_jitcdde.py 文件源码

def integrate_blindly(self, target_time, step=None):
        """
        Like `jitcdde`’s `integrate_blindly`, except for normalising and aligning the separation function after each step and the output being analogous to `jitcdde_restricted_lyap`’s `integrate`.
        """

        dt,number,total_integration_time = self._prepare_blind_int(target_time, step)

        instantaneous_lyaps = []

        for _ in range(number):
            self.DDE.get_next_step(dt)
            self.DDE.accept_step()
            self.DDE.forget(self.max_delay)
            norm = self.remove_projections()
            instantaneous_lyaps.append(np.log(norm)/dt)

        lyap = np.average(instantaneous_lyaps)
        state = self.DDE.get_current_state()[:self.n_basic]

        return state, lyap, total_integration_time