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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 ... |