forked from personal/squiggle.c
reformat squiggle.c, remake examples.
This commit is contained in:
parent
8f69dd1e58
commit
68e7730f24
Binary file not shown.
Binary file not shown.
Binary file not shown.
Binary file not shown.
|
@ -4,7 +4,7 @@
|
||||||
#include <stdint.h>
|
#include <stdint.h>
|
||||||
#include <stdio.h>
|
#include <stdio.h>
|
||||||
#include <stdlib.h>
|
#include <stdlib.h>
|
||||||
#include <sys/types.h>
|
// #include <sys/types.h>
|
||||||
#include <time.h>
|
#include <time.h>
|
||||||
|
|
||||||
#define EXIT_ON_ERROR 0
|
#define EXIT_ON_ERROR 0
|
||||||
|
|
65
squiggle.c
65
squiggle.c
|
@ -3,29 +3,29 @@
|
||||||
#include <stdlib.h>
|
#include <stdlib.h>
|
||||||
|
|
||||||
// PI constant
|
// PI constant
|
||||||
const float PI = M_PI;// 3.14159265358979323846;
|
const float PI = M_PI; // 3.14159265358979323846;
|
||||||
|
|
||||||
// Pseudo Random number generator
|
// Pseudo Random number generator
|
||||||
|
|
||||||
uint32_t xorshift32
|
uint32_t xorshift32(uint32_t* seed)
|
||||||
(uint32_t* seed)
|
|
||||||
{
|
{
|
||||||
// Algorithm "xor" from p. 4 of Marsaglia, "Xorshift RNGs"
|
// Algorithm "xor" from p. 4 of Marsaglia, "Xorshift RNGs"
|
||||||
// See <https://stackoverflow.com/questions/53886131/how-does-xorshift32-works>
|
// See <https://stackoverflow.com/questions/53886131/how-does-xorshift32-works>
|
||||||
// https://en.wikipedia.org/wiki/Xorshift
|
// https://en.wikipedia.org/wiki/Xorshift
|
||||||
// Also some drama: <https://www.pcg-random.org/posts/on-vignas-pcg-critique.html>, <https://prng.di.unimi.it/>
|
// Also some drama: <https://www.pcg-random.org/posts/on-vignas-pcg-critique.html>, <https://prng.di.unimi.it/>
|
||||||
|
|
||||||
uint32_t x = *seed;
|
uint32_t x = *seed;
|
||||||
x ^= x << 13;
|
x ^= x << 13;
|
||||||
x ^= x >> 17;
|
x ^= x >> 17;
|
||||||
x ^= x << 5;
|
x ^= x << 5;
|
||||||
return *seed = x;
|
return *seed = x;
|
||||||
}
|
}
|
||||||
|
|
||||||
// Distribution & sampling functions
|
// Distribution & sampling functions
|
||||||
|
|
||||||
float rand_0_to_1(uint32_t* seed){
|
float rand_0_to_1(uint32_t* seed)
|
||||||
return ((float) xorshift32(seed)) / ((float) UINT32_MAX);
|
{
|
||||||
|
return ((float)xorshift32(seed)) / ((float)UINT32_MAX);
|
||||||
}
|
}
|
||||||
|
|
||||||
float rand_float(float max, uint32_t* seed)
|
float rand_float(float max, uint32_t* seed)
|
||||||
|
@ -33,7 +33,7 @@ float rand_float(float max, uint32_t* seed)
|
||||||
return rand_0_to_1(seed) * max;
|
return rand_0_to_1(seed) * max;
|
||||||
}
|
}
|
||||||
|
|
||||||
float ur_normal(uint32_t* seed)
|
float unit_normal(uint32_t* seed)
|
||||||
{
|
{
|
||||||
float u1 = rand_0_to_1(seed);
|
float u1 = rand_0_to_1(seed);
|
||||||
float u2 = rand_0_to_1(seed);
|
float u2 = rand_0_to_1(seed);
|
||||||
|
@ -48,7 +48,7 @@ float random_uniform(float from, float to, uint32_t* seed)
|
||||||
|
|
||||||
float random_normal(float mean, float sigma, uint32_t* seed)
|
float random_normal(float mean, float sigma, uint32_t* seed)
|
||||||
{
|
{
|
||||||
return (mean + sigma * ur_normal(seed));
|
return (mean + sigma * unit_normal(seed));
|
||||||
}
|
}
|
||||||
|
|
||||||
float random_lognormal(float logmean, float logsigma, uint32_t* seed)
|
float random_lognormal(float logmean, float logsigma, uint32_t* seed)
|
||||||
|
@ -90,24 +90,25 @@ float mixture(float (*samplers[])(uint32_t*), float* weights, int n_dists, uint3
|
||||||
// You can see a simpler version of this function in the git history
|
// You can see a simpler version of this function in the git history
|
||||||
// or in C-02-better-algorithm-one-thread/
|
// or in C-02-better-algorithm-one-thread/
|
||||||
float sum_weights = array_sum(weights, n_dists);
|
float sum_weights = array_sum(weights, n_dists);
|
||||||
float* cumsummed_normalized_weights = (float*) malloc(n_dists * sizeof(float));
|
float* cumsummed_normalized_weights = (float*)malloc(n_dists * sizeof(float));
|
||||||
cumsummed_normalized_weights[0] = weights[0]/sum_weights;
|
cumsummed_normalized_weights[0] = weights[0] / sum_weights;
|
||||||
for (int i = 1; i < n_dists; i++) {
|
for (int i = 1; i < n_dists; i++) {
|
||||||
cumsummed_normalized_weights[i] = cumsummed_normalized_weights[i - 1] + weights[i]/sum_weights;
|
cumsummed_normalized_weights[i] = cumsummed_normalized_weights[i - 1] + weights[i] / sum_weights;
|
||||||
}
|
}
|
||||||
|
|
||||||
float result;
|
float result;
|
||||||
int result_set_flag = 0;
|
int result_set_flag = 0;
|
||||||
float p = random_uniform(0, 1, seed);
|
float p = random_uniform(0, 1, seed);
|
||||||
for (int k = 0; k < n_dists; k++) {
|
for (int k = 0; k < n_dists; k++) {
|
||||||
if (p < cumsummed_normalized_weights[k]) {
|
if (p < cumsummed_normalized_weights[k]) {
|
||||||
result = samplers[k](seed);
|
result = samplers[k](seed);
|
||||||
result_set_flag = 1;
|
result_set_flag = 1;
|
||||||
break;
|
break;
|
||||||
}
|
}
|
||||||
}
|
}
|
||||||
if(result_set_flag == 0) result = samplers[n_dists-1](seed);
|
if (result_set_flag == 0)
|
||||||
|
result = samplers[n_dists - 1](seed);
|
||||||
|
|
||||||
free(cumsummed_normalized_weights);
|
free(cumsummed_normalized_weights);
|
||||||
return result;
|
return result;
|
||||||
}
|
}
|
||||||
|
|
Loading…
Reference in New Issue
Block a user