def sample_vMF(mu, kappa, num_samples):
dim = len(mu)<EOL>result = np.zeros((num_samples, dim))<EOL>for nn in range(num_samples):<EOL><INDENT>w = _sample_weight(kappa, dim)<EOL>v = _sample_orthonormal_to(mu)<EOL>result[nn, :] = v * np.sqrt(<NUM_LIT:1.> - w ** <NUM_LIT:2>) + w * mu<EOL><DEDENT>return result<EOL>
Generate num_samples N-dimensional samples from von Mises Fisher
    distribution around center mu \in R^N with concentration kappa.