Dear Bernhard,

     That is true, and the discrepancies between repeated measurements of
the same hkl would have to be parametrised differently from those between
symmetry-related ones (e.g. in terms of radiation damage only, while the
others would also involve absorption effects). However I am not aware that
the existing data processing programs we use actually make and exploit this
distinction.

     Going back to the initial topic of this thread, the main take-home
lesson for Murpholino should be: preoccupations about minimising the number
of frames to get completeness belong to a now obsolete age - instead use the
new paragigm of high-(redundancy/multiplicity) data collection with a low
transmission so that you can spread the dose your crystal can withstand over
the requisite angular range. No matter how you call the "abundance" property
of your final dataset, make sure it is high!

     The case of low symmetry has been mentioned: the extra guidance for
Murpolino is that if you are in P1, you will never get completeness with a
single orientation, so make sure that you use a multi-axis goniometer and
collect data in at least two sufficiently different orientations.


     With best wishes,

          Gerard.

--
On Tue, Jun 30, 2020 at 08:49:53AM -0700, Bernhard Rupp wrote:
> .…but there is a difference whether I measure the same identical hkl over 
> again or ‘preferably in more than one symmetry-equivalent position’, to quote 
> the
> 
> IUCr. So do we have a MPSR for the same reflection and a MPRR for the related 
> reflections?
> 
>  
> 
> Cacophonically yours,
> 
>  
> 
> BR
> 
>  
> 
> From: CCP4 bulletin board <CCP4BB@JISCMAIL.AC.UK> On Behalf Of John R 
> Helliwell
> Sent: Tuesday, June 30, 2020 08:36
> To: CCP4BB@JISCMAIL.AC.UK
> Subject: Re: [ccp4bb] [EXTERNAL] Re: [ccp4bb] number of frames to get a full 
> dataset?
> 
>  
> 
> Dear Herman,
> 
> I think that MPR is a very neat and tidy, excellent, proposal.
> 
> Moreover it uses the word “measurements”, and we are an experimental based 
> science.
> 
> I support it.
> 
> Great.
> 
> Greetings,
> 
> John 
> 
> Emeritus Professor John R Helliwell DSc
> 
>  
> 
>  
> 
>  
> 
>  
> 
> On 30 Jun 2020, at 15:10, Schreuder, Herman /DE <herman.schreu...@sanofi.com 
> <mailto:herman.schreu...@sanofi.com> > wrote:
> 
>  
> 
> Dear BB,
> 
>  
> 
> Since there does not seem a generally accepted term for the subject of this 
> discussions, and since even the IUCR scriptures do not give any guidance, I 
> would propose to introduce a completely new term:
> 
>  
> 
> Measurements per reflection or MPR
> 
>  
> 
> This term is politically neutral, should adequately describe this particular 
> statistic and is not associated with entrenched traditions at either side of 
> the Atlantic.
> 
>  
> 
> What do you think?
> 
> Herman
> 
>  
> 
>  
> 
> Von: CCP4 bulletin board <CCP4BB@JISCMAIL.AC.UK 
> <mailto:CCP4BB@JISCMAIL.AC.UK> > Im Auftrag von John R Helliwell
> Gesendet: Dienstag, 30. Juni 2020 14:34
> An: CCP4BB@JISCMAIL.AC.UK <mailto:CCP4BB@JISCMAIL.AC.UK> 
> Betreff: [EXTERNAL] Re: [ccp4bb] number of frames to get a full dataset?
> 
>  
> 
> EXTERNAL : Real sender is owner-ccp...@jiscmail.ac.uk 
> <mailto:owner-ccp...@jiscmail.ac.uk>  
> 
>  
> 
> Dear Colleagues,
> 
> In an effort to break this naming deadlock, and with Massimo and Ian not 
> showing up as yet, I checked the IUCr Dictionary.
> 
> “Redundancy“ and “Multiplicity“ are not listed.
> 
> The more generic term “Statistical Descriptors“ is though and even offers 
> Recommendations:-
> 
> http://ww1.iucr.org/iucr-top/comm/cnom/statdes/recomm.html 
> <https://urldefense.proofpoint.com/v2/url?u=http-3A__ww1.iucr.org_iucr-2Dtop_comm_cnom_statdes_recomm.html&d=DwMFaQ&c=Dbf9zoswcQ-CRvvI7VX5j3HvibIuT3ZiarcKl5qtMPo&r=HK-CY_tL8CLLA93vdywyu3qI70R4H8oHzZyRHMQu1AQ&m=vb2CFOGKla49hE2sbHAt6LCUz63K7uis9PmSUxUgMcM&s=-45HByHsLJPmc2KRmPKamiFNf1WFCI51GonllFyIRTE&e=>
>  
> 
> Point 1, first sentence, fits the various wishes of this thread succinctly, 
> if not in a single word, and even not readily allowing an easy acronym. 
> 
> Greetings,
> 
> John 
> 
>  
> 
> Emeritus Professor John R Helliwell DSc
> 
>  
> 
>  
> 
> 
> 
> 
> 
> On 30 Jun 2020, at 13:11, Phil Jeffrey <pjeff...@princeton.edu 
> <mailto:pjeff...@princeton.edu> > wrote:
> 
> The people that already use multiplicity are going to find reasons why it's 
> the superior naming scheme - although the underlying reason has a lot to do 
> with negative associations with 'redundant', perhaps hightened in the current 
> environment.  And conversely redundant works for many others - Graeme's 
> pragmatic defense of multiplicity actually works both ways - any person who 
> takes the trouble to read the stats table, now exiled to Supplementary Data, 
> knows what it means.  Surely, then, the only way forward on this almost 
> totally irrelevant discussion is to come up with a universally-loathed 
> nomenclature that pleases nobody, preferably an acronym whose origins will be 
> lost to history and the dusty CCP4 archives (which contain threads similar to 
> this one).  I humbly submit:
> 
> NFDOF: Nearly Futile Data Overcollection Factor ?
> [*]
> 
> Or, even better, could we not move on to equally pointless discussions of the 
> inappropriateness of "R-factor" ?  I have a long history of rearguard action 
> trying to give stupid acronyms a wider audience, so you're guaranteed to hear 
> from me on this for years.
> 
> (Personally I'm pining for Gerard Kleywegt to resume his quest for 
> overextended naming rationales, of which ValLigURL is a personal 
> 'favo[u]rite'.  But I'm just old-fashioned.)
> 
> Ironically,
> Phil Jeffrey
> Princeton
> 
> [* I too have collected 540 degrees in P1 to solve a SAD structure, just 
> because I could, hence "nearly"]
> [** The actual answer to this thread is: history is written by the authors of 
> scaling programs - and I think the Americans are currently losing at this 
> game, thus perilously close to making themselves redundant.]
> 
> On 6/30/20 4:14 AM, Winter, Graeme (DLSLtd,RAL,LSCI) wrote:
> 
> 
> 
> Or, we could accept the fact that crystallographers are kinda used to 
> multiplicity of an individual Miller index being different to multiplicity of 
> observations, and in Table 1 know which one you mean? 😉 Given that they add 
> new information (at the very least to the scaling model) they are strictly 
> not “redundant”.
> 
> The amount that anyone outside of methods development cares about the 
> “epsilon” multiplicity of reflections is … negligible?
> 
> Sorry for chucking pragmatism into a dogmatic debate 😀
> 
> Cheerio Graeme
> 
> 
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