Make tests more robust and increment version

setup.py

@@ -9,7 +9,7 @@
 
 setup(
     name='modularitypruning',
-    version='1.1.3',
+    version='1.2.0',
     package_dir={'modularitypruning': 'utilities'},
     packages=['modularitypruning'],
     url='https://github.com/ragibson/ModularityPruning',

tests/shared_testing_functions.py

@@ -1,4 +1,5 @@
 import igraph as ig
+from math import isnan
 from modularitypruning.partition_utilities import num_communities
 from random import randint, random, uniform
 
@@ -87,3 +88,12 @@ def generate_multilayer_intralayer_SBM(copying_probability, p_in, p_out, first_l
     G_intralayer = ig.Graph(intralayer_edges, directed=False)
 
     return G_intralayer, layer_membership
+
+
+def assert_almost_equal_or_both_none_or_nan(self, first, second, places=10):
+    if first is None:
+        self.assertIsNone(second)  # isnan only accepts floats
+    elif isnan(first):
+        self.assertTrue(isnan(second))  # NaN is != NaN according to IEEE-754
+    else:
+        self.assertAlmostEqual(first, second, places=places)

tests/test_monolayer_parameter_estimation.py

@@ -1,4 +1,4 @@
-from .shared_testing_functions import generate_igraph_famous, generate_random_partition
+from .shared_testing_functions import assert_almost_equal_or_both_none_or_nan, generate_igraph_famous, generate_random_partition
 import igraph as ig
 from math import log
 from numpy import mean
@@ -45,7 +45,7 @@ def test_directed_consistency_igraph_famous(self):
             G.to_directed()
             gamma_directed = gamma_estimate(G, random_membership)
 
-            self.assertAlmostEqual(gamma_undirected, gamma_directed, places=10)
+            assert_almost_equal_or_both_none_or_nan(self, gamma_undirected, gamma_directed, places=10)
 
 
 if __name__ == "__main__":

tests/test_multiplex_parameter_estimation.py

@@ -1,4 +1,5 @@
-from .shared_testing_functions import generate_random_partition, generate_multilayer_intralayer_SBM
+from .shared_testing_functions import assert_almost_equal_or_both_none_or_nan, generate_random_partition, \
+    generate_multilayer_intralayer_SBM
 import igraph as ig
 from math import log
 from numpy import mean
@@ -109,8 +110,8 @@ def test_directed_consistency_multiplex_SBM_louvain(self):
             gamma_directed, omega_directed = gamma_omega_estimate(G_intralayer, G_interlayer, layer_membership,
                                                                   partition, model="multiplex")
 
-            self.assertAlmostEqual(gamma_undirected, gamma_directed, places=10)
-            self.assertAlmostEqual(omega_undirected, omega_directed, places=10)
+            assert_almost_equal_or_both_none_or_nan(self, gamma_undirected, gamma_directed, places=10)
+            assert_almost_equal_or_both_none_or_nan(self, omega_undirected, omega_directed, places=10)
 
 
 if __name__ == "__main__":

tests/test_temporal_multilevel_parameter_estimation.py

@@ -1,4 +1,5 @@
-from .shared_testing_functions import generate_random_partition, generate_multilayer_intralayer_SBM
+from .shared_testing_functions import assert_almost_equal_or_both_none_or_nan, generate_random_partition, \
+    generate_multilayer_intralayer_SBM
 import igraph as ig
 from math import log
 from numpy import mean
@@ -112,8 +113,8 @@ def test_directed_consistency_temporal_SBM_louvain(self):
             gamma_directed, omega_directed = gamma_omega_estimate(G_intralayer, G_interlayer, layer_membership,
                                                                   partition, model="temporal")
 
-            self.assertAlmostEqual(gamma_undirected, gamma_directed, places=10)
-            self.assertAlmostEqual(omega_undirected, omega_directed, places=10)
+            assert_almost_equal_or_both_none_or_nan(self, gamma_undirected, gamma_directed, places=10)
+            assert_almost_equal_or_both_none_or_nan(self, omega_undirected, omega_directed, places=10)
 
             # check multilevel parameter estimation as well
             gamma_undirected, omega_undirected = gamma_omega_estimate(G_intralayer, G_interlayer, layer_membership,
@@ -123,8 +124,8 @@ def test_directed_consistency_temporal_SBM_louvain(self):
             gamma_directed, omega_directed = gamma_omega_estimate(G_intralayer, G_interlayer, layer_membership,
                                                                   partition, model="multilevel")
 
-            self.assertAlmostEqual(gamma_undirected, gamma_directed, places=10)
-            self.assertAlmostEqual(omega_undirected, omega_directed, places=10)
+            assert_almost_equal_or_both_none_or_nan(self, gamma_undirected, gamma_directed, places=10)
+            assert_almost_equal_or_both_none_or_nan(self, omega_undirected, omega_directed, places=10)
 
 
 if __name__ == "__main__":

utilities/champ_utilities.py

@@ -2,7 +2,6 @@
     membership_to_layered_communities
 from collections import defaultdict
 import numpy as np
-from numpy import VisibleDeprecationWarning
 from numpy.random import choice
 from math import floor
 from multiprocessing import Pool, cpu_count