Relative Vorticity Contouring

[Austin Conaty]

Here is sample output from displaying slp after
 'set gxout stat'
ga-> set gxout stat
ga-> d slp
Data Type = grid
Dimensions = 0 1
I Dimension = 1 to 289 Linear 0 1.25
J Dimension = 1 to 181 Linear -90 1
Sizes = 289 181 52309
Undef value = 9.999e+20
Undef count = 0  Valid count = 52309
Min, Max = 93261.6 103502
Cmin, cmax, cint = 94000 103000 1000
Stats[sum,sumsqr,root(sumsqr),n]:     5.27395e+09 5.31859e+14
2.30621e+07 52309
Stats[(sum,sumsqr,root(sumsqr))/n]:     100823 1.01676e+10 100835
Stats[(sum,sumsqr,root(sumsqr))/(n-1)]: 100825 1.01678e+10 100836
Stats[(sigma,var)(n)]:     1542.32 2.37875e+06
Stats[(sigma,var)(n-1)]:   1542.33 2.3788e+06

This tiny bit of grads script, if run immediately after you
display when 'set gxout stat' is set, should help you capture
the line with the min and max, and then assign values
to min1 and m ax1.  Then you write a script to loop through
and compare min and max throughout the time series and
use that to set the contour levels...

rec = sublin(result,9)
min1 = subwrd(rec,5)
max1 = subwrd(rec,6)


Dizzle Man wrote:
> Excellent!, I have tried option two and that works fine. There is one slight
> issue though. Is it possible to remove the numbers that come up on the
> display when I use contour plotting. They kind of get in the way when I am
> observing my data. Also in option 1, what do the min and max represent in
> set gxout stat?
>
> On Tue, Aug 5, 2008 at 2:38 PM, Austin Conaty <Austin.L.Conaty at nasa.gov>wrote:
>
>
>> One possible solution is to
>> 1) set gxout stat
>> 2) loop through the data and capture min and max
>> 3) using the min/max info, use the same set ccols and
>>   set clevs commands before each display
>> 4) set gxout shaded and plot.
>>
>> Or, if you're happy with the color and shading used in the first time
>> period
>> another possible solution is to
>> 1) set t 1
>> 2) set gxout shaded
>> 3) d relvort
>> 4) q shades
>> 5) set ccols and set clevs according to info returned
>>   by q shades.
>>
>>
>> Eric Altshuler wrote:
>>
>>
>>> That is odd because in my experience it is in animations that contouring
>>> and color schemes can be ill-suited to the data being plotted. That's
>>> because whatever contouring scheme is used (or chosen by grads) for the
>>> first frame, is also applied to all the remaining frames so as to ensure the
>>> same contouring scheme for the whole animation. This can be a problem,
>>> though, if the data field being animated changes a lot during the animation
>>> (e.g. a rapidly intensifying hurricane).
>>>
>>> When your are plotting each time step individually, grads chooses the
>>> contouring/color scheme separately for each step unless you set it yourself.
>>> In this situation, if the character of the data field changes significantly
>>> in time, grads will choose new contouring schemes to suit the data at each
>>> time step. The disadvantage here is that the contouring scheme is not
>>> consistent across all frames. It's a tradeoff.
>>>
>>> How are you doing your animations? Are you setting T to vary and plotting
>>> the variable, or have you set up a script loop to display one time step,
>>> sleep for some interval, advance T and then display the next time step? The
>>> behavior of animations using these two methods can be quite different.
>>>
>>> ----- Original Message -----
>>> From: "Dizzle Man" <selfscience06 at GMAIL.COM>
>>> To: GRADSUSR at LIST.CINECA.IT
>>> Sent: Saturday, August 2, 2008 1:28:03 PM GMT -05:00 US/Canada Eastern
>>> Subject: Relative Vorticity Contouring
>>>
>>> Hello Everyone,
>>>
>>> I am doing a plots for relative voricity [hcurl(u,v)].  The issue that I
>>> am
>>> having is when I run my animation I get a beautiful sequence of images, so
>>> when I begin the plot each time step individually I do not receive that
>>> same
>>> contouring intervals that is displayed in the animation. Its like the
>>> individual plotting loses coloring, but that animation gives me what I am
>>> looking for. Does this make sense? I was wondering how can I maintain the
>>> color sequence that the animation gives for individual time step plotting?
>>>
>>>
>>>
>>>
>
>

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