nelder_mead_simplex.h

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/*
  This file is part of darktable,
  Copyright (C) 2016 Tobias Ellinghaus.
  Copyright (C) 2016 Ulrich Pegelow.
  Copyright (C) 2017 luzpaz.
  Copyright (C) 2020 Hubert Kowalski.
  Copyright (C) 2020 Pascal Obry.
  Copyright (C) 2022 Martin Bařinka.
  Copyright (C) 2023, 2025 Aurélien PIERRE.
  
  darktable is free software: you can redistribute it and/or modify
  it under the terms of the GNU General Public License as published by
  the Free Software Foundation, either version 3 of the License, or
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  MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
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*/
 
/* For parameter optimization we are using the Nelder-Mead simplex method
 * implemented by Michael F. Hutt.
 * Changes versus the original code:
 *      do not include "nmsimplex.h" (not needed)
 *      renamed configuration variables to NMS_*
 *      add additional argument to objfun for arbitrary parameters
 *      simplex() returns number of used iterations instead of min value
 *      maximum number of iterations as function parameter
 *      make interface function simplex() static  *      initialize i and j to avoid compiler warnings
 *      comment out printing of status inormation
 *      reformat according to darktable's clang standards
 */
 
/*==================================================================================
 * begin nmsimplex code downloaded from http://www.mikehutt.com/neldermead.html
 * on February 6, 2016
 *==================================================================================*/
/*
 * Program: nmsimplex.c
 * Author : Michael F. Hutt
 * http://www.mikehutt.com
 * 11/3/97
 *
 * An implementation of the Nelder-Mead simplex method.
 *
 * Copyright (c) 1997-2011 <Michael F. Hutt>
 *
 * Permission is hereby granted, free of charge, to any person obtaining
 * a copy of this software and associated documentation files (the
 * "Software"), to deal in the Software without restriction, including
 * without limitation the rights to use, copy, modify, merge, publish,
 * distribute, sublicense, and/or sell copies of the Software, and to
 * permit persons to whom the Software is furnished to do so, subject to
 * the following conditions:
 *
 * The above copyright notice and this permission notice shall be
 * included in all copies or substantial portions of the Software.
 *
 * THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND,
 * EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF
 * MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND
 * NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE
 * LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION
 * OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION
 * WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.
 *
 *
 * Jan. 6, 1999
 * Modified to conform to the algorithm presented
 * in Margaret H. Wright's paper on Direct Search Methods.
 *
 * Jul. 23, 2007
 * Fixed memory leak.
 *
 * Mar. 1, 2011
 * Added constraints.
 */
 
#ifndef DT_MATH_NELDER_MEAD_SIMPLEX_H
#define DT_MATH_NELDER_MEAD_SIMPLEX_H
 
// Nelder-Mead reflection / contraction / expansion coefficients (the algorithm's standard
// constants). Guarded so a caller may override them before including this header.
#ifndef NMS_ALPHA
#define NMS_ALPHA 1.0
#endif
#ifndef NMS_BETA
#define NMS_BETA 0.5
#endif
#ifndef NMS_GAMMA
#define NMS_GAMMA 2.0
#endif
 
// Nelder-Mead simplex minimizer of objfunc over n parameters, starting from start[] (overwritten
// with the best point). EPSILON = convergence threshold, scale = initial simplex size, maxiter =
// iteration cap, constrain = optional projection of a trial point onto the feasible set (may be
// NULL), params = opaque pointer forwarded to objfunc/constrain. Returns the iteration count.
static int simplex(double (*objfunc)(double[], void *params), double start[], int n, double EPSILON, double scale,
                   int maxiter, void (*constrain)(double[], int n), void *params)
{
 
  int vs; /* vertex with smallest value */
  int vh; /* vertex with next smallest value */
  int vg; /* vertex with largest value */
 
  int i = 0, j = 0, m, row;
  int itr; /* track the number of iterations */
 
  double **v;    /* holds vertices of simplex */
  double pn, qn; /* values used to create initial simplex */
  double *f;     /* value of function at each vertex */
  double fr;     /* value of function at reflection point */
  double fe;     /* value of function at expansion point */
  double fc;     /* value of function at contraction point */
  double *vr;    /* reflection - coordinates */
  double *ve;    /* expansion - coordinates */
  double *vc;    /* contraction - coordinates */
  double *vm;    /* centroid - coordinates */
  //double min;
 
  double fsum, favg, s, cent;
 
