path: root/src/database/KolmogorovSmirnovDist.c

// SPDX-License-Identifier: GPL-3.0

/********************************************************************
 *
 * File:          KolmogorovSmirnovDist.c
 * Environment:   ISO C99 or ANSI C89
 * Author:        Richard Simard
 * Organization:  DIRO, Université de Montréal
 * Date:          1 February 2012
 * Version        1.1

 * Copyright 1 march 2010 by Université de Montréal,
                             Richard Simard and Pierre L'Ecuyer
 =====================================================================

    This program 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, version 3 of the License.

    This program is distributed in the hope that it will be useful,
    but WITHOUT ANY WARRANTY; without even the implied warranty of
    MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
    GNU General Public License for more details.

    You should have received a copy of the GNU General Public License
    along with this program.  If not, see <http://www.gnu.org/licenses/>.

 =====================================================================*/

#include "KolmogorovSmirnovDist.h"
#include <math.h>
#include <stdlib.h>

#define num_Pi     3.14159265358979323846 /* PI */
#define num_Ln2    0.69314718055994530941 /* log(2) */

/* For x close to 0 or 1, we use the exact formulae of Ruben-Gambino in all
   cases. For n <= NEXACT, we use exact algorithms: the Durbin matrix and
   the Pomeranz algorithms. For n > NEXACT, we use asymptotic methods
   except for x close to 0 where we still use the method of Durbin
   for n <= NKOLMO. For n > NKOLMO, we use asymptotic methods only and
   so the precision is less for x close to 0.
   We could increase the limit NKOLMO to 10^6 to get better precision
   for x close to 0, but at the price of a slower speed. */
#define NEXACT 500
#define NKOLMO 100000

/* The Durbin matrix algorithm for the Kolmogorov-Smirnov distribution */
static double DurbinMatrix (int n, double d);


/*========================================================================*/
#if 0

/* For ANSI C89 only, not for ISO C99 */
#define MAXI 50
#define EPSILON 1.0e-15

double log1p (double x)
{
   /* returns a value equivalent to log(1 + x) accurate also for small x. */
   if (fabs (x) > 0.1) {
      return log (1.0 + x);
   } else {
      double term = x;
      double sum = x;
      int s = 2;
      while ((fabs (term) > EPSILON * fabs (sum)) && (s < MAXI)) {
         term *= -x;
         sum += term / s;
         s++;
      }
      return sum;
   }
}

#undef MAXI
#undef EPSILON

#endif

/*========================================================================*/
#define MFACT 30

/* The natural logarithm of factorial n! for  0 <= n <= MFACT */
static double LnFactorial[MFACT + 1] = {
   0.,
   0.,
   0.6931471805599453,
   1.791759469228055,
   3.178053830347946,
   4.787491742782046,
   6.579251212010101,
   8.525161361065415,
   10.60460290274525,
   12.80182748008147,
   15.10441257307552,
   17.50230784587389,
   19.98721449566188,
   22.55216385312342,
   25.19122118273868,
   27.89927138384088,
   30.67186010608066,
   33.50507345013688,
   36.39544520803305,
   39.33988418719949,
   42.33561646075348,
   45.3801388984769,
   48.47118135183522,
   51.60667556776437,
   54.7847293981123,
   58.00360522298051,
   61.26170176100199,
   64.55753862700632,
   67.88974313718154,
   71.257038967168,
   74.65823634883016
};

/*------------------------------------------------------------------------*/

static double getLogFactorial (int n)
{
   /* Returns the natural logarithm of factorial n! */
   if (n <= MFACT) {
      return LnFactorial[n];

   } else {
      double x = (double) (n + 1);
      double y = 1.0 / (x * x);
      double z = ((-(5.95238095238E-4 * y) + 7.936500793651E-4) * y -
         2.7777777777778E-3) * y + 8.3333333333333E-2;
      z = ((x - 0.5) * log (x) - x) + 9.1893853320467E-1 + z / x;
      return z;
   }
}

