NXmx: handle multidimensional arrays

[phyy-nx]

Data in NeXus can be 3 or 4 dimensional:
3D: Nimages by slow by fast
4D: Nimages by Nmodules by slow fast

Slice image_size and reshape the raw_data in these cases

Adapted from FormatNexus.py:
https://github.com/cctbx/dxtbx/blob/main/src/dxtbx/format/nexus.py#L852-L857
https://github.com/cctbx/dxtbx/blob/main/src/dxtbx/format/nexus.py#L1329-L1331

[codecov]

Codecov Report

Merging #612 (969c87d) into main (d516f20) will increase coverage by 0.01%.
Report is 2 commits behind head on main.
The diff coverage is 100.00%.

Additional details and impacted files

@@            Coverage Diff             @@
##             main     #612      +/-   ##
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+ Coverage   39.11%   39.13%   +0.01%     
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  Files         179      179              
  Lines       15823    15828       +5     
  Branches     3057     3057              
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+ Hits         6189     6194       +5     
  Misses       9052     9052              
  Partials      582      582              

[phyy-nx]

I think this line needs to be worked on as well, but I don't have a use case for it right now:
https://github.com/cctbx/dxtbx/blob/main/src/dxtbx/nexus/__init__.py#L478

[phyy-nx]

I think this line needs to be worked on as well, but I don't have a use case for it right now: https://github.com/cctbx/dxtbx/blob/main/src/dxtbx/nexus/__init__.py#L478

Fixed! I have a usecase for a 3D mask now

[ndevenish]

Do you have any test files/files we can make in the right shape, to add to the testing?

[rjgildea]

@phyy-nx I've attempted to add a basic test for what I understand of this use case. Could you take a look and verify that it makes sense from your perspective?

[rjgildea]

This adds support for a use case that wasn't previously handled, LGTM 👍

[phyy-nx]

Hi @ndevenish I reviewed @rjgildea's test and it looks perfect. I think this is ok to merge as is.