Autogenerated parts of the model
    - [PAK-9 #332] fix cos(theta) issue on angular dispersion 
    - [PAK-9] mixture models/product models
    - [PAK-8] tied parameters
    - [PAK-7 #363] 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
    - [WP-?] 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
    - [steve, richard?] check docs [#19]

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)