer: Carlos<br />
<br />
Topics: Basic linear algebra; vectors; basic differential geometry (space curves, tangents, normals, surfaces); basic vector calculus (gradient, divergence, curl, gauss' theorem, green's theorem) <br />
<br />
== 9/25: 2D Visualization Techniques ==<br />
<br />
Lecturer: Carlos<br />
<br />
Topics: 2-D vector fields, div, grad, curl in 2D; Steady vs Unsteady flows; Glyphs; 2-D streamlines, streaklines, pathlines<br />
<br />
Slides: [http://www.sci.utah.edu/~cscheid/scivis_fall07/2d_vector_vis.pdf pdf file]<br />
<br />
Notes: coming soon<br />
<br />
Vistrails: [http://www.sci.utah.edu/~cscheid/scivis_fall07/vector_vis_1.zip vistrail with steady vector field vis and data] [http://www.sci.utah.edu/~cscheid/scivis_fall07/unsteady.zip vistrail with unsteady vector field vis and data] '''Note:''' Because VTK does not support time-varying datasets directly, we had to create a reasonably ugly hack to simulate unsteady fields. This means the datasets are quite big (80MB in total).<br />
<br />
== 9/27 (a): 2D Visualization Techniques ==<br />
<br />
Lecturer Carlos<br />
<br />
Same material as last lecture.<br />
<br />
== 9/27 (b): Volume Vis ==<br />
<br />
Lecturer: Claudio<br />
<br />
Topics: Slicing; Contours; Marching algorithms<br />
<br />
Slides: [http://www.cs.utah.edu/~csilva/courses/cs5630/iso-basic.pdf iso-basic.pdf]<br />
<br />
References:<br />
<br />
[http://portal.acm.org/citation.cfm?id=37401.37422 Marching cubes: A high resolution 3D surface construction algorithm]<br />
<br />
[http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=175782 The asymptotic decider: resolving the ambiguity in marching cubes]<br />
<br />
== 10/2: Volume Vis == <br />
<br />
Lecturer: Claudio<br />
<br />
Topics: Accelerating structures; High-quality contours<br />
<br />
Slides: <br />
<br />
[http://www.cs.utah.edu/~csilva/courses/cs5630/iso-speed.pdf iso-speed.pdf]<br />
<br />
[http://www.cs.utah.edu/~csilva/courses/cs5630/iso-speed-2.pdf iso-speed-2.pdf]<br />
<br />
References:<br />
<br />
[http://doi.ieeecomputersociety.org/10.1109/2945.489388 A Near Optimal Isosurface Extraction Algorithm Using the Span Space]<br />
<br />
[http://doi.ieeecomputersociety.org/10.1109/2945.485619 Automatic Isosurface Propagation Using an Extrema Graph and Sorted Boundary Cell Lists]<br />
<br />
[http://doi.ieeecomputersociety.org/10.1109/2945.597798 Speeding Up Isosurface Extraction Using Interval Trees]<br />
<br />
[http://doi.ieeecomputersociety.org/10.1109/SVVG.2004.5 Implicit Occluders]<br />
<br />
== 10/4: Volume Vis ==<br />
<br />
Lecturer: Claudio<br />
<br />
Topics: High quality isosurfaces<br />
<br />
Slides: [http://www.cs.utah.edu/~csilva/courses/cs5630/iso-quality.pdf iso-quality.pdf]<br />
<br />
References:<br />
<br />
[http://www.cs.utah.edu/~csilva/2007-sub/macet.pdf Edge Transformations for Improving Mesh Quality of Marching Cubes]<br />
<br />
[http://www.sci.utah.edu/~csilva/papers/tvcg2006acr.pdf High-Quality Extraction of Isosurfaces from Regular and Irregular Grids]<br />
<br />
[http://portal.acm.org/citation.cfm?id=566570.566586 Dual contouring of hermite data]<br />
<br />
[http://www.sci.utah.edu/%7Emiriah/research/meshing/vis07meyer.pdf Topology, Accuracy, and Quality of Isosurface Meshes Using Dynamic Particles]<br />
<br />
[http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=1260744 Material interface reconstruction]<br />
<br />
== 10/9: Fall break == <br />
<br />
== 10/11: Fall break == <br />
<br />
== 10/16: Volume Vis ==<br />
<br />
Lecturer: Claudio<br />
<br />
Topics: continued from last class<br />
<br />
== 10/18: Volume Vis ==<br />
<br />
Lecturer: Steve<br />
<br />
Topics: Transfer functions; function statistics (histograms); multi-dimensional; contour spectrum<br />
<br />
== 10/23: Midterm 1 ==<br />
<br />
== 10/25: Vector and Tensor Visualization ==<br />
<br />
Lecturer: Carlos<br />
<br />
Topics: Differential Geometry in 3D: Div, Grad, Curl; Revisit Unsteady vs. Steady flows; Streamribbons, surfaces, tubes, streamlines and streaklines<br />
<br />
== 10/30: Vector and Tensor Visualization ==<br />
<br />
Lecturer: Claudio<br />
<br />
Topics: LIC; hyper LIC; Topology-based techniques<br />
<br />
== 11/1: Simplification Techniques == <br />
<br />
Guest lecture: Yuan Zhou<br />
<br />
== 11/6: Cosmology and EEG analysis ==<br />
<br />
Guest lecture: Erik Anderson<br />
<br />
== 11/8: Vector and Tensor Vis ==<br />
<br />
Lecturer: Carlos<br />
<br />
Topics: Glyphs; DTI techniques<br />
<br />
== 11/13: Aesthetic Issues in Vis ==<br />
<br />
Lecturer: Claudio<br />
<br />
Topics: Volume Illustration and NPR<br />
<br />
== 11/15: Aesthetic Issues in Vis ==<br />
<br />
Lecturer: Steve<br />
<br />
Topics: Tufte<br />
<br />
== 11/20: Aesthetic Issues in Vis ==<br />
<br />
Lecturer: Steve<br />
<br />
Topics: Tufte<br />
<br />
== 11/22: Thanksgiving == <br />
<br />
== 11/27: Information Visualization ==<br />
<br />
Lecturer: Carlos<br />
<br />
Topics: Parallel coordinates; Graph visualization<br />
<br />
== 11/29: Information Visualization ==<br />
<br />
Lecturer: Claudio<br />
<br />
Topics: Hierarchical data vis; brushing; sizing text<br />
<br />
== 12/4: Data Management for Vis ==<br />
<br />
== 12/6: Vis for presentation/discovery ==<br />
<br />
== 12/11: Open research questions ==</div>Thu, 25 Oct 2007 21:15:14 GMTStevechttps://www.vistrails.org//index.php/Talk:SciVisFall2007/ScheduleSciVisFall2007/Schedule
https://www.vistrails.org//index.php?title=SciVisFall2007/Schedule&diff=856
https://www.vistrails.org//index.php?title=SciVisFall2007/Schedule&diff=856<p>Stevec: /* 10/4: Volume Vis */</p>
<hr />
<div>== 8/21: Introduction to visualization ==<br />
<br />
Lecturer: Claudio<br />
<br />
Topics: Scientific Visualization<br />
<br />
Notes: [http://www.cs.utah.edu/~csilva/courses/cs5630/lec01-notes.pdf lec01-notes.pdf]<br />
<br />
Slides: [http://www.cs.utah.edu/~csilva/courses/cs5630/lec01.pdf lec01.pdf]<br />
<br />
Animations: [http://www.cs.utah.edu/~csilva/courses/cs5630/explosion_640x480-5.mov explosion_640x480-5.mov], [http://www.cs.utah.edu/~csilva/courses/cs5630/fig7.mov fig7.mov], [http://www.cs.utah.edu/~csilva/courses/cs5630/fig8.mov fig8.mov], [http://www.cs.utah.edu/~csilva/courses/cs5630/fig9.mov fig9.mov], [http://www.cs.utah.edu/~csilva/courses/cs5630/SevereTstorm.mov SevereTstorm.mov]<br />
<br />
Further reading: <br />
<br />
[http://www.sci.utah.edu/~csilva/papers/vis2003.pdf Visualizing Spatial and Temporal Variability in Coastal Observatories], W. Herrera-Jimenez, W. Correa, C. Silva, and A. Baptista, IEEE Visualization 2003.<br />
<br />
== 8/23: The visualization pipeline ==<br />
<br />
Lecturer: Claudio<br />
<br />
Topics: Procedural vs. Dataflow programming; Using Dataflow for the Vis Pipeline; Dataflow programming with VTK; Dataflow programming with VisTrails; python.<br />
<br />
Notes: [http://www.cs.utah.edu/~csilva/courses/cs5630/lec02-notes.pdf lec02-notes.pdf]<br />
<br />
Slides: [http://www.cs.utah.edu/~csilva/courses/cs5630/lec02.pdf lec02.pdf]<br />
<br />
VisTrails: During this class, we built a pipeline equivalent to the cone.tcl (see class slides). Here is the vistrails file: [http://www.cs.utah.edu/~csilva/courses/cs5630/cone.vt cone.vt]<br />
<br />
Further reading: <br />
<br />
[http://www.cs.utah.edu/~csilva/courses/cs5630/reproducible_vis.pdf Provenance for Visualizations: Reproducibility and Beyond], C. Silva, J. Freire, and S. Callahan, IEEE Computing in Science and Engineering, to appear.<br />
<br />
== 8/28: Modeling Data for Visualization ==<br />
<br />
Lecturer: Carlos<br />
<br />
Topics: Discrete vs continous data; Sampling and interpolation; Point vs triangulated data; Meshing data types; Regular vs irregular data; Tabular data; Vector and tensor fields<br />
<br />
Notes: TBA<br />
<br />
Slides: [http://www.sci.utah.edu/~cscheid/scivis_fall07/modelling_1.ppt .ppt file]<br />
<br />
Further reading: <br />
<br />
There is no required reading for this lecture. The notes will be available shortly. The following papers are there for people that are looking to get more advanced material that will not be covered in class.<br />
<br />
=== Interpolation ===<br />
<br />
[http://lmi.bwh.harvard.edu/papers/papers/geodesic-loxodromes-final.html Geodesic-loxodromes...] This is the fancy interpolation for diffusion tensors I mentioned in class.<br />
<br />
[http://en.wikipedia.org/wiki/Bernstein_polynomial Bernstein polynomials] These are the polynomials used for cubic Bezier curves that I mentioned in class.<br />
<br />
==== Separability ====<br />
<br />
[http://portal.acm.org/citation.cfm?id=1187793 Extensions of the Zwart-Powell Box spline...] This is a recent paper that shows a class of trivariate reconstruction techniques that are ''not'' separable.<br />
<br />
==== Tensors ====<br />
<br />
[http://www.cs.utah.edu/research/techreports/2004/pdf/UUCS-04-014.pdf Visualization and Analysis of Diffusion Tensor Fields] Gordon Kindlmann's PhD. thesis, with everything you ever wanted to know about DTI. Section 2.1 has a good primer in tensor algebra.<br />
<br />
== 8/30: Modeling Data for Visualization == <br />
<br />
Lecturer: Carlos<br />
<br />
Topics: Geometry Processing: Reconstruction and meshing; Simplification; Smoothing; Other Filtering algorithms<br />
