MINIMUM ZETA - Revision history

Kay: update links

2019-10-22T10:24:30Z

update links

← Older revision		Revision as of 12:24, 22 October 2019
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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 (Kay Diederichs) routinely use 0.05 now.

	Update March 2012: the default was changed to 0.05 (Version December 31, 2011) after changing the integration algorithm to deal better with reflections near the rotation axis - see [http://homes.mpimf-heidelberg.mpg.de/~kabsch/xds/html_doc/Release_Notes.html].

	== 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? ==

Kay at 14:56, 22 March 2012

2012-03-22T14:56:40Z

← Older revision		Revision as of 16:56, 22 March 2012
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	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 (Kay Diederichs) routinely use 0.05 now.		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 (Kay Diederichs) routinely use 0.05 now.

			Update March 2012: the default was changed to 0.05 (Version December 31, 2011) after changing the integration algorithm to deal better with reflections near the rotation axis - see [http://homes.mpimf-heidelberg.mpg.de/~kabsch/xds/html_doc/Release_Notes.html].

	== 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? ==
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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

Kay: /* An example */

2007-12-05T21:01:19Z

An example

← Older revision		Revision as of 23:01, 5 December 2007
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	[[Image:ms688-frame.png]]		[[Image:ms688-frame.png]]

	From looking at rf.pck of many datasets, it is my experience that at the SLS (X06SA~~, Pilatus detector~~), 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.		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.

Kay at 11:12, 17 November 2007

2007-11-17T11:12:11Z

← Older revision		Revision as of 13:12, 17 November 2007
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	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~~.		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 (Kay Diederichs) routinely use 0.05 now.

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

	From 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 accurately measured reflections are added to the data set.		From looking at rf.pck of many datasets, it is my experience that at the SLS (X06SA, Pilatus detector), 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.

Kay at 22:22, 15 November 2007

2007-11-15T22:22:28Z

← Older revision		Revision as of 00:22, 16 November 2007
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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]]

Kay at 22:21, 15 November 2007

2007-11-15T22:21:20Z

← Older revision		Revision as of 00:21, 16 November 2007
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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 (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 accurately measured reflections are added to the data set.

Kay: /* An example */

2007-11-09T15:35:47Z

An example

← Older revision		Revision as of 17:35, 9 November 2007
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	== An example ==		== An example ==

	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.		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 default value of MINIMUM_ZETA= 0.15, one obtains in CORRECT.LP:
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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]]

			Finally, we may take a look at FRAME.pck and see that very few reflections are missing. The resolution of this image is not good enough to actually see the circles but one can see that all observed reflections are indeed hit by predictions.
			[[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.		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.

	Finally, we may take a look at FRAME.pck and see that very few reflections are missing. The resolution of this image is not good enough to see the circles but one can see that all observed reflections are indeed hit by predictions.
	~~[[Image:ms688-frame.png]]~~

Kay: /* Examples */

2007-11-09T15:33:13Z

Examples

← Older revision		Revision as of 17:33, 9 November 2007
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	For a finer evaluation, you might want to inspect with [[VIEW]] the file 'rf.pck' of [[XDSSTAT]] .		For a finer evaluation, you might want to inspect with [[VIEW]] the file 'rf.pck' of [[XDSSTAT]] .

	== ~~Examples~~ ==		== An example ==

			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.

	Using the default value of MINIMUM_ZETA= 0.15, one obtains in CORRECT.LP:		Using the default value of MINIMUM_ZETA= 0.15, one obtains in CORRECT.LP:

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	[[Image:zeta-0.15.png]]		[[Image:zeta-0.15.png]]

	~~However with~~ MIMUM_ZETA=0.1 the R-factors and ~~completenesses get~~ a ~~bit better~~:		With MIMUM_ZETA=0.1 the R-factors and completeness stays the same, but a closer look (not unexpectedly) reveals that the total number of observed reflections rises:
	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
	RESOLUTION NUMBER OF REFLECTIONS COMPLETENESS R-FACTOR R-FACTOR COMPARED I/SIGMA R-meas Rmrgd-F Anomal SigAno Nano		RESOLUTION NUMBER OF REFLECTIONS COMPLETENESS R-FACTOR R-FACTOR COMPARED I/SIGMA R-meas Rmrgd-F Anomal SigAno Nano
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	total 1725574 506106 524178 96.6% 18.6% 19.2% 1691046 5.43 22.0% 43.1% 2% 0.783 216270		total 1725574 506106 524178 96.6% 18.6% 19.2% 1691046 5.43 22.0% 43.1% 2% 0.783 216270

	~~and~~ the cones along the spindle are narrower:		obviously the cones along the spindle are narrower:
	[[Image:zeta-0.1.png]]		[[Image:zeta-0.1.png]]

	Finally, with MINIMUM_ZETA=0.01 the ~~statistics get~~ even ~~better~~:		Finally, with MINIMUM_ZETA=0.01 the number of observed reflections gets even higher:
	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
	RESOLUTION NUMBER OF REFLECTIONS COMPLETENESS R-FACTOR R-FACTOR COMPARED I/SIGMA R-meas Rmrgd-F Anomal SigAno Nano		RESOLUTION NUMBER OF REFLECTIONS COMPLETENESS R-FACTOR R-FACTOR COMPARED I/SIGMA R-meas Rmrgd-F Anomal SigAno Nano
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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]]

			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.

			Finally, we may take a look at FRAME.pck and see that very few reflections are missing. The resolution of this image is not good enough to see the circles but one can see that all observed reflections are indeed hit by predictions.
			[[Image:ms688-frame.png]]

Kay at 15:18, 9 November 2007

2007-11-09T15:18:06Z

@@ Line 16: / Line 16: @@
 == Examples ==
 [[Image:zeta-0.15.png]]
 [[Image:zeta-0.1.png]]
 [[Image:zeta-0.01.png]]

Kay at 15:08, 9 November 2007

2007-11-09T15:08:33Z

← Older revision		Revision as of 17:08, 9 November 2007
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	== Examples ==		== Examples ==

			[[Image:zeta-0.15.png]]

			[[Image:zeta-0.1.png]]

	[[Image:zeta-0.01.png]]		[[Image:zeta-0.01.png]]