reformat squiggle.c, remake examples.

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

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/>
+    // 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;
+    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;
 }