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5d28295a15
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b352cdf3ba
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@ -381,9 +381,7 @@ Overall, I'd describe the error handling capabilities of this library as pretty
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### To do
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- [ ] Drive in a few more real-life applications
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- [ ] US election modelling?
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- [ ] Look into using size_t instead of int for sample numbers
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- [ ] Reorganize code a little bit to reduce usage of gcc's nested functions
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### Done
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@ -3,24 +3,26 @@
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#include <stdlib.h>
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// Estimate functions
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double sample_0(uint64_t* seed)
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{
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UNUSED(seed);
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return 0;
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}
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double sample_0(uint64_t* seed) { UNUSED(seed); return 0; }
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double sample_1(uint64_t* seed) { UNUSED(seed); return 1; }
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double sample_few(uint64_t* seed) { return sample_to(1, 3, seed); }
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double sample_many(uint64_t* seed) { return sample_to(2, 10, seed); }
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double sample_1(uint64_t* seed)
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{
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UNUSED(seed);
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return 1;
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}
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double sample_model(uint64_t* seed){
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double sample_few(uint64_t* seed)
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{
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return sample_to(1, 3, seed);
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}
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double p_a = 0.8;
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double p_b = 0.5;
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double p_c = p_a * p_b;
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int n_dists = 4;
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double weights[] = { 1 - p_c, p_c / 2, p_c / 4, p_c / 4 };
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double (*samplers[])(uint64_t*) = { sample_0, sample_1, sample_few, sample_many };
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double result = sample_mixture(samplers, weights, n_dists, seed);
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return result;
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double sample_many(uint64_t* seed)
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{
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return sample_to(2, 10, seed);
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}
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int main()
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@ -29,6 +31,15 @@ int main()
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uint64_t* seed = malloc(sizeof(uint64_t));
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*seed = 1000; // xorshift can't start with 0
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printf("result_one: %f\n", sample_model(seed));
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double p_a = 0.8;
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double p_b = 0.5;
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double p_c = p_a * p_b;
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int n_dists = 4;
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double weights[] = { 1 - p_c, p_c / 2, p_c / 4, p_c / 4 };
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double (*samplers[])(uint64_t*) = { sample_0, sample_1, sample_few, sample_many };
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double result_one = sample_mixture(samplers, weights, n_dists, seed);
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printf("result_one: %f\n", result_one);
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free(seed);
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}
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@ -2,35 +2,37 @@
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#include <stdio.h>
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#include <stdlib.h>
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double sample_0(uint64_t* seed) { UNUSED(seed); return 0; }
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double sample_1(uint64_t* seed) { UNUSED(seed); return 1; }
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double sample_few(uint64_t* seed) { return sample_to(1, 3, seed); }
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double sample_many(uint64_t* seed) { return sample_to(2, 10, seed); }
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double sample_model(uint64_t* seed){
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double p_a = 0.8;
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double p_b = 0.5;
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double p_c = p_a * p_b;
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int n_dists = 4;
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double weights[] = { 1 - p_c, p_c / 2, p_c / 4, p_c / 4 };
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double (*samplers[])(uint64_t*) = { sample_0, sample_1, sample_few, sample_many };
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double result = sample_mixture(samplers, weights, n_dists, seed);
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return result;
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}
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int main()
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{
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// set randomness seed
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uint64_t* seed = malloc(sizeof(uint64_t));
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*seed = 1000; // xorshift can't start with 0
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double p_a = 0.8;
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double p_b = 0.5;
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double p_c = p_a * p_b;
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double sample_0(uint64_t * seed)
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{
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UNUSED(seed);
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return 0;
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}
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double sample_1(uint64_t * seed)
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{
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UNUSED(seed);
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return 1;
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}
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double sample_few(uint64_t * seed) { return sample_to(1, 3, seed); }
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double sample_many(uint64_t * seed) { return sample_to(2, 10, seed); }
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int n_dists = 4;
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double weights[] = { 1 - p_c, p_c / 2, p_c / 4, p_c / 4 };
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double (*samplers[])(uint64_t*) = { sample_0, sample_1, sample_few, sample_many };
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int n_samples = 1000000;
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double* result_many = (double*)malloc((size_t)n_samples * sizeof(double));
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for (int i = 0; i < n_samples; i++) {
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result_many[i] = sample_model(seed);
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result_many[i] = sample_mixture(samplers, weights, n_dists, seed);
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}
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printf("Mean: %f\n", array_mean(result_many, n_samples));
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@ -2,36 +2,39 @@
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#include <stdio.h>
