Refactors various setup steps out of purify main and into separate functions so that they can be shared with UQ
Calculates likelihood / prior terms assuming they are L2 and L1 norms (will need update when pytorch models are in place)
Currently needs
I think sigma can be derived from the purify config parameters so that should be updated
We need some purify config files to test the UQ and purify apps with to make sure nothing is breaking
There are two paths for the setup, one using a purify config file and one based on the algo_factory test case. This is so there's something I can run this with and check that the app is doing something sensible in lieu of a purify config file but it should be taken out later.
Some appropriate tests need to be devised.
Issues
Replacing the line:
const VectorC wavelet_rep = wavelet_operator->adjoint() * image;
in UQ with
const auto wavelet_rep = wavelet_operator->adjoint() * image;
causes a seg-fault, although I don't know why yet. The inferred type of wavelet_rep is AppliedFunction, and in the next line when we call the sum and things are evaluated we get a seg-fault.
Changes
main
and into separate functions so that they can be shared with UQCurrently needs
algo_factory
test case. This is so there's something I can run this with and check that the app is doing something sensible in lieu of a purify config file but it should be taken out later.Issues Replacing the line:
const VectorC wavelet_rep = wavelet_operator->adjoint() * image;
in UQ withconst auto wavelet_rep = wavelet_operator->adjoint() * image;
causes a seg-fault, although I don't know why yet. The inferred type ofwavelet_rep
isAppliedFunction
, and in the next line when we call the sum and things are evaluated we get a seg-fault.