<br />
Notes: [http://www.sci.utah.edu/~cscheid/scivis_fall07/week2.pdf .pdf file]. If you want to print these, you might want to wait for a week or two, until I finish polishing them.<br />
<br />
Slides: [http://www.sci.utah.edu/~cscheid/scivis_fall07/processing.ppt .ppt file] ''These slides include simplificatin algorithms, which I'll talk about next week.''<br />
<br />
== 9/4: Elementary Plotting Techniques == <br />
<br />
Lecturer: Steve<br />
<br />
Topics: Principles of Graph Construction<br />
<br />
Notes: [http://www.sci.utah.edu/~stevec/classes/cs5630/PlottingNotes.pdf PlottingNotes.pdf]<br />
<br />
Slides: [http://www.sci.utah.edu/~stevec/slides/SciVis/Plotting1.pdf Plotting1.pdf]<br />
<br />
Vistrails: See next lecture.<br />
<br />
Further Reading: There is no required reading for this lecture. For those interested in more depth, the following books are very useful:<br />
<br />
* The Elements of Graphing Data. William S. Cleveland, Hobart Press, 2nd Edition, 1994.<br />
* Visualizing Data. William S. Cleveland, Hobart Press, 1993.<br />
* The Visual Display of Quantitative Information. Edward R. Tufte, Graphics Press, 2001.<br />
* Visual Explanations: Images and Quantities, Evidence and Narrative. Edward R. Tufte, Graphics Press, 2997.<br />
<br />
== 9/6: Elementary Plotting Techniques ==<br />
<br />
Lecturer: Steve<br />
<br />
Topics: Simple Plotting Methods: Dot Plots, Connected Symbol Plots, Scatter Plots, Histograms, Others. Advanced Plotting Methods: Multimodal, Higher Dimensional, Correlation, Uncertainty and Variation.<br />
<br />
Notes: [http://www.sci.utah.edu/~stevec/classes/cs5630/PlottingNotes.pdf PlottingNotes.pdf]<br />
<br />
Slides: [http://www.sci.utah.edu/~stevec/slides/SciVis/Plotting2.pdf Plotting2.pdf]<br />
<br />
Vistrails: [http://www.sci.utah.edu/~stevec/classes/cs5630/PlottingVistrails.zip PlottingVistrails.zip] - Unzip this file in the examples directory of your VisTrails installation and it will add the vistrails along with their data sets (in the data directory). If you don't have permission to write to this directory (CADE users), then unzip the file where you want. Just be aware that in this case the paths for the data files may not be correct for most vistrails and will need to be fixed before they will execute properly.<br />
<br />
<br />
Further Reading: There is no required reading for this lecture. Some articles of interest:<br />
<br />
* [http://www.fmrib.ox.ac.uk/analysis/techrep/tr00mj2/tr00mj2/node24.html Histogram Bin Size]<br />
* [http://en.wikipedia.org/wiki/Correlation Correlation]<br />
* [http://en.wikipedia.org/wiki/Linear_regression Linear Regression]<br />
* [http://en.wikipedia.org/wiki/Box_plot Box Plots]<br />
<br />
== 9/11: Color and Human Perception ==<br />
<br />
Lecturer: Claudio<br />
<br />
Topics: Human vision system; Optical illusions<br />
<br />
Notes: TBA<br />
<br />
Slides: [http://www.cs.utah.edu/~csilva/courses/cs5630/human-vision.pdf human-vision.pdf]<br />
<br />
Links:<br />
<br />
http://en.wikipedia.org/wiki/Eye<br />
<br />
http://www.grand-illusions.com/gregory2.htm (also, see the related book: [http://www.amazon.com/Eye-Brain-Richard-L-Gregory/dp/0691048371])<br />
<br />
http://en.wikipedia.org/wiki/Purkinje_effect<br />
<br />
http://www.handprint.com/HP/WCL/color2.html<br />
<br />
== 9/13: Color and Human Perception ==<br />
<br />
Lecturer: Claudio<br />
<br />
Topics: Color Science; Color spaces; Color Blindness; Color maps; Tone mapping<br />
<br />
Notes: TBA<br />
<br />
Slides: [http://www.cs.utah.edu/~csilva/courses/cs5630/colorvision.pdf colorvision.pdf]<br />
<br />
Links:<br />
<br />
Further reading: <br />
<br />
[http://www.research.ibm.com/dx/proceedings/pravda/truevis.htm How Not to Lie with Visualization]<br />
<br />
http://en.wikipedia.org/wiki/Opponent_process<br />
<br />
http://en.wikipedia.org/wiki/Color_models<br />
<br />
http://en.wikipedia.org/wiki/Absolute_color_space<br />
<br />
http://en.wikipedia.org/wiki/Additive_color<br />
<br />
http://en.wikipedia.org/wiki/Subtractive_color<br />
<br />
http://en.wikipedia.org/wiki/RGB_color_model<br />
<br />
http://en.wikipedia.org/wiki/SRGB_color_space<br />
<br />
http://en.wikipedia.org/wiki/CIE_XYZ_color_space<br />
<br />
== 9/18 (a): Color and Human Perception ==<br />
<br />
Lecturer: Claudio<br />
<br />
Same material as previous lecture. <br />
<br />
== 9/18 (b): 2D Visualization Techniques ==<br />
<br />
Lecturer: Carlos<br />
<br />
Topics: 2-D contours, marching quads, marching tris; Color mapping; height fields; NPR<br />
<br />
Slides: [http://www.sci.utah.edu/~cscheid/scivis_fall07/2d_scalar_vis.pdf pdf file]<br />
<br />
Notes: [http://www.sci.utah.edu/~cscheid/scivis_fall07/2d_scalar_vis_notes.pdf pdf file]<br />
<br />
Vistrails: [http://www.sci.utah.edu/~cscheid/scivis_fall07/ozone_and_data.zip zip file with ozone.vt and data] [http://www.sci.utah.edu/~cscheid/scivis_fall07/asymptotic_decider.vt asymptotic decider in 2d] [http://www.sci.utah.edu/~cscheid/scivis_fall07/elevation.zip heightfields]<br />
<br />
Note: These vistrails use relative file paths so you don't need to change each of them individually to match your directory structure. Simply unzip the file to whichever location is more convenient. Then, inside VisTrails, open the VisTrails shell, type:<br />
<br />
import os<br />
os.chdir("c:/directory/where/you/unzipped/it")<br />
<br />
This will change the directory so you should be able to just run the pipelines.<br />
<br />
== 9/20: Math refresher ==<br />
<br />
Lecturer: Carlos<br />
<br />
Topics: Basic linear algebra; vectors; basic differential geometry (space curves, tangents, normals, surfaces); basic vector calculus (gradient, divergence, curl, gauss' theorem, green's theorem) <br />
<br />
== 9/25: 2D Visualization Techniques ==<br />
<br />
Lecturer: Carlos<br />
<br />
Topics: 2-D vector fields, div, grad, curl in 2D; Steady vs Unsteady flows; Glyphs; 2-D streamlines, streaklines, pathlines<br />
<br />
Slides: [http://www.sci.utah.edu/~cscheid/scivis_fall07/2d_vector_vis.pdf pdf file]<br />
<br />
Notes: coming soon<br />
<br />
Vistrails: [http://www.sci.utah.edu/~cscheid/scivis_fall07/vector_vis_1.zip vistrail with steady vector field vis and data] [http://www.sci.utah.edu/~cscheid/scivis_fall07/unsteady.zip vistrail with unsteady vector field vis and data] '''Note:''' Because VTK does not support time-varying datasets directly, we had to create a reasonably ugly hack to simulate unsteady fields. This means the datasets are quite big (80MB in total).<br />
<br />
== 9/27 (a): 2D Visualization Techniques ==<br />
<br />
Lecturer Carlos<br />
<br />
Same material as last lecture.<br />
<br />
== 9/27 (b): Volume Vis ==<br />
<br />
Lecturer: Claudio<br />
<br />
Topics: Slicing; Contours; Marching algorithms<br />
<br />
Slides: [http://www.cs.utah.edu/~csilva/courses/cs5630/iso-basic.pdf iso-basic.pdf]<br />
<br />
References:<br />
<br />
[http://portal.acm.org/citation.cfm?id=37401.37422 Marching cubes: A high resolution 3D surface construction algorithm]<br />
<br />
[http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=175782 The asymptotic decider: resolving the ambiguity in marching cubes]<br />
<br />
== 10/2: Volume Vis == <br />
<br />
Lecturer: Claudio<br />
<br />
Topics: Accelerating structures; High-quality contours<br />
<br />
Slides: <br />
<br />
[http://www.cs.utah.edu/~csilva/courses/cs5630/iso-speed.pdf iso-speed.pdf]<br />
<br />
[http://www.cs.utah.edu/~csilva/courses/cs5630/iso-speed-2.pdf iso-speed-2.pdf]<br />
<br />
References:<br />
<br />
[http://doi.ieeecomputersociety.org/10.1109/2945.489388 A Near Optimal Isosurface Extraction Algorithm Using the Span Space]<br />
<br />
[http://doi.ieeecomputersociety.org/10.1109/2945.485619 Automatic Isosurface Propagation Using an Extrema Graph and Sorted Boundary Cell Lists]<br />
<br />
[http://doi.ieeecomputersociety.org/10.1109/2945.597798 Speeding Up Isosurface Extraction Using Interval Trees]<br />
<br />
[http://doi.ieeecomputersociety.org/10.1109/SVVG.2004.5 Implicit Occluders]<br />
<br />
== 10/4: Volume Vis ==<br />
<br />
Lecturer: Claudio<br />
<br />
Topics: High quality isosurfaces<br />
<br />
Slides: [http://www.cs.utah.edu/~csilva/courses/cs5630/iso-quality.pdf iso-quality.pdf]<br />
<br />
References:<br />
<br />
[http://www.cs.utah.edu/~csilva/2007-sub/macet.pdf Edge Transformations for Improving Mesh Quality of Marching Cubes]<br />
<br />
[http://www.sci.utah.edu/~csilva/papers/tvcg2006acr.pdf High-Quality Extraction of Isosurfaces from Regular and Irregular Grids]<br />
<br />
[http://portal.acm.org/citation.cfm?id=566570.566586 Dual contouring of hermite data]<br />
<br />
[http://www.sci.utah.edu/%7Emiriah/research/meshing/vis07meyer.pdf Topology, Accuracy, and Quality of Isosurface Meshes Using Dynamic Particles]<br />
<br />
[http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=1260744 Material interface reconstruction]<br />
<br />
== 10/9: Fall break == <br />
<br />
== 10/11: Fall break == <br />
<br />
== 10/16: Volume Vis ==<br />
<br />
Lecturer: Steve<br />
<br />
Topics: Unstructured techniques; ray casting; pt; zsweep; havs<br />
<br />
== 10/18: Volume Vis ==<br />
<br />
