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/*! \internal \file
 * \brief
 * Tests density fitting routines.
 *
 * \author Christian Blau <blau@kth.se>
 * \ingroup module_math
 */
#include "gmxpre.h"

#include "gromacs/math/densityfit.h"

#include <numeric>

#include <gtest/gtest.h>

#include "gromacs/math/multidimarray.h"

#include "testutils/refdata.h"
#include "testutils/testasserts.h"
#include "testutils/testmatchers.h"

namespace gmx
{

namespace test
{

TEST(DensitySimilarityTest, InnerProductIsCorrect)
{
    MultiDimArray<std::vector<float>, dynamicExtents3D> referenceDensity(3, 3, 3);
    std::iota(begin(referenceDensity), end(referenceDensity), 0);

    DensitySimilarityMeasure measure(DensitySimilarityMeasureMethod::innerProduct,
                                     referenceDensity.asConstView());

    MultiDimArray<std::vector<float>, dynamicExtents3D> comparedDensity(3, 3, 3);
    std::iota(begin(comparedDensity), end(comparedDensity), -18);

    // 0*(-18) + 1*(-17) .. + 26 * 8 / Number elements
    const float expectedSimilarity =
            -117.0 / comparedDensity.asConstView().mapping().required_span_size();
    EXPECT_FLOAT_EQ(expectedSimilarity, measure.similarity(comparedDensity.asConstView()));
}

TEST(DensitySimilarityTest, InnerProductGradientIsCorrect)
{
    MultiDimArray<std::vector<float>, dynamicExtents3D> referenceDensity(3, 3, 3);
    std::iota(begin(referenceDensity), end(referenceDensity), 0);

    DensitySimilarityMeasure measure(DensitySimilarityMeasureMethod::innerProduct,
                                     referenceDensity.asConstView());

    MultiDimArray<std::vector<float>, dynamicExtents3D> comparedDensity(3, 3, 3);
    std::iota(begin(comparedDensity), end(comparedDensity), -18);

    std::vector<float> expectedSimilarityGradient;
    std::copy(begin(referenceDensity), end(referenceDensity), std::back_inserter(expectedSimilarityGradient));
    for (auto& x : expectedSimilarityGradient)
    {
        x /= comparedDensity.asConstView().mapping().required_span_size();
    }

    FloatingPointTolerance tolerance(defaultFloatTolerance());

    // Need this conversion to vector of float, because Pointwise requires size()
    // member function not provided by basic_mdspan
    const basic_mdspan<const float, dynamicExtents3D> gradient =
            measure.gradient(comparedDensity.asConstView());
    ArrayRef<const float> gradientView(gradient.data(),
                                       gradient.data() + gradient.mapping().required_span_size());
    EXPECT_THAT(expectedSimilarityGradient, Pointwise(FloatEq(tolerance), gradientView));
}

TEST(DensitySimilarityTest, GradientThrowsIfDensitiesDontMatch)
{
    MultiDimArray<std::vector<float>, dynamicExtents3D> referenceDensity(3, 3, 3);
    DensitySimilarityMeasure measure(DensitySimilarityMeasureMethod::innerProduct,
                                     referenceDensity.asConstView());

    MultiDimArray<std::vector<float>, dynamicExtents3D> comparedDensity(3, 3, 5);
    EXPECT_THROW(measure.gradient(comparedDensity.asConstView()), RangeError);
}

TEST(DensitySimilarityTest, SimilarityThrowsIfDensitiesDontMatch)
{
    MultiDimArray<std::vector<float>, dynamicExtents3D> referenceDensity(3, 3, 3);
    DensitySimilarityMeasure measure(DensitySimilarityMeasureMethod::innerProduct,
                                     referenceDensity.asConstView());
    MultiDimArray<std::vector<float>, dynamicExtents3D> comparedDensity(3, 3, 5);
    EXPECT_THROW(measure.similarity(comparedDensity.asConstView()), RangeError);
}

TEST(DensitySimilarityTest, CopiedMeasureInnerProductIsCorrect)
{
    MultiDimArray<std::vector<float>, dynamicExtents3D> referenceDensity(3, 3, 3);
    std::iota(begin(referenceDensity), end(referenceDensity), 0);

    DensitySimilarityMeasure measure(DensitySimilarityMeasureMethod::innerProduct,
                                     referenceDensity.asConstView());

    DensitySimilarityMeasure                            copiedMeasure = measure;
    MultiDimArray<std::vector<float>, dynamicExtents3D> comparedDensity(3, 3, 3);
    std::iota(begin(comparedDensity), end(comparedDensity), -18);

