Commit Graph

15 Commits

Author SHA1 Message Date
Thomas Ales [M S E] efecc154fe Keep stored row-averaged caches eligible on the fallback compute path
ComputeWorker dropped row_avg_n, so a stored row-averaged cache was
ineligible whenever the fallback compute served the image instead of the
DC precompute path. Thread the viewer's precomputed_row_avg_n through
ComputeWorker and the batch export worker's compute_rf_image call.

Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
2026-08-12 10:17:16 -05:00
Thomas Ales [M S E] 105b9514a5 Merge remote-tracking branch 'origin/main' into main
# Conflicts:
#	sras_compute.py
#	sras_viewer.py
#	sras_workers.py
#	tools/make_test_sras.py
#	tools/test_refactor.py
2026-08-10 18:58:21 -05:00
Thomas Ales [M S E] 6976cbf767 Add batch export of DC/RF/Velocity map images
Add Export -> Batch Export Images..., which renders and saves one PNG
per angle for whichever of CH1 (RF), CH3 (DC-A), CH4 (DC-B), and
Velocity the user selects, for the currently open file. Each channel
gets its own fixed min/max colorbar range, entered once in the dialog
and held constant across every exported angle, so the resulting images
are directly comparable to each other instead of each auto-scaling to
its own data (today's live-view default).

BatchExportDialog (sras_viewer.py) collects the output folder, file
prefix, and per-channel checkbox + range, seeded from whatever's
already cached (session DC/FFT caches, or the file's own v7 cache
blocks) so opening the dialog never triggers a fresh compute. Export
runs on a background thread via a new BatchExportWorker
(sras_workers.py), which computes each angle's channel image with the
existing dc_image_mv/compute_rf_image helpers (reusing one FFT per
angle for both RF and Velocity) and renders it with a headless
matplotlib Agg canvas.

Also includes several small correctness/robustness fixes that were
already staged in the working tree: an int16-vs-float32 accumulator
mismatch in sras_average.py's row averaging, a DC4-mask cache reuse and
atomic sidecar write in sras_compute.py, a dc3/dc4 pairing guard in
sras_format.py's v7 cache writer, and matching updates to the
tools/ test fixtures.

Co-Authored-By: Claude Sonnet 5 <noreply@anthropic.com>
2026-08-10 18:30:00 -05:00
Thomas Ales c30c8b1815 Refactor cache validation and optimize alignment wizard incremental updates
- Extract cache mismatch logic into reusable cache_mismatch_reasons() function
  for cleaner validation and consistent miss reporting
- Expose memory_budget_bytes() for external callers (aligned exporter)
- Optimize rebuild_stack() with incremental layer updates when only one angle
  parameters change, avoiding full reprojection overhead
- Remove unused seed_per_angle parameter from alignment wizard
- Simplify cached_rf_image() DC masking with cleaner early exit logic
- Clean up internal state tracking with explicit origin caching

Co-Authored-By: Claude Haiku 4.5 <noreply@anthropic.com>
2026-08-09 14:30:02 -05:00
Thomas Ales 8348ad313c Implement FFT pad-factor caching and the stored-cache display fast path
tests/test_stored_cache.py exercised two features that were never built,
so six of its tests had been failing on main. Both are now implemented.

Pad-factor caching. A padded view could not use a stored FFT cache at all:
the store was pad 1 by definition and cached_rf_image rejected any n_fft
outright, so a user working at a pad factor got nothing from batch-computing
a file. CACH tail v3 records the pad the images were resolved at, cache_file
computes at a requested pad, and the batch actions pass the viewer's own pad
down — while still refusing a store resolved at a different pad, since a
padded FFT interpolates between the natural bins and so resolves genuinely
different peak frequencies. v1/v2 tails read as pad 1 and keep working.

Stored-cache dispatch. _refresh_display only ever consulted this window's
in-session dicts, so after a batch every angle change still queued a worker
and a progress popup for an image already on disk — the exact cost the batch
was run to avoid. It now checks the file's own DC/FFT blocks first, asking
with allow_dc_recompute=False so the GUI thread never touches I/O. When the
stored cache genuinely cannot serve the view, the scan info panel says why
rather than leaving the silent recompute a mystery.