/*------------------------------------------------------------------------*/

static double rapfac (int n)
{
   /* Computes n! / n^n */
   int i;
   double res = 1.0 / n;
   for (i = 2; i <= n; i++) {
      res *= (double) i / n;
   }
   return res;
}


/*========================================================================*/

static double **CreateMatrixD (int N, int M)
{
   int i;
   double **T2;

   T2 = (double **) malloc (N * sizeof (double *));
   T2[0] = (double *) malloc ((size_t) N * M * sizeof (double));
   for (i = 1; i < N; i++)
      T2[i] = T2[0] + i * M;
   return T2;
}


static void DeleteMatrixD (double **T)
{
   free (T[0]);
   free (T);
}


/*========================================================================*/

static double KSPlusbarAsymp (int n, double x)
{
   /* Compute the probability of the KS+ distribution using an asymptotic
      formula */
   double t = (6.0 * n * x + 1);
   double z = t * t / (18.0 * n);
   double v = 1.0 - (2.0 * z * z - 4.0 * z - 1.0) / (18.0 * n);
   if (v <= 0.0)
      return 0.0;
   v = v * exp (-z);
   if (v >= 1.0)
      return 1.0;
   return v;
}


/*-------------------------------------------------------------------------*/

static double KSPlusbarUpper (int n, double x)
{
   /* Compute the probability of the KS+ distribution in the upper tail using
      Smirnov's stable formula */
   const double EPSILON = 1.0E-12;
   double q;
   double Sum = 0.0;
   double term;
   double t;
   double LogCom;
   double LOGJMAX;
   int j;
   int jdiv;
   int jmax = (int) (n * (1.0 - x));

   if (n > 200000)
      return KSPlusbarAsymp (n, x);

   /* Avoid log(0) for j = jmax and q ~ 1.0 */
   if ((1.0 - x - (double) jmax / n) <= 0.0)
      jmax--;

   if (n > 3000)
      jdiv = 2;
   else
      jdiv = 3;

   j = jmax / jdiv + 1;
   LogCom = getLogFactorial (n) - getLogFactorial (j) -
            getLogFactorial (n - j);
   LOGJMAX = LogCom;

   while (j <= jmax) {
      q = (double) j / n + x;
      term = LogCom + (j - 1) * log (q) + (n - j) * log1p (-q);
      t = exp (term);
      Sum += t;
      LogCom += log ((double) (n - j) / (j + 1));
      if (t <= Sum * EPSILON)
         break;
      j++;
   }

   j = jmax / jdiv;
   LogCom = LOGJMAX + log ((double) (j + 1) / (n - j));

   while (j > 0) {
      q = (double) j / n + x;
      term = LogCom + (j - 1) * log (q) + (n - j) * log1p (-q);
      t = exp (term);
      Sum += t;
      LogCom += log ((double) j / (n - j + 1));
      if (t <= Sum * EPSILON)
         break;
      j--;
   }

   Sum *= x;
   /* add the term j = 0 */
   Sum += exp (n * log1p (-x));
   return Sum;
}


/*========================================================================*/

static double Pelz (int n, double x)
{
   /* Approximating the Lower Tail-Areas of the Kolmogorov-Smirnov One-Sample
      Statistic,
      Wolfgang Pelz and I. J. Good,
      Journal of the Royal Statistical Society, Series B.
      Vol. 38, No. 2 (1976), pp. 152-156
   */

   const int JMAX = 20;
   const double EPS = 1.0e-10;
   const double C = 2.506628274631001;         /* sqrt(2*Pi) */
   const double C2 = 1.2533141373155001;       /* sqrt(Pi/2) */
   const double PI2 = num_Pi * num_Pi;
   const double PI4 = PI2 * PI2;
   const double RACN = sqrt ((double) n);
   const double z = RACN * x;
   const double z2 = z * z;
   const double z4 = z2 * z2;
   const double z6 = z4 * z2;
   const double w = PI2 / (2.0 * z * z);
   double ti, term, tom;
   double sum;
   int j;

