--- /dev/null
+#ifndef RANDOMNUMBER_H
+#define RANDOMNUMBER_H
+
+/*
+ * randomnumber.cpp
+ *
+ *
+ * Created by Pat Schloss on 7/6/11.
+ * Copyright 2011 Patrick D. Schloss. All rights reserved.
+ *
+ */
+
+#include "randomnumber.h"
+#include <cmath>
+
+/**************************************************************************************************/
+
+RandomNumberGenerator::RandomNumberGenerator(){
+ srand( (unsigned)time( NULL ) );
+}
+
+/**************************************************************************************************/
+
+float RandomNumberGenerator::randomUniform(){
+
+ float randUnif = 0.0000;
+
+ while(randUnif == 0.0000){
+
+ randUnif = rand() / (float)RAND_MAX;
+
+ }
+
+ return randUnif;
+}
+
+/**************************************************************************************************/
+//
+//Code shamelessly swiped and modified from Numerical Recipes in C++
+//
+/**************************************************************************************************/
+
+float RandomNumberGenerator::randomExp(){
+
+ float randExp = 0.0000;
+
+ while(randExp == 0.0000){
+
+ randExp = -log(randomUniform());
+
+ }
+
+ return randExp;
+}
+
+/**************************************************************************************************/
+//
+//Code shamelessly swiped and modified from Numerical Recipes in C++
+//
+/**************************************************************************************************/
+
+float RandomNumberGenerator::randomNorm(){
+
+ float x, y, rsquare;
+
+ do{
+ x = 2.0 * randomUniform() - 1.0;
+ y = 2.0 * randomUniform() - 1.0;
+
+ rsquare = x * x + y * y;
+ } while(rsquare >= 1.0 || rsquare == 0.0);
+
+ float fac = sqrt(-2.0 * log(rsquare)/rsquare);
+
+ return x * fac;
+}
+
+
+/**************************************************************************************************/
+/*
+ * Slightly modified version of:
+ *
+ * Mathlib : A C Library of Special Functions
+ * Copyright (C) 1998 Ross Ihaka
+ * Copyright (C) 2000-2005 The R Development Core Team
+ *
+ * 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; either version 2 of the License, or
+ * (at your option) any later version.
+ *
+ * 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, a copy is available at
+ * http://www.r-project.org/Licenses/
+ *
+ * SYNOPSIS
+ *
+ * #include <Rmath.h>
+ * float rgamma(float a, float scale);
+ *
+ * DESCRIPTION
+ *
+ * Random variates from the gamma distribution.
+ *
+ * REFERENCES
+ *
+ * [1] Shape parameter a >= 1. Algorithm GD in:
+ *
+ * Ahrens, J.H. and Dieter, U. (1982).
+ * Generating gamma variates by a modified
+ * rejection technique.
+ * Comm. ACM, 25, 47-54.
+ *
+ *
+ * [2] Shape parameter 0 < a < 1. Algorithm GS in:
+ *
+ * Ahrens, J.H. and Dieter, U. (1974).
+ * Computer methods for sampling from gamma, beta,
+ * poisson and binomial distributions.
+ * Computing, 12, 223-246.
+ *
+ * Input: a = parameter (mean) of the standard gamma distribution.
+ * Output: a variate from the gamma(a)-distribution
+ */
+
+float RandomNumberGenerator::randomGamma(float a)
+{
+ /* Constants : */
+ const static float sqrt32 = 5.656854;
+ const static float exp_m1 = 0.36787944117144232159;/* exp(-1) = 1/e */
+ float scale = 1.0;
+
+ /* Coefficients q[k] - for q0 = sum(q[k]*a^(-k))
+ * Coefficients a[k] - for q = q0+(t*t/2)*sum(a[k]*v^k)
+ * Coefficients e[k] - for exp(q)-1 = sum(e[k]*q^k)
+ */
+ const static float q1 = 0.04166669;
+ const static float q2 = 0.02083148;
+ const static float q3 = 0.00801191;
+ const static float q4 = 0.00144121;
+ const static float q5 = -7.388e-5;
+ const static float q6 = 2.4511e-4;
+ const static float q7 = 2.424e-4;
+
+ const static float a1 = 0.3333333;
+ const static float a2 = -0.250003;
+ const static float a3 = 0.2000062;
+ const static float a4 = -0.1662921;
+ const static float a5 = 0.1423657;
+ const static float a6 = -0.1367177;
+ const static float a7 = 0.1233795;
+
+ /* State variables [FIXME for threading!] :*/
+ static float aa = 0.;
