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The Idea of Automated Fitting

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Valutazione

Difficoltà
5/5
Tempo stimato
Più di una settimana
Idoneità per principianti
45/100
Tipo di issue
Funzionalità
Chiarezza
Abbastanza chiara
Stato di attività
Attiva
Stack tecnologico
python
Ambito
backend, data

Direzione di ricerca

Start by reading the Bluesky callbacks documentation linked in the issue and reviewing the existing rscan and go peak workflow shown there. Define how multiple fitting options and post-scan results would support future plans, then verify that the mechanism is centrally available and satisfies both acceptance criteria.

Scritto dal modello di indicizzazione a partire dal testo della issue.

Descrizione

Currently GDA provides automated fitting for 1D datasets, and serves results to users to act upon. This is incredibly useful for alignment scans. It fits multiple options (see the image below, from left to right):

  1. One Gaussian to a scan: Used for aligning to the centre of something vaguely guassian shaped, here an imperfect top-hat. This can be used for determining the centre position of any multitude of objects.
  2. One Gaussian to the 1st derivative of a scan: Usually used for aligning to a knife edge scan, for example finding the edge of a slit or any other object with a hard edge.
  3. Two Gaussians to the 1st derivative of a scan: Usually used to find the middle of two edges something vaguely top-hat shaped. This can be used for aligning a number of things which have an inconsistent intensity across (a heterogeneous sample for instance), but have clear edges.
Image

The current use of this feature is by doing a scan, then requesting to move to a particular position:

rscan my_motor -5 5 1 my_detector
go peak

This is particularly useful for more complex (automated) fitting routines which are in regular use around the ring. Need to align your slits? That's a relatively stable process which takes 15 minutes, but you don't need there to be making the decisions about where your slit edge sits. You just need reliable fitting which your plan can act on.

There is a potential solution in bluesky, but currently I believe this implementation has drawbacks:

  1. It seems you can only fit one model at a time - not ideal if we're not sure if fit 1 or fit 3 will work better for us (usually this distinction is made by eye and by asking the question "Is my signal Gaussian enough for that Gaussian fit?")
  2. As far as I can tell, you need to provide a model and initial guess before you collect your signal (when you subscribe before the scan). I've found that even relatively good guesses for a perfect Gaussian (accurate position and sigma, but inaccurate intensities) will fail to find a fit completely. Not ideal for a generic scan when I may have decades of intensity differences across different detectors.

Perhaps this is a candidate for use with the new live-processing service, perhaps @RJCD-Diamond could comment on this?

Acceptance Criteria

  • There is a mechanism for automated alignment which allows users to action future plans based on these fitting results.
  • This mechanism is centrally available so at least the most-used fitting procedures don't need to be defined at each instrument.
Lingua principale
Python
Stelle
13
Fork
14
Merge medio
6g 15h
PR unite (30g)
14

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