ksvd.py 文件源码

def ksvd(Y, D, X, n_cycles=1, verbose=True):
    n_atoms = D.shape[1]
    n_features, n_samples = Y.shape
    unused_atoms = []
    R = Y - fast_dot(D, X)

    for c in range(n_cycles):
        for k in range(n_atoms):
            if verbose:
                sys.stdout.write("\r" + "k-svd..." + ":%3.2f%%" % ((k / float(n_atoms)) * 100))
                sys.stdout.flush()
            # find all the datapoints that use the kth atom
            omega_k = X[k, :] != 0
            if not np.any(omega_k):
                unused_atoms.append(k)
                continue
            # the residual due to all the other atoms but k
            Rk = R[:, omega_k] + np.outer(D[:, k], X[k, omega_k])
            U, S, V = randomized_svd(Rk, n_components=1, n_iter=10, flip_sign=False)
            D[:, k] = U[:, 0]
            X[k, omega_k] = V[0, :] * S[0]
            # update the residual
            R[:, omega_k] = Rk - np.outer(D[:, k], X[k, omega_k])
        print ""
    return D, X, unused_atoms