Independent of Waves 1–2 — can run in parallel.
The reuse story here is unusually good. SpyDE already depends on orix and already has IPF views, orientation maps and a 3D IPF toolbar from the 4D-STEM work (ipf_view.py, ipf_density.py, orientation_map.py), so a CrystalMap feeds straight into existing display code. The new work is the indexing math, not the display.
Scope decision: kikuchipy supplies signal classes, IO, detector geometry and master-pattern simulation. Dictionary indexing and refinement we implement in torch ourselves — that is the point of the wave, per "use the same methods but speed them up".
Plan: RELEASE_0_3_0_PLAN.md
Independent of Waves 1–2 — can run in parallel.
The reuse story here is unusually good. SpyDE already depends on orix and already has IPF views, orientation maps and a 3D IPF toolbar from the 4D-STEM work (
ipf_view.py,ipf_density.py,orientation_map.py), so aCrystalMapfeeds straight into existing display code. The new work is the indexing math, not the display.Scope decision: kikuchipy supplies signal classes, IO, detector geometry and master-pattern simulation. Dictionary indexing and refinement we implement in torch ourselves — that is the point of the wave, per "use the same methods but speed them up".
Plan:
RELEASE_0_3_0_PLAN.md