Two bugs surfaced on the way:

- The angle spinbox was wired on editingFinished, which QAbstractSpinBox
  emits only on Return or focus-out — never on a step. Clicking its arrows,
  the ordinary way to walk a scan, moved the number and left the image
  behind. Now valueChanged with keyboard tracking off, which fires on a step
  and once on commit, but not per keystroke mid-typing. Every existing GUI
  test called _on_view_changed() by hand and so could not have caught this;
  two new tests pin it and fail against the old wiring.

- A plain "fft" batch over a file previously cached with fft_rowavg carried
  the old row_avg_n forward, labelling raw images as row-averaged. It now
  writes row_avg_n=0 explicitly.

Verified: 111 passed (was 103 passed / 6 failed), and
tools/check_equivalence.py is byte-identical to the pre-change baseline.

Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
2026-08-09 13:50:37 -05:00
Thomas Ales f40c965b74 Replace the two Fusion alignment actions with a three-step wizard
Alignment was two disconnected menu actions. `Angle Alignment` ran the
registration with ref_angle_idx hard-coded to 0, no exposed parameters and
no way to retry; `Manual Alignment...` was a separate dialog that
deliberately refused to inherit the automatic result, so a bad fit meant
starting over by hand. Neither told you whether the alignment was any
good, and neither produced anything durable beyond an in-memory result.

Fusion -> Alignment Wizard... now covers all of it in three steps:

  1. Correlate. Reference angle, DC threshold, source, rotation seed and
     sign, search window, coarse step and fine grid are all on the page,
     and Run/Re-run is repeatable. Angles start pre-rotated from the
     stage angles in the file, so the page is informative before any
     correlation runs. The verdict is a picture: every angle's DC mask
     reprojected onto the shared canvas and summed, coloured by how many
     angles cover each pixel, so a good alignment reads as one saturated
     plateau and a bad one as a fringe of low-count halos. A per-angle
     fit table flags angles that did not register or that disagree with
     their stage angle by more than a degree.
  2. Crop. An axis-aligned rectangle on that canvas, with numeric
     canvas-pixel boxes synced both ways and a live size estimate.
     "Fit to full overlap" uses a largest-rectangle sweep rather than a
     bounding box: the overlap region of several rotated scans is roughly
     a disc, whose bounding box has corners no angle covers.
  3. Save. Writes the aligned, cropped stack to a new .sras.

Because the wizard replaces both actions it absorbs the old dialog's
by-eye nudge editor — without it, a scan the search cannot fit would
have no fallback at all. ManualAlignmentDialog is therefore deleted
rather than left orphaned, and its tests move to the wizard.

Two bugs found while driving it end to end and fixed here: QSpinBox
setRange clamps and emits valueChanged, which committed a 1x1 crop
before the default preset could run; and the mm round trip returns an
exact pixel boundary as 11.000000000000002, so a bare ceil() added a
spurious column on every rectangle edit.

Verified: 103 pass, the 6 test_stored_cache failures are pre-existing on
main, and tools/check_equivalence.py is byte-identical to main.

Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
2026-08-07 23:00:59 -05:00
Thomas Ales 6d0e30b9ce Add aligned/cropped .sras export and the compute pieces behind it
The alignment machinery never modified a scan: it produced an
AlignmentResult and every consumer resampled on the fly. That is right
for a viewer but means the aligned stack cannot leave the process, so no
other tool can read it and reopening the scan redoes the registration.

sras_align_export.write_aligned_sras bakes an alignment into a new v6
file: each angle is gathered onto the shared canvas by nearest neighbour,
so every output angle shares one grid and the file opens already aligned.
Registering the export against itself returns identity, which is the test
that pins the whole index chain.

