51 lines
1.5 KiB
C++
51 lines
1.5 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 "IntegrationStats.h"
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#include "Regression.h"
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#include <cmath>
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IntegrationStats::IntegrationStats(float d_max_A, float d_min_A, int32_t in_nshells) {
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d_min = d_min_A;
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d_max = d_max_A;
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one_over_dmax = 1.0f / (d_max);
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one_over_dmin = 1.0f / (d_min);
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nshells = in_nshells;
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I.resize(nshells);
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I_sigma.resize(nshells);
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count.resize(nshells);
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}
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void IntegrationStats::AddReflection(const Reflection &r) {
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if (r.d == 0.0f)
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return;
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float one_over_d = 1.0f / (r.d);
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int64_t shell = std::lround((one_over_d - one_over_dmax) / (one_over_dmin - one_over_dmax)
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* static_cast<float>(nshells));
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if (shell >= 0 && shell < nshells) {
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I.at(shell) += r.I;
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I_sigma.at(shell) += r.I / r.sigma;
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count.at(shell) += 1;
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}
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}
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float IntegrationStats::BFactor() {
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std::vector<float> x;
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std::vector<float> y;
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for (int i = 0; i < nshells; i++) {
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if (count[i] == 0 || I[i] < 0.0 || I_sigma[i] < 0.2)
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continue;
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float one_over_d = one_over_dmax
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+ (static_cast<float>(i) + 0.5) * (one_over_dmin - one_over_dmax) / static_cast<float>(nshells);
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x.push_back(one_over_d);
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y.push_back(log(I[i] / count[i]));
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}
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if (!x.empty()) {
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auto res = regression(x,y);
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return -2.0f * res.slope;
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} else
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return 0.0;
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} |