Alex,
While I can understand the general rationale for the idea (minimize theThe massive random spikes can be made to disappear? Works on things like reflections from diamond anvil cells, mixtures of two phases where one has a very large grain size compared to the other, ice peaks etc. Most people will try to "mask" this stuff out manually in fit2d in the absence of some other method. Sometimes means having data you can treat instead of deleting it and repeating the experiment with a faster spinner.
weight of the very strong reflections to the final integrated intensity
for the reflection), could you expand further on your level of success
and any analysis you have carried out on this plan?
In particular, ifI'll ask around, can't think of any papers right now. One program to do it is "ascake", by Gavin Vaughan, if you are lucky enough to have data from ID11 at ESRF and access to our computers. Otherwise "cake" your data in fit2d into (say) 360 one degree azimuth bins, giving you 360 powder diffraction patterns. Then go to "image processing", select "filter", then "median", then the x bins should be 1 and the ybins should be 359. Rather slow, but effective at picking out the smooth rings and killing the spots. If there are only a few problematic outliers you can get away with fewer azimuthal bins. Via the "keyboard interface" in fit2d you can also compute a "histogram" of intensity values for an "ROI" containing one two theta and the whole range of azimuth. That is currently a bit painful as you need a long macro to do it for all two thetas, but you could then try to write out and fit the intensity distribution at each two theta to some meaningful function, like a lognormal distribution. I've never tried, as one ought to put in a Lorentz correction for the rotation, which is a bit difficult. Nothing intractable, but it is easier to measure grain sizes when you have resolved the spots by scanning the grains through the beam, so not a lot of point in making life difficult. There is an extensive literature on what to do when you can resolve individual spots - eg: "Three-Dimensional X-ray Diffraction Microscopy" by Henning Poulsen, Springer 2004.
you or anyone else has anything out in print that discusses this I would
be very interested.
Median filters are pretty much accepted, so it is not a great leap to realise that a 2D image has a high "redundancy" in terms of having measured the same 1D pattern multiple times. Even with only one image that information can confirm or rule out granularity and texture as long as you didn't rotate the sample around the incident beam during collection.
HTH,
Jon
