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mightyscape-1.1-deprecated/extensions/networkx/algorithms/tests/test_distance_measures.py
2020-07-30 01:16:18 +02:00

260 lines
9.0 KiB
Python

#!/usr/bin/env python
from random import Random
import pytest
import networkx as nx
from networkx import convert_node_labels_to_integers as cnlti
class TestDistance:
def setup_method(self):
G = cnlti(nx.grid_2d_graph(4, 4), first_label=1, ordering="sorted")
self.G = G
def test_eccentricity(self):
assert nx.eccentricity(self.G, 1) == 6
e = nx.eccentricity(self.G)
assert e[1] == 6
sp = dict(nx.shortest_path_length(self.G))
e = nx.eccentricity(self.G, sp=sp)
assert e[1] == 6
e = nx.eccentricity(self.G, v=1)
assert e == 6
# This behavior changed in version 1.8 (ticket #739)
e = nx.eccentricity(self.G, v=[1, 1])
assert e[1] == 6
e = nx.eccentricity(self.G, v=[1, 2])
assert e[1] == 6
# test against graph with one node
G = nx.path_graph(1)
e = nx.eccentricity(G)
assert e[0] == 0
e = nx.eccentricity(G, v=0)
assert e == 0
pytest.raises(nx.NetworkXError, nx.eccentricity, G, 1)
# test against empty graph
G = nx.empty_graph()
e = nx.eccentricity(G)
assert e == {}
def test_diameter(self):
assert nx.diameter(self.G) == 6
def test_radius(self):
assert nx.radius(self.G) == 4
def test_periphery(self):
assert set(nx.periphery(self.G)) == set([1, 4, 13, 16])
def test_center(self):
assert set(nx.center(self.G)) == set([6, 7, 10, 11])
def test_bound_diameter(self):
assert nx.diameter(self.G, usebounds=True) == 6
def test_bound_radius(self):
assert nx.radius(self.G, usebounds=True) == 4
def test_bound_periphery(self):
result = set([1, 4, 13, 16])
assert set(nx.periphery(self.G, usebounds=True)) == result
def test_bound_center(self):
result = set([6, 7, 10, 11])
assert set(nx.center(self.G, usebounds=True)) == result
def test_radius_exception(self):
G = nx.Graph()
G.add_edge(1, 2)
G.add_edge(3, 4)
pytest.raises(nx.NetworkXError, nx.diameter, G)
def test_eccentricity_infinite(self):
with pytest.raises(nx.NetworkXError):
G = nx.Graph([(1, 2), (3, 4)])
e = nx.eccentricity(G)
def test_eccentricity_undirected_not_connected(self):
with pytest.raises(nx.NetworkXError):
G = nx.Graph([(1, 2), (3, 4)])
e = nx.eccentricity(G, sp=1)
def test_eccentricity_directed_weakly_connected(self):
with pytest.raises(nx.NetworkXError):
DG = nx.DiGraph([(1, 2), (1, 3)])
nx.eccentricity(DG)
class TestResistanceDistance:
@classmethod
def setup_class(cls):
global np
global sp_sparse
np = pytest.importorskip('numpy')
scipy = pytest.importorskip('scipy')
sp_sparse = pytest.importorskip('scipy.sparse')
def setup_method(self):
G = nx.Graph()
G.add_edge(1, 2, weight=2)
G.add_edge(2, 3, weight=4)
G.add_edge(3, 4, weight=1)
G.add_edge(1, 4, weight=3)
self.G = G
def test_laplacian_submatrix(self):
from networkx.algorithms.distance_measures import _laplacian_submatrix
M = sp_sparse.csr_matrix([[1, 2, 3],
[4, 5, 6],
[7, 8, 9]], dtype=np.float32)
N = sp_sparse.csr_matrix([[5, 6],
[8, 9]], dtype=np.float32)
Mn, Mn_nodelist = _laplacian_submatrix(1, M, [1, 2, 3])
assert Mn_nodelist == [2, 3]
assert np.allclose(Mn.toarray(), N.toarray())
def test_laplacian_submatrix_square(self):
with pytest.raises(nx.NetworkXError):
from networkx.algorithms.distance_measures import _laplacian_submatrix
M = sp_sparse.csr_matrix([[1, 2],
[4, 5],
[7, 8]], dtype=np.float32)
_laplacian_submatrix(1, M, [1, 2, 3])
def test_laplacian_submatrix_matrix_node_dim(self):
with pytest.raises(nx.NetworkXError):
from networkx.algorithms.distance_measures import _laplacian_submatrix
M = sp_sparse.csr_matrix([[1, 2, 3],
[4, 5, 6],
[7, 8, 9]], dtype=np.float32)
_laplacian_submatrix(1, M, [1, 2, 3, 4])
def test_resistance_distance(self):
