Add support for Non-negative Matrix Factorization (NMF) templates, whose coefficients should be solved with scipy.optimize.nnls (non-negative least squares) rather than numpy/cupy.linalg.solve.
Proposal: add new header keyword RRMETHOD which could be "PCA" or "NMF", and propagate that through Template.solve_matrices_algorithm to know which algorithm to use. Include legacy support for existing templates to default to "PCA" if the header keyword is missing. Perhaps only do that for specific versions, while requiring this keyword for all future templates.
I'm working on this, but am adding this as a ticket for tracking.
sbailey
commented
5 months ago
Add support for Non-negative Matrix Factorization (NMF) templates, whose coefficients should be solved with
scipy.optimize.nnls(non-negative least squares) rather thannumpy/cupy.linalg.solve.Proposal: add new header keyword RRMETHOD which could be "PCA" or "NMF", and propagate that through
Template.solve_matrices_algorithmto know which algorithm to use. Include legacy support for existing templates to default to "PCA" if the header keyword is missing. Perhaps only do that for specific versions, while requiring this keyword for all future templates.I'm working on this, but am adding this as a ticket for tracking.