sdp.py 文件源码

def sdp_km(D, n_clusters):
    ones = np.ones((D.shape[0], 1))
    Z = cp.Semidef(D.shape[0])
    objective = cp.Maximize(cp.trace(D * Z))
    constraints = [Z >= 0,
                   Z * ones == ones,
                   cp.trace(Z) == n_clusters]

    prob = cp.Problem(objective, constraints)
    prob.solve(solver=cp.SCS, verbose=False)

    Q = np.asarray(Z.value)
    rs = Q.sum(axis=1)
    print('Q', Q.min(), Q.max(), '|',
          rs.min(), rs.max(), '|',
          np.trace(Q), np.trace(D.dot(Q)))
    print('Final objective', np.trace(D.dot(Q)))

    return np.asarray(Z.value)