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This is an UNSTABLE release. The release has significant modifications and bug fixes, if things go wrong, it is better to revert to 1.0.0-rc.132. * Multiple small bug fixes scattered across the whole code base. (detected with GPT-5.4) * jfjoch_viewer: Improve image render performance Reviewed-on: #44 Co-authored-by: Filip Leonarski <filip.leonarski@psi.ch> Co-committed-by: Filip Leonarski <filip.leonarski@psi.ch>
81 lines
2.2 KiB
C++
81 lines
2.2 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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#ifndef JUNGFRAUJOCH_REGRESSION_H
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#define JUNGFRAUJOCH_REGRESSION_H
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#include <vector>
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#include <utility>
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#include <cmath>
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#include "../../common/JFJochException.h"
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struct RegressionResult {
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float intercept;
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float slope;
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float r_square;
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};
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template <class fptype = float>
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RegressionResult regression(std::vector<float> &x, std::vector<float> &y, const size_t N) {
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if (N < 3)
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throw JFJochException(JFJochExceptionCategory::InputParameterInvalid,
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"Regression: minimum 3 points needed for any meaningful result");
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if (x.size() < N || y.size() < N)
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throw JFJochException(JFJochExceptionCategory::InputParameterInvalid,
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"Regression: mismatch between input parameter size");
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fptype x_sum = 0.0;
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fptype y_sum = 0.0;
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fptype xy_sum = 0.0;
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fptype x2_sum = 0.0;
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int64_t nelem = 0;
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for (int i = 0; i < N; i++) {
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if (std::isfinite(y[i]) && std::isfinite(x[i])) {
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x_sum += x[i];
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y_sum += y[i];
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x2_sum += x[i] * x[i];
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xy_sum += x[i] * y[i];
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nelem++;
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}
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}
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if (nelem < 3)
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return {
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.intercept = 0,
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.slope = 0,
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.r_square = 0
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};
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fptype denominator = nelem * x2_sum - x_sum * x_sum;
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fptype intercept = (y_sum * x2_sum - x_sum * xy_sum) / denominator;
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fptype slope = (nelem * xy_sum - x_sum * y_sum) / denominator;
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fptype y_mean = y_sum / nelem;
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fptype ss_tot = 0.0;
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fptype ss_reg = 0.0;
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for (int i = 0; i < nelem; i++) {
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if (std::isfinite(y[i]) && std::isfinite(x[i])) {
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fptype pred = slope * x[i] + intercept;
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ss_tot += (y[i] - y_mean) * (y[i] - y_mean);
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ss_reg += (pred - y_mean) * (pred - y_mean);
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}
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}
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fptype r_square = 0.0;
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if (ss_tot != 0.0)
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r_square = ss_reg / ss_tot;
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return {
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.intercept = static_cast<float>(intercept),
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.slope = static_cast<float>(slope),
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.r_square = static_cast<float>(r_square)
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};
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};
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#endif //JUNGFRAUJOCH_REGRESSION_H
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