Hi Sara,
Here is a template Jupyter notebook that can be used to create netCDF
gridded data that can be read into the IDV:
https://gist.github.com/julienchastang/2129368a26ce0d85cff13cf0bc05cbf4
You will have to supply your own geophysical variables, etc.
Good Luck,
-Julien
On Mon, Aug 22, 2016 at 11:48 AM, Don Murray (NOAA Affiliate) <
don.murray@xxxxxxxx> wrote:
> Hi Sara-
>
> It's obvious that you are creating a grid given your x/y/z dimensions, but
> you do need to get the metadata right. I think the IDV may not like a time
> unit of just "hours" - you might try "hours since 1970-01-01 00:00:00".
> That's a limitation of the way the IDV handles time. And you might also
> try Brian's suggestion of changing the dimension names. The IDV should not
> need a Conventions global attribute - I would think that the underlying
> netCDF-Java library should be able to handle some sort of default
> convention that closely resembles the CF defaults. Maybe you could send a
> sample file to Unidata and they could help you adjust the the metadata so
> you'd just need the minimal amount. You shouldn't need to make such a file
> CF compliant just to get it into the IDV. It was designed to handle a
> variety of conventions (even none) - or at least it used to.
>
> Don Murray
>
>
> On 8/22/16 9:20 AM, Julien Chastang wrote:
>
>> Hi Sara,
>>
>> There are a variety of problems here. For starters, there are no global
>> attributes and metadata related to CF conventions. Moreover, the IDV is
>> trying to find gridded data and can't, but is that really what you intend?
>> I can't tell what kind of data these data are meant to be. I once wrote a
>> blog entry on creating a CF compliant netCDF files with Python that can
>> subsequently be read in to the IDV.
>>
>> http://www.unidata.ucar.edu/blogs/developer/entry/ipynb_cook
>> books_to_create_cf
>> http://nbviewer.jupyter.org/github/julienchastang/py-netcdf-
>> cf-cookbooks/blob/master/traj.ipynb
>>
>> The example is for trajectory data, but you will be able to find many
>> hints
>> for the kind of data you wish to create, e.g., gridded data if that is
>> what
>> you intend. Again, make sure to follow CF conventions and checkout those
>> NODC templates (described in the blog) for examples.
>>
>> Best,
>>
>> Unidata IDV Support
>>
>> On Mon, Aug 22, 2016 at 7:45 AM, Sara Loureiro Solla <
>> sara.solla@xxxxxxxxxxxxx> wrote:
>>
>> Hello everyone!
>>>
>>> I am having trouble opening a *.nc file using IDV. The error I encounter
>>> is " No gridded data found". I found some posts about the same problem in
>>> the idvusers list, but I cannot find a proper solution.
>>>
>>> I create a nc file using python 2.7 and netCDF4.1.2.4 module. The
>>> dimensions and the variables related to them are created this way:
>>>
>>> Dimensions:
>>> dataout.createDimension('t', None)
>>> dataout.createDimension('y', 361)
>>> dataout.createDimension('x', 720)
>>> dataout.createDimension('z', 1)
>>>
>>> Variables:
>>> lat = self.dataout.createVariable('y', 'f4',( 'y',), zlib=True)
>>> lat.units = 'degrees_north'
>>> lon = self.dataout.createVariable('x', 'f4', ('x',), zlib=True)
>>> lon.units = 'degrees_east'
>>> time = self.dataout.createVariable('t', 'f4', ('t',), zlib=True)
>>> time.units = 'hours'
>>> time.calendar = 'gregorian'
>>> vertical = self.dataout.createVariable('z','f4',('z',),zlib=True)
>>> vertical.units = 'hPa'
>>> vertical.positive = 'down'
>>>
>>> Variable filling:
>>> lat[:] = np.arange(-90,90.5,.5)
>>> lon[:] = np.arange(-180,180,.5)
>>> time[:] = 80
>>> vertical[:] = 850
>>>
>>> According to ncdump my file has the follow coordinate variable data:
>>> t = 180 ;
>>> z = 850 ;
>>> y = -90, -89.5, -89, -88.5 ...... 85.5, 86, 86.5, 87, 87.5, 88, 88.5, 89,
>>> 89.5, 90 ;
>>> x = -180, -179.5, -179, ...... 178, 178.5, 179, 179.5 ;
>>>
>>> Any idea about what could lead to the "no gridded data found" error?
>>>
>>> Thank you very much!
>>> Sara
>>>
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>>
> --
> Don Murray
> NOAA/ESRL/PSD and CU-CIRES
> 303-497-3596
> http://www.esrl.noaa.gov/psd/people/don.murray/
>
--
Julien Chastang
Scientific Software Developer
Unidata-UCAR