   term = 1;
   j = 0;
   sum = 0;
   while (j <= JMAX && term > EPS * sum) {
      ti = j + 0.5;
      term = exp (-ti * ti * w);
      sum += term;
      j++;
   }
   sum *= C / z;

   term = 1;
   tom = 0;
   j = 0;
   while (j <= JMAX && fabs (term) > EPS * fabs (tom)) {
      ti = j + 0.5;
      term = (PI2 * ti * ti - z2) * exp (-ti * ti * w);
      tom += term;
      j++;
   }
   sum += tom * C2 / (RACN * 3.0 * z4);

   term = 1;
   tom = 0;
   j = 0;
   while (j <= JMAX && fabs (term) > EPS * fabs (tom)) {
      ti = j + 0.5;
      term = 6 * z6 + 2 * z4 + PI2 * (2 * z4 - 5 * z2) * ti * ti +
         PI4 * (1 - 2 * z2) * ti * ti * ti * ti;
      term *= exp (-ti * ti * w);
      tom += term;
      j++;
   }
   sum += tom * C2 / (n * 36.0 * z * z6);

   term = 1;
   tom = 0;
   j = 1;
   while (j <= JMAX && term > EPS * tom) {
      ti = j;
      term = PI2 * ti * ti * exp (-ti * ti * w);
      tom += term;
      j++;
   }
   sum -= tom * C2 / (n * 18.0 * z * z2);

   term = 1;
   tom = 0;
   j = 0;
   while (j <= JMAX && fabs (term) > EPS * fabs (tom)) {
      ti = j + 0.5;
      ti = ti * ti;
      term = -30 * z6 - 90 * z6 * z2 + PI2 * (135 * z4 - 96 * z6) * ti +
         PI4 * (212 * z4 - 60 * z2) * ti * ti + PI2 * PI4 * ti * ti * ti * (5 -
         30 * z2);
      term *= exp (-ti * w);
      tom += term;
      j++;
   }
   sum += tom * C2 / (RACN * n * 3240.0 * z4 * z6);

   term = 1;
   tom = 0;
   j = 1;
   while (j <= JMAX && fabs (term) > EPS * fabs (tom)) {
      ti = j * j;
      term = (3 * PI2 * ti * z2 - PI4 * ti * ti) * exp (-ti * w);
      tom += term;
      j++;
   }
   sum += tom * C2 / (RACN * n * 108.0 * z6);

   return sum;
}


/*=========================================================================*/

static void CalcFloorCeil (
   int n,                         /* sample size */
   double t,                      /* = nx */
   double *A,                     /* A_i */
   double *Atflo,                 /* floor (A_i - t) */
   double *Atcei                  /* ceiling (A_i + t) */
   )
{
   /* Precompute A_i, floors, and ceilings for limits of sums in the Pomeranz
      algorithm */
   int i;
   int ell = (int) t;             /* floor (t) */
   double z = t - ell;            /* t - floor (t) */
   double w = ceil (t) - t;

   if (z > 0.5) {
      for (i = 2; i <= 2 * n + 2; i += 2)
         Atflo[i] = i / 2 - 2 - ell;
      for (i = 1; i <= 2 * n + 2; i += 2)
         Atflo[i] = i / 2 - 1 - ell;

      for (i = 2; i <= 2 * n + 2; i += 2)
         Atcei[i] = i / 2 + ell;
      for (i = 1; i <= 2 * n + 2; i += 2)
         Atcei[i] = i / 2 + 1 + ell;

   } else if (z > 0.0) {
      for (i = 1; i <= 2 * n + 2; i++)
         Atflo[i] = i / 2 - 1 - ell;

      for (i = 2; i <= 2 * n + 2; i++)
         Atcei[i] = i / 2 + ell;
      Atcei[1] = 1 + ell;

