Fix nans on eigenmoses variable, and add some tests.

Author: MXB6669

axelrod/result_set.py

@@ -2,6 +2,7 @@
 import csv
 import itertools
 from multiprocessing import cpu_count
+from typing import List
 import warnings
 
 import numpy as np
@@ -609,6 +610,17 @@ def __eq__(self, other):
             other : axelrod.ResultSet
                 Another results set against which to check equality
         """
+        def list_equal(v1: List[float], v2: List[float]) -> bool:
+            """Matches lists, accounting for NaNs."""
+            if len(v1) != len(v2):
+                return False
+            for i1, i2 in zip(v1, v2):
+                if np.isnan(i1) and np.isnan(i2):
+                    continue
+                if i1 != i2:
+                    return False
+            return True
+
         return all(
             [
                 self.wins == other.wins,
@@ -628,8 +640,8 @@ def __eq__(self, other):
                 self.cooperating_rating == other.cooperating_rating,
                 self.good_partner_matrix == other.good_partner_matrix,
                 self.good_partner_rating == other.good_partner_rating,
-                self.eigenmoses_rating == other.eigenmoses_rating,
-                self.eigenjesus_rating == other.eigenjesus_rating,
+                list_equal(self.eigenmoses_rating, other.eigenmoses_rating),
+                list_equal(self.eigenjesus_rating, other.eigenjesus_rating),
             ]
         )
 

axelrod/tests/unit/test_eigen.py

@@ -15,6 +15,13 @@ def test_identity_matrices(self):
             self.assertAlmostEqual(evalue, 1)
             assert_array_almost_equal(evector, _normalise(numpy.ones(size)))
 
+    def test_zero_matrix(self):
+        mat = numpy.array([[0, 0], [0, 0]])
+        evector, evalue = principal_eigenvector(mat)
+        self.assertTrue(numpy.isnan(evalue))
+        self.assertTrue(numpy.isnan(evector[0]))
+        self.assertTrue(numpy.isnan(evector[1]))
+
     def test_2x2_matrix(self):
         mat = numpy.array([[2, 1], [1, 2]])
         evector, evalue = principal_eigenvector(mat)

axelrod/tests/unit/test_resultset.py

@@ -7,7 +7,7 @@
 import pandas as pd
 from axelrod.result_set import create_counter_dict
 from axelrod.tests.property import prob_end_tournaments, tournaments
-from numpy import mean, nanmedian, std
+from numpy import mean, nan, nanmedian, std
 
 from dask.dataframe.core import DataFrame
 from hypothesis import given, settings
@@ -190,6 +190,34 @@ def test_init(self):
         self.assertEqual(rs.players, self.players)
         self.assertEqual(rs.num_players, len(self.players))
 
+    def _clear_matrix(self, matrix):
+        for i in range(len(matrix)):
+            for j in range(len(matrix[i])):
+                matrix[i][j] = 0
+
+    def test_nan_vectors(self):
+        rs_1 = axelrod.ResultSet(
+            self.filename,
+            self.players,
+            self.repetitions
+        )
+        # Force a broken eigenmoses, by replacing vengeful_cooperation with
+        # zeroes.
+        self._clear_matrix(rs_1.vengeful_cooperation)
+        rs_1.eigenmoses_rating = rs_1._build_eigenmoses_rating()
+
+        rs_2 = axelrod.ResultSet(
+            self.filename,
+            self.players,
+            self.repetitions
+        )
+        # Force a broken eigenmoses, by replacing vengeful_cooperation with
+        # zeroes.
+        self._clear_matrix(rs_2.vengeful_cooperation)
+        rs_2.eigenmoses_rating = rs_2._build_eigenmoses_rating()
+
+        self.assertEqual(rs_1, rs_2)
+
     def test_init_multiprocessing(self):
         rs = axelrod.ResultSet(
             self.filename,