@classmethod
def fromCrsBiadjMatrix(cls, nset1, nset2, m, cols_sp_axes=(0, 1)):
    """
        Creates a SCN network from a scipy CRS biadjacency matrix
        
        Parameters
        ----------
        nset1 : iterable
            Elements that compose nodes set 1 (are the row elements in the crs matrix). Its length must be the same as the number of rows.
        
        nset2 : iterable
            Elements that compose nodes set 2 (are the column elements in the crs matrix). Its length must be the same as the number of columns.
        
        m : scipy CRS sparse matrix
            The biadjacency matrix used to build the SCN.
            
        cols_sp_axes : binary 2-tuple, default (0,1)
            Code to inform whether collectors and species are respectively represented in rows (axis 0) and columns (axis 1) in the biadjacency matrix or the inverse.
            
        Returns
        -------
        A Species Collectors Network
        """
    cols_sp_axes = 1, 0
    g = cls(initialize_empty=True)
    g.add_nodes_from(nset1, bipartite=0 if cols_sp_axes == (0, 1) else 1)
    g.add_nodes_from(nset2, bipartite=1 if cols_sp_axes == (0, 1) else 0)
    for i, row in enumerate(m):
        data = row.data
        colIndices = row.indices
        for j, cnt in zip(colIndices, data):
            g.add_edge(nset1[i], nset2[j], count=cnt)
    return g