Lecturer: Steve<br />
<br />
Topics: Transfer functions; function statistics (histograms); multi-dimensional; contour spectrum<br />
<br />
== 10/23: Midterm 1 ==<br />
<br />
== 10/25: Vector and Tensor Visualization ==<br />
<br />
Lecturer: Carlos<br />
<br />
Topics: Differential Geometry in 3D: Div, Grad, Curl; Revisit Unsteady vs. Steady flows; Streamribbons, surfaces, tubes, streamlines and streaklines<br />
<br />
== 10/30: Vector and Tensor Visualization ==<br />
<br />
Lecturer: Claudio<br />
<br />
Topics: LIC; hyper LIC; Topology-based techniques<br />
<br />
== 11/1: Simplification Techniques == <br />
<br />
Guest lecture: Yuan Zhou<br />
<br />
== 11/6: Cosmology and EEG analysis ==<br />
<br />
Guest lecture: Erik Anderson<br />
<br />
== 11/8: Vector and Tensor Vis ==<br />
<br />
Lecturer: Carlos<br />
<br />
Topics: Glyphs; DTI techniques<br />
<br />
== 11/13: Aesthetic Issues in Vis ==<br />
<br />
Lecturer: Claudio<br />
<br />
Topics: Volume Illustration and NPR<br />
<br />
== 11/15: Aesthetic Issues in Vis ==<br />
<br />
Lecturer: Steve<br />
<br />
Topics: Tufte<br />
<br />
== 11/20: Aesthetic Issues in Vis ==<br />
<br />
Lecturer: Steve<br />
<br />
Topics: Tufte<br />
<br />
== 11/22: Thanksgiving == <br />
<br />
== 11/27: Information Visualization ==<br />
<br />
Lecturer: Carlos<br />
<br />
Topics: Parallel coordinates; Graph visualization<br />
<br />
== 11/29: Information Visualization ==<br />
<br />
Lecturer: Claudio<br />
<br />
Topics: Hierarchical data vis; brushing; sizing text<br />
<br />
== 12/4: Data Management for Vis ==<br />
<br />
== 12/6: Vis for presentation/discovery ==<br />
<br />
== 12/11: Open research questions ==</div>Thu, 25 Oct 2007 21:13:31 GMTStevechttps://www.vistrails.org//index.php/Talk:SciVisFall2007/ScheduleSciVisFall2007/Assignment 1
https://www.vistrails.org//index.php?title=SciVisFall2007/Assignment_1&diff=780
https://www.vistrails.org//index.php?title=SciVisFall2007/Assignment_1&diff=780<p>Stevec: /* Problem 1 */</p>
<hr />
<div>The assignment is due at midnight on October 4, 2007. You will need to use the CADE handin functionality to turn in your assignment. The class account is "cs5630".<br />
<br />
The purpose of this assignment is to make sure you understand the basic plotting concepts covered in class. Examples of plotting were provided after the lectures and can be found here: [http://www.sci.utah.edu/~stevec/classes/cs5630/PlottingVistrails.zip PlottingVistrails.zip]. As you work on the assignment, we encourage you to read the available documentation on both [http://matplotlib.sourceforge.net/ matplotlib] and [http://www.diveintopython.org/ python].<br />
<br />
Here is the initial vistrail file [http://www.sci.utah.edu/~stevec/classes/cs5630/hw1.vt hw1.vt] and plotting data [http://www.sci.utah.edu/~stevec/classes/cs5630/hw1_data.zip hw1_data.zip] that you should use for completing your work. The paths in the existing File modules may need to be updated in the vistrail to correctly execute the existing nodes. You should add upon this vistrail to do your assignment. As before, show your work by submitting the complete vistrail you used to solve the problem<br />
<br />
The data we will be using for this assignment comes from weather measurements near Snowbird Ski Resort in Little Cottonwood Canyon (original data found [http://www.wcc.nrcs.usda.gov/snotel/snotel.pl?sitenum=766&state=ut here] and [http://www.skiengine.com/resorts/usa/utah/ski-resorts.html here]). To make things simpler, the data we provide has been reformatted so that it is easy to parse. The measurements were taken daily (or monthly) for a water year (Starting Oct 1 and ending Sep 30).<br />
<br />
== Problem 1 ==<br />
<br />
This problem deals with simple connected symbol plots, as shown in the MaunaLoaPlot.vt example. The "Precip" node in the history tree plots a list accumulated precipitation in inches for monthly measurements in 2007. Start with this node and perform the following changes. Label them "Problem 1a", "Problem 1b", etc.<br />
<br />
a. Apply the principles of plotting described in class (and in the class notes) to improve the vision and the understanding of the plot. Note, not all principles may be addressable with matplotlib. In the notes for the node, list the principles that were addressed and how they were addressed.<br />
<br />
b. The "Precip" pipeline reads data for 2007 from precip07.dat. Directly compare this with the 2006 measurements found in precip06.dat by Superposition (on the same plot).<br />
<br />
c. Repeat part b, but compare using Juxtaposition (each plot in a different spreadsheet cell). In the notes, describe which technique (superpostion vs. juxtaposition) makes the most sense for this data and why.<br />
<br />
== Problem 2 ==<br />
<br />
This problem deals with histograms and showing distributions of data, for an example see the "Histogram" node in terminator.vt in the VisTrails examples directory. The data file snowdepth07.dat contains snow depths in inches for the entire water year (one entry per line). Show the distribution of snow depths using a histogram. In the notes, describe how you chose the number of bins that were used.<br />
<br />
== Problem 3 ==<br />
<br />
This problem deals with dot plots for labeled data, as an example, see DeathRate.vt. The annual_snowfall.dat file consists of all the Utah ski resorts and their average annual snowfall in inches (in the form string:int just like the DeathRate data). Interestingly, there is no correlation between snow fall and ticket cost. Plot the data on a dot plot and in the notes, describe what you had to did to the plot.<br />
<br />
== Problem 4 ==<br />
This problem deals with correlation (for an example, see the Correlation.vt example). The temp_precip07.dat file contains a line for each day of the year which includes the air temperature in Celcius and amount of precipitation in inches (in form "10:0.5" for 10 degrees C and 0.5 inches). Note, this is a similar format that the labeled data in the MammalScaling.vt example is provided, so you can use a similar parser. Perform the following tasks and label the nodes "Problem4a", "Problem4b", etc.<br />
<br />
a. (Grads and UGrads) Plot the data using a scatterplot with temperature on the X axis and precipitation on the Y axis. Be sure to use the basic principles of plotting. In the notes for this node, describe any correlation that you can perceive (rough judgement, not calculated) and any conclusions that could be drawn. <br />
<br />
b. (Grads only) Because of the limited resolution of the measurements, the data takes a regular spacing and points are stacked. This makes it difficult to analyze concentrations of the data. Resolve this problem by using one of the following techniques:<br />
* jittering: Perturb the points by a small amount of randomness such that the overlap is reduced.<br />
* symbols: Find stacked points and represent them using one point that is drawn differently (heavier weight or different symbol)<br />
* colormap: Find stacked points and color them differently depending on how many are in the stack.<br />
<br />
In the notes for the node, describe what you did.<br />
<br />
c. (Grads only) Perform a linear regression to fit a line through the data. Is a degree 1 polynomial (line) what you would expect to see for this data? What happens with a higher degree polynomial such as a cubic (degree 3) polynomial? Note, the 3rd parameter of the scipy.polyfit function defines the degree of the polynomial. The number of coefficients returned from scipy.polyfit is determined by the degree. Thus (ar,br) = scipy.polyfit(x,y,1) would need to be (ar,br,cr) = scipy.polyfit(x,y,2). The polyval function would need to be changed in a similar way. Also note that a sort on the x axis may need to be performed on the data for the polyval points to be monotonic (and thus not overlapping). In the notes, describe what fit you settled on and why.</div>Wed, 26 Sep 2007 16:41:44 GMTStevechttps://www.vistrails.org//index.php/Talk:SciVisFall2007/Assignment_1SciVisFall2007/Assignment 1
https://www.vistrails.org//index.php?title=SciVisFall2007/Assignment_1&diff=778
https://www.vistrails.org//index.php?title=SciVisFall2007/Assignment_1&diff=778<p>Stevec: /* Problem 1 */</p>
<hr />
<div>The assignment is due at midnight on October 4, 2007. You will need to use the CADE handin functionality to turn in your assignment. The class account is "cs5630".<br />
<br />
The purpose of this assignment is to make sure you understand the basic plotting concepts covered in class. Examples of plotting were provided after the lectures and can be found here: [http://www.sci.utah.edu/~stevec/classes/cs5630/PlottingVistrails.zip PlottingVistrails.zip]. As you work on the assignment, we encourage you to read the available documentation on both [http://matplotlib.sourceforge.net/ matplotlib] and [http://www.diveintopython.org/ python].<br />
<br />
Here is the initial vistrail file [http://www.sci.utah.edu/~stevec/classes/cs5630/hw1.vt hw1.vt] and plotting data [http://www.sci.utah.edu/~stevec/classes/cs5630/hw1_data.zip hw1_data.zip] that you should use for completing your work. The paths in the existing File modules may need to be updated in the vistrail to correctly execute the existing nodes. You should add upon this vistrail to do your assignment. As before, show your work by submitting the complete vistrail you used to solve the problem<br />
<br />
The data we will be using for this assignment comes from weather measurements near Snowbird Ski Resort in Little Cottonwood Canyon (original data found [http://www.wcc.nrcs.usda.gov/snotel/snotel.pl?sitenum=766&state=ut here] and [http://www.skiengine.com/resorts/usa/utah/ski-resorts.html here]). To make things simpler, the data we provide has been reformatted so that it is easy to parse. The measurements were taken daily (or monthly) for a water year (Starting Oct 1 and ending Sep 30).<br />
<br />
== Problem 1 ==<br />
<br />
This problem deals with simple connected symbol plots, as shown in the MaunaLoaPlot.vt example. The "Precip" node in the history tree plots a list accumulated precipitation in inches for monthly measurements in 2007. Start with this node and perform the following changes. Label them "Problem 1a", "Problem 1b", etc.<br />
<br />
a. Apply the principles of plotting described in class (and in the class notes) to improve the vision and the understanding of the plot. In the notes, list the principles that were addressed and how they were addressed.<br />
<br />
b. The "Precip" pipeline reads data for 2007 from precip07.dat. Directly compare this with the 2006 measurements found in precip06.dat by Superposition (on the same plot).<br />
<br />
c. Repeat part b, but compare using Juxtaposition (each plot in a different spreadsheet cell). In the notes, describe which technique (superpostion vs. juxtaposition) makes the most sense for this data and why.<br />
<br />
== Problem 2 ==<br />
<br />
This problem deals with histograms and showing distributions of data, for an example see the "Histogram" node in terminator.vt in the VisTrails examples directory. The data file snowdepth07.dat contains snow depths in inches for the entire water year (one entry per line). Show the distribution of snow depths using a histogram. In the notes, describe how you chose the number of bins that were used.<br />
<br />
== Problem 3 ==<br />
<br />
This problem deals with dot plots for labeled data, as an example, see DeathRate.vt. The annual_snowfall.dat file consists of all the Utah ski resorts and their average annual snowfall in inches (in the form string:int just like the DeathRate data). Interestingly, there is no correlation between snow fall and ticket cost. Plot the data on a dot plot and in the notes, describe what you had to did to the plot.<br />
<br />
== Problem 4 ==<br />
This problem deals with correlation (for an example, see the Correlation.vt example). The temp_precip07.dat file contains a line for each day of the year which includes the air temperature in Celcius and amount of precipitation in inches (in form "10:0.5" for 10 degrees C and 0.5 inches). Note, this is a similar format that the labeled data in the MammalScaling.vt example is provided, so you can use a similar parser. Perform the following tasks and label the nodes "Problem4a", "Problem4b", etc.<br />
<br />
a. (Grads and UGrads) Plot the data using a scatterplot with temperature on the X axis and precipitation on the Y axis. Be sure to use the basic principles of plotting. In the notes for this node, describe any correlation that you can perceive (rough judgement, not calculated) and any conclusions that could be drawn. <br />
<br />
b. (Grads only) Because of the limited resolution of the measurements, the data takes a regular spacing and points are stacked. This makes it difficult to analyze concentrations of the data. Resolve this problem by using one of the following techniques:<br />
* jittering: Perturb the points by a small amount of randomness such that the overlap is reduced.<br />
* symbols: Find stacked points and represent them using one point that is drawn differently (heavier weight or different symbol)<br />
* colormap: Find stacked points and color them differently depending on how many are in the stack.<br />
<br />
In the notes for the node, describe what you did.<br />
<br />
c. (Grads only) Perform a linear regression to fit a line through the data. Is a degree 1 polynomial (line) what you would expect to see for this data? What happens with a higher degree polynomial such as a cubic (degree 3) polynomial? Note, the 3rd parameter of the scipy.polyfit function defines the degree of the polynomial. The number of coefficients returned from scipy.polyfit is determined by the degree. Thus (ar,br) = scipy.polyfit(x,y,1) would need to be (ar,br,cr) = scipy.polyfit(x,y,2). The polyval function would need to be changed in a similar way. Also note that a sort on the x axis may need to be performed on the data for the polyval points to be monotonic (and thus not overlapping). In the notes, describe what fit you settled on and why.</div>Wed, 26 Sep 2007 15:28:34 GMTStevechttps://www.vistrails.org//index.php/Talk:SciVisFall2007/Assignment_1SciVisFall2007
https://www.vistrails.org//index.php?title=SciVisFall2007&diff=777
https://www.vistrails.org//index.php?title=SciVisFall2007&diff=777<p>Stevec: /* Assignments */</p>
<hr />
<div>This page contains information on the Scientific Visualization course (CS 5630/6630) taught by [http://www.cs.utah.edu/~csilva Professor Cl&aacute;udio Silva] during Fall 2007 in the [http://www.cs.utah.edu School of Computing], [http://www.utah.edu University of Utah].<br />
<br />
This class meets on Tuesday and Thursdays, 10:45am-12:05am, WEB 112.<br />
<br />
== Course Overview == <br />
<br />
The demand for the construction of [http://en.wikipedia.org/wiki/Scientific_visualization complex visualizations] is growing in many disciplines of science, as users are faced with ever increasing volumes of data to analyze. In this class, we will cover the principles and techniques necessary to generate these visualizations. <br />
<br />
There will be no required textbook, although we recommend that students get a copy of the [http://www.amazon.com/Visualization-Handbook-Charles-D-Hansen/dp/012387582X Visualization Handbook] as a "reference at large". Also, Kitware's [http://www.kitware.com/products/vtkguide.html VTK User's Guide] might be useful. We will be providing a detailed set of course notes for the class.<br />
<br />
For the assignments, we will be using [http://www.vistrails.org VisTrails], [http://www.vtk.org VTK], and [http://matplotlib.sourceforge.net matplotlib] in this class. For each assignment, the students will need to turn in their complete "vistrail" for the work. <br />
<br />
Besides the assignments, there will be one midterm and one final. <br />
<br />
== Lectures, and consulting hours ==<br />
<br />
We will meet twice a week: Tuesday, Thursday, 10:45am-12:05pm, WEB 112.<br />
<br />
The instructor for the class is Claudio Silva.<br />
<br />
The lectures (and corresponding notes) will be giving by Claudio Silva, Steve Callahan, and Carlos Scheidegger.<br />
<br />
The TA for the course is Harsh Doshi.<br />
<br />
Silva office hours: Tuesdays and Thursdays (9:45 - 10:45 am), WEB 4893.<br />
<br />
Doshi office hours: Mondays and Wednesdays (1:00 - 4:00 pm), MEB 3115.<br />
<br />
== Schedule ==<br />
<br />
[http://www.vistrails.org/index.php/SciVisFall2007/Schedule Schedule]<br />
<br />
== Reading ==<br />
<br />
The class wiki page will contain up-to-date notes that reflect the material covered in class. We will also add pointers to supplementary material.<br />
<br />
In the tentative schedule, there are hints on what to read before attending the class. <br />
<br />
[http://www.vistrails.org/index.php/SciVisFall2007/VTK_Tips Tips for converting VTK pipelines]<br />
<br />
== Assignments ==<br />
<br />
For the assignments, you will be turning in ".vt" files produced with VisTrails. Here is a link to a Windows XP (also works for Vista) installer with the version that you will need: [http://www.vistrails.org/download/download.php?id=vistrails-setup-1.0brev921.zip VisTrails 1.0 beta]<br />
<br />
[http://www.vistrails.org/index.php/SciVisFall2007/Assignment_0 Assignment_0]<br />
<br />
[http://www.vistrails.org/index.php/SciVisFall2007/Assignment_1 Assignment_1]<br />
<br />
== Late Assignments ==<br />
<br />
Assignments will not be accepted late. Students will be given a one-time two-day exemption for an unexpected event.<br />
<br />
== Grading ==<br />
<br />
Your grade will be a combination of assignments (70%) and midterm (15%) and final (15%).<br />
<br />
== Mailing List ==<br />
<br />
http://mailman.cs.utah.edu/mailman/listinfo/cs5630<br />
<br />
== Students With Disabilities ==<br />
<br />
The University of Utah seeks to provide equal access to its programs, services and activities for people with disabilities. If you will need accommodations in the class, reasonable prior notice needs to be given to the Center for Disability Services, 162 Olpin Union Building, 581-5020 (V/TDD). CDS will work with you and the instructor to make arrangements for accommodations.<br />
<br />
All written information in this course can be made available in alternative format with prior notification to the Center for Disability Services.</div>Mon, 24 Sep 2007 23:16:08 GMTStevechttps://www.vistrails.org//index.php/Talk:SciVisFall2007SciVisFall2007/Assignment 1
