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NOTICE: This version of the NSF Unidata web site (archive.unidata.ucar.edu) is no longer being updated.
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In the System Jython library, under "Grid routines" is a function called "oldaverageOverTime()" -- you could modify this (by copying it to the Local Jython/User library and editing it) to compute the cumulative sum. (I'm assuming here that you already know how to do the first part of your computation -- that of computing the anomalies). Since you want a running sum of only positive values, another approach would be to use the built-in sumOverTime() function, but zero-out the array elements that are less than 0 before you do that...for example: inx = find(field, "<",0.0) replace(field, inx, 0.0) (the "find()" function returns an int[] array with the indecies where the comparison is 'true'). You could also use the "mask()" function and then multiply the returned field by the original one. Note that these functions only work on a single time, so you would have to loop over times, using the first index of the "field" as the time index, most likely. Hope that helps. tom On Tue, May 11, 2010 at 4:03 AM, Joseph Maina <jmaina@xxxxxxx> wrote: > Hi List, I intend to compute temperature anomalies of a long time series by > taking the difference between each time step in a monthly mean time series > and the temperature anomaly (single grid). The output would be a time series > of this difference (anomalies), which I would then compute a cumulative sum > of only the positive anomalies, more like the current inbuilt sum over time > steps formula but in this case only the positive anomalies would be > summed..any help would be much appreciated. Thanks > Maina > _______________________________________________ > idvusers mailing list > idvusers@xxxxxxxxxxxxxxxx > For list information, to unsubscribe, visit: > http://www.unidata.ucar.edu/mailing_lists/ > -- Tom Whittaker University of Wisconsin-Madison Space Science & Engineering Center (SSEC) Cooperative Institute for Meteorological Satellite Studies (CIMSS) 1225 W. Dayton Street Madison, WI 53706 USA ph: +1 608 262 2759
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