// SPDX-FileCopyrightText: 2026 Filip Leonarski, Paul Scherrer Institute <filip.leonarski@psi.ch>
// SPDX-License-Identifier: GPL-3.0-only

#include <catch2/catch_all.hpp>

#include <cmath>
#include <vector>

#include "../image_analysis/scale_merge/FrenchWilson.h"

namespace {
    MergedReflection Refl(int h, int k, int l, float d, float I, float sigma) {
        MergedReflection r;
        r.h = h; r.k = k; r.l = l; r.d = d; r.I = I; r.sigma = sigma;
        return r;
    }
    // A resolution-spread of ordinary reflections so a Wilson mean can be formed per shell.
    std::vector<MergedReflection> Background() {
        std::vector<MergedReflection> v;
        for (int h = 1; h <= 12; ++h)
            for (int k = 0; k <= 12; ++k)
                for (int l = 0; l <= 12; ++l)
                    v.push_back(Refl(h, k, l, 40.0f / (1 + h * h + k * k + l * l), 800.0f, 20.0f));
        return v;
    }
}

TEST_CASE("French-Wilson: strong reflections reduce to sqrt(I)", "[french_wilson]") {
    auto v = Background();
    v.push_back(Refl(1, 0, 0, 25.0f, 40000.0f, 50.0f));   // I/sigma = 800, clearly strong
    ApplyFrenchWilson(v, 1);
    CHECK(v.back().F == Catch::Approx(std::sqrt(40000.0)).epsilon(0.02));   // ~200
    CHECK(v.back().sigmaF >= 0.0f);
    CHECK(std::isfinite(v.back().sigmaF));
}

TEST_CASE("French-Wilson: weak and negative intensities get a positive amplitude", "[french_wilson]") {
    auto v = Background();
    v.push_back(Refl(2, 0, 0, 20.0f, -40.0f, 50.0f));   // negative measured intensity
    v.push_back(Refl(3, 0, 0, 15.0f, 10.0f, 50.0f));    // weak, I < sigma
    ApplyFrenchWilson(v, 1);
    const auto& neg = v[v.size() - 2];
    const auto& weak = v.back();
    CHECK(std::isfinite(neg.F));
    CHECK(neg.F > 0.0f);          // Bayesian estimate is positive (naive sqrt would give 0)
    CHECK(std::isfinite(weak.F));
    CHECK(weak.F > 0.0f);
}

TEST_CASE("French-Wilson: amplitudes are always finite and non-negative", "[french_wilson]") {
    std::vector<MergedReflection> v;
    // A deliberate mix: strong, weak, negative, tiny sigma, across resolution.
    for (int i = 0; i < 300; ++i) {
        const float d = 20.0f / (1 + 0.05f * i);
        const float I = (i % 7 == 0) ? -30.0f : static_cast<float>((i % 50) * 40);
        v.push_back(Refl(1 + i, 2, 3, d, I, 25.0f));
    }
    ApplyFrenchWilson(v, 96);   // P4(3)2(1)2 (has centric reflections + epsilon>1 axes)
    for (const auto& r : v) {
        CHECK(std::isfinite(r.F));
        CHECK(r.F >= 0.0f);
        CHECK(std::isfinite(r.sigmaF));
        CHECK(r.sigmaF >= 0.0f);
    }
}

TEST_CASE("French-Wilson: unusable sigma falls back to sqrt(max(I,0))", "[french_wilson]") {
    auto v = Background();
    v.push_back(Refl(4, 0, 0, 12.0f, 144.0f, NAN));   // no sigma
    v.push_back(Refl(5, 0, 0, 11.0f, -5.0f, NAN));    // no sigma, negative I
    ApplyFrenchWilson(v, 1);
    CHECK(v[v.size() - 2].F == Catch::Approx(12.0f));   // sqrt(144)
    CHECK(v.back().F == Catch::Approx(0.0f));           // sqrt(max(-5,0))
}