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
    - #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 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)