   } else {                       /* z == 0 */
      for (i = 2; i <= 2 * n + 2; i += 2)
         Atflo[i] = i / 2 - 1 - ell;
      for (i = 1; i <= 2 * n + 2; i += 2)
         Atflo[i] = i / 2 - ell;

      for (i = 2; i <= 2 * n + 2; i += 2)
         Atcei[i] = i / 2 - 1 + ell;
      for (i = 1; i <= 2 * n + 2; i += 2)
         Atcei[i] = i / 2 + ell;
   }

   if (w < z)
      z = w;
   A[0] = A[1] = 0;
   A[2] = z;
   A[3] = 1 - A[2];
   for (i = 4; i <= 2 * n + 1; i++)
      A[i] = A[i - 2] + 1;
   A[2 * n + 2] = n;
}


/*========================================================================*/

static double Pomeranz (int n, double x)
{
   /* The Pomeranz algorithm to compute the KS distribution */
   const double EPS = 1.0e-15;
   const int ENO = 350;
   const double RENO = ldexp (1.0, ENO); /* for renormalization of V */
   int coreno;                    /* counter: how many renormalizations */
   const double t = n * x;
   double w, sum, minsum;
   int i, j, k, s;
   int r1, r2;                    /* Indices i and i-1 for V[i][] */
   int jlow, jup, klow, kup, kup0;
   double *A;
   double *Atflo;
   double *Atcei;
   double **V;
   double **H;                    /* = pow(w, j) / Factorial(j) */

   A = (double *) calloc ((size_t) (2 * n + 3), sizeof (double));
   Atflo = (double *) calloc ((size_t) (2 * n + 3), sizeof (double));
   Atcei = (double *) calloc ((size_t) (2 * n + 3), sizeof (double));
   V = (double **) CreateMatrixD (2, n + 2);
   H = (double **) CreateMatrixD (4, n + 2);

   CalcFloorCeil (n, t, A, Atflo, Atcei);

   for (j = 1; j <= n + 1; j++)
      V[0][j] = 0;
   for (j = 2; j <= n + 1; j++)
      V[1][j] = 0;
   V[1][1] = RENO;
   coreno = 1;

   /* Precompute H[][] = (A[j] - A[j-1]^k / k! for speed */
   H[0][0] = 1;
   w = 2.0 * A[2] / n;
   for (j = 1; j <= n + 1; j++)
      H[0][j] = w * H[0][j - 1] / j;

   H[1][0] = 1;
   w = (1.0 - 2.0 * A[2]) / n;
   for (j = 1; j <= n + 1; j++)
      H[1][j] = w * H[1][j - 1] / j;

   H[2][0] = 1;
   w = A[2] / n;
   for (j = 1; j <= n + 1; j++)
      H[2][j] = w * H[2][j - 1] / j;

   H[3][0] = 1;
   for (j = 1; j <= n + 1; j++)
      H[3][j] = 0;

   r1 = 0;
   r2 = 1;
   for (i = 2; i <= 2 * n + 2; i++) {
      jlow = 2 + (int) Atflo[i];
      if (jlow < 1)
         jlow = 1;
      jup = (int) Atcei[i];
      if (jup > n + 1)
         jup = n + 1;

      klow = 2 + (int) Atflo[i - 1];
      if (klow < 1)
         klow = 1;
      kup0 = (int) Atcei[i - 1];

      /* Find to which case it corresponds */
      w = (A[i] - A[i - 1]) / n;
      s = -1;
      for (j = 0; j < 4; j++) {
         if (fabs (w - H[j][1]) <= EPS) {
            s = j;
            break;
         }
      }
      /* assert (s >= 0, "Pomeranz: s < 0"); */

      minsum = RENO;
      r1 = (r1 + 1) & 1;          /* i - 1 */
      r2 = (r2 + 1) & 1;          /* i */

