add in xorshift rand function. begin reworking job queue to use cell entry pointers instead of just cells so results can be posted directly to the relevant entry

inc/genetic.h

@@ -30,12 +30,15 @@ template <class T> struct Strategy {
   bool enable_mutation;            // Cells may be mutated
                                    // before fitness evaluation
   float mutation_chance; // Chance to mutate cells before fitness evaluation
+  uint64_t rand_seed;
+  bool higher_fitness_is_better; // Sets whether or not to consider higher
+                                 // fitness values better or worse. Set this to
+                                 // false if fitness is an error function.
 
   // User defined functions
   T (*make_default_cell)();
   void (*mutate)(T &cell_to_modify);
-  void (*crossover)(const ReadonlySpan<T> &parents,
-                    const Span<T> &out_children);
+  void (*crossover)(const Span<T *> parents, const Span<T *> out_children);
   float (*fitness)(const T &cell);
 };
 
@@ -44,13 +47,6 @@ template <class T> struct Stats {
   std::vector<float> average_fitness;
 };
 
-template <class T> struct ReadonlySpan {
-  T *_data;
-  int len;
-
-  const T &operator[](int i);
-};
-
 template <class T> struct Span {
   T *_data;
   int len;

inc/rand.h

@@ -0,0 +1,18 @@
+// TODO: This file needs a serious audit
+
+#include <cstdint>
+
+constexpr uint64_t half_max = UINT64_MAX / 2;
+
+// From https://en.wikipedia.org/wiki/Xorshift
+inline void xorshift64(uint64_t &state) {
+  state ^= state << 13;
+  state ^= state >> 7;
+  state ^= state << 17;
+}
+
+// returns a random value between -1 and 1. modifies seed
+inline float norm_rand(uint64_t &state) {
+  xorshift64(state);
+  return (state - half_max) / half_max;
+}