[ncl-talk] Area average while using shapefile

Mary Haley haley at ucar.edu
Fri Mar 24 09:20:30 MDT 2017


Hi Ipshita,

Sorry for misspelling your name earlier.

I was able to run your script using a previous data file you sent me, and I
realize that your "mask" array is not set up the way I thought.

Your original mask command was very close, but remember what I said about
what the function does. It actually *keeps* (protects) the values of your
first array at locations where your second array equals the third array.

So, in your case, you were effectively keeping all the values of precc at
locations where precc_mask3d was equal to -9999, which is the opposite of
what you want.

A better way to think of this is "at locations where precc_mask_3d is not
missing, keep the values of precc":

  precc_3d = mask(precc,.not.ismissing(precc_mask_3d),True)
You could also use the where function:

precc_3d = where(.not.ismissing(precc_mask_3d),precc,precc at _FillValue)

--Mary




On Thu, Mar 23, 2017 at 12:36 PM, Ipshita Majhi <ipmajhi at alaska.edu> wrote:

> Hi Mary,
>
> I have tried that in the past as well. I am not sure what I am missing but
> , it is not able to plot if  I put 1 instead of -9999
> It gives the following error:-
> warning:ContourPlotIntialize: no valid values in scalar field; ContourPlot
> not possible:[errno=1101]
> I am not sure how to resolve it. I will be grateful for any suggestions
>
> On Thu, Mar 23, 2017 at 6:09 AM, Mary Haley <haley at ucar.edu> wrote:
>
>> Ipsita,
>>
>> I think the problem is with the "mask" function.
>>
>> I always have a hard time remembering how this function works, so I
>> remember this:
>>
>>   The mask function protects the first argument at locations where the
>> second argument is equal to the third argument.
>>
>> The script has this line:
>>
>>   precc_3d=mask(precc,precc_mask_3d,-9999)
>>
>> Which effectively is going to keep the values of "precc" at locations
>> where precc_mask_3d is equal to -9999.
>>
>> I think what it should be is:
>>
>>   precc_3d=mask(precc,precc_mask_3d,1)
>>
>> I'm assuming that "precc_mask_3d" is set to the value 1 at locations
>> where the data is inside India.
>>
>> --Mary
>>
>>
>>
>>
>> On Wed, Mar 22, 2017 at 2:24 PM, Ipshita Majhi <ipmajhi at alaska.edu>
>> wrote:
>>
>>> Hi Mary,
>>>
>>> I looked at the plot , it is creating a plot where it is masking value
>>> over India, but I want value over India only with rest of the world masked
>>> out,I am attaching the plot with this email.Could you suggest the required
>>> changes. Thank you in advance.
>>>
>>>
>>> On Fri, Mar 17, 2017 at 7:07 AM, Mary Haley <haley at ucar.edu> wrote:
>>>
>>>> Hi Ipshita,
>>>>
>>>> The "conform" function doesn't do the masking. It simply propagates a
>>>> 2D array to a 3D array.
>>>>
>>>> You need to take this 2D mask array, conform it to 3D, and then apply
>>>> it to your original "ts" data in order to "mask" the locations in "ts"
>>>> where the values are 1:
>>>>
>>>> ;---Create a 2D mask array using India shapefile outlines
>>>>   ts_mask_2d = mask_data_with_India_country(India_code,ts(0,:,:))
>>>>
>>>> ;---Conform this 2D array to a 3D array
>>>>   ts_mask_3d = conform(ts,ts_mask_2d,(/1,2/))
>>>>
>>>> ;---Apply the 3D mask to "ts"
>>>>   tm_3d = mask(ts,ts_mask_3d,1)    ; Keep ts when ts_mask_3d equal 1
>>>>
>>>>
>>>> The tm_3d array should now be the one that you can average.
>>>>
>>>> By the way, there are some things you can do to clean up your code a
>>>> little.
>>>>
>>>> [1] You don't need to use a "do" loop to calculate the average.  You
>>>> can use "dim_avg_n" or "dim_avg_n_Wrap" (preserves metadata):
>>>>
>>>> prec_avg = dim_avg_n_Wrap(tm_3d,(/1,2/))
>>>>
>>>> [2] You generally don't ever need to use "new" unless you need to
>>>> populate that array inside a do loop by indexing it, or you just need to
>>>> create an empty array for some reason.
>>>>
>>>> So, you can replace this code:
>>>>
>>>>  precp_mon_avg = new((/100,12/),"float")
>>>>
>>>>  precp_mon_avg=reshape(prec_avg,(/100,12/))
>>>>
>>>> with just one line:
>>>>
>>>>  precp_mon_avg = reshape(prec_avg,(/100,12/))
