[ncl-talk] Grainy image

[Tim Risner]

Thanks Mary and Rick. I'll work with the examples you mentioned and see
what I can do to correct it.

Attached is a google maps image showing the data and placement, to answer
your questions.



*Tim Risner*
*Operational Meteorologist*
*(888) 798-9955 ext 1006*

<http://www.awis.com>[image: https://www.facebook.com/AWISWeatherServices/]
<https://www.facebook.com/AWISWeatherServices/>
<https://twitter.com/awisweather>


On Thu, Jan 10, 2019 at 11:32 AM Mary Haley <haley at ucar.edu> wrote:

> Hi Tim,
>
> I echo what Rick says about not being certain without seeing the data.
>
> Is your data a set of random points, or on a gridded structure, or
> something else? If it's on a gridded structure, then what happens if you
> don't set trGridType at all?
>
> I'm also interested to know the structure of your lat/lon data and how
> dense the values are. Does your data contain any missing values? I don't
> think this is the issue here, but it is important to be aware of this.
>
> One thing I like to do for problem plots like this is to zoom in on the
> area with the problem, and then plot dots where the lat/lon locations are
> just to see if there's anything going on with regard to the density of the
> locations and/or potential missing values.
>
> If you look at this page:
>
> http://www.ncl.ucar.edu/Applications/datagrid.shtml
>
> you will see some examples of using gsn_coordinates to plot the lat/lon
> locations of your data, and also use different colors for where the data is
> missing or not.
>
> In particular, datagrid_6.ncl might be useful if you have curvilinear data.
>
> http://www.ncl.ucar.edu/Applications/datagrid.shtml#ex6
>
> If you have random data, then contour1d.ncl on the same same might be
> useful.
>
> --Mary
>
>
> On Thu, Jan 10, 2019 at 10:07 AM Rick Brownrigg <brownrig at ucar.edu> wrote:
>
>> Hi Tim,
>>
>> I don't know for certain without looking at the data, but I have to
>> imagine its manifest in the data itself, and that in those regions you
>> mentioned the probability is hovering right around 50%.  The color contrast
>> between 40% and 50% is rather abrupt, relative to the rest of the
>> successive colors, which I think draws attention to the fluctuations. There
>> also appears to be similar fluctuations going on in Montana and Minnesota,
>> but its harder to see because those colors "closer" to each other,
>> perceptually.
>>
>> FWIW...
>> Rick
>>
>>
>> On Thu, Jan 10, 2019 at 9:52 AM Tim Risner <trisner at awis.com> wrote:
>>
>>> I'm curious as to what may be causing a grainy section in Central
>>> Mississippi and SE Ohio of the attached image.
>>> I'm using "RasterFill" and cnRasterSmoothingOn is set to True.
>>> trGridType of all types causes it.
>>> Data is pretty uniform in those regions.
>>>
>>>
>>> *Tim Risner*
>>> *Operational Meteorologist*
>>> *(888) 798-9955 ext 1006*
>>>
>>> <http://www.awis.com>[image:
>>> https://www.facebook.com/AWISWeatherServices/]
>>> <https://www.facebook.com/AWISWeatherServices/>
>>> <https://twitter.com/awisweather>
>>> _______________________________________________
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