listmode projectors/ parallelproj for listmode

Current listmode objective functions are essentially written in terms of ProjMatrixByBin. This is not suitable for GPU.

Some pointers:

• actual multi-threaded gradient calculation is here
  https://github.com/UCL/STIR/blob/8ced2d73933420457e0bc76074964b7d4ff00f0c/src/recon_buildblock/distributable.cxx#L599-L607
• This takes BinAndCorr:
  https://github.com/UCL/STIR/blob/8ced2d73933420457e0bc76074964b7d4ff00f0c/src/include/stir/Bin.h#L110-L114
  which sadly is not a Bin (although that has a value field, and in the caching we re-use that for the "additive correction" I believe)
• non-multi-threaded calculation of gradient, i.e. without caching is here
• the Listmode objective hierarchy is split into 2 (not always logically)
  • PoissonLogLikelihoodWithLinearModelForMeanAndListModeData
  • PoissonLogLikelihoodWithLinearModelForMeanAndListModeDataWithProjMatrixByBin, adding stuff for computing sensitivity and obviously the gradient

Probably with not too much work the PoissonLogLikelihoodWithLinearModelForMeanAndListModeDataWithProjMatrixByBin can be generalised. We might need (and seem relatively easily add)

• virtual void ForwardProjectorByBin::forward_project(std::vector<Bin>&), storing results in the value. (Currently a by bin version is disabled).
• virtual void BackProjectorByBin::back_project(std::vector<Bin>&)

These would have to be implemented for the ProjMatrixByBin and Parallelproj projectors, but throw an error by default (for other projectors).

Start with PoissonLogLikelihoodWithLinearModelForMeanAndListModeDataWithProjMatrixByBin and its gradient and sensitivity code, then read ForwardProjectorByBin.h, BackProjectorByBin, and the distributable.cxx gradient path. Compare the existing ProjMatrixByBin interfaces with the Parallelproj projector implementations. Done means listmode objective calculations can use vector for forward and back projection, with supported projectors implementing the operations and other projectors reporting an error.