<div dir="ltr">I am not using the 1k data, but I have the same i/o speed issues with the nested nam conus. I've optimized by converting to netcdf. I download the grib2 and run g2ctl and gribmap. Then lats4d to convert to netcdf. This makes a lat/lon file and de-compresses the grib2. This is substantially faster than dealing with grib2 and pdef.<div><br></div><div>Here is a live example:</div><div><br></div><div><a href="http://www.meteogram.com/servlet/metChart?zoom=20&gs=wrfradar&tau=2&lat=38.83&lon=-77.31&units=e">http://www.meteogram.com/servlet/metChart?zoom=20&gs=wrfradar&tau=2&lat=38.83&lon=-77.31&units=e</a></div><div><br></div><div>You can change the chart by adjusting the inputs. The zoom is roughly the longitude domain in degrees. As shown the larger the domain the longer it takes to load. If you change that to 50 and then to 5 you'll notice the speed difference. Overall it is fine for my needs. If I left it grib2 and pdef, it takes too long.</div><div><br></div><div>Dan<br><div><br><div><br></div><div><br></div></div></div></div><div class="gmail_extra"><br><div class="gmail_quote">On Tue, Feb 9, 2016 at 12:37 PM, Travis Wilson - NOAA Federal <span dir="ltr"><<a href="mailto:travis.wilson@noaa.gov" target="_blank">travis.wilson@noaa.gov</a>></span> wrote:<br><blockquote class="gmail_quote" style="margin:0 0 0 .8ex;border-left:1px #ccc solid;padding-left:1ex"><div dir="ltr"><p class="MsoNormal" style="margin-bottom:0.0001pt"><span style="font-size:9.5pt;font-family:Arial,sans-serif;background-image:initial;background-repeat:initial">Hi
All,</span><span style="font-size:12pt;font-family:'Times New Roman',serif"></span></p>
<p class="MsoNormal" style="margin-bottom:0.0001pt;background-image:initial;background-repeat:initial"><span style="font-size:9.5pt;font-family:Arial,sans-serif"> </span></p>
<p class="MsoNormal" style="margin-bottom:0.0001pt;background-image:initial;background-repeat:initial"><span style="font-size:9.5pt;font-family:Arial,sans-serif">Attached is a very
short ppt on grads performance vs python using grib files. In most cases,
grads blows python away. Times are relative to our machine and consider
everything from starting grads/opening the file, to closing the file. </span></p>
<p class="MsoNormal" style="margin-bottom:0.0001pt;background-image:initial;background-repeat:initial"><span style="font-size:9.5pt;font-family:Arial,sans-serif"> </span></p>
<p class="MsoNormal" style="margin-bottom:0.0001pt;background-image:initial;background-repeat:initial"><span style="font-size:9.5pt;font-family:Arial,sans-serif">- In particular we
have found that shaded1 is much faster. Up to 40% faster on our machines.
</span></p>
<p class="MsoNormal" style="margin-bottom:0.0001pt;background-image:initial;background-repeat:initial"><span style="font-size:9.5pt;font-family:Arial,sans-serif">- Wesley Ebisuzaki
recommended converting the grib files to a lat/lon grid to eliminate the PDEF
entry to significantly speed up the opening time of high resolution grib
files. <a href="http://gradsusr.org/pipermail/gradsusr/2016-January/039339.html" target="_blank">http://gradsusr.org/pipermail/gradsusr/2016-January/039339.html</a></span></p>
<p class="MsoNormal" style="margin-bottom:0.0001pt;background-image:initial;background-repeat:initial"><span style="font-size:9.5pt;font-family:Arial,sans-serif">- Again noted by
Wesley, grib packing can have an impact on performance <a href="http://gradsusr.org/pipermail/gradsusr/2010-May/027683.html" target="_blank">http://gradsusr.org/pipermail/gradsusr/2010-May/027683.html</a> </span></p>
<p class="MsoNormal" style="margin-bottom:0.0001pt;background-image:initial;background-repeat:initial"><span style="font-size:9.5pt;font-family:Arial,sans-serif"> </span></p>
<p class="MsoNormal" style="margin-bottom:0.0001pt;background-image:initial;background-repeat:initial"><span style="font-size:9.5pt;font-family:Arial,sans-serif">One thing we show in
the ppt is that as the view gets wider (i.e. the number of points that are plotted
increase), the slower grads is relative to python. At some point, python
will become faster. Anyways, to battle with this, regridding (using the
re() function) the data within grads significantly speeds up the plotting time
(see last slide) when you have a lot of points.
As far as I know, you can’t use re() in grads 2.1a3. You do have lterp() but a grid is
needed. Is there anything that will
allow me to lterp to my image dimensions?
Say my image dimensions are x800 y600 then lterp would interpolate my
high resolution grib file to x800 y600 (or some multiple of) when a view
exceeds 800 points across. This will significantly
speed up the plotting time when viewing a wide view of a high resolution grib
file while not degrading the image quality by much (again, see last slide). </span></p>
<p class="MsoNormal" style="margin-bottom:0.0001pt;background-image:initial;background-repeat:initial"><span style="font-size:9.5pt;font-family:Arial,sans-serif"> </span></p>
<p class="MsoNormal" style="margin-bottom:0.0001pt;background-image:initial;background-repeat:initial"><span style="font-size:9.5pt;font-family:Arial,sans-serif">Also, if anyone has
other performance tips on plotting high resolution grib files we would love to
hear them.</span></p>
<p class="MsoNormal" style="margin-bottom:0.0001pt;background-image:initial;background-repeat:initial"><span style="font-size:9.5pt;font-family:Arial,sans-serif"> </span></p>
<p class="MsoNormal" style="margin-bottom:0.0001pt;background-image:initial;background-repeat:initial"><span style="font-size:9.5pt;font-family:Arial,sans-serif">Thanks,</span></p>
<p class="MsoNormal" style="margin-bottom:0.0001pt;background-image:initial;background-repeat:initial"><span style="font-size:9.5pt;font-family:Arial,sans-serif">Travis</span></p></div>
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