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*Subject*: visualizing data in 3-D*From*: patrick(at)es.ucsc.edu (Patrick McEnaney)*Date*: 7 Aug 2001 10:56:47 -0700*Newsgroups*: comp.lang.idl-pvwave*Organization*: http://groups.google.com/*Xref*: news.doit.wisc.edu comp.lang.idl-pvwave:26070

Folks- I'm attempting to construct a 3-D visualization of oceanographic data. My data is in columnar ascii format. I need to interpolate corresponding data values at three different locations. For example, I have a density value of 21.9 kg/m^3 measured at three different locations and I want to visualize a density stratification surface interpolated between the three locations where the horizontal axes are space between the locations and the vertical axes are depth. What I have currently for the procedure is below. It is currently just a mangled set of lines which obviously won't work. the *pstate variables correspond to 3 different data sets in a pointer array stacked on top of each other. So x1 is a depth column, and y1 is a density column, x2 & y2 are depth and density columns from a second location, ditto with x3/y3 at a third location. Could xplot3d or slicer3 work for this? Or should I use a combination of surfr and t3d as opposed to the current code? x1 = reform((*pstate).profiledata(0,*,0)) y1 = reform((*pstate).profiledata(1,*,0)) x2 = reform((*pstate).profiledata(0,*,1)) y2 = reform((*pstate).profiledata(1,*,1)) x3 = reform((*pstate).profiledata(0,*,2)) y3 = reform((*pstate).profiledata(1,*,2)) print, 'working' ; interpolate 1st data onto 2nd data alt grid y01 = interpol(y1, x1, x2) ; interpolate 3rd data onto 2nd data alt grid y03 = interpol(y3, x3, x2) ; concatenate arrays y = [transpose(y01), transpose(y2), transpose(y03)] x = [0,1,2] contour, y, x, x2 Thanks for any suggestions, Patrick

**Follow-Ups**:**Re: visualizing data in 3-D***From:*Craig Markwardt

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