MAT-82306 Scientific Visualization, 4 cr

Lisätiedot

Lectured every second calendar year (during academic years starting with an odd number).
Suitable for postgraduate studies. Ei toteuteta lukuvuonna 2016-2017.

Vastuuhenkilö

Ossi Nykänen

Opetus

Toteutuskerta Periodi Vastuuhenkilö Suoritusvaatimukset
MAT-82306 2016-01 - Ossi Nykänen
Esko Turunen
The grade is based on the assignments and the final exam.

Osaamistavoitteet

Scientific visualization is about rigorously and semi-automatically processing and projecting data in terms of visual and interactive representations with analysis or application utility. After actively studying the course, the student understands the basic concepts, methods, and applications related to scientific (data) visualization. Further, the student knows a wide range of different specific visualization techniques, can implement certain kinds of simple scientific visualizations using Matlab and Paraview, and has basic understanding how to critically evaluate the resulting visualizations.

Sisältö

Sisältö Ydinsisältö Täydentävä tietämys Erityistietämys
1. Fundamental scientific (data) visualization concepts (incl. interpolation, artefacts, use of symmetry, etc.); Visualization targets and benefits; Dataset and grid concepts  Identification of the "nearby tasks" (incl. data pre-processing, scientific computing, and planning for perception)   
2. Examples of various scientific visualizations techniques by dataset type; Visualization process and visualization pipeline   Classification of visualization software; Hands-on skills using the selected applications (Matlab, ParaView); Interaction and feedback mechanisms   
3. Data structures and techniques related to basic scalar visualization techniques (colormaps, contours, isosurfaces, elevation plots); Data structures and techniques related to basic vector visualization techniques (vector glyphs, vector color coding, displacement plots, stream objects);   Selected, more specific scientific visualization areas (tensor, image, and volume visualization)   
4. Information visualization basics and application examples (incl. table lens, graph, tree, and parallel coordinate visualisation techniques)  Relationship to general-purpose data processing pipelines and visualization systems   

Ohjeita opiskelijalle osaamisen tasojen saavuttamiseksi

Working actively with the exercises and the assignments, hands-on and throughout the course, is essential. (Simply "listening" and "reading" is not enough.)

Arvosteluasteikko:

Numerical evaluation scale (0-5)

Tietoa esitietovaatimuksista
Hands-on programming/scripting skills are recommended. Basic understanding on the rudimentary (numerical) scientific computation methods is helpful, but strictly speaking not needed in every application.



Vastaavuudet

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MAT-82306 Scientific Visualization, 4 cr MAT-63606 Scientific Visualization, 5 cr  

Päivittäjä: Ikonen Suvi-Päivikki, 18.04.2016