Stephen,<div><br></div><div> This is the kind of problem that can be easily solved in PyGrADS. For example, the module Pylab implements several Matlab compatible functions, in particular prctile() which computes percentiles. The overall approach is:</div>
<div><br></div><div>1. Open the file</div><div>2. Export the GrADS variables, say the 3D time/lat/lon array, to Python</div><div>3. Transpose the array and use prctile() to compute the percentiles in each gridpoint, transposing the array back in the end</div>
<div>4. At this point you can chose to plot the results in Python (with Matplotlib) or in GrADS; see sample plots attached.</div><div><br></div><div>I am including a self contained script which does the above calculation on the sample "<a href="http://slp_djf.nc">slp_djf.nc</a>" file that is included as test data (either in PyGrADS tarball or in the Win32 superpack). Your particular application will involve a bit more programming for selecting the timeseries for each day of the year, but I hope this script gives you the general idea.</div>
<div><br></div><div>You can download PyGrADS (including the Win32 Superpck version) from <a href="http://sf.net">sf.net</a>:</div><div><br></div><div> <a href="http://sourceforge.net/project/showfiles.php?group_id=161773&package_id=256758">http://sourceforge.net/project/showfiles.php?group_id=161773&package_id=256758</a><br>
</div><div><br></div><div>You can find some documentation on the Wiki:</div><div><br></div><div> <a href="http://opengrads.org/wiki/index.php?title=Python_Interface_to_GrADS">http://opengrads.org/wiki/index.php?title=Python_Interface_to_GrADS</a><br>
</div><div><br></div><div> Let me know if you have questions,</div><div><br></div><div> Good Luck,</div><div><br></div><div> Arlindo</div><div><br></div><div><br><div class="gmail_quote">On Mon, Apr 28, 2008 at 2:34 PM, Stephen R McMillan <<a href="mailto:smcmillan@planalytics.com">smcmillan@planalytics.com</a>> wrote:<br>
<blockquote class="gmail_quote" style="margin:0 0 0 .8ex;border-left:1px #ccc solid;padding-left:1ex;">
<br><font size="2" face="sans-serif">I found nothing in the user archives
to address this question: Is there a relatively simple way to calculate
various percentiles in GrADS? For example:</font><br><br><font size="2" face="sans-serif">1. Assume I have a 30-year dataset
of daily mean temperature values for an x-y domain, contained in a single
3D (x,y,t) gridded file</font><br><font size="2" face="sans-serif">2. Desired output: a single 3D
gridded file containing 11 variables for each gridpoint, per day of year
(excluding Feb 29th): 0th pcntile, 10th pcntile, 20th pcntile...100th pcntile.
In other words, there would be 30 data values to analyze per grid location
(each Jan 1st, each Jan 2nd...each Dec 31st).</font><br><br><font size="2" face="sans-serif">My alternative would be to evaluate
text output in Excel then re-convert to gridded, but I'd prefer to keep
in GrADS.</font><br><br><font size="2" face="sans-serif">I'm using GrADS v1.9.0-rc1 (win32) on
Win XP Pro. </font><br><br><font size="2" face="sans-serif">Stephen Mc</font><br>
<br>
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***************************************************<br></blockquote></div><br><br clear="all"><br>-- <br>Arlindo da Silva<br><a href="mailto:dasilva@alum.mit.edu">dasilva@alum.mit.edu</a>
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