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Merge tests for nodal metrics into a TestCase.
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‎brainx/tests/test_metrics.py

Lines changed: 75 additions & 73 deletions
Original file line numberDiff line numberDiff line change
@@ -4,6 +4,8 @@
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# Imports
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#-----------------------------------------------------------------------------
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from unittest import TestCase
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# Third party
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import networkx as nx
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import nose.tools as nt
@@ -17,81 +19,81 @@
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# Functions
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#-----------------------------------------------------------------------------
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def test_nodal_pathlengths():
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corr_mat = np.array([[0.0, 0.0, 0.0, 0.0, 0.0],
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[0.5, 0.0, 0.0, 0.0, 0.0],
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[0.3, 0.4, 0.0, 0.0, 0.0],
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[0.0, 0.0, 0.7, 0.0, 0.0],
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[0.0, 0.0, 0.0, 0.4, 0.0]])
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n_nodes = 5
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g = nx.from_numpy_matrix(corr_mat)
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path_lengths = metrics.nodal_pathlengths(g, n_nodes)
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# Distances for all node pairs:
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# 0-1: 1 1-2: 1 2-3: 1 3-4: 1
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# 0-2: 1 1-3: 2 2-4: 2
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# 0-3: 2 1-4: 3
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# 0-4: 3
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desired = 1.0 / (n_nodes - 1) * np.array([1 + 1 + 2 + 3,
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1 + 1 + 2 + 3,
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1 + 1 + 1 + 2,
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2 + 2 + 1 + 1,
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3 + 3 + 2 + 1])
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npt.assert_array_almost_equal(path_lengths, desired)
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# Check how unreachability is handled.
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g.remove_edge(2, 3)
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# Now all nodes have at least one edge, but not all nodes are reachable
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# from all others.
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path_lengths = metrics.nodal_pathlengths(g, n_nodes)
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# Distances for all node pairs:
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# 0-1: 1 1-2: 1 2-3: Inf 3-4: 1
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# 0-2: 1 1-3: Inf 2-4: Inf
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# 0-3: Inf 1-4: Inf
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# 0-4: Inf
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desired = 1.0 / (n_nodes - 1) * np.array([1 + 1 + np.inf + np.inf,
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1 + 1 + np.inf + np.inf,
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1 + 1 + np.inf + np.inf,
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np.inf + np.inf + np.inf + 1,
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np.inf + np.inf + np.inf + 1])
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npt.assert_array_almost_equal(path_lengths, desired)
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class NodalMetricsTestCase(TestCase):
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24+
def setUp(self):
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self.corr_mat = np.array([[0.0, 0.0, 0.0, 0.0, 0.0],
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[0.5, 0.0, 0.0, 0.0, 0.0],
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[0.3, 0.4, 0.0, 0.0, 0.0],
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[0.0, 0.0, 0.7, 0.0, 0.0],
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[0.0, 0.0, 0.0, 0.4, 0.0]])
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self.n_nodes = self.corr_mat.shape[0]
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self.g = nx.from_numpy_matrix(self.corr_mat)
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def test_nodal_pathlengths_conn(self):
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path_lengths = metrics.nodal_pathlengths(self.g, self.n_nodes)
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# Distances for all node pairs:
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# 0-1: 1 1-2: 1 2-3: 1 3-4: 1
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# 0-2: 1 1-3: 2 2-4: 2
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# 0-3: 2 1-4: 3
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# 0-4: 3
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desired = 1.0 / (self.n_nodes - 1) * np.array([1 + 1 + 2 + 3,
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1 + 1 + 2 + 3,
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1 + 1 + 1 + 2,
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2 + 2 + 1 + 1,
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3 + 3 + 2 + 1])
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npt.assert_array_almost_equal(path_lengths, desired)
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def test_nodal_pathlengths_disconn(self):
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self.g.remove_edge(2, 3)
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# Now all nodes still have at least one edge, but not all nodes are
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# reachable from all others.
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path_lengths = metrics.nodal_pathlengths(self.g, self.n_nodes)
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# Distances for all node pairs:
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# 0-1: 1 1-2: 1 2-3: Inf 3-4: 1
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# 0-2: 1 1-3: Inf 2-4: Inf
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# 0-3: Inf 1-4: Inf
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# 0-4: Inf
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desired = (1.0 / (self.n_nodes - 1) *
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np.array([1 + 1 + np.inf + np.inf,
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1 + 1 + np.inf + np.inf,
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1 + 1 + np.inf + np.inf,
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np.inf + np.inf + np.inf + 1,
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np.inf + np.inf + np.inf + 1]))
63+
npt.assert_array_almost_equal(path_lengths, desired)
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65+
def test_nodal_efficiency_conn(self):
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n_eff_array = metrics.nodal_efficiency(self.g, self.n_nodes)
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# Distances for all node pairs:
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# 0-1: 1 1-2: 1 2-3: 1 3-4: 1
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# 0-2: 1 1-3: 2 2-4: 2
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# 0-3: 2 1-4: 3
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# 0-4: 3
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desired = (1.0 / (self.n_nodes - 1) *
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np.array([1 + 1 + 1 / 2.0 + 1 / 3.0,
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1 + 1 + 1 / 2.0 + 1 / 3.0,
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1 + 1 + 1 + 1 / 2.0,
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1 / 2.0 + 1 / 2.0 + 1 + 1,
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1 / 3.0 + 1 / 3.0 + 1 / 2.0 + 1]))
78+
npt.assert_array_almost_equal(n_eff_array, desired)
5779

