Ticket #7383 (closed: fixed)

Opened 7 years ago

Last modified 5 years ago

Investigating using poisson cost function

Reported by: Anders Markvardsen Owned by: Mike Thomas
Priority: major Milestone: Release 3.0
Component: Framework Keywords:
Cc: james.lord@… Blocked By:
Blocking: Tester: Anders Markvardsen

Description (last modified by Anders Markvardsen) (diff)

James has identified some cases where Mantid fit struggles.

Here investigate the potential benefit of using poisson statistics.

See attached python scripts and James writes:

(a) a plain "background" count level in a single group

(b) Asymmetry, with a constant value

(c) a more real example: a slowly relaxing oscillating signal (TF muSR).

Attachments

FitLowStatsAsymChallenge.py (2.6 KB) - added by Anders Markvardsen 7 years ago.
FitLowStatsChallenge.py (1.7 KB) - added by Anders Markvardsen 7 years ago.
FitLowStatsOscChallenge.py (3.1 KB) - added by Anders Markvardsen 7 years ago.
flatBGfigs.png (29.1 KB) - added by Mike Thomas 7 years ago.
fitLowStats.m (972 bytes) - added by Mike Thomas 7 years ago.
flatBG.m (226 bytes) - added by Mike Thomas 7 years ago.
flatBGpo.m (244 bytes) - added by Mike Thomas 7 years ago.

Change History

Changed 7 years ago by Anders Markvardsen

Changed 7 years ago by Anders Markvardsen

Changed 7 years ago by Anders Markvardsen

comment:1 Changed 7 years ago by Anders Markvardsen

  • Description modified (diff)

In addition investigate the effect of the different minimizers. I.e. would changing the minimizer give different results for James' examples

comment:2 Changed 7 years ago by Nick Draper

  • Milestone changed from Release 2.6 to Backlog

Moved to backlog at the code freeze for R2.6

comment:3 Changed 7 years ago by Anders Markvardsen

  • Milestone changed from Backlog to Release 3.0

comment:4 Changed 7 years ago by Anders Markvardsen

  • Summary changed from Investigate examples where Mantid fit fails to Investigating using poisson cost function

comment:5 Changed 7 years ago by Anders Markvardsen

  • Description modified (diff)

Changed 7 years ago by Mike Thomas

Changed 7 years ago by Mike Thomas

Changed 7 years ago by Mike Thomas

Changed 7 years ago by Mike Thomas

comment:6 Changed 7 years ago by Mike Thomas

The python script (a) was adapted into a matlab script and a fit using poisson cost function added. Poisson data is generated according to a count rate and each cost function is used to calculate the background rate. The difference between the two calculated rates and the rate used to generate the poisson data is plotted, showing clear regions where the poisson cost function is better than the gaussian based least squares cost function. The scripts and functions are attached(fitLowStats.m, flatBG.m, flatBGpo.m), as are the result plots (flatBGfigs.png). The results suggest it is necessary to implement the cost function in Mantid Fit. See ticket #7914

comment:7 Changed 7 years ago by Mike Thomas

  • Owner changed from Anders Markvardsen to Mike Thomas
  • Status changed from new to verify
  • Resolution set to fixed

comment:8 Changed 7 years ago by Anders Markvardsen

  • Status changed from verify to verifying
  • Tester set to Anders Markvardsen

comment:9 Changed 7 years ago by Anders Markvardsen

  • Status changed from verifying to closed

As mike showed me attached data show poisson give at least as good as least squares for higher counts and better for lower count data

comment:10 Changed 5 years ago by Stuart Campbell

This ticket has been transferred to github issue 8229

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