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388 lines
14 KiB
C++
388 lines
14 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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#include <cstdint>
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#include <vector>
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#include <cmath>
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#include <algorithm>
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#include "AnalyzeIndexing.h"
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#include "FitProfileRadius.h"
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namespace {
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inline bool ok(float x) {
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if (!std::isfinite(x))
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return false;
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if (x < 0.0)
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return false;
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return true;
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}
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inline float deg_to_rad(float deg) {
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return deg * (static_cast<float>(M_PI) / 180.0f);
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}
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inline float rad_to_deg(float rad) {
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return rad * (180.0f / static_cast<float>(M_PI));
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}
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// Wrap to [-180, 180] (useful for residuals)
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inline float wrap_deg_pm180(float deg) {
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while (deg > 180.0f) deg -= 360.0f;
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while (deg < -180.0f) deg += 360.0f;
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return deg;
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}
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// XDS convention: zeta = |m2 · e1| where e1 = (S × S0) / |S × S0|
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// This is the Lorentz factor component related to the rotation axis
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inline float calc_zeta(const Coord& S, const Coord& S0, const Coord& m2) {
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Coord S_cross_S0 = S % S0;
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float len = S_cross_S0.Length();
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if (len < 1e-12f) return 0.0f;
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Coord e1 = S_cross_S0 * (1.0f / len);
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return std::fabs(m2 * e1);
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}
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// XDS R(τ; σM/ζ) function - fraction of observed reflection intensity
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// τ = angular difference between reflection and Bragg maximum (radians)
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// delta_phi = oscillation range (radians)
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// sigma_M = mosaicity (radians)
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// zeta = |m2 · e1| Lorentz factor component
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inline float R_fraction(float tau, float delta_phi, float sigma_M, float zeta) {
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if (zeta < 1e-6f || sigma_M < 1e-9f)
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return 0.0f;
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const float sigma_eff = sigma_M / zeta;
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const float sqrt2_sigma = std::sqrt(2.0f) * sigma_eff;
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if (sqrt2_sigma < 1e-12f)
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return 0.0f;
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const float arg_plus = (tau + delta_phi / 2.0f) / sqrt2_sigma;
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const float arg_minus = (tau - delta_phi / 2.0f) / sqrt2_sigma;
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return 0.5f * (std::erf(arg_plus) - std::erf(arg_minus));
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}
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// Log-likelihood for a given sigma_M value
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// Returns sum of log(R) for all reflections
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inline double log_likelihood(const std::vector<float>& tau_values,
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const std::vector<float>& zeta_values,
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float delta_phi,
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float sigma_M) {
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double ll = 0.0;
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for (size_t i = 0; i < tau_values.size(); ++i) {
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float R = R_fraction(tau_values[i], delta_phi, sigma_M, zeta_values[i]);
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if (R > 1e-30f) {
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ll += std::log(static_cast<double>(R));
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} else {
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ll += -70.0; // Large penalty for zero probability
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}
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}
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return ll;
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}
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// Golden section search for maximum likelihood sigma_M
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inline float find_sigma_M_mle(const std::vector<float>& tau_values,
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const std::vector<float>& zeta_values,
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float delta_phi,
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float sigma_min_deg = 0.001f,
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float sigma_max_deg = 2.0f) {
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const float golden = 0.618033988749895f;
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float a = deg_to_rad(sigma_min_deg);
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float b = deg_to_rad(sigma_max_deg);
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float c = b - golden * (b - a);
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float d = a + golden * (b - a);
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const float tol = 1e-6f;
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while (std::fabs(b - a) > tol) {
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double fc = log_likelihood(tau_values, zeta_values, delta_phi, c);
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double fd = log_likelihood(tau_values, zeta_values, delta_phi, d);
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if (fc > fd) {
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b = d;
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d = c;
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c = b - golden * (b - a);
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} else {
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a = c;
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c = d;
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d = a + golden * (b - a);
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}
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}
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return (a + b) / 2.0f;
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}
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// Solve A cos(phi) + B sin(phi) + D = 0, return solutions in [phi0, phi1] (radians)
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inline int solve_trig(float A, float B, float D,
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float phi0, float phi1,
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float out_phi[2]) {
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const float R = std::sqrt(A * A + B * B);
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if (!(R > 0.0f))
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return 0;
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const float rhs = -D / R;
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if (rhs < -1.0f || rhs > 1.0f)
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return 0;
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const float phi_ref = std::atan2(B, A);
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const float delta = std::acos(rhs);
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float s1 = phi_ref + delta;
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float s2 = phi_ref - delta;
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const float two_pi = 2.0f * static_cast<float>(M_PI);
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auto shift_near = [&](float x) {
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while (x < phi0 - two_pi) x += two_pi;
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while (x > phi1 + two_pi) x -= two_pi;
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return x;
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};
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s1 = shift_near(s1);
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s2 = shift_near(s2);
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int n = 0;
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if (s1 >= phi0 && s1 <= phi1) out_phi[n++] = s1;
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if (s2 >= phi0 && s2 <= phi1) {
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if (n == 0 || std::fabs(s2 - out_phi[0]) > 1e-6f) out_phi[n++] = s2;
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}
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return n;
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}
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// Find predicted phi (deg) for given g0 around phi_obs (deg) within +/- half_window_deg.
