Re: Where function inserting missing values. Why?

Bridget,

Here, clearly that you missing values of factors, matches mon_avg_obs.

So, you may want to change the whole paragraph:

mon_avg_obs(m,:,:) = where(mon_avg_obs(m,:,:).eq.
0,-2222,mon_avg_obs(m,:,:))
factors(a*12+m,:,:) = data_all(a*12+m,:,:)/mon_avg_20c(m,:,:)
print("1. "+num(ismissing(factors(a*12+m,:,:))))

factors(a*12+m,:,:) = where(.not.ismissing(mon_avg_obs(m,:,:)),
dvar(a*12+m,:,:)/mon_avg_obs(m,:,:),factors(a*12+m,:,:))
print("2. "+num(ismissing(factors(a*12+m,:,:))))

printVarSummary(mon_avg_obs)
printMinMax(mon_avg_obs,True)
printVarSummary(factors(a*12+m,:,:))
printMinMax(factors(a*12+m,:,:),True)
print("debug: "+num(.not.ismissing(mon_avg_obs(m,:,:)).and.
(mon_avg_obs(m,:,:).eq.-2222)))

factors(a*12+m,:,:) = where(.not.ismissing(mon_avg_obs(m,:,:)).and.
(mon_avg_obs(m,:,:).eq.-2222),0.,factors(a*12+m,:,:))
print("3. "+num(ismissing(factors(a*12+m,:,:))))

to:

factors(a*12+m,:,:) = where(ismissing(mon_avg_obs(m,:,:)) .or.
mon_avg_obs(m,:,:) .le. 0., \
                                              data_all(a*12+m,:,:)/
mon_avg_20c(m,:,:), \
                                              dvar(a*12+m,:,:)/
mon_avg_obs(m,:,:))

Then check with:

print("3. "+num(ismissing(factors(a*12+m,:,:))))
printVarSummary(factors(a*12+m,:,:))
printMinMax(factors(a*12+m,:,:),True)

Wei Huang
huangwei@ucar.edu
VETS/CISL
National Center for Atmospheric Research
P.O. Box 3000 (1850 Table Mesa Dr.)
Boulder, CO 80307-3000 USA
(303) 497-8924

On Oct 20, 2009, at 3:17 PM, Bridget Thrasher wrote:

