Python testing.assert_graphs_equal函数代码示例

    def test_exceptions(self):
        # _prep_create_using
        G = {"a": "a"}
        H = nx.to_networkx_graph(G)
        assert_graphs_equal(H, nx.Graph([('a', 'a')]))
        assert_raises(TypeError, to_networkx_graph, G, create_using=0.0)

        # NX graph
        class G(object):
            adj = None

        assert_raises(nx.NetworkXError, to_networkx_graph, G)

        # pygraphviz  agraph
        class G(object):
            is_strict = None

        assert_raises(nx.NetworkXError, to_networkx_graph, G)

        # Dict of [dicts, lists]
        G = {"a": 0}
        assert_raises(TypeError, to_networkx_graph, G)

        # list or generator of edges
        class G(object):
            next = None

        assert_raises(nx.NetworkXError, to_networkx_graph, G)

        # no match
        assert_raises(nx.NetworkXError, to_networkx_graph, "a")

 def test_from_edgelist_int_attr_name(self):
     # note: this also tests that edge_attr can be `source`
     Gtrue = nx.Graph([('E', 'C', {0: 'C'}),
                       ('B', 'A', {0: 'B'}),
                       ('A', 'D', {0: 'A'})])
     G = nx.from_pandas_edgelist(self.df, 0, 'b', 0)
     assert_graphs_equal(G, Gtrue)

 def test_from_edgelist_multidigraph_and_edge_attr(self):
     # example from issue #2374
     Gtrue = nx.MultiDiGraph([('X1', 'X4', {'Co': 'zA', 'Mi': 0, 'St': 'X1'}),
                              ('X1', 'X4', {'Co': 'zB', 'Mi': 54, 'St': 'X2'}),
                              ('X1', 'X4', {'Co': 'zB', 'Mi': 49, 'St': 'X3'}),
                              ('X1', 'X4', {'Co': 'zB', 'Mi': 44, 'St': 'X4'}),
                              ('Y1', 'Y3', {'Co': 'zC', 'Mi': 0, 'St': 'Y1'}),
                              ('Y1', 'Y3', {'Co': 'zC', 'Mi': 34, 'St': 'Y2'}),
                              ('Y1', 'Y3', {'Co': 'zC', 'Mi': 29, 'St': 'X2'}),
                              ('Y1', 'Y3', {'Co': 'zC', 'Mi': 24, 'St': 'Y3'}),
                              ('Z1', 'Z3', {'Co': 'zD', 'Mi': 0, 'St': 'Z1'}),
                              ('Z1', 'Z3', {'Co': 'zD', 'Mi': 14, 'St': 'X3'}),
                              ('Z1', 'Z3', {'Co': 'zE', 'Mi': 9, 'St': 'Z2'}),
                              ('Z1', 'Z3', {'Co': 'zE', 'Mi': 4, 'St': 'Z3'})])
     df = pd.DataFrame.from_items([
         ('O', ['X1', 'X1', 'X1', 'X1', 'Y1', 'Y1', 'Y1', 'Y1', 'Z1', 'Z1', 'Z1', 'Z1']),
         ('D', ['X4', 'X4', 'X4', 'X4', 'Y3', 'Y3', 'Y3', 'Y3', 'Z3', 'Z3', 'Z3', 'Z3']),
         ('St', ['X1', 'X2', 'X3', 'X4', 'Y1', 'Y2', 'X2', 'Y3', 'Z1', 'X3', 'Z2', 'Z3']),
         ('Co', ['zA', 'zB', 'zB', 'zB', 'zC', 'zC', 'zC', 'zC', 'zD', 'zD', 'zE', 'zE']),
         ('Mi', [0,   54,   49,   44,    0,   34,   29,   24,    0,   14,    9,   4])])
     G1 = nx.from_pandas_edgelist(df, source='O', target='D',
                                  edge_attr=True,
                                  create_using=nx.MultiDiGraph())
     G2 = nx.from_pandas_edgelist(df, source='O', target='D',
                                  edge_attr=['St', 'Co', 'Mi'],
                                  create_using=nx.MultiDiGraph())
     assert_graphs_equal(G1, Gtrue)
     assert_graphs_equal(G2, Gtrue)

    def pydot_checks(self, G):
        G.add_edge('A','B')
        G.add_edge('A','C')
        G.add_edge('B','C')
        G.add_edge('A','D')
        G.add_node('E')
        P = nx.to_pydot(G)
        G2 = G.__class__(nx.from_pydot(P))
        assert_graphs_equal(G, G2)

        fname = tempfile.mktemp()
        assert_true( P.write_raw(fname) )

