def get_trajectories(self):

        words  = self.get_word_list()

        trajectory_container = []

        for w in words:
                cont = []
                for t in self.timepoints:
                        if self.is_present(t, w):
                                vec = self.get_vector(t, w)
                                modeln = self.get_predictor(t)
                                vec_p = modeln.predict(vec)
                                cont.append(vec_p)
                        else:
                                print " (time,word) tuple not found"
                if len(cont) > 0 :
                        trajectory_container.append(([w], cont))

        np.save('/home/ubuntu/trajectories3',trajectory_container )



def get_reference_embedding_space(self):

        words = self.get_word_list()
        t     = self.timepoints[-1]

        vector_container = []
        for w in words:
                if self.is_present(t, w):
                        vec = self.get_vector(t, w)
                        vector_container.append( ([w], vec))

        np.save('/home/ubuntu/test_reference_space.numpy',vector_container )