add entropy readings and plot

src/common.odin

@@ -23,5 +23,5 @@ Problem :: struct {
 }
 
 Stats :: struct {
-	best, mean, worst: f64,
+	best, mean, worst, entropy: f64,
 }

src/ga.odin

@@ -26,22 +26,21 @@ run_ga :: proc(problem: Problem, survivor_selection: Survivor_Selection) {
 
 	for gen in 0 ..< GENERATIONS {
 		pop_fitnesses := evaluate_population(&population, problem.fitness_proc)
-		stats := compute_stats(pop_fitnesses[:], problem.maximize)
+		stats := compute_stats(&population, pop_fitnesses[:], problem.chromosome_size, problem.maximize)
 		append(&generation_stats, stats)
 
 		fmt.printfln(
-			"Gen %d: Best=%.4f Mean=%.4f Worst=%.4f",
+			"Gen %d: Best=%.4f Mean=%.4f Worst=%.4f Entropy=%.4f",
 			gen,
 			stats.best,
 			stats.mean,
 			stats.worst,
+			stats.entropy,
 		)
 
-		// Create offspring (no selection decisions here)
 		offspring := create_offspring_simple(&population)
 		offspring_fitnesses := evaluate_population(&offspring, problem.fitness_proc)
 
-		// Survivor selection decides who lives
 		next_gen := survivor_selection(
 			&population,
 			&offspring,
@@ -86,7 +85,35 @@ evaluate_population :: proc(
 	return fitnesses
 }
 
-compute_stats :: proc(fitnesses: []f64, maximize: bool) -> Stats {
+compute_population_entropy :: proc(pop: ^Population, chromosome_size: int) -> f64 {
+	bit_counts := make([]int, chromosome_size, context.temp_allocator)
+	defer delete(bit_counts, context.temp_allocator)
+
+	// Count 1s at each bit position
+	for i in 0 ..< POPULATION_SIZE {
+		for j in 0 ..< chromosome_size {
+			if bit_array.get(pop[i], j) {
+				bit_counts[j] += 1
+			}
+		}
+	}
+
+	// Calculate entropy: H = -Σ p_i * log2(p_i)
+	entropy: f64 = 0.0
+	for count in bit_counts {
+		if count == 0 || count == POPULATION_SIZE {
+			continue // Skip if all 0s or all 1s (log(0) undefined)
+		}
+
+		p := f64(count) / f64(POPULATION_SIZE)
+		entropy -= p * math.log2(p)
+	}
+
+	return entropy
+}
+
+// Modified compute_stats to include entropy
+compute_stats :: proc(pop: ^Population, fitnesses: []f64, chromosome_size: int, maximize: bool) -> Stats {
 	best := maximize ? -math.F64_MAX : math.F64_MAX
 	worst := maximize ? math.F64_MAX : -math.F64_MAX
 	sum := 0.0
@@ -102,7 +129,9 @@ compute_stats :: proc(fitnesses: []f64, maximize: bool) -> Stats {
 		sum += f
 	}
 
-	return {best, sum / f64(len(fitnesses)), worst}
+	entropy := compute_population_entropy(pop, chromosome_size)
+
+	return {best, sum / f64(len(fitnesses)), worst, entropy}
 }
 
 tournament_selection :: proc(pop: ^Population, fitnesses: []f64, maximize: bool) -> Chromosome {
@@ -360,7 +389,7 @@ write_results :: proc(filename: string, stats: []Stats) -> bool {
 	w: csv.Writer
 	csv.writer_init(&w, os.stream_from_handle(handle))
 
-	csv.write(&w, []string{"Generation", "Best", "Mean", "Worst"})
+	csv.write(&w, []string{"Generation", "Best", "Mean", "Worst", "Entropy"})
 
 	for stat, gen in stats {
 		csv.write(
@@ -370,6 +399,7 @@ write_results :: proc(filename: string, stats: []Stats) -> bool {
 				fmt.tprintf("%.6f", stat.best),
 				fmt.tprintf("%.6f", stat.mean),
 				fmt.tprintf("%.6f", stat.worst),
+				fmt.tprintf("%.6f", stat.entropy),
 			},
 		)
 	}

src/plot.ua

@@ -3,9 +3,13 @@
 ↥0⋕↘1°csv
 ≡°⊂
 °⍉≡⊟
-⍜°⊟₃∩₃Line
+⍜°⊟₃∩₃Line °⊂⌟
 °⊸≡°◇°Data~Label {"best" "mean" "worst"}
 Plot!(
   °⊸XLabel "generations"
 )
 &fwa"output/plot.png"img"png"
+
+°⊸Data~Label "entropy" Line
+Plot!(°⊸XLabel "generations")
+&fwa"output/entropy.png"img"png"