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This is an UNSTABLE release. It includes many experimental features, as well as many AI generated fixes. We recommend using rc.152 for production use. * rugnux: Add `--model model.pdb` - score the merged data against an atomic model and compute initial maps. It reports R-work/R-free (scaling the model to the observed amplitudes with an overall scale, an anisotropic B and a flat bulk solvent - the standard few-parameter model, so a batch of maps stays directly comparable) and writes 2Fo-Fc / Fo-Fc electron-density maps (CCP4) plus a map-coefficient MTZ. The structure itself is not refined; the model is only re-fractionalised into the data cell. * rugnux: The merged reflection output now carries French-Wilson amplitudes (|F| and its sigma) next to the intensities - MTZ `F`/`SIGF`, mmCIF `_refln.F_meas_au`, and the text HKL - computed with the correct centric/acentric Wilson prior and epsilon multiplicity, so a downstream program (e.g. phenix.refine) can refine against amplitudes. The intensity columns are unchanged. * rugnux: R-free test-set flags are now assigned deterministically and consistently across symmetry - a Bijvoet pair I(+)/I(-) is never split between the work and free sets, and the assignment is a reproducible per-hkl hash that depends only on the reflection index, so every dataset of one crystal form gets the same ~5% free set (what a multi-dataset campaign such as PanDDA needs). On small data the fraction is floored so the test set stays large enough for a stable R-free (~500 reflections, capped at 10%); it stays flat at 5% on ordinary data. When a reference MTZ carries a `FreeR_flag` column its test set is imported instead, letting a whole campaign inherit one shared free set. * rugnux: A reference MTZ (`--reference-mtz`) can now fix the space group and cell for rotation data too (previously rejected), without being used to scale - the rotation merge stays self-consistent. When the crystal has an indexing (merohedral) ambiguity - a lattice symmetry higher than its Laue symmetry, e.g. P3/P4/P6/C2 - the reference also resolves it: each candidate reindexing (identity plus the twin-law cosets of the metric symmetry) is scored by its intensity correlation against the reference and the data are re-merged in the best-correlating one. This is a metric-preserving relabelling of hkl (the cell is unchanged) and a no-op for a holohedral crystal such as lysozyme. * rugnux: `--model` validation now aligns the data to the model before scoring - the observed reflections are reindexed into the model's enantiomorph when the two differ only by hand (indistinguishable from merged intensities). A merohedral indexing ambiguity is resolved against the reference MTZ when one is given (so a whole campaign shares one indexing convention); only with a model and no reference does validation fall back to fitting each candidate reindexing and keeping the lowest R-free. * rugnux: De-novo symmetry - recover a genuine high-symmetry group whose data are imperfectly scaled. Such a merge's within-orbit chi² lands just past the self-consistency bound (each real symmetry step adds a little systematic scatter), right where a merohedral twin also lands, so the chi² ratio alone cannot separate them. The candidate is now rescued when the extra intensity-proportional systematic error it invokes stays small relative to the confirmed subgroup - a genuine symmetry step gains multiplicity without inflating the merge error model's b, whereas a twin forces non-equivalent reflections together and b balloons. Fixes cubic insulin (I23 instead of I222) with no change to any other crystal in the test battery, including the twins that must stay in their lower symmetry. * Docs: Document the French-Wilson amplitude estimation, R-free flagging, reference-based space-group/ambiguity resolution, and model-based validation/maps in CPU_DATA_ANALYSIS.md. * Frontend: The status-bar pill now shows a progress bar during detector calibration (previously only during measurement), and the calibration state and its button are labelled "Calibration"/"CALIBRATE" (the internal `Pedestal` state name is unchanged for back-compatibility).Reviewed-on: #70 Co-authored-by: Filip Leonarski <filip.leonarski@psi.ch>
287 lines
8.1 KiB
C++
287 lines
8.1 KiB
C++
// SPDX-FileCopyrightText: 2026 Filip Leonarski, Paul Scherrer Institute <filip.leonarski@psi.ch>
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// SPDX-License-Identifier: GPL-3.0-only
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#include "ScalingSettings.h"
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ScalingSettings& ScalingSettings::RefineB(bool input) {
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refine_b = input;
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return *this;
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}
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ScalingSettings& ScalingSettings::MergeFriedel(bool input) {
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merge_friedel = input;
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return *this;
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}
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ScalingSettings& ScalingSettings::HighResolutionLimit_A(double limit) {
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if (limit <= 0.0)
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throw JFJochException(JFJochExceptionCategory::InputParameterBelowMin, "High resolution limit must be positive");
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high_resolution_limit_A = limit;
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return *this;
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}
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ScalingSettings& ScalingSettings::HighResolutionLimit_A(std::optional<double> limit) {
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if (limit.has_value() && limit.value() <= 0.0)
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throw JFJochException(JFJochExceptionCategory::InputParameterBelowMin, "High resolution limit must be positive");
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high_resolution_limit_A = limit;
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return *this;
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}
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bool ScalingSettings::GetRefineB() const {
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return refine_b;
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}
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bool ScalingSettings::GetMergeFriedel() const {
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return merge_friedel;
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}
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ScalingSettings &ScalingSettings::RefineRotationWedge(bool input) {
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refine_wedge = input;
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return *this;
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}
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bool ScalingSettings::GetRefineWedge() const {
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return refine_wedge;
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}
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std::optional<double> ScalingSettings::GetHighResolutionLimit_A() const {
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return high_resolution_limit_A;
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}
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double ScalingSettings::GetMinB() const {
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return min_b;
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}
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double ScalingSettings::GetMaxB() const {
