NOTICE: This version of the NSF Unidata web site (archive.unidata.ucar.edu) is no longer being updated.
Current content can be found at unidata.ucar.edu.
To learn about what's going on, see About the Archive Site.
Hi guys, We are making heavy use of contour lines in our applications (hardly surprising so far) ... A couple of points have come up where we would like to improve on the way things are done. Firstly, we find that it is possible to zoom in over an area where no contour labels are visible. This is undesirable, so we would really like to force a relabelling of contour lines based on what is currently visible after every zoom action. Also, the contour lines are clearly linear lines of best fit. Just taking a guess, it looks like the contour lines are built by drawing a straight line until the line of best fit diverges too much from the data, at which point a new line is started. We would like to use a smoother line-fitting algorithm, which I suppose would be done by fitting nonlinear lines of best fit instead. I'm happy to do the legwork, but am having trouble finding where the relevant areas of code are. I'd really appreciate an overview of the contour labelling algorithm and event structure, and also a description of how the current contour fitting algorithm works. Thanks, -Tennessee
visad
archives: