Autogenerated parts of the model - #332 [PAK-9] fix cos(theta) issue on angular dispersion - [PAK-9] mixture models/product models - [PAK-8] tied parameters - #363 [PAK-7] linearize for loop to avoid OpenCL problems when model runs too long - [PAK-5] vector parameters - [PAK-0] magnetism on each of the sld parameters - [MG-?] autogenerate figures for docs from demo parameters (or maybe default) - [PAK?-7] need an easy way to reparameterize an existing model - [PAK?-?] can't currently reference other models from within one model - #492 reparameterize orientation Existing models - [various] #364, #377, #439, #410, #288, #347, #472, #484 fix problems with specific models (see tickets) - [various] clean up model code (e.g., use J1c, sinc, etc.) - #509 [WP] move from NR J1 (higher precision--current is 1e-9;licensing issues) l - #19 [steve, richard?] check docs Integration - slowly evolve the sasview model api - #505 Thoroughly test sasview with new sasmodels (e.g., is sas.models. !SubComponent needed/supported) - #348 [MG] preserve parameter order using ordered dict, with removing sort in GUI - #506 introspect to find available models - redo interface to resolution within sasview GUI so that it doesn't recalc q every time - show min max in gui GUI aspects - show components separately for product and sum models - weighted sum of several models (mixture models) to avoid e.g., p1_p2_radius - can we do mixture models "on the fly" - #504 generate new model.py file from GUI - #411 no stop button for constrained fits - #473 - Bumps improvements - #270 check bumps error bars - #456 better handling of bumps plots - integer parameters not fit properly Parameter enhancements - display ER and VR when available - access to effective radius in constraints - don't use automatic constraint to set effective radius in product model - allow model to define the derived parameters (possibly polydisperse) - allow parameters not part of existing models for use in constraints (e.g., by having a zero model with k parameters) Fitting Enhancements - deweighting SAXS fits - downsampling SAXS data - assign cost to structure in the residuals - mask of middle part of data (e. g., spurions)