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[gromacs.git] / src / gromacs / tables / cubicsplinetable.cpp

/*
 * This file is part of the GROMACS molecular simulation package.
 *
 * Copyright (c) 2016,2017,2018,2019, by the GROMACS development team, led by
 * Mark Abraham, David van der Spoel, Berk Hess, and Erik Lindahl,
 * and including many others, as listed in the AUTHORS file in the
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/*! \internal \file
 * \brief
 * Implements classes for cubic spline table functions
 *
 * \author Erik Lindahl <erik.lindahl@gmail.com>
 * \ingroup module_tables
 */
#include "gmxpre.h"

#include "cubicsplinetable.h"

#include <cmath>

#include <algorithm>
#include <functional>
#include <initializer_list>
#include <utility>
#include <vector>

#include "gromacs/tables/tableinput.h"
#include "gromacs/utility/alignedallocator.h"
#include "gromacs/utility/arrayref.h"
#include "gromacs/utility/exceptions.h"
#include "gromacs/utility/real.h"

#include "splineutil.h"

namespace gmx
{

namespace
{

/*! \brief Calculate table elements from function/derivative data
 *
 * \param functionValue0   Function value for the present table index
 * \param functionValue1   Function value for the next table index
 * \param derivativeValue0 Derivative value for the present table index
 * \param derivativeValue1 Derivative value for the next table index
 * \param spacing          Distance between table points
 * \param Y                Function value for table index
 * \param F                Component to multiply with offset eps
 * \param G                Component to multiply with eps^2
 * \param H                Component to multiply with eps^3
 */
void calculateCubicSplineCoefficients(double  functionValue0,
                                      double  functionValue1,
                                      double  derivativeValue0,
                                      double  derivativeValue1,
                                      double  spacing,
                                      double* Y,
                                      double* F,
                                      double* G,
                                      double* H)
{
    *Y = functionValue0;
    *F = spacing * derivativeValue0;
    *G = 3.0 * (functionValue1 - functionValue0) - spacing * (derivativeValue1 + 2.0 * derivativeValue0);
    *H = -2.0 * (functionValue1 - functionValue0) + spacing * (derivativeValue1 + derivativeValue0);
}

/*! \brief Perform cubic spline interpolation in interval from function/derivative
 *
 * \param      functionValue0               Function value for the present table index
 * \param      functionValue1               Function value for the next table index
 * \param      derivativeValue0             Derivative value for the present table index
 * \param      derivativeValue1             Derivative value for the next table index
 * \param      spacing                      Distance between table points
 * \param      eps                          Offset from lower table point for evaluation
 * \param[out] interpolatedFunctionValue    Output function value
 * \param[out] interpolatedDerivativeValue  Output derivative value
 */
void cubicSplineInterpolationFromFunctionAndDerivative(double  functionValue0,
                                                       double  functionValue1,
                                                       double  derivativeValue0,
                                                       double  derivativeValue1,
                                                       double  spacing,
                                                       double  eps,
                                                       double* interpolatedFunctionValue,
                                                       double* interpolatedDerivativeValue)
{
    double Y, F, G, H;

    calculateCubicSplineCoefficients(functionValue0, functionValue1, derivativeValue0,
                                     derivativeValue1, spacing, &Y, &F, &G, &H);

    double Fp = fma(fma(H, eps, G), eps, F);

    *interpolatedFunctionValue   = fma(Fp, eps, Y);
    *interpolatedDerivativeValue = fma(eps, fma(2.0 * eps, H, G), Fp) / spacing;
}