      for (j = jlow; j <= jup; j++) {
         kup = kup0;
         if (kup > j)
            kup = j;
         sum = 0;
         for (k = kup; k >= klow; k--)
            sum += V[r1][k] * H[s][j - k];
         V[r2][j] = sum;
         if (sum < minsum)
            minsum = sum;
      }

      if (minsum < 1.0e-280) {
         /* V is too small: renormalize to avoid underflow of probabilities */
         for (j = jlow; j <= jup; j++)
            V[r2][j] *= RENO;
         coreno++;                /* keep track of log of RENO */
      }
   }

   sum = V[r2][n + 1];
   free (A);
   free (Atflo);
   free (Atcei);
   DeleteMatrixD (H);
   DeleteMatrixD (V);
   w = getLogFactorial (n) - coreno * ENO * num_Ln2 + log (sum);
   if (w >= 0.)
      return 1.;
   return exp (w);
}


/*========================================================================*/

static double cdfSpecial (int n, double x)
{
   /* The KS distribution is known exactly for these cases */

   /* For nx^2 > 18, KSfbar(n, x) is smaller than 5e-16 */
   if ((n * x * x >= 18.0) || (x >= 1.0))
      return 1.0;

   if (x <= 0.5 / n)
      return 0.0;

   if (n == 1)
      return 2.0 * x - 1.0;

   if (x <= 1.0 / n) {
      double t = 2.0 * x * n - 1.0;
      double w;
      if (n <= NEXACT) {
         w = rapfac (n);
         return w * pow (t, (double) n);
      }
      w = getLogFactorial (n) + n * log (t / n);
      return exp (w);
   }

   if (x >= 1.0 - 1.0 / n) {
      return 1.0 - 2.0 * pow (1.0 - x, (double) n);
   }

   return -1.0;
}


/*========================================================================*/

double KScdf (int n, double x)
{
   const double w = n * x * x;
   double u = cdfSpecial (n, x);
   if (u >= 0.0)
      return u;

   if (n <= NEXACT) {
      if (w < 0.754693)
         return DurbinMatrix (n, x);
      if (w < 4.0)
         return Pomeranz (n, x);
      return 1.0 - KSfbar (n, x);
   }

   if ((w * x * n <= 7.0) && (n <= NKOLMO))
      return DurbinMatrix (n, x);

   return Pelz (n, x);
}


/*=========================================================================*/

static double fbarSpecial (int n, double x)
{
   const double w = n * x * x;

   if ((w >= 370.0) || (x >= 1.0))
      return 0.0;
   if ((w <= 0.0274) || (x <= 0.5 / n))
      return 1.0;
   if (n == 1)
      return 2.0 - 2.0 * x;

   if (x <= 1.0 / n) {
      double z;
      double t = 2.0 * x * n - 1.0;
      if (n <= NEXACT) {
         z = rapfac (n);
         return 1.0 - z * pow (t, (double) n);
      }
      z = getLogFactorial (n) + n * log (t / n);
      return 1.0 - exp (z);
   }

   if (x >= 1.0 - 1.0 / n) {
      return 2.0 * pow (1.0 - x, (double) n);
   }
   return -1.0;
}


/*========================================================================*/

double KSfbar (int n, double x)
{
   const double w = n * x * x;
   double v = fbarSpecial (n, x);
   if (v >= 0.0)
      return v;

   if (n <= NEXACT) {
      if (w < 4.0)
         return 1.0 - KScdf (n, x);
      else
         return 2.0 * KSPlusbarUpper (n, x);
   }

   if (w >= 2.65)
      return 2.0 * KSPlusbarUpper (n, x);

   return 1.0 - KScdf (n, x);
}


/*=========================================================================

The following implements the Durbin matrix algorithm and was programmed by
G. Marsaglia, Wai Wan Tsang and Jingbo Wong.