  /* dynamically allocate arrays */
 
  /* allocate the rows of the arrays */
  v = (double **)malloc(sizeof(double *) * (n + 1));
  f = (double *)malloc(sizeof(double) * (n + 1));
  vr = (double *)malloc(sizeof(double) * n);
  ve = (double *)malloc(sizeof(double) * n);
  vc = (double *)malloc(sizeof(double) * n);
  vm = (double *)malloc(sizeof(double) * n);
 
  /* allocate the columns of the arrays */
  for(i = 0; i <= n; i++)
  {
    v[i] = (double *)malloc(sizeof(double) * n);
  }
 
  /* create the initial simplex */
  /* assume one of the vertices is 0,0 */
 
  pn = scale * (sqrt(n + 1) - 1 + n) / (n * sqrt(2));
  qn = scale * (sqrt(n + 1) - 1) / (n * sqrt(2));
 
  for(i = 0; i < n; i++)
  {
    v[0][i] = start[i];
  }
 
  for(i = 1; i <= n; i++)
  {
    for(j = 0; j < n; j++)
    {
      if(i - 1 == j)
      {
        v[i][j] = pn + start[j];
      }
      else
      {
        v[i][j] = qn + start[j];
      }
    }
  }
 
  if(!IS_NULL_PTR(constrain))
  {
    constrain(v[j], n);
  }
  /* find the initial function values */
  for(j = 0; j <= n; j++)
  {
    f[j] = objfunc(v[j], params);
  }
 
#if 0
  /* print out the initial values */
  printf("Initial Values\n");
  for(j = 0; j <= n; j++)
  {
    for(i = 0; i < n; i++)
    {
      printf("%f %f\n", v[j][i], f[j]);
    }
  }
#endif
 
  /* begin the main loop of the minimization */
  for(itr = 1; itr <= maxiter; itr++)
  {
    /* find the index of the largest value */
    vg = 0;
    for(j = 0; j <= n; j++)
    {
      if(f[j] > f[vg])
      {
        vg = j;
      }
    }
 
    /* find the index of the smallest value */
    vs = 0;
    for(j = 0; j <= n; j++)
    {
      if(f[j] < f[vs])
      {
        vs = j;
      }
    }
 
    /* find the index of the second largest value */
    vh = vs;
    for(j = 0; j <= n; j++)
    {
      if(f[j] > f[vh] && f[j] < f[vg])
      {
        vh = j;
      }
    }
 
    /* calculate the centroid */
    for(j = 0; j <= n - 1; j++)
    {
      cent = 0.0;
      for(m = 0; m <= n; m++)
      {
        if(m != vg)
        {
          cent += v[m][j];
        }
      }
      vm[j] = cent / n;
    }
 
    /* reflect vg to new vertex vr */
    for(j = 0; j <= n - 1; j++)
    {
      /*vr[j] = (1+NMS_ALPHA)*vm[j] - NMS_ALPHA*v[vg][j];*/
      vr[j] = vm[j] + NMS_ALPHA * (vm[j] - v[vg][j]);
    }
    if(!IS_NULL_PTR(constrain))
    {
      constrain(vr, n);
    }
    fr = objfunc(vr, params);
 
    if(fr < f[vh] && fr >= f[vs])
    {
      for(j = 0; j <= n - 1; j++)
      {
        v[vg][j] = vr[j];
      }
      f[vg] = fr;
    }
 
    /* investigate a step further in this direction */
    if(fr < f[vs])
    {
      for(j = 0; j <= n - 1; j++)
      {
        /*ve[j] = NMS_GAMMA*vr[j] + (1-NMS_GAMMA)*vm[j];*/
        ve[j] = vm[j] + NMS_GAMMA * (vr[j] - vm[j]);
      }
      if(!IS_NULL_PTR(constrain))
      {
        constrain(ve, n);
      }
      fe = objfunc(ve, params);
 
