[ncl-talk] stat_dispersion

jbuzan jbuzan at purdue.edu
Fri Sep 26 15:30:42 MDT 2014


I am having some issues with stat_dispersion.
Perhaps my code ‘fixes’ cause the issue.  I am not sure.

I have 2 datasets:
time: 1460 lat: 192, lon 288
time: 2920 lat: 192, lon 288
I have added a second year to the original year (both 1460 time steps).  The stat_dispersion, in theory, should have the same minimum and maximum values.

The data is partitioned by Temperature and by a difference field.  
Here is a snippet of the code that does the partitioning:
do k = 0, dimsizes(numvar)-1
;do k = 16, 16
   thresholdstart = k*5.d + 200.d
   print(thresholdstart)
   thresholdend = k*5.d + 205.d
   print(thresholdend)
;   location = ind(temperature1d.lt.thresholdend)
   location = ind(temperature1d.lt.thresholdend.and.temperature1d.ge.thresholdstart)
;   printVarSummary(location)
;   print(location)
   if(.not.all(ismissing(location)))
        tbin = wetbulb1d(location)
        else
        tbin = value
        tbin at _FillValue = value
   end if       
 ;  print(tbin)

   if(.not.all(ismissing(tbin)))
        tbin at _FillValue = -999.d
        delete(tbin at _FillValue)
        numarray(:,k) = stat_dispersion(tbin,opt)
        else
        numarray(:,k) = value
   end if       
   delete(tbin)
   delete(location)
  ; print(numarray)
end do
numarray = where(numarray.eq.-999.d,value,numarray)

replace_ieeenan (numarray, value, 0)
numarray at _FillValue = value
numarray at missing_value = numarray at _FillValue
numarray!0 = "stat"
numarray!1 = "bin"
numarray&bin = numvar
printVarSummary(numarray)

Here is a snippet of the code that grabs the values:
box_var = numvar
box_var at long_name = longnamea
box_var at units = unitsa
;box_var(:,0) = field1c(22,:)
box_var(:,0) = field1c(2,:)
box_var(:,1) = field1c(24,:)
box_var(:,2) = field1c(8,:)
box_var(:,3) = field1c(25,:)
box_var(:,4) = field1c(14,:)
;box_var(:,4) = field1c(26,:)

field1c of 14 and 2 are the maximum and minimums from Stat_Dispersion.
I think the issue is that stat_dispersion field becomes too large, and drops something.  It might be how I characterize the missing values.

Any help would be appreciated.

-Jonathan

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