[phenixbb] phenix.auto_sharpen expected filtration of input map

Tom Terwilliger tterwilliger at newmexicoconsortium.org
Wed Jan 24 05:45:45 PST 2018


Hi Ricardo,

If you are using phenix.auto_sharpen with just a map and resolution as
inputs, then it will (by default) apply an overall sharpening B-factor up
to the resolution limit you supply, and then a blurring B-factor beyond
that.  This means that any filtering applied to the input map will make a
difference.  I haven't tested systematically, but my guess is that the
better the map you start with with the better the map you'll get. So I
would recommend starting with the weighted map as in Rosenthal and
Henderson.  In this case phenix.auto_sharpen will basically be identifying
the overall sharpening that optimizes the clarity and connectivity of the
map.

If you sharpen using a model, then a different sharpening is applied at
each resolution (basically as in Rosenthal and Henderson, but based on the
match between model and map, not between two half-maps), so the starting
map should make only a small difference.

All the best,
Tom T

On Wed, Jan 24, 2018 at 6:00 AM, Ricardo Righetto <ricardorighetto at gmail.com
> wrote:

> Hi,
>
> So far I have liked very much the results of phenix.auto_sharpen, but one
> thing is not yet clear to me: how does it expect the input map to be
> filtered?
>
> Would be something like:
>
> a) Unsharpened, unfiltered map (e.g. the simple average of the half-maps)
> b) Unsharpened, SSNR-weighted (Cref) (Rosenthal & Henderson, JMB 2003)
> c) Doesn't matter / other?
>
> Thanks in advance!
>
> Best wishes,
>
>
> --
> Ricardo Diogo Righetto
>
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-- 
Thomas C Terwilliger
Laboratory Fellow, Los Alamos National Laboratory
Senior Scientist, New Mexico Consortium
100 Entrada Dr, Los Alamos, NM 87544
Email: tterwilliger at newmexicoconsortium.org
Tel: 505-431-0033
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