      /* by making fe < fr as opposed to fe < f[vs],
         Rosenbrocks function takes 63 iterations as opposed
         to 64 when using double variables. */
 
      if(fe < fr)
      {
        for(j = 0; j <= n - 1; j++)
        {
          v[vg][j] = ve[j];
        }
        f[vg] = fe;
      }
      else
      {
        for(j = 0; j <= n - 1; j++)
        {
          v[vg][j] = vr[j];
        }
        f[vg] = fr;
      }
    }
 
    /* check to see if a contraction is necessary */
    if(fr >= f[vh])
    {
      if(fr < f[vg] && fr >= f[vh])
      {
        /* perform outside contraction */
        for(j = 0; j <= n - 1; j++)
        {
          /*vc[j] = NMS_BETA*v[vg][j] + (1-NMS_BETA)*vm[j];*/
          vc[j] = vm[j] + NMS_BETA * (vr[j] - vm[j]);
        }
        if(!IS_NULL_PTR(constrain))
        {
          constrain(vc, n);
        }
        fc = objfunc(vc, params);
      }
      else
      {
        /* perform inside contraction */
        for(j = 0; j <= n - 1; j++)
        {
          /*vc[j] = NMS_BETA*v[vg][j] + (1-NMS_BETA)*vm[j];*/
          vc[j] = vm[j] - NMS_BETA * (vm[j] - v[vg][j]);
        }
        if(!IS_NULL_PTR(constrain))
        {
          constrain(vc, n);
        }
        fc = objfunc(vc, params);
      }
 
 
      if(fc < f[vg])
      {
        for(j = 0; j <= n - 1; j++)
        {
          v[vg][j] = vc[j];
        }
        f[vg] = fc;
      }
      /* at this point the contraction is not successful,
         we must halve the distance from vs to all the
         vertices of the simplex and then continue.
         10/31/97 - modified to account for ALL vertices.
      */
      else
      {
        for(row = 0; row <= n; row++)
        {
          if(row != vs)
          {
            for(j = 0; j <= n - 1; j++)
            {
              v[row][j] = v[vs][j] + (v[row][j] - v[vs][j]) / 2.0;
            }
          }
        }
        if(!IS_NULL_PTR(constrain))
        {
          constrain(v[vg], n);
        }
        f[vg] = objfunc(v[vg], params);
        if(!IS_NULL_PTR(constrain))
        {
          constrain(v[vh], n);
        }
        f[vh] = objfunc(v[vh], params);
      }
    }
#if 0
    /* print out the value at each iteration */
    printf("Iteration %d\n", itr);
    for(j = 0; j <= n; j++)
    {
      for(i = 0; i < n; i++)
      {
        printf("%f %f\n", v[j][i], f[j]);
      }
    }
#endif
    /* test for convergence */
    fsum = 0.0;
    for(j = 0; j <= n; j++)
    {
      fsum += f[j];
    }
    favg = fsum / (n + 1);
    s = 0.0;
    for(j = 0; j <= n; j++)
    {
      s += pow((f[j] - favg), 2.0) / (n);
    }
    s = sqrt(s);
    if(s < EPSILON) break;
  }
  /* end main loop of the minimization */
 
  /* find the index of the smallest value */
  vs = 0;
  for(j = 0; j <= n; j++)
  {
    if(f[j] < f[vs])
    {
      vs = j;
    }
  }
#if 0
  printf("The minimum was found at\n");
  for(j = 0; j < n; j++)
  {
    printf("%e\n", v[vs][j]);
    start[j] = v[vs][j];
  }
  double min = objfunc(v[vs], params);
  printf("The minimum value is %f\n", min);
  printf("%d Iterations through program\n", itr);
#else
  for(j = 0; j < n; j++)
  {
    start[j] = v[vs][j];
  }
#endif
  dt_free(f);
  dt_free(vr);
  dt_free(ve);
  dt_free(vc);
  dt_free(vm);
  for(i = 0; i <= n; i++)
  {
    dt_free(v[i]);
  }
  dt_free(v);
  return itr;
}
 
/*==================================================================================
 * end of nmsimplex code
 *==================================================================================*/
 
#endif // DT_MATH_NELDER_MEAD_SIMPLEX_H
 
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