Scipy/numpy implementation of the French & Wilson algorithm #2100
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This gives more even number of reflections per bin
As used in the phenix "massage_intensities" option. This uses the formula |F| = sqrt((Io+sqrt(Io**2 +2sigma**2))/2.0) to obtain amplitudes if fewer than min_reflection (default=200) are present.
Codecov Report
@@ Coverage Diff @@
## main #2100 +/- ##
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+ Coverage 80.31% 80.36% +0.04%
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Files 576 578 +2
Lines 65245 65413 +168
Branches 9208 9219 +11
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+ Hits 52402 52567 +165
- Misses 10805 10806 +1
- Partials 2038 2040 +2 |
jbeilstenedmands
approved these changes
Jun 1, 2022
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I tested this on some ssx data that gets very weak/noisy at higher resolution, and the new implementation clearly handles the weak data better.
This PR:
Current main:
It seems to do that by filtering out more of the data, which is probably the right thing to do in this case.
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This implementation uses the standardized median as an M-estimator for the average intensity of resolution bins, as mentioned in #2067 (comment) which makes the procedure robust against the presence of very negative intensities as highlighted in that issue.
The choice between the new
dialsand existingcctbximplementations can be made using the parameterfrench_wilson.implementation=dials|cctbx.Resolves #2067