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implemented taylor stuff

master
Ruben-FreddyLoafers 2025-10-28 20:24:52 +01:00
parent 4de71f8850
commit cf9131b760
2 changed files with 9 additions and 6 deletions
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8
03_euler_gen_alg/main.py
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@ -63,7 +63,7 @@ def eval_fitness(bin_pop_values):
quad_error = quadratic_error(e_func, approx, 3) # the bigger the error, the worse the fitness quad_error = quadratic_error(e_func, approx, 3) # the bigger the error, the worse the fitness
inverse_fitness = 1 / quad_error # using inverse to find small errors easier inverse_fitness = 1 / quad_error # using inverse to find small errors easier
# print("Fitness: " + str(inverse_fitness)) # debugging print("Fitness: " + str(inverse_fitness)) # debugging
fitness_arr.append(inverse_fitness) # save fitness fitness_arr.append(inverse_fitness) # save fitness
return fitness_arr return fitness_arr
@ -131,9 +131,9 @@ def mutate(population, mutation_rate):
bin_pop_values = generate_random_population(POPULATION_SIZE) bin_pop_values = generate_random_population(POPULATION_SIZE)
print("Working...") print("Working...")
# iteration = 0 # debugging iteration = 0 # debugging
while not np.any((np.array(fitness_arr)) > 200): # Continue while any fitness value is > 1 while not np.any((np.array(fitness_arr)) > 200): # Continue while any fitness value is > 1
# print("Iteration: " + str(iteration)) # debugging print("Iteration: " + str(iteration)) # debugging
# Evaluate fitness # Evaluate fitness
fitness_arr = eval_fitness(bin_pop_values) fitness_arr = eval_fitness(bin_pop_values)
@ -157,7 +157,7 @@ while not np.any((np.array(fitness_arr)) > 200): # Continue while any fitness v
bin_pop_values.append(params) bin_pop_values.append(params)
# time.sleep(0.5) # debugging # time.sleep(0.5) # debugging
# iteration += 1 # debugging iteration += 1 # debugging
max_fitness_index = np.argmax(np.array(fitness_arr)) 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]] a, b, c, d = [utils.bin_to_param(param) for param in bin_pop_values[max_fitness_index]]

7
03_euler_gen_alg/utils.py
View File

@ -1,5 +1,6 @@
import matplotlib.pyplot as plt import matplotlib.pyplot as plt
import numpy as np import numpy as np
import scipy.interpolate as interpolate
def gray_to_bin(gray): def gray_to_bin(gray):
""" """
@ -22,12 +23,12 @@ def bin_to_gray(binary):
gray = num ^ (num >> 1) # Gray code formula: G = B ^ (B >> 1) gray = num ^ (num >> 1) # Gray code formula: G = B ^ (B >> 1)
return format(gray, '032b') # Always return 32-bit string return format(gray, '032b') # Always return 32-bit string
def bin_to_param(binary, q_min = 0.0, q_max = 10.0): def bin_to_param(binary, q_min = 0.0, q_max = 8.0):
""" """
Convert one binary string to float parameter in range [q_min, q_max] Convert one binary string to float parameter in range [q_min, q_max]
:returns: float :returns: float
""" """
val = int(binary, 2) / 25.5 * 10 # conversion to 0.0 - 10.0 float val = int(binary, 2) / 25.5 * q_max # conversion to 0.0 - 10.0 float
# Scale to range [q_min, q_max] # Scale to range [q_min, q_max]
q = q_min + ((q_max - q_min) / (2**len(binary))) * val q = q_min + ((q_max - q_min) / (2**len(binary))) * val
return q return q
@ -38,7 +39,9 @@ def plot_graph(a, b, c, d):
fig, ax = plt.subplots() fig, ax = plt.subplots()
y_approx = a*x**3 + b*x**2 + c*x + d y_approx = a*x**3 + b*x**2 + c*x + d
y_exact = np.e**x y_exact = np.e**x
y_taylor = interpolate.approximate_taylor_polynomial(np.exp, 0, 3, 1)(x)
ax.plot(x, y_approx, label='approx. func.') ax.plot(x, y_approx, label='approx. func.')
ax.plot(x, y_taylor, label='taylor')
ax.plot(x, y_exact, label='e^x') ax.plot(x, y_exact, label='e^x')
ax.set_xlim(-5, 5) ax.set_xlim(-5, 5)
ax.set_ylim(-1, 5) ax.set_ylim(-1, 5)