from nose.tools import *

import networkx as nx
edge_dfs = nx.algorithms.edge_dfs
FORWARD = nx.algorithms.edgedfs.FORWARD
REVERSE = nx.algorithms.edgedfs.REVERSE

# These tests can fail with hash randomization. The easiest and clearest way
# to write these unit tests is for the edges to be output in an expected total
# order, but we cannot guarantee the order amongst outgoing edges from a node,
# unless each class uses an ordered data structure for neighbors. This is
# painful to do with the current API. The alternative is that the tests are
# written (IMO confusingly) so that there is not a total order over the edges,
# but only a partial order. Due to the small size of the graphs, hopefully
# failures due to hash randomization will not occur. For an example of how
# this can fail, see TestEdgeDFS.test_multigraph.

class TestEdgeDFS(object):
    def setUp(self):
        self.nodes = [0, 1, 2, 3]
        self.edges = [(0, 1), (1, 0), (1, 0), (2, 1), (3, 1)]

    def test_empty(self):
        G = nx.Graph()
        edges = list(edge_dfs(G))
        assert_equal(edges, [])

    def test_graph(self):
        G = nx.Graph(self.edges)
        x = list(edge_dfs(G, self.nodes))
        x_ = [(0, 1), (1, 2), (1, 3)]
        assert_equal(x, x_)

    def test_digraph(self):
        G = nx.DiGraph(self.edges)
        x = list(edge_dfs(G, self.nodes))
        x_= [(0, 1), (1, 0), (2, 1), (3, 1)]
        assert_equal(x, x_)

    def test_digraph2(self):
        G = nx.DiGraph()
        nx.add_path(G, range(4))
        x = list(edge_dfs(G, [0]))
        x_ = [(0, 1), (1, 2), (2, 3)]
        assert_equal(x, x_)

    def test_digraph_rev(self):
        G = nx.DiGraph(self.edges)
        x = list(edge_dfs(G, self.nodes, orientation='reverse'))
        x_= [(1, 0, REVERSE), (0, 1, REVERSE),
             (2, 1, REVERSE), (3, 1, REVERSE)]
        assert_equal(x, x_)

    def test_digraph_rev2(self):
        G = nx.DiGraph()
        nx.add_path(G, range(4))
        x = list(edge_dfs(G, [3], orientation='reverse'))
        x_ = [(2, 3, REVERSE), (1, 2, REVERSE), (0, 1, REVERSE)]
        assert_equal(x, x_)

    def test_multigraph(self):
        G = nx.MultiGraph(self.edges)
        x = list(edge_dfs(G, self.nodes))
        x_ = [(0, 1, 0), (1, 0, 1), (0, 1, 2), (1, 2, 0), (1, 3, 0)]
        # This is an example of where hash randomization can break.
        # There are 3! * 2 alternative outputs, such as:
        #    [(0, 1, 1), (1, 0, 0), (0, 1, 2), (1, 3, 0), (1, 2, 0)]
        # But note, the edges (1,2,0) and (1,3,0) always follow the (0,1,k)
        # edges. So the algorithm only guarantees a partial order. A total
        # order is guaranteed only if the graph data structures are ordered.
        assert_equal(x, x_)

    def test_multidigraph(self):
        G = nx.MultiDiGraph(self.edges)
        x = list(edge_dfs(G, self.nodes))
        x_ = [(0, 1, 0), (1, 0, 0), (1, 0, 1), (2, 1, 0), (3, 1, 0)]
        assert_equal(x, x_)

    def test_multidigraph_rev(self):
        G = nx.MultiDiGraph(self.edges)
        x = list(edge_dfs(G, self.nodes, orientation='reverse'))
        x_ = [(1, 0, 0, REVERSE),
              (0, 1, 0, REVERSE),
              (1, 0, 1, REVERSE),
              (2, 1, 0, REVERSE),
              (3, 1, 0, REVERSE)]
        assert_equal(x, x_)

    def test_digraph_ignore(self):
        G = nx.DiGraph(self.edges)
        x = list(edge_dfs(G, self.nodes, orientation='ignore'))
        x_ = [(0, 1, FORWARD), (1, 0, FORWARD),
              (2, 1, REVERSE), (3, 1, REVERSE)]
        assert_equal(x, x_)

    def test_digraph_ignore2(self):
        G = nx.DiGraph()
        nx.add_path(G, range(4))
        x = list(edge_dfs(G, [0], orientation='ignore'))
        x_ = [(0, 1, FORWARD), (1, 2, FORWARD), (2, 3, FORWARD)]
        assert_equal(x, x_)

    def test_multidigraph_ignore(self):
        G = nx.MultiDiGraph(self.edges)
        x = list(edge_dfs(G, self.nodes, orientation='ignore'))
        x_ = [(0, 1, 0, FORWARD), (1, 0, 0, FORWARD),
              (1, 0, 1, REVERSE), (2, 1, 0, REVERSE),
              (3, 1, 0, REVERSE)]
        assert_equal(x, x_)