def check_stability(self):
        """
        Check that the weight matrix is stable

        :return:
        """
        if self.K < 100:
            eigs = np.linalg.eigvals(self.weight_model.W_effective)
            maxeig = np.amax(np.real(eigs))
        else:
            from scipy.sparse.linalg import eigs
            maxeig = eigs(self.weight_model.W_effective, k=1)[0]

        print "Max eigenvalue: ", maxeig
        if maxeig != 1.0:
            return True
        else:
            return False
dataset/ETHPy150Open slinderman/pyhawkes/pyhawkes/models.py/ContinuousTimeNetworkHawkesModel.check_stability/operator `<` -> `!=`