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efca844bce |
calibration: --no-refine-tilt holds the header tilt, it does not zero it
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GuessInitialGeometry resets rot1/rot2/rot3 to zero before seeding, and the branch that puts the header's tilt back was guarded by `refine_tilt && !tilt_refined`. With --no-refine-tilt the tilt is never free, so tilt_refined is false, so the guard is false, so the restore never ran - and the fit reported a zero tilt while the CLI printed "held at the header value". The guard only needs !tilt_refined: a tilt that was declined and a tilt nobody asked to refine both want the header put back and the beam centre and distance refitted around it. That is what the branch already does. Measured on a LaB6 sweep with a tilt imposed on the command line and asked to be held, --calibration spots: before Rot1= +0.0000 deg (+0.001400 rad from the header) after Rot1= -0.0802 deg (+0.000000 rad from the header) The rings path reaches this only when the spot-derived start wins, which is why it does not show on a file whose profile start is chosen; the spots path always did. A calibration whose header tilt is already zero is unaffected - checked, byte-equal distance either way. Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01EFEJG6WBQv8th4UJFNe53N |
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8691bf4876 |
calibration: write the result as JSON, not only as a PONI file
A calibration run produced one file, and it was a pyFAI PONI - which pyFAI and
its neighbours read and nothing in this system does. Carrying the answer back
into the instrument meant a person reading numbers off a printed report and
retyping them into a dataset_settings body, and the report is where the two
points a "beam centre" can mean are easiest to confuse.
So write <prefix>.json beside it. Its "dataset_settings" member holds the
geometry under the property names broker/jfjoch_api.yaml gives them and holds
nothing else, so it is a valid dataset_settings body as it stands:
curl -X POST -H 'Content-Type: application/json' \
-d "$(jq -c .dataset_settings det.json)" http://broker:5232/start
beam_x_pxl is the PONI, as everywhere here. The three poni_rot*_rad ride along
whenever any is non-zero and are left out when all are zero: a body without them
does not leave the tilt unstated, it states a FLAT detector, so they travel
together or not at all - the same rule the report's JFJOCH_DATASET_SETTINGS
block already follows.
The "calibration" member holds what the run knows about that geometry: the
residual, the fit's own sigmas and the correlation between the tilt and the beam
centre, whether the tilt cleared its significance test or was declined and
pinned, where the direct beam lands, and where the spots independently put the
beam. A calibration that has gone wrong looks exactly like one that has not until
those are read, and a machine-readable file that carried only the geometry would
be the easiest possible way to feed a bad one into an instrument.
Tested against the model generated from the spec rather than against a list of
field names written out by hand: the file's dataset_settings member is parsed
into org::openapitools::server::model::Dataset_settings and validated, so a
field renamed or newly required in jfjoch_api.yaml fails here rather than at
someone's POST. The tilted and untilted branches are both covered, and the
PONI/direct-beam distinction is asserted rather than assumed.
Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01NfuDvf5ipV3Hi8TiCUKD27
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16b368739e |
calibration: re-integrate the images about the geometry that was fitted
Everything the ring fit reads was binned with the geometry the run started from, and a calibration is run precisely because that geometry is in doubt. Binning is not something a later fit can undo: which pixel landed in which (q, phi) bin was decided when the images were read. Get the distance wrong and the radial sampling is the wrong scale - a run recovering 110 mm from a 250 mm header ended at rms 1.07 px where the same data from a right header gives 0.42. Get the centre wrong and every ring is smeared across its own sectors, and past about a hundred pixels the fit leaves rms 4.8 px even when it is started from the exact answer, because there is nothing left in the profile to fit. So integrate the images a second time, binned about what was fitted, and fit that. A calibration run is a handful of images and the answer is worth far more than the extra read. Re-binning about the FIRST fit is not enough on its own. Where the beam centre was badly out that fit is itself wrong, and binning about it digs deeper - rms 3.75 -> 5.66 on an exposure 200 px off. The spots' geometry is the one that does not degrade there, having never read the header, so both are tried where they differ and whichever comes back better is kept. On that exposure the first candidate gives 288 points at rms 5.66 and the second 369 at 0.81. The second pass is taken only if it is actually better, by the same rule that ranks everything else here - at least half as many ring points and a smaller residual - and it is skipped altogether when the fitted geometry moves a ring by less than the radial width of one profile bin, since re-binning would then put every pixel back where it already is. On the 110 mm exposure with its own header that is 1.77 px against a 1.84 px bin, so the run is untouched and its answer bit-identical. Measured on the 110 mm LaB6 exposure, true PONI x 765.90 at 110.03 mm. The calibration is now independent of the header it was given: beam-x out by +20 +40 +100 +200 +400 px -> 765.9-766.6, 110.02-110.05 mm 250 mm header, beam-x 780 -> 765.998 at 110.037, rms 0.394 250 mm header, beam-x 867 -> 765.723 at 110.038, rms 0.413 900 mm header, beam-x 1167 -> 766.496 at 110.038, rms 0.804 30 mm header, beam-x 967 -> 766.486 at 110.039, rms 0.807 All of those failed before this, most of them catastrophically. The residual inflation is gone with them: the 250 mm case now leaves 0.394 px, better than the same data from its own correct header. The four other datasets are unchanged where the re-bin fires, and slightly better where it does: rms 0.433 -> 0.423 at 150 mm and 0.555 -> 0.550 at 200 mm, with the geometry moving under a tenth of a pixel. A run that needs the second pass costs about twice one that does not. Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01NfuDvf5ipV3Hi8TiCUKD27 |
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49dd01331b |
calibration: let the spots vote on the geometry in ring mode too
The rings and the spots fail in different regimes, which is the whole reason to carry both. The header is right on a well-configured instrument and is the thing a calibration is run to check. The profile's own estimates are exact while the error stays small and stop meaning anything beyond that - past about half a ring spacing each ring reaches the azimuthally averaged profile as two horns rather than one peak, and the distance search reads a list of horns as a list of rings. The circle through the spots reads nothing from the header at all: measured on a 110 mm LaB6 exposure, --calibration spots returns the same geometry from a header 400 px out in the centre AND eight times out in distance. So ring mode now finds spots as well - half a second - and offers what they make of the geometry as one more starting hypothesis, fitted like the others with the residual left to choose. It is added whole rather than as a centre alone: GuessGeometry votes for the circle centre, clusters the radii into rings and takes the distance from the innermost, and those two belong together. Taking only its centre would not have helped, because the distance candidates come from a profile averaged about the header's centre, and a ring smeared over hundreds of pixels cannot be un-smeared by reading its bins differently. Measured on the 110 mm exposure, whose true PONI is 765.90 at 110.03 mm. A header 40 px out in the centre now lands within 0.6 px (it landed 41 px away before). The cases with BOTH wrong, which failed before this and equally before the beam centre work, now come out: 250 mm / 780 px gives 110.041 mm and 766.10 px against 42.3 mm and 782.7; 250 mm / 867 px gives 110.065 and 765.48. All five datasets are unchanged from their correct headers and the