add: RSM Volume Builder — merge scan(s) into a gridded reciprocal-space volume

[pecomyint]

Summary

Adds the one thing rsMap3D (https://github.com/AdvancedPhotonSource/rsMap3D) can do that DashPVA could not: gridding every frame of one or more completed scans onto a single interpolated 3D reciprocal-space volume (xu.Gridder3D). We already converted angles to Q per frame, but could only show a bounded live point cloud — never a merged volume.

Launch with DashPVA rsmgrid or the Post Analysis launcher tile. Output uses the existing HDF5 volume format, so results open in Workbench's 3D viewer with no new viewer code.

Design notes worth reviewing

• Two passes are required, not an optimization. Gridder3D latches fixed_range on its first call when KeepData is set, after which points outside the first batch's range are silently dropped. Global bounds must be known and set via dataRange(fixed=True) before any gridding.
• Masked pixels are excluded, never zeroed. Gridder3D.data is a per-bin mean, so a zeroed-but-present pixel would count as a real intensity = 0 measurement and bias its voxel low.
• Energy/UB differences warn, they don't block. Each file's own UB is applied, so the merge already lands in a common crystal-fixed HKL frame — that's why rsMap3D applies UB per scan and doesn't block either. HKL is also geometrically energy-independent.
• Axes are labelled H/K/L, not Q — passing UB to Ang2Q.area returns hkl, not Q in Å⁻¹.
• Optional I0 normalization from entry/data/metadata/ca/<name>, matching rsMap3D's monitor division. Without it, scans at different exposure/attenuation won't match in intensity where they overlap.
• Batch size comes from a byte budget, not a frame count — a fixed 32 frames needs ~6 GB of coordinate arrays on a 2048² detector.
• grid_origin is shifted half a voxel: Gridder3D's axes are bin centers, but the PyVista viewer treats the origin as a cell corner.
• The mask is stored in the viewer's display orientation and that state is never persisted, so the dialog asks rather than guessing.

Refactor

utils/rsm_converter.py gains build_file_geometry() / q_for_frames() so QConversion/HXRD/init_area are built once per file instead of once per frame, using xrayutilities' batched angle arguments. Purely additive — no existing def removed, create_rsm() and get_sample_and_detector_circles() keep their signatures and behavior (a test asserts bit-identical Q against the old path). area_det_viewer.py and hpc_rsm_consumer.py have their own inline setups and are untouched.

Separate commit

687e943 fixes a pre-existing bug found while testing: the HDF5 metadata readers used hasattr(ds, 'asstr') to detect string datasets, but every Dataset has that method — it only raises on numeric ones, and the error was swallowed. voxel_spacing/grid_origin/grid_dimensions_cells/intensity_range were coming back as reprs like '[6 6 6]'. Reviewable/cherry-pickable on its own.

Testing

227 tests pass (18 new). Grid dims in tests are deliberately asymmetric — with nx==ny==nz a transpose bug still produces a correctly-shaped array. Coverage: batched-vs-per-frame Q equivalence, hot-pixel→voxel round trip through save/load, mask exclusion vs zeroing, mask transpose, I0 normalization, cell-corner origin, and a guard on the fixed_range latch we depend on.

Disjoint from #127 — zero file overlap.

Not yet validated on real data

• Detector axis-0 convention (cch1/pw1 vs row/col) against a known Bragg peak — pre-existing in rsm_converter, but now load-bearing. A swap would produce a transposed volume that still looks plausible.
• Half-voxel origin, visually in Workbench.
• Which metadata/ca/ key is I0 at the beamline.

Known gaps vs rsMap3D

No flat-field correction, no user-specified grid crop, no detector tilt (pre-existing rsm_converter limitation).

[pecomyint]

@Osayi-ANL Please let me know if you have started working on this. Open to hearing your thoughts on this since you have extensively worked on 3D HKL work. This is a new feature that beamlines would find useful.

[pecomyint]

@Osayi-ANL when you have a chance, please work on this.