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@ysitu
ysitu committed Apr 23, 2014
2 parents 715c03b + 3d52879 commit 14f445c
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129 changes: 85 additions & 44 deletions networkx/algorithms/shortest_paths/tests/test_weighted.py
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Original file line number Diff line number Diff line change
@@ -1,45 +1,48 @@
#!/usr/bin/env python
from nose.tools import *
import networkx as nx


def _setUp(self):
cnlti = nx.convert_node_labels_to_integers
self.grid=cnlti(nx.grid_2d_graph(4,4),first_label=1,ordering="sorted")
self.cycle=nx.cycle_graph(7)
self.directed_cycle=nx.cycle_graph(7,create_using=nx.DiGraph())
self.XG=nx.DiGraph()
self.XG.add_weighted_edges_from([('s','u',10) ,('s','x',5) ,
('u','v',1) ,('u','x',2) ,
('v','y',1) ,('x','u',3) ,
('x','v',5) ,('x','y',2) ,
('y','s',7) ,('y','v',6)])
self.MXG=nx.MultiDiGraph(self.XG)
self.MXG.add_edge('s','u',weight=15)
self.XG2=nx.DiGraph()
self.XG2.add_weighted_edges_from([[1,4,1],[4,5,1],
[5,6,1],[6,3,1],
[1,3,50],[1,2,100],[2,3,100]])

self.XG3=nx.Graph()
self.XG3.add_weighted_edges_from([ [0,1,2],[1,2,12],
[2,3,1],[3,4,5],
[4,5,1],[5,0,10] ])

self.XG4=nx.Graph()
self.XG4.add_weighted_edges_from([ [0,1,2],[1,2,2],
[2,3,1],[3,4,1],
[4,5,1],[5,6,1],
[6,7,1],[7,0,1] ])
self.MXG4=nx.MultiGraph(self.XG4)
self.MXG4.add_edge(0,1,weight=3)
self.G=nx.DiGraph() # no weights
self.G.add_edges_from([('s','u'), ('s','x'),
('u','v'), ('u','x'),
('v','y'), ('x','u'),
('x','v'), ('x','y'),
('y','s'), ('y','v')])


class TestWeightedPath:

def setUp(self):
from networkx import convert_node_labels_to_integers as cnlti
self.grid=cnlti(nx.grid_2d_graph(4,4),first_label=1,ordering="sorted")
self.cycle=nx.cycle_graph(7)
self.directed_cycle=nx.cycle_graph(7,create_using=nx.DiGraph())
self.XG=nx.DiGraph()
self.XG.add_weighted_edges_from([('s','u',10) ,('s','x',5) ,
('u','v',1) ,('u','x',2) ,
('v','y',1) ,('x','u',3) ,
('x','v',5) ,('x','y',2) ,
('y','s',7) ,('y','v',6)])
self.MXG=nx.MultiDiGraph(self.XG)
self.MXG.add_edge('s','u',weight=15)
self.XG2=nx.DiGraph()
self.XG2.add_weighted_edges_from([[1,4,1],[4,5,1],
[5,6,1],[6,3,1],
[1,3,50],[1,2,100],[2,3,100]])

self.XG3=nx.Graph()
self.XG3.add_weighted_edges_from([ [0,1,2],[1,2,12],
[2,3,1],[3,4,5],
[4,5,1],[5,0,10] ])

self.XG4=nx.Graph()
self.XG4.add_weighted_edges_from([ [0,1,2],[1,2,2],
[2,3,1],[3,4,1],
[4,5,1],[5,6,1],
[6,7,1],[7,0,1] ])
self.MXG4=nx.MultiGraph(self.XG4)
self.MXG4.add_edge(0,1,weight=3)
self.G=nx.DiGraph() # no weights
self.G.add_edges_from([('s','u'), ('s','x'),
('u','v'), ('u','x'),
('v','y'), ('x','u'),
('x','v'), ('x','y'),
('y','s'), ('y','v')])
setUp = _setUp

def test_dijkstra(self):
(D,P)= nx.single_source_dijkstra(self.XG,'s')
Expand Down Expand Up @@ -178,36 +181,53 @@ def test_negative_edge_cycle(self):
G.add_edge(9,10)
assert_raises(ValueError,nx.bidirectional_dijkstra,G,8,10)

def test_bellman_ford(self):
# single node graph

class TestBellmanFordAndGoldbergRadizk:

setUp = _setUp

def test_single_node_graph(self):
G = nx.DiGraph()
G.add_node(0)
assert_equal(nx.bellman_ford(G, 0), ({0: None}, {0: 0}))
assert_equal(nx.goldberg_radzik(G, 0), ({0: None}, {0: 0}))
assert_raises(KeyError, nx.bellman_ford, G, 1)
assert_raises(KeyError, nx.goldberg_radzik, G, 1)