+ static float aaa = 0.;
+ static float s, s2, d; /* no. 1 (step 1) */
+ static float q0, b, si, c;/* no. 2 (step 4) */
+
+ float e, p, q, r, t, u, v, w, x, ret_val;
+
+ if (a <= 0.0 || scale <= 0.0){ cout << "error alpha or scale parameter are less than zero." << endl; exit(1); }
+
+ if (a < 1.) { /* GS algorithm for parameters a < 1 */
+ e = 1.0 + exp_m1 * a;
+ for(;;) {
+ p = e * randomUniform();
+ if (p >= 1.0) {
+ x = -log((e - p) / a);
+ if (randomExp() >= (1.0 - a) * log(x))
+ break;
+ } else {
+ x = exp(log(p) / a);
+ if (randomExp() >= x)
+ break;
+ }
+ }
+ return scale * x;
+ }
+
+ /* --- a >= 1 : GD algorithm --- */
+
+ /* Step 1: Recalculations of s2, s, d if a has changed */
+ if (a != aa) {
+ aa = a;
+ s2 = a - 0.5;
+ s = sqrt(s2);
+ d = sqrt32 - s * 12.0;
+ }
+ /* Step 2: t = standard normal deviate,
+ x = (s,1/2) -normal deviate. */
+
+ /* immediate acceptance (i) */
+ t = randomNorm();
+ x = s + 0.5 * t;
+ ret_val = x * x;
+ if (t >= 0.0)
+ return scale * ret_val;
+
+ /* Step 3: u = 0,1 - uniform sample. squeeze acceptance (s) */
+ u = randomUniform();
+ if (d * u <= t * t * t)
+ return scale * ret_val;
+
+ /* Step 4: recalculations of q0, b, si, c if necessary */
+
+ if (a != aaa) {
+ aaa = a;
+ r = 1.0 / a;
+ q0 = ((((((q7 * r + q6) * r + q5) * r + q4) * r + q3) * r
+ + q2) * r + q1) * r;
+
+ /* Approximation depending on size of parameter a */
+ /* The constants in the expressions for b, si and c */
+ /* were established by numerical experiments */
+
+ if (a <= 3.686) {
+ b = 0.463 + s + 0.178 * s2;
+ si = 1.235;
+ c = 0.195 / s - 0.079 + 0.16 * s;
+ } else if (a <= 13.022) {
+ b = 1.654 + 0.0076 * s2;
+ si = 1.68 / s + 0.275;
+ c = 0.062 / s + 0.024;
+ } else {
+ b = 1.77;
+ si = 0.75;
+ c = 0.1515 / s;
+ }
+ }
+ /* Step 5: no quotient test if x not positive */
+
+ if (x > 0.0) {
+ /* Step 6: calculation of v and quotient q */
+ v = t / (s + s);
+ if (fabs(v) <= 0.25)
+ q = q0 + 0.5 * t * t * ((((((a7 * v + a6) * v + a5) * v + a4) * v
+ + a3) * v + a2) * v + a1) * v;
+ else
+ q = q0 - s * t + 0.25 * t * t + (s2 + s2) * log(1.0 + v);
+
+
+ /* Step 7: quotient acceptance (q) */
+ if (log(1.0 - u) <= q)
+ return scale * ret_val;
+ }
+
+ for(;;) {
+ /* Step 8: e = standard exponential deviate
+ * u = 0,1 -uniform deviate
+ * t = (b,si)-float exponential (laplace) sample */
+ e = randomExp();
+ u = randomUniform();
+ u = u + u - 1.0;
+ if (u < 0.0)
+ t = b - si * e;
+ else
+ t = b + si * e;
+ /* Step 9: rejection if t < tau(1) = -0.71874483771719 */
+ if (t >= -0.71874483771719) {
+ /* Step 10: calculation of v and quotient q */
+ v = t / (s + s);
+ if (fabs(v) <= 0.25)
+ q = q0 + 0.5 * t * t *
+ ((((((a7 * v + a6) * v + a5) * v + a4) * v + a3) * v
+ + a2) * v + a1) * v;
+ else
+ q = q0 - s * t + 0.25 * t * t + (s2 + s2) * log(1.0 + v);
+ /* Step 11: hat acceptance (h) */
+ /* (if q not positive go to step 8) */
+ if (q > 0.0) {
+ w = expm1(q);
+ /* ^^^^^ original code had approximation with rel.err < 2e-7 */
+ /* if t is rejected sample again at step 8 */
+ if (c * fabs(u) <= w * exp(e - 0.5 * t * t))
+ break;
+ }
+ }
+ } /* for(;;) .. until `t' is accepted */
+ x = s + 0.5 * t;
+ return scale * x * x;
+}
+
+/**************************************************************************************************/
+//
+// essentially swiped from http://en.wikipedia.org/wiki/Dirichlet_distribution#Random_number_generation
+//
+/**************************************************************************************************/
+
+vector<float> RandomNumberGenerator::randomDirichlet(vector<float> alphas){
+
+ int nAlphas = (int)alphas.size();
+ vector<float> dirs(nAlphas, 0.0000);
+
+ float sum = 0.0000;
+ for(int i=0;i<nAlphas;i++){
+ dirs[i] = randomGamma(alphas[i]);
+ sum += dirs[i];
+ }
+
+ for(int i=0;i<nAlphas;i++){
+ dirs[i] /= sum;
+ }
+
+ return dirs;
+
+}
+
+/**************************************************************************************************/
+
+#endif
projects / mothur.git / blobdiff