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Follow-up to making max_hkl a setting: it is now an optional, and unset means "take it from this crystal". The predictor keeps only |q| <= 1/d_min and h = a.q for the real-space axis a, so |h| <= a/d_min exactly - and likewise |k| <= b/d_min and |l| <= c/d_min. max(a,b,c)/d_min therefore bounds all three at once: nothing that could be predicted lies outside it, and nothing inside it is reached by a shorter axis. It applies to rotation and stills alike, both going through the one place the prediction settings are built. Offline (rugnux, viewer) the default is unset, so every crystal gets its own range; --max-hkl overrides it. Online the broker holds a concrete number, because the cost is the cube of it per image and a live acquisition should not have its frame rate decided by whichever sample is mounted: max_hkl joins bragg_integration_settings in the OpenAPI with a default of 100, so an omitted field arrives as that default (the generated model carries it) rather than as "derive it", and the frontend exposes it next to the integration model. Measured against a fixed 100 on six rotation crystals: three are bit-identical, two were being truncated and recover 419k and 5.8k observations with the high-shell CC1/2 going 15.1 -> 25.8% and 52.1 -> 55.3%, and the space group is unchanged 6/6. It reproduces a fixed 200 exactly, which is the bound being tight rather than merely safe. The sixth is worth recording: a 149/83/226 A cell derives 227, and because a single scalar has to cover the longest axis the cube is ~16x what a per-axis box would be - 22% wall clock, for a net 22 observations out of 364k (the per-frame 65536-reflection cap re-selects at the margin when more candidates are offered) and identical CC1/2, ISa and space group. Per-axis limits would remove that; the predictors already map a thread index to h, k and l separately. Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
61 lines
3.1 KiB
C++
61 lines
3.1 KiB
C++
// SPDX-FileCopyrightText: 2025 Filip Leonarski, Paul Scherrer Institute <filip.leonarski@psi.ch>
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// SPDX-License-Identifier: GPL-3.0-only
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#pragma once
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#include <optional>
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// Spot-intensity extraction method used by the Bragg integration engine. ProfileGaussian (default)
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// profile-fits with a measured-width Gaussian (Kabsch-style) - more accurate intensities than the
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// classical uniform BoxSum; validated on anomalous data (stronger S/Cl peaks vs box-sum). BoxSum is
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// the simpler, faster fallback. ProfileEmpirical learns the profile per resolution shell from strong
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// spots - see docs/CPU_DATA_ANALYSIS.md (Bragg integration).
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enum class IntegratorMode { BoxSum, ProfileGaussian, ProfileEmpirical };
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class BraggIntegrationSettings {
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IntegratorMode integrator_mode = IntegratorMode::ProfileGaussian;
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float r_1 = 4;
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float r_2 = 6;
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float r_3 = 10;
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float d_min_limit_A = 1.0;
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std::optional<float> fixed_profile_radius;
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float minimum_sigma_in_regards_to_i = 0.02;
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// Symmetric trimmed-mean fraction for the r2..r3 background ring: drop the lowest and highest this
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// fraction of ring pixels before averaging. Resists the high-side contamination (neighbour-spot
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// wings, tails, zingers) that biases the plain ring mean up and makes it over-subtract weak
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// high-angle reflections. Applied to monochromatic data (rotation and still); the integration engine
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// keeps the tuned high-side sigma-clip for broadband (non-zero bandwidth) data instead. 0 = plain ring
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// mean (rugnux --background-trim).
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float bkg_trim_fraction = 0.10f;
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// Half-width of the hkl cube the predictor walks: every reflection with |h|,|k|,|l| <= this is
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// tested against the Ewald sphere, and nothing outside it can ever be predicted. An axis is
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// truncated once a/d_min exceeds this, and the GPU cost is the cube (2n+1)^3 of candidates, so
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// neither a small nor a large fixed value is right for every crystal.
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//
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// Unset (the default) means "take it from the refined cell", which is exact: the predictor keeps
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// only |q| <= 1/d_min and h = a.q, so no reflection can have |h| > a/d_min. See MaxHKLForCell.
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std::optional<int> max_hkl;
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public:
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BraggIntegrationSettings& R1(float input);
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BraggIntegrationSettings& R2(float input);
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BraggIntegrationSettings& R3(float input);
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BraggIntegrationSettings& DMinLimit_A(float input);
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BraggIntegrationSettings& FixedProfileRadius_recipA(std::optional<float> input);
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BraggIntegrationSettings& Integrator(IntegratorMode input);
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BraggIntegrationSettings& BackgroundTrimFraction(float input);
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BraggIntegrationSettings& MaxHKL(std::optional<int> input);
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[[nodiscard]] IntegratorMode GetIntegrator() const;
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[[nodiscard]] float GetR1() const;
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[[nodiscard]] float GetR2() const;
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[[nodiscard]] float GetR3() const;
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[[nodiscard]] std::optional<float> GetFixedProfileRadius_recipA() const;
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[[nodiscard]] float GetDMinLimit_A() const;
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[[nodiscard]] float GetMinimumSigmaInRegardsToI() const;
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[[nodiscard]] float GetBackgroundTrimFraction() const;
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[[nodiscard]] std::optional<int> GetMaxHKL() const;
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};
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