https://www.vistrails.org//index.php?title=SciVisFall2007/Assignment_1&diff=776
https://www.vistrails.org//index.php?title=SciVisFall2007/Assignment_1&diff=776<p>Stevec: </p>
<hr />
<div>The assignment is due at midnight on October 4, 2007. You will need to use the CADE handin functionality to turn in your assignment. The class account is "cs5630".<br />
<br />
The purpose of this assignment is to make sure you understand the basic plotting concepts covered in class. Examples of plotting were provided after the lectures and can be found here: [http://www.sci.utah.edu/~stevec/classes/cs5630/PlottingVistrails.zip PlottingVistrails.zip]. As you work on the assignment, we encourage you to read the available documentation on both [http://matplotlib.sourceforge.net/ matplotlib] and [http://www.diveintopython.org/ python].<br />
<br />
Here is the initial vistrail file [http://www.sci.utah.edu/~stevec/classes/cs5630/hw1.vt hw1.vt] and plotting data [http://www.sci.utah.edu/~stevec/classes/cs5630/hw1_data.zip hw1_data.zip] that you should use for completing your work. The paths in the existing File modules may need to be updated in the vistrail to correctly execute the existing nodes. You should add upon this vistrail to do your assignment. As before, show your work by submitting the complete vistrail you used to solve the problem<br />
<br />
The data we will be using for this assignment comes from weather measurements near Snowbird Ski Resort in Little Cottonwood Canyon (original data found [http://www.wcc.nrcs.usda.gov/snotel/snotel.pl?sitenum=766&state=ut here] and [http://www.skiengine.com/resorts/usa/utah/ski-resorts.html here]). To make things simpler, the data we provide has been reformatted so that it is easy to parse. The measurements were taken daily (or monthly) for a water year (Starting Oct 1 and ending Sep 30).<br />
<br />
== Problem 1 ==<br />
<br />
This problem deals with simple connected symbol plots, as shown in the MaunaLoaPlot.vt example. The "Precip" node in the history tree plots a list accumulated precipitation in inches for monthly measurements in 2007. Start with this node and perform the following changes. Label them "Problem 1a", "Problem 1b", etc.<br />
<br />
a. Apply the principles of plotting described in the notes to improve the vision and the understanding of the plot. In the notes, list the principles that were addressed and how they were addressed.<br />
<br />
b. The "Precip" pipeline reads data for 2007 from precip07.dat. Directly compare this with the 2006 measurements found in precip06.dat by Superposition (on the same plot).<br />
<br />
c. Repeat part b, but compare using Juxtaposition (each plot in a different spreadsheet cell). In the notes, describe which technique (superpostion vs. juxtaposition) makes the most sense for this data and why.<br />
<br />
== Problem 2 ==<br />
<br />
This problem deals with histograms and showing distributions of data, for an example see the "Histogram" node in terminator.vt in the VisTrails examples directory. The data file snowdepth07.dat contains snow depths in inches for the entire water year (one entry per line). Show the distribution of snow depths using a histogram. In the notes, describe how you chose the number of bins that were used.<br />
<br />
== Problem 3 ==<br />
<br />
This problem deals with dot plots for labeled data, as an example, see DeathRate.vt. The annual_snowfall.dat file consists of all the Utah ski resorts and their average annual snowfall in inches (in the form string:int just like the DeathRate data). Interestingly, there is no correlation between snow fall and ticket cost. Plot the data on a dot plot and in the notes, describe what you had to did to the plot.<br />
<br />
== Problem 4 ==<br />
This problem deals with correlation (for an example, see the Correlation.vt example). The temp_precip07.dat file contains a line for each day of the year which includes the air temperature in Celcius and amount of precipitation in inches (in form "10:0.5" for 10 degrees C and 0.5 inches). Note, this is a similar format that the labeled data in the MammalScaling.vt example is provided, so you can use a similar parser. Perform the following tasks and label the nodes "Problem4a", "Problem4b", etc.<br />
<br />
a. (Grads and UGrads) Plot the data using a scatterplot with temperature on the X axis and precipitation on the Y axis. Be sure to use the basic principles of plotting. In the notes for this node, describe any correlation that you can perceive (rough judgement, not calculated) and any conclusions that could be drawn. <br />
<br />
b. (Grads only) Because of the limited resolution of the measurements, the data takes a regular spacing and points are stacked. This makes it difficult to analyze concentrations of the data. Resolve this problem by using one of the following techniques:<br />
* jittering: Perturb the points by a small amount of randomness such that the overlap is reduced.<br />
* symbols: Find stacked points and represent them using one point that is drawn differently (heavier weight or different symbol)<br />
* colormap: Find stacked points and color them differently depending on how many are in the stack.<br />
<br />
In the notes for the node, describe what you did.<br />
<br />
c. (Grads only) Perform a linear regression to fit a line through the data. Is a degree 1 polynomial (line) what you would expect to see for this data? What happens with a higher degree polynomial such as a cubic (degree 3) polynomial? Note, the 3rd parameter of the scipy.polyfit function defines the degree of the polynomial. The number of coefficients returned from scipy.polyfit is determined by the degree. Thus (ar,br) = scipy.polyfit(x,y,1) would need to be (ar,br,cr) = scipy.polyfit(x,y,2). The polyval function would need to be changed in a similar way. Also note that a sort on the x axis may need to be performed on the data for the polyval points to be monotonic (and thus not overlapping). In the notes, describe what fit you settled on and why.</div>Mon, 24 Sep 2007 21:28:54 GMTStevechttps://www.vistrails.org//index.php/Talk:SciVisFall2007/Assignment_1SciVisFall2007/Assignment 1
https://www.vistrails.org//index.php?title=SciVisFall2007/Assignment_1&diff=775
https://www.vistrails.org//index.php?title=SciVisFall2007/Assignment_1&diff=775<p>Stevec: </p>
<hr />
<div>This is your first real assignment for CS 5630/6630. <br />
<br />
The assignment is due at midnight on October 4, 2007. You will need to use the CADE handin functionality to turn in your assignment. The class account is "cs5630".<br />
<br />
The purpose of this assignment is to make sure you understand the basic plotting concepts covered in class. Examples of plotting were provided after the lectures and can be found here: [http://www.sci.utah.edu/~stevec/classes/cs5630/PlottingVistrails.zip PlottingVistrails.zip]. As you work on the assignment, we encourage you to read the available documentation on both [http://matplotlib.sourceforge.net/ matplotlib] and [http://www.diveintopython.org/ python].<br />
<br />
Here is the initial vistrail file [http://www.sci.utah.edu/~stevec/classes/cs5630/hw1.vt hw1.vt] and plotting data [http://www.sci.utah.edu/~stevec/classes/cs5630/hw1_data.zip hw1_data.zip] that you should use for completing your work. The paths in the existing File modules may need to be updated in the vistrail to correctly execute the existing nodes. You should add upon this vistrail to do your assignment. As before, show your work by submitting the complete vistrail you used to solve the problem<br />
<br />
The data we will be using for this assignment comes from weather measurements near Snowbird Ski Resort in Little Cottonwood Canyon (original data found [http://www.wcc.nrcs.usda.gov/snotel/snotel.pl?sitenum=766&state=ut here] and [http://www.skiengine.com/resorts/usa/utah/ski-resorts.html here]). To make things simpler, the data we provide has been reformatted so that it is easy to parse. The measurements were taken daily (or monthly) for a water year (Starting Oct 1 and ending Sep 30).<br />
<br />
== Problem 1 ==<br />
<br />
This problem deals with simple connected symbol plots, as shown in the MaunaLoaPlot.vt example. The "Precip" node in the history tree plots a list accumulated precipitation in inches for monthly measurements in 2007. Start with this node and perform the following changes. Label them "Problem 1a", "Problem 1b", etc.<br />
<br />
a. Apply the principles of plotting described in the notes to improve the vision and the understanding of the plot. In the notes, list the principles that were addressed and how they were addressed.<br />
<br />
b. The "Precip" pipeline reads data for 2007 from precip07.dat. Directly compare this with the 2006 measurements found in precip06.dat by Superposition (on the same plot).<br />
<br />
c. Repeat part b, but compare using Juxtaposition (each plot in a different spreadsheet cell). In the notes, describe which technique (superpostion vs. juxtaposition) makes the most sense for this data and why.<br />
<br />
== Problem 2 ==<br />
<br />
This problem deals with histograms and showing distributions of data, for an example see the "Histogram" node in terminator.vt in the VisTrails examples directory. The data file snowdepth07.dat contains snow depths in inches for the entire water year (one entry per line). Show the distribution of snow depths using a histogram. In the notes, describe how you chose the number of bins that were used.<br />
