SNooPy generates light-curves of different decline rates by interpolating on a sparse surface defined by CSP photometry.
The Carnegie Supernova Project has developed an analysis package, written in python, called SNooPy. It's fundamental use is for fitting TypeIa supernova light-curves using template derived from the CSP uBVgriYJH photometry. SNooPy can therefore determine distances to SNeIa using any combination of these filters. More generally, SNooPy includes tools for computing S- and K-corrections, determining galactic extinction, producing synthetic photometry based on filter responses and spectral energy distributions, and general-purpose curve fitting. The code is available for download here.