McSAS Integration Project

There is a desire to incorporate McSAS into SasView as another optimization tool for the users without having to install and run a separate package. From the development and maintenance perspective this should also simplify keeping all the features working and updated in a consistent manner.

McSAS fits data using an MC algorithm to extract a parameter distribution. For example for a system of spheres, it will return a distribution of sphere sizes with minimal a priori information. As such it most resembles an optimizer in SasView which optimized the center and polydispersity of a parameter. The integration thus probably should involve changing the optimization framework in SasView to allow a different optimization engine per FitPage and provide McSAS as an optimizer. Care needs to be taken with how the parameters are presented in this case as McSAS always optimizes scale and background and otherwise always fits a polydispersity — so there may need to be a switching of GUI for parameter set ups. Finally the output needs to be fed back so that a fit can continue using a different optimizer but maintaining the McSAS distribution output as a fixed array polydispersity on that parameter. Of course the primary output of McSAS would be the plots of the distribution of the parameters which actually should use the underlying infrastructure created for ticket #17.

Tasks

We can take a stepwise approach where each part could be worked on independently. For example number 2 and 4 would be useful independently of integrating or not McSAS.

1. Get McSAS running as an optimizer within SasView
2. Build infrastructure to plot distribution of a parameter
3. Output McSAS "population" to work as an array distribution
4. Change UI to allow separate optimizer choice in each fit page
5. Refine UI for ease of use of McSAS fitting and switching between regular fitting vs McSAS fitting.

Tickets

Milestone: SasView 4.2.0 (1 match)

Ticket	Resolution	Summary	Owner	Reporter
#1173	fixed	more problems with math in plugins	pkienzle	butler
Milestone: SasView 4.2.1 (1 match)
Ticket	Resolution	Summary	Owner	Reporter
#1206	fixed	Incorrect (and confusing) presentation of dQ from data in instrumental smearing section	GitHub <noreply@…>	butler
Milestone: SasView 5.0.0 (2 matches)
Ticket	Resolution	Summary	Owner	Reporter
#1182		python old buffer interface deprecated in python 3		pkienzle
#1171		Expose volume calculation in SasModels	pkienzle	toqduj
Milestone: SasView 4.3.0 (7 matches)
Ticket	Resolution	Summary	Owner	Reporter
#1230		parallelize polydispersity loops		pkienzle
#1224		Add warning to smearing sizer in fitpage when dq is too large		butler
#1220	fixed	log scale 2D data with zeros and negative values not plotted correctly	GitHub <noreply@…>	pkienzle
#1219		custom_config.py and categories.json are overwriten when running from run.py		wojciech
#1207		don't create .pyc files in ~/.sasview		pkienzle
#1186		be_polyelectrolyte model needs proper validation check		butler
#1169		Limit of core_shell_cylinder should be exactly the same as hollow_cylinder		butler
Milestone: SasView 5.1.0 (5 matches)
Ticket	Resolution	Summary	Owner	Reporter
#1270		Add McSAS as optimizer	ibressler	ibressler
#1269		build fitting options from optimizer defaults automatically	ibressler	ibressler
#1268		abstract optimizer handling	ibressler	ibressler
#1172		Allow "polydispersity" to be defined by series/sets of uncorrelated, discrete points		toqduj
#17	fixed	Ability to plot the distribution functions from polydispersity		ajjackson
Milestone: SasView Next Release +1 (1 match)
Ticket	Resolution	Summary	Owner	Reporter
#1177		array distribution not respecting hard limits on parameter		pkienzle
Milestone: sasmodels 1.0 (1 match)
Ticket	Resolution	Summary	Owner	Reporter
#1193		improve implementation of Si and JN		pkienzle