Files
Jungfraujoch/common/BraggIntegrationSettings.cpp
T
leonarski_f 711f902aa7 One gain mechanism: frames analysed in their own units, the gain applied where a photon count is assumed
The gain of an input in detector units (SMV, marCCD, XTC, the XFEL formats) is measured once, before
anything reads the frames (RugnuxMeasureGain: photon-peak spacing and background variance per unit
mean), or given with --gain, and handed to the integration and the spot finding by one function
(ApplyRugnuxPixelGain). The rotation pre-scan no longer measures it, and the stills reader no longer
converts frames of a detector whose photons are not resolved: SACLA MPCCD, Rayonix and CCD frames are
integrated in ADU at the gain, rotation and stills alike.

Where a photon count was assumed, it is now taken at the gain (bit-identical at gain 1):
- integration: the background clip's one-photon floor, the sigma floor (one photon), the profile fit's
  background floor (0.01 photon), and a still's overload kept as a lower bound, which was left in ADU
  while every other reflection left the integrator in photons - the cause of the earlier loss of the
  engine route on clipped CCD stills (merged low resolution inflated by the gain, the rocking-width
  fit's bandwidth collapsing); CPU and CUDA, Metal through the shared CPU code;
- the adaptive spot threshold (Poisson arm and its one-photon floor), CPU and GPU;
- the pre-scan spot-width measurement (strong-spot SNR, the ring clip) behind the stills bandwidth and
  the rotation signal radius;
- the hot/dead pixel tests, CPU and GPU; the empty-aperture ring clip.
BackgroundPixelGain is gone: one pixel_gain.

A detector whose background resolves single photons (photon peaks: JUNGFRAU in keV, AGIPD) is a photon
counter and its frames are still counted in whole photons as read: analysed in keV at the gain instead,
a photon-counting still set lost 0.008 R-free (fewer spots, a noisier beam-centre trial) - the rounding
is the detector's own discrimination. --gain sets the value, the background still says which kind.

Validation, against rc178: photon-counting and g<=1 rotation p.hkl md5-identical (lyso, thau, cytc,
myob, insu, a small-molecule set, 5reo, 6cee, 6i3j, 2xfw, 6s1u, 8v4j); CCD g>1 at or within noise of rc178 (5uth
R_meas 0.113 -> 0.108). Stills R-free (0-cycle REFMAC): MPCCD sets 0.184 -> 0.185 and 0.199 -> 0.196,
Rayonix identical, photon-resolving sets back on their rc178 numbers.

Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_015CeEGgpKdfkCTJb3YNMJcu
(cherry picked from commit da8dbfc8147354b63e375f2d9521dffb80938b6d)
2026-10-23 17:56:51 +02:00