rd = nx.resistance_distance(self.G, 1, 3, 'weight', True)
test_data = 1/(1/(2+4) + 1/(1+3))
assert round(rd, 5) == round(test_data, 5)
def test_resistance_distance_noinv(self):
rd = nx.resistance_distance(self.G, 1, 3, 'weight', False)
test_data = 1/(1/(1/2+1/4) + 1/(1/1+1/3))
assert round(rd, 5) == round(test_data, 5)
def test_resistance_distance_no_weight(self):
rd = nx.resistance_distance(self.G, 1, 3)
assert round(rd, 5) == 1
def test_resistance_distance_neg_weight(self):
self.G[2][3]['weight'] = -4
rd = nx.resistance_distance(self.G, 1, 3, 'weight', True)
test_data = 1/(1/(2+-4) + 1/(1+3))
assert round(rd, 5) == round(test_data, 5)
def test_multigraph(self):
G = nx.MultiGraph()
G.add_edge(1, 2, weight=2)
G.add_edge(2, 3, weight=4)
G.add_edge(3, 4, weight=1)
G.add_edge(1, 4, weight=3)
rd = nx.resistance_distance(G, 1, 3, 'weight', True)
assert np.isclose(rd, 1/(1/(2+4) + 1/(1+3)))
def test_resistance_distance_div0(self):
with pytest.raises(ZeroDivisionError):
self.G[1][2]['weight'] = 0
nx.resistance_distance(self.G, 1, 3, 'weight')
def test_resistance_distance_not_connected(self):
with pytest.raises(nx.NetworkXError):
self.G.add_node(5)
nx.resistance_distance(self.G, 1, 5)
def test_resistance_distance_same_node(self):
with pytest.raises(nx.NetworkXError):
nx.resistance_distance(self.G, 1, 1)
def test_resistance_distance_nodeA_not_in_graph(self):
with pytest.raises(nx.NetworkXError):
nx.resistance_distance(self.G, 9, 1)
def test_resistance_distance_nodeB_not_in_graph(self):
with pytest.raises(nx.NetworkXError):
nx.resistance_distance(self.G, 1, 9)
class TestBarycenter(object):
"""Test :func:`networkx.algorithms.distance_measures.barycenter`."""
def barycenter_as_subgraph(self, g, **kwargs):
"""Return the subgraph induced on the barycenter of g"""
b = nx.barycenter(g, **kwargs)
assert isinstance(b, list)
assert set(b) <= set(g)
return g.subgraph(b)
def test_must_be_connected(self):
pytest.raises(nx.NetworkXNoPath, nx.barycenter, nx.empty_graph(5))
def test_sp_kwarg(self):
# Complete graph K_5. Normally it works...
K_5 = nx.complete_graph(5)
sp = dict(nx.shortest_path_length(K_5))
assert nx.barycenter(K_5, sp=sp) == list(K_5)
# ...but not with the weight argument
for u, v, data in K_5.edges.data():
data['weight'] = 1
pytest.raises(ValueError, nx.barycenter, K_5, sp=sp, weight='weight')
# ...and a corrupted sp can make it seem like K_5 is disconnected
del sp[0][1]
pytest.raises(nx.NetworkXNoPath, nx.barycenter, K_5, sp=sp)
def test_trees(self):
"""The barycenter of a tree is a single vertex or an edge.
See [West01]_, p. 78.
"""
prng = Random(0xdeadbeef)
for i in range(50):
RT = nx.random_tree(prng.randint(1, 75), prng)
b = self.barycenter_as_subgraph(RT)
if len(b) == 2:
assert b.size() == 1
else:
assert len(b) == 1
assert b.size() == 0
def test_this_one_specific_tree(self):
"""Test the tree pictured at the bottom of [West01]_, p. 78."""
g = nx.Graph({
'a': ['b'],
'b': ['a', 'x'],
'x': ['b', 'y'],
'y': ['x', 'z'],
'z': ['y', 0, 1, 2, 3, 4],
0: ['z'], 1: ['z'], 2: ['z'], 3: ['z'], 4: ['z']})
b = self.barycenter_as_subgraph(g, attr='barycentricity')
assert list(b) == ['z']
assert not b.edges
expected_barycentricity = {0: 23, 1: 23, 2: 23, 3: 23, 4: 23,
'a': 35, 'b': 27, 'x': 21, 'y': 17, 'z': 15
}
for node, barycentricity in expected_barycentricity.items():
assert g.nodes[node]['barycentricity'] == barycentricity
# Doubling weights should do nothing but double the barycentricities
for edge in g.edges:
g.edges[edge]['weight'] = 2
b = self.barycenter_as_subgraph(g, weight='weight',
attr='barycentricity2')
assert list(b) == ['z']
assert not b.edges
for node, barycentricity in expected_barycentricity.items():
assert g.nodes[node]['barycentricity2'] == barycentricity*2