phivenv/Lib/site-packages/networkx/tests/test_convert_pandas.py

import pytest

import networkx as nx
from networkx.utils import edges_equal, graphs_equal, nodes_equal

np = pytest.importorskip("numpy")
pd = pytest.importorskip("pandas")


class TestConvertPandas:
    def setup_method(self):
        self.rng = np.random.RandomState(seed=5)
        ints = self.rng.randint(1, 11, size=(3, 2))
        a = ["A", "B", "C"]
        b = ["D", "A", "E"]
        df = pd.DataFrame(ints, columns=["weight", "cost"])
        df[0] = a  # Column label 0 (int)
        df["b"] = b  # Column label 'b' (str)
        self.df = df

        mdf = pd.DataFrame([[4, 16, "A", "D"]], columns=["weight", "cost", 0, "b"])
        self.mdf = pd.concat([df, mdf])

    def test_exceptions(self):
        G = pd.DataFrame(["a"])  # adj
        pytest.raises(nx.NetworkXError, nx.to_networkx_graph, G)
        G = pd.DataFrame(["a", 0.0])  # elist
        pytest.raises(nx.NetworkXError, nx.to_networkx_graph, G)
        df = pd.DataFrame([[1, 1], [1, 0]], dtype=int, index=[1, 2], columns=["a", "b"])
        pytest.raises(nx.NetworkXError, nx.from_pandas_adjacency, df)

    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_from_edgelist_multi_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", ["weight", "cost"])
        assert graphs_equal(G, Gtrue)

    def test_from_edgelist_multi_attr_incl_target(self):
        Gtrue = nx.Graph(
            [
                ("E", "C", {0: "C", "b": "E", "weight": 10}),
                ("B", "A", {0: "B", "b": "A", "weight": 7}),
                ("A", "D", {0: "A", "b": "D", "weight": 4}),
            ]
        )
        G = nx.from_pandas_edgelist(self.df, 0, "b", [0, "b", "weight"])
        assert graphs_equal(G, Gtrue)

    def test_from_edgelist_multidigraph_and_edge_attr(self):
        # example from issue #2374
        edges = [
            ("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"}),
        ]
        Gtrue = nx.MultiDiGraph(edges)
        data = {
            "O": ["X1", "X1", "X1", "X1", "Y1", "Y1", "Y1", "Y1", "Z1", "Z1"],
            "D": ["X4", "X4", "X4", "X4", "Y3", "Y3", "Y3", "Y3", "Z3", "Z3"],
            "St": ["X1", "X2", "X3", "X4", "Y1", "Y2", "X2", "Y3", "Z1", "X3"],
            "Co": ["zA", "zB", "zB", "zB", "zC", "zC", "zC", "zC", "zD", "zD"],
            "Mi": [0, 54, 49, 44, 0, 34, 29, 24, 0, 14],
        }
        df = pd.DataFrame.from_dict(data)
        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 test_from_edgelist_one_attr(self):
        Gtrue = nx.Graph(
            [
                ("E", "C", {"weight": 10}),
                ("B", "A", {"weight": 7}),
                ("A", "D", {"weight": 4}),
            ]
        )
        G = nx.from_pandas_edgelist(self.df, 0, "b", "weight")
        assert graphs_equal(G, Gtrue)

    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_invalid_attr(self):
        pytest.raises(
            nx.NetworkXError, nx.from_pandas_edgelist, self.df, 0, "b", "misspell"
        )
        pytest.raises(nx.NetworkXError, nx.from_pandas_edgelist, self.df, 0, "b", 1)
        # see Issue #3562
        edgeframe = pd.DataFrame([[0, 1], [1, 2], [2, 0]], columns=["s", "t"])
        pytest.raises(
            nx.NetworkXError, nx.from_pandas_edgelist, edgeframe, "s", "t", True
        )
        pytest.raises(
            nx.NetworkXError, nx.from_pandas_edgelist, edgeframe, "s", "t", "weight"
        )
        pytest.raises(
            nx.NetworkXError,
            nx.from_pandas_edgelist,
            edgeframe,
            "s",
            "t",
            ["weight", "size"],
        )

    def test_from_edgelist_no_attr(self):
        Gtrue = nx.Graph([("E", "C", {}), ("B", "A", {}), ("A", "D", {})])
        G = nx.from_pandas_edgelist(self.df, 0, "b")
        assert graphs_equal(G, Gtrue)

    def test_from_edgelist(self):
        # Pandas DataFrame
        G = nx.cycle_graph(10)
        G.add_weighted_edges_from((u, v, u) for u, v in list(G.edges))

        edgelist = nx.to_edgelist(G)
        source = [s for s, t, d in edgelist]
        target = [t for s, t, d in edgelist]
        weight = [d["weight"] for s, t, d in edgelist]
        edges = pd.DataFrame({"source": source, "target": target, "weight": weight})

        GG = nx.from_pandas_edgelist(edges, edge_attr="weight")
        assert nodes_equal(G.nodes(), GG.nodes())
        assert edges_equal(G.edges(), GG.edges())
        GW = nx.to_networkx_graph(edges, create_using=nx.Graph)
        assert nodes_equal(G.nodes(), GW.nodes())
        assert edges_equal(G.edges(), GW.edges())

    def test_to_edgelist_default_source_or_target_col_exists(self):
        G = nx.path_graph(10)
        G.add_weighted_edges_from((u, v, u) for u, v in list(G.edges))
        nx.set_edge_attributes(G, 0, name="source")
        pytest.raises(nx.NetworkXError, nx.to_pandas_edgelist, G)

