Calculate average I/sigma from .sca file: Difference between revisions
Jump to navigation
Jump to search
No edit summary |
No edit summary |
||
(One intermediate revision by the same user not shown) | |||
Line 1: | Line 1: | ||
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. Syntax is quite simple | 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. Syntax is quite simple | ||
./ioversigma.py <.sca-file name> <number of shells> | ./ioversigma.py <.sca-file name> <number of shells> | ||
The number of shells is an optional parameter and defaults to 10 if omitted. | The number of shells is an optional parameter and defaults to 10 if omitted. | ||
Line 25: | Line 25: | ||
Same trick also works with data from XDS/XSCALE; in that case use | Same trick also works with data from XDS/XSCALE; in that case use | ||
pointless xdsin ... | pointless xdsin ... | ||
Back to [[Useful scripts (aka smart piece of code)]] |
Latest revision as of 16:06, 16 December 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.
This works on merged intensities, i.e. the standard scalepack output. An alternative below uses the unmerged output from scalepack.
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 ...