Andrew! You don't believe me? Well, I suppose it serves me right for
not explaining where the idea came from (see below).
I do, however, agree with Andrew's assessment that the default-chosen
gain in MOSFLM is adequate for all practical purposes. Any error in
GAIN will be almost exactly compensated for by a corresponding change in
Sdfac in SCALA, and the final value of sigma(I) will be essentially the
same. The only possible difference will be in the sigma-based outlier
rejection within MOSFLM, but since the typical errors in the sigma are
only ~30%, I predict it will be hard to find a situation where this
makes or breaks a structure determination.
So, by way of explanation: there are three things that led me to this
conclusion:
1) the control: fake data with all pixels independent.
adjusting the GAIN as MOSFLM recommends from the BGRATIO analysis
does, in fact, reproduce the "correct" value of the gain used to
generate the fake data. In SCALA, Sdfac refines to ~1.0, SdB refines to
0, and Sdadd refines to the actual magnitude of fractional error
(introduced by beam flicker, shutter jitter, etc.). No surprises here.
2) "blur" the fake data with the point-spread function (PSF) empirically
derived for my detector
In this case, the "MOSFLM-refined gain" is too low. In SCALA,
Sdfac refines to ~1.3, SdB refines to 3-5, and Sdadd is a bit low.
These parameters are about what I see processing good real data.
3) use real data, but force MOSFLM to use the GAIN calibrated
independently for the detector
MOSFLM grumbles a lot about the BGRATIO. In SCALA, Sdfac refines to
~1, and SdB refines to ~0. Sdadd is consistent with my
independently-measured fractional error sources.
Now, I have not evaluated this approach on a huge number of data sets,
but in this case the PSF was both necessary and sufficient to explain
the "mystery of SdB". That is: the need for SdB arises because using an
"incorrect" gain creates a correlation between Sdfac and Sdadd. I
imagine there are other ways to get a non-zero SdB as well, but for
"good data" I suspect this is the dominant mechanism. I never wrote
this up because I am fairly certain the article would do nothing to
improve the impact factor of the journal in which it was published, but
this anecdote might perhaps be useful to Andrew, Phil, and a few other
readers of this list.
-James Holton
MAD Scientist
On 3/7/2011 2:00 AM, A Leslie wrote:
I have to say that I don't fully agree with James' recommendation to
adjust the GAIN in MOSFLM until the calculated SDFAC parameter in
SCALA is 1.0.
(Background information, the sigmas from Mosflm sd(I) are corrected in
SCALA according to
sd(I) corrected = SdFac * sqrt{sd(I)**2 + SdB*Ihl +
(SdAdd*Ihl)**2}
in order to get the best agreement between corrected sigmas and the
observed differences between symmtery/Friedel related intensities)
While I fully agree with his argument that systematic errors such as
absorption, etc give an error proportional to the intensity, and
therefore should be corrected by the SDADD term rather than SDFAC, in
any "real world" data set that I have come across the situation is not
so simple. Indeed, according to the usual treatment of errors there
should be no need for the SDB term in SCALA, but in practice it is
essential to have this term to be able to match corrected sigmas with
the observed differences between symmetry related reflections. It also
turns out that the three variable parameters SDFAC, SDB and SDADD are
highly correlated, so one can get rather different values for any
individual parameter from very similar datasets. Radiation damage is
certainly one source of error which would not be expected to follow a
simple error model, or non-isomorphism if multiple crystals have been
used.
Phil Evans is not entirely happy with the behaviour of the refinement
of these parameters and is in fact currently looking at this, but
there is a basic problem here that one is trying to use a simple
error model for a situation where (for whatever reason) it does not
really apply.
The sigma estimates from MOSFLM are only intended to give an estimate
of the random error in the intensities. In my opinion, trying to
account for systematic errors is best done at the point of merging the
data where much more information is available (ie symmetry related
measurements).
I would be most interested to hear of any examples where the default
value of the GAIN in MOSFLM is clearly wrong, but to the best of my
current knowledge the default GAIN is perfectly adequate.
