move to squiggle.c file, instead of just squiggle.h

This commit is contained in:
NunoSempere 2023-07-16 21:00:30 +02:00
parent cd6eb5203c
commit 8f69dd1e58
8 changed files with 132 additions and 105 deletions

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@ -9,7 +9,7 @@ CC=gcc
# CC=tcc # <= faster compilation # CC=tcc # <= faster compilation
# Main file # Main file
SRC=example.c SRC=example.c ../../squiggle.c
OUTPUT=example OUTPUT=example
## Dependencies ## Dependencies

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@ -9,7 +9,7 @@ CC=gcc
# CC=tcc # <= faster compilation # CC=tcc # <= faster compilation
# Main file # Main file
SRC=example.c SRC=example.c ../../squiggle.c
OUTPUT=example OUTPUT=example
## Dependencies ## Dependencies

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@ -9,7 +9,7 @@ CC=gcc # required for nested functions
# CC=tcc # <= faster compilation # CC=tcc # <= faster compilation
# Main file # Main file
SRC=example.c SRC=example.c ../../squiggle.c
OUTPUT=example OUTPUT=example
## Dependencies ## Dependencies

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

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@ -1,112 +1,26 @@
#include <math.h> #ifndef SQUIGGLEC
#include <stdint.h> #define SQUIGGLEC
#include <stdlib.h>
const float PI = 3.14159265358979323846; // uint32_t header
#include <stdint.h>
// Pseudo Random number generator // Pseudo Random number generator
uint32_t xorshift32(uint32_t* seed);
uint32_t xorshift32
(uint32_t* seed)
{
// Algorithm "xor" from p. 4 of Marsaglia, "Xorshift RNGs"
// See <https://stackoverflow.com/questions/53886131/how-does-xorshift32-works>
// 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/>
uint32_t x = *seed;
x ^= x << 13;
x ^= x >> 17;
x ^= x << 5;
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){ float rand_float(float max, uint32_t* seed);
return ((float) xorshift32(seed)) / ((float) UINT32_MAX); float ur_normal(uint32_t* seed);
} float random_uniform(float from, float to, uint32_t* seed);
float random_normal(float mean, float sigma, uint32_t* seed);
float rand_float(float max, uint32_t* seed) float random_lognormal(float logmean, float logsigma, uint32_t* seed);
{ float random_to(float low, float high, uint32_t* seed);
return rand_0_to_1(seed) * max;
}
float ur_normal(uint32_t* seed)
{
float u1 = rand_0_to_1(seed);
float u2 = rand_0_to_1(seed);
float z = sqrtf(-2.0 * log(u1)) * sin(2 * PI * u2);
return z;
}
float random_uniform(float from, float to, uint32_t* seed)
{
return rand_0_to_1(seed) * (to - from) + from;
}
float random_normal(float mean, float sigma, uint32_t* seed)
{
return (mean + sigma * ur_normal(seed));
}
float random_lognormal(float logmean, float logsigma, uint32_t* seed)
{
return expf(random_normal(logmean, logsigma, seed));
}
float random_to(float low, float high, uint32_t* seed)
{
const float NORMAL95CONFIDENCE = 1.6448536269514722;
float loglow = logf(low);
float loghigh = logf(high);
float logmean = (loglow + loghigh) / 2;
float logsigma = (loghigh - loglow) / (2.0 * NORMAL95CONFIDENCE);
return random_lognormal(logmean, logsigma, seed);
}
// Array helpers // Array helpers
float array_sum(float* array, int length) float array_sum(float* array, int length);
{ void array_cumsum(float* array_to_sum, float* array_cumsummed, int length);
float output = 0.0;
for (int i = 0; i < length; i++) {
output += array[i];
}
return output;
}
void array_cumsum(float* array_to_sum, float* array_cumsummed, int length)
{
array_cumsummed[0] = array_to_sum[0];
for (int i = 1; i < length; i++) {
array_cumsummed[i] = array_cumsummed[i - 1] + array_to_sum[i];
}
}
// Mixture function // Mixture function
float mixture(float (*samplers[])(uint32_t*), float* weights, int n_dists, uint32_t* seed) float mixture(float (*samplers[])(uint32_t*), float* weights, int n_dists, uint32_t* seed);
{
// You can see a simpler version of this function in the git history
// or in C-02-better-algorithm-one-thread/
float sum_weights = array_sum(weights, n_dists);
float* cumsummed_normalized_weights = (float*) malloc(n_dists * sizeof(float));
cumsummed_normalized_weights[0] = weights[0]/sum_weights;
for (int i = 1; i < n_dists; i++) {
cumsummed_normalized_weights[i] = cumsummed_normalized_weights[i - 1] + weights[i]/sum_weights;
}
float result; #endif
int result_set_flag = 0;
float p = random_uniform(0, 1, seed);
for (int k = 0; k < n_dists; k++) {
if (p < cumsummed_normalized_weights[k]) {
result = samplers[k](seed);
result_set_flag = 1;
break;
}
}
if(result_set_flag == 0) result = samplers[n_dists-1](seed);
free(cumsummed_normalized_weights);
return result;
}