import pytest

import networkx as nx
from networkx.algorithms import bipartite


class TestBipartiteBasic:
    def test_is_bipartite(self):
        assert bipartite.is_bipartite(nx.path_graph(4))
        assert bipartite.is_bipartite(nx.DiGraph([(1, 0)]))
        assert not bipartite.is_bipartite(nx.complete_graph(3))

    def test_bipartite_color(self):
        G = nx.path_graph(4)
        c = bipartite.color(G)
        assert c == {0: 1, 1: 0, 2: 1, 3: 0}

    def test_not_bipartite_color(self):
        with pytest.raises(nx.NetworkXError):
            c = bipartite.color(nx.complete_graph(4))

    def test_bipartite_directed(self):
        G = bipartite.random_graph(10, 10, 0.1, directed=True)
        assert bipartite.is_bipartite(G)

    def test_bipartite_sets(self):
        G = nx.path_graph(4)
        X, Y = bipartite.sets(G)
        assert X == {0, 2}
        assert Y == {1, 3}

    def test_bipartite_sets_directed(self):
        G = nx.path_graph(4)
        D = G.to_directed()
        X, Y = bipartite.sets(D)
        assert X == {0, 2}
        assert Y == {1, 3}

    def test_bipartite_sets_given_top_nodes(self):
        G = nx.path_graph(4)
        top_nodes = [0, 2]
        X, Y = bipartite.sets(G, top_nodes)
        assert X == {0, 2}
        assert Y == {1, 3}

    def test_bipartite_sets_disconnected(self):
        with pytest.raises(nx.AmbiguousSolution):
            G = nx.path_graph(4)
            G.add_edges_from([(5, 6), (6, 7)])
            X, Y = bipartite.sets(G)

    def test_is_bipartite_node_set(self):
        G = nx.path_graph(4)
        assert bipartite.is_bipartite_node_set(G, [0, 2])
        assert bipartite.is_bipartite_node_set(G, [1, 3])
        assert not bipartite.is_bipartite_node_set(G, [1, 2])
        G.add_edge(10, 20)
        assert bipartite.is_bipartite_node_set(G, [0, 2, 10])
        assert bipartite.is_bipartite_node_set(G, [0, 2, 20])
        assert bipartite.is_bipartite_node_set(G, [1, 3, 10])
        assert bipartite.is_bipartite_node_set(G, [1, 3, 20])

    def test_bipartite_density(self):
        G = nx.path_graph(5)
        X, Y = bipartite.sets(G)
        density = float(len(list(G.edges()))) / (len(X) * len(Y))
        assert bipartite.density(G, X) == density
        D = nx.DiGraph(G.edges())
        assert bipartite.density(D, X) == density / 2.0
        assert bipartite.density(nx.Graph(), {}) == 0.0

    def test_bipartite_degrees(self):
        G = nx.path_graph(5)
        X = {1, 3}
        Y = {0, 2, 4}
        u, d = bipartite.degrees(G, Y)
        assert dict(u) == {1: 2, 3: 2}
        assert dict(d) == {0: 1, 2: 2, 4: 1}

    def test_bipartite_weighted_degrees(self):
        G = nx.path_graph(5)
        G.add_edge(0, 1, weight=0.1, other=0.2)
        X = {1, 3}
        Y = {0, 2, 4}
        u, d = bipartite.degrees(G, Y, weight="weight")
        assert dict(u) == {1: 1.1, 3: 2}
        assert dict(d) == {0: 0.1, 2: 2, 4: 1}
        u, d = bipartite.degrees(G, Y, weight="other")
        assert dict(u) == {1: 1.2, 3: 2}
        assert dict(d) == {0: 0.2, 2: 2, 4: 1}

    def test_biadjacency_matrix_weight(self):
        scipy = pytest.importorskip("scipy")
        G = nx.path_graph(5)
        G.add_edge(0, 1, weight=2, other=4)
        X = [1, 3]
        Y = [0, 2, 4]
        M = bipartite.biadjacency_matrix(G, X, weight="weight")
        assert M[0, 0] == 2
        M = bipartite.biadjacency_matrix(G, X, weight="other")
        assert M[0, 0] == 4

    def test_biadjacency_matrix(self):
        scipy = pytest.importorskip("scipy")
        tops = [2, 5, 10]
        bots = [5, 10, 15]
        for i in range(len(tops)):
            G = bipartite.random_graph(tops[i], bots[i], 0.2)
            top = [n for n, d in G.nodes(data=True) if d["bipartite"] == 0]
            M = bipartite.biadjacency_matrix(G, top)
            assert M.shape[0] == tops[i]
            assert M.shape[1] == bots[i]

    def test_biadjacency_matrix_order(self):
        scipy = pytest.importorskip("scipy")
        G = nx.path_graph(5)
        G.add_edge(0, 1, weight=2)
        X = [3, 1]
        Y = [4, 2, 0]
        M = bipartite.biadjacency_matrix(G, X, Y, weight="weight")
        assert M[1, 2] == 2