    // 0*(-18) + 1*(-17) .. + 26 * 8 / Number elements
    const float expectedSimilarity =
            -117.0 / comparedDensity.asConstView().mapping().required_span_size();
    EXPECT_FLOAT_EQ(expectedSimilarity, copiedMeasure.similarity(comparedDensity.asConstView()));
}

TEST(DensitySimilarityTest, RelativeEntropyOfSameDensityIsZero)
{
    MultiDimArray<std::vector<float>, dynamicExtents3D> referenceDensity(3, 3, 3);
    std::iota(begin(referenceDensity), end(referenceDensity), -2);

    DensitySimilarityMeasure measure(DensitySimilarityMeasureMethod::relativeEntropy,
                                     referenceDensity.asConstView());

    MultiDimArray<std::vector<float>, dynamicExtents3D> comparedDensity(3, 3, 3);
    std::iota(begin(comparedDensity), end(comparedDensity), -2);

    const float expectedSimilarity = 0;
    EXPECT_REAL_EQ(expectedSimilarity, measure.similarity(comparedDensity.asConstView()));
}


TEST(DensitySimilarityTest, RelativeEntropyIsCorrect)
{
    MultiDimArray<std::vector<float>, dynamicExtents3D> referenceDensity(3, 3, 3);
    std::iota(begin(referenceDensity), end(referenceDensity), -2);

    DensitySimilarityMeasure measure(DensitySimilarityMeasureMethod::relativeEntropy,
                                     referenceDensity.asConstView());

    MultiDimArray<std::vector<float>, dynamicExtents3D> comparedDensity(3, 3, 3);
    std::iota(begin(comparedDensity), end(comparedDensity), -1);

    const real expectedSimilarity = 22.468290398724498791;
    EXPECT_REAL_EQ(expectedSimilarity, measure.similarity(comparedDensity.asConstView()));
}

TEST(DensitySimilarityTest, RelativeEntropyGradientIsCorrect)
{
    MultiDimArray<std::vector<float>, dynamicExtents3D> referenceDensity(3, 3, 3);
    std::iota(begin(referenceDensity), end(referenceDensity), -1);

    DensitySimilarityMeasure measure(DensitySimilarityMeasureMethod::relativeEntropy,
                                     referenceDensity.asConstView());

    MultiDimArray<std::vector<float>, dynamicExtents3D> comparedDensity(3, 3, 3);
    std::iota(begin(comparedDensity), end(comparedDensity), -2);

    // Need this conversion to ArrayRef, because Pointwise requires size()
    // member function not provided by basic_mdspan
    const basic_mdspan<const float, dynamicExtents3D> gradient =
            measure.gradient(comparedDensity.asConstView());
    ArrayRef<const float> gradientView(gradient.data(),
                                       gradient.data() + gradient.mapping().required_span_size());

    TestReferenceData    refData;
    TestReferenceChecker checker(refData.rootChecker());
    checker.setDefaultTolerance(defaultFloatTolerance());
    checker.checkSequence(gradientView.begin(), gradientView.end(), "relative-entropy-gradient");
}

TEST(DensitySimilarityTest, CrossCorrelationIsOne)
{
    MultiDimArray<std::vector<float>, dynamicExtents3D> referenceDensity(100, 100, 100);
    std::iota(begin(referenceDensity), end(referenceDensity), 10000);

    DensitySimilarityMeasure measure(DensitySimilarityMeasureMethod::crossCorrelation,
                                     referenceDensity.asConstView());

    MultiDimArray<std::vector<float>, dynamicExtents3D> comparedDensity(100, 100, 100);
    std::iota(begin(comparedDensity), end(comparedDensity), -10000);

    const real             expectedSimilarity = 1;
    FloatingPointTolerance tolerance(relativeToleranceAsUlp(1.0, 100'000));
    EXPECT_REAL_EQ_TOL(expectedSimilarity, measure.similarity(comparedDensity.asConstView()), tolerance);
}

TEST(DensitySimilarityTest, CrossCorrelationIsMinusOneWhenAntiCorrelated)
{
    MultiDimArray<std::vector<float>, dynamicExtents3D> referenceDensity(100, 100, 100);
    std::iota(begin(referenceDensity), end(referenceDensity), 10000);
    for (auto& referenceDensityValue : referenceDensity)
    {
        referenceDensityValue *= -1;
    }

    DensitySimilarityMeasure measure(DensitySimilarityMeasureMethod::crossCorrelation,
                                     referenceDensity.asConstView());

