// SPDX-FileCopyrightText: 2025 Filip Leonarski, Paul Scherrer Institute <filip.leonarski@psi.ch>
// SPDX-License-Identifier: GPL-3.0-only

#include "IntegrationStats.h"
#include "Regression.h"
#include <cmath>

IntegrationStats::IntegrationStats(float d_max_A, float d_min_A, int32_t in_nshells) {
    d_min = d_min_A;
    d_max = d_max_A;
    one_over_dmax = 1.0f / (d_max);
    one_over_dmin = 1.0f / (d_min);
    nshells = in_nshells;
    I.resize(nshells);
    I_sigma.resize(nshells);
    count.resize(nshells);
}

void IntegrationStats::AddReflection(const Reflection &r) {
    if (r.d == 0.0f)
        return;

    float one_over_d = 1.0f / (r.d);
    int64_t shell = std::lround((one_over_d - one_over_dmax) / (one_over_dmin - one_over_dmax)
            * static_cast<float>(nshells));
    if (shell >= 0 && shell < nshells) {
        I.at(shell) += r.I;
        I_sigma.at(shell) += r.I / r.sigma;
        count.at(shell) += 1;
    }
}

float IntegrationStats::BFactor() {
    std::vector<float> x;
    std::vector<float> y;

    for (int i = 0; i < nshells; i++) {
        if (count[i] == 0 || I[i] < 0.0)
            continue;

        float one_over_d = one_over_dmax
                           + (static_cast<float>(i) + 0.5) * (one_over_dmin - one_over_dmax) / static_cast<float>(nshells);
        x.push_back(one_over_d);
        y.push_back(log(I[i] / count[i]));
    }
    if (!x.empty()) {
        auto res = regression(x,y);
        return -2.0f * res.slope;
    } else
        return 0.0;
}