distance still recovers from any header between 25 and 1200 mm. Past about a hundred pixels nothing rescues ring mode, and the reason is the profile rather than the seeding: binned about a centre that far out it shows each ring smeared across its own sectors, so even started from the exact answer the fit leaves rms 4.8 px and drifts. Re-binning would fix it and would need the images read a second time; --calibration spots, which never touches the profile, already covers it. That regime is now visible rather than silent. The spots' beam centre is printed beside the fitted one as a cross-check - two methods sharing no assumption, so a reader can see at a glance whether they agree. It costs nothing, the spots having been found already, and it separates cleanly: 0.3-0.4 px on the good runs against 201.4 px on the exposure whose profile could not be fitted at all. Reported as a fact and not gated on, since at long distance both methods weaken together and the honest thing is to show the number (5.2 px at 300 mm, 12.6 at 500). Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01NfuDvf5ipV3Hi8TiCUKD27 |
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c84b91be8a |
calibration: take the beam centre from the rings too
The header's beam centre was the last input the ring fit had to be roughly right about. Each ring is looked for in a window a few pixels of radius wide, and a centre wrong by (dx, dy) puts a ring at a different q in every sector, so past about ten pixels the ring leaves that window over much of the turn - and the fit then reads its cos(phi) signal off whichever sectors are left, which are the ones where the signal is weakest. A 20 px error ended 31 px wrong. The rings answer this without a calibrant and without a distance. A powder ring is a conic centred on the beam, so a wrong centre makes EVERY ring's radius oscillate once per turn by the same amount: r(phi) = R + dx cos(phi) + dy sin(phi), solved directly and pooled over every ring the profile shows, with each ring searched about its own measured radius rather than about where a standard says it should be. Using it needs the extraction to follow the rings sector by sector, which is what ProfileRingTrack now does - exactly, and in all five parameters at once, by walking the ring in the geometry believed true and asking the binned geometry what q and azimuth it would have given each point. That replaces the flat-detector distance correction it grew out of. Following the rings is not free, and the reason is worth stating: a window that moves with phi makes every systematic of the peak finder - where the background line is taken, how the centroid sits in the window - vary with phi as well, and phi is exactly the axis the beam centre is read off. Measured, it costs rms 0.415 -> 0.525 px on a good 110 mm fit, and 0.831 when the window follows the fitted tilt too. So a second measurement is taken with a window that is the same in every sector - the binned geometry with only its DISTANCE replaced, which is phi-independent by construction - and both are offered to the same rule that ranks everything else here. Acquire by following, measure by holding still. The seeded centre is likewise a hypothesis and not a belief. It reads a once-per-turn wobble, and a tilt puts a term of that shape there too - one that grows as the radius squared, where a centre error does not - so pooling the rings absorbs part of the tilt into the centre. Believed outright it made a good 110 mm fit worse; offered as an alternative start it costs one more fit and needs no rule about when it applies. It is skipped entirely below a pixel, where it is not a different hypothesis at all, which keeps a well-headed run at 0.71 s. Measured on the 110 mm LaB6 exposure, whose true PONI is 765.90: a header centre 20 px out now lands within 0.5 px, where before it landed 31 px away. All five datasets are unchanged from their correct headers, and the distance still recovers from any header between 25 and 1200 mm. The limit is now understood rather than merely reached. Past a few pixels the azimuthally averaged profile stops showing rings: a ring tracing r(phi) piles up density where that turns round, so it averages into the two HORNS of the sinusoid, at R-|d| and R+|d|. The radius finder reports two rings where there is one, and the gap between them is 2|d| - the search window shrinks to exactly the offset it was meant to span. That caps recovery at roughly half the ring spacing, about 20 px here and failing by 40. Beyond it nothing is left in an azimuthally binned profile, and --calibration spots, which works from the spot positions themselves, is the method that still can. One pre-existing limit measured and NOT introduced here: a wrong distance together with a centre more than about 5 px out fails, because the centre error splits the radius list the distance search reads. The committed code before this change fails identically on those cases. Also fixed: fit_from now takes a whole geometry rather than a distance, and the declined-tilt refit was inheriting rot1/rot2 from it - pinning the tilt at exactly the unvalidated value the gate had just rejected. Same fault the gate exists to catch, one level up. Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01NfuDvf5ipV3Hi8TiCUKD27 |
