81 lines
2.3 KiB
C++
81 lines
2.3 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 "CalcISigma.h"
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#include "Regression.h"
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#include "../../common/ResolutionShells.h"
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void CalcISigma(DataMessage &msg) {
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if (msg.reflections.empty())
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return;
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const int nshells = 20;
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ResolutionShells shells(1.5, 50.0, nshells);
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std::vector<float> Isigma_sum(nshells);
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std::vector<float> count(nshells);
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for (const auto &r: msg.reflections) {
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auto s = shells.GetShell(r.d);
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if (s && (r.sigma != 0.0)) {
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Isigma_sum[*s] += r.I / r.sigma;
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++count[*s];
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}
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}
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std::vector<float> result(nshells);
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for (int i = 0; i < nshells; ++i) {
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if (count[i] > 0)
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result[i] = Isigma_sum[i] / count[i];
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else
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result[i] = 0.0f;
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}
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msg.integration_Isigma = result;
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msg.integration_Isigma_one_over_d_square = shells.GetShellMeanOneOverResSq();
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}
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void CalcWilsonBFactor(DataMessage &msg, bool replace_b) {
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if (msg.reflections.empty())
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return;
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const int nshells = 20;
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ResolutionShells shells(1.5, 6.0, nshells);
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std::vector<float> I_sum(nshells);
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std::vector<float> count(nshells);
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for (const auto& r: msg.reflections) {
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auto s = shells.GetShell(r.d);
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if (s && (r.sigma != 0.0)) {
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I_sum[*s] += r.I;
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++count[*s];
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}
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}
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std::vector<float> log_I_mean(nshells);
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int32_t valid_shells = nshells;
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for (int i = 0; i < nshells; ++i) {
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if (count[i] > 0 && I_sum[i] > 0) {
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log_I_mean[i] = std::log(I_sum[i] / count[i]);
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} else {
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log_I_mean[i] = 0.0f;
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// First shell that has improper value limits how far the Wilson plot is interpolated
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valid_shells = std::min(valid_shells, i + 1);
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}
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}
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auto shells_mean_one_over_d_square = shells.GetShellMeanOneOverResSq();
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if (replace_b && valid_shells > 2) {
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auto reg_result = regression(shells_mean_one_over_d_square, log_I_mean, valid_shells);
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if (reg_result.r_square > 0.3)
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msg.b_factor = -2.0f * reg_result.slope;
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}
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msg.integration_B_logI = log_I_mean;
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msg.integration_B_one_over_d_square = shells_mean_one_over_d_square;
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}
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