Hello, Continuing and confirmating Pavel's last comments: yes, we saw a number of practical cases when non-uniformly distributed missed data, even a small percent, caused great map distortions (some example are listed in our manuscript recently submitted to J.Appl.Cryst). To track this situation, recently we have developed a small python-based program that starting from your MTZ file searches for connected regions of such unmeasured reflections, gives their characteristics and visualizes the regions on the user's request. Presence of such regions may make your maps ugly even when the phases are perfect. For an official release when ready the program will be available at the Web site of the institute; for a time being if you want to test the current version please send me a mail to [email protected] With best regards, Sacha Urzhumtsev -----Message d'origine----- De : [email protected] [mailto:[email protected]] De la part de Pavel Afonine Hi Fengyun,
I am interesting in that at what completeness of the dataset, will one
use the missing fobs filled map for model building confidently without
too much bias included?
I'm not aware of any systematic study on this matter, although at some point I reviewed the available literature. There are numerous examples of how the data incompleteness distorts the map, and literature that discusses this. Interestingly, sometimes much smaller amount of systematically missing reflections, such as plane or cone in reciprocal space, may have much drastic effect than a larger amount of randomly missing data (if you are "lucky" enough it can mask entire structural domain).