# Gridding options

• Subject: Gridding options
• From: Ben Tupper <btupper(at)bigelow.org>
• Date: Tue, 29 Aug 2000 09:11:28 -0600
• Newsgroups: comp.lang.idl-pvwave
• Organization: Bigelow Laboratory for Ocean Science
• Xref: news.doit.wisc.edu comp.lang.idl-pvwave:21142

```Hello,

I'm staring (again) at largish set of CTD casts from a recent cruise.
The cast data is comprised of sample information from every 0.5 meters
from the surface to the seafloor.   The 20 or so casts are separated
from each other by about 10-20km and are nearly colinear.   I need to
interpolate a 2d grid from these values.   In the past I have used the
techniques described to grid the data.   I list them here in hopes that
someone familiar with this kind of data can suggest alternatives.

1.   Triangulation and TRIGRID, this method works quickly and
preserves the different 'clines' (pycno-, halo- thermo-, ...) very
well.   Since the seafloor is very irregular, I spend a good deal of
effort fiddling with masks and blanking the boundaries.   This method
also accentuates the noisiness of the data (median filtering of each
cast prior to gridding helps.)   Despite having to play twister with the
boundary/masking stuff, this is the method we use right now.

2. MIN_CURVE_SURF, this method is fairly fast but the details are
lost.

3.  A home grown Inverse-Distance-To-A-Power method, this method is
slow for large datasets and tends to produce a bull's eye pattern around
isolated features (especially common in the biological data set.)
(Sorry, JD, it does have loopity-loops.  You can flick a worm into the
air... but that doesn't mean it knows how to fly!  I'm still trying to
figure out what .....

****************************************
tt=total(a[(((dy=((di=lindgen(((n=nx<ny)),nx+ny-1)))/n))*(nx gt
ny?1:nx)+ \$
(nx gt ny?1:-1)*((dx=di mod n))*(nx-1))>0<(nx*ny-1)]* \$
(dy ge dx AND (dy-dx) lt nx>ny),1)
****************************************

means.   Maybe I need to drink less/more coffee. )

4. KRIG_2D,  this method is so slow (for the size of the data set)
that I haven't had the patience to wait for the result.   I know that
KRIGING routine that will interpolate large grids quickly ( I have seen
it produce a grid in a matter of minutes from similar data... I have
waited hours for a similar result from IDL.)

So, are there alternatives for gridding in IDL?

Thanks,

Ben
--
Ben Tupper
Bigelow Laboratory for Ocean Science
West Boothbay Harbor, Maine
btupper@bigelow.org
note: email address new as of 25JULY2000

```