[ncl-talk] Grainy image

[Tim Risner]

Easiest solution beyond manipulating data is setting the mpDataResolution
to "FinestResolution"
This gets rid of most of the graininess, as well as smooths the RasterFill
a little more.

*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 1:01 PM Tim Risner <trisner at awis.com> wrote:

> 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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