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01ad1e1743 |
calibration: only report a tilt the fit actually measured
The detector tilt is refined by default, and on a pattern that cannot separate it from the beam centre the fit returns one anyway - there was nothing to stop it. Both displace a ring's radius as cos(phi), and only how that amplitude grows with the ring's radius tells them apart, which takes two well-sampled rings. At 500 mm on the LaB6 series only two rings reach the detector and the outer one is barely there: the tilt came out at the opposite sign to every shorter distance, dragged the PONI 28 px, and bought a residual of 0.960 px against 0.962 pinned. The covariance says so plainly - 0.1 sigma, and a beam centre quoted to +-180 px. So ask it. A tilt is kept only where the fit had it free AND it stands at least three times its own uncertainty; otherwise rot1/rot2 go back to the header's values and the beam centre and distance are refitted around them. Over the series the tilt stands at 50, 33, 15 and 8 sigma at 110 to 300 mm and 0.1 at 500 mm, so any threshold between 2 and 5 gives the same verdict on all five - this says which regime a fit is in, not where a line was drawn. The declined 500 mm fit lands on a direct beam of 773.53 px, against 773.56 for the pinned fit measured independently. It is a rejection criterion and nothing more. Clearing it does not certify a tilt: that estimator is limited by systematics rather than by this sigma, and a coherent half-pixel error in the ring positions fakes a tilt of the usual size while leaving sigma small. The report says "refined", never "verified". Writing the gate turned up a related fault in the pass loop. RingOptimizer pins the tilt by itself when every point it is given lies on one ring, and on a barely-sampled pattern a later pass lands in exactly that state - which froze the tilt at whatever the FIRST pass had produced and returned it with sigma zero, an unmeasured tilt wearing the appearance of a fixed one. The gate reads that as "not measured" and refits pinned, which is why it is stated over the geometry that gets reported rather than over what the last fit happened to do. Both paths are covered, profile and spots; the spots path was reporting a refined tilt as declined for the same reason. Two things measured and NOT taken: A robust loss. A Cauchy loss scaled to the previous pass's median residual changed nothing on the series - rms 0.415 to 0.421 at 110 mm, no case improved, every direct beam within 0.06 px. Ring points are per-sector peaks that already had to stand 3 sigma clear of their own background, so there are no gross outliers left to reject. Recorded at the call site rather than left as an unused option. A quality gate that refuses a bad calibration. Three candidate signals, all measured against naming the wrong standard on LaB6 data: sigma(PONI) does not see it at all (0.52-0.65 px, indistinguishable from healthy); the residual only half sees it (3.2-3.6 px wrong against 0.4-1.0 right, but a correct run from a wrong header sits at 1.0-2.4 and would be caught too); and the seed's match score is dominated by how many rings the calibrant lists, scoring 0.29 for a perfect LaB6 fit against 0.21 for a wrongly named silicon. None of the three separates, so no gate is shipped. What the run does say is the recovered distance against the header, and a wrong standard moves that to 446 mm on a 110 mm exposure - unmissable, and the operator's call rather than a threshold's. Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01NfuDvf5ipV3Hi8TiCUKD27 |
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a5f416fcdc |
calibration: take the detector distance from the rings, not from the header
A powder calibration is run because nobody is sure the header is right, and the header's distance was the one number the fit could not survive being wrong about. The ring search is local - each ring is looked for inside a window a few pixels of radius wide - so a distance more than a percent or two out puts every ring outside its own window, and the fit then converges on whatever background fluctuation each window contains. It does not fail: a 110 mm exposure told the detector was at 150 mm reported 149.8 mm, with 146 ring points and exit 0. Only its residual said anything, 5.3 px against 0.4 px, and nothing read it. Measure the distance from the rings instead. The peaks of the azimuthally averaged profile give ring RADII, and a radius does not depend on the assumed distance at all - bin i holds the pixels at one