commit 68e7730f24c33268a151dd197534f8c28ed376e0
parent 8f69dd1e588db16d8f59a523dbe2ebc448683663
Author: NunoSempere <nuno.sempere@protonmail.com>
Date: Sun, 16 Jul 2023 21:08:05 +0200
reformat squiggle.c, remake examples.
Diffstat:
6 files changed, 36 insertions(+), 35 deletions(-)
diff --git a/examples/01_one_sample/example b/examples/01_one_sample/example
Binary files differ.
diff --git a/examples/02_many_samples/example b/examples/02_many_samples/example
Binary files differ.
diff --git a/examples/03_gcc_nested_function/example b/examples/03_gcc_nested_function/example
Binary files differ.
diff --git a/scratchpad/scratchpad b/scratchpad/scratchpad
Binary files differ.
diff --git a/scratchpad/scratchpad.c b/scratchpad/scratchpad.c
@@ -4,7 +4,7 @@
#include <stdint.h>
#include <stdio.h>
#include <stdlib.h>
-#include <sys/types.h>
+// #include <sys/types.h>
#include <time.h>
#define EXIT_ON_ERROR 0
diff --git a/squiggle.c b/squiggle.c
@@ -3,29 +3,29 @@
#include <stdlib.h>
// PI constant
-const float PI = M_PI;// 3.14159265358979323846;
+const float PI = M_PI; // 3.14159265358979323846;
// 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;
+ // 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_0_to_1(uint32_t* seed)
+{
+ return ((float)xorshift32(seed)) / ((float)UINT32_MAX);
}
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;
}
-float ur_normal(uint32_t* seed)
+float unit_normal(uint32_t* seed)
{
float u1 = 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)
{
- return (mean + sigma * ur_normal(seed));
+ return (mean + sigma * unit_normal(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
// 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;
+ 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;
+ 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);
- 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;
+ free(cumsummed_normalized_weights);
+ return result;
}