2000-01-18 Lecture 1: Course administrivia. Presentations of the - - PowerPoint PPT Presentation

Mats Nyl´ en January 19, 2000 Slide 1 of 21

2000-01-18

• Lecture 1:

– Course administrivia. – Presentations of the lecturer, the students and the course.

• Lecture 2:

– Introduction to scientific visualization. – Object oriented design.

• Textbook: Lecture 2 covers chapter 1 and 2 in the textbook.
• Exercises: 2.4, 2.5, 2.7.

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Mats Nyl´ en January 19, 2000 Slide 2 of 21

The home of the course

The web page for this course is located at: http://www.cs.umu.se/kurser/TDBD13/VT00/ I will try to put all relevant information there. VIS00

Mats Nyl´ en January 19, 2000 Slide 3 of 21

Schedule change

• Friday 21/1: Lectures from 8.15 – 12.00
• Friday 28/1: Cancelled
• Tuesday 1/2: Lectures from 8.15 – 12.00 Note: from 10-12 we’re in

MA378. VIS00

Mats Nyl´ en January 19, 2000 Slide 4 of 21

And the lecturer is ...

Mats Nyl´ en

• PhD in Theoretical Physics (1985)
• Lecturer (in theoretical physics) since 1989
• Advanced consultant at HPC2N since 1997.

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And the students are ...

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Examination

There will be four assignments on this course, two (very) short and two

• longer. The reports on the assignments will be in the form of web-pages!

There is a written exam at the end of the course. Home-work problems towards bonus on the exam? VIS00

Mats Nyl´ en January 19, 2000 Slide 7 of 21

Goals

The goals of this course is to

• Give students an introduction to Scientific Visualization and a working

knowledge of the more common techniques and algorithms.

• Give students experience of developing visualizationapplications.
• Give students an overview of application areas where Scientific Visual-

ization is of importance VIS00

Mats Nyl´ en January 19, 2000 Slide 8 of 21

Main contents

• Graphical representation of data.
• Basic visualization algorithms for fields.
• Volume visualization.
• Visualization systems and toolkits.
• Application examples.

Textbook: William Schroeder, Ken Martin and Bill Lorensen (1998) The Visualization Toolkit, 2nd ed. Prentice Hall. We cover most of this book (chapters 11-12 excluded). VIS00

Mats Nyl´ en January 19, 2000 Slide 9 of 21

Scientific Visualization

Scientific Visualization is the process of exploring data, in order to gain insight and understanding. Important characteristics of visualization is: 1 Typically the dimensionality of the data is at least 3. 2 Visualization concerns itself with data transformation. 3 Visualization is naturally interactive. VIS00

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The visualization loop

The figure below illustrates the visualization loop, or pipeline. The data may come from most anywhere: simulations, experiments, observations etc.

Data Transform Mapping Display Interactive Feedback

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A trivial example

Consider the function defined by f′′(x) + f(x) = f(0) = f′(0) = 1 VIS00

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Mathematical analysis

A mathematical analysis gives a lot of information, for example f(x)2 + f′(x)2 = 1 and f(x + 2π) = f(x) and f(x + π) = −f(x) etc. We also get a Taylor-expansion f(x) = x − x3 6 + x5 120 + O(x7) VIS00

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Visualizing it

We just plot the function for x-values from -10 to 10.

• 1
• 0.8
• 0.6
• 0.4
• 0.2

0.2 0.4 0.6 0.8 1

• 10
• 5

5 10 f(x) x

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Roadmap

1D 0D 1D 2D 3D

Dimensionality of the representation

nD 3D 2D

Dimensionality of the computational domain

Lines Curves Attribute Mapping Attribute Icons Mapping Height Fields Pseudo Color Contour Maps Images Tiled Surfaces Stacked Textures Ribbons Volume Rendering Solids Modelling 3D Vector Nets Field Vectors Hedge Hogs Ribbons Points Contour Maps Field Vectors Space Curves Scatter Plots Particles Dot Lines Scatter Plots Particle Tracers Dot Surfaces

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Mats Nyl´ en January 19, 2000 Slide 15 of 21

Visualization software

There is a lot of different types of software in use for the purpose of

• visualization. From a users point of view we can see three basic types:

1 Modular visualization environments (MVE), complete enviroments for the development of visualizations. 2 Software toolkits, i.e., libraries that can be helpful when creating visu- alization applications. 3 Specialized visualization applications. VIS00

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MVE’s

These environments gives the user direct interactive control over the visual- ization pipeline, usually through a visual programming interface. Canonical examples are:

• AVS/Express, from AVS,
• IBM OpenDX, from IBM,
• IRIX Explorer, from NAG.

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Toolkits

Toolkits offer the possibility to develop visualisation applications using a variety of visualization techniques. A typical example of a toolkit is “vtk”, the visualization toolkit. Using a toolkit, like “vtk” for example, gives greater flexibility and more

• pportunities to optimize the visualization pipeline in comparison with us-

ing a MVE. This is paid for in terms of a longer and more cumbersome development cycle. VIS00

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Specialized applications

These are applications specialised for a certain type of data visualisation. Two examples (out of very many)

• rasmol for viewing large molecules,
• vis5d to visualize weather data.

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Object oriented design

• Good software design
• Terminology

– Objects, attributes and methods – Inheritance

• Modelling and design

– The object model – The dynamic model – The functional model VIS00

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Why object oriented

Some major reasons:

• Visualization is a complex task

– OO kan handle complexity

• Easy to map application domain to implementation domain

– Great fit with graphics

• OO promotes modular systems
• OO technology i mature
• OO technology is accepted by industry

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Summary and outlook

• Visualization is about discovery not presentation.
• It is all in the data.
• On Friday we will work through chapters 3-4 and begin with 5

– Computer graphics overview – The visualization pipeline – Basic data representation.

• And on next Tuesday we will get an introduction to AVS/Express.

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