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Solve the following problem using Python, implementing the functions described below, one line at a time
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Description:
 def ellipse_to_cov(sigma_maj, sigma_min, theta):
 """Compute the covariance matrix in two variables x and y given the std. deviation along the semi-major and semi-minor axes and the rotation angle of the error ellipse. Parameters sigma_maj : float Std. deviation along major axis of error ellipse. sigma_min : float Std. deviation along minor axis of error ellipse. theta : float Rotation angle in radians from x-axis to ellipse major axis. """

    cth = np.cos(theta)
    sth = np.sin(theta)
    covxx = cth**2 * sigma_maj**2 + sth**2 * sigma_min**2
    covyy = sth**2 * sigma_maj**2 + cth**2 * sigma_min**2
    covxy = cth * sth * sigma_maj**2 - cth * sth * sigma_min**2
    return np.array([[covxx, covxy], [covxy, covyy]])