After successful completion of the course, students are able to (among others)

•     to judge geometric algorithms and data structures with respect to their runtime complexity;
•     to describe geometric algorithms and data structures and weigh their pros and cons;
•     implement geometric algorithms and data structures in a problem-centered manner.

The content of this course covers the representation and analysis of geometric data using different algorithmic methods. This includes fundamental aspects of algorithms per se (definition, complexity analysis, efficiency). In particular, algorithms and data structures for simple and advanced geometric problems as well as sweep and spatial access methods are covered.

The content of the course particularly includes the acquisition of the skills and abilities to solve these problems programmatically using Python.

 

Lecture; solving exercises independently (with help)

The lectures and lab sessions will be held in presence. Upon prior notice, individual sessions can be held in distance learning mode if required by the circumstances.

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Oral exam (closed book)

Working knowledge in Python.