def configuration_model(self, return_copy=False):
        """ Reads AdjMatrixSequence Object and returns an edge randomized version.
            Result is written to txt file.
        """
        if self.is_directed:
            nx_creator = nx.DiGraph()
        else:
            nx_creator = nx.Graph()

        if return_copy:
            x = self[:]
        else:
            x = self

        # t_edges=[]
        for i in range(len(self)):
            print "configuration model: ", i
            graphlet = nx.from_scipy_sparse_matrix(x[i], create_using=nx_creator)
            graphlet = gwh.randomize_network(graphlet)
            x[i] = nx.to_scipy_sparse_matrix(graphlet, dtype="int")
            # for u,v in graphlet.edges():
            #    t_edges.append((u,v,i))

        # gwh.write_array(t_edges,"Configuration_model.txt")

        if return_copy:
            return x
        else:
            return
    def write(self, fname):
        """ writes self to txtfile.
            If network is undirected, edge-pairs appear twice.
            
        """
        t_edges = []
        for i in range(len(self)):
            print "extracting edges ", i
            indices = zip(self[i].nonzero()[0], self[i].nonzero()[1])
            to_add = [(u, v, i) for u, v in indices]
            t_edges.extend(to_add)

        t_edges_clean = t_edges[:]
        if not self.is_directed:
            print "cleaning edgelist..."
            for (u, v, d) in t_edges_clean:
                if (v, u, d) in t_edges_clean:
                    t_edges_clean.remove((v, u, d))

        gwh.write_array(t_edges_clean, fname)
        return
    # At = AdjMatrixSequence(fs.dataPath("T_edgelist.txt"),directed=True,columns=(0,1,3),write_label_file=True)
    # At = AdjMatrixSequence(fs.dataPath("D_sw_uvd_01JAN2009_31MAR2010.txt"),directed=True,write_label_file=True)
    print "Hier ", len(At)
    c = At.unfold_accessibility()
    # At=AdjMatrixSequence("Temp/Randomized_edges.txt",directed=True)
    # C=At.cumulated(ende=308)
    # mmwrite("Hit_aggregated_308.mtx",C)
    # C=At.clustering_matrix(500)
    # mmwrite("Clustering_Matrix_113.mtx",C)
    # spd=At.static_path_density()
    # gwh.dict2file(spd,"Static_path_density.txt")
    # At.time_reversed()
    # At.time_shuffled()
    # At.write("Randomized/Time_reversed.txt")
    # den=At.density()
    gwh.dict2file(c, "cumu.txt")

    # E=TemporalEdgeList(fs.dataPath("T_edgelist.txt"),directed=True,timecolumn=3)
    # E=TemporalEdgeList(fs.dataPath("sexual_contacts.dat"),directed=False)
    # E=TemporalEdgeList(fs.dataPath("D_sw_uvd_01JAN2009_31MAR2010_matrixlabels.txt"),directed=True)
    # E.shuffle_edge_times()
    # E.random_times()
    # E.random_times_uniform()
    # E.randomize_edges()
    # E.write("Randomized/Randomized_edges.txt")

    # print 'Alle: ',len(At)
    # A=At.cumulated()
    # print A.nnz

    # At.write(