MINIMUM ZETA: Difference between revisions

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As always, the authoritative documentation is at http://www.mpimf-heidelberg.mpg.de/~kabsch/xds/html_doc/xds_parameters.html#MINIMUM_ZETA= !
As always, the authoritative documentation is at http://xds.mpimf-heidelberg.mpg.de/html_doc/xds_parameters.html#MINIMUM_ZETA= !


== What is MINIMUM_ZETA? ==
== What is MINIMUM_ZETA? ==


MINIMUM_ZETA is a parameter determining how close reflections may be to the 'blind region' of reciprocal space to still be integrated. On the detector, the blind region consists of two cones starting at the direct beam position, and extending along the spindle, to both directions.
MINIMUM_ZETA is a parameter determining how close reflections may be to the 'blind region' of reciprocal space to still be integrated. On the detector, the blind region consists of two cones starting at the direct beam position, and extending along the spindle, to both directions.
A high value (corresponding to a large blind region) is "safe" but produces lower completeness because more pixels of the detector are considered to be in the blind region. The default of 0.15 is on the safe side. I routinely use 0.1, and 0.05 turns out to still be good.


== How could I check if a low value of MINIMUM_ZETA is beneficial for my data reduction? ==
== How could I check if a low value of MINIMUM_ZETA is beneficial for my data reduction? ==


It does not hurt to use a low value of MINIMUM_ZETA (e.g. 0.05) in INTEGRATE, because in CORRECT you may still choose higher values (i.e. you don't then have to re-run INTEGRATE if you want to test a different value).
It does not hurt to use a low value of MINIMUM_ZETA (e.g. 0.03) in INTEGRATE, because in CORRECT you may still choose higher values (i.e. you don't then have to re-run INTEGRATE if you want to test a different value).


Then, run CORRECT with the low values and with higher values and compare the resulting completeness and R-factors.
Then, run CORRECT with the low values and with higher values and compare the resulting completeness and R-factors.
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We collected data at the SLS, beamline X06SA, on a MarCCD 225 detector. Below, I show the final output of CORRECT.LP and a mapping of R-factors on the surface of the detector (file rf.pck produced by XDSSTAT).
We collected data at the SLS, beamline X06SA, on a MarCCD 225 detector. Below, I show the final output of CORRECT.LP and a mapping of R-factors on the surface of the detector (file rf.pck produced by XDSSTAT).


Using the default value of MINIMUM_ZETA= 0.15, one obtains in CORRECT.LP:
Using the former default value of MINIMUM_ZETA= 0.15, one obtains in CORRECT.LP (this is from a 2010 version of XDS):


  SUBSET OF INTENSITY DATA WITH SIGNAL/NOISE >= -3.0 AS FUNCTION OF RESOLUTION
  SUBSET OF INTENSITY DATA WITH SIGNAL/NOISE >= -3.0 AS FUNCTION OF RESOLUTION
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and there are few reflections missing in the blind region:
and there are few reflections missing in the blind region:
[[Image:zeta-0.01.png]]
[[Image:zeta-0.01.png]]


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[[Image:ms688-frame.png]]
[[Image:ms688-frame.png]]


Form looking at rf.pck of many datasets, it is my experience that at the SLS (X06SA), the R-factors along the spindle are better than perpendicular to it, which is quite surprising (and should be investigated). However it is clear that for these data, it is a good thing to decrease MINIMUM_ZETA because good reflections are added to the data set.
From looking at rf.pck of many datasets, it is my experience that at the SLS (beamline X06SA), the R-factors along the spindle are better than perpendicular to it, which is quite surprising (and should be investigated). Therefore it is clear that in particular for these data it is a good thing to decrease MINIMUM_ZETA because accurately measured reflections are added to the data set.
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