>>>>
>>>> --Mary
>>>>
>>>>
>>>> On Thu, Mar 16, 2017 at 1:48 PM, Ipshita Majhi <ipmajhi at alaska.edu>
>>>> wrote:
>>>>
>>>>> Dear NCL Users,
>>>>>
>>>>> I am using shapefile to analyze data over India, thanks to Mary got
>>>>> the shape file working and then also got the data conformed. But when I am
>>>>> doing area average for each month the values are the same . I am not sure
>>>>> what is going wrong. I am pasting my code in this email.
>>>>>
>>>>>
>>>>> ;************************************************
>>>>> load "$NCARG_ROOT/lib/ncarg/nclscripts/csm/gsn_code.ncl"
>>>>> load "$NCARG_ROOT/lib/ncarg/nclscripts/csm/gsn_csm.ncl"
>>>>> load "$NCARG_ROOT/lib/ncarg/nclscripts/csm/contributed.ncl"
>>>>> load "$NCARG_ROOT/lib/ncarg/nclscripts/csm/shea_util.ncl"
>>>>> ;************************************************
>>>>> ;Read data to plot and mask
>>>>> ;************************************************
>>>>> function mask_data_with_India_country(country_code,data)
>>>>> begin
>>>>>
>>>>> mask_start_time = get_cpu_time()     ; For timing results
>>>>>
>>>>> ;---Convert rectilinear grid to 2D grid, but laid out as 1D array.
>>>>>   dims  = dimsizes(data)
>>>>>   lat1d = ndtooned(conform_dims(dims,data&$data!0$,0))
>>>>>   lon1d = ndtooned(conform_dims(dims,data&$data!1$,1))
>>>>>
>>>>>   shapefile_name = "IND_adm0.shx"
>>>>>  ;---Open shapefile and read lat/lon values.
>>>>>   sfilename = "IND_adm0.shp"
>>>>>   f = addfile(sfilename,"r")
>>>>>   segments = f->segments
>>>>>   geometry = f->geometry
>>>>>   segsDims = dimsizes(segments)
>>>>>   geomDims = dimsizes(geometry)
>>>>>
>>>>> ;---Read global attributes
>>>>>   geom_segIndex = f at geom_segIndex
>>>>>   geom_numSegs  = f at geom_numSegs
>>>>>   segs_xyzIndex = f at segs_xyzIndex
>>>>>   segs_numPnts  = f at segs_numPnts
>>>>>   numFeatures   = geomDims(0)
>>>>>
>>>>>   lon  = f->x
>>>>>   lat  = f->y
>>>>>   nlatlon = dimsizes(lat)
>>>>>
>>>>>   min_lat = min(lat)
>>>>>   max_lat = max(lat)
>>>>>   min_lon = min(lon)
>>>>>   max_lon = max(lon)
>>>>>
>>>>>   print("==================================================")
>>>>>   print("Shapefile : "  + sfilename)
>>>>>   print("min_lat " + min_lat)
>>>>>   print("max_lat " + max_lat)
>>>>>   print("min_lon " + min_lon)
>>>>>   print("max_lon " + max_lon)
>>>>>
>>>>>    ii_latlon = ind(min_lat.le.lat1d.and.lat1d.le.max_lat.and.\
>>>>>                   min_lon.le.lon1d.and.lon1d.le.max_lon)
>>>>>   nii = dimsizes(ii_latlon)
>>>>>   print(nii + " values to check")
>>>>>   print(numFeatures + " feature(s) to traverse with a maximum of " + \
>>>>>         nlatlon + " points")
>>>>>
>>>>>
>>>>>  ;---Create array to hold new data mask, and set all values to 0
>>>>> initially.
>>>>>   data_mask_1d = new(dimsizes(lat1d),integer)
>>>>>   data_mask_1d = 0
>>>>>
>>>>> ;
>>>>> ; This is the loop that checks every point in lat1d/lon1d to see if it
>>>>> ; is inside or outside of the country. If it is inside, then
>>>>> data_mask_1d
>>>>> ; will be set to 1.
>>>>> ;
>>>>>   ikeep = 0    ; Counter to see how many points were found inside the
>>>>> country
>>>>>   do n=0,nii-1
>>>>>     ii = ii_latlon(n)
>>>>>     is_inside = False
>>>>>     i = 0
>>>>>     do while(.not.is_inside.and.i.lt.numFeatures)
>>>>>        startSegment = geometry(i, geom_segIndex)
>>>>>        numSegments  = geometry(i, geom_numSegs)
>>>>>        do seg=startSegment, startSegment+numSegments-1
>>>>>          startPT = segments(seg, segs_xyzIndex)
>>>>>          endPT   = startPT + segments(seg, segs_numPnts) - 1
>>>>>          if(data_mask_1d(ii).ne.1.and.\
>>>>>             gc_inout(lat1d(ii),lon1d(ii),\
>>>>>                      lat(startPT:endPT),lon(startPT:endPT))) then
>>>>>            data_mask_1d(ii) = 1
>>>>>            ikeep = ikeep+1
>>>>>            is_inside = True
>>>>>            continue
>>>>>          end if
>>>>>        end do
>>>>>        i = i + 1
>>>>>     end do
>>>>>   end do
>>>>>   print(ikeep + " values kept")
>>>>>   print("==================================================")
>>>>>
>>>>> ; Create a 2D data array of same size as original data,
