/*
 * This file is part of the GROMACS molecular simulation package.
 *
 * Copyright 1991- The GROMACS Authors
 * and the project initiators Erik Lindahl, Berk Hess and David van der Spoel.
 * Consult the AUTHORS/COPYING files and https://www.gromacs.org for details.
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 */
/*! \brief
 * Implement routines for integrating a data set
 *
 * \author David van der Spoel <david.vanderspoel@icm.uu.se>
 */
#include "gmxpre.h"

#include "integrate.h"

#include <cmath>
#include <cstdio>

#include "gromacs/math/functions.h"
#include "gromacs/math/vec.h"
#include "gromacs/utility/fatalerror.h"

/*! \brief Integrate a function and printe the integral value. */
real print_and_integrate(FILE* fp, int n, real dt, const real c[], const real* fit, int nskip)
{
    real c0, sum;
    int  j;

    /* Use trapezoidal rule for calculating integral */
    sum = 0.0;
    for (j = 0; (j < n); j++)
    {
        c0 = c[j];
        if (fp && (nskip == 0 || j % nskip == 0))
        {
            fprintf(fp, "%10.3f  %10.5f\n", j * dt, c0);
        }
        if (j > 0)
        {
            sum += dt * (c0 + c[j - 1]);
        }
    }
    if (fp)
    {
        fprintf(fp, "&\n");
        if (fit)
        {
            for (j = 0; (j < n); j++)
            {
                if (nskip == 0 || j % nskip == 0)
                {
                    fprintf(fp, "%10.3f  %10.5f\n", j * dt, fit[j]);
                }
            }
            fprintf(fp, "&\n");
        }
    }
    return sum * 0.5;
}

/*! \brief Compute and return the integral of a function. */
real evaluate_integral(int n, const real x[], const real y[], const real dy[], real aver_start, real* stddev)
{
    double sum, sum_var, w;
    double sum_tail = 0, sum2_tail = 0;
    int    j, nsum_tail            = 0;

    /* Use trapezoidal rule for calculating integral */
    if (n <= 0)
    {
        gmx_fatal(FARGS, "Evaluating integral: n = %d (file %s, line %d)", n, __FILE__, __LINE__);
    }

    sum     = 0;
    sum_var = 0;
    for (j = 0; (j < n); j++)
    {
        w = 0;
        if (j > 0)
        {
            w += 0.5 * (x[j] - x[j - 1]);
        }
        if (j < n - 1)
        {
            w += 0.5 * (x[j + 1] - x[j]);
        }
        sum += w * y[j];
        if (dy)
        {
            /* Assume all errors are uncorrelated */
            sum_var += gmx::square(w * dy[j]);
        }

        if ((aver_start > 0) && (x[j] >= aver_start))
        {
            sum_tail += sum;
            sum2_tail += std::sqrt(sum_var);
            nsum_tail += 1;
        }
    }

    if (nsum_tail > 0)
    {
        sum = sum_tail / nsum_tail;
        /* This is a worst case estimate, assuming all stddev's are correlated. */
        *stddev = sum2_tail / nsum_tail;
    }
    else
    {
        *stddev = std::sqrt(sum_var);
    }

    return sum;
}