231 lines
7.6 KiB
C++

// SPDX-FileCopyrightText: 2025 Filip Leonarski, Paul Scherrer Institute <filip.leonarski@psi.ch>
// SPDX-License-Identifier: GPL-3.0-only
#include <cmath>
#include "BraggIntegrationSettings.h"
#include "JFJochException.h"
#define check_max(param, val, max) if ((val) > (max)) throw JFJochException(JFJochExceptionCategory::InputParameterAboveMax, param)
#define check_min(param, val, min) if ((val) < (min)) throw JFJochException(JFJochExceptionCategory::InputParameterBelowMin, param)
#define check_finite(param, val) if (!std::isfinite(val)) throw JFJochException(JFJochExceptionCategory::InputParameterInvalid, param)
BraggIntegrationSettings &BraggIntegrationSettings::R1(float input) {
check_finite("Integration radius R1", input);
check_min("Integration radius R1", input, 0.1);
check_max("Integration radius R1", input, 20.0);
r_1 = input;
return *this;
}
BraggIntegrationSettings &BraggIntegrationSettings::R2(float input) {
check_finite("Background inner radius R2", input);
check_min("Background inner radius R2", input, 0.1);
check_max("Background inner radius R2", input, 30.0);
if (input <= r_1)
throw JFJochException(JFJochExceptionCategory::InputParameterInvalid,
"Background inner radius (R2) must be larger than integration radius (R1)");
r_2 = input;
return *this;
}
BraggIntegrationSettings &BraggIntegrationSettings::R3(float input) {
check_finite("Background outer radius R3", input);
check_min("Background outer radius R3", input, 0.1);
check_max("Background outer radius R3", input, 40.0);
if (input <= r_2)
throw JFJochException(JFJochExceptionCategory::InputParameterInvalid,
"Background outer radius (R3) must be larger than background inner radius (R2)");
r_3 = input;
return *this;
}
BraggIntegrationSettings &BraggIntegrationSettings::StencilKSigma(float input) {
check_finite("Integration stencil elongation", input);
check_min("Integration stencil elongation", input, 0.0);
check_max("Integration stencil elongation", input, 10.0);
stencil_k_sigma = input;
return *this;
}
BraggIntegrationSettings &BraggIntegrationSettings::DMinLimit_A(std::optional<float> input) {
if (input) {
check_finite("Minimum d-spacing", *input);
check_min("Minimum d-spacing", *input, 0.5);
check_max("Minimum d-spacing", *input, 100.0);
}
d_min_limit_A = input;
return *this;
}
BraggIntegrationSettings & BraggIntegrationSettings::FixedProfileRadius_recipA(std::optional<float> input) {
if (input) {
check_finite("Profile radius", input.value());
check_min("Profile radius [A^-1]", input.value(), 0.000001);
check_max("Profile radius [A^-1]", input.value(), 0.01);
}
fixed_profile_radius = input;
return *this;
}
std::optional<float> BraggIntegrationSettings::GetFixedProfileRadius_recipA() const {
return fixed_profile_radius;
}
BraggIntegrationSettings & BraggIntegrationSettings::ForcedPredictionMosaicity_deg(std::optional<float> input) {
if (input) {
check_finite("Prediction mosaicity", input.value());
check_min("Prediction mosaicity [deg]", input.value(), 0.001);
check_max("Prediction mosaicity [deg]", input.value(), 10.0);
}
forced_prediction_mosaicity_deg = input;
return *this;
}
std::optional<float> BraggIntegrationSettings::GetForcedPredictionMosaicity_deg() const {
return forced_prediction_mosaicity_deg;
}
BraggIntegrationSettings &BraggIntegrationSettings::Integrator(IntegratorMode input) {
integrator_mode = input;
return *this;
}
IntegratorMode BraggIntegrationSettings::GetIntegrator() const {
return integrator_mode;
}
float BraggIntegrationSettings::GetR1() const {
return r_1;
}
float BraggIntegrationSettings::GetR2() const {
return r_2;
}
float BraggIntegrationSettings::GetR3() const {
return r_3;
}
float BraggIntegrationSettings::GetStencilKSigma() const {
return stencil_k_sigma;
}
std::optional<float> BraggIntegrationSettings::GetDMinLimit_A() const {
return d_min_limit_A;
}
float BraggIntegrationSettings::GetMinimumSigmaInRegardsToI() const {
return minimum_sigma_in_regards_to_i;
}
BraggIntegrationSettings &BraggIntegrationSettings::BackgroundTrimFraction(float input) {
check_finite("Background trim fraction", input);
check_min("Background trim fraction", input, 0.0);
check_max("Background trim fraction", input, 0.49); // must leave a central majority after trimming
bkg_trim_fraction = input;
if (input > 0.0f)
bkg_clip_nsigma = 0.0f; // the two ring estimators are alternatives, not a stack
return *this;
}
float BraggIntegrationSettings::GetBackgroundTrimFraction() const {
return bkg_trim_fraction;
}
BraggIntegrationSettings &BraggIntegrationSettings::MaxHKL(std::optional<int> input) {
if (input) {
check_min("Maximum hkl index", *input, 1);
// The GPU predictor launches one thread per candidate, so the cost is (2n+1)^3: 511 is 1.1e9
// candidates per frame, already far past the point where prediction dominates a run.
check_max("Maximum hkl index", *input, 511);
}
max_hkl = input;
return *this;
}
std::optional<int> BraggIntegrationSettings::GetMaxHKL() const {
return max_hkl;
}
BraggIntegrationSettings &BraggIntegrationSettings::BackgroundClipNSigma(float input) {
check_finite("Background clip nsigma", input);
check_min("Background clip nsigma", input, 0.0);
bkg_clip_nsigma = input;
if (input > 0.0f)
bkg_trim_fraction = 0.0f; // the two ring estimators are alternatives, not a stack
return *this;
}
float BraggIntegrationSettings::GetBackgroundClipNSigma() const {
return bkg_clip_nsigma;
}
BraggIntegrationSettings &BraggIntegrationSettings::PixelGain(float input) {
check_finite("Pixel gain", input);
check_min("Pixel gain", input, 1.0);
pixel_gain = input;
return *this;
}
float BraggIntegrationSettings::GetPixelGain() const {
return pixel_gain;
}
BraggIntegrationSettings &BraggIntegrationSettings::BackgroundRadialCorrection(std::optional<bool> input) {
bkg_radial_correction = input;
return *this;
}
std::optional<bool> BraggIntegrationSettings::GetBackgroundRadialCorrection() const {
return bkg_radial_correction;
}
BraggIntegrationSettings &BraggIntegrationSettings::Overlap(OverlapMode input) {
overlap_mode = input;
return *this;
}
OverlapMode BraggIntegrationSettings::GetOverlap() const {
return overlap_mode;
}
BraggIntegrationSettings &BraggIntegrationSettings::OverlapMinPeak(float input) {
check_finite("Overlap minimum peak fraction", input);
check_min("Overlap minimum peak fraction", input, 0.0);
check_max("Overlap minimum peak fraction", input, 1.0);
overlap_min_peak = input;
return *this;
}
float BraggIntegrationSettings::GetOverlapMinPeak() const {
return overlap_min_peak;
}
BraggIntegrationSettings &BraggIntegrationSettings::FlightPath(FlightPathMedium input) {
flight_path = input;
return *this;
}
FlightPathMedium BraggIntegrationSettings::GetFlightPath() const {
return flight_path;
}
BraggIntegrationSettings &BraggIntegrationSettings::Footprint(const SpotFootprint &input) {
if (input.sigma_rad.size() != input.sigma_tan.size()
|| input.sigma_rad.size() > static_cast<size_t>(SpotFootprint::MAX_BINS)
|| (!input.empty() && !(input.bin_px > 0.0f)))
throw JFJochException(JFJochExceptionCategory::InputParameterInvalid, "Invalid spot footprint table");
footprint = input;
return *this;
}
const SpotFootprint &BraggIntegrationSettings::GetFootprint() const {
return footprint;
}