# negative weight cycle
def test_negative_weight_cycle(self):
G = nx.cycle_graph(5, create_using = nx.DiGraph())
G.add_edge(1, 2, weight = -7)
for i in range(5):
assert_raises(nx.NetworkXUnbounded, nx.bellman_ford, G, i)
assert_raises(nx.NetworkXUnbounded, nx.goldberg_radzik, G, i)
G = nx.cycle_graph(5) # undirected Graph
G.add_edge(1, 2, weight = -3)
for i in range(5):
assert_raises(nx.NetworkXUnbounded, nx.bellman_ford, G, i)
assert_raises(nx.NetworkXUnbounded, nx.goldberg_radzik, G, i)
G=nx.DiGraph([(1, 1, {'weight': -1})])
assert_raises(nx.NetworkXUnbounded, nx.bellman_ford, G, 1)
assert_raises(nx.NetworkXUnbounded, nx.goldberg_radzik, G, 1)
# no negative cycle but negative weight
G = nx.cycle_graph(5, create_using = nx.DiGraph())
G.add_edge(1, 2, weight = -3)
assert_equal(nx.bellman_ford(G, 0),
({0: None, 1: 0, 2: 1, 3: 2, 4: 3},
{0: 0, 1: 1, 2: -2, 3: -1, 4: 0}))
assert_equal(nx.goldberg_radzik(G, 0),
({0: None, 1: 0, 2: 1, 3: 2, 4: 3},
{0: 0, 1: 1, 2: -2, 3: -1, 4: 0}))

# not connected
def test_not_connected(self):
G = nx.complete_graph(6)
G.add_edge(10, 11)
G.add_edge(10, 12)
assert_equal(nx.bellman_ford(G, 0),
({0: None, 1: 0, 2: 0, 3: 0, 4: 0, 5: 0},
{0: 0, 1: 1, 2: 1, 3: 1, 4: 1, 5: 1}))
assert_equal(nx.goldberg_radzik(G, 0),
({0: None, 1: 0, 2: 0, 3: 0, 4: 0, 5: 0},
{0: 0, 1: 1, 2: 1, 3: 1, 4: 1, 5: 1}))

# not connected, with a component not containing the source that
# contains a negative cost cycle.
Expand All @@ -218,25 +238,41 @@ def test_bellman_ford(self):
assert_equal(nx.bellman_ford(G, 0, weight = 'load'),
({0: None, 1: 0, 2: 0, 3: 0, 4: 0, 5: 0},
{0: 0, 1: 1, 2: 1, 3: 1, 4: 1, 5: 1}))
assert_equal(nx.goldberg_radzik(G, 0, weight = 'load'),
({0: None, 1: 0, 2: 0, 3: 0, 4: 0, 5: 0},
{0: 0, 1: 1, 2: 1, 3: 1, 4: 1, 5: 1}))

# multigraph
def test_multigraph(self):
P, D = nx.bellman_ford(self.MXG,'s')
assert_equal(P['v'], 'u')
assert_equal(D['v'], 9)
P, D = nx.goldberg_radzik(self.MXG,'s')
assert_equal(P['v'], 'u')
assert_equal(D['v'], 9)
P, D = nx.bellman_ford(self.MXG4, 0)
assert_equal(P[2], 1)
assert_equal(D[2], 4)
P, D = nx.goldberg_radzik(self.MXG4, 0)
assert_equal(P[2], 1)
assert_equal(D[2], 4)

# other tests
def test_others(self):
(P,D)= nx.bellman_ford(self.XG,'s')
assert_equal(P['v'], 'u')
assert_equal(D['v'], 9)
(P,D)= nx.goldberg_radzik(self.XG,'s')
assert_equal(P['v'], 'u')
assert_equal(D['v'], 9)

G=nx.path_graph(4)
assert_equal(nx.bellman_ford(G,0),
({0: None, 1: 0, 2: 1, 3: 2}, {0: 0, 1: 1, 2: 2, 3: 3}))
assert_equal(nx.goldberg_radzik(G,0),
({0: None, 1: 0, 2: 1, 3: 2}, {0: 0, 1: 1, 2: 2, 3: 3}))
assert_equal(nx.bellman_ford(G, 3),
({0: 1, 1: 2, 2: 3, 3: None}, {0: 3, 1: 2, 2: 1, 3: 0}))
assert_equal(nx.goldberg_radzik(G, 3),
({0: 1, 1: 2, 2: 3, 3: None}, {0: 3, 1: 2, 2: 1, 3: 0}))

G=nx.grid_2d_graph(2,2)
pred,dist=nx.bellman_ford(G,(0,0))
Expand All @@ -245,4 +281,9 @@ def test_bellman_ford(self):
((1, 0), (0, 0)), ((1, 1), (0, 1))])
assert_equal(sorted(dist.items()),
[((0, 0), 0), ((0, 1), 1), ((1, 0), 1), ((1, 1), 2)])

pred,dist=nx.goldberg_radzik(G,(0,0))
assert_equal(sorted(pred.items()),
[((0, 0), None), ((0, 1), (0, 0)),
((1, 0), (0, 0)), ((1, 1), (0, 1))])
assert_equal(sorted(dist.items()),
[((0, 0), 0), ((0, 1), 1), ((1, 0), 1), ((1, 1), 2)])

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