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#include <stdlib.h>
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double sample_model(uint64_t* seed){
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double sample_0(uint64_t* seed) { UNUSED(seed); return 0; }
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// Using a gcc extension, you can define a function inside another function
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double sample_1(uint64_t* seed) { UNUSED(seed); return 1; }
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double sample_few(uint64_t* seed) { return sample_to(1, 3, seed); }
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double sample_many(uint64_t* seed) { return sample_to(2, 10, seed); }
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double p_a = 0.8;
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double p_b = 0.5;
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double p_c = p_a * p_b;
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int n_dists = 4;
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double weights[] = { 1 - p_c, p_c / 2, p_c / 4, p_c / 4 };
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double (*samplers[])(uint64_t*) = { sample_0, sample_1, sample_few, sample_many };
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double result = sample_mixture(samplers, weights, n_dists, seed);
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return result;
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}
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int main()
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{
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// set randomness seed
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uint64_t* seed = malloc(sizeof(uint64_t));
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*seed = 1000; // xorshift can't start with 0
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double p_a = 0.8;
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double p_b = 0.5;
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double p_c = p_a * p_b;
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int n_dists = 4;
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// These are nested functions. They will not compile without gcc.
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double sample_0(uint64_t * seed)
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{
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UNUSED(seed);
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return 0;
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}
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double sample_1(uint64_t * seed)
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{
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UNUSED(seed);
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return 1;
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}
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double sample_few(uint64_t * seed) { return sample_to(1, 3, seed); }
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double sample_many(uint64_t * seed) { return sample_to(2, 10, seed); }
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double (*samplers[])(uint64_t*) = { sample_0, sample_1, sample_few, sample_many };
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double weights[] = { 1 - p_c, p_c / 2, p_c / 4, p_c / 4 };
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int n_samples = 1000000;
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double* result_many = (double*)malloc((size_t)n_samples * sizeof(double));
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for (int i = 0; i < n_samples; i++) {
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result_many[i] = sample_model(seed);
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result_many[i] = sample_mixture(samplers, weights, n_dists, seed);
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}
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printf("result_many: [");
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@ -39,6 +42,5 @@ int main()
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printf("%.2f, ", result_many[i]);
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}
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printf("]\n");
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free(seed);
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}
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@ -2,6 +2,8 @@
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#include <stdio.h>
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#include <stdlib.h>
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// Estimate functions
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int main()
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{
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// set randomness seed
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@ -9,21 +11,33 @@ int main()
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*seed = 1000; // xorshift can't start with 0
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int n = 1000 * 1000;
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double* gamma_array = malloc(sizeof(double) * (size_t)n);
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/*
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for (int i = 0; i < n; i++) {
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gamma_array[i] = sample_gamma(1.0, seed);
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double gamma_0 = sample_gamma(0.0, seed);
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// printf("sample_gamma(0.0): %f\n", gamma_0);
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}
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printf("gamma(1) summary statistics = mean: %f, std: %f\n", array_mean(gamma_array, n), array_std(gamma_array, n));
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printf("\n");
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*/
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double* gamma_1_array = malloc(sizeof(double) * (size_t)n);
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for (int i = 0; i < n; i++) {
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double gamma_1 = sample_gamma(1.0, seed);
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// printf("sample_gamma(1.0): %f\n", gamma_1);
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gamma_1_array[i] = gamma_1;
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}
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printf("gamma(1) summary statistics = mean: %f, std: %f\n", array_mean(gamma_1_array, n), array_std(gamma_1_array, n));
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free(gamma_1_array);
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printf("\n");
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double* beta_array = malloc(sizeof(double) * (size_t)n);
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double* beta_1_2_array = malloc(sizeof(double) * (size_t)n);
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for (int i = 0; i < n; i++) {
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beta_array[i] = sample_beta(1, 2.0, seed);
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double beta_1_2 = sample_beta(1, 2.0, seed);
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// printf("sample_beta(1.0, 2.0): %f\n", beta_1_2);
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beta_1_2_array[i] = beta_1_2;
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}
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printf("beta(1,2) summary statistics: mean: %f, std: %f\n", array_mean(beta_array, n), array_std(beta_array, n));
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printf("beta(1,2) summary statistics: mean: %f, std: %f\n", array_mean(beta_1_2_array, n), array_std(beta_1_2_array, n));
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free(beta_1_2_array);
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printf("\n");
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free(gamma_array);
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free(beta_array);
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free(seed);
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}
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@ -4,9 +4,16 @@
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#include <stdio.h>
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#include <stdlib.h>
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double sample_fermi_logspace(uint64_t * seed)
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int main()
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{
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// Replicate <https://arxiv.org/pdf/1806.02404.pdf>, and in particular the red line in page 11.
