import numpy as np
import random
import struct
# import matplotlib.pyplot as plt

def generate_random_individuals():
    g = format(random.getrandbits(32), '32b')
    # val = int(b, 2) / 25.5 * 10 # conversion to 0.0 - 10.0 float


    return val

def grey_to_bin(gray):
    """Convert Gray code to binary, operating on the integer value directly"""
    num = int(gray, 2)  # Convert string to integer
    mask = num
    while mask != 0:
        mask >>= 1
        num ^= mask
    return format(num, f'0{len(gray)}b')  # Convert back to binary string with same length

def bin_to_grey(binary):
    """Convert binary to Gray code using XOR with right shift"""
    num = int(binary, 2)  # Convert string to integer
    gray = num ^ (num >> 1)  # Gray code formula: G = B ^ (B >> 1)
    return format(gray, f'0{len(binary)}b')  # Convert back to binary string with same length

def quadratic_error(original_fn, approx_fn, n):
    error = 0.0
    
    for i in range(n):
        error += (original_fn(i) - approx_fn(i))**2
        
    return error

def e_fn_approx(a, b, c, d, x = 1):
    return a*x**3 + b*x**2 + c*x + d

def fuck_that_shit_up():
    e_func = lambda x: np.e**x
    fixed_approx = lambda x: e_fn_approx(1.0, 0.1, 0.2, 1.0, x)
    
    while quadratic_error(e_func, fixed_approx, 6) > 0.01:
        pass
    # berechne fitness
    # selection
    # crossover
    # mutation
    
    # neue population
    return 0

b = format(random.getrandbits(32), '32b')
print(b)
# print(quadratic_error(e_func, fixed_approx, 6)) # hopefully works