/*! \brief Construct the data for a single cubic table from analytical functions
 *
 * \param[in]  function             Analytical functiojn
 * \param[in]  derivative           Analytical derivative
 * \param[in]  range                Upper/lower limit of region to tabulate
 * \param[in]  spacing              Distance between table points
 * \param[out] yfghTableData        Output cubic spline table with Y,F,G,H entries
 */
void fillSingleCubicSplineTableData(const std::function<double(double)>& function,
                                    const std::function<double(double)>& derivative,
                                    const std::pair<real, real>&         range,
                                    double                               spacing,
                                    std::vector<real>*                   yfghTableData)
{
    int endIndex = static_cast<int>(range.second / spacing + 2);

    yfghTableData->resize(4 * endIndex);

    double      maxMagnitude      = 0.0001 * GMX_REAL_MAX;
    bool        functionIsInRange = true;
    std::size_t lastIndexInRange  = endIndex - 1;

    for (int i = endIndex - 1; i >= 0; i--)
    {
        double x = i * spacing;
        double tmpFunctionValue;
        double tmpDerivativeValue;
        double nextHigherFunction;
        double nextHigherDerivative;
        double Y, F, G, H;

        if (range.first > 0 && i == 0)
        {
            // Avoid x==0 if it is not in the range, since it can lead to
            // singularities even if the value for i==1 was within or required magnitude
            functionIsInRange = false;
        }

        if (functionIsInRange)
        {
            tmpFunctionValue     = function(x);
            tmpDerivativeValue   = derivative(x);
            nextHigherFunction   = ((i + 1) < endIndex) ? function(x + spacing) : 0.0;
            nextHigherDerivative = ((i + 1) < endIndex) ? derivative(x + spacing) : 0.0;

            if (std::abs(tmpFunctionValue) > maxMagnitude || std::abs(tmpDerivativeValue) > maxMagnitude)
            {
                functionIsInRange = false; // Once this happens, it never resets to true again
            }
        }

        if (functionIsInRange)
        {
            calculateCubicSplineCoefficients(tmpFunctionValue, nextHigherFunction, tmpDerivativeValue,
                                             nextHigherDerivative, spacing, &Y, &F, &G, &H);
            lastIndexInRange--;
        }
        else
        {
            double lastIndexY = (*yfghTableData)[4 * lastIndexInRange];
            double lastIndexF = (*yfghTableData)[4 * lastIndexInRange + 1];

            Y = lastIndexY + lastIndexF * (i - lastIndexInRange);
            F = lastIndexF;
            G = 0.0;
            H = 0.0;
        }

        (*yfghTableData)[4 * i]     = Y;
        (*yfghTableData)[4 * i + 1] = F;
        (*yfghTableData)[4 * i + 2] = G;
        (*yfghTableData)[4 * i + 3] = H;
    }
}


/*! \brief Construct the data for a single cubic table from vector data
 *
 * \param[in]  function             Input vector with function data
 * \param[in]  derivative           Input vector with derivative data
 * \param[in]  inputSpacing         Distance between points in input vectors
 * \param[in]  range                Upper/lower limit of region to tabulate
 * \param[in]  spacing              Distance between table points
 * \param[out] yfghTableData        Output cubic spline table with Y,F,G,H entries
 */
void fillSingleCubicSplineTableData(ArrayRef<const double>       function,
                                    ArrayRef<const double>       derivative,
                                    double                       inputSpacing,
                                    const std::pair<real, real>& range,
                                    double                       spacing,
                                    std::vector<real>*           yfghTableData)
{
    int endIndex = static_cast<int>(range.second / spacing + 2);

    std::vector<double> tmpFunction(endIndex);
    std::vector<double> tmpDerivative(endIndex);

    double      maxMagnitude      = 0.0001 * GMX_REAL_MAX;
    bool        functionIsInRange = true;
    std::size_t lastIndexInRange  = endIndex - 1;

    // Interpolate function and derivative values in positions needed for output
    for (int i = endIndex - 1; i >= 0; i--)
    {
        double x     = i * spacing;
        double xtab  = x / inputSpacing;
        int    index = static_cast<int>(xtab);
        double eps   = xtab - index;

        if (range.first > 0 && i == 0)
        {
            // Avoid x==0 if it is not in the range, since it can lead to
            // singularities even if the value for i==1 was within or required magnitude
            functionIsInRange = false;
        }

        if (functionIsInRange
            && (std::abs(function[index]) > maxMagnitude || std::abs(derivative[index]) > maxMagnitude))
        {
            functionIsInRange = false; // Once this happens, it never resets to true again
        }