<br />
== Problem 3 ==<br />
<br />
This problem deals with dot plots for labeled data, as an example, see DeathRate.vt. The annual_snowfall.dat file consists of all the Utah ski resorts and their average annual snowfall in inches (in the form string:int just like the DeathRate data). Interestingly, there is no correlation between snow fall and ticket cost. Plot the data on a dot plot and in the notes, describe what you had to did to the plot.<br />
<br />
== Problem 4 ==<br />
This problem deals with correlation (for an example, see the Correlation.vt example). The temp_precip07.dat file contains a line for each day of the year which includes the air temperature in Celcius and amount of precipitation in inches (in form "10:0.5" for 10 degrees C and 0.5 inches). Note, this is a similar format that the labeled data in the MammalScaling.vt example is provided, so you can use a similar parser. Perform the following tasks and label the nodes "Problem4a", "Problem4b", etc.<br />
<br />
a. (Grads and UGrads) Plot the data using a scatterplot with temperature on the X axis and precipitation on the Y axis. Be sure to use the basic principles of plotting. In the notes for this node, describe any correlation that you can perceive (rough judgement, not calculated) and any conclusions that could be drawn. <br />
<br />
b. (Grads only) Because of the limited resolution of the measurements, the data takes a regular spacing and points are stacked. This makes it difficult to analyze concentrations of the data. Resolve this problem by using one of the following techniques:<br />
* jittering: Perturb the points by a small amount of randomness such that the overlap is reduced.<br />
* symbols: Find stacked points and represent them using one point that is drawn differently (heavier weight or different symbol)<br />
* colormap: Find stacked points and color them differently depending on how many are in the stack.<br />
<br />
In the notes for the node, describe what you did.<br />
<br />
c. (Grads only) Perform a linear regression to fit a line through the data. Is a degree 1 polynomial (line) what you would expect to see for this data? What happens with a higher degree polynomial such as a cubic (degree 3) polynomial? Note, the 3rd parameter of the scipy.polyfit function defines the degree of the polynomial. The number of coefficients returned from scipy.polyfit is determined by the degree. Thus (ar,br) = scipy.polyfit(x,y,1) would need to be (ar,br,cr) = scipy.polyfit(x,y,2). The polyval function would need to be changed in a similar way. Also note that a sort on the x axis may need to be performed on the data for the polyval points to be monotonic (and thus not overlapping). In the notes, describe what fit you settled on and why.</div>Mon, 24 Sep 2007 21:28:43 GMTStevechttps://www.vistrails.org//index.php/Talk:SciVisFall2007/Assignment_1SciVisFall2007/Assignment 1
https://www.vistrails.org//index.php?title=SciVisFall2007/Assignment_1&diff=774
https://www.vistrails.org//index.php?title=SciVisFall2007/Assignment_1&diff=774<p>Stevec: </p>
<hr />
<div>This is your first real assignment for CS 5630/6630. <br />
<br />
The assignment is due at midnight on October 4, 2007. You will need to use the CADE handin functionality to turn in your assignment. The class account is "cs5630".<br />
<br />
The purpose of this initial assignment is to make sure you understand the basic plotting concepts covered in class. Examples of plotting were provided after the lectures and can be found here: [http://www.sci.utah.edu/~stevec/classes/cs5630/PlottingVistrails.zip PlottingVistrails.zip]. As you work on the assignment, we encourage you to read the available documentation on both [http://matplotlib.sourceforge.net/ matplotlib] and [http://www.diveintopython.org/ python].<br />
<br />
Here is the initial vistrail file [http://www.sci.utah.edu/~stevec/classes/cs5630/hw1.vt hw1.vt] and plotting data [http://www.sci.utah.edu/~stevec/classes/cs5630/hw1_data.zip hw1_data.zip] that you should use for completing your work. The paths in the existing File modules may need to be updated in the vistrail to correctly execute the existing nodes. You should add upon this vistrail to do your assignment. As before, show your work by submitting the complete vistrail you used to solve the problem<br />
<br />
The data we will be using for this assignment comes from weather measurements near Snowbird Ski Resort in Little Cottonwood Canyon (original data found [http://www.wcc.nrcs.usda.gov/snotel/snotel.pl?sitenum=766&state=ut here] and [http://www.skiengine.com/resorts/usa/utah/ski-resorts.html here]). To make things simpler, the data we provide has been reformatted so that it is easy to parse. The measurements were taken daily (or monthly) for a water year (Starting Oct 1 and ending Sep 30).<br />
<br />
== Problem 1 ==<br />
<br />
This problem deals with simple connected symbol plots, as shown in the MaunaLoaPlot.vt example. The "Precip" node in the history tree plots a list accumulated precipitation in inches for monthly measurements in 2007. Start with this node and perform the following changes. Label them "Problem 1a", "Problem 1b", etc.<br />
<br />
a. Apply the principles of plotting described in the notes to improve the vision and the understanding of the plot. In the notes, list the principles that were addressed and how they were addressed.<br />
<br />
b. The "Precip" pipeline reads data for 2007 from precip07.dat. Directly compare this with the 2006 measurements found in precip06.dat by Superposition (on the same plot).<br />
<br />
c. Repeat part b, but compare using Juxtaposition (each plot in a different spreadsheet cell). In the notes, describe which technique (superpostion vs. juxtaposition) makes the most sense for this data and why.<br />
<br />
== Problem 2 ==<br />
<br />
This problem deals with histograms and showing distributions of data, for an example see the "Histogram" node in terminator.vt in the VisTrails examples directory. The data file snowdepth07.dat contains snow depths in inches for the entire water year (one entry per line). Show the distribution of snow depths using a histogram. In the notes, describe how you chose the number of bins that were used.<br />
<br />
== Problem 3 ==<br />
<br />
This problem deals with dot plots for labeled data, as an example, see DeathRate.vt. The annual_snowfall.dat file consists of all the Utah ski resorts and their average annual snowfall in inches (in the form string:int just like the DeathRate data). Interestingly, there is no correlation between snow fall and ticket cost. Plot the data on a dot plot and in the notes, describe what you had to did to the plot.<br />
<br />
== Problem 4 ==<br />
This problem deals with correlation (for an example, see the Correlation.vt example). The temp_precip07.dat file contains a line for each day of the year which includes the air temperature in Celcius and amount of precipitation in inches (in form "10:0.5" for 10 degrees C and 0.5 inches). Note, this is a similar format that the labeled data in the MammalScaling.vt example is provided, so you can use a similar parser. Perform the following tasks and label the nodes "Problem4a", "Problem4b", etc.<br />
<br />
a. (Grads and UGrads) Plot the data using a scatterplot with temperature on the X axis and precipitation on the Y axis. Be sure to use the basic principles of plotting. In the notes for this node, describe any correlation that you can perceive (rough judgement, not calculated) and any conclusions that could be drawn. <br />
<br />
b. (Grads only) Because of the limited resolution of the measurements, the data takes a regular spacing and points are stacked. This makes it difficult to analyze concentrations of the data. Resolve this problem by using one of the following techniques:<br />
* jittering: Perturb the points by a small amount of randomness such that the overlap is reduced.<br />
* symbols: Find stacked points and represent them using one point that is drawn differently (heavier weight or different symbol)<br />
* colormap: Find stacked points and color them differently depending on how many are in the stack.<br />
<br />
In the notes for the node, describe what you did.<br />
<br />
c. (Grads only) Perform a linear regression to fit a line through the data. Is a degree 1 polynomial (line) what you would expect to see for this data? What happens with a higher degree polynomial such as a cubic (degree 3) polynomial? Note, the 3rd parameter of the scipy.polyfit function defines the degree of the polynomial. The number of coefficients returned from scipy.polyfit is determined by the degree. Thus (ar,br) = scipy.polyfit(x,y,1) would need to be (ar,br,cr) = scipy.polyfit(x,y,2). The polyval function would need to be changed in a similar way. Also note that a sort on the x axis may need to be performed on the data for the polyval points to be monotonic (and thus not overlapping). In the notes, describe what fit you settled on and why.</div>Mon, 24 Sep 2007 21:28:20 GMTStevechttps://www.vistrails.org//index.php/Talk:SciVisFall2007/Assignment_1SciVisFall2007/Assignment 1
