Go to Main Content

Purdue Self-Service

 

HELP | EXIT

Catalog Entries

 

Spring 2022
Mar 28, 2024
Transparent Image
Information Select the Course Number to get further detail on the course. Select the desired Schedule Type to find available classes for the course. The Schedule Type links will be available only when the schedule of classes is available for the selected term.

CS 53000 - Introduction To Scientific Visualization
Credit Hours: 3.00. Teaches the fundamentals of scientific visualization and prepares students to apply these techniques in fields such as astronomy, biology, chemistry, engineering, and physics. Emphasis is on the representation of scalar, vector, and tensor fields; data sampling and resampling; and reconstruction using multivariate finite elements (surfaces, volumes, and surfaces on surfaces).
3.000 Credit hours

Syllabus Available
Levels: Graduate, Professional, Undergraduate
Schedule Types: Distance Learning, Lecture

Offered By: College of Science
Department: Computer Science

Course Attributes:
Upper Division

May be offered at any of the following campuses:     
      West Lafayette Continuing Ed
      West Lafayette

Learning Outcomes: 1. Learn basic notions of human vision and color perception that inform the design of effective visual representations. 2. Know different models of color perception and understand their connection to the anatomy of the visual system. 3. Be familiar with several color spaces and know their perceptual properties. 4. Know how to devise effective color scales suitable for different data mapping needs. 5. Learn the data structures and data reconstruction techniques that are needed to create continuous visual representations of discrete simulation or experimental datasets. 6. Be familiar with the main grid types used in numerical simulations, know what data structures can be used to represent them in memory, and the associated footprint. 7. Know various data interpolation methods and understand their relationship with grid topology. 8. Know how to efficiently solve the point location problem, whereby the cell must be determined that encloses an arbitrary spatial location. 9. Learn the main visualization techniques for scalar, vector, and tensor datasets.



Return to Previous New Search XML Extract
Transparent Image
Skip to top of page
Release: 8.7.2.4