2022-12-01 15:04:37 +00:00
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#include <gsl/gsl_randist.h>
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2023-05-21 00:20:43 +00:00
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#include <gsl/gsl_rng.h>
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#include <math.h>
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#include <stdio.h>
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#include <stdlib.h>
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2022-12-01 15:04:37 +00:00
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2022-12-01 16:10:29 +00:00
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#define N 1000000
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2022-12-01 15:04:37 +00:00
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/*
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* For very high values of N, you will want to increase the maximum stack trace, otherwise you will suffer a segmentation fault
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* In Ubuntu/bash you can do this with $ ulimit -Ss 256000 ## ~256Mbs
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* And confirm it with $ ulimit -a
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*/
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/* Helpers */
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2023-05-21 00:20:43 +00:00
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void print(double* ys)
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{
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for (int i = 0; i < N; i++) {
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printf("%f\n", ys[i]);
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}
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printf("\n");
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2022-12-01 15:04:37 +00:00
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}
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2023-05-21 00:20:43 +00:00
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void fill(double* ys, float f)
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{
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for (int i = 0; i < N; i++) {
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ys[i] = f;
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}
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2022-12-01 15:04:37 +00:00
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}
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2023-05-21 00:20:43 +00:00
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double sum(double* ps, int n)
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{
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double result = 0;
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for (int i = 0; i < n; i++) {
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result += ps[i];
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}
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return (result);
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2022-12-01 15:04:37 +00:00
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}
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2023-05-21 00:20:43 +00:00
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void cumsum(double* ps, double* rs, int n)
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{
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double counter = 0;
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for (int i = 0; i < n; i++) {
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counter += ps[i];
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rs[i] = counter;
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}
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2022-12-01 15:04:37 +00:00
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}
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/* Distributions*/
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2023-05-21 00:20:43 +00:00
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void normal(gsl_rng* r, double* ys, double mean, double std)
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{
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for (int i = 0; i < N; i++) {
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ys[i] = mean + gsl_ran_gaussian(r, std);
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}
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2022-12-01 15:04:37 +00:00
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}
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void lognormal(gsl_rng* r, double* ys, double zeta, double sigma)
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{
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for (int i = 0; i < N; i++) {
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ys[i] = gsl_ran_lognormal(r, zeta, sigma);
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}
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}
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void to(gsl_rng* r, double* ys, double low, double high)
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{
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double normal95confidencePoint = 1.6448536269514722;
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double log_low = log(low);
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double log_high = log(high);
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double zeta = (log_low + log_high) / 2;
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double sigma = (log_high - log_low) / (2.0 * normal95confidencePoint);
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lognormal(r, ys, zeta, sigma);
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2022-12-01 15:04:37 +00:00
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}
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/* Mixture of distributions */
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void mixture(gsl_rng* r, double* dists[], double* weights, int n, double* results)
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{
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/* Get cummulative, normalized weights */
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double sum_weights = sum(weights, n);
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double normalized_weights[n];
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for (int i = 0; i < n; i++) {
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normalized_weights[i] = weights[i] / sum_weights;
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}
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double cummulative_weights[n];
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cumsum(normalized_weights, cummulative_weights, n);
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/* Get N samples, drawn from the different distributions in proportion to their weights. */
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for (int i = 0; i < N; i++) {
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double p_1 = gsl_rng_uniform(r);
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double p_2 = gsl_rng_uniform(r);
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int index_found = 0;
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int index_counter = 0;
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while ((index_found == 0) && (index_counter < n)) {
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if (p_1 < cummulative_weights[index_counter]) {
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index_found = 1;
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} else {
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index_counter++;
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}
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}
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if (index_found == 0) {
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printf("\nThis shouldn't be able to happen");
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// gsl_rng_free (r);
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// abort(); // this shouldn't have happened.
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} else {
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int sample_index = (int)floor(p_2 * N);
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results[i] = dists[index_counter][sample_index];
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}
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2022-12-01 15:04:37 +00:00
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}
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}
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/* Main */
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int main(void)
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{
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/* Initialize GNU Statistical Library (GSL) stuff */
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const gsl_rng_type* T;
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gsl_rng* r;
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// gsl_rng_env_setup();
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T = gsl_rng_default;
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r = gsl_rng_alloc(T);
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/* Toy example */
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/* Declare variables in play */
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double p_a, p_b, p_c;
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double dist_none[N], dist_one[N], dist_few[N], dist_many[N], dist_mixture[N];
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/* Initialize variables */
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p_a = 0.8;
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p_b = 0.5;
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p_c = p_a * p_b;
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fill(dist_none, 0);
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fill(dist_one, 1);
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to(r, dist_few, 1, 3);
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to(r, dist_many, 2, 10);
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/* Generate mixture */
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int n = 4;
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double weights[] = { 1 - p_c, p_c / 2, p_c / 4, p_c / 4 };
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double* dists[] = { dist_none, dist_one, dist_few, dist_many };
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mixture(r, dists, weights, n, dist_mixture);
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printf("%f\n", sum(dist_mixture, N) / N);
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/* Clean up GSL */
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gsl_rng_free(r);
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/* Return success*/
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return EXIT_SUCCESS;
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2022-12-01 15:04:37 +00:00
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}
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