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authorDaniel Baumann <daniel.baumann@progress-linux.org>2024-05-05 11:19:16 +0000
committerDaniel Baumann <daniel.baumann@progress-linux.org>2024-05-05 12:07:37 +0000
commitb485aab7e71c1625cfc27e0f92c9509f42378458 (patch)
treeae9abe108601079d1679194de237c9a435ae5b55 /src/database/KolmogorovSmirnovDist.c
parentAdding upstream version 1.44.3. (diff)
downloadnetdata-b485aab7e71c1625cfc27e0f92c9509f42378458.tar.xz
netdata-b485aab7e71c1625cfc27e0f92c9509f42378458.zip
Adding upstream version 1.45.3+dfsg.
Signed-off-by: Daniel Baumann <daniel.baumann@progress-linux.org>
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diff --git a/src/database/KolmogorovSmirnovDist.c b/src/database/KolmogorovSmirnovDist.c
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+// 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 *) malloc ((m * m) * sizeof (double));
+ Q = (double *) malloc ((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);
+}