It might just be possible that background modelling of diffraction data
in the presence of ice rings is better done in more modern software.
Paul.
On 06/03/2021 00:10, Edward A. Berry wrote:
(Obviously this is for culling the bad data after data reduction is
complete- doesn't do anything to prevent the ice ring from introducing
error in the scaling process. Not really what you were asking for, and
maybe not even useful now, given automatic outlier rejection in
today's programs)
On 03/05/2021 04:00 PM, Edward A. Berry wrote:
For manually masking out the rings, you can use mtz2various to dump
reflections in resolution ranges without ice in ascii, cat them all
together and use f2mtz to read them into a new mtz file. Example
attached.
You might also be able to do it using mtzutils to write out mtz files
in limited resolution ranges, and then to merge them back into one file.
On 03/04/2021 10:39 AM, Alexander Brown wrote:
Hi all,
I'm struggling with a dataset I have which shows very poor data
quality around 3.6A, or exactly where I can see a significant ice
ring in the images. I'm trying to use mosflm to process the image
files, and I have seen a previous thread on the message board where
it is recommended to turn on three tick boxes for ice ring
exclusion, but despite this, as I continue through the processing
sequence and use aimless, it still flags that the data is affected
by an ice ring at that resolution, which you can also see in the
quality/resolution graphs.
I have even tried making a mask in the moslfm viewer using the mask
tool to cover the entire ice ring, but to no avail.
Finally I did have a go at using EVAL which is mentioned in the
original post about ice rings, but it seems it depends on
libgfortran3 packages which have now been replaced with libgfortran5
and so I didn't get very far.
Is there a manual way to mask out certain data, or could there be
something with my data that is causing the automatic ice ring
resolution not to be as effective?
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