From 839f023ee8d92bcc12abecf51e055f74dd09bcf7 Mon Sep 17 00:00:00 2001
From: Ruben-FreddyLoafers <rubenseitz.q@gmail.com>
Date: Mon, 13 Oct 2025 15:16:26 +0200
Subject: [PATCH] creating params

---
 03_euler_gen_alg.py | 31 ++++++++++++++++++++++++-------
 1 file changed, 24 insertions(+), 7 deletions(-)

diff --git a/03_euler_gen_alg.py b/03_euler_gen_alg.py
index 8ab78e8..28e7f6c 100644
--- a/03_euler_gen_alg.py
+++ b/03_euler_gen_alg.py
@@ -4,11 +4,13 @@ import struct
 # import matplotlib.pyplot as plt
 
 def generate_random_individuals():
-    g = format(random.getrandbits(32), '32b')
+    pop_grey = format(random.getrandbits(32), '32b')
+    pop_bin = grey_to_bin(pop_grey)
+    a, b, c, d = pop_bin[0:7], pop_bin[8:15], pop_bin[16:23], pop_bin[24:31]
     # val = int(b, 2) / 25.5 * 10 # conversion to 0.0 - 10.0 float
 
 
-    return val
+    return [a, b, c, d]
 
 def grey_to_bin(gray):
     """Convert Gray code to binary, operating on the integer value directly"""
@@ -25,6 +27,15 @@ def bin_to_grey(binary):
     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 bin_to_param(binary, q_min = 0.0, q_max = 10.0):
+    """Convert binary string to float parameter in range [q_min, q_max]"""
+    # Convert binary string to integer
+    val = int(binary, 2)
+    # Scale to range [q_min, q_max]
+    q = q_min + ((q_max - q_min) / (2**len(binary))) * val
+    return q
+
+
 def quadratic_error(original_fn, approx_fn, n):
     error = 0.0
     
@@ -37,15 +48,21 @@ 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():
+    bin_values = generate_random_individuals()
+    # Convert all binary strings to parameters in range 0.0-10.0
+    float_values = [bin_to_param(bin) for bin in bin_values]
+    a, b, c, d = float_values
+    
     e_func = lambda x: np.e**x
-    fixed_approx = lambda x: e_fn_approx(1.0, 0.1, 0.2, 1.0, x)
+    fixed_approx = lambda x: e_fn_approx(a, b, c, d, x)
     
     while quadratic_error(e_func, fixed_approx, 6) > 0.01:
+        
         pass
-    # berechne fitness
-    # selection
-    # crossover
-    # mutation
+        # berechne fitness
+        # selection
+        # crossover
+        # mutation
     
     # neue population
     return 0