Changed the subject line to try and keep the original thread on-topic.
George is right that the acceleration/decelleration introduces error,
but only in what I like to call "standing start" mode. These days I
think most facilities use "running starts" where the spindle is brought
up to the degrees/second required by the the exposure just before
opening the shutter at the desired "starting phi" position, and then
closing the shutter at the "ending phi" with the sample still moving at
full speed, allowing it to decelerate afterward. The "overhead" for
achieving a stable velocity depends on the speed, of course, but this
"prep time" is generally not more than a few hundred milliseconds. This
is NOT the same thing as the shutter jitter! In fact, the "opening
time" of the shutter is also not the jitter. Even if the shutter takes
100 ms to "open", as long as that is reproducible, it won't hurt the
data quality. Shutter jitter is the rms deviation of all the "true
opening times" from the average. I have not measured this on any
beamline other than my own, but here the shutter jitter is rms ~0.6
millisecond, which translates to 0.0006 degrees at 1 degree/s. Assuming
a mosaic spread of 0.5 degrees, this introduces an error as large as
0.3%. I say "as large as" because only partials are affected by shutter
jitter, not fulls.
All that said, however, if Rmerge is 3%, then sqrt(3%^2-0.3%^2)= 2.985%
error is due to something other than "the shutter".
We thought ourselves quite clever here at ALS 10 years ago when we
implemented the running-starts for exposures on these new-fangled (at
the time) "air bearing" spindles. Only to find that they didn't really
make all that much difference when compared side-by-side with standing
starts. Unless, of course, we started doing REALLY short exposures,
like 0.08s or less. Then the noise power spectrum of the beam (flicker
noise) starts to become important. This is actually easier to measure
than you might think: just put up a photodiode and record samples of the
"beam intensity" as fast as you can. The rms variation in the recorded
intensity, divided by the square root of the sampling rate is the
"flicker noise". I typically get 0.15%/sqrt(Hz), which means that the
average variation in integrated beam intensity over a 1s exposure is
0.15%, and that of a 0.01s exposure is 1.5%. That is, the longer you
average, the more the "flicker noise" of the beam is averaged out. The
trick with flicker noise, however, is that the relevant "exposure time"
is the time it takes the relp to transit the Ewald sphere, and not the
commanded "exposure time" of the image. This means that low-mosaic
crystal data collections are more sensitive to beam instability.
An important property of flicker noise is that sampling more finely and
averaging afterward does not change the signal-to-noise ratio (by
definition, actually). You can try this by generating random numbers
with a mean of "100" and rms error "10%" each. If you average them in
groups of 100, the result will be 100 +/- 1%, and if you take them in
groups of 10 and then average 10 of those groups at a time, you still
get the same answer no matter what: 1% error. However, if you
"attenuate the beam" 10 fold and collect 10x more data points (averaging
1000 values of 10 +/- 10%) you will get 10 +/- 0.3%, reducing the
flicker noise by a factor of ~3. This may seem magical if you are used
to thinking about photon-counting noise because photon-counting noise
does not depend on how much time you take to collect the photons, but
every other kind of noise does!
It is therefore important not to forget that counting detectors
introduce a "new" kind of error: pile-up. The Lambert omega function
can be used to correct for pile-up (and that is was Pilatus does), but
this correction relies on the assumption that the "true" intensity over
a given acquisition time was constant (Poisson statistics). This is
definitely not the case with spots moving quickly through the Ewald
sphere, and that is why Dectris recommends fine phi-slicing. Fine
slicing has advantages on any detector (Pflugrath, 1999), but it is an
absolute requirement for getting good data from any counting device,
including the Pilatus. Of course, this does not mean you can't add up
fine-sliced images after they are acquired to form a coarser-sliced data
set, but that is a form of "lossy compression".
Formally, pile-up, beam flicker and shutter jitter fall into what I call
the "% error" category, as does the noise induced by crystal vibration
(usually buffeting in the cryostream) or simply a "noisy" velocity
control on the spindle motor. But since continuous-readout detectors
are not immune to beam flicker, sample vibration nor velocity control
instability, I decided not to mention them earlier.
-James Holton
MAD Scientist
On 10/27/2011 6:36 AM, George M. Sheldrick wrote:
> There are two further complications. In non-continuous mode, the goniometer has
> to accelerate at the start of a frame and decellerate at the end, then wait for
> the frame to be read. So even if the shutter always functions perfectly, my
> intuition tells me that it must be more accurate to rotate at constant speed
> (however my intuition is often wrong). Secondly, in continuous mode, usually
> not all pixels are read out at precisely the same time.