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return max_b;
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}
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double ScalingSettings::GetMinMosaicity() const {
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return 0.001;
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}
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double ScalingSettings::GetMaxMosaicity() const {
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return 1.0;
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}
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double ScalingSettings::GetMinWedge() const {
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return 0.001;
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}
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double ScalingSettings::GetMaxWedge() const {
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return 10.0;
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}
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double ScalingSettings::GetDefaultMosaicity() const {
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return 0.1;
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}
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ScalingSettings &ScalingSettings::RotationWedgeForScaling(std::optional<double> input) {
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if (input) {
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// TODO: Use fmt
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if (input.value() < GetMinWedge() || input.value() > GetMaxWedge())
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throw JFJochException(JFJochExceptionCategory::InputParameterInvalid,
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"Wedge for scaling must be between " + std::to_string(GetMinWedge()) +
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" and " + std::to_string(GetMaxWedge()));
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}
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wedge_for_scaling = input;
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return *this;
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}
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std::optional<double> ScalingSettings::GetRotationWedgeForScaling() const {
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return wedge_for_scaling;
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}
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ScalingSettings &ScalingSettings::MinPartiality(double input) {
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if (min_partiality < 0.0 || min_partiality > 1.0)
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throw JFJochException(JFJochExceptionCategory::InputParameterInvalid, "Min partiality must be between 0 and 1");
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min_partiality = input;
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return *this;
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}
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double ScalingSettings::GetMinCCForImage() const {
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return min_cc_for_image;
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}
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ScalingSettings &ScalingSettings::MinCCForImage(double input) {
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if (input < 0.0 || input > 1.0)
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throw JFJochException(JFJochExceptionCategory::InputParameterInvalid, "Min CC for image must be between 0 and 1");
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min_cc_for_image = input;
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return *this;
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}
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double ScalingSettings::GetOutlierRejectNsigma() const {
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return outlier_reject_nsigma;
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}
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ScalingSettings &ScalingSettings::OutlierRejectNsigma(double input) {
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outlier_reject_nsigma = input; // <= 0 disables; no upper bound (large = effectively off)
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return *this;
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}
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ScalingSettings &ScalingSettings::ScaleFulls(bool input) {
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scale_fulls = input;
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return *this;
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}
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bool ScalingSettings::GetScaleFulls() const {
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return scale_fulls;
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}
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ScalingSettings &ScalingSettings::AbsorptionIter(int input) {
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if (input < 0)
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throw JFJochException(JFJochExceptionCategory::InputParameterInvalid, "Absorption iterations must be non-negative");
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absorption_iter = input;
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return *this;
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}
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int ScalingSettings::GetAbsorptionIter() const {
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return absorption_iter;
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}
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ScalingSettings &ScalingSettings::CorrectionSurfaces(bool input) {
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correction_surfaces = input;
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return *this;
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}
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bool ScalingSettings::GetCorrectionSurfaces() const {
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return correction_surfaces;
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}
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ScalingSettings &ScalingSettings::StillsModulation(bool input) {
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stills_modulation = input;
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return *this;
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}
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bool ScalingSettings::GetStillsModulation() const {
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return stills_modulation;
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}
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ScalingSettings &ScalingSettings::SmoothGDegrees(double input) {
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if (input < 0)
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throw JFJochException(JFJochExceptionCategory::InputParameterInvalid, "Smooth-G range must be non-negative");
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smooth_g_deg = input;
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return *this;
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}
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double ScalingSettings::GetSmoothGDegrees() const {
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return smooth_g_deg;
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}
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ScalingSettings &ScalingSettings::RelativeBDegrees(double input) {
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if (input < 0)
