Fix all tests

tests/components/test_lazy_dynamic.py

@@ -6,6 +6,7 @@ from unittest.mock import Mock
 
 import numpy as np
 from numpy.linalg import norm
+from numpy.testing import assert_array_equal
 
 from miplearn.classifiers import Classifier
 from miplearn.components.lazy_dynamic import DynamicLazyConstraintsComponent
@@ -42,15 +43,36 @@ def test_lazy_fit():
     assert norm(expected_x_train_c - actual_x_train_c) < E
 
     # Should provide correct y_train to each classifier
-    expected_y_train_a = np.array([1.0, 0.0])
-    expected_y_train_b = np.array([1.0, 1.0])
-    expected_y_train_c = np.array([0.0, 1.0])
-    actual_y_train_a = component.classifiers["a"].fit.call_args[0][1]
-    actual_y_train_b = component.classifiers["b"].fit.call_args[0][1]
-    actual_y_train_c = component.classifiers["c"].fit.call_args[0][1]
-    assert norm(expected_y_train_a - actual_y_train_a) < E
-    assert norm(expected_y_train_b - actual_y_train_b) < E
-    assert norm(expected_y_train_c - actual_y_train_c) < E
+    expected_y_train_a = np.array(
+        [
+            [False, True],
+            [True, False],
+        ]
+    )
+    expected_y_train_b = np.array(
+        [
+            [False, True],
+            [False, True],
+        ]
+    )
+    expected_y_train_c = np.array(
+        [
+            [True, False],
+            [False, True],
+        ]
+    )
+    assert_array_equal(
+        component.classifiers["a"].fit.call_args[0][1],
+        expected_y_train_a,
+    )
+    assert_array_equal(
+        component.classifiers["b"].fit.call_args[0][1],
+        expected_y_train_b,
+    )
+    assert_array_equal(
+        component.classifiers["c"].fit.call_args[0][1],
+        expected_y_train_c,
+    )
 
 
 def test_lazy_before():

tests/solvers/test_learning_solver.py

@@ -3,6 +3,7 @@
 #  Released under the modified BSD license. See COPYING.md for more details.
 
 import logging
+import dill
 import pickle
 import tempfile
 import os
@@ -44,7 +45,7 @@ def test_learning_solver():
 
             # Assert solver is picklable
             with tempfile.TemporaryFile() as file:
-                pickle.dump(solver, file)
+                dill.dump(solver, file)
 
 
 def test_solve_without_lp():