>
> George
>
> On Thu, Oct 27, 2011 at 11:05:01AM +0100, David Waterman wrote:
>> I agree with Colin here. Framing is simply a process of sampling an original
>> signal at some 'frequency' (related to the phi-width of each frame). At some
>> point, delta phi is small enough that the original signal is oversampled, and
>> can be reconstructed _within the bounds of noise_. Beyond that point I see no
>> advantage to sampling finer - and certainly not going to the limit of
>> representing your data in some unframed continuous readout form.
>>
>> Perhaps I am missing something, and I realise this is another OT diversion from
>> this most fruitful of threads.
>>
>> Cheers
>>
>> -- David
>>
>>
>> On 27 October 2011 08:55, Martin M. Ripoll<[log in to unmask]> wrote:
>>
>> Dear Colin,
>>
>> I think you understood perfectly what George was saying regarding the loss
>> of information, but he will probably answer better than I.
>>
>> In any case, and for the ones that did not understand it, what George was
>> telling is related to the fact that a data collection made with a
>> continuous
>> crystal rotation contains more information than when this information is
>> transformed into frames... The loss of information that we are referring to
>> has the same meaning as when we calculate electron density maps with
>> different grid sizes. The finer the grid, the greater is the information on
>> the map.
>>
>> But you are right saying that the shorter the interval between produced
>> frames, the lower the loss of information. However, the procedure that you
>> are suggesting should have some limits... otherwise the amount of
>> information would grow dramatically.
>>
>> All the best,
>> Martin
>> ________________________________________
>> Dr. Martin Martinez-Ripoll
>> Research Professor
>> [log in to unmask]
>> Department of Crystallography& Structural Biology
>> www.xtal.iqfr.csic.es
>> Telf.: +34 917459550
>> Consejo Superior de Investigaciones Cient ficas
>> Spanish National Research Council
>> www.csic.es
>>
>>
>> -----Mensaje original-----
>> De: CCP4 bulletin board [mailto:[log in to unmask]] En nombre de Colin
>> Nave
>> Enviado el: jueves, 27 de octubre de 2011 0:49
>> Para: [log in to unmask]
>> Asunto: Re: [ccp4bb] IUCr committees, depositing images
>>
>> Dear George, Martin
>>
>> I don't understand the point that one is throwing away information by
>> storing in frames. If the frames have sufficiently fine intervals (given by
>> some sampling theorem consideration) I can't see how one loses information.
>> Can one of you explain?
>> Thanks
>> Colin
>>
>>
>>
>> -----Original Message-----
>> From: CCP4 bulletin board [mailto:[log in to unmask]] On Behalf Of
>> Martin
>> M. Ripoll
>> Sent: 26 October 2011 22:50
>> To: ccp4bb
>> Subject: Re: [ccp4bb] IUCr committees, depositing images
>>
>> Dear George, dear all,
>>
>> I was just trying to summarize my point of view regarding this important
>> issue when I got your e-mail, that reflects exactly my own opinion!
>>
>> Martin
>> ________________________________________
>> Dr. Martin Martinez-Ripoll
>> Research Professor
>> [log in to unmask]
>> Department of Crystallography& Structural Biology
>> www.xtal.iqfr.csic.es
>> Telf.: +34 917459550
>> Consejo Superior de Investigaciones Cient ficas
>> Spanish National Research Council
>> www.csic.es
>>
>>
>>
>> -----Mensaje original-----
>> De: CCP4 bulletin board [mailto:[log in to unmask]] En nombre de George
>> M. Sheldrick
>> Enviado el: mi rcoles, 26 de octubre de 2011 11:52
>> Para: [log in to unmask]
>> Asunto: Re: [ccp4bb] IUCr committees, depositing images
>>
>> This raises an important point. The new continuous readout detectors such
>> as
>> the
>> Pilatus for beamlines or the Bruker Photon for in-house use enable the
>> crystal to
>> be rotated at constant velocity, eliminating the mechanical errors
>> associated with
>> 'stop and go' data collection. Storing their data in 'frames' is an
>> artifical
>> construction that is currently required for the established data
>> integration
>> programs but is in fact throwing away information. Maybe in 10 years time
>> 'frames'
>> will be as obsolete as punched cards!
>>
>> George
>>
>> On Wed, Oct 26, 2011 at 09:39:40AM +0100, Graeme Winter wrote:
>> > Hi James,
>> >
>> > Just to pick up on your point about the Pilatus detectors. Yesterday
>> > in 2 hours of giving a beamline a workout (admittedly with Thaumatin)
>> > we acquired 400 + GB of data*. Now I appreciate that this is not
>> > really routine operation, but it does raise an interesting point - if
>> > you have loaded a sample and centred it, collected test shots and
>> > decided it's not that great, why not collect anyway as it may later
>> > prove to be useful?
>> >
>> > Bzzt. 2 minutes or less later you have a full data set, and barely
>> > even time to go get a cup of tea.