https://www.vistrails.org//index.php?title=SciVisFall2007/Assignment_1&diff=773
https://www.vistrails.org//index.php?title=SciVisFall2007/Assignment_1&diff=773<p>Stevec: /* Problem 4 */</p>
<hr />
<div>This is your first real assignment for CS 5630/6630. <br />
<br />
The assignment is due at midnight on September ??, 2007. You will need to use the CADE handin functionality to turn in your assignment. The class account is "cs5630".<br />
<br />
The purpose of this initial assignment is to make sure you understand the basic plotting concepts covered in class. Examples of plotting were provided after the lectures and can be found here: [http://www.sci.utah.edu/~stevec/classes/cs5630/PlottingVistrails.zip PlottingVistrails.zip]. As you work on the assignment, we encourage you to read the available documentation on both [http://matplotlib.sourceforge.net/ matplotlib] and [http://www.diveintopython.org/ python].<br />
<br />
Here is the initial vistrail file [http://www.sci.utah.edu/~stevec/classes/cs5630/hw1.vt hw1.vt] and plotting data [http://www.sci.utah.edu/~stevec/classes/cs5630/hw1_data.zip hw1_data.zip] that you should use for completing your work. The paths in the existing File modules may need to be updated in the vistrail to correctly execute the existing nodes. You should add upon this vistrail to do your assignment. As before, show your work by submitting the complete vistrail you used to solve the problem<br />
<br />
The data we will be using for this assignment comes from weather measurements near Snowbird Ski Resort in Little Cottonwood Canyon (original data found [http://www.wcc.nrcs.usda.gov/snotel/snotel.pl?sitenum=766&state=ut here] and [http://www.skiengine.com/resorts/usa/utah/ski-resorts.html here]). To make things simpler, the data we provide has been reformatted so that it is easy to parse. The measurements were taken daily (or monthly) for a water year (Starting Oct 1 and ending Sep 30).<br />
<br />
== Problem 1 ==<br />
<br />
This problem deals with simple connected symbol plots, as shown in the MaunaLoaPlot.vt example. The "Precip" node in the history tree plots a list accumulated precipitation in inches for monthly measurements in 2007. Start with this node and perform the following changes. Label them "Problem 1a", "Problem 1b", etc.<br />
<br />
a. Apply the principles of plotting described in the notes to improve the vision and the understanding of the plot. In the notes, list the principles that were addressed and how they were addressed.<br />
<br />
b. The "Precip" pipeline reads data for 2007 from precip07.dat. Directly compare this with the 2006 measurements found in precip06.dat by Superposition (on the same plot).<br />
<br />
c. Repeat part b, but compare using Juxtaposition (each plot in a different spreadsheet cell). In the notes, describe which technique (superpostion vs. juxtaposition) makes the most sense for this data and why.<br />
<br />
== Problem 2 ==<br />
<br />
This problem deals with histograms and showing distributions of data, for an example see the "Histogram" node in terminator.vt in the VisTrails examples directory. The data file snowdepth07.dat contains snow depths in inches for the entire water year (one entry per line). Show the distribution of snow depths using a histogram. In the notes, describe how you chose the number of bins that were used.<br />
<br />
== Problem 3 ==<br />
<br />
This problem deals with dot plots for labeled data, as an example, see DeathRate.vt. The annual_snowfall.dat file consists of all the Utah ski resorts and their average annual snowfall in inches (in the form string:int just like the DeathRate data). Interestingly, there is no correlation between snow fall and ticket cost. Plot the data on a dot plot and in the notes, describe what you had to did to the plot.<br />
<br />
== Problem 4 ==<br />
This problem deals with correlation (for an example, see the Correlation.vt example). The temp_precip07.dat file contains a line for each day of the year which includes the air temperature in Celcius and amount of precipitation in inches (in form "10:0.5" for 10 degrees C and 0.5 inches). Note, this is a similar format that the labeled data in the MammalScaling.vt example is provided, so you can use a similar parser. Perform the following tasks and label the nodes "Problem4a", "Problem4b", etc.<br />
<br />
a. (Grads and UGrads) Plot the data using a scatterplot with temperature on the X axis and precipitation on the Y axis. Be sure to use the basic principles of plotting. In the notes for this node, describe any correlation that you can perceive (rough judgement, not calculated) and any conclusions that could be drawn. <br />
<br />
b. (Grads only) Because of the limited resolution of the measurements, the data takes a regular spacing and points are stacked. This makes it difficult to analyze concentrations of the data. Resolve this problem by using one of the following techniques:<br />
* jittering: Perturb the points by a small amount of randomness such that the overlap is reduced.<br />
* symbols: Find stacked points and represent them using one point that is drawn differently (heavier weight or different symbol)<br />
* colormap: Find stacked points and color them differently depending on how many are in the stack.<br />
<br />
In the notes for the node, describe what you did.<br />
<br />
c. (Grads only) Perform a linear regression to fit a line through the data. Is a degree 1 polynomial (line) what you would expect to see for this data? What happens with a higher degree polynomial such as a cubic (degree 3) polynomial? Note, the 3rd parameter of the scipy.polyfit function defines the degree of the polynomial. The number of coefficients returned from scipy.polyfit is determined by the degree. Thus (ar,br) = scipy.polyfit(x,y,1) would need to be (ar,br,cr) = scipy.polyfit(x,y,2). The polyval function would need to be changed in a similar way. Also note that a sort on the x axis may need to be performed on the data for the polyval points to be monotonic (and thus not overlapping). In the notes, describe what fit you settled on and why.</div>Mon, 24 Sep 2007 15:26:28 GMTStevechttps://www.vistrails.org//index.php/Talk:SciVisFall2007/Assignment_1SciVisFall2007/Assignment 1
https://www.vistrails.org//index.php?title=SciVisFall2007/Assignment_1&diff=772
https://www.vistrails.org//index.php?title=SciVisFall2007/Assignment_1&diff=772<p>Stevec: /* Problem 1 */</p>
<hr />
<div>This is your first real assignment for CS 5630/6630. <br />
<br />
The assignment is due at midnight on September ??, 2007. You will need to use the CADE handin functionality to turn in your assignment. The class account is "cs5630".<br />
<br />
The purpose of this initial assignment is to make sure you understand the basic plotting concepts covered in class. Examples of plotting were provided after the lectures and can be found here: [http://www.sci.utah.edu/~stevec/classes/cs5630/PlottingVistrails.zip PlottingVistrails.zip]. As you work on the assignment, we encourage you to read the available documentation on both [http://matplotlib.sourceforge.net/ matplotlib] and [http://www.diveintopython.org/ python].<br />
<br />
Here is the initial vistrail file [http://www.sci.utah.edu/~stevec/classes/cs5630/hw1.vt hw1.vt] and plotting data [http://www.sci.utah.edu/~stevec/classes/cs5630/hw1_data.zip hw1_data.zip] that you should use for completing your work. The paths in the existing File modules may need to be updated in the vistrail to correctly execute the existing nodes. You should add upon this vistrail to do your assignment. As before, show your work by submitting the complete vistrail you used to solve the problem<br />
<br />
The data we will be using for this assignment comes from weather measurements near Snowbird Ski Resort in Little Cottonwood Canyon (original data found [http://www.wcc.nrcs.usda.gov/snotel/snotel.pl?sitenum=766&state=ut here] and [http://www.skiengine.com/resorts/usa/utah/ski-resorts.html here]). To make things simpler, the data we provide has been reformatted so that it is easy to parse. The measurements were taken daily (or monthly) for a water year (Starting Oct 1 and ending Sep 30).<br />
<br />
== Problem 1 ==<br />
<br />
This problem deals with simple connected symbol plots, as shown in the MaunaLoaPlot.vt example. The "Precip" node in the history tree plots a list accumulated precipitation in inches for monthly measurements in 2007. Start with this node and perform the following changes. Label them "Problem 1a", "Problem 1b", etc.<br />
<br />
a. Apply the principles of plotting described in the notes to improve the vision and the understanding of the plot. In the notes, list the principles that were addressed and how they were addressed.<br />
<br />
b. The "Precip" pipeline reads data for 2007 from precip07.dat. Directly compare this with the 2006 measurements found in precip06.dat by Superposition (on the same plot).<br />
<br />
c. Repeat part b, but compare using Juxtaposition (each plot in a different spreadsheet cell). In the notes, describe which technique (superpostion vs. juxtaposition) makes the most sense for this data and why.<br />
<br />
== Problem 2 ==<br />
<br />