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// Returns nullopt if no solution in the local window.
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inline std::optional<float> predict_phi_deg_local(const Coord &g0,
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const Coord &S0,
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const Coord &w_unit,
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float phi_obs_deg,
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float half_window_deg) {
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const float phi0 = deg_to_rad(phi_obs_deg - half_window_deg);
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const float phi1 = deg_to_rad(phi_obs_deg + half_window_deg);
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// Decompose g0 into parallel/perp to w
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const float g_par_s = g0 * w_unit;
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const Coord g_par = w_unit * g_par_s;
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const Coord g_perp = g0 - g_par;
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const float g_perp2 = g_perp * g_perp;
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if (g_perp2 < 1e-12f)
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return std::nullopt;
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const float k2 = (S0 * S0); // |S0|^2 = (1/lambda)^2
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// Equation: |S0 + g(phi)|^2 = |S0|^2
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const Coord p = S0 + g_par;
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const Coord w_x_gperp = w_unit % g_perp;
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const float A = 2.0f * (p * g_perp);
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const float B = 2.0f * (p * w_x_gperp);
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const float D = (p * p) + g_perp2 - k2;
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float sols[2]{};
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const int nsol = solve_trig(A, B, D, phi0, phi1, sols);
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if (nsol == 0)
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return std::nullopt;
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// Pick the solution closest to phi_obs
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const float phi_obs = deg_to_rad(phi_obs_deg);
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float best_phi = sols[0];
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float best_err = std::fabs(sols[0] - phi_obs);
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if (nsol == 2) {
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const float err2 = std::fabs(sols[1] - phi_obs);
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if (err2 < best_err) {
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best_err = err2;
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best_phi = sols[1];
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}
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}
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return rad_to_deg(best_phi);
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}
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// XDS-style mosaicity calculation using maximum likelihood
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// Following Kabsch (2010) Acta Cryst. D66, 133-144
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std::optional<float> CalcMosaicityXDS(const DiffractionExperiment& experiment,
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const std::vector<SpotToSave> &spots,
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const Coord &astar, const Coord &bstar, const Coord &cstar) {
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const auto &axis_opt = experiment.GetGoniometer();
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if (!axis_opt.has_value())
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return std::nullopt;
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const GoniometerAxis& axis = *axis_opt;
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const Coord m2 = axis.GetAxis().Normalize(); // XDS notation: m2 is rotation axis
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const Coord S0 = experiment.GetScatteringVector();
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const float delta_phi_rad = deg_to_rad(axis.GetWedge_deg());
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std::vector<float> tau_values;
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std::vector<float> zeta_values;
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tau_values.reserve(spots.size());
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zeta_values.reserve(spots.size());
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for (const auto &s : spots) {
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if (!s.indexed)
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continue;
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const Coord pstar = astar * static_cast<float>(s.h)
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+ bstar * static_cast<float>(s.k)
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+ cstar * static_cast<float>(s.l);
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// Find predicted phi angle
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const auto phi_pred_opt = predict_phi_deg_local(pstar, S0, m2, 0.0f, axis.GetWedge_deg());
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if (!phi_pred_opt.has_value())
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continue;
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// τ (tau) = angular deviation from Bragg position to center of oscillation range
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float tau_rad = deg_to_rad(wrap_deg_pm180(phi_pred_opt.value()));
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// Calculate diffracted beam direction S = S0 + p (at diffracting condition)
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// For zeta calculation, we need S at the predicted phi angle
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const float phi_pred_rad = deg_to_rad(phi_pred_opt.value());
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const float cos_phi = std::cos(phi_pred_rad);
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const float sin_phi = std::sin(phi_pred_rad);
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// Rotate pstar by predicted phi around m2 axis
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const float p_m2 = pstar * m2;
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const Coord p_parallel = m2 * p_m2;
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const Coord p_perp = pstar - p_parallel;
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const Coord m2_cross_p = m2 % pstar;
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const Coord p_rotated = p_parallel + p_perp * cos_phi + m2_cross_p * sin_phi;
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const Coord S = S0 + p_rotated;
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// Calculate zeta (XDS convention)
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float zeta = calc_zeta(S, S0, m2);
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// Filter out reflections with very small zeta (poorly determined)
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if (zeta < 0.1f)
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continue;
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tau_values.push_back(tau_rad);
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zeta_values.push_back(zeta);
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}
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if (tau_values.size() < 10)
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return std::nullopt;
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// Find sigma_M by maximizing log-likelihood
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float sigma_M_rad = find_sigma_M_mle(tau_values, zeta_values, delta_phi_rad);
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return rad_to_deg(sigma_M_rad);
