OPR

[plnyyanks]

Originally Posted by Ether

Just a minor observation FWIW:

To solve [M][x]=[s], that code uses numpy.linalg.solve which uses LAPACK routine gesv which does LU decomposition.

Since [M] is symmetric positive definite, Cholesky decomposition can be used instead to take advantage of that particular matrix structure.

For OPR computation for single events the difference will likely be negligible, but when computing combined OPR for all events for an entire season Cholesky will be noticeably faster than LU.

Really interesting, thanks for input. This'll be a good offseason hackathon project!