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throw JFJochException(JFJochExceptionCategory::InputParameterInvalid, "Relative-B batch width must be non-negative");
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relative_b_deg = input;
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return *this;
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}
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double ScalingSettings::GetRelativeBDegrees() const {
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return relative_b_deg;
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}
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double ScalingSettings::GetMinPartiality() const {
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return min_partiality;
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}
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ScalingSettings &ScalingSettings::ForcedMosaicity(std::optional<double> input) {
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if (input.has_value() && (input.value() < GetMinMosaicity() || input.value() > GetMaxMosaicity()))
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throw JFJochException(JFJochExceptionCategory::InputParameterInvalid,
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"Forced mosaicity must be between " + std::to_string(GetMinMosaicity()) +
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" and " + std::to_string(GetMaxMosaicity()));
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forced_mosaicity = input;
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return *this;
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}
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std::optional<double> ScalingSettings::GetForcedMosaicity() const {
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return forced_mosaicity;
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}
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ScalingSettings &ScalingSettings::CaptureUncertaintyCoeff(double input) {
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if (input < 0.0)
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throw JFJochException(JFJochExceptionCategory::InputParameterInvalid,
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"Capture uncertainty coefficient must be non-negative");
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capture_uncertainty_coeff = input;
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return *this;
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}
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double ScalingSettings::GetCaptureUncertaintyCoeff() const {
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return capture_uncertainty_coeff;
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}
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ScalingSettings &ScalingSettings::PartialityUncertaintyCoeff(double input) {
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partiality_uncertainty_coeff = input;
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return *this;
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}
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double ScalingSettings::GetPartialityUncertaintyCoeff() const {
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return partiality_uncertainty_coeff;
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}
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ScalingSettings &ScalingSettings::MinCapturedFraction(double input) {
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if (input < 0.0)
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throw JFJochException(JFJochExceptionCategory::InputParameterInvalid,
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"Minimum captured fraction must be non-negative");
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min_captured_fraction = input;
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return *this;
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}
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double ScalingSettings::GetMinCapturedFraction() const {
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return min_captured_fraction;
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}
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ScalingSettings &ScalingSettings::RfreeFraction(double input) {
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if (input < 0.0 || input > 1.0)
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throw JFJochException(JFJochExceptionCategory::InputParameterInvalid, "R-free fraction must be between 0 and 1");
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rfree_fraction = input;
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return *this;
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}
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double ScalingSettings::GetRfreeFraction() const {
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return rfree_fraction;
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}
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ScalingSettings &ScalingSettings::ScalingRegularize(bool input) {
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scaling_regularize = input;
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return *this;
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}
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bool ScalingSettings::GetScalingRegularize() const {
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return scaling_regularize;
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}
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ScalingSettings &ScalingSettings::ResolutionCutoff(ResolutionCutoffMethod input) {
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resolution_cutoff = input;
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return *this;
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}
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ResolutionCutoffMethod ScalingSettings::GetResolutionCutoff() const {
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return resolution_cutoff;
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}
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ScalingSettings &ScalingSettings::ResolutionCCTarget(double input) {
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if (input <= 0.0 || input >= 1.0)
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throw JFJochException(JFJochExceptionCategory::InputParameterInvalid,
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"Resolution CC target must be between 0 and 1");
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resolution_cc_target = input;
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return *this;
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}
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double ScalingSettings::GetResolutionCCTarget() const {
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return resolution_cc_target;
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}
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ScalingSettings &ScalingSettings::ReportShellCount(int input) {
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if (input < 1)
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throw JFJochException(JFJochExceptionCategory::InputParameterInvalid,
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"Number of report shells must be at least 1");
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report_shell_count = input;
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return *this;
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}
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int ScalingSettings::GetReportShellCount() const {
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return report_shell_count;
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}
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