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Hi Ed, <br>
<br>
I agree I was too generous in my statement and you promptly caught it,
thanks! <br>
<br>
phenix.refine does catch and deal with clearly nonsensical situations,
like having Fobs<=0 in refinement. So, saying "phenix.refine does
not use any data cutoff for refinement" was not precise, indeed. In
addition, phenix.refine automatically removes Fobs outliers based on
R.Read paper.<br>
<br>
I don't see much sense having a term (0-Fcalc)**2 in least-squares
target or equivalent one in ML target. Implementing an intensity based
ML target function (or corresponding LS) would allow using Iobs<=0,
but this is not done yet, and this is a different story - your
original question below was about Fo (Fobs).<br>
<br>
Do you have rock solid evidence that substituting missing (unmeasured)
Fobs with 0 would be better than just using actual set (Fobs>0) in
refinement? Or did I miss any relevant paper on this matter? I would
appreciate if you point me out. Unless I see a clear evidence that this
would improve things I wouldn't waste time on implementing it.
Unfortunately I don't have time right now for experimenting with this
myself.<br>
<br>
Thanks!<br>
Pavel.<br>
<br>
<br>
On 5/17/10 6:52 AM, Ed Pozharski wrote:
<blockquote cite="mid:1274104366.15379.1.camel@shardik.rx.umaryland.edu"
type="cite">
<pre wrap="">On Fri, 2010-05-14 at 15:35 -0700, Pavel Afonine wrote:
</pre>
<blockquote type="cite">
<pre wrap="">phenix.refine does not use any data cutoff for refinement.
</pre>
</blockquote>
<pre wrap=""><!---->
So was the Fo>0 hard-wired cutoff removed? I don't have the latest
version so I can't check myself.
</pre>
</blockquote>
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