58-
def test_nodal_efficiency():
59-
corr_mat = np.array([[0.0, 0.0, 0.0, 0.0, 0.0],
60-
[0.5, 0.0, 0.0, 0.0, 0.0],
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[0.3, 0.4, 0.0, 0.0, 0.0],
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[0.0, 0.0, 0.7, 0.0, 0.0],
63-
[0.0, 0.0, 0.0, 0.4, 0.0]])
64-
n_nodes = 5
65-
g = nx.from_numpy_matrix(corr_mat)
66-
n_eff_array = metrics.nodal_efficiency(g, n_nodes)
67-
# Distances for all node pairs:
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# 0-1: 1 1-2: 1 2-3: 1 3-4: 1
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# 0-2: 1 1-3: 2 2-4: 2
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# 0-3: 2 1-4: 3
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# 0-4: 3
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desired = 1.0 / (n_nodes - 1) * np.array([1 + 1 + 1 / 2.0 + 1 / 3.0,
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1 + 1 + 1 / 2.0 + 1 / 3.0,
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1 + 1 + 1 + 1 / 2.0,
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1 / 2.0 + 1 / 2.0 + 1 + 1,
76-
1 / 3.0 + 1 / 3.0 + 1 / 2.0 + 1])
77-
npt.assert_array_almost_equal(n_eff_array, desired)
78-
# Check how unreachability is handled.
79-
g.remove_edge(2, 3)
80-
# Now all nodes have at least one edge, but not all nodes are reachable
81-
# from all others.
82-
n_eff_array = metrics.nodal_efficiency(g, n_nodes)
83-
# Distances for all node pairs:
84-
# 0-1: 1 1-2: 1 2-3: Inf 3-4: 1
85-
# 0-2: 1 1-3: Inf 2-4: Inf
86-
# 0-3: Inf 1-4: Inf
87-
# 0-4: Inf
88-
desired = (1.0 / (n_nodes - 1) *
89-
np.array([1 + 1 + 1 / np.inf + 1 / np.inf,
90-
1 + 1 + 1 / np.inf + 1 / np.inf,
91-
1 + 1 + 1 / np.inf + 1 / np.inf,
92-
1 / np.inf + 1 / np.inf + 1 / np.inf + 1,
93-
1 / np.inf + 1 / np.inf + 1 / np.inf + 1]))
94-
npt.assert_array_almost_equal(n_eff_array, desired)
80+
def test_nodal_efficiency_disconn(self):
81+
self.g.remove_edge(2, 3)
82+
# Now all nodes still have at least one edge, but not all nodes are
83+
# reachable from all others.
84+
n_eff_array = metrics.nodal_efficiency(self.g, self.n_nodes)
85+
# Distances for all node pairs:
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# 0-1: 1 1-2: 1 2-3: Inf 3-4: 1
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# 0-2: 1 1-3: Inf 2-4: Inf
88+
# 0-3: Inf 1-4: Inf
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# 0-4: Inf
90+
desired = (1.0 / (self.n_nodes - 1) *
91+
np.array([1 + 1 + 1 / np.inf + 1 / np.inf,
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1 + 1 + 1 / np.inf + 1 / np.inf,
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1 + 1 + 1 / np.inf + 1 / np.inf,
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1 / np.inf + 1 / np.inf + 1 / np.inf + 1,
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1 / np.inf + 1 / np.inf + 1 / np.inf + 1]))
96+
npt.assert_array_almost_equal(n_eff_array, desired)
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def test_path_lengths():

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