[ncl-talk] array indexing in ncl

[Jatin Kala]

Hi,

Suppose we have a 3-D array, size (103,lat,lon), or whatever...

If i want to extract a time series at two points, say (:,1,2) and 
(:,2,4), then in Python you can do it quite simply, and you end up with 
an array which is size (103,2), which one would expect:

import netCDF4 as nc
f = nc.Dataset('wrfout_d03_cntl')
hfx = f.variables['HFX'][:]
hfx2 = hfx[:,[1,2],[2,4]]
print(hfx2.shape)

But if i do the same thing in ncl, i actually get an array (103,2,2), 
which is not what one would expect:

f = addfile("wrfout_d03_cntl","r")
hfx = f->HFX
hfx2 = hfx(:,(/1,2/),(/2,4/))
print(dimsizes(hfx2))

The only way to get the right answer in ncl, is to pre-define hfx as 
(103,2), then loop through the indices, and put in the array within the 
loop.

Does anyone else find this rather counter-intuitive? I.e., the way ncl 
does array indexing in such cases? Is there a way to achieve the same 
result in ncl without having to loop?

Cheers,

Jatin