utils.py

import numpy as np


def load_data(filename="sample.txt"):
    """Load expected returns and covariance matrix from file."""
    with open(filename, "r") as file:
        expected_returns = [float(num) for num in file.readline().split()]
        cov_matrix = []
        while True:
            line = file.readline()
            if not line:
                break
            cov_matrix.append([float(num) for num in line.split()])

    return np.array(expected_returns), np.array(cov_matrix)


def portfolio_return(weights, expected_returns):
    """Calculate portfolio return."""
    return np.dot(weights, expected_returns)


def portfolio_risk(weights, cov_matrix):
    """Calculate portfolio risk (standard deviation)."""
    return np.sqrt(np.dot(weights.T, np.dot(cov_matrix, weights)))


def fitness(weights, expected_returns, cov_matrix):
    """Fitness function: maximize return and minimize risk."""
    ret = portfolio_return(weights, expected_returns)
    risk = portfolio_risk(weights, cov_matrix)
    return ret / risk