Direct phase reconstruction and viewer handoff

Question and scope

Can a full-field regularized phase reconstruction feed the interactive viewer without preparing identical equations again?

Development source 5e2a153b53f4 plus the live-convergence and unchanged-rotation cache changes was exercised in a real Jupyter workflow. Private evidence id: 20261024-direct-live-full-field. The evidence retains the executed notebook, calibration, source fingerprint, package profile and original comparison array. No acquisition images or raw data are included here.

The input has 512 × 512 scan positions and native 192 × 192 detector pixels; 300 kV, 30 mrad aperture, 0.373046875 Å scan sampling and 0.5515329888475119 mrad detector sampling. Fifth-order optics, tilt and effective depth were reused from the archived fit. Auto output is 1536 × 1536 over 19.1 nm. The phase solve uses regularization 0.01, uniform detector weighting and smoothness crossover 1 Å⁻¹. No new binning, cropping of scan positions, optics search or diagnostic loss was introduced.

Observations

CUDA ran on an NVIDIA RTX PRO 6000 Blackwell Max-Q with other GPU jobs active. These are single notebook observations, not isolated benchmark medians or cold-disk measurements. Regularization timing includes stream synchronization; viewer timing ends after Python creates its object, before browser painting.

Operation	Before cache fix	After cache fix
First phase solve	11.2 s	11.1 s
Cached regularization change	1.258 ms	1.298 ms
Create viewer after the phase solve	10.8 s	88.7 ms

The viewer reapplied the same rotation through set_rotation, which discarded the prepared direct equations. An unchanged rotation now preserves that cache; a changed rotation still invalidates it. Reconstruction equations and precision are unchanged. Defocus changes still need new preparation and are slower than regularization changes.

The current full-field phase correlates with the archived phase at 0.999999, with RMS difference 0.000066 rad. This comparison is not bit-exact: historical and current bad-pixel handling differ for one pixel inside the aperture. It is a replay check, not independent physical resolution validation.

The browser used JavaScript fallback display, while reconstruction used CUDA. These timings do not demonstrate 60 fps. The live convergence chart was checked separately on a public experimental acquisition; it reuses optimizer values, throttles rendering and excludes display work from the numerical fit clock.

Verification

Both executed notebooks completed without errors. Independent review confirmed the unchanged scientific calculation and timing separation. The contract suite reported 497 passed, 57 skipped and 5 deselected; skips are not passes. Changed rotation invalidation and unchanged rotation reuse are covered explicitly.

2026-10-24: regularized methods in stream

Question: can stream(frames, fit, method=("phase", "complex")) reconstruct both regularized methods on every frame live, without changing the registration?

Setup: a real experimental 4D-STEM time series, 40 frames (512 x 512 scan, 192 x 192 detector) after the reference frame, output 1536 x 1536 at upsampling_factor="auto", GPU 0, show=False, a fresh scratch save_dir (every frame refit). Each frame runs SSB (for registration), then phase-only, then amplitude + phase, each with force=True, compute_loss=False.

Per frame, s (frames 1-39)	median	max
Load	0.483	0.603
Setup	0.170	0.311
Refit	0.047	0.096
SSB	0.033	0.068
Phase-only	0.037	0.103
Amplitude + phase	0.048	0.096
Align	0.078	0.165
Total	0.898	1.442

Frame 0: phase-only 0.121 s, amplitude + phase 0.074 s (first preparation). SSB alone: total median 0.837 s, wall 34.4 s for 40 frames; with both methods 36.9 s.

• Shifts and confidences with both methods equal the SSB-only run exactly (max difference 0.0 Å): registration is measured on the SSB phase whatever the methods.

• All 40 frames placed; one frame flagged Near threshold (confidence within 10% above 0.04).

• Memory: each frame’s SSB engine and its thick-sample model reference each other, so del alone left about 10 GB a frame until Python’s cycle collector ran (process peak 66 GB SSB-only, 95.5 GB with both methods). stream now calls the session’s close() after each frame, which breaks that cycle: process peak 40.5 GB (SSB) and 43.1 GB (both methods), 24-26 GB above the reference session (one frame in flight), with the cycle collector disabled for the whole run and no session or engine left afterwards. Stacks kept: 0.45 GB (SSB) and 1.56 GB (SSB, phase-only, amplitude + phase, amplitude), preallocated; torch keeps 0.03 GB after the series.

• Fix-round rerun (same setup): phase-only median 0.039 s, amplitude + phase 0.050 s, SSB 0.034 s, total 0.919 s a frame (max 0.967 s) against 0.861 s for SSB alone; shifts identical again.

• The combined phase, complex phase and amplitude show sharp atomic columns and the moiré at full resolution; no smearing from the shared shifts.