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

@@ -7,8 +7,7 @@ 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>
@@ -24,7 +23,8 @@ uint32_t xorshift32
 
 // 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);
 }
 
@@ -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)
@@ -106,7 +106,8 @@ float mixture(float (*samplers[])(uint32_t*), float* weights, int n_dists, uint3
             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);
     return result;