Xscale: Difference between revisions

← Older edit

Xscale (view source)

Revision as of 12:11, 20 March 2024

433 bytes removed , 20 March 2024

m

→‎keywords unique to XSCALE: REIDX_ISET

Kay

Bureaucrats

2,710

edits

@@ Line 5: / Line 5: @@
 One advantage of using XSCALE for a single dataset is that the user can specify the number and limits of the resolution shells. Another is that zero-dose extrapolation can be done.
-At the XDS website, there is a short and a long commented example of [http://www.mpimf-heidelberg.mpg.de/~kabsch/xds/html_doc/INPUT_templates/XSCALE.INP XSCALE.INP]
+At the XDS website, there is a short and a long commented example of [http://xds.mpimf-heidelberg.mpg.de/html_doc/INPUT_templates/XSCALE.INP XSCALE.INP]
 ----
@@ Line 51: / Line 51: @@
 === keywords unique to XSCALE ===
+* REIDX_ISET=                    ! re-index data from the most recent INPUT_FILE
 * MERGE=                         ! average intensities from all input files, applies to output file
 * WEIGHT=                        ! applies to input file
@@ Line 112: / Line 113: @@
 and check the column "ACCEPTED REFLECTIONS". Then remove the dataset(s) with fewest accepted reflections, and re-run the program. Repeat if necessary.
-The latest XSCALE (March 1, 2015) makes it explicit which dataset(s) it cannot scale; it prints out e.g. "no common reflections with data set          197". If you get this message for many datasets, I suggest to have a line
+XSCALE makes it explicit which dataset(s) it cannot scale; it prints out e.g. "no common reflections with data set          197".
- MINIMUM_I/SIGMA=2 ! reduce to 1, or 0.5, or 0.25, or 0.125, or ... to lower the cutoff
-after each INPUT_FILE= line, to increase the number of reflections available for scaling. However, MINIMUM_I/SIGMA= should not be decreased needlessly below its default of 3.
-Old versions of XSCALE may also finish with the error message !!! ERROR !!! INACCURATE SCALING FACTORS. This usually indicates that one or more datasets are linearly depending on others (this happens if the ''same'' data are included more than once as INPUT_FILE), or are pure noise. The latest version of XSCALE (March 1, 2015) copes much better with this situation; I have not seen this error message any more.
+XSCALE may also finish with the error message !!! ERROR !!! INACCURATE SCALING FACTORS. This usually indicates that one or more datasets are linearly depending on others (this happens if the ''same'' data are included more than once as INPUT_FILE), or are pure noise.