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// set randomness seed
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uint64_t* seed = malloc(sizeof(uint64_t));
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*seed = 1001; // xorshift can't start with a seed of 0
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double sample_fermi_logspace(uint64_t * seed)
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{
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// You can see a simple version of this function in naive.c in this same folder
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double log_rate_of_star_formation = sample_uniform(log(1), log(100), seed);
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double log_fraction_of_stars_with_planets = sample_uniform(log(0.1), log(1), seed);
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// log_n > 0 => n > 1
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}
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int main()
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{
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// set randomness seed
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uint64_t* seed = malloc(sizeof(uint64_t));
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*seed = 1001; // xorshift can't start with a seed of 0
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double logspace_fermi_proportion = 0;
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int n_samples = 1000 * 1000;
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for (int i = 0; i < n_samples; i++) {
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@ -3,10 +3,6 @@
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#include <stdio.h>
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#include <stdlib.h>
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double sample_model(uint64_t* seed){
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return sample_to(1, 10, seed);
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}
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int main()
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{
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// set randomness seed
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@ -3,10 +3,6 @@
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#include <stdio.h>
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#include <stdlib.h>
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double sample_model(uint64_t * seed)
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{
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return sample_lognormal(0, 10, seed);
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}
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// Estimate functions
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int main()
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{
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@ -17,9 +13,13 @@ int main()
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int n_samples = 1000 * 1000 * 1000;
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int n_threads = 16;
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double sampler(uint64_t * seed)
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{
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return sample_lognormal(0, 10, seed);
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}
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double* results = malloc((size_t)n_samples * sizeof(double));
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sampler_parallel(sample_model, results, n_threads, n_samples);
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sampler_parallel(sampler, results, n_threads, n_samples);
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double avg = array_sum(results, n_samples) / n_samples;
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printf("Average of 1B lognormal(0,10): %f\n", avg);
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@ -3,7 +3,7 @@
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#include <stdio.h>
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#include <stdlib.h>
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double sampler_result(uint64_t * seed)
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int main()
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{
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double p_a = 0.8;
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double p_b = 0.5;
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int n_dists = 4;
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double weights[] = { 1 - p_c, p_c / 2, p_c / 4, p_c / 4 };
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double (*samplers[])(uint64_t*) = { sample_0, sample_1, sample_few, sample_many };
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double sampler_result(uint64_t * seed)
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{
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return sample_mixture(samplers, weights, n_dists, seed);
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}
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int main()
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{
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int n_samples = 1000 * 1000, n_threads = 16;
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double* results = malloc((size_t)n_samples * sizeof(double));
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sampler_parallel(sampler_result, results, n_threads, n_samples);
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@ -63,8 +63,6 @@ void sampler_parallel(double (*sampler)(uint64_t* seed), double* results, int n_
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{
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#pragma omp for
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for (i = 0; i < n_threads; i++) {
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// It's possible I don't need the for, and could instead call omp
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// in some different way and get the thread number with omp_get_thread_num()
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int lower_bound_inclusive = i * quotient;
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int upper_bound_not_inclusive = ((i + 1) * quotient); // note the < in the for loop below,
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