>>>>> ; but with appropriate values masked.
>>>>> ;
>>>>>   data_mask = (where(onedtond(data_mask_1d,dims).eq.1,data,\
>>>>>               data at _FillValue))
>>>>>   copy_VarMeta(data,data_mask)      ; Copy all metadata
>>>>>
>>>>> ;---Print timings
>>>>>   mask_end_time = get_cpu_time()
>>>>>   print("Elapsed time in CPU second for 'mask_data_with_India_country'
>>>>> = " + \
>>>>>          (mask_end_time-mask_start_time))
>>>>>
>>>>>   return(data_mask)
>>>>> end
>>>>>
>>>>> ;-----------------------------------------------------------
>>>>> -----------
>>>>> ; Main code
>>>>> ;-----------------------------------------------------------
>>>>> -----------
>>>>>
>>>>> ;---Shapefile to use for masking. Using India (IND)
>>>>> India_code = "IND"
>>>>> India_name = "IND" + "_adm0"
>>>>> India_shp  = "IND_adm0.shp"
>>>>>
>>>>> ;---Read lat/lon off shapefile
>>>>>  s         = addfile(India_shp,"r")
>>>>>  slat      = s->y
>>>>>  slon      = s->x
>>>>>
>>>>> ;---Read precipitation data to contour and mask
>>>>>   filename = "b.e11.B1850C5CN.f09_g16.005.c
>>>>> am.h0.PRECC.070001-079912.nc"
>>>>>   f        =  addfile(filename,"r")
>>>>>   ts       = f->PRECC(:,:,:)
>>>>>
>>>>>
>>>>> ;---Mask "ts" against India shapefile outlines
>>>>>   ts_mask = mask_data_with_India_country(India_code,ts(0,:,:))
>>>>>   tm_3d=conform(ts,ts_mask,(/1,2/))
>>>>>
>>>>>
>>>>>
>>>>>   tm_3d at _FillValue = ts at _FillValue
>>>>>
>>>>> ;  copy_VarAtts(ts,tm_3d)
>>>>>   copy_VarCoords(ts,tm_3d)
>>>>>
>>>>>  print(tm_3d(100,{25},{70}))
>>>>>  print(tm_3d(110,{25},{74}))
>>>>>
>>>>>  printVarSummary(tm_3d)
>>>>>  printMinMax(tm_3d, True)
>>>>>
>>>>>  prec_avg = new((/1200/),"float")
>>>>>
>>>>>  do ii =0,1199
>>>>>
>>>>>  prec_avg(ii) = avg(tm_3d(ii,:,:))
>>>>>
>>>>>  end do
>>>>>
>>>>>  precp_mon_avg = new((/100,12/),"float")
>>>>>
>>>>>  precp_mon_avg=reshape(prec_avg,(/100,12/))
>>>>>
>>>>>
>>>>>  precp_mon = dim_avg_n(precp_mon_avg,0)
>>>>>
>>>>>  print(precp_mon)
>>>>>
>>>>>
>>>>>
>>>>>
>>>>>
>>>>>
>>>>>
>>>>>
>>>>> --
>>>>> ************************************************************
>>>>> *******************************************************
>>>>> "I slept and dreamt that life was joy. I awoke and saw that life was
>>>>> service. I acted and behold, service was joy." - Rabindranath Tagore
>>>>> ************************************************************
>>>>> ********************************************************
>>>>>
>>>>> Ipshita Majhi
>>>>> PhD Candidate
>>>>> University of Alaska , Fairbanks
>>>>> Atmospheric Science Department
>>>>> (907)978-4220 <(907)%20978-4220> ipmajhi at alaska.edu
>>>>>
>>>>> _______________________________________________
>>>>> ncl-talk mailing list
>>>>> ncl-talk at ucar.edu
>>>>> List instructions, subscriber options, unsubscribe:
>>>>> http://mailman.ucar.edu/mailman/listinfo/ncl-talk
>>>>>
>>>>>
>>>>
>>>
>>>
>>> --
>>> ************************************************************
>>> *******************************************************
>>> "I slept and dreamt that life was joy. I awoke and saw that life was
>>> service. I acted and behold, service was joy." - Rabindranath Tagore
>>> ************************************************************
>>> ********************************************************
>>>
>>> Ipshita Majhi
>>> PhD Candidate
>>> University of Alaska , Fairbanks
>>> Atmospheric Science Department
>>> (907)978-4220 <(907)%20978-4220> ipmajhi at alaska.edu
>>>
>>
>>
>
>
> --
> ************************************************************
> *******************************************************
> "I slept and dreamt that life was joy. I awoke and saw that life was
> service. I acted and behold, service was joy." - Rabindranath Tagore
> ************************************************************
> ********************************************************
>
> Ipshita Majhi
> PhD Candidate
> University of Alaska , Fairbanks
> Atmospheric Science Department
> (907)978-4220 <(907)%20978-4220> ipmajhi at alaska.edu
>
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