Best wishes
Andrew
On 4 Mar 2011, at 19:47, James Holton wrote:
I have found that the best way to get the GAIN "right" in MOSFLM is
to have a look at the optimum "Sdfac" parameter at the end of SCALA
(the first of the three SDCORRection values). Specifically, if SDFac
is > 1, then you need to increase the GAIN. This is because SDFac>1
means that the spots were noisier than MOSFLM thought they should be,
and if a given number of ADU is noisier than expected, then there
must have been fewer photons involved in generating the signal. This
means that the "true gain" was higher. Yes, there are other sources
of error, like shutter jitter, beam flicker, calibration errors,
absorption effects, scale factor errors, etc. But these are all
directly proportional to the intensity, and therefore accounted for
by adjusting SDadd (the last of the three SDCORR values). SDfac
accounts for noise proportional to the square root of intensity, and
only shot noise (like photon counting) behaves like that.
David Waterman makes an excellent point that the point-spread
function (PSF) acts like a smoothing filter and makes the background
look less noisy than photon-counting error permits. This makes the
BGRATIO-estimated GAIN lower than the "true" GAIN. However, one can
argue that this is not always a bad thing, since the error in
measuring the intensity of a given area of flat background really is
"better than photon counting". This is because you have the
smoothing effect of the PSF working "for you": bringing in signal
from areas outside the region you are measuring (prior knowledge of
"flatness" if you will). However, this smoothing effect of the PSF
does not apply to spots because spot photons all arrive in
essentially the same place, and no "smoothing" will change the
intrinsic noise of the total number of photons that actually
arrived. The upshot of this is that we really need two different
values for GAIN, one for the background and one for the
background-subtracted spot intensity. The influence on sigma(I)
would depend on the relative contributions from the spot vs the
background under it. I am pretty sure this is not implemented.
It is perhaps interesting that there is also a third type of noise
which is independent of the spot intensity: "read-out noise". This
used to be called "fog" on film detectors. Despite all the money we
spend on detectors that minimize it, there is no specific accounting
for read-out noise in MOSFLM or any other integration package I am
aware of. However, a "trick" to account for it is to simply lower
the ADCOFFSET. For example, using 1 A X-rays on an ADSC Q315r
detector in hwbin mode, the true GAIN is 1.8 ADU/photon, the
ADCOFFSET is 40 ADU, and the read-out noise is equivalent to the
noise deposited by ~2 photon/pixel of x-ray background. This means
that a blank image has an average value of 40 ADU and rms variation
of ~2.5 ADU, but this is equivalent to an image from a detector with
the same gain, no read-out noise, and ADCOFFSET of 36 that was
"fogged" by 2 photons/pixel (regardless of exposure time). Yes, this
is a small change in ADCOFFSET, and I doubt you will notice the
difference. I think this speaks to the fact that, on modern
detectors at least, read-out noise is essentially negligible.
Another way to get the GAIN, of course, is to measure it directly. I
did this on an ADSC Q315 detector in swbin mode by comparison to a
NaI:Tl scintillator (after accounting for the window and sensor
thickness of the latter device):
http://bl831.als.lbl.gov/~jamesh/pickup/Q315_gain.png
You can see how the GAIN changes appreciably with photon energy, and
this is largely because lower-energy photons generate less signal.
GAIN also changes with the detector read-out mode. For example, this
number is 3 times higher for a Q315r in hwbin mode. I have listed my
best information on the typical GAIN and read-out noise of common
detectors on my "minimum crystal size" page here:
http://bl831.als.lbl.gov/xtalsize.html
You can extract the parameters by selecting the "detector type = "
you want, and then switching it again to "Custom..."
-James Holton
MAD Scientist
On 3/3/2011 12:34 PM, Bryan Lepore wrote:
wondering if mosflm can automatically estimate the gain.
i.e. i gather it is still estimated the usual way.
-Bryan