        if (functionIsInRange)
        {
            cubicSplineInterpolationFromFunctionAndDerivative(
                    function[index], function[index + 1], derivative[index], derivative[index + 1],
                    inputSpacing, eps, &(tmpFunction[i]), &(tmpDerivative[i]));
            lastIndexInRange--;
        }
        else
        {
            double lastIndexFunction   = tmpFunction[lastIndexInRange];
            double lastIndexDerivative = tmpDerivative[lastIndexInRange];
            tmpFunction[i] = lastIndexFunction + lastIndexDerivative * (i - lastIndexInRange) * spacing;
            tmpDerivative[i] = lastIndexDerivative;
        }
    }

    yfghTableData->resize(4 * endIndex);

    for (int i = 0; i < endIndex; i++)
    {
        double Y, F, G, H;

        double nextFunction   = ((i + 1) < endIndex) ? tmpFunction[i + 1] : 0.0;
        double nextDerivative = ((i + 1) < endIndex) ? tmpDerivative[i + 1] : 0.0;

        calculateCubicSplineCoefficients(tmpFunction[i], nextFunction, tmpDerivative[i],
                                         nextDerivative, spacing, &Y, &F, &G, &H);
        (*yfghTableData)[4 * i]     = Y;
        (*yfghTableData)[4 * i + 1] = F;
        (*yfghTableData)[4 * i + 2] = G;
        (*yfghTableData)[4 * i + 3] = H;
    }
}

} // namespace


#if GMX_DOUBLE
const real CubicSplineTable::defaultTolerance = 1e-10;
#else
const real CubicSplineTable::defaultTolerance = 10.0 * GMX_FLOAT_EPS;
#endif

CubicSplineTable::CubicSplineTable(std::initializer_list<AnalyticalSplineTableInput> analyticalInputList,
                                   const std::pair<real, real>&                      range,
                                   real                                              tolerance) :
    numFuncInTable_(analyticalInputList.size()),
    range_(range)
{
    // Sanity check on input values
    if (range_.first < 0.0 || (range_.second - range_.first) < 0.001)
    {
        GMX_THROW(InvalidInputError(
                "Range to tabulate cannot include negative values and must span at least 0.001"));
    }

    if (tolerance < GMX_REAL_EPS)
    {
        GMX_THROW(ToleranceError("Table tolerance cannot be smaller than GMX_REAL_EPS"));
    }

    double minQuotient = GMX_REAL_MAX;

    // loop over all functions to find smallest spacing
    for (const auto& thisFuncInput : analyticalInputList)
    {
        try
        {
            internal::throwUnlessDerivativeIsConsistentWithFunction(
                    thisFuncInput.function, thisFuncInput.derivative, range_);
        }
        catch (gmx::GromacsException& ex)
        {
            ex.prependContext("Error generating cubic spline table for function '"
                              + thisFuncInput.desc + "'");
            throw;
        }
        // Calculate the required table spacing h. The error we make with a third order polynomial
        // (second order for derivative) will be described by the fourth-derivative correction term.
        //
        // This means we can compute the required spacing as h =
        // 0.5*cbrt(72*sqrt(3)*tolerance**min(f'/f'''')), where f'/f'''' is the first and fourth
        // derivative of the function, respectively. Since we already have an analytical form of the
        // derivative, we reduce the numerical errors by calculating the quotient of the function
        // and third derivative of the input-derivative-analytical function instead.

        double thisMinQuotient = internal::findSmallestQuotientOfFunctionAndThirdDerivative(
                thisFuncInput.derivative, range_);

        minQuotient = std::min(minQuotient, thisMinQuotient);
    }

    double spacing = 0.5 * std::cbrt(72.0 * std::sqrt(3.0) * tolerance * minQuotient);

    tableScale_ = 1.0 / spacing;

    if (range_.second * tableScale_ > 2e6)
    {
        GMX_THROW(
                ToleranceError("Over a million points would be required for table; decrease range "
                               "or increase tolerance"));
    }

