<div dir="ltr"><div class="gmail_default" style="font-size:small">Qi,</div><div class="gmail_default" style="font-size:small"><br></div><div class="gmail_default" style="font-size:small">For the record, we do have a dim_kde already implemented in our internal development version, but we haven't had a chance to heavily test it.</div><div class="gmail_default" style="font-size:small"><br></div><div class="gmail_default" style="font-size:small">We are going to revisit this tomorrow to see what state it's in. If you are interested, we can provide you with a test NCL to try.</div><div class="gmail_default" style="font-size:small"><br></div><div class="gmail_default" style="font-size:small">--Mary</div><div class="gmail_default" style="font-size:small"><br></div></div><div class="gmail_extra"><br><div class="gmail_quote">On Wed, Jul 26, 2017 at 11:32 AM, LI Qi <span dir="ltr"><<a href="mailto:liqi123sh@qq.com" target="_blank">liqi123sh@qq.com</a>></span> wrote:<br><blockquote class="gmail_quote" style="margin:0 0 0 .8ex;border-left:1px #ccc solid;padding-left:1ex"><div>Dear Dennis,</div><div><br></div><div>Thank you for your reply!</div><div>Yesterday I just googled "ncl kernel density estimation" and that page popped up. At that time Im so happy to find NCL also has this function (means I don't need to learn R).</div><div>What's your said (hist_binwidth and invoking kde ) is exactly what I want.</div><div>But if it's very bother to invoke the funciton or it's need much time and energy in the develepment, then just ignore me. I can learn R for the moment.</div><div><br></div><div>Best,</div><div>Qi</div><div><div><br></div><div><br></div><div style="font-size:12px;font-family:Arial Narrow;padding:2px 0 2px 0">------------------ Original --<wbr>----------------</div><div style="font-size:12px;background:#efefef;padding:8px"><div><b>From: </b> "Dennis Shea";<<a href="mailto:shea@ucar.edu" target="_blank">shea@ucar.edu</a>>;</div><div><b>Date: </b> Thu, Jul 27, 2017 00:42 AM</div><div><b>To: </b> "LI Qi"<<a href="mailto:liqi123sh@qq.com" target="_blank">liqi123sh@qq.com</a>>; </div><div><b>Cc: </b> "ncl-talk"<<a href="mailto:ncl-talk@ucar.edu" target="_blank">ncl-talk@ucar.edu</a>><wbr>; </div><div><b>Subject: </b> Re: [ncl-talk] could i try dim_kde function before ncl 6.5 released</div></div><div><div class="h5"><div><br></div><div dir="ltr"><div>Placing the 6.5.0 KDE function documentation onto the publicly available NCL URL was a mistake on my part. <br> <a href="https://www.ncl.ucar.edu/Document/Functions/Built-in/dim_kde.shtml" target="_blank">https://www.ncl.ucar.edu/Docum<wbr>ent/Functions/Built-in/dim_<wbr>kde.shtml</a><br>It was meant for NCL's internal draft documentation URL. I used<br><br></div><div>%> unw dim_kde.xml<br><br></div><div>instead of<br><br></div><div>%> unw -t dim_kde.xml<br><br>----<br></div><div><br></div><div>If you look at:<br> <a href="http://www.ncl.ucar.edu/future_release.shtml" target="_blank">http://www.ncl.ucar.edu/future<wbr>_release.shtml</a><br></div><div>there is no mention of the 'dim_kde' function. Hence, 'dim_dke' is not yet in the development NCL 6.5.0. There is no time estimate of when it will be included.<br><br>---<br></div><div>An NCL script that invokes the KDE fortran subroutine via a shared object is available. It returns the PDF (ie: "smooth curve"). I can make this available. Let ncl-talk know if you want this. <br><br></div><div>There is also an as-yet undocumented NCL language 'hist_binwidth' that estimates optimal bin-widths using Silverman's rule-of-thumb for normal and quantile densities; and, uses the 'dim_kde' function. An NCL script that invokes the shared object is available for this also.<br><br></div><div>Regards<br></div></div><div class="gmail_extra"><br><div class="gmail_quote">On Tue, Jul 25, 2017 at 2:23 PM, LI Qi <span dir="ltr"><<a href="mailto:liqi123sh@qq.com" target="_blank">liqi123sh@qq.com</a>></span> wrote:<br><blockquote class="gmail_quote" style="margin:0 0 0 .8ex;border-left:1px #ccc solid;padding-left:1ex"><div>Dear NCL,</div><div><br></div><div>Is there any way I can try the gaussian kernel density estimation (KDE) (<a href="https://www.ncl.ucar.edu/Document/Functions/Built-in/dim_kde.shtml" target="_blank">https://www.ncl.ucar.edu/Docu<wbr>ment/Functions/Built-in/dim_<wbr>kde.shtml</a>) before next version released?</div><div>I have sample histograms and would like a smooth curve overlaid.</div><div><br></div><div>Thanks and best regards,</div><div>Qi</div><br>______________________________<wbr>_________________<br>
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