code cleanup

03_euler_gen_alg/main.py

@@ -10,7 +10,6 @@ Taylor-Reihe um 0.
 
 import numpy as np
 import random
-import struct
 import time
 import utils
 
@@ -61,9 +60,9 @@ def eval_fitness(bin_pop_values):
         # Create polynomial function with current parameters
         approx = lambda x: a*x**3 + b*x**2 + c*x + d
         e_func = lambda x: np.e**x
-        quad_error = quadratic_error(e_func, approx, 3)
+        quad_error = quadratic_error(e_func, approx, 3) # the bigger the error, the worse the fitness
         
-        inverse_fitness = 1 / quad_error # the bigger the error, the worse the fitness
+        inverse_fitness = 1 / quad_error # using inverse to find small errors easier
         # print("Fitness: " + str(inverse_fitness)) # debugging
         fitness_arr.append(inverse_fitness) # save fitness
         
@@ -129,13 +128,10 @@ def mutate(population, mutation_rate):
         # Convert back to string and update population
         population[random_num] = ''.join(bits) # will work because lists are passed by reference
 
-def main():
-    global gray_pop, bin_pop, bin_pop_params, new_pop, fitness, fitness_arr
-    
 bin_pop_values = generate_random_population(POPULATION_SIZE)
 
-    iteration = 0
 print("Working...")
+# iteration = 0 # debugging
 while not np.any((np.array(fitness_arr)) > 200):  # Continue while any fitness value is > 1
     # print("Iteration: " + str(iteration)) # debugging
     
@@ -160,21 +156,13 @@ def main():
         params = [bin_str[i:i+7] for i in range(0, 31, 8)]
         bin_pop_values.append(params)
     
-        # time.sleep(0.5)
-        
-        iteration += 1
+    # time.sleep(0.5) # debugging
+    # iteration += 1 # debugging
 
 max_fitness_index = np.argmax(np.array(fitness_arr))
 a, b, c, d = [utils.bin_to_param(param) for param in bin_pop_values[max_fitness_index]]
 
-    
-    print("index: " + str(max_fitness_index))
+# print("index: " + str(max_fitness_index)) # debugging
 print("a: " + str(a) + "; b: " + str(b) + "; c: " + str(c) + "; d: " + str(d) )
 
 utils.plot_graph(a, b, c, d)
-    
-    return 0
-
-if __name__ == "__main__":
-    main()
-    print("found that shit")

03_euler_gen_alg/utils.py

@@ -6,43 +6,31 @@ def gray_to_bin(gray):
     Convert Gray code to binary, operating on the integer value directly.
     :returns: 32-bit String
     """
-    try:
     num = int(gray, 2)  # Convert string to integer
     mask = num
     while mask != 0:
         mask >>= 1
         num ^= mask
     return format(num, '032b')  # Always return 32-bit string
-    except ValueError as e:
-        print(f"Error in gray_to_bin with input: '{gray}'")
-        raise e
 
 def bin_to_gray(binary):
     """
     Convert binary to Gray code using XOR with right shift
     :returns: 32-bit String
     """
-    try:
     num = int(binary, 2)  # Convert string to integer
     gray = num ^ (num >> 1)  # Gray code formula: G = B ^ (B >> 1)
     return format(gray, '032b')  # Always return 32-bit string
-    except ValueError as e:
-        print(f"Error in bin_to_gray with input: '{binary}'")
-        raise e
 
 def bin_to_param(binary, q_min = 0.0, q_max = 10.0):
     """
     Convert one binary string to float parameter in range [q_min, q_max]
     :returns: float 
     """
-    try:
     val = int(binary, 2) / 25.5 * 10 # conversion to 0.0 - 10.0 float
     # Scale to range [q_min, q_max]
     q = q_min + ((q_max - q_min) / (2**len(binary))) * val
     return q
-    except ValueError as e:
-        print(f"Error in bin_to_param with input: '{binary}'")
-        raise e
 
 def plot_graph(a, b, c, d): 
     x = np.arange(-5., 5., 0.1)