Three details that are easy to get wrong and are now covered:

  * Rounding must be floor(x + 0.5), not np.rint. scipy's order=0 rounds
    halves away from zero, and the canvas is snapped to the reference's
    pixel grid, so exact halves are common rather than hypothetical.
  * Out-of-bounds must be tested on the fractional coordinate against
    [0, n-1], not on the rounded index, or a one-pixel rim gets real data
    everywhere the Aligned View shows padding.
  * ...but with a tolerance, because the mm-space affine chain lands an
    exactly-integer transform a few times 1e-13 off. A bare >= 0 drops
    the *reference* angle's entire first row and last column.

Padding is the per-channel ADC code nearest 0 mV, not zero: zero ADC
decodes to ~+100 mV on real calibration and would masquerade as sample.

Source rows are served from sliding in-RAM bands. A rotated angle maps
one output row to a diagonal across the source, so indexing a memmap in
output order refaults nearly the whole angle per row — terabytes of
paging for a gigabyte of data.

Also in compute: crop_alignment_result (a crop is pure index translation,
so it folds into the affine's offset rather than becoming a second
transform), overlap_stats, largest_rect_at_least for a crop that stays
inside the overlap region, and seed/sign/refine knobs on
register_angle_to_reference whose defaults leave existing behaviour and
tests byte-identical.

Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
2026-08-07 22:34:18 -05:00
Thomas Ales 3989c2a1b8 Implement row-averaged FFT feature for same-row SNR cleanup
Add row-averaged FFT feature with configurable window size (row_avg_n
parameter) for improved signal-to-noise ratio on noisy scans. Includes:

- Gaussian-weighted same-row neighbor averaging (never crosses rows)
- Masked/renormalized convolution handling for edge cases and masked samples
- Cache format v2 with row_avg_n tracking to prevent silent cache mismatches
- GUI dialog option for row-average window configuration
- Comprehensive tests validating kernel properties, background subtraction
  invariance, and cache dispatch

Co-Authored-By: Claude Haiku 4.5 <noreply@anthropic.com>
2026-08-07 21:50:05 -05:00
Thomas Ales 00a7afade0 Dedup format layer; public accessors replace private reach-throughs
- SrasFile: _parse_v6 now retains per-angle x_delta and the verbatim
  preamble/background byte spans, and gains public data_offset,
  y_pos_per_angle, and iter_angle_blocks() (which now owns the ragged
  block-offset walk used three separate places before).
- sras_edit_scans: the 70-line re-parse of the v6 header sections
  (_read_v6_sections/_reread_span/_v6_angle_offsets) collapses into a
  _write_v6 that consumes SrasFile directly — verified byte-identical
  round-trip on v6 int8/int16 and legacy files. Eight print-and-exit
  pairs become _die().
- tools/make_test_sras imports the struct layouts from sras_format and
  the rotation matrix from sras_compute instead of re-declaring them
  (byte assembly stays independent of the reader).
- sras_compute: block_mean_2d, pixel_pitch_mm, nominal_delta_deg made
  public (they were GUI-facing); registration_workers() and
  default_max_workers() wrap the remaining private reach-throughs from
  sras_workers.

Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
2026-08-06 10:40:42 -05:00
Thomas Ales e80717d5c5 Dedup workers: one _PooledWorker base for the three pool fan-outs
DcPrecomputeWorker, Ch4MaskWorker and CrossCorrelateWorker shared the
same submit/as_completed/emit/shutdown skeleton; they are now
constructors plus _plan/_items/_one/_emit hooks. All three inherit the
cancellation-aware shutdown (wait=not stopped, cancel_futures) that
only DcPrecomputeWorker had before, and the per-run budget attributes
are initialised in __init__ instead of appearing mid-run.

Also removes the viewer's write-only _dc_precompute_worker plumbing
(job tracking already owns worker lifetime via _jobs).

Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
2026-08-06 10:32:06 -05:00
Thomas Ales d5028db445 Add scan-editing CLI and alignment tests; extend Manual Alignment correlation
Continues the Manual Alignment work: refines the FFT cross-correlation and
mask handling, adds sras_edit_scans.py (drop/renumber bad angle scans),
tools/test_alignment.py (registration ground-truth suite), and a rotating
test fixture in make_test_sras.py.

Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
2026-08-06 09:35:30 -05:00
Thomas Ales bbb075ff34 Add FFT cross-correlation to Manual Alignment, with tunable options
Manual mode previously offered only Auto De-rotate (rotation from known
scan angles) plus keyboard nudging, so every angle's translation had to
be found entirely by eye — fine for a small correction, unworkable for
the tens-of-mm scatter a real many-angle scan can have between angles
before any translation search runs at all.

Add an "Auto Cross-Correlate (vs Reference)" action that, for every
non-reference angle, sets rotation to the known analytic angle (same as
Auto De-rotate) and translation to the FFT-phase-correlation best fit
against angle #0 (always the reference/ground truth). This is meant to
land every angle's outline roughly stacked on the others so keyboard
nudging only has to make small corrections afterward, per the intended
workflow: cross-correlate first, then nudge.

Exposes two tunable options, since real data may correlate better one
way than the other: "Correlate on" (raw CH4 signal, minus its own
minimum -- the default, robust to a shared threshold not suiting every
angle's real signal level -- or the thresholded binary mask), and
"Search margin" (how far a shift the phase correlation searches before
wraparound bias becomes a risk).

Runs on a background thread (new CrossCorrelateWorker in
sras_workers.py) since correlating many high-resolution angles can take
long enough to visibly freeze the dialog otherwise.

The underlying per-angle correlation math is factored out of
compute_angle_alignment's Step 2 into a new, reusable
correlate_translation_mm, so the existing automatic Fusion -> Angle
Alignment action and the new manual button now share one implementation
instead of two copies of the same phase-correlation logic.

Co-Authored-By: Claude Sonnet 5 <noreply@anthropic.com>
2026-07-31 11:31:14 -05:00
Thomas Ales 3c835f4592 Add manual angle alignment mode with overlay, keyboard nudge, and save/clear
Automatic alignment's phase-correlation translation search is unreliable, so
add a Fusion -> Manual Alignment dialog: every angle's CH4 threshold mask
overlaid at once with distinct colors/opacity, a selector for the active
angle, arrow keys to nudge translation and Q/E to nudge rotation, an Auto
De-rotate button that snaps to the known scan angle, and Save/Clear
controls backed by a JSON sidecar that's restored automatically on reload.

Co-Authored-By: Claude Sonnet 5 <noreply@anthropic.com>
2026-07-31 09:19:17 -05:00
Thomas Ales 9a7cc396e7 Bound nested parallelism, make compute cancellable, harden batch pool
Three defects found by testing the parallel paths end to end.

Nested parallelism was unbounded. DcPrecomputeWorker and the alignment
driver both parallelise over angles, and each angle's compute_dc_image
then parallelised over rows again: 14 x 14 threads, and — worse — every
angle sized its chunk against the *whole* memory budget, so worst-case
live buffers were ~13.9 GB against a 1 GB budget. Capping the inner
worker count alone does not fix it; the chunk is still sized against the
full budget. plan_angle_level now hands each angle both max_workers=1
and its share of the budget, which bounds the real file at 1002 MB.

Chunk planning could not produce concurrency at all. _plan_chunks sized
chunk_rows first, and _chunk_rows_for spends whatever budget it is given
— so a single chunk consumed the lot and budget//chunk_bytes came back
as one worker. It now picks the worker count first and sizes the chunk to
it, giving 7-16 workers on the real file instead of 1.

Cancellation was too coarse to shut down. stop() was only checked between
angles, and one angle of the real scan is ~40 s, so closing the window
sat through it and returned with threads still running. should_stop is
now polled per row chunk and closeEvent signals every worker before
waiting: close went from 4.0 s with two live threads to 1.04 s with both
finished. A cancelled ComputeWorker emits None so a half-filled image is
never cached.

Also: BatchCacheWorker no longer reports every file as failed when the
process pool itself dies (unguarded __main__, frozen build, sandbox) —
it retries those files in-process. Batches below 512 MB skip the pool
entirely, since interpreter startup would otherwise make small jobs
slower. cache_file rejects an unknown mode instead of silently treating
it as "fft".