>> >
>> > This does to some extent move the goalposts, as you can acquire far
>> > more data than you need. You never know, you may learn something
>> > interesting from it - perhaps it has different symmetry or packing?
>> > What it does mean is if we can have a method of tagging this data
>> > there may be massively more opportunity to get also-ran data sets for
>> > methods development types. What it also means however is that the cost
>> > of curating this data is then an order of magnitude higher.
>> >
>> > Also moving it around is also rather more painful.
>> >
>> > Anyhow, I would try to avoid dismissing the effect that new continuous
>> > readout detectors will have on data rates, from experience it is
>> > pretty substantial.
>> >
>> > Cheerio,
>> >
>> > Graeme
>> >
>> > *by "data" here what I mean is images, rather than information which
>> > is rather more time consuming to acquire. I would argue you get that
>> > from processing / analysing the data...
>> >
>> > On 24 October 2011 22:56, James Holton<[log in to unmask]> wrote:
>> > > The Pilatus is fast, but or decades now we have had detectors that can
>> read
>> > > out in ~1s. This means that you can collect a typical ~100 image
>> dataset in
>> > > a few minutes (if flux is not limiting). Since there are ~150
>> beamlines
>> > > currently operating around the world and they are open about 200
>> days/year,
>> > > we should be collecting ~20,000,000 datasets each year.
>> > >
>> > > We're not.
>> > >
>> > > The PDB only gets about 8000 depositions per year, which means either
>> we
>> > > throw away 99.96% of our images, or we don't actually collect images
>> > > anywhere near the ultimate capacity of the equipment we have. In my
>> > > estimation, both of these play about equal roles, with ~50-fold
>> attrition
>> > > between ultimate data collection capacity and actual collected data,
>> and
>> > > another ~50 fold attrition between collected data sets and published
>> > > structures.
>> > >
>> > > Personally, I think this means that the time it takes to collect the
>> final
>> > > dataset is not rate-limiting in a "typical" structural biology
>> > > project/paper. This does not mean that the dataset is of little value.
>> > > Quite the opposite! About 3000x more time and energy is expended
>> preparing
>> > > for the final dataset than is spent collecting it, and these efforts
>> require
>> > > experimental feedback. The trick is figuring out how best to compress
>> the
>> > > "data used to solve a structure" for archival storage. Do the
>> "previous
>> > > data sets" count? Or should the compression be "lossy" about such
>> > > historical details? Does the stuff between the spots matter? After
>> all,
>> > > h,k,l,F,sigF is really just a form of data compression. In fact, there
>> is
>> > > no such thing as "raw" data. Even "raw" diffraction images are a
>> > > simplification of the signals that came out of the detector
>> electronics.
>> > > But we round-off and average over a lot of things to remove "noise".
>> > > Largely because "noise" is difficult to compress. The question of how
>> much
>> > > compression is too much compression depends on which information (aka
>> noise)
>> > > you think could be important in the future.
>> > >
>> > > When it comes to fine-sliced data, such as that from Pilatus, the main
>> > > reason why it doesn't compress very well is not because of the spots,
>> but
>> > > the background. It occupies thousands of times more pixels than the
>> spots.
>> > > Yes, there is diffuse scattering information in the background pixels,
>> but
>> > > this kind of data is MUCH smoother than the spot data (by definition),
>> and
>> > > therefore is optimally stored in larger pixels. Last year, I messed
>> around
>> > > a bit with applying different compression protocols to the spots and
>> the
>> > > background, and found that ~30 fold compression can be easily achieved
>> if
>> > > you apply h264 to the background and store the "spots" with lossless
>> png
>> > > compression:
>> > >
>> > > http://bl831.als.lbl.gov/~jamesh/lossy_compression/
>> > >
>> > > I think these results "speak" to the relative information content of
>> the
>> > > spots and the pixels between them. Perhaps at least the "online
>> version" of
>> > > archived images could be in some sort of lossy-background format? With
>> the
>> > > "real images" in some sort of slower storage (like a room full of tapes
>> that
>> > > are available upon request)? Would 30-fold compression make the
>> storage
>> of
>> > > image data tractable enough for some entity like the PDB to be able to
>> > > afford it?