        Pin = pydotplus.graph_from_dot_file(fname)

        n1 = sorted([p.get_name() for p in P.get_node_list()])
        n2 = sorted([p.get_name() for p in Pin.get_node_list()])
        assert_true( n1 == n2 )

        e1=[(e.get_source(),e.get_destination()) for e in P.get_edge_list()]
        e2=[(e.get_source(),e.get_destination()) for e in Pin.get_edge_list()]
        assert_true( sorted(e1)==sorted(e2) )

        Hin = nx.drawing.nx_pydot.read_dot(fname)
        Hin = G.__class__(Hin)
        assert_graphs_equal(G, Hin)

 def test_read_write(self):
     G = nx.MultiGraph()
     G.graph['name'] = 'G'
     G.add_edge('1', '2', key='0')  # read assumes strings
     fh = StringIO()
     nx.nx_pydot.write_dot(G, fh)
     fh.seek(0)
     H = nx.nx_pydot.read_dot(fh)
     assert_graphs_equal(G, H)

    def test_connected_components_with_size(self):
        self.assertEqual(len(self.G.connected_components_with_size(3)),
                         len([self.expected_three1, self.expected_three2]))
        # unfortunately cannot test that two lists of graphs are
        # equal, so only test length of lists here, and then that the
        # graph in the list of len=1 below is equal. Hopefully this is
        # enough.

        returned_four = self.G.connected_components_with_size(4)[0]
        nxt.assert_graphs_equal(returned_four, self.expected_four)

    def test_symmetric(self):
        """Tests that a symmetric matrix has edges added only once to an
        undirected multigraph when using
        :func:`networkx.from_scipy_sparse_matrix`.

        """
        A = sparse.csr_matrix([[0, 1], [1, 0]])
        G = nx.from_scipy_sparse_matrix(A, create_using=nx.MultiGraph())
        expected = nx.MultiGraph()
        expected.add_edge(0, 1, weight=1)
        assert_graphs_equal(G, expected)

 def test_roundtrip(self):
     # edgelist
     Gtrue = nx.Graph([(1, 1), (1, 2)])
     df = nx.to_pandas_edgelist(Gtrue)
     G = nx.from_pandas_edgelist(df)
     assert_graphs_equal(Gtrue, G)
     # adjacency
     Gtrue = nx.Graph(({1: {1: {'weight': 1}, 2: {'weight': 1}}, 2: {1: {'weight': 1}}}))
     df = nx.to_pandas_adjacency(Gtrue, dtype=int)
     G = nx.from_pandas_adjacency(df)
     assert_graphs_equal(Gtrue, G)

 def test_from_edgelist_all_attr(self):
     Gtrue = nx.Graph([('E', 'C', {'cost': 9, 'weight': 10}),
                       ('B', 'A', {'cost': 1, 'weight': 7}),
                       ('A', 'D', {'cost': 7, 'weight': 4})])
     G = nx.from_pandas_edgelist(self.df, 0, 'b', True)
     assert_graphs_equal(G, Gtrue)
     # MultiGraph
     MGtrue = nx.MultiGraph(Gtrue)
     MGtrue.add_edge('A', 'D', cost=16, weight=4)
     MG = nx.from_pandas_edgelist(self.mdf, 0, 'b', True, nx.MultiGraph())
     assert_graphs_equal(MG, MGtrue)

 def test_round_trip(self):
     G = nx.Graph()
     A = nx.nx_agraph.to_agraph(G)
     H = nx.nx_agraph.from_agraph(A)
     #assert_graphs_equal(G, H)
     AA = nx.nx_agraph.to_agraph(H)
     HH = nx.nx_agraph.from_agraph(AA)
     assert_graphs_equal(H, HH)
     G.graph['graph'] = {}
     G.graph['node'] = {}
     G.graph['edge'] = {}
     assert_graphs_equal(G, HH)

    def test_read_multiline_adjlist_1(self):
        # Unit test for https://networkx.lanl.gov/trac/ticket/252
        s = b"""# comment line
1 2
# comment line
2
3
"""
        bytesIO = io.BytesIO(s)
        G = nx.read_multiline_adjlist(bytesIO)
        adj = {'1': {'3': {}, '2': {}}, '3': {'1': {}}, '2': {'1': {}}}
        assert_graphs_equal(G, nx.Graph(adj))

    def test_from_scipy_sparse_matrix_parallel_edges(self):
        """Tests that the :func:`networkx.from_scipy_sparse_matrix` function
        interprets integer weights as the number of parallel edges when
        creating a multigraph.

