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<!--Copyright (C) 1988-2005 by the Institute of Global Environment and Society (IGES). See file COPYRIGHT for more information.-->
<code>set gxout stat <br>
d </code><br>
<ul>sends output to the terminal as opposed to a
plot or data output (e.g., <code>set fwrite out.dat ; set gxout fwrite;
d rh</code>). Or the output goes to the script variable
<code>result</code> which
can be parsed inside a script (see the <code>corr.gs</code> GrADS
script)<p>
The output allows many statistical calculations to be made.
Here's an example of opening up a global model file and looking
at the 1000 mb relative humidity, statistically,<p>
<ul>
<code>ga-> set gxout stat <br>
ga-> d rh <br>
Data Type = grid <br>
Dimensions = 0 1<br>
I Dimension = 1 to 145 <br>
J Dimension = 1 to 73 <br>
Sizes = 145 73 10585<br>
Undef value = 1e+20 <br>
Undef count = 0 Valid count = 10585 <br>
Min, Max = 0.0610352 100.061 <br>
Stats(sum,sumsqr,n): 787381 6.35439e+07 10585 <br>
Stats(sum,sumsqr)/n: 74.3865 6003.2<br>
Stats(sum,sumsqr)/(n-1): 74.3935 6003.77 <br>
Stats(sigma,var)(n): 21.6761 469.854 <br>
Stats(sigma,var)(n-1): 21.6771 469.898<br>
Cmin, cmax, cint = 10 100 10</code></ul><p>
Let's break it down:<p>
<ul>
<code>Data Type = grid</code> ----- you have a grid <p>
<code>Dimensions = 0 1</code> ----- the dimension type for the variable
<br>
<ul>
<code>0</code> - lon <br>
<code>1</code> - lat <br>
<code>2</code> - lev <br>
<code>3</code> - time </ul><br>
<code>1</code> - not varying <p>
<code>I Dimension = 1 to 145</code> ------ obvious <p>
<code>J Dimension = 1 to 73</code><p>
<code>Sizes = 145 73 10585</code> ------- <code>10585</code> is 145*73
or total number of points <p>
<code>Undef value = 1e+20</code> ------- undefined value <p>
<code>Undef count = 0 Valid count = 10585</code> ----- # of defined and
undefined points in the grid. Remember that if GrADS can't find
any data it returns undefs. This is useful for checking if you
have any data, <code>Valid count = 0</code> means no... <p>
<code>Min, Max = 0.0610352 100.061</code> ---- UHHH OHHHH! we have slight
supersaturation..<p>
<code>Stats(sum,sumsqr,n): 787381 6.35439e+07 10585</code> - This
should
be fairly obvious, sum = the simple sum of all <b>defined</b> points.<p>
<code>sumsqr</code> = sum of, in this case, <code>rh*rh</code> and
<code>10585</code> is <code>n</code>.<p>
<code>Stats(sum,sumsqr)/n: 74.3865 6003.2</code> - Divide by
<code>n</code> for convenience, the first number is the "biased"
mean...<p>
<code>Stats(sum,sumsqr)/(n-1): 74.3935 6003.77</code> - the so called
<code>unbiased</code> mean (remove 1 degree of freedom), etc.<p>
<code>Stats(sigma,var)(n): 21.6761 469.854</code> - the standard
deviation
and variance "biased" (<code>n</code>) <p>
<code>Stats(sigma,var)(n-1): 21.6771 469.898</code> - the standard
deviation and variance "unbiased" (<code>n-1</code>)<p>
<code>Cmin, cmax, cint = 10 100 10</code> - What GrADS will use when
contouring.<p>
</ul><b>NOTE</b>: This works for both <code>gridded</code> and
<b>station</b> data
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