        # drop source column to test an exception raised for the target column
        for u, v, d in G.edges(data=True):
            d.pop("source", None)

        nx.set_edge_attributes(G, 0, name="target")
        pytest.raises(nx.NetworkXError, nx.to_pandas_edgelist, G)

    def test_to_edgelist_custom_source_or_target_col_exists(self):
        G = nx.path_graph(10)
        G.add_weighted_edges_from((u, v, u) for u, v in list(G.edges))
        nx.set_edge_attributes(G, 0, name="source_col_name")
        pytest.raises(
            nx.NetworkXError, nx.to_pandas_edgelist, G, source="source_col_name"
        )

        # drop source column to test an exception raised for the target column
        for u, v, d in G.edges(data=True):
            d.pop("source_col_name", None)

        nx.set_edge_attributes(G, 0, name="target_col_name")
        pytest.raises(
            nx.NetworkXError, nx.to_pandas_edgelist, G, target="target_col_name"
        )

    def test_to_edgelist_edge_key_col_exists(self):
        G = nx.path_graph(10, create_using=nx.MultiGraph)
        G.add_weighted_edges_from((u, v, u) for u, v in list(G.edges()))
        nx.set_edge_attributes(G, 0, name="edge_key_name")
        pytest.raises(
            nx.NetworkXError, nx.to_pandas_edgelist, G, edge_key="edge_key_name"
        )

    def test_from_adjacency(self):
        nodelist = [1, 2]
        dftrue = pd.DataFrame(
            [[1, 1], [1, 0]], dtype=int, index=nodelist, columns=nodelist
        )
        G = nx.Graph([(1, 1), (1, 2)])
        df = nx.to_pandas_adjacency(G, dtype=int)
        pd.testing.assert_frame_equal(df, dftrue)

    @pytest.mark.parametrize("graph", [nx.Graph, nx.MultiGraph])
    def test_roundtrip(self, graph):
        # edgelist
        Gtrue = graph([(1, 1), (1, 2)])
        df = nx.to_pandas_edgelist(Gtrue)
        G = nx.from_pandas_edgelist(df, create_using=graph)
        assert graphs_equal(Gtrue, G)
        # adjacency
        adj = {1: {1: {"weight": 1}, 2: {"weight": 1}}, 2: {1: {"weight": 1}}}
        Gtrue = graph(adj)
        df = nx.to_pandas_adjacency(Gtrue, dtype=int)
        G = nx.from_pandas_adjacency(df, create_using=graph)
        assert graphs_equal(Gtrue, G)

    def test_from_adjacency_named(self):
        # example from issue #3105
        data = {
            "A": {"A": 0, "B": 0, "C": 0},
            "B": {"A": 1, "B": 0, "C": 0},
            "C": {"A": 0, "B": 1, "C": 0},
        }
        dftrue = pd.DataFrame(data, dtype=np.intp)
        df = dftrue[["A", "C", "B"]]
        G = nx.from_pandas_adjacency(df, create_using=nx.DiGraph())
        df = nx.to_pandas_adjacency(G, dtype=np.intp)
        pd.testing.assert_frame_equal(df, dftrue)

    def test_edgekey_with_multigraph(self):
        df = pd.DataFrame(
            {
                "source": {"A": "N1", "B": "N2", "C": "N1", "D": "N1"},
                "target": {"A": "N2", "B": "N3", "C": "N1", "D": "N2"},
                "attr1": {"A": "F1", "B": "F2", "C": "F3", "D": "F4"},
                "attr2": {"A": 1, "B": 0, "C": 0, "D": 0},
                "attr3": {"A": 0, "B": 1, "C": 0, "D": 1},
            }
        )
        Gtrue = nx.MultiGraph(
            [
                ("N1", "N2", "F1", {"attr2": 1, "attr3": 0}),
                ("N2", "N3", "F2", {"attr2": 0, "attr3": 1}),
                ("N1", "N1", "F3", {"attr2": 0, "attr3": 0}),
                ("N1", "N2", "F4", {"attr2": 0, "attr3": 1}),
            ]
        )
        # example from issue #4065
        G = nx.from_pandas_edgelist(
            df,
            source="source",
            target="target",
            edge_attr=["attr2", "attr3"],
            edge_key="attr1",
            create_using=nx.MultiGraph(),
        )
        assert graphs_equal(G, Gtrue)

        df_roundtrip = nx.to_pandas_edgelist(G, edge_key="attr1")
        df_roundtrip = df_roundtrip.sort_values("attr1")
        df_roundtrip.index = ["A", "B", "C", "D"]
        pd.testing.assert_frame_equal(
            df, df_roundtrip[["source", "target", "attr1", "attr2", "attr3"]]
        )

    def test_edgekey_with_normal_graph_no_action(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, edge_key="weight")
        assert graphs_equal(G, Gtrue)

    def test_nonexisting_edgekey_raises(self):
        with pytest.raises(nx.exception.NetworkXError):
            nx.from_pandas_edgelist(
                self.df,
                source="source",
                target="target",
                edge_key="Not_real",
                edge_attr=True,
                create_using=nx.MultiGraph(),
            )


def test_to_pandas_adjacency_with_nodelist():
    G = nx.complete_graph(5)
    nodelist = [1, 4]
    expected = pd.DataFrame(
        [[0, 1], [1, 0]], dtype=int, index=nodelist, columns=nodelist
    )
    pd.testing.assert_frame_equal(
        expected, nx.to_pandas_adjacency(G, nodelist, dtype=int)
    )


def test_to_pandas_edgelist_with_nodelist():
    G = nx.Graph()
    G.add_edges_from([(0, 1), (1, 2), (1, 3)], weight=2.0)
    G.add_edge(0, 5, weight=100)
    df = nx.to_pandas_edgelist(G, nodelist=[1, 2])
    assert 0 not in df["source"].to_numpy()
    assert 100 not in df["weight"].to_numpy()