    MultiDimArray<std::vector<float>, dynamicExtents3D> comparedDensity(100, 100, 100);
    std::iota(begin(comparedDensity), end(comparedDensity), -10000);

    const real             expectedSimilarity = -1;
    FloatingPointTolerance tolerance(relativeToleranceAsUlp(-1.0, 100'000));
    EXPECT_REAL_EQ_TOL(expectedSimilarity, measure.similarity(comparedDensity.asConstView()), tolerance);
}

TEST(DensitySimilarityTest, CrossCorrelationGradientIsZeroWhenCorrelated)
{
    MultiDimArray<std::vector<float>, dynamicExtents3D> referenceDensity(30, 30, 30);
    std::iota(begin(referenceDensity), end(referenceDensity), -1);

    DensitySimilarityMeasure measure(DensitySimilarityMeasureMethod::crossCorrelation,
                                     referenceDensity.asConstView());

    MultiDimArray<std::vector<float>, dynamicExtents3D> comparedDensity(30, 30, 30);
    std::iota(begin(comparedDensity), end(comparedDensity), -2);

    // Need this conversion to ArrayRef, because Pointwise requires size()
    // member function not provided by basic_mdspan
    const basic_mdspan<const float, dynamicExtents3D> gradient =
            measure.gradient(comparedDensity.asConstView());
    ArrayRef<const float> gradientView(gradient.data(),
                                       gradient.data() + gradient.mapping().required_span_size());

    std::array<float, 27000> expectedSimilarityGradient = {};

    EXPECT_THAT(expectedSimilarityGradient, Pointwise(FloatEq(defaultFloatTolerance()), gradientView));
}

TEST(DensitySimilarityTest, CrossCorrelationGradientIsCorrect)
{
    MultiDimArray<std::vector<float>, dynamicExtents3D> referenceDensity(3, 3, 3);
    std::iota(begin(referenceDensity), end(referenceDensity), -1);

    DensitySimilarityMeasure measure(DensitySimilarityMeasureMethod::crossCorrelation,
                                     referenceDensity.asConstView());

    MultiDimArray<std::vector<float>, dynamicExtents3D> comparedDensity(3, 3, 3);
    std::iota(begin(comparedDensity), end(comparedDensity), -2);

    // some non-linear transformation, so that we break the correlation
    for (float& valueToCompare : comparedDensity)
    {
        valueToCompare *= valueToCompare;
    }

    // Need this conversion to ArrayRef, because Pointwise requires size()
    // member function not provided by basic_mdspan
    const basic_mdspan<const float, dynamicExtents3D> gradient =
            measure.gradient(comparedDensity.asConstView());
    ArrayRef<const float> gradientView(gradient.data(),
                                       gradient.data() + gradient.mapping().required_span_size());

    TestReferenceData    refData;
    TestReferenceChecker checker(refData.rootChecker());
    checker.setDefaultTolerance(defaultFloatTolerance());
    checker.checkSequence(gradientView.begin(), gradientView.end(), "cross-correlation-gradient");
}

TEST(DensitySimilarityTest, NormalizationCorrect)
{
    // normalize -22,-21,..,0,1,2,3,4 so that all positive elements sum to unity
    // expect -22/10., -21/10. ,...,1/10.,2/10.,3/10.,4/10. (1+2+3+4 = 10)
    std::array<float, 27> arrayToNormalize = {};
    std::iota(begin(arrayToNormalize), end(arrayToNormalize), -22);
    normalizeSumPositiveValuesToUnity(makeArrayRef(arrayToNormalize));

    std::array<float, 27> expectedNormalizsationResult = {};
    std::iota(std::begin(expectedNormalizsationResult), std::end(expectedNormalizsationResult), -22);

    std::transform(std::begin(expectedNormalizsationResult),
                   std::end(expectedNormalizsationResult),
                   std::begin(expectedNormalizsationResult),
                   [](float& c) { return c / 10.; });

    EXPECT_THAT(expectedNormalizsationResult,
                Pointwise(FloatEq(defaultFloatTolerance()), arrayToNormalize));
}

TEST(DensitySimilarityTest, NormalizationAllNonPositive)
{
    // normalize -50,...,-23 so that all positive elements sum to one,
    // should not do anything to the array
    std::array<float, 27> array = {};
    std::iota(begin(array), end(array), -50);

    const std::array<float, 27> expected = array;
    normalizeSumPositiveValuesToUnity(makeArrayRef(array));

    EXPECT_THAT(expected, Pointwise(FloatEq(defaultFloatTolerance()), array));
}

} // namespace test

} // namespace gmx