>> > >
>> > >
>> > > I go to a lot of methods meetings, and it pains me to see the most
>> brilliant
>> > > minds in the field starved for "interesting" data sets. The problem is
>> that
>> > > it is very easy to get people to send you data that is so bad that it
>> can't
>> > > be solved by any software imaginable (I've got piles of that!). As a
>> > > developer, what you really need is a "right answer" so you can come up
>> with
>> > > better metrics for how close you are to it. Ironically, bad,
>> unsolvable
>> > > data that is connected to a right answer (aka a PDB ID) is very
>> difficult to
>> > > obtain. The explanations usually involve protestations about being in
>> the
>> > > middle of writing up the paper, the student graduated and we don't
>> > > understand how he/she labeled the tapes, or the RAID crashed and we
>> lost
>> it
>> > > all, etc. etc. Then again, just finding someone who has a data set
>> with
>> the
>> > > kind of problem you are interested in is a lot of work! So is figuring
>> out
>> > > which problem affects the most people, and is therefore "interesting".
>> > >
>> > > Is this not exactly the kind of thing that publicly-accessible
>> centralized
>> > > scientific databases are created to address?
>> > >
>> > > -James Holton
>> > > MAD Scientist
>> > >
>> > > On 10/16/2011 11:38 AM, Frank von Delft wrote:
>> > >>
>> > >> On the deposition of raw data:
>> > >>
>> > >> I recommend to the committee that before it convenes again, every
>> member
>> > >> should go collect some data on a beamline with a Pilatus detector
>> [feel
>> free
>> > >> to join us at Diamond]. Because by the probable time any
>> recommendations
>> > >> actually emerge, most beamlines will have one of those (or similar),
>> we'll
>> > >> be generating more data than the LHC, and users will be happy just to
>> have
>> > >> it integrated, never mind worry about its fate.
>> > >>
>> > >> That's not an endorsement, btw, just an observation/prediction.
>> > >>
>> > >> phx.
>> > >>
>> > >>
>> > >>
>> > >>
>> > >> On 14/10/2011 23:56, Thomas C. Terwilliger wrote:
>> > >>>
>> > >>> For those who have strong opinions on what data should be
>> deposited...
>> > >>>
>> > >>> The IUCR is just starting a serious discussion of this subject. Two
>> > >>> committees, the "Data Deposition Working Group", led by John
>> Helliwell,
>> > >>> and the Commission on Biological Macromolecules (chaired by Xiao-Dong
>> Su)
>> > >>> are working on this.
>> > >>>
>> > >>> Two key issues are (1) feasibility and importance of deposition of
>> raw
>> > >>> images and (2) deposition of sufficient information to fully
>> reproduce
>> > >>> the
>> > >>> crystallographic analysis.
>> > >>>
>> > >>> I am on both committees and would be happy to hear your ideas
>> (off-list).
>> > >>> I am sure the other members of the committees would welcome your
>> thoughts
>> > >>> as well.
>> > >>>
>> > >>> -Tom T
>> > >>>
>> > >>> Tom Terwilliger
>> > >>> [log in to unmask]
>> > >>>
>> > >>>
>> > >>>>> This is a follow up (or a digression) to James comparing test set
>> to
>> > >>>>> missing reflections. I also heard this issue mentioned before but
>> was
>> > >>>>> always too lazy to actually pursue it.
>> > >>>>>
>> > >>>>> So.
>> > >>>>>
>> > >>>>> The role of the test set is to prevent overfitting. Let's say I
>> have
>> > >>>>> the final model and I monitored the Rfree every step of the way and
>> can
>> > >>>>> conclude that there is no overfitting. Should I do the final
>> > >>>>> refinement
>> > >>>>> against complete dataset?
>> > >>>>>
>> > >>>>> IMCO, I absolutely should. The test set reflections contain
>> > >>>>> information, and the "final" model is actually biased towards the
>> > >>>>> working set. Refining using all the data can only improve the
>> accuracy
>> > >>>>> of the model, if only slightly.
>> > >>>>>
>> > >>>>> The second question is practical. Let's say I want to deposit the
>> > >>>>> results of the refinement against the full dataset as my final
>> model.
>> > >>>>> Should I not report the Rfree and instead insert a remark
>> explaining
>> > >>>>> the
>> > >>>>> situation? If I report the Rfree prior to the test set removal, it
>> is
>> > >>>>> certain that every validation tool will report a mismatch. It does
>> not
>> > >>>>> seem that the PDB has a mechanism to deal with this.
>> > >>>>>
>> > >>>>> Cheers,
>> > >>>>>
>> > >>>>> Ed.
>> > >>>>>
>> > >>>>>
>> > >>>>>
>> > >>>>> --
>> > >>>>> Oh, suddenly throwing a giraffe into a volcano to make water is
>> crazy?
>> > >>>>> Julian, King of
>> Lemurs
>> > >>>>>
>> > >
>> >
>>
>> --
>> Prof. George M. Sheldrick FRS
>> Dept. Structural Chemistry,
>> University of Goettingen,
>> Tammannstr. 4,
>> D37077 Goettingen, Germany
>> Tel. +49-551-39-3021 or -3068
>> Fax. +49-551-39-22582
>>
>>
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