| Akima interpolation methods in IDL? [message #81296] |
Fri, 31 August 2012 03:08 |
Jasdeep Anand
Messages: 16
Registered: August 2011
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Junior Member |
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I have a set of atmospheric profiles (that is, concentrations of trace
gases that vary with altitude) that I'd like to interpolate onto a
smaller, coarser grid. The concentrations vary quite rapidly with
altitude, such that there are a number of very small and very large
values present in the same dataset, and I would ideally like to use an
interpolation method that would allow this variation to be maintained
in some form. The data is only 1-D (that is, I have only one abscissa
and one ordinate), so I don't think I can use functions like TRIGRID.
To date I've tried using SPLINE and INTERPOL to perform this
interpolation, but due to how irregular my data is these produce
wildly incorrect results. I've been told by colleagues that the Akima
interpolation method (described in this paper: http://student.ndhu.edu.tw/~u9111023/akima.pdf)
is best suited for situations like these, but I've been unable to find
any libraries that perform this algorithm. Does such a library exist,
or are their other interpolation methods available that would be more
sensitive to local variations than SPLINE or INTERPOL? I'd be grateful
for any advice on this matter.
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