I have made small modifications in their program. (Richard Simard)



=========================================================================*/

/*
 The C program to compute Kolmogorov's distribution

             K(n,d) = Prob(D_n < d),         where

      D_n = max(x_1-0/n,x_2-1/n...,x_n-(n-1)/n,1/n-x_1,2/n-x_2,...,n/n-x_n)

    with  x_1<x_2,...<x_n  a purported set of n independent uniform [0,1)
    random variables sorted into increasing order.
    See G. Marsaglia, Wai Wan Tsang and Jingbo Wong,
       J.Stat.Software, 8, 18, pp 1--4, (2003).
*/

#define NORM 1.0e140
#define INORM 1.0e-140
#define LOGNORM 140


/* Matrix product */
static void mMultiply (double *A, double *B, double *C, int m);

/* Matrix power */
static void mPower (double *A, int eA, double *V, int *eV, int m, int n);


static double DurbinMatrix (int n, double d)
{
   int k, m, i, j, g, eH, eQ;
   double h, s, *H, *Q;
   /* OMIT NEXT TWO LINES IF YOU REQUIRE >7 DIGIT ACCURACY IN THE RIGHT TAIL */
#if 0
   s = d * d * n;
   if (s > 7.24 || (s > 3.76 && n > 99))
      return 1 - 2 * exp (-(2.000071 + .331 / sqrt (n) + 1.409 / n) * s);
#endif
   k = (int) (n * d) + 1;
   m = 2 * k - 1;
   h = k - n * d;
   H = (double *) calloc ((m * m), sizeof (double));
   Q = (double *) calloc ((m * m), sizeof (double));
   for (i = 0; i < m; i++)
      for (j = 0; j < m; j++)
         if (i - j + 1 < 0)
            H[i * m + j] = 0;
         else
            H[i * m + j] = 1;
   for (i = 0; i < m; i++) {
      H[i * m] -= pow (h, (double) (i + 1));
      H[(m - 1) * m + i] -= pow (h, (double) (m - i));
   }
   H[(m - 1) * m] += (2 * h - 1 > 0 ? pow (2 * h - 1, (double) m) : 0);
   for (i = 0; i < m; i++)
      for (j = 0; j < m; j++)
         if (i - j + 1 > 0)
            for (g = 1; g <= i - j + 1; g++)
               H[i * m + j] /= g;
   eH = 0;
   mPower (H, eH, Q, &eQ, m, n);
   s = Q[(k - 1) * m + k - 1];

   for (i = 1; i <= n; i++) {
      s = s * (double) i / n;
      if (s < INORM) {
         s *= NORM;
         eQ -= LOGNORM;
      }
   }
   s *= pow (10., (double) eQ);
   free (H);
   free (Q);
   return s;
}


static void mMultiply (double *A, double *B, double *C, int m)
{
   int i, j, k;
   double s;
   for (i = 0; i < m; i++)
      for (j = 0; j < m; j++) {
         s = 0.;
         for (k = 0; k < m; k++)
            s += A[i * m + k] * B[k * m + j];
         C[i * m + j] = s;
      }
}


static void renormalize (double *V, int m, int *p)
{
   int i;
   for (i = 0; i < m * m; i++)
      V[i] *= INORM;
   *p += LOGNORM;
}


static void mPower (double *A, int eA, double *V, int *eV, int m, int n)
{
   double *B;
   int eB, i;
   if (n == 1) {
      for (i = 0; i < m * m; i++)
         V[i] = A[i];
      *eV = eA;
      return;
   }
   mPower (A, eA, V, eV, m, n / 2);
   B = (double *) malloc ((m * m) * sizeof (double));
   mMultiply (V, V, B, m);
   eB = 2 * (*eV);
   if (B[(m / 2) * m + (m / 2)] > NORM)
      renormalize (B, m, &eB);

   if (n % 2 == 0) {
      for (i = 0; i < m * m; i++)
         V[i] = B[i];
      *eV = eB;
   } else {
      mMultiply (A, B, V, m);
      *eV = eA + eB;
   }

   if (V[(m / 2) * m + (m / 2)] > NORM)
      renormalize (V, m, eV);
   free (B);
}