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Xscale: Difference between revisions
→Possible problems in scaling many datasets
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and check the column "ACCEPTED REFLECTIONS". Then remove the dataset(s) with fewest accepted reflections, and re-run the program. Repeat if necessary. | and check the column "ACCEPTED REFLECTIONS". Then remove the dataset(s) with fewest accepted reflections, and re-run the program. Repeat if necessary. | ||
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 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 | ||
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. | |||