forked from personal/squiggle.c
113 lines
3.0 KiB
C
113 lines
3.0 KiB
C
#include <math.h>
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#include <stdint.h>
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#include <stdlib.h>
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const float PI = 3.14159265358979323846;
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// Pseudo Random number generator
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uint32_t xorshift32
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(uint32_t* seed)
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{
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// Algorithm "xor" from p. 4 of Marsaglia, "Xorshift RNGs"
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// See <https://stackoverflow.com/questions/53886131/how-does-xorshift32-works>
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// https://en.wikipedia.org/wiki/Xorshift
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// Also some drama: <https://www.pcg-random.org/posts/on-vignas-pcg-critique.html>, <https://prng.di.unimi.it/>
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uint32_t x = *seed;
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x ^= x << 13;
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x ^= x >> 17;
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x ^= x << 5;
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return *seed = x;
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}
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// Distribution & sampling functions
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float rand_0_to_1(uint32_t* seed){
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return ((float) xorshift32(seed)) / ((float) UINT32_MAX);
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}
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float rand_float(float max, uint32_t* seed)
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{
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return rand_0_to_1(seed) * max;
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}
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float ur_normal(uint32_t* seed)
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{
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float u1 = rand_0_to_1(seed);
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float u2 = rand_0_to_1(seed);
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float z = sqrtf(-2.0 * log(u1)) * sin(2 * PI * u2);
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return z;
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}
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float random_uniform(float from, float to, uint32_t* seed)
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{
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return rand_0_to_1(seed) * (to - from) + from;
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}
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float random_normal(float mean, float sigma, uint32_t* seed)
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{
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return (mean + sigma * ur_normal(seed));
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}
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float random_lognormal(float logmean, float logsigma, uint32_t* seed)
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{
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return expf(random_normal(logmean, logsigma, seed));
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}
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float random_to(float low, float high, uint32_t* seed)
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{
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const float NORMAL95CONFIDENCE = 1.6448536269514722;
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float loglow = logf(low);
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float loghigh = logf(high);
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float logmean = (loglow + loghigh) / 2;
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float logsigma = (loghigh - loglow) / (2.0 * NORMAL95CONFIDENCE);
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return random_lognormal(logmean, logsigma, seed);
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}
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// Array helpers
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float array_sum(float* array, int length)
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{
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float output = 0.0;
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for (int i = 0; i < length; i++) {
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output += array[i];
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}
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return output;
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}
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void array_cumsum(float* array_to_sum, float* array_cumsummed, int length)
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{
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array_cumsummed[0] = array_to_sum[0];
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for (int i = 1; i < length; i++) {
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array_cumsummed[i] = array_cumsummed[i - 1] + array_to_sum[i];
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}
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}
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// Mixture function
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float mixture(float (*samplers[])(uint32_t*), float* weights, int n_dists, uint32_t* seed)
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{
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// You can see a simpler version of this function in the git history
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// or in C-02-better-algorithm-one-thread/
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float sum_weights = array_sum(weights, n_dists);
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float* cumsummed_normalized_weights = (float*) malloc(n_dists * sizeof(float));
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cumsummed_normalized_weights[0] = weights[0]/sum_weights;
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for (int i = 1; i < n_dists; i++) {
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cumsummed_normalized_weights[i] = cumsummed_normalized_weights[i - 1] + weights[i]/sum_weights;
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}
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float result;
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int result_set_flag = 0;
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float p = random_uniform(0, 1, seed);
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for (int k = 0; k < n_dists; k++) {
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if (p < cumsummed_normalized_weights[k]) {
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result = samplers[k](seed);
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result_set_flag = 1;
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break;
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}
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}
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if(result_set_flag == 0) result = samplers[n_dists-1](seed);
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free(cumsummed_normalized_weights);
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return result;
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}
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