This problem deals with histograms and showing distributions of data, for an example see the "Histogram" node in terminator.vt in the VisTrails examples directory. The data file snowdepth07.dat contains snow depths in inches for the entire water year (one entry per line). Show the distribution of snow depths using a histogram. In the notes, describe how you chose the number of bins that were used.<br />
<br />
== Problem 3 ==<br />
<br />
This problem deals with dot plots for labeled data, as an example, see DeathRate.vt. The annual_snowfall.dat file consists of all the Utah ski resorts and their average annual snowfall in inches (in the form string:int just like the DeathRate data). Interestingly, there is no correlation between snow fall and ticket cost. Plot the data on a dot plot and in the notes, describe what you had to did to the plot.<br />
<br />
== Problem 4 ==<br />
This problem deals with correlation (for an example, see the Correlation.vt example). The temp_precip07.dat file contains a line for each day of the year which includes the air temperature in Celcius and amount of precipitation in inches (in form "10:0.5" for 10 degrees C and 0.5 inches). Note, this is a similar format that the labeled data in the MammalScaling.vt example is provided, so you can use a similar parser. Perform the following tasks and label the nodes "Problem4a", "Problem4b", etc.<br />
<br />
a. (Grads and UGrads) Plot the data using a scatterplot with temperature on the X axis and precipitation on the Y axis. Be sure to use the basic principles of plotting. In the notes for this node, describe any correlation that you can perceive (rough judgement, not calculated) and any conclusions that could be drawn. <br />
<br />
b. (Grads only) Because of the limited resolution of the measurements, the data takes a regular spacing and points are stacked. This makes it difficult to analyze concentrations of the data. Resolve this problem by using one of the following techniques:<br />
* jittering: Perturb the points by a small amount of randomness such that the overlap is reduced.<br />
* symbols: Find stacked points and represent them using one point that is drawn differently (heavier weight or different symbol)<br />
* colormap: Find stacked points and color them differently depending on how many are in the stack.<br />
<br />
In the notes for the node, describe what you did.<br />
<br />
c. (Grads only) Perform a linear regression to fit a line through the data. Is a degree 1 polynomial (line) sufficient? What happens with a higher degree polynomial such as a cubic (degree 3) polynomial? Note, the 3rd parameter of the scipy.polyfit function defines the degree of the polynomial. The number of coefficients returned from scipy.polyfit is determined by the degree. Thus (ar,br) = scipy.polyfit(x,y,1) would need to be (ar,br,cr) = scipy.polyfit(x,y,2). The polyval function would need to be changed in a similar way. Also note that a sort on the x axis may need to be performed on the data for the polyval points to be monotonic (and thus not overlapping). In the notes, describe what fit you settled on and why.</div>Fri, 21 Sep 2007 23:52:40 GMTStevechttps://www.vistrails.org//index.php/Talk:SciVisFall2007/Assignment_1SciVisFall2007/Assignment 1
https://www.vistrails.org//index.php?title=SciVisFall2007/Assignment_1&diff=771
https://www.vistrails.org//index.php?title=SciVisFall2007/Assignment_1&diff=771<p>Stevec: /* Problem 2 */</p>
<hr />
<div>This is your first real assignment for CS 5630/6630. <br />
<br />
The assignment is due at midnight on September ??, 2007. You will need to use the CADE handin functionality to turn in your assignment. The class account is "cs5630".<br />
<br />
The purpose of this initial assignment is to make sure you understand the basic plotting concepts covered in class. Examples of plotting were provided after the lectures and can be found here: [http://www.sci.utah.edu/~stevec/classes/cs5630/PlottingVistrails.zip PlottingVistrails.zip]. As you work on the assignment, we encourage you to read the available documentation on both [http://matplotlib.sourceforge.net/ matplotlib] and [http://www.diveintopython.org/ python].<br />
<br />
Here is the initial vistrail file [http://www.sci.utah.edu/~stevec/classes/cs5630/hw1.vt hw1.vt] and plotting data [http://www.sci.utah.edu/~stevec/classes/cs5630/hw1_data.zip hw1_data.zip] that you should use for completing your work. The paths in the existing File modules may need to be updated in the vistrail to correctly execute the existing nodes. You should add upon this vistrail to do your assignment. As before, show your work by submitting the complete vistrail you used to solve the problem<br />
<br />
The data we will be using for this assignment comes from weather measurements near Snowbird Ski Resort in Little Cottonwood Canyon (original data found [http://www.wcc.nrcs.usda.gov/snotel/snotel.pl?sitenum=766&state=ut here] and [http://www.skiengine.com/resorts/usa/utah/ski-resorts.html here]). To make things simpler, the data we provide has been reformatted so that it is easy to parse. The measurements were taken daily (or monthly) for a water year (Starting Oct 1 and ending Sep 30).<br />
<br />
== Problem 1 ==<br />
<br />
This problem deals with simple connected symbol plots, as shown in the MaunaLoa.vt example. The "Precip" node in the history tree plots a list accumulated precipitation in inches for monthly measurements in 2007. Start with this node and perform the following changes. Label them "Problem 1a", "Problem 1b", etc.<br />
<br />
a. Apply the principles of plotting described in the notes to improve the vision and the understanding of the plot. In the notes, list the principles that were addressed and how they were addressed.<br />
<br />
b. The "Precip" pipeline reads data for 2007 from precip07.dat. Directly compare this with the 2006 measurements found in precip06.dat by Superposition (on the same plot).<br />
<br />
c. Repeat part b, but compare using Juxtaposition (each plot in a different spreadsheet cell). In the notes, describe which technique (superpostion vs. juxtaposition) makes the most sense for this data and why.<br />
<br />
== Problem 2 ==<br />
<br />
This problem deals with histograms and showing distributions of data, for an example see the "Histogram" node in terminator.vt in the VisTrails examples directory. The data file snowdepth07.dat contains snow depths in inches for the entire water year (one entry per line). Show the distribution of snow depths using a histogram. In the notes, describe how you chose the number of bins that were used.<br />
<br />
== Problem 3 ==<br />
<br />
This problem deals with dot plots for labeled data, as an example, see DeathRate.vt. The annual_snowfall.dat file consists of all the Utah ski resorts and their average annual snowfall in inches (in the form string:int just like the DeathRate data). Interestingly, there is no correlation between snow fall and ticket cost. Plot the data on a dot plot and in the notes, describe what you had to did to the plot.<br />
<br />
== Problem 4 ==<br />
This problem deals with correlation (for an example, see the Correlation.vt example). The temp_precip07.dat file contains a line for each day of the year which includes the air temperature in Celcius and amount of precipitation in inches (in form "10:0.5" for 10 degrees C and 0.5 inches). Note, this is a similar format that the labeled data in the MammalScaling.vt example is provided, so you can use a similar parser. Perform the following tasks and label the nodes "Problem4a", "Problem4b", etc.<br />
<br />
a. (Grads and UGrads) Plot the data using a scatterplot with temperature on the X axis and precipitation on the Y axis. Be sure to use the basic principles of plotting. In the notes for this node, describe any correlation that you can perceive (rough judgement, not calculated) and any conclusions that could be drawn. <br />
<br />
b. (Grads only) Because of the limited resolution of the measurements, the data takes a regular spacing and points are stacked. This makes it difficult to analyze concentrations of the data. Resolve this problem by using one of the following techniques:<br />
* jittering: Perturb the points by a small amount of randomness such that the overlap is reduced.<br />
* symbols: Find stacked points and represent them using one point that is drawn differently (heavier weight or different symbol)<br />
* colormap: Find stacked points and color them differently depending on how many are in the stack.<br />
<br />
In the notes for the node, describe what you did.<br />
<br />
c. (Grads only) Perform a linear regression to fit a line through the data. Is a degree 1 polynomial (line) sufficient? What happens with a higher degree polynomial such as a cubic (degree 3) polynomial? Note, the 3rd parameter of the scipy.polyfit function defines the degree of the polynomial. The number of coefficients returned from scipy.polyfit is determined by the degree. Thus (ar,br) = scipy.polyfit(x,y,1) would need to be (ar,br,cr) = scipy.polyfit(x,y,2). The polyval function would need to be changed in a similar way. Also note that a sort on the x axis may need to be performed on the data for the polyval points to be monotonic (and thus not overlapping). In the notes, describe what fit you settled on and why.</div>Fri, 21 Sep 2007 23:52:19 GMTStevechttps://www.vistrails.org//index.php/Talk:SciVisFall2007/Assignment_1