[ncl-talk] "sum" and "avg" functions without ignoring missing values
Dave Allured - NOAA Affiliate
dave.allured at noaa.gov
Fri Nov 24 13:07:33 MST 2017
Oops, I missed something. dim_cumsum returns an array of the same shape as
the input. To get the desired "final sum" array of rank n-1, you must take
the last slice of the function result array. For dim_cumsum_n, you must
similarly take the last slice along dimension number n.
Let a be dimensioned (3,4,5). Then:
nz = dimsizes(a(0,0,:))
opt = 0
b3d = dim_cumsum (a, opt) ; dimensions (3,4,5)
b = b3d(:,:,nz-1) ; dimensions (3,4)
--Dave
On Fri, Nov 24, 2017 at 12:52 PM, Rashed Mahmood <rashidcomsis at gmail.com>
wrote:
> Thanks Dave, that is exactly what I was looking for...
>
>
> On Fri, Nov 24, 2017 at 11:46 AM, Dave Allured - NOAA Affiliate <
> dave.allured at noaa.gov> wrote:
>
>> Rasheed,
>>
>> I think dim_cumsum and dim_cumsum_n with opt=0 are intended for this
>> purpose. There is no corresponding function for "avg". However, simply
>> dividing the result array from dim_cumsum by N should give the correct
>> array result, with no extra "if" or "where" statement.
>>
>> --Dave
>>
>>
>> On Fri, Nov 24, 2017 at 12:29 PM, Rashed Mahmood <rashidcomsis at gmail.com>
>> wrote:
>>
>>> Hi Arne,
>>>
>>> Thanks for trying to answer the question, however, the things you
>>> mentioned would add confusion and possibly wrong results.
>>> Actually I know how to achieve what I want using a do loop. For example,
>>> let us say we have variable a = (ntimes,nlevel,nlat,nlon) and we want to do
>>> sum over time domain which can easily be done using: (dim_sum_n(a,0)), Now
>>> the results would be sum over all non-missing values of
>>> time1,time2,time2...timeN, which is correct.
>>>
>>> But if I want to do sum ONLY when all of the values of
>>> time1,time2,time3...timeN are non-missing then we can do this:
>>>
>>> dimz = dimsizes(a)
>>> b = new(/dimz(1),dimz(2),dimz(3),float)
>>> b at _FillValue = a at _FillValue
>>>
>>> b(:,:,:) = 0.
>>> do n=0,dimz(0)-1
>>> b = b+a(n,:,:,:)
>>> end do
>>>
>>> I just wanted to avoid the loop and use the "sum" function for
>>> efficiency. I hope this clarifies the question a bit more.
>>>
>>> Cheers,
>>> Rashed
>>>
>>>
>>> On Fri, Nov 24, 2017 at 3:01 AM, Arne Melsom <arne.melsom at met.no> wrote:
>>>
>>>> Hi!
>>>> Since 'music piano' replied, I thought I might chime in ;)
>>>> I'm pretty sure that no option(s) to functions allow you to do what you
>>>> want.
>>>> So you'll need to write alternative functions yourself (perhaps not
>>>> what you consider 'an easy way'...)
>>>> You may use something like
>>>>
>>>> aDim = dimsizes(a)
>>>> orgFill = a at _FillValue
>>>> newFill = -min(abs(a)) - 1 ; make sure newFill is out of range and
>>>> <0
>>>> if (newFill .eq. orgFill) then ; newFill must be different from orgFill
>>>> newFill = newFill - 1
>>>> end if
>>>> newVar = ndtooned(a)
>>>> newVar at _FillValue = newFill
>>>> indx = ind(ismissing(newVar))
>>>> newVar(indx) = orgFill
>>>> newa = onedtond(newVar,aDim)
>>>>
>>>> ...and, if you later want to restore:
>>>> a = newa
>>>> a at _FillValue = orgFill
>>>>
>>>> Hope this helps/clarifies!
>>>> Best regards,
>>>> Arne
>>>>
>>>>
>>>> 2017-11-24 1:49 GMT+01:00 Rashed Mahmood <rashidcomsis at gmail.com>:
>>>>
>>>>> Hello all,
>>>>> I am just wondering if there is an easy way to tell the "sum" and
>>>>> "avg" functions NOT ignore the missing values. Below lines clarify my
>>>>> question where I would like to see same values for c and d:
>>>>>
>>>>> ncl 0> a = (/(/-9.,2,-9./),(/1,-9.,2./)/)
>>>>> ncl 1> a at _FillValue = -9.
>>>>> ncl 2> c = (a(0,:)+a(1,:))
>>>>> ncl 3> d = dim_sum_n(a,0)
>>>>> ncl 4> print(" "+c+ " ... "+d)
>>>>> (0) -9 ... 1
>>>>> (1) -9 ... 2
>>>>> (2) -9 ... 2
>>>>>
>>>>> Thanks,
>>>>> Rashed
>>>>>
>>>>
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