> Here's what results:
>
> (0) 0. 0
> (0) 1. 11753
> (0) 2. 0
> (0) 3. 11753
>
>
> Variable: mon_avg_20c
> Type: float
> Total Size: 790608 bytes
> 197652 values
> Number of Dimensions: 3
> Dimensions and sizes: [month | 12] x [lat | 91] x [lon | 181]
> Coordinates:
> month: [0..11]
> lat: [ -90.. 90]
> lon: [ 0.. 360]
> Number Of Attributes: 3
> info : function clmMonLLT: contributed.ncl
> time_op_ncl : Climatology: 50 years
> _FillValue : 1e+20
> (0)
> (0) min=3.89651e-08 max=20.0773
>
>
> Variable: mon_avg_obs
> Type: float
> Total Size: 790608 bytes
> 197652 values
> Number of Dimensions: 3
> Dimensions and sizes: [month | 12] x [lat | 91] x [lon | 181]
> Coordinates:
> month: [0..11]
> lat: [ -90.. 90]
> lon: [ 0.. 360]
> Number Of Attributes: 3
> info : function clmMonLLT: contributed.ncl
> time_op_ncl : Climatology: 50 years
> _FillValue : 1e+20
> (0)
> (0) min=0 max=41.1583
>
>
> Variable: data_all (subsection)
> Type: float
> Total Size: 65884 bytes
> 16471 values
> Number of Dimensions: 2
> Dimensions and sizes: [lat | 91] x [lon | 181]
> Coordinates:
> Number Of Attributes: 1
> _FillValue : 1e+20
> (0)
> (0) min=1.46602e-21 max=23.252
>
>
> Variable: factors (subsection)
> Type: float
> Total Size: 65884 bytes
> 16471 values
> Number of Dimensions: 2
> Dimensions and sizes: [lat | 91] x [lon | 181]
> Coordinates:
> Number Of Attributes: 1
> _FillValue : 1e+20
> (0)
> (0) min=0 max=6.19144
>
>
> On Tue, Oct 20, 2009 at 2:10 PM, Wei Huang <huangwei@ucar.edu> wrote:
> Bridget,
>
> Can change the paragraph:
>
> mon_avg_obs(m,:,:) = where(mon_avg_obs(m,:,:).eq.
> 0,-2222,mon_avg_obs(m,:,:))
> factors(a*12+m,:,:) = data_all(a*12+m,:,:)/mon_avg_20c(m,:,:)
> print("1. "+num(ismissing(factors(a*12+m,:,:))))
>
> factors(a*12+m,:,:) = where(.not.ismissing(mon_avg_obs(m,:,:)),
> dvar(a*12+m,:,:)/mon_avg_obs(m,:,:),factors(a*12+m,:,:))
> print("2. "+num(ismissing(factors(a*12+m,:,:))))
>
> printVarSummary(mon_avg_obs)
> printMinMax(mon_avg_obs,True)
> printVarSummary(factors(a*12+m,:,:))
> printMinMax(factors(a*12+m,:,:),True)
> print("debug: "+num(.not.ismissing(mon_avg_obs(m,:,:)).and.
> (mon_avg_obs(m,:,:).eq.-2222)))
>
> factors(a*12+m,:,:) = where(.not.ismissing(mon_avg_obs(m,:,:)).and.
> (mon_avg_obs(m,:,:).eq.-2222),0.,factors(a*12+m,:,:))
> print("3. "+num(ismissing(factors(a*12+m,:,:))))
>
>
> to:
>
> factors(a*12+m,:,:) = where(mon_avg_obs(m,:,:) .le. 0., 0.,
> data_all(a*12+m,:,:)/mon_avg_20c(m,:,:))
> print("0. "+num(ismissing(mon_avg_20c(m,:,:))))
> print("1. "+num(ismissing(mon_avg_obs(m,:,:))))
> print("2. "+num(ismissing(data_all(a*12+m,:,:))))
> print("3. "+num(ismissing(factors(a*12+m,:,:))))
>
> printVarSummary(mon_avg_20c)
> printMinMax(mon_avg_20c,True)
> printVarSummary(mon_avg_obs)
> printMinMax(mon_avg_obs,True)
> printVarSummary(data_all(a*12+m,:,:))
> printMinMax(data_all(a*12+m,:,:),True)
> printVarSummary(factors(a*12+m,:,:))
> printMinMax(factors(a*12+m,:,:),True)
>
> Wei Huang
> huangwei@ucar.edu
> VETS/CISL
> National Center for Atmospheric Research
> P.O. Box 3000 (1850 Table Mesa Dr.)
> Boulder, CO 80307-3000 USA
> (303) 497-8924
>
>
>
>
>
> On Oct 20, 2009, at 2:57 PM, Bridget Thrasher wrote:
>
>> OK, here's what I'm printing now:
>>
>> mon_avg_obs(m,:,:) = where(mon_avg_obs(m,:,:).eq.
>> 0,-2222,mon_avg_obs(m,:,:))
>> factors(a*12+m,:,:) = data_all(a*12+m,:,:)/mon_avg_20c(m,:,:)
>> print("1. "+num(ismissing(factors(a*12+m,:,:))))
>>
>> factors(a*12+m,:,:) = where(.not.ismissing(mon_avg_obs(m,:,:)),
>> dvar(a*12+m,:,:)/mon_avg_obs(m,:,:),factors(a*12+m,:,:))
>> print("2. "+num(ismissing(factors(a*12+m,:,:))))
>>
>> printVarSummary(mon_avg_obs)
>> printMinMax(mon_avg_obs,True)
>> printVarSummary(factors(a*12+m,:,:))
>> printMinMax(factors(a*12+m,:,:),True)
>> print("debug: "+num(.not.ismissing(mon_avg_obs(m,:,:)).and.
>> (mon_avg_obs(m,:,:).eq.-2222)))
>>
>> factors(a*12+m,:,:) = where(.not.ismissing(mon_avg_obs(m,:,:)).and.
>> (mon_avg_obs(m,:,:).eq.-2222),0.,factors(a*12+m,:,:))
>> print("3. "+num(ismissing(factors(a*12+m,:,:))))
>>
>> With the result being:
>>
>> (0) 1. 0
>> (0) 2. 0
>>
>>
>> Variable: mon_avg_obs
>> Type: float
>> Total Size: 790608 bytes
>> 197652 values
>> Number of Dimensions: 3
>> Dimensions and sizes: [month | 12] x [lat | 91] x [lon | 181]
>> Coordinates:
>> month: [0..11]
>> lat: [ -90.. 90]
>> lon: [ 0.. 360]
>> Number Of Attributes: 3
>> info : function clmMonLLT: contributed.ncl
>> time_op_ncl : Climatology: 50 years
>> _FillValue : 1e+20
>> (0)
>> (0) min=-2222 max=41.1583
>>
>>
>> Variable: factors (subsection)
>> Type: float
>> Total Size: 65884 bytes
>> 16471 values
>> Number of Dimensions: 2
>> Dimensions and sizes: [lat | 91] x [lon | 181]
>> Coordinates:
>> Number Of Attributes: 1
>> _FillValue : 1e+20
>> (0)
>> (0) min=0 max=14.1053
>> (0) debug: 2
>> (0) 3. 11753
>>
>>
>> I still don't see what's wrong. Am I missing something glaring?
>>
>> -Bridget
>>
>>
>> On Tue, Oct 20, 2009 at 1:02 PM, Dennis Shea <shea@ucar.edu> wrote:
>> On topics like this, it is a good idea to include a printVarSummary
>> as suggested by Wei. Specifically,
>>
>> printVarSummary( mon_avg_obs )
>> printMinMax( mon_avg_obs, True ) ; contributed.ncl
>>
>> before you do any of the operations indicated below. The information
>> can be quite useful.
>>
>> Also,
>>
>> printVarSummary( factors(a*12+m,:,:) )
>> printMinMax(factors(a*12+m,:,:), true)
>>
>> ---
>> The one thing different with the last 'where' is the .and.
>>
>> ... where( .not.ismissing(mon_avg_obs(m,:,:)) .and.
>> mon_avg_obs(m,:,:).eq.-2222,...)
>>
>> print("debug: "+num( .not.ismissing(mon_avg_obs(m,:,:)) .and.
>> mon_avg_obs(m,:,:).eq.-2222) )
>>
>>
>>
>>
>>
>>
>>
>>
>> _______________________________________________
>> ncl-talk mailing list
>> List instructions, subscriber options, unsubscribe:
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>
>
>
>
> --
> Bridget Thrasher, PhD
> Postdoctoral Researcher
> Climate Central
> www.climatecentral.org
> (650) 376-7130
>

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Received on Tue Oct 20 15:48:03 2009