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}
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std::optional<float> CalcMosaicity(const DiffractionExperiment& experiment,
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const std::vector<SpotToSave> &spots,
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const Coord &astar, const Coord &bstar, const Coord &cstar) {
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const auto &axis = experiment.GetGoniometer();
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if (axis.has_value()) {
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const Coord w = axis->GetAxis().Normalize();
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const Coord S0 = experiment.GetScatteringVector();
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const float wedge_deg = axis->GetWedge_deg();
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double sum_sq = 0.0;
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int count = 0;
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for (const auto &s: spots) {
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if (!s.indexed)
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continue;
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const Coord pstar = astar * static_cast<float>(s.h) + bstar * static_cast<float>(s.k) + cstar * static_cast<float>(s.l);
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// Local solve window: +/- 1 wedge (easy/robust first try)
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const auto phi_pred_deg_opt = predict_phi_deg_local(pstar, S0, w, 0.0, wedge_deg);
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if (!phi_pred_deg_opt.has_value())
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continue;
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float dphi = wrap_deg_pm180(phi_pred_deg_opt.value());
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sum_sq += static_cast<double>(dphi) * static_cast<double>(dphi);
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count++;
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}
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if (count > 0) {
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return static_cast<float>(std::sqrt(sum_sq / static_cast<double>(count)));
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}
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}
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return std::nullopt;
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}
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} // namespace
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bool AnalyzeIndexing(DataMessage &message,
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const DiffractionExperiment &experiment,
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const CrystalLattice &latt) {
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std::vector<uint8_t> indexed_spots(message.spots.size());
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// Check spots
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const Coord a = latt.Vec0();
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const Coord b = latt.Vec1();
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const Coord c = latt.Vec2();
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const Coord astar = latt.Astar();
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const Coord bstar = latt.Bstar();
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const Coord cstar = latt.Cstar();
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const bool index_ice_ring = experiment.GetIndexingSettings().GetIndexIceRings();
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const auto geom = experiment.GetDiffractionGeometry();
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const auto indexing_tolerance = experiment.GetIndexingSettings().GetTolerance();
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const auto indexing_tolerance_sq = indexing_tolerance * indexing_tolerance;
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const auto viable_cell_min_spots = experiment.GetIndexingSettings().GetViableCellMinSpots();
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size_t nspots_ref = 0;
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size_t nspots_indexed = 0;
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// identify indexed spots
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for (int i = 0; i < message.spots.size(); i++) {
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auto recip = message.spots[i].ReciprocalCoord(geom);
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float h_fp = recip * a;
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float k_fp = recip * b;
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float l_fp = recip * c;
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float h_frac = h_fp - std::round(h_fp);
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float k_frac = k_fp - std::round(k_fp);
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float l_frac = l_fp - std::round(l_fp);
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float norm_sq = h_frac * h_frac + k_frac * k_frac + l_frac * l_frac;
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Coord recip_pred = std::round(h_fp) * astar + std::round(k_fp) * bstar + std::round(l_fp) * cstar;
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// See indexing_peak_check() in peaks.c in CrystFEL
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if (norm_sq < indexing_tolerance_sq) {
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if (index_ice_ring || !message.spots[i].ice_ring)
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nspots_indexed++;
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indexed_spots[i] = 1;
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message.spots[i].dist_ewald_sphere = geom.DistFromEwaldSphere(recip_pred);
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message.spots[i].h = std::lround(h_fp);
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message.spots[i].k = std::lround(k_fp);
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message.spots[i].l = std::lround(l_fp);
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}
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if (index_ice_ring || !message.spots[i].ice_ring)
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nspots_ref++;
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}
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if (nspots_indexed >= viable_cell_min_spots && nspots_indexed >= std::lround(min_percentage_spots * nspots_ref)) {
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auto uc = latt.GetUnitCell();
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if (!ok(uc.a) || !ok(uc.b) || !ok(uc.c) || !ok(uc.alpha) || !ok(uc.beta) || !ok(uc.gamma))
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return false;
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message.indexing_result = true;
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assert(indexed_spots.size() == message.spots.size());
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for (int i = 0; i < message.spots.size(); i++)
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message.spots[i].indexed = indexed_spots[i];
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message.profile_radius = FitProfileRadius(message.spots);
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message.spot_count_indexed = nspots_indexed;
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message.indexing_lattice = latt;
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message.indexing_unit_cell = latt.GetUnitCell();
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message.mosaicity_deg = CalcMosaicityXDS(experiment, message.spots, astar, bstar, cstar);
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return true;
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}
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message.indexing_result = false;
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return false;
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}
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