particular radius whatever q that radius was called - so the radii are a property of the image. Against the calibrant's d-spacings, r = D tan(2 asin(lambda/2d)) then has one unknown. It is scanned rather than solved because the pairing of observed rings to d-spacings is unknown too, and the winning basin is solved in closed form. Nothing here reads the header distance except to bin the profile; it needs only the wavelength, the pixel size and the detector's extent. A powder pattern has genuine distance aliases, so one answer is not enough. A cubic primitive standard puts its rings at radii proportional to sqrt(N), and scaling the distance by sqrt(2) maps ring N onto ring 2N - most of the comb still lands on peaks. Measured: the 110 mm exposure with a 115 mm header scored its best at 156.5 mm, which is 110*sqrt(2). No adjustment of the score removes an alias the lattice really has, so the scan hands back the few best distances and each is fitted, the header among them as one hypothesis of several. The residual then separates them - 0.4 px against 5.2 px on that case - subject to an attempt explaining a comparable share of the pattern first, because a start so wrong that one ring point survives leaves a residual of exactly zero. Each attempt re-extracts at the geometry it converged to and fits again. The seed is measured from blended peaks and is good to about a per cent, close enough to converge from but far enough to sit every search window a few pixels off its ring, and an off-centre window takes its background off the ring's own flank. Nothing is re-read from disk, so the loop is free. Measured on the LaB6 distance series. A 110 mm dataset now recovers 110.03-110.17 mm from any header between 25 and 1200 mm, against +-2 mm before. All five datasets recover their own distance from a fixed wrong 250 mm header. With correct headers, four of the five are bit-identical to before and the 500 mm one moves by a single ring point - the two-ring fit whose tilt is 0.1 sigma anyway. Run time is unchanged at 0.62 s. The residual is larger on a run whose header was wrong (1.1 px against 0.4 px on the 110 mm case), because the profile was still binned at the wrong distance and its radial sampling is correspondingly coarse. The geometry is right; only the scatter about it is inflated. Re-running with the recovered distance recovers the residual too. Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01NfuDvf5ipV3Hi8TiCUKD27 |
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fba5435c38 |
calibration: report what the ring fit knows about its own answer
The ring fit reported the SCATTER of its measurements (rms, and the beam-centre standard error that follows from it) but nothing about how well the fit pinned each parameter. Those two part company exactly where a calibration is worth doubting: as the rings run out, the tilt and the beam centre stop being separable - both displace a ring's radius as cos(phi) and only the way that amplitude scales with radius tells them apart - so the fit can sit tightly on the few points it has while being free to spend tens of pixels of beam centre on a tilt the data do not support. Take the covariance of the converged problem from Ceres and report it. Measured on a LaB6 distance series, the fitted tilt is 50 sigma at 110 mm and 0.1 sigma at 500 mm, where only two rings reach the detector; at 500 mm the fit quotes its own beam centre to +-180 px and its tilt to +-2.9 deg on a 0.35 deg value, and the correlation between them is 1.000. Nothing acts on this yet - it is printed so the next change can gate on it. Ceres returns the bare (J'J)^-1 of an unweighted problem, so it is scaled by chi2 per degree of freedom; that leaves the sigmas in pixels, mm and radians whatever unit the residual is stated in. Cost is one 5x5 SVD per run, below the noise of the surrounding I/O. Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01NfuDvf5ipV3Hi8TiCUKD27 |
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f34d9fe62b |
calibration: move the powder fit into image_analysis/geom_refinement
CalibrateFromProfile/CalibrateFromSpots/WritePoniFile sat in rugnux/, so the
only way to reach them was to link the Rugnux library - which drags in
JFJochWriter and gemmi. Nothing in them needs either: the includes are all
common/ and image_analysis/geom_refinement/, next to the RingOptimizer and
RingsFromProfile they call.
Moving them to image_analysis/geom_refinement/PowderCalibration.{h,cpp} puts
the powder fit beside the rest of the geometry refinement and makes it
reachable from anything that already links JFJochImageAnalysis - the receiver
and so the broker included, which is what an online geometry calibration would
need.
Pure move: the file contents differ from their previous form only in the
include paths.
Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01NfuDvf5ipV3Hi8TiCUKD27
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