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.SubCompenent? 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

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

• integer parameters not fit properly
• deweighting SAXS fits
• downsampling SAXS data
• assign cost to structure in the residuals
• mask of middle part of data (e. g., spurions)