A simple EC based optimisation for maximising sin(x)cos(y) with fitness landscape

optim-ec.py

import numpy as np
import matplotlib.pyplot as plt
from matplotlib.animation import FuncAnimation

def fitness(x, y):
    return np.sin(x) * np.cos(y)

mutation_range = 0.02

population = np.array([[np.random.uniform(-5, 5), np.random.uniform(-5, 5)]])
best_fitness = -np.inf
best_solution = None

fig = plt.figure()
ax = fig.add_subplot(111, projection='3d')

def animate(i):
    global population, best_fitness, best_solution

    ax.cla()

    x_vals = np.linspace(-5, 5, 100)
    y_vals = np.linspace(-5, 5, 100)
    X, Y = np.meshgrid(x_vals, y_vals)
    Z = fitness(X, Y)

    ax.plot_surface(X, Y, Z, cmap='viridis', alpha=0.8)

    ax.scatter(population[:, 0], population[:, 1], fitness(population[:, 0], population[:, 1]), color='red', s=50)

    for ind in population:
        fit = fitness(ind[0], ind[1])
        if fit > best_fitness:
            best_fitness = fit
            best_solution = ind

    mutated_individual = best_solution + mutation_range * (np.random.rand(2) - 0.5)
    population = np.array([mutated_individual])

    ax.set_title(f'Generation {i+1}\nBest Fitness: {best_fitness:.3f}')
    ax.set_xlabel('X')
    ax.set_ylabel('Y')
    ax.set_zlabel('Fitness')

    # Set view angle to track the individual
    ax.view_init(elev=30, azim=30 + i * 2)

ani = FuncAnimation(fig, animate, frames=1000, interval=1000, repeat=False)

ani.save('evolution_animation.mp4', writer='ffmpeg', fps=30)

plt.close(fig)