    // Loop over all tables again.
    // Here we create the actual table for each function, and then
    // combine them into a multiplexed table function.
    std::size_t funcIndex = 0;

    for (const auto& thisFuncInput : analyticalInputList)
    {
        try
        {
            std::vector<real> tmpYfghTableData;

            fillSingleCubicSplineTableData(thisFuncInput.function, thisFuncInput.derivative, range_,
                                           spacing, &tmpYfghTableData);

            internal::fillMultiplexedTableData(tmpYfghTableData, &yfghMultiTableData_, 4,
                                               numFuncInTable_, funcIndex);

            funcIndex++;
        }
        catch (gmx::GromacsException& ex)
        {
            ex.prependContext("Error generating cubic spline table for function '"
                              + thisFuncInput.desc + "'");
            throw;
        }
    }
}


CubicSplineTable::CubicSplineTable(std::initializer_list<NumericalSplineTableInput> numericalInputList,
                                   const std::pair<real, real>&                     range,
                                   real                                             tolerance) :
    numFuncInTable_(numericalInputList.size()),
    range_(range)
{
    // Sanity check on input values
    if (range.first < 0.0 || (range.second - range.first) < 0.001)
    {
        GMX_THROW(InvalidInputError(
                "Range to tabulate cannot include negative values and must span at least 0.001"));
    }

    if (tolerance < GMX_REAL_EPS)
    {
        GMX_THROW(ToleranceError("Table tolerance cannot be smaller than GMX_REAL_EPS"));
    }

    double minQuotient = GMX_REAL_MAX;

    // loop over all functions to find smallest spacing
    for (auto thisFuncInput : numericalInputList)
    {
        try
        {
            // We do not yet know what the margin is, but we need to test that we at least cover
            // the requested range before starting to calculate derivatives
            if (thisFuncInput.function.size() < range_.second / thisFuncInput.spacing + 1)
            {
                GMX_THROW(
                        InconsistentInputError("Table input vectors must cover requested range, "
                                               "and a margin beyond the upper endpoint"));
            }

            if (thisFuncInput.function.size() != thisFuncInput.derivative.size())
            {
                GMX_THROW(InconsistentInputError(
                        "Function and derivative vectors have different lengths"));
            }

            internal::throwUnlessDerivativeIsConsistentWithFunction(
                    thisFuncInput.function, thisFuncInput.derivative, thisFuncInput.spacing, range_);
        }
        catch (gmx::GromacsException& ex)
        {
            ex.prependContext("Error generating cubic spline table for function '"
                              + thisFuncInput.desc + "'");
            throw;
        }
        // Calculate the required table spacing h. The error we make with linear interpolation
        // of the derivative will be described by the third-derivative correction term.
        // This means we can compute the required spacing as h = sqrt(12*tolerance*min(f'/f''')),
        // where f'/f''' is the first and third derivative of the function, respectively.

        double thisMinQuotient = internal::findSmallestQuotientOfFunctionAndThirdDerivative(
                thisFuncInput.derivative, thisFuncInput.spacing, range_);

        minQuotient = std::min(minQuotient, thisMinQuotient);
    }

    double spacing = std::cbrt(72.0 * std::sqrt(3.0) * tolerance * minQuotient);

    tableScale_ = 1.0 / spacing;

    if (range_.second * tableScale_ > 1e6)
    {
        GMX_THROW(
                ToleranceError("Requested tolerance would require over a million points in table"));
    }

    // Loop over all tables again.
    // Here we create the actual table for each function, and then
    // combine them into a multiplexed table function.
    std::size_t funcIndex = 0;

    for (auto thisFuncInput : numericalInputList)
    {
        try
        {
            if (spacing < thisFuncInput.spacing)
            {
                GMX_THROW(
                        ToleranceError("Input vector spacing cannot achieve tolerance requested"));
            }

            std::vector<real> tmpYfghTableData;

            fillSingleCubicSplineTableData(thisFuncInput.function, thisFuncInput.derivative,
                                           thisFuncInput.spacing, range, spacing, &tmpYfghTableData);

            internal::fillMultiplexedTableData(tmpYfghTableData, &yfghMultiTableData_, 4,
                                               numFuncInTable_, funcIndex);

            funcIndex++;
        }
        catch (gmx::GromacsException& ex)
        {
            ex.prependContext("Error generating cubic spline table for function '"
                              + thisFuncInput.desc + "'");
            throw;
        }
    }
}

} // namespace gmx