Calculate average I/sigma from .sca file: Difference between revisions
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(Created page with 'This python script will analyze a .sca-file and print out the key statistics missing from the standard SCALEPACK log-file, namely <math><I/sigma></math> per resolution shell. Sy…') |
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[https://docs.google.com/uc?id=0Bxe0ET6Vsx-kZmM2YWZkNmYtMjQxZS00N2U3LTg1YTgtM2EwMTY5MzFlNjAw&export=download&hl=en Get ioversigma.py here] | [https://docs.google.com/uc?id=0Bxe0ET6Vsx-kZmM2YWZkNmYtMjQxZS00N2U3LTg1YTgtM2EwMTY5MzFlNjAw&export=download&hl=en Get ioversigma.py here] | ||
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An alternative is to use SCALA (you will also need to assign the cell and symmetry) after pointless : | |||
pointless -c scain ... | |||
scala hklin from_pointless.mtz hklout merged.mtz << eof | |||
run 1 all | |||
scales constant | |||
sdcorrection noadjust norefine both 1 0 0 | |||
cycles 0 | |||
eof | |||
This will just remerge the measurements and give you the usual merging analysis from Scala. | |||
Same trick also works with data from XDS/XSCALE; in that case use | |||
pointless xdsin ... | |||
Revision as of 16:50, 3 November 2010
This python script will analyze a .sca-file and print out the key statistics missing from the standard SCALEPACK log-file, namely [math]\displaystyle{ \lt I/sigma\gt }[/math] per resolution shell. Syntax is quite simple
./ioversigma.py <.sca-file name> <number of shells>
The number of shells is an optional parameter and defaults to 10 if omitted.
An alternative is to use SCALA (you will also need to assign the cell and symmetry) after pointless :
pointless -c scain ...
scala hklin from_pointless.mtz hklout merged.mtz << eof run 1 all scales constant sdcorrection noadjust norefine both 1 0 0 cycles 0 eof
This will just remerge the measurements and give you the usual merging analysis from Scala. Same trick also works with data from XDS/XSCALE; in that case use
pointless xdsin ...