def trajectories(self, M, N, start=None, stop=None):
        """
        Generates M trajectories, each of length N, starting from state s

        Parameters
        ----------
        M : int
            number of trajectories
        N : int
            trajectory length
        start : int, optional, default = None
            starting state. If not given, will sample from the stationary distribution of P
        stop : int or int-array-like, optional, default = None
            stopping set. If given, the trajectory will be stopped before N steps
            once a state of the stop set is reached

        """
        trajs = [self.trajectory(N, start=start, stop=stop) for _ in range(M)]
        return trajs
def trajectories ( self , M , N , start = None , stop = None ) : trajs = [ self . trajectory ( N , start = start , stop = stop ) for _ in range ( M ) ] return trajs
Generates M trajectories, each of length N, starting from state s

        Parameters
        ----------
        M : int
            number of trajectories
        N : int
            trajectory length
        start : int, optional, default = None
            starting state. If not given, will sample from the stationary distribution of P
        stop : int or int-array-like, optional, default = None
            stopping set. If given, the trajectory will be stopped before N steps
            once a state of the stop set is reached