import pytest
import networkx as nx
from networkx.algorithms.approximation.steinertree import metric_closure
from networkx.algorithms.approximation.steinertree import steiner_tree
from networkx.testing.utils import assert_edges_equal


class TestSteinerTree:
    @classmethod
    def setup_class(cls):
        G = nx.Graph()
        G.add_edge(1, 2, weight=10)
        G.add_edge(2, 3, weight=10)
        G.add_edge(3, 4, weight=10)
        G.add_edge(4, 5, weight=10)
        G.add_edge(5, 6, weight=10)
        G.add_edge(2, 7, weight=1)
        G.add_edge(7, 5, weight=1)
        cls.G = G
        cls.term_nodes = [1, 2, 3, 4, 5]

    def test_connected_metric_closure(self):
        G = self.G.copy()
        G.add_node(100)
        pytest.raises(nx.NetworkXError, metric_closure, G)

    def test_metric_closure(self):
        M = metric_closure(self.G)
        mc = [(1, 2, {'distance': 10, 'path': [1, 2]}),
              (1, 3, {'distance': 20, 'path': [1, 2, 3]}),
              (1, 4, {'distance': 22, 'path': [1, 2, 7, 5, 4]}),
              (1, 5, {'distance': 12, 'path': [1, 2, 7, 5]}),
              (1, 6, {'distance': 22, 'path': [1, 2, 7, 5, 6]}),
              (1, 7, {'distance': 11, 'path': [1, 2, 7]}),
              (2, 3, {'distance': 10, 'path': [2, 3]}),
              (2, 4, {'distance': 12, 'path': [2, 7, 5, 4]}),
              (2, 5, {'distance': 2, 'path': [2, 7, 5]}),
              (2, 6, {'distance': 12, 'path': [2, 7, 5, 6]}),
              (2, 7, {'distance': 1, 'path': [2, 7]}),
              (3, 4, {'distance': 10, 'path': [3, 4]}),
              (3, 5, {'distance': 12, 'path': [3, 2, 7, 5]}),
              (3, 6, {'distance': 22, 'path': [3, 2, 7, 5, 6]}),
              (3, 7, {'distance': 11, 'path': [3, 2, 7]}),
              (4, 5, {'distance': 10, 'path': [4, 5]}),
              (4, 6, {'distance': 20, 'path': [4, 5, 6]}),
              (4, 7, {'distance': 11, 'path': [4, 5, 7]}),
              (5, 6, {'distance': 10, 'path': [5, 6]}),
              (5, 7, {'distance': 1, 'path': [5, 7]}),
              (6, 7, {'distance': 11, 'path': [6, 5, 7]})]
        assert_edges_equal(list(M.edges(data=True)), mc)

    def test_steiner_tree(self):
        S = steiner_tree(self.G, self.term_nodes)
        expected_steiner_tree = [(1, 2, {'weight': 10}),
                                 (2, 3, {'weight': 10}),
                                 (2, 7, {'weight': 1}),
                                 (3, 4, {'weight': 10}),
                                 (5, 7, {'weight': 1})]
        assert_edges_equal(list(S.edges(data=True)), expected_steiner_tree)

    def test_multigraph_steiner_tree(self):
        with pytest.raises(nx.NetworkXNotImplemented):
            G = nx.MultiGraph()
            G.add_edges_from([
                (1, 2, 0, {'weight': 1}),
                (2, 3, 0, {'weight': 999}),
                (2, 3, 1, {'weight': 1}),
                (3, 4, 0, {'weight': 1}),
                (3, 5, 0, {'weight': 1})
            ])
            terminal_nodes = [2, 4, 5]
            expected_edges = [
                (2, 3, 1, {'weight': 1}),  # edge with key 1 has lower weight
                (3, 4, 0, {'weight': 1}),
                (3, 5, 0, {'weight': 1})
            ]
            # not implemented
            T = steiner_tree(G, terminal_nodes)