Measured on the real 496 GB scan, angle 3, 32 rows:
  DC   2.94s -> 0.75s   RF  6.10s -> 1.99s   peak RSS 1.40 -> 1.93 GB
Batch convert, 24 files / 1 GB: 4.03s -> 2.36s.
Memory budget defaults to 1024 MB (SRAS_MEM_BUDGET_MB), the measured knee.

Testing: tools/test_refactor.py (70 checks: cache round-trip and block
carry-forward, partial-cache handling, parallel-vs-serial identity,
no-mask path, ROI mask vs full-grid, v2/v3/v4 parsing, sras_average
round-trip incl. remainder handling) and tools/test_gui.py (46 checks
driving the real widgets and workers headlessly). check_equivalence.py
still reports all 167 outputs identical to ed0eba4.

Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
2026-07-31 00:09:46 -05:00
Thomas Ales 55a4c5e42f Split into four modules, deduplicate, and parallelize the compute paths
Structure
  sras_format.py   parsing/writing, calibration, axes  (numpy + struct)
  sras_compute.py  DC/FFT images, alignment, batch cache  (+ scipy)
  sras_workers.py  Qt background workers
  sras_viewer.py   ROI, canvases, dialog, main window

format+compute import in 0.59s with no Qt or matplotlib (vs 2.96s for the
full app), which is what makes a spawn-based process pool worth using.

Deduplication
  - SrasFile.cal() and compute.dc_image_mv() replace the ADC->mV
    calibration incantation that appeared at ten call sites.
  - _read_preambles/_read_background/_set_calibration are shared by the
    legacy and v6 parsers instead of duplicated.
  - v5 PREC images are normalised into the same ragged per-angle list
    v6/v7 uses, removing four isinstance() branches and shortening
    compute_rf_image's fast path.
  - _run_worker replaces five copies of the QThread setup and five
    near-identical teardown methods; the two lifetime hazards they
    guarded against are now documented once, authoritatively.
  - _on_channel_changed defers to _update_controls_enabled rather than
    re-deriving the same six enable rules.
  - _corners_in_ref_frame, _CHANNEL_DISPLAY dict, unified progress-dialog
    helper, dead _on_roi_angle_edited stub removed.
  - sras_average.py builds on SrasFile instead of carrying a second copy
    of the header format, and streams per angle instead of loading the
    whole file (was a ~3x file-size peak).
  Executable lines: 2390 -> 2254, despite adding all of the below.

Parallelism
  - compute_rf_image/compute_dc_image map row chunks over a thread pool.
    Worker count is derived from the memory budget rather than the core
    count: on a large scan chunk_rows is already floored at 1 row (~75 MB
    of float32 at 7507x2500), so only the worker count can bound peak RAM.
  - DcPrecomputeWorker computes angles on a pool, emitting each result
    from its own QThread as it lands.
  - BatchCacheWorker runs one process per file via cache_file(); only
    paths and scalars cross the boundary. Per-process thread counts are
    divided so the two levels don't oversubscribe. Drops the old pass 1,
    which fully parsed every file just to weight a progress bar.
  - dc_threshold_mv=None means "no mask" and skips the CH4 read entirely
    — the batch FFT job previously read all of CH4 to compare against a
    threshold of -1e9.
  - Alignment mask and correlation stages map over angles; fft2/ifft2 use
    workers=-1.

Fixes found on the way
  - A partially-cached v5 file showed an all-zero image for uncached
    angles: the fast-path check was file-wide, not per-angle.
  - v7 cached images were read-only big-endian views; now native float32.

Verified: tools/check_equivalence.py produces byte-identical hashes for
167 outputs (DC/FFT across channels, angles, bg-sub, pad factors and
thresholds, plus the full alignment result) against ed0eba4, on both
synthetic files and a real 496 GB 17-angle v6 scan.

Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
2026-07-30 23:38:08 -05:00