Hi James, you’re probably aware of this but you can edit CBF headers in place with sed. That’s what I do when I make the detector on my diffractometer go closer than the hardware limit.
All best - Andreas On Sat, 22 Sep 2018 at 00:51, James Holton <jmhol...@slac.stanford.edu> wrote: > For teaching purposes I have found that controlled pairs of data sets > are most instructive. You are right that an easy one-button-push > processing run tells you nothing, but so does a bang-it-crashed-now-what > data set. Most useful are two data sets that are identical in every > respect but one, and that one thing is the point you are trying to get > across. It's hard to collect such perfectly paired data sets, so I > ended up just simulating them. I deliberately chose a high-symmetry > space group to keep the download size small. You can download them from > here: > > http://bl831.als.lbl.gov/~jamesh/workshop/ > > These five datasets represent the four biggest problems I see users have > when trying to solve structures: 1) poor anomalous signal, 2) overlaps > from a bad crystal orientation, 3) hidden radiation damage to sites, and > 4) ice rings. The 5th "goodsignal" dataset is the positive control. > > The web page contains everything from images to processed MTZ files, > maps and the "right answer" in pdb and mtz format. A slightly more > "realistic" version with a bigger download size is here: > > http://bl831.als.lbl.gov/~jamesh/workshop2/ > > This is the one I used for my "weak anomalous challenge" a few years > back. The teaching advantage is that you can use the image-mixer script > to modulate the severity of problems like ice rings and anomalous > signal. If you make a competition of it, people tend to get more > interested. > > When it comes to beam centers, it is not all that hard to take a data > set with a "correct" beam center and just edit the headers. How you do > this depends on the file format, but I have some instructions for > editing images in general here: > > http://bl831.als.lbl.gov/~jamesh/bin_stuff/ > > In general, you can usually separate the header from the data with the > unix command "head" or "dd", edit the header with your favorite text > editor, and then put the two parts back together with "cat". As for > which beam center is "correct", it is important to tell your students > that that depends on which software you are using. I wrote all this > down in the last paragraph on page 7 of this doc: > > https://submit.biorxiv.org/submission/pdf?msid=BIORXIV/2018/394965 > > This doc also describes another simulated data set that demonstrates the > challenges of combining lots of short wedges together. May or may not > be too advanced a topic for your students? Or maybe not. As you can > guess I'm experimenting with biorxiv. So far, no comments. > > Good luck with your class! > > -James Holton > MAD Scientist > > > On 9/19/2018 5:15 PM, Whitley, Matthew J wrote: > > Dear colleagues, > > > > For teaching purposes, I am looking for a small number (< 5) of > > macromolecular diffraction datasets (raw images) that might be > > considered 'difficult' for a beginning crystallography student to > > process. By 'difficult' I generally mean not able to be processed > > automatically by a common processing package (XDS, Mosflm, DIALS, etc) > > using default settings, i.e., no black box "click and done" processing. > > The datasets I am looking for would have some stumbling block such as > > incorrect experimental parameters recorded in the image headers, > > multiple lattices that cause indexing to fail, datasets for which > > determining the correct space group is tricky, datasets for experiments > > in which the crystal slipped or moved in the beam, or anything else you > > can think of. The idea is for these beginning students to examine > > several datasets that highlight various phenomena that can lead one > > astray during processing. > > > > A good candidate dataset would also ideally comprise a modest number of > > images so as to keep integration time to a minimum. Factors that are > > mostly irrelevant for my purpose: resolution (as long as better than > > ~3.5 Å), source (home vs synchrotron), presence/absence of anomalous > > scattering, presence/absence of ligands, monomeric vs oligomeric > > structures, etc. Also, to be clear, I am not looking for datasets that > > have so many pathologies that they would require many long hours of work > > for an expert to process correctly. > > > > I have checked public repositories such as proteindiffraction.org and > > SBGrid databank, but all of the datasets I acquired from these sources > > process satisfactorily with little effort, and in any event I know of no > > way to search for 'challenging' datasets. (I also wonder whether > > anybody is in the habit of depositing, shall we say, less-than-pristine > > images to public repositories?) > > > > If you know of such a dataset that is already publicly available, or if > > you have such a dataset that you are willing to share for solely > > educational purposes, I would appreciate hearing from you, either on- or > > off-list. > > > > Thank you in advance for your suggestions. > > > > Matthew > > > > ######################################################################## > > To unsubscribe from the CCP4BB list, click the following link: > https://www.jiscmail.ac.uk/cgi-bin/webadmin?SUBED1=CCP4BB&A=1 > ######################################################################## To unsubscribe from the CCP4BB list, click the following link: https://www.jiscmail.ac.uk/cgi-bin/webadmin?SUBED1=CCP4BB&A=1
