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Collision maps and data collection

Collision maps and data collection. Introductory remarks. Collision maps. COLLISION PREVENTION Employed outside the data collection context Parallel with hardware solutions collision restriction by design restriction of experimental parameter range

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Collision maps and data collection

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  1. Collision maps and data collection Introductory remarks

  2. Collision maps • COLLISION PREVENTION • Employed outside the data • collection context • Parallel with hardware solutions • collision restriction by design • restriction of experimental • parameter range • Video, mechano/optical switches, …. • DATA COLLECTION • Description of the restrictions in the crystal orientation space that can be • exploited in the rotation method • data collection • Communication of the latter to strategy and data • collection software VRML/VBS/BIOXDM Is it the most efficient approach from the data collection point of view?

  3. Suggestion for this session:separate the topics • Collision prevention (SLS, EMBL-GR, ?) • Data Collection • Following an example demonstrated yesterday by Sasha mock up a realistic useful to the user data collection application exploiting Kappa • Develop the latter to a sufficient level of agreed details so that it can be presented to EDNA-MX communities as a suggestion for implementation • Discuss on the feasibility of a simplified approach to description of the “rotation freedom” to the strategy module(s) of such an application

  4. idealistic design of a strategized data collection application • Input: A crystal Possibly some prior knowledge (like SG) in use: SG, chem. Composition, xtal shape possible: structure, previous data collections, expected anom. Sig., xtal availability Some wishes about the data: in use: diffraction plan Instrument configuration • Output: Data collection queue (complete set) Some promises on how the data would look like

  5. The workflow • Characterize crystal • Calculate strategy, including best orientation(s) as parameter(s)

  6. The caveat • Is characterization valid after changing the orientation ? • Scattering power model void - different part of the crystal is exposed • Sample shape definition is void • mosaicity model possibly void • … • Strategy is void for a new orientation …

  7. The workflow • Characterize crystal • Optimize orientation • Implement optimal orientation • Characterize crystal • Calculate strategy Any way to fit in a multiple orientation strategy?

  8. MxCuBE: Creates CharaterizationInput, or input/edit existing CharacterizationInput or CharacterizationOutput Invokes EDNA • EDNA requires new option to start the characterization with an existing IndexingSolution (=CharacterizationOuput) EDNA returns gonio setting Executive / HTML log output • Step 1, 2: Optimize the orientation • Input: • One of the options: • Mounted sample • Reference Frames • Indexing solution of reference frames • Instrument configuration descriptor • Diffraction plan • Optional: Preferred orientation • Output: • Optional:Suggested orientation for diffraction plan • Possible methods: • Optimized by data statistics criteria • About a suitable mirror plane • About a long axis • (Close to) longest axis/w. account of blind region • Shortest total rotation range • The one the PI used in his thesis • Goniometer setting • Processing log output (justification of a choice, scores of different orientations, etc. – e.g. suggestion for a better orientation vs preferred one)

  9. Step 2: Implement gonio setting • Step 3: Characterize in a new orientation • Optionally (by configuration): • Collect new set of frames for strategy • (small beam case) • or • Re-use the data from the previous step • (large beam case) • Calculate strategy for chosen orientation • Compare two characterizations, report on • consistency MxCuBE : after user confirmation implements the gonio setting MxCuBE : Prepares EDNACharacterization interface, prompts user to re-center the sample and to re-define the crystal shape factors according to the new orientation. User launches “Collect and Characterize” with Indexing Solution of step 1 MxCuBE : launch re-characterize with Step 1 data EDNACharacterization with IndexingSolution

  10. Possible methods for optimizing the orientation • Diffraction plan always resolves anomalous (“SAD”) or “Native” data • Optimization by data statistics criteria – BEST • optimization of orientation for native or for SAD • slow

  11. Possible methods for optimizing the orientation Fast Slow • BEST optimization on statistics criteria: search low index orientation providing Highest resolution/Lowest dose for • SAD data at a given Rfriedel • for native data at a given I/SigI • About a suitable mirror plane • About a long axis • (Close to) longest axis/w. account of blind region • Shortest total rotation range • Preferred by user parallel version (in work) ~30 sec on a good machine Which method(s) to implement ? In what priority ? Let user choose? How?

  12. Discuss on the feasibility of a simplified approach to description of the “rotation freedom” Example: MiniKappa Goal : exclude all orientations with partial occlusion of the diffraction pattern Solution? : approximate parametric model to compute Omega range free of occlusions at any given Kappa Collision map approach is simple enough, and can be made even simpler if implemented directly in control software Is there any reason to consider further simplification?

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