forked from personal/squiggle.c
continue minimizing nested functions
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@ -3,6 +3,10 @@
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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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@ -3,6 +3,10 @@
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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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@ -13,13 +17,9 @@ 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(sampler, results, n_threads, n_samples);
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sampler_parallel(sample_model, 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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int main()
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double sampler_result(uint64_t * 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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@ -17,10 +17,11 @@ int main()
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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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}
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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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