Fix SSRB for ACFs in scatter estimation

[rmapree]

Changes in this pull request

Modified the make_2D_projdata_sptr function to include boolean. Added this into acfs modification to prevent converting 3d acfs to 2d.

Testing performed

rebuilt this, also used recon_test_pack tests to check scatter estimation. This works with these changes.

Related issues

Checklist before requesting a review

• I have performed a self-review of my code
• [] I have added docstrings/doxygen in line with the guidance in the developer guide
• [] I have implemented unit tests that cover any new or modified functionality (if applicable)
• The code builds and runs on my machine
• documentation/release_XXX.md has been updated with any functionality change (if applicable)

[KrisThielemans]

Looks good! Great to hear that it works!

The pre-commit checks fail due to white-space conventions.
https://github.com/UCL/STIR/actions/runs/11686408807/job/32542097224
If you're on Ubuntu 22.04, the easiest would be to

sudo apt install clang-format
clang-format -i include/stir/scatter/ScatterEstimation.h
clang-formiat -i scatter_buildblock/ScatterEstimation.cxx

If on another OS/version, we need a specific clang-format version, e.g. via conda.

There's more info on https://github.com/UCL/STIR/blob/master/documentation/devel/git-hooks.md, but it's a bit too brief...

[KrisThielemans]

Hopefully fixes #1280

[KrisThielemans]

Hi Toni, could you update the documentation/release_6.3.htm please? Add something in the "bug fixes" section, referring to this PR. May be text like (feel free to improve!)

Fixed a bug in the scatter estimation code (introduced in release 5.1.0) if input data is 3D and "cylindrical" (there was no bug for "blocksoncylindrical" data). The scatter estimation runs on data constructed via SSRB. However, the attenuation correction factors were incorrectly obtained with adding of oblique segments (as opposed to averaging). This resulted in intermediate images that had the wrong attenuation correction. This was compensated by the tail-fitting, but resulted in unexpected scale facctors (roughly smaller with a factor num_segments than expected). This means that if you used the "min/max scale factor" feature in the scatter estimate, you will have to adjust your threshold values. Expected scatter tail-fitting scale factors should now be restored to ~1-1.5 (depending on the amount of multiple and out-of-FOV scatter). See Issue 1532 for more detail.

Once done, tick the box at the start of the issue (looks like you'll need to edit it).

[KrisThielemans]

I've put #1539 on top of this one. I will therefore squash-merge this, as the history is now quite convoluted.

As #1539 is from your master, that will create some trouble, as your master will no longer be the same as UCL/master. That is bound to give trouble at some point. I'd recommend that once this is all merged, you do

git checkout master
git fetch upstream # assuming upstream == UCL
git reset --hard origin/master
git push -f origin master # assuming origin == rmapree

which will reset everything to match again.

Never do a PR from your master branch therefore 😄