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Re: Constructing Color Tables in IDL [message #8215] Tue, 18 February 1997 00:00 Go to previous message
agraps is currently offline  agraps
Messages: 35
Registered: September 1994
Member
davidf@dfanning.com (David Fanning) writes:

> Jack Saba writes:

>> Thanks for the review. However, those of us who are not used to building
>> color tables should know that generating one that gives the best
>> representation of the data for a particular purpose is trickier than
>> might be expected. See, for example,
>>
>> Rogowitz, Bernice E., and Lloyd A. Treinish
>> "How Not to Lie with Visualization",
>> Computers In Physics 10(3):268, 1996

[...]
> I would recommend two additional books by Edward Tufte if
> people are interested in this topic: _The Visual Display of
> Quantitative Information_ and _Envisoning Information_.
> These books have really changed the way I write IDL programs.

(same for me)

Anyone here seen the movie: "The Glitzomatic", which is a very funny
sequence about vizualizing data (You start with data that is
practically nothing and you end with a full-color-shaded-surface
animation with a narrator, meanwhile the Glitz factor increases and
increases until an overload value is reached.) ? This movie was shown
at a SIGRAPH 4 or 5 years ago, and later, a nice article in Science
News was written about it.

If you are interested in this subject (vizualization), there is
another reference I can recommend. Al Globus (NASA Ames), who was
strongly influenced by Edward Tufte, wrote a classic (in my opinion)
satirical paper a few years ago:

"14 Ways to Say Nothing with Scientific Visualization," A. Globus,
E. Raible, IEEE Computer, July 1994.

Which you can get in postscript form from:

http://www.nas.nasa.gov/NAS/TechReports/RNRreports/aglobus/R NR-92-006/
RNR-92-006.html

The abstract follows.

"Scientific visualization can be used to produce very beautiful images.
Frequently users and others not properly initiated into the mysteries of
visualization research fail to appreciate the artistic qualities of
these images. Scientists will frequently use our work to needlessly
understand the data from which it is derived. This paper describes a
number of effective techniques to confound such pernicious activity."

Amara


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Amara Graps email: agraps@netcom.com
Computational Physics vita: finger agraps@best.com
Multiplex Answers URL: http://www.amara.com/
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