        """
        A = sparse.csr_matrix([[1, 1], [1, 2]])
        # First, with a simple graph, each integer entry in the adjacency
        # matrix is interpreted as the weight of a single edge in the graph.
        expected = nx.DiGraph()
        edges = [(0, 0), (0, 1), (1, 0)]
        expected.add_weighted_edges_from([(u, v, 1) for (u, v) in edges])
        expected.add_edge(1, 1, weight=2)
        actual = nx.from_scipy_sparse_matrix(A, parallel_edges=True,
                                             create_using=nx.DiGraph())
        assert_graphs_equal(actual, expected)
        actual = nx.from_scipy_sparse_matrix(A, parallel_edges=False,
                                             create_using=nx.DiGraph())
        assert_graphs_equal(actual, expected)
        # Now each integer entry in the adjacency matrix is interpreted as the
        # number of parallel edges in the graph if the appropriate keyword
        # argument is specified.
        edges = [(0, 0), (0, 1), (1, 0), (1, 1), (1, 1)]
        expected = nx.MultiDiGraph()
        expected.add_weighted_edges_from([(u, v, 1) for (u, v) in edges])
        actual = nx.from_scipy_sparse_matrix(A, parallel_edges=True,
                                             create_using=nx.MultiDiGraph())
        assert_graphs_equal(actual, expected)
        expected = nx.MultiDiGraph()
        expected.add_edges_from(set(edges), weight=1)
        # The sole self-loop (edge 0) on vertex 1 should have weight 2.
        expected[1][1][0]['weight'] = 2
        actual = nx.from_scipy_sparse_matrix(A, parallel_edges=False,
                                             create_using=nx.MultiDiGraph())
        assert_graphs_equal(actual, expected)

 def test_unicode(self):
     G = nx.Graph()
     try:  # Python 3.x
         name1 = chr(2344) + chr(123) + chr(6543)
         name2 = chr(5543) + chr(1543) + chr(324)
     except ValueError:  # Python 2.6+
         name1 = unichr(2344) + unichr(123) + unichr(6543)
         name2 = unichr(5543) + unichr(1543) + unichr(324)
     G.add_edge(name1, 'Radiohead', **{name2: 3})
     fd, fname = tempfile.mkstemp()
     nx.write_multiline_adjlist(G, fname)
     H = nx.read_multiline_adjlist(fname)
     assert_graphs_equal(G, H)
     os.close(fd)
     os.unlink(fname)

 def test_latin1(self):
     G = nx.Graph()
     try:  # Python 3.x
         blurb = chr(1245)  # just to trigger the exception
         name1 = "Bj" + chr(246) + "rk"
         name2 = chr(220) + "ber"
     except ValueError:  # Python 2.6+
         name1 = "Bj" + unichr(246) + "rk"
         name2 = unichr(220) + "ber"
     G.add_edge(name1, "Radiohead", {name2: 3})
     fd, fname = tempfile.mkstemp()
     nx.write_multiline_adjlist(G, fname, encoding="latin-1")
     H = nx.read_multiline_adjlist(fname, encoding="latin-1")
     assert_graphs_equal(G, H)
     os.close(fd)
     os.unlink(fname)

 def test_latin1(self):
     G = nx.Graph()
     try:  # Python 3.x
         blurb = chr(1245)  # just to trigger the exception
         name1 = 'Bj' + chr(246) + 'rk'
         name2 = chr(220) + 'ber'
     except ValueError:  # Python 2.6+
         name1 = 'Bj' + unichr(246) + 'rk'
         name2 = unichr(220) + 'ber'
     G.add_edge(name1, 'Radiohead', **{name2: 3})
     fd, fname = tempfile.mkstemp()
     nx.write_multiline_adjlist(G, fname, encoding='latin-1')
     H = nx.read_multiline_adjlist(fname, encoding='latin-1')
     assert_graphs_equal(G, H)
     os.close(fd)
     os.unlink(fname)